id	sid	tid	token	lemma	pos
ijassa-725	1	1	adv	adv	PROPN
ijassa-725	1	2	syst	syst	PROPN
ijassa-725	1	3	sci	sci	PROPN
ijassa-725	1	4	appl	appl	PROPN
ijassa-725	1	5	2019	2019	NUM
ijassa-725	1	6	;	;	PUNCT
ijassa-725	1	7	2:23–32	2:23–32	NUM
ijassa-725	1	8	http://ijassa.ipu.ru/index.php/ijassa/article/view/725	http://ijassa.ipu.ru/index.php/ijassa/article/view/725	NOUN
ijassa-725	1	9	machine	machine	NOUN
ijassa-725	1	10	learning	learn	VERB
ijassa-725	1	11	algorithms	algorithm	NOUN
ijassa-725	1	12	for	for	ADP
ijassa-725	1	13	automatic	automatic	ADJ
ijassa-725	1	14	anomalies	anomaly	NOUN
ijassa-725	1	15	detection	detection	NOUN
ijassa-725	1	16	in	in	ADP
ijassa-725	1	17	data	datum	NOUN
ijassa-725	1	18	storage	storage	NOUN
ijassa-725	1	19	systems	system	NOUN
ijassa-725	1	20	operation	operation	NOUN
ijassa-725	1	21	mikhail	mikhail	PROPN
ijassa-725	1	22	hushchyn1,2∗	hushchyn1,2∗	PROPN
ijassa-725	1	23	,	,	PUNCT
ijassa-725	1	24	andrey	andrey	PROPN
ijassa-725	1	25	sapronov1,3	sapronov1,3	PROPN
ijassa-725	1	26	,	,	PUNCT
ijassa-725	1	27	andrey	andrey	PROPN
ijassa-725	1	28	ustyuzhanin1,2	ustyuzhanin1,2	PROPN
ijassa-725	1	29	1national	1national	NUM
ijassa-725	1	30	research	research	NOUN
ijassa-725	1	31	university	university	NOUN
ijassa-725	1	32	higher	high	ADJ
ijassa-725	1	33	school	school	NOUN
ijassa-725	1	34	of	of	ADP
ijassa-725	1	35	economics	economic	NOUN
ijassa-725	1	36	,	,	PUNCT
ijassa-725	1	37	myasnitskaya	myasnitskaya	NOUN
ijassa-725	1	38	20	20	NUM
ijassa-725	1	39	,	,	PUNCT
ijassa-725	1	40	101000	101000	NUM
ijassa-725	1	41	,	,	PUNCT
ijassa-725	1	42	moscow	moscow	PROPN
ijassa-725	1	43	,	,	PUNCT
ijassa-725	1	44	russia	russia	PROPN
ijassa-725	1	45	2moscow	2moscow	PROPN
ijassa-725	1	46	institute	institute	PROPN
ijassa-725	1	47	of	of	ADP
ijassa-725	1	48	physics	physics	PROPN
ijassa-725	1	49	and	and	CCONJ
ijassa-725	1	50	technology	technology	NOUN
ijassa-725	1	51	,	,	PUNCT
ijassa-725	1	52	institutskiy	institutskiy	NOUN
ijassa-725	1	53	per	per	ADP
ijassa-725	1	54	.	.	PROPN
ijassa-725	1	55	9	9	NUM
ijassa-725	1	56	,	,	PUNCT
ijassa-725	1	57	dolgoprudny	dolgoprudny	VERB
ijassa-725	1	58	,	,	PUNCT
ijassa-725	1	59	moscow	moscow	PROPN
ijassa-725	1	60	reg	reg	PROPN
ijassa-725	1	61	.	.	PROPN
ijassa-725	1	62	,	,	PUNCT
ijassa-725	1	63	141700	141700	NUM
ijassa-725	1	64	,	,	PUNCT
ijassa-725	1	65	russia	russia	PROPN
ijassa-725	1	66	3joint	3joint	PROPN
ijassa-725	1	67	institute	institute	NOUN
ijassa-725	1	68	for	for	ADP
ijassa-725	1	69	nuclear	nuclear	ADJ
ijassa-725	1	70	research	research	NOUN
ijassa-725	1	71	,	,	PUNCT
ijassa-725	1	72	joliot	joliot	NOUN
ijassa-725	1	73	-	-	PUNCT
ijassa-725	1	74	curie	curie	NOUN
ijassa-725	1	75	6	6	NUM
ijassa-725	1	76	,	,	PUNCT
ijassa-725	1	77	dubna	dubna	PROPN
ijassa-725	1	78	,	,	PUNCT
ijassa-725	1	79	moscow	moscow	PROPN
ijassa-725	1	80	region	region	NOUN
ijassa-725	1	81	,	,	PUNCT
ijassa-725	1	82	141980	141980	NUM
ijassa-725	1	83	,	,	PUNCT
ijassa-725	1	84	russia	russia	PROPN
ijassa-725	1	85	received	receive	VERB
ijassa-725	1	86	april	april	PROPN
ijassa-725	1	87	9	9	NUM
ijassa-725	1	88	,	,	PUNCT
ijassa-725	1	89	2019	2019	NUM
ijassa-725	1	90	;	;	PUNCT
ijassa-725	1	91	revised	revise	VERB
ijassa-725	1	92	june	june	PROPN
ijassa-725	1	93	6	6	NUM
ijassa-725	1	94	,	,	PUNCT
ijassa-725	1	95	2019	2019	NUM
ijassa-725	1	96	;	;	PUNCT
ijassa-725	1	97	published	publish	VERB
ijassa-725	1	98	july	july	PROPN
ijassa-725	1	99	10	10	NUM
ijassa-725	1	100	,	,	PUNCT
ijassa-725	1	101	2019	2019	NUM
ijassa-725	1	102	abstract	abstract	NOUN
ijassa-725	1	103	:	:	PUNCT
ijassa-725	1	104	data	datum	NOUN
ijassa-725	1	105	storage	storage	NOUN
ijassa-725	1	106	reliability	reliability	NOUN
ijassa-725	1	107	and	and	CCONJ
ijassa-725	1	108	availability	availability	NOUN
ijassa-725	1	109	play	play	VERB
ijassa-725	1	110	important	important	ADJ
ijassa-725	1	111	role	role	NOUN
ijassa-725	1	112	for	for	ADP
ijassa-725	1	113	a	a	DET
ijassa-725	1	114	wide	wide	ADJ
ijassa-725	1	115	range	range	NOUN
ijassa-725	1	116	of	of	ADP
ijassa-725	1	117	services	service	NOUN
ijassa-725	1	118	and	and	CCONJ
ijassa-725	1	119	business	business	NOUN
ijassa-725	1	120	processes	process	NOUN
ijassa-725	1	121	.	.	PUNCT
ijassa-725	2	1	manufacturers	manufacturer	NOUN
ijassa-725	2	2	provide	provide	VERB
ijassa-725	2	3	data	datum	NOUN
ijassa-725	2	4	storage	storage	NOUN
ijassa-725	2	5	systems	system	NOUN
ijassa-725	2	6	that	that	PRON
ijassa-725	2	7	resistant	resistant	ADJ
ijassa-725	2	8	to	to	ADP
ijassa-725	2	9	hardware	hardware	NOUN
ijassa-725	2	10	and	and	CCONJ
ijassa-725	2	11	software	software	NOUN
ijassa-725	2	12	failures	failure	NOUN
ijassa-725	2	13	but	but	CCONJ
ijassa-725	2	14	not	not	PART
ijassa-725	2	15	for	for	ADP
ijassa-725	2	16	all	all	DET
ijassa-725	2	17	cases	case	NOUN
ijassa-725	2	18	.	.	PUNCT
ijassa-725	3	1	well	well	ADV
ijassa-725	3	2	-	-	PUNCT
ijassa-725	3	3	timed	time	VERB
ijassa-725	3	4	detection	detection	NOUN
ijassa-725	3	5	of	of	ADP
ijassa-725	3	6	these	these	DET
ijassa-725	3	7	failures	failure	NOUN
ijassa-725	3	8	helps	help	VERB
ijassa-725	3	9	to	to	PART
ijassa-725	3	10	recover	recover	VERB
ijassa-725	3	11	the	the	DET
ijassa-725	3	12	system	system	NOUN
ijassa-725	3	13	faster	fast	ADV
ijassa-725	3	14	and	and	CCONJ
ijassa-725	3	15	prevent	prevent	VERB
ijassa-725	3	16	the	the	DET
ijassa-725	3	17	failures	failure	NOUN
ijassa-725	3	18	before	before	SCONJ
ijassa-725	3	19	they	they	PRON
ijassa-725	3	20	occur	occur	VERB
ijassa-725	3	21	.	.	PUNCT
ijassa-725	4	1	in	in	ADP
ijassa-725	4	2	this	this	DET
ijassa-725	4	3	work	work	NOUN
ijassa-725	4	4	a	a	DET
ijassa-725	4	5	range	range	NOUN
ijassa-725	4	6	of	of	ADP
ijassa-725	4	7	machine	machine	NOUN
ijassa-725	4	8	learning	learning	NOUN
ijassa-725	4	9	and	and	CCONJ
ijassa-725	4	10	time	time	NOUN
ijassa-725	4	11	series	series	PROPN
ijassa-725	4	12	analysis	analysis	NOUN
ijassa-725	4	13	algorithms	algorithm	NOUN
ijassa-725	4	14	for	for	ADP
ijassa-725	4	15	failures	failure	NOUN
ijassa-725	4	16	detection	detection	NOUN
ijassa-725	4	17	for	for	ADP
ijassa-725	4	18	data	data	NOUN
ijassa-725	4	19	storage	storage	NOUN
ijassa-725	4	20	systems	system	NOUN
ijassa-725	4	21	is	be	AUX
ijassa-725	4	22	considered	consider	VERB
ijassa-725	4	23	.	.	PUNCT
ijassa-725	5	1	the	the	DET
ijassa-725	5	2	algorithms	algorithm	NOUN
ijassa-725	5	3	are	be	AUX
ijassa-725	5	4	applied	apply	VERB
ijassa-725	5	5	and	and	CCONJ
ijassa-725	5	6	compared	compare	VERB
ijassa-725	5	7	on	on	ADP
ijassa-725	5	8	the	the	DET
ijassa-725	5	9	real	real	ADJ
ijassa-725	5	10	system	system	NOUN
ijassa-725	5	11	.	.	PUNCT
ijassa-725	6	1	preliminary	preliminary	ADJ
ijassa-725	6	2	results	result	NOUN
ijassa-725	6	3	show	show	VERB
ijassa-725	6	4	that	that	SCONJ
ijassa-725	6	5	binary	binary	ADJ
ijassa-725	6	6	classification	classification	NOUN
ijassa-725	6	7	methods	method	NOUN
ijassa-725	6	8	demonstrate	demonstrate	VERB
ijassa-725	6	9	high	high	ADJ
ijassa-725	6	10	failure	failure	NOUN
ijassa-725	6	11	detection	detection	NOUN
ijassa-725	6	12	and	and	CCONJ
ijassa-725	6	13	low	low	ADJ
ijassa-725	6	14	false	false	ADJ
ijassa-725	6	15	alarm	alarm	NOUN
ijassa-725	6	16	rates	rate	NOUN
ijassa-725	6	17	.	.	PUNCT
ijassa-725	7	1	time	time	PROPN
ijassa-725	7	2	series	series	PROPN
ijassa-725	7	3	prediction	prediction	PROPN
ijassa-725	7	4	based	base	VERB
ijassa-725	7	5	approach	approach	NOUN
ijassa-725	7	6	shows	show	VERB
ijassa-725	7	7	similar	similar	ADJ
ijassa-725	7	8	results	result	NOUN
ijassa-725	7	9	and	and	CCONJ
ijassa-725	7	10	outperforms	outperform	VERB
ijassa-725	7	11	one	one	NUM
ijassa-725	7	12	-	-	PUNCT
ijassa-725	7	13	class	class	NOUN
ijassa-725	7	14	classification	classification	NOUN
ijassa-725	7	15	methods	method	NOUN
ijassa-725	7	16	.	.	PUNCT
ijassa-725	8	1	keywords	keyword	NOUN
ijassa-725	8	2	:	:	PUNCT
ijassa-725	8	3	machine	machine	NOUN
ijassa-725	8	4	learning	learning	NOUN
ijassa-725	8	5	,	,	PUNCT
ijassa-725	8	6	time	time	NOUN
ijassa-725	8	7	series	series	PROPN
ijassa-725	8	8	analysis	analysis	NOUN
ijassa-725	8	9	,	,	PUNCT
ijassa-725	8	10	anomaly	anomaly	NOUN
ijassa-725	8	11	detection	detection	NOUN
ijassa-725	8	12	,	,	PUNCT
ijassa-725	8	13	data	datum	NOUN
ijassa-725	8	14	storage	storage	NOUN
ijassa-725	8	15	systems	system	NOUN
ijassa-725	8	16	1	1	NUM
ijassa-725	8	17	.	.	PUNCT
ijassa-725	9	1	introduction	introduction	NOUN
ijassa-725	9	2	modern	modern	ADJ
ijassa-725	9	3	data	datum	NOUN
ijassa-725	9	4	storage	storage	NOUN
ijassa-725	9	5	systems	system	NOUN
ijassa-725	9	6	are	be	AUX
ijassa-725	9	7	built	build	VERB
ijassa-725	9	8	from	from	ADP
ijassa-725	9	9	hundreds	hundred	NOUN
ijassa-725	9	10	of	of	ADP
ijassa-725	9	11	solid	solid	ADJ
ijassa-725	9	12	-	-	PUNCT
ijassa-725	9	13	state	state	NOUN
ijassa-725	9	14	drives	drive	NOUN
ijassa-725	9	15	(	(	PUNCT
ijassa-725	9	16	ssds	ssds	NOUN
ijassa-725	9	17	)	)	PUNCT
ijassa-725	9	18	and	and	CCONJ
ijassa-725	9	19	hard	hard	ADJ
ijassa-725	9	20	disk	disk	NOUN
ijassa-725	9	21	drives	drive	NOUN
ijassa-725	9	22	(	(	PUNCT
ijassa-725	9	23	hdds	hdd	NOUN
ijassa-725	9	24	)	)	PUNCT
ijassa-725	9	25	,	,	PUNCT
ijassa-725	9	26	networks	network	NOUN
ijassa-725	9	27	and	and	CCONJ
ijassa-725	9	28	controllers	controller	NOUN
ijassa-725	9	29	to	to	PART
ijassa-725	9	30	handle	handle	VERB
ijassa-725	9	31	and	and	CCONJ
ijassa-725	9	32	process	process	VERB
ijassa-725	9	33	incoming	incoming	ADJ
ijassa-725	9	34	data	datum	NOUN
ijassa-725	9	35	.	.	PUNCT
ijassa-725	10	1	a	a	DET
ijassa-725	10	2	lot	lot	NOUN
ijassa-725	10	3	of	of	ADP
ijassa-725	10	4	data	datum	NOUN
ijassa-725	10	5	generated	generate	VERB
ijassa-725	10	6	every	every	DET
ijassa-725	10	7	day	day	NOUN
ijassa-725	10	8	has	have	VERB
ijassa-725	10	9	to	to	PART
ijassa-725	10	10	be	be	AUX
ijassa-725	10	11	properly	properly	ADV
ijassa-725	10	12	saved	save	VERB
ijassa-725	10	13	for	for	ADP
ijassa-725	10	14	further	further	ADJ
ijassa-725	10	15	usage	usage	NOUN
ijassa-725	10	16	.	.	PUNCT
ijassa-725	11	1	storage	storage	NOUN
ijassa-725	11	2	systems	system	NOUN
ijassa-725	11	3	have	have	VERB
ijassa-725	11	4	to	to	PART
ijassa-725	11	5	provide	provide	VERB
ijassa-725	11	6	high	high	ADJ
ijassa-725	11	7	availability	availability	NOUN
ijassa-725	11	8	and	and	CCONJ
ijassa-725	11	9	reliability	reliability	NOUN
ijassa-725	11	10	.	.	PUNCT
ijassa-725	12	1	any	any	DET
ijassa-725	12	2	failure	failure	NOUN
ijassa-725	12	3	in	in	ADP
ijassa-725	12	4	these	these	DET
ijassa-725	12	5	systems	system	NOUN
ijassa-725	12	6	will	will	AUX
ijassa-725	12	7	negatively	negatively	ADV
ijassa-725	12	8	affect	affect	VERB
ijassa-725	12	9	any	any	DET
ijassa-725	12	10	processes	process	NOUN
ijassa-725	12	11	and	and	CCONJ
ijassa-725	12	12	applications	application	NOUN
ijassa-725	12	13	that	that	PRON
ijassa-725	12	14	use	use	VERB
ijassa-725	12	15	the	the	DET
ijassa-725	12	16	data	datum	NOUN
ijassa-725	12	17	and	and	CCONJ
ijassa-725	12	18	lead	lead	VERB
ijassa-725	12	19	to	to	ADP
ijassa-725	12	20	significant	significant	ADJ
ijassa-725	12	21	revenue	revenue	NOUN
ijassa-725	12	22	loss	loss	NOUN
ijassa-725	12	23	.	.	PUNCT
ijassa-725	13	1	any	any	DET
ijassa-725	13	2	anomalous	anomalous	ADJ
ijassa-725	13	3	system	system	NOUN
ijassa-725	13	4	behaviour	behaviour	NOUN
ijassa-725	13	5	can	can	AUX
ijassa-725	13	6	potentially	potentially	ADV
ijassa-725	13	7	be	be	AUX
ijassa-725	13	8	the	the	DET
ijassa-725	13	9	result	result	NOUN
ijassa-725	13	10	of	of	ADP
ijassa-725	13	11	a	a	DET
ijassa-725	13	12	failure	failure	NOUN
ijassa-725	13	13	of	of	ADP
ijassa-725	13	14	its	its	PRON
ijassa-725	13	15	components	component	NOUN
ijassa-725	13	16	and	and	CCONJ
ijassa-725	13	17	data	datum	NOUN
ijassa-725	13	18	loss	loss	NOUN
ijassa-725	13	19	.	.	PUNCT
ijassa-725	14	1	it	it	PRON
ijassa-725	14	2	requires	require	VERB
ijassa-725	14	3	from	from	ADP
ijassa-725	14	4	the	the	DET
ijassa-725	14	5	storage	storage	NOUN
ijassa-725	14	6	system	system	NOUN
ijassa-725	14	7	operators	operator	NOUN
ijassa-725	14	8	to	to	PART
ijassa-725	14	9	explore	explore	VERB
ijassa-725	14	10	it	it	PRON
ijassa-725	14	11	and	and	CCONJ
ijassa-725	14	12	,	,	PUNCT
ijassa-725	14	13	if	if	SCONJ
ijassa-725	14	14	necessary	necessary	ADJ
ijassa-725	14	15	,	,	PUNCT
ijassa-725	14	16	take	take	VERB
ijassa-725	14	17	actions	action	NOUN
ijassa-725	14	18	to	to	PART
ijassa-725	14	19	resolve	resolve	VERB
ijassa-725	14	20	the	the	DET
ijassa-725	14	21	problem	problem	NOUN
ijassa-725	14	22	.	.	PUNCT
ijassa-725	15	1	timely	timely	ADJ
ijassa-725	15	2	anomaly	anomaly	NOUN
ijassa-725	15	3	detection	detection	NOUN
ijassa-725	15	4	allows	allow	VERB
ijassa-725	15	5	to	to	PART
ijassa-725	15	6	react	react	VERB
ijassa-725	15	7	on	on	ADP
ijassa-725	15	8	system	system	NOUN
ijassa-725	15	9	failures	failure	NOUN
ijassa-725	15	10	faster	fast	ADV
ijassa-725	15	11	decreasing	decrease	VERB
ijassa-725	15	12	shutdown	shutdown	NOUN
ijassa-725	15	13	time	time	NOUN
ijassa-725	15	14	and	and	CCONJ
ijassa-725	15	15	preventing	prevent	VERB
ijassa-725	15	16	data	datum	NOUN
ijassa-725	15	17	loss	loss	NOUN
ijassa-725	15	18	.	.	PUNCT
ijassa-725	16	1	anomalies	anomaly	NOUN
ijassa-725	16	2	can	can	AUX
ijassa-725	16	3	be	be	AUX
ijassa-725	16	4	the	the	DET
ijassa-725	16	5	result	result	NOUN
ijassa-725	16	6	of	of	ADP
ijassa-725	16	7	the	the	DET
ijassa-725	16	8	system	system	NOUN
ijassa-725	16	9	failures	failure	NOUN
ijassa-725	16	10	that	that	PRON
ijassa-725	16	11	have	have	AUX
ijassa-725	16	12	already	already	ADV
ijassa-725	16	13	happened	happen	VERB
ijassa-725	16	14	or	or	CCONJ
ijassa-725	16	15	will	will	AUX
ijassa-725	16	16	happen	happen	VERB
ijassa-725	16	17	in	in	ADP
ijassa-725	16	18	the	the	DET
ijassa-725	16	19	near	near	ADJ
ijassa-725	16	20	future	future	NOUN
ijassa-725	16	21	.	.	PUNCT
ijassa-725	17	1	in	in	ADP
ijassa-725	17	2	the	the	DET
ijassa-725	17	3	first	first	ADJ
ijassa-725	17	4	case	case	NOUN
ijassa-725	17	5	anomalies	anomaly	NOUN
ijassa-725	17	6	detection	detection	NOUN
ijassa-725	17	7	allows	allow	VERB
ijassa-725	17	8	to	to	PART
ijassa-725	17	9	reduce	reduce	VERB
ijassa-725	17	10	time	time	NOUN
ijassa-725	17	11	delay	delay	NOUN
ijassa-725	17	12	for	for	ADP
ijassa-725	17	13	corrective	corrective	ADJ
ijassa-725	17	14	actions	action	NOUN
ijassa-725	17	15	.	.	PUNCT
ijassa-725	18	1	in	in	ADP
ijassa-725	18	2	the	the	DET
ijassa-725	18	3	second	second	ADJ
ijassa-725	18	4	case	case	NOUN
ijassa-725	18	5	it	it	PRON
ijassa-725	18	6	gives	give	VERB
ijassa-725	18	7	time	time	NOUN
ijassa-725	18	8	to	to	PART
ijassa-725	18	9	take	take	VERB
ijassa-725	18	10	actions	action	NOUN
ijassa-725	18	11	to	to	PART
ijassa-725	18	12	prevent	prevent	VERB
ijassa-725	18	13	the	the	DET
ijassa-725	18	14	failures	failure	NOUN
ijassa-725	18	15	and	and	CCONJ
ijassa-725	18	16	to	to	PART
ijassa-725	18	17	reduce	reduce	VERB
ijassa-725	18	18	undesirable	undesirable	ADJ
ijassa-725	18	19	effects	effect	NOUN
ijassa-725	18	20	.	.	PUNCT
ijassa-725	19	1	the	the	DET
ijassa-725	19	2	paper	paper	NOUN
ijassa-725	19	3	has	have	VERB
ijassa-725	19	4	the	the	DET
ijassa-725	19	5	following	follow	VERB
ijassa-725	19	6	structure	structure	NOUN
ijassa-725	19	7	.	.	PUNCT
ijassa-725	20	1	overview	overview	NOUN
ijassa-725	20	2	of	of	ADP
ijassa-725	20	3	related	related	ADJ
ijassa-725	20	4	works	work	NOUN
ijassa-725	20	5	is	be	AUX
ijassa-725	20	6	considered	consider	VERB
ijassa-725	20	7	in	in	ADP
ijassa-725	20	8	sec	sec	PROPN
ijassa-725	20	9	.	.	PROPN
ijassa-725	21	1	2	2	NUM
ijassa-725	21	2	.	.	X
ijassa-725	21	3	data	datum	NOUN
ijassa-725	21	4	storage	storage	NOUN
ijassa-725	21	5	system	system	NOUN
ijassa-725	21	6	that	that	PRON
ijassa-725	21	7	is	be	AUX
ijassa-725	21	8	used	use	VERB
ijassa-725	21	9	in	in	ADP
ijassa-725	21	10	this	this	DET
ijassa-725	21	11	work	work	NOUN
ijassa-725	21	12	for	for	ADP
ijassa-725	21	13	anomalies	anomaly	NOUN
ijassa-725	21	14	detection	detection	NOUN
ijassa-725	21	15	is	be	AUX
ijassa-725	21	16	described	describe	VERB
ijassa-725	21	17	in	in	ADP
ijassa-725	21	18	sec	sec	PROPN
ijassa-725	21	19	.	.	PROPN
ijassa-725	22	1	3	3	X
ijassa-725	22	2	.	.	X
ijassa-725	22	3	discussion	discussion	NOUN
ijassa-725	22	4	of	of	ADP
ijassa-725	22	5	different	different	ADJ
ijassa-725	22	6	anomalies	anomaly	NOUN
ijassa-725	22	7	detection	detection	NOUN
ijassa-725	22	8	algorithms	algorithm	NOUN
ijassa-725	22	9	with	with	ADP
ijassa-725	22	10	examples	example	NOUN
ijassa-725	22	11	and	and	CCONJ
ijassa-725	22	12	results	result	NOUN
ijassa-725	22	13	is	be	AUX
ijassa-725	22	14	provided	provide	VERB
ijassa-725	22	15	in	in	ADP
ijassa-725	22	16	sec	sec	PROPN
ijassa-725	22	17	.	.	PROPN
ijassa-725	23	1	4	4	X
ijassa-725	23	2	.	.	X
ijassa-725	23	3	finally	finally	ADV
ijassa-725	23	4	,	,	PUNCT
ijassa-725	23	5	conclusions	conclusion	NOUN
ijassa-725	23	6	of	of	ADP
ijassa-725	23	7	this	this	DET
ijassa-725	23	8	work	work	NOUN
ijassa-725	23	9	are	be	AUX
ijassa-725	23	10	presented	present	VERB
ijassa-725	23	11	in	in	ADP
ijassa-725	23	12	sec	sec	PROPN
ijassa-725	23	13	.	.	PROPN
ijassa-725	24	1	5	5	NUM
ijassa-725	24	2	.	.	X
ijassa-725	24	3	∗corresponding	∗corresponde	VERB
ijassa-725	24	4	author	author	NOUN
ijassa-725	24	5	:	:	PUNCT
ijassa-725	24	6	hushchyn.mikhail@gmail.com	hushchyn.mikhail@gmail.com	X
ijassa-725	25	1	24	24	NUM
ijassa-725	25	2	2	2	NUM
ijassa-725	25	3	.	.	PUNCT
ijassa-725	25	4	related	relate	VERB
ijassa-725	25	5	works	work	NOUN
ijassa-725	25	6	there	there	PRON
ijassa-725	25	7	are	be	VERB
ijassa-725	25	8	a	a	DET
ijassa-725	25	9	variety	variety	NOUN
ijassa-725	25	10	of	of	ADP
ijassa-725	25	11	anomaly	anomaly	NOUN
ijassa-725	25	12	detection	detection	NOUN
ijassa-725	25	13	methods	method	NOUN
ijassa-725	25	14	[	[	X
ijassa-725	25	15	1	1	NUM
ijassa-725	25	16	,	,	PUNCT
ijassa-725	25	17	2	2	NUM
ijassa-725	25	18	]	]	PUNCT
ijassa-725	25	19	applied	apply	VERB
ijassa-725	25	20	in	in	ADP
ijassa-725	25	21	different	different	ADJ
ijassa-725	25	22	domains	domain	NOUN
ijassa-725	25	23	of	of	ADP
ijassa-725	25	24	systems	system	NOUN
ijassa-725	25	25	.	.	PUNCT
ijassa-725	26	1	these	these	DET
ijassa-725	26	2	methods	method	NOUN
ijassa-725	26	3	are	be	AUX
ijassa-725	26	4	the	the	DET
ijassa-725	26	5	most	most	ADV
ijassa-725	26	6	widely	widely	ADV
ijassa-725	26	7	used	use	VERB
ijassa-725	26	8	in	in	ADP
ijassa-725	26	9	computer	computer	NOUN
ijassa-725	26	10	networks	network	NOUN
ijassa-725	26	11	to	to	PART
ijassa-725	26	12	detect	detect	VERB
ijassa-725	26	13	cyber	cyber	NOUN
ijassa-725	26	14	attacks	attack	NOUN
ijassa-725	26	15	[	[	X
ijassa-725	26	16	3–7	3–7	NOUN
ijassa-725	26	17	]	]	PUNCT
ijassa-725	26	18	and	and	CCONJ
ijassa-725	26	19	web	web	NOUN
ijassa-725	26	20	-	-	NOUN
ijassa-725	26	21	traffic	traffic	NOUN
ijassa-725	26	22	anomalies	anomaly	NOUN
ijassa-725	26	23	[	[	X
ijassa-725	26	24	8–10	8–10	NOUN
ijassa-725	26	25	]	]	PUNCT
ijassa-725	26	26	.	.	PUNCT
ijassa-725	27	1	there	there	PRON
ijassa-725	27	2	are	be	VERB
ijassa-725	27	3	a	a	DET
ijassa-725	27	4	set	set	NOUN
ijassa-725	27	5	of	of	ADP
ijassa-725	27	6	works	work	NOUN
ijassa-725	27	7	where	where	SCONJ
ijassa-725	27	8	system	system	NOUN
ijassa-725	27	9	logs	log	NOUN
ijassa-725	27	10	of	of	ADP
ijassa-725	27	11	online	online	ADJ
ijassa-725	27	12	service	service	NOUN
ijassa-725	27	13	systems	system	NOUN
ijassa-725	27	14	[	[	X
ijassa-725	27	15	11	11	NUM
ijassa-725	27	16	]	]	PUNCT
ijassa-725	27	17	,	,	PUNCT
ijassa-725	27	18	supercomputers	supercomputer	NOUN
ijassa-725	27	19	and	and	CCONJ
ijassa-725	27	20	distributed	distribute	VERB
ijassa-725	27	21	systems	system	NOUN
ijassa-725	27	22	[	[	X
ijassa-725	27	23	12	12	NUM
ijassa-725	27	24	,	,	PUNCT
ijassa-725	27	25	13	13	NUM
ijassa-725	27	26	]	]	PUNCT
ijassa-725	27	27	are	be	AUX
ijassa-725	27	28	analysed	analyse	VERB
ijassa-725	27	29	to	to	PART
ijassa-725	27	30	detect	detect	VERB
ijassa-725	27	31	various	various	ADJ
ijassa-725	27	32	failures	failure	NOUN
ijassa-725	27	33	and	and	CCONJ
ijassa-725	27	34	anomalies	anomaly	NOUN
ijassa-725	27	35	.	.	PUNCT
ijassa-725	28	1	several	several	ADJ
ijassa-725	28	2	approaches	approach	NOUN
ijassa-725	28	3	were	be	AUX
ijassa-725	28	4	presented	present	VERB
ijassa-725	28	5	to	to	PART
ijassa-725	28	6	predict	predict	VERB
ijassa-725	28	7	failure	failure	NOUN
ijassa-725	28	8	of	of	ADP
ijassa-725	28	9	hard	hard	ADJ
ijassa-725	28	10	drives	drive	NOUN
ijassa-725	28	11	[	[	X
ijassa-725	28	12	14	14	NUM
ijassa-725	28	13	,	,	PUNCT
ijassa-725	28	14	15	15	NUM
ijassa-725	28	15	]	]	PUNCT
ijassa-725	28	16	based	base	VERB
ijassa-725	28	17	on	on	ADP
ijassa-725	28	18	their	their	PRON
ijassa-725	28	19	smart	smart	ADJ
ijassa-725	28	20	(	(	PUNCT
ijassa-725	28	21	self	self	NOUN
ijassa-725	28	22	-	-	PUNCT
ijassa-725	28	23	monitoring	monitoring	NOUN
ijassa-725	28	24	,	,	PUNCT
ijassa-725	28	25	analysis	analysis	NOUN
ijassa-725	28	26	and	and	CCONJ
ijassa-725	28	27	reporting	report	VERB
ijassa-725	28	28	technology	technology	NOUN
ijassa-725	28	29	)	)	PUNCT
ijassa-725	28	30	data	datum	NOUN
ijassa-725	28	31	.	.	PUNCT
ijassa-725	29	1	interesting	interesting	ADJ
ijassa-725	29	2	results	result	NOUN
ijassa-725	29	3	were	be	AUX
ijassa-725	29	4	demonstrated	demonstrate	VERB
ijassa-725	29	5	at	at	ADP
ijassa-725	29	6	the	the	DET
ijassa-725	29	7	european	european	PROPN
ijassa-725	29	8	organization	organization	PROPN
ijassa-725	29	9	for	for	ADP
ijassa-725	29	10	nuclear	nuclear	ADJ
ijassa-725	29	11	research	research	NOUN
ijassa-725	29	12	(	(	PUNCT
ijassa-725	29	13	cern	cern	NOUN
ijassa-725	29	14	)	)	PUNCT
ijassa-725	29	15	where	where	SCONJ
ijassa-725	29	16	anomaly	anomaly	NOUN
ijassa-725	29	17	detection	detection	NOUN
ijassa-725	29	18	methods	method	NOUN
ijassa-725	29	19	are	be	AUX
ijassa-725	29	20	used	use	VERB
ijassa-725	29	21	in	in	ADP
ijassa-725	29	22	data	datum	NOUN
ijassa-725	29	23	quality	quality	NOUN
ijassa-725	29	24	system	system	NOUN
ijassa-725	29	25	for	for	ADP
ijassa-725	29	26	monitoring	monitor	VERB
ijassa-725	29	27	quality	quality	NOUN
ijassa-725	29	28	of	of	ADP
ijassa-725	29	29	data	datum	NOUN
ijassa-725	29	30	generated	generate	VERB
ijassa-725	29	31	in	in	ADP
ijassa-725	29	32	high	high	ADJ
ijassa-725	29	33	energy	energy	NOUN
ijassa-725	29	34	physics	physics	NOUN
ijassa-725	29	35	detectors	detector	NOUN
ijassa-725	29	36	[	[	X
ijassa-725	29	37	16	16	NUM
ijassa-725	29	38	]	]	PUNCT
ijassa-725	29	39	.	.	PUNCT
ijassa-725	30	1	the	the	DET
ijassa-725	30	2	most	most	ADV
ijassa-725	30	3	promising	promising	ADJ
ijassa-725	30	4	methods	method	NOUN
ijassa-725	30	5	of	of	ADP
ijassa-725	30	6	failures	failure	NOUN
ijassa-725	30	7	detection	detection	NOUN
ijassa-725	30	8	are	be	AUX
ijassa-725	30	9	based	base	VERB
ijassa-725	30	10	on	on	ADP
ijassa-725	30	11	machine	machine	NOUN
ijassa-725	30	12	learning	learning	NOUN
ijassa-725	30	13	and	and	CCONJ
ijassa-725	30	14	time	time	NOUN
ijassa-725	30	15	series	series	PROPN
ijassa-725	30	16	analysis	analysis	NOUN
ijassa-725	30	17	algorithms	algorithm	NOUN
ijassa-725	30	18	.	.	PUNCT
ijassa-725	31	1	these	these	DET
ijassa-725	31	2	approaches	approach	NOUN
ijassa-725	31	3	use	use	VERB
ijassa-725	31	4	clustering	clustering	NOUN
ijassa-725	31	5	,	,	PUNCT
ijassa-725	31	6	one	one	NUM
ijassa-725	31	7	-	-	PUNCT
ijassa-725	31	8	class	class	NOUN
ijassa-725	31	9	and	and	CCONJ
ijassa-725	31	10	binary	binary	ADJ
ijassa-725	31	11	classification	classification	NOUN
ijassa-725	31	12	algorithms	algorithm	NOUN
ijassa-725	31	13	for	for	ADP
ijassa-725	31	14	anomalies	anomaly	NOUN
ijassa-725	31	15	detection	detection	NOUN
ijassa-725	31	16	.	.	PUNCT
ijassa-725	32	1	clustering	cluster	VERB
ijassa-725	32	2	methods	method	NOUN
ijassa-725	32	3	[	[	X
ijassa-725	32	4	1	1	NUM
ijassa-725	32	5	,	,	PUNCT
ijassa-725	32	6	2	2	NUM
ijassa-725	32	7	]	]	PUNCT
ijassa-725	32	8	suppose	suppose	VERB
ijassa-725	32	9	that	that	SCONJ
ijassa-725	32	10	normal	normal	ADJ
ijassa-725	32	11	and	and	CCONJ
ijassa-725	32	12	anomalous	anomalous	ADJ
ijassa-725	32	13	system	system	NOUN
ijassa-725	32	14	behaviours	behaviour	NOUN
ijassa-725	32	15	form	form	VERB
ijassa-725	32	16	different	different	ADJ
ijassa-725	32	17	clusters	cluster	NOUN
ijassa-725	32	18	in	in	ADP
ijassa-725	32	19	some	some	DET
ijassa-725	32	20	parameter	parameter	NOUN
ijassa-725	32	21	space	space	NOUN
ijassa-725	32	22	.	.	PUNCT
ijassa-725	33	1	the	the	DET
ijassa-725	33	2	methods	method	NOUN
ijassa-725	33	3	learn	learn	VERB
ijassa-725	33	4	boundaries	boundary	NOUN
ijassa-725	33	5	of	of	ADP
ijassa-725	33	6	these	these	DET
ijassa-725	33	7	clusters	cluster	NOUN
ijassa-725	33	8	and	and	CCONJ
ijassa-725	33	9	use	use	VERB
ijassa-725	33	10	them	they	PRON
ijassa-725	33	11	to	to	PART
ijassa-725	33	12	distinguish	distinguish	VERB
ijassa-725	33	13	different	different	ADJ
ijassa-725	33	14	system	system	NOUN
ijassa-725	33	15	states	state	NOUN
ijassa-725	33	16	.	.	PUNCT
ijassa-725	34	1	this	this	DET
ijassa-725	34	2	approach	approach	NOUN
ijassa-725	34	3	works	work	VERB
ijassa-725	34	4	well	well	ADV
ijassa-725	34	5	when	when	SCONJ
ijassa-725	34	6	the	the	DET
ijassa-725	34	7	clusters	cluster	NOUN
ijassa-725	34	8	are	be	AUX
ijassa-725	34	9	separable	separable	ADJ
ijassa-725	34	10	from	from	ADP
ijassa-725	34	11	each	each	DET
ijassa-725	34	12	other	other	ADJ
ijassa-725	34	13	.	.	PUNCT
ijassa-725	35	1	there	there	PRON
ijassa-725	35	2	are	be	VERB
ijassa-725	35	3	variety	variety	NOUN
ijassa-725	35	4	of	of	ADP
ijassa-725	35	5	clustering	clustering	ADJ
ijassa-725	35	6	algorithms	algorithm	NOUN
ijassa-725	35	7	[	[	X
ijassa-725	35	8	17	17	NUM
ijassa-725	35	9	]	]	X
ijassa-725	35	10	:	:	PUNCT
ijassa-725	35	11	k	k	X
ijassa-725	35	12	-	-	PUNCT
ijassa-725	35	13	means	means	ADJ
ijassa-725	35	14	,	,	PUNCT
ijassa-725	35	15	hierarchical	hierarchical	ADJ
ijassa-725	35	16	clustering	clustering	NOUN
ijassa-725	35	17	,	,	PUNCT
ijassa-725	35	18	gaussian	gaussian	ADJ
ijassa-725	35	19	mixtures	mixture	NOUN
ijassa-725	35	20	,	,	PUNCT
ijassa-725	35	21	dbscan	dbscan	NOUN
ijassa-725	35	22	and	and	CCONJ
ijassa-725	35	23	others	other	NOUN
ijassa-725	35	24	.	.	PUNCT
ijassa-725	36	1	similarly	similarly	ADV
ijassa-725	36	2	,	,	PUNCT
ijassa-725	36	3	one	one	NUM
ijassa-725	36	4	-	-	PUNCT
ijassa-725	36	5	class	class	NOUN
ijassa-725	36	6	methods	method	NOUN
ijassa-725	36	7	learn	learn	VERB
ijassa-725	36	8	system	system	NOUN
ijassa-725	36	9	behaviour	behaviour	NOUN
ijassa-725	36	10	in	in	ADP
ijassa-725	36	11	the	the	DET
ijassa-725	36	12	normal	normal	ADJ
ijassa-725	36	13	state	state	NOUN
ijassa-725	36	14	.	.	PUNCT
ijassa-725	37	1	they	they	PRON
ijassa-725	37	2	suppose	suppose	VERB
ijassa-725	37	3	that	that	SCONJ
ijassa-725	37	4	normal	normal	ADJ
ijassa-725	37	5	states	state	NOUN
ijassa-725	37	6	form	form	VERB
ijassa-725	37	7	dense	dense	ADJ
ijassa-725	37	8	clusters	cluster	NOUN
ijassa-725	37	9	in	in	ADP
ijassa-725	37	10	system	system	NOUN
ijassa-725	37	11	parameter	parameter	NOUN
ijassa-725	37	12	space	space	NOUN
ijassa-725	37	13	and	and	CCONJ
ijassa-725	37	14	recognize	recognize	VERB
ijassa-725	37	15	boundaries	boundary	NOUN
ijassa-725	37	16	of	of	ADP
ijassa-725	37	17	these	these	DET
ijassa-725	37	18	clusters	cluster	NOUN
ijassa-725	37	19	.	.	PUNCT
ijassa-725	38	1	everything	everything	PRON
ijassa-725	38	2	that	that	PRON
ijassa-725	38	3	is	be	AUX
ijassa-725	38	4	beyond	beyond	ADP
ijassa-725	38	5	the	the	DET
ijassa-725	38	6	boundaries	boundary	NOUN
ijassa-725	38	7	is	be	AUX
ijassa-725	38	8	considered	consider	VERB
ijassa-725	38	9	as	as	ADP
ijassa-725	38	10	an	an	DET
ijassa-725	38	11	anomaly	anomaly	NOUN
ijassa-725	38	12	.	.	PUNCT
ijassa-725	39	1	the	the	DET
ijassa-725	39	2	most	most	ADV
ijassa-725	39	3	used	used	ADJ
ijassa-725	39	4	algorithms	algorithm	NOUN
ijassa-725	39	5	are	be	AUX
ijassa-725	39	6	isolation	isolation	NOUN
ijassa-725	39	7	forest	forest	NOUN
ijassa-725	40	1	[	[	X
ijassa-725	40	2	18	18	NUM
ijassa-725	40	3	]	]	PUNCT
ijassa-725	40	4	,	,	PUNCT
ijassa-725	40	5	elliptical	elliptical	ADJ
ijassa-725	40	6	envelope	envelope	NOUN
ijassa-725	40	7	[	[	X
ijassa-725	40	8	19	19	NUM
ijassa-725	40	9	]	]	PUNCT
ijassa-725	40	10	,	,	PUNCT
ijassa-725	40	11	one	one	NUM
ijassa-725	40	12	-	-	PUNCT
ijassa-725	40	13	class	class	NOUN
ijassa-725	40	14	svm	svm	NOUN
ijassa-725	40	15	[	[	X
ijassa-725	40	16	20	20	NUM
ijassa-725	40	17	]	]	PUNCT
ijassa-725	40	18	,	,	PUNCT
ijassa-725	40	19	asvdd	asvdd	PROPN
ijassa-725	41	1	[	[	X
ijassa-725	41	2	21	21	NUM
ijassa-725	41	3	]	]	PUNCT
ijassa-725	41	4	and	and	CCONJ
ijassa-725	41	5	wsvdd	wsvdd	NOUN
ijassa-725	41	6	-	-	PUNCT
ijassa-725	41	7	cba	cba	NOUN
ijassa-725	42	1	[	[	X
ijassa-725	42	2	22	22	NUM
ijassa-725	42	3	]	]	PUNCT
ijassa-725	42	4	.	.	PUNCT
ijassa-725	43	1	binary	binary	ADJ
ijassa-725	43	2	classification	classification	NOUN
ijassa-725	44	1	[	[	X
ijassa-725	44	2	1	1	NUM
ijassa-725	44	3	,	,	PUNCT
ijassa-725	44	4	2	2	NUM
ijassa-725	44	5	]	]	PUNCT
ijassa-725	44	6	is	be	AUX
ijassa-725	44	7	used	use	VERB
ijassa-725	44	8	when	when	SCONJ
ijassa-725	44	9	anomalies	anomaly	NOUN
ijassa-725	44	10	are	be	AUX
ijassa-725	44	11	known	know	VERB
ijassa-725	44	12	.	.	PUNCT
ijassa-725	45	1	it	it	PRON
ijassa-725	45	2	takes	take	VERB
ijassa-725	45	3	normal	normal	ADJ
ijassa-725	45	4	behaviour	behaviour	NOUN
ijassa-725	45	5	and	and	CCONJ
ijassa-725	45	6	anomalies	anomaly	NOUN
ijassa-725	45	7	as	as	ADP
ijassa-725	45	8	two	two	NUM
ijassa-725	45	9	classes	class	NOUN
ijassa-725	45	10	and	and	CCONJ
ijassa-725	45	11	learns	learn	VERB
ijassa-725	45	12	separation	separation	NOUN
ijassa-725	45	13	rule	rule	NOUN
ijassa-725	45	14	between	between	ADP
ijassa-725	45	15	them	they	PRON
ijassa-725	45	16	in	in	ADP
ijassa-725	45	17	parameters	parameter	NOUN
ijassa-725	45	18	space	space	NOUN
ijassa-725	45	19	.	.	PUNCT
ijassa-725	46	1	then	then	ADV
ijassa-725	46	2	this	this	DET
ijassa-725	46	3	rule	rule	NOUN
ijassa-725	46	4	is	be	AUX
ijassa-725	46	5	used	use	VERB
ijassa-725	46	6	to	to	PART
ijassa-725	46	7	classify	classify	VERB
ijassa-725	46	8	the	the	DET
ijassa-725	46	9	system	system	NOUN
ijassa-725	46	10	states	state	NOUN
ijassa-725	46	11	.	.	PUNCT
ijassa-725	47	1	the	the	DET
ijassa-725	47	2	most	most	ADV
ijassa-725	47	3	popular	popular	ADJ
ijassa-725	47	4	classifiers	classifier	NOUN
ijassa-725	47	5	are	be	AUX
ijassa-725	47	6	naive	naive	ADJ
ijassa-725	47	7	bayes	bayes	NOUN
ijassa-725	47	8	,	,	PUNCT
ijassa-725	47	9	logistic	logistic	ADJ
ijassa-725	47	10	regression	regression	NOUN
ijassa-725	47	11	,	,	PUNCT
ijassa-725	47	12	svm	svm	ADJ
ijassa-725	47	13	,	,	PUNCT
ijassa-725	47	14	decision	decision	NOUN
ijassa-725	47	15	tree	tree	NOUN
ijassa-725	47	16	,	,	PUNCT
ijassa-725	47	17	random	random	ADJ
ijassa-725	47	18	forest	forest	NOUN
ijassa-725	47	19	,	,	PUNCT
ijassa-725	47	20	gradient	gradient	NOUN
ijassa-725	47	21	boosting	boost	VERB
ijassa-725	47	22	over	over	ADP
ijassa-725	47	23	decision	decision	NOUN
ijassa-725	47	24	trees	tree	NOUN
ijassa-725	47	25	and	and	CCONJ
ijassa-725	47	26	artificial	artificial	ADJ
ijassa-725	47	27	neural	neural	ADJ
ijassa-725	47	28	networks	network	NOUN
ijassa-725	47	29	that	that	PRON
ijassa-725	47	30	are	be	AUX
ijassa-725	47	31	described	describe	VERB
ijassa-725	47	32	in	in	ADP
ijassa-725	47	33	[	[	X
ijassa-725	47	34	17	17	NUM
ijassa-725	47	35	]	]	PUNCT
ijassa-725	47	36	.	.	PUNCT
ijassa-725	48	1	time	time	PROPN
ijassa-725	48	2	series	series	PROPN
ijassa-725	48	3	analysis	analysis	NOUN
ijassa-725	48	4	based	base	VERB
ijassa-725	48	5	methods	method	NOUN
ijassa-725	48	6	[	[	X
ijassa-725	48	7	1	1	NUM
ijassa-725	48	8	,	,	PUNCT
ijassa-725	48	9	2	2	NUM
ijassa-725	48	10	]	]	PUNCT
ijassa-725	48	11	are	be	AUX
ijassa-725	48	12	based	base	VERB
ijassa-725	48	13	on	on	ADP
ijassa-725	48	14	prediction	prediction	NOUN
ijassa-725	48	15	of	of	ADP
ijassa-725	48	16	system	system	NOUN
ijassa-725	48	17	parameters	parameter	NOUN
ijassa-725	48	18	values	value	NOUN
ijassa-725	48	19	in	in	ADP
ijassa-725	48	20	time	time	NOUN
ijassa-725	48	21	.	.	PUNCT
ijassa-725	49	1	they	they	PRON
ijassa-725	49	2	use	use	VERB
ijassa-725	49	3	previous	previous	ADJ
ijassa-725	49	4	values	value	NOUN
ijassa-725	49	5	of	of	ADP
ijassa-725	49	6	the	the	DET
ijassa-725	49	7	parameters	parameter	NOUN
ijassa-725	49	8	to	to	PART
ijassa-725	49	9	predict	predict	VERB
ijassa-725	49	10	the	the	DET
ijassa-725	49	11	current	current	ADJ
ijassa-725	49	12	one	one	NUM
ijassa-725	49	13	.	.	PUNCT
ijassa-725	50	1	large	large	ADJ
ijassa-725	50	2	deviations	deviation	NOUN
ijassa-725	50	3	from	from	ADP
ijassa-725	50	4	the	the	DET
ijassa-725	50	5	predictions	prediction	NOUN
ijassa-725	50	6	indicate	indicate	VERB
ijassa-725	50	7	anomalies	anomaly	NOUN
ijassa-725	50	8	.	.	PUNCT
ijassa-725	51	1	there	there	PRON
ijassa-725	51	2	are	be	VERB
ijassa-725	51	3	a	a	DET
ijassa-725	51	4	lot	lot	NOUN
ijassa-725	51	5	of	of	ADP
ijassa-725	51	6	predictive	predictive	ADJ
ijassa-725	51	7	models	model	NOUN
ijassa-725	51	8	for	for	ADP
ijassa-725	51	9	time	time	NOUN
ijassa-725	51	10	series	series	NOUN
ijassa-725	51	11	[	[	X
ijassa-725	51	12	23	23	NUM
ijassa-725	51	13	]	]	X
ijassa-725	51	14	:	:	PUNCT
ijassa-725	51	15	ets	et	NOUN
ijassa-725	51	16	models	model	NOUN
ijassa-725	51	17	,	,	PUNCT
ijassa-725	51	18	autoregression	autoregression	NOUN
ijassa-725	51	19	(	(	PUNCT
ijassa-725	51	20	ar	ar	NOUN
ijassa-725	51	21	)	)	PUNCT
ijassa-725	51	22	and	and	CCONJ
ijassa-725	51	23	moving	move	VERB
ijassa-725	51	24	average	average	ADJ
ijassa-725	51	25	(	(	PUNCT
ijassa-725	51	26	ma	ma	PROPN
ijassa-725	51	27	)	)	PUNCT
ijassa-725	51	28	models	model	NOUN
ijassa-725	51	29	,	,	PUNCT
ijassa-725	51	30	arma	arma	PROPN
ijassa-725	51	31	,	,	PUNCT
ijassa-725	51	32	arima	arima	NOUN
ijassa-725	51	33	,	,	PUNCT
ijassa-725	51	34	artificial	artificial	ADJ
ijassa-725	51	35	neural	neural	ADJ
ijassa-725	51	36	networks	network	NOUN
ijassa-725	51	37	and	and	CCONJ
ijassa-725	51	38	others	other	NOUN
ijassa-725	51	39	.	.	PUNCT
ijassa-725	52	1	in	in	ADP
ijassa-725	52	2	this	this	DET
ijassa-725	52	3	work	work	NOUN
ijassa-725	52	4	several	several	ADJ
ijassa-725	52	5	approaches	approach	NOUN
ijassa-725	52	6	of	of	ADP
ijassa-725	52	7	anomaly	anomaly	NOUN
ijassa-725	52	8	detection	detection	NOUN
ijassa-725	52	9	for	for	ADP
ijassa-725	52	10	data	data	NOUN
ijassa-725	52	11	storage	storage	NOUN
ijassa-725	52	12	systems	system	NOUN
ijassa-725	52	13	are	be	AUX
ijassa-725	52	14	considered	consider	VERB
ijassa-725	52	15	.	.	PUNCT
ijassa-725	53	1	3	3	X
ijassa-725	53	2	.	.	X
ijassa-725	53	3	tatlin	tatlin	ADJ
ijassa-725	53	4	storage	storage	NOUN
ijassa-725	53	5	description	description	NOUN
ijassa-725	53	6	the	the	DET
ijassa-725	53	7	goal	goal	NOUN
ijassa-725	53	8	of	of	ADP
ijassa-725	53	9	this	this	DET
ijassa-725	53	10	work	work	NOUN
ijassa-725	53	11	is	be	AUX
ijassa-725	53	12	to	to	PART
ijassa-725	53	13	develop	develop	VERB
ijassa-725	53	14	the	the	DET
ijassa-725	53	15	algorithm	algorithm	NOUN
ijassa-725	53	16	of	of	ADP
ijassa-725	53	17	automatic	automatic	ADJ
ijassa-725	53	18	failure	failure	NOUN
ijassa-725	53	19	detection	detection	NOUN
ijassa-725	53	20	for	for	ADP
ijassa-725	53	21	tatlin	tatlin	NOUN
ijassa-725	53	22	[	[	X
ijassa-725	53	23	24	24	NUM
ijassa-725	53	24	]	]	PUNCT
ijassa-725	53	25	storage	storage	NOUN
ijassa-725	53	26	system	system	NOUN
ijassa-725	53	27	.	.	PUNCT
ijassa-725	54	1	the	the	DET
ijassa-725	54	2	system	system	NOUN
ijassa-725	54	3	contains	contain	VERB
ijassa-725	54	4	up	up	ADP
ijassa-725	54	5	to	to	PART
ijassa-725	54	6	4	4	NUM
ijassa-725	54	7	storage	storage	NOUN
ijassa-725	54	8	controllers	controller	NOUN
ijassa-725	54	9	,	,	PUNCT
ijassa-725	54	10	peripheral	peripheral	ADJ
ijassa-725	54	11	component	component	NOUN
ijassa-725	54	12	interconnect	interconnect	NOUN
ijassa-725	54	13	express	express	ADJ
ijassa-725	54	14	(	(	PUNCT
ijassa-725	54	15	pcie	pcie	NOUN
ijassa-725	54	16	)	)	PUNCT
ijassa-725	54	17	fabric	fabric	NOUN
ijassa-725	54	18	controller	controller	NOUN
ijassa-725	54	19	and	and	CCONJ
ijassa-725	54	20	up	up	ADP
ijassa-725	54	21	to	to	PART
ijassa-725	54	22	16	16	NUM
ijassa-725	54	23	drive	drive	NOUN
ijassa-725	54	24	enclosures	enclosure	NOUN
ijassa-725	54	25	as	as	SCONJ
ijassa-725	54	26	it	it	PRON
ijassa-725	54	27	is	be	AUX
ijassa-725	54	28	shown	show	VERB
ijassa-725	54	29	in	in	ADP
ijassa-725	54	30	fig	fig	NOUN
ijassa-725	54	31	.	.	PUNCT
ijassa-725	55	1	3.1	3.1	NUM
ijassa-725	55	2	.	.	PUNCT
ijassa-725	55	3	storage	storage	NOUN
ijassa-725	55	4	controllers	controller	NOUN
ijassa-725	55	5	are	be	AUX
ijassa-725	55	6	based	base	VERB
ijassa-725	55	7	on	on	ADP
ijassa-725	55	8	yadro	yadro	PRON
ijassa-725	55	9	vesnin	vesnin	NOUN
ijassa-725	56	1	[	[	X
ijassa-725	56	2	25	25	NUM
ijassa-725	56	3	]	]	PUNCT
ijassa-725	56	4	hardware	hardware	NOUN
ijassa-725	56	5	platform	platform	NOUN
ijassa-725	56	6	.	.	PUNCT
ijassa-725	57	1	they	they	PRON
ijassa-725	57	2	provide	provide	VERB
ijassa-725	57	3	user	user	NOUN
ijassa-725	57	4	access	access	NOUN
ijassa-725	57	5	to	to	ADP
ijassa-725	57	6	data	datum	NOUN
ijassa-725	57	7	,	,	PUNCT
ijassa-725	57	8	perform	perform	VERB
ijassa-725	57	9	computations	computation	NOUN
ijassa-725	57	10	and	and	CCONJ
ijassa-725	57	11	run	run	VERB
ijassa-725	57	12	the	the	DET
ijassa-725	57	13	tatlin	tatlin	ADJ
ijassa-725	57	14	software	software	NOUN
ijassa-725	57	15	.	.	PUNCT
ijassa-725	58	1	each	each	DET
ijassa-725	58	2	storage	storage	NOUN
ijassa-725	58	3	controller	controller	NOUN
ijassa-725	58	4	consists	consist	VERB
ijassa-725	58	5	of	of	ADP
ijassa-725	58	6	4	4	NUM
ijassa-725	58	7	power8	power8	NOUN
ijassa-725	58	8	turismo	turismo	PROPN
ijassa-725	58	9	scm	scm	PROPN
ijassa-725	58	10	processors	processor	NOUN
ijassa-725	58	11	,	,	PUNCT
ijassa-725	58	12	256	256	NUM
ijassa-725	58	13	gb	gb	NOUN
ijassa-725	58	14	ram	ram	NOUN
ijassa-725	58	15	,	,	PUNCT
ijassa-725	58	16	pcie	pcie	NOUN
ijassa-725	58	17	fabric	fabric	NOUN
ijassa-725	58	18	connection	connection	NOUN
ijassa-725	58	19	adapter	adapter	NOUN
ijassa-725	58	20	for	for	ADP
ijassa-725	58	21	data	datum	NOUN
ijassa-725	58	22	transfer	transfer	NOUN
ijassa-725	58	23	and	and	CCONJ
ijassa-725	58	24	2	2	NUM
ijassa-725	58	25	gigabit	gigabit	NOUN
ijassa-725	58	26	ethernet	ethernet	NOUN
ijassa-725	58	27	(	(	PUNCT
ijassa-725	58	28	gbe	gbe	NOUN
ijassa-725	58	29	)	)	PUNCT
ijassa-725	58	30	switches	switch	NOUN
ijassa-725	58	31	for	for	ADP
ijassa-725	58	32	internal	internal	ADJ
ijassa-725	58	33	network	network	NOUN
ijassa-725	58	34	.	.	PUNCT
ijassa-725	59	1	fabric	fabric	NOUN
ijassa-725	59	2	controller	controller	NOUN
ijassa-725	59	3	integrates	integrate	VERB
ijassa-725	59	4	all	all	DET
ijassa-725	59	5	components	component	NOUN
ijassa-725	59	6	of	of	ADP
ijassa-725	59	7	the	the	DET
ijassa-725	59	8	storage	storage	NOUN
ijassa-725	59	9	system	system	NOUN
ijassa-725	59	10	and	and	CCONJ
ijassa-725	59	11	provides	provide	VERB
ijassa-725	59	12	high	high	ADJ
ijassa-725	59	13	data	datum	NOUN
ijassa-725	59	14	operation	operation	NOUN
ijassa-725	59	15	performance	performance	NOUN
ijassa-725	59	16	using	use	VERB
ijassa-725	59	17	fast	fast	ADJ
ijassa-725	59	18	ssds	ssds	NOUN
ijassa-725	59	19	.	.	PUNCT
ijassa-725	60	1	it	it	PRON
ijassa-725	60	2	has	have	VERB
ijassa-725	60	3	up	up	ADP
ijassa-725	60	4	to	to	PART
ijassa-725	60	5	96	96	NUM
ijassa-725	60	6	ssds	ssds	NOUN
ijassa-725	60	7	with	with	ADP
ijassa-725	60	8	capacity	capacity	NOUN
ijassa-725	60	9	of	of	ADP
ijassa-725	60	10	2	2	NUM
ijassa-725	60	11	tb	tb	ADP
ijassa-725	60	12	each	each	PRON
ijassa-725	60	13	,	,	PUNCT
ijassa-725	60	14	2	2	NUM
ijassa-725	60	15	tb	tb	ADP
ijassa-725	60	16	ram	ram	NOUN
ijassa-725	60	17	cache	cache	NOUN
ijassa-725	60	18	,	,	PUNCT
ijassa-725	60	19	shared	share	VERB
ijassa-725	60	20	among	among	ADP
ijassa-725	60	21	storage	storage	NOUN
ijassa-725	60	22	controllers	controller	NOUN
ijassa-725	60	23	,	,	PUNCT
ijassa-725	60	24	4	4	NUM
ijassa-725	60	25	pcie	pcie	NOUN
ijassa-725	60	26	fabric	fabric	NOUN
ijassa-725	60	27	adapters	adapter	NOUN
ijassa-725	60	28	,	,	PUNCT
ijassa-725	60	29	gigabit	gigabit	VERB
ijassa-725	60	30	ethernet	ethernet	NOUN
ijassa-725	60	31	switch	switch	NOUN
ijassa-725	60	32	for	for	ADP
ijassa-725	60	33	internal	internal	ADJ
ijassa-725	60	34	network	network	NOUN
ijassa-725	60	35	and	and	CCONJ
ijassa-725	60	36	drive	drive	ADJ
ijassa-725	60	37	enclosure	enclosure	NOUN
ijassa-725	60	38	connection	connection	NOUN
ijassa-725	60	39	module	module	NOUN
ijassa-725	60	40	.	.	PUNCT
ijassa-725	61	1	drive	drive	VERB
ijassa-725	61	2	enclosures	enclosure	NOUN
ijassa-725	61	3	host	host	VERB
ijassa-725	61	4	up	up	ADP
ijassa-725	61	5	to	to	PART
ijassa-725	61	6	96	96	NUM
ijassa-725	61	7	serial	serial	ADJ
ijassa-725	61	8	attached	attach	VERB
ijassa-725	61	9	scsi	scsi	NOUN
ijassa-725	61	10	(	(	PUNCT
ijassa-725	61	11	sas	sas	PROPN
ijassa-725	61	12	)	)	PUNCT
ijassa-725	61	13	disks	disk	NOUN
ijassa-725	61	14	with	with	ADP
ijassa-725	61	15	capacity	capacity	NOUN
ijassa-725	61	16	of	of	ADP
ijassa-725	61	17	12	12	NUM
ijassa-725	61	18	tb	tb	ADP
ijassa-725	61	19	each	each	PRON
ijassa-725	61	20	to	to	PART
ijassa-725	61	21	provide	provide	VERB
ijassa-725	61	22	storage	storage	NOUN
ijassa-725	61	23	space	space	NOUN
ijassa-725	61	24	for	for	ADP
ijassa-725	61	25	data	datum	NOUN
ijassa-725	61	26	that	that	PRON
ijassa-725	61	27	does	do	AUX
ijassa-725	61	28	not	not	PART
ijassa-725	61	29	require	require	VERB
ijassa-725	61	30	high	high	ADJ
ijassa-725	61	31	speed	speed	NOUN
ijassa-725	61	32	of	of	ADP
ijassa-725	61	33	operations	operation	NOUN
ijassa-725	61	34	,	,	PUNCT
ijassa-725	61	35	compared	compare	VERB
ijassa-725	61	36	with	with	ADP
ijassa-725	61	37	ssd	ssd	NOUN
ijassa-725	61	38	.	.	PUNCT
ijassa-725	62	1	the	the	DET
ijassa-725	62	2	storage	storage	NOUN
ijassa-725	62	3	reliability	reliability	NOUN
ijassa-725	62	4	is	be	AUX
ijassa-725	62	5	provided	provide	VERB
ijassa-725	62	6	by	by	ADP
ijassa-725	62	7	policies	policy	NOUN
ijassa-725	62	8	based	base	VERB
ijassa-725	62	9	on	on	ADP
ijassa-725	62	10	reed	reed	PROPN
ijassa-725	62	11	-	-	PUNCT
ijassa-725	62	12	solomon	solomon	PROPN
ijassa-725	62	13	codes	code	NOUN
ijassa-725	62	14	with	with	ADP
ijassa-725	62	15	minimal	minimal	ADJ
ijassa-725	62	16	redundancy	redundancy	NOUN
ijassa-725	62	17	.	.	PUNCT
ijassa-725	63	1	it	it	PRON
ijassa-725	63	2	uses	use	VERB
ijassa-725	63	3	25	25	NUM
ijassa-725	63	4	%	%	NOUN
ijassa-725	63	5	redundancy	redundancy	NOUN
ijassa-725	63	6	that	that	PRON
ijassa-725	63	7	supports	support	VERB
ijassa-725	63	8	simultaneous	simultaneous	ADJ
ijassa-725	63	9	failure	failure	NOUN
ijassa-725	63	10	of	of	ADP
ijassa-725	63	11	2	2	NUM
ijassa-725	63	12	drivers	driver	NOUN
ijassa-725	63	13	in	in	ADP
ijassa-725	63	14	8	8	NUM
ijassa-725	63	15	data	datum	NOUN
ijassa-725	63	16	copyright	copyright	NOUN
ijassa-725	63	17	c	c	ADP
ijassa-725	63	18	©	©	PROPN
ijassa-725	63	19	2019	2019	NUM
ijassa-725	63	20	assa	assa	NOUN
ijassa-725	63	21	.	.	PUNCT
ijassa-725	64	1	adv	adv	PROPN
ijassa-725	64	2	syst	syst	PROPN
ijassa-725	64	3	sci	sci	PROPN
ijassa-725	64	4	appl	appl	PROPN
ijassa-725	64	5	(	(	PUNCT
ijassa-725	64	6	2019	2019	NUM
ijassa-725	64	7	)	)	PUNCT
ijassa-725	64	8	25	25	NUM
ijassa-725	64	9	fig	fig	NOUN
ijassa-725	64	10	.	.	PUNCT
ijassa-725	65	1	3.1	3.1	NUM
ijassa-725	65	2	.	.	PUNCT
ijassa-725	66	1	tatlin	tatlin	ADJ
ijassa-725	66	2	storage	storage	NOUN
ijassa-725	66	3	system	system	NOUN
ijassa-725	66	4	.	.	PUNCT
ijassa-725	67	1	+	+	CCONJ
ijassa-725	67	2	2	2	NUM
ijassa-725	67	3	parity	parity	NOUN
ijassa-725	67	4	drives	drive	VERB
ijassa-725	67	5	configuration	configuration	NOUN
ijassa-725	67	6	.	.	PUNCT
ijassa-725	68	1	the	the	DET
ijassa-725	68	2	fabric	fabric	NOUN
ijassa-725	68	3	controllers	controller	NOUN
ijassa-725	68	4	provide	provide	VERB
ijassa-725	68	5	shared	shared	ADJ
ijassa-725	68	6	access	access	NOUN
ijassa-725	68	7	to	to	ADP
ijassa-725	68	8	the	the	DET
ijassa-725	68	9	entire	entire	ADJ
ijassa-725	68	10	storage	storage	NOUN
ijassa-725	68	11	space	space	NOUN
ijassa-725	68	12	for	for	ADP
ijassa-725	68	13	all	all	DET
ijassa-725	68	14	storage	storage	NOUN
ijassa-725	68	15	controllers	controller	NOUN
ijassa-725	68	16	.	.	PUNCT
ijassa-725	69	1	shared	share	VERB
ijassa-725	69	2	ram	ram	NOUN
ijassa-725	69	3	cache	cache	NOUN
ijassa-725	69	4	gives	give	VERB
ijassa-725	69	5	hardware	hardware	NOUN
ijassa-725	69	6	improvement	improvement	NOUN
ijassa-725	69	7	by	by	ADP
ijassa-725	69	8	reducing	reduce	VERB
ijassa-725	69	9	cpu	cpu	NOUN
ijassa-725	69	10	load	load	NOUN
ijassa-725	69	11	in	in	ADP
ijassa-725	69	12	storage	storage	NOUN
ijassa-725	69	13	controllers	controller	NOUN
ijassa-725	69	14	for	for	ADP
ijassa-725	69	15	intensive	intensive	ADJ
ijassa-725	69	16	data	datum	NOUN
ijassa-725	69	17	operations	operation	NOUN
ijassa-725	69	18	.	.	PUNCT
ijassa-725	70	1	the	the	DET
ijassa-725	70	2	storage	storage	NOUN
ijassa-725	70	3	design	design	NOUN
ijassa-725	70	4	excludes	exclude	VERB
ijassa-725	70	5	one	one	NUM
ijassa-725	70	6	point	point	NOUN
ijassa-725	70	7	failure	failure	NOUN
ijassa-725	70	8	.	.	PUNCT
ijassa-725	71	1	4	4	X
ijassa-725	71	2	.	.	X
ijassa-725	71	3	anomalies	anomaly	NOUN
ijassa-725	71	4	detection	detection	VERB
ijassa-725	71	5	4.1	4.1	NUM
ijassa-725	71	6	.	.	PUNCT
ijassa-725	72	1	collected	collect	VERB
ijassa-725	72	2	data	datum	NOUN
ijassa-725	72	3	behaviour	behaviour	NOUN
ijassa-725	72	4	of	of	ADP
ijassa-725	72	5	each	each	DET
ijassa-725	72	6	component	component	NOUN
ijassa-725	72	7	of	of	ADP
ijassa-725	72	8	the	the	DET
ijassa-725	72	9	storage	storage	NOUN
ijassa-725	72	10	system	system	NOUN
ijassa-725	72	11	is	be	AUX
ijassa-725	72	12	described	describe	VERB
ijassa-725	72	13	by	by	ADP
ijassa-725	72	14	a	a	DET
ijassa-725	72	15	set	set	NOUN
ijassa-725	72	16	of	of	ADP
ijassa-725	72	17	parameters	parameter	NOUN
ijassa-725	72	18	,	,	PUNCT
ijassa-725	72	19	that	that	PRON
ijassa-725	72	20	are	be	AUX
ijassa-725	72	21	used	use	VERB
ijassa-725	72	22	for	for	ADP
ijassa-725	72	23	anomalies	anomaly	NOUN
ijassa-725	72	24	detection	detection	NOUN
ijassa-725	72	25	.	.	PUNCT
ijassa-725	73	1	examples	example	NOUN
ijassa-725	73	2	of	of	ADP
ijassa-725	73	3	these	these	DET
ijassa-725	73	4	parameters	parameter	NOUN
ijassa-725	73	5	are	be	AUX
ijassa-725	73	6	cpus	cpus	NOUN
ijassa-725	73	7	and	and	CCONJ
ijassa-725	73	8	ram	ram	NOUN
ijassa-725	73	9	usage	usage	NOUN
ijassa-725	73	10	,	,	PUNCT
ijassa-725	73	11	cpus	cpus	NOUN
ijassa-725	73	12	temperatures	temperature	NOUN
ijassa-725	73	13	and	and	CCONJ
ijassa-725	73	14	fan	fan	NOUN
ijassa-725	73	15	speed	speed	NOUN
ijassa-725	73	16	for	for	ADP
ijassa-725	73	17	storage	storage	NOUN
ijassa-725	73	18	controllers	controller	NOUN
ijassa-725	73	19	,	,	PUNCT
ijassa-725	73	20	input	input	NOUN
ijassa-725	73	21	and	and	CCONJ
ijassa-725	73	22	output	output	NOUN
ijassa-725	73	23	traffics	traffic	NOUN
ijassa-725	73	24	for	for	ADP
ijassa-725	73	25	network	network	NOUN
ijassa-725	73	26	interfaces	interface	NOUN
ijassa-725	73	27	,	,	PUNCT
ijassa-725	73	28	smart	smart	ADJ
ijassa-725	73	29	data	datum	NOUN
ijassa-725	73	30	for	for	ADP
ijassa-725	73	31	ssds	ssds	NOUN
ijassa-725	73	32	and	and	CCONJ
ijassa-725	73	33	sas	sas	PROPN
ijassa-725	73	34	drives	drive	NOUN
ijassa-725	73	35	and	and	CCONJ
ijassa-725	73	36	others	other	NOUN
ijassa-725	73	37	.	.	PUNCT
ijassa-725	74	1	except	except	SCONJ
ijassa-725	74	2	hardware	hardware	NOUN
ijassa-725	74	3	components	component	NOUN
ijassa-725	74	4	information	information	NOUN
ijassa-725	74	5	about	about	ADP
ijassa-725	74	6	logical	logical	ADJ
ijassa-725	74	7	data	datum	NOUN
ijassa-725	74	8	volumes	volume	NOUN
ijassa-725	74	9	inside	inside	ADP
ijassa-725	74	10	storage	storage	NOUN
ijassa-725	74	11	pools	pool	NOUN
ijassa-725	74	12	is	be	AUX
ijassa-725	74	13	collected	collect	VERB
ijassa-725	74	14	.	.	PUNCT
ijassa-725	75	1	each	each	DET
ijassa-725	75	2	volume	volume	NOUN
ijassa-725	75	3	is	be	AUX
ijassa-725	75	4	described	describe	VERB
ijassa-725	75	5	by	by	ADP
ijassa-725	75	6	storage	storage	NOUN
ijassa-725	75	7	pool	pool	NOUN
ijassa-725	75	8	i	i	PROPN
ijassa-725	75	9	d	d	PROPN
ijassa-725	75	10	,	,	PUNCT
ijassa-725	75	11	capacity	capacity	NOUN
ijassa-725	75	12	,	,	PUNCT
ijassa-725	75	13	state	state	NOUN
ijassa-725	75	14	,	,	PUNCT
ijassa-725	75	15	read	read	VERB
ijassa-725	75	16	and	and	CCONJ
ijassa-725	75	17	write	write	VERB
ijassa-725	75	18	speed	speed	NOUN
ijassa-725	75	19	for	for	ADP
ijassa-725	75	20	each	each	DET
ijassa-725	75	21	storage	storage	NOUN
ijassa-725	75	22	controller	controller	NOUN
ijassa-725	75	23	,	,	PUNCT
ijassa-725	75	24	number	number	NOUN
ijassa-725	75	25	of	of	ADP
ijassa-725	75	26	read	read	NOUN
ijassa-725	75	27	and	and	CCONJ
ijassa-725	75	28	write	write	VERB
ijassa-725	75	29	operations	operation	NOUN
ijassa-725	75	30	,	,	PUNCT
ijassa-725	75	31	average	average	ADJ
ijassa-725	75	32	request	request	NOUN
ijassa-725	75	33	processing	processing	NOUN
ijassa-725	75	34	time	time	NOUN
ijassa-725	75	35	,	,	PUNCT
ijassa-725	75	36	average	average	ADJ
ijassa-725	75	37	request	request	NOUN
ijassa-725	75	38	queue	queue	NOUN
ijassa-725	75	39	size	size	NOUN
ijassa-725	75	40	etc	etc	X
ijassa-725	75	41	..	..	X
ijassa-725	75	42	several	several	ADJ
ijassa-725	75	43	of	of	ADP
ijassa-725	75	44	known	know	VERB
ijassa-725	75	45	hardware	hardware	NOUN
ijassa-725	75	46	failures	failure	NOUN
ijassa-725	75	47	for	for	ADP
ijassa-725	75	48	the	the	DET
ijassa-725	75	49	all	all	DET
ijassa-725	75	50	components	component	NOUN
ijassa-725	75	51	are	be	AUX
ijassa-725	75	52	generated	generate	VERB
ijassa-725	75	53	to	to	PART
ijassa-725	75	54	test	test	VERB
ijassa-725	75	55	algorithms	algorithm	NOUN
ijassa-725	75	56	of	of	ADP
ijassa-725	75	57	anomalies	anomaly	NOUN
ijassa-725	75	58	detection	detection	NOUN
ijassa-725	75	59	.	.	PUNCT
ijassa-725	76	1	parameters	parameter	NOUN
ijassa-725	76	2	are	be	AUX
ijassa-725	76	3	measured	measure	VERB
ijassa-725	76	4	approximately	approximately	ADV
ijassa-725	76	5	every	every	DET
ijassa-725	76	6	20	20	NUM
ijassa-725	76	7	seconds	second	NOUN
ijassa-725	76	8	and	and	CCONJ
ijassa-725	76	9	saved	save	VERB
ijassa-725	76	10	for	for	ADP
ijassa-725	76	11	the	the	DET
ijassa-725	76	12	further	further	ADJ
ijassa-725	76	13	analysis	analysis	NOUN
ijassa-725	76	14	.	.	PUNCT
ijassa-725	77	1	for	for	SCONJ
ijassa-725	77	2	each	each	DET
ijassa-725	77	3	measurement	measurement	NOUN
ijassa-725	77	4	true	true	ADJ
ijassa-725	77	5	state	state	NOUN
ijassa-725	77	6	is	be	AUX
ijassa-725	77	7	recorded	record	VERB
ijassa-725	77	8	.	.	PUNCT
ijassa-725	78	1	there	there	PRON
ijassa-725	78	2	are	be	VERB
ijassa-725	78	3	two	two	NUM
ijassa-725	78	4	possible	possible	ADJ
ijassa-725	78	5	states	state	NOUN
ijassa-725	78	6	:	:	PUNCT
ijassa-725	78	7	normal	normal	ADJ
ijassa-725	78	8	and	and	CCONJ
ijassa-725	78	9	failure	failure	NOUN
ijassa-725	78	10	.	.	PUNCT
ijassa-725	79	1	measurements	measurement	NOUN
ijassa-725	79	2	of	of	ADP
ijassa-725	79	3	a	a	DET
ijassa-725	79	4	component	component	NOUN
ijassa-725	79	5	parameter	parameter	NOUN
ijassa-725	79	6	are	be	AUX
ijassa-725	79	7	represented	represent	VERB
ijassa-725	79	8	as	as	ADP
ijassa-725	79	9	a	a	DET
ijassa-725	79	10	time	time	NOUN
ijassa-725	79	11	series	series	NOUN
ijassa-725	79	12	{	{	PUNCT
ijassa-725	79	13	(	(	PUNCT
ijassa-725	79	14	ti	ti	NOUN
ijassa-725	79	15	,	,	PUNCT
ijassa-725	79	16	xi)}ni=1	xi)}ni=1	PROPN
ijassa-725	79	17	,	,	PUNCT
ijassa-725	79	18	where	where	SCONJ
ijassa-725	79	19	xi	xi	PROPN
ijassa-725	79	20	is	be	AUX
ijassa-725	79	21	a	a	DET
ijassa-725	79	22	measured	measured	ADJ
ijassa-725	79	23	parameter	parameter	NOUN
ijassa-725	79	24	value	value	NOUN
ijassa-725	79	25	and	and	CCONJ
ijassa-725	79	26	ti	ti	NOUN
ijassa-725	79	27	is	be	AUX
ijassa-725	79	28	a	a	DET
ijassa-725	79	29	timestamp	timestamp	NOUN
ijassa-725	79	30	of	of	ADP
ijassa-725	79	31	the	the	DET
ijassa-725	79	32	measurement	measurement	NOUN
ijassa-725	79	33	.	.	PUNCT
ijassa-725	80	1	each	each	DET
ijassa-725	80	2	time	time	NOUN
ijassa-725	80	3	series	series	PROPN
ijassa-725	80	4	is	be	AUX
ijassa-725	80	5	divided	divide	VERB
ijassa-725	80	6	into	into	ADP
ijassa-725	80	7	time	time	NOUN
ijassa-725	80	8	bins	bin	NOUN
ijassa-725	80	9	with	with	ADP
ijassa-725	80	10	defined	define	VERB
ijassa-725	80	11	width	width	NOUN
ijassa-725	80	12	.	.	PUNCT
ijassa-725	81	1	all	all	DET
ijassa-725	81	2	measurements	measurement	NOUN
ijassa-725	81	3	inside	inside	ADP
ijassa-725	81	4	one	one	NUM
ijassa-725	81	5	bin	bin	NOUN
ijassa-725	81	6	are	be	AUX
ijassa-725	81	7	averaged	average	VERB
ijassa-725	81	8	.	.	PUNCT
ijassa-725	82	1	this	this	DET
ijassa-725	82	2	aggregation	aggregation	NOUN
ijassa-725	82	3	helps	help	VERB
ijassa-725	82	4	to	to	PART
ijassa-725	82	5	reduce	reduce	VERB
ijassa-725	82	6	noise	noise	NOUN
ijassa-725	82	7	of	of	ADP
ijassa-725	82	8	the	the	DET
ijassa-725	82	9	measurements	measurement	NOUN
ijassa-725	82	10	and	and	CCONJ
ijassa-725	82	11	to	to	PART
ijassa-725	82	12	create	create	VERB
ijassa-725	82	13	timeregular	timeregular	ADJ
ijassa-725	82	14	observations	observation	NOUN
ijassa-725	82	15	of	of	ADP
ijassa-725	82	16	the	the	DET
ijassa-725	82	17	parameters	parameter	NOUN
ijassa-725	82	18	for	for	ADP
ijassa-725	82	19	further	further	ADJ
ijassa-725	82	20	steps	step	NOUN
ijassa-725	82	21	of	of	ADP
ijassa-725	82	22	the	the	DET
ijassa-725	82	23	analysis	analysis	NOUN
ijassa-725	82	24	.	.	PUNCT
ijassa-725	83	1	an	an	DET
ijassa-725	83	2	example	example	NOUN
ijassa-725	83	3	of	of	ADP
ijassa-725	83	4	time	time	NOUN
ijassa-725	83	5	series	series	PROPN
ijassa-725	83	6	after	after	ADP
ijassa-725	83	7	aggregation	aggregation	NOUN
ijassa-725	83	8	with	with	ADP
ijassa-725	83	9	width	width	ADJ
ijassa-725	83	10	=	=	NOUN
ijassa-725	83	11	60s	60	NOUN
ijassa-725	83	12	is	be	AUX
ijassa-725	83	13	demonstrated	demonstrate	VERB
ijassa-725	83	14	in	in	ADP
ijassa-725	83	15	fig	fig	NOUN
ijassa-725	83	16	.	.	PUNCT
ijassa-725	84	1	4.2	4.2	NUM
ijassa-725	84	2	.	.	PUNCT
ijassa-725	85	1	copyright	copyright	NOUN
ijassa-725	85	2	c	c	ADP
ijassa-725	85	3	©	©	PROPN
ijassa-725	85	4	2019	2019	NUM
ijassa-725	85	5	assa	assa	NOUN
ijassa-725	85	6	.	.	PUNCT
ijassa-725	86	1	adv	adv	PROPN
ijassa-725	86	2	syst	syst	PROPN
ijassa-725	86	3	sci	sci	PROPN
ijassa-725	86	4	appl	appl	PROPN
ijassa-725	86	5	(	(	PUNCT
ijassa-725	86	6	2019	2019	NUM
ijassa-725	86	7	)	)	PUNCT
ijassa-725	86	8	26	26	NUM
ijassa-725	86	9	anomaly	anomaly	NOUN
ijassa-725	86	10	anomaly	anomaly	NOUN
ijassa-725	86	11	anomalyanomaly	anomalyanomaly	PROPN
ijassa-725	86	12	fig	fig	NOUN
ijassa-725	86	13	.	.	PUNCT
ijassa-725	87	1	4.2	4.2	NUM
ijassa-725	87	2	.	.	PUNCT
ijassa-725	88	1	(	(	PUNCT
ijassa-725	88	2	top	top	ADJ
ijassa-725	88	3	)	)	PUNCT
ijassa-725	88	4	time	time	NOUN
ijassa-725	88	5	series	series	NOUN
ijassa-725	88	6	of	of	ADP
ijassa-725	88	7	percentage	percentage	NOUN
ijassa-725	88	8	of	of	ADP
ijassa-725	88	9	cpu	cpu	ADJ
ijassa-725	88	10	usage	usage	NOUN
ijassa-725	88	11	for	for	ADP
ijassa-725	88	12	one	one	NUM
ijassa-725	88	13	of	of	ADP
ijassa-725	88	14	the	the	DET
ijassa-725	88	15	storage	storage	NOUN
ijassa-725	88	16	components	component	NOUN
ijassa-725	88	17	of	of	ADP
ijassa-725	88	18	the	the	DET
ijassa-725	88	19	storage	storage	NOUN
ijassa-725	88	20	system	system	NOUN
ijassa-725	88	21	after	after	ADP
ijassa-725	88	22	aggregation	aggregation	NOUN
ijassa-725	88	23	.	.	PUNCT
ijassa-725	89	1	(	(	PUNCT
ijassa-725	89	2	middle	middle	ADJ
ijassa-725	89	3	)	)	PUNCT
ijassa-725	89	4	residual	residual	ADJ
ijassa-725	89	5	errors	error	NOUN
ijassa-725	89	6	for	for	ADP
ijassa-725	89	7	the	the	DET
ijassa-725	89	8	time	time	NOUN
ijassa-725	89	9	series	series	PROPN
ijassa-725	89	10	prediction	prediction	PROPN
ijassa-725	89	11	.	.	PUNCT
ijassa-725	90	1	(	(	PUNCT
ijassa-725	90	2	bottom	bottom	ADJ
ijassa-725	90	3	)	)	PUNCT
ijassa-725	90	4	cusum	cusum	NOUN
ijassa-725	90	5	test	test	NOUN
ijassa-725	90	6	values	value	NOUN
ijassa-725	90	7	for	for	ADP
ijassa-725	90	8	the	the	DET
ijassa-725	90	9	anomalies	anomaly	NOUN
ijassa-725	90	10	detection	detection	NOUN
ijassa-725	90	11	.	.	PUNCT
ijassa-725	91	1	4.2	4.2	NUM
ijassa-725	91	2	.	.	PUNCT
ijassa-725	91	3	time	time	NOUN
ijassa-725	91	4	series	series	PROPN
ijassa-725	91	5	analysis	analysis	NOUN
ijassa-725	91	6	consider	consider	VERB
ijassa-725	91	7	time	time	NOUN
ijassa-725	91	8	series	series	NOUN
ijassa-725	91	9	analysis	analysis	NOUN
ijassa-725	91	10	methods	method	NOUN
ijassa-725	91	11	to	to	PART
ijassa-725	91	12	detect	detect	VERB
ijassa-725	91	13	anomalies	anomaly	NOUN
ijassa-725	91	14	.	.	PUNCT
ijassa-725	92	1	time	time	NOUN
ijassa-725	92	2	series	series	PROPN
ijassa-725	92	3	analysis	analysis	NOUN
ijassa-725	92	4	is	be	AUX
ijassa-725	92	5	used	use	VERB
ijassa-725	92	6	to	to	PART
ijassa-725	92	7	predict	predict	VERB
ijassa-725	92	8	parameter	parameter	NOUN
ijassa-725	92	9	values	value	NOUN
ijassa-725	92	10	of	of	ADP
ijassa-725	92	11	a	a	DET
ijassa-725	92	12	component	component	NOUN
ijassa-725	92	13	.	.	PUNCT
ijassa-725	93	1	to	to	PART
ijassa-725	93	2	do	do	VERB
ijassa-725	93	3	this	this	DET
ijassa-725	93	4	vector	vector	NOUN
ijassa-725	93	5	autoregression	autoregression	NOUN
ijassa-725	93	6	(	(	PUNCT
ijassa-725	93	7	var	var	NOUN
ijassa-725	93	8	)	)	PUNCT
ijassa-725	93	9	model	model	NOUN
ijassa-725	94	1	[	[	X
ijassa-725	94	2	23	23	NUM
ijassa-725	94	3	]	]	PUNCT
ijassa-725	94	4	is	be	AUX
ijassa-725	94	5	used	use	VERB
ijassa-725	94	6	.	.	PUNCT
ijassa-725	95	1	the	the	DET
ijassa-725	95	2	principle	principle	NOUN
ijassa-725	95	3	of	of	ADP
ijassa-725	95	4	the	the	DET
ijassa-725	95	5	model	model	NOUN
ijassa-725	95	6	is	be	AUX
ijassa-725	95	7	following	follow	VERB
ijassa-725	95	8	.	.	PUNCT
ijassa-725	96	1	suppose	suppose	VERB
ijassa-725	96	2	a	a	DET
ijassa-725	96	3	group	group	NOUN
ijassa-725	96	4	of	of	ADP
ijassa-725	96	5	m	m	PROPN
ijassa-725	96	6	time	time	NOUN
ijassa-725	96	7	series	series	NOUN
ijassa-725	96	8	is	be	AUX
ijassa-725	96	9	given	give	VERB
ijassa-725	96	10	:	:	PUNCT
ijassa-725	96	11	{	{	PUNCT
ijassa-725	96	12	yi1	yi1	INTJ
ijassa-725	96	13	,	,	PUNCT
ijassa-725	96	14	yi2	yi2	PROPN
ijassa-725	96	15	,	,	PUNCT
ijassa-725	96	16	...	...	PUNCT
ijassa-725	96	17	,	,	PUNCT
ijassa-725	96	18	yit}mi=1	yit}mi=1	NUM
ijassa-725	96	19	,	,	PUNCT
ijassa-725	96	20	where	where	SCONJ
ijassa-725	96	21	yit	yit	PROPN
ijassa-725	96	22	is	be	AUX
ijassa-725	96	23	t	t	PROPN
ijassa-725	96	24	-	-	PUNCT
ijassa-725	96	25	th	th	X
ijassa-725	96	26	measurement	measurement	NOUN
ijassa-725	96	27	of	of	ADP
ijassa-725	96	28	i	i	PROPN
ijassa-725	96	29	-	-	PUNCT
ijassa-725	96	30	th	th	PROPN
ijassa-725	96	31	time	time	NOUN
ijassa-725	96	32	series	series	NOUN
ijassa-725	96	33	.	.	PUNCT
ijassa-725	97	1	measurements	measurement	NOUN
ijassa-725	97	2	of	of	ADP
ijassa-725	97	3	all	all	DET
ijassa-725	97	4	time	time	NOUN
ijassa-725	97	5	series	series	NOUN
ijassa-725	97	6	with	with	ADP
ijassa-725	97	7	the	the	DET
ijassa-725	97	8	same	same	ADJ
ijassa-725	97	9	t	t	NOUN
ijassa-725	97	10	are	be	AUX
ijassa-725	97	11	grouped	group	VERB
ijassa-725	97	12	into	into	ADP
ijassa-725	97	13	a	a	DET
ijassa-725	97	14	vector	vector	NOUN
ijassa-725	97	15	yt	yt	NOUN
ijassa-725	97	16	=	=	SYM
ijassa-725	97	17	(	(	PUNCT
ijassa-725	97	18	y1	y1	INTJ
ijassa-725	97	19	t	t	NOUN
ijassa-725	97	20	y2	y2	PROPN
ijassa-725	97	21	t	t	PROPN
ijassa-725	97	22	·	·	PUNCT
ijassa-725	97	23	·	·	PUNCT
ijassa-725	97	24	·	·	PUNCT
ijassa-725	97	25	ymt	ymt	X
ijassa-725	97	26	)	)	PUNCT
ijassa-725	97	27	t	t	PROPN
ijassa-725	97	28	.	.	PUNCT
ijassa-725	98	1	var	var	PROPN
ijassa-725	98	2	model	model	PROPN
ijassa-725	98	3	supposes	suppose	VERB
ijassa-725	98	4	that	that	SCONJ
ijassa-725	98	5	a	a	DET
ijassa-725	98	6	vector	vector	NOUN
ijassa-725	98	7	of	of	ADP
ijassa-725	98	8	predicted	predict	VERB
ijassa-725	98	9	parameters	parameter	NOUN
ijassa-725	98	10	values	value	NOUN
ijassa-725	98	11	ŷt	ŷt	VERB
ijassa-725	98	12	is	be	AUX
ijassa-725	98	13	a	a	DET
ijassa-725	98	14	function	function	NOUN
ijassa-725	98	15	of	of	ADP
ijassa-725	98	16	previous	previous	ADJ
ijassa-725	98	17	k	k	PROPN
ijassa-725	98	18	measurements	measurement	NOUN
ijassa-725	98	19	:	:	PUNCT
ijassa-725	98	20	ŷt	ŷt	PROPN
ijassa-725	98	21	=	=	SYM
ijassa-725	98	22	f(yt−1	f(yt−1	NOUN
ijassa-725	98	23	,	,	PUNCT
ijassa-725	98	24	yt−2	yt−2	NOUN
ijassa-725	98	25	,	,	PUNCT
ijassa-725	98	26	...	...	PUNCT
ijassa-725	98	27	,	,	PUNCT
ijassa-725	98	28	yt−k	yt−k	NOUN
ijassa-725	98	29	)	)	PUNCT
ijassa-725	98	30	(	(	PUNCT
ijassa-725	98	31	4.1	4.1	NUM
ijassa-725	98	32	)	)	PUNCT
ijassa-725	98	33	where	where	SCONJ
ijassa-725	98	34	ŷt	ŷt	PROPN
ijassa-725	98	35	is	be	AUX
ijassa-725	98	36	a	a	DET
ijassa-725	98	37	predicted	predict	VERB
ijassa-725	98	38	vector	vector	NOUN
ijassa-725	98	39	of	of	ADP
ijassa-725	98	40	parameters	parameter	NOUN
ijassa-725	98	41	values	value	NOUN
ijassa-725	98	42	;	;	PUNCT
ijassa-725	98	43	yt	yt	NOUN
ijassa-725	98	44	is	be	AUX
ijassa-725	98	45	a	a	DET
ijassa-725	98	46	vector	vector	NOUN
ijassa-725	98	47	of	of	ADP
ijassa-725	98	48	measured	measure	VERB
ijassa-725	98	49	values	value	NOUN
ijassa-725	98	50	of	of	ADP
ijassa-725	98	51	the	the	DET
ijassa-725	98	52	parameters	parameter	NOUN
ijassa-725	98	53	.	.	PUNCT
ijassa-725	99	1	for	for	ADP
ijassa-725	99	2	simplicity	simplicity	NOUN
ijassa-725	99	3	each	each	DET
ijassa-725	99	4	time	time	NOUN
ijassa-725	99	5	series	series	PROPN
ijassa-725	99	6	has	have	VERB
ijassa-725	99	7	its	its	PRON
ijassa-725	99	8	own	own	ADJ
ijassa-725	99	9	prediction	prediction	NOUN
ijassa-725	99	10	model	model	NOUN
ijassa-725	99	11	:	:	PUNCT
ijassa-725	99	12	ŷit	ŷit	NOUN
ijassa-725	99	13	=	=	PROPN
ijassa-725	99	14	fi(yt−1	fi(yt−1	PROPN
ijassa-725	99	15	,	,	PUNCT
ijassa-725	99	16	yt−2	yt−2	NOUN
ijassa-725	99	17	,	,	PUNCT
ijassa-725	99	18	...	...	PUNCT
ijassa-725	99	19	,	,	PUNCT
ijassa-725	99	20	yt−k	yt−k	NOUN
ijassa-725	99	21	)	)	PUNCT
ijassa-725	99	22	(	(	PUNCT
ijassa-725	99	23	4.2	4.2	NUM
ijassa-725	99	24	)	)	PUNCT
ijassa-725	99	25	where	where	SCONJ
ijassa-725	99	26	ŷit	ŷit	NOUN
ijassa-725	99	27	is	be	AUX
ijassa-725	99	28	a	a	DET
ijassa-725	99	29	predicted	predict	VERB
ijassa-725	99	30	value	value	NOUN
ijassa-725	99	31	for	for	ADP
ijassa-725	99	32	i	i	PROPN
ijassa-725	99	33	-	-	PUNCT
ijassa-725	99	34	th	th	NUM
ijassa-725	99	35	time	time	NOUN
ijassa-725	99	36	series	series	NOUN
ijassa-725	99	37	.	.	PUNCT
ijassa-725	100	1	to	to	PART
ijassa-725	100	2	approximate	approximate	VERB
ijassa-725	100	3	the	the	DET
ijassa-725	100	4	functions	function	NOUN
ijassa-725	100	5	fi	fi	NOUN
ijassa-725	100	6	different	different	ADJ
ijassa-725	100	7	machine	machine	NOUN
ijassa-725	100	8	learning	learn	VERB
ijassa-725	100	9	algorithms	algorithm	NOUN
ijassa-725	100	10	[	[	X
ijassa-725	100	11	17	17	NUM
ijassa-725	100	12	]	]	PUNCT
ijassa-725	100	13	for	for	ADP
ijassa-725	100	14	the	the	DET
ijassa-725	100	15	regression	regression	NOUN
ijassa-725	100	16	problem	problem	NOUN
ijassa-725	100	17	are	be	AUX
ijassa-725	100	18	used	use	VERB
ijassa-725	100	19	:	:	PUNCT
ijassa-725	100	20	linear	linear	ADJ
ijassa-725	100	21	regression	regression	NOUN
ijassa-725	100	22	model	model	NOUN
ijassa-725	100	23	,	,	PUNCT
ijassa-725	100	24	shallow	shallow	ADJ
ijassa-725	100	25	neural	neural	ADJ
ijassa-725	100	26	networks	network	NOUN
ijassa-725	100	27	,	,	PUNCT
ijassa-725	100	28	random	random	ADJ
ijassa-725	100	29	forest	forest	NOUN
ijassa-725	100	30	and	and	CCONJ
ijassa-725	100	31	gradient	gradient	NOUN
ijassa-725	100	32	boosting	boost	VERB
ijassa-725	100	33	over	over	ADP
ijassa-725	100	34	decision	decision	NOUN
ijassa-725	100	35	trees	tree	NOUN
ijassa-725	100	36	regressions	regression	NOUN
ijassa-725	100	37	.	.	PUNCT
ijassa-725	101	1	these	these	DET
ijassa-725	101	2	algorithms	algorithm	NOUN
ijassa-725	101	3	are	be	AUX
ijassa-725	101	4	selected	select	VERB
ijassa-725	101	5	because	because	SCONJ
ijassa-725	101	6	they	they	PRON
ijassa-725	101	7	demonstrate	demonstrate	VERB
ijassa-725	101	8	high	high	ADJ
ijassa-725	101	9	quality	quality	NOUN
ijassa-725	101	10	of	of	ADP
ijassa-725	101	11	the	the	DET
ijassa-725	101	12	prediction	prediction	NOUN
ijassa-725	101	13	and	and	CCONJ
ijassa-725	101	14	work	work	VERB
ijassa-725	101	15	well	well	ADV
ijassa-725	101	16	with	with	ADP
ijassa-725	101	17	multivariate	multivariate	NOUN
ijassa-725	101	18	time	time	NOUN
ijassa-725	101	19	series	series	NOUN
ijassa-725	101	20	.	.	PUNCT
ijassa-725	102	1	the	the	DET
ijassa-725	102	2	models	model	NOUN
ijassa-725	102	3	are	be	AUX
ijassa-725	102	4	trained	train	VERB
ijassa-725	102	5	with	with	ADP
ijassa-725	102	6	the	the	DET
ijassa-725	102	7	following	follow	VERB
ijassa-725	102	8	loss	loss	NOUN
ijassa-725	102	9	function	function	NOUN
ijassa-725	102	10	:	:	PUNCT
ijassa-725	102	11	l	l	X
ijassa-725	102	12	=	=	PUNCT
ijassa-725	102	13	∑	∑	PUNCT
ijassa-725	102	14	t	t	PROPN
ijassa-725	102	15	(	(	PUNCT
ijassa-725	102	16	ŷit	ŷit	NOUN
ijassa-725	102	17	−	−	PROPN
ijassa-725	102	18	yit)2	yit)2	PROPN
ijassa-725	102	19	(	(	PUNCT
ijassa-725	102	20	4.3	4.3	NUM
ijassa-725	102	21	)	)	PUNCT
ijassa-725	102	22	copyright	copyright	NOUN
ijassa-725	102	23	c	c	ADP
ijassa-725	102	24	©	©	PROPN
ijassa-725	102	25	2019	2019	NUM
ijassa-725	102	26	assa	assa	NOUN
ijassa-725	102	27	.	.	PUNCT
ijassa-725	103	1	adv	adv	PROPN
ijassa-725	103	2	syst	syst	PROPN
ijassa-725	103	3	sci	sci	PROPN
ijassa-725	103	4	appl	appl	PROPN
ijassa-725	103	5	(	(	PUNCT
ijassa-725	103	6	2019	2019	NUM
ijassa-725	103	7	)	)	PUNCT
ijassa-725	103	8	27	27	NUM
ijassa-725	103	9	parameters	parameter	NOUN
ijassa-725	103	10	of	of	ADP
ijassa-725	103	11	the	the	DET
ijassa-725	103	12	models	model	NOUN
ijassa-725	103	13	are	be	AUX
ijassa-725	103	14	optimized	optimize	VERB
ijassa-725	103	15	using	use	VERB
ijassa-725	103	16	grid	grid	NOUN
ijassa-725	103	17	search	search	NOUN
ijassa-725	103	18	.	.	PUNCT
ijassa-725	104	1	the	the	DET
ijassa-725	104	2	model	model	NOUN
ijassa-725	104	3	with	with	ADP
ijassa-725	104	4	the	the	DET
ijassa-725	104	5	lowest	low	ADJ
ijassa-725	104	6	loss	loss	NOUN
ijassa-725	104	7	function	function	NOUN
ijassa-725	104	8	value	value	NOUN
ijassa-725	104	9	on	on	ADP
ijassa-725	104	10	the	the	DET
ijassa-725	104	11	validation	validation	NOUN
ijassa-725	104	12	sample	sample	NOUN
ijassa-725	104	13	wins	win	NOUN
ijassa-725	104	14	and	and	CCONJ
ijassa-725	104	15	used	use	VERB
ijassa-725	104	16	for	for	ADP
ijassa-725	104	17	anomalies	anomaly	NOUN
ijassa-725	104	18	detection	detection	NOUN
ijassa-725	104	19	.	.	PUNCT
ijassa-725	105	1	for	for	ADP
ijassa-725	105	2	each	each	DET
ijassa-725	105	3	time	time	NOUN
ijassa-725	105	4	series	series	PROPN
ijassa-725	105	5	residual	residual	ADJ
ijassa-725	105	6	errors	error	NOUN
ijassa-725	105	7	rit	rit	NOUN
ijassa-725	105	8	are	be	AUX
ijassa-725	105	9	calculated	calculate	VERB
ijassa-725	105	10	:	:	PUNCT
ijassa-725	105	11	rit	rit	NOUN
ijassa-725	105	12	=	=	SYM
ijassa-725	105	13	ŷit	ŷit	NOUN
ijassa-725	105	14	−	−	PROPN
ijassa-725	105	15	yit	yit	PROPN
ijassa-725	105	16	(	(	PUNCT
ijassa-725	105	17	4.4	4.4	NUM
ijassa-725	105	18	)	)	PUNCT
ijassa-725	105	19	where	where	SCONJ
ijassa-725	105	20	rit	rit	NOUN
ijassa-725	105	21	a	a	DET
ijassa-725	105	22	residual	residual	ADJ
ijassa-725	105	23	error	error	NOUN
ijassa-725	105	24	of	of	ADP
ijassa-725	105	25	a	a	DET
ijassa-725	105	26	predicted	predict	VERB
ijassa-725	105	27	value	value	NOUN
ijassa-725	105	28	for	for	ADP
ijassa-725	105	29	i	i	PROPN
ijassa-725	105	30	-	-	PUNCT
ijassa-725	105	31	th	th	PROPN
ijassa-725	105	32	time	time	NOUN
ijassa-725	105	33	series	series	NOUN
ijassa-725	105	34	on	on	ADP
ijassa-725	105	35	t	t	PROPN
ijassa-725	105	36	-	-	PUNCT
ijassa-725	105	37	th	th	NUM
ijassa-725	105	38	measurement	measurement	NOUN
ijassa-725	105	39	.	.	PUNCT
ijassa-725	106	1	example	example	NOUN
ijassa-725	106	2	of	of	ADP
ijassa-725	106	3	a	a	DET
ijassa-725	106	4	time	time	NOUN
ijassa-725	106	5	series	series	NOUN
ijassa-725	106	6	with	with	ADP
ijassa-725	106	7	two	two	NUM
ijassa-725	106	8	anomalies	anomaly	NOUN
ijassa-725	106	9	is	be	AUX
ijassa-725	106	10	shown	show	VERB
ijassa-725	106	11	in	in	ADP
ijassa-725	106	12	fig	fig	NOUN
ijassa-725	106	13	.	.	PUNCT
ijassa-725	107	1	4.2	4.2	NUM
ijassa-725	107	2	.	.	PUNCT
ijassa-725	108	1	it	it	PRON
ijassa-725	108	2	corresponds	correspond	VERB
ijassa-725	108	3	to	to	ADP
ijassa-725	108	4	the	the	DET
ijassa-725	108	5	percentage	percentage	NOUN
ijassa-725	108	6	of	of	ADP
ijassa-725	108	7	cpu	cpu	ADJ
ijassa-725	108	8	usage	usage	NOUN
ijassa-725	108	9	for	for	ADP
ijassa-725	108	10	one	one	NUM
ijassa-725	108	11	of	of	ADP
ijassa-725	108	12	the	the	DET
ijassa-725	108	13	storage	storage	NOUN
ijassa-725	108	14	controllers	controller	NOUN
ijassa-725	108	15	.	.	PUNCT
ijassa-725	109	1	the	the	DET
ijassa-725	109	2	time	time	NOUN
ijassa-725	109	3	series	series	PROPN
ijassa-725	109	4	is	be	AUX
ijassa-725	109	5	aggregated	aggregate	VERB
ijassa-725	109	6	as	as	SCONJ
ijassa-725	109	7	it	it	PRON
ijassa-725	109	8	is	be	AUX
ijassa-725	109	9	described	describe	VERB
ijassa-725	109	10	in	in	ADP
ijassa-725	109	11	sec	sec	PROPN
ijassa-725	109	12	.	.	PROPN
ijassa-725	109	13	4.1	4.1	NUM
ijassa-725	109	14	.	.	PUNCT
ijassa-725	110	1	to	to	PART
ijassa-725	110	2	predict	predict	VERB
ijassa-725	110	3	the	the	DET
ijassa-725	110	4	current	current	ADJ
ijassa-725	110	5	value	value	NOUN
ijassa-725	110	6	ŷit	ŷit	NOUN
ijassa-725	110	7	the	the	DET
ijassa-725	110	8	previous	previous	ADJ
ijassa-725	110	9	30	30	NUM
ijassa-725	110	10	observations	observation	NOUN
ijassa-725	110	11	of	of	ADP
ijassa-725	110	12	this	this	DET
ijassa-725	110	13	time	time	NOUN
ijassa-725	110	14	series	series	NOUN
ijassa-725	110	15	are	be	AUX
ijassa-725	110	16	used	use	VERB
ijassa-725	110	17	in	in	ADP
ijassa-725	110	18	this	this	DET
ijassa-725	110	19	example	example	NOUN
ijassa-725	110	20	.	.	PUNCT
ijassa-725	111	1	there	there	PRON
ijassa-725	111	2	are	be	VERB
ijassa-725	111	3	about	about	ADV
ijassa-725	111	4	2500	2500	NUM
ijassa-725	111	5	observations	observation	NOUN
ijassa-725	111	6	that	that	PRON
ijassa-725	111	7	correspond	correspond	VERB
ijassa-725	111	8	to	to	ADP
ijassa-725	111	9	about	about	ADV
ijassa-725	111	10	150000	150000	NUM
ijassa-725	111	11	seconds	second	NOUN
ijassa-725	111	12	.	.	PUNCT
ijassa-725	112	1	the	the	DET
ijassa-725	112	2	first	first	ADJ
ijassa-725	112	3	60000	60000	NUM
ijassa-725	112	4	seconds	second	NOUN
ijassa-725	112	5	are	be	AUX
ijassa-725	112	6	used	use	VERB
ijassa-725	112	7	to	to	PART
ijassa-725	112	8	train	train	VERB
ijassa-725	112	9	var	var	NOUN
ijassa-725	112	10	model	model	NOUN
ijassa-725	112	11	and	and	CCONJ
ijassa-725	112	12	the	the	DET
ijassa-725	112	13	next	next	ADJ
ijassa-725	112	14	25000	25000	NUM
ijassa-725	112	15	seconds	second	NOUN
ijassa-725	112	16	are	be	AUX
ijassa-725	112	17	used	use	VERB
ijassa-725	112	18	for	for	ADP
ijassa-725	112	19	the	the	DET
ijassa-725	112	20	validation	validation	NOUN
ijassa-725	112	21	.	.	PUNCT
ijassa-725	113	1	residual	residual	ADJ
ijassa-725	113	2	errors	error	NOUN
ijassa-725	113	3	of	of	ADP
ijassa-725	113	4	the	the	DET
ijassa-725	113	5	prediction	prediction	NOUN
ijassa-725	113	6	are	be	AUX
ijassa-725	113	7	shown	show	VERB
ijassa-725	113	8	in	in	ADP
ijassa-725	113	9	fig	fig	NOUN
ijassa-725	113	10	.	.	PUNCT
ijassa-725	114	1	4.2	4.2	NUM
ijassa-725	114	2	.	.	PUNCT
ijassa-725	115	1	the	the	DET
ijassa-725	115	2	figure	figure	NOUN
ijassa-725	115	3	shows	show	VERB
ijassa-725	115	4	larger	large	ADJ
ijassa-725	115	5	residuals	residual	NOUN
ijassa-725	115	6	for	for	ADP
ijassa-725	115	7	the	the	DET
ijassa-725	115	8	anomalies	anomaly	NOUN
ijassa-725	115	9	.	.	PUNCT
ijassa-725	116	1	to	to	PART
ijassa-725	116	2	detect	detect	VERB
ijassa-725	116	3	them	they	PRON
ijassa-725	116	4	the	the	DET
ijassa-725	116	5	cumulative	cumulative	ADJ
ijassa-725	116	6	sum	sum	NOUN
ijassa-725	116	7	(	(	PUNCT
ijassa-725	116	8	cusum	cusum	NOUN
ijassa-725	116	9	)	)	PUNCT
ijassa-725	117	1	[	[	X
ijassa-725	117	2	26	26	NUM
ijassa-725	117	3	]	]	PUNCT
ijassa-725	117	4	test	test	NOUN
ijassa-725	117	5	is	be	AUX
ijassa-725	117	6	used	use	VERB
ijassa-725	117	7	.	.	PUNCT
ijassa-725	118	1	the	the	DET
ijassa-725	118	2	test	test	NOUN
ijassa-725	118	3	calculates	calculate	VERB
ijassa-725	118	4	new	new	ADJ
ijassa-725	118	5	time	time	NOUN
ijassa-725	118	6	series	series	PROPN
ijassa-725	118	7	{	{	PUNCT
ijassa-725	118	8	tt}nt=1	tt}nt=1	PROPN
ijassa-725	118	9	,	,	PUNCT
ijassa-725	118	10	where	where	SCONJ
ijassa-725	118	11	the	the	DET
ijassa-725	118	12	first	first	ADJ
ijassa-725	118	13	value	value	NOUN
ijassa-725	118	14	t1	t1	NOUN
ijassa-725	118	15	=	=	SYM
ijassa-725	118	16	0	0	PUNCT
ijassa-725	118	17	and	and	CCONJ
ijassa-725	118	18	the	the	DET
ijassa-725	118	19	next	next	ADJ
ijassa-725	118	20	values	value	NOUN
ijassa-725	118	21	are	be	AUX
ijassa-725	118	22	estimated	estimate	VERB
ijassa-725	118	23	by	by	ADP
ijassa-725	118	24	the	the	DET
ijassa-725	118	25	recurrent	recurrent	ADJ
ijassa-725	118	26	formula	formula	NOUN
ijassa-725	118	27	using	use	VERB
ijassa-725	118	28	residual	residual	ADJ
ijassa-725	118	29	errors	error	NOUN
ijassa-725	118	30	:	:	PUNCT
ijassa-725	118	31	tt	tt	PROPN
ijassa-725	118	32	=	=	PUNCT
ijassa-725	118	33	max(0	max(0	PROPN
ijassa-725	118	34	,	,	PUNCT
ijassa-725	118	35	tt−1	tt−1	PROPN
ijassa-725	118	36	+	+	CCONJ
ijassa-725	118	37	εt	εt	PROPN
ijassa-725	118	38	)	)	PUNCT
ijassa-725	118	39	(	(	PUNCT
ijassa-725	118	40	4.5	4.5	NUM
ijassa-725	118	41	)	)	PUNCT
ijassa-725	119	1	εt	εt	PROPN
ijassa-725	119	2	=	=	NOUN
ijassa-725	119	3	log	log	VERB
ijassa-725	119	4	f0(rit	f0(rit	NOUN
ijassa-725	119	5	)	)	PUNCT
ijassa-725	119	6	f∞(rit	f∞(rit	PROPN
ijassa-725	119	7	)	)	PUNCT
ijassa-725	119	8	(	(	PUNCT
ijassa-725	119	9	4.6	4.6	NUM
ijassa-725	119	10	)	)	PUNCT
ijassa-725	120	1	where	where	SCONJ
ijassa-725	120	2	f∞(rit	f∞(rit	NOUN
ijassa-725	120	3	)	)	PUNCT
ijassa-725	120	4	and	and	CCONJ
ijassa-725	120	5	f0(rit	f0(rit	NOUN
ijassa-725	120	6	)	)	PUNCT
ijassa-725	120	7	are	be	AUX
ijassa-725	120	8	residual	residual	ADJ
ijassa-725	120	9	distributions	distribution	NOUN
ijassa-725	120	10	for	for	ADP
ijassa-725	120	11	normal	normal	ADJ
ijassa-725	120	12	and	and	CCONJ
ijassa-725	120	13	anomalous	anomalous	ADJ
ijassa-725	120	14	states	state	NOUN
ijassa-725	120	15	respectively	respectively	ADV
ijassa-725	120	16	.	.	PUNCT
ijassa-725	121	1	normal	normal	ADJ
ijassa-725	121	2	distributions	distribution	NOUN
ijassa-725	121	3	for	for	ADP
ijassa-725	121	4	the	the	DET
ijassa-725	121	5	residuals	residual	NOUN
ijassa-725	121	6	are	be	AUX
ijassa-725	121	7	considered	consider	VERB
ijassa-725	121	8	:	:	PUNCT
ijassa-725	121	9	f∞(rit	f∞(rit	NUM
ijassa-725	121	10	)	)	PUNCT
ijassa-725	121	11	=	=	SYM
ijassa-725	121	12	1√	1√	PROPN
ijassa-725	121	13	2πσ2	2πσ2	NUM
ijassa-725	121	14	∞	∞	NUM
ijassa-725	121	15	e	e	X
ijassa-725	121	16	−	−	PROPN
ijassa-725	121	17	(	(	PUNCT
ijassa-725	121	18	rit−r∞)2	rit−r∞)2	NOUN
ijassa-725	121	19	2σ2∞	2σ2∞	NUM
ijassa-725	121	20	(	(	PUNCT
ijassa-725	121	21	4.7	4.7	NUM
ijassa-725	121	22	)	)	PUNCT
ijassa-725	121	23	f0(rit	f0(rit	NOUN
ijassa-725	121	24	)	)	PUNCT
ijassa-725	121	25	=	=	SYM
ijassa-725	122	1	1√	1√	PROPN
ijassa-725	122	2	2πσ2	2πσ2	NUM
ijassa-725	122	3	0	0	NUM
ijassa-725	122	4	e	e	X
ijassa-725	122	5	−	−	PROPN
ijassa-725	122	6	(	(	PUNCT
ijassa-725	122	7	rit−r0	rit−r0	NOUN
ijassa-725	122	8	)	)	PUNCT
ijassa-725	122	9	2	2	NUM
ijassa-725	122	10	2σ20	2σ20	NUM
ijassa-725	122	11	(	(	PUNCT
ijassa-725	122	12	4.8	4.8	NUM
ijassa-725	122	13	)	)	PUNCT
ijassa-725	122	14	where	where	SCONJ
ijassa-725	122	15	r∞	r∞	NUM
ijassa-725	122	16	,	,	PUNCT
ijassa-725	122	17	σ∞	σ∞	PROPN
ijassa-725	122	18	are	be	AUX
ijassa-725	122	19	mean	mean	ADJ
ijassa-725	122	20	and	and	CCONJ
ijassa-725	122	21	standard	standard	ADJ
ijassa-725	122	22	deviation	deviation	NOUN
ijassa-725	122	23	of	of	ADP
ijassa-725	122	24	residuals	residual	NOUN
ijassa-725	122	25	for	for	ADP
ijassa-725	122	26	normal	normal	ADJ
ijassa-725	122	27	states	state	NOUN
ijassa-725	122	28	;	;	PUNCT
ijassa-725	122	29	r0	r0	NOUN
ijassa-725	122	30	,	,	PUNCT
ijassa-725	122	31	σ0	σ0	PROPN
ijassa-725	122	32	are	be	AUX
ijassa-725	122	33	mean	mean	ADJ
ijassa-725	122	34	and	and	CCONJ
ijassa-725	122	35	standard	standard	ADJ
ijassa-725	122	36	deviation	deviation	NOUN
ijassa-725	122	37	of	of	ADP
ijassa-725	122	38	residuals	residual	NOUN
ijassa-725	122	39	for	for	ADP
ijassa-725	122	40	anomalous	anomalous	ADJ
ijassa-725	122	41	states	state	NOUN
ijassa-725	122	42	;	;	PUNCT
ijassa-725	122	43	residuals	residual	NOUN
ijassa-725	122	44	are	be	AUX
ijassa-725	122	45	not	not	PART
ijassa-725	122	46	necessary	necessary	ADJ
ijassa-725	122	47	have	have	VERB
ijassa-725	122	48	normal	normal	ADJ
ijassa-725	122	49	distributions	distribution	NOUN
ijassa-725	122	50	.	.	PUNCT
ijassa-725	123	1	however	however	ADV
ijassa-725	123	2	,	,	PUNCT
ijassa-725	123	3	it	it	PRON
ijassa-725	123	4	was	be	AUX
ijassa-725	123	5	shown	show	VERB
ijassa-725	123	6	in	in	ADP
ijassa-725	123	7	[	[	X
ijassa-725	123	8	27	27	NUM
ijassa-725	123	9	]	]	PUNCT
ijassa-725	123	10	that	that	SCONJ
ijassa-725	123	11	even	even	ADV
ijassa-725	123	12	with	with	ADP
ijassa-725	123	13	strong	strong	ADJ
ijassa-725	123	14	deviations	deviation	NOUN
ijassa-725	123	15	from	from	ADP
ijassa-725	123	16	the	the	DET
ijassa-725	123	17	normal	normal	ADJ
ijassa-725	123	18	distribution	distribution	NOUN
ijassa-725	123	19	cusum	cusum	NOUN
ijassa-725	123	20	works	work	VERB
ijassa-725	123	21	well	well	ADV
ijassa-725	123	22	.	.	PUNCT
ijassa-725	124	1	an	an	DET
ijassa-725	124	2	anomaly	anomaly	NOUN
ijassa-725	124	3	is	be	AUX
ijassa-725	124	4	detected	detect	VERB
ijassa-725	124	5	when	when	SCONJ
ijassa-725	124	6	the	the	DET
ijassa-725	124	7	tt	tt	PROPN
ijassa-725	124	8	>	>	X
ijassa-725	124	9	talarm	talarm	PROPN
ijassa-725	124	10	.	.	PUNCT
ijassa-725	125	1	the	the	DET
ijassa-725	125	2	distribution	distribution	NOUN
ijassa-725	125	3	parameters	parameter	NOUN
ijassa-725	125	4	and	and	CCONJ
ijassa-725	125	5	talarm	talarm	NOUN
ijassa-725	125	6	are	be	AUX
ijassa-725	125	7	estimated	estimate	VERB
ijassa-725	125	8	during	during	ADP
ijassa-725	125	9	calibration	calibration	NOUN
ijassa-725	125	10	on	on	ADP
ijassa-725	125	11	the	the	DET
ijassa-725	125	12	validation	validation	NOUN
ijassa-725	125	13	sample	sample	NOUN
ijassa-725	125	14	without	without	ADP
ijassa-725	125	15	anomalies	anomaly	NOUN
ijassa-725	125	16	,	,	PUNCT
ijassa-725	125	17	where	where	SCONJ
ijassa-725	125	18	tt	tt	PROPN
ijassa-725	125	19	has	have	VERB
ijassa-725	125	20	to	to	PART
ijassa-725	125	21	take	take	VERB
ijassa-725	125	22	values	value	NOUN
ijassa-725	125	23	close	close	ADJ
ijassa-725	125	24	to	to	ADP
ijassa-725	125	25	0	0	NUM
ijassa-725	125	26	without	without	ADP
ijassa-725	125	27	growing	grow	VERB
ijassa-725	125	28	trend	trend	NOUN
ijassa-725	125	29	.	.	PUNCT
ijassa-725	126	1	this	this	DET
ijassa-725	126	2	approach	approach	NOUN
ijassa-725	126	3	allows	allow	VERB
ijassa-725	126	4	to	to	PART
ijassa-725	126	5	detect	detect	VERB
ijassa-725	126	6	mean	mean	NOUN
ijassa-725	126	7	and	and	CCONJ
ijassa-725	126	8	variance	variance	NOUN
ijassa-725	126	9	changes	change	NOUN
ijassa-725	126	10	of	of	ADP
ijassa-725	126	11	the	the	DET
ijassa-725	126	12	residuals	residual	NOUN
ijassa-725	126	13	.	.	PUNCT
ijassa-725	127	1	an	an	DET
ijassa-725	127	2	example	example	NOUN
ijassa-725	127	3	of	of	ADP
ijassa-725	127	4	the	the	DET
ijassa-725	127	5	cusum	cusum	NOUN
ijassa-725	127	6	test	test	NOUN
ijassa-725	127	7	is	be	AUX
ijassa-725	127	8	demonstrated	demonstrate	VERB
ijassa-725	127	9	in	in	ADP
ijassa-725	127	10	fig	fig	NOUN
ijassa-725	127	11	.	.	PUNCT
ijassa-725	128	1	4.2	4.2	NUM
ijassa-725	128	2	.	.	PUNCT
ijassa-725	129	1	the	the	DET
ijassa-725	129	2	test	test	NOUN
ijassa-725	129	3	value	value	NOUN
ijassa-725	129	4	increases	increase	NOUN
ijassa-725	129	5	for	for	ADP
ijassa-725	129	6	anomalies	anomaly	NOUN
ijassa-725	129	7	and	and	CCONJ
ijassa-725	129	8	falls	fall	VERB
ijassa-725	129	9	when	when	SCONJ
ijassa-725	129	10	the	the	DET
ijassa-725	129	11	anomaly	anomaly	NOUN
ijassa-725	129	12	disappears	disappear	VERB
ijassa-725	129	13	.	.	PUNCT
ijassa-725	130	1	to	to	PART
ijassa-725	130	2	avoid	avoid	VERB
ijassa-725	130	3	the	the	DET
ijassa-725	130	4	test	test	NOUN
ijassa-725	130	5	values	value	NOUN
ijassa-725	130	6	relaxation	relaxation	NOUN
ijassa-725	130	7	after	after	ADP
ijassa-725	130	8	the	the	DET
ijassa-725	130	9	anomaly	anomaly	NOUN
ijassa-725	130	10	tt	tt	PROPN
ijassa-725	130	11	values	value	NOUN
ijassa-725	130	12	can	can	AUX
ijassa-725	130	13	be	be	AUX
ijassa-725	130	14	reset	reset	VERB
ijassa-725	130	15	right	right	ADV
ijassa-725	130	16	after	after	SCONJ
ijassa-725	130	17	the	the	DET
ijassa-725	130	18	anomaly	anomaly	NOUN
ijassa-725	130	19	detected	detect	VERB
ijassa-725	130	20	or	or	CCONJ
ijassa-725	130	21	by	by	ADP
ijassa-725	130	22	operator	operator	NOUN
ijassa-725	130	23	’s	’s	PART
ijassa-725	130	24	demand	demand	NOUN
ijassa-725	130	25	.	.	PUNCT
ijassa-725	131	1	4.3	4.3	NUM
ijassa-725	131	2	.	.	PUNCT
ijassa-725	131	3	one	one	NUM
ijassa-725	131	4	-	-	PUNCT
ijassa-725	131	5	class	class	NOUN
ijassa-725	131	6	classification	classification	NOUN
ijassa-725	131	7	one	one	NUM
ijassa-725	131	8	-	-	PUNCT
ijassa-725	131	9	class	class	NOUN
ijassa-725	131	10	classification	classification	NOUN
ijassa-725	131	11	algorithms	algorithm	NOUN
ijassa-725	131	12	are	be	AUX
ijassa-725	131	13	used	use	VERB
ijassa-725	131	14	for	for	ADP
ijassa-725	131	15	anomalies	anomaly	NOUN
ijassa-725	131	16	and	and	CCONJ
ijassa-725	131	17	novelty	novelty	NOUN
ijassa-725	131	18	detection	detection	NOUN
ijassa-725	131	19	in	in	ADP
ijassa-725	131	20	data	datum	NOUN
ijassa-725	131	21	.	.	PUNCT
ijassa-725	132	1	these	these	DET
ijassa-725	132	2	algorithms	algorithm	NOUN
ijassa-725	132	3	learn	learn	VERB
ijassa-725	132	4	boundaries	boundary	NOUN
ijassa-725	132	5	of	of	ADP
ijassa-725	132	6	a	a	DET
ijassa-725	132	7	normal	normal	ADJ
ijassa-725	132	8	class	class	NOUN
ijassa-725	132	9	and	and	CCONJ
ijassa-725	132	10	everything	everything	PRON
ijassa-725	132	11	that	that	PRON
ijassa-725	132	12	outside	outside	ADP
ijassa-725	132	13	that	that	DET
ijassa-725	132	14	boundary	boundary	NOUN
ijassa-725	132	15	is	be	AUX
ijassa-725	132	16	considered	consider	VERB
ijassa-725	132	17	as	as	ADP
ijassa-725	132	18	an	an	DET
ijassa-725	132	19	anomaly	anomaly	NOUN
ijassa-725	132	20	.	.	PUNCT
ijassa-725	133	1	isolation	isolation	NOUN
ijassa-725	133	2	forest	forest	NOUN
ijassa-725	134	1	[	[	X
ijassa-725	134	2	18	18	NUM
ijassa-725	134	3	]	]	PUNCT
ijassa-725	134	4	is	be	AUX
ijassa-725	134	5	one	one	NUM
ijassa-725	134	6	of	of	ADP
ijassa-725	134	7	the	the	DET
ijassa-725	134	8	best	good	ADJ
ijassa-725	134	9	one	one	NUM
ijassa-725	134	10	-	-	PUNCT
ijassa-725	134	11	class	class	NOUN
ijassa-725	134	12	algorithms	algorithm	NOUN
ijassa-725	134	13	.	.	PUNCT
ijassa-725	135	1	suppose	suppose	VERB
ijassa-725	135	2	a	a	DET
ijassa-725	135	3	sample	sample	NOUN
ijassa-725	135	4	with	with	ADP
ijassa-725	135	5	n	n	PRON
ijassa-725	135	6	objects	object	NOUN
ijassa-725	135	7	is	be	AUX
ijassa-725	135	8	given	give	VERB
ijassa-725	135	9	.	.	PUNCT
ijassa-725	136	1	each	each	DET
ijassa-725	136	2	object	object	NOUN
ijassa-725	136	3	has	have	VERB
ijassa-725	136	4	d	d	NOUN
ijassa-725	136	5	parameters	parameter	NOUN
ijassa-725	136	6	.	.	PUNCT
ijassa-725	137	1	the	the	DET
ijassa-725	137	2	idea	idea	NOUN
ijassa-725	137	3	of	of	ADP
ijassa-725	137	4	the	the	DET
ijassa-725	137	5	isolation	isolation	NOUN
ijassa-725	137	6	forest	forest	NOUN
ijassa-725	137	7	in	in	ADP
ijassa-725	137	8	the	the	DET
ijassa-725	137	9	following	following	NOUN
ijassa-725	137	10	:	:	PUNCT
ijassa-725	137	11	step	step	NOUN
ijassa-725	137	12	1	1	NUM
ijassa-725	137	13	select	select	VERB
ijassa-725	137	14	a	a	DET
ijassa-725	137	15	subsample	subsample	NOUN
ijassa-725	137	16	with	with	ADP
ijassa-725	137	17	0	0	NUM
ijassa-725	137	18	<	<	X
ijassa-725	137	19	n	n	X
ijassa-725	137	20	<	<	X
ijassa-725	137	21	n	n	PRON
ijassa-725	137	22	objects	object	VERB
ijassa-725	137	23	to	to	PART
ijassa-725	137	24	build	build	VERB
ijassa-725	137	25	a	a	DET
ijassa-725	137	26	new	new	ADJ
ijassa-725	137	27	isolation	isolation	NOUN
ijassa-725	137	28	tree	tree	NOUN
ijassa-725	137	29	.	.	PUNCT
ijassa-725	138	1	step	step	NOUN
ijassa-725	138	2	2	2	NUM
ijassa-725	138	3	randomly	randomly	ADV
ijassa-725	138	4	select	select	VERB
ijassa-725	138	5	a	a	DET
ijassa-725	138	6	parameter	parameter	NOUN
ijassa-725	138	7	.	.	PUNCT
ijassa-725	139	1	step	step	NOUN
ijassa-725	139	2	3	3	NUM
ijassa-725	139	3	randomly	randomly	ADV
ijassa-725	139	4	select	select	VERB
ijassa-725	139	5	an	an	DET
ijassa-725	139	6	object	object	NOUN
ijassa-725	139	7	from	from	ADP
ijassa-725	139	8	the	the	DET
ijassa-725	139	9	current	current	ADJ
ijassa-725	139	10	tree	tree	NOUN
ijassa-725	139	11	node	node	NOUN
ijassa-725	139	12	.	.	PUNCT
ijassa-725	140	1	use	use	VERB
ijassa-725	140	2	the	the	DET
ijassa-725	140	3	selected	select	VERB
ijassa-725	140	4	parameter	parameter	NOUN
ijassa-725	140	5	value	value	NOUN
ijassa-725	140	6	of	of	ADP
ijassa-725	140	7	this	this	DET
ijassa-725	140	8	object	object	NOUN
ijassa-725	140	9	as	as	ADP
ijassa-725	140	10	a	a	DET
ijassa-725	140	11	splitting	splitting	NOUN
ijassa-725	140	12	rule	rule	NOUN
ijassa-725	140	13	for	for	ADP
ijassa-725	140	14	the	the	DET
ijassa-725	140	15	node	node	NOUN
ijassa-725	140	16	.	.	PUNCT
ijassa-725	141	1	copyright	copyright	NOUN
ijassa-725	141	2	c	c	ADP
ijassa-725	141	3	©	©	PROPN
ijassa-725	141	4	2019	2019	NUM
ijassa-725	141	5	assa	assa	NOUN
ijassa-725	141	6	.	.	PUNCT
ijassa-725	142	1	adv	adv	PROPN
ijassa-725	142	2	syst	syst	PROPN
ijassa-725	142	3	sci	sci	PROPN
ijassa-725	142	4	appl	appl	PROPN
ijassa-725	142	5	(	(	PUNCT
ijassa-725	142	6	2019	2019	NUM
ijassa-725	142	7	)	)	PUNCT
ijassa-725	142	8	28	28	NUM
ijassa-725	142	9	step	step	NOUN
ijassa-725	142	10	4	4	NUM
ijassa-725	142	11	repeat	repeat	NOUN
ijassa-725	142	12	steps	step	NOUN
ijassa-725	142	13	3	3	NUM
ijassa-725	142	14	and	and	CCONJ
ijassa-725	142	15	4	4	NUM
ijassa-725	142	16	for	for	ADP
ijassa-725	142	17	the	the	DET
ijassa-725	142	18	left	left	ADJ
ijassa-725	142	19	and	and	CCONJ
ijassa-725	142	20	right	right	ADJ
ijassa-725	142	21	children	child	NOUN
ijassa-725	142	22	of	of	ADP
ijassa-725	142	23	the	the	DET
ijassa-725	142	24	node	node	NOUN
ijassa-725	142	25	.	.	PUNCT
ijassa-725	143	1	stop	stop	VERB
ijassa-725	143	2	the	the	DET
ijassa-725	143	3	process	process	NOUN
ijassa-725	143	4	when	when	SCONJ
ijassa-725	143	5	the	the	DET
ijassa-725	143	6	termination	termination	NOUN
ijassa-725	143	7	conditions	condition	NOUN
ijassa-725	143	8	are	be	AUX
ijassa-725	143	9	satisfied	satisfied	ADJ
ijassa-725	143	10	.	.	PUNCT
ijassa-725	144	1	step	step	NOUN
ijassa-725	144	2	5	5	NUM
ijassa-725	144	3	repeat	repeat	NOUN
ijassa-725	144	4	steps	step	NOUN
ijassa-725	144	5	1	1	NUM
ijassa-725	144	6	-	-	SYM
ijassa-725	144	7	4	4	NUM
ijassa-725	144	8	to	to	PART
ijassa-725	144	9	build	build	VERB
ijassa-725	144	10	forest	forest	NOUN
ijassa-725	144	11	of	of	ADP
ijassa-725	144	12	isolation	isolation	NOUN
ijassa-725	144	13	trees	tree	NOUN
ijassa-725	144	14	.	.	PUNCT
ijassa-725	145	1	according	accord	VERB
ijassa-725	145	2	to	to	ADP
ijassa-725	145	3	[	[	X
ijassa-725	145	4	18	18	NUM
ijassa-725	145	5	]	]	PUNCT
ijassa-725	145	6	,	,	PUNCT
ijassa-725	145	7	anomalies	anomaly	NOUN
ijassa-725	145	8	have	have	VERB
ijassa-725	145	9	shorter	short	ADJ
ijassa-725	145	10	decision	decision	NOUN
ijassa-725	145	11	paths	path	NOUN
ijassa-725	145	12	in	in	ADP
ijassa-725	145	13	isolation	isolation	NOUN
ijassa-725	145	14	trees	tree	NOUN
ijassa-725	145	15	than	than	ADP
ijassa-725	145	16	normal	normal	ADJ
ijassa-725	145	17	objects	object	NOUN
ijassa-725	145	18	.	.	PUNCT
ijassa-725	146	1	for	for	ADP
ijassa-725	146	2	an	an	DET
ijassa-725	146	3	object	object	NOUN
ijassa-725	146	4	x	x	PUNCT
ijassa-725	146	5	anomaly	anomaly	NOUN
ijassa-725	146	6	score	score	NOUN
ijassa-725	146	7	ŝ	ŝ	X
ijassa-725	146	8	is	be	AUX
ijassa-725	146	9	estimated	estimate	VERB
ijassa-725	146	10	as	as	ADP
ijassa-725	146	11	:	:	PUNCT
ijassa-725	146	12	s(x	s(x	NUM
ijassa-725	146	13	)	)	PUNCT
ijassa-725	146	14	=	=	PROPN
ijassa-725	146	15	2−	2−	NUM
ijassa-725	146	16	e(h(x	e(h(x	NOUN
ijassa-725	146	17	)	)	PUNCT
ijassa-725	146	18	)	)	PUNCT
ijassa-725	147	1	c(n	c(n	NOUN
ijassa-725	147	2	)	)	PUNCT
ijassa-725	147	3	(	(	PUNCT
ijassa-725	147	4	4.9	4.9	NUM
ijassa-725	147	5	)	)	PUNCT
ijassa-725	147	6	where	where	SCONJ
ijassa-725	147	7	h(x	h(x	PROPN
ijassa-725	147	8	)	)	PUNCT
ijassa-725	147	9	is	be	AUX
ijassa-725	147	10	a	a	DET
ijassa-725	147	11	length	length	NOUN
ijassa-725	147	12	of	of	ADP
ijassa-725	147	13	s	s	NOUN
ijassa-725	147	14	decision	decision	NOUN
ijassa-725	147	15	path	path	NOUN
ijassa-725	147	16	for	for	ADP
ijassa-725	147	17	the	the	DET
ijassa-725	147	18	object	object	NOUN
ijassa-725	147	19	in	in	ADP
ijassa-725	147	20	an	an	DET
ijassa-725	147	21	isolation	isolation	NOUN
ijassa-725	147	22	tree	tree	NOUN
ijassa-725	147	23	;	;	PUNCT
ijassa-725	147	24	e(h(x	e(h(x	PROPN
ijassa-725	147	25	)	)	PUNCT
ijassa-725	147	26	)	)	PUNCT
ijassa-725	147	27	is	be	AUX
ijassa-725	147	28	an	an	DET
ijassa-725	147	29	average	average	ADJ
ijassa-725	147	30	length	length	NOUN
ijassa-725	147	31	of	of	ADP
ijassa-725	147	32	the	the	DET
ijassa-725	147	33	decision	decision	NOUN
ijassa-725	147	34	path	path	NOUN
ijassa-725	147	35	for	for	ADP
ijassa-725	147	36	the	the	DET
ijassa-725	147	37	object	object	NOUN
ijassa-725	147	38	in	in	ADP
ijassa-725	147	39	the	the	DET
ijassa-725	147	40	forest	forest	NOUN
ijassa-725	147	41	;	;	PUNCT
ijassa-725	147	42	c(n	c(n	PROPN
ijassa-725	147	43	)	)	PUNCT
ijassa-725	147	44	is	be	AUX
ijassa-725	147	45	an	an	DET
ijassa-725	147	46	average	average	ADJ
ijassa-725	147	47	length	length	NOUN
ijassa-725	147	48	of	of	ADP
ijassa-725	147	49	the	the	DET
ijassa-725	147	50	decision	decision	NOUN
ijassa-725	147	51	path	path	NOUN
ijassa-725	147	52	for	for	ADP
ijassa-725	147	53	all	all	DET
ijassa-725	147	54	n	n	PRON
ijassa-725	147	55	objects	object	NOUN
ijassa-725	147	56	in	in	ADP
ijassa-725	147	57	the	the	DET
ijassa-725	147	58	forest	forest	NOUN
ijassa-725	147	59	.	.	PUNCT
ijassa-725	148	1	the	the	DET
ijassa-725	148	2	score	score	NOUN
ijassa-725	148	3	takes	take	VERB
ijassa-725	148	4	values	value	NOUN
ijassa-725	148	5	in	in	ADP
ijassa-725	148	6	[	[	X
ijassa-725	148	7	0	0	NUM
ijassa-725	148	8	,	,	PUNCT
ijassa-725	148	9	1	1	NUM
ijassa-725	148	10	]	]	PUNCT
ijassa-725	148	11	.	.	PUNCT
ijassa-725	149	1	objects	object	NOUN
ijassa-725	149	2	with	with	ADP
ijassa-725	149	3	the	the	DET
ijassa-725	149	4	score	score	NOUN
ijassa-725	149	5	close	close	ADV
ijassa-725	149	6	to	to	ADP
ijassa-725	149	7	1	1	NUM
ijassa-725	149	8	are	be	AUX
ijassa-725	149	9	anomalous	anomalous	ADJ
ijassa-725	149	10	.	.	PUNCT
ijassa-725	150	1	on	on	ADP
ijassa-725	150	2	the	the	DET
ijassa-725	150	3	other	other	ADJ
ijassa-725	150	4	hand	hand	NOUN
ijassa-725	150	5	,	,	PUNCT
ijassa-725	150	6	objects	object	VERB
ijassa-725	150	7	with	with	ADP
ijassa-725	150	8	small	small	ADJ
ijassa-725	150	9	score	score	NOUN
ijassa-725	150	10	are	be	AUX
ijassa-725	150	11	normal	normal	ADJ
ijassa-725	150	12	.	.	PUNCT
ijassa-725	151	1	in	in	ADP
ijassa-725	151	2	case	case	NOUN
ijassa-725	151	3	,	,	PUNCT
ijassa-725	151	4	when	when	SCONJ
ijassa-725	151	5	for	for	ADP
ijassa-725	151	6	all	all	DET
ijassa-725	151	7	objects	object	NOUN
ijassa-725	151	8	in	in	ADP
ijassa-725	151	9	a	a	DET
ijassa-725	151	10	sample	sample	NOUN
ijassa-725	151	11	s(x	s(x	PROPN
ijassa-725	151	12	)	)	PUNCT
ijassa-725	151	13	≈	≈	PROPN
ijassa-725	151	14	0.5	0.5	NUM
ijassa-725	151	15	,	,	PUNCT
ijassa-725	151	16	the	the	DET
ijassa-725	151	17	sample	sample	NOUN
ijassa-725	151	18	has	have	VERB
ijassa-725	151	19	no	no	DET
ijassa-725	151	20	anomalies	anomaly	NOUN
ijassa-725	151	21	.	.	PUNCT
ijassa-725	152	1	similar	similar	ADJ
ijassa-725	152	2	to	to	ADP
ijassa-725	152	3	the	the	DET
ijassa-725	152	4	time	time	NOUN
ijassa-725	152	5	series	series	PROPN
ijassa-725	152	6	analysis	analysis	NOUN
ijassa-725	152	7	approach	approach	NOUN
ijassa-725	152	8	,	,	PUNCT
ijassa-725	152	9	isolation	isolation	NOUN
ijassa-725	152	10	forest	forest	NOUN
ijassa-725	152	11	uses	use	VERB
ijassa-725	152	12	vectors	vector	NOUN
ijassa-725	152	13	yt	yt	PROPN
ijassa-725	152	14	of	of	ADP
ijassa-725	152	15	measured	measured	ADJ
ijassa-725	152	16	parameters	parameter	NOUN
ijassa-725	152	17	values	value	NOUN
ijassa-725	152	18	to	to	PART
ijassa-725	152	19	estimate	estimate	VERB
ijassa-725	152	20	the	the	DET
ijassa-725	152	21	anomaly	anomaly	NOUN
ijassa-725	152	22	score	score	NOUN
ijassa-725	152	23	ŝit	ŝit	NOUN
ijassa-725	152	24	for	for	ADP
ijassa-725	152	25	a	a	DET
ijassa-725	152	26	measurement	measurement	NOUN
ijassa-725	152	27	:	:	PUNCT
ijassa-725	152	28	ŝit	ŝit	NOUN
ijassa-725	152	29	=	=	X
ijassa-725	152	30	fi(yt	fi(yt	PROPN
ijassa-725	152	31	,	,	PUNCT
ijassa-725	152	32	yt−1	yt−1	PROPN
ijassa-725	152	33	,	,	PUNCT
ijassa-725	152	34	...	...	PUNCT
ijassa-725	152	35	,	,	PUNCT
ijassa-725	152	36	yt−k	yt−k	NOUN
ijassa-725	152	37	)	)	PUNCT
ijassa-725	152	38	(	(	PUNCT
ijassa-725	152	39	4.10	4.10	NUM
ijassa-725	152	40	)	)	PUNCT
ijassa-725	152	41	an	an	DET
ijassa-725	152	42	example	example	NOUN
ijassa-725	152	43	of	of	ADP
ijassa-725	152	44	working	work	VERB
ijassa-725	152	45	of	of	ADP
ijassa-725	152	46	isolation	isolation	NOUN
ijassa-725	152	47	forest	forest	NOUN
ijassa-725	152	48	is	be	AUX
ijassa-725	152	49	demonstrated	demonstrate	VERB
ijassa-725	152	50	in	in	ADP
ijassa-725	152	51	fig	fig	NOUN
ijassa-725	152	52	.	.	PUNCT
ijassa-725	153	1	4.3	4.3	NUM
ijassa-725	153	2	.	.	PUNCT
ijassa-725	154	1	the	the	DET
ijassa-725	154	2	first	first	ADJ
ijassa-725	154	3	60000	60000	NUM
ijassa-725	154	4	seconds	second	NOUN
ijassa-725	154	5	are	be	AUX
ijassa-725	154	6	used	use	VERB
ijassa-725	154	7	to	to	PART
ijassa-725	154	8	train	train	VERB
ijassa-725	154	9	a	a	DET
ijassa-725	154	10	classifier	classifier	NOUN
ijassa-725	154	11	.	.	PUNCT
ijassa-725	155	1	the	the	DET
ijassa-725	155	2	figure	figure	NOUN
ijassa-725	155	3	shows	show	VERB
ijassa-725	155	4	a	a	DET
ijassa-725	155	5	slightly	slightly	ADV
ijassa-725	155	6	higher	high	ADJ
ijassa-725	155	7	anomaly	anomaly	NOUN
ijassa-725	155	8	score	score	NOUN
ijassa-725	155	9	for	for	ADP
ijassa-725	155	10	anomalies	anomaly	NOUN
ijassa-725	155	11	.	.	PUNCT
ijassa-725	156	1	all	all	DET
ijassa-725	156	2	measurements	measurement	NOUN
ijassa-725	156	3	with	with	ADP
ijassa-725	156	4	ŝit	ŝit	NOUN
ijassa-725	156	5	≥	≥	NOUN
ijassa-725	156	6	0.5	0.5	NUM
ijassa-725	156	7	can	can	AUX
ijassa-725	156	8	be	be	AUX
ijassa-725	156	9	considered	consider	VERB
ijassa-725	156	10	as	as	ADP
ijassa-725	156	11	anomalies	anomaly	NOUN
ijassa-725	156	12	.	.	PUNCT
ijassa-725	157	1	results	result	NOUN
ijassa-725	157	2	can	can	AUX
ijassa-725	157	3	be	be	AUX
ijassa-725	157	4	improved	improve	VERB
ijassa-725	157	5	using	use	VERB
ijassa-725	157	6	cusum	cusum	NOUN
ijassa-725	157	7	test	test	NOUN
ijassa-725	157	8	similar	similar	ADJ
ijassa-725	157	9	to	to	ADP
ijassa-725	157	10	var	var	NOUN
ijassa-725	157	11	models	model	NOUN
ijassa-725	157	12	and	and	CCONJ
ijassa-725	157	13	will	will	AUX
ijassa-725	157	14	be	be	AUX
ijassa-725	157	15	considered	consider	VERB
ijassa-725	157	16	further	far	ADV
ijassa-725	157	17	.	.	PUNCT
ijassa-725	158	1	4.4	4.4	NUM
ijassa-725	158	2	.	.	PUNCT
ijassa-725	159	1	binary	binary	ADJ
ijassa-725	159	2	classification	classification	NOUN
ijassa-725	159	3	isolation	isolation	NOUN
ijassa-725	159	4	forest	forest	NOUN
ijassa-725	159	5	binary	binary	NOUN
ijassa-725	159	6	classification	classification	NOUN
ijassa-725	159	7	fig	fig	NOUN
ijassa-725	159	8	.	.	PUNCT
ijassa-725	160	1	4.3	4.3	NUM
ijassa-725	160	2	.	.	PUNCT
ijassa-725	161	1	(	(	PUNCT
ijassa-725	161	2	top	top	ADJ
ijassa-725	161	3	)	)	PUNCT
ijassa-725	161	4	time	time	NOUN
ijassa-725	161	5	series	series	NOUN
ijassa-725	161	6	of	of	ADP
ijassa-725	161	7	percentage	percentage	NOUN
ijassa-725	161	8	of	of	ADP
ijassa-725	161	9	cpu	cpu	ADJ
ijassa-725	161	10	usage	usage	NOUN
ijassa-725	161	11	for	for	ADP
ijassa-725	161	12	one	one	NUM
ijassa-725	161	13	of	of	ADP
ijassa-725	161	14	the	the	DET
ijassa-725	161	15	storage	storage	NOUN
ijassa-725	161	16	components	component	NOUN
ijassa-725	161	17	of	of	ADP
ijassa-725	161	18	the	the	DET
ijassa-725	161	19	storage	storage	NOUN
ijassa-725	161	20	system	system	NOUN
ijassa-725	161	21	after	after	ADP
ijassa-725	161	22	aggregation	aggregation	NOUN
ijassa-725	161	23	.	.	PUNCT
ijassa-725	162	1	(	(	PUNCT
ijassa-725	162	2	middle	middle	ADJ
ijassa-725	162	3	)	)	PUNCT
ijassa-725	162	4	anomaly	anomaly	NOUN
ijassa-725	162	5	score	score	NOUN
ijassa-725	162	6	predicted	predict	VERB
ijassa-725	162	7	by	by	ADP
ijassa-725	162	8	isolation	isolation	NOUN
ijassa-725	162	9	forest	forest	NOUN
ijassa-725	162	10	.	.	PUNCT
ijassa-725	163	1	(	(	PUNCT
ijassa-725	163	2	bottom	bottom	ADJ
ijassa-725	163	3	)	)	PUNCT
ijassa-725	163	4	anomaly	anomaly	NOUN
ijassa-725	163	5	score	score	NOUN
ijassa-725	163	6	predicted	predict	VERB
ijassa-725	163	7	by	by	ADP
ijassa-725	163	8	binary	binary	PROPN
ijassa-725	163	9	classifier	classifier	PROPN
ijassa-725	163	10	.	.	PUNCT
ijassa-725	164	1	binary	binary	ADJ
ijassa-725	164	2	classification	classification	NOUN
ijassa-725	164	3	is	be	AUX
ijassa-725	164	4	a	a	DET
ijassa-725	164	5	powerful	powerful	ADJ
ijassa-725	164	6	tool	tool	NOUN
ijassa-725	164	7	to	to	PART
ijassa-725	164	8	detect	detect	VERB
ijassa-725	164	9	known	known	ADJ
ijassa-725	164	10	anomalies	anomaly	NOUN
ijassa-725	164	11	.	.	PUNCT
ijassa-725	165	1	normal	normal	ADJ
ijassa-725	165	2	and	and	CCONJ
ijassa-725	165	3	anomalous	anomalous	ADJ
ijassa-725	165	4	measurements	measurement	NOUN
ijassa-725	165	5	are	be	AUX
ijassa-725	165	6	considered	consider	VERB
ijassa-725	165	7	as	as	ADP
ijassa-725	165	8	two	two	NUM
ijassa-725	165	9	classes	class	NOUN
ijassa-725	165	10	.	.	PUNCT
ijassa-725	166	1	the	the	DET
ijassa-725	166	2	classifier	classifier	NOUN
ijassa-725	166	3	learns	learn	VERB
ijassa-725	166	4	the	the	DET
ijassa-725	166	5	separation	separation	NOUN
ijassa-725	166	6	surface	surface	NOUN
ijassa-725	166	7	copyright	copyright	NOUN
ijassa-725	166	8	c	c	ADP
ijassa-725	166	9	©	©	PROPN
ijassa-725	166	10	2019	2019	NUM
ijassa-725	166	11	assa	assa	NOUN
ijassa-725	166	12	.	.	PUNCT
ijassa-725	167	1	adv	adv	PROPN
ijassa-725	167	2	syst	syst	PROPN
ijassa-725	167	3	sci	sci	PROPN
ijassa-725	167	4	appl	appl	PROPN
ijassa-725	167	5	(	(	PUNCT
ijassa-725	167	6	2019	2019	NUM
ijassa-725	167	7	)	)	PUNCT
ijassa-725	167	8	29	29	NUM
ijassa-725	167	9	between	between	ADP
ijassa-725	167	10	them	they	PRON
ijassa-725	167	11	and	and	CCONJ
ijassa-725	167	12	is	be	AUX
ijassa-725	167	13	using	use	VERB
ijassa-725	167	14	it	it	PRON
ijassa-725	167	15	for	for	ADP
ijassa-725	167	16	anomalies	anomaly	NOUN
ijassa-725	167	17	detection	detection	NOUN
ijassa-725	167	18	for	for	ADP
ijassa-725	167	19	new	new	ADJ
ijassa-725	167	20	measurements	measurement	NOUN
ijassa-725	167	21	.	.	PUNCT
ijassa-725	168	1	similarly	similarly	ADV
ijassa-725	168	2	to	to	ADP
ijassa-725	168	3	the	the	DET
ijassa-725	168	4	var	var	NOUN
ijassa-725	168	5	models	model	NOUN
ijassa-725	168	6	,	,	PUNCT
ijassa-725	168	7	several	several	ADJ
ijassa-725	168	8	binary	binary	ADJ
ijassa-725	168	9	classifiers	classifier	NOUN
ijassa-725	168	10	[	[	X
ijassa-725	168	11	17	17	NUM
ijassa-725	168	12	]	]	PUNCT
ijassa-725	168	13	are	be	AUX
ijassa-725	168	14	considered	consider	VERB
ijassa-725	168	15	:	:	PUNCT
ijassa-725	168	16	logistic	logistic	ADJ
ijassa-725	168	17	regression	regression	NOUN
ijassa-725	168	18	,	,	PUNCT
ijassa-725	168	19	naive	naive	ADJ
ijassa-725	168	20	bayes	bayes	NOUN
ijassa-725	168	21	classifier	classifier	NOUN
ijassa-725	168	22	,	,	PUNCT
ijassa-725	168	23	shallow	shallow	ADJ
ijassa-725	168	24	neural	neural	ADJ
ijassa-725	168	25	networks	network	NOUN
ijassa-725	168	26	,	,	PUNCT
ijassa-725	168	27	random	random	ADJ
ijassa-725	168	28	forest	forest	NOUN
ijassa-725	168	29	and	and	CCONJ
ijassa-725	168	30	gradient	gradient	NOUN
ijassa-725	168	31	boosting	boost	VERB
ijassa-725	168	32	over	over	ADP
ijassa-725	168	33	decision	decision	NOUN
ijassa-725	168	34	trees	tree	NOUN
ijassa-725	168	35	classifiers	classifier	NOUN
ijassa-725	168	36	.	.	PUNCT
ijassa-725	169	1	they	they	PRON
ijassa-725	169	2	are	be	AUX
ijassa-725	169	3	used	use	VERB
ijassa-725	169	4	to	to	PART
ijassa-725	169	5	predict	predict	VERB
ijassa-725	169	6	anomaly	anomaly	NOUN
ijassa-725	169	7	scores	score	NOUN
ijassa-725	169	8	:	:	PUNCT
ijassa-725	169	9	ŝit	ŝit	NOUN
ijassa-725	169	10	=	=	X
ijassa-725	169	11	fi(yt	fi(yt	PROPN
ijassa-725	169	12	,	,	PUNCT
ijassa-725	169	13	yt−1	yt−1	PROPN
ijassa-725	169	14	,	,	PUNCT
ijassa-725	169	15	...	...	PUNCT
ijassa-725	169	16	,	,	PUNCT
ijassa-725	169	17	yt−k	yt−k	NOUN
ijassa-725	169	18	)	)	PUNCT
ijassa-725	169	19	(	(	PUNCT
ijassa-725	169	20	4.11	4.11	NUM
ijassa-725	169	21	)	)	PUNCT
ijassa-725	169	22	where	where	SCONJ
ijassa-725	169	23	ŝit	ŝit	VERB
ijassa-725	169	24	∈	∈	PROPN
ijassa-725	170	1	[	[	X
ijassa-725	170	2	0	0	NUM
ijassa-725	170	3	,	,	PUNCT
ijassa-725	170	4	1	1	NUM
ijassa-725	170	5	]	]	PUNCT
ijassa-725	170	6	is	be	AUX
ijassa-725	170	7	a	a	DET
ijassa-725	170	8	predicted	predict	VERB
ijassa-725	170	9	anomaly	anomaly	NOUN
ijassa-725	170	10	score	score	NOUN
ijassa-725	170	11	.	.	PUNCT
ijassa-725	171	1	parameters	parameter	NOUN
ijassa-725	171	2	of	of	ADP
ijassa-725	171	3	the	the	DET
ijassa-725	171	4	classifiers	classifier	NOUN
ijassa-725	171	5	are	be	AUX
ijassa-725	171	6	optimized	optimize	VERB
ijassa-725	171	7	using	use	VERB
ijassa-725	171	8	grid	grid	NOUN
ijassa-725	171	9	search	search	NOUN
ijassa-725	171	10	to	to	PART
ijassa-725	171	11	minimize	minimize	VERB
ijassa-725	171	12	the	the	DET
ijassa-725	171	13	logistic	logistic	ADJ
ijassa-725	171	14	loss	loss	NOUN
ijassa-725	171	15	function	function	NOUN
ijassa-725	171	16	:	:	PUNCT
ijassa-725	172	1	l	l	X
ijassa-725	172	2	=	=	PUNCT
ijassa-725	173	1	−	−	PROPN
ijassa-725	173	2	∑	∑	PROPN
ijassa-725	173	3	t	t	PROPN
ijassa-725	173	4	(	(	PUNCT
ijassa-725	173	5	sit	sit	VERB
ijassa-725	173	6	log	log	NOUN
ijassa-725	173	7	ŝit	ŝit	NOUN
ijassa-725	173	8	+	+	CCONJ
ijassa-725	173	9	(	(	PUNCT
ijassa-725	173	10	1−	1−	NUM
ijassa-725	173	11	sit	sit	NOUN
ijassa-725	173	12	)	)	PUNCT
ijassa-725	173	13	log	log	NOUN
ijassa-725	173	14	(	(	PUNCT
ijassa-725	173	15	1−	1−	NUM
ijassa-725	173	16	ŝit	ŝit	NOUN
ijassa-725	173	17	)	)	PUNCT
ijassa-725	173	18	)	)	PUNCT
ijassa-725	173	19	(	(	PUNCT
ijassa-725	173	20	4.12	4.12	NUM
ijassa-725	173	21	)	)	PUNCT
ijassa-725	173	22	where	where	SCONJ
ijassa-725	173	23	sit	sit	VERB
ijassa-725	173	24	∈	∈	PROPN
ijassa-725	173	25	{	{	PUNCT
ijassa-725	173	26	0	0	NUM
ijassa-725	173	27	,	,	PUNCT
ijassa-725	173	28	1	1	NUM
ijassa-725	173	29	}	}	PUNCT
ijassa-725	173	30	is	be	AUX
ijassa-725	173	31	a	a	DET
ijassa-725	173	32	true	true	ADJ
ijassa-725	173	33	anomaly	anomaly	NOUN
ijassa-725	173	34	score	score	NOUN
ijassa-725	173	35	for	for	ADP
ijassa-725	173	36	t	t	PROPN
ijassa-725	173	37	-	-	PUNCT
ijassa-725	173	38	th	th	X
ijassa-725	173	39	measurement	measurement	NOUN
ijassa-725	173	40	of	of	ADP
ijassa-725	173	41	i	i	PROPN
ijassa-725	173	42	-	-	PUNCT
ijassa-725	173	43	th	th	PROPN
ijassa-725	173	44	time	time	NOUN
ijassa-725	173	45	series	series	NOUN
ijassa-725	173	46	;	;	PUNCT
ijassa-725	173	47	the	the	DET
ijassa-725	173	48	classifier	classifier	NOUN
ijassa-725	173	49	with	with	ADP
ijassa-725	173	50	the	the	DET
ijassa-725	173	51	lowest	low	ADJ
ijassa-725	173	52	value	value	NOUN
ijassa-725	173	53	of	of	ADP
ijassa-725	173	54	the	the	DET
ijassa-725	173	55	loss	loss	NOUN
ijassa-725	173	56	function	function	NOUN
ijassa-725	173	57	wins	win	VERB
ijassa-725	173	58	and	and	CCONJ
ijassa-725	173	59	is	be	AUX
ijassa-725	173	60	used	use	VERB
ijassa-725	173	61	for	for	ADP
ijassa-725	173	62	the	the	DET
ijassa-725	173	63	anomalies	anomaly	NOUN
ijassa-725	173	64	detection	detection	NOUN
ijassa-725	173	65	.	.	PUNCT
ijassa-725	174	1	the	the	DET
ijassa-725	174	2	example	example	NOUN
ijassa-725	174	3	of	of	ADP
ijassa-725	174	4	the	the	DET
ijassa-725	174	5	binary	binary	ADJ
ijassa-725	174	6	classification	classification	NOUN
ijassa-725	174	7	work	work	NOUN
ijassa-725	174	8	is	be	AUX
ijassa-725	174	9	shown	show	VERB
ijassa-725	174	10	in	in	ADP
ijassa-725	174	11	fig	fig	NOUN
ijassa-725	174	12	.	.	PUNCT
ijassa-725	175	1	4.3	4.3	NUM
ijassa-725	175	2	.	.	PUNCT
ijassa-725	176	1	the	the	DET
ijassa-725	176	2	first	first	ADJ
ijassa-725	176	3	110000	110000	NUM
ijassa-725	176	4	seconds	second	NOUN
ijassa-725	176	5	are	be	AUX
ijassa-725	176	6	used	use	VERB
ijassa-725	176	7	to	to	PART
ijassa-725	176	8	train	train	VERB
ijassa-725	176	9	the	the	DET
ijassa-725	176	10	classifiers	classifier	NOUN
ijassa-725	176	11	.	.	PUNCT
ijassa-725	177	1	4.5	4.5	NUM
ijassa-725	177	2	.	.	PUNCT
ijassa-725	177	3	models	model	NOUN
ijassa-725	177	4	comparison	comparison	NOUN
ijassa-725	177	5	0.00	0.00	NUM
ijassa-725	177	6	0.01	0.01	NUM
ijassa-725	177	7	0.02	0.02	NUM
ijassa-725	177	8	0.03	0.03	NUM
ijassa-725	177	9	0.04	0.04	NUM
ijassa-725	177	10	0.05	0.05	NUM
ijassa-725	177	11	false	false	ADJ
ijassa-725	177	12	alarm	alarm	NOUN
ijassa-725	177	13	rate	rate	NOUN
ijassa-725	177	14	0.95	0.95	NUM
ijassa-725	177	15	0.96	0.96	NUM
ijassa-725	177	16	0.97	0.97	NUM
ijassa-725	177	17	0.98	0.98	NUM
ijassa-725	177	18	0.99	0.99	NUM
ijassa-725	177	19	1.00	1.00	NUM
ijassa-725	177	20	fa	fa	NOUN
ijassa-725	177	21	ilu	ilu	INTJ
ijassa-725	177	22	re	re	PROPN
ijassa-725	177	23	d	d	X
ijassa-725	177	24	et	et	PROPN
ijassa-725	177	25	ec	ec	PROPN
ijassa-725	177	26	tio	tio	PROPN
ijassa-725	177	27	n	n	ADV
ijassa-725	177	28	ra	ra	INTJ
ijassa-725	177	29	te	te	INTJ
ijassa-725	177	30	binary	binary	ADJ
ijassa-725	177	31	classification	classification	NOUN
ijassa-725	177	32	var	var	NOUN
ijassa-725	177	33	(	(	PUNCT
ijassa-725	177	34	a	a	X
ijassa-725	177	35	)	)	PUNCT
ijassa-725	177	36	0.0	0.0	NUM
ijassa-725	177	37	0.1	0.1	NUM
ijassa-725	177	38	0.2	0.2	NUM
ijassa-725	177	39	0.3	0.3	NUM
ijassa-725	177	40	0.4	0.4	NUM
ijassa-725	177	41	0.5	0.5	NUM
ijassa-725	177	42	false	false	ADJ
ijassa-725	177	43	alarm	alarm	NOUN
ijassa-725	177	44	rate	rate	NOUN
ijassa-725	177	45	0.5	0.5	NUM
ijassa-725	177	46	0.6	0.6	NUM
ijassa-725	177	47	0.7	0.7	NUM
ijassa-725	178	1	0.8	0.8	NUM
ijassa-725	178	2	0.9	0.9	NUM
ijassa-725	178	3	1.0	1.0	NUM
ijassa-725	178	4	fa	fa	INTJ
ijassa-725	178	5	ilu	ilu	INTJ
ijassa-725	178	6	re	re	PROPN
ijassa-725	178	7	d	d	X
ijassa-725	178	8	et	et	PROPN
ijassa-725	178	9	ec	ec	PROPN
ijassa-725	178	10	tio	tio	PROPN
ijassa-725	178	11	n	n	ADV
ijassa-725	178	12	ra	ra	NOUN
ijassa-725	178	13	te	te	ADP
ijassa-725	178	14	isolation	isolation	NOUN
ijassa-725	178	15	forest	forest	NOUN
ijassa-725	178	16	+	+	CCONJ
ijassa-725	178	17	cusum	cusum	NOUN
ijassa-725	178	18	isolation	isolation	NOUN
ijassa-725	178	19	forest	forest	NOUN
ijassa-725	178	20	(	(	PUNCT
ijassa-725	178	21	b	b	NOUN
ijassa-725	178	22	)	)	PUNCT
ijassa-725	178	23	fig	fig	NOUN
ijassa-725	178	24	.	.	PUNCT
ijassa-725	179	1	4.4	4.4	NUM
ijassa-725	179	2	.	.	PUNCT
ijassa-725	179	3	dependencies	dependency	NOUN
ijassa-725	179	4	of	of	ADP
ijassa-725	179	5	failure	failure	NOUN
ijassa-725	179	6	detection	detection	NOUN
ijassa-725	179	7	rate	rate	NOUN
ijassa-725	179	8	from	from	ADP
ijassa-725	179	9	false	false	ADJ
ijassa-725	179	10	alarm	alarm	NOUN
ijassa-725	179	11	rate	rate	NOUN
ijassa-725	179	12	for	for	ADP
ijassa-725	179	13	different	different	ADJ
ijassa-725	179	14	anomaly	anomaly	NOUN
ijassa-725	179	15	detection	detection	NOUN
ijassa-725	179	16	algorithms	algorithm	NOUN
ijassa-725	179	17	:	:	PUNCT
ijassa-725	179	18	(	(	PUNCT
ijassa-725	179	19	a	a	X
ijassa-725	179	20	)	)	PUNCT
ijassa-725	179	21	binary	binary	ADJ
ijassa-725	179	22	classification	classification	NOUN
ijassa-725	179	23	and	and	CCONJ
ijassa-725	179	24	var	var	NOUN
ijassa-725	179	25	;	;	PUNCT
ijassa-725	179	26	(	(	PUNCT
ijassa-725	179	27	b	b	X
ijassa-725	179	28	)	)	PUNCT
ijassa-725	179	29	isolation	isolation	NOUN
ijassa-725	179	30	forest	forest	NOUN
ijassa-725	179	31	and	and	CCONJ
ijassa-725	179	32	isolation	isolation	NOUN
ijassa-725	179	33	forest	forest	NOUN
ijassa-725	179	34	with	with	ADP
ijassa-725	179	35	cusum	cusum	ADJ
ijassa-725	179	36	methods	method	NOUN
ijassa-725	179	37	.	.	PUNCT
ijassa-725	180	1	we	we	PRON
ijassa-725	180	2	collected	collect	VERB
ijassa-725	180	3	data	datum	NOUN
ijassa-725	180	4	with	with	ADP
ijassa-725	180	5	induced	induced	ADJ
ijassa-725	180	6	hardware	hardware	NOUN
ijassa-725	180	7	failures	failure	NOUN
ijassa-725	180	8	in	in	ADP
ijassa-725	180	9	different	different	ADJ
ijassa-725	180	10	storage	storage	NOUN
ijassa-725	180	11	system	system	NOUN
ijassa-725	180	12	components	component	NOUN
ijassa-725	180	13	.	.	PUNCT
ijassa-725	181	1	a	a	DET
ijassa-725	181	2	failure	failure	NOUN
ijassa-725	181	3	is	be	AUX
ijassa-725	181	4	considered	consider	VERB
ijassa-725	181	5	as	as	SCONJ
ijassa-725	181	6	detected	detect	VERB
ijassa-725	181	7	when	when	SCONJ
ijassa-725	181	8	at	at	ADV
ijassa-725	181	9	least	least	ADV
ijassa-725	181	10	one	one	NUM
ijassa-725	181	11	parameter	parameter	NOUN
ijassa-725	181	12	of	of	ADP
ijassa-725	181	13	the	the	DET
ijassa-725	181	14	system	system	NOUN
ijassa-725	181	15	demonstrates	demonstrate	VERB
ijassa-725	181	16	anomalous	anomalous	ADJ
ijassa-725	181	17	behaviour	behaviour	NOUN
ijassa-725	181	18	.	.	PUNCT
ijassa-725	182	1	time	time	PROPN
ijassa-725	182	2	series	series	PROPN
ijassa-725	182	3	for	for	ADP
ijassa-725	182	4	all	all	DET
ijassa-725	182	5	parameters	parameter	NOUN
ijassa-725	182	6	corresponded	correspond	VERB
ijassa-725	182	7	to	to	ADP
ijassa-725	182	8	one	one	NUM
ijassa-725	182	9	component	component	NOUN
ijassa-725	182	10	are	be	AUX
ijassa-725	182	11	united	unite	VERB
ijassa-725	182	12	into	into	ADP
ijassa-725	182	13	a	a	DET
ijassa-725	182	14	group	group	NOUN
ijassa-725	182	15	and	and	CCONJ
ijassa-725	182	16	used	use	VERB
ijassa-725	182	17	to	to	PART
ijassa-725	182	18	estimate	estimate	VERB
ijassa-725	182	19	anomaly	anomaly	NOUN
ijassa-725	182	20	scores	score	NOUN
ijassa-725	182	21	as	as	SCONJ
ijassa-725	182	22	described	describe	VERB
ijassa-725	182	23	in	in	ADP
ijassa-725	182	24	previous	previous	ADJ
ijassa-725	182	25	sections	section	NOUN
ijassa-725	182	26	.	.	PUNCT
ijassa-725	183	1	a	a	DET
ijassa-725	183	2	measurement	measurement	NOUN
ijassa-725	183	3	is	be	AUX
ijassa-725	183	4	anomalous	anomalous	ADJ
ijassa-725	183	5	when	when	SCONJ
ijassa-725	183	6	its	its	PRON
ijassa-725	183	7	anomaly	anomaly	NOUN
ijassa-725	183	8	score	score	NOUN
ijassa-725	183	9	ŝt	ŝt	NOUN
ijassa-725	183	10	>	>	X
ijassa-725	183	11	τ	τ	PROPN
ijassa-725	183	12	,	,	PUNCT
ijassa-725	183	13	where	where	SCONJ
ijassa-725	183	14	τ	τ	PROPN
ijassa-725	183	15	is	be	AUX
ijassa-725	183	16	a	a	DET
ijassa-725	183	17	threshold	threshold	NOUN
ijassa-725	183	18	value	value	NOUN
ijassa-725	183	19	.	.	PUNCT
ijassa-725	184	1	for	for	ADP
ijassa-725	184	2	a	a	DET
ijassa-725	184	3	set	set	NOUN
ijassa-725	184	4	of	of	ADP
ijassa-725	184	5	τ	τ	PROPN
ijassa-725	184	6	values	value	NOUN
ijassa-725	184	7	failure	failure	NOUN
ijassa-725	184	8	detection	detection	NOUN
ijassa-725	184	9	rate	rate	NOUN
ijassa-725	184	10	(	(	PUNCT
ijassa-725	184	11	fdr	fdr	PROPN
ijassa-725	184	12	)	)	PUNCT
ijassa-725	184	13	and	and	CCONJ
ijassa-725	184	14	false	false	ADJ
ijassa-725	184	15	alarm	alarm	NOUN
ijassa-725	184	16	rate	rate	NOUN
ijassa-725	184	17	(	(	PUNCT
ijassa-725	184	18	far	far	ADV
ijassa-725	184	19	)	)	PUNCT
ijassa-725	184	20	are	be	AUX
ijassa-725	184	21	calculated	calculate	VERB
ijassa-725	184	22	to	to	PART
ijassa-725	184	23	measure	measure	VERB
ijassa-725	184	24	the	the	DET
ijassa-725	184	25	failures	failure	NOUN
ijassa-725	184	26	detection	detection	NOUN
ijassa-725	184	27	quality	quality	NOUN
ijassa-725	184	28	:	:	PUNCT
ijassa-725	184	29	fdr(τ	fdr(τ	NOUN
ijassa-725	184	30	)	)	PUNCT
ijassa-725	184	31	=	=	SYM
ijassa-725	184	32	1	1	NUM
ijassa-725	184	33	nanomalies	nanomalie	NOUN
ijassa-725	184	34	∑	∑	PUNCT
ijassa-725	184	35	i	i	PRON
ijassa-725	184	36	i[ŝi	i[ŝi	VERB
ijassa-725	184	37	≥	≥	NOUN
ijassa-725	184	38	τ	τ	X
ijassa-725	184	39	|si	|si	ADP
ijassa-725	184	40	=	=	SYM
ijassa-725	184	41	1	1	X
ijassa-725	184	42	]	]	PUNCT
ijassa-725	184	43	(	(	PUNCT
ijassa-725	184	44	4.13	4.13	X
ijassa-725	184	45	)	)	PUNCT
ijassa-725	184	46	far(τ	far(τ	NOUN
ijassa-725	184	47	)	)	PUNCT
ijassa-725	184	48	=	=	SYM
ijassa-725	184	49	1	1	NUM
ijassa-725	184	50	nnormal	nnormal	NOUN
ijassa-725	184	51	∑	∑	PUNCT
ijassa-725	184	52	i	i	PRON
ijassa-725	184	53	i[ŝi	i[ŝi	VERB
ijassa-725	184	54	≥	≥	NOUN
ijassa-725	184	55	τ	τ	X
ijassa-725	184	56	|si	|si	ADP
ijassa-725	184	57	=	=	NOUN
ijassa-725	184	58	0	0	NUM
ijassa-725	184	59	]	]	X
ijassa-725	184	60	(	(	PUNCT
ijassa-725	184	61	4.14	4.14	NUM
ijassa-725	184	62	)	)	PUNCT
ijassa-725	184	63	wherenanomalies	wherenanomalie	NOUN
ijassa-725	184	64	in	in	ADP
ijassa-725	184	65	the	the	DET
ijassa-725	184	66	total	total	ADJ
ijassa-725	184	67	number	number	NOUN
ijassa-725	184	68	of	of	ADP
ijassa-725	184	69	anomalous	anomalous	ADJ
ijassa-725	184	70	measurements;nnormal	measurements;nnormal	NOUN
ijassa-725	184	71	is	be	AUX
ijassa-725	184	72	the	the	DET
ijassa-725	184	73	total	total	ADJ
ijassa-725	184	74	number	number	NOUN
ijassa-725	184	75	of	of	ADP
ijassa-725	184	76	normal	normal	ADJ
ijassa-725	184	77	measurements	measurement	NOUN
ijassa-725	184	78	.	.	PUNCT
ijassa-725	185	1	dependencies	dependency	NOUN
ijassa-725	185	2	of	of	ADP
ijassa-725	185	3	failure	failure	NOUN
ijassa-725	185	4	detection	detection	NOUN
ijassa-725	185	5	rate	rate	NOUN
ijassa-725	185	6	from	from	ADP
ijassa-725	185	7	false	false	ADJ
ijassa-725	185	8	alarm	alarm	NOUN
ijassa-725	185	9	rate	rate	NOUN
ijassa-725	185	10	copyright	copyright	NOUN
ijassa-725	185	11	c	c	ADP
ijassa-725	185	12	©	©	PROPN
ijassa-725	185	13	2019	2019	NUM
ijassa-725	185	14	assa	assa	NOUN
ijassa-725	185	15	.	.	PUNCT
ijassa-725	186	1	adv	adv	PROPN
ijassa-725	186	2	syst	syst	PROPN
ijassa-725	186	3	sci	sci	PROPN
ijassa-725	186	4	appl	appl	PROPN
ijassa-725	186	5	(	(	PUNCT
ijassa-725	186	6	2019	2019	NUM
ijassa-725	186	7	)	)	PUNCT
ijassa-725	186	8	30	30	NUM
ijassa-725	186	9	roc	roc	PROPN
ijassa-725	186	10	auc	auc	X
ijassa-725	186	11	fdr	fdr	PROPN
ijassa-725	186	12	(	(	PUNCT
ijassa-725	186	13	far	far	ADV
ijassa-725	186	14	=	=	SYM
ijassa-725	186	15	5	5	NUM
ijassa-725	186	16	%	%	NOUN
ijassa-725	186	17	)	)	PUNCT
ijassa-725	186	18	fdr	fdr	PROPN
ijassa-725	186	19	(	(	PUNCT
ijassa-725	186	20	far	far	ADV
ijassa-725	186	21	=	=	SYM
ijassa-725	186	22	1	1	NUM
ijassa-725	186	23	%	%	NOUN
ijassa-725	186	24	)	)	PUNCT
ijassa-725	186	25	binary	binary	NOUN
ijassa-725	186	26	classification	classification	NOUN
ijassa-725	186	27	0.999	0.999	NUM
ijassa-725	186	28	0.997	0.997	NUM
ijassa-725	186	29	0.991	0.991	NUM
ijassa-725	186	30	var	var	NOUN
ijassa-725	186	31	0.997	0.997	NUM
ijassa-725	186	32	0.987	0.987	NUM
ijassa-725	186	33	0.975	0.975	NUM
ijassa-725	186	34	isolation	isolation	NOUN
ijassa-725	186	35	forest	forest	NOUN
ijassa-725	186	36	0.755	0.755	NUM
ijassa-725	186	37	0.0	0.0	NUM
ijassa-725	186	38	0.0	0.0	NUM
ijassa-725	186	39	isolation	isolation	NOUN
ijassa-725	186	40	forest	forest	NOUN
ijassa-725	186	41	+	+	CCONJ
ijassa-725	186	42	cusum	cusum	VERB
ijassa-725	186	43	0.956	0.956	NUM
ijassa-725	186	44	0.852	0.852	NUM
ijassa-725	186	45	0.836	0.836	NUM
ijassa-725	186	46	table	table	NOUN
ijassa-725	186	47	4.1	4.1	NUM
ijassa-725	186	48	.	.	PUNCT
ijassa-725	187	1	quality	quality	NOUN
ijassa-725	187	2	metrics	metric	NOUN
ijassa-725	187	3	for	for	ADP
ijassa-725	187	4	the	the	DET
ijassa-725	187	5	anomalies	anomaly	NOUN
ijassa-725	187	6	detection	detection	NOUN
ijassa-725	187	7	algorithms	algorithm	NOUN
ijassa-725	187	8	.	.	PUNCT
ijassa-725	188	1	for	for	ADP
ijassa-725	188	2	different	different	ADJ
ijassa-725	188	3	anomaly	anomaly	NOUN
ijassa-725	188	4	detection	detection	NOUN
ijassa-725	188	5	algorithms	algorithm	NOUN
ijassa-725	188	6	are	be	AUX
ijassa-725	188	7	shown	show	VERB
ijassa-725	188	8	in	in	ADP
ijassa-725	188	9	fig	fig	NOUN
ijassa-725	188	10	.	.	PUNCT
ijassa-725	189	1	4.4	4.4	NUM
ijassa-725	189	2	.	.	PUNCT
ijassa-725	190	1	these	these	DET
ijassa-725	190	2	dependencies	dependency	NOUN
ijassa-725	190	3	are	be	AUX
ijassa-725	190	4	also	also	ADV
ijassa-725	190	5	known	know	VERB
ijassa-725	190	6	as	as	ADP
ijassa-725	190	7	roc	roc	NOUN
ijassa-725	190	8	-	-	PUNCT
ijassa-725	190	9	curves	curve	NOUN
ijassa-725	190	10	.	.	PUNCT
ijassa-725	191	1	area	area	NOUN
ijassa-725	191	2	under	under	ADP
ijassa-725	191	3	the	the	DET
ijassa-725	191	4	roc	roc	NOUN
ijassa-725	191	5	-	-	PUNCT
ijassa-725	191	6	curve	curve	NOUN
ijassa-725	191	7	(	(	PUNCT
ijassa-725	191	8	roc	roc	PROPN
ijassa-725	191	9	auc	auc	NOUN
ijassa-725	191	10	)	)	PUNCT
ijassa-725	191	11	is	be	AUX
ijassa-725	191	12	widely	widely	ADV
ijassa-725	191	13	used	use	VERB
ijassa-725	191	14	in	in	ADP
ijassa-725	191	15	machine	machine	NOUN
ijassa-725	191	16	learning	learn	VERB
ijassa-725	191	17	to	to	PART
ijassa-725	191	18	measure	measure	VERB
ijassa-725	191	19	quality	quality	NOUN
ijassa-725	191	20	of	of	ADP
ijassa-725	191	21	classification	classification	NOUN
ijassa-725	191	22	.	.	PUNCT
ijassa-725	192	1	roc	roc	PROPN
ijassa-725	192	2	aucs	aucs	PROPN
ijassa-725	192	3	,	,	PUNCT
ijassa-725	192	4	failure	failure	NOUN
ijassa-725	192	5	detection	detection	NOUN
ijassa-725	192	6	rates	rate	NOUN
ijassa-725	192	7	that	that	PRON
ijassa-725	192	8	correspond	correspond	VERB
ijassa-725	192	9	to	to	ADP
ijassa-725	192	10	false	false	ADJ
ijassa-725	192	11	alarm	alarm	NOUN
ijassa-725	192	12	rate	rate	NOUN
ijassa-725	192	13	values	value	NOUN
ijassa-725	192	14	of	of	ADP
ijassa-725	192	15	5	5	NUM
ijassa-725	192	16	%	%	NOUN
ijassa-725	192	17	and	and	CCONJ
ijassa-725	192	18	1	1	NUM
ijassa-725	192	19	%	%	NOUN
ijassa-725	192	20	for	for	ADP
ijassa-725	192	21	different	different	ADJ
ijassa-725	192	22	anomaly	anomaly	NOUN
ijassa-725	192	23	detection	detection	NOUN
ijassa-725	192	24	algorithms	algorithm	NOUN
ijassa-725	192	25	are	be	AUX
ijassa-725	192	26	presented	present	VERB
ijassa-725	192	27	in	in	ADP
ijassa-725	192	28	tab	tab	NOUN
ijassa-725	192	29	.	.	PUNCT
ijassa-725	193	1	4.1	4.1	NUM
ijassa-725	193	2	.	.	PUNCT
ijassa-725	194	1	the	the	DET
ijassa-725	194	2	results	result	NOUN
ijassa-725	194	3	demonstrate	demonstrate	VERB
ijassa-725	194	4	that	that	SCONJ
ijassa-725	194	5	the	the	DET
ijassa-725	194	6	binary	binary	ADJ
ijassa-725	194	7	classification	classification	NOUN
ijassa-725	194	8	method	method	NOUN
ijassa-725	194	9	has	have	VERB
ijassa-725	194	10	the	the	DET
ijassa-725	194	11	best	good	ADJ
ijassa-725	194	12	quality	quality	NOUN
ijassa-725	194	13	.	.	PUNCT
ijassa-725	195	1	it	it	PRON
ijassa-725	195	2	detects	detect	VERB
ijassa-725	195	3	larger	large	ADJ
ijassa-725	195	4	than	than	ADP
ijassa-725	195	5	99	99	NUM
ijassa-725	195	6	%	%	NOUN
ijassa-725	195	7	of	of	ADP
ijassa-725	195	8	all	all	DET
ijassa-725	195	9	anomalous	anomalous	ADJ
ijassa-725	195	10	states	state	NOUN
ijassa-725	195	11	with	with	ADP
ijassa-725	195	12	false	false	ADJ
ijassa-725	195	13	alarm	alarm	NOUN
ijassa-725	195	14	rate	rate	NOUN
ijassa-725	195	15	below	below	ADP
ijassa-725	195	16	5	5	NUM
ijassa-725	195	17	%	%	NOUN
ijassa-725	195	18	.	.	PUNCT
ijassa-725	196	1	these	these	DET
ijassa-725	196	2	results	result	NOUN
ijassa-725	196	3	can	can	AUX
ijassa-725	196	4	be	be	AUX
ijassa-725	196	5	explained	explain	VERB
ijassa-725	196	6	by	by	ADP
ijassa-725	196	7	the	the	DET
ijassa-725	196	8	learning	learning	NOUN
ijassa-725	196	9	procedure	procedure	NOUN
ijassa-725	196	10	of	of	ADP
ijassa-725	196	11	the	the	DET
ijassa-725	196	12	method	method	NOUN
ijassa-725	196	13	.	.	PUNCT
ijassa-725	197	1	during	during	ADP
ijassa-725	197	2	this	this	DET
ijassa-725	197	3	procedure	procedure	NOUN
ijassa-725	197	4	it	it	PRON
ijassa-725	197	5	recognizes	recognize	VERB
ijassa-725	197	6	separation	separation	NOUN
ijassa-725	197	7	surface	surface	NOUN
ijassa-725	197	8	between	between	ADP
ijassa-725	197	9	normal	normal	ADJ
ijassa-725	197	10	and	and	CCONJ
ijassa-725	197	11	anomalous	anomalous	ADJ
ijassa-725	197	12	states	state	NOUN
ijassa-725	197	13	in	in	ADP
ijassa-725	197	14	the	the	DET
ijassa-725	197	15	system	system	NOUN
ijassa-725	197	16	parameters	parameter	NOUN
ijassa-725	197	17	space	space	NOUN
ijassa-725	197	18	.	.	PUNCT
ijassa-725	198	1	then	then	ADV
ijassa-725	198	2	it	it	PRON
ijassa-725	198	3	uses	use	VERB
ijassa-725	198	4	this	this	DET
ijassa-725	198	5	surface	surface	NOUN
ijassa-725	198	6	to	to	PART
ijassa-725	198	7	distinguish	distinguish	VERB
ijassa-725	198	8	the	the	DET
ijassa-725	198	9	system	system	NOUN
ijassa-725	198	10	states	state	NOUN
ijassa-725	198	11	on	on	ADP
ijassa-725	198	12	new	new	ADJ
ijassa-725	198	13	measurements	measurement	NOUN
ijassa-725	198	14	.	.	PUNCT
ijassa-725	199	1	var	var	PROPN
ijassa-725	199	2	model	model	PROPN
ijassa-725	199	3	shows	show	VERB
ijassa-725	199	4	similar	similar	ADJ
ijassa-725	199	5	results	result	NOUN
ijassa-725	199	6	.	.	PUNCT
ijassa-725	200	1	it	it	PRON
ijassa-725	200	2	recognizes	recognize	VERB
ijassa-725	200	3	about	about	ADP
ijassa-725	200	4	98	98	NUM
ijassa-725	200	5	%	%	NOUN
ijassa-725	200	6	of	of	ADP
ijassa-725	200	7	all	all	DET
ijassa-725	200	8	anomalous	anomalous	ADJ
ijassa-725	200	9	states	state	NOUN
ijassa-725	200	10	with	with	ADP
ijassa-725	200	11	false	false	ADJ
ijassa-725	200	12	alarm	alarm	NOUN
ijassa-725	200	13	rate	rate	NOUN
ijassa-725	200	14	below	below	ADP
ijassa-725	200	15	5	5	NUM
ijassa-725	200	16	%	%	NOUN
ijassa-725	200	17	.	.	PUNCT
ijassa-725	201	1	however	however	ADV
ijassa-725	201	2	,	,	PUNCT
ijassa-725	201	3	unlike	unlike	ADP
ijassa-725	201	4	the	the	DET
ijassa-725	201	5	binary	binary	ADJ
ijassa-725	201	6	classification	classification	NOUN
ijassa-725	201	7	it	it	PRON
ijassa-725	201	8	does	do	AUX
ijassa-725	201	9	not	not	PART
ijassa-725	201	10	use	use	VERB
ijassa-725	201	11	any	any	DET
ijassa-725	201	12	information	information	NOUN
ijassa-725	201	13	about	about	ADP
ijassa-725	201	14	anomalies	anomaly	NOUN
ijassa-725	201	15	.	.	PUNCT
ijassa-725	202	1	the	the	DET
ijassa-725	202	2	model	model	NOUN
ijassa-725	202	3	takes	take	VERB
ijassa-725	202	4	only	only	ADV
ijassa-725	202	5	the	the	DET
ijassa-725	202	6	system	system	NOUN
ijassa-725	202	7	parameters	parameter	NOUN
ijassa-725	202	8	measurements	measurement	NOUN
ijassa-725	202	9	for	for	ADP
ijassa-725	202	10	normal	normal	ADJ
ijassa-725	202	11	states	state	NOUN
ijassa-725	202	12	to	to	PART
ijassa-725	202	13	learn	learn	VERB
ijassa-725	202	14	normal	normal	ADJ
ijassa-725	202	15	behaviour	behaviour	NOUN
ijassa-725	202	16	of	of	ADP
ijassa-725	202	17	the	the	DET
ijassa-725	202	18	system	system	NOUN
ijassa-725	202	19	.	.	PUNCT
ijassa-725	203	1	any	any	DET
ijassa-725	203	2	significant	significant	ADJ
ijassa-725	203	3	deviation	deviation	NOUN
ijassa-725	203	4	from	from	ADP
ijassa-725	203	5	this	this	DET
ijassa-725	203	6	behaviour	behaviour	NOUN
ijassa-725	203	7	considered	consider	VERB
ijassa-725	203	8	as	as	ADP
ijassa-725	203	9	anomaly	anomaly	NOUN
ijassa-725	203	10	.	.	PUNCT
ijassa-725	204	1	this	this	PRON
ijassa-725	204	2	allows	allow	VERB
ijassa-725	204	3	var	var	NOUN
ijassa-725	204	4	to	to	PART
ijassa-725	204	5	detect	detect	VERB
ijassa-725	204	6	unknown	unknown	ADJ
ijassa-725	204	7	anomalies	anomaly	NOUN
ijassa-725	204	8	.	.	PUNCT
ijassa-725	205	1	isolation	isolation	NOUN
ijassa-725	205	2	forest	forest	NOUN
ijassa-725	205	3	demonstrates	demonstrate	VERB
ijassa-725	205	4	high	high	ADJ
ijassa-725	205	5	false	false	ADJ
ijassa-725	205	6	alarm	alarm	NOUN
ijassa-725	205	7	rates	rate	NOUN
ijassa-725	205	8	.	.	PUNCT
ijassa-725	206	1	due	due	ADP
ijassa-725	206	2	to	to	ADP
ijassa-725	206	3	the	the	DET
ijassa-725	206	4	noise	noise	NOUN
ijassa-725	206	5	in	in	ADP
ijassa-725	206	6	the	the	DET
ijassa-725	206	7	parameters	parameter	NOUN
ijassa-725	206	8	measurements	measurement	VERB
ijassa-725	206	9	isolation	isolation	NOUN
ijassa-725	206	10	forest	forest	NOUN
ijassa-725	206	11	detects	detect	NOUN
ijassa-725	206	12	some	some	DET
ijassa-725	206	13	normal	normal	ADJ
ijassa-725	206	14	measurements	measurement	NOUN
ijassa-725	206	15	as	as	ADP
ijassa-725	206	16	anomalous	anomalous	ADJ
ijassa-725	206	17	and	and	CCONJ
ijassa-725	206	18	generates	generate	VERB
ijassa-725	206	19	false	false	ADJ
ijassa-725	206	20	alarms	alarm	NOUN
ijassa-725	206	21	.	.	PUNCT
ijassa-725	207	1	it	it	PRON
ijassa-725	207	2	does	do	AUX
ijassa-725	207	3	not	not	PART
ijassa-725	207	4	use	use	VERB
ijassa-725	207	5	any	any	DET
ijassa-725	207	6	information	information	NOUN
ijassa-725	207	7	about	about	ADP
ijassa-725	207	8	anomalies	anomaly	NOUN
ijassa-725	207	9	during	during	ADP
ijassa-725	207	10	the	the	DET
ijassa-725	207	11	training	training	NOUN
ijassa-725	207	12	procedure	procedure	NOUN
ijassa-725	207	13	,	,	PUNCT
ijassa-725	207	14	that	that	PRON
ijassa-725	207	15	makes	make	VERB
ijassa-725	207	16	it	it	PRON
ijassa-725	207	17	harder	hard	ADJ
ijassa-725	207	18	to	to	PART
ijassa-725	207	19	detect	detect	VERB
ijassa-725	207	20	anomalies	anomaly	NOUN
ijassa-725	207	21	compared	compare	VERB
ijassa-725	207	22	with	with	ADP
ijassa-725	207	23	binary	binary	ADJ
ijassa-725	207	24	classification	classification	NOUN
ijassa-725	207	25	.	.	PUNCT
ijassa-725	208	1	cusum	cusum	PROPN
ijassa-725	208	2	test	test	NOUN
ijassa-725	208	3	helps	help	VERB
ijassa-725	208	4	to	to	PART
ijassa-725	208	5	reduce	reduce	VERB
ijassa-725	208	6	a	a	DET
ijassa-725	208	7	number	number	NOUN
ijassa-725	208	8	of	of	ADP
ijassa-725	208	9	false	false	ADJ
ijassa-725	208	10	alarms	alarm	NOUN
ijassa-725	208	11	and	and	CCONJ
ijassa-725	208	12	improves	improve	VERB
ijassa-725	208	13	quality	quality	NOUN
ijassa-725	208	14	of	of	ADP
ijassa-725	208	15	the	the	DET
ijassa-725	208	16	anomalies	anomaly	NOUN
ijassa-725	208	17	detection	detection	NOUN
ijassa-725	208	18	in	in	ADP
ijassa-725	208	19	a	a	DET
ijassa-725	208	20	small	small	ADJ
ijassa-725	208	21	far	far	ADJ
ijassa-725	208	22	region	region	NOUN
ijassa-725	208	23	as	as	SCONJ
ijassa-725	208	24	it	it	PRON
ijassa-725	208	25	is	be	AUX
ijassa-725	208	26	shown	show	VERB
ijassa-725	208	27	in	in	ADP
ijassa-725	208	28	fig	fig	NOUN
ijassa-725	208	29	.	.	PUNCT
ijassa-725	209	1	4.4	4.4	NUM
ijassa-725	209	2	.	.	X
ijassa-725	210	1	5	5	NUM
ijassa-725	210	2	.	.	X
ijassa-725	210	3	conclusion	conclusion	NOUN
ijassa-725	210	4	several	several	ADJ
ijassa-725	210	5	approaches	approach	NOUN
ijassa-725	210	6	for	for	ADP
ijassa-725	210	7	automatic	automatic	ADJ
ijassa-725	210	8	anomalies	anomaly	NOUN
ijassa-725	210	9	detection	detection	NOUN
ijassa-725	210	10	for	for	ADP
ijassa-725	210	11	data	data	NOUN
ijassa-725	210	12	storage	storage	NOUN
ijassa-725	210	13	systems	system	NOUN
ijassa-725	210	14	were	be	AUX
ijassa-725	210	15	tested	test	VERB
ijassa-725	210	16	and	and	CCONJ
ijassa-725	210	17	compared	compare	VERB
ijassa-725	210	18	.	.	PUNCT
ijassa-725	211	1	these	these	DET
ijassa-725	211	2	approaches	approach	NOUN
ijassa-725	211	3	are	be	AUX
ijassa-725	211	4	based	base	VERB
ijassa-725	211	5	on	on	ADP
ijassa-725	211	6	binary	binary	ADJ
ijassa-725	211	7	and	and	CCONJ
ijassa-725	211	8	one	one	NUM
ijassa-725	211	9	-	-	PUNCT
ijassa-725	211	10	class	class	NOUN
ijassa-725	211	11	classification	classification	NOUN
ijassa-725	211	12	algorithms	algorithm	NOUN
ijassa-725	211	13	as	as	ADV
ijassa-725	211	14	well	well	ADV
ijassa-725	211	15	as	as	ADP
ijassa-725	211	16	on	on	ADP
ijassa-725	211	17	var	var	NOUN
ijassa-725	211	18	models	model	NOUN
ijassa-725	211	19	of	of	ADP
ijassa-725	211	20	time	time	NOUN
ijassa-725	211	21	series	series	PROPN
ijassa-725	211	22	analysis	analysis	NOUN
ijassa-725	211	23	.	.	PUNCT
ijassa-725	212	1	the	the	DET
ijassa-725	212	2	binary	binary	ADJ
ijassa-725	212	3	classification	classification	NOUN
ijassa-725	212	4	method	method	NOUN
ijassa-725	212	5	has	have	AUX
ijassa-725	212	6	demonstrated	demonstrate	VERB
ijassa-725	212	7	the	the	DET
ijassa-725	212	8	best	good	ADJ
ijassa-725	212	9	detection	detection	NOUN
ijassa-725	212	10	quality	quality	NOUN
ijassa-725	212	11	.	.	PUNCT
ijassa-725	213	1	it	it	PRON
ijassa-725	213	2	allows	allow	VERB
ijassa-725	213	3	to	to	PART
ijassa-725	213	4	detect	detect	VERB
ijassa-725	213	5	about	about	ADV
ijassa-725	213	6	99	99	NUM
ijassa-725	213	7	%	%	NOUN
ijassa-725	213	8	of	of	ADP
ijassa-725	213	9	anomalous	anomalous	ADJ
ijassa-725	213	10	states	state	NOUN
ijassa-725	213	11	with	with	ADP
ijassa-725	213	12	false	false	ADJ
ijassa-725	213	13	alarm	alarm	NOUN
ijassa-725	213	14	rate	rate	NOUN
ijassa-725	213	15	of	of	ADP
ijassa-725	213	16	about	about	ADV
ijassa-725	213	17	1	1	NUM
ijassa-725	213	18	%	%	NOUN
ijassa-725	213	19	.	.	PUNCT
ijassa-725	214	1	the	the	DET
ijassa-725	214	2	main	main	ADJ
ijassa-725	214	3	limitation	limitation	NOUN
ijassa-725	214	4	of	of	ADP
ijassa-725	214	5	this	this	DET
ijassa-725	214	6	method	method	NOUN
ijassa-725	214	7	is	be	AUX
ijassa-725	214	8	that	that	SCONJ
ijassa-725	214	9	it	it	PRON
ijassa-725	214	10	requires	require	VERB
ijassa-725	214	11	information	information	NOUN
ijassa-725	214	12	about	about	ADP
ijassa-725	214	13	anomalies	anomaly	NOUN
ijassa-725	214	14	to	to	PART
ijassa-725	214	15	learn	learn	VERB
ijassa-725	214	16	how	how	SCONJ
ijassa-725	214	17	to	to	PART
ijassa-725	214	18	detect	detect	VERB
ijassa-725	214	19	them	they	PRON
ijassa-725	214	20	.	.	PUNCT
ijassa-725	215	1	this	this	PRON
ijassa-725	215	2	provides	provide	VERB
ijassa-725	215	3	the	the	DET
ijassa-725	215	4	high	high	ADJ
ijassa-725	215	5	detection	detection	NOUN
ijassa-725	215	6	quality	quality	NOUN
ijassa-725	215	7	but	but	CCONJ
ijassa-725	215	8	makes	make	VERB
ijassa-725	215	9	it	it	PRON
ijassa-725	215	10	impossible	impossible	ADJ
ijassa-725	215	11	to	to	PART
ijassa-725	215	12	use	use	VERB
ijassa-725	215	13	the	the	DET
ijassa-725	215	14	method	method	NOUN
ijassa-725	215	15	for	for	ADP
ijassa-725	215	16	detection	detection	NOUN
ijassa-725	215	17	previously	previously	ADV
ijassa-725	215	18	unseen	unseen	ADJ
ijassa-725	215	19	anomalies	anomaly	NOUN
ijassa-725	215	20	.	.	PUNCT
ijassa-725	216	1	to	to	PART
ijassa-725	216	2	resolve	resolve	VERB
ijassa-725	216	3	this	this	DET
ijassa-725	216	4	limitation	limitation	NOUN
ijassa-725	216	5	two	two	NUM
ijassa-725	216	6	additional	additional	ADJ
ijassa-725	216	7	methods	method	NOUN
ijassa-725	216	8	were	be	AUX
ijassa-725	216	9	considered	consider	VERB
ijassa-725	216	10	.	.	PUNCT
ijassa-725	217	1	these	these	DET
ijassa-725	217	2	methods	method	NOUN
ijassa-725	217	3	do	do	AUX
ijassa-725	217	4	not	not	PART
ijassa-725	217	5	use	use	VERB
ijassa-725	217	6	information	information	NOUN
ijassa-725	217	7	about	about	ADP
ijassa-725	217	8	anomalies	anomaly	NOUN
ijassa-725	217	9	during	during	ADP
ijassa-725	217	10	their	their	PRON
ijassa-725	217	11	training	training	NOUN
ijassa-725	217	12	procedures	procedure	NOUN
ijassa-725	217	13	.	.	PUNCT
ijassa-725	218	1	they	they	PRON
ijassa-725	218	2	are	be	AUX
ijassa-725	218	3	able	able	ADJ
ijassa-725	218	4	to	to	PART
ijassa-725	218	5	detect	detect	VERB
ijassa-725	218	6	previously	previously	ADV
ijassa-725	218	7	unseen	unseen	ADJ
ijassa-725	218	8	anomalies	anomaly	NOUN
ijassa-725	218	9	.	.	PUNCT
ijassa-725	219	1	isolation	isolation	NOUN
ijassa-725	219	2	forest	forest	NOUN
ijassa-725	219	3	shows	show	VERB
ijassa-725	219	4	very	very	ADV
ijassa-725	219	5	small	small	ADJ
ijassa-725	219	6	failures	failure	NOUN
ijassa-725	219	7	detection	detection	NOUN
ijassa-725	219	8	rate	rate	NOUN
ijassa-725	219	9	in	in	ADP
ijassa-725	219	10	a	a	DET
ijassa-725	219	11	region	region	NOUN
ijassa-725	219	12	of	of	ADP
ijassa-725	219	13	false	false	ADJ
ijassa-725	219	14	alarm	alarm	NOUN
ijassa-725	219	15	rate	rate	NOUN
ijassa-725	219	16	below	below	ADP
ijassa-725	219	17	5	5	NUM
ijassa-725	219	18	%	%	NOUN
ijassa-725	219	19	.	.	PUNCT
ijassa-725	220	1	however	however	ADV
ijassa-725	220	2	,	,	PUNCT
ijassa-725	220	3	var	var	PROPN
ijassa-725	220	4	model	model	NOUN
ijassa-725	220	5	of	of	ADP
ijassa-725	220	6	time	time	NOUN
ijassa-725	220	7	series	series	PROPN
ijassa-725	220	8	analysis	analysis	NOUN
ijassa-725	220	9	in	in	ADP
ijassa-725	220	10	combination	combination	NOUN
ijassa-725	220	11	with	with	ADP
ijassa-725	220	12	cusum	cusum	NOUN
ijassa-725	220	13	test	test	NOUN
ijassa-725	220	14	demonstrates	demonstrate	VERB
ijassa-725	220	15	promising	promising	ADJ
ijassa-725	220	16	results	result	NOUN
ijassa-725	220	17	.	.	PUNCT
ijassa-725	221	1	it	it	PRON
ijassa-725	221	2	detects	detect	VERB
ijassa-725	221	3	about	about	ADV
ijassa-725	221	4	97	97	NUM
ijassa-725	221	5	%	%	NOUN
ijassa-725	221	6	of	of	ADP
ijassa-725	221	7	anomalous	anomalous	ADJ
ijassa-725	221	8	states	state	NOUN
ijassa-725	221	9	with	with	ADP
ijassa-725	221	10	false	false	ADJ
ijassa-725	221	11	alarm	alarm	NOUN
ijassa-725	221	12	rate	rate	NOUN
ijassa-725	221	13	is	be	AUX
ijassa-725	221	14	about	about	ADV
ijassa-725	221	15	1	1	NUM
ijassa-725	221	16	%	%	NOUN
ijassa-725	221	17	.	.	PUNCT
ijassa-725	222	1	the	the	DET
ijassa-725	222	2	method	method	NOUN
ijassa-725	222	3	learns	learn	VERB
ijassa-725	222	4	normal	normal	ADJ
ijassa-725	222	5	behaviour	behaviour	NOUN
ijassa-725	222	6	of	of	ADP
ijassa-725	222	7	the	the	DET
ijassa-725	222	8	system	system	NOUN
ijassa-725	222	9	and	and	CCONJ
ijassa-725	222	10	detects	detect	VERB
ijassa-725	222	11	any	any	DET
ijassa-725	222	12	changes	change	NOUN
ijassa-725	222	13	of	of	ADP
ijassa-725	222	14	it	it	PRON
ijassa-725	222	15	.	.	PUNCT
ijassa-725	223	1	in	in	ADP
ijassa-725	223	2	our	our	PRON
ijassa-725	223	3	future	future	ADJ
ijassa-725	223	4	works	work	NOUN
ijassa-725	223	5	we	we	PRON
ijassa-725	223	6	are	be	AUX
ijassa-725	223	7	going	go	VERB
ijassa-725	223	8	to	to	PART
ijassa-725	223	9	continue	continue	VERB
ijassa-725	223	10	developing	develop	VERB
ijassa-725	223	11	methods	method	NOUN
ijassa-725	223	12	of	of	ADP
ijassa-725	223	13	anomaly	anomaly	NOUN
ijassa-725	223	14	detection	detection	NOUN
ijassa-725	223	15	for	for	ADP
ijassa-725	223	16	data	data	NOUN
ijassa-725	223	17	storage	storage	NOUN
ijassa-725	223	18	systems	system	NOUN
ijassa-725	223	19	based	base	VERB
ijassa-725	223	20	on	on	ADP
ijassa-725	223	21	time	time	NOUN
ijassa-725	223	22	series	series	PROPN
ijassa-725	223	23	analysis	analysis	NOUN
ijassa-725	223	24	methods	method	NOUN
ijassa-725	223	25	.	.	PUNCT
ijassa-725	224	1	the	the	DET
ijassa-725	224	2	goal	goal	NOUN
ijassa-725	224	3	is	be	AUX
ijassa-725	224	4	to	to	PART
ijassa-725	224	5	investigate	investigate	VERB
ijassa-725	224	6	the	the	DET
ijassa-725	224	7	methods	method	NOUN
ijassa-725	224	8	that	that	PRON
ijassa-725	224	9	are	be	AUX
ijassa-725	224	10	able	able	ADJ
ijassa-725	224	11	to	to	PART
ijassa-725	224	12	recognize	recognize	VERB
ijassa-725	224	13	any	any	DET
ijassa-725	224	14	anomalies	anomaly	NOUN
ijassa-725	224	15	without	without	ADP
ijassa-725	224	16	training	training	NOUN
ijassa-725	224	17	procedure	procedure	NOUN
ijassa-725	224	18	that	that	PRON
ijassa-725	224	19	uses	use	VERB
ijassa-725	224	20	information	information	NOUN
ijassa-725	224	21	about	about	ADP
ijassa-725	224	22	these	these	DET
ijassa-725	224	23	anomalies	anomaly	NOUN
ijassa-725	224	24	.	.	PUNCT
ijassa-725	225	1	copyright	copyright	NOUN
ijassa-725	225	2	c	c	ADP
ijassa-725	225	3	©	©	PROPN
ijassa-725	225	4	2019	2019	NUM
ijassa-725	225	5	assa	assa	NOUN
ijassa-725	225	6	.	.	PUNCT
ijassa-725	226	1	adv	adv	PROPN
ijassa-725	226	2	syst	syst	PROPN
ijassa-725	226	3	sci	sci	PROPN
ijassa-725	226	4	appl	appl	PROPN
ijassa-725	226	5	(	(	PUNCT
ijassa-725	226	6	2019	2019	NUM
ijassa-725	226	7	)	)	PUNCT
ijassa-725	226	8	31	31	NUM
ijassa-725	226	9	6	6	NUM
ijassa-725	226	10	.	.	PUNCT
ijassa-725	226	11	acknowledgements	acknowledgement	NOUN
ijassa-725	226	12	the	the	DET
ijassa-725	226	13	research	research	NOUN
ijassa-725	226	14	was	be	AUX
ijassa-725	226	15	carried	carry	VERB
ijassa-725	226	16	out	out	ADP
ijassa-725	226	17	with	with	ADP
ijassa-725	226	18	the	the	DET
ijassa-725	226	19	financial	financial	ADJ
ijassa-725	226	20	support	support	NOUN
ijassa-725	226	21	of	of	ADP
ijassa-725	226	22	the	the	DET
ijassa-725	226	23	ministry	ministry	PROPN
ijassa-725	226	24	of	of	ADP
ijassa-725	226	25	science	science	PROPN
ijassa-725	226	26	and	and	CCONJ
ijassa-725	226	27	higher	high	ADJ
ijassa-725	226	28	education	education	NOUN
ijassa-725	226	29	of	of	ADP
ijassa-725	226	30	russian	russian	PROPN
ijassa-725	226	31	federation	federation	PROPN
ijassa-725	226	32	within	within	ADP
ijassa-725	226	33	the	the	DET
ijassa-725	226	34	framework	framework	NOUN
ijassa-725	226	35	of	of	ADP
ijassa-725	226	36	the	the	DET
ijassa-725	226	37	federal	federal	ADJ
ijassa-725	226	38	target	target	NOUN
ijassa-725	226	39	program	program	NOUN
ijassa-725	226	40	research	research	NOUN
ijassa-725	226	41	and	and	CCONJ
ijassa-725	226	42	development	development	NOUN
ijassa-725	226	43	in	in	ADP
ijassa-725	226	44	priority	priority	NOUN
ijassa-725	226	45	areas	area	NOUN
ijassa-725	226	46	of	of	ADP
ijassa-725	226	47	the	the	DET
ijassa-725	226	48	development	development	NOUN
ijassa-725	226	49	of	of	ADP
ijassa-725	226	50	the	the	DET
ijassa-725	226	51	scientific	scientific	ADJ
ijassa-725	226	52	and	and	CCONJ
ijassa-725	226	53	technological	technological	ADJ
ijassa-725	226	54	complex	complex	NOUN
ijassa-725	226	55	of	of	ADP
ijassa-725	226	56	russia	russia	PROPN
ijassa-725	226	57	for	for	ADP
ijassa-725	226	58	2014	2014	NUM
ijassa-725	226	59	-	-	SYM
ijassa-725	226	60	2020	2020	NUM
ijassa-725	226	61	.	.	PUNCT
ijassa-725	227	1	unique	unique	ADJ
ijassa-725	227	2	identifier	identifier	NOUN
ijassa-725	227	3	rfmefi58117x0023	rfmefi58117x0023	NOUN
ijassa-725	227	4	,	,	PUNCT
ijassa-725	227	5	agreement	agreement	NOUN
ijassa-725	227	6	14.581.21.0023	14.581.21.0023	NUM
ijassa-725	227	7	on	on	ADP
ijassa-725	227	8	03.10.2017	03.10.2017	NUM
ijassa-725	227	9	.	.	PROPN
ijassa-725	227	10	7	7	X
ijassa-725	227	11	.	.	X
ijassa-725	228	1	reference	reference	NOUN
ijassa-725	228	2	references	reference	NOUN
ijassa-725	228	3	1	1	NUM
ijassa-725	228	4	.	.	PUNCT
ijassa-725	228	5	a.	a.	NOUN
ijassa-725	228	6	patcha	patcha	PROPN
ijassa-725	228	7	and	and	CCONJ
ijassa-725	228	8	j.-m	j.-m	PROPN
ijassa-725	228	9	.	.	PUNCT
ijassa-725	229	1	park	park	PROPN
ijassa-725	229	2	,	,	PUNCT
ijassa-725	229	3	“	"	PUNCT
ijassa-725	229	4	an	an	DET
ijassa-725	229	5	overview	overview	NOUN
ijassa-725	229	6	of	of	ADP
ijassa-725	229	7	anomaly	anomaly	NOUN
ijassa-725	229	8	detection	detection	NOUN
ijassa-725	229	9	techniques	technique	NOUN
ijassa-725	229	10	:	:	PUNCT
ijassa-725	229	11	existing	exist	VERB
ijassa-725	229	12	solutions	solution	NOUN
ijassa-725	229	13	and	and	CCONJ
ijassa-725	229	14	latest	late	ADJ
ijassa-725	229	15	technological	technological	ADJ
ijassa-725	229	16	trends	trend	NOUN
ijassa-725	229	17	,	,	PUNCT
ijassa-725	229	18	”	"	PUNCT
ijassa-725	229	19	computer	computer	NOUN
ijassa-725	229	20	networks	network	NOUN
ijassa-725	229	21	,	,	PUNCT
ijassa-725	229	22	vol	vol	NOUN
ijassa-725	229	23	.	.	PROPN
ijassa-725	230	1	51	51	NUM
ijassa-725	230	2	,	,	PUNCT
ijassa-725	230	3	no	no	INTJ
ijassa-725	230	4	.	.	NOUN
ijassa-725	230	5	12	12	NUM
ijassa-725	230	6	,	,	PUNCT
ijassa-725	230	7	pp	pp	ADJ
ijassa-725	230	8	.	.	PUNCT
ijassa-725	230	9	3448	3448	NUM
ijassa-725	230	10	–	–	PUNCT
ijassa-725	230	11	3470	3470	NUM
ijassa-725	230	12	,	,	PUNCT
ijassa-725	230	13	2007	2007	NUM
ijassa-725	230	14	.	.	PUNCT
ijassa-725	231	1	2	2	X
ijassa-725	231	2	.	.	X
ijassa-725	231	3	v.	v.	PROPN
ijassa-725	231	4	chandola	chandola	PROPN
ijassa-725	231	5	,	,	PUNCT
ijassa-725	231	6	a.	a.	NOUN
ijassa-725	231	7	banerjee	banerjee	PROPN
ijassa-725	231	8	,	,	PUNCT
ijassa-725	231	9	and	and	CCONJ
ijassa-725	231	10	v.	v.	ADP
ijassa-725	231	11	kumar	kumar	PROPN
ijassa-725	231	12	,	,	PUNCT
ijassa-725	231	13	“	"	PUNCT
ijassa-725	231	14	anomaly	anomaly	NOUN
ijassa-725	231	15	detection	detection	NOUN
ijassa-725	231	16	:	:	PUNCT
ijassa-725	231	17	a	a	DET
ijassa-725	231	18	survey	survey	NOUN
ijassa-725	231	19	,	,	PUNCT
ijassa-725	231	20	”	"	PUNCT
ijassa-725	231	21	acm	acm	PROPN
ijassa-725	231	22	comput	comput	NOUN
ijassa-725	231	23	.	.	PUNCT
ijassa-725	232	1	surv	surv	PROPN
ijassa-725	232	2	.	.	PUNCT
ijassa-725	232	3	,	,	PUNCT
ijassa-725	232	4	vol	vol	NOUN
ijassa-725	232	5	.	.	PROPN
ijassa-725	232	6	41	41	NUM
ijassa-725	232	7	,	,	PUNCT
ijassa-725	232	8	pp	pp	ADJ
ijassa-725	232	9	.	.	PUNCT
ijassa-725	233	1	15:1–15:58	15:1–15:58	NUM
ijassa-725	233	2	,	,	PUNCT
ijassa-725	233	3	july	july	PROPN
ijassa-725	233	4	2009	2009	NUM
ijassa-725	233	5	.	.	PUNCT
ijassa-725	234	1	3	3	X
ijassa-725	234	2	.	.	X
ijassa-725	234	3	m.	m.	PROPN
ijassa-725	234	4	aiello	aiello	PROPN
ijassa-725	234	5	,	,	PUNCT
ijassa-725	234	6	m.	m.	NOUN
ijassa-725	234	7	mongelli	mongelli	PROPN
ijassa-725	234	8	,	,	PUNCT
ijassa-725	234	9	e.	e.	PROPN
ijassa-725	234	10	cambiaso	cambiaso	PROPN
ijassa-725	234	11	,	,	PUNCT
ijassa-725	234	12	and	and	CCONJ
ijassa-725	234	13	g.	g.	PROPN
ijassa-725	234	14	papaleo	papaleo	PROPN
ijassa-725	234	15	,	,	PUNCT
ijassa-725	234	16	“	"	PUNCT
ijassa-725	234	17	profiling	profile	VERB
ijassa-725	234	18	dns	dns	NOUN
ijassa-725	234	19	tunneling	tunneling	NOUN
ijassa-725	234	20	attacks	attack	NOUN
ijassa-725	234	21	with	with	ADP
ijassa-725	234	22	pca	pca	NOUN
ijassa-725	234	23	and	and	CCONJ
ijassa-725	234	24	mutual	mutual	ADJ
ijassa-725	234	25	information	information	NOUN
ijassa-725	234	26	,	,	PUNCT
ijassa-725	234	27	”	"	PUNCT
ijassa-725	234	28	logic	logic	NOUN
ijassa-725	234	29	journal	journal	NOUN
ijassa-725	234	30	of	of	ADP
ijassa-725	234	31	igpl	igpl	ADJ
ijassa-725	234	32	,	,	PUNCT
ijassa-725	234	33	vol	vol	NOUN
ijassa-725	234	34	.	.	PROPN
ijassa-725	234	35	24	24	NUM
ijassa-725	234	36	,	,	PUNCT
ijassa-725	234	37	p.	p.	PROPN
ijassa-725	234	38	jzw056	jzw056	PROPN
ijassa-725	234	39	,	,	PUNCT
ijassa-725	234	40	09	09	NUM
ijassa-725	234	41	2016	2016	NUM
ijassa-725	234	42	.	.	PUNCT
ijassa-725	235	1	4	4	X
ijassa-725	235	2	.	.	X
ijassa-725	235	3	e.	e.	PROPN
ijassa-725	235	4	cambiaso	cambiaso	PROPN
ijassa-725	235	5	,	,	PUNCT
ijassa-725	235	6	m.	m.	PROPN
ijassa-725	235	7	aiello	aiello	PROPN
ijassa-725	235	8	,	,	PUNCT
ijassa-725	235	9	m.	m.	NOUN
ijassa-725	235	10	mongelli	mongelli	PROPN
ijassa-725	235	11	,	,	PUNCT
ijassa-725	235	12	and	and	CCONJ
ijassa-725	235	13	g.	g.	PROPN
ijassa-725	235	14	papaleo	papaleo	PROPN
ijassa-725	235	15	,	,	PUNCT
ijassa-725	235	16	“	"	PUNCT
ijassa-725	235	17	feature	feature	NOUN
ijassa-725	235	18	transformation	transformation	NOUN
ijassa-725	235	19	and	and	CCONJ
ijassa-725	235	20	mutual	mutual	ADJ
ijassa-725	235	21	information	information	NOUN
ijassa-725	235	22	for	for	ADP
ijassa-725	235	23	dns	dns	NOUN
ijassa-725	235	24	tunneling	tunneling	NOUN
ijassa-725	235	25	analysis	analysis	NOUN
ijassa-725	235	26	,	,	PUNCT
ijassa-725	235	27	”	"	PUNCT
ijassa-725	235	28	in	in	ADP
ijassa-725	235	29	2016	2016	NUM
ijassa-725	235	30	eighth	eighth	ADJ
ijassa-725	235	31	international	international	ADJ
ijassa-725	235	32	conference	conference	NOUN
ijassa-725	235	33	on	on	ADP
ijassa-725	235	34	ubiquitous	ubiquitous	ADJ
ijassa-725	235	35	and	and	CCONJ
ijassa-725	235	36	future	future	ADJ
ijassa-725	235	37	networks	network	NOUN
ijassa-725	235	38	(	(	PUNCT
ijassa-725	235	39	icufn	icufn	PROPN
ijassa-725	235	40	)	)	PUNCT
ijassa-725	235	41	,	,	PUNCT
ijassa-725	235	42	pp	pp	ADP
ijassa-725	235	43	.	.	PUNCT
ijassa-725	236	1	957–959	957–959	NUM
ijassa-725	236	2	,	,	PUNCT
ijassa-725	236	3	july	july	PROPN
ijassa-725	236	4	2016	2016	NUM
ijassa-725	236	5	.	.	PUNCT
ijassa-725	237	1	5	5	X
ijassa-725	237	2	.	.	X
ijassa-725	237	3	m.	m.	NOUN
ijassa-725	237	4	mongelli	mongelli	PROPN
ijassa-725	237	5	,	,	PUNCT
ijassa-725	237	6	m.	m.	PROPN
ijassa-725	237	7	aiello	aiello	PROPN
ijassa-725	237	8	,	,	PUNCT
ijassa-725	237	9	e.	e.	PROPN
ijassa-725	237	10	cambiaso	cambiaso	PROPN
ijassa-725	237	11	,	,	PUNCT
ijassa-725	237	12	and	and	CCONJ
ijassa-725	237	13	g.	g.	PROPN
ijassa-725	237	14	papaleo	papaleo	PROPN
ijassa-725	237	15	,	,	PUNCT
ijassa-725	237	16	“	"	PUNCT
ijassa-725	237	17	detection	detection	NOUN
ijassa-725	237	18	of	of	ADP
ijassa-725	237	19	dos	do	NOUN
ijassa-725	237	20	attacks	attack	NOUN
ijassa-725	237	21	through	through	ADP
ijassa-725	237	22	fourier	fourier	NOUN
ijassa-725	237	23	transform	transform	NOUN
ijassa-725	237	24	and	and	CCONJ
ijassa-725	237	25	mutual	mutual	ADJ
ijassa-725	237	26	information	information	NOUN
ijassa-725	237	27	,	,	PUNCT
ijassa-725	237	28	”	"	PUNCT
ijassa-725	237	29	in	in	ADP
ijassa-725	237	30	2015	2015	NUM
ijassa-725	237	31	ieee	ieee	NOUN
ijassa-725	237	32	international	international	ADJ
ijassa-725	237	33	conference	conference	NOUN
ijassa-725	237	34	on	on	ADP
ijassa-725	237	35	communications	communication	NOUN
ijassa-725	237	36	(	(	PUNCT
ijassa-725	237	37	icc	icc	PROPN
ijassa-725	237	38	)	)	PUNCT
ijassa-725	237	39	,	,	PUNCT
ijassa-725	237	40	pp	pp	PROPN
ijassa-725	237	41	.	.	PUNCT
ijassa-725	238	1	7204–7209	7204–7209	NUM
ijassa-725	238	2	,	,	PUNCT
ijassa-725	238	3	june	june	PROPN
ijassa-725	238	4	2015	2015	NUM
ijassa-725	238	5	.	.	PUNCT
ijassa-725	239	1	6	6	NUM
ijassa-725	239	2	.	.	PUNCT
ijassa-725	239	3	t.	t.	PROPN
ijassa-725	239	4	shon	shon	PROPN
ijassa-725	239	5	and	and	CCONJ
ijassa-725	239	6	j.	j.	PROPN
ijassa-725	239	7	moon	moon	PROPN
ijassa-725	239	8	,	,	PUNCT
ijassa-725	239	9	“	"	PUNCT
ijassa-725	239	10	a	a	DET
ijassa-725	239	11	hybrid	hybrid	ADJ
ijassa-725	239	12	machine	machine	NOUN
ijassa-725	239	13	learning	learn	VERB
ijassa-725	239	14	approach	approach	NOUN
ijassa-725	239	15	to	to	ADP
ijassa-725	239	16	network	network	NOUN
ijassa-725	239	17	anomaly	anomaly	NOUN
ijassa-725	239	18	detection	detection	NOUN
ijassa-725	239	19	,	,	PUNCT
ijassa-725	239	20	”	"	PUNCT
ijassa-725	239	21	information	information	NOUN
ijassa-725	239	22	sciences	science	NOUN
ijassa-725	239	23	,	,	PUNCT
ijassa-725	239	24	vol	vol	NOUN
ijassa-725	239	25	.	.	PROPN
ijassa-725	239	26	177	177	NUM
ijassa-725	239	27	,	,	PUNCT
ijassa-725	239	28	no	no	INTJ
ijassa-725	239	29	.	.	NOUN
ijassa-725	239	30	18	18	NUM
ijassa-725	239	31	,	,	PUNCT
ijassa-725	239	32	pp	pp	ADJ
ijassa-725	239	33	.	.	PUNCT
ijassa-725	240	1	3799	3799	NUM
ijassa-725	240	2	–	–	PUNCT
ijassa-725	240	3	3821	3821	NUM
ijassa-725	240	4	,	,	PUNCT
ijassa-725	240	5	2007	2007	NUM
ijassa-725	240	6	.	.	PUNCT
ijassa-725	241	1	7	7	X
ijassa-725	241	2	.	.	X
ijassa-725	241	3	k.	k.	PROPN
ijassa-725	241	4	limthong	limthong	PROPN
ijassa-725	241	5	,	,	PUNCT
ijassa-725	241	6	“	"	PUNCT
ijassa-725	241	7	real	real	ADJ
ijassa-725	241	8	-	-	PUNCT
ijassa-725	241	9	time	time	NOUN
ijassa-725	241	10	computer	computer	NOUN
ijassa-725	241	11	network	network	NOUN
ijassa-725	241	12	anomaly	anomaly	NOUN
ijassa-725	241	13	detection	detection	NOUN
ijassa-725	241	14	using	use	VERB
ijassa-725	241	15	machine	machine	NOUN
ijassa-725	241	16	learning	learning	NOUN
ijassa-725	241	17	techniques	technique	NOUN
ijassa-725	241	18	,	,	PUNCT
ijassa-725	241	19	”	"	PUNCT
ijassa-725	241	20	journal	journal	NOUN
ijassa-725	241	21	of	of	ADP
ijassa-725	241	22	advances	advance	NOUN
ijassa-725	241	23	in	in	ADP
ijassa-725	241	24	computer	computer	NOUN
ijassa-725	241	25	networks	network	NOUN
ijassa-725	241	26	,	,	PUNCT
ijassa-725	241	27	pp	pp	ADV
ijassa-725	241	28	.	.	PUNCT
ijassa-725	242	1	1–5	1–5	NUM
ijassa-725	242	2	,	,	PUNCT
ijassa-725	242	3	01	01	NUM
ijassa-725	242	4	2013	2013	NUM
ijassa-725	242	5	.	.	PUNCT
ijassa-725	243	1	8	8	NUM
ijassa-725	243	2	.	.	PUNCT
ijassa-725	243	3	j.	j.	PROPN
ijassa-725	243	4	hamidzadeh	hamidzadeh	PROPN
ijassa-725	243	5	,	,	PUNCT
ijassa-725	243	6	m.	m.	NOUN
ijassa-725	243	7	zabihimayvan	zabihimayvan	PROPN
ijassa-725	243	8	,	,	PUNCT
ijassa-725	243	9	and	and	CCONJ
ijassa-725	243	10	r.	r.	PROPN
ijassa-725	243	11	sadeghi	sadeghi	PROPN
ijassa-725	243	12	,	,	PUNCT
ijassa-725	243	13	“	"	PUNCT
ijassa-725	243	14	detection	detection	NOUN
ijassa-725	243	15	of	of	ADP
ijassa-725	243	16	web	web	NOUN
ijassa-725	243	17	site	site	NOUN
ijassa-725	243	18	visitors	visitor	NOUN
ijassa-725	243	19	based	base	VERB
ijassa-725	243	20	on	on	ADP
ijassa-725	243	21	fuzzy	fuzzy	ADJ
ijassa-725	243	22	rough	rough	ADJ
ijassa-725	243	23	sets	set	NOUN
ijassa-725	243	24	,	,	PUNCT
ijassa-725	243	25	”	"	PUNCT
ijassa-725	243	26	soft	soft	ADJ
ijassa-725	243	27	computing	computing	NOUN
ijassa-725	243	28	,	,	PUNCT
ijassa-725	243	29	01	01	NUM
ijassa-725	243	30	2017	2017	NUM
ijassa-725	243	31	.	.	PUNCT
ijassa-725	244	1	9	9	X
ijassa-725	244	2	.	.	X
ijassa-725	244	3	m.	m.	NOUN
ijassa-725	244	4	zabihimayvan	zabihimayvan	PROPN
ijassa-725	244	5	,	,	PUNCT
ijassa-725	244	6	r.	r.	PROPN
ijassa-725	244	7	sadeghi	sadeghi	PROPN
ijassa-725	244	8	,	,	PUNCT
ijassa-725	244	9	h.	h.	PROPN
ijassa-725	244	10	n.	n.	PROPN
ijassa-725	244	11	rude	rude	PROPN
ijassa-725	244	12	,	,	PUNCT
ijassa-725	244	13	and	and	CCONJ
ijassa-725	244	14	d.	d.	PROPN
ijassa-725	244	15	doran	doran	PROPN
ijassa-725	244	16	,	,	PUNCT
ijassa-725	244	17	“	"	PUNCT
ijassa-725	244	18	a	a	DET
ijassa-725	244	19	soft	soft	ADJ
ijassa-725	244	20	computing	computing	NOUN
ijassa-725	244	21	approach	approach	NOUN
ijassa-725	244	22	for	for	ADP
ijassa-725	244	23	benign	benign	ADJ
ijassa-725	244	24	and	and	CCONJ
ijassa-725	244	25	malicious	malicious	ADJ
ijassa-725	244	26	web	web	NOUN
ijassa-725	244	27	robot	robot	NOUN
ijassa-725	244	28	detection	detection	NOUN
ijassa-725	244	29	,	,	PUNCT
ijassa-725	244	30	”	"	PUNCT
ijassa-725	244	31	expert	expert	NOUN
ijassa-725	244	32	syst	syst	NOUN
ijassa-725	244	33	.	.	PUNCT
ijassa-725	245	1	appl	appl	PROPN
ijassa-725	245	2	.	.	PROPN
ijassa-725	245	3	,	,	PUNCT
ijassa-725	245	4	vol	vol	NOUN
ijassa-725	245	5	.	.	PROPN
ijassa-725	246	1	87	87	NUM
ijassa-725	246	2	,	,	PUNCT
ijassa-725	246	3	pp	pp	ADJ
ijassa-725	246	4	.	.	PUNCT
ijassa-725	247	1	129–140	129–140	NUM
ijassa-725	247	2	,	,	PUNCT
ijassa-725	247	3	nov	nov	PROPN
ijassa-725	247	4	.	.	PROPN
ijassa-725	247	5	2017	2017	NUM
ijassa-725	247	6	.	.	PUNCT
ijassa-725	248	1	10	10	NUM
ijassa-725	248	2	.	.	PUNCT
ijassa-725	248	3	m.	m.	PROPN
ijassa-725	248	4	zabihi	zabihi	PROPN
ijassa-725	248	5	,	,	PUNCT
ijassa-725	248	6	m.	m.	NOUN
ijassa-725	248	7	v.	v.	ADP
ijassa-725	248	8	jahan	jahan	PROPN
ijassa-725	248	9	,	,	PUNCT
ijassa-725	248	10	and	and	CCONJ
ijassa-725	248	11	j.	j.	PROPN
ijassa-725	248	12	hamidzadeh	hamidzadeh	PROPN
ijassa-725	248	13	,	,	PUNCT
ijassa-725	248	14	“	"	PUNCT
ijassa-725	248	15	a	a	DET
ijassa-725	248	16	density	density	NOUN
ijassa-725	248	17	based	base	VERB
ijassa-725	248	18	clustering	clustering	ADJ
ijassa-725	248	19	approach	approach	NOUN
ijassa-725	248	20	for	for	ADP
ijassa-725	248	21	web	web	NOUN
ijassa-725	248	22	robot	robot	NOUN
ijassa-725	248	23	detection	detection	NOUN
ijassa-725	248	24	,	,	PUNCT
ijassa-725	248	25	”	"	PUNCT
ijassa-725	248	26	in	in	ADP
ijassa-725	248	27	2014	2014	NUM
ijassa-725	248	28	4th	4th	ADJ
ijassa-725	248	29	international	international	ADJ
ijassa-725	248	30	conference	conference	NOUN
ijassa-725	248	31	on	on	ADP
ijassa-725	248	32	computer	computer	NOUN
ijassa-725	248	33	and	and	CCONJ
ijassa-725	248	34	knowledge	knowledge	NOUN
ijassa-725	248	35	engineering	engineering	NOUN
ijassa-725	248	36	(	(	PUNCT
ijassa-725	248	37	iccke	iccke	ADJ
ijassa-725	248	38	)	)	PUNCT
ijassa-725	248	39	,	,	PUNCT
ijassa-725	248	40	pp	pp	PROPN
ijassa-725	248	41	.	.	PUNCT
ijassa-725	249	1	23–28	23–28	NUM
ijassa-725	249	2	,	,	PUNCT
ijassa-725	249	3	oct	oct	PROPN
ijassa-725	249	4	2014	2014	NUM
ijassa-725	249	5	.	.	PUNCT
ijassa-725	250	1	11	11	NUM
ijassa-725	250	2	.	.	PUNCT
ijassa-725	250	3	q.	q.	PROPN
ijassa-725	250	4	lin	lin	PROPN
ijassa-725	250	5	,	,	PUNCT
ijassa-725	250	6	h.	h.	PROPN
ijassa-725	250	7	zhang	zhang	PROPN
ijassa-725	250	8	,	,	PUNCT
ijassa-725	250	9	j.-g	j.-g	PROPN
ijassa-725	250	10	.	.	PUNCT
ijassa-725	251	1	lou	lou	PROPN
ijassa-725	251	2	,	,	PUNCT
ijassa-725	251	3	y.	y.	PROPN
ijassa-725	251	4	zhang	zhang	PROPN
ijassa-725	251	5	,	,	PUNCT
ijassa-725	251	6	and	and	CCONJ
ijassa-725	251	7	x.	x.	PROPN
ijassa-725	251	8	chen	chen	PROPN
ijassa-725	251	9	,	,	PUNCT
ijassa-725	251	10	“	"	PUNCT
ijassa-725	251	11	log	log	VERB
ijassa-725	251	12	clustering	clustering	NOUN
ijassa-725	251	13	based	base	VERB
ijassa-725	251	14	problem	problem	NOUN
ijassa-725	251	15	identification	identification	NOUN
ijassa-725	251	16	for	for	ADP
ijassa-725	251	17	online	online	ADJ
ijassa-725	251	18	service	service	NOUN
ijassa-725	251	19	systems	system	NOUN
ijassa-725	251	20	,	,	PUNCT
ijassa-725	251	21	”	"	PUNCT
ijassa-725	251	22	in	in	ADP
ijassa-725	251	23	proceedings	proceeding	NOUN
ijassa-725	251	24	of	of	ADP
ijassa-725	251	25	the	the	DET
ijassa-725	251	26	38th	38th	ADJ
ijassa-725	251	27	international	international	ADJ
ijassa-725	251	28	conference	conference	NOUN
ijassa-725	251	29	on	on	ADP
ijassa-725	251	30	software	software	NOUN
ijassa-725	251	31	engineering	engineering	NOUN
ijassa-725	251	32	companion	companion	NOUN
ijassa-725	251	33	,	,	PUNCT
ijassa-725	251	34	icse	icse	PROPN
ijassa-725	251	35	’	'	PUNCT
ijassa-725	251	36	16	16	NUM
ijassa-725	251	37	,	,	PUNCT
ijassa-725	251	38	(	(	PUNCT
ijassa-725	251	39	new	new	PROPN
ijassa-725	251	40	york	york	PROPN
ijassa-725	251	41	,	,	PUNCT
ijassa-725	251	42	ny	ny	PROPN
ijassa-725	251	43	,	,	PUNCT
ijassa-725	251	44	usa	usa	PROPN
ijassa-725	251	45	)	)	PUNCT
ijassa-725	251	46	,	,	PUNCT
ijassa-725	251	47	pp	pp	ADJ
ijassa-725	251	48	.	.	PUNCT
ijassa-725	252	1	102–111	102–111	NUM
ijassa-725	252	2	,	,	PUNCT
ijassa-725	252	3	acm	acm	PROPN
ijassa-725	252	4	,	,	PUNCT
ijassa-725	252	5	2016	2016	NUM
ijassa-725	252	6	.	.	PUNCT
ijassa-725	253	1	12	12	NUM
ijassa-725	253	2	.	.	PUNCT
ijassa-725	254	1	s.	s.	PROPN
ijassa-725	254	2	he	he	PRON
ijassa-725	254	3	,	,	PUNCT
ijassa-725	254	4	j.	j.	PROPN
ijassa-725	254	5	zhu	zhu	PROPN
ijassa-725	254	6	,	,	PUNCT
ijassa-725	254	7	p.	p.	NOUN
ijassa-725	254	8	he	he	PRON
ijassa-725	254	9	,	,	PUNCT
ijassa-725	254	10	and	and	CCONJ
ijassa-725	254	11	m.	m.	PROPN
ijassa-725	254	12	r.	r.	PROPN
ijassa-725	254	13	lyu	lyu	PROPN
ijassa-725	254	14	,	,	PUNCT
ijassa-725	254	15	“	"	PUNCT
ijassa-725	254	16	experience	experience	NOUN
ijassa-725	254	17	report	report	NOUN
ijassa-725	254	18	:	:	PUNCT
ijassa-725	254	19	system	system	NOUN
ijassa-725	254	20	log	log	VERB
ijassa-725	254	21	analysis	analysis	NOUN
ijassa-725	254	22	for	for	ADP
ijassa-725	254	23	anomaly	anomaly	NOUN
ijassa-725	254	24	detection	detection	NOUN
ijassa-725	254	25	,	,	PUNCT
ijassa-725	254	26	”	"	PUNCT
ijassa-725	254	27	in	in	ADP
ijassa-725	254	28	2016	2016	NUM
ijassa-725	254	29	ieee	ieee	NOUN
ijassa-725	254	30	27th	27th	ADJ
ijassa-725	254	31	international	international	ADJ
ijassa-725	254	32	symposium	symposium	NOUN
ijassa-725	254	33	on	on	ADP
ijassa-725	254	34	software	software	NOUN
ijassa-725	254	35	reliability	reliability	NOUN
ijassa-725	254	36	engineering	engineering	NOUN
ijassa-725	254	37	(	(	PUNCT
ijassa-725	254	38	issre	issre	NOUN
ijassa-725	254	39	)	)	PUNCT
ijassa-725	254	40	,	,	PUNCT
ijassa-725	254	41	pp	pp	ADP
ijassa-725	254	42	.	.	PUNCT
ijassa-725	255	1	207–218	207–218	NUM
ijassa-725	255	2	,	,	PUNCT
ijassa-725	255	3	oct	oct	PROPN
ijassa-725	255	4	2016	2016	NUM
ijassa-725	255	5	.	.	PUNCT
ijassa-725	256	1	13	13	NUM
ijassa-725	256	2	.	.	PUNCT
ijassa-725	256	3	w.	w.	PROPN
ijassa-725	256	4	xu	xu	PROPN
ijassa-725	256	5	,	,	PUNCT
ijassa-725	256	6	l.	l.	PROPN
ijassa-725	256	7	huang	huang	PROPN
ijassa-725	256	8	,	,	PUNCT
ijassa-725	256	9	a.	a.	PROPN
ijassa-725	256	10	fox	fox	PROPN
ijassa-725	256	11	,	,	PUNCT
ijassa-725	256	12	d.	d.	PROPN
ijassa-725	256	13	patterson	patterson	PROPN
ijassa-725	256	14	,	,	PUNCT
ijassa-725	256	15	and	and	CCONJ
ijassa-725	256	16	m.	m.	PROPN
ijassa-725	256	17	i.	i.	PROPN
ijassa-725	256	18	jordan	jordan	PROPN
ijassa-725	256	19	,	,	PUNCT
ijassa-725	256	20	“	"	PUNCT
ijassa-725	256	21	detecting	detect	VERB
ijassa-725	256	22	large	large	ADJ
ijassa-725	256	23	-	-	PUNCT
ijassa-725	256	24	scale	scale	NOUN
ijassa-725	256	25	system	system	NOUN
ijassa-725	256	26	problems	problem	NOUN
ijassa-725	256	27	by	by	ADP
ijassa-725	256	28	mining	mining	NOUN
ijassa-725	256	29	console	console	NOUN
ijassa-725	256	30	logs	log	NOUN
ijassa-725	256	31	,	,	PUNCT
ijassa-725	256	32	”	"	PUNCT
ijassa-725	256	33	in	in	ADP
ijassa-725	256	34	proceedings	proceeding	NOUN
ijassa-725	256	35	of	of	ADP
ijassa-725	256	36	the	the	DET
ijassa-725	256	37	acm	acm	PROPN
ijassa-725	256	38	sigops	sigops	PROPN
ijassa-725	256	39	22nd	22nd	NOUN
ijassa-725	256	40	symposium	symposium	NOUN
ijassa-725	256	41	on	on	ADP
ijassa-725	256	42	operating	operating	NOUN
ijassa-725	256	43	systems	system	NOUN
ijassa-725	256	44	principles	principle	NOUN
ijassa-725	256	45	,	,	PUNCT
ijassa-725	256	46	sosp	sosp	PROPN
ijassa-725	256	47	’	'	PUNCT
ijassa-725	256	48	09	09	NUM
ijassa-725	256	49	,	,	PUNCT
ijassa-725	256	50	(	(	PUNCT
ijassa-725	256	51	new	new	PROPN
ijassa-725	256	52	york	york	PROPN
ijassa-725	256	53	,	,	PUNCT
ijassa-725	256	54	ny	ny	PROPN
ijassa-725	256	55	,	,	PUNCT
ijassa-725	256	56	usa	usa	PROPN
ijassa-725	256	57	)	)	PUNCT
ijassa-725	256	58	,	,	PUNCT
ijassa-725	256	59	pp	pp	ADP
ijassa-725	256	60	.	.	PUNCT
ijassa-725	257	1	117–132	117–132	NUM
ijassa-725	257	2	,	,	PUNCT
ijassa-725	257	3	acm	acm	PROPN
ijassa-725	257	4	,	,	PUNCT
ijassa-725	257	5	2009	2009	NUM
ijassa-725	257	6	.	.	PUNCT
ijassa-725	258	1	14	14	NUM
ijassa-725	258	2	.	.	PUNCT
ijassa-725	259	1	c.	c.	PROPN
ijassa-725	259	2	a.	a.	PROPN
ijassa-725	259	3	c.	c.	PROPN
ijassa-725	259	4	rincn	rincn	PROPN
ijassa-725	259	5	,	,	PUNCT
ijassa-725	259	6	j.	j.	PROPN
ijassa-725	259	7	pris	pris	PROPN
ijassa-725	259	8	,	,	PUNCT
ijassa-725	259	9	r.	r.	PROPN
ijassa-725	259	10	vilalta	vilalta	PROPN
ijassa-725	259	11	,	,	PUNCT
ijassa-725	259	12	a.	a.	PROPN
ijassa-725	259	13	m.	m.	PROPN
ijassa-725	259	14	k.	k.	PROPN
ijassa-725	259	15	cheng	cheng	PROPN
ijassa-725	259	16	,	,	PUNCT
ijassa-725	259	17	and	and	CCONJ
ijassa-725	259	18	d.	d.	PROPN
ijassa-725	259	19	d.	d.	PROPN
ijassa-725	259	20	e.	e.	PROPN
ijassa-725	260	1	long	long	PROPN
ijassa-725	260	2	,	,	PUNCT
ijassa-725	260	3	“	"	PUNCT
ijassa-725	260	4	disk	disk	NOUN
ijassa-725	260	5	failure	failure	NOUN
ijassa-725	260	6	prediction	prediction	NOUN
ijassa-725	260	7	in	in	ADP
ijassa-725	260	8	heterogeneous	heterogeneous	ADJ
ijassa-725	260	9	environments	environment	NOUN
ijassa-725	260	10	,	,	PUNCT
ijassa-725	260	11	”	"	PUNCT
ijassa-725	260	12	in	in	ADP
ijassa-725	260	13	2017	2017	NUM
ijassa-725	260	14	international	international	ADJ
ijassa-725	260	15	symposium	symposium	NOUN
ijassa-725	260	16	copyright	copyright	NOUN
ijassa-725	260	17	c	c	ADP
ijassa-725	260	18	©	©	PROPN
ijassa-725	260	19	2019	2019	NUM
ijassa-725	260	20	assa	assa	NOUN
ijassa-725	260	21	.	.	PUNCT
ijassa-725	261	1	adv	adv	PROPN
ijassa-725	261	2	syst	syst	PROPN
ijassa-725	261	3	sci	sci	PROPN
ijassa-725	261	4	appl	appl	PROPN
ijassa-725	261	5	(	(	PUNCT
ijassa-725	261	6	2019	2019	NUM
ijassa-725	261	7	)	)	PUNCT
ijassa-725	261	8	32	32	NUM
ijassa-725	261	9	on	on	ADP
ijassa-725	261	10	performance	performance	NOUN
ijassa-725	261	11	evaluation	evaluation	NOUN
ijassa-725	261	12	of	of	ADP
ijassa-725	261	13	computer	computer	NOUN
ijassa-725	261	14	and	and	CCONJ
ijassa-725	261	15	telecommunication	telecommunication	NOUN
ijassa-725	261	16	systems	system	NOUN
ijassa-725	261	17	(	(	PUNCT
ijassa-725	261	18	spects	spect	NOUN
ijassa-725	261	19	)	)	PUNCT
ijassa-725	261	20	,	,	PUNCT
ijassa-725	261	21	pp	pp	ADP
ijassa-725	261	22	.	.	PUNCT
ijassa-725	262	1	1–7	1–7	NUM
ijassa-725	262	2	,	,	PUNCT
ijassa-725	262	3	july	july	PROPN
ijassa-725	262	4	2017	2017	NUM
ijassa-725	262	5	.	.	PUNCT
ijassa-725	263	1	15	15	NUM
ijassa-725	263	2	.	.	PUNCT
ijassa-725	264	1	j.	j.	PROPN
ijassa-725	264	2	li	li	PROPN
ijassa-725	264	3	,	,	PUNCT
ijassa-725	264	4	x.	x.	PROPN
ijassa-725	265	1	ji	ji	PROPN
ijassa-725	265	2	,	,	PUNCT
ijassa-725	265	3	y.	y.	PROPN
ijassa-725	265	4	jia	jia	PROPN
ijassa-725	265	5	,	,	PUNCT
ijassa-725	265	6	b.	b.	PROPN
ijassa-725	265	7	zhu	zhu	PROPN
ijassa-725	265	8	,	,	PUNCT
ijassa-725	265	9	g.	g.	PROPN
ijassa-725	265	10	wang	wang	PROPN
ijassa-725	265	11	,	,	PUNCT
ijassa-725	265	12	z.	z.	PROPN
ijassa-725	265	13	li	li	PROPN
ijassa-725	265	14	,	,	PUNCT
ijassa-725	265	15	and	and	CCONJ
ijassa-725	265	16	x.	x.	NOUN
ijassa-725	265	17	liu	liu	PROPN
ijassa-725	265	18	,	,	PUNCT
ijassa-725	265	19	“	"	PUNCT
ijassa-725	265	20	hard	hard	ADJ
ijassa-725	265	21	drive	drive	ADJ
ijassa-725	265	22	failure	failure	NOUN
ijassa-725	265	23	prediction	prediction	NOUN
ijassa-725	265	24	using	use	VERB
ijassa-725	265	25	classification	classification	NOUN
ijassa-725	265	26	and	and	CCONJ
ijassa-725	265	27	regression	regression	NOUN
ijassa-725	265	28	trees	tree	NOUN
ijassa-725	265	29	,	,	PUNCT
ijassa-725	265	30	”	"	PUNCT
ijassa-725	265	31	in	in	ADP
ijassa-725	265	32	2014	2014	NUM
ijassa-725	265	33	44th	44th	ADJ
ijassa-725	265	34	annual	annual	ADJ
ijassa-725	265	35	ieee	ieee	NOUN
ijassa-725	265	36	/	/	SYM
ijassa-725	265	37	ifip	ifip	PROPN
ijassa-725	265	38	international	international	ADJ
ijassa-725	265	39	conference	conference	NOUN
ijassa-725	265	40	on	on	ADP
ijassa-725	265	41	dependable	dependable	ADJ
ijassa-725	265	42	systems	system	NOUN
ijassa-725	265	43	and	and	CCONJ
ijassa-725	265	44	networks	network	NOUN
ijassa-725	265	45	,	,	PUNCT
ijassa-725	265	46	pp	pp	ADJ
ijassa-725	265	47	.	.	PUNCT
ijassa-725	266	1	383–394	383–394	NUM
ijassa-725	266	2	,	,	PUNCT
ijassa-725	266	3	june	june	PROPN
ijassa-725	266	4	2014	2014	NUM
ijassa-725	266	5	.	.	PUNCT
ijassa-725	267	1	16	16	NUM
ijassa-725	267	2	.	.	PUNCT
ijassa-725	267	3	m.	m.	NOUN
ijassa-725	267	4	borisyak	borisyak	PROPN
ijassa-725	267	5	,	,	PUNCT
ijassa-725	267	6	f.	f.	PROPN
ijassa-725	267	7	ratnikov	ratnikov	PROPN
ijassa-725	267	8	,	,	PUNCT
ijassa-725	267	9	d.	d.	PROPN
ijassa-725	267	10	derkach	derkach	PROPN
ijassa-725	267	11	,	,	PUNCT
ijassa-725	267	12	and	and	CCONJ
ijassa-725	267	13	a.	a.	NOUN
ijassa-725	267	14	ustyuzhanin	ustyuzhanin	PROPN
ijassa-725	267	15	,	,	PUNCT
ijassa-725	267	16	“	"	PUNCT
ijassa-725	267	17	towards	towards	ADP
ijassa-725	267	18	automation	automation	NOUN
ijassa-725	267	19	of	of	ADP
ijassa-725	267	20	data	datum	NOUN
ijassa-725	267	21	quality	quality	NOUN
ijassa-725	267	22	system	system	NOUN
ijassa-725	267	23	for	for	ADP
ijassa-725	267	24	cern	cern	ADJ
ijassa-725	267	25	cms	cms	NOUN
ijassa-725	267	26	experiment	experiment	NOUN
ijassa-725	267	27	,	,	PUNCT
ijassa-725	267	28	”	"	PUNCT
ijassa-725	267	29	journal	journal	NOUN
ijassa-725	267	30	of	of	ADP
ijassa-725	267	31	physics	physics	PROPN
ijassa-725	267	32	:	:	PUNCT
ijassa-725	267	33	conference	conference	NOUN
ijassa-725	267	34	series	series	NOUN
ijassa-725	267	35	,	,	PUNCT
ijassa-725	267	36	vol	vol	NOUN
ijassa-725	267	37	.	.	PROPN
ijassa-725	267	38	898	898	NUM
ijassa-725	267	39	,	,	PUNCT
ijassa-725	267	40	p.	p.	NOUN
ijassa-725	267	41	092041	092041	NUM
ijassa-725	267	42	,	,	PUNCT
ijassa-725	267	43	oct	oct	PROPN
ijassa-725	267	44	2017	2017	NUM
ijassa-725	267	45	.	.	PUNCT
ijassa-725	268	1	17	17	NUM
ijassa-725	268	2	.	.	PUNCT
ijassa-725	269	1	t.	t.	PROPN
ijassa-725	269	2	hastie	hastie	PROPN
ijassa-725	269	3	,	,	PUNCT
ijassa-725	269	4	r.	r.	PROPN
ijassa-725	269	5	tibshirani	tibshirani	PROPN
ijassa-725	269	6	,	,	PUNCT
ijassa-725	269	7	and	and	CCONJ
ijassa-725	269	8	j.	j.	PROPN
ijassa-725	269	9	friedman	friedman	PROPN
ijassa-725	269	10	,	,	PUNCT
ijassa-725	269	11	the	the	DET
ijassa-725	269	12	elements	element	NOUN
ijassa-725	269	13	of	of	ADP
ijassa-725	269	14	statistical	statistical	ADJ
ijassa-725	269	15	learning	learning	NOUN
ijassa-725	269	16	.	.	PUNCT
ijassa-725	270	1	springer	springer	NOUN
ijassa-725	270	2	series	series	PROPN
ijassa-725	270	3	in	in	ADP
ijassa-725	270	4	statistics	statistic	NOUN
ijassa-725	270	5	,	,	PUNCT
ijassa-725	270	6	new	new	PROPN
ijassa-725	270	7	york	york	PROPN
ijassa-725	270	8	,	,	PUNCT
ijassa-725	270	9	ny	ny	PROPN
ijassa-725	270	10	,	,	PUNCT
ijassa-725	270	11	usa	usa	PROPN
ijassa-725	270	12	:	:	PUNCT
ijassa-725	270	13	springer	springer	PROPN
ijassa-725	270	14	new	new	PROPN
ijassa-725	270	15	york	york	PROPN
ijassa-725	270	16	inc	inc	PROPN
ijassa-725	270	17	.	.	PROPN
ijassa-725	270	18	,	,	PUNCT
ijassa-725	270	19	2001	2001	NUM
ijassa-725	270	20	.	.	PUNCT
ijassa-725	271	1	18	18	NUM
ijassa-725	271	2	.	.	PUNCT
ijassa-725	272	1	f.	f.	PROPN
ijassa-725	272	2	t.	t.	PROPN
ijassa-725	272	3	liu	liu	PROPN
ijassa-725	272	4	,	,	PUNCT
ijassa-725	272	5	k.	k.	PROPN
ijassa-725	272	6	m.	m.	PROPN
ijassa-725	272	7	ting	ting	PROPN
ijassa-725	272	8	,	,	PUNCT
ijassa-725	272	9	and	and	CCONJ
ijassa-725	272	10	z.-h	z.-h	NOUN
ijassa-725	272	11	.	.	PUNCT
ijassa-725	273	1	zhou	zhou	PROPN
ijassa-725	273	2	,	,	PUNCT
ijassa-725	273	3	“	"	PUNCT
ijassa-725	273	4	isolation	isolation	NOUN
ijassa-725	273	5	forest	forest	NOUN
ijassa-725	273	6	,	,	PUNCT
ijassa-725	273	7	”	"	PUNCT
ijassa-725	273	8	in	in	ADP
ijassa-725	273	9	proceedings	proceeding	NOUN
ijassa-725	273	10	of	of	ADP
ijassa-725	273	11	the	the	DET
ijassa-725	273	12	2008	2008	NUM
ijassa-725	273	13	eighth	eighth	ADJ
ijassa-725	273	14	ieee	ieee	PROPN
ijassa-725	273	15	international	international	PROPN
ijassa-725	273	16	conference	conference	NOUN
ijassa-725	273	17	on	on	ADP
ijassa-725	273	18	data	datum	NOUN
ijassa-725	273	19	mining	mining	NOUN
ijassa-725	273	20	,	,	PUNCT
ijassa-725	273	21	icdm	icdm	NOUN
ijassa-725	273	22	’	'	PUNCT
ijassa-725	273	23	08	08	NUM
ijassa-725	273	24	,	,	PUNCT
ijassa-725	273	25	(	(	PUNCT
ijassa-725	273	26	washington	washington	PROPN
ijassa-725	273	27	,	,	PUNCT
ijassa-725	273	28	dc	dc	PROPN
ijassa-725	273	29	,	,	PUNCT
ijassa-725	273	30	usa	usa	PROPN
ijassa-725	273	31	)	)	PUNCT
ijassa-725	273	32	,	,	PUNCT
ijassa-725	273	33	pp	pp	ADP
ijassa-725	273	34	.	.	PUNCT
ijassa-725	274	1	413–422	413–422	NUM
ijassa-725	274	2	,	,	PUNCT
ijassa-725	274	3	ieee	ieee	NOUN
ijassa-725	274	4	computer	computer	NOUN
ijassa-725	274	5	society	society	NOUN
ijassa-725	274	6	,	,	PUNCT
ijassa-725	274	7	2008	2008	NUM
ijassa-725	274	8	.	.	PUNCT
ijassa-725	275	1	19	19	NUM
ijassa-725	275	2	.	.	X
ijassa-725	275	3	b.	b.	PROPN
ijassa-725	275	4	koo	koo	PROPN
ijassa-725	275	5	,	,	PUNCT
ijassa-725	275	6	b.	b.	PROPN
ijassa-725	275	7	shin	shin	PROPN
ijassa-725	275	8	,	,	PUNCT
ijassa-725	275	9	and	and	CCONJ
ijassa-725	275	10	t.	t.	PROPN
ijassa-725	275	11	krijnen	krijnen	PROPN
ijassa-725	275	12	,	,	PUNCT
ijassa-725	275	13	“	"	PUNCT
ijassa-725	275	14	employing	employ	VERB
ijassa-725	275	15	outlier	outlier	NOUN
ijassa-725	275	16	and	and	CCONJ
ijassa-725	275	17	novelty	novelty	NOUN
ijassa-725	275	18	detection	detection	NOUN
ijassa-725	275	19	for	for	ADP
ijassa-725	275	20	checking	check	VERB
ijassa-725	275	21	the	the	DET
ijassa-725	275	22	integrity	integrity	NOUN
ijassa-725	275	23	of	of	ADP
ijassa-725	275	24	bim	bim	NOUN
ijassa-725	275	25	to	to	PART
ijassa-725	275	26	ifc	ifc	NOUN
ijassa-725	275	27	entity	entity	NOUN
ijassa-725	275	28	associations	association	NOUN
ijassa-725	275	29	,	,	PUNCT
ijassa-725	275	30	”	"	PUNCT
ijassa-725	275	31	in	in	ADP
ijassa-725	275	32	isarc	isarc	PROPN
ijassa-725	275	33	2017	2017	NUM
ijassa-725	275	34	proceedings	proceeding	NOUN
ijassa-725	275	35	of	of	ADP
ijassa-725	275	36	the	the	DET
ijassa-725	275	37	34th	34th	ADJ
ijassa-725	275	38	international	international	ADJ
ijassa-725	275	39	symposium	symposium	NOUN
ijassa-725	275	40	on	on	ADP
ijassa-725	275	41	automation	automation	NOUN
ijassa-725	275	42	and	and	CCONJ
ijassa-725	275	43	robotics	robotic	NOUN
ijassa-725	275	44	in	in	ADP
ijassa-725	275	45	construction	construction	NOUN
ijassa-725	275	46	,	,	PUNCT
ijassa-725	275	47	28	28	NUM
ijassa-725	275	48	june	june	PROPN
ijassa-725	275	49	1	1	NUM
ijassa-725	275	50	july	july	PROPN
ijassa-725	275	51	,	,	PUNCT
ijassa-725	275	52	taipe	taipe	NOUN
ijassa-725	275	53	,	,	PUNCT
ijassa-725	275	54	taiwan	taiwan	PROPN
ijassa-725	275	55	,	,	PUNCT
ijassa-725	275	56	pp	pp	X
ijassa-725	275	57	.	.	PUNCT
ijassa-725	276	1	14–21	14–21	NUM
ijassa-725	276	2	,	,	PUNCT
ijassa-725	276	3	international	international	ADJ
ijassa-725	276	4	association	association	NOUN
ijassa-725	276	5	for	for	ADP
ijassa-725	276	6	automation	automation	NOUN
ijassa-725	276	7	and	and	CCONJ
ijassa-725	276	8	robotics	robotic	NOUN
ijassa-725	276	9	in	in	ADP
ijassa-725	276	10	construction	construction	NOUN
ijassa-725	276	11	i.a.a.r.c	i.a.a.r.c	NOUN
ijassa-725	276	12	)	)	PUNCT
ijassa-725	276	13	,	,	PUNCT
ijassa-725	276	14	2017	2017	NUM
ijassa-725	276	15	.	.	PUNCT
ijassa-725	277	1	20	20	NUM
ijassa-725	277	2	.	.	PUNCT
ijassa-725	277	3	b.	b.	PROPN
ijassa-725	277	4	schölkopf	schölkopf	PROPN
ijassa-725	277	5	,	,	PUNCT
ijassa-725	277	6	j.	j.	PROPN
ijassa-725	277	7	c.	c.	PROPN
ijassa-725	277	8	platt	platt	PROPN
ijassa-725	277	9	,	,	PUNCT
ijassa-725	277	10	j.	j.	PROPN
ijassa-725	277	11	c.	c.	PROPN
ijassa-725	277	12	shawe	shawe	PROPN
ijassa-725	277	13	-	-	PUNCT
ijassa-725	277	14	taylor	taylor	PROPN
ijassa-725	277	15	,	,	PUNCT
ijassa-725	277	16	a.	a.	PROPN
ijassa-725	277	17	j.	j.	PROPN
ijassa-725	277	18	smola	smola	PROPN
ijassa-725	277	19	,	,	PUNCT
ijassa-725	277	20	and	and	CCONJ
ijassa-725	277	21	r.	r.	PROPN
ijassa-725	277	22	c.	c.	PROPN
ijassa-725	277	23	williamson	williamson	PROPN
ijassa-725	277	24	,	,	PUNCT
ijassa-725	277	25	“	"	PUNCT
ijassa-725	277	26	estimating	estimate	VERB
ijassa-725	277	27	the	the	DET
ijassa-725	277	28	support	support	NOUN
ijassa-725	277	29	of	of	ADP
ijassa-725	277	30	a	a	DET
ijassa-725	277	31	high	high	ADJ
ijassa-725	277	32	-	-	PUNCT
ijassa-725	277	33	dimensional	dimensional	ADJ
ijassa-725	277	34	distribution	distribution	NOUN
ijassa-725	277	35	,	,	PUNCT
ijassa-725	277	36	”	"	PUNCT
ijassa-725	277	37	neural	neural	ADJ
ijassa-725	277	38	comput	comput	NOUN
ijassa-725	277	39	.	.	PUNCT
ijassa-725	277	40	,	,	PUNCT
ijassa-725	277	41	vol	vol	NOUN
ijassa-725	277	42	.	.	PROPN
ijassa-725	277	43	13	13	NUM
ijassa-725	277	44	,	,	PUNCT
ijassa-725	277	45	pp	pp	ADJ
ijassa-725	277	46	.	.	PUNCT
ijassa-725	278	1	1443–1471	1443–1471	NUM
ijassa-725	278	2	,	,	PUNCT
ijassa-725	278	3	july	july	PROPN
ijassa-725	278	4	2001	2001	NUM
ijassa-725	278	5	.	.	PUNCT
ijassa-725	279	1	21	21	NUM
ijassa-725	279	2	.	.	PUNCT
ijassa-725	279	3	r.	r.	PROPN
ijassa-725	279	4	sadeghi	sadeghi	PROPN
ijassa-725	279	5	and	and	CCONJ
ijassa-725	279	6	j.	j.	PROPN
ijassa-725	279	7	hamidzadeh	hamidzadeh	PROPN
ijassa-725	279	8	,	,	PUNCT
ijassa-725	279	9	“	"	PUNCT
ijassa-725	279	10	automatic	automatic	ADJ
ijassa-725	279	11	support	support	NOUN
ijassa-725	279	12	vector	vector	NOUN
ijassa-725	279	13	data	datum	NOUN
ijassa-725	279	14	description	description	NOUN
ijassa-725	279	15	,	,	PUNCT
ijassa-725	279	16	”	"	PUNCT
ijassa-725	279	17	soft	soft	ADJ
ijassa-725	279	18	comput	comput	NOUN
ijassa-725	279	19	.	.	PUNCT
ijassa-725	279	20	,	,	PUNCT
ijassa-725	279	21	vol	vol	NOUN
ijassa-725	279	22	.	.	PROPN
ijassa-725	279	23	22	22	NUM
ijassa-725	279	24	,	,	PUNCT
ijassa-725	279	25	pp	pp	ADJ
ijassa-725	279	26	.	.	PUNCT
ijassa-725	280	1	147–158	147–158	NUM
ijassa-725	280	2	,	,	PUNCT
ijassa-725	280	3	jan	jan	PROPN
ijassa-725	280	4	.	.	PROPN
ijassa-725	280	5	2018	2018	NUM
ijassa-725	280	6	.	.	PUNCT
ijassa-725	281	1	22	22	NUM
ijassa-725	281	2	.	.	PUNCT
ijassa-725	282	1	j.	j.	PROPN
ijassa-725	282	2	hamidzadeh	hamidzadeh	PROPN
ijassa-725	282	3	,	,	PUNCT
ijassa-725	282	4	r.	r.	PROPN
ijassa-725	282	5	sadeghi	sadeghi	PROPN
ijassa-725	282	6	,	,	PUNCT
ijassa-725	282	7	and	and	CCONJ
ijassa-725	282	8	n.	n.	PROPN
ijassa-725	282	9	namaei	namaei	PROPN
ijassa-725	282	10	,	,	PUNCT
ijassa-725	282	11	“	"	PUNCT
ijassa-725	282	12	weighted	weight	VERB
ijassa-725	282	13	support	support	NOUN
ijassa-725	282	14	vector	vector	NOUN
ijassa-725	282	15	data	datum	NOUN
ijassa-725	282	16	description	description	NOUN
ijassa-725	282	17	based	base	VERB
ijassa-725	282	18	on	on	ADP
ijassa-725	282	19	chaotic	chaotic	ADJ
ijassa-725	282	20	bat	bat	NOUN
ijassa-725	282	21	algorithm	algorithm	NOUN
ijassa-725	282	22	,	,	PUNCT
ijassa-725	282	23	”	"	PUNCT
ijassa-725	282	24	appl	appl	NOUN
ijassa-725	282	25	.	.	PUNCT
ijassa-725	282	26	soft	soft	ADJ
ijassa-725	282	27	comput	comput	NOUN
ijassa-725	282	28	.	.	PUNCT
ijassa-725	283	1	,	,	PUNCT
ijassa-725	283	2	vol	vol	NOUN
ijassa-725	283	3	.	.	PROPN
ijassa-725	283	4	60	60	NUM
ijassa-725	283	5	,	,	PUNCT
ijassa-725	283	6	pp	pp	ADJ
ijassa-725	283	7	.	.	PUNCT
ijassa-725	284	1	540–551	540–551	NUM
ijassa-725	284	2	,	,	PUNCT
ijassa-725	284	3	nov	nov	PROPN
ijassa-725	284	4	.	.	PROPN
ijassa-725	284	5	2017	2017	NUM
ijassa-725	284	6	.	.	PUNCT
ijassa-725	285	1	23	23	NUM
ijassa-725	285	2	.	.	PUNCT
ijassa-725	285	3	r.	r.	PROPN
ijassa-725	285	4	j.	j.	PROPN
ijassa-725	285	5	hyndman	hyndman	PROPN
ijassa-725	285	6	,	,	PUNCT
ijassa-725	285	7	g.	g.	PROPN
ijassa-725	285	8	athanasopoulos	athanasopoulo	NOUN
ijassa-725	285	9	,	,	PUNCT
ijassa-725	285	10	and	and	CCONJ
ijassa-725	285	11	otexts.com	otexts.com	NOUN
ijassa-725	285	12	,	,	PUNCT
ijassa-725	285	13	forecasting	forecasting	NOUN
ijassa-725	285	14	:	:	PUNCT
ijassa-725	285	15	principles	principle	NOUN
ijassa-725	285	16	and	and	CCONJ
ijassa-725	285	17	practice	practice	NOUN
ijassa-725	285	18	.	.	PUNCT
ijassa-725	286	1	otexts.com	otexts.com	X
ijassa-725	286	2	[	[	AUX
ijassa-725	286	3	heathmont	heathmont	NOUN
ijassa-725	286	4	?	?	PUNCT
ijassa-725	286	5	,	,	PUNCT
ijassa-725	286	6	victoria	victoria	PROPN
ijassa-725	286	7	]	]	PUNCT
ijassa-725	286	8	,	,	PUNCT
ijassa-725	286	9	print	print	NOUN
ijassa-725	286	10	edition	edition	NOUN
ijassa-725	286	11	.	.	PUNCT
ijassa-725	287	1	ed	ed	NOUN
ijassa-725	287	2	.	.	PROPN
ijassa-725	287	3	,	,	PUNCT
ijassa-725	287	4	2014	2014	NUM
ijassa-725	287	5	2014	2014	NUM
ijassa-725	287	6	.	.	PUNCT
ijassa-725	288	1	24	24	NUM
ijassa-725	288	2	.	.	PUNCT
ijassa-725	288	3	yadro	yadro	PROPN
ijassa-725	288	4	,	,	PUNCT
ijassa-725	288	5	“	"	PUNCT
ijassa-725	288	6	tatlin	tatlin	ADJ
ijassa-725	288	7	storage	storage	NOUN
ijassa-725	288	8	description	description	NOUN
ijassa-725	288	9	.	.	PUNCT
ijassa-725	288	10	”	"	PUNCT
ijassa-725	289	1	https://yadro.com/products/	https://yadro.com/products/	NOUN
ijassa-725	289	2	tatlin	tatlin	ADV
ijassa-725	289	3	,	,	PUNCT
ijassa-725	289	4	2019	2019	NUM
ijassa-725	289	5	.	.	PUNCT
ijassa-725	290	1	25	25	NUM
ijassa-725	290	2	.	.	PUNCT
ijassa-725	290	3	yadro	yadro	PROPN
ijassa-725	290	4	,	,	PUNCT
ijassa-725	290	5	“	"	PUNCT
ijassa-725	290	6	vesnin	vesnin	NOUN
ijassa-725	290	7	server	server	NOUN
ijassa-725	290	8	description	description	NOUN
ijassa-725	290	9	.	.	PUNCT
ijassa-725	290	10	”	"	PUNCT
ijassa-725	291	1	https://yadro.com/products/	https://yadro.com/products/	NOUN
ijassa-725	291	2	vesnin	vesnin	NOUN
ijassa-725	291	3	-	-	PUNCT
ijassa-725	291	4	tech	tech	NOUN
ijassa-725	291	5	,	,	PUNCT
ijassa-725	291	6	2019	2019	NUM
ijassa-725	291	7	.	.	PUNCT
ijassa-725	292	1	26	26	NUM
ijassa-725	292	2	.	.	PUNCT
ijassa-725	292	3	e.	e.	PROPN
ijassa-725	292	4	s.	s.	PROPN
ijassa-725	292	5	page	page	PROPN
ijassa-725	292	6	,	,	PUNCT
ijassa-725	292	7	“	"	PUNCT
ijassa-725	292	8	continuous	continuous	ADJ
ijassa-725	292	9	inspection	inspection	NOUN
ijassa-725	292	10	schemes	scheme	NOUN
ijassa-725	292	11	,	,	PUNCT
ijassa-725	292	12	”	"	PUNCT
ijassa-725	292	13	biometrika	biometrika	NOUN
ijassa-725	292	14	,	,	PUNCT
ijassa-725	292	15	vol	vol	NOUN
ijassa-725	292	16	.	.	PROPN
ijassa-725	292	17	41	41	NUM
ijassa-725	292	18	,	,	PUNCT
ijassa-725	292	19	pp	pp	ADJ
ijassa-725	292	20	.	.	PUNCT
ijassa-725	293	1	100–115	100–115	NUM
ijassa-725	293	2	,	,	PUNCT
ijassa-725	293	3	06	06	NUM
ijassa-725	293	4	1954	1954	NUM
ijassa-725	293	5	.	.	PUNCT
ijassa-725	294	1	27	27	NUM
ijassa-725	294	2	.	.	PUNCT
ijassa-725	294	3	l.	l.	PROPN
ijassa-725	294	4	koepcke	koepcke	PROPN
ijassa-725	294	5	,	,	PUNCT
ijassa-725	294	6	g.	g.	PROPN
ijassa-725	294	7	ashida	ashida	PROPN
ijassa-725	294	8	,	,	PUNCT
ijassa-725	294	9	and	and	CCONJ
ijassa-725	294	10	j.	j.	PROPN
ijassa-725	294	11	kretzberg	kretzberg	PROPN
ijassa-725	294	12	,	,	PUNCT
ijassa-725	294	13	“	"	PUNCT
ijassa-725	294	14	single	single	ADJ
ijassa-725	294	15	and	and	CCONJ
ijassa-725	294	16	multiple	multiple	ADJ
ijassa-725	294	17	change	change	NOUN
ijassa-725	294	18	point	point	NOUN
ijassa-725	294	19	detection	detection	NOUN
ijassa-725	294	20	in	in	ADP
ijassa-725	294	21	spike	spike	ADJ
ijassa-725	294	22	trains	train	NOUN
ijassa-725	294	23	:	:	PUNCT
ijassa-725	294	24	comparison	comparison	NOUN
ijassa-725	294	25	of	of	ADP
ijassa-725	294	26	different	different	ADJ
ijassa-725	294	27	cusum	cusum	NOUN
ijassa-725	294	28	methods	method	NOUN
ijassa-725	294	29	,	,	PUNCT
ijassa-725	294	30	”	"	PUNCT
ijassa-725	294	31	frontiers	frontier	NOUN
ijassa-725	294	32	in	in	ADP
ijassa-725	294	33	systems	system	NOUN
ijassa-725	294	34	neuroscience	neuroscience	NOUN
ijassa-725	294	35	,	,	PUNCT
ijassa-725	294	36	vol	vol	NOUN
ijassa-725	294	37	.	.	PROPN
ijassa-725	294	38	10	10	NUM
ijassa-725	294	39	,	,	PUNCT
ijassa-725	294	40	p.	p.	NOUN
ijassa-725	294	41	51	51	NUM
ijassa-725	294	42	,	,	PUNCT
ijassa-725	294	43	2016	2016	NUM
ijassa-725	294	44	.	.	PUNCT
ijassa-725	295	1	copyright	copyright	NOUN
ijassa-725	295	2	c	c	ADP
ijassa-725	295	3	©	©	PROPN
ijassa-725	295	4	2019	2019	NUM
ijassa-725	295	5	assa	assa	NOUN
ijassa-725	295	6	.	.	PUNCT
ijassa-725	296	1	adv	adv	PROPN
ijassa-725	296	2	syst	syst	PROPN
ijassa-725	296	3	sci	sci	PROPN
ijassa-725	296	4	appl	appl	PROPN
ijassa-725	296	5	(	(	PUNCT
ijassa-725	296	6	2019	2019	NUM
ijassa-725	296	7	)	)	PUNCT