id	sid	tid	token	lemma	pos
fcis-7524	1	1	frontiers	frontier	NOUN
fcis-7524	1	2	in	in	ADP
fcis-7524	1	3	computing	computing	NOUN
fcis-7524	1	4	and	and	CCONJ
fcis-7524	1	5	intelligent	intelligent	ADJ
fcis-7524	1	6	systems	system	NOUN
fcis-7524	1	7	issn	issn	VERB
fcis-7524	1	8	:	:	PUNCT
fcis-7524	1	9	2832	2832	NUM
fcis-7524	1	10	-	-	SYM
fcis-7524	1	11	6024	6024	NUM
fcis-7524	1	12	|	|	NOUN
fcis-7524	1	13	vol	vol	NOUN
fcis-7524	1	14	.	.	PROPN
fcis-7524	2	1	3	3	NUM
fcis-7524	2	2	,	,	PUNCT
fcis-7524	2	3	no	no	INTJ
fcis-7524	2	4	.	.	NOUN
fcis-7524	2	5	2	2	NUM
fcis-7524	2	6	,	,	PUNCT
fcis-7524	2	7	2023	2023	NUM
fcis-7524	2	8	99	99	NUM
fcis-7524	2	9	quantum	quantum	ADJ
fcis-7524	2	10	fuzzy	fuzzy	ADJ
fcis-7524	2	11	neural	neural	ADJ
fcis-7524	2	12	network	network	NOUN
fcis-7524	2	13	based	base	VERB
fcis-7524	2	14	on	on	ADP
fcis-7524	2	15	fuzzy	fuzzy	ADJ
fcis-7524	2	16	number	number	NOUN
fcis-7524	2	17	xin	xin	PROPN
fcis-7524	2	18	yang	yang	PROPN
fcis-7524	2	19	*	*	PROPN
fcis-7524	2	20	school	school	PROPN
fcis-7524	2	21	of	of	ADP
fcis-7524	2	22	cybersecurity	cybersecurity	NOUN
fcis-7524	2	23	,	,	PUNCT
fcis-7524	2	24	chengdu	chengdu	PROPN
fcis-7524	2	25	university	university	PROPN
fcis-7524	2	26	of	of	ADP
fcis-7524	2	27	information	information	NOUN
fcis-7524	2	28	technology	technology	PROPN
fcis-7524	2	29	,	,	PUNCT
fcis-7524	2	30	chengdu	chengdu	PROPN
fcis-7524	2	31	610225	610225	NUM
fcis-7524	2	32	,	,	PUNCT
fcis-7524	2	33	china	china	PROPN
fcis-7524	2	34	.	.	PUNCT
fcis-7524	3	1	*	*	PUNCT
fcis-7524	3	2	corresponding	correspond	VERB
fcis-7524	3	3	author	author	NOUN
fcis-7524	3	4	email	email	NOUN
fcis-7524	3	5	:	:	PUNCT
fcis-7524	3	6	yangxin_tut@163.com	yangxin_tut@163.com	X
fcis-7524	3	7	abstract	abstract	ADJ
fcis-7524	3	8	:	:	PUNCT
fcis-7524	3	9	neural	neural	ADJ
fcis-7524	3	10	network	network	NOUN
fcis-7524	3	11	is	be	AUX
fcis-7524	3	12	one	one	NUM
fcis-7524	3	13	of	of	ADP
fcis-7524	3	14	the	the	DET
fcis-7524	3	15	ai	ai	ADJ
fcis-7524	3	16	algorithms	algorithm	NOUN
fcis-7524	3	17	commonly	commonly	ADV
fcis-7524	3	18	used	use	VERB
fcis-7524	3	19	to	to	PART
fcis-7524	3	20	process	process	VERB
fcis-7524	3	21	data	datum	NOUN
fcis-7524	3	22	,	,	PUNCT
fcis-7524	3	23	and	and	CCONJ
fcis-7524	3	24	has	have	VERB
fcis-7524	3	25	an	an	DET
fcis-7524	3	26	extremely	extremely	ADV
fcis-7524	3	27	important	important	ADJ
fcis-7524	3	28	position	position	NOUN
fcis-7524	3	29	in	in	ADP
fcis-7524	3	30	scenarios	scenario	NOUN
fcis-7524	3	31	such	such	ADJ
fcis-7524	3	32	as	as	ADP
fcis-7524	3	33	image	image	NOUN
fcis-7524	3	34	recognition	recognition	NOUN
fcis-7524	3	35	,	,	PUNCT
fcis-7524	3	36	classification	classification	NOUN
fcis-7524	3	37	,	,	PUNCT
fcis-7524	3	38	and	and	CCONJ
fcis-7524	3	39	machine	machine	NOUN
fcis-7524	3	40	translation	translation	NOUN
fcis-7524	3	41	.	.	PUNCT
fcis-7524	4	1	with	with	ADP
fcis-7524	4	2	the	the	DET
fcis-7524	4	3	increase	increase	NOUN
fcis-7524	4	4	of	of	ADP
fcis-7524	4	5	data	datum	NOUN
fcis-7524	4	6	volume	volume	NOUN
fcis-7524	4	7	explosion	explosion	NOUN
fcis-7524	4	8	,	,	PUNCT
fcis-7524	4	9	the	the	DET
fcis-7524	4	10	required	require	VERB
fcis-7524	4	11	computing	computing	NOUN
fcis-7524	4	12	power	power	NOUN
fcis-7524	4	13	of	of	ADP
fcis-7524	4	14	neural	neural	ADJ
fcis-7524	4	15	networks	network	NOUN
fcis-7524	4	16	is	be	AUX
fcis-7524	4	17	also	also	ADV
fcis-7524	4	18	significantly	significantly	ADV
fcis-7524	4	19	increased	increase	VERB
fcis-7524	4	20	.	.	PUNCT
fcis-7524	5	1	the	the	DET
fcis-7524	5	2	emergence	emergence	NOUN
fcis-7524	5	3	of	of	ADP
fcis-7524	5	4	quantum	quantum	ADJ
fcis-7524	5	5	neural	neural	ADJ
fcis-7524	5	6	networks	network	NOUN
fcis-7524	5	7	improves	improve	VERB
fcis-7524	5	8	the	the	DET
fcis-7524	5	9	computational	computational	ADJ
fcis-7524	5	10	power	power	NOUN
fcis-7524	5	11	of	of	ADP
fcis-7524	5	12	neural	neural	ADJ
fcis-7524	5	13	networks	network	NOUN
fcis-7524	5	14	,	,	PUNCT
fcis-7524	5	15	but	but	CCONJ
fcis-7524	5	16	the	the	DET
fcis-7524	5	17	accuracy	accuracy	NOUN
fcis-7524	5	18	of	of	ADP
fcis-7524	5	19	neural	neural	ADJ
fcis-7524	5	20	networks	network	NOUN
fcis-7524	5	21	and	and	CCONJ
fcis-7524	5	22	quantum	quantum	NOUN
fcis-7524	5	23	neural	neural	ADJ
fcis-7524	5	24	networks	network	NOUN
fcis-7524	5	25	is	be	AUX
fcis-7524	5	26	not	not	PART
fcis-7524	5	27	high	high	ADJ
fcis-7524	5	28	in	in	ADP
fcis-7524	5	29	the	the	DET
fcis-7524	5	30	face	face	NOUN
fcis-7524	5	31	of	of	ADP
fcis-7524	5	32	the	the	DET
fcis-7524	5	33	complexity	complexity	NOUN
fcis-7524	5	34	and	and	CCONJ
fcis-7524	5	35	uncertainty	uncertainty	NOUN
fcis-7524	5	36	of	of	ADP
fcis-7524	5	37	big	big	ADJ
fcis-7524	5	38	data	datum	NOUN
fcis-7524	5	39	.	.	PUNCT
fcis-7524	6	1	in	in	ADP
fcis-7524	6	2	order	order	NOUN
fcis-7524	6	3	to	to	PART
fcis-7524	6	4	improve	improve	VERB
fcis-7524	6	5	the	the	DET
fcis-7524	6	6	efficiency	efficiency	NOUN
fcis-7524	6	7	and	and	CCONJ
fcis-7524	6	8	accuracy	accuracy	NOUN
fcis-7524	6	9	,	,	PUNCT
fcis-7524	6	10	the	the	DET
fcis-7524	6	11	cross	cross	NOUN
fcis-7524	6	12	-	-	NOUN
fcis-7524	6	13	fusion	fusion	NOUN
fcis-7524	6	14	of	of	ADP
fcis-7524	6	15	"	"	PUNCT
fcis-7524	6	16	fuzzy	fuzzy	ADJ
fcis-7524	6	17	number	number	NOUN
fcis-7524	6	18	theory	theory	NOUN
fcis-7524	6	19	+	+	CCONJ
fcis-7524	6	20	quantum	quantum	ADJ
fcis-7524	6	21	neural	neural	ADJ
fcis-7524	6	22	network	network	NOUN
fcis-7524	6	23	"	"	PUNCT
fcis-7524	6	24	is	be	AUX
fcis-7524	6	25	proposed	propose	VERB
fcis-7524	6	26	to	to	PART
fcis-7524	6	27	study	study	VERB
fcis-7524	6	28	the	the	DET
fcis-7524	6	29	quantum	quantum	ADJ
fcis-7524	6	30	fuzzy	fuzzy	ADJ
fcis-7524	6	31	neural	neural	ADJ
fcis-7524	6	32	network	network	NOUN
fcis-7524	6	33	(	(	PUNCT
fcis-7524	6	34	fqnn	fqnn	PROPN
fcis-7524	6	35	)	)	PUNCT
fcis-7524	6	36	based	base	VERB
fcis-7524	6	37	on	on	ADP
fcis-7524	6	38	fuzzy	fuzzy	ADJ
fcis-7524	6	39	number	number	NOUN
fcis-7524	6	40	.	.	PUNCT
fcis-7524	7	1	the	the	DET
fcis-7524	7	2	gaussian	gaussian	ADJ
fcis-7524	7	3	fuzzy	fuzzy	ADJ
fcis-7524	7	4	function	function	NOUN
fcis-7524	7	5	is	be	AUX
fcis-7524	7	6	used	use	VERB
fcis-7524	7	7	to	to	PART
fcis-7524	7	8	generate	generate	VERB
fcis-7524	7	9	the	the	DET
fcis-7524	7	10	corresponding	corresponding	ADJ
fcis-7524	7	11	fuzzy	fuzzy	ADJ
fcis-7524	7	12	affiliation	affiliation	NOUN
fcis-7524	7	13	matrix	matrix	NOUN
fcis-7524	7	14	to	to	PART
fcis-7524	7	15	describe	describe	VERB
fcis-7524	7	16	the	the	DET
fcis-7524	7	17	uncertain	uncertain	ADJ
fcis-7524	7	18	information	information	NOUN
fcis-7524	7	19	in	in	ADP
fcis-7524	7	20	the	the	DET
fcis-7524	7	21	data	datum	NOUN
fcis-7524	7	22	.	.	PUNCT
fcis-7524	8	1	the	the	DET
fcis-7524	8	2	fuzzy	fuzzy	ADJ
fcis-7524	8	3	independent	independent	ADJ
fcis-7524	8	4	variables	variable	NOUN
fcis-7524	8	5	are	be	AUX
fcis-7524	8	6	trained	train	VERB
fcis-7524	8	7	through	through	ADP
fcis-7524	8	8	the	the	DET
fcis-7524	8	9	fqnn	fqnn	PROPN
fcis-7524	8	10	model	model	NOUN
fcis-7524	8	11	,	,	PUNCT
fcis-7524	8	12	and	and	CCONJ
fcis-7524	8	13	the	the	DET
fcis-7524	8	14	model	model	NOUN
fcis-7524	8	15	is	be	AUX
fcis-7524	8	16	output	output	NOUN
fcis-7524	8	17	after	after	ADP
fcis-7524	8	18	changing	change	VERB
fcis-7524	8	19	the	the	DET
fcis-7524	8	20	parameters	parameter	NOUN
fcis-7524	8	21	of	of	ADP
fcis-7524	8	22	the	the	DET
fcis-7524	8	23	quantum	quantum	ADJ
fcis-7524	8	24	forward	forward	ADJ
fcis-7524	8	25	propagation	propagation	NOUN
fcis-7524	8	26	layer	layer	NOUN
fcis-7524	8	27	.	.	PUNCT
fcis-7524	9	1	simulation	simulation	NOUN
fcis-7524	9	2	experiments	experiment	NOUN
fcis-7524	9	3	show	show	VERB
fcis-7524	9	4	that	that	SCONJ
fcis-7524	9	5	the	the	DET
fcis-7524	9	6	quantum	quantum	ADJ
fcis-7524	9	7	fuzzy	fuzzy	ADJ
fcis-7524	9	8	neural	neural	ADJ
fcis-7524	9	9	network	network	NOUN
fcis-7524	9	10	model	model	NOUN
fcis-7524	9	11	based	base	VERB
fcis-7524	9	12	on	on	ADP
fcis-7524	9	13	fuzzy	fuzzy	ADJ
fcis-7524	9	14	number	number	NOUN
fcis-7524	9	15	is	be	AUX
fcis-7524	9	16	more	more	ADV
fcis-7524	9	17	efficient	efficient	ADJ
fcis-7524	9	18	and	and	CCONJ
fcis-7524	9	19	accurate	accurate	ADJ
fcis-7524	9	20	in	in	ADP
fcis-7524	9	21	this	this	DET
fcis-7524	9	22	study	study	NOUN
fcis-7524	9	23	compared	compare	VERB
fcis-7524	9	24	with	with	ADP
fcis-7524	9	25	the	the	DET
fcis-7524	9	26	quantum	quantum	ADJ
fcis-7524	9	27	neural	neural	ADJ
fcis-7524	9	28	network	network	NOUN
fcis-7524	9	29	model	model	NOUN
fcis-7524	9	30	.	.	PUNCT
fcis-7524	10	1	keywords	keyword	NOUN
fcis-7524	10	2	:	:	PUNCT
fcis-7524	10	3	fuzzy	fuzzy	ADJ
fcis-7524	10	4	set	set	NOUN
fcis-7524	10	5	theory	theory	NOUN
fcis-7524	10	6	;	;	PUNCT
fcis-7524	10	7	fuzzy	fuzzy	ADJ
fcis-7524	10	8	book	book	NOUN
fcis-7524	10	9	;	;	PUNCT
fcis-7524	10	10	quantum	quantum	NOUN
fcis-7524	10	11	computing	computing	NOUN
fcis-7524	10	12	;	;	PUNCT
fcis-7524	10	13	artificial	artificial	ADJ
fcis-7524	10	14	intelligence	intelligence	NOUN
fcis-7524	10	15	;	;	PUNCT
fcis-7524	10	16	quantum	quantum	X
fcis-7524	10	17	fuzzy	fuzzy	ADJ
fcis-7524	10	18	neural	neural	ADJ
fcis-7524	10	19	network	network	NOUN
fcis-7524	10	20	.	.	PUNCT
fcis-7524	11	1	1	1	X
fcis-7524	11	2	.	.	X
fcis-7524	11	3	introduction	introduction	NOUN
fcis-7524	11	4	with	with	ADP
fcis-7524	11	5	the	the	DET
fcis-7524	11	6	rapid	rapid	ADJ
fcis-7524	11	7	development	development	NOUN
fcis-7524	11	8	and	and	CCONJ
fcis-7524	11	9	extensive	extensive	ADJ
fcis-7524	11	10	use	use	NOUN
fcis-7524	11	11	of	of	ADP
fcis-7524	11	12	information	information	NOUN
fcis-7524	11	13	technology	technology	NOUN
fcis-7524	11	14	,	,	PUNCT
fcis-7524	11	15	the	the	DET
fcis-7524	11	16	explosive	explosive	ADJ
fcis-7524	11	17	growth	growth	NOUN
fcis-7524	11	18	of	of	ADP
fcis-7524	11	19	business	business	NOUN
fcis-7524	11	20	data	datum	NOUN
fcis-7524	11	21	in	in	ADP
fcis-7524	11	22	the	the	DET
fcis-7524	11	23	information	information	NOUN
fcis-7524	11	24	field	field	NOUN
fcis-7524	11	25	has	have	AUX
fcis-7524	11	26	announced	announce	VERB
fcis-7524	11	27	the	the	DET
fcis-7524	11	28	arrival	arrival	NOUN
fcis-7524	11	29	of	of	ADP
fcis-7524	11	30	the	the	DET
fcis-7524	11	31	era	era	NOUN
fcis-7524	11	32	of	of	ADP
fcis-7524	11	33	big	big	ADJ
fcis-7524	11	34	data	datum	NOUN
fcis-7524	11	35	.	.	PUNCT
fcis-7524	12	1	big	big	ADJ
fcis-7524	12	2	data	datum	NOUN
fcis-7524	12	3	is	be	AUX
fcis-7524	12	4	not	not	PART
fcis-7524	12	5	only	only	ADV
fcis-7524	12	6	a	a	DET
fcis-7524	12	7	significant	significant	ADJ
fcis-7524	12	8	increase	increase	NOUN
fcis-7524	12	9	in	in	ADP
fcis-7524	12	10	the	the	DET
fcis-7524	12	11	volume	volume	NOUN
fcis-7524	12	12	of	of	ADP
fcis-7524	12	13	data	datum	NOUN
fcis-7524	12	14	,	,	PUNCT
fcis-7524	12	15	but	but	CCONJ
fcis-7524	12	16	also	also	ADV
fcis-7524	12	17	implies	imply	VERB
fcis-7524	12	18	a	a	DET
fcis-7524	12	19	lot	lot	NOUN
fcis-7524	12	20	of	of	ADP
fcis-7524	12	21	valuable	valuable	ADJ
fcis-7524	12	22	information	information	NOUN
fcis-7524	12	23	.	.	PUNCT
fcis-7524	13	1	by	by	ADP
fcis-7524	13	2	mining	mining	NOUN
fcis-7524	13	3	and	and	CCONJ
fcis-7524	13	4	analyzing	analyze	VERB
fcis-7524	13	5	big	big	ADJ
fcis-7524	13	6	data	datum	NOUN
fcis-7524	13	7	,	,	PUNCT
fcis-7524	13	8	valuable	valuable	ADJ
fcis-7524	13	9	information	information	NOUN
fcis-7524	13	10	can	can	AUX
fcis-7524	13	11	be	be	AUX
fcis-7524	13	12	obtained	obtain	VERB
fcis-7524	13	13	to	to	PART
fcis-7524	13	14	support	support	VERB
fcis-7524	13	15	people	people	NOUN
fcis-7524	13	16	's	's	PART
fcis-7524	13	17	decision	decision	NOUN
fcis-7524	13	18	making	making	NOUN
fcis-7524	13	19	.	.	PUNCT
fcis-7524	14	1	neural	neural	ADJ
fcis-7524	14	2	network	network	NOUN
fcis-7524	14	3	[	[	X
fcis-7524	14	4	1	1	NUM
fcis-7524	14	5	]	]	PUNCT
fcis-7524	14	6	with	with	ADP
fcis-7524	14	7	powerful	powerful	ADJ
fcis-7524	14	8	computation	computation	NOUN
fcis-7524	14	9	and	and	CCONJ
fcis-7524	14	10	learning	learning	NOUN
fcis-7524	14	11	ability	ability	NOUN
fcis-7524	14	12	is	be	AUX
fcis-7524	14	13	one	one	NUM
fcis-7524	14	14	of	of	ADP
fcis-7524	14	15	the	the	DET
fcis-7524	14	16	most	most	ADV
fcis-7524	14	17	effective	effective	ADJ
fcis-7524	14	18	tools	tool	NOUN
fcis-7524	14	19	to	to	PART
fcis-7524	14	20	analyze	analyze	VERB
fcis-7524	14	21	big	big	ADJ
fcis-7524	14	22	data	datum	NOUN
fcis-7524	14	23	.	.	PUNCT
fcis-7524	15	1	in	in	ADP
fcis-7524	15	2	recent	recent	ADJ
fcis-7524	15	3	years	year	NOUN
fcis-7524	15	4	,	,	PUNCT
fcis-7524	15	5	although	although	SCONJ
fcis-7524	15	6	neural	neural	ADJ
fcis-7524	15	7	networks	network	NOUN
fcis-7524	15	8	have	have	AUX
fcis-7524	15	9	made	make	VERB
fcis-7524	15	10	rapid	rapid	ADJ
fcis-7524	15	11	development	development	NOUN
fcis-7524	15	12	in	in	ADP
fcis-7524	15	13	both	both	CCONJ
fcis-7524	15	14	theoretical	theoretical	ADJ
fcis-7524	15	15	research	research	NOUN
fcis-7524	15	16	and	and	CCONJ
fcis-7524	15	17	practical	practical	ADJ
fcis-7524	15	18	applications	application	NOUN
fcis-7524	15	19	.	.	PUNCT
fcis-7524	16	1	however	however	ADV
fcis-7524	16	2	,	,	PUNCT
fcis-7524	16	3	we	we	PRON
fcis-7524	16	4	also	also	ADV
fcis-7524	16	5	see	see	VERB
fcis-7524	16	6	that	that	SCONJ
fcis-7524	16	7	there	there	PRON
fcis-7524	16	8	are	be	VERB
fcis-7524	16	9	some	some	DET
fcis-7524	16	10	problems	problem	NOUN
fcis-7524	16	11	in	in	ADP
fcis-7524	16	12	the	the	DET
fcis-7524	16	13	face	face	NOUN
fcis-7524	16	14	of	of	ADP
fcis-7524	16	15	the	the	DET
fcis-7524	16	16	growing	grow	VERB
fcis-7524	16	17	,	,	PUNCT
fcis-7524	16	18	complex	complex	ADJ
fcis-7524	16	19	,	,	PUNCT
fcis-7524	16	20	and	and	CCONJ
fcis-7524	16	21	uncertain	uncertain	ADJ
fcis-7524	16	22	big	big	ADJ
fcis-7524	16	23	data	datum	NOUN
fcis-7524	17	1	[	[	X
fcis-7524	17	2	2	2	NUM
fcis-7524	17	3	]	]	PUNCT
fcis-7524	17	4	:	:	PUNCT
fcis-7524	17	5	first	first	ADV
fcis-7524	17	6	,	,	PUNCT
fcis-7524	17	7	as	as	ADP
fcis-7524	17	8	the	the	DET
fcis-7524	17	9	amount	amount	NOUN
fcis-7524	17	10	of	of	ADP
fcis-7524	17	11	data	data	NOUN
fcis-7524	17	12	increases	increase	NOUN
fcis-7524	17	13	,	,	PUNCT
fcis-7524	17	14	neural	neural	ADJ
fcis-7524	17	15	networks	network	NOUN
fcis-7524	17	16	need	need	VERB
fcis-7524	17	17	to	to	PART
fcis-7524	17	18	consume	consume	VERB
fcis-7524	17	19	a	a	DET
fcis-7524	17	20	large	large	ADJ
fcis-7524	17	21	amount	amount	NOUN
fcis-7524	17	22	of	of	ADP
fcis-7524	17	23	computational	computational	ADJ
fcis-7524	17	24	resources	resource	NOUN
fcis-7524	17	25	,	,	PUNCT
fcis-7524	17	26	which	which	PRON
fcis-7524	17	27	leads	lead	VERB
fcis-7524	17	28	to	to	ADP
fcis-7524	17	29	an	an	DET
fcis-7524	17	30	increase	increase	NOUN
fcis-7524	17	31	in	in	ADP
fcis-7524	17	32	computation	computation	NOUN
fcis-7524	17	33	time	time	NOUN
fcis-7524	17	34	;	;	PUNCT
fcis-7524	17	35	second	second	X
fcis-7524	17	36	,	,	PUNCT
fcis-7524	17	37	neural	neural	ADJ
fcis-7524	17	38	networks	network	NOUN
fcis-7524	17	39	can	can	AUX
fcis-7524	17	40	not	not	PART
fcis-7524	17	41	effectively	effectively	ADV
fcis-7524	17	42	deal	deal	VERB
fcis-7524	17	43	with	with	ADP
fcis-7524	17	44	the	the	DET
fcis-7524	17	45	uncertainty	uncertainty	NOUN
fcis-7524	17	46	problem	problem	NOUN
fcis-7524	17	47	that	that	SCONJ
fcis-7524	17	48	big	big	ADJ
fcis-7524	17	49	data	datum	NOUN
fcis-7524	17	50	has	have	VERB
fcis-7524	17	51	,	,	PUNCT
fcis-7524	17	52	and	and	CCONJ
fcis-7524	17	53	the	the	DET
fcis-7524	17	54	accuracy	accuracy	NOUN
fcis-7524	17	55	of	of	ADP
fcis-7524	17	56	computation	computation	NOUN
fcis-7524	17	57	will	will	AUX
fcis-7524	17	58	decrease	decrease	VERB
fcis-7524	17	59	.	.	PUNCT
fcis-7524	18	1	quantum	quantum	NOUN
fcis-7524	18	2	machine	machine	NOUN
fcis-7524	18	3	learning	learning	NOUN
fcis-7524	18	4	is	be	AUX
fcis-7524	18	5	an	an	DET
fcis-7524	18	6	approach	approach	NOUN
fcis-7524	18	7	that	that	PRON
fcis-7524	18	8	combines	combine	VERB
fcis-7524	18	9	quantum	quantum	ADJ
fcis-7524	18	10	computers	computer	NOUN
fcis-7524	18	11	with	with	ADP
fcis-7524	18	12	machine	machine	NOUN
fcis-7524	18	13	learning	learn	VERB
fcis-7524	18	14	to	to	PART
fcis-7524	18	15	achieve	achieve	VERB
fcis-7524	18	16	more	more	ADV
fcis-7524	18	17	efficient	efficient	ADJ
fcis-7524	18	18	computation	computation	NOUN
fcis-7524	18	19	in	in	ADP
fcis-7524	18	20	many	many	ADJ
fcis-7524	18	21	machine	machine	NOUN
fcis-7524	18	22	learning	learning	NOUN
fcis-7524	18	23	tasks	task	NOUN
fcis-7524	18	24	.	.	PUNCT
fcis-7524	19	1	recent	recent	ADJ
fcis-7524	19	2	research	research	NOUN
fcis-7524	19	3	results	result	NOUN
fcis-7524	19	4	include	include	VERB
fcis-7524	19	5	the	the	DET
fcis-7524	19	6	use	use	NOUN
fcis-7524	19	7	of	of	ADP
fcis-7524	19	8	quantum	quantum	NOUN
fcis-7524	19	9	machine	machine	NOUN
fcis-7524	19	10	learning	learn	VERB
fcis-7524	19	11	for	for	ADP
fcis-7524	19	12	tasks	task	NOUN
fcis-7524	19	13	such	such	ADJ
fcis-7524	19	14	as	as	ADP
fcis-7524	19	15	image	image	NOUN
fcis-7524	19	16	classification	classification	NOUN
fcis-7524	19	17	and	and	CCONJ
fcis-7524	19	18	target	target	NOUN
fcis-7524	19	19	recognition	recognition	NOUN
fcis-7524	19	20	.	.	PUNCT
fcis-7524	20	1	quantum	quantum	PROPN
fcis-7524	20	2	neural	neural	ADJ
fcis-7524	20	3	networks	network	NOUN
fcis-7524	20	4	are	be	AUX
fcis-7524	20	5	one	one	NUM
fcis-7524	20	6	of	of	ADP
fcis-7524	20	7	the	the	DET
fcis-7524	20	8	very	very	ADV
fcis-7524	20	9	important	important	ADJ
fcis-7524	20	10	branches	branch	NOUN
fcis-7524	20	11	.	.	PUNCT
fcis-7524	21	1	in	in	ADP
fcis-7524	21	2	quantum	quantum	ADJ
fcis-7524	21	3	neural	neural	ADJ
fcis-7524	21	4	network	network	NOUN
fcis-7524	21	5	research	research	NOUN
fcis-7524	21	6	,	,	PUNCT
fcis-7524	21	7	quantum	quantum	ADJ
fcis-7524	21	8	variational	variational	ADJ
fcis-7524	21	9	circuits	circuit	NOUN
fcis-7524	21	10	are	be	AUX
fcis-7524	21	11	a	a	DET
fcis-7524	21	12	very	very	ADV
fcis-7524	21	13	important	important	ADJ
fcis-7524	21	14	part	part	NOUN
fcis-7524	21	15	of	of	ADP
fcis-7524	21	16	quantum	quantum	ADJ
fcis-7524	21	17	neural	neural	ADJ
fcis-7524	21	18	networks	network	NOUN
fcis-7524	21	19	.	.	PUNCT
fcis-7524	22	1	francesco	francesco	PROPN
fcis-7524	23	1	[	[	X
fcis-7524	23	2	3	3	NUM
fcis-7524	23	3	]	]	PUNCT
fcis-7524	23	4	et	et	PROPN
fcis-7524	23	5	al	al	PROPN
fcis-7524	23	6	.	.	PROPN
fcis-7524	23	7	proposed	propose	VERB
fcis-7524	23	8	quantum	quantum	ADJ
fcis-7524	23	9	variational	variational	ADJ
fcis-7524	23	10	circuits	circuit	NOUN
fcis-7524	23	11	based	base	VERB
fcis-7524	23	12	on	on	ADP
fcis-7524	23	13	variational	variational	ADJ
fcis-7524	23	14	protocols	protocol	NOUN
fcis-7524	23	15	,	,	PUNCT
fcis-7524	23	16	which	which	PRON
fcis-7524	23	17	have	have	VERB
fcis-7524	23	18	better	well	ADJ
fcis-7524	23	19	adaptability	adaptability	NOUN
fcis-7524	23	20	in	in	ADP
fcis-7524	23	21	quantum	quantum	ADJ
fcis-7524	23	22	neural	neural	ADJ
fcis-7524	23	23	networks	network	NOUN
fcis-7524	23	24	.	.	PUNCT
fcis-7524	24	1	arthur	arthur	PROPN
fcis-7524	25	1	[	[	X
fcis-7524	25	2	4	4	NUM
fcis-7524	25	3	]	]	PUNCT
fcis-7524	25	4	et	et	PROPN
fcis-7524	25	5	al	al	PROPN
fcis-7524	25	6	.	.	PROPN
fcis-7524	25	7	proposed	propose	VERB
fcis-7524	25	8	a	a	DET
fcis-7524	25	9	hybrid	hybrid	ADJ
fcis-7524	25	10	quantum	quantum	ADJ
fcis-7524	25	11	classical	classical	ADJ
fcis-7524	25	12	neural	neural	ADJ
fcis-7524	25	13	network	network	NOUN
fcis-7524	25	14	structure	structure	NOUN
fcis-7524	25	15	in	in	ADP
fcis-7524	25	16	which	which	PRON
fcis-7524	25	17	each	each	DET
fcis-7524	25	18	neuron	neuron	NOUN
fcis-7524	25	19	is	be	AUX
fcis-7524	25	20	a	a	DET
fcis-7524	25	21	variational	variational	ADJ
fcis-7524	25	22	quantum	quantum	NOUN
fcis-7524	25	23	circuit	circuit	NOUN
fcis-7524	25	24	,	,	PUNCT
fcis-7524	25	25	compared	compare	VERB
fcis-7524	25	26	to	to	ADP
fcis-7524	25	27	a	a	DET
fcis-7524	25	28	single	single	ADJ
fcis-7524	25	29	variational	variational	ADJ
fcis-7524	25	30	quantum	quantum	NOUN
fcis-7524	25	31	circuit	circuit	NOUN
fcis-7524	25	32	for	for	ADP
fcis-7524	25	33	significantly	significantly	ADV
fcis-7524	25	34	better	well	ADJ
fcis-7524	25	35	accuracy	accuracy	NOUN
fcis-7524	25	36	in	in	ADP
fcis-7524	25	37	classification	classification	NOUN
fcis-7524	25	38	.	.	PUNCT
fcis-7524	26	1	there	there	PRON
fcis-7524	26	2	are	be	VERB
fcis-7524	26	3	also	also	ADV
fcis-7524	26	4	classical	classical	ADJ
fcis-7524	26	5	learning	learning	NOUN
fcis-7524	26	6	methods	method	NOUN
fcis-7524	26	7	combined	combine	VERB
fcis-7524	26	8	in	in	ADP
fcis-7524	26	9	quantum	quantum	ADJ
fcis-7524	26	10	neural	neural	ADJ
fcis-7524	26	11	networks	network	NOUN
fcis-7524	26	12	to	to	PART
fcis-7524	26	13	improve	improve	VERB
fcis-7524	26	14	efficiency	efficiency	NOUN
fcis-7524	26	15	and	and	CCONJ
fcis-7524	26	16	performance	performance	NOUN
fcis-7524	26	17	.	.	PUNCT
fcis-7524	27	1	for	for	ADP
fcis-7524	27	2	example	example	NOUN
fcis-7524	27	3	,	,	PUNCT
fcis-7524	27	4	kawase	kawase	PROPN
fcis-7524	27	5	[	[	X
fcis-7524	27	6	4	4	NUM
fcis-7524	27	7	]	]	PUNCT
fcis-7524	27	8	et	et	PROPN
fcis-7524	27	9	al	al	PROPN
fcis-7524	27	10	.	.	PROPN
fcis-7524	27	11	proposed	propose	VERB
fcis-7524	27	12	to	to	PART
fcis-7524	27	13	use	use	VERB
fcis-7524	27	14	the	the	DET
fcis-7524	27	15	parameter	parameter	NOUN
fcis-7524	27	16	tsne	tsne	NOUN
fcis-7524	27	17	of	of	ADP
fcis-7524	27	18	quantum	quantum	ADJ
fcis-7524	27	19	neural	neural	ADJ
fcis-7524	27	20	network	network	NOUN
fcis-7524	27	21	to	to	PART
fcis-7524	27	22	reflect	reflect	VERB
fcis-7524	27	23	the	the	DET
fcis-7524	27	24	properties	property	NOUN
fcis-7524	27	25	of	of	ADP
fcis-7524	27	26	high	high	ADJ
fcis-7524	27	27	-	-	PUNCT
fcis-7524	27	28	dimensional	dimensional	ADJ
fcis-7524	27	29	quantum	quantum	ADJ
fcis-7524	27	30	data	datum	NOUN
fcis-7524	27	31	on	on	ADP
fcis-7524	27	32	low	low	ADJ
fcis-7524	27	33	-	-	PUNCT
fcis-7524	27	34	dimensional	dimensional	ADJ
fcis-7524	27	35	data	datum	NOUN
fcis-7524	27	36	to	to	PART
fcis-7524	27	37	improve	improve	VERB
fcis-7524	27	38	the	the	DET
fcis-7524	27	39	efficiency	efficiency	NOUN
fcis-7524	27	40	of	of	ADP
fcis-7524	27	41	neural	neural	ADJ
fcis-7524	27	42	network	network	NOUN
fcis-7524	27	43	in	in	ADP
fcis-7524	27	44	processing	processing	NOUN
fcis-7524	27	45	data	datum	NOUN
fcis-7524	27	46	.	.	PUNCT
fcis-7524	28	1	osakabe	osakabe	PROPN
fcis-7524	29	1	[	[	X
fcis-7524	29	2	5	5	NUM
fcis-7524	29	3	]	]	PUNCT
fcis-7524	29	4	et	et	PROPN
fcis-7524	29	5	al	al	PROPN
fcis-7524	29	6	.	.	PROPN
fcis-7524	29	7	proposed	propose	VERB
fcis-7524	29	8	a	a	DET
fcis-7524	29	9	hebb	hebb	PROPN
fcis-7524	29	10	rule	rule	NOUN
fcis-7524	29	11	-	-	PUNCT
fcis-7524	29	12	based	base	VERB
fcis-7524	29	13	learning	learning	NOUN
fcis-7524	29	14	method	method	NOUN
fcis-7524	29	15	for	for	ADP
fcis-7524	29	16	quantum	quantum	ADJ
fcis-7524	29	17	neural	neural	ADJ
fcis-7524	29	18	network	network	NOUN
fcis-7524	29	19	,	,	PUNCT
fcis-7524	29	20	in	in	ADP
fcis-7524	29	21	which	which	PRON
fcis-7524	29	22	hebb	hebb	NOUN
fcis-7524	29	23	and	and	CCONJ
fcis-7524	29	24	inverse	inverse	NOUN
fcis-7524	29	25	hebb	hebb	NOUN
fcis-7524	29	26	rules	rule	NOUN
fcis-7524	29	27	improve	improve	VERB
fcis-7524	29	28	the	the	DET
fcis-7524	29	29	learning	learning	NOUN
fcis-7524	29	30	performance	performance	NOUN
fcis-7524	29	31	of	of	ADP
fcis-7524	29	32	neural	neural	ADJ
fcis-7524	29	33	network	network	NOUN
fcis-7524	29	34	.	.	PUNCT
fcis-7524	30	1	fuzzy	fuzzy	ADJ
fcis-7524	30	2	theory	theory	NOUN
fcis-7524	30	3	[	[	X
fcis-7524	30	4	6	6	NUM
fcis-7524	30	5	-	-	SYM
fcis-7524	30	6	8	8	NUM
fcis-7524	30	7	]	]	PUNCT
fcis-7524	30	8	is	be	AUX
fcis-7524	30	9	a	a	DET
fcis-7524	30	10	mathematical	mathematical	ADJ
fcis-7524	30	11	theory	theory	NOUN
fcis-7524	30	12	for	for	ADP
fcis-7524	30	13	dealing	deal	VERB
fcis-7524	30	14	with	with	ADP
fcis-7524	30	15	uncertainty	uncertainty	NOUN
fcis-7524	30	16	and	and	CCONJ
fcis-7524	30	17	vagueness	vagueness	NOUN
fcis-7524	30	18	,	,	PUNCT
fcis-7524	30	19	which	which	PRON
fcis-7524	30	20	was	be	AUX
fcis-7524	30	21	proposed	propose	VERB
fcis-7524	30	22	by	by	ADP
fcis-7524	30	23	the	the	DET
fcis-7524	30	24	american	american	ADJ
fcis-7524	30	25	mathematician	mathematician	PROPN
fcis-7524	30	26	lotfi	lotfi	PROPN
fcis-7524	30	27	zadeh	zadeh	PROPN
fcis-7524	30	28	.	.	PUNCT
fcis-7524	31	1	fuzzy	fuzzy	ADJ
fcis-7524	31	2	theory	theory	NOUN
fcis-7524	31	3	can	can	AUX
fcis-7524	31	4	be	be	AUX
fcis-7524	31	5	used	use	VERB
fcis-7524	31	6	to	to	PART
fcis-7524	31	7	describe	describe	VERB
fcis-7524	31	8	concepts	concept	NOUN
fcis-7524	31	9	such	such	ADJ
fcis-7524	31	10	as	as	ADP
fcis-7524	31	11	fuzzy	fuzzy	ADJ
fcis-7524	31	12	,	,	PUNCT
fcis-7524	31	13	fuzzy	fuzzy	ADJ
fcis-7524	31	14	boundaries	boundary	NOUN
fcis-7524	31	15	and	and	CCONJ
fcis-7524	31	16	fuzzy	fuzzy	ADJ
fcis-7524	31	17	rules	rule	NOUN
fcis-7524	31	18	,	,	PUNCT
fcis-7524	31	19	and	and	CCONJ
fcis-7524	31	20	can	can	AUX
fcis-7524	31	21	be	be	AUX
fcis-7524	31	22	applied	apply	VERB
fcis-7524	31	23	in	in	ADP
fcis-7524	31	24	modeling	modeling	NOUN
fcis-7524	31	25	and	and	CCONJ
fcis-7524	31	26	analysis	analysis	NOUN
fcis-7524	31	27	of	of	ADP
fcis-7524	31	28	many	many	ADJ
fcis-7524	31	29	practical	practical	ADJ
fcis-7524	31	30	problems	problem	NOUN
fcis-7524	31	31	.	.	PUNCT
fcis-7524	32	1	meanwhile	meanwhile	ADV
fcis-7524	32	2	,	,	PUNCT
fcis-7524	32	3	with	with	ADP
fcis-7524	32	4	the	the	DET
fcis-7524	32	5	development	development	NOUN
fcis-7524	32	6	of	of	ADP
fcis-7524	32	7	technologies	technology	NOUN
fcis-7524	32	8	such	such	ADJ
fcis-7524	32	9	as	as	ADP
fcis-7524	32	10	neural	neural	ADJ
fcis-7524	32	11	networks	network	NOUN
fcis-7524	32	12	,	,	PUNCT
fcis-7524	32	13	fuzzy	fuzzy	ADJ
fcis-7524	32	14	theory	theory	NOUN
fcis-7524	32	15	has	have	AUX
fcis-7524	32	16	been	be	AUX
fcis-7524	32	17	widely	widely	ADV
fcis-7524	32	18	used	use	VERB
fcis-7524	32	19	.	.	PUNCT
fcis-7524	33	1	for	for	ADP
fcis-7524	33	2	example	example	NOUN
fcis-7524	33	3	,	,	PUNCT
fcis-7524	33	4	in	in	ADP
fcis-7524	33	5	neural	neural	ADJ
fcis-7524	33	6	networks	network	NOUN
fcis-7524	33	7	,	,	PUNCT
fcis-7524	33	8	researchers	researcher	NOUN
fcis-7524	33	9	can	can	AUX
fcis-7524	33	10	use	use	VERB
fcis-7524	33	11	fuzzy	fuzzy	ADJ
fcis-7524	33	12	theory	theory	NOUN
fcis-7524	33	13	to	to	PART
fcis-7524	33	14	fuzzify	fuzzify	VERB
fcis-7524	33	15	the	the	DET
fcis-7524	33	16	output	output	NOUN
fcis-7524	33	17	of	of	ADP
fcis-7524	33	18	neural	neural	ADJ
fcis-7524	33	19	networks	network	NOUN
fcis-7524	33	20	to	to	PART
fcis-7524	33	21	improve	improve	VERB
fcis-7524	33	22	the	the	DET
fcis-7524	33	23	performance	performance	NOUN
fcis-7524	33	24	and	and	CCONJ
fcis-7524	33	25	robustness	robustness	NOUN
fcis-7524	33	26	of	of	ADP
fcis-7524	33	27	neural	neural	ADJ
fcis-7524	33	28	networks.gu	networks.gu	NOUN
fcis-7524	34	1	[	[	X
fcis-7524	34	2	9	9	NUM
fcis-7524	34	3	]	]	PUNCT
fcis-7524	34	4	et	et	PROPN
fcis-7524	34	5	al	al	PROPN
fcis-7524	34	6	.	.	PUNCT
fcis-7524	35	1	we	we	PRON
fcis-7524	35	2	extracted	extract	VERB
fcis-7524	35	3	knowledge	knowledge	NOUN
fcis-7524	35	4	from	from	ADP
fcis-7524	35	5	deep	deep	ADJ
fcis-7524	35	6	neural	neural	ADJ
fcis-7524	35	7	networks	network	NOUN
fcis-7524	35	8	(	(	PUNCT
fcis-7524	35	9	dnns	dnn	NOUN
fcis-7524	35	10	)	)	PUNCT
fcis-7524	35	11	into	into	ADP
fcis-7524	35	12	a	a	DET
fcis-7524	35	13	takagi	takagi	NOUN
fcis-7524	35	14	-	-	PUNCT
fcis-7524	35	15	sugeno	sugeno	NOUN
fcis-7524	35	16	-	-	PUNCT
fcis-7524	35	17	kang	kang	PROPN
fcis-7524	35	18	(	(	PUNCT
fcis-7524	35	19	tsk)-based	tsk)-base	VERB
fcis-7524	35	20	fuzzy	fuzzy	ADJ
fcis-7524	35	21	inference	inference	NOUN
fcis-7524	35	22	system	system	NOUN
fcis-7524	35	23	,	,	PUNCT
fcis-7524	35	24	which	which	PRON
fcis-7524	35	25	is	be	AUX
fcis-7524	35	26	able	able	ADJ
fcis-7524	35	27	to	to	PART
fcis-7524	35	28	express	express	VERB
fcis-7524	35	29	fuzzy	fuzzy	ADJ
fcis-7524	35	30	rules	rule	NOUN
fcis-7524	35	31	based	base	VERB
fcis-7524	35	32	on	on	ADP
fcis-7524	35	33	knowledge	knowledge	NOUN
fcis-7524	35	34	obtained	obtain	VERB
fcis-7524	35	35	from	from	ADP
fcis-7524	35	36	dnns	dnn	NOUN
fcis-7524	35	37	,	,	PUNCT
fcis-7524	35	38	which	which	PRON
fcis-7524	35	39	makes	make	VERB
fcis-7524	35	40	it	it	PRON
fcis-7524	35	41	easier	easy	ADJ
fcis-7524	35	42	to	to	PART
fcis-7524	35	43	explain	explain	VERB
fcis-7524	35	44	specific	specific	ADJ
fcis-7524	35	45	decisions	decision	NOUN
fcis-7524	35	46	and	and	CCONJ
fcis-7524	35	47	has	have	VERB
fcis-7524	35	48	better	well	ADJ
fcis-7524	35	49	generalization	generalization	NOUN
fcis-7524	35	50	capabilities	capability	NOUN
fcis-7524	35	51	.	.	PUNCT
fcis-7524	36	1	the	the	DET
fcis-7524	36	2	above	above	ADV
fcis-7524	36	3	-	-	PUNCT
fcis-7524	36	4	mentioned	mention	VERB
fcis-7524	36	5	quantum	quantum	NOUN
fcis-7524	36	6	neural	neural	ADJ
fcis-7524	36	7	networks	network	NOUN
fcis-7524	36	8	[	[	X
fcis-7524	36	9	10	10	NUM
fcis-7524	36	10	-	-	SYM
fcis-7524	36	11	12	12	NUM
fcis-7524	36	12	]	]	PUNCT
fcis-7524	36	13	are	be	AUX
fcis-7524	36	14	the	the	DET
fcis-7524	36	15	product	product	NOUN
fcis-7524	36	16	of	of	ADP
fcis-7524	36	17	the	the	DET
fcis-7524	36	18	fusion	fusion	NOUN
fcis-7524	36	19	of	of	ADP
fcis-7524	36	20	quantum	quantum	NOUN
fcis-7524	36	21	computing	computing	NOUN
fcis-7524	36	22	and	and	CCONJ
fcis-7524	36	23	artificial	artificial	ADJ
fcis-7524	36	24	neural	neural	ADJ
fcis-7524	36	25	networks	network	NOUN
fcis-7524	36	26	,	,	PUNCT
fcis-7524	36	27	aiming	aim	VERB
fcis-7524	36	28	to	to	PART
fcis-7524	36	29	improve	improve	VERB
fcis-7524	36	30	the	the	DET
fcis-7524	36	31	efficiency	efficiency	NOUN
fcis-7524	36	32	of	of	ADP
fcis-7524	36	33	neural	neural	ADJ
fcis-7524	36	34	networks	network	NOUN
fcis-7524	36	35	in	in	ADP
fcis-7524	36	36	processing	process	VERB
fcis-7524	36	37	big	big	ADJ
fcis-7524	36	38	data	datum	NOUN
fcis-7524	36	39	by	by	ADP
fcis-7524	36	40	introducing	introduce	VERB
fcis-7524	36	41	quantum	quantum	NOUN
fcis-7524	36	42	computing	computing	NOUN
fcis-7524	36	43	into	into	ADP
fcis-7524	36	44	traditional	traditional	ADJ
fcis-7524	36	45	neural	neural	ADJ
fcis-7524	36	46	networks	network	NOUN
fcis-7524	36	47	.	.	PUNCT
fcis-7524	37	1	there	there	PRON
fcis-7524	37	2	are	be	VERB
fcis-7524	37	3	many	many	ADJ
fcis-7524	37	4	quantum	quantum	ADJ
fcis-7524	37	5	neural	neural	ADJ
fcis-7524	37	6	network	network	NOUN
fcis-7524	37	7	models	model	NOUN
fcis-7524	37	8	currently	currently	ADV
fcis-7524	37	9	available	available	ADJ
fcis-7524	37	10	,	,	PUNCT
fcis-7524	37	11	and	and	CCONJ
fcis-7524	37	12	they	they	PRON
fcis-7524	37	13	are	be	AUX
fcis-7524	37	14	still	still	ADV
fcis-7524	37	15	under	under	ADP
fcis-7524	37	16	continuous	continuous	ADJ
fcis-7524	37	17	development	development	NOUN
fcis-7524	37	18	and	and	CCONJ
fcis-7524	37	19	improvement	improvement	NOUN
fcis-7524	37	20	.	.	PUNCT
fcis-7524	38	1	however	however	ADV
fcis-7524	38	2	,	,	PUNCT
fcis-7524	38	3	quantum	quantum	ADJ
fcis-7524	38	4	neural	neural	ADJ
fcis-7524	38	5	networks	network	NOUN
fcis-7524	38	6	do	do	AUX
fcis-7524	38	7	not	not	PART
fcis-7524	38	8	deal	deal	VERB
fcis-7524	38	9	well	well	ADV
fcis-7524	38	10	with	with	ADP
fcis-7524	38	11	the	the	DET
fcis-7524	38	12	problem	problem	NOUN
fcis-7524	38	13	of	of	ADP
fcis-7524	38	14	uncertainty	uncertainty	NOUN
fcis-7524	38	15	in	in	ADP
fcis-7524	38	16	big	big	ADJ
fcis-7524	38	17	data	datum	NOUN
fcis-7524	38	18	,	,	PUNCT
fcis-7524	38	19	resulting	result	VERB
fcis-7524	38	20	in	in	ADP
fcis-7524	38	21	low	low	ADJ
fcis-7524	38	22	accuracy	accuracy	NOUN
fcis-7524	38	23	.	.	PUNCT
fcis-7524	39	1	the	the	DET
fcis-7524	39	2	fuzzy	fuzzy	ADJ
fcis-7524	39	3	neural	neural	ADJ
fcis-7524	39	4	network	network	NOUN
fcis-7524	39	5	formed	form	VERB
fcis-7524	39	6	by	by	ADP
fcis-7524	39	7	introducing	introduce	VERB
fcis-7524	39	8	fuzzy	fuzzy	ADJ
fcis-7524	39	9	theory	theory	NOUN
fcis-7524	39	10	into	into	ADP
fcis-7524	39	11	neural	neural	ADJ
fcis-7524	39	12	network	network	NOUN
fcis-7524	39	13	learning	learning	NOUN
fcis-7524	39	14	has	have	VERB
fcis-7524	39	15	a	a	DET
fcis-7524	39	16	factual	factual	ADJ
fcis-7524	39	17	description	description	NOUN
fcis-7524	39	18	of	of	ADP
fcis-7524	39	19	the	the	DET
fcis-7524	39	20	uncertainty	uncertainty	NOUN
fcis-7524	39	21	of	of	ADP
fcis-7524	39	22	big	big	ADJ
fcis-7524	39	23	data	datum	NOUN
fcis-7524	39	24	,	,	PUNCT
fcis-7524	39	25	and	and	CCONJ
fcis-7524	39	26	the	the	DET
fcis-7524	39	27	above	above	ADJ
fcis-7524	39	28	research	research	NOUN
fcis-7524	39	29	results	result	NOUN
fcis-7524	39	30	have	have	VERB
fcis-7524	39	31	higher	high	ADJ
fcis-7524	39	32	accuracy	accuracy	NOUN
fcis-7524	39	33	compared	compare	VERB
fcis-7524	39	34	with	with	ADP
fcis-7524	39	35	traditional	traditional	ADJ
fcis-7524	39	36	neural	neural	ADJ
fcis-7524	39	37	networks	network	NOUN
fcis-7524	39	38	,	,	PUNCT
fcis-7524	39	39	but	but	CCONJ
fcis-7524	39	40	due	due	ADP
fcis-7524	39	41	to	to	ADP
fcis-7524	39	42	the	the	DET
fcis-7524	39	43	bottleneck	bottleneck	NOUN
fcis-7524	39	44	of	of	ADP
fcis-7524	39	45	classical	classical	ADJ
fcis-7524	39	46	computer	computer	NOUN
fcis-7524	39	47	's	's	PART
fcis-7524	39	48	computing	computing	NOUN
fcis-7524	39	49	power	power	NOUN
fcis-7524	39	50	,	,	PUNCT
fcis-7524	39	51	fuzzy	fuzzy	ADJ
fcis-7524	39	52	neural	neural	ADJ
fcis-7524	39	53	networks	network	NOUN
fcis-7524	39	54	are	be	AUX
fcis-7524	39	55	inevitably	inevitably	ADV
fcis-7524	39	56	limited	limit	VERB
fcis-7524	39	57	in	in	ADP
fcis-7524	39	58	the	the	DET
fcis-7524	39	59	face	face	NOUN
fcis-7524	39	60	of	of	ADP
fcis-7524	39	61	big	big	ADJ
fcis-7524	39	62	data	datum	NOUN
fcis-7524	39	63	.	.	PUNCT
fcis-7524	40	1	100	100	NUM
fcis-7524	40	2	how	how	SCONJ
fcis-7524	40	3	to	to	PART
fcis-7524	40	4	combine	combine	VERB
fcis-7524	40	5	fuzzy	fuzzy	ADJ
fcis-7524	40	6	theory	theory	NOUN
fcis-7524	40	7	and	and	CCONJ
fcis-7524	40	8	quantum	quantum	ADJ
fcis-7524	40	9	neural	neural	ADJ
fcis-7524	40	10	network	network	NOUN
fcis-7524	40	11	,	,	PUNCT
fcis-7524	40	12	and	and	CCONJ
fcis-7524	40	13	take	take	VERB
fcis-7524	40	14	advantage	advantage	NOUN
fcis-7524	40	15	of	of	ADP
fcis-7524	40	16	the	the	DET
fcis-7524	40	17	properties	property	NOUN
fcis-7524	40	18	of	of	ADP
fcis-7524	40	19	quantum	quantum	NOUN
fcis-7524	40	20	parallel	parallel	NOUN
fcis-7524	40	21	computing	computing	NOUN
fcis-7524	40	22	and	and	CCONJ
fcis-7524	40	23	exponential	exponential	ADJ
fcis-7524	40	24	storage	storage	NOUN
fcis-7524	40	25	capacity	capacity	NOUN
fcis-7524	40	26	and	and	CCONJ
fcis-7524	40	27	the	the	DET
fcis-7524	40	28	natural	natural	ADJ
fcis-7524	40	29	advantages	advantage	NOUN
fcis-7524	40	30	of	of	ADP
fcis-7524	40	31	fuzzy	fuzzy	ADJ
fcis-7524	40	32	theory	theory	NOUN
fcis-7524	40	33	in	in	ADP
fcis-7524	40	34	dealing	deal	VERB
fcis-7524	40	35	with	with	ADP
fcis-7524	40	36	the	the	DET
fcis-7524	40	37	uncertainty	uncertainty	NOUN
fcis-7524	40	38	of	of	ADP
fcis-7524	40	39	big	big	ADJ
fcis-7524	40	40	data	datum	NOUN
fcis-7524	40	41	is	be	AUX
fcis-7524	40	42	one	one	NUM
fcis-7524	40	43	of	of	ADP
fcis-7524	40	44	the	the	DET
fcis-7524	40	45	current	current	ADJ
fcis-7524	40	46	researches	research	NOUN
fcis-7524	40	47	focuses	focus	VERB
fcis-7524	40	48	of	of	ADP
fcis-7524	40	49	quantum	quantum	ADJ
fcis-7524	40	50	neural	neural	ADJ
fcis-7524	40	51	network	network	NOUN
fcis-7524	40	52	.	.	PUNCT
fcis-7524	41	1	2	2	X
fcis-7524	41	2	.	.	X
fcis-7524	41	3	the	the	DET
fcis-7524	41	4	framework	framework	NOUN
fcis-7524	41	5	of	of	ADP
fcis-7524	41	6	quantum	quantum	ADJ
fcis-7524	41	7	fuzzy	fuzzy	ADJ
fcis-7524	41	8	neural	neural	ADJ
fcis-7524	41	9	network	network	NOUN
fcis-7524	41	10	model	model	NOUN
fcis-7524	41	11	based	base	VERB
fcis-7524	41	12	on	on	ADP
fcis-7524	41	13	fuzzy	fuzzy	ADJ
fcis-7524	41	14	number	number	NOUN
fcis-7524	41	15	the	the	DET
fcis-7524	41	16	quantum	quantum	ADJ
fcis-7524	41	17	fuzzy	fuzzy	ADJ
fcis-7524	41	18	neural	neural	ADJ
fcis-7524	41	19	network	network	NOUN
fcis-7524	41	20	model	model	NOUN
fcis-7524	41	21	based	base	VERB
fcis-7524	41	22	on	on	ADP
fcis-7524	41	23	fuzzy	fuzzy	ADJ
fcis-7524	41	24	numbers	number	NOUN
fcis-7524	41	25	is	be	AUX
fcis-7524	41	26	an	an	DET
fcis-7524	41	27	improved	improved	ADJ
fcis-7524	41	28	model	model	NOUN
fcis-7524	41	29	combining	combine	VERB
fcis-7524	41	30	fuzzy	fuzzy	ADJ
fcis-7524	41	31	theory	theory	NOUN
fcis-7524	41	32	and	and	CCONJ
fcis-7524	41	33	quantum	quantum	ADJ
fcis-7524	41	34	neural	neural	ADJ
fcis-7524	41	35	network	network	NOUN
fcis-7524	41	36	,	,	PUNCT
fcis-7524	41	37	which	which	PRON
fcis-7524	41	38	combines	combine	VERB
fcis-7524	41	39	fuzzy	fuzzy	ADJ
fcis-7524	41	40	theory	theory	NOUN
fcis-7524	41	41	to	to	PART
fcis-7524	41	42	better	well	ADV
fcis-7524	41	43	describe	describe	VERB
fcis-7524	41	44	uncertainty	uncertainty	NOUN
fcis-7524	41	45	in	in	ADP
fcis-7524	41	46	real	real	ADJ
fcis-7524	41	47	data	datum	NOUN
fcis-7524	41	48	and	and	CCONJ
fcis-7524	41	49	the	the	DET
fcis-7524	41	50	advantages	advantage	NOUN
fcis-7524	41	51	of	of	ADP
fcis-7524	41	52	quantum	quantum	NOUN
fcis-7524	41	53	computing	computing	NOUN
fcis-7524	41	54	with	with	ADP
fcis-7524	41	55	high	high	ADJ
fcis-7524	41	56	parallelism	parallelism	NOUN
fcis-7524	41	57	and	and	CCONJ
fcis-7524	41	58	exponential	exponential	ADJ
fcis-7524	41	59	storage	storage	NOUN
fcis-7524	41	60	capacity	capacity	NOUN
fcis-7524	41	61	.	.	PUNCT
fcis-7524	42	1	the	the	DET
fcis-7524	42	2	quantum	quantum	ADJ
fcis-7524	42	3	fuzzy	fuzzy	ADJ
fcis-7524	42	4	neural	neural	ADJ
fcis-7524	42	5	network	network	NOUN
fcis-7524	42	6	model	model	NOUN
fcis-7524	42	7	based	base	VERB
fcis-7524	42	8	on	on	ADP
fcis-7524	42	9	fuzzy	fuzzy	ADJ
fcis-7524	42	10	numbers	number	NOUN
fcis-7524	42	11	is	be	AUX
fcis-7524	42	12	mainly	mainly	ADV
fcis-7524	42	13	divided	divide	VERB
fcis-7524	42	14	into	into	ADP
fcis-7524	42	15	data	data	NOUN
fcis-7524	42	16	preprocessing	preprocessing	NOUN
fcis-7524	42	17	unit	unit	NOUN
fcis-7524	42	18	,	,	PUNCT
fcis-7524	42	19	fuzzy	fuzzy	ADJ
fcis-7524	42	20	unit	unit	NOUN
fcis-7524	42	21	and	and	CCONJ
fcis-7524	42	22	quantum	quantum	ADJ
fcis-7524	42	23	fuzzy	fuzzy	ADJ
fcis-7524	42	24	neural	neural	ADJ
fcis-7524	42	25	network	network	NOUN
fcis-7524	42	26	unit	unit	NOUN
fcis-7524	42	27	.	.	PUNCT
fcis-7524	43	1	the	the	DET
fcis-7524	43	2	model	model	NOUN
fcis-7524	43	3	needs	need	VERB
fcis-7524	43	4	to	to	PART
fcis-7524	43	5	be	be	AUX
fcis-7524	43	6	trained	train	VERB
fcis-7524	43	7	before	before	SCONJ
fcis-7524	43	8	the	the	DET
fcis-7524	43	9	output	output	NOUN
fcis-7524	43	10	model	model	NOUN
fcis-7524	43	11	can	can	AUX
fcis-7524	43	12	enter	enter	VERB
fcis-7524	43	13	the	the	DET
fcis-7524	43	14	use	use	NOUN
fcis-7524	43	15	process	process	NOUN
fcis-7524	43	16	,	,	PUNCT
fcis-7524	43	17	which	which	PRON
fcis-7524	43	18	can	can	AUX
fcis-7524	43	19	be	be	AUX
fcis-7524	43	20	divided	divide	VERB
fcis-7524	43	21	into	into	ADP
fcis-7524	43	22	training	training	NOUN
fcis-7524	43	23	process	process	NOUN
fcis-7524	43	24	and	and	CCONJ
fcis-7524	43	25	use	use	NOUN
fcis-7524	43	26	process	process	NOUN
fcis-7524	43	27	according	accord	VERB
fcis-7524	43	28	to	to	ADP
fcis-7524	43	29	different	different	ADJ
fcis-7524	43	30	processes	process	NOUN
fcis-7524	43	31	.	.	PUNCT
fcis-7524	44	1	the	the	DET
fcis-7524	44	2	quantum	quantum	ADJ
fcis-7524	44	3	fuzzy	fuzzy	ADJ
fcis-7524	44	4	neural	neural	ADJ
fcis-7524	44	5	network	network	NOUN
fcis-7524	44	6	model	model	NOUN
fcis-7524	44	7	based	base	VERB
fcis-7524	44	8	on	on	ADP
fcis-7524	44	9	fuzzy	fuzzy	ADJ
fcis-7524	44	10	number	number	NOUN
fcis-7524	44	11	in	in	ADP
fcis-7524	44	12	the	the	DET
fcis-7524	44	13	training	training	NOUN
fcis-7524	44	14	process	process	NOUN
fcis-7524	44	15	is	be	AUX
fcis-7524	44	16	shown	show	VERB
fcis-7524	44	17	in	in	ADP
fcis-7524	44	18	figure	figure	NOUN
fcis-7524	44	19	1	1	NUM
fcis-7524	44	20	.	.	PUNCT
fcis-7524	44	21	training	training	NOUN
fcis-7524	44	22	process	process	NOUN
fcis-7524	44	23	data	datum	NOUN
fcis-7524	44	24	pre	pre	ADJ
fcis-7524	44	25	-	-	ADJ
fcis-7524	44	26	processing	processing	ADJ
fcis-7524	44	27	unit	unit	NOUN
fcis-7524	44	28	data	datum	NOUN
fcis-7524	44	29	set	set	VERB
fcis-7524	44	30	x	x	PUNCT
fcis-7524	44	31	for	for	ADP
fcis-7524	44	32	dimensionality	dimensionality	NOUN
fcis-7524	44	33	reduction	reduction	NOUN
fcis-7524	44	34	generation	generation	NOUN
fcis-7524	44	35	generating	generate	VERB
fcis-7524	44	36	fuzzy	fuzzy	ADJ
fcis-7524	44	37	affiliation	affiliation	NOUN
fcis-7524	44	38	using	use	VERB
fcis-7524	44	39	fuzzy	fuzzy	ADJ
fcis-7524	44	40	functions	function	NOUN
fcis-7524	44	41	generate	generate	VERB
fcis-7524	44	42	fuzzy	fuzzy	ADJ
fcis-7524	44	43	independent	independent	ADJ
fcis-7524	44	44	variables	variable	NOUN
fcis-7524	44	45	(	(	PUNCT
fcis-7524	44	46	x	x	X
fcis-7524	44	47	)	)	PUNCT
fcis-7524	44	48			NOUN
fcis-7524	44	49	x	x	PUNCT
fcis-7524	44	50	x	x	X
fcis-7524	44	51	*	*	PUNCT
fcis-7524	44	52	(	(	PUNCT
fcis-7524	44	53	x	x	X
fcis-7524	44	54	)	)	PUNCT
fcis-7524	44	55			NOUN
fcis-7524	44	56	=	=	NOUN
fcis-7524	44	57	x	x	SYM
fcis-7524	44	58	quantum	quantum	ADJ
fcis-7524	44	59	fuzzy	fuzzy	ADJ
fcis-7524	44	60	neural	neural	ADJ
fcis-7524	44	61	network	network	NOUN
fcis-7524	44	62	unit	unit	NOUN
fcis-7524	44	63	the	the	DET
fcis-7524	44	64	amplitude	amplitude	NOUN
fcis-7524	44	65	coding	coding	NOUN
fcis-7524	44	66	of	of	ADP
fcis-7524	44	67	the	the	DET
fcis-7524	44	68	fuzzy	fuzzy	ADJ
fcis-7524	44	69	independent	independent	ADJ
fcis-7524	44	70	variable	variable	NOUN
fcis-7524	44	71	is	be	AUX
fcis-7524	44	72	transformed	transform	VERB
fcis-7524	44	73	intox	intox	ADJ
fcis-7524	44	74			NOUN
fcis-7524	44	75	enters	enter	VERB
fcis-7524	44	76	the	the	DET
fcis-7524	44	77	positive	positive	ADJ
fcis-7524	44	78	conduction	conduction	NOUN
fcis-7524	44	79	layer	layer	NOUN
fcis-7524	44	80	for	for	ADP
fcis-7524	44	81	conversion	conversion	NOUN
fcis-7524	44	82	to	to	ADP
fcis-7524	44	83	tuning	tune	VERB
fcis-7524	44	84	parameters	parameter	NOUN
fcis-7524	44	85	at	at	ADP
fcis-7524	44	86	the	the	DET
fcis-7524	44	87	quantum	quantum	PROPN
fcis-7524	44	88	back	back	NOUN
fcis-7524	44	89	propagation	propagation	NOUN
fcis-7524	44	90	layer	layer	NOUN
fcis-7524	44	91	based	base	VERB
fcis-7524	44	92	on	on	ADP
fcis-7524	44	93	the	the	DET
fcis-7524	44	94	label	label	NOUN
fcis-7524	44	95	and	and	CCONJ
fcis-7524	44	96	output	output	NOUN
fcis-7524	44	97	values	value	NOUN
fcis-7524	44	98	of	of	ADP
fcis-7524	44	99	the	the	DET
fcis-7524	44	100	dataset	dataset	NOUN
fcis-7524	44	101	(	(	PUNCT
fcis-7524	44	102	x	x	X
fcis-7524	44	103	)	)	PUNCT
fcis-7524	44	104			NOUN
fcis-7524	44	105	(	(	PUNCT
fcis-7524	44	106	x	x	X
fcis-7524	44	107	)	)	PUNCT
fcis-7524	44	108			NOUN
fcis-7524	44	109	(	(	PUNCT
fcis-7524	44	110	x	x	X
fcis-7524	44	111	)	)	PUNCT
fcis-7524	44	112	u	u	NOUN
fcis-7524	44	113	(	(	PUNCT
fcis-7524	44	114	)	)	PUNCT
fcis-7524	44	115			NOUN
fcis-7524	44	116			NOUN
fcis-7524	44	117	output	output	NOUN
fcis-7524	44	118	values	value	NOUN
fcis-7524	44	119	obtained	obtain	VERB
fcis-7524	44	120	from	from	ADP
fcis-7524	44	121	quantum	quantum	PROPN
fcis-7524	44	122	measurementso	measurementso	PROPN
fcis-7524	44	123	(	(	PUNCT
fcis-7524	44	124	x	x	NOUN
fcis-7524	44	125	,	,	PUNCT
fcis-7524	44	126	)	)	PUNCT
fcis-7524	44	127			PROPN
fcis-7524	44	128			PROPN
fcis-7524	44	129	fuzzy	fuzzy	PROPN
fcis-7524	44	130	unit	unit	NOUN
fcis-7524	44	131	figure	figure	NOUN
fcis-7524	44	132	1	1	NUM
fcis-7524	44	133	.	.	PUNCT
fcis-7524	44	134	framework	framework	NOUN
fcis-7524	44	135	of	of	ADP
fcis-7524	44	136	quantum	quantum	ADJ
fcis-7524	44	137	fuzzy	fuzzy	ADJ
fcis-7524	44	138	neural	neural	ADJ
fcis-7524	44	139	network	network	NOUN
fcis-7524	44	140	model	model	NOUN
fcis-7524	44	141	based	base	VERB
fcis-7524	44	142	on	on	ADP
fcis-7524	44	143	fuzzy	fuzzy	ADJ
fcis-7524	44	144	number	number	NOUN
fcis-7524	44	145	in	in	ADP
fcis-7524	44	146	the	the	DET
fcis-7524	44	147	training	training	NOUN
fcis-7524	44	148	process	process	NOUN
fcis-7524	44	149	in	in	ADP
fcis-7524	44	150	the	the	DET
fcis-7524	44	151	training	training	NOUN
fcis-7524	44	152	process	process	NOUN
fcis-7524	44	153	,	,	PUNCT
fcis-7524	44	154	the	the	DET
fcis-7524	44	155	data	datum	NOUN
fcis-7524	44	156	pre	pre	ADJ
fcis-7524	44	157	-	-	ADJ
fcis-7524	44	158	processing	processing	ADJ
fcis-7524	44	159	unit	unit	NOUN
fcis-7524	44	160	extracts	extract	VERB
fcis-7524	44	161	features	feature	NOUN
fcis-7524	44	162	from	from	ADP
fcis-7524	44	163	the	the	DET
fcis-7524	44	164	huge	huge	ADJ
fcis-7524	44	165	data	datum	NOUN
fcis-7524	44	166	,	,	PUNCT
fcis-7524	44	167	retains	retain	VERB
fcis-7524	44	168	the	the	DET
fcis-7524	44	169	valuable	valuable	ADJ
fcis-7524	44	170	parameters	parameter	NOUN
fcis-7524	44	171	,	,	PUNCT
fcis-7524	44	172	reduces	reduce	VERB
fcis-7524	44	173	the	the	DET
fcis-7524	44	174	model	model	NOUN
fcis-7524	44	175	computation	computation	NOUN
fcis-7524	44	176	and	and	CCONJ
fcis-7524	44	177	improves	improve	VERB
fcis-7524	44	178	the	the	DET
fcis-7524	44	179	computing	computing	NOUN
fcis-7524	44	180	efficiency	efficiency	NOUN
fcis-7524	44	181	.	.	PUNCT
fcis-7524	45	1	in	in	ADP
fcis-7524	45	2	the	the	DET
fcis-7524	45	3	fuzzy	fuzzy	ADJ
fcis-7524	45	4	unit	unit	NOUN
fcis-7524	45	5	,	,	PUNCT
fcis-7524	45	6	the	the	DET
fcis-7524	45	7	gaussian	gaussian	ADJ
fcis-7524	45	8	fuzzy	fuzzy	ADJ
fcis-7524	45	9	number	number	NOUN
fcis-7524	45	10	is	be	AUX
fcis-7524	45	11	used	use	VERB
fcis-7524	45	12	to	to	PART
fcis-7524	45	13	calculate	calculate	VERB
fcis-7524	45	14	the	the	DET
fcis-7524	45	15	fuzzy	fuzzy	ADJ
fcis-7524	45	16	affiliation	affiliation	NOUN
fcis-7524	45	17	of	of	ADP
fcis-7524	45	18	the	the	DET
fcis-7524	45	19	data	datum	NOUN
fcis-7524	45	20	and	and	CCONJ
fcis-7524	45	21	combine	combine	VERB
fcis-7524	45	22	with	with	ADP
fcis-7524	45	23	the	the	DET
fcis-7524	45	24	data	datum	NOUN
fcis-7524	45	25	to	to	PART
fcis-7524	45	26	generate	generate	VERB
fcis-7524	45	27	fuzzy	fuzzy	ADJ
fcis-7524	45	28	independent	independent	ADJ
fcis-7524	45	29	variables	variable	NOUN
fcis-7524	45	30	.	.	PUNCT
fcis-7524	46	1	in	in	ADP
fcis-7524	46	2	the	the	DET
fcis-7524	46	3	quantum	quantum	ADJ
fcis-7524	46	4	fuzzy	fuzzy	ADJ
fcis-7524	46	5	neural	neural	ADJ
fcis-7524	46	6	network	network	NOUN
fcis-7524	46	7	unit	unit	NOUN
fcis-7524	46	8	,	,	PUNCT
fcis-7524	46	9	it	it	PRON
fcis-7524	46	10	is	be	AUX
fcis-7524	46	11	further	far	ADV
fcis-7524	46	12	divided	divide	VERB
fcis-7524	46	13	into	into	ADP
fcis-7524	46	14	quantum	quantum	ADJ
fcis-7524	46	15	amplitude	amplitude	NOUN
fcis-7524	46	16	encoding	encoding	NOUN
fcis-7524	46	17	layer	layer	NOUN
fcis-7524	46	18	,	,	PUNCT
fcis-7524	46	19	quantum	quantum	NOUN
fcis-7524	46	20	forward	forward	ADJ
fcis-7524	46	21	propagation	propagation	NOUN
fcis-7524	46	22	layer	layer	NOUN
fcis-7524	46	23	,	,	PUNCT
fcis-7524	46	24	quantum	quantum	NOUN
fcis-7524	46	25	measurement	measurement	NOUN
fcis-7524	46	26	layer	layer	NOUN
fcis-7524	46	27	and	and	CCONJ
fcis-7524	46	28	quantum	quantum	NOUN
fcis-7524	46	29	back	back	NOUN
fcis-7524	46	30	propagation	propagation	NOUN
fcis-7524	46	31	layer	layer	NOUN
fcis-7524	46	32	.	.	PUNCT
fcis-7524	47	1	the	the	DET
fcis-7524	47	2	quantum	quantum	ADJ
fcis-7524	47	3	amplitude	amplitude	NOUN
fcis-7524	47	4	encoding	encoding	NOUN
fcis-7524	47	5	layer	layer	NOUN
fcis-7524	47	6	encodes	encode	VERB
fcis-7524	47	7	the	the	DET
fcis-7524	47	8	quantum	quantum	ADJ
fcis-7524	47	9	states	state	NOUN
fcis-7524	47	10	of	of	ADP
fcis-7524	47	11	the	the	DET
fcis-7524	47	12	input	input	NOUN
fcis-7524	47	13	fuzzy	fuzzy	ADJ
fcis-7524	47	14	independent	independent	ADJ
fcis-7524	47	15	variables	variable	NOUN
fcis-7524	47	16	and	and	CCONJ
fcis-7524	47	17	transfers	transfer	VERB
fcis-7524	47	18	the	the	DET
fcis-7524	47	19	information	information	NOUN
fcis-7524	47	20	to	to	ADP
fcis-7524	47	21	the	the	DET
fcis-7524	47	22	quantum	quantum	ADJ
fcis-7524	47	23	states	state	NOUN
fcis-7524	47	24	;	;	PUNCT
fcis-7524	47	25	the	the	DET
fcis-7524	47	26	quantum	quantum	ADJ
fcis-7524	47	27	forward	forward	ADJ
fcis-7524	47	28	propagation	propagation	NOUN
fcis-7524	47	29	layer	layer	NOUN
fcis-7524	47	30	puts	put	VERB
fcis-7524	47	31	the	the	DET
fcis-7524	47	32	quantum	quantum	ADJ
fcis-7524	47	33	states	state	NOUN
fcis-7524	47	34	into	into	ADP
fcis-7524	47	35	linear	linear	NOUN
fcis-7524	47	36	and	and	CCONJ
fcis-7524	47	37	nonlinear	nonlinear	ADJ
fcis-7524	47	38	you	you	PRON
fcis-7524	47	39	matrix	matrix	VERB
fcis-7524	47	40	changes	change	NOUN
fcis-7524	47	41	simulating	simulate	VERB
fcis-7524	47	42	the	the	DET
fcis-7524	47	43	propagation	propagation	NOUN
fcis-7524	47	44	process	process	NOUN
fcis-7524	47	45	of	of	ADP
fcis-7524	47	46	traditional	traditional	ADJ
fcis-7524	47	47	neural	neural	ADJ
fcis-7524	47	48	networks	network	NOUN
fcis-7524	47	49	;	;	PUNCT
fcis-7524	47	50	the	the	DET
fcis-7524	47	51	quantum	quantum	ADJ
fcis-7524	47	52	measurement	measurement	NOUN
fcis-7524	47	53	layer	layer	NOUN
fcis-7524	47	54	measures	measure	VERB
fcis-7524	47	55	the	the	DET
fcis-7524	47	56	quantum	quantum	ADJ
fcis-7524	47	57	states	state	NOUN
fcis-7524	47	58	and	and	CCONJ
fcis-7524	47	59	uses	use	VERB
fcis-7524	47	60	them	they	PRON
fcis-7524	47	61	as	as	ADP
fcis-7524	47	62	output	output	NOUN
fcis-7524	47	63	values	value	NOUN
fcis-7524	47	64	;	;	PUNCT
fcis-7524	47	65	in	in	ADP
fcis-7524	47	66	the	the	DET
fcis-7524	47	67	quantum	quantum	PROPN
fcis-7524	47	68	back	back	NOUN
fcis-7524	47	69	propagation	propagation	NOUN
fcis-7524	47	70	layer	layer	NOUN
fcis-7524	47	71	the	the	DET
fcis-7524	47	72	gradient	gradient	NOUN
fcis-7524	47	73	is	be	AUX
fcis-7524	47	74	calculated	calculate	VERB
fcis-7524	47	75	based	base	VERB
fcis-7524	47	76	on	on	ADP
fcis-7524	47	77	the	the	DET
fcis-7524	47	78	labeled	label	VERB
fcis-7524	47	79	and	and	CCONJ
fcis-7524	47	80	output	output	NOUN
fcis-7524	47	81	values	value	NOUN
fcis-7524	47	82	to	to	PART
fcis-7524	47	83	make	make	VERB
fcis-7524	47	84	the	the	DET
fcis-7524	47	85	parameters	parameter	NOUN
fcis-7524	47	86	of	of	ADP
fcis-7524	47	87	the	the	DET
fcis-7524	47	88	forward	forward	ADJ
fcis-7524	47	89	propagation	propagation	NOUN
fcis-7524	47	90	layer	layer	NOUN
fcis-7524	47	91	adjustment	adjustment	NOUN
fcis-7524	47	92	.	.	PUNCT
fcis-7524	48	1	in	in	ADP
fcis-7524	48	2	use	use	NOUN
fcis-7524	48	3	,	,	PUNCT
fcis-7524	48	4	there	there	PRON
fcis-7524	48	5	is	be	VERB
fcis-7524	48	6	no	no	DET
fcis-7524	48	7	quantum	quantum	ADJ
fcis-7524	48	8	backpropagation	backpropagation	NOUN
fcis-7524	48	9	layer	layer	NOUN
fcis-7524	48	10	.	.	PUNCT
fcis-7524	49	1	3	3	X
fcis-7524	49	2	.	.	X
fcis-7524	49	3	quantum	quantum	ADJ
fcis-7524	49	4	fuzzy	fuzzy	ADJ
fcis-7524	49	5	neural	neural	ADJ
fcis-7524	49	6	network	network	NOUN
fcis-7524	49	7	model	model	NOUN
fcis-7524	49	8	based	base	VERB
fcis-7524	49	9	on	on	ADP
fcis-7524	49	10	fuzzy	fuzzy	ADJ
fcis-7524	49	11	number	number	NOUN
fcis-7524	49	12	3.1	3.1	NUM
fcis-7524	49	13	.	.	PUNCT
fcis-7524	50	1	data	datum	NOUN
fcis-7524	50	2	pre	pre	ADJ
fcis-7524	50	3	-	-	ADJ
fcis-7524	50	4	processing	processing	ADJ
fcis-7524	50	5	unit	unit	NOUN
fcis-7524	50	6	due	due	ADP
fcis-7524	50	7	to	to	ADP
fcis-7524	50	8	the	the	DET
fcis-7524	50	9	increasing	increase	VERB
fcis-7524	50	10	size	size	NOUN
fcis-7524	50	11	of	of	ADP
fcis-7524	50	12	the	the	DET
fcis-7524	50	13	input	input	NOUN
fcis-7524	50	14	data	datum	NOUN
fcis-7524	50	15	and	and	CCONJ
fcis-7524	50	16	the	the	DET
fcis-7524	50	17	limitations	limitation	NOUN
fcis-7524	50	18	of	of	ADP
fcis-7524	50	19	the	the	DET
fcis-7524	50	20	quantum	quantum	ADJ
fcis-7524	50	21	neural	neural	ADJ
fcis-7524	50	22	network	network	NOUN
fcis-7524	50	23	circuits	circuit	NOUN
fcis-7524	50	24	,	,	PUNCT
fcis-7524	50	25	preprocessing	preprocessing	NOUN
fcis-7524	50	26	of	of	ADP
fcis-7524	50	27	the	the	DET
fcis-7524	50	28	data	data	NOUN
fcis-7524	50	29	is	be	AUX
fcis-7524	50	30	a	a	DET
fcis-7524	50	31	very	very	ADV
fcis-7524	50	32	critical	critical	ADJ
fcis-7524	50	33	step	step	NOUN
fcis-7524	50	34	.	.	PUNCT
fcis-7524	51	1	preprocessing	preprocessing	NOUN
fcis-7524	51	2	of	of	ADP
fcis-7524	51	3	the	the	DET
fcis-7524	51	4	data	datum	NOUN
fcis-7524	51	5	cleans	clean	VERB
fcis-7524	51	6	up	up	ADP
fcis-7524	51	7	errors	error	NOUN
fcis-7524	51	8	,	,	PUNCT
fcis-7524	51	9	missing	missing	ADJ
fcis-7524	51	10	and	and	CCONJ
fcis-7524	51	11	outliers	outlier	NOUN
fcis-7524	51	12	in	in	ADP
fcis-7524	51	13	the	the	DET
fcis-7524	51	14	data	datum	NOUN
fcis-7524	51	15	,	,	PUNCT
fcis-7524	51	16	which	which	PRON
fcis-7524	51	17	can	can	AUX
fcis-7524	51	18	improve	improve	VERB
fcis-7524	51	19	the	the	DET
fcis-7524	51	20	accuracy	accuracy	NOUN
fcis-7524	51	21	and	and	CCONJ
fcis-7524	51	22	stability	stability	NOUN
fcis-7524	51	23	of	of	ADP
fcis-7524	51	24	the	the	DET
fcis-7524	51	25	model	model	NOUN
fcis-7524	51	26	.	.	PUNCT
fcis-7524	52	1	it	it	PRON
fcis-7524	52	2	also	also	ADV
fcis-7524	52	3	reduces	reduce	VERB
fcis-7524	52	4	the	the	DET
fcis-7524	52	5	dimensionality	dimensionality	NOUN
fcis-7524	52	6	of	of	ADP
fcis-7524	52	7	the	the	DET
fcis-7524	52	8	dataset	dataset	NOUN
fcis-7524	52	9	by	by	ADP
fcis-7524	52	10	retaining	retain	VERB
fcis-7524	52	11	key	key	ADJ
fcis-7524	52	12	information	information	NOUN
fcis-7524	52	13	and	and	CCONJ
fcis-7524	52	14	reducing	reduce	VERB
fcis-7524	52	15	redundant	redundant	ADJ
fcis-7524	52	16	information	information	NOUN
fcis-7524	52	17	,	,	PUNCT
fcis-7524	52	18	which	which	PRON
fcis-7524	52	19	can	can	AUX
fcis-7524	52	20	improve	improve	VERB
fcis-7524	52	21	the	the	DET
fcis-7524	52	22	speed	speed	NOUN
fcis-7524	52	23	and	and	CCONJ
fcis-7524	52	24	efficiency	efficiency	NOUN
fcis-7524	52	25	of	of	ADP
fcis-7524	52	26	the	the	DET
fcis-7524	52	27	model	model	NOUN
fcis-7524	52	28	.	.	PUNCT
fcis-7524	53	1	similarity	similarity	NOUN
fcis-7524	53	2	coefficient	coefficient	NOUN
fcis-7524	53	3	is	be	AUX
fcis-7524	53	4	a	a	DET
fcis-7524	53	5	statistic	statistic	NOUN
fcis-7524	53	6	used	use	VERB
fcis-7524	53	7	to	to	PART
fcis-7524	53	8	measure	measure	VERB
fcis-7524	53	9	the	the	DET
fcis-7524	53	10	similarity	similarity	NOUN
fcis-7524	53	11	between	between	ADP
fcis-7524	53	12	two	two	NUM
fcis-7524	53	13	variables	variable	NOUN
fcis-7524	53	14	.	.	PUNCT
fcis-7524	54	1	it	it	PRON
fcis-7524	54	2	is	be	AUX
fcis-7524	54	3	a	a	DET
fcis-7524	54	4	form	form	NOUN
fcis-7524	54	5	of	of	ADP
fcis-7524	54	6	pearson	pearson	PROPN
fcis-7524	54	7	's	's	PART
fcis-7524	54	8	correlation	correlation	NOUN
fcis-7524	54	9	coefficient	coefficient	NOUN
fcis-7524	54	10	and	and	CCONJ
fcis-7524	54	11	is	be	AUX
fcis-7524	54	12	usually	usually	ADV
fcis-7524	54	13	used	use	VERB
fcis-7524	54	14	to	to	PART
fcis-7524	54	15	calculate	calculate	VERB
fcis-7524	54	16	the	the	DET
fcis-7524	54	17	linear	linear	ADJ
fcis-7524	54	18	correlation	correlation	NOUN
fcis-7524	54	19	between	between	ADP
fcis-7524	54	20	two	two	NUM
fcis-7524	54	21	numerical	numerical	ADJ
fcis-7524	54	22	variables	variable	NOUN
fcis-7524	54	23	.	.	PUNCT
fcis-7524	55	1	it	it	PRON
fcis-7524	55	2	takes	take	VERB
fcis-7524	55	3	values	value	NOUN
fcis-7524	55	4	ranging	range	VERB
fcis-7524	55	5	from	from	ADP
fcis-7524	55	6	-1	-1	INTJ
fcis-7524	55	7	to	to	ADP
fcis-7524	55	8	1	1	NUM
fcis-7524	55	9	,	,	PUNCT
fcis-7524	55	10	where	where	SCONJ
fcis-7524	55	11	1	1	NUM
fcis-7524	55	12	indicates	indicate	VERB
fcis-7524	55	13	a	a	DET
fcis-7524	55	14	perfectly	perfectly	ADV
fcis-7524	55	15	positive	positive	ADJ
fcis-7524	55	16	correlation	correlation	NOUN
fcis-7524	55	17	,	,	PUNCT
fcis-7524	55	18	-1	-1	PUNCT
fcis-7524	55	19	indicates	indicate	VERB
fcis-7524	55	20	a	a	DET
fcis-7524	55	21	perfectly	perfectly	ADV
fcis-7524	55	22	negative	negative	ADJ
fcis-7524	55	23	correlation	correlation	NOUN
fcis-7524	55	24	,	,	PUNCT
fcis-7524	55	25	and	and	CCONJ
fcis-7524	55	26	0	0	NUM
fcis-7524	55	27	indicates	indicate	VERB
fcis-7524	55	28	no	no	DET
fcis-7524	55	29	linear	linear	ADJ
fcis-7524	55	30	correlation	correlation	NOUN
fcis-7524	55	31	.	.	PUNCT
fcis-7524	56	1	the	the	DET
fcis-7524	56	2	similarity	similarity	NOUN
fcis-7524	56	3	coefficient	coefficient	NOUN
fcis-7524	56	4	is	be	AUX
fcis-7524	56	5	calculated	calculate	VERB
fcis-7524	56	6	in	in	ADP
fcis-7524	56	7	the	the	DET
fcis-7524	56	8	same	same	ADJ
fcis-7524	56	9	way	way	NOUN
fcis-7524	56	10	as	as	SCONJ
fcis-7524	56	11	the	the	DET
fcis-7524	56	12	pearson	pearson	PROPN
fcis-7524	56	13	correlation	correlation	NOUN
fcis-7524	56	14	coefficient	coefficient	NOUN
fcis-7524	56	15	,	,	PUNCT
fcis-7524	56	16	by	by	ADP
fcis-7524	56	17	calculating	calculate	VERB
fcis-7524	56	18	the	the	DET
fcis-7524	56	19	covariance	covariance	NOUN
fcis-7524	56	20	and	and	CCONJ
fcis-7524	56	21	standard	standard	ADJ
fcis-7524	56	22	deviation	deviation	NOUN
fcis-7524	56	23	between	between	ADP
fcis-7524	56	24	two	two	NUM
fcis-7524	56	25	variables	variable	NOUN
fcis-7524	56	26	.	.	PUNCT
fcis-7524	57	1	the	the	DET
fcis-7524	57	2	specific	specific	ADJ
fcis-7524	57	3	calculation	calculation	NOUN
fcis-7524	57	4	formula	formula	NOUN
fcis-7524	57	5	is	be	AUX
fcis-7524	57	6	as	as	SCONJ
fcis-7524	57	7	follows	follow	VERB
fcis-7524	57	8	:	:	PUNCT
fcis-7524	57	9	corr	corr	NOUN
fcis-7524	57	10	(	(	PUNCT
fcis-7524	57	11	x	x	PROPN
fcis-7524	57	12	,	,	PUNCT
fcis-7524	57	13	y	y	PROPN
fcis-7524	57	14	)	)	PUNCT
fcis-7524	57	15	cov	cov	PROPN
fcis-7524	57	16	(	(	PUNCT
fcis-7524	57	17	x	x	NOUN
fcis-7524	57	18	,	,	PUNCT
fcis-7524	57	19	y	y	PROPN
fcis-7524	57	20	)	)	PUNCT
fcis-7524	57	21	/	/	PUNCT
fcis-7524	57	22	(	(	PUNCT
fcis-7524	57	23	std	std	X
fcis-7524	57	24	(	(	PUNCT
fcis-7524	57	25	x	x	SYM
fcis-7524	57	26	)	)	PUNCT
fcis-7524	57	27	*	*	PUNCT
fcis-7524	57	28	std(y	std(y	PROPN
fcis-7524	57	29	)	)	PUNCT
fcis-7524	57	30	)	)	PUNCT
fcis-7524	57	31	=	=	PRON
fcis-7524	58	1	(	(	PUNCT
fcis-7524	58	2	1	1	X
fcis-7524	58	3	)	)	PUNCT
fcis-7524	58	4	where	where	SCONJ
fcis-7524	58	5	cov(x	cov(x	PROPN
fcis-7524	58	6	,	,	PUNCT
fcis-7524	58	7	y	y	PROPN
fcis-7524	58	8	)	)	PUNCT
fcis-7524	58	9	is	be	AUX
fcis-7524	58	10	the	the	DET
fcis-7524	58	11	covariance	covariance	NOUN
fcis-7524	58	12	of	of	ADP
fcis-7524	58	13	x	x	PROPN
fcis-7524	58	14	and	and	CCONJ
fcis-7524	58	15	y	y	PROPN
fcis-7524	58	16	,	,	PUNCT
fcis-7524	58	17	and	and	CCONJ
fcis-7524	58	18	std(x	std(x	NOUN
fcis-7524	58	19	)	)	PUNCT
fcis-7524	58	20	and	and	CCONJ
fcis-7524	58	21	std(y	std(y	PROPN
fcis-7524	58	22	)	)	PUNCT
fcis-7524	58	23	are	be	AUX
fcis-7524	58	24	the	the	DET
fcis-7524	58	25	standard	standard	ADJ
fcis-7524	58	26	deviations	deviation	NOUN
fcis-7524	58	27	of	of	ADP
fcis-7524	58	28	x	x	X
fcis-7524	58	29	and	and	CCONJ
fcis-7524	58	30	y	y	PROPN
fcis-7524	58	31	,	,	PUNCT
fcis-7524	58	32	respectively	respectively	ADV
fcis-7524	58	33	.	.	PUNCT
fcis-7524	59	1	the	the	PRON
fcis-7524	59	2	closer	close	ADJ
fcis-7524	59	3	the	the	DET
fcis-7524	59	4	value	value	NOUN
fcis-7524	59	5	of	of	ADP
fcis-7524	59	6	the	the	DET
fcis-7524	59	7	similarity	similarity	NOUN
fcis-7524	59	8	coefficient	coefficient	NOUN
fcis-7524	59	9	is	be	AUX
fcis-7524	59	10	to	to	ADP
fcis-7524	59	11	1	1	NUM
fcis-7524	59	12	or	or	CCONJ
fcis-7524	59	13	-1	-1	ADP
fcis-7524	59	14	,	,	PUNCT
fcis-7524	59	15	the	the	PRON
fcis-7524	59	16	stronger	strong	ADJ
fcis-7524	59	17	the	the	DET
fcis-7524	59	18	linear	linear	ADJ
fcis-7524	59	19	correlation	correlation	NOUN
fcis-7524	59	20	between	between	ADP
fcis-7524	59	21	the	the	DET
fcis-7524	59	22	two	two	NUM
fcis-7524	59	23	variables	variable	NOUN
fcis-7524	59	24	;	;	PUNCT
fcis-7524	59	25	while	while	SCONJ
fcis-7524	59	26	the	the	PRON
fcis-7524	59	27	closer	close	ADJ
fcis-7524	59	28	the	the	DET
fcis-7524	59	29	similarity	similarity	NOUN
fcis-7524	59	30	coefficient	coefficient	NOUN
fcis-7524	59	31	is	be	AUX
fcis-7524	59	32	to	to	ADP
fcis-7524	59	33	0	0	NUM
fcis-7524	59	34	,	,	PUNCT
fcis-7524	59	35	the	the	PRON
fcis-7524	59	36	weaker	weak	ADJ
fcis-7524	59	37	the	the	DET
fcis-7524	59	38	linear	linear	ADJ
fcis-7524	59	39	correlation	correlation	NOUN
fcis-7524	59	40	between	between	ADP
fcis-7524	59	41	the	the	DET
fcis-7524	59	42	two	two	NUM
fcis-7524	59	43	variables	variable	NOUN
fcis-7524	59	44	.	.	PUNCT
fcis-7524	60	1	it	it	PRON
fcis-7524	60	2	is	be	AUX
fcis-7524	60	3	a	a	DET
fcis-7524	60	4	good	good	ADJ
fcis-7524	60	5	choice	choice	NOUN
fcis-7524	60	6	to	to	PART
fcis-7524	60	7	use	use	VERB
fcis-7524	60	8	in	in	ADP
fcis-7524	60	9	data	datum	NOUN
fcis-7524	60	10	preprocessing	preprocesse	VERB
fcis-7524	60	11	to	to	PART
fcis-7524	60	12	select	select	VERB
fcis-7524	60	13	useful	useful	ADJ
fcis-7524	60	14	data	datum	NOUN
fcis-7524	60	15	based	base	VERB
fcis-7524	60	16	on	on	ADP
fcis-7524	60	17	the	the	DET
fcis-7524	60	18	similarity	similarity	NOUN
fcis-7524	60	19	coefficients	coefficient	NOUN
fcis-7524	60	20	of	of	ADP
fcis-7524	60	21	the	the	DET
fcis-7524	60	22	input	input	NOUN
fcis-7524	60	23	data	datum	NOUN
fcis-7524	60	24	parameters	parameter	NOUN
fcis-7524	60	25	.	.	PUNCT
fcis-7524	61	1	data	datum	NOUN
fcis-7524	61	2	normalization	normalization	NOUN
fcis-7524	61	3	is	be	AUX
fcis-7524	61	4	the	the	DET
fcis-7524	61	5	scaling	scaling	NOUN
fcis-7524	61	6	of	of	ADP
fcis-7524	61	7	data	datum	NOUN
fcis-7524	61	8	to	to	ADP
fcis-7524	61	9	the	the	DET
fcis-7524	61	10	same	same	ADJ
fcis-7524	61	11	range	range	NOUN
fcis-7524	61	12	to	to	PART
fcis-7524	61	13	ensure	ensure	VERB
fcis-7524	61	14	that	that	SCONJ
fcis-7524	61	15	the	the	DET
fcis-7524	61	16	model	model	NOUN
fcis-7524	61	17	does	do	AUX
fcis-7524	61	18	not	not	PART
fcis-7524	61	19	fail	fail	VERB
fcis-7524	61	20	due	due	ADJ
fcis-7524	61	21	to	to	ADP
fcis-7524	61	22	too	too	ADV
fcis-7524	61	23	large	large	ADJ
fcis-7524	61	24	or	or	CCONJ
fcis-7524	61	25	too	too	ADV
fcis-7524	61	26	small	small	ADJ
fcis-7524	61	27	a	a	DET
fcis-7524	61	28	range	range	NOUN
fcis-7524	61	29	of	of	ADP
fcis-7524	61	30	values	value	NOUN
fcis-7524	61	31	for	for	ADP
fcis-7524	61	32	some	some	DET
fcis-7524	61	33	features	feature	NOUN
fcis-7524	61	34	.	.	PUNCT
fcis-7524	62	1	this	this	PRON
fcis-7524	62	2	is	be	AUX
fcis-7524	62	3	especially	especially	ADV
fcis-7524	62	4	true	true	ADJ
fcis-7524	62	5	in	in	ADP
fcis-7524	62	6	feature	feature	NOUN
fcis-7524	62	7	selection	selection	NOUN
fcis-7524	62	8	.	.	PUNCT
fcis-7524	63	1	in	in	ADP
fcis-7524	63	2	feature	feature	NOUN
fcis-7524	63	3	selection	selection	NOUN
fcis-7524	63	4	,	,	PUNCT
fcis-7524	63	5	a	a	DET
fcis-7524	63	6	similarity	similarity	NOUN
fcis-7524	63	7	coefficient	coefficient	NOUN
fcis-7524	63	8	can	can	AUX
fcis-7524	63	9	be	be	AUX
fcis-7524	63	10	used	use	VERB
fcis-7524	63	11	to	to	PART
fcis-7524	63	12	determine	determine	VERB
fcis-7524	63	13	if	if	SCONJ
fcis-7524	63	14	there	there	PRON
fcis-7524	63	15	is	be	VERB
fcis-7524	63	16	a	a	DET
fcis-7524	63	17	linear	linear	ADJ
fcis-7524	63	18	relationship	relationship	NOUN
fcis-7524	63	19	between	between	ADP
fcis-7524	63	20	two	two	NUM
fcis-7524	63	21	variables	variable	NOUN
fcis-7524	63	22	in	in	ADP
fcis-7524	63	23	order	order	NOUN
fcis-7524	63	24	to	to	PART
fcis-7524	63	25	determine	determine	VERB
fcis-7524	63	26	if	if	SCONJ
fcis-7524	63	27	they	they	PRON
fcis-7524	63	28	both	both	PRON
fcis-7524	63	29	need	need	VERB
fcis-7524	63	30	to	to	PART
fcis-7524	63	31	be	be	AUX
fcis-7524	63	32	included	include	VERB
fcis-7524	63	33	in	in	ADP
fcis-7524	63	34	the	the	DET
fcis-7524	63	35	model	model	NOUN
fcis-7524	63	36	.	.	PUNCT
fcis-7524	64	1	feature	feature	NOUN
fcis-7524	64	2	selection	selection	NOUN
fcis-7524	64	3	is	be	AUX
fcis-7524	64	4	performed	perform	VERB
fcis-7524	64	5	using	use	VERB
fcis-7524	64	6	the	the	DET
fcis-7524	64	7	dataset	dataset	NOUN
fcis-7524	64	8	to	to	PART
fcis-7524	64	9	generate	generate	VERB
fcis-7524	64	10	a	a	DET
fcis-7524	64	11	heat	heat	NOUN
fcis-7524	64	12	map	map	NOUN
fcis-7524	64	13	about	about	ADP
fcis-7524	64	14	the	the	DET
fcis-7524	64	15	data	datum	NOUN
fcis-7524	64	16	feature	feature	NOUN
fcis-7524	64	17	values	value	NOUN
fcis-7524	64	18	,	,	PUNCT
fcis-7524	64	19	and	and	CCONJ
fcis-7524	64	20	one	one	NUM
fcis-7524	64	21	or	or	CCONJ
fcis-7524	64	22	more	more	ADJ
fcis-7524	64	23	features	feature	NOUN
fcis-7524	64	24	are	be	AUX
fcis-7524	64	25	selected	select	VERB
fcis-7524	64	26	from	from	ADP
fcis-7524	64	27	those	those	PRON
fcis-7524	64	28	with	with	ADP
fcis-7524	64	29	high	high	ADJ
fcis-7524	64	30	similarity	similarity	NOUN
fcis-7524	64	31	coefficients	coefficient	NOUN
fcis-7524	64	32	.	.	PUNCT
fcis-7524	65	1	the	the	DET
fcis-7524	65	2	number	number	NOUN
fcis-7524	65	3	of	of	ADP
fcis-7524	65	4	these	these	DET
fcis-7524	65	5	features	feature	NOUN
fcis-7524	65	6	is	be	AUX
fcis-7524	65	7	also	also	ADV
fcis-7524	65	8	combined	combine	VERB
fcis-7524	65	9	with	with	ADP
fcis-7524	65	10	quantum	quantum	ADJ
fcis-7524	65	11	lines	line	NOUN
fcis-7524	65	12	to	to	PART
fcis-7524	65	13	make	make	VERB
fcis-7524	65	14	a	a	DET
fcis-7524	65	15	comprehensive	comprehensive	ADJ
fcis-7524	65	16	decision	decision	NOUN
fcis-7524	65	17	.	.	PUNCT
fcis-7524	66	1	101	101	NUM
fcis-7524	66	2	3.2	3.2	NUM
fcis-7524	66	3	.	.	PUNCT
fcis-7524	66	4	fuzzy	fuzzy	ADJ
fcis-7524	66	5	unit	unit	NOUN
fcis-7524	66	6	in	in	ADP
fcis-7524	66	7	fuzzy	fuzzy	ADJ
fcis-7524	66	8	theory	theory	NOUN
fcis-7524	66	9	,	,	PUNCT
fcis-7524	66	10	a	a	DET
fcis-7524	66	11	fuzzy	fuzzy	ADJ
fcis-7524	66	12	number	number	NOUN
fcis-7524	66	13	is	be	AUX
fcis-7524	66	14	usually	usually	ADV
fcis-7524	66	15	described	describe	VERB
fcis-7524	66	16	by	by	ADP
fcis-7524	66	17	an	an	DET
fcis-7524	66	18	affiliation	affiliation	NOUN
fcis-7524	66	19	function	function	NOUN
fcis-7524	66	20	that	that	PRON
fcis-7524	66	21	takes	take	VERB
fcis-7524	66	22	values	value	NOUN
fcis-7524	66	23	in	in	ADP
fcis-7524	66	24	the	the	DET
fcis-7524	66	25	range	range	NOUN
fcis-7524	66	26	[	[	X
fcis-7524	66	27	0,1	0,1	NUM
fcis-7524	66	28	]	]	PUNCT
fcis-7524	66	29	.	.	PUNCT
fcis-7524	67	1	the	the	DET
fcis-7524	67	2	affiliation	affiliation	NOUN
fcis-7524	67	3	function	function	NOUN
fcis-7524	67	4	describes	describe	VERB
fcis-7524	67	5	the	the	DET
fcis-7524	67	6	relationship	relationship	NOUN
fcis-7524	67	7	between	between	ADP
fcis-7524	67	8	an	an	DET
fcis-7524	67	9	element	element	NOUN
fcis-7524	67	10	and	and	CCONJ
fcis-7524	67	11	a	a	DET
fcis-7524	67	12	fuzzy	fuzzy	ADJ
fcis-7524	67	13	concept	concept	NOUN
fcis-7524	67	14	,	,	PUNCT
fcis-7524	67	15	and	and	CCONJ
fcis-7524	67	16	its	its	PRON
fcis-7524	67	17	value	value	NOUN
fcis-7524	67	18	indicates	indicate	VERB
fcis-7524	67	19	the	the	DET
fcis-7524	67	20	degree	degree	NOUN
fcis-7524	67	21	to	to	PART
fcis-7524	67	22	which	which	PRON
fcis-7524	67	23	the	the	DET
fcis-7524	67	24	element	element	NOUN
fcis-7524	67	25	belongs	belong	VERB
fcis-7524	67	26	to	to	ADP
fcis-7524	67	27	the	the	DET
fcis-7524	67	28	fuzzy	fuzzy	ADJ
fcis-7524	67	29	concept	concept	NOUN
fcis-7524	67	30	.	.	PUNCT
fcis-7524	68	1	the	the	DET
fcis-7524	68	2	common	common	ADJ
fcis-7524	68	3	fuzzy	fuzzy	ADJ
fcis-7524	68	4	numbers	number	NOUN
fcis-7524	68	5	are	be	AUX
fcis-7524	68	6	triangular	triangular	NOUN
fcis-7524	68	7	fuzzy	fuzzy	ADJ
fcis-7524	68	8	number	number	NOUN
fcis-7524	68	9	,	,	PUNCT
fcis-7524	68	10	trapezoidal	trapezoidal	ADJ
fcis-7524	68	11	fuzzy	fuzzy	ADJ
fcis-7524	68	12	number	number	NOUN
fcis-7524	68	13	,	,	PUNCT
fcis-7524	68	14	square	square	ADJ
fcis-7524	68	15	fuzzy	fuzzy	ADJ
fcis-7524	68	16	number	number	NOUN
fcis-7524	68	17	,	,	PUNCT
fcis-7524	68	18	gaussian	gaussian	ADJ
fcis-7524	68	19	fuzzy	fuzzy	ADJ
fcis-7524	68	20	number	number	NOUN
fcis-7524	68	21	and	and	CCONJ
fcis-7524	68	22	exponential	exponential	ADJ
fcis-7524	68	23	fuzzy	fuzzy	ADJ
fcis-7524	68	24	number	number	NOUN
fcis-7524	68	25	.	.	PUNCT
fcis-7524	69	1	this	this	DET
fcis-7524	69	2	model	model	NOUN
fcis-7524	69	3	uses	use	VERB
fcis-7524	69	4	gaussian	gaussian	ADJ
fcis-7524	69	5	fuzzy	fuzzy	ADJ
fcis-7524	69	6	number	number	NOUN
fcis-7524	69	7	for	for	ADP
fcis-7524	69	8	fuzzing	fuzzing	NOUN
fcis-7524	69	9	,	,	PUNCT
fcis-7524	69	10	which	which	PRON
fcis-7524	69	11	is	be	AUX
fcis-7524	69	12	used	use	VERB
fcis-7524	69	13	to	to	PART
fcis-7524	69	14	measure	measure	VERB
fcis-7524	69	15	the	the	DET
fcis-7524	69	16	correlation	correlation	NOUN
fcis-7524	69	17	between	between	ADP
fcis-7524	69	18	the	the	DET
fcis-7524	69	19	input	input	NOUN
fcis-7524	69	20	values	value	NOUN
fcis-7524	69	21	and	and	CCONJ
fcis-7524	69	22	the	the	DET
fcis-7524	69	23	members	member	NOUN
fcis-7524	69	24	of	of	ADP
fcis-7524	69	25	a	a	DET
fcis-7524	69	26	particular	particular	ADJ
fcis-7524	69	27	set	set	NOUN
fcis-7524	69	28	.	.	PUNCT
fcis-7524	70	1	the	the	DET
fcis-7524	70	2	mathematical	mathematical	ADJ
fcis-7524	70	3	expression	expression	NOUN
fcis-7524	70	4	of	of	ADP
fcis-7524	70	5	gaussian	gaussian	ADJ
fcis-7524	70	6	affiliation	affiliation	NOUN
fcis-7524	70	7	function	function	NOUN
fcis-7524	70	8	is	be	AUX
fcis-7524	70	9	2	2	NUM
fcis-7524	70	10	22	22	NUM
fcis-7524	70	11	(	(	PUNCT
fcis-7524	70	12	x	x	NOUN
fcis-7524	70	13	m	m	VERB
fcis-7524	70	14	)	)	PUNCT
fcis-7524	70	15	(	(	PUNCT
fcis-7524	70	16	x	x	X
fcis-7524	70	17	,	,	PUNCT
fcis-7524	70	18	m	m	PROPN
fcis-7524	70	19	,	,	PUNCT
fcis-7524	70	20	)	)	PUNCT
fcis-7524	70	21	e	e	PROPN
fcis-7524	70	22			PROPN
fcis-7524	70	23			PROPN
fcis-7524	71	1	−	−	PROPN
fcis-7524	72	1	−	−	PROPN
fcis-7524	73	1	=	=	SYM
fcis-7524	74	1	(	(	PUNCT
fcis-7524	74	2	2	2	NUM
fcis-7524	74	3	)	)	PUNCT
fcis-7524	74	4	where	where	SCONJ
fcis-7524	74	5	m	m	NOUN
fcis-7524	74	6	represents	represent	VERB
fcis-7524	74	7	the	the	DET
fcis-7524	74	8	membership	membership	NOUN
fcis-7524	74	9	value	value	NOUN
fcis-7524	74	10	of	of	ADP
fcis-7524	74	11	the	the	DET
fcis-7524	74	12	set	set	NOUN
fcis-7524	74	13	and	and	CCONJ
fcis-7524	74	14	σ	σ	PROPN
fcis-7524	74	15	represents	represent	VERB
fcis-7524	74	16	the	the	DET
fcis-7524	74	17	standard	standard	ADJ
fcis-7524	74	18	deviation	deviation	NOUN
fcis-7524	74	19	,	,	PUNCT
fcis-7524	74	20	i.e.	i.e.	X
fcis-7524	74	21	,	,	PUNCT
fcis-7524	74	22	the	the	DET
fcis-7524	74	23	value	value	NOUN
fcis-7524	74	24	of	of	ADP
fcis-7524	74	25	the	the	DET
fcis-7524	74	26	affiliation	affiliation	NOUN
fcis-7524	74	27	function	function	NOUN
fcis-7524	74	28	decreases	decrease	VERB
fcis-7524	74	29	sharply	sharply	ADV
fcis-7524	74	30	when	when	SCONJ
fcis-7524	74	31	the	the	DET
fcis-7524	74	32	deviation	deviation	NOUN
fcis-7524	74	33	of	of	ADP
fcis-7524	74	34	the	the	DET
fcis-7524	74	35	variable	variable	NOUN
fcis-7524	74	36	x	x	PUNCT
fcis-7524	74	37	with	with	ADP
fcis-7524	74	38	respect	respect	NOUN
fcis-7524	74	39	to	to	ADP
fcis-7524	74	40	m	m	PROPN
fcis-7524	74	41	exceeds	exceed	NOUN
fcis-7524	74	42	σ	σ	PROPN
fcis-7524	74	43	.	.	PUNCT
fcis-7524	75	1	the	the	DET
fcis-7524	75	2	gaussian	gaussian	ADJ
fcis-7524	75	3	affiliation	affiliation	NOUN
fcis-7524	75	4	function	function	NOUN
fcis-7524	75	5	can	can	AUX
fcis-7524	75	6	be	be	AUX
fcis-7524	75	7	used	use	VERB
fcis-7524	75	8	to	to	PART
fcis-7524	75	9	describe	describe	VERB
fcis-7524	75	10	different	different	ADJ
fcis-7524	75	11	kinds	kind	NOUN
fcis-7524	75	12	of	of	ADP
fcis-7524	75	13	input	input	NOUN
fcis-7524	75	14	values	value	NOUN
fcis-7524	75	15	and	and	CCONJ
fcis-7524	75	16	can	can	AUX
fcis-7524	75	17	even	even	ADV
fcis-7524	75	18	be	be	AUX
fcis-7524	75	19	used	use	VERB
fcis-7524	75	20	for	for	ADP
fcis-7524	75	21	fuzzy	fuzzy	ADJ
fcis-7524	75	22	sets	set	NOUN
fcis-7524	75	23	in	in	ADP
fcis-7524	75	24	multivariate	multivariate	NOUN
fcis-7524	75	25	systems	system	NOUN
fcis-7524	75	26	.	.	PUNCT
fcis-7524	76	1	it	it	PRON
fcis-7524	76	2	is	be	AUX
fcis-7524	76	3	important	important	ADJ
fcis-7524	76	4	in	in	ADP
fcis-7524	76	5	expressing	express	VERB
fcis-7524	76	6	fuzzy	fuzzy	ADJ
fcis-7524	76	7	sets	set	NOUN
fcis-7524	76	8	and	and	CCONJ
fcis-7524	76	9	defining	define	VERB
fcis-7524	76	10	fuzzy	fuzzy	ADJ
fcis-7524	76	11	rules	rule	NOUN
fcis-7524	76	12	because	because	SCONJ
fcis-7524	76	13	it	it	PRON
fcis-7524	76	14	can	can	AUX
fcis-7524	76	15	perfectly	perfectly	ADV
fcis-7524	76	16	express	express	VERB
fcis-7524	76	17	and	and	CCONJ
fcis-7524	76	18	measure	measure	VERB
fcis-7524	76	19	the	the	DET
fcis-7524	76	20	interconnection	interconnection	NOUN
fcis-7524	76	21	between	between	ADP
fcis-7524	76	22	fuzzy	fuzzy	ADJ
fcis-7524	76	23	variables	variable	NOUN
fcis-7524	76	24	.	.	PUNCT
fcis-7524	77	1	from	from	ADP
fcis-7524	77	2	the	the	DET
fcis-7524	77	3	data	datum	NOUN
fcis-7524	77	4	preprocessing	preprocesse	VERB
fcis-7524	77	5	dataset	dataset	NOUN
fcis-7524	77	6	(	(	PUNCT
fcis-7524	77	7	x	x	NOUN
fcis-7524	77	8	,	,	PUNCT
fcis-7524	77	9	y	y	NOUN
fcis-7524	77	10	)	)	PUNCT
fcis-7524	77	11	containing	contain	VERB
fcis-7524	77	12	p	p	PROPN
fcis-7524	77	13	data	data	NOUN
fcis-7524	77	14	points	point	NOUN
fcis-7524	77	15	and	and	CCONJ
fcis-7524	77	16	n	n	NOUN
fcis-7524	77	17	features	feature	NOUN
fcis-7524	77	18	,	,	PUNCT
fcis-7524	77	19	the	the	DET
fcis-7524	77	20	autocovariance	autocovariance	NOUN
fcis-7524	77	21	matrix	matrix	NOUN
fcis-7524	77	22	x	x	PUNCT
fcis-7524	77	23	is	be	AUX
fcis-7524	77	24	generated	generate	VERB
fcis-7524	77	25	as	as	SCONJ
fcis-7524	77	26	shown	show	VERB
fcis-7524	77	27	in	in	ADP
fcis-7524	77	28	eq	eq	ADP
fcis-7524	77	29	.	.	PUNCT
fcis-7524	78	1	(	(	PUNCT
fcis-7524	78	2	3	3	NUM
fcis-7524	78	3	)	)	PUNCT
fcis-7524	78	4	.	.	PUNCT
fcis-7524	79	1	1	1	NUM
fcis-7524	79	2	1	1	NUM
fcis-7524	79	3	1	1	NUM
fcis-7524	79	4	0	0	NUM
fcis-7524	79	5	1	1	NUM
fcis-7524	79	6	1	1	NUM
fcis-7524	79	7	2	2	NUM
fcis-7524	79	8	2	2	NUM
fcis-7524	79	9	2	2	NUM
fcis-7524	79	10	0	0	NUM
fcis-7524	79	11	1	1	NUM
fcis-7524	79	12	1	1	NUM
fcis-7524	79	13	0	0	NUM
fcis-7524	79	14	1	1	NUM
fcis-7524	79	15	1	1	NUM
fcis-7524	79	16	n	n	NUM
fcis-7524	79	17	n	n	NOUN
fcis-7524	79	18	p	p	NOUN
fcis-7524	79	19	p	p	X
fcis-7524	79	20	p	p	X
fcis-7524	79	21	n	n	NOUN
fcis-7524	79	22	x	x	NOUN
fcis-7524	79	23	x	x	X
fcis-7524	79	24	...	...	PUNCT
fcis-7524	80	1	x	x	PUNCT
fcis-7524	80	2	x	x	PUNCT
fcis-7524	80	3	x	x	X
fcis-7524	80	4	...	...	PUNCT
fcis-7524	80	5	x	x	SYM
fcis-7524	80	6	x	x	X
fcis-7524	80	7	...	...	PUNCT
fcis-7524	80	8	...	...	PUNCT
fcis-7524	80	9	...	...	PUNCT
fcis-7524	80	10	...	...	PUNCT
fcis-7524	81	1	x	x	X
fcis-7524	81	2	x	x	X
fcis-7524	81	3	...	...	PUNCT
fcis-7524	81	4	x	x	X
fcis-7524	82	1	−	−	NOUN
fcis-7524	82	2	−	−	NOUN
fcis-7524	83	1	−	−	PROPN
fcis-7524	83	2			PROPN
fcis-7524	83	3			ADJ
fcis-7524	83	4			NOUN
fcis-7524	83	5			PROPN
fcis-7524	83	6			NOUN
fcis-7524	83	7	=	=	X
fcis-7524	83	8			NOUN
fcis-7524	83	9			NOUN
fcis-7524	83	10			NOUN
fcis-7524	83	11			NOUN
fcis-7524	83	12			NOUN
fcis-7524	83	13			PROPN
fcis-7524	83	14			PROPN
fcis-7524	83	15	(	(	PUNCT
fcis-7524	83	16	3	3	X
fcis-7524	83	17	)	)	PUNCT
fcis-7524	83	18	the	the	DET
fcis-7524	83	19	mean	mean	ADJ
fcis-7524	83	20	and	and	CCONJ
fcis-7524	83	21	standard	standard	ADJ
fcis-7524	83	22	deviation	deviation	NOUN
fcis-7524	83	23	of	of	ADP
fcis-7524	83	24	each	each	DET
fcis-7524	83	25	feature	feature	NOUN
fcis-7524	83	26	are	be	AUX
fcis-7524	83	27	calculated	calculate	VERB
fcis-7524	83	28	,	,	PUNCT
fcis-7524	83	29	and	and	CCONJ
fcis-7524	83	30	the	the	DET
fcis-7524	83	31	gaussian	gaussian	ADJ
fcis-7524	83	32	fuzzy	fuzzy	ADJ
fcis-7524	83	33	degree	degree	NOUN
fcis-7524	83	34	matrix	matrix	NOUN
fcis-7524	83	35	x	x	X
fcis-7524	83	36	is	be	AUX
fcis-7524	83	37	generated	generate	VERB
fcis-7524	83	38	by	by	ADP
fcis-7524	83	39	using	use	VERB
fcis-7524	83	40	the	the	DET
fcis-7524	83	41	gaussian	gaussian	ADJ
fcis-7524	83	42	fuzzy	fuzzy	ADJ
fcis-7524	83	43	number	number	NOUN
fcis-7524	83	44	function	function	NOUN
fcis-7524	83	45	to	to	PART
fcis-7524	83	46	calculate	calculate	VERB
fcis-7524	83	47	the	the	DET
fcis-7524	83	48	gaussian	gaussian	ADJ
fcis-7524	83	49	affiliation	affiliation	NOUN
fcis-7524	83	50	,	,	PUNCT
fcis-7524	83	51	as	as	SCONJ
fcis-7524	83	52	shown	show	VERB
fcis-7524	83	53	in	in	ADP
fcis-7524	83	54	eq	eq	ADP
fcis-7524	83	55	.	.	PUNCT
fcis-7524	84	1	(	(	PUNCT
fcis-7524	84	2	4	4	NUM
fcis-7524	84	3	)	)	PUNCT
fcis-7524	84	4	.	.	PUNCT
fcis-7524	85	1	1	1	NUM
fcis-7524	85	2	1	1	NUM
fcis-7524	85	3	1	1	NUM
fcis-7524	85	4	0	0	NUM
fcis-7524	85	5	1	1	NUM
fcis-7524	85	6	1	1	NUM
fcis-7524	85	7	2	2	NUM
fcis-7524	85	8	2	2	NUM
fcis-7524	85	9	2	2	NUM
fcis-7524	85	10	0	0	NUM
fcis-7524	85	11	1	1	NUM
fcis-7524	85	12	1	1	NUM
fcis-7524	85	13	0	0	NUM
fcis-7524	85	14	1	1	NUM
fcis-7524	85	15	1	1	NUM
fcis-7524	85	16	n	n	NUM
fcis-7524	85	17	n	n	NOUN
fcis-7524	85	18	p	p	NOUN
fcis-7524	85	19	p	p	X
fcis-7524	85	20	p	p	X
fcis-7524	85	21	n	n	NOUN
fcis-7524	85	22	x	x	NOUN
fcis-7524	85	23	x	x	PUNCT
fcis-7524	85	24	x	x	PUNCT
fcis-7524	85	25	x	x	PUNCT
fcis-7524	85	26	x	x	PUNCT
fcis-7524	85	27	x	x	PUNCT
fcis-7524	85	28	x	x	PUNCT
fcis-7524	85	29	x	x	PUNCT
fcis-7524	85	30	x	x	PUNCT
fcis-7524	85	31	x	x	X
fcis-7524	85	32	...	...	PUNCT
fcis-7524	85	33	...	...	PUNCT
fcis-7524	85	34	...	...	PUNCT
fcis-7524	85	35	...	...	PUNCT
fcis-7524	85	36	...	...	PUNCT
fcis-7524	85	37	...	...	PUNCT
fcis-7524	85	38	...	...	PUNCT
fcis-7524	86	1			NOUN
fcis-7524	86	2			NOUN
fcis-7524	86	3			NOUN
fcis-7524	86	4			NOUN
fcis-7524	86	5			NOUN
fcis-7524	86	6			NOUN
fcis-7524	86	7			NOUN
fcis-7524	86	8			NOUN
fcis-7524	86	9			NOUN
fcis-7524	86	10			NOUN
fcis-7524	86	11	−	−	ADP
fcis-7524	86	12	−	−	NOUN
fcis-7524	86	13	−	−	PROPN
fcis-7524	86	14			PROPN
fcis-7524	86	15			ADJ
fcis-7524	86	16			NOUN
fcis-7524	86	17			PROPN
fcis-7524	86	18			NOUN
fcis-7524	86	19			NOUN
fcis-7524	86	20	=	=	SYM
fcis-7524	86	21			NOUN
fcis-7524	86	22			NOUN
fcis-7524	86	23			NOUN
fcis-7524	86	24			NOUN
fcis-7524	86	25			NOUN
fcis-7524	86	26			NOUN
fcis-7524	86	27			NOUN
fcis-7524	86	28			PROPN
fcis-7524	86	29	(	(	PUNCT
fcis-7524	86	30	4	4	NUM
fcis-7524	86	31	)	)	PUNCT
fcis-7524	86	32	the	the	DET
fcis-7524	86	33	matrix	matrix	NOUN
fcis-7524	86	34	x	x	NOUN
fcis-7524	86	35			NOUN
fcis-7524	86	36	of	of	ADP
fcis-7524	86	37	fuzzy	fuzzy	ADJ
fcis-7524	86	38	independent	independent	ADJ
fcis-7524	86	39	variables	variable	NOUN
fcis-7524	86	40	is	be	AUX
fcis-7524	86	41	generated	generate	VERB
fcis-7524	86	42	by	by	ADP
fcis-7524	86	43	multiplying	multiply	VERB
fcis-7524	86	44	the	the	DET
fcis-7524	86	45	variable	variable	ADJ
fcis-7524	86	46	matrix	matrix	NOUN
fcis-7524	86	47	x	x	PUNCT
fcis-7524	86	48	with	with	ADP
fcis-7524	86	49	the	the	DET
fcis-7524	86	50	corresponding	correspond	VERB
fcis-7524	86	51	elements	element	NOUN
fcis-7524	86	52	of	of	ADP
fcis-7524	86	53	the	the	DET
fcis-7524	86	54	corresponding	corresponding	ADJ
fcis-7524	86	55	gaussian	gaussian	ADJ
fcis-7524	86	56	fuzziness	fuzziness	NOUN
fcis-7524	86	57	matrix	matrix	NOUN
fcis-7524	86	58	x	x	PROPN
fcis-7524	86	59	.	.	PUNCT
fcis-7524	87	1	as	as	SCONJ
fcis-7524	87	2	shown	show	VERB
fcis-7524	87	3	in	in	ADP
fcis-7524	87	4	eq	eq	ADP
fcis-7524	87	5	.	.	PUNCT
fcis-7524	88	1	(	(	PUNCT
fcis-7524	88	2	5	5	NUM
fcis-7524	88	3	)	)	PUNCT
fcis-7524	88	4	.	.	PUNCT
fcis-7524	89	1	1	1	NUM
fcis-7524	89	2	1	1	NUM
fcis-7524	89	3	1	1	NUM
fcis-7524	89	4	0	0	NUM
fcis-7524	89	5	1	1	NUM
fcis-7524	89	6	1	1	NUM
fcis-7524	89	7	2	2	NUM
fcis-7524	89	8	2	2	NUM
fcis-7524	89	9	2	2	NUM
fcis-7524	89	10	0	0	NUM
fcis-7524	89	11	1	1	NUM
fcis-7524	89	12	1	1	NUM
fcis-7524	89	13	0	0	NUM
fcis-7524	89	14	1	1	NUM
fcis-7524	89	15	1	1	NUM
fcis-7524	89	16	1	1	NUM
fcis-7524	89	17	1	1	NUM
fcis-7524	89	18	1	1	NUM
fcis-7524	89	19	0	0	NUM
fcis-7524	89	20	1	1	NUM
fcis-7524	89	21	1	1	NUM
fcis-7524	89	22	2	2	NUM
fcis-7524	89	23	2	2	NUM
fcis-7524	89	24	2	2	NUM
fcis-7524	89	25	0	0	NUM
fcis-7524	89	26	1	1	NUM
fcis-7524	89	27	1	1	NUM
fcis-7524	89	28	0	0	NUM
fcis-7524	89	29	1	1	NUM
fcis-7524	89	30	1	1	NUM
fcis-7524	89	31	n	n	NUM
fcis-7524	89	32	n	n	NOUN
fcis-7524	89	33	p	p	NOUN
fcis-7524	89	34	p	p	PROPN
fcis-7524	89	35	p	p	X
fcis-7524	89	36	n	n	INTJ
fcis-7524	89	37	nx	nx	NOUN
fcis-7524	89	38	x	x	SYM
fcis-7524	89	39	x	x	X
fcis-7524	89	40	nx	nx	PROPN
fcis-7524	89	41	x	x	SYM
fcis-7524	89	42	x	x	X
fcis-7524	89	43	x	x	X
fcis-7524	89	44	p	p	X
fcis-7524	89	45	p	p	X
fcis-7524	89	46	p	p	X
fcis-7524	89	47	nx	nx	NOUN
fcis-7524	89	48	x	x	NOUN
fcis-7524	89	49	x	x	PUNCT
fcis-7524	89	50	x	x	PUNCT
fcis-7524	89	51	x	x	X
fcis-7524	89	52	...	...	PUNCT
fcis-7524	89	53	x	x	PUNCT
fcis-7524	90	1	x	x	PUNCT
fcis-7524	90	2	x	x	X
fcis-7524	90	3	...	...	PUNCT
fcis-7524	90	4	x	x	PUNCT
fcis-7524	91	1	x	x	PUNCT
fcis-7524	91	2	x	x	PUNCT
fcis-7524	91	3	*	*	PUNCT
fcis-7524	91	4	...	...	PUNCT
fcis-7524	91	5	...	...	PUNCT
fcis-7524	91	6	...	...	PUNCT
fcis-7524	91	7	...	...	PUNCT
fcis-7524	92	1	x	x	X
fcis-7524	92	2	x	x	X
fcis-7524	92	3	...	...	PUNCT
fcis-7524	92	4	x	x	PUNCT
fcis-7524	92	5			NOUN
fcis-7524	92	6			NOUN
fcis-7524	92	7			NOUN
fcis-7524	92	8			NOUN
fcis-7524	92	9			NOUN
fcis-7524	92	10			NOUN
fcis-7524	92	11			NOUN
fcis-7524	92	12			NOUN
fcis-7524	92	13			NOUN
fcis-7524	92	14			NOUN
fcis-7524	92	15			NOUN
fcis-7524	92	16	−	−	ADP
fcis-7524	92	17	−	−	NOUN
fcis-7524	92	18	−	−	PROPN
fcis-7524	92	19	−	−	PROPN
fcis-7524	92	20	−	−	PROPN
fcis-7524	92	21	−	−	PROPN
fcis-7524	92	22			PROPN
fcis-7524	92	23			ADJ
fcis-7524	92	24			NOUN
fcis-7524	92	25			PROPN
fcis-7524	92	26			NOUN
fcis-7524	92	27			NOUN
fcis-7524	92	28	=	=	SYM
fcis-7524	92	29	=	=	SYM
fcis-7524	92	30			NOUN
fcis-7524	92	31			NOUN
fcis-7524	92	32			NOUN
fcis-7524	92	33			NOUN
fcis-7524	92	34			NOUN
fcis-7524	92	35			NOUN
fcis-7524	92	36			NOUN
fcis-7524	92	37			PROPN
fcis-7524	92	38			PROPN
fcis-7524	92	39	(	(	PUNCT
fcis-7524	92	40	5	5	NUM
fcis-7524	92	41	)	)	PUNCT
fcis-7524	92	42	3.3	3.3	NUM
fcis-7524	92	43	.	.	PUNCT
fcis-7524	93	1	quantum	quantum	ADJ
fcis-7524	93	2	fuzzy	fuzzy	ADJ
fcis-7524	93	3	neural	neural	ADJ
fcis-7524	93	4	network	network	NOUN
fcis-7524	93	5	unit	unit	NOUN
fcis-7524	93	6	3.3.1	3.3.1	NUM
fcis-7524	93	7	.	.	PUNCT
fcis-7524	93	8	quantum	quantum	ADJ
fcis-7524	93	9	forward	forward	ADJ
fcis-7524	93	10	propagation	propagation	NOUN
fcis-7524	93	11	layer	layer	NOUN
fcis-7524	93	12	each	each	DET
fcis-7524	93	13	row	row	NOUN
fcis-7524	93	14	of	of	ADP
fcis-7524	93	15	the	the	DET
fcis-7524	93	16	fuzzy	fuzzy	ADJ
fcis-7524	93	17	autocovariance	autocovariance	NOUN
fcis-7524	93	18	matrix	matrix	NOUN
fcis-7524	93	19	represents	represent	VERB
fcis-7524	93	20	one	one	NUM
fcis-7524	93	21	data	datum	NOUN
fcis-7524	93	22	point	point	NOUN
fcis-7524	93	23	information	information	NOUN
fcis-7524	93	24	,	,	PUNCT
fcis-7524	93	25	as	as	SCONJ
fcis-7524	93	26	shown	show	VERB
fcis-7524	93	27	in	in	ADP
fcis-7524	93	28	the	the	DET
fcis-7524	93	29	figure	figure	NOUN
fcis-7524	93	30	will	will	AUX
fcis-7524	93	31	be	be	AUX
fcis-7524	93	32	quantum	quantum	ADJ
fcis-7524	93	33	amplitude	amplitude	NOUN
fcis-7524	93	34	coding	coding	NOUN
fcis-7524	93	35	of	of	ADP
fcis-7524	93	36	each	each	DET
fcis-7524	93	37	row	row	NOUN
fcis-7524	93	38	of	of	ADP
fcis-7524	93	39	the	the	DET
fcis-7524	93	40	fuzzy	fuzzy	ADJ
fcis-7524	93	41	autocovariance	autocovariance	NOUN
fcis-7524	93	42	matrix	matrix	NOUN
fcis-7524	93	43	data	datum	NOUN
fcis-7524	93	44	in	in	ADP
fcis-7524	93	45	turn	turn	NOUN
fcis-7524	93	46	into	into	ADP
fcis-7524	93	47	the	the	DET
fcis-7524	93	48	quantum	quantum	NOUN
fcis-7524	93	49	forward	forward	ADJ
fcis-7524	93	50	propagation	propagation	NOUN
fcis-7524	93	51	layer	layer	NOUN
fcis-7524	93	52	,	,	PUNCT
fcis-7524	93	53	after	after	ADP
fcis-7524	93	54	the	the	DET
fcis-7524	93	55	quantum	quantum	ADJ
fcis-7524	93	56	forward	forward	ADV
fcis-7524	93	57	propagation	propagation	NOUN
fcis-7524	93	58	layer	layer	NOUN
fcis-7524	93	59	amplitude	amplitude	NOUN
fcis-7524	93	60	coding	coding	NOUN
fcis-7524	93	61	,	,	PUNCT
fcis-7524	93	62	linear	linear	ADJ
fcis-7524	93	63	and	and	CCONJ
fcis-7524	93	64	nonlinear	nonlinear	ADJ
fcis-7524	93	65	changes	change	NOUN
fcis-7524	93	66	,	,	PUNCT
fcis-7524	93	67	the	the	DET
fcis-7524	93	68	output	output	NOUN
fcis-7524	93	69	value	value	NOUN
fcis-7524	93	70	is	be	AUX
fcis-7524	93	71	obtained	obtain	VERB
fcis-7524	93	72	,	,	PUNCT
fcis-7524	93	73	and	and	CCONJ
fcis-7524	93	74	its	its	PRON
fcis-7524	93	75	quantum	quantum	NOUN
fcis-7524	93	76	circuit	circuit	NOUN
fcis-7524	93	77	diagram	diagram	NOUN
fcis-7524	93	78	is	be	AUX
fcis-7524	93	79	shown	show	VERB
fcis-7524	93	80	in	in	ADP
fcis-7524	93	81	figure	figure	NOUN
fcis-7524	93	82	2	2	NUM
fcis-7524	93	83	.	.	PUNCT
fcis-7524	93	84	figure	figure	NOUN
fcis-7524	93	85	2	2	NUM
fcis-7524	93	86	.	.	PUNCT
fcis-7524	93	87	quantum	quantum	ADJ
fcis-7524	93	88	forward	forward	ADJ
fcis-7524	93	89	propagation	propagation	NOUN
fcis-7524	93	90	layer	layer	NOUN
fcis-7524	93	91	diagram	diagram	NOUN
fcis-7524	93	92	figure	figure	NOUN
fcis-7524	93	93	2	2	NUM
fcis-7524	93	94	mainly	mainly	ADV
fcis-7524	93	95	consists	consist	VERB
fcis-7524	93	96	of	of	ADP
fcis-7524	93	97	two	two	NUM
fcis-7524	93	98	parts	part	NOUN
fcis-7524	93	99	xu	xu	PROPN
fcis-7524	93	100	andu	andu	NOUN
fcis-7524	93	101	(	(	PUNCT
fcis-7524	93	102	)	)	PUNCT
fcis-7524	93	103			X
fcis-7524	93	104	:	:	PUNCT
fcis-7524	93	105	after	after	ADP
fcis-7524	93	106	the	the	DET
fcis-7524	93	107	first	first	ADJ
fcis-7524	93	108	part	part	NOUN
fcis-7524	93	109	of	of	ADP
fcis-7524	93	110	the	the	DET
fcis-7524	93	111	quantum	quantum	ADJ
fcis-7524	93	112	amplitude	amplitude	NOUN
fcis-7524	93	113	encoding	encode	VERB
fcis-7524	93	114	quantum	quantum	ADJ
fcis-7524	93	115	state	state	NOUN
fcis-7524	93	116	as	as	ADP
fcis-7524	93	117	x|	x|	PROPN
fcis-7524	93	118			PROPN
fcis-7524	93	119	,	,	PUNCT
fcis-7524	93	120	where	where	SCONJ
fcis-7524	93	121	the	the	DET
fcis-7524	93	122	data	datum	NOUN
fcis-7524	93	123	of	of	ADP
fcis-7524	93	124	the	the	DET
fcis-7524	93	125	i	i	PROPN
fcis-7524	93	126	-	-	PUNCT
fcis-7524	93	127	th	th	X
fcis-7524	93	128	row	row	NOUN
fcis-7524	93	129	of	of	ADP
fcis-7524	93	130	the	the	DET
fcis-7524	93	131	fuzzy	fuzzy	ADJ
fcis-7524	93	132	autocovariance	autocovariance	NOUN
fcis-7524	93	133	matrix	matrix	NOUN
fcis-7524	93	134	into	into	ADP
fcis-7524	93	135	the	the	DET
fcis-7524	93	136	quantum	quantum	NOUN
fcis-7524	93	137	forward	forward	NOUN
fcis-7524	93	138	propagation	propagation	NOUN
fcis-7524	93	139	layer	layer	NOUN
fcis-7524	93	140	as	as	ADP
fcis-7524	93	141	in	in	ADP
fcis-7524	93	142	eq.(6	eq.(6	NOUN
fcis-7524	93	143	)	)	PUNCT
fcis-7524	93	144	for	for	ADP
fcis-7524	93	145	the	the	DET
fcis-7524	93	146	corresponding	corresponding	ADJ
fcis-7524	93	147	quantum	quantum	NOUN
fcis-7524	93	148	superposition	superposition	NOUN
fcis-7524	93	149	state	state	NOUN
fcis-7524	93	150	to	to	PART
fcis-7524	93	151	transfer	transfer	VERB
fcis-7524	93	152	the	the	DET
fcis-7524	93	153	data	data	NOUN
fcis-7524	93	154	information	information	NOUN
fcis-7524	93	155	to	to	ADP
fcis-7524	93	156	the	the	DET
fcis-7524	93	157	quantum	quantum	ADJ
fcis-7524	93	158	amplitude	amplitude	NOUN
fcis-7524	93	159	.	.	PUNCT
fcis-7524	94	1	2	2	NUM
fcis-7524	94	2	1	1	NUM
fcis-7524	94	3	0	0	NUM
fcis-7524	94	4	=	=	SYM
fcis-7524	94	5	0	0	SYM
fcis-7524	95	1	n	n	NOUN
fcis-7524	96	1	i	i	PRON
fcis-7524	96	2	j	j	PROPN
fcis-7524	96	3	n	n	CCONJ
fcis-7524	96	4	log	log	VERB
fcis-7524	96	5	i	i	PRON
fcis-7524	96	6	x	x	NOUN
fcis-7524	97	1	x	x	VERB
fcis-7524	97	2	jx	jx	PROPN
fcis-7524	97	3	j	j	PROPN
fcis-7524	98	1	|	|	ADV
fcis-7524	98	2	u	u	NOUN
fcis-7524	98	3	|	|	ADV
fcis-7524	98	4	x	x	SYM
fcis-7524	98	5	|	|	NOUN
fcis-7524	98	6	j	j	NUM
fcis-7524	98	7			NOUN
fcis-7524	98	8	−	−	NOUN
fcis-7524	98	9			NOUN
fcis-7524	98	10	=	=	PUNCT
fcis-7524	98	11			VERB
fcis-7524	98	12			PROPN
fcis-7524	98	13	=	=	SYM
fcis-7524	98	14			PROPN
fcis-7524	98	15	(	(	PUNCT
fcis-7524	98	16	6	6	NUM
fcis-7524	98	17	)	)	PUNCT
fcis-7524	98	18	the	the	DET
fcis-7524	98	19	second	second	ADJ
fcis-7524	98	20	part	part	NOUN
fcis-7524	98	21	is	be	AUX
fcis-7524	98	22	the	the	DET
fcis-7524	98	23	quantum	quantum	ADJ
fcis-7524	98	24	forward	forward	ADJ
fcis-7524	98	25	propagation	propagation	NOUN
fcis-7524	98	26	part	part	NOUN
fcis-7524	98	27	,	,	PUNCT
fcis-7524	98	28	whereu	whereu	NOUN
fcis-7524	98	29	(	(	PUNCT
fcis-7524	98	30	)	)	PUNCT
fcis-7524	98	31			PROPN
fcis-7524	98	32	consists	consist	VERB
fcis-7524	98	33	of	of	ADP
fcis-7524	98	34	n	n	PRON
fcis-7524	98	35	i	i	PRON
fcis-7524	98	36	iu	iu	ADP
fcis-7524	98	37			PROPN
fcis-7524	98	38	（	（	PUNCT
fcis-7524	98	39	）	）	PUNCT
fcis-7524	98	40	and	and	CCONJ
fcis-7524	98	41	the	the	DET
fcis-7524	98	42	expression	expression	NOUN
fcis-7524	98	43	is	be	AUX
fcis-7524	98	44	shown	show	VERB
fcis-7524	98	45	in	in	ADP
fcis-7524	98	46	eq	eq	ADP
fcis-7524	98	47	.	.	PUNCT
fcis-7524	99	1	(	(	PUNCT
fcis-7524	99	2	7	7	NUM
fcis-7524	99	3	)	)	PUNCT
fcis-7524	99	4	.	.	PUNCT
fcis-7524	100	1	1	1	NUM
fcis-7524	100	2	n	n	NOUN
fcis-7524	100	3	i	i	PRON
fcis-7524	101	1	i	i	PRON
fcis-7524	101	2	i	i	VERB
fcis-7524	101	3	u	u	VERB
fcis-7524	101	4	(	(	PUNCT
fcis-7524	101	5	)	)	PUNCT
fcis-7524	101	6	u	u	NOUN
fcis-7524	101	7	(	(	PUNCT
fcis-7524	101	8	)	)	PUNCT
fcis-7524	101	9			X
fcis-7524	101	10			X
fcis-7524	102	1	=	=	PUNCT
fcis-7524	103	1	=	=	SYM
fcis-7524	103	2			X
fcis-7524	103	3	(	(	PUNCT
fcis-7524	103	4	7	7	NUM
fcis-7524	103	5	)	)	PUNCT
fcis-7524	103	6	the	the	DET
fcis-7524	103	7	quantum	quantum	ADJ
fcis-7524	103	8	line	line	NOUN
fcis-7524	103	9	diagram	diagram	NOUN
fcis-7524	103	10	of	of	ADP
fcis-7524	103	11	i	i	PRON
fcis-7524	103	12	iu	iu	ADP
fcis-7524	103	13			PROPN
fcis-7524	103	14	（	（	PUNCT
fcis-7524	103	15	）	）	PUNCT
fcis-7524	104	1	in	in	ADP
fcis-7524	104	2	eq	eq	ADP
fcis-7524	104	3	.	.	PUNCT
fcis-7524	104	4	(	(	PUNCT
fcis-7524	104	5	7	7	X
fcis-7524	104	6	)	)	PUNCT
fcis-7524	104	7	consists	consist	VERB
fcis-7524	104	8	of	of	ADP
fcis-7524	104	9	the	the	DET
fcis-7524	104	10	you	you	PRON
fcis-7524	104	11	matrix	matrix	NOUN
fcis-7524	104	12	g	g	PROPN
fcis-7524	104	13	gate	gate	NOUN
fcis-7524	104	14	(	(	PUNCT
fcis-7524	104	15	as	as	SCONJ
fcis-7524	104	16	shown	show	VERB
fcis-7524	104	17	in	in	ADP
fcis-7524	104	18	eq	eq	ADP
fcis-7524	104	19	.	.	PUNCT
fcis-7524	105	1	(	(	PUNCT
fcis-7524	105	2	8)	8)	NUM
fcis-7524	105	3	)	)	PUNCT
fcis-7524	105	4	and	and	CCONJ
fcis-7524	105	5	the	the	DET
fcis-7524	105	6	control	control	ADJ
fcis-7524	105	7	non	non	ADJ
fcis-7524	105	8	-	-	ADJ
fcis-7524	105	9	gate	gate	ADJ
fcis-7524	105	10	,	,	PUNCT
fcis-7524	105	11	which	which	PRON
fcis-7524	105	12	realize	realize	VERB
fcis-7524	105	13	the	the	DET
fcis-7524	105	14	linear	linear	ADJ
fcis-7524	105	15	and	and	CCONJ
fcis-7524	105	16	nonlinear	nonlinear	ADJ
fcis-7524	105	17	transformations	transformation	NOUN
fcis-7524	105	18	of	of	ADP
fcis-7524	105	19	the	the	DET
fcis-7524	105	20	quantum	quantum	ADJ
fcis-7524	105	21	state	state	NOUN
fcis-7524	105	22	,	,	PUNCT
fcis-7524	105	23	respectively	respectively	ADV
fcis-7524	105	24	,	,	PUNCT
fcis-7524	105	25	and	and	CCONJ
fcis-7524	105	26	each	each	DET
fcis-7524	105	27	i	i	PRON
fcis-7524	105	28	iu	iu	VERB
fcis-7524	105	29	(	(	PUNCT
fcis-7524	105	30	)	)	PUNCT
fcis-7524	105	31			PROPN
fcis-7524	105	32	is	be	AUX
fcis-7524	105	33	located	locate	VERB
fcis-7524	105	34	in	in	ADP
fcis-7524	105	35	a	a	DET
fcis-7524	105	36	quantum	quantum	ADJ
fcis-7524	105	37	line	line	NOUN
fcis-7524	105	38	position	position	NOUN
fcis-7524	105	39	different	different	ADJ
fcis-7524	105	40	from	from	ADP
fcis-7524	105	41	that	that	PRON
fcis-7524	105	42	of	of	ADP
fcis-7524	105	43	1	1	NUM
fcis-7524	105	44	1i	1i	NOUN
fcis-7524	105	45	iu	iu	ADP
fcis-7524	105	46	(	(	PUNCT
fcis-7524	105	47	)	)	PUNCT
fcis-7524	105	48	−	−	X
fcis-7524	106	1	−	−	X
fcis-7524	106	2	where	where	SCONJ
fcis-7524	106	3	i	i	NOUN
fcis-7524	106	4	is	be	AUX
fcis-7524	106	5	a	a	DET
fcis-7524	106	6	parameter	parameter	NOUN
fcis-7524	106	7	that	that	PRON
fcis-7524	106	8	can	can	AUX
fcis-7524	106	9	be	be	AUX
fcis-7524	106	10	tuned	tune	VERB
fcis-7524	106	11	by	by	ADP
fcis-7524	106	12	the	the	DET
fcis-7524	106	13	quantum	quantum	ADJ
fcis-7524	106	14	neural	neural	ADJ
fcis-7524	106	15	network	network	NOUN
fcis-7524	106	16	and	and	CCONJ
fcis-7524	106	17	is	be	AUX
fcis-7524	106	18	also	also	ADV
fcis-7524	106	19	tuned	tune	VERB
fcis-7524	106	20	later	later	ADV
fcis-7524	106	21	in	in	ADP
fcis-7524	106	22	the	the	DET
fcis-7524	106	23	quantum	quantum	ADJ
fcis-7524	106	24	backpropagation	backpropagation	NOUN
fcis-7524	106	25	.	.	PUNCT
fcis-7524	107	1	i	i	PRON
fcis-7524	107	2	i	i	PRON
fcis-7524	108	1	i	i	PRON
fcis-7524	108	2	i	i	PRON
fcis-7524	108	3	cos	cos	VERB
fcis-7524	108	4	(	(	PUNCT
fcis-7524	108	5	)	)	PUNCT
fcis-7524	108	6	sin	sin	NOUN
fcis-7524	108	7	(	(	PUNCT
fcis-7524	108	8	)	)	PUNCT
fcis-7524	108	9	sin	sin	NOUN
fcis-7524	108	10	(	(	PUNCT
fcis-7524	108	11	)	)	PUNCT
fcis-7524	108	12	cos	cos	PROPN
fcis-7524	108	13	(	(	PUNCT
fcis-7524	108	14	)	)	PUNCT
fcis-7524	108	15			PROPN
fcis-7524	109	1			X
fcis-7524	109	2			PROPN
fcis-7524	109	3			PROPN
fcis-7524	109	4			PROPN
fcis-7524	109	5			ADJ
fcis-7524	109	6			NOUN
fcis-7524	109	7			PROPN
fcis-7524	109	8	−	−	PROPN
fcis-7524	109	9			PROPN
fcis-7524	109	10	(	(	PUNCT
fcis-7524	109	11	8)	8)	NUM
fcis-7524	109	12	the	the	DET
fcis-7524	109	13	|	|	NOUN
fcis-7524	109	14	(	(	PUNCT
fcis-7524	109	15	x	x	X
fcis-7524	109	16	)	)	PUNCT
fcis-7524	109	17			ADJ
fcis-7524	109	18			ADJ
fcis-7524	109	19	quantum	quantum	ADJ
fcis-7524	109	20	state	state	NOUN
fcis-7524	109	21	is	be	AUX
fcis-7524	109	22	u	u	NOUN
fcis-7524	109	23	(	(	PUNCT
fcis-7524	109	24	)	)	PUNCT
fcis-7524	109	25	|	|	ADV
fcis-7524	109	26	(	(	PUNCT
fcis-7524	109	27	x	x	X
fcis-7524	109	28	)	)	PUNCT
fcis-7524	109	29			PROPN
fcis-7524	110	1			PROPN
fcis-7524	110	2			PROPN
fcis-7524	110	3	after	after	ADP
fcis-7524	110	4	passing	pass	VERB
fcis-7524	110	5	through	through	ADP
fcis-7524	110	6	the	the	DET
fcis-7524	110	7	quantum	quantum	NOUN
fcis-7524	110	8	forward	forward	ADV
fcis-7524	110	9	propagation	propagation	NOUN
fcis-7524	110	10	layer	layer	NOUN
fcis-7524	110	11	state	state	NOUN
fcis-7524	110	12	.	.	PUNCT
fcis-7524	111	1	the	the	DET
fcis-7524	111	2	probability	probability	NOUN
fcis-7524	111	3	of	of	ADP
fcis-7524	111	4	measuring	measure	VERB
fcis-7524	111	5	at	at	ADP
fcis-7524	111	6	the	the	DET
fcis-7524	111	7	last	last	ADJ
fcis-7524	111	8	quantum	quantum	NOUN
fcis-7524	111	9	bit	bit	NOUN
fcis-7524	111	10	to	to	PART
fcis-7524	111	11	be	be	AUX
fcis-7524	111	12	state	state	NOUN
fcis-7524	111	13	1|	1|	NUM
fcis-7524	111	14			NOUN
fcis-7524	111	15	is	be	AUX
fcis-7524	111	16	added	add	VERB
fcis-7524	111	17	with	with	ADP
fcis-7524	111	18	a	a	DET
fcis-7524	111	19	classical	classical	ADJ
fcis-7524	111	20	bias	bias	NOUN
fcis-7524	111	21	b	b	NOUN
fcis-7524	111	22	term	term	NOUN
fcis-7524	111	23	as	as	ADP
fcis-7524	111	24	the	the	DET
fcis-7524	111	25	output	output	NOUN
fcis-7524	111	26	value	value	NOUN
fcis-7524	111	27	o	o	NOUN
fcis-7524	111	28	(	(	PUNCT
fcis-7524	111	29	x	x	NOUN
fcis-7524	111	30	,	,	PUNCT
fcis-7524	111	31	)	)	PUNCT
fcis-7524	111	32			PROPN
fcis-7524	111	33	,	,	PUNCT
fcis-7524	111	34	whose	whose	DET
fcis-7524	111	35	expression	expression	NOUN
fcis-7524	111	36	is	be	AUX
fcis-7524	111	37	shown	show	VERB
fcis-7524	111	38	in	in	ADP
fcis-7524	111	39	eq	eq	ADP
fcis-7524	111	40	.	.	PUNCT
fcis-7524	112	1	(	(	PUNCT
fcis-7524	112	2	9	9	NUM
fcis-7524	112	3	)	)	PUNCT
fcis-7524	112	4	.	.	PUNCT
fcis-7524	113	1	1	1	NUM
fcis-7524	113	2	1	1	NUM
fcis-7524	113	3	1	1	NUM
fcis-7524	113	4	2	2	NUM
fcis-7524	113	5	|u	|u	ADJ
fcis-7524	113	6	(	(	PUNCT
fcis-7524	113	7	)	)	PUNCT
fcis-7524	113	8	†	†	PROPN
fcis-7524	113	9	n	n	CCONJ
fcis-7524	113	10	o	o	PROPN
fcis-7524	113	11	(	(	PUNCT
fcis-7524	113	12	x	x	NOUN
fcis-7524	113	13	,	,	PUNCT
fcis-7524	113	14	)	)	PUNCT
fcis-7524	114	1	p	p	X
fcis-7524	114	2	(	(	PUNCT
fcis-7524	114	3	r	r	NOUN
fcis-7524	114	4	|	|	ADV
fcis-7524	114	5	)	)	PUNCT
fcis-7524	114	6	(	(	PUNCT
fcis-7524	114	7	(	(	PUNCT
fcis-7524	114	8	x	x	X
fcis-7524	114	9	)	)	PUNCT
fcis-7524	114	10	z	z	NOUN
fcis-7524	114	11	u	u	NOUN
fcis-7524	114	12	(	(	PUNCT
fcis-7524	114	13	)	)	PUNCT
fcis-7524	114	14	|	|	ADV
fcis-7524	114	15	(	(	PUNCT
fcis-7524	114	16	x	x	X
fcis-7524	114	17	)	)	PUNCT
fcis-7524	114	18	)	)	PUNCT
fcis-7524	115	1	b	b	X
fcis-7524	115	2			X
fcis-7524	115	3			PROPN
fcis-7524	115	4			PROPN
fcis-7524	115	5			X
fcis-7524	115	6			PROPN
fcis-7524	115	7	=	=	NOUN
fcis-7524	115	8	=	=	PUNCT
fcis-7524	115	9			NOUN
fcis-7524	115	10	=	=	PUNCT
fcis-7524	116	1	+	+	NUM
fcis-7524	116	2			X
fcis-7524	116	3			NOUN
fcis-7524	116	4	+	+	CCONJ
fcis-7524	116	5	(	(	PUNCT
fcis-7524	116	6	9	9	NUM
fcis-7524	116	7	)	)	SYM
fcis-7524	116	8	3.4	3.4	NUM
fcis-7524	116	9	.	.	PUNCT
fcis-7524	116	10	quantum	quantum	PROPN
fcis-7524	116	11	back	back	NOUN
fcis-7524	116	12	propagation	propagation	NOUN
fcis-7524	116	13	layer	layer	NOUN
fcis-7524	116	14	the	the	DET
fcis-7524	116	15	quantum	quantum	PROPN
fcis-7524	116	16	back	back	NOUN
fcis-7524	116	17	propagation	propagation	NOUN
fcis-7524	116	18	layer	layer	NOUN
fcis-7524	116	19	implements	implement	VERB
fcis-7524	116	20	the	the	DET
fcis-7524	116	21	parameter	parameter	NOUN
fcis-7524	116	22	learning	learn	VERB
fcis-7524	116	23	update	update	NOUN
fcis-7524	116	24	in	in	ADP
fcis-7524	116	25	the	the	DET
fcis-7524	116	26	quantum	quantum	ADJ
fcis-7524	116	27	neural	neural	ADJ
fcis-7524	116	28	network	network	NOUN
fcis-7524	116	29	,	,	PUNCT
fcis-7524	116	30	and	and	CCONJ
fcis-7524	116	31	the	the	DET
fcis-7524	116	32	parameter	parameter	NOUN
fcis-7524	116	33	to	to	PART
fcis-7524	116	34	be	be	AUX
fcis-7524	116	35	adjusted	adjust	VERB
fcis-7524	116	36	is	be	AUX
fcis-7524	116	37	1	1	NUM
fcis-7524	116	38	2	2	NUM
fcis-7524	116	39	n	n	CCONJ
fcis-7524	116	40	,	,	PUNCT
fcis-7524	116	41	,	,	PUNCT
fcis-7524	116	42	...	...	PUNCT
fcis-7524	116	43	,	,	PUNCT
fcis-7524	116	44			PROPN
fcis-7524	116	45			PROPN
fcis-7524	116	46			PROPN
fcis-7524	116	47	in	in	ADP
fcis-7524	116	48	u	u	PROPN
fcis-7524	116	49	(	(	PUNCT
fcis-7524	116	50	)	)	PUNCT
fcis-7524	116	51			PROPN
fcis-7524	116	52	in	in	ADP
fcis-7524	116	53	the	the	DET
fcis-7524	116	54	quantum	quantum	ADJ
fcis-7524	116	55	neural	neural	ADJ
fcis-7524	116	56	network	network	NOUN
fcis-7524	116	57	layer	layer	NOUN
fcis-7524	116	58	.	.	PUNCT
fcis-7524	117	1	this	this	DET
fcis-7524	117	2	model	model	NOUN
fcis-7524	117	3	uses	use	VERB
fcis-7524	117	4	the	the	DET
fcis-7524	117	5	mean	mean	ADJ
fcis-7524	117	6	square	square	ADJ
fcis-7524	117	7	error	error	NOUN
fcis-7524	117	8	as	as	ADP
fcis-7524	117	9	the	the	DET
fcis-7524	117	10	loss	loss	NOUN
fcis-7524	117	11	function	function	NOUN
fcis-7524	117	12	,	,	PUNCT
fcis-7524	117	13	as	as	SCONJ
fcis-7524	117	14	shown	show	VERB
fcis-7524	117	15	in	in	ADP
fcis-7524	117	16	eq	eq	ADP
fcis-7524	117	17	.	.	PUNCT
fcis-7524	118	1	(	(	PUNCT
fcis-7524	118	2	10	10	NUM
fcis-7524	118	3	)	)	PUNCT
fcis-7524	118	4	.	.	PUNCT
fcis-7524	119	1	21	21	NUM
fcis-7524	119	2	2	2	NUM
fcis-7524	119	3	e	e	NOUN
fcis-7524	119	4	(	(	PUNCT
fcis-7524	119	5	x	x	NOUN
fcis-7524	119	6	,	,	PUNCT
fcis-7524	119	7	y	y	PROPN
fcis-7524	119	8	(	(	PUNCT
fcis-7524	119	9	x	x	NOUN
fcis-7524	119	10	)	)	PUNCT
fcis-7524	119	11	)	)	PUNCT
fcis-7524	119	12	(	(	PUNCT
fcis-7524	119	13	o	o	X
fcis-7524	119	14	(	(	PUNCT
fcis-7524	119	15	x	x	NOUN
fcis-7524	119	16	,	,	PUNCT
fcis-7524	119	17	)	)	PUNCT
fcis-7524	119	18	y	y	PROPN
fcis-7524	119	19	(	(	PUNCT
fcis-7524	119	20	x	x	NOUN
fcis-7524	119	21	)	)	PUNCT
fcis-7524	119	22	)	)	PUNCT
fcis-7524	119	23			VERB
fcis-7524	120	1	=	=	NOUN
fcis-7524	120	2	−	−	X
fcis-7524	120	3	(	(	PUNCT
fcis-7524	120	4	10	10	NUM
fcis-7524	120	5	)	)	PUNCT
fcis-7524	120	6	y	y	PROPN
fcis-7524	120	7	(	(	PUNCT
fcis-7524	120	8	x	x	X
fcis-7524	120	9	)	)	PUNCT
fcis-7524	120	10	in	in	ADP
fcis-7524	120	11	eq	eq	ADP
fcis-7524	120	12	.	.	PUNCT
fcis-7524	121	1	(	(	PUNCT
fcis-7524	121	2	10	10	NUM
fcis-7524	121	3	)	)	PUNCT
fcis-7524	121	4	is	be	AUX
fcis-7524	121	5	the	the	DET
fcis-7524	121	6	label	label	NOUN
fcis-7524	121	7	of	of	ADP
fcis-7524	121	8	the	the	DET
fcis-7524	121	9	training	training	NOUN
fcis-7524	121	10	sample	sample	NOUN
fcis-7524	121	11	data	datum	NOUN
fcis-7524	121	12	,	,	PUNCT
fcis-7524	121	13	and	and	CCONJ
fcis-7524	121	14	the	the	DET
fcis-7524	121	15	optimal	optimal	ADJ
fcis-7524	121	16	parameters	parameter	NOUN
fcis-7524	121	17	need	need	VERB
fcis-7524	121	18	to	to	PART
fcis-7524	121	19	be	be	AUX
fcis-7524	121	20	found	find	VERB
fcis-7524	121	21	during	during	ADP
fcis-7524	121	22	the	the	DET
fcis-7524	121	23	training	training	NOUN
fcis-7524	121	24	process	process	NOUN
fcis-7524	121	25	to	to	PART
fcis-7524	121	26	make	make	VERB
fcis-7524	121	27	the	the	DET
fcis-7524	121	28	loss	loss	NOUN
fcis-7524	121	29	function	function	NOUN
fcis-7524	121	30	smaller	small	ADJ
fcis-7524	121	31	.	.	PUNCT
fcis-7524	122	1	this	this	DET
fcis-7524	122	2	model	model	NOUN
fcis-7524	122	3	is	be	AUX
fcis-7524	122	4	optimized	optimize	VERB
fcis-7524	122	5	using	use	VERB
fcis-7524	122	6	the	the	DET
fcis-7524	122	7	gradient	gradient	ADJ
fcis-7524	122	8	descent	descent	NOUN
fcis-7524	122	9	algorithm	algorithm	NOUN
fcis-7524	122	10	,	,	PUNCT
fcis-7524	122	11	and	and	CCONJ
fcis-7524	122	12	the	the	DET
fcis-7524	122	13	formula	formula	NOUN
fcis-7524	122	14	for	for	ADP
fcis-7524	122	15	calculating	calculate	VERB
fcis-7524	122	16	the	the	DET
fcis-7524	122	17	gradient	gradient	ADJ
fcis-7524	122	18	i	i	NOUN
fcis-7524	122	19	is	be	AUX
fcis-7524	122	20	as	as	SCONJ
fcis-7524	122	21	follows	follow	VERB
fcis-7524	122	22	:	:	PUNCT
fcis-7524	122	23	102	102	NUM
fcis-7524	122	24	1	1	NUM
fcis-7524	122	25	u	u	NOUN
fcis-7524	122	26	(	(	PUNCT
fcis-7524	122	27	)	)	PUNCT
fcis-7524	122	28	|	|	ADV
fcis-7524	122	29	u	u	NOUN
fcis-7524	122	30	(	(	PUNCT
fcis-7524	122	31	)	)	PUNCT
fcis-7524	122	32	2	2	NUM
fcis-7524	122	33	u	u	NOUN
fcis-7524	122	34	(	(	PUNCT
fcis-7524	122	35	)	)	PUNCT
fcis-7524	122	36	|u	|u	ADJ
fcis-7524	122	37	(	(	PUNCT
fcis-7524	122	38	)	)	PUNCT
fcis-7524	122	39	i	i	PROPN
fcis-7524	122	40	†	†	PROPN
fcis-7524	122	41	n	n	CCONJ
fcis-7524	122	42	i	i	PROPN
fcis-7524	122	43	†	†	PROPN
fcis-7524	122	44	n	n	CCONJ
fcis-7524	122	45	i	i	NOUN
fcis-7524	122	46	e	e	PROPN
fcis-7524	122	47	(	(	PUNCT
fcis-7524	122	48	x	x	NOUN
fcis-7524	122	49	,	,	PUNCT
fcis-7524	122	50	,	,	PUNCT
fcis-7524	122	51	y	y	PROPN
fcis-7524	122	52	(	(	PUNCT
fcis-7524	122	53	x	x	NOUN
fcis-7524	122	54	)	)	PUNCT
fcis-7524	122	55	)	)	PUNCT
fcis-7524	123	1	(	(	PUNCT
fcis-7524	123	2	o	o	X
fcis-7524	123	3	(	(	PUNCT
fcis-7524	123	4	x	x	NOUN
fcis-7524	123	5	,	,	PUNCT
fcis-7524	123	6	)	)	PUNCT
fcis-7524	123	7	y	y	PROPN
fcis-7524	123	8	(	(	PUNCT
fcis-7524	123	9	x	x	NOUN
fcis-7524	123	10	)	)	PUNCT
fcis-7524	123	11	(	(	PUNCT
fcis-7524	123	12	(	(	PUNCT
fcis-7524	123	13	x	x	X
fcis-7524	123	14	)	)	PUNCT
fcis-7524	123	15	z	z	NOUN
fcis-7524	124	1	|	|	INTJ
fcis-7524	124	2	(	(	PUNCT
fcis-7524	124	3	x	x	X
fcis-7524	124	4	)	)	PUNCT
fcis-7524	124	5	(	(	PUNCT
fcis-7524	124	6	x	x	X
fcis-7524	124	7	)	)	PUNCT
fcis-7524	124	8	z	z	NOUN
fcis-7524	125	1	|	|	NOUN
fcis-7524	125	2	(	(	PUNCT
fcis-7524	125	3	x	x	NOUN
fcis-7524	125	4	)	)	PUNCT
fcis-7524	125	5	)	)	PUNCT
fcis-7524	126	1			X
fcis-7524	127	1			X
fcis-7524	127	2			PROPN
fcis-7524	127	3			PROPN
fcis-7524	127	4			X
fcis-7524	128	1			PROPN
fcis-7524	128	2			PROPN
fcis-7524	128	3			PROPN
fcis-7524	128	4			PROPN
fcis-7524	128	5			PROPN
fcis-7524	128	6			PROPN
fcis-7524	128	7			NOUN
fcis-7524	128	8			PROPN
fcis-7524	128	9			X
fcis-7524	128	10			PROPN
fcis-7524	128	11	=	=	SYM
fcis-7524	128	12			PROPN
fcis-7524	128	13	−	−	PROPN
fcis-7524	128	14			SYM
fcis-7524	128	15			ADJ
fcis-7524	128	16			PROPN
fcis-7524	128	17	+	+	CCONJ
fcis-7524	128	18			NUM
fcis-7524	128	19			PRON
fcis-7524	128	20			ADJ
fcis-7524	128	21	(	(	PUNCT
fcis-7524	128	22	11	11	NUM
fcis-7524	128	23	)	)	PUNCT
fcis-7524	128	24	the	the	DET
fcis-7524	128	25	value	value	NOUN
fcis-7524	128	26	of	of	ADP
fcis-7524	128	27	eq	eq	PROPN
fcis-7524	128	28	.	.	PUNCT
fcis-7524	129	1	(	(	PUNCT
fcis-7524	129	2	12	12	NUM
fcis-7524	129	3	)	)	PUNCT
fcis-7524	129	4	is	be	AUX
fcis-7524	129	5	calculated	calculate	VERB
fcis-7524	129	6	by	by	ADP
fcis-7524	129	7	quantum	quantum	ADJ
fcis-7524	129	8	calculation	calculation	NOUN
fcis-7524	129	9	.	.	PUNCT
fcis-7524	130	1	setting	set	VERB
fcis-7524	130	2	eq	eq	NOUN
fcis-7524	130	3	.	.	PUNCT
fcis-7524	131	1	(	(	PUNCT
fcis-7524	131	2	3	3	NUM
fcis-7524	131	3	-	-	SYM
fcis-7524	131	4	12	12	NUM
fcis-7524	131	5	)	)	PUNCT
fcis-7524	131	6	to	to	ADP
fcis-7524	131	7	i	i	PROPN
fcis-7524	131	8	d	d	PROPN
fcis-7524	131	9	(	(	PUNCT
fcis-7524	131	10	,	,	PUNCT
fcis-7524	131	11	x	x	X
fcis-7524	131	12	)	)	PUNCT
fcis-7524	131	13			NOUN
fcis-7524	131	14	,	,	PUNCT
fcis-7524	131	15	we	we	PRON
fcis-7524	131	16	obtain	obtain	VERB
fcis-7524	131	17	the	the	DET
fcis-7524	131	18	gradient	gradient	NOUN
fcis-7524	131	19	of	of	ADP
fcis-7524	131	20	i	i	NOUN
fcis-7524	131	21	as	as	ADP
fcis-7524	131	22	1	1	NUM
fcis-7524	131	23	2	2	NUM
fcis-7524	131	24	(	(	PUNCT
fcis-7524	131	25	o	o	X
fcis-7524	131	26	(	(	PUNCT
fcis-7524	131	27	x	x	NOUN
fcis-7524	131	28	,	,	PUNCT
fcis-7524	131	29	)	)	PUNCT
fcis-7524	131	30	y	y	PROPN
fcis-7524	131	31	(	(	PUNCT
fcis-7524	131	32	x	x	NOUN
fcis-7524	131	33	)	)	PUNCT
fcis-7524	131	34	)	)	PUNCT
fcis-7524	132	1			X
fcis-7524	133	1	−	−	PROPN
fcis-7524	133	2	i	i	PROPN
fcis-7524	133	3	d	d	PROPN
fcis-7524	133	4	(	(	PUNCT
fcis-7524	133	5	,	,	PUNCT
fcis-7524	133	6	x	x	X
fcis-7524	133	7	)	)	PUNCT
fcis-7524	133	8			X
fcis-7524	133	9	.	.	PUNCT
fcis-7524	134	1	u	u	PROPN
fcis-7524	134	2	(	(	PUNCT
fcis-7524	134	3	)	)	PUNCT
fcis-7524	135	1	|	|	ADV
fcis-7524	135	2	u	u	NOUN
fcis-7524	135	3	(	(	PUNCT
fcis-7524	135	4	)	)	PUNCT
fcis-7524	135	5	u	u	NOUN
fcis-7524	135	6	(	(	PUNCT
fcis-7524	135	7	)	)	PUNCT
fcis-7524	135	8	|u	|u	ADJ
fcis-7524	135	9	(	(	PUNCT
fcis-7524	135	10	)	)	PUNCT
fcis-7524	135	11	†	†	PROPN
fcis-7524	135	12	n	n	CCONJ
fcis-7524	135	13	i	i	PROPN
fcis-7524	135	14	†	†	PROPN
fcis-7524	136	1	n	n	CCONJ
fcis-7524	136	2	i	i	PRON
fcis-7524	136	3	(	(	PUNCT
fcis-7524	136	4	x	x	X
fcis-7524	136	5	)	)	PUNCT
fcis-7524	136	6	z	z	NOUN
fcis-7524	137	1	|	|	INTJ
fcis-7524	137	2	(	(	PUNCT
fcis-7524	137	3	x	x	X
fcis-7524	137	4	)	)	PUNCT
fcis-7524	137	5	(	(	PUNCT
fcis-7524	137	6	x	x	X
fcis-7524	137	7	)	)	PUNCT
fcis-7524	137	8	z	z	NOUN
fcis-7524	138	1	|	|	NOUN
fcis-7524	138	2	(	(	PUNCT
fcis-7524	138	3	x	x	X
fcis-7524	138	4	)	)	PUNCT
fcis-7524	138	5			X
fcis-7524	139	1			ADJ
fcis-7524	139	2			PROPN
fcis-7524	139	3			PROPN
fcis-7524	139	4			PROPN
fcis-7524	139	5			X
fcis-7524	139	6			PROPN
fcis-7524	139	7			PROPN
fcis-7524	139	8			PROPN
fcis-7524	139	9			PROPN
fcis-7524	139	10			CCONJ
fcis-7524	139	11			PROPN
fcis-7524	139	12			PROPN
fcis-7524	139	13	+	+	PROPN
fcis-7524	139	14			X
fcis-7524	139	15			ADJ
fcis-7524	139	16			ADJ
fcis-7524	139	17	(	(	PUNCT
fcis-7524	139	18	12	12	NUM
fcis-7524	139	19	)	)	PUNCT
fcis-7524	139	20	update	update	NOUN
fcis-7524	139	21	the	the	DET
fcis-7524	139	22	parameter	parameter	NOUN
fcis-7524	139	23	i	i	NOUN
fcis-7524	139	24	,	,	PUNCT
fcis-7524	139	25	calculated	calculate	VERB
fcis-7524	139	26	as	as	SCONJ
fcis-7524	139	27	follows	follow	VERB
fcis-7524	139	28	:	:	PUNCT
fcis-7524	140	1	i	i	NOUN
fcis-7524	140	2	1	1	NUM
fcis-7524	140	3	2	2	NUM
fcis-7524	140	4	new	new	ADJ
fcis-7524	140	5	old	old	ADJ
fcis-7524	140	6	(	(	PUNCT
fcis-7524	140	7	(	(	PUNCT
fcis-7524	140	8	x	x	NOUN
fcis-7524	140	9	,	,	PUNCT
fcis-7524	140	10	)	)	PUNCT
fcis-7524	140	11	y	y	PROPN
fcis-7524	140	12	(	(	PUNCT
fcis-7524	140	13	x	x	NOUN
fcis-7524	140	14	)	)	PUNCT
fcis-7524	140	15	)	)	PUNCT
fcis-7524	141	1	d	d	X
fcis-7524	141	2	(	(	PUNCT
fcis-7524	141	3	,	,	PUNCT
fcis-7524	141	4	x	x	X
fcis-7524	141	5	)	)	PUNCT
fcis-7524	141	6			PROPN
fcis-7524	141	7			NOUN
fcis-7524	141	8			X
fcis-7524	141	9			X
fcis-7524	141	10			X
fcis-7524	141	11	=	=	NOUN
fcis-7524	141	12	+	+	CCONJ
fcis-7524	141	13	−	−	PROPN
fcis-7524	141	14	(	(	PUNCT
fcis-7524	141	15	13	13	NUM
fcis-7524	141	16	)	)	PUNCT
fcis-7524	141	17	next	next	ADV
fcis-7524	141	18	,	,	PUNCT
fcis-7524	141	19	the	the	DET
fcis-7524	141	20	quantum	quantum	NOUN
fcis-7524	141	21	gradient	gradient	NOUN
fcis-7524	141	22	calculation	calculation	NOUN
fcis-7524	141	23	algorithm	algorithm	NOUN
fcis-7524	141	24	is	be	AUX
fcis-7524	141	25	used	use	VERB
fcis-7524	141	26	to	to	PART
fcis-7524	141	27	find	find	VERB
fcis-7524	141	28	i	i	PRON
fcis-7524	141	29	d	d	PROPN
fcis-7524	141	30	(	(	PUNCT
fcis-7524	141	31	,	,	PUNCT
fcis-7524	141	32	x	x	X
fcis-7524	141	33	)	)	PUNCT
fcis-7524	141	34			X
fcis-7524	141	35	.	.	PUNCT
fcis-7524	142	1	i	i	PRON
fcis-7524	142	2	iu	iu	ADP
fcis-7524	142	3			PROPN
fcis-7524	142	4	（	（	PUNCT
fcis-7524	142	5	）	）	PUNCT
fcis-7524	142	6	is	be	AUX
fcis-7524	142	7	composed	compose	VERB
fcis-7524	142	8	of	of	ADP
fcis-7524	142	9	a	a	DET
fcis-7524	142	10	your	your	PRON
fcis-7524	142	11	matrix	matrix	NOUN
fcis-7524	142	12	g	g	NOUN
fcis-7524	142	13	gate	gate	NOUN
fcis-7524	142	14	and	and	CCONJ
fcis-7524	142	15	a	a	DET
fcis-7524	142	16	control	control	ADJ
fcis-7524	142	17	non	non	ADJ
fcis-7524	142	18	-	-	ADJ
fcis-7524	142	19	gate	gate	NOUN
fcis-7524	142	20	.	.	PUNCT
fcis-7524	143	1	the	the	DET
fcis-7524	143	2	control	control	ADJ
fcis-7524	143	3	non	non	ADJ
fcis-7524	143	4	-	-	ADJ
fcis-7524	143	5	gate	gate	NOUN
fcis-7524	143	6	has	have	VERB
fcis-7524	143	7	no	no	DET
fcis-7524	143	8	parameters	parameter	NOUN
fcis-7524	143	9	and	and	CCONJ
fcis-7524	143	10	can	can	AUX
fcis-7524	143	11	be	be	AUX
fcis-7524	143	12	viewed	view	VERB
fcis-7524	143	13	as	as	ADP
fcis-7524	143	14	a	a	DET
fcis-7524	143	15	constant	constant	ADJ
fcis-7524	143	16	,	,	PUNCT
fcis-7524	143	17	so	so	SCONJ
fcis-7524	143	18	the	the	DET
fcis-7524	143	19	derivative	derivative	NOUN
fcis-7524	143	20	of	of	ADP
fcis-7524	143	21	i	i	PRON
fcis-7524	143	22	iu	iu	ADP
fcis-7524	143	23			PROPN
fcis-7524	143	24	（	（	PUNCT
fcis-7524	143	25	）	）	PUNCT
fcis-7524	143	26	is	be	AUX
fcis-7524	143	27	equivalent	equivalent	ADJ
fcis-7524	143	28	to	to	ADP
fcis-7524	143	29	the	the	DET
fcis-7524	143	30	derivative	derivative	NOUN
fcis-7524	143	31	of	of	ADP
fcis-7524	143	32	the	the	DET
fcis-7524	143	33	g	g	PROPN
fcis-7524	143	34	gate	gate	NOUN
fcis-7524	143	35	,	,	PUNCT
fcis-7524	143	36	and	and	CCONJ
fcis-7524	143	37	the	the	DET
fcis-7524	143	38	derivative	derivative	NOUN
fcis-7524	143	39	of	of	ADP
fcis-7524	143	40	the	the	DET
fcis-7524	143	41	g	g	PROPN
fcis-7524	143	42	gate	gate	NOUN
fcis-7524	143	43	is	be	AUX
fcis-7524	143	44	shown	show	VERB
fcis-7524	143	45	in	in	ADP
fcis-7524	143	46	eq	eq	ADP
fcis-7524	143	47	.	.	PUNCT
fcis-7524	144	1	(	(	PUNCT
fcis-7524	144	2	14	14	NUM
fcis-7524	144	3	):	):	SYM
fcis-7524	144	4	2	2	NUM
fcis-7524	145	1	i	i	NUM
fcis-7524	145	2	ii	ii	NOUN
fcis-7524	146	1	i	i	NOUN
fcis-7524	146	2	ii	ii	VERB
fcis-7524	146	3	sin	sin	NOUN
fcis-7524	146	4	(	(	PUNCT
fcis-7524	146	5	)	)	PUNCT
fcis-7524	146	6	cos	cos	PROPN
fcis-7524	146	7	(	(	PUNCT
fcis-7524	146	8	)	)	PUNCT
fcis-7524	146	9	g	g	NOUN
fcis-7524	146	10	(	(	PUNCT
fcis-7524	146	11	)	)	PUNCT
fcis-7524	146	12	g	g	NOUN
fcis-7524	146	13	(	(	PUNCT
fcis-7524	146	14	)	)	PUNCT
fcis-7524	146	15	cos	cos	PROPN
fcis-7524	146	16	(	(	PUNCT
fcis-7524	146	17	)	)	PUNCT
fcis-7524	146	18	sin	sin	NOUN
fcis-7524	146	19	(	(	PUNCT
fcis-7524	146	20	)	)	PUNCT
fcis-7524	146	21			PROPN
fcis-7524	146	22			PROPN
fcis-7524	147	1			ADJ
fcis-7524	147	2			PROPN
fcis-7524	148	1	+	+	CCONJ
fcis-7524	148	2			X
fcis-7524	148	3			NOUN
fcis-7524	149	1	−	−	PRON
fcis-7524	149	2			VERB
fcis-7524	149	3	=	=	SYM
fcis-7524	150	1	=	=	SYM
fcis-7524	150	2			NOUN
fcis-7524	150	3			NOUN
fcis-7524	150	4	−	−	NOUN
fcis-7524	150	5	−	−	NOUN
fcis-7524	150	6			NOUN
fcis-7524	150	7			PROPN
fcis-7524	150	8	(	(	PUNCT
fcis-7524	150	9	14	14	NUM
fcis-7524	150	10	)	)	PUNCT
fcis-7524	150	11	the	the	DET
fcis-7524	150	12	partial	partial	ADJ
fcis-7524	150	13	derivative	derivative	NOUN
fcis-7524	150	14	of	of	ADP
fcis-7524	150	15	i	i	NOUN
fcis-7524	150	16	for	for	ADP
fcis-7524	150	17	u	u	NOUN
fcis-7524	150	18	(	(	PUNCT
fcis-7524	150	19	)	)	PUNCT
fcis-7524	150	20			PROPN
fcis-7524	150	21	is	be	AUX
fcis-7524	150	22	given	give	VERB
fcis-7524	150	23	by	by	ADP
fcis-7524	150	24	1	1	NUM
fcis-7524	150	25	1	1	NUM
fcis-7524	150	26	1	1	NUM
fcis-7524	150	27	1	1	NUM
fcis-7524	150	28	2	2	NUM
fcis-7524	150	29	n	n	CCONJ
fcis-7524	150	30	n	n	CCONJ
fcis-7524	150	31	n	n	CCONJ
fcis-7524	150	32	n	n	NOUN
fcis-7524	150	33	i	i	PRON
fcis-7524	151	1	i	i	PRON
fcis-7524	151	2	u	u	VERB
fcis-7524	151	3	(	(	PUNCT
fcis-7524	151	4	)	)	PUNCT
fcis-7524	151	5	u	u	NOUN
fcis-7524	151	6	(	(	PUNCT
fcis-7524	151	7	)	)	PUNCT
fcis-7524	151	8	u	u	NOUN
fcis-7524	151	9	(	(	PUNCT
fcis-7524	151	10	)	)	PUNCT
fcis-7524	151	11	...	...	PUNCT
fcis-7524	151	12	u	u	NOUN
fcis-7524	151	13	(	(	PUNCT
fcis-7524	151	14	)	)	PUNCT
fcis-7524	151	15	...	...	PUNCT
fcis-7524	151	16	u	u	NOUN
fcis-7524	151	17	(	(	PUNCT
fcis-7524	151	18	)	)	PUNCT
fcis-7524	151	19			PROPN
fcis-7524	152	1			PROPN
fcis-7524	152	2			X
fcis-7524	152	3			X
fcis-7524	152	4			PROPN
fcis-7524	152	5			PROPN
fcis-7524	152	6			PROPN
fcis-7524	152	7	−	−	PROPN
fcis-7524	153	1	−=	−=	PROPN
fcis-7524	153	2	+	+	CCONJ
fcis-7524	153	3			ADJ
fcis-7524	153	4	(	(	PUNCT
fcis-7524	153	5	15	15	NUM
fcis-7524	153	6	)	)	PUNCT
fcis-7524	153	7	3.5	3.5	NUM
fcis-7524	153	8	.	.	PUNCT
fcis-7524	153	9	quantum	quantum	PROPN
fcis-7524	153	10	gradient	gradient	NOUN
fcis-7524	153	11	calculation	calculation	NOUN
fcis-7524	153	12	algorithm	algorithm	NOUN
fcis-7524	153	13	the	the	DET
fcis-7524	153	14	line	line	NOUN
fcis-7524	153	15	of	of	ADP
fcis-7524	153	16	the	the	DET
fcis-7524	153	17	quantum	quantum	NOUN
fcis-7524	153	18	gradient	gradient	NOUN
fcis-7524	153	19	calculation	calculation	NOUN
fcis-7524	153	20	algorithm	algorithm	NOUN
fcis-7524	153	21	is	be	AUX
fcis-7524	153	22	shown	show	VERB
fcis-7524	153	23	in	in	ADP
fcis-7524	153	24	figure	figure	NOUN
fcis-7524	153	25	3	3	NUM
fcis-7524	153	26	,	,	PUNCT
fcis-7524	153	27	where	where	SCONJ
fcis-7524	153	28	the	the	DET
fcis-7524	153	29	first	first	ADJ
fcis-7524	153	30	initial	initial	ADJ
fcis-7524	153	31	value	value	NOUN
fcis-7524	153	32	is	be	AUX
fcis-7524	153	33	the	the	DET
fcis-7524	153	34	auxiliary	auxiliary	ADJ
fcis-7524	153	35	quantum	quantum	ADJ
fcis-7524	153	36	bit	bit	NOUN
fcis-7524	153	37	0	0	NUM
fcis-7524	153	38	c|	c|	VERB
fcis-7524	153	39			NOUN
fcis-7524	153	40	and	and	CCONJ
fcis-7524	153	41	the	the	DET
fcis-7524	153	42	remaining	remain	VERB
fcis-7524	153	43	quantum	quantum	NOUN
fcis-7524	153	44	bits	bit	NOUN
fcis-7524	153	45	have	have	VERB
fcis-7524	153	46	the	the	DET
fcis-7524	153	47	initial	initial	ADJ
fcis-7524	153	48	value	value	NOUN
fcis-7524	153	49	0|	0|	NUM
fcis-7524	153	50			PROPN
fcis-7524	153	51	.	.	PUNCT
fcis-7524	154	1	figure	figure	VERB
fcis-7524	154	2	3	3	NUM
fcis-7524	154	3	.	.	PUNCT
fcis-7524	154	4	quantum	quantum	NOUN
fcis-7524	154	5	gradient	gradient	NOUN
fcis-7524	154	6	calculation	calculation	NOUN
fcis-7524	154	7	algorithm	algorithm	NOUN
fcis-7524	154	8	diagram	diagram	NOUN
fcis-7524	154	9	after	after	ADP
fcis-7524	154	10	a	a	DET
fcis-7524	154	11	series	series	NOUN
fcis-7524	154	12	of	of	ADP
fcis-7524	154	13	changes	change	NOUN
fcis-7524	154	14	,	,	PUNCT
fcis-7524	154	15	the	the	DET
fcis-7524	154	16	auxiliary	auxiliary	ADJ
fcis-7524	154	17	quantum	quantum	NOUN
fcis-7524	154	18	bits	bit	NOUN
fcis-7524	154	19	are	be	AUX
fcis-7524	154	20	measured	measure	VERB
fcis-7524	154	21	and	and	CCONJ
fcis-7524	154	22	the	the	DET
fcis-7524	154	23	probability	probability	NOUN
fcis-7524	154	24	result	result	NOUN
fcis-7524	154	25	of	of	ADP
fcis-7524	154	26	measuring	measure	VERB
fcis-7524	154	27	as	as	ADP
fcis-7524	154	28	1|	1|	NUM
fcis-7524	154	29			PROPN
fcis-7524	154	30	state	state	NOUN
fcis-7524	154	31	is	be	AUX
fcis-7524	154	32	1	1	NUM
fcis-7524	154	33	1	1	NUM
fcis-7524	154	34	u	u	NOUN
fcis-7524	154	35	(	(	PUNCT
fcis-7524	154	36	)	)	PUNCT
fcis-7524	154	37	1	1	NUM
fcis-7524	155	1	|	|	ADV
fcis-7524	155	2	u	u	NOUN
fcis-7524	155	3	(	(	PUNCT
fcis-7524	155	4	)	)	PUNCT
fcis-7524	155	5	2	2	NUM
fcis-7524	155	6	4	4	NUM
fcis-7524	155	7	u	u	NOUN
fcis-7524	155	8	(	(	PUNCT
fcis-7524	155	9	)	)	PUNCT
fcis-7524	155	10	|u	|u	ADJ
fcis-7524	155	11	(	(	PUNCT
fcis-7524	155	12	)	)	PUNCT
fcis-7524	155	13	†	†	PROPN
fcis-7524	155	14	n	n	CCONJ
fcis-7524	155	15	i	i	PROPN
fcis-7524	155	16	†	†	PROPN
fcis-7524	155	17	n	n	CCONJ
fcis-7524	156	1	i	i	PRON
fcis-7524	156	2	p	p	X
fcis-7524	156	3	(	(	PUNCT
fcis-7524	156	4	r	r	NOUN
fcis-7524	156	5	|	|	ADV
fcis-7524	156	6	)	)	PUNCT
fcis-7524	156	7	(	(	PUNCT
fcis-7524	156	8	(	(	PUNCT
fcis-7524	156	9	x	x	X
fcis-7524	156	10	)	)	PUNCT
fcis-7524	156	11	z	z	NOUN
fcis-7524	157	1	|	|	INTJ
fcis-7524	157	2	(	(	PUNCT
fcis-7524	157	3	x	x	X
fcis-7524	157	4	)	)	PUNCT
fcis-7524	157	5	(	(	PUNCT
fcis-7524	157	6	x	x	X
fcis-7524	157	7	)	)	PUNCT
fcis-7524	157	8	z	z	NOUN
fcis-7524	158	1	|	|	NOUN
fcis-7524	158	2	(	(	PUNCT
fcis-7524	158	3	x	x	NOUN
fcis-7524	158	4	)	)	PUNCT
fcis-7524	158	5	)	)	PUNCT
fcis-7524	159	1			X
fcis-7524	160	1			ADJ
fcis-7524	160	2			PROPN
fcis-7524	160	3			PROPN
fcis-7524	160	4			PROPN
fcis-7524	160	5			PROPN
fcis-7524	160	6			PROPN
fcis-7524	160	7			PROPN
fcis-7524	160	8			PROPN
fcis-7524	160	9			X
fcis-7524	160	10	=	=	PUNCT
fcis-7524	160	11			PROPN
fcis-7524	160	12	=	=	PUNCT
fcis-7524	160	13	−	−	PROPN
fcis-7524	160	14			ADP
fcis-7524	160	15			ADJ
fcis-7524	160	16			PROPN
fcis-7524	160	17	+	+	CCONJ
fcis-7524	160	18			NUM
fcis-7524	160	19			PRON
fcis-7524	160	20			ADJ
fcis-7524	160	21	(	(	PUNCT
fcis-7524	160	22	16	16	NUM
fcis-7524	160	23	)	)	PUNCT
fcis-7524	160	24	4	4	NUM
fcis-7524	160	25	.	.	PUNCT
fcis-7524	160	26	simulation	simulation	NOUN
fcis-7524	160	27	experiments	experiment	NOUN
fcis-7524	160	28	and	and	CCONJ
fcis-7524	160	29	analysis	analysis	NOUN
fcis-7524	160	30	this	this	DET
fcis-7524	160	31	subsection	subsection	NOUN
fcis-7524	160	32	is	be	AUX
fcis-7524	160	33	based	base	VERB
fcis-7524	160	34	on	on	ADP
fcis-7524	160	35	ibm	ibm	PROPN
fcis-7524	160	36	quantum	quantum	ADJ
fcis-7524	160	37	platform	platform	NOUN
fcis-7524	160	38	for	for	ADP
fcis-7524	160	39	simulation	simulation	NOUN
fcis-7524	160	40	experiments	experiment	NOUN
fcis-7524	160	41	and	and	CCONJ
fcis-7524	160	42	analysis	analysis	NOUN
fcis-7524	160	43	.	.	PUNCT
fcis-7524	161	1	firstly	firstly	ADV
fcis-7524	161	2	,	,	PUNCT
fcis-7524	161	3	the	the	DET
fcis-7524	161	4	caner	caner	NOUN
fcis-7524	161	5	dataset	dataset	NOUN
fcis-7524	161	6	and	and	CCONJ
fcis-7524	161	7	evaluation	evaluation	NOUN
fcis-7524	161	8	metrics	metric	NOUN
fcis-7524	161	9	are	be	AUX
fcis-7524	161	10	introduced	introduce	VERB
fcis-7524	161	11	,	,	PUNCT
fcis-7524	161	12	then	then	ADV
fcis-7524	161	13	,	,	PUNCT
fcis-7524	161	14	finally	finally	ADV
fcis-7524	161	15	,	,	PUNCT
fcis-7524	161	16	the	the	DET
fcis-7524	161	17	fuzzy	fuzzy	ADJ
fcis-7524	161	18	quantum	quantum	ADJ
fcis-7524	161	19	sub	sub	NOUN
fcis-7524	161	20	neural	neural	ADJ
fcis-7524	161	21	network	network	NOUN
fcis-7524	161	22	model	model	NOUN
fcis-7524	161	23	experiments	experiment	NOUN
fcis-7524	161	24	and	and	CCONJ
fcis-7524	161	25	analysis	analysis	NOUN
fcis-7524	161	26	are	be	AUX
fcis-7524	161	27	performed	perform	VERB
fcis-7524	161	28	.	.	PUNCT
fcis-7524	162	1	4.1	4.1	NUM
fcis-7524	162	2	.	.	PUNCT
fcis-7524	162	3	breast	breast	NOUN
fcis-7524	162	4	cancer	cancer	NOUN
fcis-7524	162	5	dataset	dataset	PROPN
fcis-7524	162	6	breast	breast	NOUN
fcis-7524	162	7	cancer	cancer	NOUN
fcis-7524	162	8	is	be	AUX
fcis-7524	162	9	one	one	NUM
fcis-7524	162	10	of	of	ADP
fcis-7524	162	11	the	the	DET
fcis-7524	162	12	most	most	ADV
fcis-7524	162	13	common	common	ADJ
fcis-7524	162	14	types	type	NOUN
fcis-7524	162	15	of	of	ADP
fcis-7524	162	16	cancer	cancer	NOUN
fcis-7524	162	17	and	and	CCONJ
fcis-7524	162	18	is	be	AUX
fcis-7524	162	19	an	an	DET
fcis-7524	162	20	abnormal	abnormal	ADJ
fcis-7524	162	21	growth	growth	NOUN
fcis-7524	162	22	of	of	ADP
fcis-7524	162	23	malignant	malignant	ADJ
fcis-7524	162	24	cells	cell	NOUN
fcis-7524	162	25	in	in	ADP
fcis-7524	162	26	the	the	DET
fcis-7524	162	27	breast	breast	NOUN
fcis-7524	162	28	tissue	tissue	NOUN
fcis-7524	162	29	.	.	PUNCT
fcis-7524	163	1	breast	breast	NOUN
fcis-7524	163	2	cancer	cancer	NOUN
fcis-7524	163	3	can	can	AUX
fcis-7524	163	4	occur	occur	VERB
fcis-7524	163	5	in	in	ADP
fcis-7524	163	6	both	both	DET
fcis-7524	163	7	women	woman	NOUN
fcis-7524	163	8	and	and	CCONJ
fcis-7524	163	9	men	man	NOUN
fcis-7524	163	10	,	,	PUNCT
fcis-7524	163	11	but	but	CCONJ
fcis-7524	163	12	women	woman	NOUN
fcis-7524	163	13	are	be	AUX
fcis-7524	163	14	much	much	ADV
fcis-7524	163	15	more	more	ADV
fcis-7524	163	16	likely	likely	ADJ
fcis-7524	163	17	to	to	PART
fcis-7524	163	18	develop	develop	VERB
fcis-7524	163	19	it.the	it.the	PROPN
fcis-7524	163	20	breast	breast	NOUN
fcis-7524	163	21	cancer	cancer	NOUN
fcis-7524	163	22	dataset	dataset	NOUN
fcis-7524	163	23	is	be	AUX
fcis-7524	163	24	a	a	DET
fcis-7524	163	25	commonly	commonly	ADV
fcis-7524	163	26	used	use	VERB
fcis-7524	163	27	medical	medical	ADJ
fcis-7524	163	28	dataset	dataset	NOUN
fcis-7524	163	29	for	for	ADP
fcis-7524	163	30	the	the	DET
fcis-7524	163	31	diagnosis	diagnosis	NOUN
fcis-7524	163	32	and	and	CCONJ
fcis-7524	163	33	prediction	prediction	NOUN
fcis-7524	163	34	of	of	ADP
fcis-7524	163	35	breast	breast	NOUN
fcis-7524	163	36	cancer	cancer	NOUN
fcis-7524	163	37	.	.	PUNCT
fcis-7524	164	1	the	the	DET
fcis-7524	164	2	dataset	dataset	NOUN
fcis-7524	164	3	contains	contain	VERB
fcis-7524	164	4	digitized	digitize	VERB
fcis-7524	164	5	images	image	NOUN
fcis-7524	164	6	sampled	sample	VERB
fcis-7524	164	7	from	from	ADP
fcis-7524	164	8	breast	breast	NOUN
fcis-7524	164	9	tissue	tissue	NOUN
fcis-7524	164	10	and	and	CCONJ
fcis-7524	164	11	its	its	PRON
fcis-7524	164	12	associated	associated	ADJ
fcis-7524	164	13	clinical	clinical	ADJ
fcis-7524	164	14	data	datum	NOUN
fcis-7524	164	15	.	.	PUNCT
fcis-7524	165	1	originally	originally	ADV
fcis-7524	165	2	collected	collect	VERB
fcis-7524	165	3	by	by	ADP
fcis-7524	165	4	the	the	DET
fcis-7524	165	5	university	university	PROPN
fcis-7524	165	6	of	of	ADP
fcis-7524	165	7	wisconsin	wisconsin	PROPN
fcis-7524	165	8	medical	medical	PROPN
fcis-7524	165	9	physics	physics	PROPN
fcis-7524	165	10	laboratory	laboratory	PROPN
fcis-7524	165	11	,	,	PUNCT
fcis-7524	165	12	the	the	DET
fcis-7524	165	13	dataset	dataset	NOUN
fcis-7524	165	14	has	have	AUX
fcis-7524	165	15	become	become	VERB
fcis-7524	165	16	one	one	NUM
fcis-7524	165	17	of	of	ADP
fcis-7524	165	18	the	the	DET
fcis-7524	165	19	standard	standard	ADJ
fcis-7524	165	20	datasets	dataset	NOUN
fcis-7524	165	21	in	in	ADP
fcis-7524	165	22	the	the	DET
fcis-7524	165	23	uci	uci	PROPN
fcis-7524	165	24	machine	machine	NOUN
fcis-7524	165	25	learning	learn	VERB
fcis-7524	165	26	warehouse	warehouse	NOUN
fcis-7524	165	27	.	.	PUNCT
fcis-7524	166	1	the	the	DET
fcis-7524	166	2	dataset	dataset	NOUN
fcis-7524	166	3	contains	contain	VERB
fcis-7524	166	4	569	569	NUM
fcis-7524	166	5	samples	sample	NOUN
fcis-7524	166	6	,	,	PUNCT
fcis-7524	166	7	each	each	PRON
fcis-7524	166	8	with	with	ADP
fcis-7524	166	9	30	30	NUM
fcis-7524	166	10	features	feature	NOUN
fcis-7524	166	11	,	,	PUNCT
fcis-7524	166	12	including	include	VERB
fcis-7524	166	13	characteristics	characteristic	NOUN
fcis-7524	166	14	such	such	ADJ
fcis-7524	166	15	as	as	ADP
fcis-7524	166	16	size	size	NOUN
fcis-7524	166	17	,	,	PUNCT
fcis-7524	166	18	shape	shape	NOUN
fcis-7524	166	19	,	,	PUNCT
fcis-7524	166	20	and	and	CCONJ
fcis-7524	166	21	texture	texture	NOUN
fcis-7524	166	22	of	of	ADP
fcis-7524	166	23	breast	breast	NOUN
fcis-7524	166	24	tissue	tissue	NOUN
fcis-7524	166	25	nuclei	nucleus	NOUN
fcis-7524	166	26	,	,	PUNCT
fcis-7524	166	27	as	as	ADV
fcis-7524	166	28	well	well	ADV
fcis-7524	166	29	as	as	ADP
fcis-7524	166	30	clinical	clinical	ADJ
fcis-7524	166	31	information	information	NOUN
fcis-7524	166	32	such	such	ADJ
fcis-7524	166	33	as	as	ADP
fcis-7524	166	34	the	the	DET
fcis-7524	166	35	patient	patient	NOUN
fcis-7524	166	36	's	's	PART
fcis-7524	166	37	age	age	NOUN
fcis-7524	166	38	,	,	PUNCT
fcis-7524	166	39	gender	gender	NOUN
fcis-7524	166	40	,	,	PUNCT
fcis-7524	166	41	and	and	CCONJ
fcis-7524	166	42	tumor	tumor	NOUN
fcis-7524	166	43	size	size	NOUN
fcis-7524	166	44	.	.	PUNCT
fcis-7524	167	1	each	each	DET
fcis-7524	167	2	sample	sample	NOUN
fcis-7524	167	3	was	be	AUX
fcis-7524	167	4	labeled	label	VERB
fcis-7524	167	5	as	as	ADP
fcis-7524	167	6	benign	benign	ADJ
fcis-7524	167	7	or	or	CCONJ
fcis-7524	167	8	malignant	malignant	ADJ
fcis-7524	167	9	,	,	PUNCT
fcis-7524	167	10	with	with	ADP
fcis-7524	167	11	357	357	NUM
fcis-7524	167	12	benign	benign	ADJ
fcis-7524	167	13	samples	sample	NOUN
fcis-7524	167	14	and	and	CCONJ
fcis-7524	167	15	212	212	NUM
fcis-7524	167	16	malignant	malignant	ADJ
fcis-7524	167	17	samples	sample	NOUN
fcis-7524	167	18	.	.	PUNCT
fcis-7524	168	1	the	the	DET
fcis-7524	168	2	breast	breast	NOUN
fcis-7524	168	3	cancer	cancer	NOUN
fcis-7524	168	4	dataset	dataset	NOUN
fcis-7524	168	5	is	be	AUX
fcis-7524	168	6	a	a	DET
fcis-7524	168	7	classical	classical	ADJ
fcis-7524	168	8	dataset	dataset	NOUN
fcis-7524	168	9	for	for	ADP
fcis-7524	168	10	classification	classification	NOUN
fcis-7524	168	11	and	and	CCONJ
fcis-7524	168	12	regression	regression	NOUN
fcis-7524	168	13	problems	problem	NOUN
fcis-7524	168	14	and	and	CCONJ
fcis-7524	168	15	is	be	AUX
fcis-7524	168	16	commonly	commonly	ADV
fcis-7524	168	17	used	use	VERB
fcis-7524	168	18	for	for	ADP
fcis-7524	168	19	machine	machine	NOUN
fcis-7524	168	20	learning	learning	NOUN
fcis-7524	168	21	and	and	CCONJ
fcis-7524	168	22	deep	deep	ADJ
fcis-7524	168	23	learning	learning	NOUN
fcis-7524	168	24	exercises	exercise	NOUN
fcis-7524	168	25	and	and	CCONJ
fcis-7524	168	26	studies	study	NOUN
fcis-7524	168	27	.	.	PUNCT
fcis-7524	169	1	some	some	PRON
fcis-7524	169	2	of	of	ADP
fcis-7524	169	3	the	the	DET
fcis-7524	169	4	data	datum	NOUN
fcis-7524	169	5	are	be	AUX
fcis-7524	169	6	shown	show	VERB
fcis-7524	169	7	in	in	ADP
fcis-7524	169	8	table	table	NOUN
fcis-7524	169	9	1	1	NUM
fcis-7524	169	10	.	.	PUNCT
fcis-7524	169	11	table	table	NOUN
fcis-7524	169	12	1	1	NUM
fcis-7524	169	13	.	.	PUNCT
fcis-7524	169	14	breast	breast	NOUN
fcis-7524	169	15	cancer	cancer	NOUN
fcis-7524	169	16	data	datum	NOUN
fcis-7524	169	17	set	set	VERB
fcis-7524	169	18	diagno	diagno	NOUN
fcis-7524	169	19	si	si	PROPN
fcis-7524	169	20	radius_mea	radius_mea	PROPN
fcis-7524	169	21	n	n	ADP
fcis-7524	169	22	texture_mea	texture_mea	NUM
fcis-7524	169	23	n	n	NOUN
fcis-7524	169	24	...	...	PUNCT
fcis-7524	169	25	concavity_me	concavity_me	PROPN
fcis-7524	169	26	an	an	DET
fcis-7524	169	27	m	m	PROPN
fcis-7524	169	28	17.99	17.99	NUM
fcis-7524	169	29	10.38	10.38	NUM
fcis-7524	169	30	...	...	PUNCT
fcis-7524	170	1	0.4601	0.4601	NUM
fcis-7524	170	2	m	m	NUM
fcis-7524	170	3	20.57	20.57	NUM
fcis-7524	170	4	17.77	17.77	NUM
fcis-7524	170	5	...	...	PUNCT
fcis-7524	171	1	0.275	0.275	NUM
fcis-7524	171	2	m	m	NOUN
fcis-7524	171	3	19.69	19.69	NUM
fcis-7524	171	4	21.25	21.25	NUM
fcis-7524	171	5	...	...	PUNCT
fcis-7524	172	1	0.3613	0.3613	NUM
fcis-7524	172	2	m	m	NUM
fcis-7524	172	3	11.42	11.42	NUM
fcis-7524	172	4	20.38	20.38	NUM
fcis-7524	172	5	...	...	PUNCT
fcis-7524	173	1	0.6638	0.6638	NUM
fcis-7524	173	2	m	m	NOUN
fcis-7524	173	3	20.29	20.29	NUM
fcis-7524	173	4	14.34	14.34	NUM
fcis-7524	173	5	...	...	PUNCT
fcis-7524	174	1	0.2364	0.2364	NUM
fcis-7524	174	2	m	m	PROPN
fcis-7524	174	3	12.45	12.45	NUM
fcis-7524	174	4	15.7	15.7	NUM
fcis-7524	174	5	...	...	PUNCT
fcis-7524	175	1	0.3985	0.3985	NUM
fcis-7524	175	2	m	m	NUM
fcis-7524	175	3	18.25	18.25	NUM
fcis-7524	175	4	19.98	19.98	NUM
fcis-7524	175	5	...	...	PUNCT
fcis-7524	176	1	0.3063	0.3063	NUM
fcis-7524	176	2	…	…	PUNCT
fcis-7524	176	3	…	…	PUNCT
fcis-7524	176	4	…	…	PUNCT
fcis-7524	176	5	…	…	PUNCT
fcis-7524	176	6	…	…	PUNCT
fcis-7524	176	7	m	m	VERB
fcis-7524	176	8	19.81	19.81	NUM
fcis-7524	176	9	22.15	22.15	NUM
fcis-7524	176	10	...	...	PUNCT
fcis-7524	177	1	0.2768	0.2768	NUM
fcis-7524	177	2	b	b	NOUN
fcis-7524	177	3	13.54	13.54	NUM
fcis-7524	177	4	14.36	14.36	NUM
fcis-7524	177	5	...	...	PUNCT
fcis-7524	178	1	0.2977	0.2977	NUM
fcis-7524	178	2	b	b	NOUN
fcis-7524	178	3	13.08	13.08	NUM
fcis-7524	178	4	15.71	15.71	NUM
fcis-7524	178	5	...	...	PUNCT
fcis-7524	179	1	0.3184	0.3184	NUM
fcis-7524	179	2	b	b	X
fcis-7524	179	3	9.504	9.504	NUM
fcis-7524	179	4	12.44	12.44	NUM
fcis-7524	179	5	...	...	PUNCT
fcis-7524	179	6	0.245	0.245	NUM
fcis-7524	179	7	m	m	NUM
fcis-7524	179	8	15.34	15.34	NUM
fcis-7524	179	9	14.26	14.26	NUM
fcis-7524	179	10	...	...	PUNCT
fcis-7524	179	11	0.4667	0.4667	NUM
fcis-7524	179	12	m	m	NOUN
fcis-7524	179	13	21.16	21.16	NUM
fcis-7524	179	14	23.04	23.04	NUM
fcis-7524	179	15	...	...	PUNCT
fcis-7524	179	16	0.2822	0.2822	NUM
fcis-7524	179	17	4.2	4.2	NUM
fcis-7524	179	18	.	.	PUNCT
fcis-7524	179	19	evaluation	evaluation	NOUN
fcis-7524	179	20	indicators	indicator	NOUN
fcis-7524	179	21	evaluation	evaluation	NOUN
fcis-7524	179	22	metrics	metric	NOUN
fcis-7524	179	23	are	be	AUX
fcis-7524	179	24	a	a	DET
fcis-7524	179	25	quantitative	quantitative	ADJ
fcis-7524	179	26	indicator	indicator	NOUN
fcis-7524	179	27	of	of	ADP
fcis-7524	179	28	model	model	NOUN
fcis-7524	179	29	performance	performance	NOUN
fcis-7524	179	30	.	.	PUNCT
fcis-7524	180	1	one	one	NUM
fcis-7524	180	2	evaluation	evaluation	NOUN
fcis-7524	180	3	metric	metric	NOUN
fcis-7524	180	4	can	can	AUX
fcis-7524	180	5	only	only	ADV
fcis-7524	180	6	reflect	reflect	VERB
fcis-7524	180	7	part	part	NOUN
fcis-7524	180	8	of	of	ADP
fcis-7524	180	9	the	the	DET
fcis-7524	180	10	model	model	NOUN
fcis-7524	180	11	performance	performance	NOUN
fcis-7524	180	12	,	,	PUNCT
fcis-7524	180	13	so	so	CCONJ
fcis-7524	180	14	different	different	ADJ
fcis-7524	180	15	evaluation	evaluation	NOUN
fcis-7524	180	16	metrics	metric	NOUN
fcis-7524	180	17	should	should	AUX
fcis-7524	180	18	be	be	AUX
fcis-7524	180	19	selected	select	VERB
fcis-7524	180	20	for	for	ADP
fcis-7524	180	21	specific	specific	ADJ
fcis-7524	180	22	data	datum	NOUN
fcis-7524	180	23	and	and	CCONJ
fcis-7524	180	24	models	model	NOUN
fcis-7524	180	25	.	.	PUNCT
fcis-7524	181	1	in	in	ADP
fcis-7524	181	2	this	this	DET
fcis-7524	181	3	paper	paper	NOUN
fcis-7524	181	4	,	,	PUNCT
fcis-7524	181	5	we	we	PRON
fcis-7524	181	6	use	use	VERB
fcis-7524	181	7	the	the	DET
fcis-7524	181	8	most	most	ADV
fcis-7524	181	9	commonly	commonly	ADV
fcis-7524	181	10	used	use	VERB
fcis-7524	181	11	evaluation	evaluation	NOUN
fcis-7524	181	12	metrics	metric	NOUN
fcis-7524	181	13	in	in	ADP
fcis-7524	181	14	classification	classification	NOUN
fcis-7524	181	15	problems	problem	NOUN
fcis-7524	181	16	to	to	PART
fcis-7524	181	17	demonstrate	demonstrate	VERB
fcis-7524	181	18	the	the	DET
fcis-7524	181	19	classification	classification	NOUN
fcis-7524	181	20	accuracy	accuracy	NOUN
fcis-7524	181	21	performance	performance	NOUN
fcis-7524	181	22	of	of	ADP
fcis-7524	181	23	the	the	DET
fcis-7524	181	24	proposed	propose	VERB
fcis-7524	181	25	algorithm	algorithm	NOUN
fcis-7524	181	26	model	model	NOUN
fcis-7524	181	27	.	.	PUNCT
fcis-7524	182	1	table	table	NOUN
fcis-7524	182	2	2	2	NUM
fcis-7524	182	3	shows	show	VERB
fcis-7524	182	4	the	the	DET
fcis-7524	182	5	evaluation	evaluation	NOUN
fcis-7524	182	6	metrics	metric	NOUN
fcis-7524	182	7	,	,	PUNCT
fcis-7524	182	8	and	and	CCONJ
fcis-7524	182	9	the	the	PRON
fcis-7524	182	10	higher	high	ADJ
fcis-7524	182	11	the	the	DET
fcis-7524	182	12	value	value	NOUN
fcis-7524	182	13	of	of	ADP
fcis-7524	182	14	the	the	DET
fcis-7524	182	15	metric	metric	NOUN
fcis-7524	182	16	,	,	PUNCT
fcis-7524	182	17	the	the	PRON
fcis-7524	182	18	better	well	ADJ
fcis-7524	182	19	the	the	DET
fcis-7524	182	20	classification	classification	NOUN
fcis-7524	182	21	accuracy	accuracy	NOUN
fcis-7524	182	22	of	of	ADP
fcis-7524	182	23	the	the	DET
fcis-7524	182	24	model	model	NOUN
fcis-7524	182	25	.	.	PUNCT
fcis-7524	183	1	for	for	ADP
fcis-7524	183	2	the	the	DET
fcis-7524	183	3	evaluation	evaluation	NOUN
fcis-7524	183	4	of	of	ADP
fcis-7524	183	5	the	the	DET
fcis-7524	183	6	classification	classification	NOUN
fcis-7524	183	7	efficiency	efficiency	NOUN
fcis-7524	183	8	performance	performance	NOUN
fcis-7524	183	9	of	of	ADP
fcis-7524	183	10	the	the	DET
fcis-7524	183	11	algorithm	algorithm	NOUN
fcis-7524	183	12	model	model	NOUN
fcis-7524	183	13	,	,	PUNCT
fcis-7524	183	14	the	the	DET
fcis-7524	183	15	loss	loss	NOUN
fcis-7524	183	16	function	function	NOUN
fcis-7524	183	17	value	value	NOUN
fcis-7524	183	18	of	of	ADP
fcis-7524	183	19	the	the	DET
fcis-7524	183	20	training	training	NOUN
fcis-7524	183	21	and	and	CCONJ
fcis-7524	183	22	the	the	DET
fcis-7524	183	23	accuracy	accuracy	NOUN
fcis-7524	183	24	of	of	ADP
fcis-7524	183	25	the	the	DET
fcis-7524	183	26	test	test	NOUN
fcis-7524	183	27	prediction	prediction	NOUN
fcis-7524	183	28	are	be	AUX
fcis-7524	183	29	used	use	VERB
fcis-7524	183	30	.	.	PUNCT
fcis-7524	184	1	table	table	NOUN
fcis-7524	184	2	2	2	NUM
fcis-7524	184	3	.	.	PUNCT
fcis-7524	184	4	evaluation	evaluation	NOUN
fcis-7524	184	5	indicators	indicator	NOUN
fcis-7524	184	6	metric	metric	ADJ
fcis-7524	184	7	definition	definition	NOUN
fcis-7524	184	8	recall	recall	VERB
fcis-7524	184	9	tp	tp	ADP
fcis-7524	184	10	tp	tp	ADP
fcis-7524	184	11	fn+	fn+	PROPN
fcis-7524	184	12	precision	precision	NOUN
fcis-7524	184	13	tp	tp	NOUN
fcis-7524	184	14	tp	tp	PROPN
fcis-7524	184	15	fp+	fp+	PROPN
fcis-7524	184	16	f1	f1	PROPN
fcis-7524	184	17	-	-	PUNCT
fcis-7524	184	18	score	score	NOUN
fcis-7524	184	19	r	r	NOUN
fcis-7524	184	20	2	2	NUM
fcis-7524	184	21	re	re	NOUN
fcis-7524	184	22	e	e	NOUN
fcis-7524	184	23	call	call	VERB
fcis-7524	184	24	precision	precision	NOUN
fcis-7524	184	25	call	call	NOUN
fcis-7524	185	1	precision+	precision+	NOUN
fcis-7524	185	2			NOUN
fcis-7524	185	3			PROPN
fcis-7524	185	4	accuracy	accuracy	NOUN
fcis-7524	185	5	tp	tp	ADP
fcis-7524	185	6	tn	tn	PROPN
fcis-7524	185	7	tp	tp	ADP
fcis-7524	185	8	fp	fp	PROPN
fcis-7524	185	9	tn	tn	PROPN
fcis-7524	185	10	fn	fn	NOUN
fcis-7524	186	1	+	+	CCONJ
fcis-7524	187	1	+	+	PUNCT
fcis-7524	187	2	+	+	PUNCT
fcis-7524	187	3	+	+	NUM
fcis-7524	187	4	103	103	NUM
fcis-7524	187	5	4.3	4.3	NUM
fcis-7524	187	6	.	.	PUNCT
fcis-7524	187	7	experiment	experiment	NOUN
fcis-7524	187	8	and	and	CCONJ
fcis-7524	187	9	analysis	analysis	NOUN
fcis-7524	187	10	of	of	ADP
fcis-7524	187	11	quantum	quantum	ADJ
fcis-7524	187	12	neural	neural	ADJ
fcis-7524	187	13	network	network	NOUN
fcis-7524	187	14	model	model	NOUN
fcis-7524	187	15	based	base	VERB
fcis-7524	187	16	on	on	ADP
fcis-7524	187	17	fuzzy	fuzzy	ADJ
fcis-7524	187	18	number	number	NOUN
fcis-7524	187	19	4.3.1	4.3.1	NUM
fcis-7524	187	20	.	.	PUNCT
fcis-7524	188	1	data	datum	NOUN
fcis-7524	188	2	pre	pre	ADJ
fcis-7524	188	3	-	-	ADJ
fcis-7524	188	4	processing	processing	ADJ
fcis-7524	188	5	use	use	NOUN
fcis-7524	188	6	correlation	correlation	NOUN
fcis-7524	188	7	coefficient	coefficient	NOUN
fcis-7524	188	8	corr	corr	NOUN
fcis-7524	188	9	to	to	PART
fcis-7524	188	10	calculate	calculate	VERB
fcis-7524	188	11	the	the	DET
fcis-7524	188	12	correlation	correlation	NOUN
fcis-7524	188	13	coefficient	coefficient	NOUN
fcis-7524	188	14	of	of	ADP
fcis-7524	188	15	each	each	DET
fcis-7524	188	16	feature	feature	NOUN
fcis-7524	188	17	and	and	CCONJ
fcis-7524	188	18	other	other	ADJ
fcis-7524	188	19	features	feature	NOUN
fcis-7524	188	20	,	,	PUNCT
fcis-7524	188	21	and	and	CCONJ
fcis-7524	188	22	then	then	ADV
fcis-7524	188	23	make	make	VERB
fcis-7524	188	24	feature	feature	NOUN
fcis-7524	188	25	selection	selection	NOUN
fcis-7524	188	26	according	accord	VERB
fcis-7524	188	27	to	to	ADP
fcis-7524	188	28	the	the	DET
fcis-7524	188	29	correlation	correlation	NOUN
fcis-7524	188	30	coefficient	coefficient	NOUN
fcis-7524	188	31	.	.	PUNCT
fcis-7524	189	1	for	for	ADP
fcis-7524	189	2	display	display	NOUN
fcis-7524	189	3	convenience	convenience	NOUN
fcis-7524	189	4	,	,	PUNCT
fcis-7524	189	5	the	the	DET
fcis-7524	189	6	correlation	correlation	NOUN
fcis-7524	189	7	coefficient	coefficient	NOUN
fcis-7524	189	8	of	of	ADP
fcis-7524	189	9	features	feature	NOUN
fcis-7524	189	10	is	be	AUX
fcis-7524	189	11	displayed	display	VERB
fcis-7524	189	12	using	use	VERB
fcis-7524	189	13	a	a	DET
fcis-7524	189	14	heat	heat	NOUN
fcis-7524	189	15	map	map	NOUN
fcis-7524	189	16	,	,	PUNCT
fcis-7524	189	17	and	and	CCONJ
fcis-7524	189	18	the	the	DET
fcis-7524	189	19	diagonal	diagonal	NOUN
fcis-7524	189	20	of	of	ADP
fcis-7524	189	21	the	the	DET
fcis-7524	189	22	heat	heat	NOUN
fcis-7524	189	23	map	map	NOUN
fcis-7524	189	24	is	be	AUX
fcis-7524	189	25	the	the	DET
fcis-7524	189	26	correlation	correlation	NOUN
fcis-7524	189	27	coefficient	coefficient	NOUN
fcis-7524	189	28	of	of	ADP
fcis-7524	189	29	the	the	DET
fcis-7524	189	30	univariate	univariate	ADJ
fcis-7524	189	31	itself	itself	PRON
fcis-7524	189	32	is	be	AUX
fcis-7524	189	33	1	1	NUM
fcis-7524	189	34	.	.	PUNCT
fcis-7524	190	1	the	the	PRON
fcis-7524	190	2	lighter	light	ADJ
fcis-7524	190	3	the	the	DET
fcis-7524	190	4	color	color	NOUN
fcis-7524	190	5	represents	represent	VERB
fcis-7524	190	6	the	the	DET
fcis-7524	190	7	greater	great	ADJ
fcis-7524	190	8	the	the	DET
fcis-7524	190	9	correlation	correlation	NOUN
fcis-7524	190	10	.	.	PUNCT
fcis-7524	191	1	as	as	SCONJ
fcis-7524	191	2	shown	show	VERB
fcis-7524	191	3	in	in	ADP
fcis-7524	191	4	figure	figure	NOUN
fcis-7524	191	5	4	4	NUM
fcis-7524	191	6	.	.	PUNCT
fcis-7524	191	7	figure	figure	VERB
fcis-7524	191	8	4	4	NUM
fcis-7524	191	9	.	.	PUNCT
fcis-7524	191	10	heat	heat	NOUN
fcis-7524	191	11	map	map	NOUN
fcis-7524	191	12	of	of	ADP
fcis-7524	191	13	breast	breast	NOUN
fcis-7524	191	14	cancer	cancer	NOUN
fcis-7524	191	15	dataset	dataset	VERB
fcis-7524	191	16	the	the	DET
fcis-7524	191	17	purpose	purpose	NOUN
fcis-7524	191	18	of	of	ADP
fcis-7524	191	19	feature	feature	NOUN
fcis-7524	191	20	selection	selection	NOUN
fcis-7524	191	21	is	be	AUX
fcis-7524	191	22	to	to	PART
fcis-7524	191	23	reduce	reduce	VERB
fcis-7524	191	24	the	the	DET
fcis-7524	191	25	dimensionality	dimensionality	NOUN
fcis-7524	191	26	and	and	CCONJ
fcis-7524	191	27	use	use	VERB
fcis-7524	191	28	a	a	DET
fcis-7524	191	29	small	small	ADJ
fcis-7524	191	30	number	number	NOUN
fcis-7524	191	31	of	of	ADP
fcis-7524	191	32	features	feature	NOUN
fcis-7524	191	33	to	to	PART
fcis-7524	191	34	represent	represent	VERB
fcis-7524	191	35	the	the	DET
fcis-7524	191	36	characteristics	characteristic	NOUN
fcis-7524	191	37	of	of	ADP
fcis-7524	191	38	the	the	DET
fcis-7524	191	39	data	datum	NOUN
fcis-7524	191	40	,	,	PUNCT
fcis-7524	191	41	which	which	PRON
fcis-7524	191	42	can	can	AUX
fcis-7524	191	43	also	also	ADV
fcis-7524	191	44	enhance	enhance	VERB
fcis-7524	191	45	the	the	DET
fcis-7524	191	46	generalization	generalization	NOUN
fcis-7524	191	47	ability	ability	NOUN
fcis-7524	191	48	of	of	ADP
fcis-7524	191	49	the	the	DET
fcis-7524	191	50	classifier	classifier	NOUN
fcis-7524	191	51	and	and	CCONJ
fcis-7524	191	52	avoid	avoid	VERB
fcis-7524	191	53	overfitting	overfitte	VERB
fcis-7524	191	54	the	the	DET
fcis-7524	191	55	data	datum	NOUN
fcis-7524	191	56	.	.	PUNCT
fcis-7524	192	1	the	the	DET
fcis-7524	192	2	quantum	quantum	PROPN
fcis-7524	192	3	neural	neural	ADJ
fcis-7524	192	4	net	net	NOUN
fcis-7524	192	5	can	can	AUX
fcis-7524	192	6	accept	accept	VERB
fcis-7524	192	7	four	four	NUM
fcis-7524	192	8	parameters	parameter	NOUN
fcis-7524	192	9	,	,	PUNCT
fcis-7524	192	10	according	accord	VERB
fcis-7524	192	11	to	to	ADP
fcis-7524	192	12	which	which	PRON
fcis-7524	192	13	the	the	DET
fcis-7524	192	14	mean	mean	NOUN
fcis-7524	192	15	is	be	AUX
fcis-7524	192	16	selected	select	VERB
fcis-7524	192	17	from	from	ADP
fcis-7524	192	18	mean	mean	VERB
fcis-7524	192	19	,	,	PUNCT
fcis-7524	192	20	se	se	X
fcis-7524	192	21	,	,	PUNCT
fcis-7524	192	22	and	and	CCONJ
fcis-7524	192	23	worst	bad	ADJ
fcis-7524	192	24	,	,	PUNCT
fcis-7524	192	25	and	and	CCONJ
fcis-7524	192	26	then	then	ADV
fcis-7524	192	27	the	the	DET
fcis-7524	192	28	radius	radius	NOUN
fcis-7524	192	29	mean	mean	NOUN
fcis-7524	192	30	,	,	PUNCT
fcis-7524	192	31	perimeter	perimeter	NOUN
fcis-7524	192	32	mean	mean	NOUN
fcis-7524	192	33	,	,	PUNCT
fcis-7524	192	34	compactness	compactness	NOUN
fcis-7524	192	35	mean	mean	NOUN
fcis-7524	192	36	,	,	PUNCT
fcis-7524	192	37	and	and	CCONJ
fcis-7524	192	38	concavity	concavity	NOUN
fcis-7524	192	39	mean	mean	VERB
fcis-7524	192	40	are	be	AUX
fcis-7524	192	41	selected	select	VERB
fcis-7524	192	42	from	from	ADP
fcis-7524	192	43	the	the	DET
fcis-7524	192	44	mean	mean	NOUN
fcis-7524	192	45	.	.	PUNCT
fcis-7524	193	1	4.3.2	4.3.2	X
fcis-7524	193	2	.	.	PUNCT
fcis-7524	193	3	fuzzy	fuzzy	ADJ
fcis-7524	193	4	processing	processing	NOUN
fcis-7524	193	5	in	in	ADP
fcis-7524	193	6	this	this	DET
fcis-7524	193	7	subsection	subsection	NOUN
fcis-7524	193	8	,	,	PUNCT
fcis-7524	193	9	the	the	DET
fcis-7524	193	10	mean	mean	ADJ
fcis-7524	193	11	and	and	CCONJ
fcis-7524	193	12	standard	standard	ADJ
fcis-7524	193	13	deviation	deviation	NOUN
fcis-7524	193	14	of	of	ADP
fcis-7524	193	15	radius	radius	NOUN
fcis-7524	193	16	mean	mean	NOUN
fcis-7524	193	17	,	,	PUNCT
fcis-7524	193	18	perimeter	perimeter	NOUN
fcis-7524	193	19	mean	mean	NOUN
fcis-7524	193	20	,	,	PUNCT
fcis-7524	193	21	compactness	compactness	NOUN
fcis-7524	193	22	mean	mean	NOUN
fcis-7524	193	23	and	and	CCONJ
fcis-7524	193	24	concavity	concavity	NOUN
fcis-7524	193	25	mean	mean	VERB
fcis-7524	193	26	are	be	AUX
fcis-7524	193	27	calculated	calculate	VERB
fcis-7524	193	28	respectively	respectively	ADV
fcis-7524	193	29	to	to	PART
fcis-7524	193	30	support	support	VERB
fcis-7524	193	31	the	the	DET
fcis-7524	193	32	calculation	calculation	NOUN
fcis-7524	193	33	of	of	ADP
fcis-7524	193	34	gaussian	gaussian	ADJ
fcis-7524	193	35	fuzzy	fuzzy	ADJ
fcis-7524	193	36	affiliation	affiliation	NOUN
fcis-7524	193	37	.	.	PUNCT
fcis-7524	194	1	the	the	DET
fcis-7524	194	2	results	result	NOUN
fcis-7524	194	3	are	be	AUX
fcis-7524	194	4	shown	show	VERB
fcis-7524	194	5	in	in	ADP
fcis-7524	194	6	tables	table	NOUN
fcis-7524	194	7	3	3	NUM
fcis-7524	194	8	.	.	PUNCT
fcis-7524	195	1	the	the	DET
fcis-7524	195	2	gaussian	gaussian	ADJ
fcis-7524	195	3	fuzzy	fuzzy	ADJ
fcis-7524	195	4	affiliation	affiliation	NOUN
fcis-7524	195	5	function	function	NOUN
fcis-7524	195	6	is	be	AUX
fcis-7524	195	7	used	use	VERB
fcis-7524	195	8	to	to	PART
fcis-7524	195	9	calculate	calculate	VERB
fcis-7524	195	10	each	each	DET
fcis-7524	195	11	fuzzy	fuzzy	ADJ
fcis-7524	195	12	affiliation	affiliation	NOUN
fcis-7524	195	13	degree	degree	NOUN
fcis-7524	195	14	,	,	PUNCT
fcis-7524	195	15	as	as	SCONJ
fcis-7524	195	16	shown	show	VERB
fcis-7524	195	17	in	in	ADP
fcis-7524	195	18	table	table	NOUN
fcis-7524	195	19	4	4	NUM
fcis-7524	195	20	.	.	PUNCT
fcis-7524	196	1	the	the	DET
fcis-7524	196	2	values	value	NOUN
fcis-7524	196	3	of	of	ADP
fcis-7524	196	4	the	the	DET
fcis-7524	196	5	variable	variable	ADJ
fcis-7524	196	6	matrix	matrix	NOUN
fcis-7524	196	7	and	and	CCONJ
fcis-7524	196	8	the	the	DET
fcis-7524	196	9	fuzzy	fuzzy	ADJ
fcis-7524	196	10	affiliation	affiliation	NOUN
fcis-7524	196	11	matrix	matrix	NOUN
fcis-7524	196	12	are	be	AUX
fcis-7524	196	13	multiplied	multiply	VERB
fcis-7524	196	14	correspondingly	correspondingly	ADV
fcis-7524	196	15	to	to	PART
fcis-7524	196	16	generate	generate	VERB
fcis-7524	196	17	the	the	DET
fcis-7524	196	18	fuzzy	fuzzy	ADJ
fcis-7524	196	19	independent	independent	ADJ
fcis-7524	196	20	variable	variable	ADJ
fcis-7524	196	21	matrix	matrix	NOUN
fcis-7524	196	22	.	.	PUNCT
fcis-7524	197	1	finally	finally	ADV
fcis-7524	197	2	,	,	PUNCT
fcis-7524	197	3	the	the	DET
fcis-7524	197	4	fuzzy	fuzzy	ADJ
fcis-7524	197	5	independent	independent	ADJ
fcis-7524	197	6	variables	variable	NOUN
fcis-7524	197	7	are	be	AUX
fcis-7524	197	8	normalized	normalize	VERB
fcis-7524	197	9	to	to	PART
fcis-7524	197	10	facilitate	facilitate	VERB
fcis-7524	197	11	the	the	DET
fcis-7524	197	12	next	next	ADJ
fcis-7524	197	13	quantum	quantum	ADJ
fcis-7524	197	14	neural	neural	ADJ
fcis-7524	197	15	network	network	NOUN
fcis-7524	197	16	operation	operation	NOUN
fcis-7524	197	17	.	.	PUNCT
fcis-7524	198	1	the	the	DET
fcis-7524	198	2	fuzzy	fuzzy	ADJ
fcis-7524	198	3	autocovariance	autocovariance	NOUN
fcis-7524	198	4	matrix	matrix	NOUN
fcis-7524	198	5	was	be	AUX
fcis-7524	198	6	first	first	ADV
fcis-7524	198	7	randomly	randomly	ADV
fcis-7524	198	8	divided	divide	VERB
fcis-7524	198	9	into	into	ADP
fcis-7524	198	10	75	75	NUM
fcis-7524	198	11	%	%	NOUN
fcis-7524	198	12	training	training	NOUN
fcis-7524	198	13	set	set	NOUN
fcis-7524	198	14	and	and	CCONJ
fcis-7524	198	15	25	25	NUM
fcis-7524	198	16	%	%	NOUN
fcis-7524	198	17	test	test	NOUN
fcis-7524	198	18	set	set	VERB
fcis-7524	198	19	before	before	ADP
fcis-7524	198	20	the	the	DET
fcis-7524	198	21	experiment	experiment	NOUN
fcis-7524	198	22	.	.	PUNCT
fcis-7524	199	1	table	table	NOUN
fcis-7524	199	2	3	3	NUM
fcis-7524	199	3	.	.	PUNCT
fcis-7524	199	4	evaluation	evaluation	NOUN
fcis-7524	199	5	values	value	NOUN
fcis-7524	199	6	and	and	CCONJ
fcis-7524	199	7	standard	standard	ADJ
fcis-7524	199	8	deviations	deviation	NOUN
fcis-7524	199	9	of	of	ADP
fcis-7524	199	10	the	the	DET
fcis-7524	199	11	data	datum	NOUN
fcis-7524	199	12	set	set	VERB
fcis-7524	200	1	radius	radius	NOUN
fcis-7524	200	2	mean	mean	NOUN
fcis-7524	200	3	texture	texture	NOUN
fcis-7524	200	4	mean	mean	ADJ
fcis-7524	200	5	compactness	compactness	NOUN
fcis-7524	200	6	mean	mean	NOUN
fcis-7524	200	7	concavity	concavity	NOUN
fcis-7524	200	8	mean	mean	VERB
fcis-7524	200	9	evaluation	evaluation	NOUN
fcis-7524	200	10	value	value	NOUN
fcis-7524	200	11	14.1272917	14.1272917	NUM
fcis-7524	200	12	19.28964851	19.28964851	NUM
fcis-7524	200	13	0.09636028	0.09636028	NUM
fcis-7524	200	14	0.10434098	0.10434098	NUM
fcis-7524	200	15	standarddeviations	standarddeviation	NOUN
fcis-7524	200	16	3.52095076	3.52095076	NUM
fcis-7524	200	17	4.29725464	4.29725464	NUM
fcis-7524	200	18	0.01405176	0.01405176	NUM
fcis-7524	200	19	0.05276633	0.05276633	NUM
fcis-7524	200	20	table	table	NOUN
fcis-7524	200	21	4	4	NUM
fcis-7524	200	22	.	.	PUNCT
fcis-7524	200	23	breast	breast	NOUN
fcis-7524	200	24	cancer	cancer	NOUN
fcis-7524	200	25	fuzzy	fuzzy	ADJ
fcis-7524	200	26	affiliation	affiliation	NOUN
fcis-7524	200	27	degree	degree	NOUN
fcis-7524	200	28	radius	radius	NOUN
fcis-7524	200	29	mean	mean	NOUN
fcis-7524	200	30	texture	texture	NOUN
fcis-7524	200	31	mean	mean	ADJ
fcis-7524	200	32	compactness	compactness	NOUN
fcis-7524	200	33	mean	mean	NOUN
fcis-7524	200	34	concavity	concavity	NOUN
fcis-7524	200	35	mean	mean	VERB
fcis-7524	200	36	0.300127054	0.300127054	NUM
fcis-7524	201	1	0.013585964	0.013585964	NUM
fcis-7524	201	2	0.08542755	0.08542755	NUM
fcis-7524	201	3	2.078111231	2.078111231	NUM
fcis-7524	201	4	0.035146036	0.035146036	NUM
fcis-7524	201	5	0.88244759	0.88244759	NUM
fcis-7524	201	6	0.504661744	0.504661744	NUM
fcis-7524	201	7	0.788802888	0.788802888	NUM
fcis-7524	201	8	0.082410168	0.082410168	NUM
fcis-7524	201	9	0.812120513	0.812120513	NUM
fcis-7524	201	10	0.411576441	0.411576441	NUM
fcis-7524	201	11	0.33000344	0.33000344	NUM
fcis-7524	201	12	0.553650592	0.553650592	NUM
fcis-7524	201	13	0.93764864	0.93764864	NUM
fcis-7524	201	14	2.07758e-05	2.07758e-05	NUM
fcis-7524	201	15	9.3532e-06	9.3532e-06	NUM
fcis-7524	201	16	0.046722086	0.046722086	NUM
fcis-7524	201	17	0.265356495	0.265356495	NUM
fcis-7524	201	18	0.924401884	0.924401884	NUM
fcis-7524	201	19	0.747599312	0.747599312	NUM
fcis-7524	201	20	0.79697432	0.79697432	NUM
fcis-7524	201	21	0.497686425	0.497686425	NUM
fcis-7524	201	22	0.006697273	0.006697273	NUM
fcis-7524	201	23	0.21259405	0.21259405	NUM
fcis-7524	201	24	0.25384669	0.25384669	NUM
fcis-7524	201	25	0.974521948	0.974521948	NUM
fcis-7524	201	26	0.984951842	0.984951842	NUM
fcis-7524	201	27	0.992234261	0.992234261	NUM
fcis-7524	201	28	…	…	PUNCT
fcis-7524	201	29	…	…	PUNCT
fcis-7524	201	30	…	…	PUNCT
fcis-7524	201	31	…	…	PUNCT
fcis-7524	201	32	4.3.3	4.3.3	X
fcis-7524	201	33	.	.	PUNCT
fcis-7524	201	34	quantum	quantum	ADJ
fcis-7524	201	35	fuzzy	fuzzy	ADJ
fcis-7524	201	36	neural	neural	ADJ
fcis-7524	201	37	network	network	NOUN
fcis-7524	201	38	experiment	experiment	NOUN
fcis-7524	201	39	and	and	CCONJ
fcis-7524	201	40	analysis	analysis	NOUN
fcis-7524	201	41	in	in	ADP
fcis-7524	201	42	this	this	DET
fcis-7524	201	43	paper	paper	NOUN
fcis-7524	201	44	,	,	PUNCT
fcis-7524	201	45	a	a	DET
fcis-7524	201	46	gaussian	gaussian	ADJ
fcis-7524	201	47	fuzzy	fuzzy	ADJ
fcis-7524	201	48	quantum	quantum	ADJ
fcis-7524	201	49	neural	neural	ADJ
fcis-7524	201	50	network	network	NOUN
fcis-7524	201	51	is	be	AUX
fcis-7524	201	52	designed	design	VERB
fcis-7524	201	53	based	base	VERB
fcis-7524	201	54	on	on	ADP
fcis-7524	201	55	ibm	ibm	PROPN
fcis-7524	201	56	quantum	quantum	ADJ
fcis-7524	201	57	platform	platform	NOUN
fcis-7524	201	58	for	for	ADP
fcis-7524	201	59	validation	validation	NOUN
fcis-7524	201	60	,	,	PUNCT
fcis-7524	201	61	and	and	CCONJ
fcis-7524	201	62	the	the	DET
fcis-7524	201	63	fuzzy	fuzzy	ADJ
fcis-7524	201	64	independent	independent	ADJ
fcis-7524	201	65	variable	variable	ADJ
fcis-7524	201	66	matrices	matrix	NOUN
fcis-7524	201	67	are	be	AUX
fcis-7524	201	68	entered	enter	VERB
fcis-7524	201	69	into	into	ADP
fcis-7524	201	70	the	the	DET
fcis-7524	201	71	quantum	quantum	ADJ
fcis-7524	201	72	neural	neural	ADJ
fcis-7524	201	73	network	network	NOUN
fcis-7524	201	74	sequentially	sequentially	ADV
fcis-7524	201	75	,	,	PUNCT
fcis-7524	201	76	and	and	CCONJ
fcis-7524	201	77	the	the	DET
fcis-7524	201	78	quantum	quantum	ADJ
fcis-7524	201	79	fuzzy	fuzzy	ADJ
fcis-7524	201	80	neural	neural	ADJ
fcis-7524	201	81	network	network	NOUN
fcis-7524	201	82	line	line	NOUN
fcis-7524	201	83	is	be	AUX
fcis-7524	201	84	shown	show	VERB
fcis-7524	201	85	in	in	ADP
fcis-7524	201	86	figure	figure	NOUN
fcis-7524	201	87	5	5	NUM
fcis-7524	201	88	.	.	PUNCT
fcis-7524	201	89	figure	figure	NOUN
fcis-7524	201	90	5	5	NUM
fcis-7524	201	91	.	.	PUNCT
fcis-7524	201	92	quantum	quantum	ADJ
fcis-7524	201	93	fuzzy	fuzzy	ADJ
fcis-7524	201	94	neural	neural	ADJ
fcis-7524	201	95	network	network	NOUN
fcis-7524	201	96	line	line	NOUN
fcis-7524	201	97	diagram	diagram	NOUN
fcis-7524	201	98	figure	figure	NOUN
fcis-7524	201	99	5	5	NUM
fcis-7524	201	100	includes	include	VERB
fcis-7524	201	101	the	the	DET
fcis-7524	201	102	quantum	quantum	ADJ
fcis-7524	201	103	line	line	NOUN
fcis-7524	201	104	of	of	ADP
fcis-7524	201	105	two	two	NUM
fcis-7524	201	106	quantum	quantum	ADJ
fcis-7524	201	107	bits	bit	NOUN
fcis-7524	201	108	and	and	CCONJ
fcis-7524	201	109	the	the	DET
fcis-7524	201	110	classical	classical	ADJ
fcis-7524	201	111	data	data	NOUN
fcis-7524	201	112	line	line	NOUN
fcis-7524	201	113	of	of	ADP
fcis-7524	201	114	one	one	NUM
fcis-7524	201	115	.	.	PUNCT
fcis-7524	202	1	the	the	DET
fcis-7524	202	2	first	first	ADJ
fcis-7524	202	3	part	part	NOUN
fcis-7524	202	4	is	be	AUX
fcis-7524	202	5	the	the	DET
fcis-7524	202	6	quantum	quantum	ADJ
fcis-7524	202	7	amplitude	amplitude	NOUN
fcis-7524	202	8	part	part	NOUN
fcis-7524	202	9	,	,	PUNCT
fcis-7524	202	10	which	which	PRON
fcis-7524	202	11	realizes	realize	VERB
fcis-7524	202	12	the	the	DET
fcis-7524	202	13	assignment	assignment	NOUN
fcis-7524	202	14	of	of	ADP
fcis-7524	202	15	the	the	DET
fcis-7524	202	16	fuzzy	fuzzy	ADJ
fcis-7524	202	17	autocovariance	autocovariance	NOUN
fcis-7524	202	18	matrix	matrix	NOUN
fcis-7524	202	19	to	to	ADP
fcis-7524	202	20	the	the	DET
fcis-7524	202	21	quantum	quantum	ADJ
fcis-7524	202	22	state	state	NOUN
fcis-7524	202	23	;	;	PUNCT
fcis-7524	202	24	the	the	DET
fcis-7524	202	25	second	second	ADJ
fcis-7524	202	26	part	part	NOUN
fcis-7524	202	27	is	be	AUX
fcis-7524	202	28	the	the	DET
fcis-7524	202	29	quantum	quantum	ADJ
fcis-7524	202	30	forward	forward	ADJ
fcis-7524	202	31	propagation	propagation	NOUN
fcis-7524	202	32	part	part	NOUN
fcis-7524	202	33	,	,	PUNCT
fcis-7524	202	34	which	which	PRON
fcis-7524	202	35	has	have	VERB
fcis-7524	202	36	ten	ten	NUM
fcis-7524	202	37	g	g	NOUN
fcis-7524	202	38	gates	gate	NOUN
fcis-7524	202	39	and	and	CCONJ
fcis-7524	202	40	five	five	NUM
fcis-7524	202	41	controlled	control	VERB
fcis-7524	202	42	non	non	NOUN
fcis-7524	202	43	-	-	ADJ
fcis-7524	202	44	gates	gate	NOUN
fcis-7524	202	45	to	to	PART
fcis-7524	202	46	realize	realize	VERB
fcis-7524	202	47	the	the	DET
fcis-7524	202	48	linear	linear	ADJ
fcis-7524	202	49	and	and	CCONJ
fcis-7524	202	50	nonlinear	nonlinear	ADJ
fcis-7524	202	51	variation	variation	NOUN
fcis-7524	202	52	of	of	ADP
fcis-7524	202	53	the	the	DET
fcis-7524	202	54	data	datum	NOUN
fcis-7524	202	55	;	;	PUNCT
fcis-7524	202	56	and	and	CCONJ
fcis-7524	202	57	finally	finally	ADV
fcis-7524	202	58	,	,	PUNCT
fcis-7524	202	59	the	the	DET
fcis-7524	202	60	measurement	measurement	NOUN
fcis-7524	202	61	part	part	NOUN
fcis-7524	202	62	,	,	PUNCT
fcis-7524	202	63	which	which	PRON
fcis-7524	202	64	performs	perform	VERB
fcis-7524	202	65	the	the	DET
fcis-7524	202	66	quantum	quantum	ADJ
fcis-7524	202	67	measurement	measurement	NOUN
fcis-7524	202	68	and	and	CCONJ
fcis-7524	202	69	saves	save	VERB
fcis-7524	202	70	the	the	DET
fcis-7524	202	71	output	output	NOUN
fcis-7524	202	72	value	value	NOUN
fcis-7524	202	73	in	in	ADP
fcis-7524	202	74	the	the	DET
fcis-7524	202	75	classical	classical	ADJ
fcis-7524	202	76	data	data	NOUN
fcis-7524	202	77	line	line	NOUN
fcis-7524	202	78	.	.	PUNCT
fcis-7524	203	1	the	the	DET
fcis-7524	203	2	output	output	NOUN
fcis-7524	203	3	values	value	NOUN
fcis-7524	203	4	are	be	AUX
fcis-7524	203	5	obtained	obtain	VERB
fcis-7524	203	6	and	and	CCONJ
fcis-7524	203	7	the	the	DET
fcis-7524	203	8	loss	loss	NOUN
fcis-7524	203	9	function	function	NOUN
fcis-7524	203	10	is	be	AUX
fcis-7524	203	11	calculated	calculate	VERB
fcis-7524	203	12	with	with	ADP
fcis-7524	203	13	the	the	DET
fcis-7524	203	14	labeled	label	VERB
fcis-7524	203	15	values	value	NOUN
fcis-7524	203	16	of	of	ADP
fcis-7524	203	17	the	the	DET
fcis-7524	203	18	fuzzy	fuzzy	ADJ
fcis-7524	203	19	autocovariance	autocovariance	NOUN
fcis-7524	203	20	matrix	matrix	NOUN
fcis-7524	203	21	.	.	PUNCT
fcis-7524	204	1	using	use	VERB
fcis-7524	204	2	the	the	DET
fcis-7524	204	3	quantum	quantum	ADJ
fcis-7524	204	4	gradient	gradient	NOUN
fcis-7524	204	5	calculation	calculation	NOUN
fcis-7524	204	6	algorithm	algorithm	NOUN
fcis-7524	204	7	to	to	PART
fcis-7524	204	8	quickly	quickly	ADV
fcis-7524	204	9	calculate	calculate	VERB
fcis-7524	204	10	the	the	DET
fcis-7524	204	11	value	value	NOUN
fcis-7524	204	12	of	of	ADP
fcis-7524	204	13	eq	eq	PROPN
fcis-7524	204	14	.	.	PUNCT
fcis-7524	205	1	and	and	CCONJ
fcis-7524	205	2	bring	bring	VERB
fcis-7524	205	3	it	it	PRON
fcis-7524	205	4	into	into	ADP
fcis-7524	205	5	the	the	DET
fcis-7524	205	6	loss	loss	NOUN
fcis-7524	205	7	function	function	NOUN
fcis-7524	205	8	,	,	PUNCT
fcis-7524	205	9	the	the	DET
fcis-7524	205	10	gradient	gradient	NOUN
fcis-7524	205	11	can	can	AUX
fcis-7524	205	12	be	be	AUX
fcis-7524	205	13	calculated	calculate	VERB
fcis-7524	205	14	quickly	quickly	ADV
fcis-7524	205	15	,	,	PUNCT
fcis-7524	205	16	thus	thus	ADV
fcis-7524	205	17	improving	improve	VERB
fcis-7524	205	18	the	the	DET
fcis-7524	205	19	efficiency	efficiency	NOUN
fcis-7524	205	20	of	of	ADP
fcis-7524	205	21	the	the	DET
fcis-7524	205	22	quantum	quantum	ADJ
fcis-7524	205	23	neural	neural	ADJ
fcis-7524	205	24	network	network	NOUN
fcis-7524	205	25	.	.	PUNCT
fcis-7524	206	1	the	the	DET
fcis-7524	206	2	quantum	quantum	PROPN
fcis-7524	206	3	gradient	gradient	NOUN
fcis-7524	206	4	calculation	calculation	NOUN
fcis-7524	206	5	algorithm	algorithm	NOUN
fcis-7524	206	6	is	be	AUX
fcis-7524	206	7	shown	show	VERB
fcis-7524	206	8	in	in	ADP
fcis-7524	206	9	figure	figure	NOUN
fcis-7524	206	10	6	6	NUM
fcis-7524	206	11	.	.	PUNCT
fcis-7524	207	1	figure	figure	VERB
fcis-7524	207	2	6	6	NUM
fcis-7524	207	3	.	.	PUNCT
fcis-7524	207	4	line	line	NOUN
fcis-7524	207	5	diagram	diagram	NOUN
fcis-7524	207	6	of	of	ADP
fcis-7524	207	7	quantum	quantum	NOUN
fcis-7524	207	8	gradient	gradient	NOUN
fcis-7524	207	9	calculation	calculation	NOUN
fcis-7524	207	10	algorithm	algorithm	NOUN
fcis-7524	207	11	figure	figure	NOUN
fcis-7524	207	12	6	6	NUM
fcis-7524	207	13	includes	include	VERB
fcis-7524	207	14	three	three	NUM
fcis-7524	207	15	quantum	quantum	ADJ
fcis-7524	207	16	lines	line	NOUN
fcis-7524	207	17	of	of	ADP
fcis-7524	207	18	quantum	quantum	ADJ
fcis-7524	207	19	bits	bit	NOUN
fcis-7524	207	20	and	and	CCONJ
fcis-7524	207	21	one	one	NUM
fcis-7524	207	22	classical	classical	ADJ
fcis-7524	207	23	data	datum	NOUN
fcis-7524	207	24	line	line	NOUN
fcis-7524	207	25	.	.	PUNCT
fcis-7524	208	1	the	the	DET
fcis-7524	208	2	quantum	quantum	PROPN
fcis-7524	208	3	line	line	NOUN
fcis-7524	208	4	diagram	diagram	NOUN
fcis-7524	208	5	is	be	AUX
fcis-7524	208	6	designed	design	VERB
fcis-7524	208	7	strictly	strictly	ADV
fcis-7524	208	8	according	accord	VERB
fcis-7524	208	9	to	to	PART
fcis-7524	208	10	figure	figure	VERB
fcis-7524	208	11	3	3	NUM
fcis-7524	208	12	,	,	PUNCT
fcis-7524	208	13	and	and	CCONJ
fcis-7524	208	14	the	the	DET
fcis-7524	208	15	partitioned	partition	VERB
fcis-7524	208	16	lines	line	NOUN
fcis-7524	208	17	are	be	AUX
fcis-7524	208	18	given	give	VERB
fcis-7524	208	19	for	for	ADP
fcis-7524	208	20	easy	easy	ADJ
fcis-7524	208	21	viewing	viewing	NOUN
fcis-7524	208	22	,	,	PUNCT
fcis-7524	208	23	and	and	CCONJ
fcis-7524	208	24	the	the	DET
fcis-7524	208	25	final	final	ADJ
fcis-7524	208	26	measurements	measurement	NOUN
fcis-7524	208	27	are	be	AUX
fcis-7524	208	28	made	make	VERB
fcis-7524	208	29	and	and	CCONJ
fcis-7524	208	30	the	the	DET
fcis-7524	208	31	output	output	NOUN
fcis-7524	208	32	values	value	NOUN
fcis-7524	208	33	are	be	AUX
fcis-7524	208	34	stored	store	VERB
fcis-7524	208	35	in	in	ADP
fcis-7524	208	36	the	the	DET
fcis-7524	208	37	classical	classical	ADJ
fcis-7524	208	38	data	data	NOUN
fcis-7524	208	39	line	line	NOUN
fcis-7524	208	40	.	.	PUNCT
fcis-7524	209	1	after	after	SCONJ
fcis-7524	209	2	the	the	DET
fcis-7524	209	3	training	training	NOUN
fcis-7524	209	4	set	set	NOUN
fcis-7524	209	5	is	be	AUX
fcis-7524	209	6	trained	train	VERB
fcis-7524	209	7	,	,	PUNCT
fcis-7524	209	8	the	the	DET
fcis-7524	209	9	test	test	NOUN
fcis-7524	209	10	set	set	NOUN
fcis-7524	209	11	is	be	AUX
fcis-7524	209	12	tested	test	VERB
fcis-7524	209	13	in	in	ADP
fcis-7524	209	14	the	the	DET
fcis-7524	209	15	104	104	NUM
fcis-7524	209	16	gaussian	gaussian	ADJ
fcis-7524	209	17	fuzzy	fuzzy	ADJ
fcis-7524	209	18	quantum	quantum	ADJ
fcis-7524	209	19	neural	neural	ADJ
fcis-7524	209	20	network	network	NOUN
fcis-7524	209	21	.	.	PUNCT
fcis-7524	210	1	we	we	PRON
fcis-7524	210	2	can	can	AUX
fcis-7524	210	3	get	get	VERB
fcis-7524	210	4	is	be	AUX
fcis-7524	210	5	the	the	DET
fcis-7524	210	6	value	value	NOUN
fcis-7524	210	7	of	of	ADP
fcis-7524	210	8	the	the	DET
fcis-7524	210	9	loss	loss	NOUN
fcis-7524	210	10	function	function	NOUN
fcis-7524	210	11	for	for	ADP
fcis-7524	210	12	each	each	DET
fcis-7524	210	13	training	training	NOUN
fcis-7524	210	14	in	in	ADP
fcis-7524	210	15	training	training	NOUN
fcis-7524	210	16	and	and	CCONJ
fcis-7524	210	17	the	the	DET
fcis-7524	210	18	accuracy	accuracy	NOUN
fcis-7524	210	19	of	of	ADP
fcis-7524	210	20	the	the	DET
fcis-7524	210	21	predicted	predict	VERB
fcis-7524	210	22	values	value	NOUN
fcis-7524	210	23	in	in	ADP
fcis-7524	210	24	testing	testing	NOUN
fcis-7524	210	25	.	.	PUNCT
fcis-7524	211	1	to	to	PART
fcis-7524	211	2	illustrate	illustrate	VERB
fcis-7524	211	3	the	the	DET
fcis-7524	211	4	accuracy	accuracy	NOUN
fcis-7524	211	5	and	and	CCONJ
fcis-7524	211	6	efficiency	efficiency	NOUN
fcis-7524	211	7	of	of	ADP
fcis-7524	211	8	the	the	DET
fcis-7524	211	9	quantum	quantum	ADJ
fcis-7524	211	10	fuzzy	fuzzy	ADJ
fcis-7524	211	11	neural	neural	ADJ
fcis-7524	211	12	network	network	NOUN
fcis-7524	211	13	model	model	NOUN
fcis-7524	211	14	,	,	PUNCT
fcis-7524	211	15	we	we	PRON
fcis-7524	211	16	will	will	AUX
fcis-7524	211	17	use	use	VERB
fcis-7524	211	18	the	the	DET
fcis-7524	211	19	same	same	ADJ
fcis-7524	211	20	breast	breast	NOUN
fcis-7524	211	21	cancer	cancer	NOUN
fcis-7524	211	22	dataset	dataset	VERB
fcis-7524	211	23	in	in	ADP
fcis-7524	211	24	the	the	DET
fcis-7524	211	25	traditional	traditional	ADJ
fcis-7524	211	26	quantum	quantum	ADJ
fcis-7524	211	27	neural	neural	ADJ
fcis-7524	211	28	network	network	NOUN
fcis-7524	211	29	model	model	NOUN
fcis-7524	211	30	for	for	ADP
fcis-7524	211	31	training	training	NOUN
fcis-7524	211	32	and	and	CCONJ
fcis-7524	211	33	testing	testing	NOUN
fcis-7524	211	34	,	,	PUNCT
fcis-7524	211	35	and	and	CCONJ
fcis-7524	211	36	also	also	ADV
fcis-7524	211	37	obtained	obtain	VERB
fcis-7524	211	38	the	the	DET
fcis-7524	211	39	loss	loss	NOUN
fcis-7524	211	40	function	function	NOUN
fcis-7524	211	41	values	value	NOUN
fcis-7524	211	42	for	for	ADP
fcis-7524	211	43	each	each	DET
fcis-7524	211	44	training	training	NOUN
fcis-7524	211	45	and	and	CCONJ
fcis-7524	211	46	the	the	DET
fcis-7524	211	47	accuracy	accuracy	NOUN
fcis-7524	211	48	of	of	ADP
fcis-7524	211	49	the	the	DET
fcis-7524	211	50	predicted	predict	VERB
fcis-7524	211	51	values	value	NOUN
fcis-7524	211	52	in	in	ADP
fcis-7524	211	53	the	the	DET
fcis-7524	211	54	test	test	NOUN
fcis-7524	211	55	.	.	PUNCT
fcis-7524	212	1	to	to	PART
fcis-7524	212	2	visualize	visualize	VERB
fcis-7524	212	3	the	the	DET
fcis-7524	212	4	classification	classification	NOUN
fcis-7524	212	5	efficiency	efficiency	NOUN
fcis-7524	212	6	of	of	ADP
fcis-7524	212	7	the	the	DET
fcis-7524	212	8	quantum	quantum	ADJ
fcis-7524	212	9	neural	neural	ADJ
fcis-7524	212	10	network	network	NOUN
fcis-7524	212	11	qnn	qnn	NOUN
fcis-7524	212	12	and	and	CCONJ
fcis-7524	212	13	the	the	DET
fcis-7524	212	14	quantum	quantum	ADJ
fcis-7524	212	15	fuzzy	fuzzy	ADJ
fcis-7524	212	16	neural	neural	ADJ
fcis-7524	212	17	network	network	NOUN
fcis-7524	212	18	fqnn	fqnn	PROPN
fcis-7524	212	19	model	model	NOUN
fcis-7524	212	20	based	base	VERB
fcis-7524	212	21	on	on	ADP
fcis-7524	212	22	fuzzy	fuzzy	ADJ
fcis-7524	212	23	number	number	NOUN
fcis-7524	212	24	,	,	PUNCT
fcis-7524	212	25	the	the	DET
fcis-7524	212	26	loss	loss	NOUN
fcis-7524	212	27	function	function	NOUN
fcis-7524	212	28	values	value	NOUN
fcis-7524	212	29	of	of	ADP
fcis-7524	212	30	the	the	DET
fcis-7524	212	31	two	two	NUM
fcis-7524	212	32	models	model	NOUN
fcis-7524	212	33	at	at	ADP
fcis-7524	212	34	different	different	ADJ
fcis-7524	212	35	number	number	NOUN
fcis-7524	212	36	of	of	ADP
fcis-7524	212	37	iterations	iteration	NOUN
fcis-7524	212	38	are	be	AUX
fcis-7524	212	39	shown	show	VERB
fcis-7524	212	40	in	in	ADP
fcis-7524	212	41	figure	figure	NOUN
fcis-7524	212	42	7	7	NUM
fcis-7524	212	43	.	.	PUNCT
fcis-7524	212	44	figure	figure	NOUN
fcis-7524	212	45	7	7	NUM
fcis-7524	212	46	.	.	PUNCT
fcis-7524	212	47	plot	plot	NOUN
fcis-7524	212	48	of	of	ADP
fcis-7524	212	49	loss	loss	NOUN
fcis-7524	212	50	function	function	NOUN
fcis-7524	212	51	values	value	NOUN
fcis-7524	212	52	for	for	ADP
fcis-7524	212	53	qnn	qnn	NOUN
fcis-7524	212	54	and	and	CCONJ
fcis-7524	212	55	fqnn	fqnn	NOUN
fcis-7524	212	56	with	with	ADP
fcis-7524	212	57	different	different	ADJ
fcis-7524	212	58	number	number	NOUN
fcis-7524	212	59	of	of	ADP
fcis-7524	212	60	iterations	iteration	NOUN
fcis-7524	212	61	figure	figure	NOUN
fcis-7524	212	62	7	7	NUM
fcis-7524	212	63	shows	show	VERB
fcis-7524	212	64	the	the	DET
fcis-7524	212	65	values	value	NOUN
fcis-7524	212	66	of	of	ADP
fcis-7524	212	67	the	the	DET
fcis-7524	212	68	loss	loss	NOUN
fcis-7524	212	69	functions	function	NOUN
fcis-7524	212	70	of	of	ADP
fcis-7524	212	71	the	the	DET
fcis-7524	212	72	qnn	qnn	NOUN
fcis-7524	212	73	and	and	CCONJ
fcis-7524	212	74	fqnn	fqnn	NOUN
fcis-7524	212	75	models	model	NOUN
fcis-7524	212	76	for	for	ADP
fcis-7524	212	77	different	different	ADJ
fcis-7524	212	78	number	number	NOUN
fcis-7524	212	79	of	of	ADP
fcis-7524	212	80	iterations	iteration	NOUN
fcis-7524	212	81	in	in	ADP
fcis-7524	212	82	the	the	DET
fcis-7524	212	83	breast	breast	NOUN
fcis-7524	212	84	cancer	cancer	NOUN
fcis-7524	212	85	dataset	dataset	NOUN
fcis-7524	212	86	,	,	PUNCT
fcis-7524	212	87	where	where	SCONJ
fcis-7524	212	88	qnn	qnn	NOUN
fcis-7524	212	89	and	and	CCONJ
fcis-7524	212	90	fqnn	fqnn	NOUN
fcis-7524	212	91	are	be	AUX
fcis-7524	212	92	shown	show	VERB
fcis-7524	212	93	by	by	ADP
fcis-7524	212	94	the	the	DET
fcis-7524	212	95	green	green	PROPN
fcis-7524	212	96	dashed	dash	VERB
fcis-7524	212	97	line	line	NOUN
fcis-7524	212	98	and	and	CCONJ
fcis-7524	212	99	the	the	DET
fcis-7524	212	100	red	red	ADJ
fcis-7524	212	101	solid	solid	ADJ
fcis-7524	212	102	line	line	NOUN
fcis-7524	212	103	,	,	PUNCT
fcis-7524	212	104	respectively	respectively	ADV
fcis-7524	212	105	.	.	PUNCT
fcis-7524	213	1	by	by	ADP
fcis-7524	213	2	comparing	compare	VERB
fcis-7524	213	3	qnn	qnn	NOUN
fcis-7524	213	4	and	and	CCONJ
fcis-7524	213	5	fqnn	fqnn	NOUN
fcis-7524	213	6	,	,	PUNCT
fcis-7524	213	7	we	we	PRON
fcis-7524	213	8	can	can	AUX
fcis-7524	213	9	get	get	VERB
fcis-7524	213	10	that	that	DET
fcis-7524	213	11	fqnn	fqnn	NOUN
fcis-7524	213	12	has	have	VERB
fcis-7524	213	13	a	a	DET
fcis-7524	213	14	smaller	small	ADJ
fcis-7524	213	15	value	value	NOUN
fcis-7524	213	16	of	of	ADP
fcis-7524	213	17	the	the	DET
fcis-7524	213	18	initial	initial	ADJ
fcis-7524	213	19	loss	loss	NOUN
fcis-7524	213	20	function	function	NOUN
fcis-7524	213	21	compared	compare	VERB
fcis-7524	213	22	with	with	ADP
fcis-7524	213	23	qnn	qnn	NOUN
fcis-7524	213	24	,	,	PUNCT
fcis-7524	213	25	and	and	CCONJ
fcis-7524	213	26	the	the	DET
fcis-7524	213	27	gradient	gradient	NOUN
fcis-7524	213	28	decreases	decrease	VERB
fcis-7524	213	29	faster	fast	ADV
fcis-7524	213	30	when	when	SCONJ
fcis-7524	213	31	the	the	DET
fcis-7524	213	32	number	number	NOUN
fcis-7524	213	33	of	of	ADP
fcis-7524	213	34	iterations	iteration	NOUN
fcis-7524	213	35	increases	increase	NOUN
fcis-7524	213	36	,	,	PUNCT
fcis-7524	213	37	and	and	CCONJ
fcis-7524	213	38	the	the	DET
fcis-7524	213	39	value	value	NOUN
fcis-7524	213	40	of	of	ADP
fcis-7524	213	41	the	the	DET
fcis-7524	213	42	loss	loss	NOUN
fcis-7524	213	43	function	function	NOUN
fcis-7524	213	44	of	of	ADP
fcis-7524	213	45	qnn	qnn	NOUN
fcis-7524	213	46	is	be	AUX
fcis-7524	213	47	around	around	ADV
fcis-7524	213	48	1.9	1.9	NUM
fcis-7524	213	49	after	after	ADP
fcis-7524	213	50	50	50	NUM
fcis-7524	213	51	iterations	iteration	NOUN
fcis-7524	213	52	,	,	PUNCT
fcis-7524	213	53	while	while	SCONJ
fcis-7524	213	54	the	the	DET
fcis-7524	213	55	value	value	NOUN
fcis-7524	213	56	of	of	ADP
fcis-7524	213	57	the	the	DET
fcis-7524	213	58	loss	loss	NOUN
fcis-7524	213	59	function	function	NOUN
fcis-7524	213	60	of	of	ADP
fcis-7524	213	61	qfnn	qfnn	NOUN
fcis-7524	213	62	is	be	AUX
fcis-7524	213	63	around	around	ADV
fcis-7524	213	64	1.0	1.0	NUM
fcis-7524	213	65	after	after	ADP
fcis-7524	213	66	50	50	NUM
fcis-7524	213	67	iterations	iteration	NOUN
fcis-7524	213	68	,	,	PUNCT
fcis-7524	213	69	and	and	CCONJ
fcis-7524	213	70	the	the	DET
fcis-7524	213	71	final	final	ADJ
fcis-7524	213	72	loss	loss	NOUN
fcis-7524	213	73	function	function	NOUN
fcis-7524	213	74	of	of	ADP
fcis-7524	213	75	qfnn	qfnn	NOUN
fcis-7524	213	76	is	be	AUX
fcis-7524	213	77	also	also	ADV
fcis-7524	213	78	smaller	small	ADJ
fcis-7524	213	79	.	.	PUNCT
fcis-7524	214	1	this	this	PRON
fcis-7524	214	2	indicates	indicate	VERB
fcis-7524	214	3	that	that	SCONJ
fcis-7524	214	4	qfnn	qfnn	NOUN
fcis-7524	214	5	has	have	VERB
fcis-7524	214	6	faster	fast	ADJ
fcis-7524	214	7	gradient	gradient	ADJ
fcis-7524	214	8	descent	descent	NOUN
fcis-7524	214	9	speed	speed	NOUN
fcis-7524	214	10	and	and	CCONJ
fcis-7524	214	11	smaller	small	ADJ
fcis-7524	214	12	loss	loss	NOUN
fcis-7524	214	13	function	function	NOUN
fcis-7524	214	14	compared	compare	VERB
fcis-7524	214	15	to	to	ADP
fcis-7524	214	16	qnn	qnn	NOUN
fcis-7524	214	17	.	.	PUNCT
fcis-7524	215	1	it	it	PRON
fcis-7524	215	2	shows	show	VERB
fcis-7524	215	3	that	that	SCONJ
fcis-7524	215	4	qfnn	qfnn	NOUN
fcis-7524	215	5	has	have	VERB
fcis-7524	215	6	better	well	ADJ
fcis-7524	215	7	classification	classification	NOUN
fcis-7524	215	8	efficiency	efficiency	NOUN
fcis-7524	215	9	in	in	ADP
fcis-7524	215	10	the	the	DET
fcis-7524	215	11	same	same	ADJ
fcis-7524	215	12	data	datum	NOUN
fcis-7524	215	13	set	set	VERB
fcis-7524	215	14	.	.	PUNCT
fcis-7524	216	1	the	the	DET
fcis-7524	216	2	accuracy	accuracy	NOUN
fcis-7524	216	3	of	of	ADP
fcis-7524	216	4	qnn	qnn	NOUN
fcis-7524	216	5	and	and	CCONJ
fcis-7524	216	6	fqnn	fqnn	NOUN
fcis-7524	216	7	models	model	NOUN
fcis-7524	216	8	at	at	ADP
fcis-7524	216	9	different	different	ADJ
fcis-7524	216	10	number	number	NOUN
fcis-7524	216	11	of	of	ADP
fcis-7524	216	12	iterations	iteration	NOUN
fcis-7524	216	13	is	be	AUX
fcis-7524	216	14	shown	show	VERB
fcis-7524	216	15	in	in	ADP
fcis-7524	216	16	figure	figure	NOUN
fcis-7524	216	17	8	8	NUM
fcis-7524	216	18	.	.	PUNCT
fcis-7524	217	1	figure	figure	NOUN
fcis-7524	217	2	8	8	NUM
fcis-7524	217	3	.	.	PUNCT
fcis-7524	218	1	shows	show	VERB
fcis-7524	218	2	the	the	DET
fcis-7524	218	3	correctness	correctness	NOUN
fcis-7524	218	4	of	of	ADP
fcis-7524	218	5	qnn	qnn	NOUN
fcis-7524	218	6	and	and	CCONJ
fcis-7524	218	7	fqnn	fqnn	NOUN
fcis-7524	218	8	models	model	NOUN
fcis-7524	218	9	for	for	ADP
fcis-7524	218	10	the	the	DET
fcis-7524	218	11	test	test	NOUN
fcis-7524	218	12	dataset	dataset	VERB
fcis-7524	218	13	with	with	ADP
fcis-7524	218	14	different	different	ADJ
fcis-7524	218	15	number	number	NOUN
fcis-7524	218	16	of	of	ADP
fcis-7524	218	17	iterations	iteration	NOUN
fcis-7524	218	18	in	in	ADP
fcis-7524	218	19	the	the	DET
fcis-7524	218	20	breast	breast	NOUN
fcis-7524	218	21	cancer	cancer	NOUN
fcis-7524	218	22	dataset	dataset	NOUN
fcis-7524	218	23	,	,	PUNCT
fcis-7524	218	24	where	where	SCONJ
fcis-7524	218	25	qnn	qnn	NOUN
fcis-7524	218	26	and	and	CCONJ
fcis-7524	218	27	fqnn	fqnn	NOUN
fcis-7524	218	28	are	be	AUX
fcis-7524	218	29	shown	show	VERB
fcis-7524	218	30	by	by	ADP
fcis-7524	218	31	green	green	ADJ
fcis-7524	218	32	dashed	dash	VERB
fcis-7524	218	33	line	line	NOUN
fcis-7524	218	34	and	and	CCONJ
fcis-7524	218	35	red	red	ADJ
fcis-7524	218	36	solid	solid	ADJ
fcis-7524	218	37	line	line	NOUN
fcis-7524	218	38	respectively	respectively	ADV
fcis-7524	218	39	.	.	PUNCT
fcis-7524	219	1	by	by	ADP
fcis-7524	219	2	comparing	compare	VERB
fcis-7524	219	3	figure	figure	NOUN
fcis-7524	219	4	8	8	NUM
fcis-7524	219	5	,	,	PUNCT
fcis-7524	219	6	we	we	PRON
fcis-7524	219	7	can	can	AUX
fcis-7524	219	8	see	see	VERB
fcis-7524	219	9	that	that	SCONJ
fcis-7524	219	10	the	the	DET
fcis-7524	219	11	qnn	qnn	ADJ
fcis-7524	219	12	model	model	NOUN
fcis-7524	219	13	stabilizes	stabilize	VERB
fcis-7524	219	14	to	to	ADP
fcis-7524	219	15	97	97	NUM
fcis-7524	219	16	%	%	NOUN
fcis-7524	219	17	correct	correct	ADJ
fcis-7524	219	18	rate	rate	NOUN
fcis-7524	219	19	after	after	ADP
fcis-7524	219	20	about	about	ADV
fcis-7524	219	21	11	11	NUM
fcis-7524	219	22	iterations	iteration	NOUN
fcis-7524	219	23	,	,	PUNCT
fcis-7524	219	24	while	while	SCONJ
fcis-7524	219	25	the	the	DET
fcis-7524	219	26	fqnn	fqnn	NOUN
fcis-7524	219	27	only	only	ADV
fcis-7524	219	28	needs	need	VERB
fcis-7524	219	29	about	about	ADV
fcis-7524	219	30	8	8	NUM
fcis-7524	219	31	iterations	iteration	NOUN
fcis-7524	219	32	to	to	PART
fcis-7524	219	33	stabilize	stabilize	VERB
fcis-7524	219	34	to	to	ADP
fcis-7524	219	35	99	99	NUM
fcis-7524	219	36	%	%	NOUN
fcis-7524	219	37	correct	correct	ADJ
fcis-7524	219	38	rate	rate	NOUN
fcis-7524	219	39	,	,	PUNCT
fcis-7524	219	40	and	and	CCONJ
fcis-7524	219	41	the	the	DET
fcis-7524	219	42	initial	initial	ADJ
fcis-7524	219	43	correct	correct	ADJ
fcis-7524	219	44	rate	rate	NOUN
fcis-7524	219	45	of	of	ADP
fcis-7524	219	46	the	the	DET
fcis-7524	219	47	fqnn	fqnn	NOUN
fcis-7524	219	48	model	model	NOUN
fcis-7524	219	49	is	be	AUX
fcis-7524	219	50	also	also	ADV
fcis-7524	219	51	higher	high	ADJ
fcis-7524	219	52	than	than	ADP
fcis-7524	219	53	that	that	PRON
fcis-7524	219	54	of	of	ADP
fcis-7524	219	55	the	the	DET
fcis-7524	219	56	qnn	qnn	ADJ
fcis-7524	219	57	model	model	NOUN
fcis-7524	219	58	.	.	PUNCT
fcis-7524	220	1	it	it	PRON
fcis-7524	220	2	can	can	AUX
fcis-7524	220	3	be	be	AUX
fcis-7524	220	4	judged	judge	VERB
fcis-7524	220	5	that	that	SCONJ
fcis-7524	220	6	fqnn	fqnn	NOUN
fcis-7524	220	7	requires	require	VERB
fcis-7524	220	8	fewer	few	ADJ
fcis-7524	220	9	iterations	iteration	NOUN
fcis-7524	220	10	to	to	PART
fcis-7524	220	11	reach	reach	VERB
fcis-7524	220	12	the	the	DET
fcis-7524	220	13	final	final	ADJ
fcis-7524	220	14	accuracy	accuracy	NOUN
fcis-7524	220	15	compared	compare	VERB
fcis-7524	220	16	to	to	ADP
fcis-7524	220	17	qnn	qnn	PROPN
fcis-7524	220	18	.	.	PUNCT
fcis-7524	221	1	for	for	ADP
fcis-7524	221	2	the	the	DET
fcis-7524	221	3	same	same	ADJ
fcis-7524	221	4	class	class	NOUN
fcis-7524	221	5	of	of	ADP
fcis-7524	221	6	experiments	experiment	NOUN
fcis-7524	221	7	,	,	PUNCT
fcis-7524	221	8	the	the	DET
fcis-7524	221	9	qfnn	qfnn	NOUN
fcis-7524	221	10	has	have	VERB
fcis-7524	221	11	a	a	DET
fcis-7524	221	12	higher	high	ADJ
fcis-7524	221	13	correct	correct	ADJ
fcis-7524	221	14	rate	rate	NOUN
fcis-7524	221	15	than	than	ADP
fcis-7524	221	16	the	the	DET
fcis-7524	221	17	qnn	qnn	NOUN
fcis-7524	221	18	for	for	ADP
fcis-7524	221	19	the	the	DET
fcis-7524	221	20	same	same	ADJ
fcis-7524	221	21	number	number	NOUN
fcis-7524	221	22	of	of	ADP
fcis-7524	221	23	iterations	iteration	NOUN
fcis-7524	221	24	before	before	ADP
fcis-7524	221	25	reaching	reach	VERB
fcis-7524	221	26	the	the	DET
fcis-7524	221	27	final	final	ADJ
fcis-7524	221	28	correct	correct	ADJ
fcis-7524	221	29	rate	rate	NOUN
fcis-7524	221	30	,	,	PUNCT
fcis-7524	221	31	indicating	indicate	VERB
fcis-7524	221	32	that	that	SCONJ
fcis-7524	221	33	fewer	few	ADJ
fcis-7524	221	34	iterations	iteration	NOUN
fcis-7524	221	35	are	be	AUX
fcis-7524	221	36	needed	need	VERB
fcis-7524	221	37	to	to	PART
fcis-7524	221	38	achieve	achieve	VERB
fcis-7524	221	39	a	a	DET
fcis-7524	221	40	higher	high	ADJ
fcis-7524	221	41	correct	correct	ADJ
fcis-7524	221	42	rate	rate	NOUN
fcis-7524	221	43	and	and	CCONJ
fcis-7524	221	44	that	that	SCONJ
fcis-7524	221	45	the	the	DET
fcis-7524	221	46	fqnn	fqnn	NOUN
fcis-7524	221	47	has	have	VERB
fcis-7524	221	48	a	a	DET
fcis-7524	221	49	better	well	ADJ
fcis-7524	221	50	classification	classification	NOUN
fcis-7524	221	51	efficiency	efficiency	NOUN
fcis-7524	221	52	in	in	ADP
fcis-7524	221	53	the	the	DET
fcis-7524	221	54	same	same	ADJ
fcis-7524	221	55	data	datum	NOUN
fcis-7524	221	56	set	set	VERB
fcis-7524	221	57	.	.	PUNCT
fcis-7524	222	1	this	this	PRON
fcis-7524	222	2	is	be	AUX
fcis-7524	222	3	due	due	ADJ
fcis-7524	222	4	to	to	ADP
fcis-7524	222	5	the	the	DET
fcis-7524	222	6	fact	fact	NOUN
fcis-7524	222	7	that	that	SCONJ
fcis-7524	222	8	fqnn	fqnn	PROPN
fcis-7524	222	9	has	have	AUX
fcis-7524	222	10	a	a	DET
fcis-7524	222	11	better	well	ADJ
fcis-7524	222	12	description	description	NOUN
fcis-7524	222	13	of	of	ADP
fcis-7524	222	14	the	the	DET
fcis-7524	222	15	uncertainty	uncertainty	NOUN
fcis-7524	222	16	in	in	ADP
fcis-7524	222	17	the	the	DET
fcis-7524	222	18	real	real	ADJ
fcis-7524	222	19	data	datum	NOUN
fcis-7524	222	20	set	set	VERB
fcis-7524	222	21	after	after	ADP
fcis-7524	222	22	the	the	DET
fcis-7524	222	23	gaussian	gaussian	ADJ
fcis-7524	222	24	fuzzy	fuzzy	ADJ
fcis-7524	222	25	number	number	NOUN
fcis-7524	222	26	operation	operation	NOUN
fcis-7524	222	27	,	,	PUNCT
fcis-7524	222	28	and	and	CCONJ
fcis-7524	222	29	the	the	DET
fcis-7524	222	30	fuzzy	fuzzy	ADJ
fcis-7524	222	31	operation	operation	NOUN
fcis-7524	222	32	of	of	ADP
fcis-7524	222	33	gaussian	gaussian	ADJ
fcis-7524	222	34	fuzzy	fuzzy	ADJ
fcis-7524	222	35	number	number	NOUN
fcis-7524	222	36	on	on	ADP
fcis-7524	222	37	the	the	DET
fcis-7524	222	38	data	datum	NOUN
fcis-7524	222	39	set	set	VERB
fcis-7524	222	40	also	also	ADV
fcis-7524	222	41	improves	improve	VERB
fcis-7524	222	42	the	the	DET
fcis-7524	222	43	model	model	NOUN
fcis-7524	222	44	to	to	PART
fcis-7524	222	45	deal	deal	VERB
fcis-7524	222	46	with	with	ADP
fcis-7524	222	47	data	datum	NOUN
fcis-7524	222	48	uncertainty	uncertainty	NOUN
fcis-7524	222	49	,	,	PUNCT
fcis-7524	222	50	which	which	PRON
fcis-7524	222	51	is	be	AUX
fcis-7524	222	52	more	more	ADV
fcis-7524	222	53	beneficial	beneficial	ADJ
fcis-7524	222	54	to	to	PART
fcis-7524	222	55	improve	improve	VERB
fcis-7524	222	56	the	the	DET
fcis-7524	222	57	accuracy	accuracy	NOUN
fcis-7524	222	58	of	of	ADP
fcis-7524	222	59	the	the	DET
fcis-7524	222	60	predicted	predict	VERB
fcis-7524	222	61	values	value	NOUN
fcis-7524	222	62	.	.	PUNCT
fcis-7524	223	1	5	5	X
fcis-7524	223	2	.	.	X
fcis-7524	223	3	conclusion	conclusion	NOUN
fcis-7524	223	4	in	in	ADP
fcis-7524	223	5	this	this	DET
fcis-7524	223	6	paper	paper	NOUN
fcis-7524	223	7	,	,	PUNCT
fcis-7524	223	8	we	we	PRON
fcis-7524	223	9	propose	propose	VERB
fcis-7524	223	10	a	a	DET
fcis-7524	223	11	quantum	quantum	ADJ
fcis-7524	223	12	fuzzy	fuzzy	ADJ
fcis-7524	223	13	neural	neural	ADJ
fcis-7524	223	14	network	network	NOUN
fcis-7524	223	15	model	model	NOUN
fcis-7524	223	16	(	(	PUNCT
fcis-7524	223	17	fqnn	fqnn	PROPN
fcis-7524	223	18	)	)	PUNCT
fcis-7524	223	19	based	base	VERB
fcis-7524	223	20	on	on	ADP
fcis-7524	223	21	fuzzy	fuzzy	ADJ
fcis-7524	223	22	numbers	number	NOUN
fcis-7524	223	23	,	,	PUNCT
fcis-7524	223	24	which	which	PRON
fcis-7524	223	25	can	can	AUX
fcis-7524	223	26	not	not	PART
fcis-7524	223	27	only	only	ADV
fcis-7524	223	28	take	take	VERB
fcis-7524	223	29	advantage	advantage	NOUN
fcis-7524	223	30	of	of	ADP
fcis-7524	223	31	the	the	DET
fcis-7524	223	32	computational	computational	ADJ
fcis-7524	223	33	acceleration	acceleration	NOUN
fcis-7524	223	34	of	of	ADP
fcis-7524	223	35	quantum	quantum	NOUN
fcis-7524	223	36	computing	computing	NOUN
fcis-7524	223	37	,	,	PUNCT
fcis-7524	223	38	but	but	CCONJ
fcis-7524	223	39	also	also	ADV
fcis-7524	223	40	introduce	introduce	VERB
fcis-7524	223	41	the	the	DET
fcis-7524	223	42	concept	concept	NOUN
fcis-7524	223	43	of	of	ADP
fcis-7524	223	44	gaussian	gaussian	ADJ
fcis-7524	223	45	fuzzy	fuzzy	ADJ
fcis-7524	223	46	numbers	number	NOUN
fcis-7524	223	47	into	into	ADP
fcis-7524	223	48	the	the	DET
fcis-7524	223	49	learning	learning	NOUN
fcis-7524	223	50	of	of	ADP
fcis-7524	223	51	quantum	quantum	ADJ
fcis-7524	223	52	neural	neural	ADJ
fcis-7524	223	53	networks	network	NOUN
fcis-7524	223	54	,	,	PUNCT
fcis-7524	223	55	and	and	CCONJ
fcis-7524	223	56	fuse	fuse	NOUN
fcis-7524	223	57	fuzzy	fuzzy	ADJ
fcis-7524	223	58	numbers	number	NOUN
fcis-7524	223	59	and	and	CCONJ
fcis-7524	223	60	quantum	quantum	NOUN
fcis-7524	223	61	neural	neural	ADJ
fcis-7524	223	62	networks	network	NOUN
fcis-7524	223	63	.	.	PUNCT
fcis-7524	224	1	in	in	ADP
fcis-7524	224	2	dealing	deal	VERB
fcis-7524	224	3	with	with	ADP
fcis-7524	224	4	data	datum	NOUN
fcis-7524	224	5	uncertainty	uncertainty	NOUN
fcis-7524	224	6	and	and	CCONJ
fcis-7524	224	7	fuzziness	fuzziness	NOUN
fcis-7524	224	8	,	,	PUNCT
fcis-7524	224	9	gaussian	gaussian	ADJ
fcis-7524	224	10	fuzzy	fuzzy	ADJ
fcis-7524	224	11	numbers	number	NOUN
fcis-7524	224	12	are	be	AUX
fcis-7524	224	13	used	use	VERB
fcis-7524	224	14	to	to	PART
fcis-7524	224	15	calculate	calculate	VERB
fcis-7524	224	16	the	the	DET
fcis-7524	224	17	affiliation	affiliation	NOUN
fcis-7524	224	18	degree	degree	NOUN
fcis-7524	224	19	on	on	ADP
fcis-7524	224	20	the	the	DET
fcis-7524	224	21	input	input	NOUN
fcis-7524	224	22	data	datum	NOUN
fcis-7524	224	23	set	set	VERB
fcis-7524	224	24	to	to	PART
fcis-7524	224	25	describe	describe	VERB
fcis-7524	224	26	the	the	DET
fcis-7524	224	27	information	information	NOUN
fcis-7524	224	28	of	of	ADP
fcis-7524	224	29	data	datum	NOUN
fcis-7524	224	30	uncertainty	uncertainty	NOUN
fcis-7524	224	31	and	and	CCONJ
fcis-7524	224	32	fuzziness	fuzziness	NOUN
fcis-7524	224	33	.	.	PUNCT
fcis-7524	225	1	fqnn	fqnn	PROPN
fcis-7524	225	2	model	model	NOUN
fcis-7524	225	3	can	can	AUX
fcis-7524	225	4	effectively	effectively	ADV
fcis-7524	225	5	utilize	utilize	VERB
fcis-7524	225	6	the	the	DET
fcis-7524	225	7	advantages	advantage	NOUN
fcis-7524	225	8	of	of	ADP
fcis-7524	225	9	fuzzy	fuzzy	ADJ
fcis-7524	225	10	numbers	number	NOUN
fcis-7524	225	11	to	to	PART
fcis-7524	225	12	deal	deal	VERB
fcis-7524	225	13	with	with	ADP
fcis-7524	225	14	uncertainty	uncertainty	NOUN
fcis-7524	225	15	and	and	CCONJ
fcis-7524	225	16	ambiguity	ambiguity	NOUN
fcis-7524	225	17	problems	problem	NOUN
fcis-7524	225	18	and	and	CCONJ
fcis-7524	225	19	the	the	DET
fcis-7524	225	20	advantages	advantage	NOUN
fcis-7524	225	21	of	of	ADP
fcis-7524	225	22	parallel	parallel	ADJ
fcis-7524	225	23	computing	computing	NOUN
fcis-7524	225	24	of	of	ADP
fcis-7524	225	25	neural	neural	ADJ
fcis-7524	225	26	networks	network	NOUN
fcis-7524	225	27	to	to	PART
fcis-7524	225	28	make	make	VERB
fcis-7524	225	29	up	up	ADP
fcis-7524	225	30	for	for	ADP
fcis-7524	225	31	the	the	DET
fcis-7524	225	32	shortcomings	shortcoming	NOUN
fcis-7524	225	33	of	of	ADP
fcis-7524	225	34	each	each	PRON
fcis-7524	225	35	.	.	PUNCT
fcis-7524	226	1	the	the	DET
fcis-7524	226	2	simulation	simulation	NOUN
fcis-7524	226	3	experiments	experiment	NOUN
fcis-7524	226	4	show	show	VERB
fcis-7524	226	5	that	that	SCONJ
fcis-7524	226	6	the	the	DET
fcis-7524	226	7	quantum	quantum	ADJ
fcis-7524	226	8	fuzzy	fuzzy	ADJ
fcis-7524	226	9	neural	neural	ADJ
fcis-7524	226	10	network	network	NOUN
fcis-7524	226	11	model	model	NOUN
fcis-7524	226	12	based	base	VERB
fcis-7524	226	13	on	on	ADP
fcis-7524	226	14	fuzzy	fuzzy	ADJ
fcis-7524	226	15	numbers	number	NOUN
fcis-7524	226	16	has	have	VERB
fcis-7524	226	17	higher	high	ADJ
fcis-7524	226	18	efficiency	efficiency	NOUN
fcis-7524	226	19	and	and	CCONJ
fcis-7524	226	20	accuracy	accuracy	NOUN
fcis-7524	226	21	compared	compare	VERB
fcis-7524	226	22	with	with	ADP
fcis-7524	226	23	the	the	DET
fcis-7524	226	24	existing	exist	VERB
fcis-7524	226	25	quantum	quantum	ADJ
fcis-7524	226	26	neural	neural	ADJ
fcis-7524	226	27	network	network	NOUN
fcis-7524	226	28	model	model	NOUN
fcis-7524	226	29	(	(	PUNCT
fcis-7524	226	30	qnn	qnn	X
fcis-7524	226	31	)	)	PUNCT
fcis-7524	226	32	.	.	PUNCT
fcis-7524	227	1	references	reference	NOUN
fcis-7524	227	2	[	[	X
fcis-7524	227	3	1	1	X
fcis-7524	227	4	]	]	PUNCT
fcis-7524	227	5	wright	wright	PROPN
fcis-7524	227	6	l	l	PROPN
fcis-7524	227	7	g	g	PROPN
fcis-7524	227	8	,	,	PUNCT
fcis-7524	227	9	onodera	onodera	NOUN
fcis-7524	227	10	t	t	PROPN
fcis-7524	227	11	,	,	PUNCT
fcis-7524	227	12	stein	stein	PROPN
fcis-7524	227	13	m	m	PROPN
fcis-7524	227	14	m	m	PROPN
fcis-7524	227	15	,	,	PUNCT
fcis-7524	227	16	et	et	PROPN
fcis-7524	227	17	al	al	PROPN
fcis-7524	227	18	.	.	PUNCT
fcis-7524	228	1	deep	deep	ADJ
fcis-7524	228	2	physical	physical	ADJ
fcis-7524	228	3	neural	neural	ADJ
fcis-7524	228	4	networks	network	NOUN
fcis-7524	228	5	trained	train	VERB
fcis-7524	228	6	with	with	ADP
fcis-7524	228	7	backpropagation[j	backpropagation[j	PROPN
fcis-7524	228	8	]	]	PUNCT
fcis-7524	228	9	.	.	PUNCT
fcis-7524	229	1	nature	nature	NOUN
fcis-7524	229	2	,	,	PUNCT
fcis-7524	229	3	2022	2022	NUM
fcis-7524	229	4	,	,	PUNCT
fcis-7524	229	5	601	601	NUM
fcis-7524	229	6	.	.	PUNCT
fcis-7524	230	1	[	[	X
fcis-7524	230	2	2	2	NUM
fcis-7524	230	3	]	]	X
fcis-7524	230	4	zhang	zhang	PROPN
fcis-7524	230	5	s	s	PROPN
fcis-7524	230	6	b	b	PROPN
fcis-7524	230	7	,	,	PUNCT
fcis-7524	230	8	huang	huang	PROPN
fcis-7524	230	9	x	x	PROPN
fcis-7524	230	10	,	,	PUNCT
fcis-7524	230	11	chang	chang	PROPN
fcis-7524	230	12	y	y	PROPN
fcis-7524	230	13	,	,	PUNCT
fcis-7524	230	14	et	et	PROPN
fcis-7524	230	15	al	al	PROPN
fcis-7524	230	16	.	.	PUNCT
fcis-7524	230	17	research	research	NOUN
fcis-7524	230	18	progress	progress	NOUN
fcis-7524	230	19	and	and	CCONJ
fcis-7524	230	20	development	development	NOUN
fcis-7524	230	21	trend	trend	NOUN
fcis-7524	230	22	of	of	ADP
fcis-7524	230	23	quantum	quantum	NOUN
fcis-7524	230	24	machine	machine	NOUN
fcis-7524	230	25	learning	learn	VERB
fcis-7524	230	26	in	in	ADP
fcis-7524	230	27	big	big	ADJ
fcis-7524	230	28	data	datum	NOUN
fcis-7524	230	29	environment[j	environment[j	PROPN
fcis-7524	230	30	]	]	X
fcis-7524	230	31	.	.	PUNCT
fcis-7524	230	32	journal	journal	PROPN
fcis-7524	230	33	of	of	ADP
fcis-7524	230	34	university	university	PROPN
fcis-7524	230	35	of	of	ADP
fcis-7524	230	36	electronic	electronic	ADJ
fcis-7524	230	37	science	science	NOUN
fcis-7524	230	38	and	and	CCONJ
fcis-7524	230	39	technology	technology	NOUN
fcis-7524	230	40	of	of	ADP
fcis-7524	230	41	china	china	PROPN
fcis-7524	230	42	,	,	PUNCT
fcis-7524	230	43	2021	2021	NUM
fcis-7524	230	44	,	,	PUNCT
fcis-7524	230	45	50(6	50(6	NUM
fcis-7524	230	46	):	):	PUNCT
fcis-7524	230	47	18	18	NUM
fcis-7524	230	48	.	.	PUNCT
fcis-7524	231	1	[	[	X
fcis-7524	231	2	3	3	X
fcis-7524	231	3	]	]	X
fcis-7524	231	4	chen	chen	PROPN
fcis-7524	231	5	w	w	PROPN
fcis-7524	231	6	,	,	PUNCT
fcis-7524	231	7	wang	wang	PROPN
fcis-7524	232	1	x	x	PROPN
fcis-7524	232	2	,	,	PUNCT
fcis-7524	232	3	wang	wang	PROPN
fcis-7524	232	4	w	w	PROPN
fcis-7524	232	5	,	,	PUNCT
fcis-7524	232	6	et	et	PROPN
fcis-7524	232	7	al	al	PROPN
fcis-7524	232	8	.	.	PUNCT
fcis-7524	233	1	a	a	DET
fcis-7524	233	2	heterogeneous	heterogeneous	ADJ
fcis-7524	233	3	gracbr	gracbr	NOUN
fcis-7524	233	4	-	-	PUNCT
fcis-7524	233	5	based	base	VERB
fcis-7524	233	6	multi	multi	ADJ
fcis-7524	233	7	-	-	ADJ
fcis-7524	233	8	attribute	attribute	ADJ
fcis-7524	233	9	emergency	emergency	NOUN
fcis-7524	233	10	decision	decision	NOUN
fcis-7524	233	11	-	-	PUNCT
fcis-7524	233	12	making	make	VERB
fcis-7524	233	13	model	model	NOUN
fcis-7524	233	14	considering	consider	VERB
fcis-7524	233	15	weight	weight	NOUN
fcis-7524	233	16	optimization	optimization	NOUN
fcis-7524	233	17	with	with	ADP
fcis-7524	233	18	dual	dual	ADJ
fcis-7524	233	19	information	information	NOUN
fcis-7524	233	20	correlation[j	correlation[j	PROPN
fcis-7524	233	21	]	]	PUNCT
fcis-7524	233	22	.	.	PUNCT
fcis-7524	234	1	expert	expert	NOUN
fcis-7524	234	2	systems	system	NOUN
fcis-7524	234	3	with	with	ADP
fcis-7524	234	4	applications	application	NOUN
fcis-7524	234	5	,	,	PUNCT
fcis-7524	234	6	2021	2021	NUM
fcis-7524	234	7	.	.	PUNCT
fcis-7524	235	1	[	[	X
fcis-7524	235	2	4	4	NUM
fcis-7524	235	3	]	]	X
fcis-7524	235	4	arthur	arthur	PROPN
fcis-7524	235	5	d	d	PROPN
fcis-7524	235	6	,	,	PUNCT
fcis-7524	235	7	date	date	NOUN
fcis-7524	235	8	p	p	NOUN
fcis-7524	235	9	.	.	PUNCT
fcis-7524	236	1	a	a	DET
fcis-7524	236	2	hybrid	hybrid	ADJ
fcis-7524	236	3	quantum	quantum	NOUN
fcis-7524	236	4	-	-	PUNCT
fcis-7524	236	5	classical	classical	ADJ
fcis-7524	236	6	neural	neural	ADJ
fcis-7524	236	7	network	network	NOUN
fcis-7524	236	8	architecture	architecture	NOUN
fcis-7524	236	9	for	for	ADP
fcis-7524	236	10	binary	binary	ADJ
fcis-7524	236	11	classification[j	classification[j	PROPN
fcis-7524	236	12	]	]	X
fcis-7524	236	13	.	.	PUNCT
fcis-7524	237	1	2022	2022	NUM
fcis-7524	237	2	.	.	PUNCT
fcis-7524	238	1	[	[	X
fcis-7524	238	2	5	5	X
fcis-7524	238	3	]	]	X
fcis-7524	238	4	kawase	kawase	PROPN
fcis-7524	238	5	y	y	PROPN
fcis-7524	238	6	,	,	PUNCT
fcis-7524	238	7	mitarai	mitarai	PROPN
fcis-7524	238	8	k	k	PROPN
fcis-7524	238	9	,	,	PUNCT
fcis-7524	238	10	fujii	fujii	PROPN
fcis-7524	238	11	k	k	PROPN
fcis-7524	238	12	.	.	PUNCT
fcis-7524	239	1	parametric	parametric	PROPN
fcis-7524	239	2	t	t	PROPN
fcis-7524	239	3	-	-	PUNCT
fcis-7524	239	4	stochastic	stochastic	NOUN
fcis-7524	239	5	neighbor	neighbor	NOUN
fcis-7524	239	6	embedding	embed	VERB
fcis-7524	239	7	with	with	ADP
fcis-7524	239	8	quantum	quantum	ADJ
fcis-7524	239	9	neural	neural	ADJ
fcis-7524	239	10	network[j	network[j	PROPN
fcis-7524	239	11	]	]	PUNCT
fcis-7524	239	12	.	.	PUNCT
fcis-7524	240	1	arxiv	arxiv	PROPN
fcis-7524	240	2	e	e	PROPN
fcis-7524	240	3	-	-	NOUN
fcis-7524	240	4	prints	print	NOUN
fcis-7524	240	5	,	,	PUNCT
fcis-7524	240	6	2022	2022	NUM
fcis-7524	240	7	.	.	PUNCT
fcis-7524	241	1	[	[	X
fcis-7524	241	2	6	6	NUM
fcis-7524	241	3	]	]	SYM
fcis-7524	241	4	osakabe	osakabe	PROPN
fcis-7524	241	5	y	y	PROPN
fcis-7524	241	6	,	,	PUNCT
fcis-7524	241	7	sato	sato	PROPN
fcis-7524	241	8	s	s	PART
fcis-7524	241	9	,	,	PUNCT
fcis-7524	241	10	akima	akima	PROPN
fcis-7524	241	11	h	h	NOUN
fcis-7524	241	12	,	,	PUNCT
fcis-7524	241	13	et	et	PROPN
fcis-7524	241	14	al	al	PROPN
fcis-7524	241	15	.	.	PUNCT
fcis-7524	242	1	learning	learn	VERB
fcis-7524	242	2	rule	rule	NOUN
fcis-7524	242	3	for	for	ADP
fcis-7524	242	4	a	a	DET
fcis-7524	242	5	quantum	quantum	ADJ
fcis-7524	242	6	neural	neural	ADJ
fcis-7524	242	7	network	network	NOUN
fcis-7524	242	8	inspired	inspire	VERB
fcis-7524	242	9	by	by	ADP
fcis-7524	242	10	hebbian	hebbian	PROPN
fcis-7524	242	11	learning[j	learning[j	PROPN
fcis-7524	242	12	]	]	PUNCT
fcis-7524	242	13	.	.	PUNCT
fcis-7524	243	1	ieice	ieice	NOUN
fcis-7524	243	2	transactions	transaction	NOUN
fcis-7524	243	3	on	on	ADP
fcis-7524	243	4	information	information	NOUN
fcis-7524	243	5	and	and	CCONJ
fcis-7524	243	6	systems	system	NOUN
fcis-7524	243	7	,	,	PUNCT
fcis-7524	243	8	2021	2021	NUM
fcis-7524	243	9	,	,	PUNCT
fcis-7524	243	10	e104.d(2):237	e104.d(2):237	PROPN
fcis-7524	243	11	-	-	NOUN
fcis-7524	243	12	245	245	NUM
fcis-7524	243	13	.	.	PUNCT
fcis-7524	244	1	[	[	X
fcis-7524	244	2	7	7	X
fcis-7524	244	3	]	]	X
fcis-7524	244	4	rui	rui	PROPN
fcis-7524	244	5	m	m	VERB
fcis-7524	244	6	a	a	PRON
fcis-7524	244	7	,	,	PUNCT
fcis-7524	244	8	jl	jl	PROPN
fcis-7524	244	9	a	a	PRON
fcis-7524	244	10	,	,	PUNCT
fcis-7524	244	11	fei	fei	PROPN
fcis-7524	244	12	j	j	PROPN
fcis-7524	244	13	a	a	PROPN
fcis-7524	244	14	,	,	PUNCT
fcis-7524	244	15	et	et	PROPN
fcis-7524	244	16	al	al	PROPN
fcis-7524	244	17	.	.	PROPN
fcis-7524	244	18	fuzzy	fuzzy	ADJ
fcis-7524	244	19	theory	theory	NOUN
fcis-7524	244	20	-	-	PUNCT
fcis-7524	244	21	based	base	VERB
fcis-7524	244	22	energysaving	energysaving	NOUN
fcis-7524	244	23	control	control	NOUN
fcis-7524	244	24	of	of	ADP
fcis-7524	244	25	solar	solar	ADJ
fcis-7524	244	26	thermal	thermal	ADJ
fcis-7524	244	27	supplemental	supplemental	ADJ
fcis-7524	244	28	multi	multi	ADJ
fcis-7524	244	29	-	-	ADJ
fcis-7524	244	30	energy	energy	ADJ
fcis-7524	244	31	heating	heating	NOUN
fcis-7524	244	32	system[j	system[j	NOUN
fcis-7524	244	33	]	]	PUNCT
fcis-7524	244	34	.	.	PUNCT
fcis-7524	245	1	energy	energy	NOUN
fcis-7524	245	2	reports	report	NOUN
fcis-7524	245	3	,	,	PUNCT
fcis-7524	245	4	2022	2022	NUM
fcis-7524	245	5	,	,	PUNCT
fcis-7524	245	6	8:636	8:636	NOUN
fcis-7524	245	7	-	-	SYM
fcis-7524	245	8	646	646	NUM
fcis-7524	245	9	.	.	PUNCT
fcis-7524	246	1	105	105	NUM
fcis-7524	247	1	[	[	SYM
fcis-7524	247	2	8	8	NUM
fcis-7524	247	3	]	]	X
fcis-7524	247	4	wei	wei	PROPN
fcis-7524	247	5	s	s	PROPN
fcis-7524	247	6	,	,	PUNCT
fcis-7524	247	7	guo	guo	PROPN
fcis-7524	247	8	c	c	PROPN
fcis-7524	247	9	.	.	PUNCT
fcis-7524	248	1	study	study	NOUN
fcis-7524	248	2	on	on	ADP
fcis-7524	248	3	regional	regional	ADJ
fcis-7524	248	4	control	control	NOUN
fcis-7524	248	5	of	of	ADP
fcis-7524	248	6	tourism	tourism	NOUN
fcis-7524	248	7	flow	flow	NOUN
fcis-7524	248	8	based	base	VERB
fcis-7524	248	9	on	on	ADP
fcis-7524	248	10	fuzzy	fuzzy	ADJ
fcis-7524	248	11	theory[j	theory[j	NOUN
fcis-7524	248	12	]	]	PUNCT
fcis-7524	248	13	.	.	PUNCT
fcis-7524	249	1	wireless	wireless	ADJ
fcis-7524	249	2	communications	communication	NOUN
fcis-7524	249	3	and	and	CCONJ
fcis-7524	249	4	mobile	mobile	NOUN
fcis-7524	249	5	computing	computing	NOUN
fcis-7524	249	6	,	,	PUNCT
fcis-7524	249	7	2021	2021	NUM
fcis-7524	249	8	,	,	PUNCT
fcis-7524	249	9	2021(179(5)):1	2021(179(5)):1	NOUN
fcis-7524	249	10	-	-	SYM
fcis-7524	249	11	7	7	NUM
fcis-7524	249	12	.	.	PUNCT
fcis-7524	250	1	[	[	X
fcis-7524	250	2	9	9	NUM
fcis-7524	250	3	]	]	PUNCT
fcis-7524	250	4	gangopadhyay	gangopadhyay	NOUN
fcis-7524	250	5	s	s	PART
fcis-7524	250	6	,	,	PUNCT
fcis-7524	250	7	das	das	PROPN
fcis-7524	250	8	s	s	PROPN
fcis-7524	250	9	.	.	PUNCT
fcis-7524	250	10	fuzzy	fuzzy	ADJ
fcis-7524	250	11	theory	theory	NOUN
fcis-7524	250	12	based	base	VERB
fcis-7524	250	13	quality	quality	NOUN
fcis-7524	250	14	assessment	assessment	NOUN
fcis-7524	250	15	of	of	ADP
fcis-7524	250	16	multivariate	multivariate	ADJ
fcis-7524	250	17	electrical	electrical	ADJ
fcis-7524	250	18	measurements	measurement	NOUN
fcis-7524	250	19	of	of	ADP
fcis-7524	250	20	smart	smart	ADJ
fcis-7524	250	21	grids[j	grids[j	PROPN
fcis-7524	250	22	]	]	PUNCT
fcis-7524	250	23	.	.	PUNCT
fcis-7524	251	1	ieee	ieee	NOUN
fcis-7524	251	2	access	access	NOUN
fcis-7524	251	3	,	,	PUNCT
fcis-7524	251	4	2021	2021	NUM
fcis-7524	251	5	,	,	PUNCT
fcis-7524	251	6	pp(99):1	pp(99):1	NOUN
fcis-7524	251	7	-	-	SYM
fcis-7524	251	8	1	1	NUM
fcis-7524	251	9	.	.	PUNCT
fcis-7524	252	1	[	[	X
fcis-7524	252	2	10	10	NUM
fcis-7524	252	3	]	]	SYM
fcis-7524	252	4	gu	gu	NOUN
fcis-7524	252	5	x	x	SYM
fcis-7524	252	6	,	,	PUNCT
fcis-7524	252	7	cheng	cheng	PROPN
fcis-7524	252	8	x	x	PUNCT
fcis-7524	252	9	.	.	PUNCT
fcis-7524	253	1	distilling	distil	VERB
fcis-7524	253	2	a	a	DET
fcis-7524	253	3	deep	deep	ADJ
fcis-7524	253	4	neural	neural	ADJ
fcis-7524	253	5	network	network	NOUN
fcis-7524	253	6	into	into	ADP
fcis-7524	253	7	a	a	DET
fcis-7524	253	8	takagi	takagi	NOUN
fcis-7524	253	9	-	-	PUNCT
fcis-7524	253	10	sugeno	sugeno	NOUN
fcis-7524	253	11	-	-	PUNCT
fcis-7524	253	12	kang	kang	PROPN
fcis-7524	253	13	fuzzy	fuzzy	ADJ
fcis-7524	253	14	inference	inference	PROPN
fcis-7524	253	15	system[j	system[j	PROPN
fcis-7524	253	16	]	]	PUNCT
fcis-7524	253	17	.	.	PUNCT
fcis-7524	254	1	2020	2020	NUM
fcis-7524	254	2	.	.	PUNCT
fcis-7524	255	1	[	[	X
fcis-7524	255	2	11	11	NUM
fcis-7524	255	3	]	]	X
fcis-7524	255	4	wan	wan	PROPN
fcis-7524	255	5	s.	s.	PROPN
fcis-7524	255	6	agricultural	agricultural	PROPN
fcis-7524	255	7	water	water	NOUN
fcis-7524	255	8	resources	resource	NOUN
fcis-7524	255	9	utilization	utilization	NOUN
fcis-7524	255	10	and	and	CCONJ
fcis-7524	255	11	management	management	NOUN
fcis-7524	255	12	under	under	ADP
fcis-7524	255	13	agricultural	agricultural	ADJ
fcis-7524	255	14	safety	safety	NOUN
fcis-7524	255	15	aim	aim	NOUN
fcis-7524	255	16	based	base	VERB
fcis-7524	255	17	on	on	ADP
fcis-7524	255	18	fuzzy	fuzzy	ADJ
fcis-7524	255	19	neural	neural	ADJ
fcis-7524	255	20	network	network	NOUN
fcis-7524	255	21	algorithm[j	algorithm[j	PROPN
fcis-7524	255	22	]	]	PUNCT
fcis-7524	255	23	.	.	PUNCT
fcis-7524	256	1	asian	asian	ADJ
fcis-7524	256	2	agricultural	agricultural	ADJ
fcis-7524	256	3	research	research	NOUN
fcis-7524	256	4	,	,	PUNCT
fcis-7524	256	5	2021	2021	NUM
fcis-7524	256	6	,	,	PUNCT
fcis-7524	256	7	13	13	NUM
fcis-7524	256	8	.	.	PUNCT
fcis-7524	257	1	[	[	X
fcis-7524	257	2	12	12	NUM
fcis-7524	257	3	]	]	X
fcis-7524	257	4	jia	jia	PROPN
fcis-7524	257	5	y	y	PROPN
fcis-7524	257	6	,	,	PUNCT
fcis-7524	257	7	zhang	zhang	PROPN
fcis-7524	257	8	r	r	PROPN
fcis-7524	257	9	,	,	PUNCT
fcis-7524	257	10	zhang	zhang	PROPN
fcis-7524	257	11	t	t	PROPN
fcis-7524	257	12	,	,	PUNCT
fcis-7524	257	13	et	et	PROPN
fcis-7524	257	14	al	al	PROPN
fcis-7524	257	15	.	.	PROPN
fcis-7524	257	16	coordinated	coordinated	ADJ
fcis-7524	257	17	control	control	NOUN
fcis-7524	257	18	of	of	ADP
fcis-7524	257	19	the	the	DET
fcis-7524	257	20	fuel	fuel	NOUN
fcis-7524	257	21	cell	cell	NOUN
fcis-7524	257	22	air	air	NOUN
fcis-7524	257	23	supply	supply	NOUN
fcis-7524	257	24	system	system	NOUN
fcis-7524	257	25	based	base	VERB
fcis-7524	257	26	on	on	ADP
fcis-7524	257	27	fuzzy	fuzzy	ADJ
fcis-7524	257	28	neural	neural	ADJ
fcis-7524	257	29	network	network	NOUN
fcis-7524	257	30	decoupling[j	decoupling[j	PROPN
fcis-7524	257	31	]	]	PUNCT
fcis-7524	257	32	.	.	PUNCT
fcis-7524	257	33	2021	2021	NUM
fcis-7524	257	34	.	.	PUNCT
fcis-7524	258	1	[	[	X
fcis-7524	258	2	13	13	NUM
fcis-7524	258	3	]	]	X
fcis-7524	258	4	liu	liu	PROPN
fcis-7524	258	5	q	q	PROPN
fcis-7524	258	6	,	,	PUNCT
fcis-7524	258	7	zeng	zeng	PROPN
fcis-7524	258	8	m	m	PROPN
fcis-7524	258	9	.	.	PUNCT
fcis-7524	259	1	network	network	NOUN
fcis-7524	259	2	security	security	NOUN
fcis-7524	259	3	situation	situation	NOUN
fcis-7524	259	4	detection	detection	NOUN
fcis-7524	259	5	of	of	ADP
fcis-7524	259	6	internet	internet	NOUN
fcis-7524	259	7	of	of	ADP
fcis-7524	259	8	things	thing	NOUN
fcis-7524	259	9	for	for	ADP
fcis-7524	259	10	smart	smart	ADJ
fcis-7524	259	11	city	city	NOUN
fcis-7524	259	12	based	base	VERB
fcis-7524	259	13	on	on	ADP
fcis-7524	259	14	fuzzy	fuzzy	ADJ
fcis-7524	259	15	neural	neural	ADJ
fcis-7524	259	16	network[j	network[j	PROPN
fcis-7524	259	17	]	]	PUNCT
fcis-7524	259	18	.	.	PUNCT
fcis-7524	260	1	international	international	ADJ
fcis-7524	260	2	journal	journal	NOUN
fcis-7524	260	3	of	of	ADP
fcis-7524	260	4	reasoning	reasoning	NOUN
fcis-7524	260	5	-	-	PUNCT
fcis-7524	260	6	based	base	VERB
fcis-7524	260	7	intelligent	intelligent	ADJ
fcis-7524	260	8	systems	system	NOUN
fcis-7524	260	9	,	,	PUNCT
fcis-7524	260	10	2020	2020	NUM
fcis-7524	260	11	,	,	PUNCT
fcis-7524	260	12	12(3):222	12(3):222	NUM
fcis-7524	260	13	.	.	PUNCT