id	sid	tid	token	lemma	pos
ajst-15457	1	1	academic	academic	ADJ
ajst-15457	1	2	journal	journal	NOUN
ajst-15457	1	3	of	of	ADP
ajst-15457	1	4	science	science	NOUN
ajst-15457	1	5	and	and	CCONJ
ajst-15457	1	6	technology	technology	NOUN
ajst-15457	1	7	issn	issn	NOUN
ajst-15457	1	8	:	:	PUNCT
ajst-15457	1	9	2771	2771	NUM
ajst-15457	1	10	-	-	SYM
ajst-15457	1	11	3032	3032	NUM
ajst-15457	1	12	|	|	NOUN
ajst-15457	1	13	vol	vol	NOUN
ajst-15457	1	14	.	.	PROPN
ajst-15457	1	15	8	8	NUM
ajst-15457	1	16	,	,	PUNCT
ajst-15457	1	17	no	no	INTJ
ajst-15457	1	18	.	.	NOUN
ajst-15457	1	19	3	3	NUM
ajst-15457	1	20	,	,	PUNCT
ajst-15457	1	21	2023	2023	NUM
ajst-15457	1	22	69	69	NUM
ajst-15457	1	23	research	research	NOUN
ajst-15457	1	24	on	on	ADP
ajst-15457	1	25	continuous	continuous	ADJ
ajst-15457	1	26	pipeline	pipeline	NOUN
ajst-15457	1	27	life	life	NOUN
ajst-15457	1	28	prediction	prediction	NOUN
ajst-15457	1	29	method	method	NOUN
ajst-15457	1	30	based	base	VERB
ajst-15457	1	31	on	on	ADP
ajst-15457	1	32	fully	fully	ADV
ajst-15457	1	33	connected	connect	VERB
ajst-15457	1	34	neural	neural	ADJ
ajst-15457	1	35	network	network	NOUN
ajst-15457	1	36	zhikui	zhikui	PROPN
ajst-15457	1	37	zhang1	zhang1	PROPN
ajst-15457	1	38	,	,	PUNCT
ajst-15457	1	39	lina	lina	PROPN
ajst-15457	1	40	wu2	wu2	PROPN
ajst-15457	1	41	1	1	NUM
ajst-15457	1	42	school	school	NOUN
ajst-15457	1	43	of	of	ADP
ajst-15457	1	44	mechanical	mechanical	ADJ
ajst-15457	1	45	engineering	engineering	NOUN
ajst-15457	1	46	,	,	PUNCT
ajst-15457	1	47	xi'an	xi'an	PROPN
ajst-15457	1	48	shiyou	shiyou	PROPN
ajst-15457	1	49	university	university	PROPN
ajst-15457	1	50	,	,	PUNCT
ajst-15457	1	51	xi'an	xi'an	PROPN
ajst-15457	1	52	city	city	PROPN
ajst-15457	1	53	,	,	PUNCT
ajst-15457	1	54	shaanxi	shaanxi	PROPN
ajst-15457	1	55	province	province	PROPN
ajst-15457	1	56	,	,	PUNCT
ajst-15457	1	57	710065	710065	NUM
ajst-15457	1	58	,	,	PUNCT
ajst-15457	1	59	china	china	PROPN
ajst-15457	1	60	2	2	NUM
ajst-15457	1	61	linyi	linyi	PROPN
ajst-15457	1	62	dongxing	dongxe	VERB
ajst-15457	1	63	experimental	experimental	ADJ
ajst-15457	1	64	school	school	NOUN
ajst-15457	1	65	,	,	PUNCT
ajst-15457	1	66	linyi	linyi	PROPN
ajst-15457	1	67	city	city	PROPN
ajst-15457	1	68	,	,	PUNCT
ajst-15457	1	69	shandong	shandong	PROPN
ajst-15457	1	70	province	province	PROPN
ajst-15457	1	71	,	,	PUNCT
ajst-15457	1	72	276000	276000	NUM
ajst-15457	1	73	,	,	PUNCT
ajst-15457	1	74	china	china	PROPN
ajst-15457	1	75	abstract	abstract	NOUN
ajst-15457	1	76	:	:	PUNCT
ajst-15457	1	77	aiming	aim	VERB
ajst-15457	1	78	at	at	ADP
ajst-15457	1	79	the	the	DET
ajst-15457	1	80	low	low	ADJ
ajst-15457	1	81	accuracy	accuracy	NOUN
ajst-15457	1	82	of	of	ADP
ajst-15457	1	83	traditional	traditional	ADJ
ajst-15457	1	84	empirical	empirical	ADJ
ajst-15457	1	85	formulas	formula	NOUN
ajst-15457	1	86	in	in	ADP
ajst-15457	1	87	predicting	predict	VERB
ajst-15457	1	88	the	the	DET
ajst-15457	1	89	fatigue	fatigue	NOUN
ajst-15457	1	90	life	life	NOUN
ajst-15457	1	91	of	of	ADP
ajst-15457	1	92	continuous	continuous	ADJ
ajst-15457	1	93	oil	oil	NOUN
ajst-15457	1	94	pipelines	pipeline	NOUN
ajst-15457	1	95	,	,	PUNCT
ajst-15457	1	96	a	a	DET
ajst-15457	1	97	fully	fully	ADV
ajst-15457	1	98	connected	connect	VERB
ajst-15457	1	99	neural	neural	ADJ
ajst-15457	1	100	network	network	NOUN
ajst-15457	1	101	is	be	AUX
ajst-15457	1	102	utilized	utilize	VERB
ajst-15457	1	103	to	to	PART
ajst-15457	1	104	predict	predict	VERB
ajst-15457	1	105	the	the	DET
ajst-15457	1	106	low	low	ADJ
ajst-15457	1	107	-	-	PUNCT
ajst-15457	1	108	week	week	NOUN
ajst-15457	1	109	fatigue	fatigue	NOUN
ajst-15457	1	110	life	life	NOUN
ajst-15457	1	111	of	of	ADP
ajst-15457	1	112	continuous	continuous	ADJ
ajst-15457	1	113	oil	oil	NOUN
ajst-15457	1	114	pipelines	pipeline	NOUN
ajst-15457	1	115	.	.	PUNCT
ajst-15457	2	1	considering	consider	VERB
ajst-15457	2	2	the	the	DET
ajst-15457	2	3	influence	influence	NOUN
ajst-15457	2	4	of	of	ADP
ajst-15457	2	5	internal	internal	ADJ
ajst-15457	2	6	pressure	pressure	NOUN
ajst-15457	2	7	on	on	ADP
ajst-15457	2	8	the	the	DET
ajst-15457	2	9	fatigue	fatigue	NOUN
ajst-15457	2	10	life	life	NOUN
ajst-15457	2	11	of	of	ADP
ajst-15457	2	12	continuous	continuous	ADJ
ajst-15457	2	13	oil	oil	NOUN
ajst-15457	2	14	pipeline	pipeline	NOUN
ajst-15457	2	15	during	during	ADP
ajst-15457	2	16	operation	operation	NOUN
ajst-15457	2	17	,	,	PUNCT
ajst-15457	2	18	a	a	DET
ajst-15457	2	19	prediction	prediction	NOUN
ajst-15457	2	20	method	method	NOUN
ajst-15457	2	21	combining	combine	VERB
ajst-15457	2	22	the	the	DET
ajst-15457	2	23	fully	fully	ADV
ajst-15457	2	24	connected	connected	ADJ
ajst-15457	2	25	neural	neural	ADJ
ajst-15457	2	26	network	network	NOUN
ajst-15457	2	27	and	and	CCONJ
ajst-15457	2	28	gated	gate	VERB
ajst-15457	2	29	recirculation	recirculation	NOUN
ajst-15457	2	30	unit	unit	NOUN
ajst-15457	2	31	is	be	AUX
ajst-15457	2	32	proposed	propose	VERB
ajst-15457	2	33	,	,	PUNCT
ajst-15457	2	34	and	and	CCONJ
ajst-15457	2	35	the	the	DET
ajst-15457	2	36	experiment	experiment	NOUN
ajst-15457	2	37	proves	prove	VERB
ajst-15457	2	38	that	that	SCONJ
ajst-15457	2	39	the	the	DET
ajst-15457	2	40	fcnn	fcnn	PROPN
ajst-15457	2	41	-	-	PUNCT
ajst-15457	2	42	gru	gru	NOUN
ajst-15457	2	43	neural	neural	ADJ
ajst-15457	2	44	network	network	NOUN
ajst-15457	2	45	performs	perform	VERB
ajst-15457	2	46	better	well	ADV
ajst-15457	2	47	in	in	ADP
ajst-15457	2	48	terms	term	NOUN
ajst-15457	2	49	of	of	ADP
ajst-15457	2	50	prediction	prediction	NOUN
ajst-15457	2	51	accuracy	accuracy	NOUN
ajst-15457	2	52	and	and	CCONJ
ajst-15457	2	53	stability	stability	NOUN
ajst-15457	2	54	compared	compare	VERB
ajst-15457	2	55	with	with	ADP
ajst-15457	2	56	the	the	DET
ajst-15457	2	57	bp	bp	PROPN
ajst-15457	2	58	neural	neural	ADJ
ajst-15457	2	59	network	network	NOUN
ajst-15457	2	60	.	.	PUNCT
ajst-15457	3	1	keywords	keyword	NOUN
ajst-15457	3	2	:	:	PUNCT
ajst-15457	3	3	continuous	continuous	ADJ
ajst-15457	3	4	oil	oil	NOUN
ajst-15457	3	5	pipeline	pipeline	NOUN
ajst-15457	3	6	;	;	PUNCT
ajst-15457	3	7	life	life	NOUN
ajst-15457	3	8	prediction	prediction	NOUN
ajst-15457	3	9	;	;	PUNCT
ajst-15457	3	10	fully	fully	ADV
ajst-15457	3	11	connected	connected	ADJ
ajst-15457	3	12	neural	neural	ADJ
ajst-15457	3	13	network	network	NOUN
ajst-15457	3	14	;	;	PUNCT
ajst-15457	3	15	gated	gate	VERB
ajst-15457	3	16	cyclic	cyclic	ADJ
ajst-15457	3	17	unit	unit	NOUN
ajst-15457	3	18	.	.	PUNCT
ajst-15457	4	1	1	1	X
ajst-15457	4	2	.	.	X
ajst-15457	4	3	introduction	introduction	NOUN
ajst-15457	4	4	coiled	coil	VERB
ajst-15457	4	5	tubing	tubing	NOUN
ajst-15457	4	6	(	(	PUNCT
ajst-15457	4	7	ct	ct	NOUN
ajst-15457	4	8	)	)	PUNCT
ajst-15457	4	9	is	be	AUX
ajst-15457	4	10	made	make	VERB
ajst-15457	4	11	of	of	ADP
ajst-15457	4	12	low	low	ADJ
ajst-15457	4	13	carbon	carbon	NOUN
ajst-15457	4	14	alloy	alloy	NOUN
ajst-15457	4	15	steel	steel	NOUN
ajst-15457	4	16	and	and	CCONJ
ajst-15457	4	17	is	be	AUX
ajst-15457	4	18	widely	widely	ADV
ajst-15457	4	19	used	use	VERB
ajst-15457	4	20	in	in	ADP
ajst-15457	4	21	various	various	ADJ
ajst-15457	4	22	fields	field	NOUN
ajst-15457	4	23	such	such	ADJ
ajst-15457	4	24	as	as	ADP
ajst-15457	4	25	well	well	ADV
ajst-15457	4	26	workover	workover	PROPN
ajst-15457	4	27	,	,	PUNCT
ajst-15457	4	28	drilling	drill	VERB
ajst-15457	4	29	and	and	CCONJ
ajst-15457	4	30	logging	log	VERB
ajst-15457	4	31	in	in	ADP
ajst-15457	4	32	oil	oil	NOUN
ajst-15457	4	33	and	and	CCONJ
ajst-15457	4	34	gas	gas	NOUN
ajst-15457	4	35	fields	field	NOUN
ajst-15457	4	36	[	[	X
ajst-15457	4	37	1	1	NUM
ajst-15457	4	38	]	]	PUNCT
ajst-15457	4	39	.	.	PUNCT
ajst-15457	5	1	in	in	ADP
ajst-15457	5	2	the	the	DET
ajst-15457	5	3	actual	actual	ADJ
ajst-15457	5	4	working	working	NOUN
ajst-15457	5	5	process	process	NOUN
ajst-15457	5	6	,	,	PUNCT
ajst-15457	5	7	ct	ct	PROPN
ajst-15457	5	8	is	be	AUX
ajst-15457	5	9	prone	prone	ADJ
ajst-15457	5	10	to	to	AUX
ajst-15457	5	11	surface	surface	VERB
ajst-15457	5	12	mechanical	mechanical	ADJ
ajst-15457	5	13	damage	damage	NOUN
ajst-15457	5	14	due	due	ADP
ajst-15457	5	15	to	to	ADP
ajst-15457	5	16	the	the	DET
ajst-15457	5	17	friction	friction	NOUN
ajst-15457	5	18	and	and	CCONJ
ajst-15457	5	19	extrusion	extrusion	NOUN
ajst-15457	5	20	with	with	ADP
ajst-15457	5	21	the	the	DET
ajst-15457	5	22	drum	drum	NOUN
ajst-15457	5	23	,	,	PUNCT
ajst-15457	5	24	injection	injection	NOUN
ajst-15457	5	25	head	head	NOUN
ajst-15457	5	26	,	,	PUNCT
ajst-15457	5	27	well	well	ADV
ajst-15457	5	28	casing	casing	NOUN
ajst-15457	5	29	and	and	CCONJ
ajst-15457	5	30	other	other	ADJ
ajst-15457	5	31	objects	object	NOUN
ajst-15457	5	32	[	[	X
ajst-15457	5	33	2	2	NUM
ajst-15457	5	34	]	]	PUNCT
ajst-15457	5	35	.	.	PUNCT
ajst-15457	6	1	when	when	SCONJ
ajst-15457	6	2	the	the	DET
ajst-15457	6	3	surface	surface	NOUN
ajst-15457	6	4	mechanical	mechanical	ADJ
ajst-15457	6	5	damage	damage	NOUN
ajst-15457	6	6	and	and	CCONJ
ajst-15457	6	7	fatigue	fatigue	NOUN
ajst-15457	6	8	load	load	NOUN
ajst-15457	6	9	act	act	NOUN
ajst-15457	6	10	on	on	ADP
ajst-15457	6	11	the	the	DET
ajst-15457	6	12	tubing	tubing	NOUN
ajst-15457	6	13	body	body	NOUN
ajst-15457	6	14	at	at	ADP
ajst-15457	6	15	the	the	DET
ajst-15457	6	16	same	same	ADJ
ajst-15457	6	17	time	time	NOUN
ajst-15457	6	18	,	,	PUNCT
ajst-15457	6	19	it	it	PRON
ajst-15457	6	20	leads	lead	VERB
ajst-15457	6	21	to	to	ADP
ajst-15457	6	22	fracture	fracture	NOUN
ajst-15457	6	23	failure	failure	NOUN
ajst-15457	6	24	of	of	ADP
ajst-15457	6	25	the	the	DET
ajst-15457	6	26	continuous	continuous	ADJ
ajst-15457	6	27	tubing	tubing	NOUN
ajst-15457	6	28	in	in	ADP
ajst-15457	6	29	serious	serious	ADJ
ajst-15457	6	30	cases	case	NOUN
ajst-15457	6	31	[	[	X
ajst-15457	6	32	3	3	NUM
ajst-15457	6	33	]	]	PUNCT
ajst-15457	6	34	,	,	PUNCT
ajst-15457	6	35	and	and	CCONJ
ajst-15457	6	36	may	may	AUX
ajst-15457	6	37	even	even	ADV
ajst-15457	6	38	lead	lead	VERB
ajst-15457	6	39	to	to	ADP
ajst-15457	6	40	significant	significant	ADJ
ajst-15457	6	41	economic	economic	ADJ
ajst-15457	6	42	losses	loss	NOUN
ajst-15457	6	43	.	.	PUNCT
ajst-15457	7	1	therefore	therefore	ADV
ajst-15457	7	2	,	,	PUNCT
ajst-15457	7	3	timely	timely	ADJ
ajst-15457	7	4	and	and	CCONJ
ajst-15457	7	5	accurate	accurate	ADJ
ajst-15457	7	6	prediction	prediction	NOUN
ajst-15457	7	7	of	of	ADP
ajst-15457	7	8	the	the	DET
ajst-15457	7	9	fatigue	fatigue	NOUN
ajst-15457	7	10	life	life	NOUN
ajst-15457	7	11	of	of	ADP
ajst-15457	7	12	continuous	continuous	ADJ
ajst-15457	7	13	oil	oil	NOUN
ajst-15457	7	14	pipelines	pipeline	NOUN
ajst-15457	7	15	is	be	AUX
ajst-15457	7	16	crucial	crucial	ADJ
ajst-15457	7	17	to	to	PART
ajst-15457	7	18	ensure	ensure	VERB
ajst-15457	7	19	the	the	DET
ajst-15457	7	20	safe	safe	ADJ
ajst-15457	7	21	operation	operation	NOUN
ajst-15457	7	22	of	of	ADP
ajst-15457	7	23	continuous	continuous	ADJ
ajst-15457	7	24	oil	oil	NOUN
ajst-15457	7	25	pipelines	pipeline	NOUN
ajst-15457	7	26	and	and	CCONJ
ajst-15457	7	27	oilfields	oilfield	NOUN
ajst-15457	7	28	.	.	PUNCT
ajst-15457	8	1	joanne	joanne	PROPN
ajst-15457	8	2	ishak	ishak	PROPN
ajst-15457	8	3	et	et	PROPN
ajst-15457	8	4	al.[4	al.[4	PROPN
ajst-15457	8	5	]	]	PUNCT
ajst-15457	8	6	showed	show	VERB
ajst-15457	8	7	that	that	SCONJ
ajst-15457	8	8	small	small	ADJ
ajst-15457	8	9	defects	defect	NOUN
ajst-15457	8	10	occurring	occur	VERB
ajst-15457	8	11	in	in	ADP
ajst-15457	8	12	oilfield	oilfield	NOUN
ajst-15457	8	13	environments	environment	NOUN
ajst-15457	8	14	can	can	AUX
ajst-15457	8	15	significantly	significantly	ADV
ajst-15457	8	16	reduce	reduce	VERB
ajst-15457	8	17	the	the	DET
ajst-15457	8	18	fatigue	fatigue	NOUN
ajst-15457	8	19	life	life	NOUN
ajst-15457	8	20	of	of	ADP
ajst-15457	8	21	continuous	continuous	ADJ
ajst-15457	8	22	pipelines	pipeline	NOUN
ajst-15457	8	23	.	.	PUNCT
ajst-15457	9	1	a	a	DET
ajst-15457	9	2	modified	modify	VERB
ajst-15457	9	3	neuber	neuber	NOUN
ajst-15457	9	4	's	's	PART
ajst-15457	9	5	rule	rule	NOUN
ajst-15457	9	6	was	be	AUX
ajst-15457	9	7	proposed	propose	VERB
ajst-15457	9	8	using	use	VERB
ajst-15457	9	9	notched	notch	VERB
ajst-15457	9	10	root	root	NOUN
ajst-15457	9	11	strain	strain	NOUN
ajst-15457	9	12	results	result	NOUN
ajst-15457	9	13	.	.	PUNCT
ajst-15457	10	1	wan	wan	PROPN
ajst-15457	10	2	f	f	PROPN
ajst-15457	10	3	et	et	PROPN
ajst-15457	10	4	al.[5	al.[5	PROPN
ajst-15457	10	5	]	]	PUNCT
ajst-15457	10	6	an	an	DET
ajst-15457	10	7	evaluation	evaluation	NOUN
ajst-15457	10	8	method	method	NOUN
ajst-15457	10	9	combining	combine	VERB
ajst-15457	10	10	in	in	ADP
ajst-15457	10	11	-	-	PUNCT
ajst-15457	10	12	line	line	NOUN
ajst-15457	10	13	inspection	inspection	NOUN
ajst-15457	10	14	technology	technology	NOUN
ajst-15457	10	15	and	and	CCONJ
ajst-15457	10	16	fatigue	fatigue	NOUN
ajst-15457	10	17	life	life	NOUN
ajst-15457	10	18	can	can	AUX
ajst-15457	10	19	predict	predict	VERB
ajst-15457	10	20	the	the	DET
ajst-15457	10	21	remaining	remain	VERB
ajst-15457	10	22	life	life	NOUN
ajst-15457	10	23	more	more	ADV
ajst-15457	10	24	accurately	accurately	ADV
ajst-15457	10	25	.	.	PUNCT
ajst-15457	11	1	the	the	DET
ajst-15457	11	2	actual	actual	ADJ
ajst-15457	11	3	defect	defect	NOUN
ajst-15457	11	4	size	size	NOUN
ajst-15457	11	5	is	be	AUX
ajst-15457	11	6	further	far	ADV
ajst-15457	11	7	incorporated	incorporate	VERB
ajst-15457	11	8	into	into	ADP
ajst-15457	11	9	the	the	DET
ajst-15457	11	10	fatigue	fatigue	NOUN
ajst-15457	11	11	life	life	NOUN
ajst-15457	11	12	evaluation	evaluation	NOUN
ajst-15457	11	13	calculation	calculation	NOUN
ajst-15457	11	14	to	to	PART
ajst-15457	11	15	eliminate	eliminate	VERB
ajst-15457	11	16	the	the	DET
ajst-15457	11	17	unreliability	unreliability	NOUN
ajst-15457	11	18	of	of	ADP
ajst-15457	11	19	the	the	DET
ajst-15457	11	20	existing	exist	VERB
ajst-15457	11	21	calculation	calculation	NOUN
ajst-15457	11	22	model	model	NOUN
ajst-15457	11	23	that	that	PRON
ajst-15457	11	24	does	do	AUX
ajst-15457	11	25	not	not	PART
ajst-15457	11	26	consider	consider	VERB
ajst-15457	11	27	the	the	DET
ajst-15457	11	28	defect	defect	NOUN
ajst-15457	11	29	influence	influence	NOUN
ajst-15457	11	30	factor	factor	NOUN
ajst-15457	11	31	.	.	PUNCT
ajst-15457	12	1	song	song	PROPN
ajst-15457	12	2	peng	peng	PROPN
ajst-15457	12	3	et	et	PROPN
ajst-15457	12	4	al.[6	al.[6	PROPN
ajst-15457	12	5	]	]	PUNCT
ajst-15457	12	6	proposed	propose	VERB
ajst-15457	12	7	a	a	DET
ajst-15457	12	8	method	method	NOUN
ajst-15457	12	9	to	to	PART
ajst-15457	12	10	construct	construct	VERB
ajst-15457	12	11	a	a	DET
ajst-15457	12	12	fatigue	fatigue	NOUN
ajst-15457	12	13	life	life	NOUN
ajst-15457	12	14	prediction	prediction	NOUN
ajst-15457	12	15	model	model	NOUN
ajst-15457	12	16	for	for	ADP
ajst-15457	12	17	continuous	continuous	ADJ
ajst-15457	12	18	oil	oil	NOUN
ajst-15457	12	19	pipelines	pipeline	NOUN
ajst-15457	12	20	using	use	VERB
ajst-15457	12	21	lmbp	lmbp	NOUN
ajst-15457	12	22	artificial	artificial	ADJ
ajst-15457	12	23	neural	neural	ADJ
ajst-15457	12	24	network	network	NOUN
ajst-15457	12	25	(	(	PUNCT
ajst-15457	12	26	ann	ann	PROPN
ajst-15457	12	27	)	)	PUNCT
ajst-15457	12	28	.	.	PUNCT
ajst-15457	13	1	and	and	CCONJ
ajst-15457	13	2	the	the	DET
ajst-15457	13	3	prediction	prediction	NOUN
ajst-15457	13	4	accuracy	accuracy	NOUN
ajst-15457	13	5	is	be	AUX
ajst-15457	13	6	significantly	significantly	ADV
ajst-15457	13	7	better	well	ADJ
ajst-15457	13	8	than	than	ADP
ajst-15457	13	9	the	the	DET
ajst-15457	13	10	conventional	conventional	ADJ
ajst-15457	13	11	modeling	modeling	NOUN
ajst-15457	13	12	method	method	NOUN
ajst-15457	13	13	.	.	PUNCT
ajst-15457	14	1	yu	yu	PROPN
ajst-15457	14	2	guijie	guijie	PROPN
ajst-15457	15	1	[	[	X
ajst-15457	15	2	7	7	X
ajst-15457	15	3	]	]	PUNCT
ajst-15457	15	4	used	use	VERB
ajst-15457	15	5	sofm	sofm	NOUN
ajst-15457	15	6	and	and	CCONJ
ajst-15457	15	7	rbf	rbf	PROPN
ajst-15457	15	8	to	to	PART
ajst-15457	15	9	construct	construct	VERB
ajst-15457	15	10	a	a	DET
ajst-15457	15	11	hybrid	hybrid	ADJ
ajst-15457	15	12	network	network	NOUN
ajst-15457	15	13	model	model	NOUN
ajst-15457	15	14	to	to	PART
ajst-15457	15	15	predict	predict	VERB
ajst-15457	15	16	the	the	DET
ajst-15457	15	17	life	life	NOUN
ajst-15457	15	18	of	of	ADP
ajst-15457	15	19	continuous	continuous	ADJ
ajst-15457	15	20	oil	oil	NOUN
ajst-15457	15	21	pipeline	pipeline	NOUN
ajst-15457	15	22	..	..	PUNCT
ajst-15457	16	1	no	no	DET
ajst-15457	16	2	scholars	scholar	NOUN
ajst-15457	16	3	have	have	AUX
ajst-15457	16	4	conducted	conduct	VERB
ajst-15457	16	5	research	research	NOUN
ajst-15457	16	6	on	on	ADP
ajst-15457	16	7	the	the	DET
ajst-15457	16	8	fatigue	fatigue	NOUN
ajst-15457	16	9	life	life	NOUN
ajst-15457	16	10	prediction	prediction	NOUN
ajst-15457	16	11	of	of	ADP
ajst-15457	16	12	continuous	continuous	ADJ
ajst-15457	16	13	oil	oil	NOUN
ajst-15457	16	14	pipeline	pipeline	NOUN
ajst-15457	16	15	based	base	VERB
ajst-15457	16	16	on	on	ADP
ajst-15457	16	17	fully	fully	ADV
ajst-15457	16	18	connected	connect	VERB
ajst-15457	16	19	neural	neural	ADJ
ajst-15457	16	20	network	network	NOUN
ajst-15457	16	21	.	.	PUNCT
ajst-15457	17	1	in	in	ADP
ajst-15457	17	2	order	order	NOUN
ajst-15457	17	3	to	to	PART
ajst-15457	17	4	enrich	enrich	VERB
ajst-15457	17	5	the	the	DET
ajst-15457	17	6	fatigue	fatigue	NOUN
ajst-15457	17	7	life	life	NOUN
ajst-15457	17	8	prediction	prediction	NOUN
ajst-15457	17	9	method	method	NOUN
ajst-15457	17	10	of	of	ADP
ajst-15457	17	11	continuous	continuous	ADJ
ajst-15457	17	12	oil	oil	NOUN
ajst-15457	17	13	pipeline	pipeline	NOUN
ajst-15457	17	14	,	,	PUNCT
ajst-15457	17	15	a	a	DET
ajst-15457	17	16	network	network	NOUN
ajst-15457	17	17	model	model	NOUN
ajst-15457	17	18	based	base	VERB
ajst-15457	17	19	on	on	ADP
ajst-15457	17	20	fcnn	fcnn	PROPN
ajst-15457	17	21	-	-	PUNCT
ajst-15457	17	22	gru	gru	NOUN
ajst-15457	17	23	network	network	NOUN
ajst-15457	17	24	is	be	AUX
ajst-15457	17	25	established	establish	VERB
ajst-15457	17	26	to	to	PART
ajst-15457	17	27	predict	predict	VERB
ajst-15457	17	28	the	the	DET
ajst-15457	17	29	life	life	NOUN
ajst-15457	17	30	of	of	ADP
ajst-15457	17	31	continuous	continuous	ADJ
ajst-15457	17	32	oil	oil	NOUN
ajst-15457	17	33	pipeline	pipeline	NOUN
ajst-15457	17	34	.	.	PUNCT
ajst-15457	18	1	2	2	X
ajst-15457	18	2	.	.	X
ajst-15457	18	3	fcnn	fcnn	PROPN
ajst-15457	18	4	-	-	PUNCT
ajst-15457	18	5	gru	gru	NOUN
ajst-15457	18	6	model	model	NOUN
ajst-15457	18	7	construction	construction	NOUN
ajst-15457	18	8	the	the	DET
ajst-15457	18	9	essence	essence	NOUN
ajst-15457	18	10	of	of	ADP
ajst-15457	18	11	fcnn	fcnn	ADJ
ajst-15457	18	12	computation	computation	NOUN
ajst-15457	18	13	is	be	AUX
ajst-15457	18	14	matrix	matrix	NOUN
ajst-15457	18	15	operation	operation	NOUN
ajst-15457	18	16	,	,	PUNCT
ajst-15457	18	17	and	and	CCONJ
ajst-15457	18	18	the	the	DET
ajst-15457	18	19	loss	loss	NOUN
ajst-15457	18	20	value	value	NOUN
ajst-15457	18	21	is	be	AUX
ajst-15457	18	22	reduced	reduce	VERB
ajst-15457	18	23	by	by	ADP
ajst-15457	18	24	forward	forward	ADJ
ajst-15457	18	25	propagation	propagation	NOUN
ajst-15457	18	26	computation	computation	NOUN
ajst-15457	18	27	and	and	CCONJ
ajst-15457	18	28	back	back	ADJ
ajst-15457	18	29	propagation	propagation	NOUN
ajst-15457	18	30	computation	computation	NOUN
ajst-15457	18	31	during	during	ADP
ajst-15457	18	32	the	the	DET
ajst-15457	18	33	computation	computation	NOUN
ajst-15457	18	34	process	process	NOUN
ajst-15457	18	35	,	,	PUNCT
ajst-15457	18	36	which	which	PRON
ajst-15457	18	37	has	have	VERB
ajst-15457	18	38	high	high	ADJ
ajst-15457	18	39	accuracy	accuracy	NOUN
ajst-15457	19	1	[	[	X
ajst-15457	19	2	8].gru	8].gru	NUM
ajst-15457	19	3	can	can	AUX
ajst-15457	19	4	effectively	effectively	ADV
ajst-15457	19	5	solve	solve	VERB
ajst-15457	19	6	the	the	DET
ajst-15457	19	7	problem	problem	NOUN
ajst-15457	19	8	of	of	ADP
ajst-15457	19	9	gradient	gradient	NOUN
ajst-15457	19	10	vanishing	vanishing	NOUN
ajst-15457	19	11	during	during	ADP
ajst-15457	19	12	the	the	DET
ajst-15457	19	13	propagation	propagation	NOUN
ajst-15457	19	14	process	process	NOUN
ajst-15457	19	15	,	,	PUNCT
ajst-15457	19	16	and	and	CCONJ
ajst-15457	19	17	the	the	DET
ajst-15457	19	18	structure	structure	NOUN
ajst-15457	19	19	of	of	ADP
ajst-15457	19	20	the	the	DET
ajst-15457	19	21	network	network	NOUN
ajst-15457	19	22	is	be	AUX
ajst-15457	19	23	simpler	simple	ADJ
ajst-15457	19	24	and	and	CCONJ
ajst-15457	19	25	has	have	VERB
ajst-15457	19	26	fewer	few	ADJ
ajst-15457	19	27	training	training	NOUN
ajst-15457	19	28	parameters	parameter	NOUN
ajst-15457	19	29	compared	compare	VERB
ajst-15457	19	30	to	to	ADP
ajst-15457	19	31	long	long	ADJ
ajst-15457	19	32	short	short	ADJ
ajst-15457	19	33	term	term	NOUN
ajst-15457	19	34	memory	memory	NOUN
ajst-15457	19	35	(	(	PUNCT
ajst-15457	19	36	lstm	lstm	NOUN
ajst-15457	19	37	)	)	PUNCT
ajst-15457	19	38	.	.	PUNCT
ajst-15457	20	1	the	the	DET
ajst-15457	20	2	combination	combination	NOUN
ajst-15457	20	3	of	of	ADP
ajst-15457	20	4	fcnn	fcnn	NOUN
ajst-15457	20	5	and	and	CCONJ
ajst-15457	20	6	gru	gru	PROPN
ajst-15457	20	7	can	can	AUX
ajst-15457	20	8	better	well	ADV
ajst-15457	20	9	handle	handle	VERB
ajst-15457	20	10	flow	flow	NOUN
ajst-15457	20	11	pattern	pattern	NOUN
ajst-15457	20	12	data	datum	NOUN
ajst-15457	20	13	and	and	CCONJ
ajst-15457	20	14	improve	improve	VERB
ajst-15457	20	15	the	the	DET
ajst-15457	20	16	accuracy	accuracy	NOUN
ajst-15457	20	17	of	of	ADP
ajst-15457	20	18	recognizing	recognize	VERB
ajst-15457	20	19	flow	flow	NOUN
ajst-15457	20	20	patterns	pattern	NOUN
ajst-15457	20	21	.	.	PUNCT
ajst-15457	21	1	2.1	2.1	NUM
ajst-15457	21	2	.	.	PUNCT
ajst-15457	22	1	fcnn	fcnn	PROPN
ajst-15457	22	2	model	model	PROPN
ajst-15457	22	3	fcnn	fcnn	PROPN
ajst-15457	22	4	is	be	AUX
ajst-15457	22	5	the	the	DET
ajst-15457	22	6	most	most	ADV
ajst-15457	22	7	basic	basic	ADJ
ajst-15457	22	8	neural	neural	ADJ
ajst-15457	22	9	network	network	NOUN
ajst-15457	22	10	structure	structure	NOUN
ajst-15457	22	11	,	,	PUNCT
ajst-15457	22	12	neurons	neuron	NOUN
ajst-15457	22	13	are	be	AUX
ajst-15457	22	14	a	a	DET
ajst-15457	22	15	nonlinear	nonlinear	ADJ
ajst-15457	22	16	model	model	NOUN
ajst-15457	22	17	with	with	ADP
ajst-15457	22	18	multiple	multiple	ADJ
ajst-15457	22	19	inputs	input	NOUN
ajst-15457	22	20	and	and	CCONJ
ajst-15457	22	21	single	single	ADJ
ajst-15457	22	22	outputs.there	outputs.there	NOUN
ajst-15457	22	23	is	be	AUX
ajst-15457	22	24	only	only	ADV
ajst-15457	22	25	one	one	NUM
ajst-15457	22	26	input	input	NOUN
ajst-15457	22	27	and	and	CCONJ
ajst-15457	22	28	output	output	NOUN
ajst-15457	22	29	layer	layer	NOUN
ajst-15457	22	30	in	in	ADP
ajst-15457	22	31	fcnn	fcnn	NOUN
ajst-15457	22	32	,	,	PUNCT
ajst-15457	22	33	which	which	PRON
ajst-15457	22	34	can	can	AUX
ajst-15457	22	35	contain	contain	VERB
ajst-15457	22	36	multiple	multiple	ADJ
ajst-15457	22	37	hidden	hide	VERB
ajst-15457	22	38	layers	layer	NOUN
ajst-15457	22	39	as	as	SCONJ
ajst-15457	22	40	shown	show	VERB
ajst-15457	22	41	in	in	ADP
ajst-15457	22	42	the	the	DET
ajst-15457	22	43	fcnn	fcnn	PROPN
ajst-15457	22	44	model	model	NOUN
ajst-15457	22	45	diagram	diagram	NOUN
ajst-15457	22	46	in	in	ADP
ajst-15457	22	47	fig	fig	NOUN
ajst-15457	22	48	.	.	PUNCT
ajst-15457	23	1	1	1	X
ajst-15457	23	2	.	.	X
ajst-15457	23	3	figure	figure	NOUN
ajst-15457	23	4	1	1	NUM
ajst-15457	23	5	.	.	PUNCT
ajst-15457	24	1	fcnn	fcnn	PROPN
ajst-15457	24	2	model	model	PROPN
ajst-15457	24	3	diagram	diagram	NOUN
ajst-15457	24	4	between	between	ADP
ajst-15457	24	5	two	two	NUM
ajst-15457	24	6	adjacent	adjacent	ADJ
ajst-15457	24	7	layers	layer	NOUN
ajst-15457	24	8	of	of	ADP
ajst-15457	24	9	fcnn	fcnn	NOUN
ajst-15457	24	10	,	,	PUNCT
ajst-15457	24	11	the	the	DET
ajst-15457	24	12	output	output	NOUN
ajst-15457	24	13	of	of	ADP
ajst-15457	24	14	the	the	DET
ajst-15457	24	15	previous	previous	ADJ
ajst-15457	24	16	layer	layer	NOUN
ajst-15457	24	17	is	be	AUX
ajst-15457	24	18	the	the	DET
ajst-15457	24	19	input	input	NOUN
ajst-15457	24	20	of	of	ADP
ajst-15457	24	21	the	the	DET
ajst-15457	24	22	next	next	ADJ
ajst-15457	24	23	layer	layer	NOUN
ajst-15457	24	24	,	,	PUNCT
ajst-15457	24	25	and	and	CCONJ
ajst-15457	24	26	each	each	DET
ajst-15457	24	27	node	node	NOUN
ajst-15457	24	28	contains	contain	VERB
ajst-15457	24	29	weights	weight	NOUN
ajst-15457	24	30	,	,	PUNCT
ajst-15457	24	31	biases	bias	NOUN
ajst-15457	24	32	,	,	PUNCT
ajst-15457	24	33	and	and	CCONJ
ajst-15457	24	34	activation	activation	NOUN
ajst-15457	24	35	functions	function	NOUN
ajst-15457	24	36	,	,	PUNCT
ajst-15457	24	37	the	the	DET
ajst-15457	24	38	computational	computational	ADJ
ajst-15457	24	39	process	process	NOUN
ajst-15457	24	40	of	of	ADP
ajst-15457	24	41	fcnn	fcnn	PROPN
ajst-15457	24	42	is	be	AUX
ajst-15457	24	43	essentially	essentially	ADV
ajst-15457	24	44	matrix	matrix	NOUN
ajst-15457	24	45	operations	operation	NOUN
ajst-15457	24	46	.	.	PUNCT
ajst-15457	25	1	suppose	suppose	VERB
ajst-15457	25	2	the	the	DET
ajst-15457	25	3	output	output	NOUN
ajst-15457	25	4	of	of	ADP
ajst-15457	25	5	the	the	DET
ajst-15457	25	6	jth	jth	PROPN
ajst-15457	25	7	node	node	NOUN
ajst-15457	25	8	in	in	ADP
ajst-15457	25	9	the	the	DET
ajst-15457	25	10	kth	kth	PROPN
ajst-15457	25	11	layer	layer	NOUN
ajst-15457	25	12	is	be	AUX
ajst-15457	25	13	k	k	PROPN
ajst-15457	25	14	jy	jy	PROPN
ajst-15457	25	15	,	,	PUNCT
ajst-15457	25	16	then	then	ADV
ajst-15457	25	17	the	the	DET
ajst-15457	25	18	correspondence	correspondence	NOUN
ajst-15457	25	19	between	between	ADP
ajst-15457	25	20	it	it	PRON
ajst-15457	25	21	and	and	CCONJ
ajst-15457	25	22	the	the	DET
ajst-15457	25	23	n	n	NOUN
ajst-15457	25	24	nodes	node	NOUN
ajst-15457	25	25	in	in	ADP
ajst-15457	25	26	the	the	DET
ajst-15457	25	27	k-1	k-1	PROPN
ajst-15457	25	28	layer	layer	NOUN
ajst-15457	25	29	is	be	AUX
ajst-15457	25	30	:	:	PUNCT
ajst-15457	25	31	k	k	NOUN
ajst-15457	25	32	1	1	NUM
ajst-15457	25	33	1	1	NUM
ajst-15457	25	34	y	y	PROPN
ajst-15457	25	35	(	(	PUNCT
ajst-15457	25	36	)	)	PUNCT
ajst-15457	25	37			VERB
ajst-15457	25	38			PROPN
ajst-15457	25	39			PROPN
ajst-15457	25	40	n	n	PROPN
ajst-15457	26	1	k	k	PROPN
ajst-15457	26	2	k	k	PROPN
ajst-15457	27	1	k	k	PROPN
ajst-15457	27	2	j	j	PROPN
ajst-15457	28	1	i	i	PRON
ajst-15457	28	2	ij	ij	INTJ
ajst-15457	28	3	ji	ji	INTJ
ajst-15457	29	1	f	f	PROPN
ajst-15457	29	2	y	y	PROPN
ajst-15457	29	3	w	w	PROPN
ajst-15457	29	4	b	b	PROPN
ajst-15457	29	5	(	(	PUNCT
ajst-15457	29	6	1	1	NUM
ajst-15457	29	7	)	)	PUNCT
ajst-15457	29	8	k	k	NOUN
ajst-15457	29	9	ijw	ijw	NOUN
ajst-15457	29	10	where	where	SCONJ
ajst-15457	29	11	is	be	AUX
ajst-15457	29	12	the	the	DET
ajst-15457	29	13	weight	weight	NOUN
ajst-15457	29	14	occupied	occupy	VERB
ajst-15457	29	15	by	by	ADP
ajst-15457	29	16	the	the	DET
ajst-15457	29	17	output	output	NOUN
ajst-15457	29	18	of	of	ADP
ajst-15457	29	19	the	the	DET
ajst-15457	29	20	ith	ith	PROPN
ajst-15457	29	21	node	node	NOUN
ajst-15457	29	22	in	in	ADP
ajst-15457	29	23	layer	layer	NOUN
ajst-15457	29	24	k-1	k-1	PROPN
ajst-15457	29	25	when	when	SCONJ
ajst-15457	29	26	passed	pass	VERB
ajst-15457	29	27	to	to	ADP
ajst-15457	29	28	the	the	DET
ajst-15457	29	29	jth	jth	PROPN
ajst-15457	29	30	node	node	PROPN
ajst-15457	29	31	in	in	ADP
ajst-15457	29	32	layer	layer	NOUN
ajst-15457	29	33	k	k	PROPN
ajst-15457	29	34	,	,	PUNCT
ajst-15457	29	35	k	k	PROPN
ajst-15457	29	36	jb	jb	PROPN
ajst-15457	29	37	is	be	AUX
ajst-15457	29	38	the	the	DET
ajst-15457	29	39	bias	bias	NOUN
ajst-15457	29	40	corresponding	correspond	VERB
ajst-15457	29	41	to	to	ADP
ajst-15457	29	42	the	the	DET
ajst-15457	29	43	jth	jth	PROPN
ajst-15457	29	44	node	node	NOUN
ajst-15457	29	45	in	in	ADP
ajst-15457	29	46	layer	layer	NOUN
ajst-15457	29	47	k	k	NOUN
ajst-15457	29	48	,	,	PUNCT
ajst-15457	29	49	and	and	CCONJ
ajst-15457	29	50	f	f	PROPN
ajst-15457	29	51	is	be	AUX
ajst-15457	29	52	the	the	DET
ajst-15457	29	53	activation	activation	NOUN
ajst-15457	29	54	function	function	NOUN
ajst-15457	29	55	.	.	PUNCT
ajst-15457	30	1	activation	activation	NOUN
ajst-15457	30	2	function	function	NOUN
ajst-15457	30	3	is	be	AUX
ajst-15457	30	4	a	a	DET
ajst-15457	30	5	function	function	NOUN
ajst-15457	30	6	that	that	PRON
ajst-15457	30	7	enhances	enhance	VERB
ajst-15457	30	8	the	the	DET
ajst-15457	30	9	70	70	NUM
ajst-15457	30	10	nonlinearity	nonlinearity	NOUN
ajst-15457	30	11	of	of	ADP
ajst-15457	30	12	the	the	DET
ajst-15457	30	13	network	network	NOUN
ajst-15457	30	14	model	model	NOUN
ajst-15457	30	15	,	,	PUNCT
ajst-15457	30	16	the	the	DET
ajst-15457	30	17	introduction	introduction	NOUN
ajst-15457	30	18	of	of	ADP
ajst-15457	30	19	nonlinear	nonlinear	ADJ
ajst-15457	30	20	transformation	transformation	NOUN
ajst-15457	30	21	as	as	ADP
ajst-15457	30	22	an	an	DET
ajst-15457	30	23	activation	activation	NOUN
ajst-15457	30	24	function	function	NOUN
ajst-15457	30	25	can	can	AUX
ajst-15457	30	26	map	map	VERB
ajst-15457	30	27	the	the	DET
ajst-15457	30	28	input	input	NOUN
ajst-15457	30	29	data	datum	NOUN
ajst-15457	30	30	to	to	ADP
ajst-15457	30	31	a	a	DET
ajst-15457	30	32	higher	high	ADJ
ajst-15457	30	33	dimensional	dimensional	ADJ
ajst-15457	30	34	feature	feature	NOUN
ajst-15457	30	35	space	space	NOUN
ajst-15457	30	36	and	and	CCONJ
ajst-15457	30	37	improve	improve	VERB
ajst-15457	30	38	the	the	DET
ajst-15457	30	39	expressive	expressive	ADJ
ajst-15457	30	40	ability	ability	NOUN
ajst-15457	30	41	of	of	ADP
ajst-15457	30	42	the	the	DET
ajst-15457	30	43	network	network	NOUN
ajst-15457	30	44	,	,	PUNCT
ajst-15457	30	45	the	the	DET
ajst-15457	30	46	commonly	commonly	ADV
ajst-15457	30	47	used	use	VERB
ajst-15457	30	48	activation	activation	NOUN
ajst-15457	30	49	functions	function	NOUN
ajst-15457	30	50	are	be	AUX
ajst-15457	30	51	mainly	mainly	ADV
ajst-15457	30	52	sigmoid	sigmoid	NOUN
ajst-15457	30	53	,	,	PUNCT
ajst-15457	30	54	tanh	tanh	NOUN
ajst-15457	30	55	,	,	PUNCT
ajst-15457	30	56	relu	relu	NOUN
ajst-15457	30	57	,	,	PUNCT
ajst-15457	30	58	leaky	leaky	ADJ
ajst-15457	30	59	relu	relu	NOUN
ajst-15457	30	60	,	,	PUNCT
ajst-15457	30	61	softplus	softplus	NOUN
ajst-15457	30	62	,	,	PUNCT
ajst-15457	30	63	and	and	CCONJ
ajst-15457	30	64	mish	mish	PROPN
ajst-15457	30	65	,	,	PUNCT
ajst-15457	30	66	etc	etc	X
ajst-15457	30	67	.	.	X
ajst-15457	30	68	,	,	PUNCT
ajst-15457	30	69	and	and	CCONJ
ajst-15457	30	70	the	the	DET
ajst-15457	30	71	activation	activation	NOUN
ajst-15457	30	72	function	function	NOUN
ajst-15457	30	73	of	of	ADP
ajst-15457	30	74	each	each	DET
ajst-15457	30	75	activation	activation	NOUN
ajst-15457	30	76	function	function	NOUN
ajst-15457	30	77	is	be	AUX
ajst-15457	30	78	shown	show	VERB
ajst-15457	30	79	in	in	ADP
ajst-15457	30	80	fig	fig	NOUN
ajst-15457	30	81	.	.	PUNCT
ajst-15457	31	1	2	2	X
ajst-15457	31	2	.	.	X
ajst-15457	31	3	figure	figure	NOUN
ajst-15457	31	4	2	2	NUM
ajst-15457	31	5	.	.	PUNCT
ajst-15457	31	6	plot	plot	NOUN
ajst-15457	31	7	of	of	ADP
ajst-15457	31	8	common	common	ADJ
ajst-15457	31	9	activation	activation	NOUN
ajst-15457	31	10	functions	function	NOUN
ajst-15457	31	11	sigmoid	sigmoid	NOUN
ajst-15457	31	12	activation	activation	NOUN
ajst-15457	31	13	function	function	NOUN
ajst-15457	31	14	contains	contain	VERB
ajst-15457	31	15	power	power	NOUN
ajst-15457	31	16	operation	operation	NOUN
ajst-15457	31	17	and	and	CCONJ
ajst-15457	31	18	division	division	NOUN
ajst-15457	31	19	,	,	PUNCT
ajst-15457	31	20	in	in	ADP
ajst-15457	31	21	the	the	DET
ajst-15457	31	22	training	training	NOUN
ajst-15457	31	23	process	process	NOUN
ajst-15457	31	24	of	of	ADP
ajst-15457	31	25	computation	computation	NOUN
ajst-15457	31	26	is	be	AUX
ajst-15457	31	27	large	large	ADJ
ajst-15457	31	28	,	,	PUNCT
ajst-15457	31	29	easy	easy	ADJ
ajst-15457	31	30	to	to	PART
ajst-15457	31	31	appear	appear	VERB
ajst-15457	31	32	gradient	gradient	ADJ
ajst-15457	31	33	disappearance	disappearance	NOUN
ajst-15457	31	34	,	,	PUNCT
ajst-15457	31	35	can	can	AUX
ajst-15457	31	36	not	not	PART
ajst-15457	31	37	complete	complete	VERB
ajst-15457	31	38	the	the	DET
ajst-15457	31	39	deep	deep	ADJ
ajst-15457	31	40	network	network	NOUN
ajst-15457	31	41	training	training	NOUN
ajst-15457	31	42	.	.	PUNCT
ajst-15457	32	1	tanh	tanh	NOUN
ajst-15457	32	2	activation	activation	NOUN
ajst-15457	32	3	function	function	NOUN
ajst-15457	32	4	in	in	ADP
ajst-15457	32	5	the	the	DET
ajst-15457	32	6	positive	positive	ADJ
ajst-15457	32	7	and	and	CCONJ
ajst-15457	32	8	negative	negative	ADJ
ajst-15457	32	9	semiaxis	semiaxis	NOUN
ajst-15457	32	10	of	of	ADP
ajst-15457	32	11	the	the	DET
ajst-15457	32	12	limit	limit	NOUN
ajst-15457	32	13	of	of	ADP
ajst-15457	32	14	the	the	DET
ajst-15457	32	15	case	case	NOUN
ajst-15457	32	16	tends	tend	VERB
ajst-15457	32	17	to	to	ADP
ajst-15457	32	18	1	1	NUM
ajst-15457	32	19	,	,	PUNCT
ajst-15457	32	20	the	the	DET
ajst-15457	32	21	training	training	NOUN
ajst-15457	32	22	is	be	AUX
ajst-15457	32	23	also	also	ADV
ajst-15457	32	24	easy	easy	ADJ
ajst-15457	32	25	to	to	PART
ajst-15457	32	26	appear	appear	VERB
ajst-15457	32	27	gradient	gradient	ADJ
ajst-15457	32	28	disappearance	disappearance	NOUN
ajst-15457	32	29	.	.	PUNCT
ajst-15457	33	1	relu	relu	NOUN
ajst-15457	33	2	activation	activation	NOUN
ajst-15457	33	3	function	function	NOUN
ajst-15457	33	4	,	,	PUNCT
ajst-15457	33	5	although	although	SCONJ
ajst-15457	33	6	to	to	ADP
ajst-15457	33	7	a	a	DET
ajst-15457	33	8	certain	certain	ADJ
ajst-15457	33	9	extent	extent	NOUN
ajst-15457	33	10	to	to	PART
ajst-15457	33	11	improve	improve	VERB
ajst-15457	33	12	the	the	DET
ajst-15457	33	13	gradient	gradient	NOUN
ajst-15457	33	14	disappearance	disappearance	NOUN
ajst-15457	33	15	and	and	CCONJ
ajst-15457	33	16	the	the	DET
ajst-15457	33	17	gradient	gradient	NOUN
ajst-15457	33	18	explosion	explosion	NOUN
ajst-15457	33	19	of	of	ADP
ajst-15457	33	20	the	the	DET
ajst-15457	33	21	problem	problem	NOUN
ajst-15457	33	22	,	,	PUNCT
ajst-15457	33	23	but	but	CCONJ
ajst-15457	33	24	in	in	ADP
ajst-15457	33	25	the	the	DET
ajst-15457	33	26	backward	backward	ADJ
ajst-15457	33	27	propagation	propagation	NOUN
ajst-15457	33	28	process	process	NOUN
ajst-15457	33	29	,	,	PUNCT
ajst-15457	33	30	if	if	SCONJ
ajst-15457	33	31	the	the	DET
ajst-15457	33	32	input	input	NOUN
ajst-15457	33	33	is	be	AUX
ajst-15457	33	34	negative	negative	ADJ
ajst-15457	33	35	,	,	PUNCT
ajst-15457	33	36	the	the	DET
ajst-15457	33	37	gradient	gradient	NOUN
ajst-15457	33	38	will	will	AUX
ajst-15457	33	39	be	be	AUX
ajst-15457	33	40	completely	completely	ADV
ajst-15457	33	41	zero	zero	NUM
ajst-15457	33	42	,	,	PUNCT
ajst-15457	33	43	and	and	CCONJ
ajst-15457	33	44	the	the	DET
ajst-15457	33	45	problem	problem	NOUN
ajst-15457	33	46	of	of	ADP
ajst-15457	33	47	neural	neural	ADJ
ajst-15457	33	48	death	death	NOUN
ajst-15457	33	49	will	will	AUX
ajst-15457	33	50	occur	occur	VERB
ajst-15457	33	51	.	.	PUNCT
ajst-15457	34	1	leaky	leaky	ADJ
ajst-15457	34	2	relu	relu	NOUN
ajst-15457	34	3	activation	activation	NOUN
ajst-15457	34	4	function	function	NOUN
ajst-15457	34	5	can	can	AUX
ajst-15457	34	6	solve	solve	VERB
ajst-15457	34	7	the	the	DET
ajst-15457	34	8	problem	problem	NOUN
ajst-15457	34	9	of	of	ADP
ajst-15457	34	10	neuron	neuron	PROPN
ajst-15457	34	11	death	death	NOUN
ajst-15457	34	12	,	,	PUNCT
ajst-15457	34	13	but	but	CCONJ
ajst-15457	34	14	due	due	ADP
ajst-15457	34	15	to	to	ADP
ajst-15457	34	16	its	its	PRON
ajst-15457	34	17	linearity	linearity	NOUN
ajst-15457	34	18	,	,	PUNCT
ajst-15457	34	19	it	it	PRON
ajst-15457	34	20	can	can	AUX
ajst-15457	34	21	not	not	PART
ajst-15457	34	22	be	be	AUX
ajst-15457	34	23	used	use	VERB
ajst-15457	34	24	for	for	ADP
ajst-15457	34	25	complex	complex	ADJ
ajst-15457	34	26	classification	classification	NOUN
ajst-15457	34	27	.	.	PUNCT
ajst-15457	35	1	softplus	softplus	ADJ
ajst-15457	35	2	,	,	PUNCT
ajst-15457	35	3	although	although	SCONJ
ajst-15457	35	4	it	it	PRON
ajst-15457	35	5	can	can	AUX
ajst-15457	35	6	be	be	AUX
ajst-15457	35	7	derived	derive	VERB
ajst-15457	35	8	everywhere	everywhere	ADV
ajst-15457	35	9	and	and	CCONJ
ajst-15457	35	10	can	can	AUX
ajst-15457	35	11	constrain	constrain	VERB
ajst-15457	35	12	the	the	DET
ajst-15457	35	13	neuron	neuron	NOUN
ajst-15457	35	14	output	output	NOUN
ajst-15457	35	15	to	to	PART
ajst-15457	35	16	be	be	AUX
ajst-15457	35	17	constant	constant	ADJ
ajst-15457	35	18	greater	great	ADJ
ajst-15457	35	19	than	than	ADP
ajst-15457	35	20	0	0	NUM
ajst-15457	35	21	,	,	PUNCT
ajst-15457	35	22	but	but	CCONJ
ajst-15457	35	23	it	it	PRON
ajst-15457	35	24	is	be	AUX
ajst-15457	35	25	not	not	PART
ajst-15457	35	26	centered	center	VERB
ajst-15457	35	27	on	on	ADP
ajst-15457	35	28	0	0	NUM
ajst-15457	35	29	making	make	VERB
ajst-15457	35	30	the	the	DET
ajst-15457	35	31	gradient	gradient	NOUN
ajst-15457	35	32	update	update	NOUN
ajst-15457	35	33	slower	slow	ADV
ajst-15457	35	34	during	during	ADP
ajst-15457	35	35	training	training	NOUN
ajst-15457	35	36	.	.	PUNCT
ajst-15457	36	1	compared	compare	VERB
ajst-15457	36	2	to	to	ADP
ajst-15457	36	3	other	other	ADJ
ajst-15457	36	4	activation	activation	NOUN
ajst-15457	36	5	functions	function	NOUN
ajst-15457	36	6	,	,	PUNCT
ajst-15457	36	7	the	the	DET
ajst-15457	36	8	mish	mish	ADJ
ajst-15457	36	9	activation	activation	NOUN
ajst-15457	36	10	function	function	NOUN
ajst-15457	36	11	is	be	AUX
ajst-15457	36	12	overall	overall	ADV
ajst-15457	36	13	a	a	DET
ajst-15457	36	14	smooth	smooth	ADJ
ajst-15457	36	15	function	function	NOUN
ajst-15457	36	16	with	with	ADP
ajst-15457	36	17	non	non	ADJ
ajst-15457	36	18	-	-	ADJ
ajst-15457	36	19	monotonically	monotonically	ADV
ajst-15457	36	20	smooth	smooth	ADJ
ajst-15457	36	21	variations	variation	NOUN
ajst-15457	36	22	in	in	ADP
ajst-15457	36	23	the	the	DET
ajst-15457	36	24	negative	negative	ADJ
ajst-15457	36	25	semiaxis	semiaxis	NOUN
ajst-15457	36	26	allowing	allow	VERB
ajst-15457	36	27	for	for	ADP
ajst-15457	36	28	better	well	ADJ
ajst-15457	36	29	gradient	gradient	ADJ
ajst-15457	36	30	flow	flow	NOUN
ajst-15457	36	31	,	,	PUNCT
ajst-15457	36	32	which	which	PRON
ajst-15457	36	33	ensures	ensure	VERB
ajst-15457	36	34	better	well	ADJ
ajst-15457	36	35	generalization	generalization	NOUN
ajst-15457	36	36	and	and	CCONJ
ajst-15457	36	37	effective	effective	ADJ
ajst-15457	36	38	optimization	optimization	NOUN
ajst-15457	36	39	capabilities	capability	NOUN
ajst-15457	36	40	,	,	PUNCT
ajst-15457	36	41	with	with	ADP
ajst-15457	36	42	greater	great	ADJ
ajst-15457	36	43	stability	stability	NOUN
ajst-15457	36	44	in	in	ADP
ajst-15457	36	45	deeper	deep	ADJ
ajst-15457	36	46	networks	network	NOUN
ajst-15457	36	47	.	.	PUNCT
ajst-15457	37	1	the	the	DET
ajst-15457	37	2	mish	mish	ADJ
ajst-15457	37	3	activation	activation	NOUN
ajst-15457	37	4	function	function	NOUN
ajst-15457	37	5	is	be	AUX
ajst-15457	37	6	:	:	PUNCT
ajst-15457	37	7	(	(	PUNCT
ajst-15457	37	8	)	)	PUNCT
ajst-15457	37	9	tan	tan	PROPN
ajst-15457	37	10	(	(	PUNCT
ajst-15457	37	11	ln(1	ln(1	NOUN
ajst-15457	37	12	)	)	PUNCT
ajst-15457	37	13	)	)	PUNCT
ajst-15457	38	1			NUM
ajst-15457	38	2			PUNCT
ajst-15457	38	3	xf	xf	PROPN
ajst-15457	38	4	x	x	PUNCT
ajst-15457	38	5	x	x	SYM
ajst-15457	38	6	h	h	NOUN
ajst-15457	38	7	e	e	X
ajst-15457	38	8	(	(	PUNCT
ajst-15457	38	9	2	2	NUM
ajst-15457	38	10	)	)	PUNCT
ajst-15457	38	11	(	(	PUNCT
ajst-15457	38	12	)	)	PUNCT
ajst-15457	38	13	tan	tan	PROPN
ajst-15457	38	14	(	(	PUNCT
ajst-15457	38	15	)	)	PUNCT
ajst-15457	38	16	(	(	PUNCT
ajst-15457	38	17	)	)	PUNCT
ajst-15457	38	18			PROPN
ajst-15457	38	19			PROPN
ajst-15457	38	20			PROPN
ajst-15457	38	21			PRON
ajst-15457	38	22			ADV
ajst-15457	38	23	x	x	PUNCT
ajst-15457	38	24	x	x	PUNCT
ajst-15457	38	25	x	x	PUNCT
ajst-15457	38	26	x	x	PUNCT
ajst-15457	38	27	e	e	X
ajst-15457	38	28	e	e	NOUN
ajst-15457	38	29	h	h	NOUN
ajst-15457	38	30	x	x	PUNCT
ajst-15457	38	31	e	e	X
ajst-15457	38	32	e	e	X
ajst-15457	38	33	(	(	PUNCT
ajst-15457	38	34	3	3	NUM
ajst-15457	38	35	)	)	PUNCT
ajst-15457	38	36	2.2	2.2	NUM
ajst-15457	38	37	.	.	PUNCT
ajst-15457	39	1	gru	gru	PROPN
ajst-15457	39	2	model	model	PROPN
ajst-15457	39	3	gru	gru	PROPN
ajst-15457	39	4	was	be	AUX
ajst-15457	39	5	first	first	ADV
ajst-15457	39	6	proposed	propose	VERB
ajst-15457	39	7	by	by	ADP
ajst-15457	39	8	cho	cho	PROPN
ajst-15457	39	9	et	et	PROPN
ajst-15457	39	10	al	al	PROPN
ajst-15457	39	11	to	to	PART
ajst-15457	39	12	capture	capture	VERB
ajst-15457	39	13	the	the	DET
ajst-15457	39	14	dependencies	dependency	NOUN
ajst-15457	39	15	between	between	ADP
ajst-15457	39	16	different	different	ADJ
ajst-15457	39	17	time	time	NOUN
ajst-15457	39	18	scales.gru	scales.gru	PRON
ajst-15457	39	19	is	be	AUX
ajst-15457	39	20	similar	similar	ADJ
ajst-15457	39	21	in	in	ADP
ajst-15457	39	22	structure	structure	NOUN
ajst-15457	39	23	to	to	ADP
ajst-15457	39	24	lstm	lstm	PROPN
ajst-15457	39	25	,	,	PUNCT
ajst-15457	39	26	which	which	PRON
ajst-15457	39	27	can	can	AUX
ajst-15457	39	28	achieve	achieve	VERB
ajst-15457	39	29	almost	almost	ADV
ajst-15457	39	30	the	the	DET
ajst-15457	39	31	same	same	ADJ
ajst-15457	39	32	prediction	prediction	NOUN
ajst-15457	39	33	as	as	ADP
ajst-15457	39	34	the	the	DET
ajst-15457	39	35	same	same	ADJ
ajst-15457	39	36	,	,	PUNCT
ajst-15457	39	37	and	and	CCONJ
ajst-15457	39	38	is	be	AUX
ajst-15457	39	39	able	able	ADJ
ajst-15457	39	40	to	to	PART
ajst-15457	39	41	solve	solve	VERB
ajst-15457	39	42	the	the	DET
ajst-15457	39	43	problem	problem	NOUN
ajst-15457	39	44	of	of	ADP
ajst-15457	39	45	gradient	gradient	ADJ
ajst-15457	39	46	explosion	explosion	NOUN
ajst-15457	39	47	and	and	CCONJ
ajst-15457	39	48	disappearance	disappearance	NOUN
ajst-15457	39	49	that	that	PRON
ajst-15457	39	50	occurs	occur	VERB
ajst-15457	39	51	in	in	ADP
ajst-15457	39	52	fcnn	fcnn	NOUN
ajst-15457	39	53	in	in	ADP
ajst-15457	39	54	practical	practical	ADJ
ajst-15457	39	55	applications.gru	applications.gru	X
ajst-15457	39	56	contains	contain	VERB
ajst-15457	39	57	only	only	ADV
ajst-15457	39	58	two	two	NUM
ajst-15457	39	59	gate	gate	NOUN
ajst-15457	39	60	structures	structure	NOUN
ajst-15457	39	61	,	,	PUNCT
ajst-15457	39	62	the	the	DET
ajst-15457	39	63	update	update	NOUN
ajst-15457	39	64	gate	gate	PROPN
ajst-15457	39	65	rt	rt	PROPN
ajst-15457	39	66	and	and	CCONJ
ajst-15457	39	67	the	the	DET
ajst-15457	39	68	reset	reset	PROPN
ajst-15457	39	69	gate	gate	NOUN
ajst-15457	39	70	zt	zt	PROPN
ajst-15457	39	71	.	.	PUNCT
ajst-15457	40	1	the	the	DET
ajst-15457	40	2	structure	structure	NOUN
ajst-15457	40	3	of	of	ADP
ajst-15457	40	4	the	the	DET
ajst-15457	40	5	gru	gru	PROPN
ajst-15457	40	6	network	network	NOUN
ajst-15457	40	7	unit	unit	NOUN
ajst-15457	40	8	is	be	AUX
ajst-15457	40	9	shown	show	VERB
ajst-15457	40	10	in	in	ADP
ajst-15457	40	11	fig	fig	NOUN
ajst-15457	40	12	.	.	PUNCT
ajst-15457	41	1	3	3	X
ajst-15457	41	2	.	.	PUNCT
ajst-15457	41	3	compared	compare	VERB
ajst-15457	41	4	with	with	ADP
ajst-15457	41	5	lstm	lstm	PROPN
ajst-15457	41	6	,	,	PUNCT
ajst-15457	41	7	the	the	DET
ajst-15457	41	8	structure	structure	NOUN
ajst-15457	41	9	is	be	AUX
ajst-15457	41	10	simpler	simple	ADJ
ajst-15457	41	11	,	,	PUNCT
ajst-15457	41	12	requires	require	VERB
ajst-15457	41	13	fewer	few	ADJ
ajst-15457	41	14	training	training	NOUN
ajst-15457	41	15	parameters	parameter	NOUN
ajst-15457	41	16	,	,	PUNCT
ajst-15457	41	17	and	and	CCONJ
ajst-15457	41	18	is	be	AUX
ajst-15457	41	19	faster	fast	ADJ
ajst-15457	41	20	to	to	PART
ajst-15457	41	21	train	train	VERB
ajst-15457	41	22	.	.	PUNCT
ajst-15457	42	1	figure	figure	VERB
ajst-15457	42	2	3	3	NUM
ajst-15457	42	3	.	.	PROPN
ajst-15457	42	4	gru	gru	PROPN
ajst-15457	42	5	network	network	NOUN
ajst-15457	42	6	unit	unit	NOUN
ajst-15457	42	7	structure	structure	NOUN
ajst-15457	42	8	in	in	ADP
ajst-15457	42	9	the	the	DET
ajst-15457	42	10	gru	gru	NOUN
ajst-15457	42	11	network	network	NOUN
ajst-15457	42	12	structure	structure	NOUN
ajst-15457	42	13	,	,	PUNCT
ajst-15457	43	1	xt	xt	PROPN
ajst-15457	43	2	is	be	AUX
ajst-15457	43	3	the	the	DET
ajst-15457	43	4	new	new	ADJ
ajst-15457	43	5	input	input	NOUN
ajst-15457	43	6	at	at	ADP
ajst-15457	43	7	the	the	DET
ajst-15457	43	8	current	current	ADJ
ajst-15457	43	9	moment	moment	NOUN
ajst-15457	43	10	and	and	CCONJ
ajst-15457	43	11	ht-1	ht-1	PRON
ajst-15457	43	12	is	be	AUX
ajst-15457	43	13	the	the	DET
ajst-15457	43	14	hidden	hidden	ADJ
ajst-15457	43	15	state	state	NOUN
ajst-15457	43	16	at	at	ADP
ajst-15457	43	17	the	the	DET
ajst-15457	43	18	previous	previous	ADJ
ajst-15457	43	19	moment	moment	NOUN
ajst-15457	43	20	,	,	PUNCT
ajst-15457	43	21	and	and	CCONJ
ajst-15457	43	22	the	the	DET
ajst-15457	43	23	model	model	NOUN
ajst-15457	43	24	equation	equation	NOUN
ajst-15457	43	25	is	be	AUX
ajst-15457	43	26	expressed	express	VERB
ajst-15457	43	27	as	as	ADP
ajst-15457	43	28	[	[	X
ajst-15457	43	29	26	26	NUM
ajst-15457	43	30	]	]	X
ajst-15457	43	31	:	:	PUNCT
ajst-15457	43	32			NOUN
ajst-15457	43	33			SYM
ajst-15457	43	34			NOUN
ajst-15457	43	35			PROPN
ajst-15457	43	36			ADJ
ajst-15457	43	37			NOUN
ajst-15457	43	38			PROPN
ajst-15457	43	39			ADJ
ajst-15457	43	40			NOUN
ajst-15457	43	41			PROPN
ajst-15457	43	42	⊙	⊙	PROPN
ajst-15457	43	43	⊙	⊙	PROPN
ajst-15457	43	44	⊙	⊙	PROPN
ajst-15457	44	1			ADP
ajst-15457	44	2			NUM
ajst-15457	44	3			NUM
ajst-15457	44	4			NUM
ajst-15457	44	5			NUM
ajst-15457	44	6			NUM
ajst-15457	44	7			PRON
ajst-15457	44	8			PROPN
ajst-15457	45	1	x	x	PROPN
ajst-15457	45	2	h	h	NOUN
ajst-15457	46	1	t	t	PROPN
ajst-15457	46	2	z	z	PROPN
ajst-15457	46	3	t	t	PROPN
ajst-15457	46	4	z	z	PROPN
ajst-15457	46	5	t	t	NOUN
ajst-15457	47	1	-1	-1	NOUN
ajst-15457	47	2	z	z	NOUN
ajst-15457	47	3	x	x	PUNCT
ajst-15457	47	4	h	h	NOUN
ajst-15457	47	5	t	t	NOUN
ajst-15457	47	6	r	r	NOUN
ajst-15457	47	7	t	t	PROPN
ajst-15457	47	8	r	r	NOUN
ajst-15457	47	9	t	t	NOUN
ajst-15457	47	10	-1	-1	NOUN
ajst-15457	48	1	r	r	NOUN
ajst-15457	48	2	x	x	PUNCT
ajst-15457	48	3	h	h	NOUN
ajst-15457	48	4	t	t	NOUN
ajst-15457	48	5	h	h	NOUN
ajst-15457	49	1	t	t	PROPN
ajst-15457	49	2	t	t	PROPN
ajst-15457	49	3	h	h	NOUN
ajst-15457	49	4	t	t	PROPN
ajst-15457	49	5	-1	-1	INTJ
ajst-15457	50	1	h	h	PROPN
ajst-15457	51	1	tt	tt	PROPN
ajst-15457	51	2	t	t	PROPN
ajst-15457	51	3	t	t	PROPN
ajst-15457	51	4	t	t	PROPN
ajst-15457	51	5	-1	-1	PUNCT
ajst-15457	51	6	z	z	X
ajst-15457	52	1	=	=	PUNCT
ajst-15457	52	2	s	s	PART
ajst-15457	52	3	w	w	NOUN
ajst-15457	52	4	x	x	X
ajst-15457	53	1	+	+	NUM
ajst-15457	53	2	w	w	PROPN
ajst-15457	53	3	h	h	NOUN
ajst-15457	54	1	+	+	CCONJ
ajst-15457	54	2	b	b	NOUN
ajst-15457	54	3	r	r	NOUN
ajst-15457	54	4	=	=	SYM
ajst-15457	54	5	s	s	PART
ajst-15457	54	6	w	w	NOUN
ajst-15457	54	7	x	x	X
ajst-15457	54	8	+	+	NUM
ajst-15457	54	9	w	w	PROPN
ajst-15457	54	10	h	h	NOUN
ajst-15457	55	1	+	+	CCONJ
ajst-15457	55	2	b	b	PROPN
ajst-15457	55	3	h	h	NOUN
ajst-15457	55	4	=	=	SYM
ajst-15457	55	5	tanh	tanh	PROPN
ajst-15457	55	6	w	w	NOUN
ajst-15457	55	7	x	x	PROPN
ajst-15457	56	1	+	+	CCONJ
ajst-15457	56	2	r	r	NOUN
ajst-15457	56	3	w	w	NOUN
ajst-15457	56	4	h	h	NOUN
ajst-15457	56	5	+	+	CCONJ
ajst-15457	57	1	b	b	PROPN
ajst-15457	57	2	h	h	NOUN
ajst-15457	57	3	=	=	NOUN
ajst-15457	57	4	z	z	NOUN
ajst-15457	57	5	h	h	NOUN
ajst-15457	58	1	+	+	CCONJ
ajst-15457	58	2	1	1	NUM
ajst-15457	58	3	z	z	NOUN
ajst-15457	58	4	h	h	NOUN
ajst-15457	58	5	(	(	PUNCT
ajst-15457	58	6	4	4	NUM
ajst-15457	58	7	)	)	PUNCT
ajst-15457	58	8			NOUN
ajst-15457	58	9	th	th	X
ajst-15457	58	10	is	be	AUX
ajst-15457	58	11	the	the	DET
ajst-15457	58	12	candidate	candidate	NOUN
ajst-15457	58	13	hidden	hide	VERB
ajst-15457	58	14	layer	layer	NOUN
ajst-15457	58	15	state	state	NOUN
ajst-15457	58	16	;	;	PUNCT
ajst-15457	58	17	ht	ht	PROPN
ajst-15457	58	18	is	be	AUX
ajst-15457	58	19	the	the	DET
ajst-15457	58	20	hidden	hide	VERB
ajst-15457	58	21	layer	layer	NOUN
ajst-15457	58	22	state	state	NOUN
ajst-15457	58	23	at	at	ADP
ajst-15457	58	24	time	time	NOUN
ajst-15457	58	25	t	t	PROPN
ajst-15457	58	26	;	;	PUNCT
ajst-15457	58	27	ʘ	ʘ	PROPN
ajst-15457	58	28	denotes	denote	VERB
ajst-15457	58	29	the	the	DET
ajst-15457	58	30	same	same	ADJ
ajst-15457	58	31	-	-	PUNCT
ajst-15457	58	32	or	or	CCONJ
ajst-15457	58	33	operation	operation	NOUN
ajst-15457	58	34	;	;	PUNCT
ajst-15457	58	35	x	x	SYM
ajst-15457	58	36	zw	zw	PROPN
ajst-15457	58	37	,	,	PUNCT
ajst-15457	58	38	h	h	NOUN
ajst-15457	58	39	zw	zw	PROPN
ajst-15457	58	40	,	,	PUNCT
ajst-15457	58	41	x	x	PUNCT
ajst-15457	58	42	rw	rw	NOUN
ajst-15457	58	43	,	,	PUNCT
ajst-15457	58	44	h	h	PROPN
ajst-15457	58	45	rw	rw	PROPN
ajst-15457	58	46	is	be	AUX
ajst-15457	58	47	the	the	DET
ajst-15457	58	48	weighting	weighting	NOUN
ajst-15457	58	49	matrix	matrix	NOUN
ajst-15457	58	50	for	for	ADP
ajst-15457	58	51	each	each	DET
ajst-15457	58	52	door	door	NOUN
ajst-15457	58	53	;	;	PUNCT
ajst-15457	58	54	bz	bz	PROPN
ajst-15457	58	55	,	,	PUNCT
ajst-15457	58	56	br	br	PROPN
ajst-15457	58	57	and	and	CCONJ
ajst-15457	58	58	bh	bh	PROPN
ajst-15457	58	59	is	be	AUX
ajst-15457	58	60	the	the	DET
ajst-15457	58	61	offset	offset	ADJ
ajst-15457	58	62	parameter	parameter	NOUN
ajst-15457	58	63	of	of	ADP
ajst-15457	58	64	the	the	DET
ajst-15457	58	65	respective	respective	ADJ
ajst-15457	58	66	gate	gate	NOUN
ajst-15457	58	67	;	;	PUNCT
ajst-15457	58	68	σ	σ	X
ajst-15457	58	69	is	be	AUX
ajst-15457	58	70	a	a	DET
ajst-15457	58	71	sigmoid	sigmoid	NOUN
ajst-15457	58	72	activation	activation	NOUN
ajst-15457	58	73	function	function	NOUN
ajst-15457	58	74	that	that	PRON
ajst-15457	58	75	can	can	AUX
ajst-15457	58	76	act	act	VERB
ajst-15457	58	77	as	as	ADP
ajst-15457	58	78	a	a	DET
ajst-15457	58	79	gating	gate	VERB
ajst-15457	58	80	signal	signal	NOUN
ajst-15457	58	81	.	.	PUNCT
ajst-15457	59	1	2.3	2.3	NUM
ajst-15457	59	2	.	.	PUNCT
ajst-15457	60	1	regularization	regularization	NOUN
ajst-15457	60	2	techniques	technique	NOUN
ajst-15457	60	3	regularization	regularization	NOUN
ajst-15457	60	4	technique	technique	NOUN
ajst-15457	60	5	refers	refer	VERB
ajst-15457	60	6	to	to	ADP
ajst-15457	60	7	the	the	DET
ajst-15457	60	8	introduction	introduction	NOUN
ajst-15457	60	9	of	of	ADP
ajst-15457	60	10	additional	additional	ADJ
ajst-15457	60	11	information	information	NOUN
ajst-15457	60	12	on	on	ADP
ajst-15457	60	13	the	the	DET
ajst-15457	60	14	original	original	ADJ
ajst-15457	60	15	learning	learning	NOUN
ajst-15457	60	16	model	model	NOUN
ajst-15457	60	17	to	to	PART
ajst-15457	60	18	solve	solve	VERB
ajst-15457	60	19	the	the	DET
ajst-15457	60	20	overfitting	overfitting	NOUN
ajst-15457	60	21	problem[9	problem[9	NOUN
ajst-15457	60	22	]	]	PUNCT
ajst-15457	60	23	.	.	PUNCT
ajst-15457	61	1	commonly	commonly	ADV
ajst-15457	61	2	used	use	VERB
ajst-15457	61	3	regularization	regularization	NOUN
ajst-15457	61	4	schemes	scheme	NOUN
ajst-15457	61	5	mainly	mainly	ADV
ajst-15457	61	6	include	include	VERB
ajst-15457	61	7	l1	l1	PROPN
ajst-15457	61	8	,	,	PUNCT
ajst-15457	61	9	l2	l2	NOUN
ajst-15457	61	10	and	and	CCONJ
ajst-15457	61	11	dropout	dropout	NOUN
ajst-15457	61	12	regularization	regularization	NOUN
ajst-15457	61	13	techniques.the	techniques.the	DET
ajst-15457	61	14	principle	principle	NOUN
ajst-15457	61	15	of	of	ADP
ajst-15457	61	16	dropout	dropout	NOUN
ajst-15457	61	17	regularization	regularization	NOUN
ajst-15457	61	18	technique	technique	NOUN
ajst-15457	61	19	refers	refer	VERB
ajst-15457	61	20	to	to	PART
ajst-15457	61	21	randomly	randomly	VERB
ajst-15457	61	22	culling	cull	VERB
ajst-15457	61	23	with	with	ADP
ajst-15457	61	24	a	a	DET
ajst-15457	61	25	certain	certain	ADJ
ajst-15457	61	26	probability	probability	NOUN
ajst-15457	61	27	during	during	ADP
ajst-15457	61	28	each	each	DET
ajst-15457	61	29	iteration	iteration	NOUN
ajst-15457	61	30	of	of	ADP
ajst-15457	61	31	training	training	NOUN
ajst-15457	61	32	,	,	PUNCT
ajst-15457	61	33	and	and	CCONJ
ajst-15457	61	34	using	use	VERB
ajst-15457	61	35	the	the	DET
ajst-15457	61	36	network	network	NOUN
ajst-15457	61	37	composed	compose	VERB
ajst-15457	61	38	of	of	ADP
ajst-15457	61	39	the	the	DET
ajst-15457	61	40	remaining	remain	VERB
ajst-15457	61	41	neurons	neuron	NOUN
ajst-15457	61	42	to	to	PART
ajst-15457	61	43	train	train	VERB
ajst-15457	61	44	the	the	DET
ajst-15457	61	45	sample	sample	NOUN
ajst-15457	61	46	data	datum	NOUN
ajst-15457	61	47	of	of	ADP
ajst-15457	61	48	this	this	DET
ajst-15457	61	49	iteration	iteration	NOUN
ajst-15457	61	50	,	,	PUNCT
ajst-15457	61	51	as	as	SCONJ
ajst-15457	61	52	shown	show	VERB
ajst-15457	61	53	in	in	ADP
ajst-15457	61	54	figure	figure	NOUN
ajst-15457	61	55	4	4	NUM
ajst-15457	61	56	.	.	PUNCT
ajst-15457	61	57	during	during	ADP
ajst-15457	61	58	the	the	DET
ajst-15457	61	59	training	training	NOUN
ajst-15457	61	60	process	process	NOUN
ajst-15457	61	61	of	of	ADP
ajst-15457	61	62	fully	fully	ADV
ajst-15457	61	63	connected	connect	VERB
ajst-15457	61	64	neural	neural	ADJ
ajst-15457	61	65	networks	network	NOUN
ajst-15457	61	66	,	,	PUNCT
ajst-15457	61	67	the	the	DET
ajst-15457	61	68	dropout	dropout	NOUN
ajst-15457	61	69	mechanism	mechanism	NOUN
ajst-15457	61	70	is	be	AUX
ajst-15457	61	71	employed	employ	VERB
ajst-15457	61	72	to	to	PART
ajst-15457	61	73	significantly	significantly	ADV
ajst-15457	61	74	simplify	simplify	VERB
ajst-15457	61	75	the	the	DET
ajst-15457	61	76	network	network	NOUN
ajst-15457	61	77	structure	structure	NOUN
ajst-15457	61	78	and	and	CCONJ
ajst-15457	61	79	effectively	effectively	ADV
ajst-15457	61	80	prevent	prevent	VERB
ajst-15457	61	81	the	the	DET
ajst-15457	61	82	neural	neural	ADJ
ajst-15457	61	83	network	network	NOUN
ajst-15457	61	84	from	from	ADP
ajst-15457	61	85	overfitting	overfitte	VERB
ajst-15457	61	86	,	,	PUNCT
ajst-15457	61	87	thus	thus	ADV
ajst-15457	61	88	improving	improve	VERB
ajst-15457	61	89	the	the	DET
ajst-15457	61	90	training	training	NOUN
ajst-15457	61	91	efficiency	efficiency	NOUN
ajst-15457	61	92	and	and	CCONJ
ajst-15457	61	93	prediction	prediction	NOUN
ajst-15457	61	94	accuracy	accuracy	NOUN
ajst-15457	61	95	of	of	ADP
ajst-15457	61	96	the	the	DET
ajst-15457	61	97	model	model	NOUN
ajst-15457	61	98	.	.	PUNCT
ajst-15457	62	1	therefore	therefore	ADV
ajst-15457	62	2	,	,	PUNCT
ajst-15457	62	3	the	the	DET
ajst-15457	62	4	dependence	dependence	NOUN
ajst-15457	62	5	of	of	ADP
ajst-15457	62	6	the	the	DET
ajst-15457	62	7	prediction	prediction	NOUN
ajst-15457	62	8	results	result	VERB
ajst-15457	62	9	on	on	ADP
ajst-15457	62	10	the	the	DET
ajst-15457	62	11	hidden	hide	VERB
ajst-15457	62	12	layer	layer	NOUN
ajst-15457	62	13	nodes	node	NOUN
ajst-15457	62	14	is	be	AUX
ajst-15457	62	15	successfully	successfully	ADV
ajst-15457	62	16	reduced	reduce	VERB
ajst-15457	62	17	by	by	ADP
ajst-15457	62	18	applying	apply	VERB
ajst-15457	62	19	the	the	DET
ajst-15457	62	20	dropout	dropout	NOUN
ajst-15457	62	21	regularization	regularization	NOUN
ajst-15457	62	22	technique	technique	NOUN
ajst-15457	62	23	to	to	PART
ajst-15457	62	24	enhance	enhance	VERB
ajst-15457	62	25	the	the	DET
ajst-15457	62	26	generalization	generalization	NOUN
ajst-15457	62	27	ability	ability	NOUN
ajst-15457	62	28	of	of	ADP
ajst-15457	62	29	gru	gru	PROPN
ajst-15457	62	30	.	.	PUNCT
ajst-15457	63	1	71	71	NUM
ajst-15457	63	2	figure	figure	NOUN
ajst-15457	63	3	4	4	NUM
ajst-15457	63	4	.	.	PUNCT
ajst-15457	63	5	schematic	schematic	ADJ
ajst-15457	63	6	diagram	diagram	NOUN
ajst-15457	63	7	of	of	ADP
ajst-15457	63	8	neural	neural	ADJ
ajst-15457	63	9	network	network	NOUN
ajst-15457	63	10	dropout	dropout	NOUN
ajst-15457	63	11	3	3	NUM
ajst-15457	63	12	.	.	PUNCT
ajst-15457	63	13	data	datum	NOUN
ajst-15457	63	14	set	set	VERB
ajst-15457	63	15	and	and	CCONJ
ajst-15457	63	16	experimental	experimental	ADJ
ajst-15457	63	17	environment	environment	NOUN
ajst-15457	63	18	3.1	3.1	NUM
ajst-15457	63	19	.	.	PUNCT
ajst-15457	64	1	data	datum	NOUN
ajst-15457	64	2	set	set	VERB
ajst-15457	64	3	processing	process	VERB
ajst-15457	64	4	the	the	DET
ajst-15457	64	5	dataset	dataset	NOUN
ajst-15457	64	6	used	use	VERB
ajst-15457	64	7	for	for	ADP
ajst-15457	64	8	the	the	DET
ajst-15457	64	9	experiments	experiment	NOUN
ajst-15457	64	10	is	be	AUX
ajst-15457	64	11	derived	derive	VERB
ajst-15457	64	12	from	from	ADP
ajst-15457	64	13	the	the	DET
ajst-15457	64	14	results	result	NOUN
ajst-15457	64	15	of	of	ADP
ajst-15457	64	16	continuous	continuous	ADJ
ajst-15457	64	17	pipeline	pipeline	NOUN
ajst-15457	64	18	fatigue	fatigue	NOUN
ajst-15457	64	19	tests	test	NOUN
ajst-15457	64	20	in	in	ADP
ajst-15457	64	21	literature	literature	NOUN
ajst-15457	64	22	[	[	X
ajst-15457	64	23	10	10	NUM
ajst-15457	64	24	]	]	PUNCT
ajst-15457	64	25	and	and	CCONJ
ajst-15457	64	26	literature	literature	NOUN
ajst-15457	64	27	[	[	X
ajst-15457	64	28	7	7	NUM
ajst-15457	64	29	]	]	PUNCT
ajst-15457	64	30	,	,	PUNCT
ajst-15457	64	31	and	and	CCONJ
ajst-15457	64	32	is	be	AUX
ajst-15457	64	33	summarized	summarize	VERB
ajst-15457	64	34	in	in	ADP
ajst-15457	64	35	a	a	DET
ajst-15457	64	36	total	total	NOUN
ajst-15457	64	37	of	of	ADP
ajst-15457	64	38	20	20	NUM
ajst-15457	64	39	sets	set	NOUN
ajst-15457	64	40	of	of	ADP
ajst-15457	64	41	data	datum	NOUN
ajst-15457	64	42	,	,	PUNCT
ajst-15457	64	43	as	as	SCONJ
ajst-15457	64	44	shown	show	VERB
ajst-15457	64	45	in	in	ADP
ajst-15457	64	46	table	table	NOUN
ajst-15457	64	47	1	1	NUM
ajst-15457	64	48	.	.	PUNCT
ajst-15457	65	1	numbered	number	VERB
ajst-15457	65	2	1	1	NUM
ajst-15457	65	3	-	-	SYM
ajst-15457	65	4	15	15	NUM
ajst-15457	65	5	is	be	AUX
ajst-15457	65	6	the	the	DET
ajst-15457	65	7	training	training	NOUN
ajst-15457	65	8	set	set	NOUN
ajst-15457	65	9	,	,	PUNCT
ajst-15457	65	10	and	and	CCONJ
ajst-15457	65	11	16	16	NUM
ajst-15457	65	12	-	-	SYM
ajst-15457	65	13	20	20	NUM
ajst-15457	65	14	is	be	AUX
ajst-15457	65	15	the	the	DET
ajst-15457	65	16	test	test	NOUN
ajst-15457	65	17	set	set	VERB
ajst-15457	65	18	.	.	PUNCT
ajst-15457	66	1	table	table	NOUN
ajst-15457	66	2	1	1	NUM
ajst-15457	66	3	.	.	PUNCT
ajst-15457	67	1	summary	summary	NOUN
ajst-15457	67	2	of	of	ADP
ajst-15457	67	3	continuous	continuous	ADJ
ajst-15457	67	4	pipeline	pipeline	NOUN
ajst-15457	67	5	fatigue	fatigue	NOUN
ajst-15457	67	6	data	data	NOUN
ajst-15457	67	7	sample	sample	NOUN
ajst-15457	67	8	number	number	NOUN
ajst-15457	67	9	coiled	coil	VERB
ajst-15457	67	10	tubing	tubing	NOUN
ajst-15457	67	11	outer	outer	ADJ
ajst-15457	67	12	diameter	diameter	NOUN
ajst-15457	67	13	/mm	/mm	PUNCT
ajst-15457	67	14	wall	wall	PROPN
ajst-15457	67	15	thickness	thickness	PROPN
ajst-15457	67	16	/mm	/mm	PUNCT
ajst-15457	67	17	bend	bend	ADJ
ajst-15457	67	18	radius	radius	NOUN
ajst-15457	67	19	/mm	/mm	PUNCT
ajst-15457	67	20	internal	internal	ADJ
ajst-15457	67	21	pressure	pressure	NOUN
ajst-15457	67	22	/mpa	/mpa	PUNCT
ajst-15457	67	23	test	test	NOUN
ajst-15457	67	24	cycles	cycle	NOUN
ajst-15457	67	25	frequency	frequency	VERB
ajst-15457	67	26	1	1	NUM
ajst-15457	67	27	31.75	31.75	NUM
ajst-15457	67	28	2.210	2.210	NUM
ajst-15457	67	29	1219.0	1219.0	NUM
ajst-15457	67	30	1.72	1.72	NUM
ajst-15457	67	31	522	522	NUM
ajst-15457	67	32	2	2	NUM
ajst-15457	67	33	31.75	31.75	NUM
ajst-15457	67	34	2.210	2.210	NUM
ajst-15457	67	35	1219.0	1219.0	NUM
ajst-15457	67	36	10.34	10.34	NUM
ajst-15457	67	37	517	517	NUM
ajst-15457	67	38	3	3	NUM
ajst-15457	67	39	31.75	31.75	NUM
ajst-15457	67	40	2.210	2.210	NUM
ajst-15457	67	41	1219.0	1219.0	NUM
ajst-15457	67	42	27.58	27.58	NUM
ajst-15457	67	43	212	212	NUM
ajst-15457	67	44	4	4	NUM
ajst-15457	67	45	31.75	31.75	NUM
ajst-15457	67	46	2.210	2.210	NUM
ajst-15457	67	47	1219.0	1219.0	NUM
ajst-15457	67	48	34.48	34.48	NUM
ajst-15457	67	49	128	128	NUM
ajst-15457	67	50	5	5	NUM
ajst-15457	67	51	38.10	38.10	NUM
ajst-15457	67	52	4.445	4.445	NUM
ajst-15457	67	53	1828.8	1828.8	NUM
ajst-15457	67	54	31.03	31.03	NUM
ajst-15457	67	55	325	325	NUM
ajst-15457	67	56	6	6	NUM
ajst-15457	67	57	38.10	38.10	NUM
ajst-15457	67	58	4.445	4.445	NUM
ajst-15457	67	59	1828.8	1828.8	NUM
ajst-15457	67	60	31.03	31.03	NUM
ajst-15457	67	61	354	354	NUM
ajst-15457	67	62	7	7	NUM
ajst-15457	67	63	44.45	44.45	NUM
ajst-15457	67	64	2.769	2.769	NUM
ajst-15457	67	65	1828.8	1828.8	NUM
ajst-15457	67	66	27.58	27.58	NUM
ajst-15457	67	67	93	93	NUM
ajst-15457	67	68	8	8	NUM
ajst-15457	67	69	44.45	44.45	NUM
ajst-15457	67	70	3.962	3.962	NUM
ajst-15457	67	71	1828.8	1828.8	NUM
ajst-15457	67	72	27.58	27.58	NUM
ajst-15457	67	73	247	247	NUM
ajst-15457	67	74	9	9	NUM
ajst-15457	67	75	44.45	44.45	NUM
ajst-15457	67	76	2.769	2.769	NUM
ajst-15457	67	77	1219.0	1219.0	NUM
ajst-15457	67	78	1.72	1.72	NUM
ajst-15457	67	79	362	362	NUM
ajst-15457	67	80	10	10	NUM
ajst-15457	67	81	44.45	44.45	NUM
ajst-15457	67	82	2.769	2.769	NUM
ajst-15457	67	83	1219.0	1219.0	NUM
ajst-15457	67	84	6.89	6.89	NUM
ajst-15457	67	85	262	262	NUM
ajst-15457	67	86	11	11	NUM
ajst-15457	67	87	44.45	44.45	NUM
ajst-15457	67	88	2.769	2.769	NUM
ajst-15457	67	89	1219.0	1219.0	NUM
ajst-15457	67	90	13.79	13.79	NUM
ajst-15457	67	91	216	216	NUM
ajst-15457	67	92	12	12	NUM
ajst-15457	67	93	44.45	44.45	NUM
ajst-15457	67	94	2.769	2.769	NUM
ajst-15457	67	95	1219.0	1219.0	NUM
ajst-15457	67	96	27.58	27.58	NUM
ajst-15457	67	97	99	99	NUM
ajst-15457	67	98	13	13	NUM
ajst-15457	67	99	44.45	44.45	NUM
ajst-15457	67	100	2.769	2.769	NUM
ajst-15457	67	101	1219.0	1219.0	NUM
ajst-15457	67	102	34.48	34.48	NUM
ajst-15457	67	103	49	49	NUM
ajst-15457	67	104	14	14	NUM
ajst-15457	67	105	44.45	44.45	NUM
ajst-15457	67	106	3.962	3.962	NUM
ajst-15457	67	107	1219.0	1219.0	NUM
ajst-15457	67	108	13.79	13.79	NUM
ajst-15457	67	109	311	311	NUM
ajst-15457	67	110	15	15	NUM
ajst-15457	67	111	44.45	44.45	NUM
ajst-15457	67	112	3.962	3.962	NUM
ajst-15457	67	113	1219.0	1219.0	NUM
ajst-15457	67	114	27.58	27.58	NUM
ajst-15457	67	115	235	235	NUM
ajst-15457	67	116	16	16	NUM
ajst-15457	67	117	60.32	60.32	NUM
ajst-15457	67	118	3.404	3.404	NUM
ajst-15457	67	119	1828.8	1828.8	NUM
ajst-15457	67	120	17.24	17.24	NUM
ajst-15457	67	121	74	74	NUM
ajst-15457	67	122	17	17	NUM
ajst-15457	67	123	31.75	31.75	NUM
ajst-15457	67	124	2.210	2.210	NUM
ajst-15457	67	125	1219.0	1219.0	NUM
ajst-15457	67	126	20.68	20.68	NUM
ajst-15457	67	127	333	333	NUM
ajst-15457	67	128	18	18	NUM
ajst-15457	67	129	38.10	38.10	NUM
ajst-15457	67	130	3.962	3.962	NUM
ajst-15457	67	131	1828.8	1828.8	NUM
ajst-15457	67	132	37.58	37.58	NUM
ajst-15457	67	133	247	247	NUM
ajst-15457	67	134	19	19	NUM
ajst-15457	67	135	44.45	44.45	NUM
ajst-15457	67	136	3.175	3.175	NUM
ajst-15457	67	137	1828.8	1828.8	NUM
ajst-15457	67	138	31.03	31.03	NUM
ajst-15457	67	139	325	325	NUM
ajst-15457	67	140	20	20	NUM
ajst-15457	67	141	44.45	44.45	NUM
ajst-15457	67	142	2.769	2.769	NUM
ajst-15457	67	143	1219.0	1219.0	NUM
ajst-15457	67	144	20.68	20.68	NUM
ajst-15457	67	145	170	170	NUM
ajst-15457	67	146	3.2	3.2	NUM
ajst-15457	67	147	.	.	PUNCT
ajst-15457	68	1	experimental	experimental	ADJ
ajst-15457	68	2	environment	environment	NOUN
ajst-15457	68	3	table	table	NOUN
ajst-15457	68	4	2	2	NUM
ajst-15457	68	5	.	.	PUNCT
ajst-15457	68	6	experimental	experimental	ADJ
ajst-15457	68	7	environment	environment	NOUN
ajst-15457	68	8	name	name	VERB
ajst-15457	68	9	exeperimental	exeperimental	ADJ
ajst-15457	68	10	configuration	configuration	NOUN
ajst-15457	68	11	operating	operating	NOUN
ajst-15457	68	12	system	system	NOUN
ajst-15457	68	13	windows11	windows11	NOUN
ajst-15457	68	14	programming	programming	NOUN
ajst-15457	68	15	language	language	PROPN
ajst-15457	68	16	python	python	NOUN
ajst-15457	68	17	deep	deep	ADJ
ajst-15457	68	18	learning	learning	NOUN
ajst-15457	68	19	framework	framework	NOUN
ajst-15457	68	20	pytorch	pytorch	NOUN
ajst-15457	68	21	cpu	cpu	NOUN
ajst-15457	68	22	intel(r	intel(r	PROPN
ajst-15457	68	23	)	)	PUNCT
ajst-15457	68	24	core(tm	core(tm	NOUN
ajst-15457	68	25	)	)	PUNCT
ajst-15457	68	26	i7	i7	NOUN
ajst-15457	68	27	-	-	PUNCT
ajst-15457	68	28	14700k	14700k	NUM
ajst-15457	68	29	gpu	gpu	PROPN
ajst-15457	68	30	nvidia	nvidia	PROPN
ajst-15457	68	31	geforce	geforce	NOUN
ajst-15457	68	32	rtx	rtx	PROPN
ajst-15457	68	33	4060	4060	NUM
ajst-15457	68	34	12	12	NUM
ajst-15457	69	1	gb	gb	PROPN
ajst-15457	69	2	cuda	cuda	NOUN
ajst-15457	69	3	cuda	cuda	PROPN
ajst-15457	69	4	12.1	12.1	NUM
ajst-15457	69	5	flat	flat	ADV
ajst-15457	69	6	-	-	PUNCT
ajst-15457	69	7	roofed	roof	VERB
ajst-15457	69	8	building	building	NOUN
ajst-15457	69	9	pycharm	pycharm	VERB
ajst-15457	69	10	2022.3	2022.3	NUM
ajst-15457	69	11	3.3	3.3	NUM
ajst-15457	69	12	.	.	PUNCT
ajst-15457	70	1	network	network	NOUN
ajst-15457	70	2	training	train	VERB
ajst-15457	70	3	the	the	DET
ajst-15457	70	4	hyperparameter	hyperparameter	NOUN
ajst-15457	70	5	settings	setting	NOUN
ajst-15457	70	6	for	for	ADP
ajst-15457	70	7	this	this	DET
ajst-15457	70	8	experiment	experiment	NOUN
ajst-15457	70	9	have	have	VERB
ajst-15457	70	10	an	an	DET
ajst-15457	70	11	initial	initial	ADJ
ajst-15457	70	12	learning	learning	NOUN
ajst-15457	70	13	rate	rate	NOUN
ajst-15457	70	14	of	of	ADP
ajst-15457	70	15	0.01,momentum	0.01,momentum	NUM
ajst-15457	70	16	of	of	ADP
ajst-15457	70	17	0.946	0.946	NUM
ajst-15457	70	18	,	,	PUNCT
ajst-15457	70	19	training	training	NOUN
ajst-15457	70	20	number	number	NOUN
ajst-15457	70	21	of	of	ADP
ajst-15457	70	22	200	200	NUM
ajst-15457	70	23	,	,	PUNCT
ajst-15457	70	24	and	and	CCONJ
ajst-15457	70	25	a	a	DET
ajst-15457	70	26	weight	weight	NOUN
ajst-15457	70	27	decay	decay	NOUN
ajst-15457	70	28	rate	rate	NOUN
ajst-15457	70	29	of	of	ADP
ajst-15457	70	30	0.0005	0.0005	NUM
ajst-15457	70	31	using	use	VERB
ajst-15457	70	32	the	the	DET
ajst-15457	70	33	sgd	sgd	PROPN
ajst-15457	70	34	optimizer	optimizer	NOUN
ajst-15457	70	35	.	.	PUNCT
ajst-15457	71	1	4	4	X
ajst-15457	71	2	.	.	X
ajst-15457	71	3	experimental	experimental	ADJ
ajst-15457	71	4	results	result	NOUN
ajst-15457	71	5	and	and	CCONJ
ajst-15457	71	6	analysis	analysis	NOUN
ajst-15457	71	7	the	the	DET
ajst-15457	71	8	evaluation	evaluation	NOUN
ajst-15457	71	9	metrics	metric	NOUN
ajst-15457	71	10	used	use	VERB
ajst-15457	71	11	in	in	ADP
ajst-15457	71	12	this	this	DET
ajst-15457	71	13	experiment	experiment	NOUN
ajst-15457	71	14	are	be	AUX
ajst-15457	71	15	precision	precision	NOUN
ajst-15457	71	16	p	p	X
ajst-15457	71	17	(	(	PUNCT
ajst-15457	71	18	precision	precision	NOUN
ajst-15457	71	19	)	)	PUNCT
ajst-15457	71	20	,	,	PUNCT
ajst-15457	71	21	recall	recall	NOUN
ajst-15457	71	22	r	r	NOUN
ajst-15457	71	23	(	(	PUNCT
ajst-15457	71	24	recall	recall	NOUN
ajst-15457	71	25	)	)	PUNCT
ajst-15457	71	26	,	,	PUNCT
ajst-15457	71	27	average	average	ADJ
ajst-15457	71	28	precision	precision	NOUN
ajst-15457	71	29	ap	ap	PROPN
ajst-15457	71	30	(	(	PUNCT
ajst-15457	71	31	average	average	ADJ
ajst-15457	71	32	precision	precision	NOUN
ajst-15457	71	33	)	)	PUNCT
ajst-15457	71	34	,	,	PUNCT
ajst-15457	71	35	mean	mean	VERB
ajst-15457	71	36	average	average	ADJ
ajst-15457	71	37	precision	precision	NOUN
ajst-15457	71	38	map	map	NOUN
ajst-15457	71	39	(	(	PUNCT
ajst-15457	71	40	meanap	meanap	NOUN
ajst-15457	71	41	,	,	PUNCT
ajst-15457	71	42	map	map	NOUN
ajst-15457	71	43	)	)	PUNCT
ajst-15457	71	44	,	,	PUNCT
ajst-15457	71	45	and	and	CCONJ
ajst-15457	71	46	the	the	DET
ajst-15457	71	47	related	relate	VERB
ajst-15457	71	48	evaluation	evaluation	NOUN
ajst-15457	71	49	metrics	metric	NOUN
ajst-15457	71	50	are	be	AUX
ajst-15457	71	51	:	:	PUNCT
ajst-15457	71	52	tp	tp	ADP
ajst-15457	71	53	p	p	NOUN
ajst-15457	71	54	precision	precision	NOUN
ajst-15457	71	55	=	=	PUNCT
ajst-15457	71	56	tp+fp	tp+fp	PROPN
ajst-15457	71	57	（	（	PUNCT
ajst-15457	71	58	）	）	PUNCT
ajst-15457	72	1	(	(	PUNCT
ajst-15457	72	2	5	5	NUM
ajst-15457	72	3	)	)	PUNCT
ajst-15457	72	4	72	72	NUM
ajst-15457	72	5	tp	tp	NOUN
ajst-15457	72	6	r	r	NOUN
ajst-15457	72	7	recall	recall	NOUN
ajst-15457	72	8	=	=	SYM
ajst-15457	72	9	tp+fn	tp+fn	PROPN
ajst-15457	72	10	（	（	PUNCT
ajst-15457	72	11	）	）	PUNCT
ajst-15457	72	12	(	(	PUNCT
ajst-15457	72	13	6	6	NUM
ajst-15457	72	14	)	)	PUNCT
ajst-15457	72	15	n	n	ADV
ajst-15457	72	16	1	1	NUM
ajst-15457	72	17	0	0	NUM
ajst-15457	72	18	i=1	i=1	PROPN
ajst-15457	73	1	ap=	ap=	PROPN
ajst-15457	73	2	p	p	X
ajst-15457	74	1	i	i	PRON
ajst-15457	74	2	δr	δr	VERB
ajst-15457	74	3	i	i	NOUN
ajst-15457	74	4	=	=	PUNCT
ajst-15457	75	1	p	p	NOUN
ajst-15457	75	2	r	r	NOUN
ajst-15457	75	3	dr	dr	X
ajst-15457	75	4			NOUN
ajst-15457	75	5	（	（	PUNCT
ajst-15457	75	6	）	）	PUNCT
ajst-15457	76	1	（	（	PUNCT
ajst-15457	77	1	）	）	PUNCT
ajst-15457	78	1	（	（	PUNCT
ajst-15457	78	2	）	）	PUNCT
ajst-15457	79	1	(	(	PUNCT
ajst-15457	79	2	7	7	NUM
ajst-15457	79	3	)	)	PUNCT
ajst-15457	79	4	n	n	NOUN
ajst-15457	80	1	i	i	PRON
ajst-15457	80	2	i=1	i=1	PROPN
ajst-15457	80	3	ap	ap	PROPN
ajst-15457	81	1	map=	map=	PROPN
ajst-15457	81	2	n	n	PRON
ajst-15457	81	3			X
ajst-15457	81	4	(	(	PUNCT
ajst-15457	81	5	8)	8)	NUM
ajst-15457	81	6	with	with	ADP
ajst-15457	81	7	the	the	DET
ajst-15457	81	8	continuous	continuous	ADJ
ajst-15457	81	9	training	training	NOUN
ajst-15457	81	10	of	of	ADP
ajst-15457	81	11	the	the	DET
ajst-15457	81	12	model	model	NOUN
ajst-15457	81	13	,	,	PUNCT
ajst-15457	81	14	the	the	DET
ajst-15457	81	15	localization	localization	NOUN
ajst-15457	81	16	loss	loss	NOUN
ajst-15457	81	17	(	(	PUNCT
ajst-15457	81	18	box_loss	box_loss	ADJ
ajst-15457	81	19	)	)	PUNCT
ajst-15457	81	20	and	and	CCONJ
ajst-15457	81	21	classification	classification	NOUN
ajst-15457	81	22	loss	loss	NOUN
ajst-15457	81	23	(	(	PUNCT
ajst-15457	81	24	cls_loss	cls_loss	NOUN
ajst-15457	81	25	)	)	PUNCT
ajst-15457	81	26	of	of	ADP
ajst-15457	81	27	the	the	DET
ajst-15457	81	28	training	training	NOUN
ajst-15457	81	29	set	set	NOUN
ajst-15457	81	30	continue	continue	VERB
ajst-15457	81	31	to	to	PART
ajst-15457	81	32	decrease	decrease	VERB
ajst-15457	81	33	,	,	PUNCT
ajst-15457	81	34	and	and	CCONJ
ajst-15457	81	35	the	the	DET
ajst-15457	81	36	confidence	confidence	NOUN
ajst-15457	81	37	loss	loss	NOUN
ajst-15457	81	38	(	(	PUNCT
ajst-15457	81	39	obj_loss	obj_loss	ADJ
ajst-15457	81	40	)	)	PUNCT
ajst-15457	81	41	of	of	ADP
ajst-15457	81	42	the	the	DET
ajst-15457	81	43	training	training	NOUN
ajst-15457	81	44	set	set	NOUN
ajst-15457	81	45	stabilizes	stabilize	VERB
ajst-15457	81	46	at	at	ADP
ajst-15457	81	47	around	around	ADV
ajst-15457	81	48	0.02	0.02	NUM
ajst-15457	81	49	after	after	ADP
ajst-15457	81	50	100	100	NUM
ajst-15457	81	51	rounds	round	NOUN
ajst-15457	81	52	of	of	ADP
ajst-15457	81	53	training	training	NOUN
ajst-15457	81	54	.	.	PUNCT
ajst-15457	82	1	the	the	DET
ajst-15457	82	2	localization	localization	NOUN
ajst-15457	82	3	loss	loss	NOUN
ajst-15457	82	4	and	and	CCONJ
ajst-15457	82	5	confidence	confidence	NOUN
ajst-15457	82	6	loss	loss	NOUN
ajst-15457	82	7	of	of	ADP
ajst-15457	82	8	the	the	DET
ajst-15457	82	9	validation	validation	NOUN
ajst-15457	82	10	set	set	NOUN
ajst-15457	82	11	stabilized	stabilize	VERB
ajst-15457	82	12	at	at	ADP
ajst-15457	82	13	around	around	ADP
ajst-15457	82	14	0.0025	0.0025	NUM
ajst-15457	82	15	and	and	CCONJ
ajst-15457	82	16	0.003	0.003	NUM
ajst-15457	82	17	respectively	respectively	ADV
ajst-15457	82	18	after	after	ADP
ajst-15457	82	19	150	150	NUM
ajst-15457	82	20	rounds	round	NOUN
ajst-15457	82	21	of	of	ADP
ajst-15457	82	22	training	training	NOUN
ajst-15457	82	23	,	,	PUNCT
ajst-15457	82	24	and	and	CCONJ
ajst-15457	82	25	the	the	DET
ajst-15457	82	26	classification	classification	NOUN
ajst-15457	82	27	loss	loss	NOUN
ajst-15457	82	28	stabilized	stabilize	VERB
ajst-15457	82	29	at	at	ADP
ajst-15457	82	30	around	around	ADP
ajst-15457	82	31	0.001	0.001	NUM
ajst-15457	82	32	.	.	PUNCT
ajst-15457	83	1	the	the	DET
ajst-15457	83	2	improved	improved	ADJ
ajst-15457	83	3	model	model	NOUN
ajst-15457	83	4	has	have	VERB
ajst-15457	83	5	a	a	DET
ajst-15457	83	6	detection	detection	NOUN
ajst-15457	83	7	accuracy	accuracy	NOUN
ajst-15457	83	8	close	close	ADV
ajst-15457	83	9	to	to	ADP
ajst-15457	83	10	0.98	0.98	NUM
ajst-15457	83	11	after	after	ADP
ajst-15457	83	12	150	150	NUM
ajst-15457	83	13	rounds	round	NOUN
ajst-15457	83	14	of	of	ADP
ajst-15457	83	15	training	training	NOUN
ajst-15457	83	16	.	.	PUNCT
ajst-15457	84	1	figure	figure	NOUN
ajst-15457	84	2	5	5	NUM
ajst-15457	84	3	.	.	PUNCT
ajst-15457	84	4	fcnn	fcnn	PROPN
ajst-15457	84	5	-	-	PUNCT
ajst-15457	84	6	gru	gru	PROPN
ajst-15457	84	7	model	model	NOUN
ajst-15457	84	8	effect	effect	PROPN
ajst-15457	84	9	diagram	diagram	VERB
ajst-15457	84	10	4.1	4.1	NUM
ajst-15457	84	11	.	.	PUNCT
ajst-15457	85	1	two	two	NUM
ajst-15457	85	2	network	network	NOUN
ajst-15457	85	3	prediction	prediction	NOUN
ajst-15457	85	4	results	result	VERB
ajst-15457	85	5	in	in	ADP
ajst-15457	85	6	order	order	NOUN
ajst-15457	85	7	to	to	PART
ajst-15457	85	8	test	test	VERB
ajst-15457	85	9	the	the	DET
ajst-15457	85	10	comprehensive	comprehensive	ADJ
ajst-15457	85	11	performance	performance	NOUN
ajst-15457	85	12	of	of	ADP
ajst-15457	85	13	the	the	DET
ajst-15457	85	14	fcnn	fcnn	PROPN
ajst-15457	85	15	-	-	PUNCT
ajst-15457	85	16	gru	gru	NOUN
ajst-15457	85	17	algorithm	algorithm	NOUN
ajst-15457	85	18	,	,	PUNCT
ajst-15457	85	19	a	a	DET
ajst-15457	85	20	bp	bp	PROPN
ajst-15457	85	21	neural	neural	ADJ
ajst-15457	85	22	network	network	NOUN
ajst-15457	85	23	was	be	AUX
ajst-15457	85	24	chosen	choose	VERB
ajst-15457	85	25	to	to	PART
ajst-15457	85	26	train	train	VERB
ajst-15457	85	27	and	and	CCONJ
ajst-15457	85	28	test	test	VERB
ajst-15457	85	29	the	the	DET
ajst-15457	85	30	fcnn	fcnn	PROPN
ajst-15457	85	31	-	-	PUNCT
ajst-15457	85	32	gru	gru	NOUN
ajst-15457	85	33	fractal	fractal	NOUN
ajst-15457	85	34	under	under	ADP
ajst-15457	85	35	the	the	DET
ajst-15457	85	36	same	same	ADJ
ajst-15457	85	37	continuous	continuous	ADJ
ajst-15457	85	38	pipeline	pipeline	NOUN
ajst-15457	85	39	fatigue	fatigue	NOUN
ajst-15457	85	40	dataset	dataset	NOUN
ajst-15457	85	41	,	,	PUNCT
ajst-15457	85	42	training	training	NOUN
ajst-15457	85	43	set	set	NOUN
ajst-15457	85	44	,	,	PUNCT
ajst-15457	85	45	and	and	CCONJ
ajst-15457	85	46	experimental	experimental	ADJ
ajst-15457	85	47	strategy	strategy	NOUN
ajst-15457	85	48	,	,	PUNCT
ajst-15457	85	49	and	and	CCONJ
ajst-15457	85	50	the	the	DET
ajst-15457	85	51	network	network	NOUN
ajst-15457	85	52	test	test	NOUN
ajst-15457	85	53	results	result	NOUN
ajst-15457	85	54	were	be	AUX
ajst-15457	85	55	obtained	obtain	VERB
ajst-15457	85	56	as	as	ADP
ajst-15457	85	57	shown	show	VERB
ajst-15457	85	58	in	in	ADP
ajst-15457	85	59	fig	fig	NOUN
ajst-15457	85	60	.	.	PUNCT
ajst-15457	86	1	6	6	NUM
ajst-15457	86	2	.	.	X
ajst-15457	86	3	(	(	PUNCT
ajst-15457	86	4	a	a	X
ajst-15457	86	5	)	)	PUNCT
ajst-15457	86	6	#	#	SYM
ajst-15457	86	7	8training	8training	NUM
ajst-15457	86	8	samples	sample	NOUN
ajst-15457	86	9	(	(	PUNCT
ajst-15457	86	10	b	b	NOUN
ajst-15457	86	11	)	)	PUNCT
ajst-15457	86	12	#	#	SYM
ajst-15457	86	13	12training	12training	NOUN
ajst-15457	86	14	samples	sample	NOUN
ajst-15457	86	15	figure	figure	VERB
ajst-15457	86	16	6	6	NUM
ajst-15457	86	17	.	.	PUNCT
ajst-15457	86	18	neural	neural	ADJ
ajst-15457	86	19	network	network	NOUN
ajst-15457	86	20	prediction	prediction	NOUN
ajst-15457	86	21	results	result	VERB
ajst-15457	86	22	for	for	ADP
ajst-15457	86	23	samples	sample	NOUN
ajst-15457	86	24	#	#	SYM
ajst-15457	86	25	8	8	NUM
ajst-15457	86	26	and	and	CCONJ
ajst-15457	86	27	#	#	SYM
ajst-15457	86	28	12	12	NUM
ajst-15457	86	29	as	as	SCONJ
ajst-15457	86	30	can	can	AUX
ajst-15457	86	31	be	be	AUX
ajst-15457	86	32	seen	see	VERB
ajst-15457	86	33	from	from	ADP
ajst-15457	86	34	figure	figure	NOUN
ajst-15457	86	35	6	6	NUM
ajst-15457	86	36	,	,	PUNCT
ajst-15457	86	37	the	the	DET
ajst-15457	86	38	two	two	NUM
ajst-15457	86	39	neural	neural	ADJ
ajst-15457	86	40	networks	network	NOUN
ajst-15457	86	41	do	do	VERB
ajst-15457	86	42	15	15	NUM
ajst-15457	86	43	experiments	experiment	NOUN
ajst-15457	86	44	under	under	ADP
ajst-15457	86	45	the	the	DET
ajst-15457	86	46	conditions	condition	NOUN
ajst-15457	86	47	of	of	ADP
ajst-15457	86	48	the	the	DET
ajst-15457	86	49	same	same	ADJ
ajst-15457	86	50	provision	provision	NOUN
ajst-15457	86	51	of	of	ADP
ajst-15457	86	52	training	training	NOUN
ajst-15457	86	53	samples	sample	NOUN
ajst-15457	86	54	and	and	CCONJ
ajst-15457	86	55	experimental	experimental	ADJ
ajst-15457	86	56	strategies	strategy	NOUN
ajst-15457	86	57	,	,	PUNCT
ajst-15457	86	58	the	the	DET
ajst-15457	86	59	test	test	NOUN
ajst-15457	86	60	results	result	NOUN
ajst-15457	86	61	of	of	ADP
ajst-15457	86	62	fcnn	fcnn	PROPN
ajst-15457	86	63	-	-	PUNCT
ajst-15457	86	64	gru	gru	PROPN
ajst-15457	86	65	's	's	PART
ajst-15457	86	66	network	network	NOUN
ajst-15457	86	67	are	be	AUX
ajst-15457	86	68	stable	stable	ADJ
ajst-15457	86	69	,	,	PUNCT
ajst-15457	86	70	while	while	SCONJ
ajst-15457	86	71	the	the	DET
ajst-15457	86	72	test	test	NOUN
ajst-15457	86	73	results	result	NOUN
ajst-15457	86	74	of	of	ADP
ajst-15457	86	75	the	the	DET
ajst-15457	86	76	bp	bp	PROPN
ajst-15457	86	77	neural	neural	PROPN
ajst-15457	86	78	network	network	PROPN
ajst-15457	86	79	fluctuate	fluctuate	NOUN
ajst-15457	86	80	up	up	ADV
ajst-15457	86	81	and	and	CCONJ
ajst-15457	86	82	down	down	ADV
ajst-15457	86	83	around	around	ADP
ajst-15457	86	84	the	the	DET
ajst-15457	86	85	experimental	experimental	ADJ
ajst-15457	86	86	values	value	NOUN
ajst-15457	86	87	,	,	PUNCT
ajst-15457	86	88	which	which	PRON
ajst-15457	86	89	indicates	indicate	VERB
ajst-15457	86	90	that	that	SCONJ
ajst-15457	86	91	the	the	DET
ajst-15457	86	92	overall	overall	ADJ
ajst-15457	86	93	stability	stability	NOUN
ajst-15457	86	94	of	of	ADP
ajst-15457	86	95	the	the	DET
ajst-15457	86	96	fcnn	fcnn	PROPN
ajst-15457	86	97	-	-	PUNCT
ajst-15457	86	98	gru	gru	NOUN
ajst-15457	86	99	network	network	NOUN
ajst-15457	86	100	is	be	AUX
ajst-15457	86	101	better	well	ADJ
ajst-15457	86	102	than	than	ADP
ajst-15457	86	103	that	that	PRON
ajst-15457	86	104	of	of	ADP
ajst-15457	86	105	the	the	DET
ajst-15457	86	106	bp	bp	PROPN
ajst-15457	86	107	neural	neural	ADJ
ajst-15457	86	108	network	network	NOUN
ajst-15457	86	109	,	,	PUNCT
ajst-15457	86	110	and	and	CCONJ
ajst-15457	86	111	thus	thus	ADV
ajst-15457	86	112	the	the	DET
ajst-15457	86	113	fcnn	fcnn	PROPN
ajst-15457	86	114	-	-	PUNCT
ajst-15457	86	115	gru	gru	NOUN
ajst-15457	86	116	neural	neural	ADJ
ajst-15457	86	117	network	network	NOUN
ajst-15457	86	118	has	have	VERB
ajst-15457	86	119	good	good	ADJ
ajst-15457	86	120	accuracy	accuracy	NOUN
ajst-15457	86	121	and	and	CCONJ
ajst-15457	86	122	generalization	generalization	NOUN
ajst-15457	86	123	fcnn	fcnn	SCONJ
ajst-15457	86	124	neural	neural	ADJ
ajst-15457	86	125	networks	network	NOUN
ajst-15457	86	126	have	have	VERB
ajst-15457	86	127	the	the	DET
ajst-15457	86	128	advantages	advantage	NOUN
ajst-15457	86	129	of	of	ADP
ajst-15457	86	130	weight	weight	NOUN
ajst-15457	86	131	sharing	sharing	NOUN
ajst-15457	86	132	and	and	CCONJ
ajst-15457	86	133	local	local	ADJ
ajst-15457	86	134	awareness	awareness	NOUN
ajst-15457	86	135	,	,	PUNCT
ajst-15457	86	136	but	but	CCONJ
ajst-15457	86	137	fcnn	fcnn	NOUN
ajst-15457	86	138	has	have	VERB
ajst-15457	86	139	some	some	DET
ajst-15457	86	140	disadvantages	disadvantage	NOUN
ajst-15457	86	141	in	in	ADP
ajst-15457	86	142	dealing	deal	VERB
ajst-15457	86	143	with	with	ADP
ajst-15457	86	144	time	time	NOUN
ajst-15457	86	145	series	series	PROPN
ajst-15457	86	146	data	data	PROPN
ajst-15457	86	147	,	,	PUNCT
ajst-15457	86	148	while	while	SCONJ
ajst-15457	86	149	gated	gate	VERB
ajst-15457	86	150	recurrent	recurrent	ADJ
ajst-15457	86	151	unit	unit	NOUN
ajst-15457	86	152	(	(	PUNCT
ajst-15457	86	153	gru	gru	PROPN
ajst-15457	86	154	)	)	PUNCT
ajst-15457	86	155	can	can	AUX
ajst-15457	86	156	deal	deal	VERB
ajst-15457	86	157	with	with	ADP
ajst-15457	86	158	the	the	DET
ajst-15457	86	159	problem	problem	NOUN
ajst-15457	86	160	of	of	ADP
ajst-15457	86	161	insufficient	insufficient	ADJ
ajst-15457	86	162	dependence	dependence	NOUN
ajst-15457	86	163	on	on	ADP
ajst-15457	86	164	long	long	ADJ
ajst-15457	86	165	distance	distance	NOUN
ajst-15457	86	166	of	of	ADP
ajst-15457	86	167	time	time	NOUN
ajst-15457	86	168	series	series	NOUN
ajst-15457	86	169	.	.	PUNCT
ajst-15457	87	1	73	73	NUM
ajst-15457	87	2	5	5	NUM
ajst-15457	87	3	.	.	PUNCT
ajst-15457	88	1	concluding	conclude	VERB
ajst-15457	88	2	a	a	DET
ajst-15457	88	3	neural	neural	ADJ
ajst-15457	88	4	network	network	NOUN
ajst-15457	88	5	model	model	NOUN
ajst-15457	88	6	combining	combine	VERB
ajst-15457	88	7	a	a	DET
ajst-15457	88	8	fully	fully	ADV
ajst-15457	88	9	connected	connected	ADJ
ajst-15457	88	10	neural	neural	ADJ
ajst-15457	88	11	network	network	NOUN
ajst-15457	88	12	(	(	PUNCT
ajst-15457	88	13	fcnn	fcnn	PROPN
ajst-15457	88	14	)	)	PUNCT
ajst-15457	88	15	and	and	CCONJ
ajst-15457	88	16	a	a	DET
ajst-15457	88	17	gated	gate	VERB
ajst-15457	88	18	recurrent	recurrent	ADJ
ajst-15457	88	19	unit	unit	NOUN
ajst-15457	88	20	(	(	PUNCT
ajst-15457	88	21	gru	gru	PROPN
ajst-15457	88	22	)	)	PUNCT
ajst-15457	88	23	is	be	AUX
ajst-15457	88	24	applied	apply	VERB
ajst-15457	88	25	to	to	PART
ajst-15457	88	26	predict	predict	VERB
ajst-15457	88	27	the	the	DET
ajst-15457	88	28	fatigue	fatigue	NOUN
ajst-15457	88	29	life	life	NOUN
ajst-15457	88	30	of	of	ADP
ajst-15457	88	31	a	a	DET
ajst-15457	88	32	continuous	continuous	ADJ
ajst-15457	88	33	oil	oil	NOUN
ajst-15457	88	34	pipe	pipe	NOUN
ajst-15457	88	35	.	.	PUNCT
ajst-15457	89	1	among	among	ADP
ajst-15457	89	2	them	they	PRON
ajst-15457	89	3	,	,	PUNCT
ajst-15457	89	4	the	the	DET
ajst-15457	89	5	gru	gru	NOUN
ajst-15457	89	6	,	,	PUNCT
ajst-15457	89	7	as	as	ADP
ajst-15457	89	8	a	a	DET
ajst-15457	89	9	variant	variant	NOUN
ajst-15457	89	10	of	of	ADP
ajst-15457	89	11	the	the	DET
ajst-15457	89	12	rnn	rnn	NOUN
ajst-15457	89	13	,	,	PUNCT
ajst-15457	89	14	has	have	VERB
ajst-15457	89	15	a	a	DET
ajst-15457	89	16	memory	memory	NOUN
ajst-15457	89	17	function	function	NOUN
ajst-15457	89	18	and	and	CCONJ
ajst-15457	89	19	incorporates	incorporate	VERB
ajst-15457	89	20	temporal	temporal	ADJ
ajst-15457	89	21	features	feature	NOUN
ajst-15457	89	22	,	,	PUNCT
ajst-15457	89	23	so	so	SCONJ
ajst-15457	89	24	that	that	SCONJ
ajst-15457	89	25	the	the	DET
ajst-15457	89	26	fcnn	fcnn	PROPN
ajst-15457	89	27	-	-	PUNCT
ajst-15457	89	28	gru	gru	NOUN
ajst-15457	89	29	model	model	NOUN
ajst-15457	89	30	is	be	AUX
ajst-15457	89	31	able	able	ADJ
ajst-15457	89	32	to	to	PART
ajst-15457	89	33	capture	capture	VERB
ajst-15457	89	34	the	the	DET
ajst-15457	89	35	time	time	NOUN
ajst-15457	89	36	nodes	node	NOUN
ajst-15457	89	37	at	at	ADP
ajst-15457	89	38	which	which	PRON
ajst-15457	89	39	the	the	DET
ajst-15457	89	40	degradation	degradation	NOUN
ajst-15457	89	41	characteristics	characteristic	NOUN
ajst-15457	89	42	of	of	ADP
ajst-15457	89	43	the	the	DET
ajst-15457	89	44	continuous	continuous	ADJ
ajst-15457	89	45	pipeline	pipeline	NOUN
ajst-15457	89	46	life	life	NOUN
ajst-15457	89	47	appear	appear	VERB
ajst-15457	89	48	,	,	PUNCT
ajst-15457	89	49	and	and	CCONJ
ajst-15457	89	50	to	to	PART
ajst-15457	89	51	improve	improve	VERB
ajst-15457	89	52	the	the	DET
ajst-15457	89	53	prediction	prediction	NOUN
ajst-15457	89	54	accuracy	accuracy	NOUN
ajst-15457	89	55	of	of	ADP
ajst-15457	89	56	the	the	DET
ajst-15457	89	57	remaining	remain	VERB
ajst-15457	89	58	service	service	NOUN
ajst-15457	89	59	life	life	NOUN
ajst-15457	89	60	of	of	ADP
ajst-15457	89	61	the	the	DET
ajst-15457	89	62	continuous	continuous	ADJ
ajst-15457	89	63	pipeline	pipeline	NOUN
ajst-15457	89	64	.	.	PUNCT
ajst-15457	90	1	references	reference	NOUN
ajst-15457	90	2	[	[	X
ajst-15457	90	3	1	1	X
ajst-15457	90	4	]	]	PUNCT
ajst-15457	90	5	he	he	PRON
ajst-15457	90	6	huiqun	huiqun	VERB
ajst-15457	90	7	(	(	PUNCT
ajst-15457	90	8	china	china	PROPN
ajst-15457	90	9	university	university	PROPN
ajst-15457	90	10	of	of	ADP
ajst-15457	90	11	petroleum	petroleum	PROPN
ajst-15457	90	12	,	,	PUNCT
ajst-15457	90	13	beijing	beijing	PROPN
ajst-15457	90	14	)	)	PUNCT
ajst-15457	90	15	development	development	NOUN
ajst-15457	90	16	of	of	ADP
ajst-15457	90	17	coiled	coil	VERB
ajst-15457	90	18	tubing	tubing	NOUN
ajst-15457	90	19	technique	technique	NOUN
ajst-15457	90	20	and	and	CCONJ
ajst-15457	90	21	equipment	equipment	NOUN
ajst-15457	90	22	.	.	PUNCT
ajst-15457	91	1	cpm	cpm	PROPN
ajst-15457	91	2	,	,	PUNCT
ajst-15457	91	3	2006	2006	NUM
ajst-15457	91	4	,	,	PUNCT
ajst-15457	91	5	34(1	34(1	NUM
ajst-15457	91	6	):	):	PUNCT
ajst-15457	91	7	1~6	1~6	NUM
ajst-15457	91	8	[	[	X
ajst-15457	91	9	2	2	NUM
ajst-15457	91	10	]	]	PUNCT
ajst-15457	91	11	tipton	tipton	PROPN
ajst-15457	91	12	s	s	PART
ajst-15457	91	13	m	m	PROPN
ajst-15457	91	14	,	,	PUNCT
ajst-15457	91	15	carlson	carlson	PROPN
ajst-15457	91	16	g	g	PROPN
ajst-15457	91	17	h	h	PROPN
ajst-15457	91	18	,	,	PUNCT
ajst-15457	91	19	sorem	sorem	VERB
ajst-15457	91	20	j	j	PROPN
ajst-15457	91	21	r	r	NOUN
ajst-15457	91	22	.fatigue	.fatigue	NOUN
ajst-15457	91	23	integrity	integrity	NOUN
ajst-15457	91	24	analysis	analysis	NOUN
ajst-15457	91	25	of	of	ADP
ajst-15457	91	26	rotating	rotate	VERB
ajst-15457	91	27	coiled	coil	VERB
ajst-15457	91	28	tubing	tubing	NOUN
ajst-15457	92	1	[	[	X
ajst-15457	92	2	j	j	X
ajst-15457	92	3	]	]	X
ajst-15457	92	4	.	.	PUNCT
ajst-15457	93	1	society	society	NOUN
ajst-15457	93	2	of	of	ADP
ajst-15457	93	3	petroleum	petroleum	NOUN
ajst-15457	93	4	engineers	engineer	NOUN
ajst-15457	93	5	,	,	PUNCT
ajst-15457	93	6	2006.doi:10.2118/100068	2006.doi:10.2118/100068	NUM
ajst-15457	93	7	-	-	PUNCT
ajst-15457	93	8	ms	ms	NOUN
ajst-15457	93	9	.	.	PUNCT
ajst-15457	94	1	[	[	X
ajst-15457	94	2	3	3	NUM
ajst-15457	94	3	]	]	X
ajst-15457	94	4	li	li	PROPN
ajst-15457	94	5	lei	lei	PROPN
ajst-15457	94	6	et.al	et.al	PROPN
ajst-15457	94	7	.	.	PUNCT
ajst-15457	95	1	an	an	DET
ajst-15457	95	2	experimental	experimental	ADJ
ajst-15457	95	3	study	study	NOUN
ajst-15457	95	4	of	of	ADP
ajst-15457	95	5	the	the	DET
ajst-15457	95	6	coiled	coil	VERB
ajst-15457	95	7	tubing	tubing	NOUN
ajst-15457	95	8	under	under	ADP
ajst-15457	95	9	the	the	DET
ajst-15457	95	10	effect	effect	NOUN
ajst-15457	95	11	of	of	ADP
ajst-15457	95	12	internal	internal	ADJ
ajst-15457	95	13	pressure	pressure	NOUN
ajst-15457	95	14	and	and	CCONJ
ajst-15457	95	15	cyclic	cyclic	ADJ
ajst-15457	95	16	bending	bending	NOUN
ajst-15457	95	17	[	[	X
ajst-15457	95	18	j	j	X
ajst-15457	95	19	]	]	X
ajst-15457	95	20	.	.	PUNCT
ajst-15457	96	1	cpm	cpm	PROPN
ajst-15457	96	2	,	,	PUNCT
ajst-15457	96	3	2011,39(1):5	2011,39(1):5	NOUN
ajst-15457	96	4	-	-	SYM
ajst-15457	96	5	7	7	NUM
ajst-15457	96	6	.	.	PUNCT
ajst-15457	97	1	[	[	X
ajst-15457	97	2	4	4	X
ajst-15457	97	3	]	]	X
ajst-15457	97	4	shak	shak	PROPN
ajst-15457	97	5	j	j	PROPN
ajst-15457	97	6	,	,	PUNCT
ajst-15457	97	7	badr	badr	PROPN
ajst-15457	97	8	e	e	PROPN
ajst-15457	97	9	a.	a.	NOUN
ajst-15457	97	10	a	a	DET
ajst-15457	97	11	modified	modify	VERB
ajst-15457	97	12	rule	rule	NOUN
ajst-15457	97	13	for	for	ADP
ajst-15457	97	14	estimating	estimate	VERB
ajst-15457	97	15	notch	notch	NOUN
ajst-15457	97	16	root	root	NOUN
ajst-15457	97	17	strains	strain	NOUN
ajst-15457	97	18	in	in	ADP
ajst-15457	97	19	ball	ball	NOUN
ajst-15457	97	20	defects	defect	NOUN
ajst-15457	97	21	existing	exist	VERB
ajst-15457	97	22	in	in	ADP
ajst-15457	97	23	coiled	coil	VERB
ajst-15457	97	24	tubing[j	tubing[j	NOUN
ajst-15457	97	25	]	]	PUNCT
ajst-15457	97	26	.	.	PUNCT
ajst-15457	98	1	engineering	engineering	NOUN
ajst-15457	98	2	failure	failure	NOUN
ajst-15457	98	3	analysis	analysis	NOUN
ajst-15457	98	4	,	,	PUNCT
ajst-15457	98	5	2022	2022	NUM
ajst-15457	98	6	,	,	PUNCT
ajst-15457	98	7	134	134	NUM
ajst-15457	98	8	:	:	SYM
ajst-15457	98	9	106026	106026	NUM
ajst-15457	99	1	[	[	X
ajst-15457	99	2	5	5	NUM
ajst-15457	99	3	]	]	PUNCT
ajst-15457	99	4	wanf	wanf	PROPN
ajst-15457	99	5	,	,	PUNCT
ajst-15457	99	6	zhou	zhou	PROPN
ajst-15457	99	7	zhaoming	zhaoming	PROPN
ajst-15457	99	8	,	,	PUNCT
ajst-15457	99	9	zhang	zhang	PROPN
ajst-15457	99	10	jian	jian	PROPN
ajst-15457	99	11	,	,	PUNCT
ajst-15457	99	12	et	et	PROPN
ajst-15457	99	13	al	al	PROPN
ajst-15457	99	14	.	.	PUNCT
ajst-15457	99	15	optimization	optimization	NOUN
ajst-15457	99	16	of	of	ADP
ajst-15457	99	17	fatigue	fatigue	NOUN
ajst-15457	99	18	life	life	NOUN
ajst-15457	99	19	prediction	prediction	NOUN
ajst-15457	99	20	of	of	ADP
ajst-15457	99	21	continuous	continuous	ADJ
ajst-15457	99	22	oil	oil	NOUN
ajst-15457	99	23	pipe	pipe	NOUN
ajst-15457	99	24	based	base	VERB
ajst-15457	99	25	on	on	ADP
ajst-15457	99	26	online	online	ADJ
ajst-15457	99	27	inspection	inspection	NOUN
ajst-15457	99	28	data_wanfu[j	data_wanfu[j	PROPN
ajst-15457	99	29	]	]	PUNCT
ajst-15457	99	30	.	.	PUNCT
ajst-15457	100	1	drilling	drilling	NOUN
ajst-15457	100	2	process	process	NOUN
ajst-15457	100	3	,	,	PUNCT
ajst-15457	100	4	2020	2020	NUM
ajst-15457	100	5	,	,	PUNCT
ajst-15457	100	6	43(06	43(06	NUM
ajst-15457	100	7	):	):	PUNCT
ajst-15457	100	8	9	9	NUM
ajst-15457	100	9	-	-	SYM
ajst-15457	100	10	12	12	NUM
ajst-15457	100	11	,	,	PUNCT
ajst-15457	100	12	6	6	NUM
ajst-15457	100	13	.	.	PUNCT
ajst-15457	101	1	[	[	X
ajst-15457	101	2	6	6	NUM
ajst-15457	101	3	]	]	X
ajst-15457	101	4	peng	peng	PROPN
ajst-15457	101	5	song	song	PROPN
ajst-15457	101	6	,	,	PUNCT
ajst-15457	101	7	zhang	zhang	PROPN
ajst-15457	101	8	quanli	quanli	PROPN
ajst-15457	101	9	,	,	PUNCT
ajst-15457	101	10	wang	wang	PROPN
ajst-15457	101	11	hongwei	hongwei	PROPN
ajst-15457	101	12	,	,	PUNCT
ajst-15457	101	13	et	et	PROPN
ajst-15457	101	14	al	al	PROPN
ajst-15457	101	15	.	.	PROPN
ajst-15457	101	16	fatigue	fatigue	NOUN
ajst-15457	101	17	life	life	NOUN
ajst-15457	101	18	prediction	prediction	NOUN
ajst-15457	101	19	method	method	NOUN
ajst-15457	101	20	of	of	ADP
ajst-15457	101	21	continuous	continuous	ADJ
ajst-15457	101	22	oil	oil	NOUN
ajst-15457	101	23	pipe	pipe	NOUN
ajst-15457	101	24	based	base	VERB
ajst-15457	101	25	on	on	ADP
ajst-15457	101	26	lmbp	lmbp	NOUN
ajst-15457	101	27	neural	neural	PROPN
ajst-15457	101	28	network[j	network[j	PROPN
ajst-15457	101	29	]	]	PUNCT
ajst-15457	101	30	.	.	PUNCT
ajst-15457	102	1	petroleum	petroleum	NOUN
ajst-15457	102	2	pipes	pipe	NOUN
ajst-15457	102	3	and	and	CCONJ
ajst-15457	102	4	instruments	instrument	NOUN
ajst-15457	102	5	,	,	PUNCT
ajst-15457	102	6	2018	2018	NUM
ajst-15457	102	7	,	,	PUNCT
ajst-15457	102	8	4(06	4(06	NUM
ajst-15457	102	9	):	):	PUNCT
ajst-15457	102	10	36	36	NUM
ajst-15457	102	11	-	-	SYM
ajst-15457	102	12	40	40	NUM
ajst-15457	102	13	.	.	PUNCT
ajst-15457	103	1	[	[	X
ajst-15457	103	2	7	7	NUM
ajst-15457	103	3	]	]	X
ajst-15457	103	4	yu	yu	PROPN
ajst-15457	103	5	guijie	guijie	PROPN
ajst-15457	103	6	,	,	PUNCT
ajst-15457	103	7	zhao	zhao	PROPN
ajst-15457	103	8	chong	chong	PROPN
ajst-15457	103	9	,	,	PUNCT
ajst-15457	103	10	chi	chi	PROPN
ajst-15457	103	11	jianwei	jianwei	PROPN
ajst-15457	103	12	,	,	PUNCT
ajst-15457	103	13	et	et	PROPN
ajst-15457	103	14	al	al	PROPN
ajst-15457	103	15	.	.	PROPN
ajst-15457	103	16	fatigue	fatigue	NOUN
ajst-15457	103	17	life	life	NOUN
ajst-15457	103	18	prediction	prediction	NOUN
ajst-15457	103	19	of	of	ADP
ajst-15457	103	20	continuous	continuous	ADJ
ajst-15457	103	21	oil	oil	NOUN
ajst-15457	103	22	pipeline	pipeline	NOUN
ajst-15457	103	23	based	base	VERB
ajst-15457	103	24	on	on	ADP
ajst-15457	103	25	artificial	artificial	ADJ
ajst-15457	103	26	neural	neural	ADJ
ajst-15457	103	27	network[j	network[j	NOUN
ajst-15457	103	28	]	]	PUNCT
ajst-15457	103	29	.	.	PUNCT
ajst-15457	104	1	journal	journal	PROPN
ajst-15457	104	2	of	of	ADP
ajst-15457	104	3	china	china	PROPN
ajst-15457	104	4	university	university	PROPN
ajst-15457	104	5	of	of	ADP
ajst-15457	104	6	petroleum	petroleum	NOUN
ajst-15457	104	7	(	(	PUNCT
ajst-15457	104	8	natural	natural	ADJ
ajst-15457	104	9	science	science	NOUN
ajst-15457	104	10	edition	edition	NOUN
ajst-15457	104	11	)	)	PUNCT
ajst-15457	104	12	,	,	PUNCT
ajst-15457	104	13	2018	2018	NUM
ajst-15457	104	14	,	,	PUNCT
ajst-15457	104	15	42(03	42(03	NOUN
ajst-15457	104	16	):	):	PUNCT
ajst-15457	104	17	131	131	NUM
ajst-15457	104	18	-	-	SYM
ajst-15457	104	19	136	136	NUM
ajst-15457	104	20	[	[	NOUN
ajst-15457	104	21	8	8	NUM
ajst-15457	104	22	]	]	X
ajst-15457	104	23	pratt	pratt	PROPN
ajst-15457	104	24	h	h	PROPN
ajst-15457	104	25	,	,	PUNCT
ajst-15457	104	26	williams	williams	PROPN
ajst-15457	104	27	b	b	PROPN
ajst-15457	104	28	,	,	PUNCT
ajst-15457	104	29	coenen	coenen	PROPN
ajst-15457	104	30	f	f	PROPN
ajst-15457	104	31	,	,	PUNCT
ajst-15457	104	32	et	et	PROPN
ajst-15457	104	33	al	al	PROPN
ajst-15457	104	34	.	.	PUNCT
ajst-15457	105	1	fcnn	fcnn	PROPN
ajst-15457	105	2	:	:	PUNCT
ajst-15457	105	3	fourier	fourier	ADJ
ajst-15457	105	4	convolutional	convolutional	ADJ
ajst-15457	105	5	neural	neural	ADJ
ajst-15457	105	6	networks[c]//machine	networks[c]//machine	PROPN
ajst-15457	105	7	learning	learning	NOUN
ajst-15457	105	8	and	and	CCONJ
ajst-15457	105	9	knowledge	knowledge	NOUN
ajst-15457	105	10	discovery	discovery	NOUN
ajst-15457	105	11	in	in	ADP
ajst-15457	105	12	databases	database	NOUN
ajst-15457	105	13	:	:	PUNCT
ajst-15457	105	14	european	european	ADJ
ajst-15457	105	15	conference	conference	NOUN
ajst-15457	105	16	,	,	PUNCT
ajst-15457	105	17	ecml	ecml	PROPN
ajst-15457	105	18	pkdd	pkdd	NOUN
ajst-15457	105	19	2017	2017	NUM
ajst-15457	105	20	,	,	PUNCT
ajst-15457	105	21	skopje	skopje	PROPN
ajst-15457	105	22	,	,	PUNCT
ajst-15457	105	23	macedonia	macedonia	PROPN
ajst-15457	105	24	,	,	PUNCT
ajst-15457	105	25	september	september	PROPN
ajst-15457	105	26	18–22	18–22	NUM
ajst-15457	105	27	,	,	PUNCT
ajst-15457	105	28	2017	2017	NUM
ajst-15457	105	29	,	,	PUNCT
ajst-15457	105	30	proceedings	proceeding	NOUN
ajst-15457	105	31	,	,	PUNCT
ajst-15457	105	32	part	part	NOUN
ajst-15457	105	33	i	i	PRON
ajst-15457	105	34	17	17	NUM
ajst-15457	105	35	.	.	PUNCT
ajst-15457	106	1	springer	springer	NOUN
ajst-15457	106	2	international	international	ADJ
ajst-15457	106	3	publishing	publishing	NOUN
ajst-15457	106	4	,	,	PUNCT
ajst-15457	106	5	2017	2017	NUM
ajst-15457	106	6	:	:	PUNCT
ajst-15457	106	7	786	786	NUM
ajst-15457	106	8	-	-	SYM
ajst-15457	106	9	798	798	NUM
ajst-15457	106	10	.	.	PUNCT
ajst-15457	107	1	[	[	X
ajst-15457	107	2	9	9	NUM
ajst-15457	107	3	]	]	X
ajst-15457	107	4	huang	huang	PROPN
ajst-15457	107	5	bingjia	bingjia	PROPN
ajst-15457	107	6	,	,	PUNCT
ajst-15457	107	7	wang	wang	PROPN
ajst-15457	107	8	jian	jian	PROPN
ajst-15457	107	9	,	,	PUNCT
ajst-15457	107	10	wen	wen	PROPN
ajst-15457	107	11	yanqing	yanqing	PROPN
ajst-15457	107	12	,	,	PUNCT
ajst-15457	107	13	et	et	PROPN
ajst-15457	107	14	al	al	PROPN
ajst-15457	107	15	.	.	PROPN
ajst-15457	107	16	convergence	convergence	NOUN
ajst-15457	107	17	analysis	analysis	NOUN
ajst-15457	107	18	of	of	ADP
ajst-15457	107	19	inverse	inverse	ADJ
ajst-15457	107	20	iterative	iterative	NOUN
ajst-15457	107	21	algorithms	algorithm	NOUN
ajst-15457	107	22	forneural	forneural	ADJ
ajst-15457	107	23	networks	network	NOUN
ajst-15457	107	24	with	with	ADP
ajst-15457	107	25	l(1/2)penalty	l(1/2)penalty	PROPN
ajst-15457	107	26	[	[	X
ajst-15457	107	27	j	j	X
ajst-15457	107	28	]	]	X
ajst-15457	107	29	.	.	PUNCT
ajst-15457	108	1	journal	journal	PROPN
ajst-15457	108	2	of	of	ADP
ajst-15457	108	3	chi	chi	PROPN
ajst-15457	108	4	-	-	PUNCT
ajst-15457	108	5	na	na	NOUN
ajst-15457	108	6	university	university	NOUN
ajst-15457	108	7	of	of	ADP
ajst-15457	108	8	petroleum(edition	petroleum(edition	NOUN
ajst-15457	108	9	of	of	ADP
ajst-15457	108	10	natural	natural	ADJ
ajst-15457	108	11	sci	sci	PROPN
ajst-15457	108	12	-	-	PUNCT
ajst-15457	108	13	ence	ence	NOUN
ajst-15457	108	14	)	)	PUNCT
ajst-15457	108	15	,	,	PUNCT
ajst-15457	108	16	2015	2015	NUM
ajst-15457	108	17	,	,	PUNCT
ajst-15457	108	18	39(2	39(2	NUM
ajst-15457	108	19	):	):	PUNCT
ajst-15457	108	20	164170	164170	NUM
ajst-15457	108	21	.	.	PUNCT
ajst-15457	109	1	[	[	X
ajst-15457	109	2	10	10	NUM
ajst-15457	109	3	]	]	X
ajst-15457	109	4	newman	newman	PROPN
ajst-15457	109	5	kr	kr	PROPN
ajst-15457	109	6	,	,	PUNCT
ajst-15457	109	7	brown	brown	NOUN
ajst-15457	110	1	p	p	NOUN
ajst-15457	110	2	a	a	NOUN
ajst-15457	110	3	,	,	PUNCT
ajst-15457	110	4	development	development	NOUN
ajst-15457	110	5	of	of	ADP
ajst-15457	110	6	a	a	DET
ajst-15457	110	7	standardcoiled－tubing	standardcoiled－tube	VERB
ajst-15457	110	8	fatigue	fatigue	NOUN
ajst-15457	110	9	test	test	NOUN
ajst-15457	110	10	[	[	X
ajst-15457	110	11	c]//paper	c]//paper	PROPN
ajst-15457	110	12	presented	present	VERB
ajst-15457	110	13	at	at	ADP
ajst-15457	110	14	the	the	DET
ajst-15457	110	15	spe	spe	PROPN
ajst-15457	110	16	an	an	PROPN
ajst-15457	110	17	-	-	PUNCT
ajst-15457	110	18	nual	nual	ADJ
ajst-15457	110	19	technical	technical	ADJ
ajst-15457	110	20	conference	conference	NOUN
ajst-15457	110	21	and	and	CCONJ
ajst-15457	110	22	exhibition	exhibition	NOUN
ajst-15457	110	23	,	,	PUNCT
ajst-15457	110	24	houston	houston	PROPN
ajst-15457	110	25	,	,	PUNCT
ajst-15457	110	26	texas	texas	PROPN
ajst-15457	110	27	,	,	PUNCT
ajst-15457	110	28	usa	usa	PROPN
ajst-15457	110	29	:	:	PUNCT
ajst-15457	110	30	society	society	NOUN
ajst-15457	110	31	of	of	ADP
ajst-15457	110	32	petroleum	petroleum	NOUN
ajst-15457	110	33	engineers	engineer	NOUN
ajst-15457	110	34	,	,	PUNCT
ajst-15457	110	35	1993,3	1993,3	NUM
ajst-15457	110	36	-	-	SYM
ajst-15457	110	37	6	6	NUM
ajst-15457	110	38	.	.	PUNCT