id	sid	tid	token	lemma	pos
ajst-13407	1	1	academic	academic	ADJ
ajst-13407	1	2	journal	journal	NOUN
ajst-13407	1	3	of	of	ADP
ajst-13407	1	4	science	science	NOUN
ajst-13407	1	5	and	and	CCONJ
ajst-13407	1	6	technology	technology	NOUN
ajst-13407	1	7	issn	issn	NOUN
ajst-13407	1	8	:	:	PUNCT
ajst-13407	1	9	2771	2771	NUM
ajst-13407	1	10	-	-	SYM
ajst-13407	1	11	3032	3032	NUM
ajst-13407	1	12	|	|	NOUN
ajst-13407	1	13	vol	vol	NOUN
ajst-13407	1	14	.	.	PROPN
ajst-13407	2	1	7	7	NUM
ajst-13407	2	2	,	,	PUNCT
ajst-13407	2	3	no	no	INTJ
ajst-13407	2	4	.	.	NOUN
ajst-13407	2	5	3	3	NUM
ajst-13407	2	6	,	,	PUNCT
ajst-13407	2	7	2023	2023	NUM
ajst-13407	2	8	248	248	NUM
ajst-13407	2	9	research	research	NOUN
ajst-13407	2	10	on	on	ADP
ajst-13407	2	11	the	the	DET
ajst-13407	2	12	noise	noise	NOUN
ajst-13407	2	13	suppression	suppression	NOUN
ajst-13407	2	14	of	of	ADP
ajst-13407	2	15	the	the	DET
ajst-13407	2	16	tem	tem	PROPN
ajst-13407	2	17	signal	signal	NOUN
ajst-13407	2	18	by	by	ADP
ajst-13407	2	19	neural	neural	ADJ
ajst-13407	2	20	network	network	PROPN
ajst-13407	2	21	huihui	huihui	PROPN
ajst-13407	2	22	sun1	sun1	PROPN
ajst-13407	2	23	,	,	PUNCT
ajst-13407	2	24	lijun	lijun	PROPN
ajst-13407	2	25	liu2	liu2	PROPN
ajst-13407	2	26	,	,	PUNCT
ajst-13407	2	27	bingxuan	bingxuan	PROPN
ajst-13407	2	28	du3	du3	PROPN
ajst-13407	2	29	,	,	PUNCT
ajst-13407	2	30	*	*	SYM
ajst-13407	2	31	1	1	NUM
ajst-13407	2	32	department	department	NOUN
ajst-13407	2	33	of	of	ADP
ajst-13407	2	34	instrumentation	instrumentation	NOUN
ajst-13407	2	35	and	and	CCONJ
ajst-13407	2	36	electrical	electrical	ADJ
ajst-13407	2	37	engineering	engineering	NOUN
ajst-13407	2	38	jilin	jilin	PROPN
ajst-13407	2	39	university	university	PROPN
ajst-13407	2	40	,	,	PUNCT
ajst-13407	2	41	changchun	changchun	NOUN
ajst-13407	2	42	130026	130026	NUM
ajst-13407	2	43	,	,	PUNCT
ajst-13407	2	44	china	china	PROPN
ajst-13407	2	45	2	2	NUM
ajst-13407	2	46	state	state	NOUN
ajst-13407	2	47	grid	grid	NOUN
ajst-13407	2	48	jilin	jilin	PROPN
ajst-13407	2	49	marketing	marketing	PROPN
ajst-13407	2	50	service	service	NOUN
ajst-13407	2	51	center	center	NOUN
ajst-13407	2	52	,	,	PUNCT
ajst-13407	2	53	changchun	changchun	NOUN
ajst-13407	2	54	130062	130062	NUM
ajst-13407	2	55	,	,	PUNCT
ajst-13407	2	56	china	china	PROPN
ajst-13407	2	57	3	3	NUM
ajst-13407	2	58	state	state	NOUN
ajst-13407	2	59	grid	grid	NOUN
ajst-13407	2	60	zhejiang	zhejiang	PROPN
ajst-13407	2	61	ningbo	ningbo	PROPN
ajst-13407	2	62	power	power	PROPN
ajst-13407	2	63	supply	supply	PROPN
ajst-13407	2	64	co.	co.	PROPN
ajst-13407	2	65	,	,	PUNCT
ajst-13407	2	66	ltd	ltd	PROPN
ajst-13407	2	67	.	.	PROPN
ajst-13407	2	68	,	,	PUNCT
ajst-13407	2	69	ningbo	ningbo	PROPN
ajst-13407	2	70	315000	315000	NUM
ajst-13407	2	71	,	,	PUNCT
ajst-13407	2	72	china	china	PROPN
ajst-13407	2	73	*	*	PUNCT
ajst-13407	2	74	corresponding	correspond	VERB
ajst-13407	2	75	author	author	NOUN
ajst-13407	2	76	abstract	abstract	NOUN
ajst-13407	2	77	:	:	PUNCT
ajst-13407	2	78	the	the	DET
ajst-13407	2	79	groud	groud	NOUN
ajst-13407	2	80	-	-	PUNCT
ajst-13407	2	81	source	source	NOUN
ajst-13407	2	82	airborne	airborne	ADJ
ajst-13407	2	83	time	time	NOUN
ajst-13407	2	84	-	-	PUNCT
ajst-13407	2	85	domain	domain	NOUN
ajst-13407	2	86	electromagnetic(gatem	electromagnetic(gatem	PROPN
ajst-13407	2	87	)	)	PUNCT
ajst-13407	2	88	system	system	NOUN
ajst-13407	2	89	is	be	AUX
ajst-13407	2	90	susceptible	susceptible	ADJ
ajst-13407	2	91	to	to	PART
ajst-13407	2	92	interference	interference	VERB
ajst-13407	2	93	during	during	ADP
ajst-13407	2	94	flight	flight	NOUN
ajst-13407	2	95	,	,	PUNCT
ajst-13407	2	96	including	include	VERB
ajst-13407	2	97	motion	motion	NOUN
ajst-13407	2	98	noise	noise	NOUN
ajst-13407	2	99	(	(	PUNCT
ajst-13407	2	100	caused	cause	VERB
ajst-13407	2	101	by	by	ADP
ajst-13407	2	102	factors	factor	NOUN
ajst-13407	2	103	such	such	ADJ
ajst-13407	2	104	as	as	ADP
ajst-13407	2	105	wind	wind	NOUN
ajst-13407	2	106	direction	direction	NOUN
ajst-13407	2	107	,	,	PUNCT
ajst-13407	2	108	cable	cable	NOUN
ajst-13407	2	109	vibrations	vibration	NOUN
ajst-13407	2	110	,	,	PUNCT
ajst-13407	2	111	and	and	CCONJ
ajst-13407	2	112	sensor	sensor	NOUN
ajst-13407	2	113	attitude	attitude	NOUN
ajst-13407	2	114	)	)	PUNCT
ajst-13407	2	115	,	,	PUNCT
ajst-13407	2	116	power	power	NOUN
ajst-13407	2	117	frequency	frequency	NOUN
ajst-13407	2	118	noise	noise	NOUN
ajst-13407	2	119	,	,	PUNCT
ajst-13407	2	120	and	and	CCONJ
ajst-13407	2	121	atmospheric	atmospheric	ADJ
ajst-13407	2	122	noise	noise	NOUN
ajst-13407	2	123	.	.	PUNCT
ajst-13407	3	1	to	to	PART
ajst-13407	3	2	obtain	obtain	VERB
ajst-13407	3	3	field	field	NOUN
ajst-13407	3	4	data	datum	NOUN
ajst-13407	3	5	,	,	PUNCT
ajst-13407	3	6	and	and	CCONJ
ajst-13407	3	7	enhance	enhance	VERB
ajst-13407	3	8	the	the	DET
ajst-13407	3	9	precision	precision	NOUN
ajst-13407	3	10	of	of	ADP
ajst-13407	3	11	abnormal	abnormal	ADJ
ajst-13407	3	12	target	target	NOUN
ajst-13407	3	13	identification	identification	NOUN
ajst-13407	3	14	,	,	PUNCT
ajst-13407	3	15	it	it	PRON
ajst-13407	3	16	is	be	AUX
ajst-13407	3	17	necessary	necessary	ADJ
ajst-13407	3	18	to	to	PART
ajst-13407	3	19	suppress	suppress	VERB
ajst-13407	3	20	noise	noise	NOUN
ajst-13407	3	21	to	to	ADP
ajst-13407	3	22	the	the	DET
ajst-13407	3	23	field	field	NOUN
ajst-13407	3	24	data	datum	NOUN
ajst-13407	3	25	.	.	PUNCT
ajst-13407	4	1	in	in	ADP
ajst-13407	4	2	this	this	DET
ajst-13407	4	3	paper	paper	NOUN
ajst-13407	4	4	,	,	PUNCT
ajst-13407	4	5	a	a	DET
ajst-13407	4	6	neural	neural	ADJ
ajst-13407	4	7	network	network	NOUN
ajst-13407	4	8	approach	approach	NOUN
ajst-13407	4	9	is	be	AUX
ajst-13407	4	10	employed	employ	VERB
ajst-13407	4	11	to	to	PART
ajst-13407	4	12	reconstruct	reconstruct	VERB
ajst-13407	4	13	the	the	DET
ajst-13407	4	14	gatem	gatem	NOUN
ajst-13407	4	15	signals	signal	NOUN
ajst-13407	4	16	.	.	PUNCT
ajst-13407	5	1	this	this	PRON
ajst-13407	5	2	includes	include	VERB
ajst-13407	5	3	the	the	DET
ajst-13407	5	4	establishment	establishment	NOUN
ajst-13407	5	5	of	of	ADP
ajst-13407	5	6	a	a	DET
ajst-13407	5	7	sample	sample	NOUN
ajst-13407	5	8	sets	set	NOUN
ajst-13407	5	9	,	,	PUNCT
ajst-13407	5	10	parallel	parallel	ADJ
ajst-13407	5	11	numerical	numerical	PROPN
ajst-13407	5	12	simulation	simulation	PROPN
ajst-13407	5	13	method	method	NOUN
ajst-13407	5	14	of	of	ADP
ajst-13407	5	15	gatem	gatem	NOUN
ajst-13407	5	16	responses	response	NOUN
ajst-13407	5	17	based	base	VERB
ajst-13407	5	18	on	on	ADP
ajst-13407	5	19	the	the	DET
ajst-13407	5	20	openmp	openmp	NOUN
ajst-13407	5	21	,	,	PUNCT
ajst-13407	5	22	deployment	deployment	NOUN
ajst-13407	5	23	and	and	CCONJ
ajst-13407	5	24	execution	execution	NOUN
ajst-13407	5	25	of	of	ADP
ajst-13407	5	26	parallel	parallel	ADJ
ajst-13407	5	27	computing	computing	NOUN
ajst-13407	5	28	programs	program	NOUN
ajst-13407	5	29	on	on	ADP
ajst-13407	5	30	cloud	cloud	NOUN
ajst-13407	5	31	computing	computing	NOUN
ajst-13407	5	32	platforms	platform	NOUN
ajst-13407	5	33	,	,	PUNCT
ajst-13407	5	34	and	and	CCONJ
ajst-13407	5	35	neural	neural	ADJ
ajst-13407	5	36	networks	network	NOUN
ajst-13407	5	37	implementation	implementation	NOUN
ajst-13407	5	38	for	for	ADP
ajst-13407	5	39	noise	noise	NOUN
ajst-13407	5	40	suppression	suppression	NOUN
ajst-13407	5	41	in	in	ADP
ajst-13407	5	42	noisy	noisy	ADJ
ajst-13407	5	43	gatem	gatem	NOUN
ajst-13407	5	44	signals	signal	NOUN
ajst-13407	5	45	.	.	PUNCT
ajst-13407	6	1	when	when	SCONJ
ajst-13407	6	2	the	the	DET
ajst-13407	6	3	signal	signal	NOUN
ajst-13407	6	4	-	-	PUNCT
ajst-13407	6	5	to	to	ADP
ajst-13407	6	6	-	-	PUNCT
ajst-13407	6	7	noise	noise	NOUN
ajst-13407	6	8	ratio	ratio	NOUN
ajst-13407	6	9	is	be	AUX
ajst-13407	6	10	above	above	ADP
ajst-13407	6	11	30db	30db	NOUN
ajst-13407	6	12	,	,	PUNCT
ajst-13407	6	13	the	the	DET
ajst-13407	6	14	error	error	NOUN
ajst-13407	6	15	between	between	ADP
ajst-13407	6	16	the	the	DET
ajst-13407	6	17	denoised	denoise	VERB
ajst-13407	6	18	signal	signal	NOUN
ajst-13407	6	19	and	and	CCONJ
ajst-13407	6	20	the	the	DET
ajst-13407	6	21	original	original	ADJ
ajst-13407	6	22	signal	signal	NOUN
ajst-13407	6	23	is	be	AUX
ajst-13407	6	24	very	very	ADV
ajst-13407	6	25	small	small	ADJ
ajst-13407	6	26	,	,	PUNCT
ajst-13407	6	27	with	with	ADP
ajst-13407	6	28	an	an	DET
ajst-13407	6	29	average	average	ADJ
ajst-13407	6	30	relative	relative	ADJ
ajst-13407	6	31	error	error	NOUN
ajst-13407	6	32	not	not	PART
ajst-13407	6	33	exceeding	exceed	VERB
ajst-13407	6	34	1	1	NUM
ajst-13407	6	35	%	%	NOUN
ajst-13407	6	36	.	.	PUNCT
ajst-13407	7	1	this	this	DET
ajst-13407	7	2	method	method	NOUN
ajst-13407	7	3	can	can	AUX
ajst-13407	7	4	effectively	effectively	ADV
ajst-13407	7	5	improve	improve	VERB
ajst-13407	7	6	the	the	DET
ajst-13407	7	7	accuracy	accuracy	NOUN
ajst-13407	7	8	of	of	ADP
ajst-13407	7	9	interpretation	interpretation	NOUN
ajst-13407	7	10	and	and	CCONJ
ajst-13407	7	11	imaging	imaging	NOUN
ajst-13407	7	12	of	of	ADP
ajst-13407	7	13	gatem	gatem	NOUN
ajst-13407	7	14	signals	signal	NOUN
ajst-13407	7	15	,	,	PUNCT
ajst-13407	7	16	opening	open	VERB
ajst-13407	7	17	up	up	ADP
ajst-13407	7	18	new	new	ADJ
ajst-13407	7	19	research	research	NOUN
ajst-13407	7	20	directions	direction	NOUN
ajst-13407	7	21	in	in	ADP
ajst-13407	7	22	noise	noise	NOUN
ajst-13407	7	23	suppression	suppression	NOUN
ajst-13407	7	24	for	for	ADP
ajst-13407	7	25	electromagnetic	electromagnetic	ADJ
ajst-13407	7	26	signals	signal	NOUN
ajst-13407	7	27	.	.	PUNCT
ajst-13407	8	1	1	1	X
ajst-13407	8	2	.	.	X
ajst-13407	8	3	introduction	introduction	NOUN
ajst-13407	8	4	the	the	DET
ajst-13407	8	5	gatem	gatem	NOUN
ajst-13407	8	6	system	system	NOUN
ajst-13407	8	7	possesses	possess	VERB
ajst-13407	8	8	advantages	advantage	NOUN
ajst-13407	8	9	such	such	ADJ
ajst-13407	8	10	as	as	ADP
ajst-13407	8	11	high	high	ADJ
ajst-13407	8	12	efficiency	efficiency	NOUN
ajst-13407	8	13	and	and	CCONJ
ajst-13407	8	14	deep	deep	ADJ
ajst-13407	8	15	exploration	exploration	NOUN
ajst-13407	8	16	depth	depth	NOUN
ajst-13407	8	17	,	,	PUNCT
ajst-13407	8	18	making	make	VERB
ajst-13407	8	19	it	it	PRON
ajst-13407	8	20	suitable	suitable	ADJ
ajst-13407	8	21	for	for	ADP
ajst-13407	8	22	rapid	rapid	ADJ
ajst-13407	8	23	geological	geological	ADJ
ajst-13407	8	24	surveying	surveying	NOUN
ajst-13407	8	25	in	in	ADP
ajst-13407	8	26	special	special	ADJ
ajst-13407	8	27	conditions	condition	NOUN
ajst-13407	8	28	,	,	PUNCT
ajst-13407	8	29	such	such	ADJ
ajst-13407	8	30	as	as	ADP
ajst-13407	8	31	mountainous	mountainous	ADJ
ajst-13407	8	32	areas	area	NOUN
ajst-13407	8	33	and	and	CCONJ
ajst-13407	8	34	coastal	coastal	ADJ
ajst-13407	8	35	zones	zone	NOUN
ajst-13407	8	36	.	.	PUNCT
ajst-13407	9	1	time	time	NOUN
ajst-13407	9	2	-	-	PUNCT
ajst-13407	9	3	domain	domain	NOUN
ajst-13407	9	4	electromagnetic	electromagnetic	NOUN
ajst-13407	9	5	signals	signal	NOUN
ajst-13407	9	6	are	be	AUX
ajst-13407	9	7	susceptible	susceptible	ADJ
ajst-13407	9	8	to	to	PART
ajst-13407	9	9	interference	interference	VERB
ajst-13407	9	10	from	from	ADP
ajst-13407	9	11	motion	motion	NOUN
ajst-13407	9	12	noise	noise	NOUN
ajst-13407	9	13	,	,	PUNCT
ajst-13407	9	14	power	power	NOUN
ajst-13407	9	15	frequency	frequency	NOUN
ajst-13407	9	16	noise	noise	NOUN
ajst-13407	9	17	,	,	PUNCT
ajst-13407	9	18	and	and	CCONJ
ajst-13407	9	19	atmospheric	atmospheric	ADJ
ajst-13407	9	20	noise	noise	NOUN
ajst-13407	9	21	.	.	PUNCT
ajst-13407	10	1	the	the	DET
ajst-13407	10	2	interference	interference	NOUN
ajst-13407	10	3	is	be	AUX
ajst-13407	10	4	particularly	particularly	ADV
ajst-13407	10	5	severe	severe	ADJ
ajst-13407	10	6	for	for	ADP
ajst-13407	10	7	late	late	ADJ
ajst-13407	10	8	signals	signal	NOUN
ajst-13407	10	9	,	,	PUNCT
ajst-13407	10	10	and	and	CCONJ
ajst-13407	10	11	the	the	DET
ajst-13407	10	12	effective	effective	ADJ
ajst-13407	10	13	extraction	extraction	NOUN
ajst-13407	10	14	of	of	ADP
ajst-13407	10	15	late	late	ADJ
ajst-13407	10	16	signals	signal	NOUN
ajst-13407	10	17	directly	directly	ADV
ajst-13407	10	18	affects	affect	VERB
ajst-13407	10	19	the	the	DET
ajst-13407	10	20	interpretative	interpretative	ADJ
ajst-13407	10	21	accuracy	accuracy	NOUN
ajst-13407	10	22	of	of	ADP
ajst-13407	10	23	deep	deep	ADJ
ajst-13407	10	24	exploration	exploration	NOUN
ajst-13407	10	25	.	.	PUNCT
ajst-13407	11	1	scholars	scholar	NOUN
ajst-13407	11	2	have	have	AUX
ajst-13407	11	3	conducted	conduct	VERB
ajst-13407	11	4	extensive	extensive	ADJ
ajst-13407	11	5	work	work	NOUN
ajst-13407	11	6	in	in	ADP
ajst-13407	11	7	recent	recent	ADJ
ajst-13407	11	8	years	year	NOUN
ajst-13407	11	9	to	to	PART
ajst-13407	11	10	address	address	VERB
ajst-13407	11	11	the	the	DET
ajst-13407	11	12	noise	noise	NOUN
ajst-13407	11	13	suppression	suppression	NOUN
ajst-13407	11	14	issue	issue	NOUN
ajst-13407	11	15	in	in	ADP
ajst-13407	11	16	time	time	NOUN
ajst-13407	11	17	-	-	PUNCT
ajst-13407	11	18	domain	domain	NOUN
ajst-13407	11	19	electromagnetic	electromagnetic	ADJ
ajst-13407	11	20	signals	signal	NOUN
ajst-13407	11	21	.	.	PUNCT
ajst-13407	12	1	qiu	qiu	PROPN
ajst-13407	12	2	et	et	PROPN
ajst-13407	12	3	al	al	PROPN
ajst-13407	12	4	.	.	PROPN
ajst-13407	12	5	(	(	PUNCT
ajst-13407	12	6	2006	2006	NUM
ajst-13407	12	7	)	)	PUNCT
ajst-13407	12	8	applied	apply	VERB
ajst-13407	12	9	wavelet	wavelet	NOUN
ajst-13407	12	10	transform	transform	NOUN
ajst-13407	12	11	to	to	PART
ajst-13407	12	12	remove	remove	VERB
ajst-13407	12	13	noise	noise	NOUN
ajst-13407	12	14	from	from	ADP
ajst-13407	12	15	time	time	NOUN
ajst-13407	12	16	-	-	PUNCT
ajst-13407	12	17	domain	domain	NOUN
ajst-13407	12	18	electromagnetic	electromagnetic	ADJ
ajst-13407	12	19	data	datum	NOUN
ajst-13407	12	20	and	and	CCONJ
ajst-13407	12	21	analyzed	analyze	VERB
ajst-13407	12	22	the	the	DET
ajst-13407	12	23	denoising	denoising	NOUN
ajst-13407	12	24	results	result	NOUN
ajst-13407	12	25	under	under	ADP
ajst-13407	12	26	different	different	ADJ
ajst-13407	12	27	threshold	threshold	NOUN
ajst-13407	12	28	conditions	condition	NOUN
ajst-13407	12	29	.	.	PUNCT
ajst-13407	13	1	the	the	DET
ajst-13407	13	2	heuristic	heuristic	ADJ
ajst-13407	13	3	threshold	threshold	NOUN
ajst-13407	13	4	was	be	AUX
ajst-13407	13	5	found	find	VERB
ajst-13407	13	6	to	to	PART
ajst-13407	13	7	be	be	AUX
ajst-13407	13	8	more	more	ADV
ajst-13407	13	9	suitable	suitable	ADJ
ajst-13407	13	10	for	for	ADP
ajst-13407	13	11	noise	noise	NOUN
ajst-13407	13	12	reduction	reduction	NOUN
ajst-13407	13	13	in	in	ADP
ajst-13407	13	14	time	time	NOUN
ajst-13407	13	15	-	-	PUNCT
ajst-13407	13	16	domain	domain	NOUN
ajst-13407	13	17	electromagnetic	electromagnetic	ADJ
ajst-13407	13	18	data	datum	NOUN
ajst-13407	13	19	.	.	PUNCT
ajst-13407	14	1	bouchedda	bouchedda	PROPN
ajst-13407	14	2	et	et	PROPN
ajst-13407	14	3	al	al	PROPN
ajst-13407	14	4	.	.	PROPN
ajst-13407	15	1	(	(	PUNCT
ajst-13407	15	2	2010	2010	NUM
ajst-13407	15	3	)	)	PUNCT
ajst-13407	15	4	used	use	VERB
ajst-13407	15	5	wavelet	wavelet	NOUN
ajst-13407	15	6	transform	transform	NOUN
ajst-13407	15	7	to	to	PART
ajst-13407	15	8	restore	restore	VERB
ajst-13407	15	9	the	the	DET
ajst-13407	15	10	effective	effective	ADJ
ajst-13407	15	11	electromagnetic	electromagnetic	ADJ
ajst-13407	15	12	signal	signal	NOUN
ajst-13407	15	13	,	,	PUNCT
ajst-13407	15	14	eliminating	eliminate	VERB
ajst-13407	15	15	the	the	DET
ajst-13407	15	16	atmospheric	atmospheric	ADJ
ajst-13407	15	17	noise	noise	NOUN
ajst-13407	15	18	from	from	ADP
ajst-13407	15	19	the	the	DET
ajst-13407	15	20	data	datum	NOUN
ajst-13407	15	21	.	.	PUNCT
ajst-13407	16	1	liu	liu	PROPN
ajst-13407	16	2	xiangping	xiangping	PROPN
ajst-13407	16	3	et	et	PROPN
ajst-13407	16	4	al	al	PROPN
ajst-13407	16	5	.	.	PROPN
ajst-13407	17	1	(	(	PUNCT
ajst-13407	17	2	2011	2011	NUM
ajst-13407	17	3	)	)	PUNCT
ajst-13407	17	4	employed	employ	VERB
ajst-13407	17	5	an	an	DET
ajst-13407	17	6	improved	improve	VERB
ajst-13407	17	7	independent	independent	ADJ
ajst-13407	17	8	component	component	NOUN
ajst-13407	17	9	analysis	analysis	NOUN
ajst-13407	17	10	method	method	NOUN
ajst-13407	17	11	to	to	PART
ajst-13407	17	12	remove	remove	VERB
ajst-13407	17	13	power	power	NOUN
ajst-13407	17	14	frequency	frequency	NOUN
ajst-13407	17	15	interference	interference	NOUN
ajst-13407	17	16	from	from	ADP
ajst-13407	17	17	transient	transient	ADJ
ajst-13407	17	18	electromagnetic	electromagnetic	ADJ
ajst-13407	17	19	data	datum	NOUN
ajst-13407	17	20	,	,	PUNCT
ajst-13407	17	21	achieving	achieve	VERB
ajst-13407	17	22	good	good	ADJ
ajst-13407	17	23	results	result	NOUN
ajst-13407	17	24	.	.	PUNCT
ajst-13407	18	1	reninger	reninger	NOUN
ajst-13407	18	2	(	(	PUNCT
ajst-13407	18	3	2011	2011	NUM
ajst-13407	18	4	)	)	PUNCT
ajst-13407	18	5	applied	apply	VERB
ajst-13407	18	6	singular	singular	ADJ
ajst-13407	18	7	value	value	NOUN
ajst-13407	18	8	decomposition	decomposition	NOUN
ajst-13407	18	9	to	to	PART
ajst-13407	18	10	suppress	suppress	VERB
ajst-13407	18	11	atmospheric	atmospheric	ADJ
ajst-13407	18	12	noise	noise	NOUN
ajst-13407	18	13	in	in	ADP
ajst-13407	18	14	airborne	airborne	ADJ
ajst-13407	18	15	electromagnetic	electromagnetic	ADJ
ajst-13407	18	16	data	datum	NOUN
ajst-13407	18	17	.	.	PUNCT
ajst-13407	19	1	chen	chen	PROPN
ajst-13407	19	2	bin	bin	PROPN
ajst-13407	19	3	et	et	PROPN
ajst-13407	19	4	al	al	PROPN
ajst-13407	19	5	.	.	PROPN
ajst-13407	19	6	(	(	PUNCT
ajst-13407	19	7	2014	2014	NUM
ajst-13407	19	8	)	)	PUNCT
ajst-13407	19	9	effectively	effectively	ADV
ajst-13407	19	10	removed	remove	VERB
ajst-13407	19	11	natural	natural	ADJ
ajst-13407	19	12	and	and	CCONJ
ajst-13407	19	13	human	human	ADJ
ajst-13407	19	14	noise	noise	NOUN
ajst-13407	19	15	in	in	ADP
ajst-13407	19	16	time	time	NOUN
ajst-13407	19	17	-	-	PUNCT
ajst-13407	19	18	domain	domain	NOUN
ajst-13407	19	19	airborne	airborne	ADJ
ajst-13407	19	20	electromagnetic	electromagnetic	ADJ
ajst-13407	19	21	data	datum	NOUN
ajst-13407	19	22	by	by	ADP
ajst-13407	19	23	component	component	NOUN
ajst-13407	19	24	analysis	analysis	NOUN
ajst-13407	19	25	and	and	CCONJ
ajst-13407	19	26	applied	apply	VERB
ajst-13407	19	27	it	it	PRON
ajst-13407	19	28	in	in	ADP
ajst-13407	19	29	the	the	DET
ajst-13407	19	30	field	field	NOUN
ajst-13407	19	31	data	datum	NOUN
ajst-13407	19	32	.	.	PUNCT
ajst-13407	20	1	xu	xu	PROPN
ajst-13407	20	2	ting	te	VERB
ajst-13407	20	3	et	et	PROPN
ajst-13407	20	4	al	al	PROPN
ajst-13407	20	5	.	.	PROPN
ajst-13407	21	1	(	(	PUNCT
ajst-13407	21	2	2014	2014	NUM
ajst-13407	21	3	)	)	PUNCT
ajst-13407	21	4	used	use	VERB
ajst-13407	21	5	a	a	DET
ajst-13407	21	6	data	data	NOUN
ajst-13407	21	7	-	-	PUNCT
ajst-13407	21	8	driven	drive	VERB
ajst-13407	21	9	empirical	empirical	ADJ
ajst-13407	21	10	mode	mode	NOUN
ajst-13407	21	11	decomposition	decomposition	NOUN
ajst-13407	21	12	algorithm	algorithm	NOUN
ajst-13407	21	13	to	to	PART
ajst-13407	21	14	suppress	suppress	VERB
ajst-13407	21	15	wideband	wideband	NOUN
ajst-13407	21	16	noise	noise	NOUN
ajst-13407	21	17	in	in	ADP
ajst-13407	21	18	transient	transient	ADJ
ajst-13407	21	19	electromagnetic	electromagnetic	ADJ
ajst-13407	21	20	decay	decay	NOUN
ajst-13407	21	21	curves	curve	NOUN
ajst-13407	21	22	without	without	ADP
ajst-13407	21	23	waveform	waveform	NOUN
ajst-13407	21	24	distortion	distortion	NOUN
ajst-13407	21	25	.	.	PUNCT
ajst-13407	22	1	hou	hou	PROPN
ajst-13407	22	2	sian	sian	PROPN
ajst-13407	22	3	et	et	PROPN
ajst-13407	22	4	al	al	PROPN
ajst-13407	22	5	.	.	PROPN
ajst-13407	23	1	(	(	PUNCT
ajst-13407	23	2	2017	2017	NUM
ajst-13407	23	3	)	)	PUNCT
ajst-13407	23	4	implemented	implement	VERB
ajst-13407	23	5	random	random	ADJ
ajst-13407	23	6	noise	noise	NOUN
ajst-13407	23	7	suppression	suppression	NOUN
ajst-13407	23	8	and	and	CCONJ
ajst-13407	23	9	signal	signal	ADJ
ajst-13407	23	10	reconstruction	reconstruction	NOUN
ajst-13407	23	11	in	in	ADP
ajst-13407	23	12	multi	multi	ADJ
ajst-13407	23	13	-	-	ADJ
ajst-13407	23	14	channel	channel	ADJ
ajst-13407	23	15	seismic	seismic	ADJ
ajst-13407	23	16	data	datum	NOUN
ajst-13407	23	17	by	by	ADP
ajst-13407	23	18	the	the	DET
ajst-13407	23	19	k	k	PROPN
ajst-13407	23	20	-	-	PUNCT
ajst-13407	23	21	svd	svd	PROPN
ajst-13407	23	22	method	method	NOUN
ajst-13407	23	23	.	.	PUNCT
ajst-13407	24	1	liu	liu	PROPN
ajst-13407	24	2	yiru	yiru	PROPN
ajst-13407	24	3	et	et	PROPN
ajst-13407	24	4	al	al	PROPN
ajst-13407	24	5	.	.	PUNCT
ajst-13407	25	1	(	(	PUNCT
ajst-13407	25	2	2018	2018	NUM
ajst-13407	25	3	)	)	PUNCT
ajst-13407	25	4	employed	employ	VERB
ajst-13407	25	5	a	a	DET
ajst-13407	25	6	gaussian	gaussian	ADJ
ajst-13407	25	7	process	process	NOUN
ajst-13407	25	8	regression	regression	NOUN
ajst-13407	25	9	algorithm	algorithm	NOUN
ajst-13407	25	10	to	to	PART
ajst-13407	25	11	remove	remove	VERB
ajst-13407	25	12	atmospheric	atmospheric	ADJ
ajst-13407	25	13	and	and	CCONJ
ajst-13407	25	14	random	random	ADJ
ajst-13407	25	15	noise	noise	NOUN
ajst-13407	25	16	from	from	ADP
ajst-13407	25	17	airborne	airborne	ADJ
ajst-13407	25	18	transient	transient	ADJ
ajst-13407	25	19	electromagnetic	electromagnetic	ADJ
ajst-13407	25	20	data	datum	NOUN
ajst-13407	25	21	,	,	PUNCT
ajst-13407	25	22	although	although	SCONJ
ajst-13407	25	23	the	the	DET
ajst-13407	25	24	late	late	ADJ
ajst-13407	25	25	signals	signal	NOUN
ajst-13407	25	26	were	be	AUX
ajst-13407	25	27	relatively	relatively	ADV
ajst-13407	25	28	less	less	ADV
ajst-13407	25	29	satisfactory	satisfactory	ADJ
ajst-13407	25	30	.	.	PUNCT
ajst-13407	26	1	liu	liu	PROPN
ajst-13407	26	2	fei	fei	PROPN
ajst-13407	26	3	et	et	PROPN
ajst-13407	26	4	al	al	PROPN
ajst-13407	26	5	.	.	PROPN
ajst-13407	27	1	(	(	PUNCT
ajst-13407	27	2	2019	2019	NUM
ajst-13407	27	3	)	)	PUNCT
ajst-13407	27	4	changed	change	VERB
ajst-13407	27	5	the	the	DET
ajst-13407	27	6	mechanical	mechanical	ADJ
ajst-13407	27	7	vibration	vibration	NOUN
ajst-13407	27	8	frequency	frequency	NOUN
ajst-13407	27	9	from	from	ADP
ajst-13407	27	10	the	the	DET
ajst-13407	27	11	tem	tem	PROPN
ajst-13407	27	12	signal	signal	NOUN
ajst-13407	27	13	by	by	ADP
ajst-13407	27	14	combining	combine	VERB
ajst-13407	27	15	parallel	parallel	ADJ
ajst-13407	27	16	cable	cable	NOUN
ajst-13407	27	17	technology	technology	NOUN
ajst-13407	27	18	and	and	CCONJ
ajst-13407	27	19	aircore	aircore	PROPN
ajst-13407	27	20	coil	coil	NOUN
ajst-13407	27	21	sensor	sensor	NOUN
ajst-13407	27	22	,	,	PUNCT
ajst-13407	27	23	thus	thus	ADV
ajst-13407	27	24	achieving	achieve	VERB
ajst-13407	27	25	an	an	DET
ajst-13407	27	26	efficient	efficient	ADJ
ajst-13407	27	27	separation	separation	NOUN
ajst-13407	27	28	of	of	ADP
ajst-13407	27	29	mechanical	mechanical	ADJ
ajst-13407	27	30	vibration	vibration	NOUN
ajst-13407	27	31	frequency	frequency	NOUN
ajst-13407	27	32	and	and	CCONJ
ajst-13407	27	33	tem	tem	PROPN
ajst-13407	27	34	signal	signal	NOUN
ajst-13407	27	35	frequency	frequency	NOUN
ajst-13407	27	36	.	.	PUNCT
ajst-13407	28	1	this	this	DET
ajst-13407	28	2	study	study	NOUN
ajst-13407	28	3	focuses	focus	VERB
ajst-13407	28	4	on	on	ADP
ajst-13407	28	5	the	the	DET
ajst-13407	28	6	issues	issue	NOUN
ajst-13407	28	7	that	that	PRON
ajst-13407	28	8	exists	exist	VERB
ajst-13407	28	9	in	in	ADP
ajst-13407	28	10	the	the	DET
ajst-13407	28	11	noise	noise	NOUN
ajst-13407	28	12	suppression	suppression	NOUN
ajst-13407	28	13	field	field	NOUN
ajst-13407	28	14	.	.	PUNCT
ajst-13407	29	1	the	the	DET
ajst-13407	29	2	main	main	ADJ
ajst-13407	29	3	research	research	NOUN
ajst-13407	29	4	contents	content	NOUN
ajst-13407	29	5	consist	consist	VERB
ajst-13407	29	6	of	of	ADP
ajst-13407	29	7	three	three	NUM
ajst-13407	29	8	aspects	aspect	NOUN
ajst-13407	29	9	:	:	PUNCT
ajst-13407	29	10	the	the	DET
ajst-13407	29	11	shared	share	VERB
ajst-13407	29	12	-	-	PUNCT
ajst-13407	29	13	memory	memory	NOUN
ajst-13407	29	14	parallel	parallel	ADJ
ajst-13407	29	15	numerical	numerical	ADJ
ajst-13407	29	16	simulation	simulation	NOUN
ajst-13407	29	17	of	of	ADP
ajst-13407	29	18	the	the	DET
ajst-13407	29	19	groud	groud	NOUN
ajst-13407	29	20	-	-	PUNCT
ajst-13407	29	21	source	source	NOUN
ajst-13407	29	22	airborne	airborne	ADJ
ajst-13407	29	23	time	time	NOUN
ajst-13407	29	24	-	-	PUNCT
ajst-13407	29	25	domain	domain	NOUN
ajst-13407	29	26	electromagnetic	electromagnetic	NOUN
ajst-13407	29	27	responses	response	NOUN
ajst-13407	29	28	by	by	ADP
ajst-13407	29	29	openmp	openmp	NOUN
ajst-13407	29	30	,	,	PUNCT
ajst-13407	29	31	the	the	DET
ajst-13407	29	32	deployment	deployment	NOUN
ajst-13407	29	33	and	and	CCONJ
ajst-13407	29	34	execution	execution	NOUN
ajst-13407	29	35	of	of	ADP
ajst-13407	29	36	openmp	openmp	ADJ
ajst-13407	29	37	parallel	parallel	ADJ
ajst-13407	29	38	computing	compute	VERB
ajst-13407	29	39	programs	program	NOUN
ajst-13407	29	40	on	on	ADP
ajst-13407	29	41	public	public	ADJ
ajst-13407	29	42	cloud	cloud	NOUN
ajst-13407	29	43	,	,	PUNCT
ajst-13407	29	44	and	and	CCONJ
ajst-13407	29	45	finally	finally	ADV
ajst-13407	29	46	,	,	PUNCT
ajst-13407	29	47	the	the	DET
ajst-13407	29	48	reconstruction	reconstruction	NOUN
ajst-13407	29	49	of	of	ADP
ajst-13407	29	50	the	the	DET
ajst-13407	29	51	gatem	gatem	NOUN
ajst-13407	29	52	signals	signal	NOUN
ajst-13407	29	53	by	by	ADP
ajst-13407	29	54	neural	neural	ADJ
ajst-13407	29	55	network	network	NOUN
ajst-13407	29	56	methods	method	NOUN
ajst-13407	29	57	.	.	PUNCT
ajst-13407	30	1	2	2	X
ajst-13407	30	2	.	.	X
ajst-13407	30	3	methodology	methodology	NOUN
ajst-13407	30	4	2.1	2.1	NUM
ajst-13407	30	5	.	.	PUNCT
ajst-13407	31	1	the	the	DET
ajst-13407	31	2	gatem	gatem	PROPN
ajst-13407	31	3	numerical	numerical	PROPN
ajst-13407	31	4	simulation	simulation	PROPN
ajst-13407	31	5	for	for	ADP
ajst-13407	31	6	layered	layered	ADJ
ajst-13407	31	7	model	model	NOUN
ajst-13407	31	8	the	the	DET
ajst-13407	31	9	expression	expression	NOUN
ajst-13407	31	10	for	for	ADP
ajst-13407	31	11	the	the	DET
ajst-13407	31	12	frequency	frequency	NOUN
ajst-13407	31	13	-	-	PUNCT
ajst-13407	31	14	domain	domain	NOUN
ajst-13407	31	15	magnetic	magnetic	ADJ
ajst-13407	31	16	field	field	NOUN
ajst-13407	31	17	response	response	NOUN
ajst-13407	31	18	in	in	ADP
ajst-13407	31	19	the	the	DET
ajst-13407	31	20	z	z	NOUN
ajst-13407	31	21	direction	direction	NOUN
ajst-13407	31	22	for	for	ADP
ajst-13407	31	23	a	a	DET
ajst-13407	31	24	grounded	ground	VERB
ajst-13407	31	25	long	long	ADJ
ajst-13407	31	26	wire	wire	NOUN
ajst-13407	31	27	source	source	NOUN
ajst-13407	31	28	is	be	AUX
ajst-13407	31	29	as	as	SCONJ
ajst-13407	31	30	follows	follow	VERB
ajst-13407	31	31	:	:	PUNCT
ajst-13407	31	32			NOUN
ajst-13407	32	1			PROPN
ajst-13407	32	2	10	10	NUM
ajst-13407	32	3	1	1	NUM
ajst-13407	32	4	(	(	PUNCT
ajst-13407	32	5	)	)	PUNCT
ajst-13407	33	1	d	d	X
ajst-13407	33	2	d	d	SYM
ajst-13407	33	3	4	4	NUM
ajst-13407	33	4	l	l	NOUN
ajst-13407	33	5	z	z	NOUN
ajst-13407	33	6	z	z	NOUN
ajst-13407	34	1	tel	tel	INTJ
ajst-13407	34	2	i	i	PRON
ajst-13407	35	1	y	y	NOUN
ajst-13407	35	2	h	h	NOUN
ajst-13407	35	3	r	r	NOUN
ajst-13407	35	4	e	e	X
ajst-13407	35	5	j	j	NOUN
ajst-13407	35	6	r	r	NOUN
ajst-13407	35	7	x	x	PUNCT
ajst-13407	35	8	r	r	NOUN
ajst-13407	35	9			X
ajst-13407	35	10			ADJ
ajst-13407	35	11			ADJ
ajst-13407	35	12			ADJ
ajst-13407	35	13			PROPN
ajst-13407	35	14			VERB
ajst-13407	35	15			NOUN
ajst-13407	35	16			ADP
ajst-13407	35	17			NUM
ajst-13407	35	18			SYM
ajst-13407	35	19	1	1	NUM
ajst-13407	35	20	(	(	PUNCT
ajst-13407	35	21	1	1	NUM
ajst-13407	35	22	)	)	PUNCT
ajst-13407	35	23	where	where	SCONJ
ajst-13407	35	24	l	l	NOUN
ajst-13407	35	25	is	be	AUX
ajst-13407	35	26	the	the	DET
ajst-13407	35	27	half	half	ADJ
ajst-13407	35	28	-	-	PUNCT
ajst-13407	35	29	length	length	NOUN
ajst-13407	35	30	of	of	ADP
ajst-13407	35	31	the	the	DET
ajst-13407	35	32	grounded	ground	VERB
ajst-13407	35	33	wire	wire	NOUN
ajst-13407	35	34	,	,	PUNCT
ajst-13407	35	35	i	i	PRON
ajst-13407	35	36	is	be	AUX
ajst-13407	35	37	the	the	DET
ajst-13407	35	38	transmitting	transmit	VERB
ajst-13407	35	39	current	current	NOUN
ajst-13407	35	40	,	,	PUNCT
ajst-13407	35	41	x	x	PUNCT
ajst-13407	35	42	is	be	AUX
ajst-13407	35	43	the	the	DET
ajst-13407	35	44	x	x	NOUN
ajst-13407	35	45	-	-	NOUN
ajst-13407	35	46	coordinate	coordinate	NOUN
ajst-13407	35	47	of	of	ADP
ajst-13407	35	48	the	the	DET
ajst-13407	35	49	observation	observation	NOUN
ajst-13407	35	50	point	point	NOUN
ajst-13407	35	51	,	,	PUNCT
ajst-13407	35	52	y	y	PROPN
ajst-13407	35	53	is	be	AUX
ajst-13407	35	54	the	the	DET
ajst-13407	35	55	y	y	NOUN
ajst-13407	35	56	-	-	PUNCT
ajst-13407	35	57	coordinate	coordinate	NOUN
ajst-13407	35	58	of	of	ADP
ajst-13407	35	59	the	the	DET
ajst-13407	35	60	observation	observation	NOUN
ajst-13407	35	61	point	point	NOUN
ajst-13407	35	62	,	,	PUNCT
ajst-13407	35	63	z	z	PROPN
ajst-13407	35	64	is	be	AUX
ajst-13407	35	65	the	the	DET
ajst-13407	35	66	zcoordinate	zcoordinate	NOUN
ajst-13407	35	67	of	of	ADP
ajst-13407	35	68	the	the	DET
ajst-13407	35	69	observation	observation	NOUN
ajst-13407	35	70	point	point	NOUN
ajst-13407	35	71	,	,	PUNCT
ajst-13407	35	72			PROPN
ajst-13407	35	73			PROPN
ajst-13407	35	74	1/22	1/22	NUM
ajst-13407	35	75	2r	2r	NUM
ajst-13407	35	76	x	x	PUNCT
ajst-13407	35	77	x	x	PUNCT
ajst-13407	35	78	y	y	NOUN
ajst-13407	35	79			NOUN
ajst-13407	35	80			PROPN
ajst-13407	35	81			PROPN
ajst-13407	35	82			PROPN
ajst-13407	35	83	，	，	PUNCT
ajst-13407	35	84			ADJ
ajst-13407	35	85	and	and	CCONJ
ajst-13407	35	86	x	x	PROPN
ajst-13407	35	87	are	be	AUX
ajst-13407	35	88	variable	variable	ADJ
ajst-13407	35	89	of	of	ADP
ajst-13407	35	90	integration	integration	NOUN
ajst-13407	35	91	,	,	PUNCT
ajst-13407	35	92	and	and	CCONJ
ajst-13407	35	93	j1	j1	PROPN
ajst-13407	35	94	represents	represent	VERB
ajst-13407	35	95	the	the	DET
ajst-13407	35	96	bessel	bessel	ADJ
ajst-13407	35	97	function	function	NOUN
ajst-13407	35	98	.	.	PUNCT
ajst-13407	36	1	the	the	DET
ajst-13407	36	2	reflection	reflection	NOUN
ajst-13407	36	3	coefficient	coefficient	NOUN
ajst-13407	36	4	for	for	ADP
ajst-13407	36	5	a	a	DET
ajst-13407	36	6	uniform	uniform	ADJ
ajst-13407	36	7	halfspace	halfspace	NOUN
ajst-13407	36	8	model	model	NOUN
ajst-13407	36	9	is	be	AUX
ajst-13407	36	10	denoted	denote	VERB
ajst-13407	36	11	as	as	ADP
ajst-13407	36	12	2	2	NUM
ajst-13407	36	13	0	0	NUM
ajst-13407	36	14	2	2	NUM
ajst-13407	36	15	0	0	NUM
ajst-13407	37	1	i	i	PRON
ajst-13407	37	2	r	r	VERB
ajst-13407	37	3	i	i	PRON
ajst-13407	37	4			VERB
ajst-13407	37	5			ADJ
ajst-13407	37	6			PROPN
ajst-13407	37	7			X
ajst-13407	37	8			ADJ
ajst-13407	37	9			ADJ
ajst-13407	37	10			PROPN
ajst-13407	37	11			PROPN
ajst-13407	37	12			NOUN
ajst-13407	37	13			VERB
ajst-13407	37	14			PROPN
ajst-13407	37	15			ADV
ajst-13407	37	16			VERB
ajst-13407	37	17	te	te	ADP
ajst-13407	37	18	，	，	PROPN
ajst-13407	37	19	249	249	NUM
ajst-13407	37	20	2	2	NUM
ajst-13407	37	21	1i	1i	NOUN
ajst-13407	37	22			PROPN
ajst-13407	37	23			PROPN
ajst-13407	37	24	，	，	PUNCT
ajst-13407	37	25			PROPN
ajst-13407	37	26	is	be	AUX
ajst-13407	37	27	the	the	DET
ajst-13407	37	28	angular	angular	ADJ
ajst-13407	37	29	frequency	frequency	NOUN
ajst-13407	37	30	,	,	PUNCT
ajst-13407	37	31			PROPN
ajst-13407	37	32	is	be	AUX
ajst-13407	37	33	the	the	DET
ajst-13407	37	34	electrical	electrical	ADJ
ajst-13407	37	35	conductivity	conductivity	NOUN
ajst-13407	37	36	,	,	PUNCT
ajst-13407	37	37	and	and	CCONJ
ajst-13407	37	38	0	0	NUM
ajst-13407	37	39	is	be	AUX
ajst-13407	37	40	the	the	DET
ajst-13407	37	41	magnetic	magnetic	ADJ
ajst-13407	37	42	permeability	permeability	NOUN
ajst-13407	37	43	of	of	ADP
ajst-13407	37	44	the	the	DET
ajst-13407	37	45	vacuum	vacuum	NOUN
ajst-13407	37	46	.	.	PUNCT
ajst-13407	38	1	by	by	ADP
ajst-13407	38	2	integrating	integrate	VERB
ajst-13407	38	3	equation	equation	NOUN
ajst-13407	38	4	(	(	PUNCT
ajst-13407	38	5	1	1	NUM
ajst-13407	38	6	)	)	PUNCT
ajst-13407	38	7	and	and	CCONJ
ajst-13407	38	8	then	then	ADV
ajst-13407	38	9	performing	perform	VERB
ajst-13407	38	10	a	a	DET
ajst-13407	38	11	time	time	NOUN
ajst-13407	38	12	-	-	PUNCT
ajst-13407	38	13	frequency	frequency	NOUN
ajst-13407	38	14	transformation	transformation	NOUN
ajst-13407	38	15	,	,	PUNCT
ajst-13407	38	16	you	you	PRON
ajst-13407	38	17	can	can	AUX
ajst-13407	38	18	obtain	obtain	VERB
ajst-13407	38	19	the	the	DET
ajst-13407	38	20	timedomain	timedomain	ADJ
ajst-13407	38	21	electromagnetic	electromagnetic	ADJ
ajst-13407	38	22	response	response	NOUN
ajst-13407	38	23	zv	zv	INTJ
ajst-13407	38	24	.	.	PUNCT
ajst-13407	39	1	2.2	2.2	NUM
ajst-13407	39	2	.	.	PUNCT
ajst-13407	40	1	openmp	openmp	NOUN
ajst-13407	40	2	the	the	DET
ajst-13407	40	3	openmp	openmp	PROPN
ajst-13407	40	4	is	be	AUX
ajst-13407	40	5	a	a	DET
ajst-13407	40	6	multi	multi	ADJ
ajst-13407	40	7	-	-	ADJ
ajst-13407	40	8	threading	threading	ADJ
ajst-13407	40	9	design	design	NOUN
ajst-13407	40	10	approach	approach	NOUN
ajst-13407	40	11	that	that	PRON
ajst-13407	40	12	is	be	AUX
ajst-13407	40	13	based	base	VERB
ajst-13407	40	14	on	on	ADP
ajst-13407	40	15	the	the	DET
ajst-13407	40	16	shared	share	VERB
ajst-13407	40	17	memory	memory	NOUN
ajst-13407	40	18	and	and	CCONJ
ajst-13407	40	19	leverages	leverage	VERB
ajst-13407	40	20	multi	multi	ADJ
ajst-13407	40	21	-	-	ADJ
ajst-13407	40	22	core	core	ADJ
ajst-13407	40	23	processors	processor	NOUN
ajst-13407	40	24	for	for	ADP
ajst-13407	40	25	parallel	parallel	ADJ
ajst-13407	40	26	computing	computing	NOUN
ajst-13407	40	27	.	.	PUNCT
ajst-13407	41	1	it	it	PRON
ajst-13407	41	2	is	be	AUX
ajst-13407	41	3	suitable	suitable	ADJ
ajst-13407	41	4	for	for	ADP
ajst-13407	41	5	a	a	DET
ajst-13407	41	6	single	single	ADJ
ajst-13407	41	7	computer	computer	NOUN
ajst-13407	41	8	and	and	CCONJ
ajst-13407	41	9	provides	provide	VERB
ajst-13407	41	10	api	api	NOUN
ajst-13407	41	11	specifications	specification	NOUN
ajst-13407	41	12	that	that	PRON
ajst-13407	41	13	support	support	NOUN
ajst-13407	41	14	programming	programming	NOUN
ajst-13407	41	15	in	in	ADP
ajst-13407	41	16	c	c	NOUN
ajst-13407	41	17	,	,	PUNCT
ajst-13407	41	18	c++	c++	NOUN
ajst-13407	41	19	,	,	PUNCT
ajst-13407	41	20	and	and	CCONJ
ajst-13407	41	21	fortran	fortran	NOUN
ajst-13407	41	22	,	,	PUNCT
ajst-13407	41	23	which	which	PRON
ajst-13407	41	24	makes	make	VERB
ajst-13407	41	25	it	it	PRON
ajst-13407	41	26	being	be	AUX
ajst-13407	41	27	suitable	suitable	ADJ
ajst-13407	41	28	for	for	ADP
ajst-13407	41	29	parallel	parallel	ADJ
ajst-13407	41	30	program	program	NOUN
ajst-13407	41	31	design	design	NOUN
ajst-13407	41	32	on	on	ADP
ajst-13407	41	33	multiprocessor	multiprocessor	NOUN
ajst-13407	41	34	computers	computer	NOUN
ajst-13407	41	35	.	.	PUNCT
ajst-13407	42	1	in	in	ADP
ajst-13407	42	2	the	the	DET
ajst-13407	42	3	case	case	NOUN
ajst-13407	42	4	of	of	ADP
ajst-13407	42	5	calculating	calculate	VERB
ajst-13407	42	6	the	the	DET
ajst-13407	42	7	electromagnetic	electromagnetic	ADJ
ajst-13407	42	8	response	response	NOUN
ajst-13407	42	9	for	for	ADP
ajst-13407	42	10	a	a	DET
ajst-13407	42	11	single	single	ADJ
ajst-13407	42	12	measurement	measurement	NOUN
ajst-13407	42	13	point	point	NOUN
ajst-13407	42	14	based	base	VERB
ajst-13407	42	15	on	on	ADP
ajst-13407	42	16	the	the	DET
ajst-13407	42	17	layered	layered	ADJ
ajst-13407	42	18	model	model	NOUN
ajst-13407	42	19	,	,	PUNCT
ajst-13407	42	20	the	the	DET
ajst-13407	42	21	computation	computation	NOUN
ajst-13407	42	22	time	time	NOUN
ajst-13407	42	23	typically	typically	ADV
ajst-13407	42	24	ranges	range	VERB
ajst-13407	42	25	from	from	ADP
ajst-13407	42	26	2	2	NUM
ajst-13407	42	27	to	to	ADP
ajst-13407	42	28	4	4	NUM
ajst-13407	42	29	seconds	second	NOUN
ajst-13407	42	30	.	.	PUNCT
ajst-13407	43	1	when	when	SCONJ
ajst-13407	43	2	there	there	PRON
ajst-13407	43	3	are	be	VERB
ajst-13407	43	4	many	many	ADJ
ajst-13407	43	5	measurement	measurement	NOUN
ajst-13407	43	6	points	point	NOUN
ajst-13407	43	7	,	,	PUNCT
ajst-13407	43	8	performing	perform	VERB
ajst-13407	43	9	these	these	DET
ajst-13407	43	10	calculations	calculation	NOUN
ajst-13407	43	11	sequentially	sequentially	ADV
ajst-13407	43	12	would	would	AUX
ajst-13407	43	13	require	require	VERB
ajst-13407	43	14	an	an	DET
ajst-13407	43	15	astonishing	astonishing	ADJ
ajst-13407	43	16	amount	amount	NOUN
ajst-13407	43	17	of	of	ADP
ajst-13407	43	18	time	time	NOUN
ajst-13407	43	19	.	.	PUNCT
ajst-13407	44	1	therefore	therefore	ADV
ajst-13407	44	2	,	,	PUNCT
ajst-13407	44	3	this	this	DET
ajst-13407	44	4	paper	paper	NOUN
ajst-13407	44	5	employs	employ	VERB
ajst-13407	44	6	parallel	parallel	ADJ
ajst-13407	44	7	computing	computing	NOUN
ajst-13407	44	8	to	to	PART
ajst-13407	44	9	get	get	VERB
ajst-13407	44	10	the	the	DET
ajst-13407	44	11	electromagnetic	electromagnetic	ADJ
ajst-13407	44	12	response	response	NOUN
ajst-13407	44	13	.	.	PUNCT
ajst-13407	45	1	prior	prior	ADV
ajst-13407	45	2	to	to	ADP
ajst-13407	45	3	parallel	parallel	ADJ
ajst-13407	45	4	computing	computing	NOUN
ajst-13407	45	5	,	,	PUNCT
ajst-13407	45	6	it	it	PRON
ajst-13407	45	7	is	be	AUX
ajst-13407	45	8	necessary	necessary	ADJ
ajst-13407	45	9	to	to	PART
ajst-13407	45	10	configure	configure	VERB
ajst-13407	45	11	openmp	openmp	NOUN
ajst-13407	45	12	in	in	ADP
ajst-13407	45	13	dev	dev	PROPN
ajst-13407	45	14	-	-	NOUN
ajst-13407	45	15	c++	c++	NOUN
ajst-13407	45	16	,	,	PUNCT
ajst-13407	45	17	then	then	ADV
ajst-13407	45	18	the	the	DET
ajst-13407	45	19	program	program	NOUN
ajst-13407	45	20	's	's	PART
ajst-13407	45	21	for	for	ADP
ajst-13407	45	22	loops	loop	NOUN
ajst-13407	45	23	can	can	AUX
ajst-13407	45	24	be	be	AUX
ajst-13407	45	25	parallelized	parallelize	VERB
ajst-13407	45	26	.	.	PUNCT
ajst-13407	46	1	2.3	2.3	NUM
ajst-13407	46	2	.	.	PUNCT
ajst-13407	47	1	cloud	cloud	NOUN
ajst-13407	47	2	computing	computing	NOUN
ajst-13407	47	3	platform	platform	NOUN
ajst-13407	47	4	parallel	parallel	ADJ
ajst-13407	47	5	computing	computing	NOUN
ajst-13407	47	6	is	be	AUX
ajst-13407	47	7	an	an	DET
ajst-13407	47	8	effective	effective	ADJ
ajst-13407	47	9	method	method	NOUN
ajst-13407	47	10	to	to	PART
ajst-13407	47	11	overcome	overcome	VERB
ajst-13407	47	12	the	the	DET
ajst-13407	47	13	drawbacks	drawback	NOUN
ajst-13407	47	14	of	of	ADP
ajst-13407	47	15	slow	slow	ADJ
ajst-13407	47	16	sequential	sequential	ADJ
ajst-13407	47	17	computing	computing	NOUN
ajst-13407	47	18	and	and	CCONJ
ajst-13407	47	19	improve	improve	VERB
ajst-13407	47	20	computational	computational	ADJ
ajst-13407	47	21	efficiency	efficiency	NOUN
ajst-13407	47	22	.	.	PUNCT
ajst-13407	48	1	cloud	cloud	NOUN
ajst-13407	48	2	computing	computing	NOUN
ajst-13407	48	3	,	,	PUNCT
ajst-13407	48	4	as	as	ADP
ajst-13407	48	5	an	an	DET
ajst-13407	48	6	emerging	emerge	VERB
ajst-13407	48	7	parallel	parallel	ADJ
ajst-13407	48	8	computing	computing	NOUN
ajst-13407	48	9	approach	approach	NOUN
ajst-13407	48	10	in	in	ADP
ajst-13407	48	11	recent	recent	ADJ
ajst-13407	48	12	years	year	NOUN
ajst-13407	48	13	,	,	PUNCT
ajst-13407	48	14	is	be	AUX
ajst-13407	48	15	based	base	VERB
ajst-13407	48	16	on	on	ADP
ajst-13407	48	17	a	a	DET
ajst-13407	48	18	network	network	NOUN
ajst-13407	48	19	computing	computing	NOUN
ajst-13407	48	20	model	model	NOUN
ajst-13407	48	21	,	,	PUNCT
ajst-13407	48	22	providing	provide	VERB
ajst-13407	48	23	users	user	NOUN
ajst-13407	48	24	with	with	ADP
ajst-13407	48	25	access	access	NOUN
ajst-13407	48	26	to	to	ADP
ajst-13407	48	27	computational	computational	ADJ
ajst-13407	48	28	resources	resource	NOUN
ajst-13407	48	29	,	,	PUNCT
ajst-13407	48	30	storage	storage	NOUN
ajst-13407	48	31	,	,	PUNCT
ajst-13407	48	32	and	and	CCONJ
ajst-13407	48	33	applications	application	NOUN
ajst-13407	48	34	.	.	PUNCT
ajst-13407	49	1	the	the	DET
ajst-13407	49	2	parallel	parallel	ADJ
ajst-13407	49	3	acceleration	acceleration	NOUN
ajst-13407	49	4	method	method	NOUN
ajst-13407	49	5	based	base	VERB
ajst-13407	49	6	on	on	ADP
ajst-13407	49	7	a	a	DET
ajst-13407	49	8	cloud	cloud	NOUN
ajst-13407	49	9	computing	compute	VERB
ajst-13407	49	10	platform	platform	NOUN
ajst-13407	49	11	for	for	ADP
ajst-13407	49	12	the	the	DET
ajst-13407	49	13	gatem	gatem	NOUN
ajst-13407	49	14	responses	response	NOUN
ajst-13407	49	15	includes	include	VERB
ajst-13407	49	16	the	the	DET
ajst-13407	49	17	following	follow	VERB
ajst-13407	49	18	steps	step	NOUN
ajst-13407	49	19	:	:	PUNCT
ajst-13407	50	1	1	1	X
ajst-13407	50	2	.	.	X
ajst-13407	51	1	in	in	ADP
ajst-13407	51	2	this	this	DET
ajst-13407	51	3	paper	paper	NOUN
ajst-13407	51	4	,	,	PUNCT
ajst-13407	51	5	a	a	DET
ajst-13407	51	6	cloud	cloud	NOUN
ajst-13407	51	7	computing	computing	NOUN
ajst-13407	51	8	platform	platform	NOUN
ajst-13407	51	9	is	be	AUX
ajst-13407	51	10	established	establish	VERB
ajst-13407	51	11	by	by	ADP
ajst-13407	51	12	installing	instal	VERB
ajst-13407	51	13	hadoop	hadoop	NOUN
ajst-13407	51	14	on	on	ADP
ajst-13407	51	15	six	six	NUM
ajst-13407	51	16	computational	computational	ADJ
ajst-13407	51	17	sub	sub	NOUN
ajst-13407	51	18	-	-	NOUN
ajst-13407	51	19	nodes	node	NOUN
ajst-13407	51	20	.	.	PUNCT
ajst-13407	52	1	2	2	X
ajst-13407	52	2	.	.	X
ajst-13407	52	3	the	the	DET
ajst-13407	52	4	gatem	gatem	NOUN
ajst-13407	52	5	response	response	NOUN
ajst-13407	52	6	based	base	VERB
ajst-13407	52	7	on	on	ADP
ajst-13407	52	8	the	the	DET
ajst-13407	52	9	layered	layered	ADJ
ajst-13407	52	10	model	model	NOUN
ajst-13407	52	11	is	be	AUX
ajst-13407	52	12	employed	employ	VERB
ajst-13407	52	13	in	in	ADP
ajst-13407	52	14	c++	c++	NOUN
ajst-13407	52	15	programme	programme	NOUN
ajst-13407	52	16	.	.	PUNCT
ajst-13407	53	1	3	3	X
ajst-13407	53	2	.	.	X
ajst-13407	53	3	variables	variable	NOUN
ajst-13407	53	4	such	such	ADJ
ajst-13407	53	5	as	as	ADP
ajst-13407	53	6	electrical	electrical	ADJ
ajst-13407	53	7	conductivity	conductivity	NOUN
ajst-13407	53	8	and	and	CCONJ
ajst-13407	53	9	layer	layer	NOUN
ajst-13407	53	10	thickness	thickness	NOUN
ajst-13407	53	11	are	be	AUX
ajst-13407	53	12	created	create	VERB
ajst-13407	53	13	as	as	ADP
ajst-13407	53	14	text	text	NOUN
ajst-13407	53	15	files	file	NOUN
ajst-13407	53	16	and	and	CCONJ
ajst-13407	53	17	uploaded	upload	VERB
ajst-13407	53	18	to	to	ADP
ajst-13407	53	19	the	the	DET
ajst-13407	53	20	hadoop	hadoop	NOUN
ajst-13407	53	21	distributed	distribute	VERB
ajst-13407	53	22	file	file	NOUN
ajst-13407	53	23	system	system	NOUN
ajst-13407	53	24	.	.	PUNCT
ajst-13407	54	1	4	4	X
ajst-13407	54	2	.	.	X
ajst-13407	54	3	parallel	parallel	ADJ
ajst-13407	54	4	electromagnetic	electromagnetic	ADJ
ajst-13407	54	5	response	response	NOUN
ajst-13407	54	6	based	base	VERB
ajst-13407	54	7	on	on	ADP
ajst-13407	54	8	openmp	openmp	NOUN
ajst-13407	54	9	are	be	AUX
ajst-13407	54	10	carried	carry	VERB
ajst-13407	54	11	out	out	ADP
ajst-13407	54	12	on	on	ADP
ajst-13407	54	13	individual	individual	ADJ
ajst-13407	54	14	computing	computing	NOUN
ajst-13407	54	15	node	node	NOUN
ajst-13407	54	16	.	.	PUNCT
ajst-13407	55	1	5	5	X
ajst-13407	55	2	.	.	PUNCT
ajst-13407	55	3	the	the	DET
ajst-13407	55	4	computation	computation	NOUN
ajst-13407	55	5	results	result	NOUN
ajst-13407	55	6	are	be	AUX
ajst-13407	55	7	then	then	ADV
ajst-13407	55	8	uploaded	upload	VERB
ajst-13407	55	9	back	back	ADV
ajst-13407	55	10	to	to	ADP
ajst-13407	55	11	the	the	DET
ajst-13407	55	12	main	main	ADJ
ajst-13407	55	13	computing	computing	NOUN
ajst-13407	55	14	node	node	NOUN
ajst-13407	55	15	.	.	PUNCT
ajst-13407	56	1	2.4	2.4	NUM
ajst-13407	56	2	.	.	PUNCT
ajst-13407	57	1	neural	neural	ADJ
ajst-13407	57	2	networks	network	NOUN
ajst-13407	57	3	neural	neural	ADJ
ajst-13407	57	4	networks	network	NOUN
ajst-13407	57	5	have	have	AUX
ajst-13407	57	6	gained	gain	VERB
ajst-13407	57	7	widespread	widespread	ADJ
ajst-13407	57	8	application	application	NOUN
ajst-13407	57	9	in	in	ADP
ajst-13407	57	10	various	various	ADJ
ajst-13407	57	11	fields	field	NOUN
ajst-13407	57	12	in	in	ADP
ajst-13407	57	13	recent	recent	ADJ
ajst-13407	57	14	years	year	NOUN
ajst-13407	57	15	,	,	PUNCT
ajst-13407	57	16	and	and	CCONJ
ajst-13407	57	17	achieved	achieve	VERB
ajst-13407	57	18	notable	notable	ADJ
ajst-13407	57	19	successes	success	NOUN
ajst-13407	57	20	.	.	PUNCT
ajst-13407	58	1	when	when	SCONJ
ajst-13407	58	2	applying	apply	VERB
ajst-13407	58	3	neural	neural	ADJ
ajst-13407	58	4	network	network	NOUN
ajst-13407	58	5	methods	method	NOUN
ajst-13407	58	6	to	to	PART
ajst-13407	58	7	noise	noise	VERB
ajst-13407	58	8	suppression	suppression	NOUN
ajst-13407	58	9	in	in	ADP
ajst-13407	58	10	the	the	DET
ajst-13407	58	11	gatem	gatem	NOUN
ajst-13407	58	12	data	datum	NOUN
ajst-13407	58	13	,	,	PUNCT
ajst-13407	58	14	it	it	PRON
ajst-13407	58	15	is	be	AUX
ajst-13407	58	16	crucial	crucial	ADJ
ajst-13407	58	17	to	to	PART
ajst-13407	58	18	find	find	VERB
ajst-13407	58	19	the	the	DET
ajst-13407	58	20	most	most	ADV
ajst-13407	58	21	suitable	suitable	ADJ
ajst-13407	58	22	number	number	NOUN
ajst-13407	58	23	of	of	ADP
ajst-13407	58	24	layers	layer	NOUN
ajst-13407	58	25	and	and	CCONJ
ajst-13407	58	26	neurons	neuron	NOUN
ajst-13407	58	27	per	per	ADP
ajst-13407	58	28	layer	layer	NOUN
ajst-13407	58	29	for	for	ADP
ajst-13407	58	30	the	the	DET
ajst-13407	58	31	specific	specific	ADJ
ajst-13407	58	32	problem	problem	NOUN
ajst-13407	58	33	at	at	ADP
ajst-13407	58	34	hand	hand	NOUN
ajst-13407	58	35	.	.	PUNCT
ajst-13407	59	1	additionally	additionally	ADV
ajst-13407	59	2	,	,	PUNCT
ajst-13407	59	3	considerations	consideration	NOUN
ajst-13407	59	4	must	must	AUX
ajst-13407	59	5	be	be	AUX
ajst-13407	59	6	given	give	VERB
ajst-13407	59	7	to	to	ADP
ajst-13407	59	8	issues	issue	NOUN
ajst-13407	59	9	like	like	ADP
ajst-13407	59	10	parameter	parameter	NOUN
ajst-13407	59	11	initialization	initialization	NOUN
ajst-13407	59	12	and	and	CCONJ
ajst-13407	59	13	modifying	modify	VERB
ajst-13407	59	14	the	the	DET
ajst-13407	59	15	learning	learning	NOUN
ajst-13407	59	16	rate	rate	NOUN
ajst-13407	59	17	.	.	PUNCT
ajst-13407	60	1	proper	proper	ADJ
ajst-13407	60	2	parameter	parameter	NOUN
ajst-13407	60	3	initialization	initialization	NOUN
ajst-13407	60	4	can	can	AUX
ajst-13407	60	5	lead	lead	VERB
ajst-13407	60	6	to	to	ADP
ajst-13407	60	7	faster	fast	ADJ
ajst-13407	60	8	convergence	convergence	NOUN
ajst-13407	60	9	of	of	ADP
ajst-13407	60	10	training	training	NOUN
ajst-13407	60	11	loss	loss	NOUN
ajst-13407	60	12	while	while	SCONJ
ajst-13407	60	13	avoiding	avoid	VERB
ajst-13407	60	14	getting	get	VERB
ajst-13407	60	15	stuck	stick	VERB
ajst-13407	60	16	in	in	ADP
ajst-13407	60	17	local	local	ADJ
ajst-13407	60	18	minima	minima	NOUN
ajst-13407	60	19	.	.	PUNCT
ajst-13407	61	1	during	during	ADP
ajst-13407	61	2	the	the	DET
ajst-13407	61	3	initial	initial	ADJ
ajst-13407	61	4	stages	stage	NOUN
ajst-13407	61	5	of	of	ADP
ajst-13407	61	6	training	training	NOUN
ajst-13407	61	7	,	,	PUNCT
ajst-13407	61	8	a	a	DET
ajst-13407	61	9	relatively	relatively	ADV
ajst-13407	61	10	large	large	ADJ
ajst-13407	61	11	learning	learning	NOUN
ajst-13407	61	12	rate	rate	NOUN
ajst-13407	61	13	is	be	AUX
ajst-13407	61	14	often	often	ADV
ajst-13407	61	15	set	set	VERB
ajst-13407	61	16	to	to	PART
ajst-13407	61	17	enhance	enhance	VERB
ajst-13407	61	18	efficiency	efficiency	NOUN
ajst-13407	61	19	.	.	PUNCT
ajst-13407	62	1	in	in	ADP
ajst-13407	62	2	the	the	DET
ajst-13407	62	3	later	later	ADJ
ajst-13407	62	4	stages	stage	NOUN
ajst-13407	62	5	of	of	ADP
ajst-13407	62	6	training	training	NOUN
ajst-13407	62	7	,	,	PUNCT
ajst-13407	62	8	the	the	DET
ajst-13407	62	9	learning	learning	NOUN
ajst-13407	62	10	rate	rate	NOUN
ajst-13407	62	11	is	be	AUX
ajst-13407	62	12	typically	typically	ADV
ajst-13407	62	13	reduced	reduce	VERB
ajst-13407	62	14	in	in	ADP
ajst-13407	62	15	some	some	DET
ajst-13407	62	16	manner	manner	NOUN
ajst-13407	62	17	to	to	AUX
ajst-13407	62	18	further	far	ADV
ajst-13407	62	19	decrease	decrease	VERB
ajst-13407	62	20	training	train	VERB
ajst-13407	62	21	loss	loss	NOUN
ajst-13407	62	22	.	.	PUNCT
ajst-13407	63	1	in	in	ADP
ajst-13407	63	2	this	this	DET
ajst-13407	63	3	paper	paper	NOUN
ajst-13407	63	4	,	,	PUNCT
ajst-13407	63	5	a	a	DET
ajst-13407	63	6	sample	sample	NOUN
ajst-13407	63	7	sets	set	NOUN
ajst-13407	63	8	for	for	ADP
ajst-13407	63	9	the	the	DET
ajst-13407	63	10	gatem	gatem	NOUN
ajst-13407	63	11	responses	response	NOUN
ajst-13407	63	12	are	be	AUX
ajst-13407	63	13	constructed	construct	VERB
ajst-13407	63	14	by	by	ADP
ajst-13407	63	15	openmp	openmp	NOUN
ajst-13407	63	16	and	and	CCONJ
ajst-13407	63	17	a	a	DET
ajst-13407	63	18	cloud	cloud	NOUN
ajst-13407	63	19	computing	computing	NOUN
ajst-13407	63	20	platform	platform	NOUN
ajst-13407	63	21	.	.	PUNCT
ajst-13407	64	1	random	random	ADJ
ajst-13407	64	2	noise	noise	NOUN
ajst-13407	64	3	based	base	VERB
ajst-13407	64	4	on	on	ADP
ajst-13407	64	5	different	different	ADJ
ajst-13407	64	6	signal	signal	NOUN
ajst-13407	64	7	-	-	PUNCT
ajst-13407	64	8	to	to	ADP
ajst-13407	64	9	-	-	PUNCT
ajst-13407	64	10	noise	noise	NOUN
ajst-13407	64	11	ratios	ratio	NOUN
ajst-13407	64	12	is	be	AUX
ajst-13407	64	13	added	add	VERB
ajst-13407	64	14	to	to	ADP
ajst-13407	64	15	the	the	DET
ajst-13407	64	16	samples	sample	NOUN
ajst-13407	64	17	.	.	PUNCT
ajst-13407	65	1	a	a	DET
ajst-13407	65	2	suitable	suitable	ADJ
ajst-13407	65	3	neural	neural	ADJ
ajst-13407	65	4	network	network	NOUN
ajst-13407	65	5	model	model	NOUN
ajst-13407	65	6	is	be	AUX
ajst-13407	65	7	built	build	VERB
ajst-13407	65	8	and	and	CCONJ
ajst-13407	65	9	trained	train	VERB
ajst-13407	65	10	by	by	ADP
ajst-13407	65	11	the	the	DET
ajst-13407	65	12	training	training	NOUN
ajst-13407	65	13	dataset	dataset	NOUN
ajst-13407	65	14	.	.	PUNCT
ajst-13407	66	1	the	the	DET
ajst-13407	66	2	training	training	NOUN
ajst-13407	66	3	results	result	NOUN
ajst-13407	66	4	are	be	AUX
ajst-13407	66	5	then	then	ADV
ajst-13407	66	6	used	use	VERB
ajst-13407	66	7	to	to	PART
ajst-13407	66	8	predict	predict	VERB
ajst-13407	66	9	the	the	DET
ajst-13407	66	10	electrical	electrical	ADJ
ajst-13407	66	11	conductivity	conductivity	NOUN
ajst-13407	66	12	of	of	ADP
ajst-13407	66	13	the	the	DET
ajst-13407	66	14	test	test	NOUN
ajst-13407	66	15	sets	set	NOUN
ajst-13407	66	16	.	.	PUNCT
ajst-13407	67	1	subsequently	subsequently	ADV
ajst-13407	67	2	,	,	PUNCT
ajst-13407	67	3	the	the	DET
ajst-13407	67	4	predicted	predict	VERB
ajst-13407	67	5	electrical	electrical	ADJ
ajst-13407	67	6	conductivity	conductivity	NOUN
ajst-13407	67	7	obtained	obtain	VERB
ajst-13407	67	8	from	from	ADP
ajst-13407	67	9	the	the	DET
ajst-13407	67	10	training	training	NOUN
ajst-13407	67	11	dataset	dataset	NOUN
ajst-13407	67	12	is	be	AUX
ajst-13407	67	13	used	use	VERB
ajst-13407	67	14	for	for	ADP
ajst-13407	67	15	reconstruction	reconstruction	NOUN
ajst-13407	67	16	to	to	PART
ajst-13407	67	17	improve	improve	VERB
ajst-13407	67	18	the	the	DET
ajst-13407	67	19	effectiveness	effectiveness	NOUN
ajst-13407	67	20	of	of	ADP
ajst-13407	67	21	noise	noise	NOUN
ajst-13407	67	22	suppression	suppression	NOUN
ajst-13407	67	23	in	in	ADP
ajst-13407	67	24	the	the	DET
ajst-13407	67	25	data	datum	NOUN
ajst-13407	67	26	.	.	PUNCT
ajst-13407	68	1	3	3	X
ajst-13407	68	2	.	.	X
ajst-13407	68	3	results	result	VERB
ajst-13407	68	4	3.1	3.1	NUM
ajst-13407	68	5	.	.	PUNCT
ajst-13407	69	1	openmp	openmp	ADJ
ajst-13407	69	2	test	test	NOUN
ajst-13407	69	3	results	result	NOUN
ajst-13407	69	4	we	we	PRON
ajst-13407	69	5	use	use	VERB
ajst-13407	69	6	the	the	DET
ajst-13407	69	7	openmp	openmp	NOUN
ajst-13407	69	8	to	to	PART
ajst-13407	69	9	reconstruct	reconstruct	VERB
ajst-13407	69	10	the	the	DET
ajst-13407	69	11	program	program	NOUN
ajst-13407	69	12	,	,	PUNCT
ajst-13407	69	13	primarily	primarily	ADV
ajst-13407	69	14	by	by	ADP
ajst-13407	69	15	parallelizing	parallelize	VERB
ajst-13407	69	16	the	the	PRON
ajst-13407	69	17	for	for	ADP
ajst-13407	69	18	loops	loop	NOUN
ajst-13407	69	19	.	.	PUNCT
ajst-13407	70	1	taking	take	VERB
ajst-13407	70	2	a	a	DET
ajst-13407	70	3	three	three	NUM
ajst-13407	70	4	-	-	PUNCT
ajst-13407	70	5	layer	layer	NOUN
ajst-13407	70	6	model	model	NOUN
ajst-13407	70	7	as	as	ADP
ajst-13407	70	8	an	an	DET
ajst-13407	70	9	example	example	NOUN
ajst-13407	70	10	,	,	PUNCT
ajst-13407	70	11	with	with	ADP
ajst-13407	70	12	the	the	DET
ajst-13407	70	13	electrical	electrical	ADJ
ajst-13407	70	14	conductivity	conductivity	NOUN
ajst-13407	70	15	0.005s	0.005s	NOUN
ajst-13407	70	16	/	/	SYM
ajst-13407	70	17	m	m	PROPN
ajst-13407	70	18	of	of	ADP
ajst-13407	70	19	the	the	DET
ajst-13407	70	20	first	first	ADJ
ajst-13407	70	21	layer	layer	NOUN
ajst-13407	70	22	,	,	PUNCT
ajst-13407	70	23	the	the	DET
ajst-13407	70	24	second	second	ADJ
ajst-13407	70	25	layer	layer	NOUN
ajst-13407	70	26	0.033s	0.033s	NUM
ajst-13407	70	27	/	/	SYM
ajst-13407	70	28	m	m	PROPN
ajst-13407	70	29	,	,	PUNCT
ajst-13407	70	30	and	and	CCONJ
ajst-13407	70	31	the	the	DET
ajst-13407	70	32	third	third	ADJ
ajst-13407	70	33	layer	layer	NOUN
ajst-13407	70	34	0.002s	0.002	NOUN
ajst-13407	70	35	/	/	SYM
ajst-13407	70	36	m	m	PROPN
ajst-13407	70	37	,	,	PUNCT
ajst-13407	70	38	and	and	CCONJ
ajst-13407	70	39	the	the	DET
ajst-13407	70	40	thickness	thickness	NOUN
ajst-13407	70	41	390	390	NUM
ajst-13407	70	42	m	m	NOUN
ajst-13407	70	43	of	of	ADP
ajst-13407	70	44	the	the	DET
ajst-13407	70	45	first	first	ADJ
ajst-13407	70	46	layer	layer	NOUN
ajst-13407	70	47	,	,	PUNCT
ajst-13407	70	48	and	and	CCONJ
ajst-13407	70	49	the	the	DET
ajst-13407	70	50	thickness	thickness	NOUN
ajst-13407	70	51	550	550	NUM
ajst-13407	70	52	m	m	NOUN
ajst-13407	70	53	of	of	ADP
ajst-13407	70	54	the	the	DET
ajst-13407	70	55	second	second	ADJ
ajst-13407	70	56	layer	layer	NOUN
ajst-13407	70	57	.	.	PUNCT
ajst-13407	71	1	the	the	DET
ajst-13407	71	2	length	length	NOUN
ajst-13407	71	3	of	of	ADP
ajst-13407	71	4	the	the	DET
ajst-13407	71	5	long	long	ADV
ajst-13407	71	6	grounded	ground	VERB
ajst-13407	71	7	electric	electric	ADJ
ajst-13407	71	8	source	source	NOUN
ajst-13407	71	9	is	be	AUX
ajst-13407	71	10	2000	2000	NUM
ajst-13407	71	11	m	m	NOUN
ajst-13407	71	12	,	,	PUNCT
ajst-13407	71	13	the	the	DET
ajst-13407	71	14	transmitter	transmitter	NOUN
ajst-13407	71	15	current	current	NOUN
ajst-13407	71	16	i	i	X
ajst-13407	71	17	=	=	NOUN
ajst-13407	72	1	40	40	NUM
ajst-13407	72	2	a	a	PRON
ajst-13407	72	3	,	,	PUNCT
ajst-13407	72	4	the	the	DET
ajst-13407	72	5	receiver	receiver	ADJ
ajst-13407	72	6	coil	coil	NOUN
ajst-13407	72	7	equivalent	equivalent	ADJ
ajst-13407	72	8	area	area	NOUN
ajst-13407	72	9	s	s	PART
ajst-13407	72	10	=	=	SYM
ajst-13407	72	11	2160	2160	NUM
ajst-13407	72	12	m2	m2	PROPN
ajst-13407	72	13	,	,	PUNCT
ajst-13407	72	14	and	and	CCONJ
ajst-13407	72	15	the	the	DET
ajst-13407	72	16	receiver	receiver	ADJ
ajst-13407	72	17	location	location	NOUN
ajst-13407	72	18	coordinates	coordinate	VERB
ajst-13407	72	19	x	x	PUNCT
ajst-13407	73	1	=	=	SYM
ajst-13407	73	2	45	45	NUM
ajst-13407	73	3	m	m	PROPN
ajst-13407	73	4	,	,	PUNCT
ajst-13407	73	5	y	y	PROPN
ajst-13407	73	6	=	=	PROPN
ajst-13407	73	7	45	45	NUM
ajst-13407	73	8	m	m	PROPN
ajst-13407	73	9	,	,	PUNCT
ajst-13407	73	10	z	z	NOUN
ajst-13407	73	11	=	=	SYM
ajst-13407	73	12	30	30	NUM
ajst-13407	73	13	m.	m.	NOUN
ajst-13407	73	14	the	the	DET
ajst-13407	73	15	serial	serial	ADJ
ajst-13407	73	16	and	and	CCONJ
ajst-13407	73	17	parallel	parallel	ADJ
ajst-13407	73	18	execution	execution	NOUN
ajst-13407	73	19	results	result	NOUN
ajst-13407	73	20	are	be	AUX
ajst-13407	73	21	shown	show	VERB
ajst-13407	73	22	in	in	ADP
ajst-13407	73	23	figure	figure	NOUN
ajst-13407	73	24	1	1	NUM
ajst-13407	73	25	,	,	PUNCT
ajst-13407	73	26	where	where	SCONJ
ajst-13407	73	27	the	the	DET
ajst-13407	73	28	solid	solid	ADJ
ajst-13407	73	29	line	line	NOUN
ajst-13407	73	30	represents	represent	VERB
ajst-13407	73	31	the	the	DET
ajst-13407	73	32	serial	serial	ADJ
ajst-13407	73	33	execution	execution	NOUN
ajst-13407	73	34	result	result	NOUN
ajst-13407	73	35	,	,	PUNCT
ajst-13407	73	36	and	and	CCONJ
ajst-13407	73	37	the	the	DET
ajst-13407	73	38	dashed	dash	VERB
ajst-13407	73	39	line	line	NOUN
ajst-13407	73	40	represents	represent	VERB
ajst-13407	73	41	the	the	DET
ajst-13407	73	42	parallel	parallel	ADJ
ajst-13407	73	43	execution	execution	NOUN
ajst-13407	73	44	result	result	NOUN
ajst-13407	73	45	.	.	PUNCT
ajst-13407	74	1	from	from	ADP
ajst-13407	74	2	figure	figure	NOUN
ajst-13407	74	3	1	1	NUM
ajst-13407	74	4	,	,	PUNCT
ajst-13407	74	5	it	it	PRON
ajst-13407	74	6	can	can	AUX
ajst-13407	74	7	be	be	AUX
ajst-13407	74	8	observed	observe	VERB
ajst-13407	74	9	that	that	SCONJ
ajst-13407	74	10	the	the	DET
ajst-13407	74	11	curves	curve	NOUN
ajst-13407	74	12	completely	completely	ADV
ajst-13407	74	13	overlap	overlap	VERB
ajst-13407	74	14	,	,	PUNCT
ajst-13407	74	15	demonstrating	demonstrate	VERB
ajst-13407	74	16	that	that	SCONJ
ajst-13407	74	17	parallelizing	parallelize	VERB
ajst-13407	74	18	the	the	DET
ajst-13407	74	19	program	program	NOUN
ajst-13407	74	20	by	by	ADP
ajst-13407	74	21	openmp	openmp	PROPN
ajst-13407	74	22	does	do	AUX
ajst-13407	74	23	not	not	PART
ajst-13407	74	24	affect	affect	VERB
ajst-13407	74	25	computational	computational	ADJ
ajst-13407	74	26	accuracy	accuracy	NOUN
ajst-13407	74	27	.	.	PUNCT
ajst-13407	75	1	openmp	openmp	NOUN
ajst-13407	75	2	provides	provide	VERB
ajst-13407	75	3	different	different	ADJ
ajst-13407	75	4	scheduling	scheduling	NOUN
ajst-13407	75	5	options	option	NOUN
ajst-13407	75	6	,	,	PUNCT
ajst-13407	75	7	including	include	VERB
ajst-13407	75	8	static	static	ADJ
ajst-13407	75	9	scheduling	scheduling	NOUN
ajst-13407	75	10	,	,	PUNCT
ajst-13407	75	11	dynamic	dynamic	ADJ
ajst-13407	75	12	scheduling	scheduling	NOUN
ajst-13407	75	13	,	,	PUNCT
ajst-13407	75	14	and	and	CCONJ
ajst-13407	75	15	heuristic	heuristic	ADJ
ajst-13407	75	16	scheduling	scheduling	NOUN
ajst-13407	75	17	.	.	PUNCT
ajst-13407	76	1	these	these	DET
ajst-13407	76	2	different	different	ADJ
ajst-13407	76	3	scheduling	scheduling	NOUN
ajst-13407	76	4	options	option	NOUN
ajst-13407	76	5	can	can	AUX
ajst-13407	76	6	lead	lead	VERB
ajst-13407	76	7	to	to	ADP
ajst-13407	76	8	variations	variation	NOUN
ajst-13407	76	9	in	in	ADP
ajst-13407	76	10	program	program	NOUN
ajst-13407	76	11	execution	execution	NOUN
ajst-13407	76	12	times	time	NOUN
ajst-13407	76	13	.	.	PUNCT
ajst-13407	77	1	figure	figure	NOUN
ajst-13407	77	2	1	1	NUM
ajst-13407	77	3	.	.	PUNCT
ajst-13407	78	1	the	the	DET
ajst-13407	78	2	gatem	gatem	NOUN
ajst-13407	78	3	responses	response	NOUN
ajst-13407	78	4	for	for	ADP
ajst-13407	78	5	serial	serial	ADJ
ajst-13407	78	6	and	and	CCONJ
ajst-13407	78	7	parallel	parallel	ADJ
ajst-13407	78	8	execution	execution	NOUN
ajst-13407	78	9	results	result	VERB
ajst-13407	78	10	the	the	DET
ajst-13407	78	11	gatem	gatem	NOUN
ajst-13407	78	12	responses	response	NOUN
ajst-13407	78	13	were	be	AUX
ajst-13407	78	14	generated	generate	VERB
ajst-13407	78	15	on	on	ADP
ajst-13407	78	16	an	an	DET
ajst-13407	78	17	intel(r	intel(r	NOUN
ajst-13407	78	18	)	)	PUNCT
ajst-13407	78	19	core(tm	core(tm	NOUN
ajst-13407	78	20	)	)	PUNCT
ajst-13407	78	21	i9	i9	NOUN
ajst-13407	78	22	-	-	PUNCT
ajst-13407	78	23	10900k	10900k	NOUN
ajst-13407	78	24	cpu@3.70ghz	cpu@3.70ghz	NOUN
ajst-13407	78	25	and	and	CCONJ
ajst-13407	78	26	128	128	NUM
ajst-13407	78	27	gb	gb	NOUN
ajst-13407	78	28	ram	ram	NOUN
ajst-13407	78	29	.	.	PUNCT
ajst-13407	79	1	for	for	ADP
ajst-13407	79	2	the	the	DET
ajst-13407	79	3	three	three	NUM
ajst-13407	79	4	-	-	PUNCT
ajst-13407	79	5	layer	layer	NOUN
ajst-13407	79	6	model	model	NOUN
ajst-13407	79	7	,	,	PUNCT
ajst-13407	79	8	the	the	DET
ajst-13407	79	9	serial	serial	ADJ
ajst-13407	79	10	computation	computation	NOUN
ajst-13407	79	11	time	time	NOUN
ajst-13407	79	12	is	be	AUX
ajst-13407	79	13	8.6	8.6	NUM
ajst-13407	79	14	seconds	second	NOUN
ajst-13407	79	15	.	.	PUNCT
ajst-13407	80	1	when	when	SCONJ
ajst-13407	80	2	using	use	VERB
ajst-13407	80	3	static	static	ADJ
ajst-13407	80	4	scheduling	scheduling	NOUN
ajst-13407	80	5	,	,	PUNCT
ajst-13407	80	6	the	the	DET
ajst-13407	80	7	program	program	NOUN
ajst-13407	80	8	's	's	PART
ajst-13407	80	9	computation	computation	NOUN
ajst-13407	80	10	time	time	NOUN
ajst-13407	80	11	is	be	AUX
ajst-13407	80	12	reduced	reduce	VERB
ajst-13407	80	13	to	to	ADP
ajst-13407	80	14	2.16	2.16	NUM
ajst-13407	80	15	seconds	second	NOUN
ajst-13407	80	16	,	,	PUNCT
ajst-13407	80	17	resulting	result	VERB
ajst-13407	80	18	in	in	ADP
ajst-13407	80	19	an	an	DET
ajst-13407	80	20	speedup	speedup	NOUN
ajst-13407	80	21	of	of	ADP
ajst-13407	80	22	3.98	3.98	NUM
ajst-13407	80	23	.	.	PUNCT
ajst-13407	81	1	with	with	ADP
ajst-13407	81	2	dynamic	dynamic	ADJ
ajst-13407	81	3	scheduling	scheduling	NOUN
ajst-13407	81	4	,	,	PUNCT
ajst-13407	81	5	the	the	DET
ajst-13407	81	6	program	program	NOUN
ajst-13407	81	7	's	's	PART
ajst-13407	81	8	computation	computation	NOUN
ajst-13407	81	9	time	time	NOUN
ajst-13407	81	10	is	be	AUX
ajst-13407	81	11	further	far	ADV
ajst-13407	81	12	reduced	reduce	VERB
ajst-13407	81	13	to	to	ADP
ajst-13407	81	14	2.01	2.01	NUM
ajst-13407	81	15	seconds	second	NOUN
ajst-13407	81	16	,	,	PUNCT
ajst-13407	81	17	achieving	achieve	VERB
ajst-13407	81	18	an	an	DET
ajst-13407	81	19	speedup	speedup	NOUN
ajst-13407	81	20	of	of	ADP
ajst-13407	81	21	4.28	4.28	NUM
ajst-13407	81	22	.	.	PUNCT
ajst-13407	82	1	when	when	SCONJ
ajst-13407	82	2	using	use	VERB
ajst-13407	82	3	heuristic	heuristic	ADJ
ajst-13407	82	4	scheduling	scheduling	NOUN
ajst-13407	82	5	,	,	PUNCT
ajst-13407	82	6	the	the	DET
ajst-13407	82	7	program	program	NOUN
ajst-13407	82	8	's	's	PART
ajst-13407	82	9	computation	computation	NOUN
ajst-13407	82	10	time	time	NOUN
ajst-13407	82	11	is	be	AUX
ajst-13407	82	12	minimized	minimize	VERB
ajst-13407	82	13	to	to	ADP
ajst-13407	82	14	1.85	1.85	NUM
ajst-13407	82	15	seconds	second	NOUN
ajst-13407	82	16	,	,	PUNCT
ajst-13407	82	17	with	with	ADP
ajst-13407	82	18	an	an	DET
ajst-13407	82	19	speedup	speedup	NOUN
ajst-13407	82	20	of	of	ADP
ajst-13407	82	21	4.64	4.64	NUM
ajst-13407	82	22	.	.	PUNCT
ajst-13407	83	1	it	it	PRON
ajst-13407	83	2	can	can	AUX
ajst-13407	83	3	be	be	AUX
ajst-13407	83	4	observed	observe	VERB
ajst-13407	83	5	that	that	SCONJ
ajst-13407	83	6	the	the	DET
ajst-13407	83	7	heuristic	heuristic	ADJ
ajst-13407	83	8	scheduling	scheduling	NOUN
ajst-13407	83	9	leads	lead	VERB
ajst-13407	83	10	to	to	ADP
ajst-13407	83	11	the	the	DET
ajst-13407	83	12	most	most	ADV
ajst-13407	83	13	significant	significant	ADJ
ajst-13407	83	14	improvement	improvement	NOUN
ajst-13407	83	15	in	in	ADP
ajst-13407	83	16	efficiency	efficiency	NOUN
ajst-13407	83	17	,	,	PUNCT
ajst-13407	83	18	as	as	SCONJ
ajst-13407	83	19	shown	show	VERB
ajst-13407	83	20	in	in	ADP
ajst-13407	83	21	table	table	NOUN
ajst-13407	83	22	1	1	NUM
ajst-13407	83	23	.	.	PUNCT
ajst-13407	84	1	250	250	NUM
ajst-13407	84	2	table	table	NOUN
ajst-13407	84	3	1	1	NUM
ajst-13407	84	4	.	.	PUNCT
ajst-13407	84	5	comparison	comparison	NOUN
ajst-13407	84	6	of	of	ADP
ajst-13407	84	7	different	different	ADJ
ajst-13407	84	8	scheduling	scheduling	NOUN
ajst-13407	84	9	methods	method	NOUN
ajst-13407	84	10	computation	computation	NOUN
ajst-13407	84	11	time	time	NOUN
ajst-13407	84	12	(	(	PUNCT
ajst-13407	84	13	s	s	NOUN
ajst-13407	84	14	)	)	PUNCT
ajst-13407	84	15	speedup	speedup	NOUN
ajst-13407	84	16	serial	serial	ADJ
ajst-13407	84	17	program	program	NOUN
ajst-13407	84	18	8.6	8.6	NUM
ajst-13407	84	19	static	static	ADJ
ajst-13407	84	20	scheduling	scheduling	NOUN
ajst-13407	84	21	2.16	2.16	NUM
ajst-13407	84	22	3.98	3.98	NUM
ajst-13407	84	23	dynamic	dynamic	ADJ
ajst-13407	84	24	scheduling	scheduling	NOUN
ajst-13407	84	25	2.01	2.01	NUM
ajst-13407	84	26	4.28	4.28	NUM
ajst-13407	84	27	heuristic	heuristic	ADJ
ajst-13407	84	28	scheduling	scheduling	NOUN
ajst-13407	84	29	1.85	1.85	NUM
ajst-13407	84	30	4.64	4.64	NUM
ajst-13407	84	31	3.2	3.2	NUM
ajst-13407	84	32	.	.	PUNCT
ajst-13407	85	1	openmp	openmp	PROPN
ajst-13407	85	2	+	+	CCONJ
ajst-13407	85	3	cloud	cloud	NOUN
ajst-13407	85	4	computing	compute	VERB
ajst-13407	85	5	test	test	NOUN
ajst-13407	85	6	results	result	NOUN
ajst-13407	85	7	to	to	PART
ajst-13407	85	8	compare	compare	VERB
ajst-13407	85	9	the	the	DET
ajst-13407	85	10	computational	computational	ADJ
ajst-13407	85	11	efficiency	efficiency	NOUN
ajst-13407	85	12	of	of	ADP
ajst-13407	85	13	the	the	DET
ajst-13407	85	14	openmp	openmp	ADJ
ajst-13407	85	15	+	+	CCONJ
ajst-13407	85	16	cloud	cloud	ADJ
ajst-13407	85	17	computing	computing	NOUN
ajst-13407	85	18	method	method	NOUN
ajst-13407	85	19	,	,	PUNCT
ajst-13407	85	20	this	this	DET
ajst-13407	85	21	paper	paper	NOUN
ajst-13407	85	22	takes	take	VERB
ajst-13407	85	23	the	the	DET
ajst-13407	85	24	uniform	uniform	ADJ
ajst-13407	85	25	halfspace	halfspace	NOUN
ajst-13407	85	26	model	model	NOUN
ajst-13407	85	27	as	as	ADP
ajst-13407	85	28	an	an	DET
ajst-13407	85	29	example	example	NOUN
ajst-13407	85	30	and	and	CCONJ
ajst-13407	85	31	calculates	calculate	VERB
ajst-13407	85	32	the	the	DET
ajst-13407	85	33	gatem	gatem	NOUN
ajst-13407	85	34	responses	response	NOUN
ajst-13407	85	35	for	for	ADP
ajst-13407	85	36	10	10	NUM
ajst-13407	85	37	sets	set	NOUN
ajst-13407	85	38	to	to	ADP
ajst-13407	85	39	290	290	NUM
ajst-13407	85	40	sets	set	NOUN
ajst-13407	85	41	,	,	PUNCT
ajst-13407	85	42	with	with	ADP
ajst-13407	85	43	intervals	interval	NOUN
ajst-13407	85	44	of	of	ADP
ajst-13407	85	45	20	20	NUM
ajst-13407	85	46	.	.	PUNCT
ajst-13407	86	1	the	the	DET
ajst-13407	86	2	electrical	electrical	ADJ
ajst-13407	86	3	conductivity	conductivity	NOUN
ajst-13407	86	4	varies	vary	VERB
ajst-13407	86	5	uniformly	uniformly	ADV
ajst-13407	86	6	from	from	ADP
ajst-13407	86	7	0.001	0.001	NUM
ajst-13407	86	8	s	s	NOUN
ajst-13407	86	9	/	/	SYM
ajst-13407	86	10	m	m	NOUN
ajst-13407	86	11	to	to	ADP
ajst-13407	86	12	1	1	NUM
ajst-13407	86	13	s	s	NOUN
ajst-13407	86	14	/	/	SYM
ajst-13407	86	15	m.	m.	NOUN
ajst-13407	86	16	the	the	DET
ajst-13407	86	17	specific	specific	ADJ
ajst-13407	86	18	calculation	calculation	NOUN
ajst-13407	86	19	steps	step	NOUN
ajst-13407	86	20	are	be	AUX
ajst-13407	86	21	as	as	SCONJ
ajst-13407	86	22	described	describe	VERB
ajst-13407	86	23	in	in	ADP
ajst-13407	86	24	section	section	NOUN
ajst-13407	86	25	1.3	1.3	NUM
ajst-13407	86	26	.	.	PUNCT
ajst-13407	87	1	the	the	DET
ajst-13407	87	2	speedup	speedup	NOUN
ajst-13407	87	3	for	for	ADP
ajst-13407	87	4	varying	vary	VERB
ajst-13407	87	5	numbers	number	NOUN
ajst-13407	87	6	of	of	ADP
ajst-13407	87	7	computational	computational	ADJ
ajst-13407	87	8	models	model	NOUN
ajst-13407	87	9	is	be	AUX
ajst-13407	87	10	shown	show	VERB
ajst-13407	87	11	in	in	ADP
ajst-13407	87	12	figure	figure	NOUN
ajst-13407	87	13	2	2	NUM
ajst-13407	87	14	.	.	PUNCT
ajst-13407	87	15	from	from	ADP
ajst-13407	87	16	the	the	DET
ajst-13407	87	17	figure	figure	NOUN
ajst-13407	87	18	2	2	NUM
ajst-13407	87	19	,	,	PUNCT
ajst-13407	87	20	it	it	PRON
ajst-13407	87	21	can	can	AUX
ajst-13407	87	22	be	be	AUX
ajst-13407	87	23	observed	observe	VERB
ajst-13407	87	24	that	that	SCONJ
ajst-13407	87	25	as	as	ADP
ajst-13407	87	26	the	the	DET
ajst-13407	87	27	number	number	NOUN
ajst-13407	87	28	of	of	ADP
ajst-13407	87	29	computational	computational	ADJ
ajst-13407	87	30	models	model	NOUN
ajst-13407	87	31	increases	increase	NOUN
ajst-13407	87	32	,	,	PUNCT
ajst-13407	87	33	the	the	DET
ajst-13407	87	34	speedup	speedup	NOUN
ajst-13407	87	35	also	also	ADV
ajst-13407	87	36	increases	increase	VERB
ajst-13407	87	37	,	,	PUNCT
ajst-13407	87	38	but	but	CCONJ
ajst-13407	87	39	the	the	DET
ajst-13407	87	40	rate	rate	NOUN
ajst-13407	87	41	of	of	ADP
ajst-13407	87	42	increase	increase	NOUN
ajst-13407	87	43	gradually	gradually	ADV
ajst-13407	87	44	slows	slow	VERB
ajst-13407	87	45	down	down	ADP
ajst-13407	87	46	.	.	PUNCT
ajst-13407	88	1	when	when	SCONJ
ajst-13407	88	2	the	the	DET
ajst-13407	88	3	number	number	NOUN
ajst-13407	88	4	of	of	ADP
ajst-13407	88	5	models	model	NOUN
ajst-13407	88	6	is	be	AUX
ajst-13407	88	7	up	up	ADP
ajst-13407	88	8	to	to	ADP
ajst-13407	88	9	290	290	NUM
ajst-13407	88	10	,	,	PUNCT
ajst-13407	88	11	the	the	DET
ajst-13407	88	12	speedup	speedup	NOUN
ajst-13407	88	13	can	can	AUX
ajst-13407	88	14	reach	reach	VERB
ajst-13407	88	15	11.37	11.37	NUM
ajst-13407	88	16	.	.	PUNCT
ajst-13407	89	1	figure	figure	NOUN
ajst-13407	89	2	2	2	NUM
ajst-13407	89	3	.	.	NOUN
ajst-13407	89	4	speedup	speedup	NOUN
ajst-13407	89	5	for	for	ADP
ajst-13407	89	6	varying	vary	VERB
ajst-13407	89	7	numbers	number	NOUN
ajst-13407	89	8	of	of	ADP
ajst-13407	89	9	computational	computational	ADJ
ajst-13407	89	10	models	model	NOUN
ajst-13407	89	11	3.3	3.3	NUM
ajst-13407	89	12	.	.	PUNCT
ajst-13407	90	1	denoising	denoise	VERB
ajst-13407	90	2	results	result	NOUN
ajst-13407	90	3	for	for	SCONJ
ajst-13407	90	4	the	the	DET
ajst-13407	90	5	neural	neural	ADJ
ajst-13407	90	6	network	network	NOUN
ajst-13407	90	7	to	to	PART
ajst-13407	90	8	create	create	VERB
ajst-13407	90	9	a	a	DET
ajst-13407	90	10	sample	sample	NOUN
ajst-13407	90	11	library	library	NOUN
ajst-13407	90	12	for	for	ADP
ajst-13407	90	13	the	the	DET
ajst-13407	90	14	time	time	NOUN
ajst-13407	90	15	-	-	PUNCT
ajst-13407	90	16	domain	domain	NOUN
ajst-13407	90	17	electromagnetic	electromagnetic	ADJ
ajst-13407	90	18	responses	response	NOUN
ajst-13407	90	19	of	of	ADP
ajst-13407	90	20	a	a	DET
ajst-13407	90	21	long	long	ADJ
ajst-13407	90	22	wire	wire	NOUN
ajst-13407	90	23	source	source	NOUN
ajst-13407	90	24	,	,	PUNCT
ajst-13407	90	25	different	different	ADJ
ajst-13407	90	26	sets	set	NOUN
ajst-13407	90	27	of	of	ADP
ajst-13407	90	28	electrical	electrical	ADJ
ajst-13407	90	29	conductivity	conductivity	NOUN
ajst-13407	90	30	-	-	PUNCT
ajst-13407	90	31	depth	depth	NOUN
ajst-13407	90	32	properties	property	NOUN
ajst-13407	90	33	are	be	AUX
ajst-13407	90	34	first	first	ADV
ajst-13407	90	35	defined	define	VERB
ajst-13407	90	36	.	.	PUNCT
ajst-13407	91	1	since	since	SCONJ
ajst-13407	91	2	the	the	DET
ajst-13407	91	3	first	first	ADJ
ajst-13407	91	4	layer	layer	NOUN
ajst-13407	91	5	in	in	ADP
ajst-13407	91	6	the	the	DET
ajst-13407	91	7	actual	actual	ADJ
ajst-13407	91	8	geological	geological	ADJ
ajst-13407	91	9	structure	structure	NOUN
ajst-13407	91	10	is	be	AUX
ajst-13407	91	11	typically	typically	ADV
ajst-13407	91	12	soil	soil	NOUN
ajst-13407	91	13	or	or	CCONJ
ajst-13407	91	14	sandstone	sandstone	NOUN
ajst-13407	91	15	with	with	ADP
ajst-13407	91	16	lower	low	ADJ
ajst-13407	91	17	electrical	electrical	ADJ
ajst-13407	91	18	conductivity	conductivity	NOUN
ajst-13407	91	19	,	,	PUNCT
ajst-13407	91	20	the	the	DET
ajst-13407	91	21	range	range	NOUN
ajst-13407	91	22	of	of	ADP
ajst-13407	91	23	electrical	electrical	ADJ
ajst-13407	91	24	conductivity	conductivity	NOUN
ajst-13407	91	25	values	value	NOUN
ajst-13407	91	26	for	for	ADP
ajst-13407	91	27	the	the	DET
ajst-13407	91	28	first	first	ADJ
ajst-13407	91	29	layer	layer	NOUN
ajst-13407	91	30	is	be	AUX
ajst-13407	91	31	chosen	choose	VERB
ajst-13407	91	32	to	to	PART
ajst-13407	91	33	be	be	AUX
ajst-13407	91	34	from	from	ADP
ajst-13407	91	35	0.01	0.01	NUM
ajst-13407	91	36	s	s	NOUN
ajst-13407	91	37	/	/	SYM
ajst-13407	91	38	m	m	NOUN
ajst-13407	91	39	to	to	ADP
ajst-13407	91	40	0.1	0.1	NUM
ajst-13407	91	41	s	s	NOUN
ajst-13407	91	42	/	/	SYM
ajst-13407	91	43	m	m	PROPN
ajst-13407	91	44	,	,	PUNCT
ajst-13407	91	45	while	while	SCONJ
ajst-13407	91	46	the	the	DET
ajst-13407	91	47	second	second	ADJ
ajst-13407	91	48	and	and	CCONJ
ajst-13407	91	49	third	third	ADJ
ajst-13407	91	50	layer	layer	NOUN
ajst-13407	91	51	's	's	PART
ajst-13407	91	52	electrical	electrical	ADJ
ajst-13407	91	53	conductivity	conductivity	NOUN
ajst-13407	91	54	ranges	range	VERB
ajst-13407	91	55	from	from	ADP
ajst-13407	91	56	0.1	0.1	NUM
ajst-13407	91	57	s	s	NOUN
ajst-13407	91	58	/	/	SYM
ajst-13407	91	59	m	m	NOUN
ajst-13407	91	60	to	to	ADP
ajst-13407	91	61	1	1	NUM
ajst-13407	91	62	s	s	NOUN
ajst-13407	91	63	/	/	SYM
ajst-13407	91	64	m.	m.	NOUN
ajst-13407	91	65	in	in	ADP
ajst-13407	91	66	a	a	DET
ajst-13407	91	67	three	three	NUM
ajst-13407	91	68	-	-	PUNCT
ajst-13407	91	69	layer	layer	NOUN
ajst-13407	91	70	model	model	NOUN
ajst-13407	91	71	,	,	PUNCT
ajst-13407	91	72	the	the	DET
ajst-13407	91	73	total	total	ADJ
ajst-13407	91	74	number	number	NOUN
ajst-13407	91	75	of	of	ADP
ajst-13407	91	76	samples	sample	NOUN
ajst-13407	91	77	is	be	AUX
ajst-13407	91	78	the	the	DET
ajst-13407	91	79	product	product	NOUN
ajst-13407	91	80	of	of	ADP
ajst-13407	91	81	the	the	DET
ajst-13407	91	82	number	number	NOUN
ajst-13407	91	83	of	of	ADP
ajst-13407	91	84	possible	possible	ADJ
ajst-13407	91	85	values	value	NOUN
ajst-13407	91	86	for	for	ADP
ajst-13407	91	87	each	each	DET
ajst-13407	91	88	layer	layer	NOUN
ajst-13407	91	89	's	's	PART
ajst-13407	91	90	electrical	electrical	ADJ
ajst-13407	91	91	conductivity	conductivity	NOUN
ajst-13407	91	92	.	.	PUNCT
ajst-13407	92	1	to	to	PART
ajst-13407	92	2	control	control	VERB
ajst-13407	92	3	the	the	DET
ajst-13407	92	4	number	number	NOUN
ajst-13407	92	5	of	of	ADP
ajst-13407	92	6	samples	sample	NOUN
ajst-13407	92	7	,	,	PUNCT
ajst-13407	92	8	it	it	PRON
ajst-13407	92	9	's	be	AUX
ajst-13407	92	10	necessary	necessary	ADJ
ajst-13407	92	11	to	to	PART
ajst-13407	92	12	adjust	adjust	VERB
ajst-13407	92	13	the	the	DET
ajst-13407	92	14	step	step	NOUN
ajst-13407	92	15	size	size	NOUN
ajst-13407	92	16	appropriately	appropriately	ADV
ajst-13407	92	17	.	.	PUNCT
ajst-13407	93	1	thus	thus	ADV
ajst-13407	93	2	,	,	PUNCT
ajst-13407	93	3	the	the	DET
ajst-13407	93	4	step	step	NOUN
ajst-13407	93	5	size	size	NOUN
ajst-13407	93	6	for	for	ADP
ajst-13407	93	7	the	the	DET
ajst-13407	93	8	first	first	ADJ
ajst-13407	93	9	layer	layer	NOUN
ajst-13407	93	10	is	be	AUX
ajst-13407	93	11	set	set	VERB
ajst-13407	93	12	at	at	ADP
ajst-13407	93	13	0.003	0.003	NUM
ajst-13407	93	14	s	s	NOUN
ajst-13407	93	15	/	/	SYM
ajst-13407	93	16	m	m	PROPN
ajst-13407	93	17	,	,	PUNCT
ajst-13407	93	18	while	while	SCONJ
ajst-13407	93	19	the	the	DET
ajst-13407	93	20	second	second	ADJ
ajst-13407	93	21	and	and	CCONJ
ajst-13407	93	22	third	third	ADJ
ajst-13407	93	23	layers	layer	NOUN
ajst-13407	93	24	have	have	VERB
ajst-13407	93	25	a	a	DET
ajst-13407	93	26	step	step	NOUN
ajst-13407	93	27	size	size	NOUN
ajst-13407	93	28	of	of	ADP
ajst-13407	93	29	0.02	0.02	NUM
ajst-13407	93	30	s	s	NOUN
ajst-13407	93	31	/	/	SYM
ajst-13407	93	32	m.	m.	NOUN
ajst-13407	93	33	this	this	PRON
ajst-13407	93	34	results	result	VERB
ajst-13407	93	35	in	in	ADP
ajst-13407	93	36	a	a	DET
ajst-13407	93	37	total	total	NOUN
ajst-13407	93	38	of	of	ADP
ajst-13407	93	39	65,596	65,596	NUM
ajst-13407	93	40	samples	sample	NOUN
ajst-13407	93	41	.	.	PUNCT
ajst-13407	94	1	the	the	DET
ajst-13407	94	2	depths	depth	NOUN
ajst-13407	94	3	of	of	ADP
ajst-13407	94	4	the	the	DET
ajst-13407	94	5	first	first	ADJ
ajst-13407	94	6	and	and	CCONJ
ajst-13407	94	7	second	second	ADJ
ajst-13407	94	8	layers	layer	NOUN
ajst-13407	94	9	are	be	AUX
ajst-13407	94	10	both	both	PRON
ajst-13407	94	11	80	80	NUM
ajst-13407	94	12	meters	meter	NOUN
ajst-13407	94	13	,	,	PUNCT
ajst-13407	94	14	while	while	SCONJ
ajst-13407	94	15	the	the	DET
ajst-13407	94	16	third	third	ADJ
ajst-13407	94	17	layer	layer	NOUN
ajst-13407	94	18	's	's	PART
ajst-13407	94	19	depth	depth	NOUN
ajst-13407	94	20	is	be	AUX
ajst-13407	94	21	considered	consider	VERB
ajst-13407	94	22	infinite	infinite	ADJ
ajst-13407	94	23	.	.	PUNCT
ajst-13407	95	1	next	next	ADJ
ajst-13407	95	2	,	,	PUNCT
ajst-13407	95	3	gaussian	gaussian	ADJ
ajst-13407	95	4	white	white	ADJ
ajst-13407	95	5	noise	noise	NOUN
ajst-13407	95	6	is	be	AUX
ajst-13407	95	7	added	add	VERB
ajst-13407	95	8	to	to	ADP
ajst-13407	95	9	the	the	DET
ajst-13407	95	10	calculated	calculate	VERB
ajst-13407	95	11	samples	sample	NOUN
ajst-13407	95	12	to	to	PART
ajst-13407	95	13	achieve	achieve	VERB
ajst-13407	95	14	signal	signal	NOUN
ajst-13407	95	15	-	-	PUNCT
ajst-13407	95	16	to	to	ADP
ajst-13407	95	17	-	-	PUNCT
ajst-13407	95	18	noise	noise	NOUN
ajst-13407	95	19	ratios	ratio	NOUN
ajst-13407	95	20	of	of	ADP
ajst-13407	95	21	20db	20db	ADJ
ajst-13407	95	22	,	,	PUNCT
ajst-13407	95	23	30db	30db	NOUN
ajst-13407	95	24	,	,	PUNCT
ajst-13407	95	25	40db	40db	ADJ
ajst-13407	95	26	,	,	PUNCT
ajst-13407	95	27	50db	50db	ADJ
ajst-13407	95	28	,	,	PUNCT
ajst-13407	95	29	and	and	CCONJ
ajst-13407	95	30	70db	70db	ADJ
ajst-13407	95	31	.	.	PUNCT
ajst-13407	96	1	during	during	ADP
ajst-13407	96	2	training	training	NOUN
ajst-13407	96	3	,	,	PUNCT
ajst-13407	96	4	60,000	60,000	NUM
ajst-13407	96	5	random	random	ADJ
ajst-13407	96	6	samples	sample	NOUN
ajst-13407	96	7	are	be	AUX
ajst-13407	96	8	selected	select	VERB
ajst-13407	96	9	to	to	PART
ajst-13407	96	10	form	form	VERB
ajst-13407	96	11	the	the	DET
ajst-13407	96	12	training	training	NOUN
ajst-13407	96	13	dataset	dataset	NOUN
ajst-13407	96	14	,	,	PUNCT
ajst-13407	96	15	while	while	SCONJ
ajst-13407	96	16	the	the	DET
ajst-13407	96	17	remaining	remain	VERB
ajst-13407	96	18	5,596	5,596	NUM
ajst-13407	96	19	samples	sample	NOUN
ajst-13407	96	20	constitute	constitute	VERB
ajst-13407	96	21	the	the	DET
ajst-13407	96	22	testing	testing	NOUN
ajst-13407	96	23	dataset	dataset	NOUN
ajst-13407	96	24	.	.	PUNCT
ajst-13407	97	1	before	before	ADP
ajst-13407	97	2	training	train	VERB
ajst-13407	97	3	with	with	ADP
ajst-13407	97	4	a	a	DET
ajst-13407	97	5	neural	neural	ADJ
ajst-13407	97	6	network	network	NOUN
ajst-13407	97	7	,	,	PUNCT
ajst-13407	97	8	data	datum	NOUN
ajst-13407	97	9	preprocessing	preprocessing	NOUN
ajst-13407	97	10	is	be	AUX
ajst-13407	97	11	performed	perform	VERB
ajst-13407	97	12	,	,	PUNCT
ajst-13407	97	13	typically	typically	ADV
ajst-13407	97	14	normalizing	normalize	VERB
ajst-13407	97	15	the	the	DET
ajst-13407	97	16	data	datum	NOUN
ajst-13407	97	17	to	to	ADP
ajst-13407	97	18	the	the	DET
ajst-13407	97	19	[	[	NOUN
ajst-13407	97	20	0,1	0,1	NUM
ajst-13407	97	21	]	]	PUNCT
ajst-13407	97	22	or	or	CCONJ
ajst-13407	97	23	[	[	X
ajst-13407	97	24	-1,1	-1,1	ADJ
ajst-13407	97	25	]	]	X
ajst-13407	97	26	range	range	NOUN
ajst-13407	97	27	.	.	PUNCT
ajst-13407	98	1	in	in	ADP
ajst-13407	98	2	this	this	DET
ajst-13407	98	3	particular	particular	ADJ
ajst-13407	98	4	problem	problem	NOUN
ajst-13407	98	5	,	,	PUNCT
ajst-13407	98	6	since	since	SCONJ
ajst-13407	98	7	both	both	DET
ajst-13407	98	8	electromotive	electromotive	ADJ
ajst-13407	98	9	force	force	NOUN
ajst-13407	98	10	and	and	CCONJ
ajst-13407	98	11	electrical	electrical	ADJ
ajst-13407	98	12	conductivity	conductivity	NOUN
ajst-13407	98	13	are	be	AUX
ajst-13407	98	14	positive	positive	ADJ
ajst-13407	98	15	values	value	NOUN
ajst-13407	98	16	,	,	PUNCT
ajst-13407	98	17	normalizing	normalize	VERB
ajst-13407	98	18	them	they	PRON
ajst-13407	98	19	to	to	ADP
ajst-13407	98	20	the	the	DET
ajst-13407	98	21	[	[	NOUN
ajst-13407	98	22	0,1	0,1	NUM
ajst-13407	98	23	]	]	PUNCT
ajst-13407	98	24	range	range	NOUN
ajst-13407	98	25	is	be	AUX
ajst-13407	98	26	more	more	ADV
ajst-13407	98	27	appropriate	appropriate	ADJ
ajst-13407	98	28	.	.	PUNCT
ajst-13407	99	1	in	in	ADP
ajst-13407	99	2	general	general	ADJ
ajst-13407	99	3	,	,	PUNCT
ajst-13407	99	4	the	the	DET
ajst-13407	99	5	representational	representational	ADJ
ajst-13407	99	6	capacity	capacity	NOUN
ajst-13407	99	7	of	of	ADP
ajst-13407	99	8	a	a	DET
ajst-13407	99	9	neural	neural	ADJ
ajst-13407	99	10	network	network	NOUN
ajst-13407	99	11	increases	increase	VERB
ajst-13407	99	12	with	with	ADP
ajst-13407	99	13	the	the	DET
ajst-13407	99	14	number	number	NOUN
ajst-13407	99	15	of	of	ADP
ajst-13407	99	16	layers	layer	NOUN
ajst-13407	99	17	and	and	CCONJ
ajst-13407	99	18	neurons	neuron	NOUN
ajst-13407	99	19	.	.	PUNCT
ajst-13407	100	1	however	however	ADV
ajst-13407	100	2	,	,	PUNCT
ajst-13407	100	3	adding	add	VERB
ajst-13407	100	4	more	more	ADJ
ajst-13407	100	5	layers	layer	NOUN
ajst-13407	100	6	and	and	CCONJ
ajst-13407	100	7	neurons	neuron	NOUN
ajst-13407	100	8	can	can	AUX
ajst-13407	100	9	lead	lead	VERB
ajst-13407	100	10	to	to	ADP
ajst-13407	100	11	a	a	DET
ajst-13407	100	12	significant	significant	ADJ
ajst-13407	100	13	increase	increase	NOUN
ajst-13407	100	14	in	in	ADP
ajst-13407	100	15	training	training	NOUN
ajst-13407	100	16	costs	cost	NOUN
ajst-13407	100	17	and	and	CCONJ
ajst-13407	100	18	a	a	DET
ajst-13407	100	19	higher	high	ADJ
ajst-13407	100	20	risk	risk	NOUN
ajst-13407	100	21	of	of	ADP
ajst-13407	100	22	overfitting	overfitte	VERB
ajst-13407	100	23	.	.	PUNCT
ajst-13407	101	1	therefore	therefore	ADV
ajst-13407	101	2	,	,	PUNCT
ajst-13407	101	3	in	in	ADP
ajst-13407	101	4	this	this	DET
ajst-13407	101	5	paper	paper	NOUN
ajst-13407	101	6	,	,	PUNCT
ajst-13407	101	7	a	a	DET
ajst-13407	101	8	two	two	NUM
ajst-13407	101	9	-	-	PUNCT
ajst-13407	101	10	layer	layer	NOUN
ajst-13407	101	11	neural	neural	ADJ
ajst-13407	101	12	network	network	NOUN
ajst-13407	101	13	is	be	AUX
ajst-13407	101	14	used	use	VERB
ajst-13407	101	15	,	,	PUNCT
ajst-13407	101	16	with	with	ADP
ajst-13407	101	17	each	each	DET
ajst-13407	101	18	layer	layer	NOUN
ajst-13407	101	19	containing	contain	VERB
ajst-13407	101	20	128	128	NUM
ajst-13407	101	21	neurons	neuron	NOUN
ajst-13407	101	22	.	.	PUNCT
ajst-13407	102	1	during	during	ADP
ajst-13407	102	2	the	the	DET
ajst-13407	102	3	training	training	NOUN
ajst-13407	102	4	process	process	NOUN
ajst-13407	102	5	,	,	PUNCT
ajst-13407	102	6	a	a	DET
ajst-13407	102	7	variable	variable	ADJ
ajst-13407	102	8	learning	learning	NOUN
ajst-13407	102	9	rate	rate	NOUN
ajst-13407	102	10	approach	approach	NOUN
ajst-13407	102	11	is	be	AUX
ajst-13407	102	12	employed	employ	VERB
ajst-13407	102	13	,	,	PUNCT
ajst-13407	102	14	starting	start	VERB
ajst-13407	102	15	with	with	ADP
ajst-13407	102	16	an	an	DET
ajst-13407	102	17	initial	initial	ADJ
ajst-13407	102	18	learning	learning	NOUN
ajst-13407	102	19	rate	rate	NOUN
ajst-13407	102	20	of	of	ADP
ajst-13407	102	21	0.01	0.01	NUM
ajst-13407	102	22	.	.	PUNCT
ajst-13407	103	1	when	when	SCONJ
ajst-13407	103	2	the	the	DET
ajst-13407	103	3	training	training	NOUN
ajst-13407	103	4	loss	loss	NOUN
ajst-13407	103	5	does	do	AUX
ajst-13407	103	6	not	not	PART
ajst-13407	103	7	show	show	VERB
ajst-13407	103	8	significant	significant	ADJ
ajst-13407	103	9	improvement	improvement	NOUN
ajst-13407	103	10	for	for	ADP
ajst-13407	103	11	10	10	NUM
ajst-13407	103	12	steps	step	NOUN
ajst-13407	103	13	,	,	PUNCT
ajst-13407	103	14	the	the	DET
ajst-13407	103	15	learning	learning	NOUN
ajst-13407	103	16	rate	rate	NOUN
ajst-13407	103	17	is	be	AUX
ajst-13407	103	18	multiplied	multiply	VERB
ajst-13407	103	19	by	by	ADP
ajst-13407	103	20	0.01	0.01	NUM
ajst-13407	103	21	.	.	PUNCT
ajst-13407	104	1	the	the	DET
ajst-13407	104	2	activation	activation	NOUN
ajst-13407	104	3	function	function	VERB
ajst-13407	104	4	for	for	ADP
ajst-13407	104	5	the	the	DET
ajst-13407	104	6	hidden	hide	VERB
ajst-13407	104	7	layer	layer	NOUN
ajst-13407	104	8	neurons	neuron	NOUN
ajst-13407	104	9	is	be	AUX
ajst-13407	104	10	the	the	DET
ajst-13407	104	11	rectified	rectified	ADJ
ajst-13407	104	12	linear	linear	NOUN
ajst-13407	104	13	unit	unit	NOUN
ajst-13407	104	14	(	(	PUNCT
ajst-13407	104	15	relu	relu	NOUN
ajst-13407	104	16	)	)	PUNCT
ajst-13407	104	17	.	.	PUNCT
ajst-13407	105	1	after	after	ADP
ajst-13407	105	2	making	make	VERB
ajst-13407	105	3	predictions	prediction	NOUN
ajst-13407	105	4	on	on	ADP
ajst-13407	105	5	the	the	DET
ajst-13407	105	6	test	test	NOUN
ajst-13407	105	7	dataset	dataset	NOUN
ajst-13407	105	8	samples	sample	NOUN
ajst-13407	105	9	,	,	PUNCT
ajst-13407	105	10	the	the	DET
ajst-13407	105	11	electrical	electrical	ADJ
ajst-13407	105	12	conductivity	conductivity	NOUN
ajst-13407	105	13	is	be	AUX
ajst-13407	105	14	obtained	obtain	VERB
ajst-13407	105	15	,	,	PUNCT
ajst-13407	105	16	then	then	ADV
ajst-13407	105	17	the	the	DET
ajst-13407	105	18	signal	signal	NOUN
ajst-13407	105	19	is	be	AUX
ajst-13407	105	20	reconstructed	reconstruct	VERB
ajst-13407	105	21	based	base	VERB
ajst-13407	105	22	on	on	ADP
ajst-13407	105	23	this	this	DET
ajst-13407	105	24	information	information	NOUN
ajst-13407	105	25	.	.	PUNCT
ajst-13407	106	1	the	the	DET
ajst-13407	106	2	reconstructed	reconstructed	ADJ
ajst-13407	106	3	signal	signal	NOUN
ajst-13407	106	4	is	be	AUX
ajst-13407	106	5	free	free	ADJ
ajst-13407	106	6	from	from	ADP
ajst-13407	106	7	noise	noise	NOUN
ajst-13407	106	8	.	.	PUNCT
ajst-13407	107	1	if	if	SCONJ
ajst-13407	107	2	the	the	DET
ajst-13407	107	3	error	error	NOUN
ajst-13407	107	4	between	between	ADP
ajst-13407	107	5	the	the	DET
ajst-13407	107	6	predicted	predict	VERB
ajst-13407	107	7	electrical	electrical	ADJ
ajst-13407	107	8	conductivity	conductivity	NOUN
ajst-13407	107	9	from	from	ADP
ajst-13407	107	10	the	the	DET
ajst-13407	107	11	noisy	noisy	ADJ
ajst-13407	107	12	data	datum	NOUN
ajst-13407	107	13	and	and	CCONJ
ajst-13407	107	14	the	the	DET
ajst-13407	107	15	actual	actual	ADJ
ajst-13407	107	16	electrical	electrical	ADJ
ajst-13407	107	17	conductivity	conductivity	NOUN
ajst-13407	107	18	is	be	AUX
ajst-13407	107	19	sufficiently	sufficiently	ADV
ajst-13407	107	20	small	small	ADJ
ajst-13407	107	21	,	,	PUNCT
ajst-13407	107	22	the	the	DET
ajst-13407	107	23	error	error	NOUN
ajst-13407	107	24	between	between	ADP
ajst-13407	107	25	the	the	DET
ajst-13407	107	26	reconstructed	reconstructed	ADJ
ajst-13407	107	27	signal	signal	NOUN
ajst-13407	107	28	and	and	CCONJ
ajst-13407	107	29	the	the	DET
ajst-13407	107	30	original	original	ADJ
ajst-13407	107	31	signal	signal	NOUN
ajst-13407	107	32	is	be	AUX
ajst-13407	107	33	also	also	ADV
ajst-13407	107	34	sufficiently	sufficiently	ADV
ajst-13407	107	35	small	small	ADJ
ajst-13407	107	36	.	.	PUNCT
ajst-13407	108	1	since	since	SCONJ
ajst-13407	108	2	the	the	DET
ajst-13407	108	3	reconstructed	reconstruct	VERB
ajst-13407	108	4	signal	signal	NOUN
ajst-13407	108	5	is	be	AUX
ajst-13407	108	6	noise	noise	NOUN
ajst-13407	108	7	-	-	PUNCT
ajst-13407	108	8	free	free	ADJ
ajst-13407	108	9	,	,	PUNCT
ajst-13407	108	10	the	the	DET
ajst-13407	108	11	goal	goal	NOUN
ajst-13407	108	12	of	of	ADP
ajst-13407	108	13	denoising	denoising	NOUN
ajst-13407	108	14	is	be	AUX
ajst-13407	108	15	achieved	achieve	VERB
ajst-13407	108	16	,	,	PUNCT
ajst-13407	108	17	as	as	SCONJ
ajst-13407	108	18	shown	show	VERB
ajst-13407	108	19	in	in	ADP
ajst-13407	108	20	figures	figure	NOUN
ajst-13407	108	21	3	3	NUM
ajst-13407	108	22	.	.	PUNCT
ajst-13407	108	23	figure	figure	NOUN
ajst-13407	108	24	3	3	NUM
ajst-13407	108	25	.	.	PUNCT
ajst-13407	108	26	signals(the	signals(the	ADJ
ajst-13407	108	27	response	response	NOUN
ajst-13407	108	28	of	of	ADP
ajst-13407	108	29	gatem	gatem	NOUN
ajst-13407	108	30	)	)	PUNCT
ajst-13407	108	31	(	(	PUNCT
ajst-13407	108	32	a	a	X
ajst-13407	108	33	)	)	PUNCT
ajst-13407	108	34	original	original	ADJ
ajst-13407	108	35	signal	signal	NOUN
ajst-13407	108	36	(	(	PUNCT
ajst-13407	108	37	b	b	NOUN
ajst-13407	108	38	)	)	PUNCT
ajst-13407	108	39	signal	signal	NOUN
ajst-13407	108	40	with	with	ADP
ajst-13407	108	41	a	a	DET
ajst-13407	108	42	signal	signal	NOUN
ajst-13407	108	43	-	-	PUNCT
ajst-13407	108	44	to	to	ADP
ajst-13407	108	45	-	-	PUNCT
ajst-13407	108	46	noise	noise	NOUN
ajst-13407	108	47	ratio	ratio	NOUN
ajst-13407	108	48	of	of	ADP
ajst-13407	108	49	40db	40db	PROPN
ajst-13407	108	50	(	(	PUNCT
ajst-13407	108	51	c	c	X
ajst-13407	108	52	)	)	PUNCT
ajst-13407	108	53	the	the	DET
ajst-13407	108	54	reconstructed	reconstruct	VERB
ajst-13407	108	55	signal	signal	NOUN
ajst-13407	108	56	at	at	ADP
ajst-13407	108	57	a	a	DET
ajst-13407	108	58	signal	signal	NOUN
ajst-13407	108	59	-	-	PUNCT
ajst-13407	108	60	to	to	ADP
ajst-13407	108	61	-	-	PUNCT
ajst-13407	108	62	noise	noise	NOUN
ajst-13407	108	63	ratio	ratio	NOUN
ajst-13407	108	64	of	of	ADP
ajst-13407	108	65	40db	40db	ADJ
ajst-13407	108	66	the	the	DET
ajst-13407	108	67	noise	noise	NOUN
ajst-13407	108	68	-	-	PUNCT
ajst-13407	108	69	free	free	ADJ
ajst-13407	108	70	data	datum	NOUN
ajst-13407	108	71	composes	compose	NOUN
ajst-13407	108	72	of	of	ADP
ajst-13407	108	73	the	the	DET
ajst-13407	108	74	matrix	matrix	NOUN
ajst-13407	108	75	a	a	PRON
ajst-13407	108	76	,	,	PUNCT
ajst-13407	108	77	and	and	CCONJ
ajst-13407	108	78	the	the	DET
ajst-13407	108	79	reconstructed	reconstruct	VERB
ajst-13407	108	80	signals	signal	NOUN
ajst-13407	108	81	composes	compose	VERB
ajst-13407	108	82	of	of	ADP
ajst-13407	108	83	the	the	DET
ajst-13407	108	84	matrix	matrix	NOUN
ajst-13407	108	85	c.	c.	NOUN
ajst-13407	108	86	assuming	assume	VERB
ajst-13407	108	87	there	there	PRON
ajst-13407	108	88	are	be	VERB
ajst-13407	108	89	n	n	DET
ajst-13407	108	90	samples	sample	NOUN
ajst-13407	108	91	and	and	CCONJ
ajst-13407	108	92	m	m	PRON
ajst-13407	108	93	time	time	NOUN
ajst-13407	108	94	points	point	NOUN
ajst-13407	108	95	,	,	PUNCT
ajst-13407	108	96	both	both	PRON
ajst-13407	108	97	a	a	PRON
ajst-13407	108	98	and	and	CCONJ
ajst-13407	108	99	c	c	NOUN
ajst-13407	108	100	are	be	AUX
ajst-13407	108	101	twodimensional	twodimensional	ADJ
ajst-13407	108	102	matrices	matrix	NOUN
ajst-13407	108	103	with	with	ADP
ajst-13407	108	104	n	n	CCONJ
ajst-13407	108	105	rows	row	NOUN
ajst-13407	108	106	and	and	CCONJ
ajst-13407	108	107	m	m	NOUN
ajst-13407	108	108	columns	column	NOUN
ajst-13407	108	109	,	,	PUNCT
ajst-13407	108	110	where	where	SCONJ
ajst-13407	108	111	each	each	DET
ajst-13407	108	112	row	row	NOUN
ajst-13407	108	113	represents	represent	VERB
ajst-13407	108	114	an	an	DET
ajst-13407	108	115	electromotive	electromotive	ADJ
ajst-13407	108	116	force	force	NOUN
ajst-13407	108	117	signal	signal	NOUN
ajst-13407	108	118	.	.	PUNCT
ajst-13407	109	1	the	the	DET
ajst-13407	109	2	average	average	ADJ
ajst-13407	109	3	relative	relative	ADJ
ajst-13407	109	4	error	error	NOUN
ajst-13407	109	5	(	(	PUNCT
ajst-13407	109	6	ae	ae	PROPN
ajst-13407	109	7	)	)	PUNCT
ajst-13407	109	8	can	can	AUX
ajst-13407	109	9	be	be	AUX
ajst-13407	109	10	calculated	calculate	VERB
ajst-13407	109	11	using	use	VERB
ajst-13407	109	12	the	the	DET
ajst-13407	109	13	following	follow	VERB
ajst-13407	109	14	formula	formula	NOUN
ajst-13407	109	15	:	:	PUNCT
ajst-13407	109	16	1	1	NUM
ajst-13407	109	17	1	1	NUM
ajst-13407	109	18	)	)	PUNCT
ajst-13407	109	19	/	/	SYM
ajst-13407	109	20	(	(	PUNCT
ajst-13407	109	21	)	)	PUNCT
ajst-13407	109	22	100	100	NUM
ajst-13407	109	23	%	%	NOUN
ajst-13407	110	1	n	n	PRON
ajst-13407	110	2	m	m	VERB
ajst-13407	110	3	ij	ij	INTJ
ajst-13407	110	4	ij	ij	INTJ
ajst-13407	111	1	i	i	PRON
ajst-13407	111	2	j	j	PROPN
ajst-13407	112	1	ij	ij	INTJ
ajst-13407	112	2	a	a	DET
ajst-13407	112	3	c	c	NOUN
ajst-13407	112	4	n	n	PRON
ajst-13407	112	5	m	m	VERB
ajst-13407	112	6	a	a	VERB
ajst-13407	112	7			ADJ
ajst-13407	112	8			PROPN
ajst-13407	112	9			NOUN
ajst-13407	112	10	ae=	ae=	NOUN
ajst-13407	112	11	(	(	PUNCT
ajst-13407	112	12	(	(	PUNCT
ajst-13407	112	13	2	2	NUM
ajst-13407	112	14	)	)	PUNCT
ajst-13407	112	15	in	in	ADP
ajst-13407	112	16	this	this	DET
ajst-13407	112	17	paper	paper	NOUN
ajst-13407	112	18	,	,	PUNCT
ajst-13407	112	19	100	100	NUM
ajst-13407	112	20	samples	sample	NOUN
ajst-13407	112	21	are	be	AUX
ajst-13407	112	22	selected	select	VERB
ajst-13407	112	23	for	for	ADP
ajst-13407	112	24	reconstruction	reconstruction	NOUN
ajst-13407	112	25	251	251	NUM
ajst-13407	112	26	and	and	CCONJ
ajst-13407	112	27	there	there	PRON
ajst-13407	112	28	are	be	VERB
ajst-13407	112	29	81	81	NUM
ajst-13407	112	30	time	time	NOUN
ajst-13407	112	31	points	point	NOUN
ajst-13407	112	32	(	(	PUNCT
ajst-13407	112	33	100	100	NUM
ajst-13407	112	34	,	,	PUNCT
ajst-13407	112	35	81n	81n	NOUN
ajst-13407	112	36	m	m	NOUN
ajst-13407	112	37			NUM
ajst-13407	112	38	)	)	PUNCT
ajst-13407	112	39	.	.	PUNCT
ajst-13407	113	1	the	the	DET
ajst-13407	113	2	ae	ae	PROPN
ajst-13407	113	3	values	value	NOUN
ajst-13407	113	4	for	for	ADP
ajst-13407	113	5	different	different	ADJ
ajst-13407	113	6	signal	signal	NOUN
ajst-13407	113	7	-	-	PUNCT
ajst-13407	113	8	to	to	ADP
ajst-13407	113	9	-	-	PUNCT
ajst-13407	113	10	noise	noise	NOUN
ajst-13407	113	11	ratios	ratio	NOUN
ajst-13407	113	12	are	be	AUX
ajst-13407	113	13	as	as	SCONJ
ajst-13407	113	14	shown	show	VERB
ajst-13407	113	15	in	in	ADP
ajst-13407	113	16	table	table	NOUN
ajst-13407	113	17	2	2	NUM
ajst-13407	113	18	.	.	PUNCT
ajst-13407	113	19	table	table	NOUN
ajst-13407	113	20	2	2	NUM
ajst-13407	113	21	.	.	X
ajst-13407	113	22	ae	ae	PROPN
ajst-13407	113	23	values	value	NOUN
ajst-13407	113	24	for	for	ADP
ajst-13407	113	25	different	different	ADJ
ajst-13407	113	26	signal	signal	NOUN
ajst-13407	113	27	-	-	PUNCT
ajst-13407	113	28	to	to	ADP
ajst-13407	113	29	-	-	PUNCT
ajst-13407	113	30	noise	noise	NOUN
ajst-13407	113	31	ratios	ratio	NOUN
ajst-13407	113	32	snr	snr	PROPN
ajst-13407	113	33	ae	ae	PROPN
ajst-13407	113	34	30db	30db	NOUN
ajst-13407	113	35	0.63	0.63	NUM
ajst-13407	113	36	%	%	NOUN
ajst-13407	113	37	40db	40db	NOUN
ajst-13407	113	38	0.35	0.35	NUM
ajst-13407	113	39	%	%	NOUN
ajst-13407	113	40	50db	50db	ADJ
ajst-13407	113	41	0.27	0.27	NUM
ajst-13407	113	42	%	%	NOUN
ajst-13407	113	43	70db	70db	ADJ
ajst-13407	113	44	0.27	0.27	NUM
ajst-13407	113	45	%	%	NOUN
ajst-13407	113	46	as	as	SCONJ
ajst-13407	113	47	observed	observe	VERB
ajst-13407	113	48	from	from	ADP
ajst-13407	113	49	the	the	DET
ajst-13407	113	50	table	table	NOUN
ajst-13407	114	1	,	,	PUNCT
ajst-13407	114	2	the	the	DET
ajst-13407	114	3	error	error	NOUN
ajst-13407	114	4	between	between	ADP
ajst-13407	114	5	the	the	DET
ajst-13407	114	6	denoised	denoise	VERB
ajst-13407	114	7	signal	signal	NOUN
ajst-13407	114	8	and	and	CCONJ
ajst-13407	114	9	the	the	DET
ajst-13407	114	10	original	original	ADJ
ajst-13407	114	11	signal	signal	NOUN
ajst-13407	114	12	is	be	AUX
ajst-13407	114	13	very	very	ADV
ajst-13407	114	14	small	small	ADJ
ajst-13407	114	15	.	.	PUNCT
ajst-13407	115	1	when	when	SCONJ
ajst-13407	115	2	the	the	DET
ajst-13407	115	3	signalto	signalto	NOUN
ajst-13407	115	4	-	-	PUNCT
ajst-13407	115	5	noise	noise	NOUN
ajst-13407	115	6	ratio	ratio	NOUN
ajst-13407	115	7	is	be	AUX
ajst-13407	115	8	above	above	ADP
ajst-13407	115	9	30db	30db	NOUN
ajst-13407	115	10	,	,	PUNCT
ajst-13407	115	11	the	the	DET
ajst-13407	115	12	average	average	ADJ
ajst-13407	115	13	relative	relative	ADJ
ajst-13407	115	14	error	error	NOUN
ajst-13407	115	15	is	be	AUX
ajst-13407	115	16	not	not	PART
ajst-13407	115	17	greater	great	ADJ
ajst-13407	115	18	than	than	ADP
ajst-13407	115	19	1	1	NUM
ajst-13407	115	20	%	%	NOUN
ajst-13407	115	21	.	.	PUNCT
ajst-13407	116	1	in	in	ADP
ajst-13407	116	2	this	this	DET
ajst-13407	116	3	paper	paper	NOUN
ajst-13407	116	4	,	,	PUNCT
ajst-13407	116	5	the	the	DET
ajst-13407	116	6	testing	testing	NOUN
ajst-13407	116	7	was	be	AUX
ajst-13407	116	8	also	also	ADV
ajst-13407	116	9	conducted	conduct	VERB
ajst-13407	116	10	with	with	ADP
ajst-13407	116	11	data	datum	NOUN
ajst-13407	116	12	at	at	ADP
ajst-13407	116	13	a	a	DET
ajst-13407	116	14	signal	signal	NOUN
ajst-13407	116	15	-	-	PUNCT
ajst-13407	116	16	to	to	ADP
ajst-13407	116	17	-	-	PUNCT
ajst-13407	116	18	noise	noise	NOUN
ajst-13407	116	19	ratio	ratio	NOUN
ajst-13407	116	20	of	of	ADP
ajst-13407	116	21	20db	20db	NOUN
ajst-13407	116	22	,	,	PUNCT
ajst-13407	116	23	where	where	SCONJ
ajst-13407	116	24	some	some	DET
ajst-13407	116	25	data	datum	NOUN
ajst-13407	116	26	had	have	VERB
ajst-13407	116	27	larger	large	ADJ
ajst-13407	116	28	errors	error	NOUN
ajst-13407	116	29	.	.	PUNCT
ajst-13407	117	1	if	if	SCONJ
ajst-13407	117	2	we	we	PRON
ajst-13407	117	3	use	use	VERB
ajst-13407	117	4	a	a	DET
ajst-13407	117	5	criterion	criterion	NOUN
ajst-13407	117	6	of	of	ADP
ajst-13407	117	7	a	a	DET
ajst-13407	117	8	relative	relative	ADJ
ajst-13407	117	9	error	error	NOUN
ajst-13407	117	10	not	not	PART
ajst-13407	117	11	exceeding	exceed	VERB
ajst-13407	117	12	1	1	NUM
ajst-13407	117	13	%	%	NOUN
ajst-13407	117	14	,	,	PUNCT
ajst-13407	117	15	the	the	DET
ajst-13407	117	16	accuracy	accuracy	NOUN
ajst-13407	117	17	of	of	ADP
ajst-13407	117	18	this	this	DET
ajst-13407	117	19	network	network	NOUN
ajst-13407	117	20	can	can	AUX
ajst-13407	117	21	reach	reach	VERB
ajst-13407	117	22	92	92	NUM
ajst-13407	117	23	%	%	NOUN
ajst-13407	117	24	.	.	PUNCT
ajst-13407	118	1	4	4	X
ajst-13407	118	2	.	.	X
ajst-13407	118	3	conclusion	conclusion	NOUN
ajst-13407	118	4	the	the	DET
ajst-13407	118	5	gatem	gatem	NOUN
ajst-13407	118	6	system	system	NOUN
ajst-13407	118	7	has	have	AUX
ajst-13407	118	8	been	be	AUX
ajst-13407	118	9	successfully	successfully	ADV
ajst-13407	118	10	applied	apply	VERB
ajst-13407	118	11	in	in	ADP
ajst-13407	118	12	various	various	ADJ
ajst-13407	118	13	fields	field	NOUN
ajst-13407	118	14	such	such	ADJ
ajst-13407	118	15	as	as	ADP
ajst-13407	118	16	groundwater	groundwater	NOUN
ajst-13407	118	17	resource	resource	NOUN
ajst-13407	118	18	exploration	exploration	NOUN
ajst-13407	118	19	and	and	CCONJ
ajst-13407	118	20	coal	coal	NOUN
ajst-13407	118	21	resource	resource	NOUN
ajst-13407	118	22	exploration	exploration	NOUN
ajst-13407	118	23	,	,	PUNCT
ajst-13407	118	24	yielding	yield	VERB
ajst-13407	118	25	promising	promising	ADJ
ajst-13407	118	26	results	result	NOUN
ajst-13407	118	27	.	.	PUNCT
ajst-13407	119	1	in	in	ADP
ajst-13407	119	2	this	this	DET
ajst-13407	119	3	paper	paper	NOUN
ajst-13407	119	4	,	,	PUNCT
ajst-13407	119	5	based	base	VERB
ajst-13407	119	6	on	on	ADP
ajst-13407	119	7	the	the	DET
ajst-13407	119	8	methods	method	NOUN
ajst-13407	119	9	mentioned	mention	VERB
ajst-13407	119	10	above	above	ADV
ajst-13407	119	11	,	,	PUNCT
ajst-13407	119	12	the	the	DET
ajst-13407	119	13	following	follow	VERB
ajst-13407	119	14	work	work	NOUN
ajst-13407	119	15	was	be	AUX
ajst-13407	119	16	conducted	conduct	VERB
ajst-13407	119	17	to	to	PART
ajst-13407	119	18	address	address	VERB
ajst-13407	119	19	issues	issue	NOUN
ajst-13407	119	20	in	in	ADP
ajst-13407	119	21	numerical	numerical	ADJ
ajst-13407	119	22	simulation	simulation	NOUN
ajst-13407	119	23	and	and	CCONJ
ajst-13407	119	24	noise	noise	NOUN
ajst-13407	119	25	suppression	suppression	NOUN
ajst-13407	119	26	:	:	PUNCT
ajst-13407	119	27	1	1	X
ajst-13407	119	28	.	.	X
ajst-13407	119	29	carrying	carry	VERB
ajst-13407	119	30	out	out	ADP
ajst-13407	119	31	the	the	DET
ajst-13407	119	32	parallel	parallel	ADJ
ajst-13407	119	33	computation	computation	NOUN
ajst-13407	119	34	of	of	ADP
ajst-13407	119	35	gatem	gatem	NOUN
ajst-13407	119	36	responses	response	NOUN
ajst-13407	119	37	based	base	VERB
ajst-13407	119	38	on	on	ADP
ajst-13407	119	39	the	the	DET
ajst-13407	119	40	openmp	openmp	NOUN
ajst-13407	119	41	.	.	PUNCT
ajst-13407	120	1	the	the	DET
ajst-13407	120	2	speedup	speedup	NOUN
ajst-13407	120	3	for	for	ADP
ajst-13407	120	4	static	static	ADJ
ajst-13407	120	5	scheduling	scheduling	NOUN
ajst-13407	120	6	,	,	PUNCT
ajst-13407	120	7	dynamic	dynamic	ADJ
ajst-13407	120	8	scheduling	scheduling	NOUN
ajst-13407	120	9	,	,	PUNCT
ajst-13407	120	10	and	and	CCONJ
ajst-13407	120	11	heuristic	heuristic	ADJ
ajst-13407	120	12	scheduling	scheduling	NOUN
ajst-13407	120	13	for	for	ADP
ajst-13407	120	14	a	a	DET
ajst-13407	120	15	three	three	NUM
ajst-13407	120	16	-	-	PUNCT
ajst-13407	120	17	layer	layer	NOUN
ajst-13407	120	18	model	model	NOUN
ajst-13407	120	19	is	be	AUX
ajst-13407	120	20	3.98	3.98	NUM
ajst-13407	120	21	,	,	PUNCT
ajst-13407	120	22	4.28	4.28	NUM
ajst-13407	120	23	,	,	PUNCT
ajst-13407	120	24	and	and	CCONJ
ajst-13407	120	25	4.64	4.64	NUM
ajst-13407	120	26	,	,	PUNCT
ajst-13407	120	27	respectively	respectively	ADV
ajst-13407	120	28	.	.	PUNCT
ajst-13407	121	1	2	2	X
ajst-13407	121	2	.	.	NUM
ajst-13407	121	3	deployed	deploy	VERB
ajst-13407	121	4	the	the	DET
ajst-13407	121	5	parallel	parallel	ADJ
ajst-13407	121	6	computing	computing	NOUN
ajst-13407	121	7	program	program	NOUN
ajst-13407	121	8	based	base	VERB
ajst-13407	121	9	on	on	ADP
ajst-13407	121	10	the	the	DET
ajst-13407	121	11	openmp	openmp	NOUN
ajst-13407	121	12	on	on	ADP
ajst-13407	121	13	a	a	DET
ajst-13407	121	14	cloud	cloud	NOUN
ajst-13407	121	15	computing	computing	NOUN
ajst-13407	121	16	platform	platform	NOUN
ajst-13407	121	17	.	.	PUNCT
ajst-13407	122	1	as	as	ADP
ajst-13407	122	2	the	the	DET
ajst-13407	122	3	number	number	NOUN
ajst-13407	122	4	of	of	ADP
ajst-13407	122	5	computational	computational	ADJ
ajst-13407	122	6	models	model	NOUN
ajst-13407	122	7	increasing	increase	VERB
ajst-13407	122	8	,	,	PUNCT
ajst-13407	122	9	the	the	DET
ajst-13407	122	10	speedup	speedup	NOUN
ajst-13407	122	11	is	be	AUX
ajst-13407	122	12	also	also	ADV
ajst-13407	122	13	increased	increase	VERB
ajst-13407	122	14	,	,	PUNCT
ajst-13407	122	15	with	with	ADP
ajst-13407	122	16	a	a	DET
ajst-13407	122	17	maximum	maximum	ADJ
ajst-13407	122	18	speedup	speedup	NOUN
ajst-13407	122	19	reaching	reach	VERB
ajst-13407	122	20	11.37	11.37	NUM
ajst-13407	122	21	.	.	PUNCT
ajst-13407	123	1	3	3	X
ajst-13407	123	2	.	.	NUM
ajst-13407	123	3	employed	employ	VERB
ajst-13407	123	4	a	a	DET
ajst-13407	123	5	neural	neural	ADJ
ajst-13407	123	6	network	network	NOUN
ajst-13407	123	7	approach	approach	NOUN
ajst-13407	123	8	to	to	PART
ajst-13407	123	9	reconstruct	reconstruct	VERB
ajst-13407	123	10	noisy	noisy	ADJ
ajst-13407	123	11	electromagnetic	electromagnetic	ADJ
ajst-13407	123	12	signals	signal	NOUN
ajst-13407	123	13	.	.	PUNCT
ajst-13407	124	1	when	when	SCONJ
ajst-13407	124	2	the	the	DET
ajst-13407	124	3	signal	signal	NOUN
ajst-13407	124	4	-	-	PUNCT
ajst-13407	124	5	to	to	ADP
ajst-13407	124	6	-	-	PUNCT
ajst-13407	124	7	noise	noise	NOUN
ajst-13407	124	8	ratio	ratio	NOUN
ajst-13407	124	9	is	be	AUX
ajst-13407	124	10	above	above	ADP
ajst-13407	124	11	30db	30db	NOUN
ajst-13407	124	12	,	,	PUNCT
ajst-13407	124	13	the	the	DET
ajst-13407	124	14	error	error	NOUN
ajst-13407	124	15	between	between	ADP
ajst-13407	124	16	the	the	DET
ajst-13407	124	17	denoised	denoise	VERB
ajst-13407	124	18	signal	signal	NOUN
ajst-13407	124	19	and	and	CCONJ
ajst-13407	124	20	the	the	DET
ajst-13407	124	21	original	original	ADJ
ajst-13407	124	22	signal	signal	NOUN
ajst-13407	124	23	is	be	AUX
ajst-13407	124	24	very	very	ADV
ajst-13407	124	25	small	small	ADJ
ajst-13407	124	26	,	,	PUNCT
ajst-13407	124	27	with	with	ADP
ajst-13407	124	28	an	an	DET
ajst-13407	124	29	average	average	ADJ
ajst-13407	124	30	relative	relative	ADJ
ajst-13407	124	31	error	error	NOUN
ajst-13407	124	32	not	not	PART
ajst-13407	124	33	exceeding	exceed	VERB
ajst-13407	124	34	1	1	NUM
ajst-13407	124	35	%	%	NOUN
ajst-13407	124	36	.	.	PUNCT
ajst-13407	125	1	acknowledgment	acknowledgment	NOUN
ajst-13407	125	2	this	this	DET
ajst-13407	125	3	study	study	NOUN
ajst-13407	125	4	was	be	AUX
ajst-13407	125	5	carried	carry	VERB
ajst-13407	125	6	out	out	ADP
ajst-13407	125	7	within	within	ADP
ajst-13407	125	8	the	the	DET
ajst-13407	125	9	framework	framework	NOUN
ajst-13407	125	10	of	of	ADP
ajst-13407	125	11	the	the	DET
ajst-13407	125	12	project	project	NOUN
ajst-13407	125	13	‘	'	PUNCT
ajst-13407	125	14	research	research	NOUN
ajst-13407	125	15	on	on	ADP
ajst-13407	125	16	the	the	DET
ajst-13407	125	17	noise	noise	NOUN
ajst-13407	125	18	suppression	suppression	NOUN
ajst-13407	125	19	of	of	ADP
ajst-13407	125	20	the	the	DET
ajst-13407	125	21	gatem	gatem	NOUN
ajst-13407	125	22	system	system	NOUN
ajst-13407	125	23	by	by	ADP
ajst-13407	125	24	neural	neural	ADJ
ajst-13407	125	25	network	network	NOUN
ajst-13407	125	26	based	base	VERB
ajst-13407	125	27	on	on	ADP
ajst-13407	125	28	cloud	cloud	NOUN
ajst-13407	125	29	computing	computing	NOUN
ajst-13407	125	30	platform	platform	NOUN
ajst-13407	125	31	(	(	PUNCT
ajst-13407	125	32	20210101394jc	20210101394jc	NOUN
ajst-13407	125	33	)	)	PUNCT
ajst-13407	125	34	’	'	PUNCT
ajst-13407	125	35	supported	support	VERB
ajst-13407	125	36	by	by	ADP
ajst-13407	125	37	the	the	DET
ajst-13407	125	38	jilin	jilin	PROPN
ajst-13407	125	39	provincial	provincial	PROPN
ajst-13407	125	40	department	department	PROPN
ajst-13407	125	41	of	of	ADP
ajst-13407	125	42	science	science	NOUN
ajst-13407	125	43	and	and	CCONJ
ajst-13407	125	44	technology	technology	NOUN
ajst-13407	125	45	.	.	PUNCT
ajst-13407	126	1	references	reference	NOUN
ajst-13407	126	2	[	[	X
ajst-13407	126	3	1	1	NUM
ajst-13407	126	4	]	]	X
ajst-13407	126	5	qiu	qiu	PROPN
ajst-13407	126	6	n	n	CCONJ
ajst-13407	126	7	,	,	PUNCT
ajst-13407	127	1	chang	chang	PROPN
ajst-13407	127	2	j	j	PROPN
ajst-13407	127	3	k	k	PROPN
ajst-13407	127	4	,	,	PUNCT
ajst-13407	127	5	he	he	PRON
ajst-13407	127	6	z	z	NOUN
ajst-13407	127	7	x.	x.	NOUN
ajst-13407	127	8	comparison	comparison	NOUN
ajst-13407	127	9	of	of	ADP
ajst-13407	127	10	several	several	ADJ
ajst-13407	127	11	threshold	threshold	NOUN
ajst-13407	127	12	selection	selection	NOUN
ajst-13407	127	13	rules	rule	NOUN
ajst-13407	127	14	of	of	ADP
ajst-13407	127	15	the	the	DET
ajst-13407	127	16	wavelet	wavelet	NOUN
ajst-13407	127	17	denoising	denoising	NOUN
ajst-13407	127	18	on	on	ADP
ajst-13407	127	19	the	the	DET
ajst-13407	127	20	transient	transient	ADJ
ajst-13407	127	21	electromagnetic	electromagnetic	ADJ
ajst-13407	127	22	response[c	response[c	NOUN
ajst-13407	127	23	]	]	PUNCT
ajst-13407	127	24	.	.	PUNCT
ajst-13407	128	1	2nd	2nd	ADJ
ajst-13407	128	2	international	international	ADJ
ajst-13407	128	3	conference	conference	NOUN
ajst-13407	128	4	on	on	ADP
ajst-13407	128	5	environmental	environmental	ADJ
ajst-13407	128	6	and	and	CCONJ
ajst-13407	128	7	engineering	engineering	NOUN
ajst-13407	128	8	geophysics	geophysic	NOUN
ajst-13407	128	9	.	.	PUNCT
ajst-13407	129	1	2006	2006	NUM
ajst-13407	129	2	.	.	PUNCT
ajst-13407	130	1	[	[	X
ajst-13407	130	2	2	2	X
ajst-13407	130	3	]	]	PUNCT
ajst-13407	130	4	bouchedda	bouchedda	PROPN
ajst-13407	130	5	a	a	PRON
ajst-13407	130	6	,	,	PUNCT
ajst-13407	130	7	chouteau	chouteau	PROPN
ajst-13407	130	8	m	m	PROPN
ajst-13407	130	9	,	,	PUNCT
ajst-13407	130	10	keating	keate	VERB
ajst-13407	130	11	p	p	X
ajst-13407	130	12	,	,	PUNCT
ajst-13407	130	13	et	et	PROPN
ajst-13407	130	14	al	al	PROPN
ajst-13407	130	15	.	.	PROPN
ajst-13407	130	16	sferics	sferic	NOUN
ajst-13407	130	17	noise	noise	NOUN
ajst-13407	130	18	reduction	reduction	NOUN
ajst-13407	130	19	in	in	ADP
ajst-13407	130	20	time	time	NOUN
ajst-13407	130	21	-	-	PUNCT
ajst-13407	130	22	domain	domain	NOUN
ajst-13407	130	23	electromagnetic	electromagnetic	ADJ
ajst-13407	130	24	systems	system	NOUN
ajst-13407	130	25	:	:	PUNCT
ajst-13407	130	26	application	application	NOUN
ajst-13407	130	27	to	to	PART
ajst-13407	130	28	megatemii	megatemii	NOUN
ajst-13407	130	29	signal	signal	PROPN
ajst-13407	130	30	enhancement[j	enhancement[j	PROPN
ajst-13407	130	31	]	]	PUNCT
ajst-13407	130	32	.	.	PUNCT
ajst-13407	131	1	exploration	exploration	NOUN
ajst-13407	131	2	geophysics	geophysic	NOUN
ajst-13407	131	3	,	,	PUNCT
ajst-13407	131	4	2010	2010	NUM
ajst-13407	131	5	,	,	PUNCT
ajst-13407	131	6	41	41	NUM
ajst-13407	131	7	,	,	PUNCT
ajst-13407	131	8	225–239	225–239	NUM
ajst-13407	131	9	.	.	PUNCT
ajst-13407	132	1	[	[	X
ajst-13407	132	2	3	3	X
ajst-13407	132	3	]	]	X
ajst-13407	132	4	liu	liu	PROPN
ajst-13407	132	5	x	x	PROPN
ajst-13407	132	6	,	,	PUNCT
ajst-13407	132	7	wang	wang	PROPN
ajst-13407	132	8	j.	j.	PROPN
ajst-13407	132	9	improved	improve	VERB
ajst-13407	132	10	ica	ica	PROPN
ajst-13407	132	11	denoising	denoising	NOUN
ajst-13407	132	12	method	method	NOUN
ajst-13407	132	13	and	and	CCONJ
ajst-13407	132	14	application	application	NOUN
ajst-13407	132	15	in	in	ADP
ajst-13407	132	16	transient	transient	ADJ
ajst-13407	132	17	electromagnetic	electromagnetic	ADJ
ajst-13407	132	18	signal	signal	NOUN
ajst-13407	132	19	processing[j	processing[j	NOUN
ajst-13407	132	20	]	]	PUNCT
ajst-13407	132	21	.	.	PUNCT
ajst-13407	133	1	journal	journal	PROPN
ajst-13407	133	2	of	of	ADP
ajst-13407	133	3	beijing	beijing	PROPN
ajst-13407	133	4	normal	normal	ADJ
ajst-13407	133	5	university	university	NOUN
ajst-13407	133	6	(	(	PUNCT
ajst-13407	133	7	natural	natural	ADJ
ajst-13407	133	8	science	science	NOUN
ajst-13407	133	9	)	)	PUNCT
ajst-13407	133	10	,	,	PUNCT
ajst-13407	133	11	2011	2011	NUM
ajst-13407	133	12	,	,	PUNCT
ajst-13407	133	13	47(1	47(1	NUM
ajst-13407	133	14	):	):	PUNCT
ajst-13407	133	15	34	34	NUM
ajst-13407	133	16	-	-	SYM
ajst-13407	133	17	39	39	NUM
ajst-13407	133	18	.	.	PUNCT
ajst-13407	134	1	[	[	X
ajst-13407	134	2	4	4	NUM
ajst-13407	134	3	]	]	X
ajst-13407	134	4	reninger	reninger	NOUN
ajst-13407	134	5	p	p	NOUN
ajst-13407	134	6	a	a	DET
ajst-13407	134	7	,	,	PUNCT
ajst-13407	134	8	martelet	martelet	NOUN
ajst-13407	134	9	g	g	NOUN
ajst-13407	134	10	,	,	PUNCT
ajst-13407	134	11	deparis	deparis	ADP
ajst-13407	134	12	j	j	PROPN
ajst-13407	134	13	,	,	PUNCT
ajst-13407	134	14	et	et	PROPN
ajst-13407	134	15	al	al	PROPN
ajst-13407	134	16	.	.	PROPN
ajst-13407	134	17	singular	singular	PROPN
ajst-13407	134	18	value	value	NOUN
ajst-13407	134	19	decomposition	decomposition	NOUN
ajst-13407	134	20	as	as	ADP
ajst-13407	134	21	a	a	DET
ajst-13407	134	22	denoising	denoise	VERB
ajst-13407	134	23	tool	tool	NOUN
ajst-13407	134	24	for	for	ADP
ajst-13407	134	25	airborne	airborne	ADJ
ajst-13407	134	26	time	time	NOUN
ajst-13407	134	27	domain	domain	NOUN
ajst-13407	134	28	electromagnetic	electromagnetic	ADJ
ajst-13407	134	29	data[j	data[j	NOUN
ajst-13407	134	30	]	]	PUNCT
ajst-13407	134	31	.	.	PUNCT
ajst-13407	135	1	journal	journal	PROPN
ajst-13407	135	2	of	of	ADP
ajst-13407	135	3	applied	apply	VERB
ajst-13407	135	4	geophysics	geophysic	NOUN
ajst-13407	135	5	.	.	PUNCT
ajst-13407	136	1	2011,75	2011,75	NOUN
ajst-13407	136	2	:	:	PUNCT
ajst-13407	136	3	264	264	NUM
ajst-13407	136	4	-	-	SYM
ajst-13407	136	5	276	276	NUM
ajst-13407	136	6	.	.	PUNCT
ajst-13407	137	1	[	[	X
ajst-13407	137	2	5	5	X
ajst-13407	137	3	]	]	X
ajst-13407	137	4	chen	chen	PROPN
ajst-13407	137	5	b	b	PROPN
ajst-13407	137	6	,	,	PUNCT
ajst-13407	137	7	lu	lu	PROPN
ajst-13407	137	8	c	c	NOUN
ajst-13407	137	9	,	,	PUNCT
ajst-13407	137	10	liu	liu	PROPN
ajst-13407	137	11	g.	g.	PROPN
ajst-13407	137	12	a	a	DET
ajst-13407	137	13	denoising	denoising	NOUN
ajst-13407	137	14	method	method	NOUN
ajst-13407	137	15	based	base	VERB
ajst-13407	137	16	on	on	ADP
ajst-13407	137	17	kernel	kernel	PROPN
ajst-13407	137	18	principal	principal	PROPN
ajst-13407	137	19	component	component	NOUN
ajst-13407	137	20	analysis	analysis	NOUN
ajst-13407	137	21	for	for	ADP
ajst-13407	137	22	airborne	airborne	ADJ
ajst-13407	137	23	time	time	NOUN
ajst-13407	137	24	-	-	PUNCT
ajst-13407	137	25	domain	domain	NOUN
ajst-13407	137	26	electromagnetic	electromagnetic	ADJ
ajst-13407	137	27	data[j	data[j	NOUN
ajst-13407	137	28	]	]	X
ajst-13407	137	29	.	.	PUNCT
ajst-13407	138	1	chinese	chinese	ADJ
ajst-13407	138	2	journal	journal	PROPN
ajst-13407	138	3	of	of	ADP
ajst-13407	138	4	geophysics	geophysic	NOUN
ajst-13407	138	5	,	,	PUNCT
ajst-13407	138	6	2014	2014	NUM
ajst-13407	138	7	,	,	PUNCT
ajst-13407	138	8	57(1	57(1	NUM
ajst-13407	138	9	):	):	PUNCT
ajst-13407	138	10	295	295	NUM
ajst-13407	138	11	-	-	SYM
ajst-13407	138	12	302	302	NUM
ajst-13407	138	13	.	.	PUNCT
ajst-13407	139	1	[	[	X
ajst-13407	139	2	6	6	NUM
ajst-13407	139	3	]	]	PUNCT
ajst-13407	139	4	xu	xu	PROPN
ajst-13407	139	5	t	t	PROPN
ajst-13407	139	6	,	,	PUNCT
ajst-13407	139	7	chang	chang	PROPN
ajst-13407	139	8	k	k	PROPN
ajst-13407	139	9	,	,	PUNCT
ajst-13407	139	10	wang	wang	PROPN
ajst-13407	139	11	h	h	PROPN
ajst-13407	139	12	,	,	PUNCT
ajst-13407	139	13	et	et	PROPN
ajst-13407	139	14	al	al	PROPN
ajst-13407	139	15	.	.	PROPN
ajst-13407	139	16	emd	emd	PROPN
ajst-13407	139	17	application	application	NOUN
ajst-13407	139	18	in	in	ADP
ajst-13407	139	19	noise	noise	NOUN
ajst-13407	139	20	suppression	suppression	NOUN
ajst-13407	139	21	of	of	ADP
ajst-13407	139	22	superconducting	superconducte	VERB
ajst-13407	139	23	transient	transient	ADJ
ajst-13407	139	24	electromagnetic	electromagnetic	NOUN
ajst-13407	139	25	.	.	PUNCT
ajst-13407	140	1	low	low	ADJ
ajst-13407	140	2	temperature	temperature	NOUN
ajst-13407	140	3	physical	physical	ADJ
ajst-13407	140	4	letters	letter	NOUN
ajst-13407	140	5	,	,	PUNCT
ajst-13407	140	6	2014，36（5）：401	2014，36（5）：401	NUM
ajst-13407	140	7	-	-	SYM
ajst-13407	140	8	404	404	NUM
ajst-13407	140	9	.	.	PUNCT
ajst-13407	141	1	[	[	X
ajst-13407	141	2	7	7	X
ajst-13407	141	3	]	]	X
ajst-13407	141	4	liu	liu	PROPN
ajst-13407	141	5	r	r	PROPN
ajst-13407	141	6	,	,	PUNCT
ajst-13407	141	7	chen	chen	PROPN
ajst-13407	141	8	l	l	PROPN
ajst-13407	141	9	,	,	PUNCT
ajst-13407	141	10	lin	lin	PROPN
ajst-13407	141	11	,	,	PUNCT
ajst-13407	141	12	x.	x.	VERB
ajst-13407	141	13	the	the	DET
ajst-13407	141	14	application	application	NOUN
ajst-13407	141	15	of	of	ADP
ajst-13407	141	16	gaussian	gaussian	ADJ
ajst-13407	141	17	process	process	NOUN
ajst-13407	141	18	regression	regression	NOUN
ajst-13407	141	19	in	in	ADP
ajst-13407	141	20	aviation	aviation	NOUN
ajst-13407	141	21	transient	transient	NOUN
ajst-13407	141	22	electromagnetic	electromagnetic	ADJ
ajst-13407	141	23	denoising[j	denoising[j	NOUN
ajst-13407	141	24	]	]	PUNCT
ajst-13407	141	25	.	.	PUNCT
ajst-13407	142	1	chinese	chinese	ADJ
ajst-13407	142	2	journal	journal	PROPN
ajst-13407	142	3	of	of	ADP
ajst-13407	142	4	engineering	engineering	NOUN
ajst-13407	142	5	geophysics	geophysic	NOUN
ajst-13407	142	6	,	,	PUNCT
ajst-13407	142	7	2018，15（6	2018，15（6	PROPN
ajst-13407	142	8	）	）	NUM
ajst-13407	142	9	：	：	PUNCT
ajst-13407	142	10	771	771	NUM
ajst-13407	142	11	-	-	SYM
ajst-13407	142	12	779	779	NUM
ajst-13407	142	13	.	.	PUNCT
ajst-13407	143	1	[	[	X
ajst-13407	143	2	8	8	NUM
ajst-13407	143	3	]	]	X
ajst-13407	143	4	lui	lui	X
ajst-13407	143	5	f	f	PROPN
ajst-13407	143	6	,	,	PUNCT
ajst-13407	143	7	lin	lin	PROPN
ajst-13407	143	8	j	j	PROPN
ajst-13407	143	9	,	,	PUNCT
ajst-13407	143	10	wang	wang	PROPN
ajst-13407	143	11	y	y	PROPN
ajst-13407	143	12	z	z	PROPN
ajst-13407	143	13	,	,	PUNCT
ajst-13407	143	14	etal	etal	NOUN
ajst-13407	143	15	.	.	PUNCT
ajst-13407	144	1	design	design	NOUN
ajst-13407	144	2	of	of	ADP
ajst-13407	144	3	cable	cable	NOUN
ajst-13407	144	4	parallel	parallel	ADJ
ajst-13407	144	5	air	air	NOUN
ajst-13407	144	6	-	-	PUNCT
ajst-13407	144	7	core	core	NOUN
ajst-13407	144	8	coil	coil	NOUN
ajst-13407	144	9	sensor	sensor	NOUN
ajst-13407	144	10	to	to	PART
ajst-13407	144	11	reduce	reduce	VERB
ajst-13407	144	12	motion	motion	NOUN
ajst-13407	144	13	-	-	PUNCT
ajst-13407	144	14	induced	induce	VERB
ajst-13407	144	15	noise	noise	NOUN
ajst-13407	144	16	in	in	ADP
ajst-13407	144	17	helicopter	helicopter	NOUN
ajst-13407	144	18	transient	transient	ADJ
ajst-13407	144	19	electromagnetic	electromagnetic	ADJ
ajst-13407	144	20	system[j	system[j	NOUN
ajst-13407	144	21	]	]	PUNCT
ajst-13407	144	22	.	.	PUNCT
ajst-13407	145	1	ieee	ieee	PROPN
ajst-13407	145	2	transaction	transaction	PROPN
ajst-13407	145	3	soninstrumentationand	soninstrumentationand	PROPN
ajst-13407	145	4	measurement	measurement	PROPN
ajst-13407	145	5	,	,	PUNCT
ajst-13407	145	6	2019	2019	NUM
ajst-13407	145	7	,	,	PUNCT
ajst-13407	145	8	68(2	68(2	NOUN
ajst-13407	145	9	):	):	PUNCT
ajst-13407	145	10	525	525	NUM
ajst-13407	145	11	-	-	SYM
ajst-13407	145	12	532	532	NUM
ajst-13407	145	13	.	.	PUNCT
ajst-13407	146	1	[	[	X
ajst-13407	146	2	9	9	NUM
ajst-13407	146	3	]	]	X
ajst-13407	146	4	hou	hou	PROPN
ajst-13407	146	5	s	s	PROPN
ajst-13407	146	6	,	,	PUNCT
ajst-13407	146	7	zhang	zhang	PROPN
ajst-13407	146	8	f	f	PROPN
ajst-13407	146	9	,	,	PUNCT
ajst-13407	146	10	li	li	PROPN
ajst-13407	146	11	x	x	PROPN
ajst-13407	146	12	,	,	PUNCT
ajst-13407	146	13	et	et	PROPN
ajst-13407	146	14	al	al	PROPN
ajst-13407	146	15	.	.	PUNCT
ajst-13407	147	1	simultaneous	simultaneous	ADJ
ajst-13407	147	2	multi	multi	ADJ
ajst-13407	147	3	-	-	ADJ
ajst-13407	147	4	component	component	ADJ
ajst-13407	147	5	seismic	seismic	ADJ
ajst-13407	147	6	denoising	denoising	NOUN
ajst-13407	147	7	and	and	CCONJ
ajst-13407	147	8	reconstruction	reconstruction	NOUN
ajst-13407	147	9	via	via	ADP
ajst-13407	147	10	k	k	NOUN
ajst-13407	147	11	-	-	PUNCT
ajst-13407	147	12	svd[j	svd[j	NOUN
ajst-13407	147	13	]	]	PUNCT
ajst-13407	147	14	.	.	PUNCT
ajst-13407	148	1	journal	journal	PROPN
ajst-13407	148	2	of	of	ADP
ajst-13407	148	3	geophysics	geophysics	PROPN
ajst-13407	148	4	&	&	CCONJ
ajst-13407	148	5	engineering	engineering	PROPN
ajst-13407	148	6	,	,	PUNCT
ajst-13407	148	7	2017	2017	NUM
ajst-13407	148	8	,	,	PUNCT
ajst-13407	148	9	15:2503	15:2503	NOUN
ajst-13407	148	10	-	-	NOUN
ajst-13407	148	11	2507	2507	NUM
ajst-13407	148	12	.	.	PUNCT