id	sid	tid	token	lemma	pos
ajst-20186	1	1	academic	academic	ADJ
ajst-20186	1	2	journal	journal	NOUN
ajst-20186	1	3	of	of	ADP
ajst-20186	1	4	science	science	NOUN
ajst-20186	1	5	and	and	CCONJ
ajst-20186	1	6	technology	technology	NOUN
ajst-20186	1	7	issn	issn	NOUN
ajst-20186	1	8	:	:	PUNCT
ajst-20186	1	9	2771	2771	NUM
ajst-20186	1	10	-	-	SYM
ajst-20186	1	11	3032	3032	NUM
ajst-20186	1	12	|	|	NOUN
ajst-20186	1	13	vol	vol	NOUN
ajst-20186	1	14	.	.	PROPN
ajst-20186	2	1	10	10	NUM
ajst-20186	2	2	,	,	PUNCT
ajst-20186	2	3	no	no	INTJ
ajst-20186	2	4	.	.	NOUN
ajst-20186	2	5	2	2	NUM
ajst-20186	2	6	,	,	PUNCT
ajst-20186	2	7	2024	2024	NUM
ajst-20186	2	8	61	61	NUM
ajst-20186	2	9	recognition	recognition	NOUN
ajst-20186	2	10	of	of	ADP
ajst-20186	2	11	α	α	PROPN
ajst-20186	2	12	and	and	CCONJ
ajst-20186	2	13	β	β	NOUN
ajst-20186	2	14	radiation	radiation	NOUN
ajst-20186	2	15	waveforms	waveform	NOUN
ajst-20186	2	16	based	base	VERB
ajst-20186	2	17	on	on	ADP
ajst-20186	2	18	neural	neural	ADJ
ajst-20186	2	19	networks	network	NOUN
ajst-20186	2	20	pengzhang	pengzhang	PROPN
ajst-20186	2	21	yu1	yu1	PROPN
ajst-20186	2	22	,	,	PUNCT
ajst-20186	2	23	ke	ke	PROPN
ajst-20186	2	24	xiong1	xiong1	PROPN
ajst-20186	2	25	,	,	PUNCT
ajst-20186	2	26	*	*	PROPN
ajst-20186	2	27	,	,	PUNCT
ajst-20186	2	28	hao	hao	PROPN
ajst-20186	2	29	wang2	wang2	PROPN
ajst-20186	2	30	1	1	NUM
ajst-20186	2	31	college	college	NOUN
ajst-20186	2	32	of	of	ADP
ajst-20186	2	33	electronic	electronic	ADJ
ajst-20186	2	34	and	and	CCONJ
ajst-20186	2	35	information	information	NOUN
ajst-20186	2	36	,	,	PUNCT
ajst-20186	2	37	southwest	southwest	PROPN
ajst-20186	2	38	minzu	minzu	PROPN
ajst-20186	2	39	university	university	PROPN
ajst-20186	2	40	,	,	PUNCT
ajst-20186	2	41	chengdu	chengdu	PROPN
ajst-20186	2	42	610225	610225	NUM
ajst-20186	2	43	,	,	PUNCT
ajst-20186	2	44	china	china	PROPN
ajst-20186	2	45	2	2	NUM
ajst-20186	2	46	key	key	ADJ
ajst-20186	2	47	laboratory	laboratory	NOUN
ajst-20186	2	48	of	of	ADP
ajst-20186	2	49	electronic	electronic	ADJ
ajst-20186	2	50	information	information	NOUN
ajst-20186	2	51	engineering	engineering	NOUN
ajst-20186	2	52	,	,	PUNCT
ajst-20186	2	53	southwest	southwest	PROPN
ajst-20186	2	54	minzu	minzu	PROPN
ajst-20186	2	55	university	university	PROPN
ajst-20186	2	56	,	,	PUNCT
ajst-20186	2	57	chengdu	chengdu	PROPN
ajst-20186	2	58	610225	610225	NUM
ajst-20186	2	59	,	,	PUNCT
ajst-20186	2	60	china	china	PROPN
ajst-20186	2	61	*	*	PUNCT
ajst-20186	2	62	corresponding	correspond	VERB
ajst-20186	2	63	author	author	NOUN
ajst-20186	2	64	:	:	PUNCT
ajst-20186	3	1	xiong	xiong	PROPN
ajst-20186	3	2	ke	ke	PROPN
ajst-20186	3	3	(	(	PUNCT
ajst-20186	3	4	email	email	NOUN
ajst-20186	3	5	:	:	PUNCT
ajst-20186	3	6	pzy9104@gmail.com	pzy9104@gmail.com	X
ajst-20186	3	7	)	)	PUNCT
ajst-20186	3	8	abstract	abstract	NOUN
ajst-20186	3	9	:	:	PUNCT
ajst-20186	3	10	alpha	alpha	NOUN
ajst-20186	3	11	and	and	CCONJ
ajst-20186	3	12	beta	beta	NOUN
ajst-20186	3	13	radiation	radiation	NOUN
ajst-20186	3	14	do	do	AUX
ajst-20186	3	15	not	not	PART
ajst-20186	3	16	possess	possess	VERB
ajst-20186	3	17	penetrating	penetrate	VERB
ajst-20186	3	18	properties	property	NOUN
ajst-20186	3	19	to	to	ADP
ajst-20186	3	20	the	the	DET
ajst-20186	3	21	skin	skin	NOUN
ajst-20186	3	22	,	,	PUNCT
ajst-20186	3	23	but	but	CCONJ
ajst-20186	3	24	they	they	PRON
ajst-20186	3	25	can	can	AUX
ajst-20186	3	26	adhere	adhere	VERB
ajst-20186	3	27	to	to	ADP
ajst-20186	3	28	the	the	DET
ajst-20186	3	29	surface	surface	NOUN
ajst-20186	3	30	of	of	ADP
ajst-20186	3	31	the	the	DET
ajst-20186	3	32	human	human	ADJ
ajst-20186	3	33	skin	skin	NOUN
ajst-20186	3	34	.	.	PUNCT
ajst-20186	4	1	inhalation	inhalation	NOUN
ajst-20186	4	2	through	through	ADP
ajst-20186	4	3	the	the	DET
ajst-20186	4	4	mouth	mouth	NOUN
ajst-20186	4	5	and	and	CCONJ
ajst-20186	4	6	nose	nose	NOUN
ajst-20186	4	7	often	often	ADV
ajst-20186	4	8	poses	pose	VERB
ajst-20186	4	9	a	a	DET
ajst-20186	4	10	greater	great	ADJ
ajst-20186	4	11	risk	risk	NOUN
ajst-20186	4	12	to	to	ADP
ajst-20186	4	13	the	the	DET
ajst-20186	4	14	human	human	ADJ
ajst-20186	4	15	body	body	NOUN
ajst-20186	4	16	compared	compare	VERB
ajst-20186	4	17	to	to	ADP
ajst-20186	4	18	gamma	gamma	NOUN
ajst-20186	4	19	radiation	radiation	NOUN
ajst-20186	4	20	.	.	PUNCT
ajst-20186	5	1	traditional	traditional	ADJ
ajst-20186	5	2	methods	method	NOUN
ajst-20186	5	3	for	for	ADP
ajst-20186	5	4	identifying	identify	VERB
ajst-20186	5	5	alpha	alpha	NOUN
ajst-20186	5	6	and	and	CCONJ
ajst-20186	5	7	beta	beta	NOUN
ajst-20186	5	8	particles	particle	NOUN
ajst-20186	5	9	have	have	VERB
ajst-20186	5	10	some	some	DET
ajst-20186	5	11	drawbacks	drawback	NOUN
ajst-20186	5	12	,	,	PUNCT
ajst-20186	5	13	such	such	ADJ
ajst-20186	5	14	as	as	ADP
ajst-20186	5	15	high	high	ADJ
ajst-20186	5	16	requirements	requirement	NOUN
ajst-20186	5	17	for	for	ADP
ajst-20186	5	18	equipment	equipment	NOUN
ajst-20186	5	19	's	's	PART
ajst-20186	5	20	signal	signal	NOUN
ajst-20186	5	21	-	-	PUNCT
ajst-20186	5	22	to	to	ADP
ajst-20186	5	23	-	-	PUNCT
ajst-20186	5	24	noise	noise	NOUN
ajst-20186	5	25	ratio	ratio	NOUN
ajst-20186	5	26	and	and	CCONJ
ajst-20186	5	27	significant	significant	ADJ
ajst-20186	5	28	impact	impact	NOUN
ajst-20186	5	29	of	of	ADP
ajst-20186	5	30	noise	noise	NOUN
ajst-20186	5	31	on	on	ADP
ajst-20186	5	32	identification	identification	NOUN
ajst-20186	5	33	results	result	NOUN
ajst-20186	5	34	.	.	PUNCT
ajst-20186	6	1	we	we	PRON
ajst-20186	6	2	propose	propose	VERB
ajst-20186	6	3	the	the	DET
ajst-20186	6	4	utilization	utilization	NOUN
ajst-20186	6	5	of	of	ADP
ajst-20186	6	6	lightweight	lightweight	ADJ
ajst-20186	6	7	neural	neural	ADJ
ajst-20186	6	8	network	network	NOUN
ajst-20186	6	9	models	model	NOUN
ajst-20186	6	10	for	for	ADP
ajst-20186	6	11	alpha	alpha	NOUN
ajst-20186	6	12	and	and	CCONJ
ajst-20186	6	13	beta	beta	NOUN
ajst-20186	6	14	particle	particle	NOUN
ajst-20186	6	15	identification	identification	NOUN
ajst-20186	6	16	.	.	PUNCT
ajst-20186	7	1	these	these	DET
ajst-20186	7	2	models	model	NOUN
ajst-20186	7	3	exhibit	exhibit	VERB
ajst-20186	7	4	strong	strong	ADJ
ajst-20186	7	5	generalization	generalization	NOUN
ajst-20186	7	6	and	and	CCONJ
ajst-20186	7	7	robustness	robustness	NOUN
ajst-20186	7	8	,	,	PUNCT
ajst-20186	7	9	enhancing	enhance	VERB
ajst-20186	7	10	the	the	DET
ajst-20186	7	11	ability	ability	NOUN
ajst-20186	7	12	to	to	PART
ajst-20186	7	13	resist	resist	VERB
ajst-20186	7	14	noise	noise	NOUN
ajst-20186	7	15	interference	interference	NOUN
ajst-20186	7	16	during	during	ADP
ajst-20186	7	17	the	the	DET
ajst-20186	7	18	identification	identification	NOUN
ajst-20186	7	19	process	process	NOUN
ajst-20186	7	20	.	.	PUNCT
ajst-20186	8	1	additionally	additionally	ADV
ajst-20186	8	2	,	,	PUNCT
ajst-20186	8	3	their	their	PRON
ajst-20186	8	4	lightweight	lightweight	ADJ
ajst-20186	8	5	nature	nature	NOUN
ajst-20186	8	6	facilitates	facilitate	VERB
ajst-20186	8	7	deployment	deployment	NOUN
ajst-20186	8	8	on	on	ADP
ajst-20186	8	9	devices	device	NOUN
ajst-20186	8	10	,	,	PUNCT
ajst-20186	8	11	thereby	thereby	ADV
ajst-20186	8	12	contributing	contribute	VERB
ajst-20186	8	13	to	to	ADP
ajst-20186	8	14	the	the	DET
ajst-20186	8	15	prevention	prevention	NOUN
ajst-20186	8	16	of	of	ADP
ajst-20186	8	17	nuclear	nuclear	ADJ
ajst-20186	8	18	proliferation	proliferation	NOUN
ajst-20186	8	19	to	to	ADP
ajst-20186	8	20	some	some	DET
ajst-20186	8	21	extent	extent	NOUN
ajst-20186	8	22	.	.	PUNCT
ajst-20186	9	1	keywords	keyword	NOUN
ajst-20186	9	2	:	:	PUNCT
ajst-20186	9	3	αβ	αβ	DET
ajst-20186	9	4	ray	ray	NOUN
ajst-20186	9	5	recognition	recognition	NOUN
ajst-20186	9	6	,	,	PUNCT
ajst-20186	9	7	lightweight	lightweight	ADJ
ajst-20186	9	8	neural	neural	ADJ
ajst-20186	9	9	networks	network	NOUN
ajst-20186	9	10	,	,	PUNCT
ajst-20186	9	11	nuclear	nuclear	ADJ
ajst-20186	9	12	diffusion	diffusion	NOUN
ajst-20186	9	13	.	.	PUNCT
ajst-20186	10	1	1	1	X
ajst-20186	10	2	.	.	X
ajst-20186	10	3	introduction	introduction	NOUN
ajst-20186	10	4	with	with	ADP
ajst-20186	10	5	the	the	DET
ajst-20186	10	6	increasing	increase	VERB
ajst-20186	10	7	global	global	ADJ
ajst-20186	10	8	risk	risk	NOUN
ajst-20186	10	9	of	of	ADP
ajst-20186	10	10	nuclear	nuclear	ADJ
ajst-20186	10	11	leaks	leak	NOUN
ajst-20186	10	12	,	,	PUNCT
ajst-20186	10	13	humanity	humanity	NOUN
ajst-20186	10	14	is	be	AUX
ajst-20186	10	15	facing	face	VERB
ajst-20186	10	16	ever	ever	ADV
ajst-20186	10	17	greater	great	ADJ
ajst-20186	10	18	risks	risk	NOUN
ajst-20186	10	19	from	from	ADP
ajst-20186	10	20	nuclear	nuclear	ADJ
ajst-20186	10	21	sources	source	NOUN
ajst-20186	10	22	.	.	PUNCT
ajst-20186	11	1	nuclear	nuclear	ADJ
ajst-20186	11	2	radiation	radiation	NOUN
ajst-20186	11	3	refers	refer	VERB
ajst-20186	11	4	to	to	ADP
ajst-20186	11	5	particles	particle	NOUN
ajst-20186	11	6	or	or	CCONJ
ajst-20186	11	7	electromagnetic	electromagnetic	ADJ
ajst-20186	11	8	radiation	radiation	NOUN
ajst-20186	11	9	emitted	emit	VERB
ajst-20186	11	10	by	by	ADP
ajst-20186	11	11	radioactive	radioactive	ADJ
ajst-20186	11	12	nuclides	nuclide	NOUN
ajst-20186	11	13	,	,	PUNCT
ajst-20186	11	14	primarily	primarily	ADV
ajst-20186	11	15	α	α	X
ajst-20186	11	16	,	,	PUNCT
ajst-20186	11	17	β	β	NOUN
ajst-20186	11	18	,	,	PUNCT
ajst-20186	11	19	and	and	CCONJ
ajst-20186	11	20	γ	γ	PROPN
ajst-20186	11	21	rays	ray	NOUN
ajst-20186	11	22	.	.	PUNCT
ajst-20186	12	1	among	among	ADP
ajst-20186	12	2	them	they	PRON
ajst-20186	12	3	,	,	PUNCT
ajst-20186	12	4	γ	γ	PROPN
ajst-20186	12	5	rays	ray	NOUN
ajst-20186	12	6	have	have	VERB
ajst-20186	12	7	the	the	DET
ajst-20186	12	8	strongest	strong	ADJ
ajst-20186	12	9	penetrating	penetrate	VERB
ajst-20186	12	10	power	power	NOUN
ajst-20186	12	11	,	,	PUNCT
ajst-20186	12	12	and	and	CCONJ
ajst-20186	12	13	their	their	PRON
ajst-20186	12	14	hazards	hazard	NOUN
ajst-20186	12	15	are	be	AUX
ajst-20186	12	16	well	well	ADV
ajst-20186	12	17	recognized	recognize	VERB
ajst-20186	12	18	.	.	PUNCT
ajst-20186	13	1	they	they	PRON
ajst-20186	13	2	can	can	AUX
ajst-20186	13	3	penetrate	penetrate	VERB
ajst-20186	13	4	the	the	DET
ajst-20186	13	5	skin	skin	NOUN
ajst-20186	13	6	,	,	PUNCT
ajst-20186	13	7	causing	cause	VERB
ajst-20186	13	8	dna	dna	NOUN
ajst-20186	13	9	strand	strand	NOUN
ajst-20186	13	10	breaks	break	NOUN
ajst-20186	13	11	.	.	PUNCT
ajst-20186	14	1	this	this	DET
ajst-20186	14	2	dna	dna	PROPN
ajst-20186	14	3	damage	damage	NOUN
ajst-20186	14	4	can	can	AUX
ajst-20186	14	5	trigger	trigger	VERB
ajst-20186	14	6	dna	dna	PROPN
ajst-20186	14	7	repair	repair	NOUN
ajst-20186	14	8	processes	process	NOUN
ajst-20186	14	9	,	,	PUNCT
ajst-20186	14	10	but	but	CCONJ
ajst-20186	14	11	if	if	SCONJ
ajst-20186	14	12	not	not	PART
ajst-20186	14	13	properly	properly	ADV
ajst-20186	14	14	or	or	CCONJ
ajst-20186	14	15	completely	completely	ADV
ajst-20186	14	16	repaired	repair	VERB
ajst-20186	14	17	,	,	PUNCT
ajst-20186	14	18	it	it	PRON
ajst-20186	14	19	may	may	AUX
ajst-20186	14	20	lead	lead	VERB
ajst-20186	14	21	to	to	ADP
ajst-20186	14	22	genetic	genetic	ADJ
ajst-20186	14	23	mutations	mutation	NOUN
ajst-20186	14	24	and	and	CCONJ
ajst-20186	14	25	the	the	DET
ajst-20186	14	26	development	development	NOUN
ajst-20186	14	27	of	of	ADP
ajst-20186	14	28	cancer[7	cancer[7	PROPN
ajst-20186	14	29	]	]	PUNCT
ajst-20186	14	30	.	.	PUNCT
ajst-20186	15	1	studies	study	NOUN
ajst-20186	15	2	have	have	AUX
ajst-20186	15	3	shown	show	VERB
ajst-20186	15	4	that	that	SCONJ
ajst-20186	15	5	α	α	PROPN
ajst-20186	15	6	and	and	CCONJ
ajst-20186	15	7	β	β	X
ajst-20186	15	8	radiation	radiation	NOUN
ajst-20186	15	9	have	have	VERB
ajst-20186	15	10	a	a	DET
ajst-20186	15	11	more	more	ADV
ajst-20186	15	12	severe	severe	ADJ
ajst-20186	15	13	impact	impact	NOUN
ajst-20186	15	14	on	on	ADP
ajst-20186	15	15	human	human	ADJ
ajst-20186	15	16	life	life	NOUN
ajst-20186	15	17	.	.	PUNCT
ajst-20186	16	1	the	the	DET
ajst-20186	16	2	penetrating	penetrate	VERB
ajst-20186	16	3	power	power	NOUN
ajst-20186	16	4	of	of	ADP
ajst-20186	16	5	α	α	PROPN
ajst-20186	16	6	and	and	CCONJ
ajst-20186	16	7	β	β	PROPN
ajst-20186	16	8	rays	ray	NOUN
ajst-20186	16	9	is	be	AUX
ajst-20186	16	10	not	not	PART
ajst-20186	16	11	as	as	ADV
ajst-20186	16	12	strong	strong	ADJ
ajst-20186	16	13	as	as	ADP
ajst-20186	16	14	that	that	PRON
ajst-20186	16	15	of	of	ADP
ajst-20186	16	16	γ	γ	PROPN
ajst-20186	16	17	rays	ray	NOUN
ajst-20186	16	18	;	;	PUNCT
ajst-20186	16	19	α	α	PRON
ajst-20186	16	20	rays	ray	NOUN
ajst-20186	16	21	can	can	AUX
ajst-20186	16	22	be	be	AUX
ajst-20186	16	23	blocked	block	VERB
ajst-20186	16	24	by	by	ADP
ajst-20186	16	25	materials	material	NOUN
ajst-20186	16	26	as	as	ADV
ajst-20186	16	27	thin	thin	ADJ
ajst-20186	16	28	as	as	ADP
ajst-20186	16	29	a	a	DET
ajst-20186	16	30	sheet	sheet	NOUN
ajst-20186	16	31	of	of	ADP
ajst-20186	16	32	paper	paper	NOUN
ajst-20186	16	33	,	,	PUNCT
ajst-20186	16	34	and	and	CCONJ
ajst-20186	16	35	β	β	NOUN
ajst-20186	16	36	rays	ray	NOUN
ajst-20186	16	37	can	can	AUX
ajst-20186	16	38	not	not	PART
ajst-20186	16	39	penetrate	penetrate	VERB
ajst-20186	16	40	human	human	ADJ
ajst-20186	16	41	skin	skin	NOUN
ajst-20186	16	42	.	.	PUNCT
ajst-20186	17	1	however	however	ADV
ajst-20186	17	2	,	,	PUNCT
ajst-20186	17	3	if	if	SCONJ
ajst-20186	17	4	nuclear	nuclear	ADJ
ajst-20186	17	5	wastewater	wastewater	NOUN
ajst-20186	17	6	is	be	AUX
ajst-20186	17	7	discharged	discharge	VERB
ajst-20186	17	8	into	into	ADP
ajst-20186	17	9	the	the	DET
ajst-20186	17	10	ocean	ocean	NOUN
ajst-20186	17	11	and	and	CCONJ
ajst-20186	17	12	evaporates	evaporate	VERB
ajst-20186	17	13	to	to	PART
ajst-20186	17	14	form	form	NOUN
ajst-20186	17	15	rainwater	rainwater	NOUN
ajst-20186	17	16	,	,	PUNCT
ajst-20186	17	17	α	α	PROPN
ajst-20186	17	18	and	and	CCONJ
ajst-20186	17	19	β	β	X
ajst-20186	17	20	particles	particle	NOUN
ajst-20186	17	21	may	may	AUX
ajst-20186	17	22	float	float	VERB
ajst-20186	17	23	in	in	ADP
ajst-20186	17	24	the	the	DET
ajst-20186	17	25	air	air	NOUN
ajst-20186	17	26	,	,	PUNCT
ajst-20186	17	27	forming	form	VERB
ajst-20186	17	28	aerosols	aerosol	NOUN
ajst-20186	17	29	that	that	PRON
ajst-20186	17	30	adhere	adhere	VERB
ajst-20186	17	31	to	to	ADP
ajst-20186	17	32	the	the	DET
ajst-20186	17	33	human	human	ADJ
ajst-20186	17	34	body	body	NOUN
ajst-20186	17	35	.	.	PUNCT
ajst-20186	18	1	if	if	SCONJ
ajst-20186	18	2	not	not	PART
ajst-20186	18	3	properly	properly	ADV
ajst-20186	18	4	addressed	address	VERB
ajst-20186	18	5	,	,	PUNCT
ajst-20186	18	6	α	α	NOUN
ajst-20186	18	7	and	and	CCONJ
ajst-20186	18	8	β	β	X
ajst-20186	18	9	particles	particle	NOUN
ajst-20186	18	10	can	can	AUX
ajst-20186	18	11	enter	enter	VERB
ajst-20186	18	12	the	the	DET
ajst-20186	18	13	body	body	NOUN
ajst-20186	18	14	through	through	ADP
ajst-20186	18	15	the	the	DET
ajst-20186	18	16	mouth	mouth	NOUN
ajst-20186	18	17	and	and	CCONJ
ajst-20186	18	18	nose	nose	NOUN
ajst-20186	18	19	,	,	PUNCT
ajst-20186	18	20	causing	cause	VERB
ajst-20186	18	21	severe	severe	ADJ
ajst-20186	18	22	damage	damage	NOUN
ajst-20186	18	23	to	to	ADP
ajst-20186	18	24	human	human	ADJ
ajst-20186	18	25	organs	organ	NOUN
ajst-20186	18	26	,	,	PUNCT
ajst-20186	18	27	tissue	tissue	NOUN
ajst-20186	18	28	damage	damage	NOUN
ajst-20186	18	29	,	,	PUNCT
ajst-20186	18	30	tumor	tumor	NOUN
ajst-20186	18	31	development	development	NOUN
ajst-20186	18	32	,	,	PUNCT
ajst-20186	18	33	and	and	CCONJ
ajst-20186	18	34	possibly	possibly	ADV
ajst-20186	18	35	genetic	genetic	ADJ
ajst-20186	18	36	mutations	mutation	NOUN
ajst-20186	18	37	,	,	PUNCT
ajst-20186	18	38	increasing	increase	VERB
ajst-20186	18	39	health	health	NOUN
ajst-20186	18	40	risks	risk	NOUN
ajst-20186	18	41	for	for	ADP
ajst-20186	18	42	future	future	ADJ
ajst-20186	18	43	generations	generation	NOUN
ajst-20186	18	44	.	.	PUNCT
ajst-20186	19	1	waveform	waveform	VERB
ajst-20186	19	2	recognition	recognition	NOUN
ajst-20186	19	3	technology	technology	NOUN
ajst-20186	19	4	has	have	AUX
ajst-20186	19	5	been	be	AUX
ajst-20186	19	6	widely	widely	ADV
ajst-20186	19	7	applied	apply	VERB
ajst-20186	19	8	in	in	ADP
ajst-20186	19	9	various	various	ADJ
ajst-20186	19	10	fields	field	NOUN
ajst-20186	19	11	such	such	ADJ
ajst-20186	19	12	as	as	ADP
ajst-20186	19	13	nuclear	nuclear	ADJ
ajst-20186	19	14	waste	waste	NOUN
ajst-20186	19	15	management	management	NOUN
ajst-20186	19	16	,	,	PUNCT
ajst-20186	19	17	radiation	radiation	NOUN
ajst-20186	19	18	detection	detection	NOUN
ajst-20186	19	19	and	and	CCONJ
ajst-20186	19	20	analysis	analysis	NOUN
ajst-20186	19	21	,	,	PUNCT
ajst-20186	19	22	and	and	CCONJ
ajst-20186	19	23	nuclear	nuclear	ADJ
ajst-20186	19	24	reactor	reactor	NOUN
ajst-20186	19	25	monitoring	monitoring	NOUN
ajst-20186	19	26	.	.	PUNCT
ajst-20186	20	1	traditional	traditional	ADJ
ajst-20186	20	2	waveform	waveform	NOUN
ajst-20186	20	3	recognition	recognition	NOUN
ajst-20186	20	4	techniques	technique	NOUN
ajst-20186	20	5	rely	rely	VERB
ajst-20186	20	6	on	on	ADP
ajst-20186	20	7	comparing	compare	VERB
ajst-20186	20	8	waveform	waveform	NOUN
ajst-20186	20	9	peaks	peak	NOUN
ajst-20186	20	10	with	with	ADP
ajst-20186	20	11	predefined	predefine	VERB
ajst-20186	20	12	thresholds	threshold	NOUN
ajst-20186	20	13	for	for	ADP
ajst-20186	20	14	identification	identification	NOUN
ajst-20186	20	15	.	.	PUNCT
ajst-20186	21	1	due	due	ADP
ajst-20186	21	2	to	to	ADP
ajst-20186	21	3	its	its	PRON
ajst-20186	21	4	simplicity	simplicity	NOUN
ajst-20186	21	5	and	and	CCONJ
ajst-20186	21	6	ease	ease	NOUN
ajst-20186	21	7	of	of	ADP
ajst-20186	21	8	deployment	deployment	NOUN
ajst-20186	21	9	,	,	PUNCT
ajst-20186	21	10	traditional	traditional	ADJ
ajst-20186	21	11	waveform	waveform	NOUN
ajst-20186	21	12	recognition	recognition	NOUN
ajst-20186	21	13	plays	play	VERB
ajst-20186	21	14	an	an	DET
ajst-20186	21	15	irreplaceable	irreplaceable	ADJ
ajst-20186	21	16	role	role	NOUN
ajst-20186	21	17	in	in	ADP
ajst-20186	21	18	many	many	ADJ
ajst-20186	21	19	domains	domain	NOUN
ajst-20186	21	20	.	.	PUNCT
ajst-20186	22	1	however	however	ADV
ajst-20186	22	2	,	,	PUNCT
ajst-20186	22	3	it	it	PRON
ajst-20186	22	4	still	still	ADV
ajst-20186	22	5	has	have	VERB
ajst-20186	22	6	certain	certain	ADJ
ajst-20186	22	7	limitations	limitation	NOUN
ajst-20186	22	8	.	.	PUNCT
ajst-20186	23	1	this	this	DET
ajst-20186	23	2	paper	paper	NOUN
ajst-20186	23	3	proposes	propose	VERB
ajst-20186	23	4	the	the	DET
ajst-20186	23	5	use	use	NOUN
ajst-20186	23	6	of	of	ADP
ajst-20186	23	7	artificial	artificial	ADJ
ajst-20186	23	8	neural	neural	ADJ
ajst-20186	23	9	networks	network	NOUN
ajst-20186	23	10	for	for	ADP
ajst-20186	23	11	waveform	waveform	NOUN
ajst-20186	23	12	recognition	recognition	NOUN
ajst-20186	23	13	,	,	PUNCT
ajst-20186	23	14	employing	employ	VERB
ajst-20186	23	15	artificial	artificial	ADJ
ajst-20186	23	16	intelligence	intelligence	NOUN
ajst-20186	23	17	algorithms	algorithm	NOUN
ajst-20186	23	18	to	to	PART
ajst-20186	23	19	contrast	contrast	VERB
ajst-20186	23	20	with	with	ADP
ajst-20186	23	21	traditional	traditional	ADJ
ajst-20186	23	22	methods	method	NOUN
ajst-20186	23	23	.	.	PUNCT
ajst-20186	24	1	we	we	PRON
ajst-20186	24	2	focus	focus	VERB
ajst-20186	24	3	on	on	ADP
ajst-20186	24	4	the	the	DET
ajst-20186	24	5	recognition	recognition	NOUN
ajst-20186	24	6	of	of	ADP
ajst-20186	24	7	α	α	PROPN
ajst-20186	24	8	and	and	CCONJ
ajst-20186	24	9	β	β	NOUN
ajst-20186	24	10	radiation	radiation	NOUN
ajst-20186	24	11	in	in	ADP
ajst-20186	24	12	nuclear	nuclear	ADJ
ajst-20186	24	13	radiation	radiation	NOUN
ajst-20186	24	14	to	to	PART
ajst-20186	24	15	enhance	enhance	VERB
ajst-20186	24	16	identification	identification	NOUN
ajst-20186	24	17	accuracy	accuracy	NOUN
ajst-20186	24	18	.	.	PUNCT
ajst-20186	25	1	2	2	X
ajst-20186	25	2	.	.	X
ajst-20186	25	3	contribution	contribution	NOUN
ajst-20186	25	4	of	of	ADP
ajst-20186	25	5	this	this	DET
ajst-20186	25	6	study	study	NOUN
ajst-20186	25	7	the	the	DET
ajst-20186	25	8	dataset	dataset	NOUN
ajst-20186	25	9	of	of	ADP
ajst-20186	25	10	α	α	PROPN
ajst-20186	25	11	and	and	CCONJ
ajst-20186	25	12	β	β	X
ajst-20186	25	13	waveforms	waveform	NOUN
ajst-20186	25	14	used	use	VERB
ajst-20186	25	15	in	in	ADP
ajst-20186	25	16	this	this	DET
ajst-20186	25	17	paper	paper	NOUN
ajst-20186	25	18	is	be	AUX
ajst-20186	25	19	generated	generate	VERB
ajst-20186	25	20	from	from	ADP
ajst-20186	25	21	desensitized	desensitize	VERB
ajst-20186	25	22	radiation	radiation	NOUN
ajst-20186	25	23	sources	source	NOUN
ajst-20186	25	24	emitting	emit	VERB
ajst-20186	25	25	α	α	PROPN
ajst-20186	25	26	and	and	CCONJ
ajst-20186	25	27	β	β	PROPN
ajst-20186	25	28	rays	ray	NOUN
ajst-20186	25	29	,	,	PUNCT
ajst-20186	25	30	resulting	result	VERB
ajst-20186	25	31	in	in	ADP
ajst-20186	25	32	waveform	waveform	NOUN
ajst-20186	25	33	data	datum	NOUN
ajst-20186	25	34	of	of	ADP
ajst-20186	25	35	electrical	electrical	ADJ
ajst-20186	25	36	signals	signal	NOUN
ajst-20186	25	37	.	.	PUNCT
ajst-20186	26	1	currently	currently	ADV
ajst-20186	26	2	,	,	PUNCT
ajst-20186	26	3	it	it	PRON
ajst-20186	26	4	is	be	AUX
ajst-20186	26	5	difficult	difficult	ADJ
ajst-20186	26	6	to	to	PART
ajst-20186	26	7	find	find	VERB
ajst-20186	26	8	datasets	dataset	NOUN
ajst-20186	26	9	specifically	specifically	ADV
ajst-20186	26	10	related	relate	VERB
ajst-20186	26	11	to	to	ADP
ajst-20186	26	12	α	α	NOUN
ajst-20186	26	13	and	and	CCONJ
ajst-20186	26	14	β	β	X
ajst-20186	26	15	in	in	ADP
ajst-20186	26	16	existing	exist	VERB
ajst-20186	26	17	open	open	ADJ
ajst-20186	26	18	-	-	PUNCT
ajst-20186	26	19	source	source	NOUN
ajst-20186	26	20	repositories	repository	NOUN
ajst-20186	26	21	.	.	PUNCT
ajst-20186	27	1	the	the	DET
ajst-20186	27	2	dataset	dataset	NOUN
ajst-20186	27	3	we	we	PRON
ajst-20186	27	4	utilize	utilize	VERB
ajst-20186	27	5	will	will	AUX
ajst-20186	27	6	be	be	AUX
ajst-20186	27	7	made	make	VERB
ajst-20186	27	8	open	open	ADJ
ajst-20186	27	9	-	-	PUNCT
ajst-20186	27	10	source	source	NOUN
ajst-20186	27	11	for	for	SCONJ
ajst-20186	27	12	future	future	ADJ
ajst-20186	27	13	researchers	researcher	NOUN
ajst-20186	27	14	to	to	PART
ajst-20186	27	15	study	study	VERB
ajst-20186	27	16	.	.	PUNCT
ajst-20186	28	1	2.this	2.this	NUM
ajst-20186	28	2	study	study	NOUN
ajst-20186	28	3	is	be	AUX
ajst-20186	28	4	the	the	DET
ajst-20186	28	5	first	first	ADJ
ajst-20186	28	6	to	to	PART
ajst-20186	28	7	employ	employ	VERB
ajst-20186	28	8	artificial	artificial	ADJ
ajst-20186	28	9	intelligence	intelligence	NOUN
ajst-20186	28	10	methods	method	NOUN
ajst-20186	28	11	for	for	ADP
ajst-20186	28	12	the	the	DET
ajst-20186	28	13	recognition	recognition	NOUN
ajst-20186	28	14	of	of	ADP
ajst-20186	28	15	α	α	PROPN
ajst-20186	28	16	and	and	CCONJ
ajst-20186	28	17	β	β	NOUN
ajst-20186	28	18	waveforms	waveform	NOUN
ajst-20186	28	19	.	.	PUNCT
ajst-20186	29	1	this	this	DET
ajst-20186	29	2	innovative	innovative	ADJ
ajst-20186	29	3	approach	approach	NOUN
ajst-20186	29	4	aims	aim	VERB
ajst-20186	29	5	to	to	PART
ajst-20186	29	6	address	address	VERB
ajst-20186	29	7	the	the	DET
ajst-20186	29	8	limitations	limitation	NOUN
ajst-20186	29	9	of	of	ADP
ajst-20186	29	10	traditional	traditional	ADJ
ajst-20186	29	11	methods	method	NOUN
ajst-20186	29	12	by	by	ADP
ajst-20186	29	13	reducing	reduce	VERB
ajst-20186	29	14	the	the	DET
ajst-20186	29	15	possibility	possibility	NOUN
ajst-20186	29	16	of	of	ADP
ajst-20186	29	17	confusion	confusion	NOUN
ajst-20186	29	18	,	,	PUNCT
ajst-20186	29	19	thereby	thereby	ADV
ajst-20186	29	20	minimizing	minimize	VERB
ajst-20186	29	21	measurement	measurement	NOUN
ajst-20186	29	22	errors	error	NOUN
ajst-20186	29	23	.	.	PUNCT
ajst-20186	30	1	we	we	PRON
ajst-20186	30	2	will	will	AUX
ajst-20186	30	3	further	far	ADV
ajst-20186	30	4	elaborate	elaborate	VERB
ajst-20186	30	5	on	on	ADP
ajst-20186	30	6	this	this	PRON
ajst-20186	30	7	in	in	ADP
ajst-20186	30	8	subsequent	subsequent	ADJ
ajst-20186	30	9	articles	article	NOUN
ajst-20186	30	10	.	.	PUNCT
ajst-20186	31	1	3	3	X
ajst-20186	31	2	.	.	X
ajst-20186	31	3	traditional	traditional	ADJ
ajst-20186	31	4	methods	method	NOUN
ajst-20186	31	5	for	for	ADP
ajst-20186	31	6	the	the	DET
ajst-20186	31	7	identification	identification	NOUN
ajst-20186	31	8	of	of	ADP
ajst-20186	31	9	α	α	NOUN
ajst-20186	31	10	and	and	CCONJ
ajst-20186	31	11	β	β	X
ajst-20186	31	12	particles	particle	NOUN
ajst-20186	31	13	traditional	traditional	ADJ
ajst-20186	31	14	waveform	waveform	VERB
ajst-20186	31	15	identification	identification	NOUN
ajst-20186	31	16	methods	method	NOUN
ajst-20186	31	17	,	,	PUNCT
ajst-20186	31	18	such	such	ADJ
ajst-20186	31	19	as	as	ADP
ajst-20186	31	20	threshold	threshold	NOUN
ajst-20186	31	21	detection	detection	NOUN
ajst-20186	31	22	and	and	CCONJ
ajst-20186	31	23	peak	peak	NOUN
ajst-20186	31	24	analysis	analysis	NOUN
ajst-20186	31	25	,	,	PUNCT
ajst-20186	31	26	are	be	AUX
ajst-20186	31	27	still	still	ADV
ajst-20186	31	28	widely	widely	ADV
ajst-20186	31	29	employed	employ	VERB
ajst-20186	31	30	in	in	ADP
ajst-20186	31	31	industry	industry	NOUN
ajst-20186	31	32	and	and	CCONJ
ajst-20186	31	33	research	research	NOUN
ajst-20186	31	34	due	due	ADP
ajst-20186	31	35	to	to	ADP
ajst-20186	31	36	their	their	PRON
ajst-20186	31	37	simplicity	simplicity	NOUN
ajst-20186	31	38	and	and	CCONJ
ajst-20186	31	39	ease	ease	NOUN
ajst-20186	31	40	of	of	ADP
ajst-20186	31	41	implementation	implementation	NOUN
ajst-20186	31	42	.	.	PUNCT
ajst-20186	32	1	this	this	DET
ajst-20186	32	2	section	section	NOUN
ajst-20186	32	3	introduces	introduce	VERB
ajst-20186	32	4	these	these	DET
ajst-20186	32	5	traditional	traditional	ADJ
ajst-20186	32	6	methods	method	NOUN
ajst-20186	32	7	and	and	CCONJ
ajst-20186	32	8	assesses	assess	VERB
ajst-20186	32	9	their	their	PRON
ajst-20186	32	10	limitations	limitation	NOUN
ajst-20186	32	11	in	in	ADP
ajst-20186	32	12	modern	modern	ADJ
ajst-20186	32	13	applications	application	NOUN
ajst-20186	32	14	.	.	PUNCT
ajst-20186	33	1	x	x	NOUN
ajst-20186	33	2	-	-	NOUN
ajst-20186	33	3	rays	ray	NOUN
ajst-20186	33	4	emitted	emit	VERB
ajst-20186	33	5	by	by	ADP
ajst-20186	33	6	a	a	DET
ajst-20186	33	7	radioactive	radioactive	ADJ
ajst-20186	33	8	source	source	NOUN
ajst-20186	33	9	pass	pass	VERB
ajst-20186	33	10	through	through	ADP
ajst-20186	33	11	a	a	DET
ajst-20186	33	12	scintillation	scintillation	NOUN
ajst-20186	33	13	crystal	crystal	NOUN
ajst-20186	33	14	,	,	PUNCT
ajst-20186	33	15	undergo	undergo	VERB
ajst-20186	33	16	absorption	absorption	NOUN
ajst-20186	33	17	and	and	CCONJ
ajst-20186	33	18	convert	convert	NOUN
ajst-20186	33	19	to	to	ADP
ajst-20186	33	20	luminescence	luminescence	NOUN
ajst-20186	33	21	,	,	PUNCT
ajst-20186	33	22	then	then	ADV
ajst-20186	33	23	enter	enter	VERB
ajst-20186	33	24	a	a	DET
ajst-20186	33	25	photomultiplier	photomultiplier	NOUN
ajst-20186	33	26	tube	tube	NOUN
ajst-20186	33	27	.	.	PUNCT
ajst-20186	34	1	within	within	ADP
ajst-20186	34	2	the	the	DET
ajst-20186	34	3	photomultiplier	photomultiplier	NOUN
ajst-20186	34	4	tube	tube	NOUN
ajst-20186	34	5	,	,	PUNCT
ajst-20186	34	6	secondary	secondary	ADJ
ajst-20186	34	7	electron	electron	NOUN
ajst-20186	34	8	emission	emission	NOUN
ajst-20186	34	9	occurs	occur	VERB
ajst-20186	34	10	in	in	ADP
ajst-20186	34	11	stages	stage	NOUN
ajst-20186	34	12	,	,	PUNCT
ajst-20186	34	13	followed	follow	VERB
ajst-20186	34	14	by	by	ADP
ajst-20186	34	15	entering	enter	VERB
ajst-20186	34	16	signal	signal	ADJ
ajst-20186	34	17	processing	processing	NOUN
ajst-20186	34	18	circuits	circuit	NOUN
ajst-20186	34	19	,	,	PUNCT
ajst-20186	34	20	resulting	result	VERB
ajst-20186	34	21	in	in	ADP
ajst-20186	34	22	pulse	pulse	NOUN
ajst-20186	34	23	-	-	PUNCT
ajst-20186	34	24	form	form	NOUN
ajst-20186	34	25	output	output	NOUN
ajst-20186	34	26	signals	signal	NOUN
ajst-20186	34	27	.	.	PUNCT
ajst-20186	35	1	ultimately	ultimately	ADV
ajst-20186	35	2	,	,	PUNCT
ajst-20186	35	3	these	these	DET
ajst-20186	35	4	signals	signal	NOUN
ajst-20186	35	5	are	be	AUX
ajst-20186	35	6	collected	collect	VERB
ajst-20186	35	7	and	and	CCONJ
ajst-20186	35	8	converted	convert	VERB
ajst-20186	35	9	into	into	ADP
ajst-20186	35	10	discrete	discrete	ADJ
ajst-20186	35	11	signals	signal	NOUN
ajst-20186	35	12	through	through	ADP
ajst-20186	35	13	an	an	DET
ajst-20186	35	14	analog	analog	NOUN
ajst-20186	35	15	-	-	PUNCT
ajst-20186	35	16	to	to	ADP
ajst-20186	35	17	-	-	PUNCT
ajst-20186	35	18	digital	digital	ADJ
ajst-20186	35	19	converter	converter	NOUN
ajst-20186	35	20	(	(	PUNCT
ajst-20186	35	21	adc	adc	PROPN
ajst-20186	35	22	)	)	PUNCT
ajst-20186	35	23	.	.	PUNCT
ajst-20186	36	1	typically	typically	ADV
ajst-20186	36	2	,	,	PUNCT
ajst-20186	36	3	the	the	DET
ajst-20186	36	4	recognition	recognition	NOUN
ajst-20186	36	5	of	of	ADP
ajst-20186	36	6	α	α	PROPN
ajst-20186	36	7	and	and	CCONJ
ajst-20186	36	8	β	β	X
ajst-20186	36	9	particles	particle	NOUN
ajst-20186	36	10	is	be	AUX
ajst-20186	36	11	based	base	VERB
ajst-20186	36	12	on	on	ADP
ajst-20186	36	13	their	their	PRON
ajst-20186	36	14	different	different	ADJ
ajst-20186	36	15	bandwidths	bandwidth	NOUN
ajst-20186	36	16	and	and	CCONJ
ajst-20186	36	17	the	the	DET
ajst-20186	36	18	varying	vary	VERB
ajst-20186	36	19	number	number	NOUN
ajst-20186	36	20	of	of	ADP
ajst-20186	36	21	points	point	NOUN
ajst-20186	36	22	within	within	ADP
ajst-20186	36	23	their	their	PRON
ajst-20186	36	24	peak	peak	NOUN
ajst-20186	36	25	intervals	interval	NOUN
ajst-20186	36	26	.	.	PUNCT
ajst-20186	37	1	however	however	ADV
ajst-20186	37	2	,	,	PUNCT
ajst-20186	37	3	these	these	DET
ajst-20186	37	4	methods	method	NOUN
ajst-20186	37	5	have	have	VERB
ajst-20186	37	6	drawbacks	drawback	NOUN
ajst-20186	37	7	,	,	PUNCT
ajst-20186	37	8	as	as	SCONJ
ajst-20186	37	9	there	there	PRON
ajst-20186	37	10	is	be	VERB
ajst-20186	37	11	a	a	DET
ajst-20186	37	12	potential	potential	NOUN
ajst-20186	37	13	for	for	ADP
ajst-20186	37	14	confusion	confusion	NOUN
ajst-20186	37	15	.	.	PUNCT
ajst-20186	38	1	in	in	ADP
ajst-20186	38	2	scenarios	scenario	NOUN
ajst-20186	38	3	where	where	SCONJ
ajst-20186	38	4	β	β	X
ajst-20186	38	5	radioactivity	radioactivity	NOUN
ajst-20186	38	6	is	be	AUX
ajst-20186	38	7	high	high	ADJ
ajst-20186	38	8	,	,	PUNCT
ajst-20186	38	9	both	both	DET
ajst-20186	38	10	pulse	pulse	NOUN
ajst-20186	38	11	width	width	NOUN
ajst-20186	38	12	and	and	CCONJ
ajst-20186	38	13	amplitude	amplitude	NOUN
ajst-20186	38	14	increase	increase	NOUN
ajst-20186	38	15	,	,	PUNCT
ajst-20186	38	16	leading	lead	VERB
ajst-20186	38	17	to	to	ADP
ajst-20186	38	18	the	the	DET
ajst-20186	38	19	misidentification	misidentification	NOUN
ajst-20186	38	20	of	of	ADP
ajst-20186	38	21	α	α	NOUN
ajst-20186	38	22	as	as	ADP
ajst-20186	38	23	β	β	X
ajst-20186	38	24	.	.	PUNCT
ajst-20186	39	1	conversely	conversely	ADV
ajst-20186	39	2	,	,	PUNCT
ajst-20186	39	3	if	if	SCONJ
ajst-20186	39	4	α	α	NOUN
ajst-20186	39	5	62	62	NUM
ajst-20186	39	6	radioactivity	radioactivity	NOUN
ajst-20186	39	7	is	be	AUX
ajst-20186	39	8	high	high	ADJ
ajst-20186	39	9	,	,	PUNCT
ajst-20186	39	10	both	both	DET
ajst-20186	39	11	pulse	pulse	NOUN
ajst-20186	39	12	width	width	NOUN
ajst-20186	39	13	and	and	CCONJ
ajst-20186	39	14	amplitude	amplitude	NOUN
ajst-20186	39	15	decrease	decrease	NOUN
ajst-20186	39	16	,	,	PUNCT
ajst-20186	39	17	causing	cause	VERB
ajst-20186	39	18	misidentification	misidentification	NOUN
ajst-20186	39	19	of	of	ADP
ajst-20186	39	20	β	β	PROPN
ajst-20186	39	21	as	as	ADP
ajst-20186	39	22	α	α	X
ajst-20186	39	23	.	.	PUNCT
ajst-20186	40	1	with	with	ADP
ajst-20186	40	2	increasing	increase	VERB
ajst-20186	40	3	measurement	measurement	NOUN
ajst-20186	40	4	requirements	requirement	NOUN
ajst-20186	40	5	,	,	PUNCT
ajst-20186	40	6	there	there	PRON
ajst-20186	40	7	are	be	VERB
ajst-20186	40	8	demands	demand	NOUN
ajst-20186	40	9	for	for	ADP
ajst-20186	40	10	the	the	DET
ajst-20186	40	11	α	α	PROPN
ajst-20186	40	12	channel	channel	NOUN
ajst-20186	40	13	ratio	ratio	NOUN
ajst-20186	40	14	and	and	CCONJ
ajst-20186	40	15	β	β	NOUN
ajst-20186	40	16	channel	channel	NOUN
ajst-20186	40	17	ratio	ratio	NOUN
ajst-20186	40	18	of	of	ADP
ajst-20186	40	19	the	the	DET
ajst-20186	40	20	equipment	equipment	NOUN
ajst-20186	40	21	,	,	PUNCT
ajst-20186	40	22	especially	especially	ADV
ajst-20186	40	23	when	when	SCONJ
ajst-20186	40	24	the	the	DET
ajst-20186	40	25	radioactive	radioactive	ADJ
ajst-20186	40	26	source	source	NOUN
ajst-20186	40	27	activity	activity	NOUN
ajst-20186	40	28	is	be	AUX
ajst-20186	40	29	high	high	ADJ
ajst-20186	40	30	,	,	PUNCT
ajst-20186	40	31	resulting	result	VERB
ajst-20186	40	32	in	in	ADP
ajst-20186	40	33	a	a	DET
ajst-20186	40	34	sharp	sharp	ADJ
ajst-20186	40	35	increase	increase	NOUN
ajst-20186	40	36	in	in	ADP
ajst-20186	40	37	the	the	DET
ajst-20186	40	38	β	β	PROPN
ajst-20186	40	39	channel	channel	NOUN
ajst-20186	40	40	ratio	ratio	NOUN
ajst-20186	40	41	,	,	PUNCT
ajst-20186	40	42	making	make	VERB
ajst-20186	40	43	it	it	PRON
ajst-20186	40	44	challenging	challenge	VERB
ajst-20186	40	45	to	to	PART
ajst-20186	40	46	meet	meet	VERB
ajst-20186	40	47	measurement	measurement	NOUN
ajst-20186	40	48	requirements	requirement	NOUN
ajst-20186	40	49	.	.	PUNCT
ajst-20186	41	1	neural	neural	ADJ
ajst-20186	41	2	network	network	NOUN
ajst-20186	41	3	models	model	NOUN
ajst-20186	41	4	,	,	PUNCT
ajst-20186	41	5	with	with	ADP
ajst-20186	41	6	their	their	PRON
ajst-20186	41	7	strong	strong	ADJ
ajst-20186	41	8	generalization	generalization	NOUN
ajst-20186	41	9	and	and	CCONJ
ajst-20186	41	10	robustness	robustness	NOUN
ajst-20186	41	11	,	,	PUNCT
ajst-20186	41	12	can	can	AUX
ajst-20186	41	13	partially	partially	ADV
ajst-20186	41	14	overcome	overcome	VERB
ajst-20186	41	15	these	these	DET
ajst-20186	41	16	limitations	limitation	NOUN
ajst-20186	41	17	and	and	CCONJ
ajst-20186	41	18	facilitate	facilitate	VERB
ajst-20186	41	19	rapid	rapid	ADJ
ajst-20186	41	20	identification	identification	NOUN
ajst-20186	41	21	.	.	PUNCT
ajst-20186	42	1	in	in	ADP
ajst-20186	42	2	traditional	traditional	ADJ
ajst-20186	42	3	waveform	waveform	NOUN
ajst-20186	42	4	analysis	analysis	NOUN
ajst-20186	42	5	,	,	PUNCT
ajst-20186	42	6	threshold	threshold	NOUN
ajst-20186	42	7	detection	detection	NOUN
ajst-20186	42	8	is	be	AUX
ajst-20186	42	9	a	a	DET
ajst-20186	42	10	common	common	ADJ
ajst-20186	42	11	signal	signal	NOUN
ajst-20186	42	12	processing	processing	NOUN
ajst-20186	42	13	technique	technique	NOUN
ajst-20186	42	14	.	.	PUNCT
ajst-20186	43	1	it	it	PRON
ajst-20186	43	2	identifies	identify	VERB
ajst-20186	43	3	critical	critical	ADJ
ajst-20186	43	4	waveform	waveform	NOUN
ajst-20186	43	5	features	feature	NOUN
ajst-20186	43	6	by	by	ADP
ajst-20186	43	7	setting	set	VERB
ajst-20186	43	8	a	a	DET
ajst-20186	43	9	fixed	fix	VERB
ajst-20186	43	10	signal	signal	NOUN
ajst-20186	43	11	threshold	threshold	NOUN
ajst-20186	43	12	.	.	PUNCT
ajst-20186	44	1	for	for	ADP
ajst-20186	44	2	instance	instance	NOUN
ajst-20186	44	3	,	,	PUNCT
ajst-20186	44	4	to	to	PART
ajst-20186	44	5	identify	identify	VERB
ajst-20186	44	6	α	α	PRON
ajst-20186	44	7	waveforms	waveform	NOUN
ajst-20186	44	8	,	,	PUNCT
ajst-20186	44	9	a	a	DET
ajst-20186	44	10	threshold	threshold	NOUN
ajst-20186	44	11	is	be	AUX
ajst-20186	44	12	set	set	VERB
ajst-20186	44	13	so	so	SCONJ
ajst-20186	44	14	that	that	SCONJ
ajst-20186	44	15	only	only	ADJ
ajst-20186	44	16	signals	signal	NOUN
ajst-20186	44	17	with	with	ADP
ajst-20186	44	18	peaks	peak	NOUN
ajst-20186	44	19	exceeding	exceed	VERB
ajst-20186	44	20	this	this	DET
ajst-20186	44	21	threshold	threshold	NOUN
ajst-20186	44	22	are	be	AUX
ajst-20186	44	23	considered	consider	VERB
ajst-20186	44	24	valid	valid	ADJ
ajst-20186	44	25	waveforms	waveform	NOUN
ajst-20186	44	26	.	.	PUNCT
ajst-20186	45	1	the	the	DET
ajst-20186	45	2	main	main	ADJ
ajst-20186	45	3	advantages	advantage	NOUN
ajst-20186	45	4	of	of	ADP
ajst-20186	45	5	this	this	DET
ajst-20186	45	6	method	method	NOUN
ajst-20186	45	7	lie	lie	NOUN
ajst-20186	45	8	in	in	ADP
ajst-20186	45	9	its	its	PRON
ajst-20186	45	10	simplicity	simplicity	NOUN
ajst-20186	45	11	and	and	CCONJ
ajst-20186	45	12	low	low	ADJ
ajst-20186	45	13	computational	computational	ADJ
ajst-20186	45	14	resource	resource	NOUN
ajst-20186	45	15	requirements	requirement	NOUN
ajst-20186	45	16	,	,	PUNCT
ajst-20186	45	17	making	make	VERB
ajst-20186	45	18	it	it	PRON
ajst-20186	45	19	suitable	suitable	ADJ
ajst-20186	45	20	for	for	ADP
ajst-20186	45	21	environments	environment	NOUN
ajst-20186	45	22	with	with	ADP
ajst-20186	45	23	limited	limited	ADJ
ajst-20186	45	24	hardware	hardware	NOUN
ajst-20186	45	25	constraints	constraint	NOUN
ajst-20186	45	26	.	.	PUNCT
ajst-20186	46	1	traditional	traditional	ADJ
ajst-20186	46	2	methods	method	NOUN
ajst-20186	46	3	,	,	PUNCT
ajst-20186	46	4	due	due	ADP
ajst-20186	46	5	to	to	ADP
ajst-20186	46	6	their	their	PRON
ajst-20186	46	7	straightforward	straightforward	ADJ
ajst-20186	46	8	algorithms	algorithm	NOUN
ajst-20186	46	9	,	,	PUNCT
ajst-20186	46	10	ease	ease	NOUN
ajst-20186	46	11	of	of	ADP
ajst-20186	46	12	implementation	implementation	NOUN
ajst-20186	46	13	,	,	PUNCT
ajst-20186	46	14	and	and	CCONJ
ajst-20186	46	15	deployment	deployment	NOUN
ajst-20186	46	16	,	,	PUNCT
ajst-20186	46	17	are	be	AUX
ajst-20186	46	18	particularly	particularly	ADV
ajst-20186	46	19	effective	effective	ADJ
ajst-20186	46	20	in	in	ADP
ajst-20186	46	21	resource	resource	NOUN
ajst-20186	46	22	-	-	PUNCT
ajst-20186	46	23	constrained	constrain	VERB
ajst-20186	46	24	settings	setting	NOUN
ajst-20186	46	25	.	.	PUNCT
ajst-20186	47	1	moreover	moreover	ADV
ajst-20186	47	2	,	,	PUNCT
ajst-20186	47	3	these	these	DET
ajst-20186	47	4	methods	method	NOUN
ajst-20186	47	5	usually	usually	ADV
ajst-20186	47	6	do	do	AUX
ajst-20186	47	7	not	not	PART
ajst-20186	47	8	require	require	VERB
ajst-20186	47	9	complex	complex	ADJ
ajst-20186	47	10	training	training	NOUN
ajst-20186	47	11	processes	process	NOUN
ajst-20186	47	12	and	and	CCONJ
ajst-20186	47	13	can	can	AUX
ajst-20186	47	14	quickly	quickly	ADV
ajst-20186	47	15	adapt	adapt	VERB
ajst-20186	47	16	to	to	ADP
ajst-20186	47	17	new	new	ADJ
ajst-20186	47	18	application	application	NOUN
ajst-20186	47	19	scenarios	scenario	NOUN
ajst-20186	47	20	.	.	PUNCT
ajst-20186	48	1	in	in	ADP
ajst-20186	48	2	fields	field	NOUN
ajst-20186	48	3	such	such	ADJ
ajst-20186	48	4	as	as	ADP
ajst-20186	48	5	seismic	seismic	ADJ
ajst-20186	48	6	signal	signal	NOUN
ajst-20186	48	7	monitoring	monitoring	NOUN
ajst-20186	48	8	or	or	CCONJ
ajst-20186	48	9	straightforward	straightforward	ADJ
ajst-20186	48	10	mechanical	mechanical	ADJ
ajst-20186	48	11	fault	fault	NOUN
ajst-20186	48	12	diagnosis	diagnosis	NOUN
ajst-20186	48	13	,	,	PUNCT
ajst-20186	48	14	traditional	traditional	ADJ
ajst-20186	48	15	methods	method	NOUN
ajst-20186	48	16	have	have	AUX
ajst-20186	48	17	been	be	AUX
ajst-20186	48	18	successfully	successfully	ADV
ajst-20186	48	19	applied	apply	VERB
ajst-20186	48	20	for	for	ADP
ajst-20186	48	21	many	many	ADJ
ajst-20186	48	22	years	year	NOUN
ajst-20186	48	23	,	,	PUNCT
ajst-20186	48	24	offering	offer	VERB
ajst-20186	48	25	stable	stable	ADJ
ajst-20186	48	26	and	and	CCONJ
ajst-20186	48	27	reliable	reliable	ADJ
ajst-20186	48	28	performance[5	performance[5	PROPN
ajst-20186	48	29	-	-	SYM
ajst-20186	48	30	6	6	NUM
ajst-20186	48	31	]	]	PUNCT
ajst-20186	48	32	.	.	PUNCT
ajst-20186	49	1	however	however	ADV
ajst-20186	49	2	,	,	PUNCT
ajst-20186	49	3	these	these	DET
ajst-20186	49	4	methods	method	NOUN
ajst-20186	49	5	perform	perform	VERB
ajst-20186	49	6	poorly	poorly	ADV
ajst-20186	49	7	when	when	SCONJ
ajst-20186	49	8	dealing	deal	VERB
ajst-20186	49	9	with	with	ADP
ajst-20186	49	10	complex	complex	ADJ
ajst-20186	49	11	or	or	CCONJ
ajst-20186	49	12	noise	noise	NOUN
ajst-20186	49	13	-	-	PUNCT
ajst-20186	49	14	intensive	intensive	ADJ
ajst-20186	49	15	signals	signal	NOUN
ajst-20186	49	16	.	.	PUNCT
ajst-20186	50	1	they	they	PRON
ajst-20186	50	2	often	often	ADV
ajst-20186	50	3	struggle	struggle	VERB
ajst-20186	50	4	to	to	PART
ajst-20186	50	5	adapt	adapt	VERB
ajst-20186	50	6	to	to	ADP
ajst-20186	50	7	subtle	subtle	ADJ
ajst-20186	50	8	waveform	waveform	NOUN
ajst-20186	50	9	variations	variation	NOUN
ajst-20186	50	10	and	and	CCONJ
ajst-20186	50	11	have	have	VERB
ajst-20186	50	12	limited	limit	VERB
ajst-20186	50	13	accuracy	accuracy	NOUN
ajst-20186	50	14	when	when	SCONJ
ajst-20186	50	15	classifying	classify	VERB
ajst-20186	50	16	diverse	diverse	ADJ
ajst-20186	50	17	waveforms	waveform	NOUN
ajst-20186	50	18	.	.	PUNCT
ajst-20186	51	1	additionally	additionally	ADV
ajst-20186	51	2	,	,	PUNCT
ajst-20186	51	3	threshold	threshold	NOUN
ajst-20186	51	4	setting	setting	NOUN
ajst-20186	51	5	usually	usually	ADV
ajst-20186	51	6	requires	require	VERB
ajst-20186	51	7	manual	manual	ADJ
ajst-20186	51	8	adjustment	adjustment	NOUN
ajst-20186	51	9	based	base	VERB
ajst-20186	51	10	on	on	ADP
ajst-20186	51	11	experience	experience	NOUN
ajst-20186	51	12	,	,	PUNCT
ajst-20186	51	13	limiting	limit	VERB
ajst-20186	51	14	its	its	PRON
ajst-20186	51	15	adaptability	adaptability	NOUN
ajst-20186	51	16	and	and	CCONJ
ajst-20186	51	17	flexibility	flexibility	NOUN
ajst-20186	51	18	.	.	PUNCT
ajst-20186	52	1	in	in	ADP
ajst-20186	52	2	contrast	contrast	NOUN
ajst-20186	52	3	,	,	PUNCT
ajst-20186	52	4	artificial	artificial	ADJ
ajst-20186	52	5	intelligence	intelligence	NOUN
ajst-20186	52	6	methods	method	NOUN
ajst-20186	52	7	,	,	PUNCT
ajst-20186	52	8	especially	especially	ADV
ajst-20186	52	9	those	those	PRON
ajst-20186	52	10	based	base	VERB
ajst-20186	52	11	on	on	ADP
ajst-20186	52	12	deep	deep	ADJ
ajst-20186	52	13	learning	learning	NOUN
ajst-20186	52	14	models	model	NOUN
ajst-20186	52	15	,	,	PUNCT
ajst-20186	52	16	provide	provide	VERB
ajst-20186	52	17	higher	high	ADJ
ajst-20186	52	18	accuracy	accuracy	NOUN
ajst-20186	52	19	and	and	CCONJ
ajst-20186	52	20	the	the	DET
ajst-20186	52	21	ability	ability	NOUN
ajst-20186	52	22	to	to	PART
ajst-20186	52	23	recognize	recognize	VERB
ajst-20186	52	24	complex	complex	ADJ
ajst-20186	52	25	patterns	pattern	NOUN
ajst-20186	52	26	.	.	PUNCT
ajst-20186	53	1	although	although	SCONJ
ajst-20186	53	2	these	these	DET
ajst-20186	53	3	models	model	NOUN
ajst-20186	53	4	incur	incur	VERB
ajst-20186	53	5	higher	high	ADJ
ajst-20186	53	6	computational	computational	ADJ
ajst-20186	53	7	costs	cost	NOUN
ajst-20186	53	8	,	,	PUNCT
ajst-20186	53	9	their	their	PRON
ajst-20186	53	10	adaptability	adaptability	NOUN
ajst-20186	53	11	and	and	CCONJ
ajst-20186	53	12	learning	learn	VERB
ajst-20186	53	13	capabilities	capability	NOUN
ajst-20186	53	14	from	from	ADP
ajst-20186	53	15	data	datum	NOUN
ajst-20186	53	16	make	make	VERB
ajst-20186	53	17	them	they	PRON
ajst-20186	53	18	excel	excel	VERB
ajst-20186	53	19	in	in	ADP
ajst-20186	53	20	handling	handle	VERB
ajst-20186	53	21	variable	variable	ADJ
ajst-20186	53	22	and	and	CCONJ
ajst-20186	53	23	nonlinear	nonlinear	ADJ
ajst-20186	53	24	waveforms	waveform	NOUN
ajst-20186	53	25	,	,	PUNCT
ajst-20186	53	26	outperforming	outperform	VERB
ajst-20186	53	27	traditional	traditional	ADJ
ajst-20186	53	28	methods	method	NOUN
ajst-20186	53	29	in	in	ADP
ajst-20186	53	30	scenarios	scenario	NOUN
ajst-20186	53	31	with	with	ADP
ajst-20186	53	32	high	high	ADJ
ajst-20186	53	33	waveform	waveform	NOUN
ajst-20186	53	34	diversity	diversity	NOUN
ajst-20186	53	35	and	and	CCONJ
ajst-20186	53	36	potential	potential	ADJ
ajst-20186	53	37	confusion	confusion	NOUN
ajst-20186	53	38	.	.	PUNCT
ajst-20186	54	1	4	4	X
ajst-20186	54	2	.	.	PUNCT
ajst-20186	54	3	based	base	VERB
ajst-20186	54	4	on	on	ADP
ajst-20186	54	5	artificial	artificial	ADJ
ajst-20186	54	6	neural	neural	ADJ
ajst-20186	54	7	networks	network	NOUN
ajst-20186	54	8	for	for	ADP
ajst-20186	54	9	the	the	DET
ajst-20186	54	10	identification	identification	NOUN
ajst-20186	54	11	of	of	ADP
ajst-20186	54	12	α	α	NOUN
ajst-20186	54	13	and	and	CCONJ
ajst-20186	54	14	β	β	X
ajst-20186	54	15	4.1	4.1	NUM
ajst-20186	54	16	.	.	PUNCT
ajst-20186	55	1	dataset	dataset	VERB
ajst-20186	55	2	in	in	ADP
ajst-20186	55	3	the	the	DET
ajst-20186	55	4	context	context	NOUN
ajst-20186	55	5	of	of	ADP
ajst-20186	55	6	waveform	waveform	NOUN
ajst-20186	55	7	recognition	recognition	NOUN
ajst-20186	55	8	using	use	VERB
ajst-20186	55	9	artificial	artificial	ADJ
ajst-20186	55	10	neural	neural	ADJ
ajst-20186	55	11	networks	network	NOUN
ajst-20186	55	12	,	,	PUNCT
ajst-20186	55	13	preprocessing	preprocessing	NOUN
ajst-20186	55	14	of	of	ADP
ajst-20186	55	15	α	α	PROPN
ajst-20186	55	16	and	and	CCONJ
ajst-20186	55	17	β	β	PROPN
ajst-20186	55	18	data	data	NOUN
ajst-20186	55	19	is	be	AUX
ajst-20186	55	20	necessary	necessary	ADJ
ajst-20186	55	21	to	to	PART
ajst-20186	55	22	ensure	ensure	VERB
ajst-20186	55	23	that	that	SCONJ
ajst-20186	55	24	they	they	PRON
ajst-20186	55	25	are	be	AUX
ajst-20186	55	26	input	input	NOUN
ajst-20186	55	27	as	as	ADP
ajst-20186	55	28	data	datum	NOUN
ajst-20186	55	29	of	of	ADP
ajst-20186	55	30	equal	equal	ADJ
ajst-20186	55	31	length	length	NOUN
ajst-20186	55	32	.	.	PUNCT
ajst-20186	56	1	the	the	DET
ajst-20186	56	2	data	datum	NOUN
ajst-20186	56	3	used	use	VERB
ajst-20186	56	4	for	for	ADP
ajst-20186	56	5	training	train	VERB
ajst-20186	56	6	the	the	DET
ajst-20186	56	7	model	model	NOUN
ajst-20186	56	8	are	be	AUX
ajst-20186	56	9	obtained	obtain	VERB
ajst-20186	56	10	from	from	ADP
ajst-20186	56	11	collected	collect	VERB
ajst-20186	56	12	α	α	PROPN
ajst-20186	56	13	and	and	CCONJ
ajst-20186	56	14	β	β	X
ajst-20186	56	15	data	datum	NOUN
ajst-20186	56	16	from	from	ADP
ajst-20186	56	17	radioactive	radioactive	ADJ
ajst-20186	56	18	nuclide	nuclide	ADJ
ajst-20186	56	19	sources	source	NOUN
ajst-20186	56	20	,	,	PUNCT
ajst-20186	56	21	extracted	extract	VERB
ajst-20186	56	22	using	use	VERB
ajst-20186	56	23	an	an	DET
ajst-20186	56	24	oscilloscope	oscilloscope	NOUN
ajst-20186	56	25	.	.	PUNCT
ajst-20186	57	1	the	the	DET
ajst-20186	57	2	following	following	NOUN
ajst-20186	57	3	indicates	indicate	VERB
ajst-20186	57	4	the	the	DET
ajst-20186	57	5	quantity	quantity	NOUN
ajst-20186	57	6	of	of	ADP
ajst-20186	57	7	data	datum	NOUN
ajst-20186	57	8	:	:	PUNCT
ajst-20186	57	9	table	table	NOUN
ajst-20186	57	10	1	1	NUM
ajst-20186	57	11	.	.	PUNCT
ajst-20186	57	12	information	information	NOUN
ajst-20186	57	13	of	of	ADP
ajst-20186	57	14	datasets	dataset	NOUN
ajst-20186	57	15	datasets	dataset	VERB
ajst-20186	57	16	α	α	X
ajst-20186	57	17	training_set	training_set	NUM
ajst-20186	57	18	β	β	X
ajst-20186	57	19	training_set	training_set	NUM
ajst-20186	57	20	α	α	PROPN
ajst-20186	57	21	testing_set	testing_set	NOUN
ajst-20186	57	22	βtesting_set	βtesting_set	X
ajst-20186	58	1	training_set	training_set	NUM
ajst-20186	58	2	testing_set	testing_set	VERB
ajst-20186	58	3	quantity	quantity	NOUN
ajst-20186	58	4	796	796	NUM
ajst-20186	58	5	1720	1720	NUM
ajst-20186	58	6	250	250	NUM
ajst-20186	58	7	250	250	NUM
ajst-20186	58	8	2516	2516	NUM
ajst-20186	58	9	500	500	NUM
ajst-20186	58	10	since	since	SCONJ
ajst-20186	58	11	our	our	PRON
ajst-20186	58	12	model	model	NOUN
ajst-20186	58	13	requires	require	VERB
ajst-20186	58	14	fixed	fix	VERB
ajst-20186	58	15	-	-	PUNCT
ajst-20186	58	16	length	length	NOUN
ajst-20186	58	17	sequential	sequential	ADJ
ajst-20186	58	18	data	datum	NOUN
ajst-20186	58	19	,	,	PUNCT
ajst-20186	58	20	and	and	CCONJ
ajst-20186	58	21	the	the	DET
ajst-20186	58	22	features	feature	NOUN
ajst-20186	58	23	of	of	ADP
ajst-20186	58	24	the	the	DET
ajst-20186	58	25	data	datum	NOUN
ajst-20186	58	26	mainly	mainly	ADV
ajst-20186	58	27	reside	reside	VERB
ajst-20186	58	28	in	in	ADP
ajst-20186	58	29	the	the	DET
ajst-20186	58	30	characteristic	characteristic	ADJ
ajst-20186	58	31	peaks	peak	NOUN
ajst-20186	58	32	of	of	ADP
ajst-20186	58	33	the	the	DET
ajst-20186	58	34	sequence	sequence	NOUN
ajst-20186	58	35	,	,	PUNCT
ajst-20186	58	36	but	but	CCONJ
ajst-20186	58	37	due	due	ADP
ajst-20186	58	38	to	to	ADP
ajst-20186	58	39	the	the	DET
ajst-20186	58	40	varying	vary	VERB
ajst-20186	58	41	bandwidths	bandwidth	NOUN
ajst-20186	58	42	of	of	ADP
ajst-20186	58	43	these	these	DET
ajst-20186	58	44	peaks	peak	NOUN
ajst-20186	58	45	,	,	PUNCT
ajst-20186	58	46	the	the	DET
ajst-20186	58	47	length	length	NOUN
ajst-20186	58	48	of	of	ADP
ajst-20186	58	49	α	α	PROPN
ajst-20186	58	50	characteristic	characteristic	ADJ
ajst-20186	58	51	peaks	peak	NOUN
ajst-20186	58	52	falls	fall	VERB
ajst-20186	58	53	within	within	ADP
ajst-20186	58	54	the	the	DET
ajst-20186	58	55	range	range	NOUN
ajst-20186	58	56	of	of	ADP
ajst-20186	58	57	50	50	NUM
ajst-20186	58	58	-	-	SYM
ajst-20186	58	59	55	55	NUM
ajst-20186	58	60	,	,	PUNCT
ajst-20186	58	61	while	while	SCONJ
ajst-20186	58	62	the	the	DET
ajst-20186	58	63	length	length	NOUN
ajst-20186	58	64	of	of	ADP
ajst-20186	58	65	β	β	X
ajst-20186	58	66	characteristic	characteristic	ADJ
ajst-20186	58	67	peaks	peak	NOUN
ajst-20186	58	68	falls	fall	VERB
ajst-20186	58	69	within	within	ADP
ajst-20186	58	70	the	the	DET
ajst-20186	58	71	range	range	NOUN
ajst-20186	58	72	of	of	ADP
ajst-20186	58	73	30	30	NUM
ajst-20186	58	74	-	-	SYM
ajst-20186	58	75	35	35	NUM
ajst-20186	58	76	.	.	PUNCT
ajst-20186	59	1	therefore	therefore	ADV
ajst-20186	59	2	,	,	PUNCT
ajst-20186	59	3	we	we	PRON
ajst-20186	59	4	employ	employ	VERB
ajst-20186	59	5	a	a	DET
ajst-20186	59	6	fixed	fix	VERB
ajst-20186	59	7	length	length	NOUN
ajst-20186	59	8	of	of	ADP
ajst-20186	59	9	40	40	NUM
ajst-20186	59	10	data	datum	NOUN
ajst-20186	59	11	points	point	NOUN
ajst-20186	59	12	.	.	PUNCT
ajst-20186	60	1	for	for	ADP
ajst-20186	60	2	α	α	DET
ajst-20186	60	3	data	datum	NOUN
ajst-20186	60	4	,	,	PUNCT
ajst-20186	60	5	we	we	PRON
ajst-20186	60	6	trim	trim	VERB
ajst-20186	60	7	the	the	DET
ajst-20186	60	8	tail	tail	NOUN
ajst-20186	60	9	,	,	PUNCT
ajst-20186	60	10	while	while	SCONJ
ajst-20186	60	11	for	for	ADP
ajst-20186	60	12	β	β	PROPN
ajst-20186	60	13	data	datum	NOUN
ajst-20186	60	14	,	,	PUNCT
ajst-20186	60	15	we	we	PRON
ajst-20186	60	16	stretch	stretch	VERB
ajst-20186	60	17	the	the	DET
ajst-20186	60	18	tail	tail	NOUN
ajst-20186	60	19	,	,	PUNCT
ajst-20186	60	20	as	as	SCONJ
ajst-20186	60	21	illustrated	illustrate	VERB
ajst-20186	60	22	in	in	ADP
ajst-20186	60	23	the	the	DET
ajst-20186	60	24	following	follow	VERB
ajst-20186	60	25	figure	figure	NOUN
ajst-20186	60	26	:	:	PUNCT
ajst-20186	60	27	figure	figure	NOUN
ajst-20186	60	28	1	1	NUM
ajst-20186	60	29	.	.	PUNCT
ajst-20186	61	1	datasets	dataset	NOUN
ajst-20186	61	2	sample	sample	VERB
ajst-20186	61	3	63	63	NUM
ajst-20186	61	4	4.2	4.2	NUM
ajst-20186	61	5	.	.	PUNCT
ajst-20186	62	1	cnn	cnn	PROPN
ajst-20186	62	2	model	model	NOUN
ajst-20186	62	3	based	base	VERB
ajst-20186	62	4	on	on	ADP
ajst-20186	62	5	our	our	PRON
ajst-20186	62	6	dataset	dataset	NOUN
ajst-20186	62	7	,	,	PUNCT
ajst-20186	62	8	we	we	PRON
ajst-20186	62	9	constructed	construct	VERB
ajst-20186	62	10	a	a	DET
ajst-20186	62	11	convolutional	convolutional	ADJ
ajst-20186	62	12	neural	neural	ADJ
ajst-20186	62	13	network	network	NOUN
ajst-20186	62	14	(	(	PUNCT
ajst-20186	62	15	cnn	cnn	PROPN
ajst-20186	62	16	)	)	PUNCT
ajst-20186	62	17	model	model	NOUN
ajst-20186	62	18	.	.	PUNCT
ajst-20186	63	1	this	this	DET
ajst-20186	63	2	model	model	NOUN
ajst-20186	63	3	employs	employ	VERB
ajst-20186	63	4	a	a	DET
ajst-20186	63	5	series	series	NOUN
ajst-20186	63	6	of	of	ADP
ajst-20186	63	7	convolutional	convolutional	ADJ
ajst-20186	63	8	layers	layer	NOUN
ajst-20186	63	9	to	to	PART
ajst-20186	63	10	learn	learn	VERB
ajst-20186	63	11	hierarchical	hierarchical	ADJ
ajst-20186	63	12	features	feature	NOUN
ajst-20186	63	13	from	from	ADP
ajst-20186	63	14	the	the	DET
ajst-20186	63	15	data	datum	NOUN
ajst-20186	63	16	.	.	PUNCT
ajst-20186	64	1	each	each	DET
ajst-20186	64	2	convolutional	convolutional	ADJ
ajst-20186	64	3	layer	layer	NOUN
ajst-20186	64	4	utilizes	utilize	VERB
ajst-20186	64	5	a	a	DET
ajst-20186	64	6	set	set	NOUN
ajst-20186	64	7	of	of	ADP
ajst-20186	64	8	filters	filter	NOUN
ajst-20186	64	9	to	to	PART
ajst-20186	64	10	extract	extract	VERB
ajst-20186	64	11	essential	essential	ADJ
ajst-20186	64	12	features	feature	NOUN
ajst-20186	64	13	from	from	ADP
ajst-20186	64	14	the	the	DET
ajst-20186	64	15	input	input	NOUN
ajst-20186	64	16	data	datum	NOUN
ajst-20186	64	17	.	.	PUNCT
ajst-20186	65	1	subsequently	subsequently	ADV
ajst-20186	65	2	,	,	PUNCT
ajst-20186	65	3	nonlinearity	nonlinearity	NOUN
ajst-20186	65	4	is	be	AUX
ajst-20186	65	5	introduced	introduce	VERB
ajst-20186	65	6	through	through	ADP
ajst-20186	65	7	activation	activation	NOUN
ajst-20186	65	8	functions	function	NOUN
ajst-20186	65	9	,	,	PUNCT
ajst-20186	65	10	and	and	CCONJ
ajst-20186	65	11	downsampling	downsampling	NOUN
ajst-20186	65	12	is	be	AUX
ajst-20186	65	13	achieved	achieve	VERB
ajst-20186	65	14	via	via	ADP
ajst-20186	65	15	pooling	pool	VERB
ajst-20186	65	16	layers	layer	NOUN
ajst-20186	65	17	to	to	PART
ajst-20186	65	18	reduce	reduce	VERB
ajst-20186	65	19	feature	feature	NOUN
ajst-20186	65	20	dimensions	dimension	NOUN
ajst-20186	65	21	,	,	PUNCT
ajst-20186	65	22	thereby	thereby	ADV
ajst-20186	65	23	enhancing	enhance	VERB
ajst-20186	65	24	the	the	DET
ajst-20186	65	25	model	model	NOUN
ajst-20186	65	26	's	's	PART
ajst-20186	65	27	abstraction	abstraction	ADJ
ajst-20186	65	28	capabilities	capability	NOUN
ajst-20186	65	29	and	and	CCONJ
ajst-20186	65	30	computational	computational	ADJ
ajst-20186	65	31	efficiency	efficiency	NOUN
ajst-20186	65	32	.	.	PUNCT
ajst-20186	66	1	following	follow	VERB
ajst-20186	66	2	these	these	DET
ajst-20186	66	3	convolutional	convolutional	ADJ
ajst-20186	66	4	layers	layer	NOUN
ajst-20186	66	5	,	,	PUNCT
ajst-20186	66	6	a	a	DET
ajst-20186	66	7	sequence	sequence	NOUN
ajst-20186	66	8	of	of	ADP
ajst-20186	66	9	fully	fully	ADV
ajst-20186	66	10	connected	connected	ADJ
ajst-20186	66	11	layers	layer	NOUN
ajst-20186	66	12	is	be	AUX
ajst-20186	66	13	employed	employ	VERB
ajst-20186	66	14	to	to	PART
ajst-20186	66	15	map	map	VERB
ajst-20186	66	16	the	the	DET
ajst-20186	66	17	learned	learn	VERB
ajst-20186	66	18	features	feature	NOUN
ajst-20186	66	19	to	to	ADP
ajst-20186	66	20	the	the	DET
ajst-20186	66	21	output	output	NOUN
ajst-20186	66	22	space	space	NOUN
ajst-20186	66	23	,	,	PUNCT
ajst-20186	66	24	preparing	prepare	VERB
ajst-20186	66	25	for	for	ADP
ajst-20186	66	26	the	the	DET
ajst-20186	66	27	final	final	ADJ
ajst-20186	66	28	classification	classification	NOUN
ajst-20186	66	29	task	task	NOUN
ajst-20186	66	30	.	.	PUNCT
ajst-20186	67	1	during	during	ADP
ajst-20186	67	2	the	the	DET
ajst-20186	67	3	training	training	NOUN
ajst-20186	67	4	process	process	NOUN
ajst-20186	67	5	,	,	PUNCT
ajst-20186	67	6	the	the	DET
ajst-20186	67	7	network	network	NOUN
ajst-20186	67	8	is	be	AUX
ajst-20186	67	9	trained	train	VERB
ajst-20186	67	10	until	until	SCONJ
ajst-20186	67	11	the	the	DET
ajst-20186	67	12	specified	specified	ADJ
ajst-20186	67	13	training	training	NOUN
ajst-20186	67	14	steps	step	NOUN
ajst-20186	67	15	are	be	AUX
ajst-20186	67	16	reached	reach	VERB
ajst-20186	67	17	.	.	PUNCT
ajst-20186	68	1	a	a	DET
ajst-20186	68	2	significant	significant	ADJ
ajst-20186	68	3	number	number	NOUN
ajst-20186	68	4	of	of	ADP
ajst-20186	68	5	training	training	NOUN
ajst-20186	68	6	iterations	iteration	NOUN
ajst-20186	68	7	are	be	AUX
ajst-20186	68	8	employed	employ	VERB
ajst-20186	68	9	to	to	PART
ajst-20186	68	10	minimize	minimize	VERB
ajst-20186	68	11	cross	cross	ADJ
ajst-20186	68	12	-	-	ADJ
ajst-20186	68	13	entropy	entropy	ADJ
ajst-20186	68	14	error	error	NOUN
ajst-20186	68	15	,	,	PUNCT
ajst-20186	68	16	ensuring	ensure	VERB
ajst-20186	68	17	that	that	SCONJ
ajst-20186	68	18	the	the	DET
ajst-20186	68	19	model	model	NOUN
ajst-20186	68	20	's	's	PART
ajst-20186	68	21	output	output	NOUN
ajst-20186	68	22	closely	closely	ADV
ajst-20186	68	23	approximates	approximate	VERB
ajst-20186	68	24	the	the	DET
ajst-20186	68	25	target	target	NOUN
ajst-20186	68	26	output	output	NOUN
ajst-20186	68	27	values	value	NOUN
ajst-20186	68	28	.	.	PUNCT
ajst-20186	69	1	this	this	DET
ajst-20186	69	2	extended	extend	VERB
ajst-20186	69	3	training	training	NOUN
ajst-20186	69	4	duration	duration	NOUN
ajst-20186	69	5	is	be	AUX
ajst-20186	69	6	undertaken	undertake	VERB
ajst-20186	69	7	at	at	ADP
ajst-20186	69	8	the	the	DET
ajst-20186	69	9	expense	expense	NOUN
ajst-20186	69	10	of	of	ADP
ajst-20186	69	11	a	a	DET
ajst-20186	69	12	higher	high	ADJ
ajst-20186	69	13	number	number	NOUN
ajst-20186	69	14	of	of	ADP
ajst-20186	69	15	training	training	NOUN
ajst-20186	69	16	cycles	cycle	NOUN
ajst-20186	69	17	to	to	PART
ajst-20186	69	18	enhance	enhance	VERB
ajst-20186	69	19	the	the	DET
ajst-20186	69	20	accuracy	accuracy	NOUN
ajst-20186	69	21	of	of	ADP
ajst-20186	69	22	the	the	DET
ajst-20186	69	23	neural	neural	ADJ
ajst-20186	69	24	network	network	NOUN
ajst-20186	69	25	in	in	ADP
ajst-20186	69	26	identifying	identify	VERB
ajst-20186	69	27	nuclear	nuclear	ADJ
ajst-20186	69	28	species[1	species[1	NOUN
ajst-20186	69	29	-	-	SYM
ajst-20186	69	30	3	3	NUM
ajst-20186	69	31	]	]	PUNCT
ajst-20186	69	32	.	.	PUNCT
ajst-20186	70	1	after	after	ADP
ajst-20186	70	2	testing	test	VERB
ajst-20186	70	3	the	the	DET
ajst-20186	70	4	trained	train	VERB
ajst-20186	70	5	artificial	artificial	ADJ
ajst-20186	70	6	neural	neural	ADJ
ajst-20186	70	7	network	network	NOUN
ajst-20186	70	8	on	on	ADP
ajst-20186	70	9	the	the	DET
ajst-20186	70	10	testing	testing	NOUN
ajst-20186	70	11	dataset	dataset	NOUN
ajst-20186	70	12	,	,	PUNCT
ajst-20186	70	13	the	the	DET
ajst-20186	70	14	results	result	NOUN
ajst-20186	70	15	are	be	AUX
ajst-20186	70	16	as	as	SCONJ
ajst-20186	70	17	follows	follow	VERB
ajst-20186	70	18	:	:	PUNCT
ajst-20186	70	19	table	table	NOUN
ajst-20186	70	20	1	1	NUM
ajst-20186	70	21	.	.	PUNCT
ajst-20186	71	1	accuracy	accuracy	NOUN
ajst-20186	71	2	of	of	ADP
ajst-20186	71	3	cnn	cnn	PROPN
ajst-20186	71	4	model	model	PROPN
ajst-20186	71	5	sample	sample	PROPN
ajst-20186	71	6	category	category	NOUN
ajst-20186	71	7	α	α	NOUN
ajst-20186	71	8	β	β	X
ajst-20186	71	9	testing	testing	NOUN
ajst-20186	71	10	accuracy	accuracy	NOUN
ajst-20186	71	11	99.8	99.8	NUM
ajst-20186	71	12	%	%	NOUN
ajst-20186	71	13	99.9	99.9	NUM
ajst-20186	71	14	%	%	NOUN
ajst-20186	71	15	based	base	VERB
ajst-20186	71	16	on	on	ADP
ajst-20186	71	17	the	the	DET
ajst-20186	71	18	data	datum	NOUN
ajst-20186	71	19	,	,	PUNCT
ajst-20186	71	20	it	it	PRON
ajst-20186	71	21	can	can	AUX
ajst-20186	71	22	be	be	AUX
ajst-20186	71	23	observed	observe	VERB
ajst-20186	71	24	that	that	SCONJ
ajst-20186	71	25	artificial	artificial	ADJ
ajst-20186	71	26	neural	neural	ADJ
ajst-20186	71	27	networks	network	NOUN
ajst-20186	71	28	exhibit	exhibit	VERB
ajst-20186	71	29	a	a	DET
ajst-20186	71	30	favorable	favorable	ADJ
ajst-20186	71	31	recognition	recognition	NOUN
ajst-20186	71	32	effect	effect	NOUN
ajst-20186	71	33	on	on	ADP
ajst-20186	71	34	sample	sample	NOUN
ajst-20186	71	35	data	datum	NOUN
ajst-20186	71	36	,	,	PUNCT
ajst-20186	71	37	and	and	CCONJ
ajst-20186	71	38	both	both	CCONJ
ajst-20186	71	39	the	the	DET
ajst-20186	71	40	features	feature	NOUN
ajst-20186	71	41	of	of	ADP
ajst-20186	71	42	the	the	DET
ajst-20186	71	43	dataset	dataset	NOUN
ajst-20186	71	44	and	and	CCONJ
ajst-20186	71	45	the	the	DET
ajst-20186	71	46	length	length	NOUN
ajst-20186	71	47	of	of	ADP
ajst-20186	71	48	the	the	DET
ajst-20186	71	49	data	datum	NOUN
ajst-20186	71	50	contribute	contribute	VERB
ajst-20186	71	51	to	to	ADP
ajst-20186	71	52	the	the	DET
ajst-20186	71	53	network	network	NOUN
ajst-20186	71	54	's	's	PART
ajst-20186	71	55	fitting	fitting	NOUN
ajst-20186	71	56	.	.	PUNCT
ajst-20186	72	1	the	the	DET
ajst-20186	72	2	parameter	parameter	NOUN
ajst-20186	72	3	count	count	NOUN
ajst-20186	72	4	of	of	ADP
ajst-20186	72	5	the	the	DET
ajst-20186	72	6	trained	train	VERB
ajst-20186	72	7	neural	neural	ADJ
ajst-20186	72	8	network	network	NOUN
ajst-20186	72	9	is	be	AUX
ajst-20186	72	10	74594	74594	NUM
ajst-20186	72	11	,	,	PUNCT
ajst-20186	72	12	with	with	ADP
ajst-20186	72	13	input	input	NOUN
ajst-20186	72	14	data	datum	NOUN
ajst-20186	72	15	processed	process	VERB
ajst-20186	72	16	in	in	ADP
ajst-20186	72	17	batches	batch	NOUN
ajst-20186	72	18	of	of	ADP
ajst-20186	72	19	10	10	NUM
ajst-20186	72	20	,	,	PUNCT
ajst-20186	72	21	yielding	yield	VERB
ajst-20186	72	22	results	result	NOUN
ajst-20186	72	23	in	in	ADP
ajst-20186	72	24	the	the	DET
ajst-20186	72	25	nanosecond	nanosecond	NOUN
ajst-20186	72	26	range	range	NOUN
ajst-20186	72	27	.	.	PUNCT
ajst-20186	73	1	among	among	ADP
ajst-20186	73	2	the	the	DET
ajst-20186	73	3	50	50	NUM
ajst-20186	73	4	collected	collect	VERB
ajst-20186	73	5	data	data	NOUN
ajst-20186	73	6	points	point	NOUN
ajst-20186	73	7	,	,	PUNCT
ajst-20186	73	8	random	random	ADJ
ajst-20186	73	9	noise	noise	NOUN
ajst-20186	73	10	ranging	range	VERB
ajst-20186	73	11	from	from	ADP
ajst-20186	73	12	1	1	NUM
ajst-20186	73	13	to	to	PART
ajst-20186	73	14	5	5	NUM
ajst-20186	73	15	units	unit	NOUN
ajst-20186	73	16	was	be	AUX
ajst-20186	73	17	introduced	introduce	VERB
ajst-20186	73	18	.	.	PUNCT
ajst-20186	74	1	despite	despite	SCONJ
ajst-20186	74	2	this	this	PRON
ajst-20186	74	3	,	,	PUNCT
ajst-20186	74	4	the	the	DET
ajst-20186	74	5	network	network	NOUN
ajst-20186	74	6	's	's	PART
ajst-20186	74	7	recognition	recognition	NOUN
ajst-20186	74	8	accuracy	accuracy	NOUN
ajst-20186	74	9	remained	remain	VERB
ajst-20186	74	10	above	above	ADP
ajst-20186	74	11	99	99	NUM
ajst-20186	74	12	%	%	NOUN
ajst-20186	74	13	.	.	PUNCT
ajst-20186	75	1	this	this	PRON
ajst-20186	75	2	demonstrates	demonstrate	VERB
ajst-20186	75	3	the	the	DET
ajst-20186	75	4	network	network	NOUN
ajst-20186	75	5	's	's	PART
ajst-20186	75	6	robustness	robustness	NOUN
ajst-20186	75	7	in	in	ADP
ajst-20186	75	8	recognizing	recognize	VERB
ajst-20186	75	9	α	α	PROPN
ajst-20186	75	10	and	and	CCONJ
ajst-20186	75	11	β	β	NOUN
ajst-20186	75	12	,	,	PUNCT
ajst-20186	75	13	even	even	ADV
ajst-20186	75	14	in	in	ADP
ajst-20186	75	15	the	the	DET
ajst-20186	75	16	presence	presence	NOUN
ajst-20186	75	17	of	of	ADP
ajst-20186	75	18	random	random	ADJ
ajst-20186	75	19	noise	noise	NOUN
ajst-20186	75	20	.	.	PUNCT
ajst-20186	76	1	4.3	4.3	NUM
ajst-20186	76	2	.	.	PUNCT
ajst-20186	76	3	dscnn	dscnn	PROPN
ajst-20186	76	4	model	model	PROPN
ajst-20186	76	5	to	to	PART
ajst-20186	76	6	reduce	reduce	VERB
ajst-20186	76	7	the	the	DET
ajst-20186	76	8	parameter	parameter	NOUN
ajst-20186	76	9	count	count	NOUN
ajst-20186	76	10	and	and	CCONJ
ajst-20186	76	11	make	make	VERB
ajst-20186	76	12	the	the	DET
ajst-20186	76	13	model	model	NOUN
ajst-20186	76	14	more	more	ADV
ajst-20186	76	15	lightweight	lightweight	ADJ
ajst-20186	76	16	,	,	PUNCT
ajst-20186	76	17	we	we	PRON
ajst-20186	76	18	replaced	replace	VERB
ajst-20186	76	19	the	the	DET
ajst-20186	76	20	basic	basic	ADJ
ajst-20186	76	21	convolution	convolution	NOUN
ajst-20186	76	22	with	with	ADP
ajst-20186	76	23	depthwise	depthwise	NOUN
ajst-20186	76	24	separable	separable	ADJ
ajst-20186	76	25	convolution	convolution	NOUN
ajst-20186	76	26	,	,	PUNCT
ajst-20186	76	27	aiming	aim	VERB
ajst-20186	76	28	to	to	PART
ajst-20186	76	29	decrease	decrease	VERB
ajst-20186	76	30	the	the	DET
ajst-20186	76	31	model	model	NOUN
ajst-20186	76	32	's	's	PART
ajst-20186	76	33	parameters	parameter	NOUN
ajst-20186	76	34	and	and	CCONJ
ajst-20186	76	35	computational	computational	ADJ
ajst-20186	76	36	complexity	complexity	NOUN
ajst-20186	76	37	while	while	SCONJ
ajst-20186	76	38	maintaining	maintain	VERB
ajst-20186	76	39	network	network	NOUN
ajst-20186	76	40	performance	performance	NOUN
ajst-20186	76	41	as	as	ADV
ajst-20186	76	42	much	much	ADV
ajst-20186	76	43	as	as	ADP
ajst-20186	76	44	possible	possible	ADJ
ajst-20186	76	45	.	.	PUNCT
ajst-20186	77	1	this	this	DET
ajst-20186	77	2	type	type	NOUN
ajst-20186	77	3	of	of	ADP
ajst-20186	77	4	convolution	convolution	NOUN
ajst-20186	77	5	is	be	AUX
ajst-20186	77	6	particularly	particularly	ADV
ajst-20186	77	7	useful	useful	ADJ
ajst-20186	77	8	in	in	ADP
ajst-20186	77	9	environments	environment	NOUN
ajst-20186	77	10	with	with	ADP
ajst-20186	77	11	mobile	mobile	ADJ
ajst-20186	77	12	devices	device	NOUN
ajst-20186	77	13	and	and	CCONJ
ajst-20186	77	14	limited	limited	ADJ
ajst-20186	77	15	resources	resource	NOUN
ajst-20186	77	16	as	as	SCONJ
ajst-20186	77	17	it	it	PRON
ajst-20186	77	18	significantly	significantly	ADV
ajst-20186	77	19	reduces	reduce	VERB
ajst-20186	77	20	the	the	DET
ajst-20186	77	21	required	require	VERB
ajst-20186	77	22	computational	computational	ADJ
ajst-20186	77	23	resources	resource	NOUN
ajst-20186	77	24	and	and	CCONJ
ajst-20186	77	25	model	model	NOUN
ajst-20186	77	26	size[4	size[4	PROPN
ajst-20186	77	27	]	]	PUNCT
ajst-20186	77	28	.	.	PUNCT
ajst-20186	78	1	depthwise	depthwise	NOUN
ajst-20186	78	2	separable	separable	ADJ
ajst-20186	78	3	convolution	convolution	NOUN
ajst-20186	78	4	,	,	PUNCT
ajst-20186	78	5	typically	typically	ADV
ajst-20186	78	6	used	use	VERB
ajst-20186	78	7	for	for	ADP
ajst-20186	78	8	twodimensional	twodimensional	ADJ
ajst-20186	78	9	data	datum	NOUN
ajst-20186	78	10	,	,	PUNCT
ajst-20186	78	11	can	can	AUX
ajst-20186	78	12	also	also	ADV
ajst-20186	78	13	be	be	AUX
ajst-20186	78	14	applied	apply	VERB
ajst-20186	78	15	to	to	ADP
ajst-20186	78	16	one	one	NUM
ajst-20186	78	17	-	-	PUNCT
ajst-20186	78	18	dimensional	dimensional	ADJ
ajst-20186	78	19	sequence	sequence	NOUN
ajst-20186	78	20	data	datum	NOUN
ajst-20186	78	21	.	.	PUNCT
ajst-20186	79	1	for	for	ADP
ajst-20186	79	2	one	one	NUM
ajst-20186	79	3	-	-	PUNCT
ajst-20186	79	4	dimensional	dimensional	ADJ
ajst-20186	79	5	sequences	sequence	NOUN
ajst-20186	79	6	,	,	PUNCT
ajst-20186	79	7	the	the	DET
ajst-20186	79	8	process	process	NOUN
ajst-20186	79	9	of	of	ADP
ajst-20186	79	10	depthwise	depthwise	NOUN
ajst-20186	79	11	separable	separable	ADJ
ajst-20186	79	12	convolution	convolution	NOUN
ajst-20186	79	13	is	be	AUX
ajst-20186	79	14	slightly	slightly	ADV
ajst-20186	79	15	different	different	ADJ
ajst-20186	79	16	,	,	PUNCT
ajst-20186	79	17	but	but	CCONJ
ajst-20186	79	18	the	the	DET
ajst-20186	79	19	basic	basic	ADJ
ajst-20186	79	20	principle	principle	NOUN
ajst-20186	79	21	remains	remain	VERB
ajst-20186	79	22	consistent	consistent	ADJ
ajst-20186	79	23	.	.	PUNCT
ajst-20186	80	1	in	in	ADP
ajst-20186	80	2	a	a	DET
ajst-20186	80	3	depthwise	depthwise	ADJ
ajst-20186	80	4	convolutional	convolutional	ADJ
ajst-20186	80	5	layer	layer	NOUN
ajst-20186	80	6	,	,	PUNCT
ajst-20186	80	7	deep	deep	ADJ
ajst-20186	80	8	convolution	convolution	NOUN
ajst-20186	80	9	is	be	AUX
ajst-20186	80	10	performed	perform	VERB
ajst-20186	80	11	on	on	ADP
ajst-20186	80	12	the	the	DET
ajst-20186	80	13	input	input	NOUN
ajst-20186	80	14	sequence	sequence	NOUN
ajst-20186	80	15	.	.	PUNCT
ajst-20186	81	1	this	this	DET
ajst-20186	81	2	step	step	NOUN
ajst-20186	81	3	involves	involve	VERB
ajst-20186	81	4	applying	apply	VERB
ajst-20186	81	5	one	one	NUM
ajst-20186	81	6	-	-	PUNCT
ajst-20186	81	7	dimensional	dimensional	ADJ
ajst-20186	81	8	convolutional	convolutional	ADJ
ajst-20186	81	9	kernels	kernel	NOUN
ajst-20186	81	10	independently	independently	ADV
ajst-20186	81	11	to	to	ADP
ajst-20186	81	12	each	each	DET
ajst-20186	81	13	channel	channel	NOUN
ajst-20186	81	14	(	(	PUNCT
ajst-20186	81	15	or	or	CCONJ
ajst-20186	81	16	feature	feature	NOUN
ajst-20186	81	17	)	)	PUNCT
ajst-20186	81	18	.	.	PUNCT
ajst-20186	82	1	assuming	assume	VERB
ajst-20186	82	2	the	the	DET
ajst-20186	82	3	shape	shape	NOUN
ajst-20186	82	4	of	of	ADP
ajst-20186	82	5	the	the	DET
ajst-20186	82	6	input	input	NOUN
ajst-20186	82	7	data	data	NOUN
ajst-20186	82	8	is	be	AUX
ajst-20186	82	9	[	[	X
ajst-20186	82	10	n	n	CCONJ
ajst-20186	82	11	,	,	PUNCT
ajst-20186	82	12	c	c	X
ajst-20186	82	13	,	,	PUNCT
ajst-20186	82	14	l	l	NOUN
ajst-20186	82	15	]	]	X
ajst-20186	82	16	,	,	PUNCT
ajst-20186	82	17	where	where	SCONJ
ajst-20186	82	18	n	n	PRON
ajst-20186	82	19	is	be	AUX
ajst-20186	82	20	the	the	DET
ajst-20186	82	21	batch	batch	NOUN
ajst-20186	82	22	size	size	NOUN
ajst-20186	82	23	,	,	PUNCT
ajst-20186	82	24	c	c	PROPN
ajst-20186	82	25	is	be	AUX
ajst-20186	82	26	the	the	DET
ajst-20186	82	27	number	number	NOUN
ajst-20186	82	28	of	of	ADP
ajst-20186	82	29	channels	channel	NOUN
ajst-20186	82	30	,	,	PUNCT
ajst-20186	82	31	and	and	CCONJ
ajst-20186	82	32	l	l	NOUN
ajst-20186	82	33	is	be	AUX
ajst-20186	82	34	the	the	DET
ajst-20186	82	35	sequence	sequence	NOUN
ajst-20186	82	36	length[8	length[8	PROPN
ajst-20186	82	37	]	]	PUNCT
ajst-20186	82	38	.	.	PUNCT
ajst-20186	83	1	in	in	ADP
ajst-20186	83	2	depthwise	depthwise	NOUN
ajst-20186	83	3	convolution	convolution	NOUN
ajst-20186	83	4	,	,	PUNCT
ajst-20186	83	5	each	each	DET
ajst-20186	83	6	input	input	NOUN
ajst-20186	83	7	channel	channel	NOUN
ajst-20186	83	8	is	be	AUX
ajst-20186	83	9	processed	process	VERB
ajst-20186	83	10	separately	separately	ADV
ajst-20186	83	11	by	by	ADP
ajst-20186	83	12	a	a	DET
ajst-20186	83	13	single	single	ADJ
ajst-20186	83	14	convolutional	convolutional	ADJ
ajst-20186	83	15	kernel	kernel	NOUN
ajst-20186	83	16	.	.	PUNCT
ajst-20186	84	1	let	let	VERB
ajst-20186	84	2	's	us	PRON
ajst-20186	84	3	assume	assume	VERB
ajst-20186	84	4	we	we	PRON
ajst-20186	84	5	have	have	VERB
ajst-20186	84	6	an	an	DET
ajst-20186	84	7	input	input	NOUN
ajst-20186	84	8	sequence	sequence	NOUN
ajst-20186	84	9	i	i	PRON
ajst-20186	84	10	with	with	ADP
ajst-20186	84	11	dimensions	dimension	NOUN
ajst-20186	84	12	of	of	ADP
ajst-20186	84	13	l×d	l×d	PROPN
ajst-20186	84	14	,	,	PUNCT
ajst-20186	84	15	where	where	SCONJ
ajst-20186	84	16	l	l	NOUN
ajst-20186	84	17	is	be	AUX
ajst-20186	84	18	the	the	DET
ajst-20186	84	19	sequence	sequence	NOUN
ajst-20186	84	20	length	length	NOUN
ajst-20186	85	1	and	and	CCONJ
ajst-20186	85	2	d	d	NOUN
ajst-20186	85	3	is	be	AUX
ajst-20186	85	4	the	the	DET
ajst-20186	85	5	number	number	NOUN
ajst-20186	85	6	of	of	ADP
ajst-20186	85	7	channels	channel	NOUN
ajst-20186	85	8	.	.	PUNCT
ajst-20186	86	1	the	the	DET
ajst-20186	86	2	formula	formula	NOUN
ajst-20186	86	3	is	be	AUX
ajst-20186	86	4	as	as	SCONJ
ajst-20186	86	5	follows	follow	VERB
ajst-20186	86	6	:	:	PUNCT
ajst-20186	86	7	o	o	X
ajst-20186	86	8	l	l	NOUN
ajst-20186	87	1	i	i	PRON
ajst-20186	87	2	l	l	VERB
ajst-20186	88	1	i	i	PRON
ajst-20186	88	2	∗	∗	VERB
ajst-20186	88	3	k	k	PROPN
ajst-20186	89	1	i	i	PRON
ajst-20186	89	2	1	1	NUM
ajst-20186	89	3	after	after	ADP
ajst-20186	89	4	the	the	DET
ajst-20186	89	5	depthwise	depthwise	NOUN
ajst-20186	89	6	convolution	convolution	NOUN
ajst-20186	89	7	,	,	PUNCT
ajst-20186	89	8	a	a	DET
ajst-20186	89	9	1x1	1x1	NUM
ajst-20186	89	10	pointwise	pointwise	NOUN
ajst-20186	89	11	convolution	convolution	NOUN
ajst-20186	89	12	(	(	PUNCT
ajst-20186	89	13	with	with	ADP
ajst-20186	89	14	a	a	DET
ajst-20186	89	15	kernel	kernel	NOUN
ajst-20186	89	16	size	size	NOUN
ajst-20186	89	17	of	of	ADP
ajst-20186	89	18	1	1	NUM
ajst-20186	89	19	in	in	ADP
ajst-20186	89	20	the	the	DET
ajst-20186	89	21	one	one	NUM
ajst-20186	89	22	-	-	PUNCT
ajst-20186	89	23	dimensional	dimensional	ADJ
ajst-20186	89	24	case	case	NOUN
ajst-20186	89	25	)	)	PUNCT
ajst-20186	89	26	is	be	AUX
ajst-20186	89	27	utilized	utilize	VERB
ajst-20186	89	28	to	to	PART
ajst-20186	89	29	combine	combine	VERB
ajst-20186	89	30	features	feature	NOUN
ajst-20186	89	31	from	from	ADP
ajst-20186	89	32	different	different	ADJ
ajst-20186	89	33	channels	channel	NOUN
ajst-20186	89	34	.	.	PUNCT
ajst-20186	90	1	now	now	ADV
ajst-20186	90	2	,	,	PUNCT
ajst-20186	90	3	we	we	PRON
ajst-20186	90	4	have	have	VERB
ajst-20186	90	5	an	an	DET
ajst-20186	90	6	intermediate	intermediate	ADJ
ajst-20186	90	7	sequence	sequence	NOUN
ajst-20186	90	8	o	o	NOUN
ajst-20186	90	9	with	with	ADP
ajst-20186	90	10	dimensions	dimension	NOUN
ajst-20186	90	11	of	of	ADP
ajst-20186	90	12	l×d	l×d	PROPN
ajst-20186	90	13	.	.	PUNCT
ajst-20186	91	1	the	the	DET
ajst-20186	91	2	formula	formula	NOUN
ajst-20186	91	3	is	be	AUX
ajst-20186	91	4	as	as	SCONJ
ajst-20186	91	5	follows	follow	VERB
ajst-20186	91	6	:	:	PUNCT
ajst-20186	91	7	p	p	X
ajst-20186	91	8	l	l	NOUN
ajst-20186	91	9	o	o	X
ajst-20186	91	10	l	l	NOUN
ajst-20186	91	11	∗	∗	NOUN
ajst-20186	91	12	k	k	PROPN
ajst-20186	92	1	d	d	PROPN
ajst-20186	92	2	2	2	NUM
ajst-20186	92	3	where	where	SCONJ
ajst-20186	92	4	p(l	p(l	PROPN
ajst-20186	92	5	)	)	PUNCT
ajst-20186	92	6	is	be	AUX
ajst-20186	92	7	an	an	DET
ajst-20186	92	8	element	element	NOUN
ajst-20186	92	9	in	in	ADP
ajst-20186	92	10	the	the	DET
ajst-20186	92	11	final	final	ADJ
ajst-20186	92	12	output	output	NOUN
ajst-20186	92	13	sequence	sequence	NOUN
ajst-20186	92	14	at	at	ADP
ajst-20186	92	15	position	position	NOUN
ajst-20186	92	16	(	(	PUNCT
ajst-20186	92	17	l	l	NOUN
ajst-20186	92	18	)	)	PUNCT
ajst-20186	92	19	,	,	PUNCT
ajst-20186	92	20	(	(	PUNCT
ajst-20186	92	21	k	k	X
ajst-20186	92	22	)	)	PUNCT
ajst-20186	92	23	is	be	AUX
ajst-20186	92	24	the	the	DET
ajst-20186	92	25	convolution	convolution	NOUN
ajst-20186	92	26	kernel	kernel	NOUN
ajst-20186	92	27	with	with	ADP
ajst-20186	92	28	a	a	DET
ajst-20186	92	29	size	size	NOUN
ajst-20186	92	30	of	of	ADP
ajst-20186	92	31	1	1	NUM
ajst-20186	92	32	,	,	PUNCT
ajst-20186	92	33	and	and	CCONJ
ajst-20186	92	34	it	it	PRON
ajst-20186	92	35	operates	operate	VERB
ajst-20186	92	36	across	across	ADP
ajst-20186	92	37	all	all	DET
ajst-20186	92	38	input	input	NOUN
ajst-20186	92	39	channels	channel	NOUN
ajst-20186	92	40	(	(	PUNCT
ajst-20186	92	41	d	d	NOUN
ajst-20186	92	42	)	)	PUNCT
ajst-20186	92	43	.	.	PUNCT
ajst-20186	93	1	in	in	ADP
ajst-20186	93	2	this	this	DET
ajst-20186	93	3	step	step	NOUN
ajst-20186	93	4	,	,	PUNCT
ajst-20186	93	5	pointwise	pointwise	NOUN
ajst-20186	93	6	convolution	convolution	NOUN
ajst-20186	93	7	integrates	integrate	NOUN
ajst-20186	93	8	features	feature	NOUN
ajst-20186	93	9	from	from	ADP
ajst-20186	93	10	different	different	ADJ
ajst-20186	93	11	channels	channel	NOUN
ajst-20186	93	12	by	by	ADP
ajst-20186	93	13	applying	apply	VERB
ajst-20186	93	14	a	a	DET
ajst-20186	93	15	convolution	convolution	NOUN
ajst-20186	93	16	kernel	kernel	NOUN
ajst-20186	93	17	of	of	ADP
ajst-20186	93	18	size	size	NOUN
ajst-20186	93	19	1×1×c	1×1×c	NUM
ajst-20186	93	20	,	,	PUNCT
ajst-20186	93	21	which	which	PRON
ajst-20186	93	22	can	can	AUX
ajst-20186	93	23	alter	alter	VERB
ajst-20186	93	24	the	the	DET
ajst-20186	93	25	number	number	NOUN
ajst-20186	93	26	of	of	ADP
ajst-20186	93	27	channels[9	channels[9	PROPN
ajst-20186	93	28	]	]	PUNCT
ajst-20186	93	29	.	.	PUNCT
ajst-20186	94	1	in	in	ADP
ajst-20186	94	2	the	the	DET
ajst-20186	94	3	dscnn	dscnn	PROPN
ajst-20186	94	4	model	model	PROPN
ajst-20186	94	5	,	,	PUNCT
ajst-20186	94	6	the	the	DET
ajst-20186	94	7	parameter	parameter	NOUN
ajst-20186	94	8	count	count	NOUN
ajst-20186	94	9	of	of	ADP
ajst-20186	94	10	the	the	DET
ajst-20186	94	11	trained	train	VERB
ajst-20186	94	12	neural	neural	ADJ
ajst-20186	94	13	network	network	NOUN
ajst-20186	94	14	is	be	AUX
ajst-20186	94	15	58,342	58,342	NUM
ajst-20186	94	16	.	.	PUNCT
ajst-20186	95	1	the	the	DET
ajst-20186	95	2	testing	testing	NOUN
ajst-20186	95	3	accuracy	accuracy	NOUN
ajst-20186	95	4	on	on	ADP
ajst-20186	95	5	the	the	DET
ajst-20186	95	6	same	same	ADJ
ajst-20186	95	7	test	test	NOUN
ajst-20186	95	8	set	set	VERB
ajst-20186	95	9	is	be	AUX
ajst-20186	95	10	as	as	SCONJ
ajst-20186	95	11	follows	follow	VERB
ajst-20186	95	12	:	:	PUNCT
ajst-20186	95	13	table	table	NOUN
ajst-20186	95	14	2	2	NUM
ajst-20186	95	15	.	.	PUNCT
ajst-20186	95	16	accuracy	accuracy	NOUN
ajst-20186	95	17	of	of	ADP
ajst-20186	95	18	dscnn	dscnn	PROPN
ajst-20186	95	19	model	model	PROPN
ajst-20186	95	20	sample	sample	NOUN
ajst-20186	95	21	category	category	NOUN
ajst-20186	95	22	α	α	NOUN
ajst-20186	95	23	β	β	X
ajst-20186	95	24	testing	testing	NOUN
ajst-20186	95	25	accuracy	accuracy	NOUN
ajst-20186	95	26	99.7	99.7	NUM
ajst-20186	95	27	%	%	NOUN
ajst-20186	95	28	99.9	99.9	NUM
ajst-20186	95	29	%	%	NOUN
ajst-20186	95	30	it	it	PRON
ajst-20186	95	31	can	can	AUX
ajst-20186	95	32	be	be	AUX
ajst-20186	95	33	observed	observe	VERB
ajst-20186	95	34	that	that	SCONJ
ajst-20186	95	35	,	,	PUNCT
ajst-20186	95	36	compared	compare	VERB
ajst-20186	95	37	to	to	ADP
ajst-20186	95	38	the	the	DET
ajst-20186	95	39	original	original	ADJ
ajst-20186	95	40	cnn	cnn	PROPN
ajst-20186	95	41	network	network	NOUN
ajst-20186	95	42	,	,	PUNCT
ajst-20186	95	43	although	although	SCONJ
ajst-20186	95	44	there	there	PRON
ajst-20186	95	45	is	be	VERB
ajst-20186	95	46	a	a	DET
ajst-20186	95	47	slight	slight	ADJ
ajst-20186	95	48	decrease	decrease	NOUN
ajst-20186	95	49	in	in	ADP
ajst-20186	95	50	model	model	NOUN
ajst-20186	95	51	accuracy	accuracy	NOUN
ajst-20186	95	52	,	,	PUNCT
ajst-20186	95	53	the	the	DET
ajst-20186	95	54	parameter	parameter	NOUN
ajst-20186	95	55	count	count	NOUN
ajst-20186	95	56	has	have	AUX
ajst-20186	95	57	been	be	AUX
ajst-20186	95	58	reduced	reduce	VERB
ajst-20186	95	59	by	by	ADP
ajst-20186	95	60	approximately	approximately	ADV
ajst-20186	95	61	21.8	21.8	NUM
ajst-20186	95	62	%	%	NOUN
ajst-20186	95	63	.	.	PUNCT
ajst-20186	96	1	therefore	therefore	ADV
ajst-20186	96	2	,	,	PUNCT
ajst-20186	96	3	replacing	replace	VERB
ajst-20186	96	4	convolutions	convolution	NOUN
ajst-20186	96	5	in	in	ADP
ajst-20186	96	6	the	the	DET
ajst-20186	96	7	cnn	cnn	PROPN
ajst-20186	96	8	model	model	NOUN
ajst-20186	96	9	with	with	ADP
ajst-20186	96	10	depthwise	depthwise	NOUN
ajst-20186	96	11	separable	separable	ADJ
ajst-20186	96	12	convolutions	convolution	NOUN
ajst-20186	96	13	has	have	AUX
ajst-20186	96	14	significantly	significantly	ADV
ajst-20186	96	15	reduced	reduce	VERB
ajst-20186	96	16	resource	resource	NOUN
ajst-20186	96	17	usage	usage	NOUN
ajst-20186	96	18	.	.	PUNCT
ajst-20186	97	1	by	by	ADP
ajst-20186	97	2	decomposing	decompose	VERB
ajst-20186	97	3	the	the	DET
ajst-20186	97	4	convolution	convolution	NOUN
ajst-20186	97	5	operation	operation	NOUN
ajst-20186	97	6	into	into	ADP
ajst-20186	97	7	depthwise	depthwise	NOUN
ajst-20186	97	8	and	and	CCONJ
ajst-20186	97	9	pointwise	pointwise	PROPN
ajst-20186	97	10	convolutions	convolution	NOUN
ajst-20186	97	11	,	,	PUNCT
ajst-20186	97	12	it	it	PRON
ajst-20186	97	13	effectively	effectively	ADV
ajst-20186	97	14	reduces	reduce	VERB
ajst-20186	97	15	the	the	DET
ajst-20186	97	16	number	number	NOUN
ajst-20186	97	17	of	of	ADP
ajst-20186	97	18	parameters	parameter	NOUN
ajst-20186	97	19	and	and	CCONJ
ajst-20186	97	20	computational	computational	ADJ
ajst-20186	97	21	burden	burden	NOUN
ajst-20186	97	22	while	while	SCONJ
ajst-20186	97	23	maintaining	maintain	VERB
ajst-20186	97	24	the	the	DET
ajst-20186	97	25	ability	ability	NOUN
ajst-20186	97	26	to	to	PART
ajst-20186	97	27	process	process	VERB
ajst-20186	97	28	one	one	NUM
ajst-20186	97	29	-	-	PUNCT
ajst-20186	97	30	dimensional	dimensional	ADJ
ajst-20186	97	31	data	datum	NOUN
ajst-20186	97	32	.	.	PUNCT
ajst-20186	98	1	this	this	DET
ajst-20186	98	2	parameter	parameter	NOUN
ajst-20186	98	3	reduction	reduction	NOUN
ajst-20186	98	4	method	method	NOUN
ajst-20186	98	5	not	not	PART
ajst-20186	98	6	only	only	ADV
ajst-20186	98	7	decreases	decrease	VERB
ajst-20186	98	8	the	the	DET
ajst-20186	98	9	model	model	NOUN
ajst-20186	98	10	size	size	NOUN
ajst-20186	98	11	but	but	CCONJ
ajst-20186	98	12	also	also	ADV
ajst-20186	98	13	helps	help	VERB
ajst-20186	98	14	prevent	prevent	VERB
ajst-20186	98	15	overfitting	overfitting	NOUN
ajst-20186	98	16	and	and	CCONJ
ajst-20186	98	17	accelerates	accelerate	VERB
ajst-20186	98	18	training	training	NOUN
ajst-20186	98	19	speed	speed	NOUN
ajst-20186	98	20	.	.	PUNCT
ajst-20186	99	1	this	this	PRON
ajst-20186	99	2	is	be	AUX
ajst-20186	99	3	particularly	particularly	ADV
ajst-20186	99	4	beneficial	beneficial	ADJ
ajst-20186	99	5	for	for	ADP
ajst-20186	99	6	running	running	NOUN
ajst-20186	99	7	models	model	NOUN
ajst-20186	99	8	on	on	ADP
ajst-20186	99	9	resourceconstrained	resourceconstraine	VERB
ajst-20186	99	10	devices	device	NOUN
ajst-20186	99	11	such	such	ADJ
ajst-20186	99	12	as	as	ADP
ajst-20186	99	13	mobile	mobile	ADJ
ajst-20186	99	14	devices	device	NOUN
ajst-20186	99	15	and	and	CCONJ
ajst-20186	99	16	embedded	embed	VERB
ajst-20186	99	17	systems	system	NOUN
ajst-20186	99	18	.	.	PUNCT
ajst-20186	100	1	5	5	X
ajst-20186	100	2	.	.	X
ajst-20186	100	3	summary	summary	NOUN
ajst-20186	100	4	although	although	SCONJ
ajst-20186	100	5	traditional	traditional	ADJ
ajst-20186	100	6	methods	method	NOUN
ajst-20186	100	7	still	still	ADV
ajst-20186	100	8	hold	hold	VERB
ajst-20186	100	9	an	an	DET
ajst-20186	100	10	irreplaceable	irreplaceable	ADJ
ajst-20186	100	11	position	position	NOUN
ajst-20186	100	12	in	in	ADP
ajst-20186	100	13	certain	certain	ADJ
ajst-20186	100	14	applications	application	NOUN
ajst-20186	100	15	,	,	PUNCT
ajst-20186	100	16	artificial	artificial	ADJ
ajst-20186	100	17	intelligence	intelligence	NOUN
ajst-20186	100	18	methods	method	NOUN
ajst-20186	100	19	offer	offer	VERB
ajst-20186	100	20	significant	significant	ADJ
ajst-20186	100	21	advantages	advantage	NOUN
ajst-20186	100	22	when	when	SCONJ
ajst-20186	100	23	dealing	deal	VERB
ajst-20186	100	24	with	with	ADP
ajst-20186	100	25	higher	high	ADJ
ajst-20186	100	26	dimensions	dimension	NOUN
ajst-20186	100	27	and	and	CCONJ
ajst-20186	100	28	complexities	complexity	NOUN
ajst-20186	100	29	.	.	PUNCT
ajst-20186	101	1	with	with	ADP
ajst-20186	101	2	the	the	DET
ajst-20186	101	3	improvement	improvement	NOUN
ajst-20186	101	4	of	of	ADP
ajst-20186	101	5	computing	compute	VERB
ajst-20186	101	6	capabilities	capability	NOUN
ajst-20186	101	7	and	and	CCONJ
ajst-20186	101	8	continuous	continuous	ADJ
ajst-20186	101	9	algorithm	algorithm	NOUN
ajst-20186	101	10	optimizations	optimization	NOUN
ajst-20186	101	11	,	,	PUNCT
ajst-20186	101	12	artificial	artificial	ADJ
ajst-20186	101	13	intelligence	intelligence	NOUN
ajst-20186	101	14	is	be	AUX
ajst-20186	101	15	playing	play	VERB
ajst-20186	101	16	an	an	DET
ajst-20186	101	17	increasingly	increasingly	ADV
ajst-20186	101	18	important	important	ADJ
ajst-20186	101	19	role	role	NOUN
ajst-20186	101	20	in	in	ADP
ajst-20186	101	21	the	the	DET
ajst-20186	101	22	field	field	NOUN
ajst-20186	101	23	of	of	ADP
ajst-20186	101	24	waveform	waveform	NOUN
ajst-20186	101	25	recognition	recognition	NOUN
ajst-20186	101	26	.	.	PUNCT
ajst-20186	102	1	in	in	ADP
ajst-20186	102	2	the	the	DET
ajst-20186	102	3	context	context	NOUN
ajst-20186	102	4	of	of	ADP
ajst-20186	102	5	waveform	waveform	NOUN
ajst-20186	102	6	recognition	recognition	NOUN
ajst-20186	102	7	for	for	ADP
ajst-20186	102	8	alpha	alpha	NOUN
ajst-20186	102	9	and	and	CCONJ
ajst-20186	102	10	beta	beta	NOUN
ajst-20186	102	11	particles	particle	NOUN
ajst-20186	102	12	,	,	PUNCT
ajst-20186	102	13	it	it	PRON
ajst-20186	102	14	also	also	ADV
ajst-20186	102	15	contributes	contribute	VERB
ajst-20186	102	16	to	to	ADP
ajst-20186	102	17	restraining	restrain	VERB
ajst-20186	102	18	nuclear	nuclear	ADJ
ajst-20186	102	19	64	64	NUM
ajst-20186	102	20	proliferation	proliferation	NOUN
ajst-20186	102	21	,	,	PUNCT
ajst-20186	102	22	enhancing	enhance	VERB
ajst-20186	102	23	nuclear	nuclear	ADJ
ajst-20186	102	24	security	security	NOUN
ajst-20186	102	25	,	,	PUNCT
ajst-20186	102	26	and	and	CCONJ
ajst-20186	102	27	providing	provide	VERB
ajst-20186	102	28	a	a	DET
ajst-20186	102	29	certain	certain	ADJ
ajst-20186	102	30	degree	degree	NOUN
ajst-20186	102	31	of	of	ADP
ajst-20186	102	32	contribution	contribution	NOUN
ajst-20186	102	33	.	.	PUNCT
ajst-20186	103	1	as	as	ADP
ajst-20186	103	2	computational	computational	ADJ
ajst-20186	103	3	power	power	NOUN
ajst-20186	103	4	and	and	CCONJ
ajst-20186	103	5	algorithmic	algorithmic	ADJ
ajst-20186	103	6	capabilities	capability	NOUN
ajst-20186	103	7	continue	continue	VERB
ajst-20186	103	8	to	to	PART
ajst-20186	103	9	advance	advance	VERB
ajst-20186	103	10	,	,	PUNCT
ajst-20186	103	11	the	the	DET
ajst-20186	103	12	role	role	NOUN
ajst-20186	103	13	of	of	ADP
ajst-20186	103	14	artificial	artificial	ADJ
ajst-20186	103	15	intelligence	intelligence	NOUN
ajst-20186	103	16	in	in	ADP
ajst-20186	103	17	waveform	waveform	NOUN
ajst-20186	103	18	recognition	recognition	NOUN
ajst-20186	103	19	,	,	PUNCT
ajst-20186	103	20	particularly	particularly	ADV
ajst-20186	103	21	for	for	ADP
ajst-20186	103	22	α	α	NOUN
ajst-20186	103	23	and	and	CCONJ
ajst-20186	103	24	β	β	NOUN
ajst-20186	103	25	particles	particle	NOUN
ajst-20186	103	26	,	,	PUNCT
ajst-20186	103	27	is	be	AUX
ajst-20186	103	28	expected	expect	VERB
ajst-20186	103	29	to	to	PART
ajst-20186	103	30	grow	grow	VERB
ajst-20186	103	31	,	,	PUNCT
ajst-20186	103	32	furthering	further	VERB
ajst-20186	103	33	its	its	PRON
ajst-20186	103	34	impact	impact	NOUN
ajst-20186	103	35	on	on	ADP
ajst-20186	103	36	nuclear	nuclear	ADJ
ajst-20186	103	37	safety	safety	NOUN
ajst-20186	103	38	and	and	CCONJ
ajst-20186	103	39	security	security	NOUN
ajst-20186	103	40	.	.	PUNCT
ajst-20186	104	1	references	reference	NOUN
ajst-20186	104	2	[	[	X
ajst-20186	104	3	1	1	NUM
ajst-20186	104	4	]	]	PUNCT
ajst-20186	104	5	krizhevsky	krizhevsky	NOUN
ajst-20186	104	6	a	a	PROPN
ajst-20186	104	7	,	,	PUNCT
ajst-20186	104	8	sutskever	sutskever	VERB
ajst-20186	104	9	i	i	PRON
ajst-20186	104	10	,	,	PUNCT
ajst-20186	104	11	hinton	hinton	PROPN
ajst-20186	104	12	g	g	PROPN
ajst-20186	104	13	e.	e.	PROPN
ajst-20186	104	14	imagenet	imagenet	PROPN
ajst-20186	104	15	classification	classification	NOUN
ajst-20186	104	16	with	with	ADP
ajst-20186	104	17	deep	deep	ADJ
ajst-20186	104	18	convolutional	convolutional	ADJ
ajst-20186	104	19	neural	neural	ADJ
ajst-20186	104	20	networks[j	networks[j	NOUN
ajst-20186	104	21	]	]	X
ajst-20186	104	22	.	.	PUNCT
ajst-20186	105	1	advances	advance	NOUN
ajst-20186	105	2	in	in	ADP
ajst-20186	105	3	neural	neural	ADJ
ajst-20186	105	4	information	information	NOUN
ajst-20186	105	5	processing	processing	NOUN
ajst-20186	105	6	systems	system	NOUN
ajst-20186	105	7	,	,	PUNCT
ajst-20186	105	8	2012	2012	NUM
ajst-20186	105	9	,	,	PUNCT
ajst-20186	105	10	25	25	NUM
ajst-20186	105	11	.	.	PUNCT
ajst-20186	106	1	[	[	X
ajst-20186	106	2	2	2	NUM
ajst-20186	106	3	]	]	X
ajst-20186	106	4	long	long	PROPN
ajst-20186	106	5	j	j	PROPN
ajst-20186	106	6	,	,	PUNCT
ajst-20186	106	7	shelhamer	shelhamer	NOUN
ajst-20186	106	8	e	e	NOUN
ajst-20186	106	9	,	,	PUNCT
ajst-20186	106	10	darrell	darrell	PROPN
ajst-20186	106	11	t.	t.	PROPN
ajst-20186	106	12	fully	fully	ADV
ajst-20186	106	13	convolutional	convolutional	ADJ
ajst-20186	106	14	networks	network	NOUN
ajst-20186	106	15	for	for	ADP
ajst-20186	106	16	semantic	semantic	ADJ
ajst-20186	106	17	segmentation[c]//proceedings	segmentation[c]//proceeding	NOUN
ajst-20186	106	18	of	of	ADP
ajst-20186	106	19	the	the	DET
ajst-20186	106	20	ieee	ieee	NOUN
ajst-20186	106	21	conference	conference	NOUN
ajst-20186	106	22	on	on	ADP
ajst-20186	106	23	computer	computer	NOUN
ajst-20186	106	24	vision	vision	NOUN
ajst-20186	106	25	and	and	CCONJ
ajst-20186	106	26	pattern	pattern	NOUN
ajst-20186	106	27	recognition	recognition	NOUN
ajst-20186	106	28	.	.	PUNCT
ajst-20186	107	1	2015	2015	NUM
ajst-20186	107	2	:	:	PUNCT
ajst-20186	107	3	3431	3431	NUM
ajst-20186	107	4	-	-	SYM
ajst-20186	107	5	3440	3440	NUM
ajst-20186	107	6	.	.	PUNCT
ajst-20186	108	1	[	[	X
ajst-20186	108	2	3	3	X
ajst-20186	108	3	]	]	X
ajst-20186	108	4	kim	kim	PROPN
ajst-20186	108	5	y.	y.	PROPN
ajst-20186	108	6	convolutional	convolutional	ADJ
ajst-20186	108	7	neural	neural	ADJ
ajst-20186	108	8	networks	network	NOUN
ajst-20186	108	9	for	for	ADP
ajst-20186	108	10	sentence	sentence	NOUN
ajst-20186	108	11	classification[j	classification[j	PROPN
ajst-20186	108	12	]	]	PUNCT
ajst-20186	108	13	.	.	PUNCT
ajst-20186	109	1	arxiv	arxiv	PROPN
ajst-20186	109	2	preprint	preprint	NOUN
ajst-20186	109	3	arxiv:1408.5882	arxiv:1408.5882	PROPN
ajst-20186	109	4	,	,	PUNCT
ajst-20186	109	5	2014	2014	NUM
ajst-20186	109	6	.	.	PUNCT
ajst-20186	110	1	[	[	X
ajst-20186	110	2	4	4	X
ajst-20186	110	3	]	]	X
ajst-20186	110	4	howard	howard	PROPN
ajst-20186	110	5	a	a	DET
ajst-20186	110	6	g	g	PROPN
ajst-20186	110	7	,	,	PUNCT
ajst-20186	110	8	zhu	zhu	PROPN
ajst-20186	110	9	m	m	PROPN
ajst-20186	110	10	,	,	PUNCT
ajst-20186	110	11	chen	chen	PROPN
ajst-20186	110	12	b	b	PROPN
ajst-20186	110	13	,	,	PUNCT
ajst-20186	110	14	et	et	PROPN
ajst-20186	110	15	al	al	PROPN
ajst-20186	110	16	.	.	PROPN
ajst-20186	110	17	mobilenets	mobilenet	NOUN
ajst-20186	110	18	:	:	PUNCT
ajst-20186	110	19	efficient	efficient	ADJ
ajst-20186	110	20	convolutional	convolutional	ADJ
ajst-20186	110	21	neural	neural	ADJ
ajst-20186	110	22	networks	network	NOUN
ajst-20186	110	23	for	for	ADP
ajst-20186	110	24	mobile	mobile	ADJ
ajst-20186	110	25	vision	vision	NOUN
ajst-20186	110	26	applications	application	NOUN
ajst-20186	110	27	[	[	X
ajst-20186	110	28	j	j	X
ajst-20186	110	29	]	]	X
ajst-20186	110	30	.	.	PUNCT
ajst-20186	111	1	arxiv	arxiv	PROPN
ajst-20186	111	2	preprint	preprint	PROPN
ajst-20186	111	3	arxiv:1704.04861	arxiv:1704.04861	NOUN
ajst-20186	111	4	,	,	PUNCT
ajst-20186	111	5	2017	2017	NUM
ajst-20186	111	6	.	.	PUNCT
ajst-20186	112	1	[	[	X
ajst-20186	112	2	5	5	NUM
ajst-20186	112	3	]	]	X
ajst-20186	112	4	kong	kong	PROPN
ajst-20186	112	5	g	g	PROPN
ajst-20186	112	6	,	,	PUNCT
ajst-20186	112	7	jung	jung	PROPN
ajst-20186	112	8	m	m	PROPN
ajst-20186	112	9	,	,	PUNCT
ajst-20186	112	10	koivunen	koivunen	PROPN
ajst-20186	112	11	v.	v.	PROPN
ajst-20186	112	12	waveform	waveform	VERB
ajst-20186	112	13	classification	classification	NOUN
ajst-20186	112	14	in	in	ADP
ajst-20186	112	15	radar	radar	NOUN
ajst-20186	112	16	-	-	PUNCT
ajst-20186	112	17	communications	communication	NOUN
ajst-20186	112	18	coexistence	coexistence	NOUN
ajst-20186	112	19	scenarios	scenario	NOUN
ajst-20186	112	20	[	[	X
ajst-20186	112	21	c]//globecom	c]//globecom	PROPN
ajst-20186	112	22	2020	2020	NUM
ajst-20186	112	23	-	-	SYM
ajst-20186	112	24	2020	2020	NUM
ajst-20186	112	25	ieee	ieee	NOUN
ajst-20186	112	26	global	global	PROPN
ajst-20186	112	27	communications	communication	NOUN
ajst-20186	112	28	conference	conference	NOUN
ajst-20186	112	29	.	.	PUNCT
ajst-20186	113	1	ieee	ieee	NOUN
ajst-20186	113	2	,	,	PUNCT
ajst-20186	113	3	2020	2020	NUM
ajst-20186	113	4	:	:	PUNCT
ajst-20186	113	5	1	1	NUM
ajst-20186	113	6	-	-	SYM
ajst-20186	113	7	6	6	NUM
ajst-20186	113	8	.	.	PUNCT
ajst-20186	114	1	[	[	X
ajst-20186	114	2	6	6	NUM
ajst-20186	114	3	]	]	PUNCT
ajst-20186	114	4	yuan	yuan	PROPN
ajst-20186	114	5	s	s	PROPN
ajst-20186	114	6	,	,	PUNCT
ajst-20186	114	7	liu	liu	PROPN
ajst-20186	114	8	j	j	PROPN
ajst-20186	114	9	,	,	PUNCT
ajst-20186	114	10	wang	wang	PROPN
ajst-20186	114	11	s	s	PROPN
ajst-20186	114	12	,	,	PUNCT
ajst-20186	114	13	et	et	PROPN
ajst-20186	114	14	al	al	PROPN
ajst-20186	114	15	.	.	PUNCT
ajst-20186	115	1	seismic	seismic	PROPN
ajst-20186	115	2	waveform	waveform	VERB
ajst-20186	115	3	classification	classification	NOUN
ajst-20186	115	4	and	and	CCONJ
ajst-20186	115	5	first	first	ADJ
ajst-20186	115	6	-	-	PUNCT
ajst-20186	115	7	break	break	NOUN
ajst-20186	115	8	picking	picking	NOUN
ajst-20186	115	9	using	use	VERB
ajst-20186	115	10	convolution	convolution	NOUN
ajst-20186	115	11	neural	neural	ADJ
ajst-20186	115	12	networks[j	networks[j	PROPN
ajst-20186	115	13	]	]	X
ajst-20186	115	14	.	.	PUNCT
ajst-20186	116	1	ieee	ieee	PROPN
ajst-20186	116	2	geoscience	geoscience	PROPN
ajst-20186	116	3	and	and	CCONJ
ajst-20186	116	4	remote	remote	ADJ
ajst-20186	116	5	sensing	sense	VERB
ajst-20186	116	6	letters	letter	NOUN
ajst-20186	116	7	,	,	PUNCT
ajst-20186	116	8	2018	2018	NUM
ajst-20186	116	9	,	,	PUNCT
ajst-20186	116	10	15(2	15(2	NUM
ajst-20186	116	11	):	):	PUNCT
ajst-20186	116	12	272	272	NUM
ajst-20186	116	13	-	-	SYM
ajst-20186	116	14	276	276	NUM
ajst-20186	116	15	.	.	PUNCT
ajst-20186	117	1	[	[	X
ajst-20186	117	2	7	7	X
ajst-20186	117	3	]	]	X
ajst-20186	117	4	yim	yim	PROPN
ajst-20186	117	5	m	m	PROPN
ajst-20186	117	6	s.	s.	PROPN
ajst-20186	117	7	radiation	radiation	NOUN
ajst-20186	117	8	hazards	hazard	NOUN
ajst-20186	117	9	from	from	ADP
ajst-20186	117	10	the	the	DET
ajst-20186	117	11	nuclear	nuclear	ADJ
ajst-20186	117	12	fuel	fuel	NOUN
ajst-20186	117	13	cycle[m]//advanced	cycle[m]//advance	VERB
ajst-20186	117	14	security	security	NOUN
ajst-20186	117	15	and	and	CCONJ
ajst-20186	117	16	safeguarding	safeguard	VERB
ajst-20186	117	17	in	in	ADP
ajst-20186	117	18	the	the	DET
ajst-20186	117	19	nuclear	nuclear	ADJ
ajst-20186	117	20	power	power	NOUN
ajst-20186	117	21	industry	industry	NOUN
ajst-20186	117	22	.	.	PUNCT
ajst-20186	118	1	academic	academic	ADJ
ajst-20186	118	2	press	press	NOUN
ajst-20186	118	3	,	,	PUNCT
ajst-20186	118	4	2020	2020	NUM
ajst-20186	118	5	:	:	PUNCT
ajst-20186	118	6	49	49	NUM
ajst-20186	118	7	-	-	SYM
ajst-20186	118	8	79	79	NUM
ajst-20186	118	9	.	.	PUNCT
ajst-20186	119	1	[	[	X
ajst-20186	119	2	8	8	NUM
ajst-20186	119	3	]	]	X
ajst-20186	119	4	qin	qin	PROPN
ajst-20186	120	1	z	z	PROPN
ajst-20186	120	2	,	,	PUNCT
ajst-20186	120	3	zhang	zhang	PROPN
ajst-20186	120	4	z	z	PROPN
ajst-20186	120	5	,	,	PUNCT
ajst-20186	120	6	chen	chen	PROPN
ajst-20186	120	7	x	x	PROPN
ajst-20186	120	8	,	,	PUNCT
ajst-20186	120	9	et	et	PROPN
ajst-20186	120	10	al	al	PROPN
ajst-20186	120	11	.	.	PUNCT
ajst-20186	120	12	fd	fd	PROPN
ajst-20186	120	13	-	-	PUNCT
ajst-20186	120	14	mobilenet	mobilenet	NOUN
ajst-20186	120	15	:	:	PUNCT
ajst-20186	120	16	improved	improve	VERB
ajst-20186	120	17	mobilenet	mobilenet	NOUN
ajst-20186	120	18	with	with	ADP
ajst-20186	120	19	a	a	DET
ajst-20186	120	20	fast	fast	ADJ
ajst-20186	120	21	downsampling	downsample	VERB
ajst-20186	120	22	strategy[c]//2018	strategy[c]//2018	PROPN
ajst-20186	120	23	25th	25th	ADJ
ajst-20186	120	24	ieee	ieee	PROPN
ajst-20186	120	25	international	international	ADJ
ajst-20186	120	26	conference	conference	NOUN
ajst-20186	120	27	on	on	ADP
ajst-20186	120	28	image	image	NOUN
ajst-20186	120	29	processing	processing	NOUN
ajst-20186	120	30	(	(	PUNCT
ajst-20186	120	31	icip	icip	PROPN
ajst-20186	120	32	)	)	PUNCT
ajst-20186	120	33	.	.	PUNCT
ajst-20186	121	1	ieee	ieee	NOUN
ajst-20186	121	2	,	,	PUNCT
ajst-20186	121	3	2018	2018	NUM
ajst-20186	121	4	:	:	PUNCT
ajst-20186	121	5	1363	1363	NUM
ajst-20186	121	6	-	-	SYM
ajst-20186	121	7	1367	1367	NUM
ajst-20186	121	8	.	.	PUNCT
ajst-20186	122	1	[	[	X
ajst-20186	122	2	9	9	NUM
ajst-20186	122	3	]	]	X
ajst-20186	122	4	howard	howard	PROPN
ajst-20186	122	5	a	a	PROPN
ajst-20186	122	6	,	,	PUNCT
ajst-20186	122	7	sandler	sandler	PROPN
ajst-20186	122	8	m	m	PROPN
ajst-20186	122	9	,	,	PUNCT
ajst-20186	122	10	chu	chu	PROPN
ajst-20186	122	11	g	g	PROPN
ajst-20186	122	12	,	,	PUNCT
ajst-20186	122	13	et	et	PROPN
ajst-20186	122	14	al	al	PROPN
ajst-20186	122	15	.	.	PUNCT
ajst-20186	122	16	searching	search	VERB
ajst-20186	122	17	for	for	ADP
ajst-20186	122	18	mobilenetv3[c]//proceedings	mobilenetv3[c]//proceeding	NOUN
ajst-20186	122	19	of	of	ADP
ajst-20186	122	20	the	the	DET
ajst-20186	122	21	ieee	ieee	NOUN
ajst-20186	122	22	/	/	SYM
ajst-20186	122	23	cvf	cvf	NOUN
ajst-20186	122	24	international	international	ADJ
ajst-20186	122	25	conference	conference	NOUN
ajst-20186	122	26	on	on	ADP
ajst-20186	122	27	computer	computer	NOUN
ajst-20186	122	28	vision	vision	NOUN
ajst-20186	122	29	.	.	PUNCT
ajst-20186	123	1	2019	2019	NUM
ajst-20186	123	2	:	:	PUNCT
ajst-20186	123	3	1314	1314	NUM
ajst-20186	123	4	-	-	SYM
ajst-20186	123	5	1324	1324	NUM
ajst-20186	123	6	.	.	PUNCT
ajst-20186	124	1	[	[	X
ajst-20186	124	2	10	10	NUM
ajst-20186	124	3	]	]	SYM
ajst-20186	124	4	hu	hu	PROPN
ajst-20186	125	1	b	b	PROPN
ajst-20186	125	2	,	,	PUNCT
ajst-20186	125	3	zhou	zhou	PROPN
ajst-20186	125	4	p	p	PROPN
ajst-20186	125	5	,	,	PUNCT
ajst-20186	125	6	yu	yu	PROPN
ajst-20186	125	7	h	h	NOUN
ajst-20186	125	8	,	,	PUNCT
ajst-20186	125	9	et	et	PROPN
ajst-20186	125	10	al	al	PROPN
ajst-20186	125	11	.	.	PUNCT
ajst-20186	126	1	leanet	leanet	NOUN
ajst-20186	126	2	:	:	PUNCT
ajst-20186	126	3	lightweight	lightweight	ADJ
ajst-20186	126	4	u	u	ADJ
ajst-20186	126	5	-	-	ADJ
ajst-20186	126	6	shaped	shape	VERB
ajst-20186	126	7	architecture	architecture	NOUN
ajst-20186	126	8	for	for	ADP
ajst-20186	126	9	high	high	ADJ
ajst-20186	126	10	-	-	PUNCT
ajst-20186	126	11	performance	performance	NOUN
ajst-20186	126	12	skin	skin	NOUN
ajst-20186	126	13	cancer	cancer	NOUN
ajst-20186	126	14	image	image	NOUN
ajst-20186	126	15	segmentation[j	segmentation[j	PROPN
ajst-20186	126	16	]	]	PUNCT
ajst-20186	126	17	.	.	PUNCT
ajst-20186	127	1	computers	computer	NOUN
ajst-20186	127	2	in	in	ADP
ajst-20186	127	3	biology	biology	NOUN
ajst-20186	127	4	and	and	CCONJ
ajst-20186	127	5	medicine	medicine	NOUN
ajst-20186	127	6	,	,	PUNCT
ajst-20186	127	7	2024	2024	NUM
ajst-20186	127	8	,	,	PUNCT
ajst-20186	127	9	169	169	NUM
ajst-20186	127	10	:	:	SYM
ajst-20186	127	11	107919	107919	NUM
ajst-20186	127	12	.	.	PUNCT