id	sid	tid	token	lemma	pos
app01-10635	1	1	acta	acta	PROPN
app01-10635	1	2	polytechnica	polytechnica	PROPN
app01-10635	1	3	ctu	ctu	NOUN
app01-10635	1	4	proceedings	proceeding	NOUN
app01-10635	1	5	https://doi.org/10.14311/app.2025.52.0063	https://doi.org/10.14311/app.2025.52.0063	PROPN
app01-10635	1	6	acta	acta	PROPN
app01-10635	1	7	polytechnica	polytechnica	PROPN
app01-10635	1	8	ctu	ctu	NOUN
app01-10635	1	9	proceedings	proceeding	NOUN
app01-10635	1	10	52:63–68	52:63–68	NUM
app01-10635	1	11	,	,	PUNCT
app01-10635	1	12	2025	2025	NUM
app01-10635	1	13	©	©	ADP
app01-10635	1	14	2025	2025	NUM
app01-10635	1	15	the	the	DET
app01-10635	1	16	author(s	author(s	NOUN
app01-10635	1	17	)	)	PUNCT
app01-10635	1	18	.	.	PUNCT
app01-10635	2	1	licensed	license	VERB
app01-10635	2	2	under	under	ADP
app01-10635	2	3	a	a	DET
app01-10635	2	4	cc	cc	NOUN
app01-10635	2	5	-	-	PUNCT
app01-10635	2	6	by	by	ADP
app01-10635	2	7	4.0	4.0	NUM
app01-10635	2	8	licence	licence	NOUN
app01-10635	2	9	published	publish	VERB
app01-10635	2	10	by	by	ADP
app01-10635	2	11	the	the	DET
app01-10635	2	12	czech	czech	PROPN
app01-10635	2	13	technical	technical	PROPN
app01-10635	2	14	university	university	PROPN
app01-10635	2	15	in	in	ADP
app01-10635	2	16	prague	prague	PROPN
app01-10635	2	17	abrupt	abrupt	PROPN
app01-10635	2	18	change	change	NOUN
app01-10635	2	19	detection	detection	NOUN
app01-10635	2	20	in	in	ADP
app01-10635	2	21	railway	railway	NOUN
app01-10635	2	22	noise	noise	NOUN
app01-10635	2	23	data	datum	NOUN
app01-10635	2	24	jan	jan	PROPN
app01-10635	2	25	kruntoráda,∗	kruntoráda,∗	PROPN
app01-10635	2	26	,	,	PUNCT
app01-10635	2	27	tetiana	tetiana	PROPN
app01-10635	2	28	reznychenkob	reznychenkob	ADV
app01-10635	2	29	,	,	PUNCT
app01-10635	2	30	petr	petr	PROPN
app01-10635	2	31	červenkaa	červenkaa	VERB
app01-10635	2	32	a	a	DET
app01-10635	2	33	czech	czech	PROPN
app01-10635	2	34	technical	technical	PROPN
app01-10635	2	35	university	university	PROPN
app01-10635	2	36	in	in	ADP
app01-10635	2	37	prague	prague	PROPN
app01-10635	2	38	,	,	PUNCT
app01-10635	2	39	faculty	faculty	NOUN
app01-10635	2	40	of	of	ADP
app01-10635	2	41	transportation	transportation	NOUN
app01-10635	2	42	sciences	sciences	PROPN
app01-10635	2	43	,	,	PUNCT
app01-10635	2	44	department	department	NOUN
app01-10635	2	45	of	of	ADP
app01-10635	2	46	transport	transport	PROPN
app01-10635	2	47	engineering	engineering	PROPN
app01-10635	2	48	,	,	PUNCT
app01-10635	2	49	konviktská	konviktská	NOUN
app01-10635	2	50	20	20	NUM
app01-10635	2	51	,	,	PUNCT
app01-10635	2	52	110	110	NUM
app01-10635	2	53	00	00	NUM
app01-10635	2	54	prague	prague	PROPN
app01-10635	2	55	,	,	PUNCT
app01-10635	2	56	czech	czech	PROPN
app01-10635	2	57	republic	republic	PROPN
app01-10635	2	58	b	b	PROPN
app01-10635	2	59	czech	czech	PROPN
app01-10635	2	60	technical	technical	PROPN
app01-10635	2	61	university	university	PROPN
app01-10635	2	62	in	in	ADP
app01-10635	2	63	prague	prague	PROPN
app01-10635	2	64	,	,	PUNCT
app01-10635	2	65	faculty	faculty	NOUN
app01-10635	2	66	of	of	ADP
app01-10635	2	67	transportation	transportation	NOUN
app01-10635	2	68	sciences	sciences	PROPN
app01-10635	2	69	,	,	PUNCT
app01-10635	2	70	department	department	NOUN
app01-10635	2	71	of	of	ADP
app01-10635	2	72	applied	apply	VERB
app01-10635	2	73	mathematics	mathematic	NOUN
app01-10635	2	74	,	,	PUNCT
app01-10635	2	75	konviktská	konviktská	NOUN
app01-10635	2	76	20	20	NUM
app01-10635	2	77	,	,	PUNCT
app01-10635	2	78	110	110	NUM
app01-10635	2	79	00	00	NUM
app01-10635	2	80	prague	prague	PROPN
app01-10635	2	81	,	,	PUNCT
app01-10635	2	82	czech	czech	PROPN
app01-10635	2	83	republic	republic	NOUN
app01-10635	2	84	∗	∗	NOUN
app01-10635	2	85	corresponding	correspond	VERB
app01-10635	2	86	author	author	NOUN
app01-10635	2	87	:	:	PUNCT
app01-10635	2	88	kruntjan@fd.cvut.cz	kruntjan@fd.cvut.cz	PROPN
app01-10635	2	89	abstract	abstract	PROPN
app01-10635	2	90	.	.	PUNCT
app01-10635	3	1	current	current	ADJ
app01-10635	3	2	methods	method	NOUN
app01-10635	3	3	for	for	ADP
app01-10635	3	4	diagnosing	diagnose	VERB
app01-10635	3	5	the	the	DET
app01-10635	3	6	quality	quality	NOUN
app01-10635	3	7	of	of	ADP
app01-10635	3	8	the	the	DET
app01-10635	3	9	railway	railway	NOUN
app01-10635	3	10	superstructure	superstructure	NOUN
app01-10635	3	11	are	be	AUX
app01-10635	3	12	mainly	mainly	ADV
app01-10635	3	13	based	base	VERB
app01-10635	3	14	on	on	ADP
app01-10635	3	15	optical	optical	ADJ
app01-10635	3	16	sensors	sensor	NOUN
app01-10635	3	17	,	,	PUNCT
app01-10635	3	18	which	which	PRON
app01-10635	3	19	are	be	AUX
app01-10635	3	20	relatively	relatively	ADV
app01-10635	3	21	expensive	expensive	ADJ
app01-10635	3	22	compared	compare	VERB
app01-10635	3	23	to	to	ADP
app01-10635	3	24	acoustic	acoustic	ADJ
app01-10635	3	25	sensors	sensor	NOUN
app01-10635	3	26	.	.	PUNCT
app01-10635	4	1	as	as	ADP
app01-10635	4	2	part	part	NOUN
app01-10635	4	3	of	of	ADP
app01-10635	4	4	the	the	DET
app01-10635	4	5	hlukos	hlukos	PROPN
app01-10635	4	6	research	research	NOUN
app01-10635	4	7	project	project	NOUN
app01-10635	4	8	,	,	PUNCT
app01-10635	4	9	a	a	DET
app01-10635	4	10	pair	pair	NOUN
app01-10635	4	11	of	of	ADP
app01-10635	4	12	microphones	microphone	NOUN
app01-10635	4	13	is	be	AUX
app01-10635	4	14	installed	instal	VERB
app01-10635	4	15	near	near	ADP
app01-10635	4	16	the	the	DET
app01-10635	4	17	wheel	wheel	NOUN
app01-10635	4	18	-	-	PUNCT
app01-10635	4	19	rail	rail	NOUN
app01-10635	4	20	contact	contact	NOUN
app01-10635	4	21	point	point	NOUN
app01-10635	4	22	on	on	ADP
app01-10635	4	23	a	a	DET
app01-10635	4	24	diagnostic	diagnostic	ADJ
app01-10635	4	25	vehicle	vehicle	NOUN
app01-10635	4	26	of	of	ADP
app01-10635	4	27	the	the	DET
app01-10635	4	28	railway	railway	NOUN
app01-10635	4	29	administration	administration	NOUN
app01-10635	4	30	(	(	PUNCT
app01-10635	4	31	czech	czech	ADJ
app01-10635	4	32	railway	railway	NOUN
app01-10635	4	33	infrastructure	infrastructure	NOUN
app01-10635	4	34	manager	manager	NOUN
app01-10635	4	35	)	)	PUNCT
app01-10635	4	36	.	.	PUNCT
app01-10635	5	1	the	the	DET
app01-10635	5	2	research	research	NOUN
app01-10635	5	3	task	task	NOUN
app01-10635	5	4	is	be	AUX
app01-10635	5	5	to	to	PART
app01-10635	5	6	detect	detect	VERB
app01-10635	5	7	when	when	SCONJ
app01-10635	5	8	the	the	DET
app01-10635	5	9	sound	sound	ADJ
app01-10635	5	10	level	level	NOUN
app01-10635	5	11	changes	change	NOUN
app01-10635	5	12	significantly	significantly	ADV
app01-10635	5	13	.	.	PUNCT
app01-10635	6	1	a	a	DET
app01-10635	6	2	likelihood	likelihood	NOUN
app01-10635	6	3	ratio	ratio	NOUN
app01-10635	6	4	method	method	NOUN
app01-10635	6	5	has	have	AUX
app01-10635	6	6	been	be	AUX
app01-10635	6	7	used	use	VERB
app01-10635	6	8	in	in	ADP
app01-10635	6	9	this	this	DET
app01-10635	6	10	paper	paper	NOUN
app01-10635	6	11	to	to	PART
app01-10635	6	12	detect	detect	VERB
app01-10635	6	13	abrupt	abrupt	ADJ
app01-10635	6	14	changes	change	NOUN
app01-10635	6	15	,	,	PUNCT
app01-10635	6	16	which	which	PRON
app01-10635	6	17	is	be	AUX
app01-10635	6	18	a	a	DET
app01-10635	6	19	current	current	ADJ
app01-10635	6	20	scientific	scientific	ADJ
app01-10635	6	21	topic	topic	NOUN
app01-10635	6	22	.	.	PUNCT
app01-10635	7	1	experiments	experiment	NOUN
app01-10635	7	2	with	with	ADP
app01-10635	7	3	different	different	ADJ
app01-10635	7	4	input	input	NOUN
app01-10635	7	5	thresholds	threshold	NOUN
app01-10635	7	6	are	be	AUX
app01-10635	7	7	performed	perform	VERB
app01-10635	7	8	on	on	ADP
app01-10635	7	9	a	a	DET
app01-10635	7	10	sample	sample	NOUN
app01-10635	7	11	of	of	ADP
app01-10635	7	12	250	250	NUM
app01-10635	7	13	m	m	NOUN
app01-10635	7	14	of	of	ADP
app01-10635	7	15	track	track	NOUN
app01-10635	7	16	data	datum	NOUN
app01-10635	7	17	.	.	PUNCT
app01-10635	8	1	initial	initial	ADJ
app01-10635	8	2	experimental	experimental	ADJ
app01-10635	8	3	results	result	NOUN
app01-10635	8	4	show	show	VERB
app01-10635	8	5	that	that	SCONJ
app01-10635	8	6	this	this	DET
app01-10635	8	7	method	method	NOUN
app01-10635	8	8	is	be	AUX
app01-10635	8	9	meaningfully	meaningfully	ADV
app01-10635	8	10	able	able	ADJ
app01-10635	8	11	to	to	PART
app01-10635	8	12	detect	detect	VERB
app01-10635	8	13	locations	location	NOUN
app01-10635	8	14	of	of	ADP
app01-10635	8	15	abrupt	abrupt	ADJ
app01-10635	8	16	changes	change	NOUN
app01-10635	8	17	with	with	ADP
app01-10635	8	18	input	input	NOUN
app01-10635	8	19	threshold	threshold	NOUN
app01-10635	8	20	values	value	NOUN
app01-10635	8	21	h	h	NOUN
app01-10635	8	22	=	=	NOUN
app01-10635	8	23	4.58	4.58	NUM
app01-10635	8	24	and	and	CCONJ
app01-10635	8	25	number	number	NOUN
app01-10635	8	26	of	of	ADP
app01-10635	8	27	steps	step	NOUN
app01-10635	8	28	from	from	ADP
app01-10635	8	29	n	n	NOUN
app01-10635	8	30	=	=	SYM
app01-10635	8	31	5	5	NUM
app01-10635	8	32	to	to	ADP
app01-10635	8	33	n	n	NOUN
app01-10635	8	34	=	=	SYM
app01-10635	8	35	40	40	NUM
app01-10635	8	36	.	.	PUNCT
app01-10635	9	1	keywords	keyword	NOUN
app01-10635	9	2	:	:	PUNCT
app01-10635	9	3	abrupt	abrupt	ADJ
app01-10635	9	4	change	change	NOUN
app01-10635	9	5	,	,	PUNCT
app01-10635	9	6	change	change	NOUN
app01-10635	9	7	detection	detection	NOUN
app01-10635	9	8	,	,	PUNCT
app01-10635	9	9	likelihood	likelihood	NOUN
app01-10635	9	10	ratio	ratio	NOUN
app01-10635	9	11	,	,	PUNCT
app01-10635	9	12	railway	railway	NOUN
app01-10635	9	13	diagnostics	diagnostic	NOUN
app01-10635	9	14	,	,	PUNCT
app01-10635	9	15	railway	railway	NOUN
app01-10635	9	16	noise	noise	NOUN
app01-10635	9	17	,	,	PUNCT
app01-10635	9	18	wheel	wheel	NOUN
app01-10635	9	19	-	-	PUNCT
app01-10635	9	20	rail	rail	NOUN
app01-10635	9	21	contact	contact	NOUN
app01-10635	9	22	.	.	PUNCT
app01-10635	10	1	1	1	X
app01-10635	10	2	.	.	X
app01-10635	10	3	introduction	introduction	NOUN
app01-10635	10	4	the	the	DET
app01-10635	10	5	last	last	ADJ
app01-10635	10	6	decades	decade	NOUN
app01-10635	10	7	have	have	AUX
app01-10635	10	8	been	be	AUX
app01-10635	10	9	marked	mark	VERB
app01-10635	10	10	by	by	ADP
app01-10635	10	11	the	the	DET
app01-10635	10	12	development	development	NOUN
app01-10635	10	13	of	of	ADP
app01-10635	10	14	technological	technological	ADJ
app01-10635	10	15	processes	process	NOUN
app01-10635	10	16	and	and	CCONJ
app01-10635	10	17	sophisticated	sophisticated	ADJ
app01-10635	10	18	sensors	sensor	NOUN
app01-10635	10	19	,	,	PUNCT
app01-10635	10	20	followed	follow	VERB
app01-10635	10	21	by	by	ADP
app01-10635	10	22	the	the	DET
app01-10635	10	23	need	need	NOUN
app01-10635	10	24	for	for	ADP
app01-10635	10	25	sophisticated	sophisticated	ADJ
app01-10635	10	26	information	information	NOUN
app01-10635	10	27	processing	processing	NOUN
app01-10635	10	28	systems	system	NOUN
app01-10635	10	29	.	.	PUNCT
app01-10635	11	1	addressing	address	VERB
app01-10635	11	2	these	these	DET
app01-10635	11	3	issues	issue	NOUN
app01-10635	11	4	is	be	AUX
app01-10635	11	5	important	important	ADJ
app01-10635	11	6	for	for	ADP
app01-10635	11	7	a	a	DET
app01-10635	11	8	number	number	NOUN
app01-10635	11	9	of	of	ADP
app01-10635	11	10	reasons	reason	NOUN
app01-10635	11	11	,	,	PUNCT
app01-10635	11	12	particularly	particularly	ADV
app01-10635	11	13	safety	safety	NOUN
app01-10635	11	14	,	,	PUNCT
app01-10635	11	15	environmental	environmental	ADJ
app01-10635	11	16	and	and	CCONJ
app01-10635	11	17	economic	economic	ADJ
app01-10635	11	18	.	.	PUNCT
app01-10635	12	1	the	the	DET
app01-10635	12	2	large	large	ADJ
app01-10635	12	3	amount	amount	NOUN
app01-10635	12	4	of	of	ADP
app01-10635	12	5	data	datum	NOUN
app01-10635	12	6	from	from	ADP
app01-10635	12	7	a	a	DET
app01-10635	12	8	wide	wide	ADJ
app01-10635	12	9	range	range	NOUN
app01-10635	12	10	of	of	ADP
app01-10635	12	11	sensors	sensor	NOUN
app01-10635	12	12	means	mean	VERB
app01-10635	12	13	that	that	SCONJ
app01-10635	12	14	algorithms	algorithm	NOUN
app01-10635	12	15	must	must	AUX
app01-10635	12	16	be	be	AUX
app01-10635	12	17	found	find	VERB
app01-10635	12	18	or	or	CCONJ
app01-10635	12	19	developed	develop	VERB
app01-10635	12	20	to	to	PART
app01-10635	12	21	analyse	analyse	VERB
app01-10635	12	22	the	the	DET
app01-10635	12	23	information	information	NOUN
app01-10635	12	24	.	.	PUNCT
app01-10635	13	1	the	the	DET
app01-10635	13	2	core	core	NOUN
app01-10635	13	3	of	of	ADP
app01-10635	13	4	the	the	DET
app01-10635	13	5	interest	interest	NOUN
app01-10635	13	6	is	be	AUX
app01-10635	13	7	the	the	DET
app01-10635	13	8	detection	detection	NOUN
app01-10635	13	9	of	of	ADP
app01-10635	13	10	one	one	NUM
app01-10635	13	11	or	or	CCONJ
app01-10635	13	12	more	more	ADV
app01-10635	13	13	abrupt	abrupt	ADJ
app01-10635	13	14	changes	change	NOUN
app01-10635	13	15	in	in	ADP
app01-10635	13	16	some	some	DET
app01-10635	13	17	characteristic	characteristic	NOUN
app01-10635	13	18	of	of	ADP
app01-10635	13	19	the	the	DET
app01-10635	13	20	system	system	NOUN
app01-10635	13	21	under	under	ADP
app01-10635	13	22	consideration	consideration	NOUN
app01-10635	13	23	.	.	PUNCT
app01-10635	14	1	an	an	DET
app01-10635	14	2	abrupt	abrupt	ADJ
app01-10635	14	3	change	change	NOUN
app01-10635	14	4	is	be	AUX
app01-10635	14	5	considered	consider	VERB
app01-10635	14	6	to	to	PART
app01-10635	14	7	be	be	AUX
app01-10635	14	8	any	any	DET
app01-10635	14	9	change	change	NOUN
app01-10635	14	10	in	in	ADP
app01-10635	14	11	system	system	NOUN
app01-10635	14	12	parameters	parameter	NOUN
app01-10635	14	13	that	that	PRON
app01-10635	14	14	occurs	occur	VERB
app01-10635	14	15	either	either	CCONJ
app01-10635	14	16	immediately	immediately	ADV
app01-10635	14	17	or	or	CCONJ
app01-10635	14	18	at	at	ADV
app01-10635	14	19	least	least	ADJ
app01-10635	14	20	very	very	ADV
app01-10635	14	21	quickly	quickly	ADV
app01-10635	14	22	relative	relative	ADJ
app01-10635	14	23	to	to	ADP
app01-10635	14	24	the	the	DET
app01-10635	14	25	measurement	measurement	NOUN
app01-10635	14	26	sampling	sampling	NOUN
app01-10635	14	27	period	period	NOUN
app01-10635	14	28	used	use	VERB
app01-10635	14	29	.	.	PUNCT
app01-10635	15	1	abrupt	abrupt	ADJ
app01-10635	15	2	changes	change	NOUN
app01-10635	15	3	certainly	certainly	ADV
app01-10635	15	4	do	do	AUX
app01-10635	15	5	not	not	PART
app01-10635	15	6	refer	refer	VERB
app01-10635	15	7	to	to	ADP
app01-10635	15	8	changes	change	NOUN
app01-10635	15	9	of	of	ADP
app01-10635	15	10	large	large	ADJ
app01-10635	15	11	magnitude	magnitude	NOUN
app01-10635	15	12	;	;	PUNCT
app01-10635	15	13	on	on	ADP
app01-10635	15	14	the	the	DET
app01-10635	15	15	contrary	contrary	NOUN
app01-10635	15	16	,	,	PUNCT
app01-10635	15	17	in	in	ADP
app01-10635	15	18	most	most	ADJ
app01-10635	15	19	applications	application	NOUN
app01-10635	15	20	the	the	DET
app01-10635	15	21	main	main	ADJ
app01-10635	15	22	problem	problem	NOUN
app01-10635	15	23	is	be	AUX
app01-10635	15	24	the	the	DET
app01-10635	15	25	detection	detection	NOUN
app01-10635	15	26	of	of	ADP
app01-10635	15	27	small	small	ADJ
app01-10635	15	28	changes	change	NOUN
app01-10635	15	29	.	.	PUNCT
app01-10635	16	1	moreover	moreover	ADV
app01-10635	16	2	,	,	PUNCT
app01-10635	16	3	in	in	ADP
app01-10635	16	4	some	some	DET
app01-10635	16	5	specific	specific	ADJ
app01-10635	16	6	cases	case	NOUN
app01-10635	16	7	,	,	PUNCT
app01-10635	16	8	early	early	ADJ
app01-10635	16	9	warning	warning	NOUN
app01-10635	16	10	of	of	ADP
app01-10635	16	11	small	small	ADJ
app01-10635	16	12	(	(	PUNCT
app01-10635	16	13	and	and	CCONJ
app01-10635	16	14	not	not	PART
app01-10635	16	15	necessarily	necessarily	ADV
app01-10635	16	16	fast	fast	VERB
app01-10635	16	17	)	)	PUNCT
app01-10635	16	18	changes	change	NOUN
app01-10635	16	19	is	be	AUX
app01-10635	16	20	essential	essential	ADJ
app01-10635	16	21	to	to	PART
app01-10635	16	22	avoid	avoid	VERB
app01-10635	16	23	economic	economic	ADJ
app01-10635	16	24	or	or	CCONJ
app01-10635	16	25	even	even	ADV
app01-10635	16	26	fatal	fatal	ADJ
app01-10635	16	27	consequences	consequence	NOUN
app01-10635	16	28	,	,	PUNCT
app01-10635	16	29	such	such	ADJ
app01-10635	16	30	as	as	ADP
app01-10635	16	31	small	small	ADJ
app01-10635	16	32	malfunctions	malfunction	NOUN
app01-10635	16	33	in	in	ADP
app01-10635	16	34	the	the	DET
app01-10635	16	35	sensors	sensor	NOUN
app01-10635	16	36	of	of	ADP
app01-10635	16	37	aircraft	aircraft	NOUN
app01-10635	16	38	navigation	navigation	NOUN
app01-10635	16	39	systems	system	NOUN
app01-10635	16	40	or	or	CCONJ
app01-10635	16	41	small	small	ADJ
app01-10635	16	42	variations	variation	NOUN
app01-10635	16	43	in	in	ADP
app01-10635	16	44	the	the	DET
app01-10635	16	45	geometric	geometric	ADJ
app01-10635	16	46	position	position	NOUN
app01-10635	16	47	of	of	ADP
app01-10635	16	48	the	the	DET
app01-10635	16	49	track	track	NOUN
app01-10635	16	50	[	[	X
app01-10635	16	51	1	1	NUM
app01-10635	16	52	]	]	PUNCT
app01-10635	16	53	.	.	PUNCT
app01-10635	17	1	the	the	DET
app01-10635	17	2	quality	quality	NOUN
app01-10635	17	3	of	of	ADP
app01-10635	17	4	track	track	NOUN
app01-10635	17	5	geometry	geometry	NOUN
app01-10635	17	6	,	,	PUNCT
app01-10635	17	7	respect	respect	NOUN
app01-10635	17	8	of	of	ADP
app01-10635	17	9	clearance	clearance	NOUN
app01-10635	17	10	profile	profile	NOUN
app01-10635	17	11	and	and	CCONJ
app01-10635	17	12	other	other	ADJ
app01-10635	17	13	parameters	parameter	NOUN
app01-10635	17	14	necessary	necessary	ADJ
app01-10635	17	15	for	for	ADP
app01-10635	17	16	safe	safe	ADJ
app01-10635	17	17	railway	railway	NOUN
app01-10635	17	18	operation	operation	NOUN
app01-10635	17	19	are	be	AUX
app01-10635	17	20	continuously	continuously	ADV
app01-10635	17	21	monitored	monitor	VERB
app01-10635	17	22	and	and	CCONJ
app01-10635	17	23	evaluated	evaluate	VERB
app01-10635	17	24	by	by	ADP
app01-10635	17	25	infrastructure	infrastructure	NOUN
app01-10635	17	26	managers	manager	NOUN
app01-10635	17	27	.	.	PUNCT
app01-10635	18	1	one	one	NUM
app01-10635	18	2	of	of	ADP
app01-10635	18	3	the	the	DET
app01-10635	18	4	objectives	objective	NOUN
app01-10635	18	5	of	of	ADP
app01-10635	18	6	the	the	DET
app01-10635	18	7	hlukos	hlukos	PROPN
app01-10635	18	8	research	research	NOUN
app01-10635	18	9	project	project	NOUN
app01-10635	18	10	is	be	AUX
app01-10635	18	11	to	to	PART
app01-10635	18	12	determine	determine	VERB
app01-10635	18	13	whether	whether	SCONJ
app01-10635	18	14	abrupt	abrupt	ADJ
app01-10635	18	15	changes	change	NOUN
app01-10635	18	16	in	in	ADP
app01-10635	18	17	rolling	rolling	ADJ
app01-10635	18	18	noise	noise	NOUN
app01-10635	18	19	recordings	recording	NOUN
app01-10635	18	20	at	at	ADP
app01-10635	18	21	the	the	DET
app01-10635	18	22	wheelrail	wheelrail	NOUN
app01-10635	18	23	contact	contact	NOUN
app01-10635	18	24	point	point	NOUN
app01-10635	18	25	can	can	AUX
app01-10635	18	26	be	be	AUX
app01-10635	18	27	detected	detect	VERB
app01-10635	18	28	,	,	PUNCT
app01-10635	18	29	and	and	CCONJ
app01-10635	18	30	to	to	PART
app01-10635	18	31	use	use	VERB
app01-10635	18	32	these	these	DET
app01-10635	18	33	changes	change	NOUN
app01-10635	18	34	to	to	PART
app01-10635	18	35	warn	warn	VERB
app01-10635	18	36	of	of	ADP
app01-10635	18	37	possible	possible	ADJ
app01-10635	18	38	local	local	ADJ
app01-10635	18	39	degradation	degradation	NOUN
app01-10635	18	40	(	(	PUNCT
app01-10635	18	41	defects	defect	NOUN
app01-10635	18	42	)	)	PUNCT
app01-10635	18	43	of	of	ADP
app01-10635	18	44	the	the	DET
app01-10635	18	45	railway	railway	NOUN
app01-10635	18	46	superstructure	superstructure	NOUN
app01-10635	18	47	.	.	PUNCT
app01-10635	19	1	2	2	X
app01-10635	19	2	.	.	X
app01-10635	19	3	theoretical	theoretical	ADJ
app01-10635	19	4	background	background	NOUN
app01-10635	19	5	abrupt	abrupt	ADJ
app01-10635	19	6	change	change	NOUN
app01-10635	19	7	detection	detection	NOUN
app01-10635	19	8	in	in	ADP
app01-10635	19	9	noisy	noisy	ADJ
app01-10635	19	10	signals	signal	NOUN
app01-10635	19	11	is	be	AUX
app01-10635	19	12	a	a	DET
app01-10635	19	13	critical	critical	ADJ
app01-10635	19	14	area	area	NOUN
app01-10635	19	15	of	of	ADP
app01-10635	19	16	research	research	NOUN
app01-10635	19	17	that	that	PRON
app01-10635	19	18	spans	span	VERB
app01-10635	19	19	various	various	ADJ
app01-10635	19	20	fields	field	NOUN
app01-10635	19	21	,	,	PUNCT
app01-10635	19	22	including	include	VERB
app01-10635	19	23	signal	signal	NOUN
app01-10635	19	24	processing	processing	NOUN
app01-10635	19	25	,	,	PUNCT
app01-10635	19	26	climate	climate	NOUN
app01-10635	19	27	science	science	NOUN
app01-10635	19	28	,	,	PUNCT
app01-10635	19	29	and	and	CCONJ
app01-10635	19	30	power	power	NOUN
app01-10635	19	31	systems	system	NOUN
app01-10635	19	32	.	.	PUNCT
app01-10635	20	1	the	the	DET
app01-10635	20	2	methods	method	NOUN
app01-10635	20	3	employed	employ	VERB
app01-10635	20	4	for	for	ADP
app01-10635	20	5	detecting	detect	VERB
app01-10635	20	6	these	these	DET
app01-10635	20	7	changes	change	NOUN
app01-10635	20	8	can	can	AUX
app01-10635	20	9	be	be	AUX
app01-10635	20	10	broadly	broadly	ADV
app01-10635	20	11	categorized	categorize	VERB
app01-10635	20	12	into	into	ADP
app01-10635	20	13	wavelet	wavelet	NOUN
app01-10635	20	14	-	-	PUNCT
app01-10635	20	15	based	base	VERB
app01-10635	20	16	techniques	technique	NOUN
app01-10635	20	17	,	,	PUNCT
app01-10635	20	18	statistical	statistical	ADJ
app01-10635	20	19	approaches	approach	NOUN
app01-10635	20	20	,	,	PUNCT
app01-10635	20	21	and	and	CCONJ
app01-10635	20	22	machine	machine	NOUN
app01-10635	20	23	learning	learning	NOUN
app01-10635	20	24	methods	method	NOUN
app01-10635	20	25	.	.	PUNCT
app01-10635	21	1	each	each	PRON
app01-10635	21	2	of	of	ADP
app01-10635	21	3	these	these	DET
app01-10635	21	4	methodologies	methodology	NOUN
app01-10635	21	5	offers	offer	VERB
app01-10635	21	6	unique	unique	ADJ
app01-10635	21	7	advantages	advantage	NOUN
app01-10635	21	8	and	and	CCONJ
app01-10635	21	9	is	be	AUX
app01-10635	21	10	suitable	suitable	ADJ
app01-10635	21	11	for	for	ADP
app01-10635	21	12	different	different	ADJ
app01-10635	21	13	types	type	NOUN
app01-10635	21	14	of	of	ADP
app01-10635	21	15	signals	signal	NOUN
app01-10635	21	16	and	and	CCONJ
app01-10635	21	17	noise	noise	NOUN
app01-10635	21	18	characteristics	characteristic	NOUN
app01-10635	21	19	.	.	PUNCT
app01-10635	22	1	2.1	2.1	NUM
app01-10635	22	2	.	.	PUNCT
app01-10635	23	1	current	current	ADJ
app01-10635	23	2	methods	method	NOUN
app01-10635	23	3	used	use	VERB
app01-10635	23	4	wavelet	wavelet	NOUN
app01-10635	23	5	transforms	transform	NOUN
app01-10635	23	6	have	have	AUX
app01-10635	23	7	emerged	emerge	VERB
app01-10635	23	8	as	as	ADP
app01-10635	23	9	a	a	DET
app01-10635	23	10	powerful	powerful	ADJ
app01-10635	23	11	tool	tool	NOUN
app01-10635	23	12	for	for	ADP
app01-10635	23	13	detecting	detect	VERB
app01-10635	23	14	abrupt	abrupt	ADJ
app01-10635	23	15	changes	change	NOUN
app01-10635	23	16	in	in	ADP
app01-10635	23	17	signals	signal	NOUN
app01-10635	23	18	,	,	PUNCT
app01-10635	23	19	particularly	particularly	ADV
app01-10635	23	20	in	in	ADP
app01-10635	23	21	the	the	DET
app01-10635	23	22	presence	presence	NOUN
app01-10635	23	23	of	of	ADP
app01-10635	23	24	noise	noise	NOUN
app01-10635	23	25	.	.	PUNCT
app01-10635	24	1	the	the	DET
app01-10635	24	2	wavelet	wavelet	NOUN
app01-10635	24	3	transform	transform	NOUN
app01-10635	24	4	allows	allow	VERB
app01-10635	24	5	for	for	ADP
app01-10635	24	6	the	the	DET
app01-10635	24	7	decomposition	decomposition	NOUN
app01-10635	24	8	of	of	ADP
app01-10635	24	9	a	a	DET
app01-10635	24	10	signal	signal	NOUN
app01-10635	24	11	into	into	ADP
app01-10635	24	12	its	its	PRON
app01-10635	24	13	constituent	constituent	ADJ
app01-10635	24	14	components	component	NOUN
app01-10635	24	15	at	at	ADP
app01-10635	24	16	various	various	ADJ
app01-10635	24	17	scales	scale	NOUN
app01-10635	24	18	,	,	PUNCT
app01-10635	24	19	making	make	VERB
app01-10635	24	20	it	it	PRON
app01-10635	24	21	easier	easy	ADJ
app01-10635	24	22	to	to	PART
app01-10635	24	23	identify	identify	VERB
app01-10635	24	24	discontinuities	discontinuity	NOUN
app01-10635	24	25	or	or	CCONJ
app01-10635	24	26	abrupt	abrupt	ADJ
app01-10635	24	27	changes	change	NOUN
app01-10635	24	28	.	.	PUNCT
app01-10635	25	1	for	for	ADP
app01-10635	25	2	instance	instance	NOUN
app01-10635	25	3	,	,	PUNCT
app01-10635	25	4	ukil	ukil	PROPN
app01-10635	25	5	and	and	CCONJ
app01-10635	25	6	živanović	živanović	NOUN
app01-10635	26	1	[	[	X
app01-10635	26	2	2	2	X
app01-10635	26	3	]	]	PUNCT
app01-10635	26	4	demonstrated	demonstrate	VERB
app01-10635	26	5	the	the	DET
app01-10635	26	6	effectiveness	effectiveness	NOUN
app01-10635	26	7	of	of	ADP
app01-10635	26	8	using	use	VERB
app01-10635	26	9	an	an	DET
app01-10635	26	10	adjusted	adjust	VERB
app01-10635	26	11	haar	haar	NOUN
app01-10635	26	12	wavelet	wavelet	NOUN
app01-10635	26	13	for	for	ADP
app01-10635	26	14	segmenting	segment	VERB
app01-10635	26	15	power	power	NOUN
app01-10635	26	16	system	system	NOUN
app01-10635	26	17	disturbance	disturbance	NOUN
app01-10635	26	18	signals	signal	NOUN
app01-10635	26	19	into	into	ADP
app01-10635	26	20	event	event	NOUN
app01-10635	26	21	-	-	PUNCT
app01-10635	26	22	specific	specific	ADJ
app01-10635	26	23	sections	section	NOUN
app01-10635	26	24	,	,	PUNCT
app01-10635	26	25	highlighting	highlight	VERB
app01-10635	26	26	the	the	DET
app01-10635	26	27	method	method	NOUN
app01-10635	26	28	’s	’s	PART
app01-10635	26	29	robustness	robustness	NOUN
app01-10635	26	30	in	in	ADP
app01-10635	26	31	noisy	noisy	ADJ
app01-10635	26	32	environments	environment	NOUN
app01-10635	26	33	.	.	PUNCT
app01-10635	27	1	in	in	ADP
app01-10635	27	2	addition	addition	NOUN
app01-10635	27	3	to	to	ADP
app01-10635	27	4	wavelet	wavelet	NOUN
app01-10635	27	5	methods	method	NOUN
app01-10635	27	6	,	,	PUNCT
app01-10635	27	7	statistical	statistical	ADJ
app01-10635	27	8	techniques	technique	NOUN
app01-10635	27	9	such	such	ADJ
app01-10635	27	10	as	as	ADP
app01-10635	27	11	the	the	DET
app01-10635	27	12	kolmogorov	kolmogorov	ADJ
app01-10635	27	13	-	-	PUNCT
app01-10635	27	14	smirnov	smirnov	ADJ
app01-10635	27	15	statistic	statistic	NOUN
app01-10635	27	16	have	have	AUX
app01-10635	27	17	been	be	AUX
app01-10635	27	18	utilized	utilize	VERB
app01-10635	27	19	for	for	ADP
app01-10635	27	20	abrupt	abrupt	ADJ
app01-10635	27	21	change	change	NOUN
app01-10635	27	22	detection	detection	NOUN
app01-10635	27	23	.	.	PUNCT
app01-10635	28	1	qi	qi	PROPN
app01-10635	28	2	et	et	PROPN
app01-10635	28	3	al	al	PROPN
app01-10635	28	4	.	.	PUNCT
app01-10635	29	1	[	[	X
app01-10635	29	2	3	3	X
app01-10635	29	3	]	]	PUNCT
app01-10635	29	4	proposed	propose	VERB
app01-10635	29	5	a	a	DET
app01-10635	29	6	fast	fast	ADJ
app01-10635	29	7	framework	framework	NOUN
app01-10635	29	8	based	base	VERB
app01-10635	29	9	on	on	ADP
app01-10635	29	10	binary	binary	ADJ
app01-10635	29	11	search	search	NOUN
app01-10635	29	12	trees	tree	NOUN
app01-10635	29	13	and	and	CCONJ
app01-10635	29	14	the	the	DET
app01-10635	29	15	kolmogorov	kolmogorov	PROPN
app01-10635	29	16	statistic	statistic	NOUN
app01-10635	29	17	to	to	PART
app01-10635	29	18	identify	identify	VERB
app01-10635	29	19	changes	change	NOUN
app01-10635	29	20	in	in	ADP
app01-10635	29	21	the	the	DET
app01-10635	29	22	statistical	statistical	ADJ
app01-10635	29	23	properties	property	NOUN
app01-10635	29	24	of	of	ADP
app01-10635	29	25	signal	signal	ADJ
app01-10635	29	26	series	series	NOUN
app01-10635	29	27	,	,	PUNCT
app01-10635	29	28	which	which	PRON
app01-10635	29	29	are	be	AUX
app01-10635	29	30	indicative	indicative	ADJ
app01-10635	29	31	of	of	ADP
app01-10635	29	32	qualitative	qualitative	ADJ
app01-10635	29	33	transitions	transition	NOUN
app01-10635	29	34	in	in	ADP
app01-10635	29	35	the	the	DET
app01-10635	29	36	underlying	underlie	VERB
app01-10635	29	37	data	data	NOUN
app01-10635	29	38	generation	generation	NOUN
app01-10635	29	39	mechanism	mechanism	NOUN
app01-10635	29	40	.	.	PUNCT
app01-10635	30	1	this	this	DET
app01-10635	30	2	approach	approach	NOUN
app01-10635	30	3	is	be	AUX
app01-10635	30	4	more	more	ADV
app01-10635	30	5	efficient	efficient	ADJ
app01-10635	30	6	due	due	ADP
app01-10635	30	7	to	to	ADP
app01-10635	30	8	the	the	DET
app01-10635	30	9	shortest	short	ADJ
app01-10635	30	10	computation	computation	NOUN
app01-10635	30	11	time	time	NOUN
app01-10635	30	12	,	,	PUNCT
app01-10635	30	13	the	the	DET
app01-10635	30	14	highest	high	ADJ
app01-10635	30	15	hit	hit	VERB
app01-10635	30	16	rate	rate	NOUN
app01-10635	30	17	and	and	CCONJ
app01-10635	30	18	accuracy	accuracy	NOUN
app01-10635	30	19	than	than	SCONJ
app01-10635	30	20	compared	compare	VERB
app01-10635	30	21	conventional	conventional	ADJ
app01-10635	30	22	methods	method	NOUN
app01-10635	30	23	kolmogorov	kolmogorov	ADJ
app01-10635	30	24	-	-	PUNCT
app01-10635	30	25	smirnov	smirnov	PROPN
app01-10635	30	26	statistic	statistic	NOUN
app01-10635	30	27	,	,	PUNCT
app01-10635	30	28	t	t	PROPN
app01-10635	30	29	-	-	PUNCT
app01-10635	30	30	statistic	statistic	NOUN
app01-10635	30	31	and	and	CCONJ
app01-10635	30	32	63	63	NUM
app01-10635	30	33	https://doi.org/10.14311/app.2025.52.0063	https://doi.org/10.14311/app.2025.52.0063	ADJ
app01-10635	30	34	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
app01-10635	30	35	https://www.cvut.cz/en	https://www.cvut.cz/en	PROPN
app01-10635	30	36	j.	j.	PROPN
app01-10635	30	37	kruntorád	kruntorád	PROPN
app01-10635	30	38	,	,	PUNCT
app01-10635	30	39	t.	t.	PROPN
app01-10635	30	40	reznychenko	reznychenko	PROPN
app01-10635	30	41	,	,	PUNCT
app01-10635	30	42	p.	p.	PROPN
app01-10635	30	43	červenka	červenka	PROPN
app01-10635	31	1	acta	acta	PROPN
app01-10635	31	2	polytechnica	polytechnica	PROPN
app01-10635	31	3	ctu	ctu	NOUN
app01-10635	31	4	proceedings	proceeding	NOUN
app01-10635	31	5	singular	singular	NOUN
app01-10635	31	6	-	-	PUNCT
app01-10635	31	7	spectrum	spectrum	NOUN
app01-10635	31	8	analyses	analysis	NOUN
app01-10635	31	9	which	which	PRON
app01-10635	31	10	was	be	AUX
app01-10635	31	11	tested	test	VERB
app01-10635	31	12	on	on	ADP
app01-10635	31	13	real	real	ADJ
app01-10635	31	14	eeg	eeg	NOUN
app01-10635	31	15	recordings	recording	NOUN
app01-10635	31	16	.	.	PUNCT
app01-10635	32	1	another	another	DET
app01-10635	32	2	significant	significant	ADJ
app01-10635	32	3	method	method	NOUN
app01-10635	32	4	for	for	ADP
app01-10635	32	5	detecting	detect	VERB
app01-10635	32	6	abrupt	abrupt	ADJ
app01-10635	32	7	changes	change	NOUN
app01-10635	32	8	is	be	AUX
app01-10635	32	9	the	the	DET
app01-10635	32	10	use	use	NOUN
app01-10635	32	11	of	of	ADP
app01-10635	32	12	bayesian	bayesian	NOUN
app01-10635	32	13	approaches	approach	NOUN
app01-10635	32	14	,	,	PUNCT
app01-10635	32	15	particularly	particularly	ADV
app01-10635	32	16	in	in	ADP
app01-10635	32	17	online	online	ADJ
app01-10635	32	18	applications	application	NOUN
app01-10635	32	19	such	such	ADJ
app01-10635	32	20	as	as	ADP
app01-10635	32	21	automatic	automatic	ADJ
app01-10635	32	22	speech	speech	NOUN
app01-10635	32	23	recognition	recognition	NOUN
app01-10635	32	24	(	(	PUNCT
app01-10635	32	25	asr	asr	PROPN
app01-10635	32	26	)	)	PUNCT
app01-10635	32	27	.	.	PUNCT
app01-10635	33	1	chowdhury	chowdhury	PROPN
app01-10635	33	2	et	et	PROPN
app01-10635	33	3	al	al	PROPN
app01-10635	33	4	.	.	PUNCT
app01-10635	34	1	[	[	X
app01-10635	34	2	4	4	X
app01-10635	34	3	]	]	PUNCT
app01-10635	34	4	emphasized	emphasize	VERB
app01-10635	34	5	the	the	DET
app01-10635	34	6	importance	importance	NOUN
app01-10635	34	7	of	of	ADP
app01-10635	34	8	developing	develop	VERB
app01-10635	34	9	noise	noise	NOUN
app01-10635	34	10	estimation	estimation	NOUN
app01-10635	34	11	algorithms	algorithm	NOUN
app01-10635	34	12	that	that	PRON
app01-10635	34	13	continuously	continuously	ADV
app01-10635	34	14	track	track	VERB
app01-10635	34	15	and	and	CCONJ
app01-10635	34	16	estimate	estimate	VERB
app01-10635	34	17	noise	noise	NOUN
app01-10635	34	18	levels	level	NOUN
app01-10635	34	19	,	,	PUNCT
app01-10635	34	20	enabling	enable	VERB
app01-10635	34	21	the	the	DET
app01-10635	34	22	detection	detection	NOUN
app01-10635	34	23	of	of	ADP
app01-10635	34	24	abrupt	abrupt	ADJ
app01-10635	34	25	changes	change	NOUN
app01-10635	34	26	in	in	ADP
app01-10635	34	27	the	the	DET
app01-10635	34	28	noise	noise	NOUN
app01-10635	34	29	spectrum	spectrum	NOUN
app01-10635	34	30	.	.	PUNCT
app01-10635	35	1	this	this	DET
app01-10635	35	2	adaptability	adaptability	NOUN
app01-10635	35	3	is	be	AUX
app01-10635	35	4	crucial	crucial	ADJ
app01-10635	35	5	in	in	ADP
app01-10635	35	6	real	real	ADJ
app01-10635	35	7	-	-	PUNCT
app01-10635	35	8	time	time	NOUN
app01-10635	35	9	systems	system	NOUN
app01-10635	35	10	where	where	SCONJ
app01-10635	35	11	the	the	DET
app01-10635	35	12	acoustic	acoustic	ADJ
app01-10635	35	13	environment	environment	NOUN
app01-10635	35	14	can	can	AUX
app01-10635	35	15	vary	vary	VERB
app01-10635	35	16	significantly	significantly	ADV
app01-10635	35	17	.	.	PUNCT
app01-10635	36	1	in	in	ADP
app01-10635	36	2	the	the	DET
app01-10635	36	3	realm	realm	NOUN
app01-10635	36	4	of	of	ADP
app01-10635	36	5	climate	climate	NOUN
app01-10635	36	6	science	science	NOUN
app01-10635	36	7	,	,	PUNCT
app01-10635	36	8	various	various	ADJ
app01-10635	36	9	detection	detection	NOUN
app01-10635	36	10	methods	method	NOUN
app01-10635	36	11	have	have	AUX
app01-10635	36	12	been	be	AUX
app01-10635	36	13	developed	develop	VERB
app01-10635	36	14	to	to	PART
app01-10635	36	15	identify	identify	VERB
app01-10635	36	16	regime	regime	NOUN
app01-10635	36	17	shifts	shift	NOUN
app01-10635	36	18	,	,	PUNCT
app01-10635	36	19	which	which	PRON
app01-10635	36	20	can	can	AUX
app01-10635	36	21	be	be	AUX
app01-10635	36	22	classified	classify	VERB
app01-10635	36	23	into	into	ADP
app01-10635	36	24	categories	category	NOUN
app01-10635	36	25	based	base	VERB
app01-10635	36	26	on	on	ADP
app01-10635	36	27	the	the	DET
app01-10635	36	28	type	type	NOUN
app01-10635	36	29	of	of	ADP
app01-10635	36	30	change	change	NOUN
app01-10635	36	31	–	–	PUNCT
app01-10635	36	32	mean	mean	NOUN
app01-10635	36	33	value	value	NOUN
app01-10635	36	34	,	,	PUNCT
app01-10635	36	35	variance	variance	NOUN
app01-10635	36	36	,	,	PUNCT
app01-10635	36	37	frequency	frequency	NOUN
app01-10635	36	38	,	,	PUNCT
app01-10635	36	39	probability	probability	NOUN
app01-10635	36	40	density	density	NOUN
app01-10635	36	41	changes	change	NOUN
app01-10635	36	42	,	,	PUNCT
app01-10635	36	43	and	and	CCONJ
app01-10635	36	44	multivariable	multivariable	ADJ
app01-10635	36	45	analysis	analysis	NOUN
app01-10635	36	46	[	[	X
app01-10635	36	47	5	5	NUM
app01-10635	36	48	]	]	PUNCT
app01-10635	36	49	.	.	PUNCT
app01-10635	37	1	these	these	DET
app01-10635	37	2	methods	method	NOUN
app01-10635	37	3	provide	provide	VERB
app01-10635	37	4	a	a	DET
app01-10635	37	5	comprehensive	comprehensive	ADJ
app01-10635	37	6	framework	framework	NOUN
app01-10635	37	7	for	for	ADP
app01-10635	37	8	analyzing	analyze	VERB
app01-10635	37	9	abrupt	abrupt	ADJ
app01-10635	37	10	changes	change	NOUN
app01-10635	37	11	in	in	ADP
app01-10635	37	12	climate	climate	NOUN
app01-10635	37	13	data	datum	NOUN
app01-10635	37	14	,	,	PUNCT
app01-10635	37	15	emphasizing	emphasize	VERB
app01-10635	37	16	the	the	DET
app01-10635	37	17	need	need	NOUN
app01-10635	37	18	for	for	ADP
app01-10635	37	19	tailored	tailored	ADJ
app01-10635	37	20	approaches	approach	NOUN
app01-10635	37	21	depending	depend	VERB
app01-10635	37	22	on	on	ADP
app01-10635	37	23	the	the	DET
app01-10635	37	24	nature	nature	NOUN
app01-10635	37	25	of	of	ADP
app01-10635	37	26	the	the	DET
app01-10635	37	27	data	datum	NOUN
app01-10635	37	28	.	.	PUNCT
app01-10635	38	1	the	the	DET
app01-10635	38	2	integration	integration	NOUN
app01-10635	38	3	of	of	ADP
app01-10635	38	4	machine	machine	NOUN
app01-10635	38	5	learning	learn	VERB
app01-10635	38	6	techniques	technique	NOUN
app01-10635	38	7	into	into	ADP
app01-10635	38	8	abrupt	abrupt	ADJ
app01-10635	38	9	change	change	NOUN
app01-10635	38	10	detection	detection	NOUN
app01-10635	38	11	has	have	AUX
app01-10635	38	12	also	also	ADV
app01-10635	38	13	shown	show	VERB
app01-10635	38	14	promise	promise	NOUN
app01-10635	38	15	.	.	PUNCT
app01-10635	39	1	for	for	ADP
app01-10635	39	2	instance	instance	NOUN
app01-10635	39	3	,	,	PUNCT
app01-10635	39	4	sparse	sparse	VERB
app01-10635	39	5	identification	identification	NOUN
app01-10635	39	6	of	of	ADP
app01-10635	39	7	nonlinear	nonlinear	ADJ
app01-10635	39	8	dynamics	dynamic	NOUN
app01-10635	39	9	has	have	AUX
app01-10635	39	10	been	be	AUX
app01-10635	39	11	utilized	utilize	VERB
app01-10635	39	12	for	for	ADP
app01-10635	39	13	rapid	rapid	ADJ
app01-10635	39	14	model	model	NOUN
app01-10635	39	15	recovery	recovery	NOUN
app01-10635	39	16	in	in	ADP
app01-10635	39	17	chaotic	chaotic	ADJ
app01-10635	39	18	systems	system	NOUN
app01-10635	39	19	,	,	PUNCT
app01-10635	39	20	allowing	allow	VERB
app01-10635	39	21	for	for	ADP
app01-10635	39	22	efficient	efficient	ADJ
app01-10635	39	23	detection	detection	NOUN
app01-10635	39	24	of	of	ADP
app01-10635	39	25	abrupt	abrupt	ADJ
app01-10635	39	26	changes	change	NOUN
app01-10635	39	27	with	with	ADP
app01-10635	39	28	reduced	reduce	VERB
app01-10635	39	29	data	data	NOUN
app01-10635	39	30	requirements	requirement	NOUN
app01-10635	39	31	[	[	X
app01-10635	39	32	6	6	NUM
app01-10635	39	33	]	]	PUNCT
app01-10635	39	34	.	.	PUNCT
app01-10635	40	1	this	this	DET
app01-10635	40	2	approach	approach	NOUN
app01-10635	40	3	exemplifies	exemplify	VERB
app01-10635	40	4	the	the	DET
app01-10635	40	5	trend	trend	NOUN
app01-10635	40	6	towards	towards	ADP
app01-10635	40	7	leveraging	leverage	VERB
app01-10635	40	8	advanced	advanced	ADJ
app01-10635	40	9	computational	computational	ADJ
app01-10635	40	10	techniques	technique	NOUN
app01-10635	40	11	to	to	PART
app01-10635	40	12	enhance	enhance	VERB
app01-10635	40	13	detection	detection	NOUN
app01-10635	40	14	capabilities	capability	NOUN
app01-10635	40	15	in	in	ADP
app01-10635	40	16	complex	complex	ADJ
app01-10635	40	17	systems	system	NOUN
app01-10635	40	18	.	.	PUNCT
app01-10635	41	1	in	in	ADP
app01-10635	41	2	summary	summary	NOUN
app01-10635	41	3	,	,	PUNCT
app01-10635	41	4	the	the	DET
app01-10635	41	5	methods	method	NOUN
app01-10635	41	6	for	for	ADP
app01-10635	41	7	detecting	detect	VERB
app01-10635	41	8	abrupt	abrupt	ADJ
app01-10635	41	9	changes	change	NOUN
app01-10635	41	10	in	in	ADP
app01-10635	41	11	noisy	noisy	ADJ
app01-10635	41	12	signals	signal	NOUN
app01-10635	41	13	are	be	AUX
app01-10635	41	14	diverse	diverse	ADJ
app01-10635	41	15	and	and	CCONJ
app01-10635	41	16	multifaceted	multifaceted	ADJ
app01-10635	41	17	,	,	PUNCT
app01-10635	41	18	encompassing	encompass	VERB
app01-10635	41	19	wavelet	wavelet	NOUN
app01-10635	41	20	transforms	transform	VERB
app01-10635	41	21	,	,	PUNCT
app01-10635	41	22	statistical	statistical	ADJ
app01-10635	41	23	techniques	technique	NOUN
app01-10635	41	24	,	,	PUNCT
app01-10635	41	25	bayesian	bayesian	NOUN
app01-10635	41	26	approaches	approach	NOUN
app01-10635	41	27	,	,	PUNCT
app01-10635	41	28	and	and	CCONJ
app01-10635	41	29	machine	machine	NOUN
app01-10635	41	30	learning	learning	NOUN
app01-10635	41	31	.	.	PUNCT
app01-10635	42	1	each	each	DET
app01-10635	42	2	method	method	NOUN
app01-10635	42	3	has	have	VERB
app01-10635	42	4	its	its	PRON
app01-10635	42	5	strengths	strength	NOUN
app01-10635	42	6	and	and	CCONJ
app01-10635	42	7	is	be	AUX
app01-10635	42	8	suited	suit	VERB
app01-10635	42	9	to	to	ADP
app01-10635	42	10	particular	particular	ADJ
app01-10635	42	11	types	type	NOUN
app01-10635	42	12	of	of	ADP
app01-10635	42	13	signals	signal	NOUN
app01-10635	42	14	and	and	CCONJ
app01-10635	42	15	noise	noise	NOUN
app01-10635	42	16	characteristics	characteristic	NOUN
app01-10635	42	17	.	.	PUNCT
app01-10635	43	1	in	in	ADP
app01-10635	43	2	this	this	DET
app01-10635	43	3	paper	paper	NOUN
app01-10635	43	4	we	we	PRON
app01-10635	43	5	focus	focus	VERB
app01-10635	43	6	on	on	ADP
app01-10635	43	7	another	another	DET
app01-10635	43	8	technique	technique	NOUN
app01-10635	43	9	for	for	ADP
app01-10635	43	10	detecting	detect	VERB
app01-10635	43	11	abrupt	abrupt	ADJ
app01-10635	43	12	changes	change	NOUN
app01-10635	43	13	,	,	PUNCT
app01-10635	43	14	namely	namely	ADV
app01-10635	43	15	the	the	DET
app01-10635	43	16	use	use	NOUN
app01-10635	43	17	of	of	ADP
app01-10635	43	18	likelihood	likelihood	NOUN
app01-10635	43	19	ratio	ratio	NOUN
app01-10635	43	20	.	.	PUNCT
app01-10635	44	1	it	it	PRON
app01-10635	44	2	is	be	AUX
app01-10635	44	3	based	base	VERB
app01-10635	44	4	on	on	ADP
app01-10635	44	5	the	the	DET
app01-10635	44	6	principle	principle	NOUN
app01-10635	44	7	of	of	ADP
app01-10635	44	8	change	change	NOUN
app01-10635	44	9	detection	detection	NOUN
app01-10635	44	10	on	on	ADP
app01-10635	44	11	difference	difference	NOUN
app01-10635	44	12	synthetic	synthetic	ADJ
app01-10635	44	13	aperture	aperture	NOUN
app01-10635	44	14	radar	radar	NOUN
app01-10635	44	15	images	image	NOUN
app01-10635	44	16	[	[	X
app01-10635	44	17	7	7	NUM
app01-10635	44	18	]	]	PUNCT
app01-10635	44	19	or	or	CCONJ
app01-10635	44	20	pipeline	pipeline	NOUN
app01-10635	44	21	damage	damage	NOUN
app01-10635	44	22	detection	detection	NOUN
app01-10635	44	23	using	use	VERB
app01-10635	44	24	torsional	torsional	ADJ
app01-10635	44	25	guided	guide	VERB
app01-10635	44	26	wave	wave	NOUN
app01-10635	44	27	mode	mode	NOUN
app01-10635	45	1	[	[	X
app01-10635	45	2	8	8	NUM
app01-10635	45	3	]	]	PUNCT
app01-10635	45	4	.	.	PUNCT
app01-10635	46	1	2.2	2.2	NUM
app01-10635	46	2	.	.	PUNCT
app01-10635	47	1	problem	problem	NOUN
app01-10635	47	2	formulation	formulation	NOUN
app01-10635	47	3	lets	let	NOUN
app01-10635	47	4	have	have	VERB
app01-10635	47	5	a	a	DET
app01-10635	47	6	dataset	dataset	NOUN
app01-10635	47	7	which	which	PRON
app01-10635	47	8	a	a	DET
app01-10635	47	9	sequence	sequence	NOUN
app01-10635	47	10	of	of	ADP
app01-10635	47	11	signal	signal	ADJ
app01-10635	47	12	level	level	NOUN
app01-10635	47	13	observations	observation	NOUN
app01-10635	47	14	x	x	PUNCT
app01-10635	48	1	=	=	PUNCT
app01-10635	49	1	[	[	X
app01-10635	49	2	x1	x1	X
app01-10635	49	3	,	,	PUNCT
app01-10635	49	4	x2	x2	PROPN
app01-10635	49	5	,	,	PUNCT
app01-10635	49	6	.	.	PUNCT
app01-10635	49	7	.	.	PUNCT
app01-10635	50	1	.	.	PUNCT
app01-10635	51	1	,	,	PUNCT
app01-10635	51	2	xn	xn	PROPN
app01-10635	51	3	]	]	X
app01-10635	51	4	,	,	PUNCT
app01-10635	51	5	where	where	SCONJ
app01-10635	51	6	n	n	PRON
app01-10635	51	7	is	be	AUX
app01-10635	51	8	a	a	DET
app01-10635	51	9	number	number	NOUN
app01-10635	51	10	of	of	ADP
app01-10635	51	11	observations	observation	NOUN
app01-10635	51	12	.	.	PUNCT
app01-10635	52	1	the	the	DET
app01-10635	52	2	task	task	NOUN
app01-10635	52	3	is	be	AUX
app01-10635	52	4	to	to	PART
app01-10635	52	5	find	find	VERB
app01-10635	52	6	a	a	DET
app01-10635	52	7	sufficient	sufficient	ADJ
app01-10635	52	8	change	change	NOUN
app01-10635	52	9	in	in	ADP
app01-10635	52	10	the	the	DET
app01-10635	52	11	signal	signal	ADJ
app01-10635	52	12	level	level	NOUN
app01-10635	52	13	.	.	PUNCT
app01-10635	53	1	this	this	PRON
app01-10635	53	2	is	be	AUX
app01-10635	53	3	achieved	achieve	VERB
app01-10635	53	4	by	by	ADP
app01-10635	53	5	identifying	identify	VERB
app01-10635	53	6	the	the	DET
app01-10635	53	7	intervals	interval	NOUN
app01-10635	53	8	at	at	ADP
app01-10635	53	9	which	which	PRON
app01-10635	53	10	significant	significant	ADJ
app01-10635	53	11	changes	change	NOUN
app01-10635	53	12	in	in	ADP
app01-10635	53	13	signal	signal	ADJ
app01-10635	53	14	strength	strength	NOUN
app01-10635	53	15	occur	occur	VERB
app01-10635	53	16	.	.	PUNCT
app01-10635	54	1	this	this	PRON
app01-10635	54	2	allows	allow	VERB
app01-10635	54	3	for	for	ADP
app01-10635	54	4	the	the	DET
app01-10635	54	5	identification	identification	NOUN
app01-10635	54	6	of	of	ADP
app01-10635	54	7	potential	potential	ADJ
app01-10635	54	8	issues	issue	NOUN
app01-10635	54	9	and	and	CCONJ
app01-10635	54	10	an	an	DET
app01-10635	54	11	improvement	improvement	NOUN
app01-10635	54	12	in	in	ADP
app01-10635	54	13	the	the	DET
app01-10635	54	14	accuracy	accuracy	NOUN
app01-10635	54	15	of	of	ADP
app01-10635	54	16	data	datum	NOUN
app01-10635	54	17	analysis	analysis	NOUN
app01-10635	54	18	.	.	PUNCT
app01-10635	55	1	2.3	2.3	NUM
app01-10635	55	2	.	.	PUNCT
app01-10635	55	3	likelihood	likelihood	NOUN
app01-10635	55	4	-	-	PUNCT
app01-10635	55	5	ratio	ratio	NOUN
app01-10635	55	6	change	change	NOUN
app01-10635	55	7	detection	detection	NOUN
app01-10635	55	8	likelihood	likelihood	NOUN
app01-10635	55	9	-	-	PUNCT
app01-10635	55	10	ratio	ratio	NOUN
app01-10635	55	11	change	change	NOUN
app01-10635	55	12	detection	detection	NOUN
app01-10635	55	13	is	be	AUX
app01-10635	55	14	a	a	DET
app01-10635	55	15	statistical	statistical	ADJ
app01-10635	55	16	method	method	NOUN
app01-10635	55	17	that	that	PRON
app01-10635	55	18	is	be	AUX
app01-10635	55	19	used	use	VERB
app01-10635	55	20	to	to	PART
app01-10635	55	21	detect	detect	VERB
app01-10635	55	22	a	a	DET
app01-10635	55	23	point	point	NOUN
app01-10635	55	24	in	in	ADP
app01-10635	55	25	time	time	NOUN
app01-10635	55	26	when	when	SCONJ
app01-10635	55	27	the	the	DET
app01-10635	55	28	distribution	distribution	NOUN
app01-10635	55	29	of	of	ADP
app01-10635	55	30	signal	signal	NOUN
app01-10635	55	31	yt	yt	NOUN
app01-10635	55	32	changes	change	NOUN
app01-10635	55	33	[	[	X
app01-10635	55	34	9	9	NUM
app01-10635	55	35	,	,	PUNCT
app01-10635	55	36	10	10	NUM
app01-10635	55	37	]	]	PUNCT
app01-10635	55	38	.	.	PUNCT
app01-10635	56	1	the	the	DET
app01-10635	56	2	goal	goal	NOUN
app01-10635	56	3	of	of	ADP
app01-10635	56	4	the	the	DET
app01-10635	56	5	detection	detection	NOUN
app01-10635	56	6	algorithm	algorithm	NOUN
app01-10635	56	7	is	be	AUX
app01-10635	56	8	to	to	PART
app01-10635	56	9	determine	determine	VERB
app01-10635	56	10	s(yt	s(yt	NOUN
app01-10635	56	11	)	)	PUNCT
app01-10635	56	12	when	when	SCONJ
app01-10635	56	13	the	the	DET
app01-10635	56	14	distribution	distribution	NOUN
app01-10635	56	15	shifts	shift	NOUN
app01-10635	56	16	from	from	ADP
app01-10635	56	17	f(yt	f(yt	NOUN
app01-10635	56	18	,	,	PUNCT
app01-10635	56	19	θ0	θ0	PROPN
app01-10635	56	20	)	)	PUNCT
app01-10635	56	21	to	to	ADP
app01-10635	56	22	f(yt	f(yt	NOUN
app01-10635	56	23	,	,	PUNCT
app01-10635	56	24	θ1	θ1	NOUN
app01-10635	56	25	)	)	PUNCT
app01-10635	56	26	where	where	SCONJ
app01-10635	56	27	it	it	PRON
app01-10635	56	28	is	be	AUX
app01-10635	56	29	assumed	assume	VERB
app01-10635	56	30	that	that	SCONJ
app01-10635	56	31	θ0	θ0	PROPN
app01-10635	56	32	and	and	CCONJ
app01-10635	56	33	θ1	θ1	NOUN
app01-10635	56	34	are	be	AUX
app01-10635	56	35	known	know	VERB
app01-10635	56	36	.	.	PUNCT
app01-10635	57	1	at	at	ADP
app01-10635	57	2	each	each	DET
app01-10635	57	3	time	time	NOUN
app01-10635	57	4	step	step	NOUN
app01-10635	57	5	t	t	PROPN
app01-10635	57	6	,	,	PUNCT
app01-10635	57	7	the	the	DET
app01-10635	57	8	log	log	NOUN
app01-10635	57	9	-	-	PUNCT
app01-10635	57	10	likelihood	likelihood	NOUN
app01-10635	57	11	-	-	PUNCT
app01-10635	57	12	ratio	ratio	NOUN
app01-10635	57	13	is	be	AUX
app01-10635	57	14	computed	compute	VERB
app01-10635	57	15	as	as	ADP
app01-10635	57	16	:	:	PUNCT
app01-10635	57	17	s(yt	s(yt	X
app01-10635	57	18	)	)	PUNCT
app01-10635	57	19	=	=	SYM
app01-10635	57	20	log	log	NOUN
app01-10635	57	21	f(yt	f(yt	NOUN
app01-10635	57	22	,	,	PUNCT
app01-10635	57	23	θ1	θ1	NOUN
app01-10635	57	24	)	)	PUNCT
app01-10635	57	25	f(yt	f(yt	NOUN
app01-10635	57	26	,	,	PUNCT
app01-10635	57	27	θ0	θ0	PROPN
app01-10635	57	28	)	)	PUNCT
app01-10635	57	29	(	(	PUNCT
app01-10635	57	30	1	1	X
app01-10635	57	31	)	)	PUNCT
app01-10635	57	32	this	this	DET
app01-10635	57	33	ratio	ratio	NOUN
app01-10635	57	34	in	in	ADP
app01-10635	57	35	eq	eq	ADP
app01-10635	57	36	.	.	PUNCT
app01-10635	58	1	(	(	PUNCT
app01-10635	58	2	1	1	X
app01-10635	58	3	)	)	PUNCT
app01-10635	58	4	compares	compare	VERB
app01-10635	58	5	the	the	DET
app01-10635	58	6	probability	probability	NOUN
app01-10635	58	7	of	of	ADP
app01-10635	58	8	observing	observe	VERB
app01-10635	58	9	the	the	DET
app01-10635	58	10	current	current	ADJ
app01-10635	58	11	value	value	NOUN
app01-10635	58	12	of	of	ADP
app01-10635	58	13	the	the	DET
app01-10635	58	14	signal	signal	NOUN
app01-10635	58	15	yt	yt	VERB
app01-10635	58	16	under	under	ADP
app01-10635	58	17	the	the	DET
app01-10635	58	18	assumption	assumption	NOUN
app01-10635	58	19	that	that	SCONJ
app01-10635	58	20	a	a	DET
app01-10635	58	21	change	change	NOUN
app01-10635	58	22	has	have	AUX
app01-10635	58	23	already	already	ADV
app01-10635	58	24	taken	take	VERB
app01-10635	58	25	place	place	NOUN
app01-10635	58	26	(	(	PUNCT
app01-10635	58	27	with	with	ADP
app01-10635	58	28	parameter	parameter	NOUN
app01-10635	58	29	θ1	θ1	NOUN
app01-10635	58	30	)	)	PUNCT
app01-10635	58	31	to	to	ADP
app01-10635	58	32	the	the	DET
app01-10635	58	33	probability	probability	NOUN
app01-10635	58	34	of	of	ADP
app01-10635	58	35	observing	observe	VERB
app01-10635	58	36	the	the	DET
app01-10635	58	37	same	same	ADJ
app01-10635	58	38	value	value	NOUN
app01-10635	58	39	under	under	ADP
app01-10635	58	40	the	the	DET
app01-10635	58	41	assumption	assumption	NOUN
app01-10635	58	42	that	that	SCONJ
app01-10635	58	43	no	no	DET
app01-10635	58	44	change	change	NOUN
app01-10635	58	45	has	have	AUX
app01-10635	58	46	yet	yet	ADV
app01-10635	58	47	occurred	occur	VERB
app01-10635	58	48	with	with	ADP
app01-10635	58	49	θ0	θ0	NOUN
app01-10635	58	50	.	.	PUNCT
app01-10635	59	1	the	the	DET
app01-10635	59	2	following	follow	VERB
app01-10635	59	3	algorithm	algorithm	NOUN
app01-10635	59	4	solves	solve	VERB
app01-10635	59	5	the	the	DET
app01-10635	59	6	detection	detection	NOUN
app01-10635	59	7	problem	problem	NOUN
app01-10635	59	8	.	.	PUNCT
app01-10635	60	1	it	it	PRON
app01-10635	60	2	detects	detect	VERB
app01-10635	60	3	the	the	DET
app01-10635	60	4	change	change	NOUN
app01-10635	60	5	in	in	ADP
app01-10635	60	6	the	the	DET
app01-10635	60	7	level	level	NOUN
app01-10635	60	8	of	of	ADP
app01-10635	60	9	the	the	DET
app01-10635	60	10	signal	signal	NOUN
app01-10635	60	11	under	under	ADP
app01-10635	60	12	test	test	NOUN
app01-10635	60	13	.	.	PUNCT
app01-10635	61	1	it	it	PRON
app01-10635	61	2	is	be	AUX
app01-10635	61	3	possible	possible	ADJ
app01-10635	61	4	to	to	PART
app01-10635	61	5	apply	apply	VERB
app01-10635	61	6	this	this	DET
app01-10635	61	7	approach	approach	NOUN
app01-10635	61	8	to	to	ADP
app01-10635	61	9	the	the	DET
app01-10635	61	10	fourier	fourier	NOUN
app01-10635	61	11	transform	transform	NOUN
app01-10635	61	12	,	,	PUNCT
app01-10635	61	13	thus	thus	ADV
app01-10635	61	14	capturing	capture	VERB
app01-10635	61	15	changes	change	NOUN
app01-10635	61	16	in	in	ADP
app01-10635	61	17	frequency	frequency	NOUN
app01-10635	61	18	.	.	PUNCT
app01-10635	62	1	initialization	initialization	NOUN
app01-10635	62	2	.	.	PUNCT
app01-10635	63	1	set	set	VERB
app01-10635	63	2	the	the	DET
app01-10635	63	3	values	value	NOUN
app01-10635	63	4	of	of	ADP
app01-10635	63	5	the	the	DET
app01-10635	63	6	signal	signal	ADJ
app01-10635	63	7	yt	yt	PROPN
app01-10635	63	8	,	,	PUNCT
app01-10635	63	9	θ0	θ0	PROPN
app01-10635	63	10	,	,	PUNCT
app01-10635	63	11	and	and	CCONJ
app01-10635	63	12	θ1	θ1	NOUN
app01-10635	63	13	–	–	PUNCT
app01-10635	63	14	means	mean	VERB
app01-10635	63	15	,	,	PUNCT
app01-10635	63	16	σ	σ	PROPN
app01-10635	63	17	–	–	PUNCT
app01-10635	63	18	standard	standard	ADJ
app01-10635	63	19	deviation	deviation	NOUN
app01-10635	63	20	of	of	ADP
app01-10635	63	21	the	the	DET
app01-10635	63	22	data	datum	NOUN
app01-10635	63	23	set	set	VERB
app01-10635	63	24	.	.	PUNCT
app01-10635	64	1	signal	signal	PROPN
app01-10635	64	2	observation	observation	NOUN
app01-10635	64	3	.	.	PUNCT
app01-10635	65	1	the	the	DET
app01-10635	65	2	signal	signal	NOUN
app01-10635	65	3	yt	yt	NOUN
app01-10635	65	4	is	be	AUX
app01-10635	65	5	sampled	sample	VERB
app01-10635	65	6	in	in	ADP
app01-10635	65	7	k	k	PROPN
app01-10635	65	8	,	,	PUNCT
app01-10635	65	9	where	where	SCONJ
app01-10635	65	10	k	k	PROPN
app01-10635	65	11	is	be	AUX
app01-10635	65	12	the	the	DET
app01-10635	65	13	sequence	sequence	NOUN
app01-10635	65	14	number	number	NOUN
app01-10635	65	15	of	of	ADP
app01-10635	65	16	the	the	DET
app01-10635	65	17	large	large	ADJ
app01-10635	65	18	period	period	NOUN
app01-10635	65	19	of	of	ADP
app01-10635	65	20	sampling	sample	VERB
app01-10635	65	21	.	.	PUNCT
app01-10635	66	1	in	in	ADP
app01-10635	66	2	addition	addition	NOUN
app01-10635	66	3	,	,	PUNCT
app01-10635	66	4	each	each	DET
app01-10635	66	5	large	large	ADJ
app01-10635	66	6	period	period	NOUN
app01-10635	66	7	is	be	AUX
app01-10635	66	8	divided	divide	VERB
app01-10635	66	9	into	into	ADP
app01-10635	66	10	n	n	CCONJ
app01-10635	66	11	small	small	ADJ
app01-10635	66	12	periods	period	NOUN
app01-10635	66	13	,	,	PUNCT
app01-10635	66	14	as	as	SCONJ
app01-10635	66	15	indicated	indicate	VERB
app01-10635	66	16	in	in	ADP
app01-10635	66	17	figure	figure	NOUN
app01-10635	66	18	1	1	NUM
app01-10635	66	19	.	.	PUNCT
app01-10635	66	20	figure	figure	NOUN
app01-10635	66	21	1	1	NUM
app01-10635	66	22	.	.	PUNCT
app01-10635	67	1	illustration	illustration	NOUN
app01-10635	67	2	of	of	ADP
app01-10635	67	3	the	the	DET
app01-10635	67	4	signal	signal	NOUN
app01-10635	67	5	divided	divide	VERB
app01-10635	67	6	into	into	ADP
app01-10635	67	7	k	k	PROPN
app01-10635	67	8	intervals	interval	NOUN
app01-10635	67	9	[	[	X
app01-10635	67	10	9	9	NUM
app01-10635	67	11	]	]	PUNCT
app01-10635	67	12	.	.	PUNCT
app01-10635	68	1	compute	compute	NOUN
app01-10635	68	2	and	and	CCONJ
app01-10635	68	3	update	update	NOUN
app01-10635	68	4	statistics	statistic	NOUN
app01-10635	68	5	.	.	PUNCT
app01-10635	69	1	calculate	calculate	VERB
app01-10635	69	2	the	the	DET
app01-10635	69	3	likelihood	likelihood	NOUN
app01-10635	69	4	ratio	ratio	NOUN
app01-10635	69	5	for	for	ADP
app01-10635	69	6	yt	yt	NOUN
app01-10635	69	7	on	on	ADP
app01-10635	69	8	n	n	PRON
app01-10635	69	9	-th	-th	ADJ
app01-10635	69	10	small	small	ADJ
app01-10635	69	11	interval	interval	NOUN
app01-10635	69	12	,	,	PUNCT
app01-10635	69	13	and	and	CCONJ
app01-10635	69	14	update	update	VERB
app01-10635	69	15	statistics	statistic	NOUN
app01-10635	69	16	over	over	ADP
app01-10635	69	17	small	small	ADJ
app01-10635	69	18	intervals	interval	NOUN
app01-10635	69	19	using	use	VERB
app01-10635	69	20	the	the	DET
app01-10635	69	21	alpha	alpha	ADJ
app01-10635	69	22	coefficient	coefficient	NOUN
app01-10635	69	23	in	in	ADP
app01-10635	69	24	eq	eq	ADP
app01-10635	69	25	.	.	PUNCT
app01-10635	70	1	(	(	PUNCT
app01-10635	70	2	2	2	NUM
app01-10635	70	3	)	)	PUNCT
app01-10635	70	4	.	.	PUNCT
app01-10635	71	1	the	the	DET
app01-10635	71	2	closer	close	ADJ
app01-10635	71	3	α	α	NOUN
app01-10635	71	4	is	be	AUX
app01-10635	71	5	to	to	ADP
app01-10635	71	6	1	1	NUM
app01-10635	71	7	,	,	PUNCT
app01-10635	71	8	the	the	DET
app01-10635	71	9	more	more	ADJ
app01-10635	71	10	weight	weight	NOUN
app01-10635	71	11	is	be	AUX
app01-10635	71	12	given	give	VERB
app01-10635	71	13	to	to	ADP
app01-10635	71	14	the	the	DET
app01-10635	71	15	value	value	NOUN
app01-10635	71	16	of	of	ADP
app01-10635	71	17	st−1	st−1	NOUN
app01-10635	71	18	:	:	PUNCT
app01-10635	71	19	st	st	PROPN
app01-10635	71	20	=	=	PROPN
app01-10635	71	21	α	α	PROPN
app01-10635	71	22	·	·	PUNCT
app01-10635	71	23	st−1	st−1	NOUN
app01-10635	71	24	+	+	CCONJ
app01-10635	71	25	(	(	PUNCT
app01-10635	71	26	θ1	θ1	PROPN
app01-10635	71	27	−	−	PROPN
app01-10635	71	28	θ2	θ2	PROPN
app01-10635	71	29	)	)	PUNCT
app01-10635	71	30	σ2	σ2	PROPN
app01-10635	71	31	[	[	PUNCT
app01-10635	71	32	yt	yt	PROPN
app01-10635	71	33	−	−	PROPN
app01-10635	71	34	θ1	θ1	PROPN
app01-10635	71	35	+	+	CCONJ
app01-10635	71	36	θ2	θ2	PROPN
app01-10635	71	37	2	2	NUM
app01-10635	71	38	]	]	PUNCT
app01-10635	71	39	,	,	PUNCT
app01-10635	71	40	(	(	PUNCT
app01-10635	71	41	2	2	X
app01-10635	71	42	)	)	PUNCT
app01-10635	71	43	where	where	SCONJ
app01-10635	71	44	st	st	PROPN
app01-10635	71	45	is	be	AUX
app01-10635	71	46	the	the	DET
app01-10635	71	47	current	current	ADJ
app01-10635	71	48	value	value	NOUN
app01-10635	71	49	of	of	ADP
app01-10635	71	50	the	the	DET
app01-10635	71	51	statistic	statistic	NOUN
app01-10635	71	52	,	,	PUNCT
app01-10635	71	53	yt	yt	PROPN
app01-10635	71	54	is	be	AUX
app01-10635	71	55	the	the	DET
app01-10635	71	56	current	current	ADJ
app01-10635	71	57	observed	observe	VERB
app01-10635	71	58	value	value	NOUN
app01-10635	71	59	,	,	PUNCT
app01-10635	71	60	and	and	CCONJ
app01-10635	71	61	α	α	PRON
app01-10635	71	62	is	be	AUX
app01-10635	71	63	the	the	DET
app01-10635	71	64	coefficient	coefficient	NOUN
app01-10635	71	65	of	of	ADP
app01-10635	71	66	forgetting	forget	VERB
app01-10635	71	67	where	where	SCONJ
app01-10635	71	68	0	0	NUM
app01-10635	71	69	<	<	X
app01-10635	71	70	α	α	X
app01-10635	71	71	<	<	X
app01-10635	71	72	1	1	NUM
app01-10635	71	73	.	.	PUNCT
app01-10635	71	74	after	after	ADP
app01-10635	71	75	obtaining	obtain	VERB
app01-10635	71	76	the	the	DET
app01-10635	71	77	result	result	NOUN
app01-10635	71	78	on	on	ADP
app01-10635	71	79	the	the	DET
app01-10635	71	80	small	small	ADJ
app01-10635	71	81	interval	interval	NOUN
app01-10635	71	82	n	n	NOUN
app01-10635	71	83	,	,	PUNCT
app01-10635	71	84	the	the	DET
app01-10635	71	85	value	value	NOUN
app01-10635	71	86	of	of	ADP
app01-10635	71	87	sn	sn	PROPN
app01-10635	71	88	1	1	NUM
app01-10635	71	89	(	(	PUNCT
app01-10635	71	90	k	k	NOUN
app01-10635	71	91	)	)	PUNCT
app01-10635	71	92	big	big	ADJ
app01-10635	71	93	interval	interval	NOUN
app01-10635	71	94	is	be	AUX
app01-10635	71	95	computed	compute	VERB
app01-10635	71	96	,	,	PUNCT
app01-10635	71	97	as	as	SCONJ
app01-10635	71	98	shown	show	VERB
app01-10635	71	99	in	in	ADP
app01-10635	71	100	eq	eq	ADP
app01-10635	71	101	.	.	PUNCT
app01-10635	72	1	(	(	PUNCT
app01-10635	72	2	3	3	NUM
app01-10635	72	3	)	)	PUNCT
app01-10635	72	4	,	,	PUNCT
app01-10635	72	5	where	where	SCONJ
app01-10635	72	6	sn	sn	PROPN
app01-10635	72	7	1	1	NUM
app01-10635	72	8	(	(	PUNCT
app01-10635	72	9	k	k	NOUN
app01-10635	72	10	)	)	PUNCT
app01-10635	72	11	is	be	AUX
app01-10635	72	12	the	the	DET
app01-10635	72	13	value	value	NOUN
app01-10635	72	14	of	of	ADP
app01-10635	72	15	the	the	DET
app01-10635	72	16	statistic	statistic	NOUN
app01-10635	72	17	on	on	ADP
app01-10635	72	18	the	the	DET
app01-10635	72	19	k	k	NOUN
app01-10635	72	20	-	-	PUNCT
app01-10635	72	21	th	th	VERB
app01-10635	72	22	interval	interval	NOUN
app01-10635	72	23	.	.	PUNCT
app01-10635	73	1	sn	sn	PROPN
app01-10635	73	2	1	1	NUM
app01-10635	73	3	(	(	PUNCT
app01-10635	73	4	k	k	NOUN
app01-10635	73	5	)	)	PUNCT
app01-10635	73	6	=	=	SYM
app01-10635	73	7	(	(	PUNCT
app01-10635	73	8	θ1−θ0	θ1−θ0	NOUN
app01-10635	73	9	)	)	PUNCT
app01-10635	73	10	σ2	σ2	NOUN
app01-10635	73	11	∑n	∑n	PROPN
app01-10635	73	12	t	t	PROPN
app01-10635	73	13	=	=	PROPN
app01-10635	73	14	n(k−1)+1	n(k−1)+1	PROPN
app01-10635	73	15	k	k	PROPN
app01-10635	73	16	[	[	PUNCT
app01-10635	73	17	yt	yt	NUM
app01-10635	73	18	−	−	NOUN
app01-10635	73	19	θ1+θ0	θ1+θ0	PROPN
app01-10635	73	20	2	2	NUM
app01-10635	73	21	]	]	PUNCT
app01-10635	73	22	.	.	PUNCT
app01-10635	74	1	(	(	PUNCT
app01-10635	74	2	3	3	X
app01-10635	74	3	)	)	PUNCT
app01-10635	74	4	threshold	threshold	NOUN
app01-10635	74	5	test	test	NOUN
app01-10635	74	6	.	.	PUNCT
app01-10635	75	1	compare	compare	VERB
app01-10635	75	2	sn	sn	PROPN
app01-10635	75	3	1	1	NUM
app01-10635	75	4	(	(	PUNCT
app01-10635	75	5	k	k	NOUN
app01-10635	75	6	)	)	PUNCT
app01-10635	75	7	with	with	ADP
app01-10635	75	8	a	a	DET
app01-10635	75	9	predetermined	predetermine	VERB
app01-10635	75	10	threshold	threshold	NOUN
app01-10635	75	11	h.	h.	NOUN
app01-10635	76	1	the	the	DET
app01-10635	76	2	decision	decision	NOUN
app01-10635	76	3	rule	rule	NOUN
app01-10635	76	4	is	be	AUX
app01-10635	76	5	:	:	PUNCT
app01-10635	76	6	d	d	X
app01-10635	76	7	=	=	SYM
app01-10635	76	8	{	{	PUNCT
app01-10635	76	9	0	0	NUM
app01-10635	76	10	,	,	PUNCT
app01-10635	76	11	if	if	SCONJ
app01-10635	76	12	sn	sn	PROPN
app01-10635	76	13	1	1	NUM
app01-10635	76	14	(	(	PUNCT
app01-10635	76	15	k	k	NOUN
app01-10635	76	16	)	)	PUNCT
app01-10635	76	17	<	<	X
app01-10635	76	18	h	h	NOUN
app01-10635	76	19	,	,	PUNCT
app01-10635	76	20	1	1	NUM
app01-10635	76	21	,	,	PUNCT
app01-10635	76	22	if	if	SCONJ
app01-10635	76	23	sn	sn	PROPN
app01-10635	76	24	i	i	PRON
app01-10635	76	25	(	(	PUNCT
app01-10635	76	26	k	k	NOUN
app01-10635	76	27	)	)	PUNCT
app01-10635	76	28	>	>	X
app01-10635	76	29	h	h	NOUN
app01-10635	76	30	,	,	PUNCT
app01-10635	76	31	(	(	PUNCT
app01-10635	76	32	4	4	NUM
app01-10635	76	33	)	)	PUNCT
app01-10635	76	34	64	64	NUM
app01-10635	76	35	vol	vol	NOUN
app01-10635	76	36	.	.	PUNCT
app01-10635	77	1	52/2025	52/2025	NUM
app01-10635	77	2	abrupt	abrupt	ADJ
app01-10635	77	3	change	change	NOUN
app01-10635	77	4	detection	detection	NOUN
app01-10635	77	5	in	in	ADP
app01-10635	77	6	railway	railway	NOUN
app01-10635	77	7	noise	noise	NOUN
app01-10635	77	8	data	datum	NOUN
app01-10635	77	9	where	where	SCONJ
app01-10635	77	10	sn	sn	PROPN
app01-10635	77	11	1	1	NUM
app01-10635	77	12	(	(	PUNCT
app01-10635	77	13	k	k	NOUN
app01-10635	77	14	)	)	PUNCT
app01-10635	77	15	=	=	SYM
app01-10635	77	16	snk	snk	PROPN
app01-10635	77	17	n(k−1)+1	n(k−1)+1	NOUN
app01-10635	78	1	[	[	X
app01-10635	78	2	10	10	NUM
app01-10635	78	3	]	]	PUNCT
app01-10635	78	4	.	.	PUNCT
app01-10635	79	1	if	if	SCONJ
app01-10635	79	2	sn	sn	PROPN
app01-10635	79	3	1	1	NUM
app01-10635	79	4	(	(	PUNCT
app01-10635	79	5	k	k	NOUN
app01-10635	79	6	)	)	PUNCT
app01-10635	79	7	>	>	X
app01-10635	80	1	h	h	NOUN
app01-10635	80	2	,	,	PUNCT
app01-10635	80	3	it	it	PRON
app01-10635	80	4	is	be	AUX
app01-10635	80	5	considered	consider	VERB
app01-10635	80	6	that	that	SCONJ
app01-10635	80	7	there	there	PRON
app01-10635	80	8	was	be	VERB
app01-10635	80	9	a	a	DET
app01-10635	80	10	change	change	NOUN
app01-10635	80	11	in	in	ADP
app01-10635	80	12	the	the	DET
app01-10635	80	13	distribution	distribution	NOUN
app01-10635	80	14	from	from	ADP
app01-10635	80	15	θ0	θ0	NOUN
app01-10635	80	16	to	to	ADP
app01-10635	80	17	θ1	θ1	NOUN
app01-10635	80	18	.	.	PUNCT
app01-10635	81	1	3	3	X
app01-10635	81	2	.	.	X
app01-10635	81	3	railway	railway	NOUN
app01-10635	81	4	noise	noise	NOUN
app01-10635	81	5	data	datum	NOUN
app01-10635	81	6	the	the	DET
app01-10635	81	7	purpose	purpose	NOUN
app01-10635	81	8	of	of	ADP
app01-10635	81	9	the	the	DET
app01-10635	81	10	experiment	experiment	NOUN
app01-10635	81	11	part	part	NOUN
app01-10635	81	12	is	be	AUX
app01-10635	81	13	to	to	PART
app01-10635	81	14	find	find	VERB
app01-10635	81	15	intervals	interval	NOUN
app01-10635	81	16	where	where	SCONJ
app01-10635	81	17	noise	noise	NOUN
app01-10635	81	18	significantly	significantly	ADV
app01-10635	81	19	and	and	CCONJ
app01-10635	81	20	rapidly	rapidly	ADV
app01-10635	81	21	changes	change	VERB
app01-10635	81	22	using	use	VERB
app01-10635	81	23	the	the	DET
app01-10635	81	24	likelihood	likelihood	NOUN
app01-10635	81	25	ratio	ratio	NOUN
app01-10635	81	26	method	method	NOUN
app01-10635	81	27	.	.	PUNCT
app01-10635	82	1	within	within	ADP
app01-10635	82	2	the	the	DET
app01-10635	82	3	framework	framework	NOUN
app01-10635	82	4	of	of	ADP
app01-10635	82	5	the	the	DET
app01-10635	82	6	hlukos	hlukos	PROPN
app01-10635	82	7	research	research	PROPN
app01-10635	82	8	project	project	NOUN
app01-10635	82	9	,	,	PUNCT
app01-10635	82	10	data	datum	NOUN
app01-10635	82	11	collection	collection	NOUN
app01-10635	82	12	is	be	AUX
app01-10635	82	13	carried	carry	VERB
app01-10635	82	14	out	out	ADP
app01-10635	82	15	by	by	ADP
app01-10635	82	16	means	mean	NOUN
app01-10635	82	17	of	of	ADP
app01-10635	82	18	microphones	microphone	NOUN
app01-10635	82	19	placed	place	VERB
app01-10635	82	20	symmetrically	symmetrically	ADV
app01-10635	82	21	on	on	ADP
app01-10635	82	22	the	the	DET
app01-10635	82	23	wheelset	wheelset	NOUN
app01-10635	82	24	of	of	ADP
app01-10635	82	25	the	the	DET
app01-10635	82	26	diagnostic	diagnostic	ADJ
app01-10635	82	27	vehicle	vehicle	NOUN
app01-10635	82	28	mvžsv2	mvžsv2	NOUN
app01-10635	82	29	(	(	PUNCT
app01-10635	82	30	owned	own	VERB
app01-10635	82	31	and	and	CCONJ
app01-10635	82	32	operated	operate	VERB
app01-10635	82	33	by	by	ADP
app01-10635	82	34	czech	czech	ADJ
app01-10635	82	35	rail	rail	NOUN
app01-10635	82	36	infrastructure	infrastructure	NOUN
app01-10635	82	37	manager	manager	NOUN
app01-10635	82	38	:	:	PUNCT
app01-10635	82	39	technology	technology	NOUN
app01-10635	82	40	and	and	CCONJ
app01-10635	82	41	diagnostics	diagnostic	NOUN
app01-10635	82	42	centre	centre	NOUN
app01-10635	82	43	,	,	PUNCT
app01-10635	82	44	railway	railway	NOUN
app01-10635	82	45	administration	administration	NOUN
app01-10635	82	46	,	,	PUNCT
app01-10635	82	47	state	state	NOUN
app01-10635	82	48	organisation	organisation	NOUN
app01-10635	82	49	)	)	PUNCT
app01-10635	82	50	,	,	PUNCT
app01-10635	82	51	in	in	ADP
app01-10635	82	52	such	such	DET
app01-10635	82	53	a	a	DET
app01-10635	82	54	reference	reference	NOUN
app01-10635	82	55	position	position	NOUN
app01-10635	82	56	(	(	PUNCT
app01-10635	82	57	see	see	VERB
app01-10635	82	58	figure	figure	NOUN
app01-10635	82	59	2	2	NUM
app01-10635	82	60	)	)	PUNCT
app01-10635	82	61	,	,	PUNCT
app01-10635	82	62	which	which	PRON
app01-10635	82	63	is	be	AUX
app01-10635	82	64	closest	close	ADJ
app01-10635	82	65	to	to	ADP
app01-10635	82	66	the	the	DET
app01-10635	82	67	measured	measured	ADJ
app01-10635	82	68	wheel	wheel	NOUN
app01-10635	82	69	and	and	CCONJ
app01-10635	82	70	,	,	PUNCT
app01-10635	82	71	according	accord	VERB
app01-10635	82	72	to	to	ADP
app01-10635	82	73	further	further	ADJ
app01-10635	82	74	technical	technical	ADJ
app01-10635	82	75	analysis	analysis	NOUN
app01-10635	82	76	and	and	CCONJ
app01-10635	82	77	listening	listen	VERB
app01-10635	82	78	to	to	ADP
app01-10635	82	79	the	the	DET
app01-10635	82	80	sound	sound	ADJ
app01-10635	82	81	recording	recording	NOUN
app01-10635	82	82	,	,	PUNCT
app01-10635	82	83	shows	show	VERB
app01-10635	82	84	the	the	DET
app01-10635	82	85	lowest	low	ADJ
app01-10635	82	86	level	level	NOUN
app01-10635	82	87	of	of	ADP
app01-10635	82	88	interference	interference	NOUN
app01-10635	82	89	by	by	ADP
app01-10635	82	90	air	air	NOUN
app01-10635	82	91	flow	flow	NOUN
app01-10635	82	92	and	and	CCONJ
app01-10635	82	93	other	other	ADJ
app01-10635	82	94	ambient	ambient	ADJ
app01-10635	82	95	phenomena	phenomenon	NOUN
app01-10635	82	96	.	.	PUNCT
app01-10635	83	1	the	the	DET
app01-10635	83	2	key	key	NOUN
app01-10635	83	3	is	be	AUX
app01-10635	83	4	the	the	DET
app01-10635	83	5	choice	choice	NOUN
app01-10635	83	6	and	and	CCONJ
app01-10635	83	7	correct	correct	ADJ
app01-10635	83	8	configuration	configuration	NOUN
app01-10635	83	9	of	of	ADP
app01-10635	83	10	the	the	DET
app01-10635	83	11	sound	sound	NOUN
app01-10635	83	12	analyser	analyser	NOUN
app01-10635	83	13	,	,	PUNCT
app01-10635	83	14	whose	whose	DET
app01-10635	83	15	function	function	NOUN
app01-10635	83	16	is	be	AUX
app01-10635	83	17	to	to	PART
app01-10635	83	18	process	process	VERB
app01-10635	83	19	the	the	DET
app01-10635	83	20	data	datum	NOUN
app01-10635	83	21	recorded	record	VERB
app01-10635	83	22	by	by	ADP
app01-10635	83	23	the	the	DET
app01-10635	83	24	measuring	measure	VERB
app01-10635	83	25	microphones	microphone	NOUN
app01-10635	83	26	in	in	ADP
app01-10635	83	27	real	real	ADJ
app01-10635	83	28	time	time	NOUN
app01-10635	83	29	and	and	CCONJ
app01-10635	83	30	convert	convert	VERB
app01-10635	83	31	them	they	PRON
app01-10635	83	32	into	into	ADP
app01-10635	83	33	specific	specific	ADJ
app01-10635	83	34	acoustic	acoustic	ADJ
app01-10635	83	35	parameters	parameter	NOUN
app01-10635	83	36	.	.	PUNCT
app01-10635	84	1	the	the	DET
app01-10635	84	2	problem	problem	NOUN
app01-10635	84	3	lies	lie	VERB
app01-10635	84	4	in	in	ADP
app01-10635	84	5	the	the	DET
app01-10635	84	6	combination	combination	NOUN
app01-10635	84	7	of	of	ADP
app01-10635	84	8	the	the	DET
app01-10635	84	9	high	high	ADJ
app01-10635	84	10	speed	speed	NOUN
app01-10635	84	11	of	of	ADP
app01-10635	84	12	the	the	DET
app01-10635	84	13	diagnostic	diagnostic	ADJ
app01-10635	84	14	vehicle	vehicle	NOUN
app01-10635	84	15	(	(	PUNCT
app01-10635	84	16	currently	currently	ADV
app01-10635	84	17	max	max	PROPN
app01-10635	84	18	.	.	PROPN
app01-10635	85	1	160	160	NUM
app01-10635	85	2	km	km	NOUN
app01-10635	85	3	h−1	h−1	PROPN
app01-10635	85	4	,	,	PUNCT
app01-10635	85	5	in	in	ADP
app01-10635	85	6	the	the	DET
app01-10635	85	7	near	near	ADJ
app01-10635	85	8	future	future	NOUN
app01-10635	85	9	up	up	ADP
app01-10635	85	10	to	to	PART
app01-10635	85	11	200	200	NUM
app01-10635	85	12	km	km	NOUN
app01-10635	85	13	h−1	h−1	PROPN
app01-10635	85	14	)	)	PUNCT
app01-10635	85	15	and	and	CCONJ
app01-10635	85	16	the	the	DET
app01-10635	85	17	requirement	requirement	NOUN
app01-10635	85	18	for	for	ADP
app01-10635	85	19	very	very	ADV
app01-10635	85	20	fine	fine	ADJ
app01-10635	85	21	sampling	sampling	NOUN
app01-10635	85	22	of	of	ADP
app01-10635	85	23	the	the	DET
app01-10635	85	24	track	track	NOUN
app01-10635	85	25	parameters	parameter	NOUN
app01-10635	85	26	.	.	PUNCT
app01-10635	86	1	for	for	ADP
app01-10635	86	2	the	the	DET
app01-10635	86	3	solution	solution	NOUN
app01-10635	86	4	of	of	ADP
app01-10635	86	5	this	this	DET
app01-10635	86	6	project	project	NOUN
app01-10635	86	7	,	,	PUNCT
app01-10635	86	8	a	a	DET
app01-10635	86	9	specially	specially	ADV
app01-10635	86	10	designed	design	VERB
app01-10635	86	11	sensor	sensor	NOUN
app01-10635	86	12	-	-	PUNCT
app01-10635	86	13	acoustic	acoustic	ADJ
app01-10635	86	14	system	system	NOUN
app01-10635	86	15	developed	develop	VERB
app01-10635	86	16	by	by	ADP
app01-10635	86	17	the	the	DET
app01-10635	86	18	project	project	NOUN
app01-10635	86	19	team	team	NOUN
app01-10635	86	20	–	–	PUNCT
app01-10635	86	21	ekola	ekola	PROPN
app01-10635	86	22	group	group	NOUN
app01-10635	86	23	,	,	PUNCT
app01-10635	86	24	spol	spol	NOUN
app01-10635	86	25	.	.	PUNCT
app01-10635	87	1	s	s	PROPN
app01-10635	87	2	r.o	r.o	PROPN
app01-10635	87	3	.	.	PROPN
app01-10635	87	4	,	,	PUNCT
app01-10635	87	5	and	and	CCONJ
app01-10635	87	6	ctu	ctu	NOUN
app01-10635	87	7	in	in	ADP
app01-10635	87	8	prague	prague	PROPN
app01-10635	87	9	,	,	PUNCT
app01-10635	87	10	faculty	faculty	NOUN
app01-10635	87	11	of	of	ADP
app01-10635	87	12	transportation	transportation	NOUN
app01-10635	87	13	sciences	science	NOUN
app01-10635	87	14	–	–	PUNCT
app01-10635	87	15	was	be	AUX
app01-10635	87	16	used	use	VERB
app01-10635	87	17	.	.	PUNCT
app01-10635	88	1	this	this	DET
app01-10635	88	2	system	system	NOUN
app01-10635	88	3	enables	enable	VERB
app01-10635	88	4	the	the	DET
app01-10635	88	5	collection	collection	NOUN
app01-10635	88	6	of	of	ADP
app01-10635	88	7	acoustic	acoustic	ADJ
app01-10635	88	8	data	datum	NOUN
app01-10635	88	9	with	with	ADP
app01-10635	88	10	an	an	DET
app01-10635	88	11	accuracy	accuracy	NOUN
app01-10635	88	12	comparable	comparable	ADJ
app01-10635	88	13	to	to	ADP
app01-10635	88	14	conventional	conventional	ADJ
app01-10635	88	15	sound	sound	NOUN
app01-10635	88	16	measurement	measurement	NOUN
app01-10635	88	17	technology	technology	NOUN
app01-10635	88	18	at	at	ADP
app01-10635	88	19	a	a	DET
app01-10635	88	20	sampling	sample	VERB
app01-10635	88	21	frequency	frequency	NOUN
app01-10635	88	22	of	of	ADP
app01-10635	88	23	up	up	ADP
app01-10635	88	24	to	to	PART
app01-10635	88	25	48	48	NUM
app01-10635	88	26	khz	khz	NOUN
app01-10635	88	27	,	,	PUNCT
app01-10635	88	28	which	which	PRON
app01-10635	88	29	corresponds	correspond	VERB
app01-10635	88	30	to	to	ADP
app01-10635	88	31	a	a	DET
app01-10635	88	32	sampling	sample	VERB
app01-10635	88	33	duration	duration	NOUN
app01-10635	88	34	of	of	ADP
app01-10635	88	35	0.02	0.02	NUM
app01-10635	88	36	ms	ms	NOUN
app01-10635	88	37	[	[	X
app01-10635	88	38	11	11	NUM
app01-10635	88	39	]	]	PUNCT
app01-10635	88	40	.	.	PUNCT
app01-10635	89	1	the	the	DET
app01-10635	89	2	study	study	NOUN
app01-10635	89	3	was	be	AUX
app01-10635	89	4	conducted	conduct	VERB
app01-10635	89	5	in	in	ADP
app01-10635	89	6	a	a	DET
app01-10635	89	7	station	station	NOUN
app01-10635	89	8	throat	throat	NOUN
app01-10635	89	9	section	section	NOUN
app01-10635	89	10	with	with	ADP
app01-10635	89	11	three	three	NUM
app01-10635	89	12	single	single	ADJ
app01-10635	89	13	rail	rail	NOUN
app01-10635	89	14	switches	switch	NOUN
app01-10635	89	15	running	run	VERB
app01-10635	89	16	against	against	ADP
app01-10635	89	17	the	the	DET
app01-10635	89	18	switch	switch	NOUN
app01-10635	89	19	blades	blade	NOUN
app01-10635	89	20	at	at	ADP
app01-10635	89	21	a	a	DET
app01-10635	89	22	low	low	ADJ
app01-10635	89	23	speed	speed	NOUN
app01-10635	89	24	,	,	PUNCT
app01-10635	89	25	within	within	ADP
app01-10635	89	26	the	the	DET
app01-10635	89	27	range	range	NOUN
app01-10635	89	28	of	of	ADP
app01-10635	89	29	35.6	35.6	NUM
app01-10635	89	30	to	to	PART
app01-10635	89	31	36.8	36.8	NUM
app01-10635	89	32	km	km	NOUN
app01-10635	89	33	h−1	h−1	PROPN
app01-10635	89	34	.	.	PUNCT
app01-10635	90	1	the	the	DET
app01-10635	90	2	data	datum	NOUN
app01-10635	90	3	set	set	VERB
app01-10635	90	4	used	use	VERB
app01-10635	90	5	of	of	ADP
app01-10635	90	6	1	1	NUM
app01-10635	90	7	001	001	NUM
app01-10635	90	8	observations	observation	NOUN
app01-10635	90	9	contained	contain	VERB
app01-10635	90	10	two	two	NUM
app01-10635	90	11	key	key	ADJ
app01-10635	90	12	variables	variable	NOUN
app01-10635	90	13	:	:	PUNCT
app01-10635	90	14	i	i	PROPN
app01-10635	90	15	d	d	PROPN
app01-10635	90	16	and	and	CCONJ
app01-10635	90	17	railway	railway	NOUN
app01-10635	90	18	noise	noise	NOUN
app01-10635	90	19	values	value	NOUN
app01-10635	90	20	.	.	PUNCT
app01-10635	91	1	the	the	DET
app01-10635	91	2	i	i	PROPN
app01-10635	91	3	d	d	PROPN
app01-10635	91	4	variable	variable	NOUN
app01-10635	91	5	is	be	AUX
app01-10635	91	6	dimensionless	dimensionless	ADJ
app01-10635	91	7	and	and	CCONJ
app01-10635	91	8	indicates	indicate	VERB
app01-10635	91	9	the	the	DET
app01-10635	91	10	order	order	NOUN
app01-10635	91	11	of	of	ADP
app01-10635	91	12	observations	observation	NOUN
app01-10635	91	13	,	,	PUNCT
app01-10635	91	14	with	with	ADP
app01-10635	91	15	measurements	measurement	NOUN
app01-10635	91	16	taken	take	VERB
app01-10635	91	17	every	every	DET
app01-10635	91	18	0.25	0.25	NUM
app01-10635	91	19	m	m	NOUN
app01-10635	91	20	of	of	ADP
app01-10635	91	21	track	track	NOUN
app01-10635	91	22	.	.	PUNCT
app01-10635	92	1	the	the	DET
app01-10635	92	2	i	i	PROPN
app01-10635	92	3	d	d	PROPN
app01-10635	92	4	range	range	NOUN
app01-10635	92	5	is	be	AUX
app01-10635	92	6	from	from	ADP
app01-10635	92	7	0	0	NUM
app01-10635	92	8	to	to	ADP
app01-10635	92	9	1	1	NUM
app01-10635	92	10	000	000	NUM
app01-10635	92	11	,	,	PUNCT
app01-10635	92	12	which	which	PRON
app01-10635	92	13	means	mean	VERB
app01-10635	92	14	that	that	SCONJ
app01-10635	92	15	the	the	DET
app01-10635	92	16	measured	measure	VERB
app01-10635	92	17	track	track	NOUN
app01-10635	92	18	sample	sample	NOUN
app01-10635	92	19	is	be	AUX
app01-10635	92	20	250	250	NUM
app01-10635	92	21	m	m	VERB
app01-10635	92	22	long	long	ADJ
app01-10635	92	23	.	.	PUNCT
app01-10635	93	1	the	the	DET
app01-10635	93	2	next	next	ADJ
app01-10635	93	3	variable	variable	NOUN
app01-10635	93	4	is	be	AUX
app01-10635	93	5	the	the	DET
app01-10635	93	6	noise	noise	NOUN
app01-10635	93	7	in	in	ADP
app01-10635	93	8	db	db	PROPN
app01-10635	93	9	.	.	PUNCT
app01-10635	94	1	these	these	DET
app01-10635	94	2	values	value	NOUN
app01-10635	94	3	reflect	reflect	VERB
app01-10635	94	4	the	the	DET
app01-10635	94	5	amplitude	amplitude	NOUN
app01-10635	94	6	of	of	ADP
app01-10635	94	7	the	the	DET
app01-10635	94	8	z	z	NOUN
app01-10635	94	9	-	-	PUNCT
app01-10635	94	10	network	network	NOUN
app01-10635	94	11	(	(	PUNCT
app01-10635	94	12	unweighted	unweighted	ADJ
app01-10635	94	13	)	)	PUNCT
app01-10635	94	14	equivalent	equivalent	ADJ
app01-10635	94	15	sound	sound	NOUN
app01-10635	94	16	pressure	pressure	NOUN
app01-10635	94	17	level	level	NOUN
app01-10635	94	18	recorded	record	VERB
app01-10635	94	19	at	at	ADP
app01-10635	94	20	corresponding	correspond	VERB
app01-10635	94	21	i	i	PROPN
app01-10635	94	22	d	d	PROPN
app01-10635	94	23	points	point	NOUN
app01-10635	94	24	.	.	PUNCT
app01-10635	95	1	the	the	DET
app01-10635	95	2	range	range	NOUN
app01-10635	95	3	of	of	ADP
app01-10635	95	4	noise	noise	NOUN
app01-10635	95	5	values	value	NOUN
app01-10635	95	6	is	be	AUX
app01-10635	95	7	from	from	ADP
app01-10635	95	8	87.5	87.5	NUM
app01-10635	95	9	to	to	ADP
app01-10635	95	10	118.4	118.4	NUM
app01-10635	95	11	db	db	NOUN
app01-10635	95	12	.	.	PROPN
app01-10635	95	13	4	4	NUM
app01-10635	95	14	.	.	NOUN
app01-10635	95	15	results	result	NOUN
app01-10635	95	16	and	and	CCONJ
app01-10635	95	17	discussion	discussion	NOUN
app01-10635	95	18	a	a	DET
app01-10635	95	19	model	model	NOUN
app01-10635	95	20	was	be	AUX
app01-10635	95	21	defined	define	VERB
app01-10635	95	22	with	with	ADP
app01-10635	95	23	the	the	DET
app01-10635	95	24	parameters	parameter	NOUN
app01-10635	96	1	θ0	θ0	PROPN
app01-10635	96	2	=	=	SYM
app01-10635	96	3	90	90	NUM
app01-10635	96	4	and	and	CCONJ
app01-10635	96	5	θ1	θ1	NOUN
app01-10635	96	6	=	=	SYM
app01-10635	96	7	107	107	NUM
app01-10635	96	8	.	.	PUNCT
app01-10635	97	1	these	these	DET
app01-10635	97	2	values	value	NOUN
app01-10635	97	3	represent	represent	VERB
app01-10635	97	4	the	the	DET
app01-10635	97	5	mean	mean	ADJ
app01-10635	97	6	values	value	NOUN
app01-10635	97	7	obtained	obtain	VERB
app01-10635	97	8	from	from	ADP
app01-10635	97	9	the	the	DET
app01-10635	97	10	measured	measure	VERB
app01-10635	97	11	signal	signal	NOUN
app01-10635	97	12	,	,	PUNCT
app01-10635	97	13	which	which	PRON
app01-10635	97	14	was	be	AUX
app01-10635	97	15	segmented	segment	VERB
app01-10635	97	16	into	into	ADP
app01-10635	97	17	two	two	NUM
app01-10635	97	18	distinct	distinct	ADJ
app01-10635	97	19	models	model	NOUN
app01-10635	97	20	.	.	PUNCT
app01-10635	98	1	the	the	DET
app01-10635	98	2	signal	signal	NOUN
app01-10635	98	3	was	be	AUX
app01-10635	98	4	divided	divide	VERB
app01-10635	98	5	into	into	ADP
app01-10635	98	6	k	k	PROPN
app01-10635	98	7	samples	sample	NOUN
app01-10635	98	8	to	to	PART
app01-10635	98	9	determine	determine	VERB
app01-10635	98	10	the	the	DET
app01-10635	98	11	moment	moment	NOUN
app01-10635	98	12	of	of	ADP
app01-10635	98	13	signal	signal	ADJ
app01-10635	98	14	change	change	NOUN
app01-10635	98	15	.	.	PUNCT
app01-10635	99	1	figure	figure	NOUN
app01-10635	99	2	2	2	NUM
app01-10635	99	3	.	.	PUNCT
app01-10635	100	1	position	position	NOUN
app01-10635	100	2	of	of	ADP
app01-10635	100	3	the	the	DET
app01-10635	100	4	microphone	microphone	NOUN
app01-10635	100	5	for	for	ADP
app01-10635	100	6	measuring	measure	VERB
app01-10635	100	7	the	the	DET
app01-10635	100	8	contact	contact	NOUN
app01-10635	100	9	noise	noise	NOUN
app01-10635	100	10	between	between	ADP
app01-10635	100	11	the	the	DET
app01-10635	100	12	rail	rail	NOUN
app01-10635	100	13	wheel	wheel	NOUN
app01-10635	100	14	and	and	CCONJ
app01-10635	100	15	the	the	DET
app01-10635	100	16	rail	rail	NOUN
app01-10635	100	17	on	on	ADP
app01-10635	100	18	the	the	DET
app01-10635	100	19	mvžsv2	mvžsv2	NOUN
app01-10635	100	20	diagnostic	diagnostic	ADJ
app01-10635	100	21	vehicle	vehicle	NOUN
app01-10635	101	1	[	[	X
app01-10635	101	2	12	12	NUM
app01-10635	101	3	]	]	PUNCT
app01-10635	101	4	.	.	PUNCT
app01-10635	102	1	table	table	NOUN
app01-10635	102	2	1	1	NUM
app01-10635	102	3	presents	present	VERB
app01-10635	102	4	the	the	DET
app01-10635	102	5	number	number	NOUN
app01-10635	102	6	of	of	ADP
app01-10635	102	7	samples	sample	NOUN
app01-10635	102	8	on	on	ADP
app01-10635	102	9	which	which	PRON
app01-10635	102	10	sn	sn	PROPN
app01-10635	102	11	1	1	NUM
app01-10635	102	12	(	(	PUNCT
app01-10635	102	13	k	k	NOUN
app01-10635	102	14	)	)	PUNCT
app01-10635	102	15	changes	change	NOUN
app01-10635	102	16	from	from	ADP
app01-10635	102	17	θ0	θ0	NOUN
app01-10635	102	18	to	to	ADP
app01-10635	102	19	θ1	θ1	NOUN
app01-10635	102	20	for	for	ADP
app01-10635	102	21	different	different	ADJ
app01-10635	102	22	values	value	NOUN
app01-10635	102	23	of	of	ADP
app01-10635	102	24	n	n	NOUN
app01-10635	102	25	,	,	PUNCT
app01-10635	102	26	where	where	SCONJ
app01-10635	102	27	n	n	PRON
app01-10635	102	28	is	be	AUX
app01-10635	102	29	5	5	NUM
app01-10635	102	30	,	,	PUNCT
app01-10635	102	31	10	10	NUM
app01-10635	102	32	,	,	PUNCT
app01-10635	102	33	20	20	NUM
app01-10635	102	34	,	,	PUNCT
app01-10635	102	35	40	40	NUM
app01-10635	102	36	.	.	PUNCT
app01-10635	103	1	the	the	DET
app01-10635	103	2	threshold	threshold	NOUN
app01-10635	103	3	h	h	NOUN
app01-10635	103	4	was	be	AUX
app01-10635	103	5	established	establish	VERB
app01-10635	103	6	at	at	ADP
app01-10635	103	7	4.58	4.58	NUM
app01-10635	103	8	.	.	PUNCT
app01-10635	104	1	n	n	CCONJ
app01-10635	104	2	5	5	NUM
app01-10635	104	3	10	10	NUM
app01-10635	104	4	20	20	NUM
app01-10635	104	5	40	40	NUM
app01-10635	104	6	total	total	NOUN
app01-10635	104	7	15	15	NUM
app01-10635	104	8	9	9	NUM
app01-10635	104	9	5	5	NUM
app01-10635	104	10	3	3	NUM
app01-10635	104	11	table	table	NOUN
app01-10635	104	12	1	1	NUM
app01-10635	104	13	.	.	PUNCT
app01-10635	104	14	demonstration	demonstration	NOUN
app01-10635	104	15	of	of	ADP
app01-10635	104	16	the	the	DET
app01-10635	104	17	relationship	relationship	NOUN
app01-10635	104	18	between	between	ADP
app01-10635	104	19	segment	segment	NOUN
app01-10635	104	20	length	length	NOUN
app01-10635	104	21	n	n	NOUN
app01-10635	104	22	and	and	CCONJ
app01-10635	104	23	detection	detection	NOUN
app01-10635	104	24	sensitivity	sensitivity	NOUN
app01-10635	104	25	h.	h.	PROPN
app01-10635	104	26	figures	figure	NOUN
app01-10635	104	27	3–6	3–6	NUM
app01-10635	104	28	presents	present	VERB
app01-10635	104	29	a	a	DET
app01-10635	104	30	comprehensive	comprehensive	ADJ
app01-10635	104	31	chart	chart	NOUN
app01-10635	104	32	detailing	detail	VERB
app01-10635	104	33	the	the	DET
app01-10635	104	34	detection	detection	NOUN
app01-10635	104	35	of	of	ADP
app01-10635	104	36	changes	change	NOUN
app01-10635	104	37	in	in	ADP
app01-10635	104	38	railway	railway	NOUN
app01-10635	104	39	noise	noise	NOUN
app01-10635	104	40	.	.	PUNCT
app01-10635	105	1	the	the	DET
app01-10635	105	2	top	top	ADJ
app01-10635	105	3	graph	graph	NOUN
app01-10635	105	4	displays	display	VERB
app01-10635	105	5	the	the	DET
app01-10635	105	6	raw	raw	ADJ
app01-10635	105	7	signal	signal	NOUN
app01-10635	105	8	data	datum	NOUN
app01-10635	105	9	,	,	PUNCT
app01-10635	105	10	the	the	DET
app01-10635	105	11	middle	middle	ADJ
app01-10635	105	12	graph	graph	NOUN
app01-10635	105	13	illustrates	illustrate	VERB
app01-10635	105	14	the	the	DET
app01-10635	105	15	values	value	NOUN
app01-10635	105	16	of	of	ADP
app01-10635	105	17	the	the	DET
app01-10635	105	18	st	st	PROPN
app01-10635	105	19	statistic	statistic	PROPN
app01-10635	105	20	on	on	ADP
app01-10635	105	21	the	the	DET
app01-10635	105	22	k	k	NOUN
app01-10635	105	23	-	-	PUNCT
app01-10635	105	24	th	th	VERB
app01-10635	105	25	sample	sample	NOUN
app01-10635	105	26	,	,	PUNCT
app01-10635	105	27	and	and	CCONJ
app01-10635	105	28	the	the	DET
app01-10635	105	29	bottom	bottom	ADJ
app01-10635	105	30	graph	graph	NOUN
app01-10635	105	31	visualizes	visualize	VERB
app01-10635	105	32	the	the	DET
app01-10635	105	33	decision	decision	NOUN
app01-10635	105	34	-	-	PUNCT
app01-10635	105	35	making	make	VERB
app01-10635	105	36	process	process	NOUN
app01-10635	105	37	for	for	ADP
app01-10635	105	38	detecting	detect	VERB
app01-10635	105	39	changes	change	NOUN
app01-10635	105	40	in	in	ADP
app01-10635	105	41	the	the	DET
app01-10635	105	42	signal	signal	NOUN
app01-10635	105	43	,	,	PUNCT
app01-10635	105	44	based	base	VERB
app01-10635	105	45	on	on	ADP
app01-10635	105	46	the	the	DET
app01-10635	105	47	analysis	analysis	NOUN
app01-10635	105	48	of	of	ADP
app01-10635	105	49	sn	sn	PROPN
app01-10635	105	50	1	1	NUM
app01-10635	105	51	(	(	PUNCT
app01-10635	105	52	k	k	NOUN
app01-10635	105	53	)	)	PUNCT
app01-10635	105	54	and	and	CCONJ
app01-10635	105	55	h.	h.	PROPN
app01-10635	105	56	the	the	DET
app01-10635	105	57	coefficient	coefficient	NOUN
app01-10635	105	58	α	α	PRON
app01-10635	105	59	was	be	AUX
app01-10635	105	60	applied	apply	VERB
app01-10635	105	61	during	during	ADP
app01-10635	105	62	calculations	calculation	NOUN
app01-10635	105	63	over	over	ADP
app01-10635	105	64	small	small	ADJ
app01-10635	105	65	periods	period	NOUN
app01-10635	105	66	,	,	PUNCT
app01-10635	105	67	preserving	preserve	VERB
app01-10635	105	68	α	α	NOUN
app01-10635	105	69	=	=	NOUN
app01-10635	105	70	0.95	0.95	NUM
app01-10635	105	71	when	when	SCONJ
app01-10635	105	72	n	n	X
app01-10635	105	73	=	=	SYM
app01-10635	105	74	5	5	NUM
app01-10635	105	75	and	and	CCONJ
app01-10635	105	76	n	n	CCONJ
app01-10635	105	77	=	=	NUM
app01-10635	105	78	10	10	NUM
app01-10635	105	79	,	,	PUNCT
app01-10635	105	80	and	and	CCONJ
app01-10635	105	81	α	α	X
app01-10635	105	82	=	=	NOUN
app01-10635	105	83	1.0	1.0	NUM
app01-10635	105	84	when	when	SCONJ
app01-10635	105	85	n	n	X
app01-10635	105	86	is	be	AUX
app01-10635	105	87	20	20	NUM
app01-10635	105	88	and	and	CCONJ
app01-10635	105	89	40	40	NUM
app01-10635	105	90	.	.	PUNCT
app01-10635	106	1	for	for	ADP
app01-10635	106	2	each	each	DET
app01-10635	106	3	combination	combination	NOUN
app01-10635	106	4	of	of	ADP
app01-10635	106	5	parameters	parameter	NOUN
app01-10635	106	6	n	n	CCONJ
app01-10635	106	7	and	and	CCONJ
app01-10635	106	8	h	h	NOUN
app01-10635	106	9	,	,	PUNCT
app01-10635	106	10	the	the	DET
app01-10635	106	11	results	result	NOUN
app01-10635	106	12	have	have	AUX
app01-10635	106	13	shown	show	VERB
app01-10635	106	14	the	the	DET
app01-10635	106	15	number	number	NOUN
app01-10635	106	16	of	of	ADP
app01-10635	106	17	detected	detect	VERB
app01-10635	106	18	changes	change	NOUN
app01-10635	106	19	were	be	AUX
app01-10635	106	20	obtained	obtain	VERB
app01-10635	106	21	:	:	PUNCT
app01-10635	106	22	•	•	NOUN
app01-10635	106	23	at	at	ADP
app01-10635	106	24	n	n	NOUN
app01-10635	106	25	=	=	SYM
app01-10635	106	26	5	5	NUM
app01-10635	106	27	and	and	CCONJ
app01-10635	106	28	h	h	NOUN
app01-10635	106	29	=	=	NOUN
app01-10635	106	30	4.58	4.58	NUM
app01-10635	106	31	,	,	PUNCT
app01-10635	106	32	changes	change	NOUN
app01-10635	106	33	were	be	AUX
app01-10635	106	34	identified	identify	VERB
app01-10635	106	35	due	due	ADP
app01-10635	106	36	to	to	ADP
app01-10635	106	37	the	the	DET
app01-10635	106	38	high	high	ADJ
app01-10635	106	39	sensitivity	sensitivity	NOUN
app01-10635	106	40	of	of	ADP
app01-10635	106	41	the	the	DET
app01-10635	106	42	threshold	threshold	NOUN
app01-10635	106	43	,	,	PUNCT
app01-10635	106	44	•	•	ADV
app01-10635	106	45	at	at	ADP
app01-10635	106	46	n	n	NOUN
app01-10635	106	47	=	=	SYM
app01-10635	106	48	10	10	NUM
app01-10635	106	49	and	and	CCONJ
app01-10635	106	50	h	h	NOUN
app01-10635	106	51	=	=	NOUN
app01-10635	106	52	4.58	4.58	NUM
app01-10635	106	53	,	,	PUNCT
app01-10635	106	54	the	the	DET
app01-10635	106	55	sensitivity	sensitivity	NOUN
app01-10635	106	56	decreased	decrease	VERB
app01-10635	106	57	and	and	CCONJ
app01-10635	106	58	the	the	DET
app01-10635	106	59	number	number	NOUN
app01-10635	106	60	of	of	ADP
app01-10635	106	61	false	false	ADJ
app01-10635	106	62	alarms	alarm	NOUN
app01-10635	106	63	decreased	decrease	VERB
app01-10635	106	64	,	,	PUNCT
app01-10635	106	65	•	•	ADV
app01-10635	106	66	at	at	ADP
app01-10635	106	67	n	n	NOUN
app01-10635	106	68	=	=	SYM
app01-10635	106	69	20	20	NUM
app01-10635	106	70	and	and	CCONJ
app01-10635	106	71	h	h	NOUN
app01-10635	106	72	=	=	NOUN
app01-10635	106	73	4.58	4.58	NUM
app01-10635	106	74	,	,	PUNCT
app01-10635	106	75	the	the	DET
app01-10635	106	76	lowest	low	ADJ
app01-10635	106	77	number	number	NOUN
app01-10635	106	78	of	of	ADP
app01-10635	106	79	false	false	ADJ
app01-10635	106	80	alarms	alarm	NOUN
app01-10635	106	81	and	and	CCONJ
app01-10635	106	82	the	the	DET
app01-10635	106	83	most	most	ADV
app01-10635	106	84	accurate	accurate	ADJ
app01-10635	106	85	detection	detection	NOUN
app01-10635	106	86	of	of	ADP
app01-10635	106	87	changes	change	NOUN
app01-10635	106	88	were	be	AUX
app01-10635	106	89	recorded	record	VERB
app01-10635	106	90	,	,	PUNCT
app01-10635	106	91	•	•	ADP
app01-10635	106	92	at	at	ADP
app01-10635	106	93	n=	n=	ADJ
app01-10635	106	94	40	40	NUM
app01-10635	106	95	and	and	CCONJ
app01-10635	106	96	h	h	NOUN
app01-10635	107	1	=	=	NOUN
app01-10635	107	2	4.58	4.58	NUM
app01-10635	107	3	,	,	PUNCT
app01-10635	107	4	three	three	NUM
app01-10635	107	5	samples	sample	NOUN
app01-10635	107	6	exhibited	exhibit	VERB
app01-10635	107	7	a	a	DET
app01-10635	107	8	change	change	NOUN
app01-10635	107	9	in	in	ADP
app01-10635	107	10	the	the	DET
app01-10635	107	11	signal	signal	NOUN
app01-10635	107	12	,	,	PUNCT
app01-10635	107	13	and	and	CCONJ
app01-10635	107	14	no	no	DET
app01-10635	107	15	other	other	ADJ
app01-10635	107	16	notable	notable	ADJ
app01-10635	107	17	peaks	peak	NOUN
app01-10635	107	18	were	be	AUX
app01-10635	107	19	identified	identify	VERB
app01-10635	107	20	.	.	PUNCT
app01-10635	108	1	this	this	PRON
app01-10635	108	2	suggests	suggest	VERB
app01-10635	108	3	that	that	SCONJ
app01-10635	108	4	this	this	DET
app01-10635	108	5	specific	specific	ADJ
app01-10635	108	6	combination	combination	NOUN
app01-10635	108	7	of	of	ADP
app01-10635	108	8	segment	segment	NOUN
app01-10635	108	9	length	length	NOUN
app01-10635	108	10	and	and	CCONJ
app01-10635	108	11	threshold	threshold	NOUN
app01-10635	108	12	might	might	AUX
app01-10635	108	13	limit	limit	VERB
app01-10635	108	14	the	the	DET
app01-10635	108	15	detection	detection	NOUN
app01-10635	108	16	of	of	ADP
app01-10635	108	17	additional	additional	ADJ
app01-10635	108	18	signal	signal	ADJ
app01-10635	108	19	changes	change	NOUN
app01-10635	108	20	.	.	PUNCT
app01-10635	109	1	5	5	X
app01-10635	109	2	.	.	X
app01-10635	109	3	conclusions	conclusion	NOUN
app01-10635	109	4	listening	listen	VERB
app01-10635	109	5	to	to	ADP
app01-10635	109	6	the	the	DET
app01-10635	109	7	sound	sound	ADJ
app01-10635	109	8	recording	recording	NOUN
app01-10635	109	9	,	,	PUNCT
app01-10635	109	10	three	three	NUM
app01-10635	109	11	clear	clear	ADJ
app01-10635	109	12	sound	sound	ADJ
app01-10635	109	13	perceptions	perception	NOUN
app01-10635	109	14	can	can	AUX
app01-10635	109	15	be	be	AUX
app01-10635	109	16	heard	hear	VERB
app01-10635	109	17	in	in	ADP
app01-10635	109	18	the	the	DET
app01-10635	109	19	analysed	analyse	VERB
app01-10635	109	20	section	section	NOUN
app01-10635	109	21	of	of	ADP
app01-10635	109	22	track	track	NOUN
app01-10635	109	23	(	(	PUNCT
app01-10635	109	24	at	at	ADP
app01-10635	109	25	i	i	PROPN
app01-10635	109	26	d	d	PROPN
app01-10635	109	27	=	=	SYM
app01-10635	109	28	81	81	NUM
app01-10635	109	29	,	,	PUNCT
app01-10635	109	30	251	251	NUM
app01-10635	109	31	and	and	CCONJ
app01-10635	109	32	834	834	NUM
app01-10635	109	33	)	)	PUNCT
app01-10635	109	34	.	.	PUNCT
app01-10635	110	1	the	the	DET
app01-10635	110	2	abrupt	abrupt	ADJ
app01-10635	110	3	change	change	NOUN
app01-10635	110	4	at	at	ADP
app01-10635	110	5	i	i	PROPN
app01-10635	110	6	d	d	PROPN
app01-10635	110	7	=	=	SYM
app01-10635	110	8	81	81	NUM
app01-10635	110	9	was	be	AUX
app01-10635	110	10	only	only	ADV
app01-10635	110	11	detected	detect	VERB
app01-10635	110	12	at	at	ADP
app01-10635	110	13	n	n	NOUN
app01-10635	110	14	=	=	SYM
app01-10635	110	15	5	5	NUM
app01-10635	110	16	;	;	PUNCT
app01-10635	110	17	at	at	ADP
app01-10635	110	18	ids	id	NOUN
app01-10635	110	19	=	=	SYM
app01-10635	110	20	251	251	NUM
app01-10635	110	21	and	and	CCONJ
app01-10635	110	22	834	834	NUM
app01-10635	110	23	at	at	ADP
app01-10635	110	24	i	i	PROPN
app01-10635	110	25	d	d	PROPN
app01-10635	110	26	=	=	SYM
app01-10635	110	27	834	834	NUM
app01-10635	110	28	at	at	ADP
app01-10635	110	29	all	all	PRON
app01-10635	110	30	n	n	DET
app01-10635	110	31	values	value	NOUN
app01-10635	110	32	examined	examine	VERB
app01-10635	110	33	.	.	PUNCT
app01-10635	111	1	65	65	NUM
app01-10635	111	2	j.	j.	PROPN
app01-10635	111	3	kruntorád	kruntorád	PROPN
app01-10635	111	4	,	,	PUNCT
app01-10635	111	5	t.	t.	PROPN
app01-10635	111	6	reznychenko	reznychenko	PROPN
app01-10635	111	7	,	,	PUNCT
app01-10635	111	8	p.	p.	PROPN
app01-10635	111	9	červenka	červenka	PROPN
app01-10635	111	10	acta	acta	PROPN
app01-10635	111	11	polytechnica	polytechnica	PROPN
app01-10635	111	12	ctu	ctu	PROPN
app01-10635	111	13	proceedings	proceeding	NOUN
app01-10635	111	14	figure	figure	VERB
app01-10635	111	15	3	3	NUM
app01-10635	111	16	.	.	PUNCT
app01-10635	111	17	abrupt	abrupt	ADJ
app01-10635	111	18	change	change	VERB
app01-10635	111	19	the	the	DET
app01-10635	111	20	visualization	visualization	NOUN
app01-10635	111	21	of	of	ADP
app01-10635	111	22	railway	railway	NOUN
app01-10635	111	23	noise	noise	NOUN
app01-10635	111	24	using	use	VERB
app01-10635	111	25	likelihood	likelihood	NOUN
app01-10635	111	26	ratio	ratio	NOUN
app01-10635	111	27	detection	detection	NOUN
app01-10635	111	28	:	:	PUNCT
app01-10635	111	29	graph	graph	NOUN
app01-10635	111	30	of	of	ADP
app01-10635	111	31	signal	signal	ADJ
app01-10635	111	32	detection	detection	NOUN
app01-10635	111	33	with	with	ADP
app01-10635	111	34	the	the	DET
app01-10635	111	35	sample	sample	NOUN
app01-10635	111	36	length	length	NOUN
app01-10635	111	37	n	n	NOUN
app01-10635	111	38	=	=	SYM
app01-10635	111	39	5	5	X
app01-10635	111	40	.	.	X
app01-10635	111	41	figure	figure	NOUN
app01-10635	111	42	4	4	NUM
app01-10635	111	43	.	.	PUNCT
app01-10635	111	44	abrupt	abrupt	ADJ
app01-10635	111	45	change	change	VERB
app01-10635	111	46	the	the	DET
app01-10635	111	47	visualization	visualization	NOUN
app01-10635	111	48	of	of	ADP
app01-10635	111	49	railway	railway	NOUN
app01-10635	111	50	noise	noise	NOUN
app01-10635	111	51	using	use	VERB
app01-10635	111	52	likelihood	likelihood	NOUN
app01-10635	111	53	ratio	ratio	NOUN
app01-10635	111	54	detection	detection	NOUN
app01-10635	111	55	:	:	PUNCT
app01-10635	111	56	graph	graph	NOUN
app01-10635	111	57	of	of	ADP
app01-10635	111	58	signal	signal	ADJ
app01-10635	111	59	detection	detection	NOUN
app01-10635	111	60	with	with	ADP
app01-10635	111	61	the	the	DET
app01-10635	111	62	sample	sample	NOUN
app01-10635	111	63	length	length	NOUN
app01-10635	111	64	n	n	NOUN
app01-10635	111	65	=	=	NOUN
app01-10635	111	66	10	10	NUM
app01-10635	111	67	.	.	PUNCT
app01-10635	112	1	66	66	NUM
app01-10635	112	2	vol	vol	NOUN
app01-10635	112	3	.	.	PUNCT
app01-10635	113	1	52/2025	52/2025	NUM
app01-10635	113	2	abrupt	abrupt	ADJ
app01-10635	113	3	change	change	NOUN
app01-10635	113	4	detection	detection	NOUN
app01-10635	113	5	in	in	ADP
app01-10635	113	6	railway	railway	NOUN
app01-10635	113	7	noise	noise	NOUN
app01-10635	113	8	data	datum	NOUN
app01-10635	113	9	figure	figure	NOUN
app01-10635	113	10	5	5	NUM
app01-10635	113	11	.	.	PUNCT
app01-10635	113	12	abrupt	abrupt	ADJ
app01-10635	113	13	change	change	VERB
app01-10635	113	14	the	the	DET
app01-10635	113	15	visualization	visualization	NOUN
app01-10635	113	16	of	of	ADP
app01-10635	113	17	railway	railway	NOUN
app01-10635	113	18	noise	noise	NOUN
app01-10635	113	19	using	use	VERB
app01-10635	113	20	likelihood	likelihood	NOUN
app01-10635	113	21	ratio	ratio	NOUN
app01-10635	113	22	detection	detection	NOUN
app01-10635	113	23	:	:	PUNCT
app01-10635	113	24	graph	graph	NOUN
app01-10635	113	25	of	of	ADP
app01-10635	113	26	signal	signal	ADJ
app01-10635	113	27	detection	detection	NOUN
app01-10635	113	28	with	with	ADP
app01-10635	113	29	the	the	DET
app01-10635	113	30	sample	sample	NOUN
app01-10635	113	31	length	length	NOUN
app01-10635	113	32	n	n	NOUN
app01-10635	113	33	=	=	SYM
app01-10635	113	34	20	20	NUM
app01-10635	113	35	.	.	PUNCT
app01-10635	113	36	figure	figure	VERB
app01-10635	113	37	6	6	NUM
app01-10635	113	38	.	.	PUNCT
app01-10635	114	1	abrupt	abrupt	ADJ
app01-10635	114	2	change	change	VERB
app01-10635	114	3	the	the	DET
app01-10635	114	4	visualization	visualization	NOUN
app01-10635	114	5	of	of	ADP
app01-10635	114	6	railway	railway	NOUN
app01-10635	114	7	noise	noise	NOUN
app01-10635	114	8	using	use	VERB
app01-10635	114	9	likelihood	likelihood	NOUN
app01-10635	114	10	ratio	ratio	NOUN
app01-10635	114	11	detection	detection	NOUN
app01-10635	114	12	:	:	PUNCT
app01-10635	114	13	graph	graph	NOUN
app01-10635	114	14	of	of	ADP
app01-10635	114	15	signal	signal	ADJ
app01-10635	114	16	detection	detection	NOUN
app01-10635	114	17	with	with	ADP
app01-10635	114	18	the	the	DET
app01-10635	114	19	sample	sample	NOUN
app01-10635	114	20	length	length	NOUN
app01-10635	114	21	n	n	PROPN
app01-10635	114	22	=	=	NUM
app01-10635	114	23	40	40	NUM
app01-10635	114	24	.	.	PUNCT
app01-10635	115	1	67	67	NUM
app01-10635	115	2	j.	j.	PROPN
app01-10635	115	3	kruntorád	kruntorád	PROPN
app01-10635	115	4	,	,	PUNCT
app01-10635	115	5	t.	t.	PROPN
app01-10635	115	6	reznychenko	reznychenko	PROPN
app01-10635	115	7	,	,	PUNCT
app01-10635	115	8	p.	p.	PROPN
app01-10635	115	9	červenka	červenka	PROPN
app01-10635	115	10	acta	acta	PROPN
app01-10635	115	11	polytechnica	polytechnica	PROPN
app01-10635	115	12	ctu	ctu	NOUN
app01-10635	115	13	proceedings	proceeding	NOUN
app01-10635	115	14	the	the	DET
app01-10635	115	15	experiment	experiment	NOUN
app01-10635	115	16	demonstrated	demonstrate	VERB
app01-10635	115	17	that	that	SCONJ
app01-10635	115	18	the	the	DET
app01-10635	115	19	parameter	parameter	NOUN
app01-10635	115	20	n	n	PART
app01-10635	115	21	is	be	AUX
app01-10635	115	22	essential	essential	ADJ
app01-10635	115	23	for	for	ADP
app01-10635	115	24	the	the	DET
app01-10635	115	25	accurate	accurate	ADJ
app01-10635	115	26	detection	detection	NOUN
app01-10635	115	27	of	of	ADP
app01-10635	115	28	signal	signal	ADJ
app01-10635	115	29	changes	change	NOUN
app01-10635	115	30	.	.	PUNCT
app01-10635	116	1	shorter	short	ADJ
app01-10635	116	2	segments	segment	NOUN
app01-10635	116	3	(	(	PUNCT
app01-10635	116	4	n	n	NOUN
app01-10635	116	5	=	=	SYM
app01-10635	116	6	5	5	NUM
app01-10635	116	7	)	)	PUNCT
app01-10635	116	8	enhance	enhance	VERB
app01-10635	116	9	sensitivity	sensitivity	NOUN
app01-10635	116	10	but	but	CCONJ
app01-10635	116	11	increase	increase	VERB
app01-10635	116	12	the	the	DET
app01-10635	116	13	likelihood	likelihood	NOUN
app01-10635	116	14	of	of	ADP
app01-10635	116	15	false	false	ADJ
app01-10635	116	16	alarms	alarm	NOUN
app01-10635	116	17	.	.	PUNCT
app01-10635	117	1	the	the	DET
app01-10635	117	2	threshold	threshold	NOUN
app01-10635	117	3	h	h	NOUN
app01-10635	117	4	must	must	AUX
app01-10635	117	5	be	be	AUX
app01-10635	117	6	selected	select	VERB
app01-10635	117	7	to	to	PART
app01-10635	117	8	achieve	achieve	VERB
app01-10635	117	9	an	an	DET
app01-10635	117	10	optimal	optimal	ADJ
app01-10635	117	11	balance	balance	NOUN
app01-10635	117	12	between	between	ADP
app01-10635	117	13	sensitivity	sensitivity	NOUN
app01-10635	117	14	and	and	CCONJ
app01-10635	117	15	accuracy	accuracy	NOUN
app01-10635	117	16	.	.	PUNCT
app01-10635	118	1	with	with	ADP
app01-10635	118	2	a	a	DET
app01-10635	118	3	chosen	choose	VERB
app01-10635	118	4	threshold	threshold	NOUN
app01-10635	118	5	of	of	ADP
app01-10635	118	6	h	h	NOUN
app01-10635	118	7	=	=	NOUN
app01-10635	118	8	4.58	4.58	NUM
app01-10635	118	9	,	,	PUNCT
app01-10635	118	10	a	a	DET
app01-10635	118	11	value	value	NOUN
app01-10635	118	12	of	of	ADP
app01-10635	118	13	n	n	NOUN
app01-10635	118	14	in	in	ADP
app01-10635	118	15	the	the	DET
app01-10635	118	16	range	range	NOUN
app01-10635	118	17	20–40	20–40	NUM
app01-10635	118	18	seems	seem	VERB
app01-10635	118	19	to	to	PART
app01-10635	118	20	be	be	AUX
app01-10635	118	21	optimal	optimal	ADJ
app01-10635	118	22	.	.	PUNCT
app01-10635	119	1	this	this	DET
app01-10635	119	2	research	research	NOUN
app01-10635	119	3	paper	paper	NOUN
app01-10635	119	4	advances	advance	VERB
app01-10635	119	5	the	the	DET
app01-10635	119	6	knowledge	knowledge	NOUN
app01-10635	119	7	base	base	NOUN
app01-10635	119	8	and	and	CCONJ
app01-10635	119	9	capabilities	capability	NOUN
app01-10635	119	10	for	for	ADP
app01-10635	119	11	identifying	identify	VERB
app01-10635	119	12	railway	railway	NOUN
app01-10635	119	13	noise	noise	NOUN
app01-10635	119	14	,	,	PUNCT
app01-10635	119	15	paving	pave	VERB
app01-10635	119	16	the	the	DET
app01-10635	119	17	way	way	NOUN
app01-10635	119	18	for	for	ADP
app01-10635	119	19	more	more	ADV
app01-10635	119	20	effective	effective	ADJ
app01-10635	119	21	monitoring	monitoring	NOUN
app01-10635	119	22	and	and	CCONJ
app01-10635	119	23	maintenance	maintenance	NOUN
app01-10635	119	24	strategies	strategy	NOUN
app01-10635	119	25	.	.	PUNCT
app01-10635	120	1	ultimately	ultimately	ADV
app01-10635	120	2	,	,	PUNCT
app01-10635	120	3	this	this	DET
app01-10635	120	4	research	research	NOUN
app01-10635	120	5	contributes	contribute	VERB
app01-10635	120	6	to	to	ADP
app01-10635	120	7	the	the	DET
app01-10635	120	8	enhancement	enhancement	NOUN
app01-10635	120	9	of	of	ADP
app01-10635	120	10	railway	railway	NOUN
app01-10635	120	11	safety	safety	NOUN
app01-10635	120	12	and	and	CCONJ
app01-10635	120	13	reliability	reliability	NOUN
app01-10635	120	14	.	.	PUNCT
app01-10635	121	1	acknowledgements	acknowledgement	NOUN
app01-10635	121	2	this	this	DET
app01-10635	121	3	paper	paper	NOUN
app01-10635	121	4	has	have	AUX
app01-10635	121	5	been	be	AUX
app01-10635	121	6	financed	finance	VERB
app01-10635	121	7	with	with	ADP
app01-10635	121	8	the	the	DET
app01-10635	121	9	state	state	NOUN
app01-10635	121	10	support	support	NOUN
app01-10635	121	11	of	of	ADP
app01-10635	121	12	the	the	DET
app01-10635	121	13	technology	technology	NOUN
app01-10635	121	14	agency	agency	NOUN
app01-10635	121	15	of	of	ADP
app01-10635	121	16	the	the	DET
app01-10635	121	17	czech	czech	PROPN
app01-10635	121	18	republic	republic	NOUN
app01-10635	121	19	and	and	CCONJ
app01-10635	121	20	the	the	DET
app01-10635	121	21	ministry	ministry	PROPN
app01-10635	121	22	of	of	ADP
app01-10635	121	23	transport	transport	NOUN
app01-10635	121	24	of	of	ADP
app01-10635	121	25	the	the	DET
app01-10635	121	26	czech	czech	PROPN
app01-10635	121	27	republic	republic	NOUN
app01-10635	121	28	within	within	ADP
app01-10635	121	29	the	the	DET
app01-10635	121	30	project	project	NOUN
app01-10635	121	31	ck03000099	ck03000099	VERB
app01-10635	121	32	dynamic	dynamic	ADJ
app01-10635	121	33	opto	opto	ADJ
app01-10635	121	34	-	-	PUNCT
app01-10635	121	35	acoustic	acoustic	ADJ
app01-10635	121	36	method	method	NOUN
app01-10635	121	37	for	for	ADP
app01-10635	121	38	railway	railway	NOUN
app01-10635	121	39	superstructure	superstructure	NOUN
app01-10635	121	40	emission	emission	NOUN
app01-10635	121	41	noise	noise	NOUN
app01-10635	121	42	assessment	assessment	NOUN
app01-10635	121	43	within	within	ADP
app01-10635	121	44	the	the	DET
app01-10635	121	45	transport	transport	NOUN
app01-10635	121	46	2020	2020	NUM
app01-10635	121	47	+	+	SYM
app01-10635	121	48	programme	programme	NOUN
app01-10635	121	49	.	.	PUNCT
app01-10635	122	1	references	reference	NOUN
app01-10635	122	2	[	[	X
app01-10635	122	3	1	1	X
app01-10635	122	4	]	]	PUNCT
app01-10635	122	5	j.	j.	PROPN
app01-10635	122	6	kruntorád	kruntorád	PROPN
app01-10635	122	7	,	,	PUNCT
app01-10635	122	8	l.	l.	PROPN
app01-10635	122	9	týfa	týfa	PROPN
app01-10635	122	10	.	.	PUNCT
app01-10635	123	1	vision	vision	NOUN
app01-10635	123	2	zero	zero	NUM
app01-10635	123	3	application	application	NOUN
app01-10635	123	4	on	on	ADP
app01-10635	123	5	czech	czech	ADJ
app01-10635	123	6	railways	railway	NOUN
app01-10635	123	7	.	.	PUNCT
app01-10635	124	1	acta	acta	PROPN
app01-10635	124	2	polytechnica	polytechnica	PROPN
app01-10635	124	3	ctu	ctu	PROPN
app01-10635	124	4	proceedings	proceeding	NOUN
app01-10635	124	5	41:15–19	41:15–19	PROPN
app01-10635	124	6	,	,	PUNCT
app01-10635	124	7	2023	2023	NUM
app01-10635	124	8	.	.	PUNCT
app01-10635	125	1	https://doi.org/10.14311/app.2023.41.0015	https://doi.org/10.14311/app.2023.41.0015	NOUN
app01-10635	126	1	[	[	X
app01-10635	126	2	2	2	NUM
app01-10635	126	3	]	]	PUNCT
app01-10635	126	4	a.	a.	NOUN
app01-10635	126	5	ukil	ukil	PROPN
app01-10635	126	6	,	,	PUNCT
app01-10635	126	7	r.	r.	PROPN
app01-10635	126	8	živanović	živanović	PROPN
app01-10635	126	9	.	.	PUNCT
app01-10635	127	1	adjusted	adjust	VERB
app01-10635	127	2	haar	haar	PROPN
app01-10635	127	3	wavelet	wavelet	NOUN
app01-10635	127	4	for	for	ADP
app01-10635	127	5	application	application	NOUN
app01-10635	127	6	in	in	ADP
app01-10635	127	7	the	the	DET
app01-10635	127	8	power	power	NOUN
app01-10635	127	9	systems	system	NOUN
app01-10635	127	10	disturbance	disturbance	NOUN
app01-10635	127	11	analysis	analysis	NOUN
app01-10635	127	12	.	.	PUNCT
app01-10635	128	1	digital	digital	ADJ
app01-10635	128	2	signal	signal	NOUN
app01-10635	128	3	processing	processing	NOUN
app01-10635	128	4	18(2):103–115	18(2):103–115	NUM
app01-10635	128	5	,	,	PUNCT
app01-10635	128	6	2008	2008	NUM
app01-10635	128	7	.	.	PUNCT
app01-10635	129	1	https://doi.org/10.1016/j.dsp.2007.04.001	https://doi.org/10.1016/j.dsp.2007.04.001	NOUN
app01-10635	129	2	[	[	X
app01-10635	129	3	3	3	NUM
app01-10635	129	4	]	]	PUNCT
app01-10635	129	5	j.-p	j.-p	PROPN
app01-10635	129	6	.	.	PUNCT
app01-10635	130	1	qi	qi	PROPN
app01-10635	130	2	,	,	PUNCT
app01-10635	130	3	j.	j.	PROPN
app01-10635	130	4	qi	qi	PROPN
app01-10635	130	5	,	,	PUNCT
app01-10635	130	6	q.	q.	PROPN
app01-10635	130	7	zhang	zhang	PROPN
app01-10635	130	8	.	.	PUNCT
app01-10635	131	1	a	a	DET
app01-10635	131	2	fast	fast	ADJ
app01-10635	131	3	framework	framework	NOUN
app01-10635	131	4	for	for	ADP
app01-10635	131	5	abrupt	abrupt	ADJ
app01-10635	131	6	change	change	NOUN
app01-10635	131	7	detection	detection	NOUN
app01-10635	131	8	based	base	VERB
app01-10635	131	9	on	on	ADP
app01-10635	131	10	binary	binary	ADJ
app01-10635	131	11	search	search	NOUN
app01-10635	131	12	trees	tree	NOUN
app01-10635	131	13	and	and	CCONJ
app01-10635	131	14	kolmogorov	kolmogorov	ADJ
app01-10635	131	15	statistic	statistic	NOUN
app01-10635	131	16	.	.	PUNCT
app01-10635	132	1	computational	computational	ADJ
app01-10635	132	2	intelligence	intelligence	NOUN
app01-10635	132	3	and	and	CCONJ
app01-10635	132	4	neuroscience	neuroscience	NOUN
app01-10635	132	5	2016(1):8343187	2016(1):8343187	NOUN
app01-10635	132	6	,	,	PUNCT
app01-10635	132	7	2016	2016	NUM
app01-10635	132	8	.	.	PUNCT
app01-10635	133	1	https://doi.org/10.1155/2016/8343187	https://doi.org/10.1155/2016/8343187	PROPN
app01-10635	134	1	[	[	X
app01-10635	134	2	4	4	NUM
app01-10635	134	3	]	]	PUNCT
app01-10635	134	4	m.	m.	PROPN
app01-10635	134	5	f.	f.	PROPN
app01-10635	134	6	r.	r.	PROPN
app01-10635	134	7	chowdhury	chowdhury	PROPN
app01-10635	134	8	,	,	PUNCT
app01-10635	134	9	s.-a	s.-a	NOUN
app01-10635	134	10	.	.	PUNCT
app01-10635	135	1	selouani	selouani	PROPN
app01-10635	135	2	,	,	PUNCT
app01-10635	135	3	d.	d.	PROPN
app01-10635	135	4	o’shaughnessy	o’shaughnessy	PROPN
app01-10635	135	5	.	.	PUNCT
app01-10635	136	1	bayesian	bayesian	NOUN
app01-10635	136	2	on	on	ADP
app01-10635	136	3	-	-	PUNCT
app01-10635	136	4	line	line	NOUN
app01-10635	136	5	spectral	spectral	ADJ
app01-10635	136	6	change	change	NOUN
app01-10635	136	7	point	point	NOUN
app01-10635	136	8	detection	detection	NOUN
app01-10635	136	9	:	:	PUNCT
app01-10635	136	10	a	a	DET
app01-10635	136	11	soft	soft	ADJ
app01-10635	136	12	computing	computing	NOUN
app01-10635	136	13	approach	approach	NOUN
app01-10635	136	14	for	for	ADP
app01-10635	136	15	on	on	ADP
app01-10635	136	16	-	-	PUNCT
app01-10635	136	17	line	line	NOUN
app01-10635	136	18	asr	asr	NOUN
app01-10635	136	19	.	.	PUNCT
app01-10635	137	1	international	international	ADJ
app01-10635	137	2	journal	journal	PROPN
app01-10635	137	3	of	of	ADP
app01-10635	137	4	speech	speech	NOUN
app01-10635	137	5	technology	technology	NOUN
app01-10635	137	6	15(1):5–23	15(1):5–23	PROPN
app01-10635	137	7	,	,	PUNCT
app01-10635	137	8	2012	2012	NUM
app01-10635	137	9	.	.	PUNCT
app01-10635	138	1	https://doi.org/10.1007/s10772-011-9116-2	https://doi.org/10.1007/s10772-011-9116-2	NUM
app01-10635	139	1	[	[	X
app01-10635	139	2	5	5	NUM
app01-10635	139	3	]	]	PUNCT
app01-10635	139	4	q.	q.	PROPN
app01-10635	139	5	liu	liu	PROPN
app01-10635	139	6	,	,	PUNCT
app01-10635	139	7	s.	s.	PROPN
app01-10635	139	8	wan	wan	PROPN
app01-10635	139	9	,	,	PUNCT
app01-10635	139	10	b.	b.	PROPN
app01-10635	139	11	gu	gu	PROPN
app01-10635	139	12	.	.	PUNCT
app01-10635	140	1	a	a	DET
app01-10635	140	2	review	review	NOUN
app01-10635	140	3	of	of	ADP
app01-10635	140	4	the	the	DET
app01-10635	140	5	detection	detection	NOUN
app01-10635	140	6	methods	method	NOUN
app01-10635	140	7	for	for	ADP
app01-10635	140	8	climate	climate	NOUN
app01-10635	140	9	regime	regime	NOUN
app01-10635	140	10	shifts	shift	NOUN
app01-10635	140	11	.	.	PUNCT
app01-10635	141	1	discrete	discrete	ADJ
app01-10635	141	2	dynamics	dynamic	NOUN
app01-10635	141	3	in	in	ADP
app01-10635	141	4	nature	nature	NOUN
app01-10635	141	5	and	and	CCONJ
app01-10635	141	6	society	society	NOUN
app01-10635	141	7	2016(1):3536183	2016(1):3536183	NUM
app01-10635	141	8	,	,	PUNCT
app01-10635	141	9	2016	2016	NUM
app01-10635	141	10	.	.	PUNCT
app01-10635	142	1	https://doi.org/10.1155/2016/3536183	https://doi.org/10.1155/2016/3536183	PROPN
app01-10635	143	1	[	[	X
app01-10635	143	2	6	6	NUM
app01-10635	143	3	]	]	PUNCT
app01-10635	143	4	m.	m.	PROPN
app01-10635	143	5	quade	quade	PROPN
app01-10635	143	6	,	,	PUNCT
app01-10635	143	7	m.	m.	PROPN
app01-10635	143	8	abel	abel	PROPN
app01-10635	143	9	,	,	PUNCT
app01-10635	143	10	j.	j.	PROPN
app01-10635	143	11	nathan	nathan	PROPN
app01-10635	143	12	kutz	kutz	PROPN
app01-10635	143	13	,	,	PUNCT
app01-10635	143	14	s.	s.	PROPN
app01-10635	143	15	l.	l.	PROPN
app01-10635	143	16	brunton	brunton	PROPN
app01-10635	143	17	.	.	PUNCT
app01-10635	144	1	sparse	sparse	ADJ
app01-10635	144	2	identification	identification	NOUN
app01-10635	144	3	of	of	ADP
app01-10635	144	4	nonlinear	nonlinear	ADJ
app01-10635	144	5	dynamics	dynamic	NOUN
app01-10635	144	6	for	for	ADP
app01-10635	144	7	rapid	rapid	ADJ
app01-10635	144	8	model	model	NOUN
app01-10635	144	9	recovery	recovery	NOUN
app01-10635	144	10	.	.	PUNCT
app01-10635	145	1	chaos	chaos	NOUN
app01-10635	145	2	:	:	PUNCT
app01-10635	145	3	an	an	DET
app01-10635	145	4	interdisciplinary	interdisciplinary	ADJ
app01-10635	145	5	journal	journal	NOUN
app01-10635	145	6	of	of	ADP
app01-10635	145	7	nonlinear	nonlinear	ADJ
app01-10635	145	8	science	science	NOUN
app01-10635	145	9	28(6):063116	28(6):063116	PROPN
app01-10635	145	10	,	,	PUNCT
app01-10635	145	11	2018	2018	NUM
app01-10635	145	12	.	.	PUNCT
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app01-10635	147	1	[	[	X
app01-10635	147	2	7	7	X
app01-10635	147	3	]	]	X
app01-10635	147	4	h.	h.	PROPN
app01-10635	147	5	zhuang	zhuang	PROPN
app01-10635	147	6	,	,	PUNCT
app01-10635	147	7	z.	z.	PROPN
app01-10635	147	8	tan	tan	PROPN
app01-10635	147	9	,	,	PUNCT
app01-10635	147	10	k.	k.	PROPN
app01-10635	147	11	deng	deng	PROPN
app01-10635	147	12	,	,	PUNCT
app01-10635	147	13	g.	g.	PROPN
app01-10635	147	14	yao	yao	PROPN
app01-10635	147	15	.	.	PUNCT
app01-10635	148	1	adaptive	adaptive	ADJ
app01-10635	148	2	generalized	generalized	ADJ
app01-10635	148	3	likelihood	likelihood	NOUN
app01-10635	148	4	ratio	ratio	NOUN
app01-10635	148	5	test	test	NOUN
app01-10635	148	6	for	for	ADP
app01-10635	148	7	change	change	NOUN
app01-10635	148	8	detection	detection	NOUN
app01-10635	148	9	in	in	ADP
app01-10635	148	10	sar	sar	PROPN
app01-10635	148	11	images	image	NOUN
app01-10635	148	12	.	.	PUNCT
app01-10635	149	1	ieee	ieee	NOUN
app01-10635	149	2	geoscience	geoscience	PROPN
app01-10635	149	3	and	and	CCONJ
app01-10635	149	4	remote	remote	ADJ
app01-10635	149	5	sensing	sense	VERB
app01-10635	149	6	letters	letter	NOUN
app01-10635	149	7	17(3):416–420	17(3):416–420	NUM
app01-10635	149	8	,	,	PUNCT
app01-10635	149	9	2020	2020	NUM
app01-10635	149	10	.	.	PUNCT
app01-10635	150	1	https://doi.org/10.1109/lgrs.2019.2922198	https://doi.org/10.1109/lgrs.2019.2922198	PROPN
app01-10635	150	2	[	[	X
app01-10635	150	3	8	8	NUM
app01-10635	150	4	]	]	X
app01-10635	150	5	s.	s.	PROPN
app01-10635	150	6	mariani	mariani	PROPN
app01-10635	150	7	,	,	PUNCT
app01-10635	150	8	p.	p.	NOUN
app01-10635	150	9	cawley	cawley	NOUN
app01-10635	150	10	.	.	PUNCT
app01-10635	151	1	change	change	NOUN
app01-10635	151	2	detection	detection	NOUN
app01-10635	151	3	using	use	VERB
app01-10635	151	4	the	the	DET
app01-10635	151	5	generalized	generalized	ADJ
app01-10635	151	6	likelihood	likelihood	NOUN
app01-10635	151	7	ratio	ratio	NOUN
app01-10635	151	8	method	method	NOUN
app01-10635	151	9	to	to	PART
app01-10635	151	10	improve	improve	VERB
app01-10635	151	11	the	the	DET
app01-10635	151	12	sensitivity	sensitivity	NOUN
app01-10635	151	13	of	of	ADP
app01-10635	151	14	guided	guide	VERB
app01-10635	151	15	wave	wave	NOUN
app01-10635	151	16	structural	structural	ADJ
app01-10635	151	17	health	health	NOUN
app01-10635	151	18	monitoring	monitoring	NOUN
app01-10635	151	19	systems	system	NOUN
app01-10635	151	20	.	.	PUNCT
app01-10635	152	1	structural	structural	ADJ
app01-10635	152	2	health	health	NOUN
app01-10635	152	3	monitoring	monitor	VERB
app01-10635	152	4	20(6):3201–3226	20(6):3201–3226	NUM
app01-10635	152	5	,	,	PUNCT
app01-10635	152	6	2021	2021	NUM
app01-10635	152	7	.	.	PUNCT
app01-10635	153	1	https://doi.org/10.1177/1475921720981831	https://doi.org/10.1177/1475921720981831	X
app01-10635	154	1	[	[	X
app01-10635	154	2	9	9	NUM
app01-10635	154	3	]	]	PUNCT
app01-10635	154	4	m.	m.	NOUN
app01-10635	154	5	basseville	basseville	NOUN
app01-10635	154	6	,	,	PUNCT
app01-10635	154	7	i.	i.	PROPN
app01-10635	154	8	v.	v.	PROPN
app01-10635	154	9	nikiforov	nikiforov	PROPN
app01-10635	154	10	.	.	PUNCT
app01-10635	155	1	detection	detection	NOUN
app01-10635	155	2	of	of	ADP
app01-10635	155	3	abrupt	abrupt	ADJ
app01-10635	155	4	changes	change	NOUN
app01-10635	155	5	:	:	PUNCT
app01-10635	155	6	theory	theory	NOUN
app01-10635	155	7	and	and	CCONJ
app01-10635	155	8	application	application	NOUN
app01-10635	155	9	.	.	PUNCT
app01-10635	156	1	prentice	prentice	NOUN
app01-10635	156	2	-	-	PUNCT
app01-10635	156	3	hall	hall	NOUN
app01-10635	156	4	,	,	PUNCT
app01-10635	156	5	new	new	PROPN
app01-10635	156	6	jersey	jersey	PROPN
app01-10635	156	7	,	,	PUNCT
app01-10635	156	8	1993	1993	NUM
app01-10635	156	9	.	.	PUNCT
app01-10635	157	1	isbn	isbn	ADJ
app01-10635	157	2	978	978	NUM
app01-10635	157	3	-	-	SYM
app01-10635	157	4	0	0	NUM
app01-10635	157	5	-	-	PUNCT
app01-10635	157	6	13	13	NUM
app01-10635	157	7	-	-	PUNCT
app01-10635	157	8	126780	126780	NUM
app01-10635	157	9	-	-	PUNCT
app01-10635	157	10	0	0	NUM
app01-10635	157	11	.	.	PUNCT
app01-10635	158	1	[	[	X
app01-10635	158	2	10	10	NUM
app01-10635	158	3	]	]	PUNCT
app01-10635	158	4	k.	k.	PROPN
app01-10635	158	5	s.	s.	PROPN
app01-10635	158	6	riedel	riedel	PROPN
app01-10635	158	7	.	.	PUNCT
app01-10635	159	1	detection	detection	NOUN
app01-10635	159	2	of	of	ADP
app01-10635	159	3	abrupt	abrupt	ADJ
app01-10635	159	4	changes	change	NOUN
app01-10635	159	5	:	:	PUNCT
app01-10635	159	6	theory	theory	NOUN
app01-10635	159	7	and	and	CCONJ
app01-10635	159	8	application	application	NOUN
app01-10635	159	9	.	.	PUNCT
app01-10635	160	1	technometrics	technometrics	PROPN
app01-10635	160	2	36(3):326–327	36(3):326–327	PROPN
app01-10635	160	3	,	,	PUNCT
app01-10635	160	4	1994	1994	NUM
app01-10635	160	5	.	.	PUNCT
app01-10635	161	1	https://doi.org/10.1080/00401706.1994.10485821	https://doi.org/10.1080/00401706.1994.10485821	NOUN
app01-10635	162	1	[	[	X
app01-10635	162	2	11	11	NUM
app01-10635	162	3	]	]	PUNCT
app01-10635	162	4	j.	j.	PROPN
app01-10635	162	5	kruntorád	kruntorád	PROPN
app01-10635	162	6	,	,	PUNCT
app01-10635	162	7	l.	l.	PROPN
app01-10635	162	8	týfa	týfa	PROPN
app01-10635	162	9	,	,	PUNCT
app01-10635	162	10	o.	o.	PROPN
app01-10635	162	11	simon	simon	PROPN
app01-10635	162	12	.	.	PUNCT
app01-10635	163	1	analysis	analysis	NOUN
app01-10635	163	2	of	of	ADP
app01-10635	163	3	noise	noise	NOUN
app01-10635	163	4	emissions	emission	NOUN
app01-10635	163	5	at	at	ADP
app01-10635	163	6	wheel	wheel	NOUN
app01-10635	163	7	-	-	PUNCT
app01-10635	163	8	rail	rail	NOUN
app01-10635	163	9	contact	contact	NOUN
app01-10635	163	10	.	.	PUNCT
app01-10635	164	1	in	in	ADP
app01-10635	164	2	o.	o.	PROPN
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app01-10635	164	4	,	,	PUNCT
app01-10635	164	5	i.	i.	NOUN
app01-10635	164	6	yatskiv	yatskiv	PROPN
app01-10635	164	7	(	(	PUNCT
app01-10635	164	8	jackiva	jackiva	NOUN
app01-10635	164	9	)	)	PUNCT
app01-10635	164	10	,	,	PUNCT
app01-10635	164	11	p.	p.	PROPN
app01-10635	164	12	skačkauskas	skačkauskas	PROPN
app01-10635	164	13	,	,	PUNCT
app01-10635	164	14	et	et	PROPN
app01-10635	164	15	al	al	PROPN
app01-10635	164	16	.	.	PUNCT
app01-10635	165	1	(	(	PUNCT
app01-10635	165	2	eds	ed	NOUN
app01-10635	165	3	.	.	PUNCT
app01-10635	165	4	)	)	PUNCT
app01-10635	165	5	,	,	PUNCT
app01-10635	165	6	transbaltica	transbaltica	INTJ
app01-10635	165	7	xv	xv	PROPN
app01-10635	165	8	:	:	PUNCT
app01-10635	165	9	transportation	transportation	NOUN
app01-10635	165	10	science	science	NOUN
app01-10635	165	11	and	and	CCONJ
app01-10635	165	12	technology	technology	NOUN
app01-10635	165	13	,	,	PUNCT
app01-10635	165	14	pp	pp	ADV
app01-10635	165	15	.	.	PUNCT
app01-10635	166	1	502–511	502–511	NUM
app01-10635	166	2	.	.	PUNCT
app01-10635	167	1	springer	springer	PROPN
app01-10635	167	2	nature	nature	PROPN
app01-10635	167	3	switzerland	switzerland	PROPN
app01-10635	167	4	,	,	PUNCT
app01-10635	167	5	cham	cham	PROPN
app01-10635	167	6	,	,	PUNCT
app01-10635	167	7	2025	2025	NUM
app01-10635	167	8	.	.	PUNCT
app01-10635	168	1	isbn	isbn	ADJ
app01-10635	168	2	978	978	NUM
app01-10635	168	3	-	-	SYM
app01-10635	168	4	3	3	NUM
app01-10635	168	5	-	-	PUNCT
app01-10635	168	6	031	031	NUM
app01-10635	168	7	-	-	PUNCT
app01-10635	168	8	85390	85390	NUM
app01-10635	168	9	-	-	SYM
app01-10635	168	10	6	6	NUM
app01-10635	168	11	.	.	PUNCT
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app01-10635	169	1	[	[	X
app01-10635	169	2	12	12	NUM
app01-10635	169	3	]	]	PUNCT
app01-10635	169	4	l.	l.	PROPN
app01-10635	169	5	ládyš	ládyš	PROPN
app01-10635	169	6	,	,	PUNCT
app01-10635	169	7	o.	o.	PROPN
app01-10635	169	8	simon	simon	PROPN
app01-10635	169	9	,	,	PUNCT
app01-10635	169	10	m.	m.	NOUN
app01-10635	169	11	ládyš	ládyš	PROPN
app01-10635	169	12	,	,	PUNCT
app01-10635	169	13	et	et	PROPN
app01-10635	169	14	al	al	PROPN
app01-10635	169	15	.	.	PUNCT
app01-10635	170	1	ck03000099	ck03000099	PROPN
app01-10635	170	2	dynamická	dynamická	NOUN
app01-10635	170	3	opto	opto	ADJ
app01-10635	170	4	-	-	PUNCT
app01-10635	170	5	akustická	akustická	NOUN
app01-10635	170	6	metoda	metoda	PROPN
app01-10635	170	7	hodnocení	hodnocení	PROPN
app01-10635	170	8	emisní	emisní	PROPN
app01-10635	170	9	hlučnosti	hlučnosti	PUNCT
app01-10635	170	10	železničního	železničního	PROPN
app01-10635	170	11	svršku	svršku	PROPN
app01-10635	170	12	.	.	PUNCT
app01-10635	170	13	interim	interim	PROPN
app01-10635	170	14	report	report	NOUN
app01-10635	170	15	2023	2023	NUM
app01-10635	170	16	,	,	PUNCT
app01-10635	170	17	ekola	ekola	PROPN
app01-10635	170	18	group	group	NOUN
app01-10635	170	19	,	,	PUNCT
app01-10635	170	20	prague	prague	PROPN
app01-10635	170	21	,	,	PUNCT
app01-10635	170	22	2024	2024	NUM
app01-10635	170	23	.	.	PUNCT
app01-10635	171	1	68	68	NUM
app01-10635	171	2	https://doi.org/10.14311/app.2023.41.0015	https://doi.org/10.14311/app.2023.41.0015	NOUN
app01-10635	171	3	https://doi.org/10.1016/j.dsp.2007.04.001	https://doi.org/10.1016/j.dsp.2007.04.001	ADJ
app01-10635	171	4	https://doi.org/10.1155/2016/8343187	https://doi.org/10.1155/2016/8343187	PROPN
app01-10635	171	5	https://doi.org/10.1007/s10772-011-9116-2	https://doi.org/10.1007/s10772-011-9116-2	NUM
app01-10635	171	6	https://doi.org/10.1155/2016/3536183	https://doi.org/10.1155/2016/3536183	NOUN
app01-10635	171	7	https://doi.org/10.1063/1.5027470	https://doi.org/10.1063/1.5027470	PROPN
app01-10635	171	8	https://doi.org/10.1109/lgrs.2019.2922198	https://doi.org/10.1109/lgrs.2019.2922198	PROPN
app01-10635	171	9	https://doi.org/10.1177/1475921720981831	https://doi.org/10.1177/1475921720981831	PROPN
app01-10635	171	10	https://doi.org/10.1080/00401706.1994.10485821	https://doi.org/10.1080/00401706.1994.10485821	NOUN
app01-10635	171	11	https://doi.org/10.1007/978-3-031-85390-6_47	https://doi.org/10.1007/978-3-031-85390-6_47	PROPN
app01-10635	171	12	acta	acta	PROPN
app01-10635	171	13	polytechnica	polytechnica	PROPN
app01-10635	171	14	ctu	ctu	NOUN
app01-10635	171	15	proceedings	proceeding	NOUN
app01-10635	171	16	52:63–68	52:63–68	NUM
app01-10635	171	17	,	,	PUNCT
app01-10635	171	18	2025	2025	NUM
app01-10635	171	19	1	1	NUM
app01-10635	171	20	introduction	introduction	NOUN
app01-10635	171	21	2	2	NUM
app01-10635	171	22	theoretical	theoretical	ADJ
app01-10635	171	23	background	background	NOUN
app01-10635	171	24	2.1	2.1	NUM
app01-10635	171	25	current	current	ADJ
app01-10635	171	26	methods	method	NOUN
app01-10635	171	27	used	use	VERB
app01-10635	171	28	2.2	2.2	NUM
app01-10635	171	29	problem	problem	NOUN
app01-10635	171	30	formulation	formulation	NOUN
app01-10635	171	31	2.3	2.3	NUM
app01-10635	171	32	likelihood	likelihood	NOUN
app01-10635	171	33	-	-	PUNCT
app01-10635	171	34	ratio	ratio	NOUN
app01-10635	171	35	change	change	NOUN
app01-10635	171	36	detection	detection	NOUN
app01-10635	171	37	3	3	NUM
app01-10635	171	38	railway	railway	NOUN
app01-10635	171	39	noise	noise	NOUN
app01-10635	171	40	data	datum	NOUN
app01-10635	171	41	4	4	NUM
app01-10635	171	42	results	result	NOUN
app01-10635	171	43	and	and	CCONJ
app01-10635	171	44	discussion	discussion	NOUN
app01-10635	171	45	5	5	NUM
app01-10635	171	46	conclusions	conclusion	NOUN
app01-10635	171	47	acknowledgements	acknowledgement	NOUN
app01-10635	171	48	references	reference	NOUN