id	sid	tid	token	lemma	pos
ijassa-1351	1	1	adv	adv	PROPN
ijassa-1351	1	2	syst	syst	PROPN
ijassa-1351	1	3	sci	sci	PROPN
ijassa-1351	1	4	appl	appl	PROPN
ijassa-1351	1	5	2023	2023	NUM
ijassa-1351	1	6	;	;	PUNCT
ijassa-1351	1	7	02:99–114	02:99–114	NUM
ijassa-1351	1	8	published	publish	VERB
ijassa-1351	1	9	online	online	ADV
ijassa-1351	1	10	at	at	ADP
ijassa-1351	1	11	https://ijassa.ipu.ru	https://ijassa.ipu.ru	ADV
ijassa-1351	1	12	.	.	PUNCT
ijassa-1351	2	1	on	on	ADP
ijassa-1351	2	2	estimating	estimate	VERB
ijassa-1351	2	3	the	the	DET
ijassa-1351	2	4	characteristics	characteristic	NOUN
ijassa-1351	2	5	of	of	ADP
ijassa-1351	2	6	a	a	DET
ijassa-1351	2	7	fork	fork	NOUN
ijassa-1351	2	8	-	-	PUNCT
ijassa-1351	2	9	join	join	NOUN
ijassa-1351	2	10	queueing	queue	VERB
ijassa-1351	2	11	system	system	NOUN
ijassa-1351	2	12	with	with	ADP
ijassa-1351	2	13	poisson	poisson	NOUN
ijassa-1351	2	14	input	input	NOUN
ijassa-1351	2	15	and	and	CCONJ
ijassa-1351	2	16	exponential	exponential	NOUN
ijassa-1351	2	17	service	service	NOUN
ijassa-1351	2	18	times	times	PROPN
ijassa-1351	2	19	anastasia	anastasia	PROPN
ijassa-1351	2	20	v.	v.	PROPN
ijassa-1351	2	21	gorbunova1	gorbunova1	PROPN
ijassa-1351	2	22	*	*	PROPN
ijassa-1351	2	23	,	,	PUNCT
ijassa-1351	2	24	alexey	alexey	PROPN
ijassa-1351	2	25	v.	v.	PROPN
ijassa-1351	2	26	lebedev2	lebedev2	PROPN
ijassa-1351	2	27	1v.a	1v.a	NUM
ijassa-1351	2	28	.	.	PUNCT
ijassa-1351	2	29	trapeznikov	trapeznikov	PROPN
ijassa-1351	2	30	institute	institute	PROPN
ijassa-1351	2	31	of	of	ADP
ijassa-1351	2	32	control	control	PROPN
ijassa-1351	2	33	sciences	sciences	PROPN
ijassa-1351	2	34	of	of	ADP
ijassa-1351	2	35	russian	russian	ADJ
ijassa-1351	2	36	academy	academy	PROPN
ijassa-1351	2	37	of	of	ADP
ijassa-1351	2	38	sciences	sciences	PROPN
ijassa-1351	2	39	,	,	PUNCT
ijassa-1351	2	40	moscow	moscow	PROPN
ijassa-1351	2	41	,	,	PUNCT
ijassa-1351	2	42	russia	russia	PROPN
ijassa-1351	2	43	2lomonosov	2lomonosov	NUM
ijassa-1351	2	44	moscow	moscow	PROPN
ijassa-1351	2	45	state	state	PROPN
ijassa-1351	2	46	university	university	PROPN
ijassa-1351	2	47	,	,	PUNCT
ijassa-1351	2	48	moscow	moscow	PROPN
ijassa-1351	2	49	,	,	PUNCT
ijassa-1351	2	50	russia	russia	PROPN
ijassa-1351	2	51	abstract	abstract	NOUN
ijassa-1351	2	52	:	:	PUNCT
ijassa-1351	2	53	the	the	DET
ijassa-1351	2	54	paper	paper	NOUN
ijassa-1351	2	55	studies	study	VERB
ijassa-1351	2	56	the	the	DET
ijassa-1351	2	57	classical	classical	ADJ
ijassa-1351	2	58	fork	fork	NOUN
ijassa-1351	2	59	-	-	PUNCT
ijassa-1351	2	60	join	join	NOUN
ijassa-1351	2	61	queueing	queue	VERB
ijassa-1351	2	62	system	system	NOUN
ijassa-1351	2	63	with	with	ADP
ijassa-1351	2	64	m	m	PROPN
ijassa-1351	2	65	|m	|m	NOUN
ijassa-1351	2	66	|1	|1	DET
ijassa-1351	2	67	subsystems	subsystem	NOUN
ijassa-1351	2	68	.	.	PUNCT
ijassa-1351	3	1	the	the	DET
ijassa-1351	3	2	analysis	analysis	NOUN
ijassa-1351	3	3	of	of	ADP
ijassa-1351	3	4	this	this	DET
ijassa-1351	3	5	system	system	NOUN
ijassa-1351	3	6	is	be	AUX
ijassa-1351	3	7	still	still	ADV
ijassa-1351	3	8	relevant	relevant	ADJ
ijassa-1351	3	9	due	due	ADP
ijassa-1351	3	10	to	to	ADP
ijassa-1351	3	11	the	the	DET
ijassa-1351	3	12	lack	lack	NOUN
ijassa-1351	3	13	of	of	ADP
ijassa-1351	3	14	exact	exact	ADJ
ijassa-1351	3	15	solutions	solution	NOUN
ijassa-1351	3	16	for	for	ADP
ijassa-1351	3	17	assessing	assess	VERB
ijassa-1351	3	18	its	its	PRON
ijassa-1351	3	19	performance	performance	NOUN
ijassa-1351	3	20	characteristics	characteristic	NOUN
ijassa-1351	3	21	if	if	SCONJ
ijassa-1351	3	22	the	the	DET
ijassa-1351	3	23	number	number	NOUN
ijassa-1351	3	24	of	of	ADP
ijassa-1351	3	25	subsystems	subsystem	NOUN
ijassa-1351	3	26	exceeds	exceed	VERB
ijassa-1351	3	27	two	two	NUM
ijassa-1351	3	28	.	.	PUNCT
ijassa-1351	4	1	in	in	ADP
ijassa-1351	4	2	addition	addition	NOUN
ijassa-1351	4	3	,	,	PUNCT
ijassa-1351	4	4	the	the	DET
ijassa-1351	4	5	fork	fork	NOUN
ijassa-1351	4	6	-	-	PUNCT
ijassa-1351	4	7	join	join	NOUN
ijassa-1351	4	8	system	system	NOUN
ijassa-1351	4	9	is	be	AUX
ijassa-1351	4	10	a	a	DET
ijassa-1351	4	11	mathematical	mathematical	ADJ
ijassa-1351	4	12	model	model	NOUN
ijassa-1351	4	13	of	of	ADP
ijassa-1351	4	14	parallel	parallel	ADJ
ijassa-1351	4	15	or	or	CCONJ
ijassa-1351	4	16	distributed	distribute	VERB
ijassa-1351	4	17	computing	computing	NOUN
ijassa-1351	4	18	systems	system	NOUN
ijassa-1351	4	19	that	that	PRON
ijassa-1351	4	20	have	have	AUX
ijassa-1351	4	21	become	become	VERB
ijassa-1351	4	22	widespread	widespread	ADJ
ijassa-1351	4	23	as	as	ADP
ijassa-1351	4	24	one	one	NUM
ijassa-1351	4	25	of	of	ADP
ijassa-1351	4	26	the	the	DET
ijassa-1351	4	27	most	most	ADV
ijassa-1351	4	28	effective	effective	ADJ
ijassa-1351	4	29	methods	method	NOUN
ijassa-1351	4	30	for	for	ADP
ijassa-1351	4	31	processing	process	VERB
ijassa-1351	4	32	big	big	ADJ
ijassa-1351	4	33	data	datum	NOUN
ijassa-1351	4	34	.	.	PUNCT
ijassa-1351	5	1	an	an	DET
ijassa-1351	5	2	approach	approach	NOUN
ijassa-1351	5	3	based	base	VERB
ijassa-1351	5	4	on	on	ADP
ijassa-1351	5	5	graphical	graphical	ADJ
ijassa-1351	5	6	analysis	analysis	NOUN
ijassa-1351	5	7	,	,	PUNCT
ijassa-1351	5	8	non	non	ADJ
ijassa-1351	5	9	-	-	ADJ
ijassa-1351	5	10	linear	linear	ADJ
ijassa-1351	5	11	regression	regression	NOUN
ijassa-1351	5	12	,	,	PUNCT
ijassa-1351	5	13	and	and	CCONJ
ijassa-1351	5	14	the	the	DET
ijassa-1351	5	15	use	use	NOUN
ijassa-1351	5	16	of	of	ADP
ijassa-1351	5	17	the	the	DET
ijassa-1351	5	18	nelder	nelder	ADJ
ijassa-1351	5	19	-	-	PUNCT
ijassa-1351	5	20	mead	mead	NOUN
ijassa-1351	5	21	optimization	optimization	NOUN
ijassa-1351	5	22	method	method	NOUN
ijassa-1351	5	23	is	be	AUX
ijassa-1351	5	24	proposed	propose	VERB
ijassa-1351	5	25	to	to	PART
ijassa-1351	5	26	estimate	estimate	VERB
ijassa-1351	5	27	the	the	DET
ijassa-1351	5	28	mathematical	mathematical	ADJ
ijassa-1351	5	29	expectation	expectation	NOUN
ijassa-1351	5	30	and	and	CCONJ
ijassa-1351	5	31	dispersion	dispersion	NOUN
ijassa-1351	5	32	of	of	ADP
ijassa-1351	5	33	the	the	DET
ijassa-1351	5	34	response	response	NOUN
ijassa-1351	5	35	time	time	NOUN
ijassa-1351	5	36	of	of	ADP
ijassa-1351	5	37	a	a	DET
ijassa-1351	5	38	fork	fork	NOUN
ijassa-1351	5	39	-	-	PUNCT
ijassa-1351	5	40	join	join	NOUN
ijassa-1351	5	41	system	system	NOUN
ijassa-1351	5	42	.	.	PUNCT
ijassa-1351	6	1	as	as	ADP
ijassa-1351	6	2	a	a	DET
ijassa-1351	6	3	result	result	NOUN
ijassa-1351	6	4	,	,	PUNCT
ijassa-1351	6	5	the	the	DET
ijassa-1351	6	6	authors	author	NOUN
ijassa-1351	6	7	managed	manage	VERB
ijassa-1351	6	8	to	to	PART
ijassa-1351	6	9	modify	modify	VERB
ijassa-1351	6	10	the	the	DET
ijassa-1351	6	11	known	know	VERB
ijassa-1351	6	12	approximations	approximation	NOUN
ijassa-1351	6	13	and	and	CCONJ
ijassa-1351	6	14	significantly	significantly	ADV
ijassa-1351	6	15	(	(	PUNCT
ijassa-1351	6	16	many	many	ADJ
ijassa-1351	6	17	times	time	NOUN
ijassa-1351	6	18	)	)	PUNCT
ijassa-1351	6	19	improve	improve	VERB
ijassa-1351	6	20	their	their	PRON
ijassa-1351	6	21	approximation	approximation	NOUN
ijassa-1351	6	22	quality	quality	NOUN
ijassa-1351	6	23	.	.	PUNCT
ijassa-1351	7	1	the	the	DET
ijassa-1351	7	2	paper	paper	NOUN
ijassa-1351	7	3	also	also	ADV
ijassa-1351	7	4	examines	examine	VERB
ijassa-1351	7	5	the	the	DET
ijassa-1351	7	6	quality	quality	NOUN
ijassa-1351	7	7	of	of	ADP
ijassa-1351	7	8	the	the	DET
ijassa-1351	7	9	experimental	experimental	ADJ
ijassa-1351	7	10	data	datum	NOUN
ijassa-1351	7	11	of	of	ADP
ijassa-1351	7	12	simulation	simulation	NOUN
ijassa-1351	7	13	modeling	modeling	NOUN
ijassa-1351	7	14	used	use	VERB
ijassa-1351	7	15	to	to	PART
ijassa-1351	7	16	estimate	estimate	VERB
ijassa-1351	7	17	the	the	DET
ijassa-1351	7	18	approximation	approximation	NOUN
ijassa-1351	7	19	error	error	NOUN
ijassa-1351	7	20	of	of	ADP
ijassa-1351	7	21	the	the	DET
ijassa-1351	7	22	obtained	obtain	VERB
ijassa-1351	7	23	expressions	expression	NOUN
ijassa-1351	7	24	.	.	PUNCT
ijassa-1351	8	1	as	as	ADP
ijassa-1351	8	2	a	a	DET
ijassa-1351	8	3	rule	rule	NOUN
ijassa-1351	8	4	,	,	PUNCT
ijassa-1351	8	5	this	this	DET
ijassa-1351	8	6	issue	issue	NOUN
ijassa-1351	8	7	remains	remain	VERB
ijassa-1351	8	8	outside	outside	ADP
ijassa-1351	8	9	the	the	DET
ijassa-1351	8	10	scope	scope	NOUN
ijassa-1351	8	11	of	of	ADP
ijassa-1351	8	12	ongoing	ongoing	ADJ
ijassa-1351	8	13	research	research	NOUN
ijassa-1351	8	14	in	in	ADP
ijassa-1351	8	15	the	the	DET
ijassa-1351	8	16	field	field	NOUN
ijassa-1351	8	17	of	of	ADP
ijassa-1351	8	18	this	this	DET
ijassa-1351	8	19	topic	topic	NOUN
ijassa-1351	8	20	due	due	ADP
ijassa-1351	8	21	to	to	ADP
ijassa-1351	8	22	the	the	DET
ijassa-1351	8	23	complexity	complexity	NOUN
ijassa-1351	8	24	of	of	ADP
ijassa-1351	8	25	such	such	DET
ijassa-1351	8	26	an	an	DET
ijassa-1351	8	27	analysis	analysis	NOUN
ijassa-1351	8	28	.	.	PUNCT
ijassa-1351	9	1	and	and	CCONJ
ijassa-1351	9	2	sometimes	sometimes	ADV
ijassa-1351	9	3	,	,	PUNCT
ijassa-1351	9	4	it	it	PRON
ijassa-1351	9	5	is	be	AUX
ijassa-1351	9	6	due	due	ADJ
ijassa-1351	9	7	to	to	ADP
ijassa-1351	9	8	the	the	DET
ijassa-1351	9	9	underestimation	underestimation	NOUN
ijassa-1351	9	10	of	of	ADP
ijassa-1351	9	11	the	the	DET
ijassa-1351	9	12	importance	importance	NOUN
ijassa-1351	9	13	of	of	ADP
ijassa-1351	9	14	this	this	DET
ijassa-1351	9	15	issue	issue	NOUN
ijassa-1351	9	16	.	.	PUNCT
ijassa-1351	10	1	the	the	DET
ijassa-1351	10	2	article	article	NOUN
ijassa-1351	10	3	proposes	propose	VERB
ijassa-1351	10	4	an	an	DET
ijassa-1351	10	5	approach	approach	NOUN
ijassa-1351	10	6	to	to	ADP
ijassa-1351	10	7	finding	find	VERB
ijassa-1351	10	8	confidence	confidence	NOUN
ijassa-1351	10	9	intervals	interval	NOUN
ijassa-1351	10	10	for	for	ADP
ijassa-1351	10	11	simulation	simulation	NOUN
ijassa-1351	10	12	results	result	NOUN
ijassa-1351	10	13	.	.	PUNCT
ijassa-1351	11	1	it	it	PRON
ijassa-1351	11	2	provides	provide	VERB
ijassa-1351	11	3	an	an	DET
ijassa-1351	11	4	algorithm	algorithm	NOUN
ijassa-1351	11	5	for	for	ADP
ijassa-1351	11	6	their	their	PRON
ijassa-1351	11	7	construction	construction	NOUN
ijassa-1351	11	8	and	and	CCONJ
ijassa-1351	11	9	also	also	ADV
ijassa-1351	11	10	gives	give	VERB
ijassa-1351	11	11	some	some	DET
ijassa-1351	11	12	recommendations	recommendation	NOUN
ijassa-1351	11	13	.	.	PUNCT
ijassa-1351	12	1	keywords	keyword	NOUN
ijassa-1351	12	2	:	:	PUNCT
ijassa-1351	12	3	fork	fork	NOUN
ijassa-1351	12	4	-	-	PUNCT
ijassa-1351	12	5	join	join	NOUN
ijassa-1351	12	6	queueing	queue	VERB
ijassa-1351	12	7	system	system	NOUN
ijassa-1351	12	8	,	,	PUNCT
ijassa-1351	12	9	parallel	parallel	ADJ
ijassa-1351	12	10	service	service	NOUN
ijassa-1351	12	11	,	,	PUNCT
ijassa-1351	12	12	parallel	parallel	ADJ
ijassa-1351	12	13	computing	computing	NOUN
ijassa-1351	12	14	,	,	PUNCT
ijassa-1351	12	15	average	average	ADJ
ijassa-1351	12	16	response	response	NOUN
ijassa-1351	12	17	time	time	NOUN
ijassa-1351	12	18	,	,	PUNCT
ijassa-1351	12	19	response	response	NOUN
ijassa-1351	12	20	time	time	PROPN
ijassa-1351	12	21	variance	variance	PROPN
ijassa-1351	12	22	,	,	PUNCT
ijassa-1351	12	23	simulation	simulation	NOUN
ijassa-1351	12	24	.	.	PUNCT
ijassa-1351	13	1	1	1	X
ijassa-1351	13	2	.	.	X
ijassa-1351	13	3	introduction	introduction	NOUN
ijassa-1351	13	4	the	the	DET
ijassa-1351	13	5	fork	fork	NOUN
ijassa-1351	13	6	-	-	PUNCT
ijassa-1351	13	7	join	join	NOUN
ijassa-1351	13	8	queueing	queue	VERB
ijassa-1351	13	9	system	system	NOUN
ijassa-1351	13	10	(	(	PUNCT
ijassa-1351	13	11	qs	qs	NOUN
ijassa-1351	13	12	)	)	PUNCT
ijassa-1351	13	13	is	be	AUX
ijassa-1351	13	14	a	a	DET
ijassa-1351	13	15	system	system	NOUN
ijassa-1351	13	16	with	with	ADP
ijassa-1351	13	17	parallel	parallel	ADJ
ijassa-1351	13	18	service	service	NOUN
ijassa-1351	13	19	where	where	SCONJ
ijassa-1351	13	20	the	the	DET
ijassa-1351	13	21	task	task	NOUN
ijassa-1351	13	22	is	be	AUX
ijassa-1351	13	23	divided	divide	VERB
ijassa-1351	13	24	into	into	ADP
ijassa-1351	13	25	a	a	DET
ijassa-1351	13	26	fixed	fix	VERB
ijassa-1351	13	27	number	number	NOUN
ijassa-1351	13	28	k	k	PROPN
ijassa-1351	13	29	of	of	ADP
ijassa-1351	13	30	smaller	small	ADJ
ijassa-1351	13	31	components	component	NOUN
ijassa-1351	13	32	(	(	PUNCT
ijassa-1351	13	33	subtasks	subtask	NOUN
ijassa-1351	13	34	)	)	PUNCT
ijassa-1351	13	35	.	.	PUNCT
ijassa-1351	14	1	then	then	ADV
ijassa-1351	14	2	each	each	PRON
ijassa-1351	14	3	of	of	ADP
ijassa-1351	14	4	the	the	DET
ijassa-1351	14	5	subtasks	subtask	NOUN
ijassa-1351	14	6	enters	enter	VERB
ijassa-1351	14	7	the	the	DET
ijassa-1351	14	8	queue	queue	NOUN
ijassa-1351	14	9	for	for	ADP
ijassa-1351	14	10	service	service	NOUN
ijassa-1351	14	11	in	in	ADP
ijassa-1351	14	12	one	one	NUM
ijassa-1351	14	13	of	of	ADP
ijassa-1351	14	14	the	the	DET
ijassa-1351	14	15	subsystems	subsystem	NOUN
ijassa-1351	14	16	in	in	ADP
ijassa-1351	14	17	the	the	DET
ijassa-1351	14	18	system	system	NOUN
ijassa-1351	14	19	with	with	ADP
ijassa-1351	14	20	an	an	DET
ijassa-1351	14	21	infinite	infinite	ADJ
ijassa-1351	14	22	storage	storage	NOUN
ijassa-1351	14	23	capacity	capacity	NOUN
ijassa-1351	14	24	and	and	CCONJ
ijassa-1351	14	25	one	one	NUM
ijassa-1351	14	26	server	server	NOUN
ijassa-1351	14	27	.	.	PUNCT
ijassa-1351	15	1	after	after	ADP
ijassa-1351	15	2	each	each	DET
ijassa-1351	15	3	subtasks	subtask	NOUN
ijassa-1351	15	4	,	,	PUNCT
ijassa-1351	15	5	initially	initially	ADV
ijassa-1351	15	6	constituting	constitute	VERB
ijassa-1351	15	7	one	one	NUM
ijassa-1351	15	8	task	task	NOUN
ijassa-1351	15	9	,	,	PUNCT
ijassa-1351	15	10	is	be	AUX
ijassa-1351	15	11	serviced	service	VERB
ijassa-1351	15	12	,	,	PUNCT
ijassa-1351	15	13	the	the	DET
ijassa-1351	15	14	task	task	NOUN
ijassa-1351	15	15	will	will	AUX
ijassa-1351	15	16	be	be	AUX
ijassa-1351	15	17	considered	consider	VERB
ijassa-1351	15	18	fully	fully	ADV
ijassa-1351	15	19	serviced	service	VERB
ijassa-1351	15	20	and	and	CCONJ
ijassa-1351	15	21	will	will	AUX
ijassa-1351	15	22	be	be	AUX
ijassa-1351	15	23	able	able	ADJ
ijassa-1351	15	24	to	to	PART
ijassa-1351	15	25	leave	leave	VERB
ijassa-1351	15	26	the	the	DET
ijassa-1351	15	27	system	system	NOUN
ijassa-1351	15	28	.	.	PUNCT
ijassa-1351	16	1	the	the	DET
ijassa-1351	16	2	described	describe	VERB
ijassa-1351	16	3	system	system	NOUN
ijassa-1351	16	4	is	be	AUX
ijassa-1351	16	5	a	a	DET
ijassa-1351	16	6	mathematical	mathematical	ADJ
ijassa-1351	16	7	model	model	NOUN
ijassa-1351	16	8	of	of	ADP
ijassa-1351	16	9	many	many	ADJ
ijassa-1351	16	10	real	real	ADJ
ijassa-1351	16	11	-	-	PUNCT
ijassa-1351	16	12	life	life	NOUN
ijassa-1351	16	13	and	and	CCONJ
ijassa-1351	16	14	similarly	similarly	ADV
ijassa-1351	16	15	functioning	function	VERB
ijassa-1351	16	16	physical	physical	ADJ
ijassa-1351	16	17	systems	system	NOUN
ijassa-1351	16	18	.	.	PUNCT
ijassa-1351	17	1	the	the	DET
ijassa-1351	17	2	most	most	ADV
ijassa-1351	17	3	striking	striking	ADJ
ijassa-1351	17	4	example	example	NOUN
ijassa-1351	17	5	of	of	ADP
ijassa-1351	17	6	it	it	PRON
ijassa-1351	17	7	is	be	AUX
ijassa-1351	17	8	data	data	NOUN
ijassa-1351	17	9	-	-	PUNCT
ijassa-1351	17	10	intensive	intensive	ADJ
ijassa-1351	17	11	systems	system	NOUN
ijassa-1351	17	12	.	.	PUNCT
ijassa-1351	18	1	it	it	PRON
ijassa-1351	18	2	is	be	AUX
ijassa-1351	18	3	because	because	SCONJ
ijassa-1351	18	4	dividing	divide	VERB
ijassa-1351	18	5	a	a	DET
ijassa-1351	18	6	large	large	ADJ
ijassa-1351	18	7	task	task	NOUN
ijassa-1351	18	8	into	into	ADP
ijassa-1351	18	9	subtasks	subtask	NOUN
ijassa-1351	18	10	with	with	ADP
ijassa-1351	18	11	their	their	PRON
ijassa-1351	18	12	subsequent	subsequent	ADJ
ijassa-1351	18	13	parallel	parallel	ADJ
ijassa-1351	18	14	processing	processing	NOUN
ijassa-1351	18	15	saves	save	VERB
ijassa-1351	18	16	time	time	NOUN
ijassa-1351	18	17	[	[	X
ijassa-1351	18	18	1,2	1,2	NUM
ijassa-1351	18	19	]	]	PUNCT
ijassa-1351	18	20	.	.	PUNCT
ijassa-1351	19	1	the	the	DET
ijassa-1351	19	2	study	study	NOUN
ijassa-1351	19	3	of	of	ADP
ijassa-1351	19	4	the	the	DET
ijassa-1351	19	5	characteristics	characteristic	NOUN
ijassa-1351	19	6	of	of	ADP
ijassa-1351	19	7	such	such	ADJ
ijassa-1351	19	8	systems	system	NOUN
ijassa-1351	19	9	is	be	AUX
ijassa-1351	19	10	currently	currently	ADV
ijassa-1351	19	11	relevant	relevant	ADJ
ijassa-1351	19	12	due	due	ADP
ijassa-1351	19	13	to	to	ADP
ijassa-1351	19	14	the	the	DET
ijassa-1351	19	15	breadth	breadth	NOUN
ijassa-1351	19	16	of	of	ADP
ijassa-1351	19	17	the	the	DET
ijassa-1351	19	18	so	so	ADV
ijassa-1351	19	19	-	-	PUNCT
ijassa-1351	19	20	called	call	VERB
ijassa-1351	19	21	“	"	PUNCT
ijassa-1351	19	22	big	big	ADJ
ijassa-1351	19	23	data	datum	NOUN
ijassa-1351	19	24	”	"	PUNCT
ijassa-1351	19	25	phenomenon	phenomenon	NOUN
ijassa-1351	19	26	and	and	CCONJ
ijassa-1351	19	27	,	,	PUNCT
ijassa-1351	19	28	accordingly	accordingly	ADV
ijassa-1351	19	29	,	,	PUNCT
ijassa-1351	19	30	the	the	DET
ijassa-1351	19	31	emergence	emergence	NOUN
ijassa-1351	19	32	of	of	ADP
ijassa-1351	19	33	an	an	DET
ijassa-1351	19	34	impressive	impressive	ADJ
ijassa-1351	19	35	number	number	NOUN
ijassa-1351	19	36	of	of	ADP
ijassa-1351	19	37	services	service	NOUN
ijassa-1351	19	38	that	that	PRON
ijassa-1351	19	39	provide	provide	VERB
ijassa-1351	19	40	services	service	NOUN
ijassa-1351	19	41	for	for	ADP
ijassa-1351	19	42	processing	processing	NOUN
ijassa-1351	19	43	and	and	CCONJ
ijassa-1351	19	44	analyzing	analyze	VERB
ijassa-1351	19	45	big	big	ADJ
ijassa-1351	19	46	data	datum	NOUN
ijassa-1351	20	1	[	[	X
ijassa-1351	20	2	3–5	3–5	NOUN
ijassa-1351	20	3	]	]	PUNCT
ijassa-1351	20	4	.	.	PUNCT
ijassa-1351	21	1	studies	study	NOUN
ijassa-1351	21	2	of	of	ADP
ijassa-1351	21	3	fork	fork	NOUN
ijassa-1351	21	4	-	-	PUNCT
ijassa-1351	21	5	join	join	NOUN
ijassa-1351	21	6	systems	system	NOUN
ijassa-1351	21	7	have	have	AUX
ijassa-1351	21	8	been	be	AUX
ijassa-1351	21	9	conducted	conduct	VERB
ijassa-1351	21	10	for	for	ADP
ijassa-1351	21	11	a	a	DET
ijassa-1351	21	12	relatively	relatively	ADV
ijassa-1351	21	13	long	long	ADJ
ijassa-1351	21	14	time	time	NOUN
ijassa-1351	21	15	.	.	PUNCT
ijassa-1351	22	1	however	however	ADV
ijassa-1351	22	2	,	,	PUNCT
ijassa-1351	22	3	the	the	DET
ijassa-1351	22	4	exact	exact	ADJ
ijassa-1351	22	5	result	result	NOUN
ijassa-1351	22	6	for	for	ADP
ijassa-1351	22	7	such	such	DET
ijassa-1351	22	8	an	an	DET
ijassa-1351	22	9	essential	essential	ADJ
ijassa-1351	22	10	characteristic	characteristic	NOUN
ijassa-1351	22	11	of	of	ADP
ijassa-1351	22	12	any	any	DET
ijassa-1351	22	13	qs	qs	NOUN
ijassa-1351	22	14	as	as	SCONJ
ijassa-1351	22	15	its	its	PRON
ijassa-1351	22	16	average	average	ADJ
ijassa-1351	22	17	response	response	NOUN
ijassa-1351	22	18	time	time	NOUN
ijassa-1351	22	19	was	be	AUX
ijassa-1351	22	20	obtained	obtain	VERB
ijassa-1351	22	21	only	only	ADV
ijassa-1351	22	22	in	in	ADP
ijassa-1351	22	23	the	the	DET
ijassa-1351	22	24	relatively	relatively	ADV
ijassa-1351	22	25	simplest	simple	ADJ
ijassa-1351	22	26	case	case	NOUN
ijassa-1351	22	27	.	.	PUNCT
ijassa-1351	23	1	namely	namely	ADV
ijassa-1351	23	2	,	,	PUNCT
ijassa-1351	23	3	when	when	SCONJ
ijassa-1351	23	4	the	the	DET
ijassa-1351	23	5	number	number	NOUN
ijassa-1351	23	6	of	of	ADP
ijassa-1351	23	7	subsystems	subsystem	NOUN
ijassa-1351	23	8	is	be	AUX
ijassa-1351	23	9	k	k	NOUN
ijassa-1351	23	10	=	=	SYM
ijassa-1351	23	11	2	2	NUM
ijassa-1351	23	12	,	,	PUNCT
ijassa-1351	23	13	the	the	DET
ijassa-1351	23	14	input	input	NOUN
ijassa-1351	23	15	flow	flow	NOUN
ijassa-1351	23	16	is	be	AUX
ijassa-1351	23	17	poissonian	poissonian	NOUN
ijassa-1351	23	18	,	,	PUNCT
ijassa-1351	23	19	and	and	CCONJ
ijassa-1351	23	20	the	the	DET
ijassa-1351	23	21	service	service	NOUN
ijassa-1351	23	22	time	time	NOUN
ijassa-1351	23	23	on	on	ADP
ijassa-1351	23	24	servers	server	NOUN
ijassa-1351	23	25	is	be	AUX
ijassa-1351	23	26	exponential	exponential	ADJ
ijassa-1351	23	27	(	(	PUNCT
ijassa-1351	23	28	in	in	ADP
ijassa-1351	23	29	other	other	ADJ
ijassa-1351	23	30	∗corresponding	∗corresponde	VERB
ijassa-1351	23	31	author	author	NOUN
ijassa-1351	23	32	:	:	PUNCT
ijassa-1351	23	33	avgorbunova@list.ru	avgorbunova@list.ru	NOUN
ijassa-1351	23	34	100	100	NUM
ijassa-1351	23	35	a.v	a.v	PROPN
ijassa-1351	23	36	.	.	PROPN
ijassa-1351	23	37	gorbunova	gorbunova	PROPN
ijassa-1351	23	38	,	,	PUNCT
ijassa-1351	23	39	a.v	a.v	PROPN
ijassa-1351	23	40	.	.	PROPN
ijassa-1351	23	41	lebedev	lebedev	PROPN
ijassa-1351	23	42	words	word	NOUN
ijassa-1351	23	43	,	,	PUNCT
ijassa-1351	23	44	subsytems	subsytem	NOUN
ijassa-1351	23	45	are	be	AUX
ijassa-1351	23	46	markov	markov	NOUN
ijassa-1351	23	47	queues	queue	NOUN
ijassa-1351	23	48	of	of	ADP
ijassa-1351	23	49	type	type	NOUN
ijassa-1351	23	50	m	m	NOUN
ijassa-1351	23	51	|m	|m	NOUN
ijassa-1351	23	52	|1	|1	PRON
ijassa-1351	23	53	)	)	PUNCT
ijassa-1351	24	1	[	[	X
ijassa-1351	24	2	6	6	NUM
ijassa-1351	24	3	]	]	PUNCT
ijassa-1351	24	4	.	.	PUNCT
ijassa-1351	25	1	if	if	SCONJ
ijassa-1351	25	2	the	the	DET
ijassa-1351	25	3	number	number	NOUN
ijassa-1351	25	4	of	of	ADP
ijassa-1351	25	5	subsystems	subsystem	NOUN
ijassa-1351	25	6	is	be	AUX
ijassa-1351	25	7	more	more	ADJ
ijassa-1351	25	8	than	than	ADP
ijassa-1351	25	9	two	two	NUM
ijassa-1351	25	10	,	,	PUNCT
ijassa-1351	25	11	then	then	ADV
ijassa-1351	25	12	only	only	ADJ
ijassa-1351	25	13	approximations	approximation	NOUN
ijassa-1351	25	14	of	of	ADP
ijassa-1351	25	15	varying	vary	VERB
ijassa-1351	25	16	degrees	degree	NOUN
ijassa-1351	25	17	of	of	ADP
ijassa-1351	25	18	accuracy	accuracy	NOUN
ijassa-1351	25	19	[	[	X
ijassa-1351	25	20	6–9	6–9	NOUN
ijassa-1351	25	21	]	]	PUNCT
ijassa-1351	25	22	are	be	AUX
ijassa-1351	25	23	known	know	VERB
ijassa-1351	25	24	.	.	PUNCT
ijassa-1351	26	1	the	the	DET
ijassa-1351	26	2	reason	reason	NOUN
ijassa-1351	26	3	for	for	ADP
ijassa-1351	26	4	the	the	DET
ijassa-1351	26	5	complexity	complexity	NOUN
ijassa-1351	26	6	of	of	ADP
ijassa-1351	26	7	the	the	DET
ijassa-1351	26	8	analysis	analysis	NOUN
ijassa-1351	26	9	of	of	ADP
ijassa-1351	26	10	the	the	DET
ijassa-1351	26	11	described	describe	VERB
ijassa-1351	26	12	system	system	NOUN
ijassa-1351	26	13	is	be	AUX
ijassa-1351	26	14	the	the	DET
ijassa-1351	26	15	presence	presence	NOUN
ijassa-1351	26	16	of	of	ADP
ijassa-1351	26	17	dependencies	dependency	NOUN
ijassa-1351	26	18	between	between	ADP
ijassa-1351	26	19	the	the	DET
ijassa-1351	26	20	sojourn	sojourn	NOUN
ijassa-1351	26	21	times	time	NOUN
ijassa-1351	26	22	of	of	ADP
ijassa-1351	26	23	subtasks	subtask	NOUN
ijassa-1351	26	24	in	in	ADP
ijassa-1351	26	25	subsystems	subsystem	NOUN
ijassa-1351	26	26	.	.	PUNCT
ijassa-1351	27	1	this	this	PRON
ijassa-1351	27	2	is	be	AUX
ijassa-1351	27	3	the	the	DET
ijassa-1351	27	4	main	main	ADJ
ijassa-1351	27	5	difference	difference	NOUN
ijassa-1351	27	6	between	between	ADP
ijassa-1351	27	7	the	the	DET
ijassa-1351	27	8	described	describe	VERB
ijassa-1351	27	9	system	system	NOUN
ijassa-1351	27	10	and	and	CCONJ
ijassa-1351	27	11	the	the	DET
ijassa-1351	27	12	set	set	NOUN
ijassa-1351	27	13	k	k	PROPN
ijassa-1351	27	14	of	of	ADP
ijassa-1351	27	15	parallel	parallel	ADJ
ijassa-1351	27	16	functioning	function	VERB
ijassa-1351	27	17	qs	qs	NOUN
ijassa-1351	27	18	.	.	PUNCT
ijassa-1351	28	1	in	in	ADP
ijassa-1351	28	2	this	this	DET
ijassa-1351	28	3	case	case	NOUN
ijassa-1351	28	4	,	,	PUNCT
ijassa-1351	28	5	the	the	DET
ijassa-1351	28	6	average	average	ADJ
ijassa-1351	28	7	response	response	NOUN
ijassa-1351	28	8	time	time	NOUN
ijassa-1351	28	9	of	of	ADP
ijassa-1351	28	10	the	the	DET
ijassa-1351	28	11	entire	entire	ADJ
ijassa-1351	28	12	system	system	NOUN
ijassa-1351	28	13	will	will	AUX
ijassa-1351	28	14	be	be	AUX
ijassa-1351	28	15	determined	determine	VERB
ijassa-1351	28	16	by	by	ADP
ijassa-1351	28	17	the	the	DET
ijassa-1351	28	18	longest	long	ADJ
ijassa-1351	28	19	sojourn	sojourn	NOUN
ijassa-1351	28	20	time	time	NOUN
ijassa-1351	28	21	in	in	ADP
ijassa-1351	28	22	the	the	DET
ijassa-1351	28	23	corresponding	corresponding	ADJ
ijassa-1351	28	24	subsystem	subsystem	NOUN
ijassa-1351	28	25	of	of	ADP
ijassa-1351	28	26	one	one	NUM
ijassa-1351	28	27	of	of	ADP
ijassa-1351	28	28	its	its	PRON
ijassa-1351	28	29	subtasks	subtask	NOUN
ijassa-1351	28	30	.	.	PUNCT
ijassa-1351	29	1	thus	thus	ADV
ijassa-1351	29	2	,	,	PUNCT
ijassa-1351	29	3	the	the	DET
ijassa-1351	29	4	average	average	ADJ
ijassa-1351	29	5	response	response	NOUN
ijassa-1351	29	6	time	time	NOUN
ijassa-1351	29	7	of	of	ADP
ijassa-1351	29	8	a	a	DET
ijassa-1351	29	9	fork	fork	NOUN
ijassa-1351	29	10	-	-	PUNCT
ijassa-1351	29	11	join	join	NOUN
ijassa-1351	29	12	qs	qs	NOUN
ijassa-1351	29	13	is	be	AUX
ijassa-1351	29	14	essentially	essentially	ADV
ijassa-1351	29	15	the	the	DET
ijassa-1351	29	16	mathematical	mathematical	ADJ
ijassa-1351	29	17	expectation	expectation	NOUN
ijassa-1351	29	18	of	of	ADP
ijassa-1351	29	19	the	the	DET
ijassa-1351	29	20	maximum	maximum	NOUN
ijassa-1351	29	21	of	of	ADP
ijassa-1351	29	22	k	k	PROPN
ijassa-1351	29	23	dependent	dependent	ADJ
ijassa-1351	29	24	random	random	ADJ
ijassa-1351	29	25	variables	variable	NOUN
ijassa-1351	29	26	of	of	ADP
ijassa-1351	29	27	sojourn	sojourn	NOUN
ijassa-1351	29	28	times	time	NOUN
ijassa-1351	29	29	in	in	ADP
ijassa-1351	29	30	subsystems	subsystem	NOUN
ijassa-1351	29	31	,	,	PUNCT
ijassa-1351	29	32	i.e.	i.e.	X
ijassa-1351	29	33	,	,	PUNCT
ijassa-1351	29	34	the	the	DET
ijassa-1351	29	35	k	k	NOUN
ijassa-1351	29	36	-	-	PUNCT
ijassa-1351	29	37	th	th	VERB
ijassa-1351	29	38	order	order	NOUN
ijassa-1351	29	39	statistic	statistic	NOUN
ijassa-1351	29	40	in	in	ADP
ijassa-1351	29	41	the	the	DET
ijassa-1351	29	42	sequence	sequence	NOUN
ijassa-1351	29	43	of	of	ADP
ijassa-1351	29	44	specified	specify	VERB
ijassa-1351	29	45	random	random	ADJ
ijassa-1351	29	46	variables	variable	NOUN
ijassa-1351	29	47	.	.	PUNCT
ijassa-1351	30	1	therefore	therefore	ADV
ijassa-1351	30	2	,	,	PUNCT
ijassa-1351	30	3	elements	element	NOUN
ijassa-1351	30	4	of	of	ADP
ijassa-1351	30	5	the	the	DET
ijassa-1351	30	6	theory	theory	NOUN
ijassa-1351	30	7	of	of	ADP
ijassa-1351	30	8	order	order	NOUN
ijassa-1351	30	9	statistics	statistic	NOUN
ijassa-1351	30	10	[	[	X
ijassa-1351	30	11	10	10	NUM
ijassa-1351	30	12	]	]	PUNCT
ijassa-1351	30	13	were	be	AUX
ijassa-1351	30	14	used	use	VERB
ijassa-1351	30	15	along	along	ADP
ijassa-1351	30	16	with	with	ADP
ijassa-1351	30	17	the	the	DET
ijassa-1351	30	18	methods	method	NOUN
ijassa-1351	30	19	of	of	ADP
ijassa-1351	30	20	queuing	queue	VERB
ijassa-1351	30	21	theory	theory	NOUN
ijassa-1351	30	22	to	to	PART
ijassa-1351	30	23	approximate	approximate	VERB
ijassa-1351	30	24	the	the	DET
ijassa-1351	30	25	average	average	ADJ
ijassa-1351	30	26	response	response	NOUN
ijassa-1351	30	27	time	time	NOUN
ijassa-1351	30	28	.	.	PUNCT
ijassa-1351	31	1	however	however	ADV
ijassa-1351	31	2	,	,	PUNCT
ijassa-1351	31	3	even	even	ADV
ijassa-1351	31	4	in	in	ADP
ijassa-1351	31	5	this	this	DET
ijassa-1351	31	6	case	case	NOUN
ijassa-1351	31	7	,	,	PUNCT
ijassa-1351	31	8	the	the	DET
ijassa-1351	31	9	obtained	obtain	VERB
ijassa-1351	31	10	estimates	estimate	NOUN
ijassa-1351	31	11	are	be	AUX
ijassa-1351	31	12	approximate	approximate	ADJ
ijassa-1351	31	13	since	since	SCONJ
ijassa-1351	31	14	the	the	DET
ijassa-1351	31	15	theory	theory	NOUN
ijassa-1351	31	16	of	of	ADP
ijassa-1351	31	17	order	order	NOUN
ijassa-1351	31	18	statistics	statistic	NOUN
ijassa-1351	31	19	focuses	focus	VERB
ijassa-1351	31	20	more	more	ADJ
ijassa-1351	31	21	on	on	ADP
ijassa-1351	31	22	the	the	DET
ijassa-1351	31	23	study	study	NOUN
ijassa-1351	31	24	of	of	ADP
ijassa-1351	31	25	samples	sample	NOUN
ijassa-1351	31	26	of	of	ADP
ijassa-1351	31	27	independent	independent	ADJ
ijassa-1351	31	28	random	random	ADJ
ijassa-1351	31	29	variables	variable	NOUN
ijassa-1351	31	30	.	.	PUNCT
ijassa-1351	32	1	in	in	ADP
ijassa-1351	32	2	addition	addition	NOUN
ijassa-1351	32	3	,	,	PUNCT
ijassa-1351	32	4	if	if	SCONJ
ijassa-1351	32	5	we	we	PRON
ijassa-1351	32	6	are	be	AUX
ijassa-1351	32	7	not	not	PART
ijassa-1351	32	8	talking	talk	VERB
ijassa-1351	32	9	about	about	ADP
ijassa-1351	32	10	the	the	DET
ijassa-1351	32	11	poisson	poisson	NOUN
ijassa-1351	32	12	input	input	NOUN
ijassa-1351	32	13	flow	flow	NOUN
ijassa-1351	32	14	and	and	CCONJ
ijassa-1351	32	15	exponential	exponential	NOUN
ijassa-1351	32	16	service	service	NOUN
ijassa-1351	32	17	times	time	NOUN
ijassa-1351	32	18	,	,	PUNCT
ijassa-1351	32	19	it	it	PRON
ijassa-1351	32	20	is	be	AUX
ijassa-1351	32	21	quite	quite	ADV
ijassa-1351	32	22	difficult	difficult	ADJ
ijassa-1351	32	23	to	to	PART
ijassa-1351	32	24	determine	determine	VERB
ijassa-1351	32	25	the	the	DET
ijassa-1351	32	26	distribution	distribution	NOUN
ijassa-1351	32	27	of	of	ADP
ijassa-1351	32	28	the	the	DET
ijassa-1351	32	29	sojourn	sojourn	NOUN
ijassa-1351	32	30	time	time	NOUN
ijassa-1351	32	31	of	of	ADP
ijassa-1351	32	32	the	the	DET
ijassa-1351	32	33	task	task	NOUN
ijassa-1351	32	34	in	in	ADP
ijassa-1351	32	35	the	the	DET
ijassa-1351	32	36	qs	qs	NOUN
ijassa-1351	32	37	.	.	PUNCT
ijassa-1351	33	1	in	in	ADP
ijassa-1351	33	2	more	more	ADV
ijassa-1351	33	3	recent	recent	ADJ
ijassa-1351	33	4	publications	publication	NOUN
ijassa-1351	33	5	in	in	ADP
ijassa-1351	33	6	the	the	DET
ijassa-1351	33	7	field	field	NOUN
ijassa-1351	33	8	of	of	ADP
ijassa-1351	33	9	this	this	DET
ijassa-1351	33	10	topic	topic	NOUN
ijassa-1351	33	11	,	,	PUNCT
ijassa-1351	33	12	an	an	DET
ijassa-1351	33	13	approach	approach	NOUN
ijassa-1351	33	14	is	be	AUX
ijassa-1351	33	15	applied	apply	VERB
ijassa-1351	33	16	to	to	ADP
ijassa-1351	33	17	the	the	DET
ijassa-1351	33	18	analysis	analysis	NOUN
ijassa-1351	33	19	of	of	ADP
ijassa-1351	33	20	fork	fork	NOUN
ijassa-1351	33	21	-	-	PUNCT
ijassa-1351	33	22	join	join	NOUN
ijassa-1351	33	23	systems	system	NOUN
ijassa-1351	33	24	using	use	VERB
ijassa-1351	33	25	machine	machine	NOUN
ijassa-1351	33	26	learning	learning	NOUN
ijassa-1351	33	27	methods	method	NOUN
ijassa-1351	33	28	,	,	PUNCT
ijassa-1351	33	29	in	in	ADP
ijassa-1351	33	30	particular	particular	ADJ
ijassa-1351	33	31	,	,	PUNCT
ijassa-1351	33	32	artificial	artificial	ADJ
ijassa-1351	33	33	neural	neural	ADJ
ijassa-1351	33	34	networks	network	NOUN
ijassa-1351	33	35	or	or	CCONJ
ijassa-1351	33	36	multiple	multiple	ADJ
ijassa-1351	33	37	non	non	ADJ
ijassa-1351	33	38	-	-	ADJ
ijassa-1351	33	39	linear	linear	ADJ
ijassa-1351	33	40	regression	regression	NOUN
ijassa-1351	33	41	[	[	X
ijassa-1351	33	42	11	11	NUM
ijassa-1351	33	43	,	,	PUNCT
ijassa-1351	33	44	12	12	NUM
ijassa-1351	33	45	]	]	PUNCT
ijassa-1351	33	46	.	.	PUNCT
ijassa-1351	34	1	as	as	ADP
ijassa-1351	34	2	a	a	DET
ijassa-1351	34	3	result	result	NOUN
ijassa-1351	34	4	,	,	PUNCT
ijassa-1351	34	5	approximations	approximation	NOUN
ijassa-1351	34	6	of	of	ADP
ijassa-1351	34	7	the	the	DET
ijassa-1351	34	8	mathematical	mathematical	ADJ
ijassa-1351	34	9	expectation	expectation	NOUN
ijassa-1351	34	10	and	and	CCONJ
ijassa-1351	34	11	higher	high	ADJ
ijassa-1351	34	12	order	order	NOUN
ijassa-1351	34	13	moments	moment	NOUN
ijassa-1351	34	14	of	of	ADP
ijassa-1351	34	15	the	the	DET
ijassa-1351	34	16	response	response	NOUN
ijassa-1351	34	17	time	time	NOUN
ijassa-1351	34	18	were	be	AUX
ijassa-1351	34	19	obtained	obtain	VERB
ijassa-1351	34	20	for	for	ADP
ijassa-1351	34	21	rather	rather	ADV
ijassa-1351	34	22	complex	complex	ADJ
ijassa-1351	34	23	fork	fork	NOUN
ijassa-1351	34	24	-	-	PUNCT
ijassa-1351	34	25	join	join	NOUN
ijassa-1351	34	26	qs	qs	NOUN
ijassa-1351	34	27	structures	structure	NOUN
ijassa-1351	34	28	,	,	PUNCT
ijassa-1351	34	29	for	for	ADP
ijassa-1351	34	30	example	example	NOUN
ijassa-1351	34	31	,	,	PUNCT
ijassa-1351	34	32	with	with	ADP
ijassa-1351	34	33	the	the	DET
ijassa-1351	34	34	pareto	pareto	ADJ
ijassa-1351	34	35	distribution	distribution	NOUN
ijassa-1351	34	36	for	for	ADP
ijassa-1351	34	37	service	service	NOUN
ijassa-1351	34	38	time	time	NOUN
ijassa-1351	34	39	.	.	PUNCT
ijassa-1351	35	1	details	detail	NOUN
ijassa-1351	35	2	of	of	ADP
ijassa-1351	35	3	the	the	DET
ijassa-1351	35	4	approach	approach	NOUN
ijassa-1351	35	5	based	base	VERB
ijassa-1351	35	6	on	on	ADP
ijassa-1351	35	7	machine	machine	NOUN
ijassa-1351	35	8	learning	learning	NOUN
ijassa-1351	35	9	methods	method	NOUN
ijassa-1351	35	10	can	can	AUX
ijassa-1351	35	11	be	be	AUX
ijassa-1351	35	12	found	find	VERB
ijassa-1351	35	13	in	in	ADP
ijassa-1351	35	14	[	[	X
ijassa-1351	35	15	13	13	NUM
ijassa-1351	35	16	]	]	PUNCT
ijassa-1351	35	17	.	.	PUNCT
ijassa-1351	36	1	there	there	PRON
ijassa-1351	36	2	are	be	VERB
ijassa-1351	36	3	other	other	ADJ
ijassa-1351	36	4	approaches	approach	NOUN
ijassa-1351	36	5	to	to	ADP
ijassa-1351	36	6	deriving	derive	VERB
ijassa-1351	36	7	an	an	DET
ijassa-1351	36	8	estimate	estimate	NOUN
ijassa-1351	36	9	of	of	ADP
ijassa-1351	36	10	the	the	DET
ijassa-1351	36	11	average	average	ADJ
ijassa-1351	36	12	response	response	NOUN
ijassa-1351	36	13	time	time	NOUN
ijassa-1351	36	14	of	of	ADP
ijassa-1351	36	15	fork	fork	NOUN
ijassa-1351	36	16	-	-	PUNCT
ijassa-1351	36	17	join	join	NOUN
ijassa-1351	36	18	systems	system	NOUN
ijassa-1351	36	19	.	.	PUNCT
ijassa-1351	37	1	many	many	ADJ
ijassa-1351	37	2	of	of	ADP
ijassa-1351	37	3	them	they	PRON
ijassa-1351	37	4	are	be	AUX
ijassa-1351	37	5	described	describe	VERB
ijassa-1351	37	6	in	in	ADP
ijassa-1351	37	7	the	the	DET
ijassa-1351	37	8	review	review	NOUN
ijassa-1351	37	9	[	[	X
ijassa-1351	37	10	14	14	NUM
ijassa-1351	37	11	]	]	PUNCT
ijassa-1351	37	12	.	.	PUNCT
ijassa-1351	38	1	you	you	PRON
ijassa-1351	38	2	can	can	AUX
ijassa-1351	38	3	also	also	ADV
ijassa-1351	38	4	highlight	highlight	VERB
ijassa-1351	38	5	[	[	X
ijassa-1351	38	6	1	1	NUM
ijassa-1351	38	7	,	,	PUNCT
ijassa-1351	38	8	15–17	15–17	NUM
ijassa-1351	38	9	]	]	PUNCT
ijassa-1351	38	10	among	among	ADP
ijassa-1351	38	11	recent	recent	ADJ
ijassa-1351	38	12	works	work	NOUN
ijassa-1351	38	13	.	.	PUNCT
ijassa-1351	39	1	this	this	DET
ijassa-1351	39	2	article	article	NOUN
ijassa-1351	39	3	proposes	propose	VERB
ijassa-1351	39	4	another	another	DET
ijassa-1351	39	5	approach	approach	NOUN
ijassa-1351	39	6	to	to	ADP
ijassa-1351	39	7	estimating	estimate	VERB
ijassa-1351	39	8	the	the	DET
ijassa-1351	39	9	response	response	NOUN
ijassa-1351	39	10	time	time	NOUN
ijassa-1351	39	11	of	of	ADP
ijassa-1351	39	12	a	a	DET
ijassa-1351	39	13	fork	fork	NOUN
ijassa-1351	39	14	-	-	PUNCT
ijassa-1351	39	15	join	join	NOUN
ijassa-1351	39	16	qs	qs	NOUN
ijassa-1351	39	17	.	.	PUNCT
ijassa-1351	40	1	this	this	DET
ijassa-1351	40	2	approach	approach	NOUN
ijassa-1351	40	3	is	be	AUX
ijassa-1351	40	4	based	base	VERB
ijassa-1351	40	5	on	on	ADP
ijassa-1351	40	6	well	well	ADV
ijassa-1351	40	7	-	-	PUNCT
ijassa-1351	40	8	known	know	VERB
ijassa-1351	40	9	approximations	approximation	NOUN
ijassa-1351	40	10	for	for	ADP
ijassa-1351	40	11	the	the	DET
ijassa-1351	40	12	mathematical	mathematical	ADJ
ijassa-1351	40	13	expectation	expectation	NOUN
ijassa-1351	40	14	and	and	CCONJ
ijassa-1351	40	15	dispersion	dispersion	NOUN
ijassa-1351	40	16	of	of	ADP
ijassa-1351	40	17	the	the	DET
ijassa-1351	40	18	sojourn	sojourn	NOUN
ijassa-1351	40	19	time	time	NOUN
ijassa-1351	40	20	of	of	ADP
ijassa-1351	40	21	the	the	DET
ijassa-1351	40	22	task	task	NOUN
ijassa-1351	40	23	in	in	ADP
ijassa-1351	40	24	the	the	DET
ijassa-1351	40	25	qs	qs	NOUN
ijassa-1351	40	26	.	.	PUNCT
ijassa-1351	40	27	using	use	VERB
ijassa-1351	40	28	graphical	graphical	ADJ
ijassa-1351	40	29	analysis	analysis	NOUN
ijassa-1351	40	30	,	,	PUNCT
ijassa-1351	40	31	as	as	ADV
ijassa-1351	40	32	well	well	ADV
ijassa-1351	40	33	as	as	ADP
ijassa-1351	40	34	using	use	VERB
ijassa-1351	40	35	the	the	DET
ijassa-1351	40	36	nelder	nelder	ADJ
ijassa-1351	40	37	-	-	PUNCT
ijassa-1351	40	38	mead	mead	NOUN
ijassa-1351	40	39	optimization	optimization	NOUN
ijassa-1351	40	40	method	method	NOUN
ijassa-1351	40	41	,	,	PUNCT
ijassa-1351	40	42	the	the	DET
ijassa-1351	40	43	authors	author	NOUN
ijassa-1351	40	44	managed	manage	VERB
ijassa-1351	40	45	to	to	PART
ijassa-1351	40	46	modify	modify	VERB
ijassa-1351	40	47	the	the	DET
ijassa-1351	40	48	known	know	VERB
ijassa-1351	40	49	approximations	approximation	NOUN
ijassa-1351	40	50	for	for	ADP
ijassa-1351	40	51	fork	fork	NOUN
ijassa-1351	40	52	-	-	PUNCT
ijassa-1351	40	53	join	join	NOUN
ijassa-1351	40	54	qs	qs	NOUN
ijassa-1351	40	55	with	with	ADP
ijassa-1351	40	56	k	k	PROPN
ijassa-1351	40	57	subsystems	subsystems	PROPN
ijassa-1351	40	58	m	m	PROPN
ijassa-1351	40	59	|m	|m	NOUN
ijassa-1351	40	60	|1	|1	X
ijassa-1351	40	61	and	and	CCONJ
ijassa-1351	40	62	significantly	significantly	ADV
ijassa-1351	40	63	(	(	PUNCT
ijassa-1351	40	64	several	several	ADJ
ijassa-1351	40	65	times	time	NOUN
ijassa-1351	40	66	)	)	PUNCT
ijassa-1351	40	67	improve	improve	VERB
ijassa-1351	40	68	their	their	PRON
ijassa-1351	40	69	quality	quality	NOUN
ijassa-1351	40	70	of	of	ADP
ijassa-1351	40	71	the	the	DET
ijassa-1351	40	72	approximation	approximation	NOUN
ijassa-1351	40	73	.	.	PUNCT
ijassa-1351	41	1	analytical	analytical	ADJ
ijassa-1351	41	2	formulas	formula	NOUN
ijassa-1351	41	3	were	be	AUX
ijassa-1351	41	4	obtained	obtain	VERB
ijassa-1351	41	5	using	use	VERB
ijassa-1351	41	6	a	a	DET
ijassa-1351	41	7	limited	limited	ADJ
ijassa-1351	41	8	set	set	NOUN
ijassa-1351	41	9	of	of	ADP
ijassa-1351	41	10	experimental	experimental	ADJ
ijassa-1351	41	11	data	datum	NOUN
ijassa-1351	41	12	;	;	PUNCT
ijassa-1351	41	13	however	however	ADV
ijassa-1351	41	14	,	,	PUNCT
ijassa-1351	41	15	as	as	SCONJ
ijassa-1351	41	16	shown	show	VERB
ijassa-1351	41	17	by	by	ADP
ijassa-1351	41	18	a	a	DET
ijassa-1351	41	19	numerical	numerical	ADJ
ijassa-1351	41	20	experiment	experiment	NOUN
ijassa-1351	41	21	,	,	PUNCT
ijassa-1351	41	22	they	they	PRON
ijassa-1351	41	23	are	be	AUX
ijassa-1351	41	24	quite	quite	ADV
ijassa-1351	41	25	accurate	accurate	ADJ
ijassa-1351	41	26	for	for	ADP
ijassa-1351	41	27	large	large	ADJ
ijassa-1351	41	28	values	value	NOUN
ijassa-1351	41	29	of	of	ADP
ijassa-1351	41	30	k.	k.	PROPN
ijassa-1351	41	31	in	in	ADP
ijassa-1351	41	32	addition	addition	NOUN
ijassa-1351	41	33	,	,	PUNCT
ijassa-1351	41	34	the	the	DET
ijassa-1351	41	35	proposed	propose	VERB
ijassa-1351	41	36	approach	approach	NOUN
ijassa-1351	41	37	can	can	AUX
ijassa-1351	41	38	be	be	AUX
ijassa-1351	41	39	used	use	VERB
ijassa-1351	41	40	to	to	PART
ijassa-1351	41	41	estimate	estimate	VERB
ijassa-1351	41	42	the	the	DET
ijassa-1351	41	43	response	response	NOUN
ijassa-1351	41	44	time	time	NOUN
ijassa-1351	41	45	of	of	ADP
ijassa-1351	41	46	a	a	DET
ijassa-1351	41	47	fork	fork	NOUN
ijassa-1351	41	48	-	-	PUNCT
ijassa-1351	41	49	join	join	NOUN
ijassa-1351	41	50	qs	qs	NOUN
ijassa-1351	41	51	not	not	PART
ijassa-1351	41	52	only	only	ADV
ijassa-1351	41	53	with	with	ADP
ijassa-1351	41	54	subsystems	subsystem	NOUN
ijassa-1351	41	55	m	m	VERB
ijassa-1351	41	56	|m	|m	NOUN
ijassa-1351	41	57	|1	|1	PUNCT
ijassa-1351	41	58	but	but	CCONJ
ijassa-1351	41	59	also	also	ADV
ijassa-1351	41	60	for	for	ADP
ijassa-1351	41	61	more	more	ADJ
ijassa-1351	41	62	complex	complex	ADJ
ijassa-1351	41	63	variants	variant	NOUN
ijassa-1351	41	64	of	of	ADP
ijassa-1351	41	65	distributions	distribution	NOUN
ijassa-1351	41	66	of	of	ADP
ijassa-1351	41	67	input	input	NOUN
ijassa-1351	41	68	flow	flow	NOUN
ijassa-1351	41	69	and	and	CCONJ
ijassa-1351	41	70	service	service	NOUN
ijassa-1351	41	71	time	time	NOUN
ijassa-1351	41	72	.	.	PUNCT
ijassa-1351	42	1	the	the	DET
ijassa-1351	42	2	vast	vast	ADJ
ijassa-1351	42	3	majority	majority	NOUN
ijassa-1351	42	4	of	of	ADP
ijassa-1351	42	5	solutions	solution	NOUN
ijassa-1351	42	6	for	for	ADP
ijassa-1351	42	7	fork	fork	NOUN
ijassa-1351	42	8	-	-	PUNCT
ijassa-1351	42	9	join	join	NOUN
ijassa-1351	42	10	qs	qs	NOUN
ijassa-1351	42	11	are	be	AUX
ijassa-1351	42	12	approximate	approximate	ADJ
ijassa-1351	42	13	.	.	PUNCT
ijassa-1351	43	1	therefore	therefore	ADV
ijassa-1351	43	2	,	,	PUNCT
ijassa-1351	43	3	the	the	DET
ijassa-1351	43	4	question	question	NOUN
ijassa-1351	43	5	of	of	ADP
ijassa-1351	43	6	the	the	DET
ijassa-1351	43	7	reliability	reliability	NOUN
ijassa-1351	43	8	of	of	ADP
ijassa-1351	43	9	the	the	DET
ijassa-1351	43	10	experimental	experimental	ADJ
ijassa-1351	43	11	data	datum	NOUN
ijassa-1351	43	12	used	use	VERB
ijassa-1351	43	13	to	to	PART
ijassa-1351	43	14	assess	assess	VERB
ijassa-1351	43	15	the	the	DET
ijassa-1351	43	16	quality	quality	NOUN
ijassa-1351	43	17	of	of	ADP
ijassa-1351	43	18	the	the	DET
ijassa-1351	43	19	approximation	approximation	NOUN
ijassa-1351	43	20	of	of	ADP
ijassa-1351	43	21	the	the	DET
ijassa-1351	43	22	obtained	obtain	VERB
ijassa-1351	43	23	expressions	expression	NOUN
ijassa-1351	43	24	comes	come	VERB
ijassa-1351	43	25	to	to	ADP
ijassa-1351	43	26	the	the	DET
ijassa-1351	43	27	fore	fore	NOUN
ijassa-1351	43	28	.	.	PUNCT
ijassa-1351	44	1	as	as	ADP
ijassa-1351	44	2	a	a	DET
ijassa-1351	44	3	rule	rule	NOUN
ijassa-1351	44	4	,	,	PUNCT
ijassa-1351	44	5	numerical	numerical	ADJ
ijassa-1351	44	6	data	datum	NOUN
ijassa-1351	44	7	can	can	AUX
ijassa-1351	44	8	only	only	ADV
ijassa-1351	44	9	be	be	AUX
ijassa-1351	44	10	obtained	obtain	VERB
ijassa-1351	44	11	through	through	ADP
ijassa-1351	44	12	simulation	simulation	NOUN
ijassa-1351	44	13	.	.	PUNCT
ijassa-1351	45	1	the	the	DET
ijassa-1351	45	2	values	value	NOUN
ijassa-1351	45	3	obtained	obtain	VERB
ijassa-1351	45	4	using	use	VERB
ijassa-1351	45	5	the	the	DET
ijassa-1351	45	6	simulation	simulation	NOUN
ijassa-1351	45	7	are	be	AUX
ijassa-1351	45	8	considered	consider	VERB
ijassa-1351	45	9	reference	reference	NOUN
ijassa-1351	45	10	or	or	CCONJ
ijassa-1351	45	11	true	true	ADJ
ijassa-1351	45	12	.	.	PUNCT
ijassa-1351	46	1	however	however	ADV
ijassa-1351	46	2	,	,	PUNCT
ijassa-1351	46	3	it	it	PRON
ijassa-1351	46	4	is	be	AUX
ijassa-1351	46	5	clear	clear	ADJ
ijassa-1351	46	6	that	that	SCONJ
ijassa-1351	46	7	in	in	ADP
ijassa-1351	46	8	order	order	NOUN
ijassa-1351	46	9	for	for	SCONJ
ijassa-1351	46	10	the	the	DET
ijassa-1351	46	11	simulation	simulation	NOUN
ijassa-1351	46	12	data	datum	NOUN
ijassa-1351	46	13	to	to	PART
ijassa-1351	46	14	become	become	VERB
ijassa-1351	46	15	the	the	DET
ijassa-1351	46	16	most	most	ADV
ijassa-1351	46	17	accurate	accurate	ADJ
ijassa-1351	46	18	,	,	PUNCT
ijassa-1351	46	19	a	a	DET
ijassa-1351	46	20	large	large	ADJ
ijassa-1351	46	21	number	number	NOUN
ijassa-1351	46	22	of	of	ADP
ijassa-1351	46	23	realizations	realization	NOUN
ijassa-1351	46	24	of	of	ADP
ijassa-1351	46	25	the	the	DET
ijassa-1351	46	26	estimated	estimate	VERB
ijassa-1351	46	27	random	random	ADJ
ijassa-1351	46	28	variable	variable	NOUN
ijassa-1351	46	29	are	be	AUX
ijassa-1351	46	30	required	require	VERB
ijassa-1351	46	31	within	within	ADP
ijassa-1351	46	32	one	one	NUM
ijassa-1351	46	33	run	run	NOUN
ijassa-1351	46	34	of	of	ADP
ijassa-1351	46	35	the	the	DET
ijassa-1351	46	36	simulation	simulation	NOUN
ijassa-1351	46	37	model	model	NOUN
ijassa-1351	46	38	.	.	PUNCT
ijassa-1351	47	1	at	at	ADP
ijassa-1351	47	2	the	the	DET
ijassa-1351	47	3	same	same	ADJ
ijassa-1351	47	4	time	time	NOUN
ijassa-1351	47	5	,	,	PUNCT
ijassa-1351	47	6	determining	determine	VERB
ijassa-1351	47	7	a	a	DET
ijassa-1351	47	8	sufficient	sufficient	ADJ
ijassa-1351	47	9	number	number	NOUN
ijassa-1351	47	10	of	of	ADP
ijassa-1351	47	11	realizations	realization	NOUN
ijassa-1351	47	12	and	and	CCONJ
ijassa-1351	47	13	confidence	confidence	NOUN
ijassa-1351	47	14	intervals	interval	NOUN
ijassa-1351	47	15	of	of	ADP
ijassa-1351	47	16	the	the	DET
ijassa-1351	47	17	obtained	obtain	VERB
ijassa-1351	47	18	estimates	estimate	NOUN
ijassa-1351	47	19	remains	remain	VERB
ijassa-1351	47	20	a	a	DET
ijassa-1351	47	21	rather	rather	ADV
ijassa-1351	47	22	difficult	difficult	ADJ
ijassa-1351	47	23	question	question	NOUN
ijassa-1351	47	24	due	due	ADP
ijassa-1351	47	25	to	to	ADP
ijassa-1351	47	26	the	the	DET
ijassa-1351	47	27	correlation	correlation	NOUN
ijassa-1351	47	28	of	of	ADP
ijassa-1351	47	29	these	these	DET
ijassa-1351	47	30	data	datum	NOUN
ijassa-1351	47	31	(	(	PUNCT
ijassa-1351	47	32	more	more	ADJ
ijassa-1351	47	33	on	on	ADP
ijassa-1351	47	34	this	this	PRON
ijassa-1351	47	35	will	will	AUX
ijassa-1351	47	36	be	be	AUX
ijassa-1351	47	37	discussed	discuss	VERB
ijassa-1351	47	38	in	in	ADP
ijassa-1351	47	39	the	the	DET
ijassa-1351	47	40	corresponding	corresponding	ADJ
ijassa-1351	47	41	section	section	NOUN
ijassa-1351	47	42	)	)	PUNCT
ijassa-1351	47	43	.	.	PUNCT
ijassa-1351	48	1	the	the	DET
ijassa-1351	48	2	article	article	NOUN
ijassa-1351	48	3	proposes	propose	VERB
ijassa-1351	48	4	an	an	DET
ijassa-1351	48	5	approach	approach	NOUN
ijassa-1351	48	6	to	to	ADP
ijassa-1351	48	7	finding	find	VERB
ijassa-1351	48	8	confidence	confidence	NOUN
ijassa-1351	48	9	intervals	interval	NOUN
ijassa-1351	48	10	,	,	PUNCT
ijassa-1351	48	11	provides	provide	VERB
ijassa-1351	48	12	an	an	DET
ijassa-1351	48	13	algorithm	algorithm	NOUN
ijassa-1351	48	14	for	for	ADP
ijassa-1351	48	15	their	their	PRON
ijassa-1351	48	16	construction	construction	NOUN
ijassa-1351	48	17	,	,	PUNCT
ijassa-1351	48	18	as	as	ADV
ijassa-1351	48	19	well	well	ADV
ijassa-1351	48	20	some	some	DET
ijassa-1351	48	21	recommendations	recommendation	NOUN
ijassa-1351	48	22	.	.	PUNCT
ijassa-1351	49	1	the	the	DET
ijassa-1351	49	2	algorithm	algorithm	NOUN
ijassa-1351	49	3	is	be	AUX
ijassa-1351	49	4	considered	consider	VERB
ijassa-1351	49	5	in	in	ADP
ijassa-1351	49	6	the	the	DET
ijassa-1351	49	7	example	example	NOUN
ijassa-1351	49	8	of	of	ADP
ijassa-1351	49	9	a	a	DET
ijassa-1351	49	10	fork	fork	NOUN
ijassa-1351	49	11	-	-	PUNCT
ijassa-1351	49	12	join	join	NOUN
ijassa-1351	49	13	qs	qs	NOUN
ijassa-1351	49	14	with	with	ADP
ijassa-1351	49	15	subsystems	subsystem	NOUN
ijassa-1351	49	16	of	of	ADP
ijassa-1351	49	17	the	the	DET
ijassa-1351	49	18	form	form	NOUN
ijassa-1351	49	19	m	m	NOUN
ijassa-1351	49	20	|m	|m	NOUN
ijassa-1351	49	21	|1	|1	PRON
ijassa-1351	49	22	;	;	PUNCT
ijassa-1351	49	23	however	however	ADV
ijassa-1351	49	24	,	,	PUNCT
ijassa-1351	49	25	it	it	PRON
ijassa-1351	49	26	can	can	AUX
ijassa-1351	49	27	also	also	ADV
ijassa-1351	49	28	be	be	AUX
ijassa-1351	49	29	extended	extend	VERB
ijassa-1351	49	30	to	to	ADP
ijassa-1351	49	31	the	the	DET
ijassa-1351	49	32	case	case	NOUN
ijassa-1351	49	33	with	with	ADP
ijassa-1351	49	34	more	more	ADV
ijassa-1351	49	35	complex	complex	ADJ
ijassa-1351	49	36	qs	qs	NOUN
ijassa-1351	49	37	as	as	ADP
ijassa-1351	49	38	subsystems	subsystem	NOUN
ijassa-1351	49	39	of	of	ADP
ijassa-1351	49	40	the	the	DET
ijassa-1351	49	41	fork	fork	NOUN
ijassa-1351	49	42	-	-	PUNCT
ijassa-1351	49	43	join	join	NOUN
ijassa-1351	49	44	system	system	NOUN
ijassa-1351	49	45	.	.	PUNCT
ijassa-1351	50	1	so	so	ADV
ijassa-1351	50	2	,	,	PUNCT
ijassa-1351	50	3	the	the	DET
ijassa-1351	50	4	article	article	NOUN
ijassa-1351	50	5	is	be	AUX
ijassa-1351	50	6	organized	organize	VERB
ijassa-1351	50	7	as	as	SCONJ
ijassa-1351	50	8	follows	follow	VERB
ijassa-1351	50	9	.	.	PUNCT
ijassa-1351	51	1	the	the	DET
ijassa-1351	51	2	second	second	ADJ
ijassa-1351	51	3	section	section	NOUN
ijassa-1351	51	4	describes	describe	VERB
ijassa-1351	51	5	an	an	DET
ijassa-1351	51	6	approach	approach	NOUN
ijassa-1351	51	7	to	to	ADP
ijassa-1351	51	8	constructing	construct	VERB
ijassa-1351	51	9	estimates	estimate	NOUN
ijassa-1351	51	10	for	for	ADP
ijassa-1351	51	11	the	the	DET
ijassa-1351	51	12	mathematical	mathematical	ADJ
ijassa-1351	51	13	expectation	expectation	NOUN
ijassa-1351	51	14	and	and	CCONJ
ijassa-1351	51	15	variance	variance	NOUN
ijassa-1351	51	16	of	of	ADP
ijassa-1351	51	17	the	the	DET
ijassa-1351	51	18	response	response	NOUN
ijassa-1351	51	19	time	time	NOUN
ijassa-1351	51	20	,	,	PUNCT
ijassa-1351	51	21	presents	present	VERB
ijassa-1351	51	22	the	the	DET
ijassa-1351	51	23	obtained	obtain	VERB
ijassa-1351	51	24	estimates	estimate	NOUN
ijassa-1351	51	25	in	in	ADP
ijassa-1351	51	26	the	the	DET
ijassa-1351	51	27	form	form	NOUN
ijassa-1351	51	28	of	of	ADP
ijassa-1351	51	29	analytical	analytical	ADJ
ijassa-1351	51	30	expressions	expression	NOUN
ijassa-1351	51	31	,	,	PUNCT
ijassa-1351	51	32	as	as	ADV
ijassa-1351	51	33	well	well	ADV
ijassa-1351	51	34	as	as	ADP
ijassa-1351	51	35	the	the	DET
ijassa-1351	51	36	results	result	NOUN
ijassa-1351	51	37	of	of	ADP
ijassa-1351	51	38	a	a	DET
ijassa-1351	51	39	numerical	numerical	ADJ
ijassa-1351	51	40	experiment	experiment	NOUN
ijassa-1351	51	41	;	;	PUNCT
ijassa-1351	51	42	the	the	DET
ijassa-1351	51	43	third	third	ADJ
ijassa-1351	51	44	section	section	NOUN
ijassa-1351	51	45	raises	raise	VERB
ijassa-1351	51	46	the	the	DET
ijassa-1351	51	47	question	question	NOUN
ijassa-1351	51	48	of	of	ADP
ijassa-1351	51	49	the	the	DET
ijassa-1351	51	50	correct	correct	ADJ
ijassa-1351	51	51	organization	organization	NOUN
ijassa-1351	51	52	of	of	ADP
ijassa-1351	51	53	simulation	simulation	PROPN
ijassa-1351	51	54	modeling	modeling	NOUN
ijassa-1351	51	55	,	,	PUNCT
ijassa-1351	51	56	evaluates	evaluate	VERB
ijassa-1351	51	57	the	the	DET
ijassa-1351	51	58	correlation	correlation	NOUN
ijassa-1351	51	59	between	between	ADP
ijassa-1351	51	60	realizations	realization	NOUN
ijassa-1351	51	61	of	of	ADP
ijassa-1351	51	62	the	the	DET
ijassa-1351	51	63	random	random	ADJ
ijassa-1351	51	64	value	value	NOUN
ijassa-1351	51	65	copyright	copyright	NOUN
ijassa-1351	51	66	©	©	ADP
ijassa-1351	51	67	2023	2023	NUM
ijassa-1351	51	68	assa	assa	NOUN
ijassa-1351	51	69	.	.	PUNCT
ijassa-1351	52	1	adv	adv	PROPN
ijassa-1351	52	2	syst	syst	PROPN
ijassa-1351	52	3	sci	sci	PROPN
ijassa-1351	52	4	appl	appl	PROPN
ijassa-1351	52	5	(	(	PUNCT
ijassa-1351	52	6	2023	2023	NUM
ijassa-1351	52	7	)	)	PUNCT
ijassa-1351	52	8	assa	assa	NOUN
ijassa-1351	52	9	latex	latex	NOUN
ijassa-1351	52	10	template	template	NOUN
ijassa-1351	52	11	101	101	NUM
ijassa-1351	52	12	of	of	ADP
ijassa-1351	52	13	the	the	DET
ijassa-1351	52	14	response	response	NOUN
ijassa-1351	52	15	time	time	NOUN
ijassa-1351	52	16	(	(	PUNCT
ijassa-1351	52	17	in	in	ADP
ijassa-1351	52	18	within	within	ADP
ijassa-1351	52	19	the	the	DET
ijassa-1351	52	20	framework	framework	NOUN
ijassa-1351	52	21	of	of	ADP
ijassa-1351	52	22	the	the	DET
ijassa-1351	52	23	simulation	simulation	NOUN
ijassa-1351	52	24	)	)	PUNCT
ijassa-1351	52	25	,	,	PUNCT
ijassa-1351	52	26	on	on	ADP
ijassa-1351	52	27	the	the	DET
ijassa-1351	52	28	basis	basis	NOUN
ijassa-1351	52	29	of	of	ADP
ijassa-1351	52	30	which	which	PRON
ijassa-1351	52	31	a	a	DET
ijassa-1351	52	32	confidence	confidence	NOUN
ijassa-1351	52	33	interval	interval	NOUN
ijassa-1351	52	34	is	be	AUX
ijassa-1351	52	35	built	build	VERB
ijassa-1351	52	36	using	use	VERB
ijassa-1351	52	37	the	the	DET
ijassa-1351	52	38	proposed	propose	VERB
ijassa-1351	52	39	algorithm	algorithm	NOUN
ijassa-1351	52	40	.	.	PUNCT
ijassa-1351	53	1	2	2	X
ijassa-1351	53	2	.	.	X
ijassa-1351	53	3	evaluation	evaluation	NOUN
ijassa-1351	53	4	of	of	ADP
ijassa-1351	53	5	the	the	DET
ijassa-1351	53	6	main	main	ADJ
ijassa-1351	53	7	performance	performance	NOUN
ijassa-1351	53	8	characteristics	characteristic	NOUN
ijassa-1351	53	9	of	of	ADP
ijassa-1351	53	10	fork	fork	NOUN
ijassa-1351	53	11	-	-	PUNCT
ijassa-1351	53	12	join	join	NOUN
ijassa-1351	53	13	qs	qs	NOUN
ijassa-1351	53	14	in	in	ADP
ijassa-1351	53	15	this	this	DET
ijassa-1351	53	16	section	section	NOUN
ijassa-1351	53	17	,	,	PUNCT
ijassa-1351	53	18	we	we	PRON
ijassa-1351	53	19	present	present	VERB
ijassa-1351	53	20	new	new	ADJ
ijassa-1351	53	21	estimates	estimate	NOUN
ijassa-1351	53	22	for	for	ADP
ijassa-1351	53	23	such	such	ADJ
ijassa-1351	53	24	important	important	ADJ
ijassa-1351	53	25	characteristics	characteristic	NOUN
ijassa-1351	53	26	of	of	ADP
ijassa-1351	53	27	a	a	DET
ijassa-1351	53	28	fork	fork	NOUN
ijassa-1351	53	29	-	-	PUNCT
ijassa-1351	53	30	join	join	NOUN
ijassa-1351	53	31	qs	qs	NOUN
ijassa-1351	53	32	with	with	ADP
ijassa-1351	53	33	k	k	PROPN
ijassa-1351	53	34	subsystems	subsystems	PROPN
ijassa-1351	53	35	m	m	VERB
ijassa-1351	53	36	|m	|m	NOUN
ijassa-1351	53	37	|1	|1	PRON
ijassa-1351	53	38	as	as	ADP
ijassa-1351	53	39	its	its	PRON
ijassa-1351	53	40	average	average	ADJ
ijassa-1351	53	41	response	response	NOUN
ijassa-1351	53	42	time	time	NOUN
ijassa-1351	53	43	and	and	CCONJ
ijassa-1351	53	44	variance	variance	NOUN
ijassa-1351	53	45	.	.	PUNCT
ijassa-1351	54	1	the	the	DET
ijassa-1351	54	2	estimates	estimate	NOUN
ijassa-1351	54	3	proposed	propose	VERB
ijassa-1351	54	4	by	by	ADP
ijassa-1351	54	5	the	the	DET
ijassa-1351	54	6	authors	author	NOUN
ijassa-1351	54	7	are	be	AUX
ijassa-1351	54	8	based	base	VERB
ijassa-1351	54	9	on	on	ADP
ijassa-1351	54	10	the	the	DET
ijassa-1351	54	11	modification	modification	NOUN
ijassa-1351	54	12	of	of	ADP
ijassa-1351	54	13	known	know	VERB
ijassa-1351	54	14	approximations	approximation	NOUN
ijassa-1351	54	15	obtained	obtain	VERB
ijassa-1351	54	16	earlier	early	ADV
ijassa-1351	54	17	.	.	PUNCT
ijassa-1351	55	1	experimental	experimental	ADJ
ijassa-1351	55	2	data	datum	NOUN
ijassa-1351	55	3	,	,	PUNCT
ijassa-1351	55	4	which	which	PRON
ijassa-1351	55	5	we	we	PRON
ijassa-1351	55	6	obtained	obtain	VERB
ijassa-1351	55	7	by	by	ADP
ijassa-1351	55	8	modeling	modeling	NOUN
ijassa-1351	55	9	,	,	PUNCT
ijassa-1351	55	10	were	be	AUX
ijassa-1351	55	11	needed	need	VERB
ijassa-1351	55	12	to	to	PART
ijassa-1351	55	13	correct	correct	VERB
ijassa-1351	55	14	these	these	DET
ijassa-1351	55	15	estimates	estimate	NOUN
ijassa-1351	55	16	.	.	PUNCT
ijassa-1351	56	1	in	in	ADP
ijassa-1351	56	2	particular	particular	ADJ
ijassa-1351	56	3	,	,	PUNCT
ijassa-1351	56	4	using	use	VERB
ijassa-1351	56	5	a	a	DET
ijassa-1351	56	6	simulation	simulation	NOUN
ijassa-1351	56	7	model	model	NOUN
ijassa-1351	56	8	written	write	VERB
ijassa-1351	56	9	in	in	ADP
ijassa-1351	56	10	the	the	DET
ijassa-1351	56	11	python	python	PROPN
ijassa-1351	56	12	software	software	NOUN
ijassa-1351	56	13	environment	environment	NOUN
ijassa-1351	56	14	,	,	PUNCT
ijassa-1351	56	15	the	the	DET
ijassa-1351	56	16	values	value	NOUN
ijassa-1351	56	17	of	of	ADP
ijassa-1351	56	18	the	the	DET
ijassa-1351	56	19	mathematical	mathematical	ADJ
ijassa-1351	56	20	expectation	expectation	NOUN
ijassa-1351	56	21	and	and	CCONJ
ijassa-1351	56	22	dispersion	dispersion	NOUN
ijassa-1351	56	23	of	of	ADP
ijassa-1351	56	24	the	the	DET
ijassa-1351	56	25	response	response	NOUN
ijassa-1351	56	26	time	time	NOUN
ijassa-1351	56	27	were	be	AUX
ijassa-1351	56	28	calculated	calculate	VERB
ijassa-1351	56	29	for	for	ADP
ijassa-1351	56	30	a	a	DET
ijassa-1351	56	31	constant	constant	ADJ
ijassa-1351	56	32	arrival	arrival	NOUN
ijassa-1351	56	33	rate	rate	NOUN
ijassa-1351	56	34	λ	λ	NOUN
ijassa-1351	56	35	=	=	SYM
ijassa-1351	56	36	1	1	NUM
ijassa-1351	56	37	and	and	CCONJ
ijassa-1351	56	38	a	a	DET
ijassa-1351	56	39	changing	change	VERB
ijassa-1351	56	40	service	service	NOUN
ijassa-1351	56	41	rate	rate	NOUN
ijassa-1351	56	42	value	value	NOUN
ijassa-1351	56	43	µ.	µ.	NOUN
ijassa-1351	56	44	namely	namely	ADV
ijassa-1351	56	45	,	,	PUNCT
ijassa-1351	56	46	the	the	DET
ijassa-1351	56	47	load	load	NOUN
ijassa-1351	56	48	factor	factor	NOUN
ijassa-1351	56	49	ρ	ρ	NOUN
ijassa-1351	56	50	=	=	PUNCT
ijassa-1351	56	51	λ/µ	λ/µ	PRON
ijassa-1351	56	52	took	take	VERB
ijassa-1351	56	53	values	value	NOUN
ijassa-1351	56	54	from	from	ADP
ijassa-1351	56	55	0.1	0.1	NUM
ijassa-1351	56	56	to	to	PART
ijassa-1351	56	57	0.9	0.9	NUM
ijassa-1351	56	58	inclusive	inclusive	ADJ
ijassa-1351	56	59	with	with	ADP
ijassa-1351	56	60	a	a	DET
ijassa-1351	56	61	step	step	NOUN
ijassa-1351	56	62	of	of	ADP
ijassa-1351	56	63	0.05	0.05	NUM
ijassa-1351	56	64	,	,	PUNCT
ijassa-1351	56	65	and	and	CCONJ
ijassa-1351	56	66	the	the	DET
ijassa-1351	56	67	number	number	NOUN
ijassa-1351	56	68	of	of	ADP
ijassa-1351	56	69	subsystems	subsystem	NOUN
ijassa-1351	56	70	k	k	PROPN
ijassa-1351	56	71	varied	varied	ADJ
ijassa-1351	56	72	from	from	ADP
ijassa-1351	56	73	3	3	NUM
ijassa-1351	56	74	to	to	PART
ijassa-1351	56	75	20	20	NUM
ijassa-1351	56	76	inclusive	inclusive	ADJ
ijassa-1351	56	77	(	(	PUNCT
ijassa-1351	56	78	because	because	SCONJ
ijassa-1351	56	79	for	for	ADP
ijassa-1351	56	80	k	k	PROPN
ijassa-1351	56	81	=	=	SYM
ijassa-1351	56	82	2	2	NUM
ijassa-1351	56	83	the	the	DET
ijassa-1351	56	84	exact	exact	ADJ
ijassa-1351	56	85	value	value	NOUN
ijassa-1351	56	86	of	of	ADP
ijassa-1351	56	87	the	the	DET
ijassa-1351	56	88	average	average	ADJ
ijassa-1351	56	89	response	response	NOUN
ijassa-1351	56	90	time	time	NOUN
ijassa-1351	56	91	)	)	PUNCT
ijassa-1351	56	92	.	.	PUNCT
ijassa-1351	57	1	the	the	DET
ijassa-1351	57	2	number	number	NOUN
ijassa-1351	57	3	of	of	ADP
ijassa-1351	57	4	tests	test	NOUN
ijassa-1351	57	5	(	(	PUNCT
ijassa-1351	57	6	r.v	r.v	PROPN
ijassa-1351	57	7	.	.	NOUN
ijassa-1351	57	8	implementations	implementation	NOUN
ijassa-1351	57	9	)	)	PUNCT
ijassa-1351	57	10	within	within	ADP
ijassa-1351	57	11	one	one	NUM
ijassa-1351	57	12	run	run	NOUN
ijassa-1351	57	13	of	of	ADP
ijassa-1351	57	14	the	the	DET
ijassa-1351	57	15	simulation	simulation	NOUN
ijassa-1351	57	16	model	model	NOUN
ijassa-1351	57	17	varied	varied	ADJ
ijassa-1351	57	18	from	from	ADP
ijassa-1351	57	19	5	5	NUM
ijassa-1351	57	20	million	million	NUM
ijassa-1351	57	21	in	in	ADP
ijassa-1351	57	22	the	the	DET
ijassa-1351	57	23	case	case	NOUN
ijassa-1351	57	24	of	of	ADP
ijassa-1351	57	25	a	a	DET
ijassa-1351	57	26	low	low	ADJ
ijassa-1351	57	27	system	system	NOUN
ijassa-1351	57	28	load	load	NOUN
ijassa-1351	57	29	to	to	ADP
ijassa-1351	57	30	10	10	NUM
ijassa-1351	57	31	million	million	NUM
ijassa-1351	57	32	in	in	ADP
ijassa-1351	57	33	the	the	DET
ijassa-1351	57	34	case	case	NOUN
ijassa-1351	57	35	of	of	ADP
ijassa-1351	57	36	a	a	DET
ijassa-1351	57	37	high	high	ADJ
ijassa-1351	57	38	system	system	NOUN
ijassa-1351	57	39	load	load	NOUN
ijassa-1351	57	40	.	.	PUNCT
ijassa-1351	58	1	next	next	ADV
ijassa-1351	58	2	,	,	PUNCT
ijassa-1351	58	3	we	we	PRON
ijassa-1351	58	4	describe	describe	VERB
ijassa-1351	58	5	the	the	DET
ijassa-1351	58	6	process	process	NOUN
ijassa-1351	58	7	of	of	ADP
ijassa-1351	58	8	deriving	derive	VERB
ijassa-1351	58	9	new	new	ADJ
ijassa-1351	58	10	estimates	estimate	NOUN
ijassa-1351	58	11	based	base	VERB
ijassa-1351	58	12	on	on	ADP
ijassa-1351	58	13	the	the	DET
ijassa-1351	58	14	results	result	NOUN
ijassa-1351	58	15	of	of	ADP
ijassa-1351	58	16	the	the	DET
ijassa-1351	58	17	simulation	simulation	NOUN
ijassa-1351	58	18	and	and	CCONJ
ijassa-1351	58	19	what	what	PRON
ijassa-1351	58	20	it	it	PRON
ijassa-1351	58	21	leads	lead	VERB
ijassa-1351	58	22	to	to	ADP
ijassa-1351	58	23	.	.	PROPN
ijassa-1351	59	1	2.1	2.1	NUM
ijassa-1351	59	2	.	.	PUNCT
ijassa-1351	60	1	average	average	ADJ
ijassa-1351	60	2	response	response	NOUN
ijassa-1351	60	3	time	time	NOUN
ijassa-1351	60	4	let	let	VERB
ijassa-1351	60	5	e[rk	e[rk	PROPN
ijassa-1351	60	6	]	]	PUNCT
ijassa-1351	60	7	and	and	CCONJ
ijassa-1351	60	8	√	√	ADP
ijassa-1351	60	9	var[rk	var[rk	PROPN
ijassa-1351	60	10	]	]	PUNCT
ijassa-1351	60	11	denote	denote	VERB
ijassa-1351	60	12	the	the	DET
ijassa-1351	60	13	mean	mean	ADJ
ijassa-1351	60	14	and	and	CCONJ
ijassa-1351	60	15	standard	standard	ADJ
ijassa-1351	60	16	deviation	deviation	NOUN
ijassa-1351	60	17	of	of	ADP
ijassa-1351	60	18	the	the	DET
ijassa-1351	60	19	response	response	NOUN
ijassa-1351	60	20	time	time	NOUN
ijassa-1351	60	21	in	in	ADP
ijassa-1351	60	22	a	a	DET
ijassa-1351	60	23	fork	fork	NOUN
ijassa-1351	60	24	-	-	PUNCT
ijassa-1351	60	25	join	join	NOUN
ijassa-1351	60	26	qs	qs	NOUN
ijassa-1351	60	27	with	with	ADP
ijassa-1351	60	28	k	k	PROPN
ijassa-1351	60	29	subsystems	subsystem	NOUN
ijassa-1351	60	30	of	of	ADP
ijassa-1351	60	31	type	type	NOUN
ijassa-1351	60	32	mλ|mµ|1	mλ|mµ|1	PROPN
ijassa-1351	60	33	.	.	PUNCT
ijassa-1351	61	1	according	accord	VERB
ijassa-1351	61	2	to	to	ADP
ijassa-1351	61	3	the	the	DET
ijassa-1351	61	4	approximate	approximate	ADJ
ijassa-1351	61	5	nelsontantawi	nelsontantawi	NOUN
ijassa-1351	61	6	formula	formula	NOUN
ijassa-1351	61	7	for	for	ADP
ijassa-1351	61	8	estimating	estimate	VERB
ijassa-1351	61	9	the	the	DET
ijassa-1351	61	10	average	average	ADJ
ijassa-1351	61	11	response	response	NOUN
ijassa-1351	61	12	time	time	NOUN
ijassa-1351	61	13	[	[	X
ijassa-1351	61	14	6	6	NUM
ijassa-1351	61	15	]	]	PUNCT
ijassa-1351	61	16	,	,	PUNCT
ijassa-1351	61	17	which	which	PRON
ijassa-1351	61	18	gives	give	VERB
ijassa-1351	61	19	the	the	DET
ijassa-1351	61	20	smallest	small	ADJ
ijassa-1351	61	21	relative	relative	ADJ
ijassa-1351	61	22	error	error	NOUN
ijassa-1351	61	23	compared	compare	VERB
ijassa-1351	61	24	to	to	ADP
ijassa-1351	61	25	other	other	ADJ
ijassa-1351	61	26	known	know	VERB
ijassa-1351	61	27	[	[	X
ijassa-1351	61	28	11	11	NUM
ijassa-1351	61	29	]	]	PUNCT
ijassa-1351	61	30	formulas	formula	NOUN
ijassa-1351	61	31	,	,	PUNCT
ijassa-1351	61	32	which	which	PRON
ijassa-1351	61	33	does	do	AUX
ijassa-1351	61	34	not	not	PART
ijassa-1351	61	35	exceed	exceed	VERB
ijassa-1351	61	36	5	5	NUM
ijassa-1351	61	37	%	%	NOUN
ijassa-1351	61	38	for	for	ADP
ijassa-1351	61	39	k	k	PROPN
ijassa-1351	61	40	⩽	⩽	PROPN
ijassa-1351	61	41	32	32	NUM
ijassa-1351	61	42	,	,	PUNCT
ijassa-1351	61	43	we	we	PRON
ijassa-1351	61	44	have	have	VERB
ijassa-1351	61	45	e[rk	e[rk	NOUN
ijassa-1351	61	46	]	]	PUNCT
ijassa-1351	62	1	≈	≈	X
ijassa-1351	63	1	e[rk	e[rk	X
ijassa-1351	63	2	]	]	X
ijassa-1351	63	3	nt	not	PART
ijassa-1351	63	4	=	=	PUNCT
ijassa-1351	63	5	[	[	PUNCT
ijassa-1351	63	6	hk	hk	PROPN
ijassa-1351	63	7	h2	h2	NOUN
ijassa-1351	63	8	+	+	CCONJ
ijassa-1351	63	9	4	4	NUM
ijassa-1351	63	10	11	11	NUM
ijassa-1351	63	11	(	(	PUNCT
ijassa-1351	63	12	1−	1−	NUM
ijassa-1351	63	13	hk	hk	PROPN
ijassa-1351	63	14	h2	h2	PROPN
ijassa-1351	63	15	)	)	PUNCT
ijassa-1351	64	1	ρ	ρ	PROPN
ijassa-1351	64	2	]	]	X
ijassa-1351	64	3	12−	12−	NUM
ijassa-1351	64	4	ρ	ρ	NUM
ijassa-1351	64	5	8	8	NUM
ijassa-1351	64	6	1	1	NUM
ijassa-1351	64	7	µ−	µ−	PROPN
ijassa-1351	64	8	λ	λ	PROPN
ijassa-1351	64	9	,	,	PUNCT
ijassa-1351	64	10	(	(	PUNCT
ijassa-1351	64	11	2.1	2.1	NUM
ijassa-1351	64	12	)	)	PUNCT
ijassa-1351	64	13	where	where	SCONJ
ijassa-1351	64	14	hk	hk	PROPN
ijassa-1351	64	15	=	=	PUNCT
ijassa-1351	64	16	∑k	∑k	PROPN
ijassa-1351	64	17	i=1	i=1	PRON
ijassa-1351	64	18	1	1	NUM
ijassa-1351	64	19	/	/	SYM
ijassa-1351	64	20	i	i	PRON
ijassa-1351	64	21	is	be	AUX
ijassa-1351	64	22	the	the	DET
ijassa-1351	64	23	partial	partial	ADJ
ijassa-1351	64	24	sum	sum	NOUN
ijassa-1351	64	25	of	of	ADP
ijassa-1351	64	26	the	the	DET
ijassa-1351	64	27	harmonic	harmonic	ADJ
ijassa-1351	64	28	series	series	NOUN
ijassa-1351	64	29	.	.	PUNCT
ijassa-1351	65	1	since	since	SCONJ
ijassa-1351	65	2	the	the	DET
ijassa-1351	65	3	dependence	dependence	NOUN
ijassa-1351	65	4	of	of	ADP
ijassa-1351	65	5	the	the	DET
ijassa-1351	65	6	average	average	ADJ
ijassa-1351	65	7	response	response	NOUN
ijassa-1351	65	8	time	time	NOUN
ijassa-1351	65	9	on	on	ADP
ijassa-1351	65	10	the	the	DET
ijassa-1351	65	11	parameters	parameter	NOUN
ijassa-1351	65	12	ρ	ρ	NUM
ijassa-1351	65	13	,	,	PUNCT
ijassa-1351	65	14	(	(	PUNCT
ijassa-1351	65	15	µ−	µ−	PROPN
ijassa-1351	65	16	λ	λ	PROPN
ijassa-1351	65	17	)	)	PUNCT
ijassa-1351	65	18	and	and	CCONJ
ijassa-1351	65	19	(	(	PUNCT
ijassa-1351	65	20	hk	hk	PROPN
ijassa-1351	65	21	/	/	SYM
ijassa-1351	65	22	h2	h2	PROPN
ijassa-1351	65	23	−	−	NOUN
ijassa-1351	65	24	1	1	NUM
ijassa-1351	65	25	)	)	PUNCT
ijassa-1351	65	26	is	be	AUX
ijassa-1351	65	27	observed	observe	VERB
ijassa-1351	65	28	in	in	ADP
ijassa-1351	65	29	the	the	DET
ijassa-1351	65	30	(	(	PUNCT
ijassa-1351	65	31	2.1	2.1	NUM
ijassa-1351	65	32	)	)	PUNCT
ijassa-1351	65	33	formula	formula	NOUN
ijassa-1351	65	34	,	,	PUNCT
ijassa-1351	65	35	it	it	PRON
ijassa-1351	65	36	is	be	AUX
ijassa-1351	65	37	natural	natural	ADJ
ijassa-1351	65	38	to	to	PART
ijassa-1351	65	39	suggest	suggest	VERB
ijassa-1351	65	40	that	that	SCONJ
ijassa-1351	65	41	our	our	PRON
ijassa-1351	65	42	correction	correction	NOUN
ijassa-1351	65	43	depends	depend	VERB
ijassa-1351	65	44	on	on	ADP
ijassa-1351	65	45	from	from	ADP
ijassa-1351	65	46	the	the	DET
ijassa-1351	65	47	same	same	ADJ
ijassa-1351	65	48	settings	setting	NOUN
ijassa-1351	65	49	.	.	PUNCT
ijassa-1351	66	1	in	in	ADP
ijassa-1351	66	2	particular	particular	ADJ
ijassa-1351	66	3	,	,	PUNCT
ijassa-1351	66	4	suppose	suppose	VERB
ijassa-1351	66	5	that	that	SCONJ
ijassa-1351	66	6	the	the	DET
ijassa-1351	66	7	improved	improved	ADJ
ijassa-1351	66	8	estimate	estimate	NOUN
ijassa-1351	66	9	for	for	ADP
ijassa-1351	66	10	the	the	DET
ijassa-1351	66	11	average	average	ADJ
ijassa-1351	66	12	response	response	NOUN
ijassa-1351	66	13	time	time	NOUN
ijassa-1351	66	14	is	be	AUX
ijassa-1351	66	15	e[rk	e[rk	PROPN
ijassa-1351	66	16	]	]	PUNCT
ijassa-1351	67	1	≈	≈	PROPN
ijassa-1351	67	2	(	(	PUNCT
ijassa-1351	67	3	hk	hk	PROPN
ijassa-1351	67	4	h2	h2	PROPN
ijassa-1351	67	5	−	−	PROPN
ijassa-1351	67	6	1	1	NUM
ijassa-1351	67	7	)	)	PUNCT
ijassa-1351	67	8	ρ	ρ	PROPN
ijassa-1351	67	9	µ−	µ−	PROPN
ijassa-1351	67	10	λ	λ	PROPN
ijassa-1351	67	11	·	·	PUNCT
ijassa-1351	67	12	µ̃+	µ̃+	X
ijassa-1351	67	13	e[rk	e[rk	X
ijassa-1351	67	14	]	]	X
ijassa-1351	67	15	nt	not	PART
ijassa-1351	67	16	,	,	PUNCT
ijassa-1351	67	17	(	(	PUNCT
ijassa-1351	67	18	2.2	2.2	NUM
ijassa-1351	67	19	)	)	PUNCT
ijassa-1351	67	20	where	where	SCONJ
ijassa-1351	67	21	we	we	PRON
ijassa-1351	67	22	assume	assume	VERB
ijassa-1351	67	23	that	that	SCONJ
ijassa-1351	67	24	the	the	DET
ijassa-1351	67	25	nelson	nelson	PROPN
ijassa-1351	67	26	-	-	PUNCT
ijassa-1351	67	27	tantawi	tantawi	PROPN
ijassa-1351	67	28	estimate	estimate	NOUN
ijassa-1351	67	29	is	be	AUX
ijassa-1351	67	30	sharp	sharp	ADJ
ijassa-1351	67	31	for	for	SCONJ
ijassa-1351	67	32	k	k	PROPN
ijassa-1351	67	33	=	=	SYM
ijassa-1351	67	34	2	2	NUM
ijassa-1351	67	35	and	and	CCONJ
ijassa-1351	67	36	asymptotically	asymptotically	ADV
ijassa-1351	67	37	sharp	sharp	ADJ
ijassa-1351	67	38	for	for	ADP
ijassa-1351	67	39	ρ	ρ	PROPN
ijassa-1351	67	40	→	→	SYM
ijassa-1351	67	41	0	0	NUM
ijassa-1351	67	42	,	,	PUNCT
ijassa-1351	67	43	while	while	SCONJ
ijassa-1351	67	44	the	the	DET
ijassa-1351	67	45	scale	scale	NOUN
ijassa-1351	67	46	factor	factor	NOUN
ijassa-1351	67	47	1/(µ−	1/(µ−	PROPN
ijassa-1351	67	48	λ	λ	PROPN
ijassa-1351	67	49	)	)	PUNCT
ijassa-1351	67	50	is	be	AUX
ijassa-1351	67	51	preserved	preserve	VERB
ijassa-1351	67	52	.	.	PUNCT
ijassa-1351	68	1	next	next	ADV
ijassa-1351	68	2	,	,	PUNCT
ijassa-1351	68	3	to	to	PART
ijassa-1351	68	4	refine	refine	VERB
ijassa-1351	68	5	µ̃	µ̃	PROPN
ijassa-1351	68	6	,	,	PUNCT
ijassa-1351	68	7	plot	plot	VERB
ijassa-1351	68	8	the	the	DET
ijassa-1351	68	9	modified	modify	VERB
ijassa-1351	68	10	mean	mean	NOUN
ijassa-1351	68	11	response	response	NOUN
ijassa-1351	68	12	time	time	NOUN
ijassa-1351	68	13	expression	expression	NOUN
ijassa-1351	68	14	as	as	ADP
ijassa-1351	68	15	a	a	DET
ijassa-1351	68	16	function	function	NOUN
ijassa-1351	68	17	of	of	ADP
ijassa-1351	68	18	ρ	ρ	PROPN
ijassa-1351	68	19	and	and	CCONJ
ijassa-1351	68	20	(	(	PUNCT
ijassa-1351	68	21	hk	hk	PROPN
ijassa-1351	68	22	/	/	SYM
ijassa-1351	68	23	h2	h2	PROPN
ijassa-1351	68	24	−	−	NOUN
ijassa-1351	68	25	1	1	NUM
ijassa-1351	68	26	)	)	PUNCT
ijassa-1351	68	27	.	.	PUNCT
ijassa-1351	69	1	in	in	ADP
ijassa-1351	69	2	this	this	DET
ijassa-1351	69	3	case	case	NOUN
ijassa-1351	69	4	,	,	PUNCT
ijassa-1351	69	5	by	by	ADP
ijassa-1351	69	6	the	the	DET
ijassa-1351	69	7	modified	modify	VERB
ijassa-1351	69	8	expression	expression	NOUN
ijassa-1351	69	9	,	,	PUNCT
ijassa-1351	69	10	we	we	PRON
ijassa-1351	69	11	mean	mean	VERB
ijassa-1351	69	12	the	the	DET
ijassa-1351	69	13	relation	relation	NOUN
ijassa-1351	69	14	µ̃	µ̃	PROPN
ijassa-1351	69	15	=	=	PUNCT
ijassa-1351	69	16	(	(	PUNCT
ijassa-1351	69	17	e[rk	e[rk	X
ijassa-1351	69	18	]	]	X
ijassa-1351	69	19	−	−	X
ijassa-1351	70	1	e[rk	e[rk	NOUN
ijassa-1351	70	2	]	]	X
ijassa-1351	70	3	nt	not	PART
ijassa-1351	70	4	)	)	PUNCT
ijassa-1351	70	5	(	(	PUNCT
ijassa-1351	70	6	µ−	µ−	PROPN
ijassa-1351	70	7	λ	λ	PROPN
ijassa-1351	70	8	)	)	PUNCT
ijassa-1351	70	9	(	(	PUNCT
ijassa-1351	70	10	hk	hk	PROPN
ijassa-1351	70	11	/	/	SYM
ijassa-1351	70	12	h2	h2	PROPN
ijassa-1351	70	13	−	−	PROPN
ijassa-1351	70	14	1)ρ	1)ρ	NUM
ijassa-1351	70	15	,	,	PUNCT
ijassa-1351	70	16	(	(	PUNCT
ijassa-1351	70	17	2.3	2.3	NUM
ijassa-1351	70	18	)	)	PUNCT
ijassa-1351	70	19	the	the	DET
ijassa-1351	70	20	calculation	calculation	NOUN
ijassa-1351	70	21	of	of	ADP
ijassa-1351	70	22	the	the	DET
ijassa-1351	70	23	right	right	ADJ
ijassa-1351	70	24	side	side	NOUN
ijassa-1351	70	25	of	of	ADP
ijassa-1351	70	26	which	which	PRON
ijassa-1351	70	27	is	be	AUX
ijassa-1351	70	28	possible	possible	ADJ
ijassa-1351	70	29	due	due	ADP
ijassa-1351	70	30	to	to	ADP
ijassa-1351	70	31	the	the	DET
ijassa-1351	70	32	results	result	NOUN
ijassa-1351	70	33	of	of	ADP
ijassa-1351	70	34	simulation	simulation	NOUN
ijassa-1351	70	35	modeling	model	VERB
ijassa-1351	70	36	for	for	ADP
ijassa-1351	70	37	e[rk	e[rk	PROPN
ijassa-1351	70	38	]	]	PUNCT
ijassa-1351	70	39	and	and	CCONJ
ijassa-1351	70	40	calculations	calculation	NOUN
ijassa-1351	70	41	using	use	VERB
ijassa-1351	70	42	the	the	DET
ijassa-1351	70	43	formula	formula	NOUN
ijassa-1351	70	44	(	(	PUNCT
ijassa-1351	70	45	2.1	2.1	NUM
ijassa-1351	70	46	)	)	PUNCT
ijassa-1351	70	47	for	for	ADP
ijassa-1351	70	48	e[rk	e[rk	NOUN
ijassa-1351	70	49	]	]	X
ijassa-1351	70	50	nt	not	PART
ijassa-1351	70	51	.	.	PUNCT
ijassa-1351	71	1	in	in	ADP
ijassa-1351	71	2	the	the	DET
ijassa-1351	71	3	figures	figure	NOUN
ijassa-1351	71	4	2.1	2.1	NUM
ijassa-1351	71	5	and	and	CCONJ
ijassa-1351	71	6	2.2	2.2	NUM
ijassa-1351	71	7	one	one	NUM
ijassa-1351	71	8	can	can	AUX
ijassa-1351	71	9	catch	catch	VERB
ijassa-1351	71	10	the	the	DET
ijassa-1351	71	11	linear	linear	ADJ
ijassa-1351	71	12	dependence	dependence	NOUN
ijassa-1351	71	13	of	of	ADP
ijassa-1351	71	14	µ̃	µ̃	PROPN
ijassa-1351	71	15	on	on	ADP
ijassa-1351	71	16	ρ	ρ	PROPN
ijassa-1351	71	17	and	and	CCONJ
ijassa-1351	71	18	hk	hk	PROPN
ijassa-1351	71	19	/	/	SYM
ijassa-1351	71	20	h2	h2	PROPN
ijassa-1351	71	21	−	−	NOUN
ijassa-1351	71	22	1	1	NUM
ijassa-1351	71	23	(	(	PUNCT
ijassa-1351	71	24	though	though	SCONJ
ijassa-1351	71	25	not	not	PART
ijassa-1351	71	26	very	very	ADV
ijassa-1351	71	27	strict	strict	ADJ
ijassa-1351	71	28	)	)	PUNCT
ijassa-1351	71	29	.	.	PUNCT
ijassa-1351	72	1	thus	thus	ADV
ijassa-1351	72	2	,	,	PUNCT
ijassa-1351	72	3	the	the	DET
ijassa-1351	72	4	analysis	analysis	NOUN
ijassa-1351	72	5	of	of	ADP
ijassa-1351	72	6	graphs	graph	NOUN
ijassa-1351	72	7	allows	allow	VERB
ijassa-1351	72	8	us	we	PRON
ijassa-1351	72	9	to	to	PART
ijassa-1351	72	10	propose	propose	VERB
ijassa-1351	72	11	an	an	DET
ijassa-1351	72	12	expression	expression	NOUN
ijassa-1351	72	13	of	of	ADP
ijassa-1351	72	14	copyright	copyright	NOUN
ijassa-1351	72	15	©	©	PROPN
ijassa-1351	72	16	2023	2023	NUM
ijassa-1351	72	17	assa	assa	NOUN
ijassa-1351	72	18	.	.	PUNCT
ijassa-1351	73	1	adv	adv	PROPN
ijassa-1351	73	2	syst	syst	PROPN
ijassa-1351	73	3	sci	sci	PROPN
ijassa-1351	73	4	appl	appl	PROPN
ijassa-1351	73	5	(	(	PUNCT
ijassa-1351	73	6	2023	2023	NUM
ijassa-1351	73	7	)	)	PUNCT
ijassa-1351	73	8	102	102	NUM
ijassa-1351	73	9	a.v	a.v	PROPN
ijassa-1351	73	10	.	.	PROPN
ijassa-1351	73	11	gorbunova	gorbunova	PROPN
ijassa-1351	73	12	,	,	PUNCT
ijassa-1351	73	13	a.v	a.v	PROPN
ijassa-1351	73	14	.	.	PROPN
ijassa-1351	73	15	lebedev	lebedev	PROPN
ijassa-1351	73	16	0.00	0.00	NUM
ijassa-1351	73	17	0.05	0.05	NUM
ijassa-1351	73	18	0.10	0.10	NUM
ijassa-1351	73	19	0.15	0.15	NUM
ijassa-1351	73	20	0.20	0.20	NUM
ijassa-1351	73	21	0	0	NUM
ijassa-1351	73	22	0.1	0.1	NUM
ijassa-1351	73	23	0.2	0.2	NUM
ijassa-1351	73	24	0.3	0.3	NUM
ijassa-1351	73	25	0.4	0.4	NUM
ijassa-1351	73	26	0.5	0.5	NUM
ijassa-1351	73	27	0.6	0.6	NUM
ijassa-1351	73	28	0.7	0.7	NUM
ijassa-1351	73	29	0.8	0.8	NUM
ijassa-1351	73	30	0.9	0.9	NUM
ijassa-1351	73	31	1	1	NUM
ijassa-1351	73	32	µ	µ	PRON
ijassa-1351	73	33	ρ	ρ	NUM
ijassa-1351	73	34	fig	fig	NOUN
ijassa-1351	73	35	.	.	PUNCT
ijassa-1351	74	1	2.1	2.1	NUM
ijassa-1351	74	2	.	.	PUNCT
ijassa-1351	74	3	dependence	dependence	NOUN
ijassa-1351	74	4	µ̃	µ̃	PROPN
ijassa-1351	74	5	from	from	ADP
ijassa-1351	74	6	(	(	PUNCT
ijassa-1351	74	7	2.3	2.3	NUM
ijassa-1351	74	8	)	)	PUNCT
ijassa-1351	74	9	on	on	ADP
ijassa-1351	74	10	ρ	ρ	PROPN
ijassa-1351	74	11	.	.	PROPN
ijassa-1351	74	12	0.00	0.00	NUM
ijassa-1351	74	13	0.05	0.05	NUM
ijassa-1351	74	14	0.10	0.10	NUM
ijassa-1351	74	15	0.15	0.15	NUM
ijassa-1351	74	16	0.20	0.20	NUM
ijassa-1351	74	17	0.2	0.2	NUM
ijassa-1351	74	18	0.3	0.3	NUM
ijassa-1351	74	19	0.4	0.4	NUM
ijassa-1351	74	20	0.5	0.5	NUM
ijassa-1351	74	21	0.6	0.6	NUM
ijassa-1351	74	22	0.7	0.7	NUM
ijassa-1351	74	23	0.8	0.8	NUM
ijassa-1351	74	24	0.9	0.9	NUM
ijassa-1351	74	25	1	1	NUM
ijassa-1351	74	26	1.1	1.1	NUM
ijassa-1351	74	27	1.2	1.2	NUM
ijassa-1351	74	28	1.3	1.3	NUM
ijassa-1351	74	29	1.4	1.4	NUM
ijassa-1351	74	30	µ	µ	PROPN
ijassa-1351	74	31	hk	hk	PROPN
ijassa-1351	74	32	/	/	SYM
ijassa-1351	74	33	h2	h2	PROPN
ijassa-1351	74	34	–	–	PUNCT
ijassa-1351	74	35	1	1	NUM
ijassa-1351	74	36	fig	fig	NOUN
ijassa-1351	74	37	.	.	PUNCT
ijassa-1351	75	1	2.2	2.2	NUM
ijassa-1351	75	2	.	.	PUNCT
ijassa-1351	75	3	dependence	dependence	NOUN
ijassa-1351	75	4	µ̃	µ̃	PROPN
ijassa-1351	75	5	from	from	ADP
ijassa-1351	75	6	(	(	PUNCT
ijassa-1351	75	7	2.3	2.3	NUM
ijassa-1351	75	8	)	)	PUNCT
ijassa-1351	75	9	on	on	ADP
ijassa-1351	75	10	(	(	PUNCT
ijassa-1351	75	11	hk	hk	PROPN
ijassa-1351	75	12	/	/	SYM
ijassa-1351	75	13	h2	h2	PROPN
ijassa-1351	75	14	−	−	NOUN
ijassa-1351	75	15	1	1	NUM
ijassa-1351	75	16	)	)	PUNCT
ijassa-1351	75	17	.	.	PUNCT
ijassa-1351	76	1	the	the	DET
ijassa-1351	76	2	form	form	NOUN
ijassa-1351	76	3	µ̃	µ̃	PROPN
ijassa-1351	76	4	=	=	SYM
ijassa-1351	76	5	µ̃(ρ	µ̃(ρ	PROPN
ijassa-1351	76	6	,	,	PUNCT
ijassa-1351	76	7	hk	hk	PROPN
ijassa-1351	76	8	)	)	PUNCT
ijassa-1351	77	1	≈	≈	PROPN
ijassa-1351	77	2	c1	c1	PROPN
ijassa-1351	77	3	−	−	PROPN
ijassa-1351	77	4	c2	c2	PROPN
ijassa-1351	77	5	(	(	PUNCT
ijassa-1351	77	6	hk	hk	PROPN
ijassa-1351	77	7	h2	h2	PROPN
ijassa-1351	77	8	−	−	PROPN
ijassa-1351	77	9	1	1	NUM
ijassa-1351	77	10	)	)	PUNCT
ijassa-1351	77	11	+	+	CCONJ
ijassa-1351	77	12	c3ρ	c3ρ	PROPN
ijassa-1351	77	13	,	,	PUNCT
ijassa-1351	77	14	(	(	PUNCT
ijassa-1351	77	15	2.4	2.4	NUM
ijassa-1351	77	16	)	)	PUNCT
ijassa-1351	77	17	i.e.	i.e.	X
ijassa-1351	77	18	e[rk	e[rk	X
ijassa-1351	77	19	]	]	PUNCT
ijassa-1351	78	1	≈	≈	PROPN
ijassa-1351	78	2	(	(	PUNCT
ijassa-1351	78	3	hk	hk	PROPN
ijassa-1351	78	4	h2	h2	PROPN
ijassa-1351	78	5	−	−	PROPN
ijassa-1351	78	6	1	1	NUM
ijassa-1351	78	7	)	)	PUNCT
ijassa-1351	78	8	ρ	ρ	PROPN
ijassa-1351	78	9	µ−	µ−	PROPN
ijassa-1351	78	10	λ	λ	PROPN
ijassa-1351	78	11	·	·	PUNCT
ijassa-1351	78	12	(	(	PUNCT
ijassa-1351	78	13	c1	c1	PROPN
ijassa-1351	78	14	−	−	PROPN
ijassa-1351	78	15	c2	c2	PROPN
ijassa-1351	78	16	(	(	PUNCT
ijassa-1351	78	17	hk	hk	PROPN
ijassa-1351	78	18	h2	h2	PROPN
ijassa-1351	78	19	−	−	PROPN
ijassa-1351	78	20	1	1	NUM
ijassa-1351	78	21	)	)	PUNCT
ijassa-1351	78	22	+	+	CCONJ
ijassa-1351	78	23	c3ρ	c3ρ	PROPN
ijassa-1351	78	24	)	)	PUNCT
ijassa-1351	79	1	+	+	CCONJ
ijassa-1351	79	2	e[rk	e[rk	X
ijassa-1351	79	3	]	]	X
ijassa-1351	79	4	nt	not	PART
ijassa-1351	79	5	.	.	PUNCT
ijassa-1351	80	1	(	(	PUNCT
ijassa-1351	80	2	2.5	2.5	NUM
ijassa-1351	80	3	)	)	PUNCT
ijassa-1351	80	4	we	we	PRON
ijassa-1351	80	5	use	use	VERB
ijassa-1351	80	6	the	the	DET
ijassa-1351	80	7	nelder	nelder	ADJ
ijassa-1351	80	8	-	-	PUNCT
ijassa-1351	80	9	mead	mead	NOUN
ijassa-1351	80	10	optimization	optimization	NOUN
ijassa-1351	80	11	method	method	NOUN
ijassa-1351	80	12	[	[	X
ijassa-1351	80	13	18	18	NUM
ijassa-1351	80	14	,	,	PUNCT
ijassa-1351	80	15	19	19	NUM
ijassa-1351	80	16	]	]	PUNCT
ijassa-1351	80	17	to	to	PART
ijassa-1351	80	18	determine	determine	VERB
ijassa-1351	80	19	the	the	DET
ijassa-1351	80	20	values	value	NOUN
ijassa-1351	80	21	of	of	ADP
ijassa-1351	80	22	the	the	DET
ijassa-1351	80	23	coefficients	coefficient	NOUN
ijassa-1351	80	24	ci	ci	PROPN
ijassa-1351	80	25	,	,	PUNCT
ijassa-1351	80	26	i	i	NOUN
ijassa-1351	80	27	=	=	NOUN
ijassa-1351	80	28	1	1	NUM
ijassa-1351	80	29	,	,	PUNCT
ijassa-1351	80	30	2	2	NUM
ijassa-1351	80	31	,	,	PUNCT
ijassa-1351	80	32	3	3	NUM
ijassa-1351	80	33	.	.	PUNCT
ijassa-1351	81	1	the	the	DET
ijassa-1351	81	2	idea	idea	NOUN
ijassa-1351	81	3	of	of	ADP
ijassa-1351	81	4	using	use	VERB
ijassa-1351	81	5	this	this	DET
ijassa-1351	81	6	method	method	NOUN
ijassa-1351	81	7	is	be	AUX
ijassa-1351	81	8	to	to	PART
ijassa-1351	81	9	minimize	minimize	VERB
ijassa-1351	81	10	the	the	DET
ijassa-1351	81	11	maximum	maximum	ADJ
ijassa-1351	81	12	value	value	NOUN
ijassa-1351	81	13	of	of	ADP
ijassa-1351	81	14	the	the	DET
ijassa-1351	81	15	modulus	modulus	NOUN
ijassa-1351	81	16	of	of	ADP
ijassa-1351	81	17	the	the	DET
ijassa-1351	81	18	relative	relative	ADJ
ijassa-1351	81	19	error	error	NOUN
ijassa-1351	81	20	of	of	ADP
ijassa-1351	81	21	approximation	approximation	NOUN
ijassa-1351	81	22	of	of	ADP
ijassa-1351	81	23	the	the	DET
ijassa-1351	81	24	average	average	ADJ
ijassa-1351	81	25	response	response	NOUN
ijassa-1351	81	26	time	time	NOUN
ijassa-1351	81	27	by	by	ADP
ijassa-1351	81	28	the	the	DET
ijassa-1351	81	29	copyright	copyright	NOUN
ijassa-1351	81	30	©	©	PROPN
ijassa-1351	81	31	2023	2023	NUM
ijassa-1351	81	32	assa	assa	NOUN
ijassa-1351	81	33	.	.	PUNCT
ijassa-1351	82	1	adv	adv	PROPN
ijassa-1351	82	2	syst	syst	PROPN
ijassa-1351	82	3	sci	sci	PROPN
ijassa-1351	82	4	appl	appl	PROPN
ijassa-1351	82	5	(	(	PUNCT
ijassa-1351	82	6	2023	2023	NUM
ijassa-1351	82	7	)	)	PUNCT
ijassa-1351	82	8	assa	assa	NOUN
ijassa-1351	82	9	latex	latex	NOUN
ijassa-1351	82	10	template	template	NOUN
ijassa-1351	82	11	103	103	NUM
ijassa-1351	82	12	expression	expression	NOUN
ijassa-1351	82	13	(	(	PUNCT
ijassa-1351	82	14	2.5	2.5	NUM
ijassa-1351	82	15	)	)	PUNCT
ijassa-1351	82	16	to	to	ADP
ijassa-1351	82	17	its	its	PRON
ijassa-1351	82	18	“	"	PUNCT
ijassa-1351	82	19	true	true	ADJ
ijassa-1351	82	20	”	"	PUNCT
ijassa-1351	82	21	values	value	NOUN
ijassa-1351	82	22	calculated	calculate	VERB
ijassa-1351	82	23	using	use	VERB
ijassa-1351	82	24	simulation	simulation	NOUN
ijassa-1351	82	25	max	max	PROPN
ijassa-1351	82	26	∣∣∣∣	∣∣∣∣	PROPN
ijassa-1351	82	27	ê[rk	ê[rk	PROPN
ijassa-1351	82	28	]	]	PUNCT
ijassa-1351	82	29	−	−	X
ijassa-1351	82	30	e[rk	e[rk	X
ijassa-1351	82	31	]	]	PUNCT
ijassa-1351	82	32	e[rk	e[rk	X
ijassa-1351	82	33	]	]	PUNCT
ijassa-1351	82	34	·	·	PUNCT
ijassa-1351	82	35	100	100	NUM
ijassa-1351	82	36	%	%	NOUN
ijassa-1351	82	37	∣∣∣∣	∣∣∣∣	PROPN
ijassa-1351	82	38	→	→	SYM
ijassa-1351	82	39	min	min	PROPN
ijassa-1351	82	40	.	.	PUNCT
ijassa-1351	83	1	(	(	PUNCT
ijassa-1351	83	2	2.6	2.6	NUM
ijassa-1351	83	3	)	)	PUNCT
ijassa-1351	83	4	as	as	ADP
ijassa-1351	83	5	a	a	DET
ijassa-1351	83	6	result	result	NOUN
ijassa-1351	83	7	of	of	ADP
ijassa-1351	83	8	minimizing	minimize	VERB
ijassa-1351	83	9	the	the	DET
ijassa-1351	83	10	error	error	NOUN
ijassa-1351	83	11	(	(	PUNCT
ijassa-1351	83	12	2.6	2.6	NUM
ijassa-1351	83	13	)	)	PUNCT
ijassa-1351	83	14	on	on	ADP
ijassa-1351	83	15	the	the	DET
ijassa-1351	83	16	entire	entire	ADJ
ijassa-1351	83	17	set	set	NOUN
ijassa-1351	83	18	of	of	ADP
ijassa-1351	83	19	data	datum	NOUN
ijassa-1351	83	20	obtained	obtain	VERB
ijassa-1351	83	21	through	through	ADP
ijassa-1351	83	22	simulation	simulation	NOUN
ijassa-1351	83	23	,	,	PUNCT
ijassa-1351	83	24	the	the	DET
ijassa-1351	83	25	optimal	optimal	ADJ
ijassa-1351	83	26	values	value	NOUN
ijassa-1351	83	27	of	of	ADP
ijassa-1351	83	28	the	the	DET
ijassa-1351	83	29	coefficients	coefficient	NOUN
ijassa-1351	83	30	c1	c1	PROPN
ijassa-1351	83	31	,	,	PUNCT
ijassa-1351	83	32	c2	c2	PROPN
ijassa-1351	83	33	and	and	CCONJ
ijassa-1351	83	34	c3	c3	PROPN
ijassa-1351	83	35	are	be	AUX
ijassa-1351	83	36	determined	determine	VERB
ijassa-1351	83	37	,	,	PUNCT
ijassa-1351	83	38	which	which	PRON
ijassa-1351	83	39	best	well	ADV
ijassa-1351	83	40	reflect	reflect	VERB
ijassa-1351	83	41	the	the	DET
ijassa-1351	83	42	dependence	dependence	NOUN
ijassa-1351	83	43	(	(	PUNCT
ijassa-1351	83	44	2.5	2.5	NUM
ijassa-1351	83	45	)	)	PUNCT
ijassa-1351	83	46	within	within	ADP
ijassa-1351	83	47	the	the	DET
ijassa-1351	83	48	chosen	choose	VERB
ijassa-1351	83	49	optimization	optimization	NOUN
ijassa-1351	83	50	method	method	NOUN
ijassa-1351	83	51	.	.	PUNCT
ijassa-1351	84	1	as	as	ADP
ijassa-1351	84	2	a	a	DET
ijassa-1351	84	3	result	result	NOUN
ijassa-1351	84	4	,	,	PUNCT
ijassa-1351	84	5	after	after	ADP
ijassa-1351	84	6	applying	apply	VERB
ijassa-1351	84	7	the	the	DET
ijassa-1351	84	8	nelder	nelder	ADJ
ijassa-1351	84	9	-	-	PUNCT
ijassa-1351	84	10	mead	mead	NOUN
ijassa-1351	84	11	optimization	optimization	NOUN
ijassa-1351	84	12	method	method	NOUN
ijassa-1351	84	13	to	to	ADP
ijassa-1351	84	14	(	(	PUNCT
ijassa-1351	84	15	2.6	2.6	NUM
ijassa-1351	84	16	)	)	PUNCT
ijassa-1351	84	17	as	as	ADP
ijassa-1351	84	18	a	a	DET
ijassa-1351	84	19	function	function	NOUN
ijassa-1351	84	20	of	of	ADP
ijassa-1351	84	21	several	several	ADJ
ijassa-1351	84	22	ci	ci	NOUN
ijassa-1351	84	23	variables	variable	NOUN
ijassa-1351	84	24	in	in	ADP
ijassa-1351	84	25	the	the	DET
ijassa-1351	84	26	python	python	NOUN
ijassa-1351	84	27	programming	programming	NOUN
ijassa-1351	84	28	environment	environment	NOUN
ijassa-1351	84	29	,	,	PUNCT
ijassa-1351	84	30	we	we	PRON
ijassa-1351	84	31	get	get	VERB
ijassa-1351	84	32	c1	c1	PROPN
ijassa-1351	84	33	≈	≈	PROPN
ijassa-1351	84	34	0.087197	0.087197	PROPN
ijassa-1351	84	35	,	,	PUNCT
ijassa-1351	84	36	c2	c2	PROPN
ijassa-1351	84	37	≈	≈	PROPN
ijassa-1351	84	38	0.070236	0.070236	PROPN
ijassa-1351	84	39	,	,	PUNCT
ijassa-1351	85	1	c3	c3	PROPN
ijassa-1351	85	2	≈	≈	PROPN
ijassa-1351	85	3	0.09638	0.09638	NUM
ijassa-1351	85	4	.	.	PUNCT
ijassa-1351	86	1	(	(	PUNCT
ijassa-1351	86	2	2.7	2.7	NUM
ijassa-1351	86	3	)	)	PUNCT
ijassa-1351	86	4	in	in	ADP
ijassa-1351	86	5	this	this	DET
ijassa-1351	86	6	case	case	NOUN
ijassa-1351	86	7	,	,	PUNCT
ijassa-1351	86	8	for	for	ADP
ijassa-1351	86	9	the	the	DET
ijassa-1351	86	10	above	above	ADJ
ijassa-1351	86	11	values	value	NOUN
ijassa-1351	86	12	λ	λ	X
ijassa-1351	86	13	=	=	SYM
ijassa-1351	86	14	1	1	NUM
ijassa-1351	86	15	,	,	PUNCT
ijassa-1351	86	16	ρ	ρ	PROPN
ijassa-1351	86	17	∈	∈	PROPN
ijassa-1351	87	1	[	[	X
ijassa-1351	87	2	0.1	0.1	NUM
ijassa-1351	87	3	,	,	PUNCT
ijassa-1351	87	4	0.9	0.9	NUM
ijassa-1351	87	5	]	]	PUNCT
ijassa-1351	87	6	with	with	ADP
ijassa-1351	87	7	step	step	NOUN
ijassa-1351	87	8	0.05	0.05	NUM
ijassa-1351	87	9	and	and	CCONJ
ijassa-1351	87	10	k	k	NOUN
ijassa-1351	87	11	=	=	SYM
ijassa-1351	87	12	3	3	NUM
ijassa-1351	87	13	,	,	PUNCT
ijassa-1351	87	14	...	...	PUNCT
ijassa-1351	87	15	,	,	PUNCT
ijassa-1351	87	16	20	20	NUM
ijassa-1351	87	17	,	,	PUNCT
ijassa-1351	87	18	the	the	DET
ijassa-1351	87	19	following	follow	VERB
ijassa-1351	87	20	holds	hold	VERB
ijassa-1351	87	21	maxape	maxape	NOUN
ijassa-1351	87	22	≈	≈	PROPN
ijassa-1351	87	23	0.343207	0.343207	NUM
ijassa-1351	87	24	%	%	NOUN
ijassa-1351	87	25	,	,	PUNCT
ijassa-1351	87	26	minape	minape	NOUN
ijassa-1351	87	27	≈	≈	PROPN
ijassa-1351	87	28	0.001150	0.001150	NUM
ijassa-1351	87	29	%	%	NOUN
ijassa-1351	87	30	,	,	PUNCT
ijassa-1351	87	31	mape	mape	NOUN
ijassa-1351	88	1	≈	≈	PROPN
ijassa-1351	88	2	0.142565	0.142565	NUM
ijassa-1351	88	3	%	%	NOUN
ijassa-1351	88	4	,	,	PUNCT
ijassa-1351	88	5	while	while	SCONJ
ijassa-1351	88	6	for	for	ADP
ijassa-1351	88	7	nelson	nelson	PROPN
ijassa-1351	88	8	-	-	PUNCT
ijassa-1351	88	9	tantawi	tantawi	PROPN
ijassa-1351	88	10	formula	formula	NOUN
ijassa-1351	88	11	(	(	PUNCT
ijassa-1351	88	12	2.1	2.1	NUM
ijassa-1351	88	13	)	)	PUNCT
ijassa-1351	88	14	with	with	ADP
ijassa-1351	88	15	the	the	DET
ijassa-1351	88	16	same	same	ADJ
ijassa-1351	88	17	values	value	NOUN
ijassa-1351	88	18	of	of	ADP
ijassa-1351	88	19	λ	λ	PROPN
ijassa-1351	88	20	,	,	PUNCT
ijassa-1351	88	21	ρ	ρ	PROPN
ijassa-1351	88	22	and	and	CCONJ
ijassa-1351	88	23	k	k	NOUN
ijassa-1351	88	24	the	the	DET
ijassa-1351	88	25	following	follow	VERB
ijassa-1351	88	26	is	be	AUX
ijassa-1351	88	27	true	true	ADJ
ijassa-1351	88	28	maxape	maxape	NOUN
ijassa-1351	89	1	≈	≈	PROPN
ijassa-1351	89	2	3.944700	3.944700	NUM
ijassa-1351	89	3	%	%	NOUN
ijassa-1351	89	4	,	,	PUNCT
ijassa-1351	89	5	minape	minape	NOUN
ijassa-1351	89	6	≈	≈	PROPN
ijassa-1351	89	7	0.000628	0.000628	NUM
ijassa-1351	89	8	%	%	NOUN
ijassa-1351	89	9	,	,	PUNCT
ijassa-1351	89	10	mape	mape	NOUN
ijassa-1351	89	11	≈	≈	PROPN
ijassa-1351	89	12	1.322934	1.322934	NUM
ijassa-1351	89	13	%	%	NOUN
ijassa-1351	89	14	.	.	PUNCT
ijassa-1351	90	1	thus	thus	ADV
ijassa-1351	90	2	,	,	PUNCT
ijassa-1351	90	3	our	our	PRON
ijassa-1351	90	4	correction	correction	NOUN
ijassa-1351	90	5	improves	improve	VERB
ijassa-1351	90	6	maxape	maxape	NOUN
ijassa-1351	90	7	by	by	ADP
ijassa-1351	90	8	a	a	DET
ijassa-1351	90	9	factor	factor	NOUN
ijassa-1351	90	10	of	of	ADP
ijassa-1351	90	11	11.5	11.5	NUM
ijassa-1351	90	12	and	and	CCONJ
ijassa-1351	90	13	mape	mape	NOUN
ijassa-1351	90	14	by	by	ADP
ijassa-1351	90	15	a	a	DET
ijassa-1351	90	16	factor	factor	NOUN
ijassa-1351	90	17	of	of	ADP
ijassa-1351	90	18	9.3	9.3	NUM
ijassa-1351	90	19	.	.	PUNCT
ijassa-1351	91	1	the	the	DET
ijassa-1351	91	2	results	result	NOUN
ijassa-1351	91	3	of	of	ADP
ijassa-1351	91	4	the	the	DET
ijassa-1351	91	5	approximation	approximation	NOUN
ijassa-1351	91	6	of	of	ADP
ijassa-1351	91	7	the	the	DET
ijassa-1351	91	8	average	average	ADJ
ijassa-1351	91	9	response	response	NOUN
ijassa-1351	91	10	time	time	NOUN
ijassa-1351	91	11	using	use	VERB
ijassa-1351	91	12	the	the	DET
ijassa-1351	91	13	(	(	PUNCT
ijassa-1351	91	14	2.5	2.5	NUM
ijassa-1351	91	15	)	)	PUNCT
ijassa-1351	91	16	formula	formula	NOUN
ijassa-1351	91	17	in	in	ADP
ijassa-1351	91	18	comparison	comparison	NOUN
ijassa-1351	91	19	with	with	ADP
ijassa-1351	91	20	the	the	DET
ijassa-1351	91	21	simulation	simulation	NOUN
ijassa-1351	91	22	results	result	NOUN
ijassa-1351	91	23	are	be	AUX
ijassa-1351	91	24	shown	show	VERB
ijassa-1351	91	25	in	in	ADP
ijassa-1351	91	26	the	the	DET
ijassa-1351	91	27	figure	figure	NOUN
ijassa-1351	91	28	.	.	PUNCT
ijassa-1351	92	1	0	0	NUM
ijassa-1351	93	1	5	5	NUM
ijassa-1351	93	2	10	10	NUM
ijassa-1351	93	3	15	15	NUM
ijassa-1351	93	4	20	20	NUM
ijassa-1351	93	5	25	25	NUM
ijassa-1351	93	6	0	0	NUM
ijassa-1351	93	7	5	5	NUM
ijassa-1351	93	8	10	10	NUM
ijassa-1351	93	9	15	15	NUM
ijassa-1351	93	10	20	20	NUM
ijassa-1351	93	11	25	25	NUM
ijassa-1351	93	12	f	f	NOUN
ijassa-1351	93	13	o	o	X
ijassa-1351	93	14	rm	rm	NOUN
ijassa-1351	93	15	u	u	PROPN
ijassa-1351	93	16	la	la	X
ijassa-1351	93	17	(	(	PUNCT
ijassa-1351	93	18	5	5	NUM
ijassa-1351	93	19	)	)	PUNCT
ijassa-1351	93	20	simulation	simulation	NOUN
ijassa-1351	93	21	fig	fig	NOUN
ijassa-1351	93	22	.	.	PUNCT
ijassa-1351	94	1	2.3	2.3	NUM
ijassa-1351	94	2	.	.	PUNCT
ijassa-1351	95	1	average	average	ADJ
ijassa-1351	95	2	response	response	NOUN
ijassa-1351	95	3	time	time	NOUN
ijassa-1351	95	4	.	.	PUNCT
ijassa-1351	96	1	the	the	DET
ijassa-1351	96	2	efficiency	efficiency	NOUN
ijassa-1351	96	3	of	of	ADP
ijassa-1351	96	4	the	the	DET
ijassa-1351	96	5	expression	expression	NOUN
ijassa-1351	96	6	(	(	PUNCT
ijassa-1351	96	7	2.5	2.5	NUM
ijassa-1351	96	8	)	)	PUNCT
ijassa-1351	96	9	is	be	AUX
ijassa-1351	96	10	not	not	PART
ijassa-1351	96	11	limited	limit	VERB
ijassa-1351	96	12	to	to	ADP
ijassa-1351	96	13	the	the	DET
ijassa-1351	96	14	maximum	maximum	ADJ
ijassa-1351	96	15	value	value	NOUN
ijassa-1351	96	16	of	of	ADP
ijassa-1351	96	17	k	k	PROPN
ijassa-1351	96	18	=	=	NOUN
ijassa-1351	96	19	20	20	NUM
ijassa-1351	96	20	.	.	PUNCT
ijassa-1351	97	1	this	this	DET
ijassa-1351	97	2	formula	formula	NOUN
ijassa-1351	97	3	is	be	AUX
ijassa-1351	97	4	expected	expect	VERB
ijassa-1351	97	5	to	to	PART
ijassa-1351	97	6	be	be	AUX
ijassa-1351	97	7	good	good	ADJ
ijassa-1351	97	8	for	for	ADP
ijassa-1351	97	9	a	a	DET
ijassa-1351	97	10	larger	large	ADJ
ijassa-1351	97	11	number	number	NOUN
ijassa-1351	97	12	of	of	ADP
ijassa-1351	97	13	subsystems	subsystem	NOUN
ijassa-1351	97	14	due	due	ADP
ijassa-1351	97	15	to	to	ADP
ijassa-1351	97	16	the	the	DET
ijassa-1351	97	17	built	build	VERB
ijassa-1351	97	18	-	-	PUNCT
ijassa-1351	97	19	in	in	ADP
ijassa-1351	97	20	logic	logic	NOUN
ijassa-1351	97	21	of	of	ADP
ijassa-1351	97	22	the	the	DET
ijassa-1351	97	23	proposed	propose	VERB
ijassa-1351	97	24	approach	approach	NOUN
ijassa-1351	97	25	to	to	ADP
ijassa-1351	97	26	approximating	approximate	VERB
ijassa-1351	97	27	the	the	DET
ijassa-1351	97	28	average	average	ADJ
ijassa-1351	97	29	response	response	NOUN
ijassa-1351	97	30	time	time	NOUN
ijassa-1351	97	31	.	.	PUNCT
ijassa-1351	98	1	in	in	ADP
ijassa-1351	98	2	particular	particular	ADJ
ijassa-1351	98	3	,	,	PUNCT
ijassa-1351	98	4	for	for	ADP
ijassa-1351	98	5	k	k	PROPN
ijassa-1351	98	6	=	=	SYM
ijassa-1351	98	7	100	100	NUM
ijassa-1351	98	8	and	and	CCONJ
ijassa-1351	98	9	values	value	NOUN
ijassa-1351	98	10	ρ	ρ	PROPN
ijassa-1351	98	11	∈	∈	PROPN
ijassa-1351	99	1	[	[	X
ijassa-1351	99	2	0.1	0.1	NUM
ijassa-1351	99	3	,	,	PUNCT
ijassa-1351	99	4	0.9	0.9	NUM
ijassa-1351	99	5	]	]	PUNCT
ijassa-1351	99	6	with	with	ADP
ijassa-1351	99	7	a	a	DET
ijassa-1351	99	8	step	step	NOUN
ijassa-1351	99	9	of	of	ADP
ijassa-1351	99	10	0.05	0.05	NUM
ijassa-1351	99	11	we	we	PRON
ijassa-1351	99	12	have	have	VERB
ijassa-1351	99	13	the	the	DET
ijassa-1351	99	14	following	follow	VERB
ijassa-1351	99	15	approximation	approximation	NOUN
ijassa-1351	99	16	errors	error	NOUN
ijassa-1351	99	17	maxape	maxape	NOUN
ijassa-1351	100	1	≈	≈	PROPN
ijassa-1351	100	2	2.666589	2.666589	NUM
ijassa-1351	100	3	%	%	NOUN
ijassa-1351	100	4	,	,	PUNCT
ijassa-1351	100	5	minape	minape	NOUN
ijassa-1351	100	6	≈	≈	PROPN
ijassa-1351	100	7	0.024029	0.024029	NUM
ijassa-1351	100	8	%	%	NOUN
ijassa-1351	100	9	,	,	PUNCT
ijassa-1351	100	10	mape	mape	NOUN
ijassa-1351	100	11	≈	≈	PROPN
ijassa-1351	100	12	0.642155	0.642155	NUM
ijassa-1351	100	13	%	%	NOUN
ijassa-1351	100	14	.	.	PUNCT
ijassa-1351	101	1	this	this	PRON
ijassa-1351	101	2	is	be	AUX
ijassa-1351	101	3	better	well	ADJ
ijassa-1351	101	4	than	than	ADP
ijassa-1351	101	5	the	the	DET
ijassa-1351	101	6	nelson	nelson	PROPN
ijassa-1351	101	7	-	-	PUNCT
ijassa-1351	101	8	tantawi	tantawi	PROPN
ijassa-1351	101	9	formula	formula	NOUN
ijassa-1351	101	10	,	,	PUNCT
ijassa-1351	101	11	which	which	PRON
ijassa-1351	101	12	gives	give	VERB
ijassa-1351	101	13	maxape	maxape	NOUN
ijassa-1351	101	14	≈	≈	PROPN
ijassa-1351	101	15	2.741596	2.741596	NUM
ijassa-1351	101	16	%	%	NOUN
ijassa-1351	101	17	,	,	PUNCT
ijassa-1351	101	18	minape	minape	NOUN
ijassa-1351	101	19	≈	≈	PROPN
ijassa-1351	101	20	0.100878	0.100878	NUM
ijassa-1351	101	21	%	%	NOUN
ijassa-1351	101	22	,	,	PUNCT
ijassa-1351	101	23	mape	mape	NOUN
ijassa-1351	101	24	≈	≈	PROPN
ijassa-1351	101	25	1.084311	1.084311	NUM
ijassa-1351	101	26	%	%	NOUN
ijassa-1351	101	27	.	.	PUNCT
ijassa-1351	102	1	copyright	copyright	NOUN
ijassa-1351	102	2	©	©	PROPN
ijassa-1351	102	3	2023	2023	NUM
ijassa-1351	102	4	assa	assa	NOUN
ijassa-1351	102	5	.	.	PUNCT
ijassa-1351	103	1	adv	adv	PROPN
ijassa-1351	103	2	syst	syst	PROPN
ijassa-1351	103	3	sci	sci	PROPN
ijassa-1351	103	4	appl	appl	PROPN
ijassa-1351	103	5	(	(	PUNCT
ijassa-1351	103	6	2023	2023	NUM
ijassa-1351	103	7	)	)	PUNCT
ijassa-1351	103	8	104	104	NUM
ijassa-1351	103	9	a.v	a.v	PROPN
ijassa-1351	103	10	.	.	PROPN
ijassa-1351	103	11	gorbunova	gorbunova	PROPN
ijassa-1351	103	12	,	,	PUNCT
ijassa-1351	103	13	a.v	a.v	PROPN
ijassa-1351	103	14	.	.	PROPN
ijassa-1351	103	15	lebedev	lebedev	PROPN
ijassa-1351	103	16	for	for	ADP
ijassa-1351	103	17	the	the	DET
ijassa-1351	103	18	value	value	NOUN
ijassa-1351	103	19	of	of	ADP
ijassa-1351	103	20	k	k	PROPN
ijassa-1351	103	21	=	=	SYM
ijassa-1351	103	22	1000	1000	NUM
ijassa-1351	103	23	,	,	PUNCT
ijassa-1351	103	24	due	due	ADP
ijassa-1351	103	25	to	to	ADP
ijassa-1351	103	26	the	the	DET
ijassa-1351	103	27	saving	saving	NOUN
ijassa-1351	103	28	of	of	ADP
ijassa-1351	103	29	computational	computational	ADJ
ijassa-1351	103	30	and	and	CCONJ
ijassa-1351	103	31	time	time	NOUN
ijassa-1351	103	32	resources	resource	NOUN
ijassa-1351	103	33	of	of	ADP
ijassa-1351	103	34	simulation	simulation	NOUN
ijassa-1351	103	35	modeling	modeling	NOUN
ijassa-1351	103	36	,	,	PUNCT
ijassa-1351	103	37	we	we	PRON
ijassa-1351	103	38	limited	limit	VERB
ijassa-1351	103	39	ourselves	ourselves	PRON
ijassa-1351	103	40	to	to	ADP
ijassa-1351	103	41	checking	check	VERB
ijassa-1351	103	42	the	the	DET
ijassa-1351	103	43	quality	quality	NOUN
ijassa-1351	103	44	of	of	ADP
ijassa-1351	103	45	the	the	DET
ijassa-1351	103	46	approximation	approximation	NOUN
ijassa-1351	103	47	under	under	ADP
ijassa-1351	103	48	low	low	ADJ
ijassa-1351	103	49	load	load	NOUN
ijassa-1351	103	50	ρ	ρ	NOUN
ijassa-1351	103	51	=	=	PUNCT
ijassa-1351	103	52	{	{	PUNCT
ijassa-1351	103	53	0.1	0.1	NUM
ijassa-1351	103	54	,	,	PUNCT
ijassa-1351	103	55	0.2	0.2	NUM
ijassa-1351	103	56	,	,	PUNCT
ijassa-1351	103	57	0.3	0.3	NUM
ijassa-1351	103	58	,	,	PUNCT
ijassa-1351	103	59	0.4	0.4	NUM
ijassa-1351	103	60	,	,	PUNCT
ijassa-1351	103	61	0.5	0.5	NUM
ijassa-1351	103	62	}	}	PUNCT
ijassa-1351	103	63	,	,	PUNCT
ijassa-1351	103	64	since	since	SCONJ
ijassa-1351	103	65	with	with	ADP
ijassa-1351	103	66	increasing	increase	VERB
ijassa-1351	103	67	values	value	NOUN
ijassa-1351	103	68	it	it	PRON
ijassa-1351	103	69	does	do	VERB
ijassa-1351	103	70	not	not	PART
ijassa-1351	103	71	only	only	ADV
ijassa-1351	103	72	k	k	ADJ
ijassa-1351	103	73	,	,	PUNCT
ijassa-1351	103	74	but	but	CCONJ
ijassa-1351	103	75	also	also	ADV
ijassa-1351	103	76	ρ	ρ	PROPN
ijassa-1351	103	77	,	,	PUNCT
ijassa-1351	103	78	it	it	PRON
ijassa-1351	103	79	is	be	AUX
ijassa-1351	103	80	necessary	necessary	ADJ
ijassa-1351	103	81	to	to	PART
ijassa-1351	103	82	significantly	significantly	ADV
ijassa-1351	103	83	increase	increase	VERB
ijassa-1351	103	84	the	the	DET
ijassa-1351	103	85	number	number	NOUN
ijassa-1351	103	86	of	of	ADP
ijassa-1351	103	87	tests	test	NOUN
ijassa-1351	103	88	(	(	PUNCT
ijassa-1351	103	89	realizations	realization	NOUN
ijassa-1351	103	90	of	of	ADP
ijassa-1351	103	91	r.v	r.v	PROPN
ijassa-1351	103	92	.	.	PROPN
ijassa-1351	103	93	)	)	PUNCT
ijassa-1351	104	1	within	within	ADP
ijassa-1351	104	2	one	one	NUM
ijassa-1351	104	3	run	run	NOUN
ijassa-1351	104	4	of	of	ADP
ijassa-1351	104	5	the	the	DET
ijassa-1351	104	6	simulation	simulation	NOUN
ijassa-1351	104	7	model	model	NOUN
ijassa-1351	104	8	.	.	PUNCT
ijassa-1351	105	1	as	as	ADP
ijassa-1351	105	2	a	a	DET
ijassa-1351	105	3	result	result	NOUN
ijassa-1351	105	4	of	of	ADP
ijassa-1351	105	5	the	the	DET
ijassa-1351	105	6	approximation	approximation	NOUN
ijassa-1351	105	7	error	error	NOUN
ijassa-1351	105	8	,	,	PUNCT
ijassa-1351	105	9	the	the	DET
ijassa-1351	105	10	formulas	formula	NOUN
ijassa-1351	105	11	(	(	PUNCT
ijassa-1351	105	12	2.5	2.5	NUM
ijassa-1351	105	13	)	)	PUNCT
ijassa-1351	105	14	amounted	amount	VERB
ijassa-1351	105	15	to	to	ADP
ijassa-1351	105	16	maxape	maxape	NOUN
ijassa-1351	105	17	≈	≈	PROPN
ijassa-1351	105	18	1.485234	1.485234	NUM
ijassa-1351	105	19	%	%	NOUN
ijassa-1351	105	20	,	,	PUNCT
ijassa-1351	105	21	minape	minape	NOUN
ijassa-1351	105	22	≈	≈	PROPN
ijassa-1351	105	23	0.010079	0.010079	NUM
ijassa-1351	105	24	%	%	NOUN
ijassa-1351	105	25	,	,	PUNCT
ijassa-1351	105	26	mape	mape	NOUN
ijassa-1351	105	27	≈	≈	PROPN
ijassa-1351	105	28	0.491061	0.491061	NUM
ijassa-1351	105	29	%	%	NOUN
ijassa-1351	105	30	,	,	PUNCT
ijassa-1351	105	31	and	and	CCONJ
ijassa-1351	105	32	by	by	ADP
ijassa-1351	105	33	the	the	DET
ijassa-1351	105	34	nelson	nelson	PROPN
ijassa-1351	105	35	-	-	PUNCT
ijassa-1351	105	36	tantawi	tantawi	PROPN
ijassa-1351	105	37	formula	formula	NOUN
ijassa-1351	105	38	,	,	PUNCT
ijassa-1351	105	39	we	we	PRON
ijassa-1351	105	40	have	have	VERB
ijassa-1351	105	41	maxape	maxape	NOUN
ijassa-1351	105	42	≈	≈	PROPN
ijassa-1351	105	43	3.389362	3.389362	NUM
ijassa-1351	105	44	%	%	NOUN
ijassa-1351	105	45	,	,	PUNCT
ijassa-1351	105	46	minape	minape	NOUN
ijassa-1351	106	1	≈	≈	PROPN
ijassa-1351	106	2	1.090899	1.090899	NUM
ijassa-1351	106	3	%	%	NOUN
ijassa-1351	106	4	,	,	PUNCT
ijassa-1351	106	5	mape	mape	NOUN
ijassa-1351	106	6	≈	≈	PROPN
ijassa-1351	106	7	2.530636	2.530636	NUM
ijassa-1351	106	8	%	%	NOUN
ijassa-1351	106	9	.	.	PUNCT
ijassa-1351	107	1	note	note	VERB
ijassa-1351	107	2	that	that	SCONJ
ijassa-1351	107	3	if	if	SCONJ
ijassa-1351	107	4	we	we	PRON
ijassa-1351	107	5	add	add	VERB
ijassa-1351	107	6	one	one	NUM
ijassa-1351	107	7	more	more	ADJ
ijassa-1351	107	8	term	term	NOUN
ijassa-1351	107	9	to	to	ADP
ijassa-1351	107	10	the	the	DET
ijassa-1351	107	11	(	(	PUNCT
ijassa-1351	107	12	2.4	2.4	NUM
ijassa-1351	107	13	)	)	PUNCT
ijassa-1351	107	14	formula	formula	NOUN
ijassa-1351	107	15	,	,	PUNCT
ijassa-1351	107	16	i.e.	i.e.	X
ijassa-1351	107	17	µ̃	µ̃	PROPN
ijassa-1351	107	18	≈	≈	PROPN
ijassa-1351	107	19	c1	c1	PROPN
ijassa-1351	107	20	−	−	PROPN
ijassa-1351	107	21	c2	c2	PROPN
ijassa-1351	107	22	(	(	PUNCT
ijassa-1351	107	23	hk	hk	PROPN
ijassa-1351	107	24	h2	h2	PROPN
ijassa-1351	107	25	−	−	PROPN
ijassa-1351	107	26	1	1	NUM
ijassa-1351	107	27	)	)	PUNCT
ijassa-1351	108	1	+	+	CCONJ
ijassa-1351	108	2	c3ρ+	c3ρ+	PRON
ijassa-1351	108	3	c4ρ	c4ρ	PUNCT
ijassa-1351	108	4	(	(	PUNCT
ijassa-1351	108	5	hk	hk	PROPN
ijassa-1351	108	6	h2	h2	PROPN
ijassa-1351	108	7	−	−	PROPN
ijassa-1351	108	8	1	1	NUM
ijassa-1351	108	9	)	)	PUNCT
ijassa-1351	108	10	,	,	PUNCT
ijassa-1351	108	11	(	(	PUNCT
ijassa-1351	108	12	2.8	2.8	NUM
ijassa-1351	108	13	)	)	PUNCT
ijassa-1351	108	14	and	and	CCONJ
ijassa-1351	108	15	recalculate	recalculate	VERB
ijassa-1351	108	16	the	the	DET
ijassa-1351	108	17	optimal	optimal	ADJ
ijassa-1351	108	18	coefficients	coefficient	NOUN
ijassa-1351	108	19	after	after	ADP
ijassa-1351	108	20	substituting	substitute	VERB
ijassa-1351	108	21	(	(	PUNCT
ijassa-1351	108	22	2.8	2.8	NUM
ijassa-1351	108	23	)	)	PUNCT
ijassa-1351	108	24	into	into	ADP
ijassa-1351	108	25	(	(	PUNCT
ijassa-1351	108	26	2.2	2.2	NUM
ijassa-1351	108	27	)	)	PUNCT
ijassa-1351	108	28	,	,	PUNCT
ijassa-1351	108	29	which	which	PRON
ijassa-1351	108	30	turn	turn	VERB
ijassa-1351	108	31	out	out	ADP
ijassa-1351	108	32	to	to	PART
ijassa-1351	108	33	be	be	AUX
ijassa-1351	108	34	equal	equal	ADJ
ijassa-1351	108	35	to	to	ADP
ijassa-1351	108	36	c1	c1	PROPN
ijassa-1351	108	37	≈	≈	PROPN
ijassa-1351	108	38	0.150293	0.150293	NUM
ijassa-1351	108	39	,	,	PUNCT
ijassa-1351	108	40	c2	c2	PROPN
ijassa-1351	108	41	≈	≈	PROPN
ijassa-1351	108	42	0.152088	0.152088	NUM
ijassa-1351	108	43	,	,	PUNCT
ijassa-1351	108	44	c3	c3	PROPN
ijassa-1351	108	45	≈	≈	PROPN
ijassa-1351	108	46	0.012684	0.012684	PROPN
ijassa-1351	108	47	,	,	PUNCT
ijassa-1351	108	48	c4	c4	NOUN
ijassa-1351	108	49	≈	≈	PROPN
ijassa-1351	108	50	0.105121	0.105121	NUM
ijassa-1351	108	51	,	,	PUNCT
ijassa-1351	108	52	then	then	ADV
ijassa-1351	108	53	we	we	PRON
ijassa-1351	108	54	obtain	obtain	VERB
ijassa-1351	108	55	a	a	DET
ijassa-1351	108	56	further	further	ADJ
ijassa-1351	108	57	significant	significant	ADJ
ijassa-1351	108	58	improvement	improvement	NOUN
ijassa-1351	108	59	in	in	ADP
ijassa-1351	108	60	the	the	DET
ijassa-1351	108	61	estimates	estimate	NOUN
ijassa-1351	108	62	for	for	ADP
ijassa-1351	108	63	k	k	PROPN
ijassa-1351	108	64	from	from	ADP
ijassa-1351	108	65	3	3	NUM
ijassa-1351	108	66	to	to	ADP
ijassa-1351	108	67	20	20	NUM
ijassa-1351	108	68	,	,	PUNCT
ijassa-1351	108	69	namely	namely	ADV
ijassa-1351	108	70	,	,	PUNCT
ijassa-1351	108	71	maxape	maxape	NOUN
ijassa-1351	108	72	≈	≈	PROPN
ijassa-1351	108	73	0.252453	0.252453	NUM
ijassa-1351	108	74	%	%	NOUN
ijassa-1351	108	75	,	,	PUNCT
ijassa-1351	108	76	minape	minape	NOUN
ijassa-1351	108	77	≈	≈	PROPN
ijassa-1351	108	78	0.000495	0.000495	NUM
ijassa-1351	108	79	%	%	NOUN
ijassa-1351	108	80	,	,	PUNCT
ijassa-1351	108	81	mape	mape	NOUN
ijassa-1351	108	82	≈	≈	PROPN
ijassa-1351	108	83	0.105624	0.105624	NUM
ijassa-1351	108	84	%	%	NOUN
ijassa-1351	108	85	.	.	PUNCT
ijassa-1351	109	1	for	for	ADP
ijassa-1351	109	2	k	k	PROPN
ijassa-1351	109	3	=	=	SYM
ijassa-1351	109	4	100	100	NUM
ijassa-1351	109	5	we	we	PRON
ijassa-1351	109	6	get	get	VERB
ijassa-1351	109	7	maxape	maxape	NOUN
ijassa-1351	109	8	≈	≈	PROPN
ijassa-1351	109	9	1.548824	1.548824	NUM
ijassa-1351	109	10	%	%	NOUN
ijassa-1351	109	11	,	,	PUNCT
ijassa-1351	109	12	minape	minape	NOUN
ijassa-1351	109	13	≈	≈	PROPN
ijassa-1351	109	14	0.467368	0.467368	NUM
ijassa-1351	109	15	%	%	NOUN
ijassa-1351	109	16	,	,	PUNCT
ijassa-1351	109	17	mape	mape	NOUN
ijassa-1351	110	1	≈	≈	PROPN
ijassa-1351	110	2	1.185327	1.185327	NUM
ijassa-1351	110	3	%	%	NOUN
ijassa-1351	110	4	.	.	PUNCT
ijassa-1351	111	1	an	an	DET
ijassa-1351	111	2	increase	increase	NOUN
ijassa-1351	111	3	in	in	ADP
ijassa-1351	111	4	mape	mape	NOUN
ijassa-1351	111	5	may	may	AUX
ijassa-1351	111	6	indicate	indicate	VERB
ijassa-1351	111	7	the	the	DET
ijassa-1351	111	8	influence	influence	NOUN
ijassa-1351	111	9	of	of	ADP
ijassa-1351	111	10	a	a	DET
ijassa-1351	111	11	small	small	ADJ
ijassa-1351	111	12	systematic	systematic	ADJ
ijassa-1351	111	13	error	error	NOUN
ijassa-1351	111	14	,	,	PUNCT
ijassa-1351	111	15	which	which	PRON
ijassa-1351	111	16	becomes	become	VERB
ijassa-1351	111	17	noticeable	noticeable	ADJ
ijassa-1351	111	18	at	at	ADP
ijassa-1351	111	19	large	large	ADJ
ijassa-1351	111	20	k.	k.	NOUN
ijassa-1351	111	21	it	it	PRON
ijassa-1351	111	22	is	be	AUX
ijassa-1351	111	23	possible	possible	ADJ
ijassa-1351	111	24	that	that	SCONJ
ijassa-1351	111	25	adjusting	adjust	VERB
ijassa-1351	111	26	the	the	DET
ijassa-1351	111	27	coefficients	coefficient	NOUN
ijassa-1351	111	28	(	(	PUNCT
ijassa-1351	111	29	while	while	SCONJ
ijassa-1351	111	30	keeping	keep	VERB
ijassa-1351	111	31	the	the	DET
ijassa-1351	111	32	general	general	ADJ
ijassa-1351	111	33	formulas	formula	NOUN
ijassa-1351	111	34	)	)	PUNCT
ijassa-1351	111	35	considering	consider	VERB
ijassa-1351	111	36	the	the	DET
ijassa-1351	111	37	simulation	simulation	NOUN
ijassa-1351	111	38	for	for	ADP
ijassa-1351	111	39	k	k	PROPN
ijassa-1351	111	40	>	>	X
ijassa-1351	111	41	20	20	NUM
ijassa-1351	111	42	can	can	AUX
ijassa-1351	111	43	further	far	ADV
ijassa-1351	111	44	improve	improve	VERB
ijassa-1351	111	45	the	the	DET
ijassa-1351	111	46	approximation	approximation	NOUN
ijassa-1351	111	47	.	.	PUNCT
ijassa-1351	112	1	2.2	2.2	NUM
ijassa-1351	112	2	.	.	PUNCT
ijassa-1351	113	1	response	response	NOUN
ijassa-1351	113	2	time	time	NOUN
ijassa-1351	113	3	standard	standard	ADJ
ijassa-1351	113	4	deviation	deviation	NOUN
ijassa-1351	113	5	in	in	ADP
ijassa-1351	113	6	[	[	X
ijassa-1351	113	7	20	20	NUM
ijassa-1351	113	8	]	]	PUNCT
ijassa-1351	113	9	a	a	DET
ijassa-1351	113	10	formula	formula	NOUN
ijassa-1351	113	11	was	be	AUX
ijassa-1351	113	12	proposed	propose	VERB
ijassa-1351	113	13	to	to	PART
ijassa-1351	113	14	estimate	estimate	VERB
ijassa-1351	113	15	the	the	DET
ijassa-1351	113	16	variance	variance	NOUN
ijassa-1351	113	17	of	of	ADP
ijassa-1351	113	18	the	the	DET
ijassa-1351	113	19	fork	fork	NOUN
ijassa-1351	113	20	-	-	PUNCT
ijassa-1351	113	21	join	join	VERB
ijassa-1351	113	22	qs	qs	NOUN
ijassa-1351	113	23	response	response	NOUN
ijassa-1351	113	24	time	time	NOUN
ijassa-1351	113	25	with	with	ADP
ijassa-1351	113	26	k	k	PROPN
ijassa-1351	113	27	subsystems	subsystem	NOUN
ijassa-1351	113	28	mλ|mµ|1	mλ|mµ|1	VERB
ijassa-1351	113	29	in	in	ADP
ijassa-1351	113	30	the	the	DET
ijassa-1351	113	31	general	general	ADJ
ijassa-1351	113	32	case	case	NOUN
ijassa-1351	113	33	of	of	ADP
ijassa-1351	113	34	different	different	ADJ
ijassa-1351	113	35	service	service	NOUN
ijassa-1351	113	36	rates	rate	NOUN
ijassa-1351	113	37	µi	µi	ADP
ijassa-1351	113	38	,	,	PUNCT
ijassa-1351	113	39	1	1	NUM
ijassa-1351	113	40	≤	≤	NUM
ijassa-1351	113	41	i	i	PRON
ijassa-1351	113	42	≤	≤	PROPN
ijassa-1351	113	43	k.	k.	INTJ
ijassa-1351	113	44	in	in	ADP
ijassa-1351	113	45	the	the	DET
ijassa-1351	113	46	case	case	NOUN
ijassa-1351	113	47	of	of	ADP
ijassa-1351	113	48	a	a	DET
ijassa-1351	113	49	single	single	ADJ
ijassa-1351	113	50	service	service	NOUN
ijassa-1351	113	51	rate	rate	NOUN
ijassa-1351	113	52	µ	µ	PROPN
ijassa-1351	113	53	,	,	PUNCT
ijassa-1351	113	54	it	it	PRON
ijassa-1351	113	55	takes	take	VERB
ijassa-1351	113	56	the	the	DET
ijassa-1351	113	57	form	form	NOUN
ijassa-1351	113	58	var[rk	var[rk	NOUN
ijassa-1351	113	59	]	]	PUNCT
ijassa-1351	114	1	≈	≈	PROPN
ijassa-1351	114	2	2	2	NUM
ijassa-1351	114	3	(	(	PUNCT
ijassa-1351	114	4	µ−	µ−	PROPN
ijassa-1351	114	5	λ)2	λ)2	NOUN
ijassa-1351	114	6	k∑	k∑	VERB
ijassa-1351	114	7	i=1	i=1	PROPN
ijassa-1351	115	1	(	(	PUNCT
ijassa-1351	115	2	k	k	X
ijassa-1351	115	3	i	i	PROPN
ijassa-1351	115	4	)	)	PUNCT
ijassa-1351	116	1	(	(	PUNCT
ijassa-1351	116	2	−1)i−1	−1)i−1	PROPN
ijassa-1351	116	3	1	1	NUM
ijassa-1351	116	4	i2	i2	PROPN
ijassa-1351	116	5	−	−	PROPN
ijassa-1351	117	1	(	(	PUNCT
ijassa-1351	117	2	1	1	NUM
ijassa-1351	117	3	µ−	µ−	PROPN
ijassa-1351	117	4	λ	λ	NOUN
ijassa-1351	117	5	k∑	k∑	VERB
ijassa-1351	117	6	i=1	i=1	PROPN
ijassa-1351	117	7	1	1	NUM
ijassa-1351	117	8	i	i	NOUN
ijassa-1351	117	9	)	)	PUNCT
ijassa-1351	117	10	2	2	NUM
ijassa-1351	117	11	,	,	PUNCT
ijassa-1351	117	12	(	(	PUNCT
ijassa-1351	117	13	2.9	2.9	NUM
ijassa-1351	117	14	)	)	PUNCT
ijassa-1351	117	15	which	which	PRON
ijassa-1351	117	16	in	in	ADP
ijassa-1351	117	17	turn	turn	NOUN
ijassa-1351	117	18	simplifies	simplifie	NOUN
ijassa-1351	117	19	to	to	PART
ijassa-1351	117	20	var[rk	var[rk	VERB
ijassa-1351	117	21	]	]	PUNCT
ijassa-1351	118	1	≈	≈	PROPN
ijassa-1351	118	2	qk	qk	NOUN
ijassa-1351	118	3	(	(	PUNCT
ijassa-1351	118	4	µ−	µ−	PROPN
ijassa-1351	118	5	λ)2	λ)2	NOUN
ijassa-1351	118	6	,	,	PUNCT
ijassa-1351	118	7	where	where	SCONJ
ijassa-1351	118	8	qk	qk	NOUN
ijassa-1351	118	9	=	=	SYM
ijassa-1351	118	10	k∑	k∑	PROPN
ijassa-1351	118	11	i=1	i=1	PROPN
ijassa-1351	118	12	1	1	NUM
ijassa-1351	118	13	i2	i2	NOUN
ijassa-1351	118	14	.	.	PUNCT
ijassa-1351	119	1	we	we	PRON
ijassa-1351	119	2	note	note	VERB
ijassa-1351	119	3	that	that	SCONJ
ijassa-1351	119	4	the	the	DET
ijassa-1351	119	5	above	above	ADJ
ijassa-1351	119	6	formula	formula	NOUN
ijassa-1351	119	7	,	,	PUNCT
ijassa-1351	119	8	by	by	ADP
ijassa-1351	119	9	its	its	PRON
ijassa-1351	119	10	construction	construction	NOUN
ijassa-1351	119	11	,	,	PUNCT
ijassa-1351	119	12	proceeds	proceed	VERB
ijassa-1351	119	13	from	from	ADP
ijassa-1351	119	14	the	the	DET
ijassa-1351	119	15	independence	independence	NOUN
ijassa-1351	119	16	of	of	ADP
ijassa-1351	119	17	the	the	DET
ijassa-1351	119	18	sojourn	sojourn	NOUN
ijassa-1351	119	19	times	time	NOUN
ijassa-1351	119	20	in	in	ADP
ijassa-1351	119	21	subsystems	subsystem	NOUN
ijassa-1351	119	22	,	,	PUNCT
ijassa-1351	119	23	i.	i.	PROPN
ijassa-1351	119	24	e.	e.	PROPN
ijassa-1351	119	25	,	,	PUNCT
ijassa-1351	119	26	we	we	PRON
ijassa-1351	119	27	are	be	AUX
ijassa-1351	119	28	talking	talk	VERB
ijassa-1351	119	29	about	about	ADP
ijassa-1351	119	30	the	the	DET
ijassa-1351	119	31	dispersion	dispersion	NOUN
ijassa-1351	119	32	of	of	ADP
ijassa-1351	119	33	the	the	DET
ijassa-1351	119	34	maximum	maximum	NOUN
ijassa-1351	119	35	of	of	ADP
ijassa-1351	119	36	independent	independent	ADJ
ijassa-1351	119	37	exponential	exponential	ADJ
ijassa-1351	119	38	random	random	ADJ
ijassa-1351	119	39	variables	variable	NOUN
ijassa-1351	119	40	.	.	PUNCT
ijassa-1351	120	1	copyright	copyright	NOUN
ijassa-1351	120	2	©	©	PROPN
ijassa-1351	120	3	2023	2023	NUM
ijassa-1351	120	4	assa	assa	NOUN
ijassa-1351	120	5	.	.	PUNCT
ijassa-1351	121	1	adv	adv	PROPN
ijassa-1351	121	2	syst	syst	PROPN
ijassa-1351	121	3	sci	sci	PROPN
ijassa-1351	121	4	appl	appl	PROPN
ijassa-1351	121	5	(	(	PUNCT
ijassa-1351	121	6	2023	2023	NUM
ijassa-1351	121	7	)	)	PUNCT
ijassa-1351	121	8	assa	assa	NOUN
ijassa-1351	121	9	latex	latex	NOUN
ijassa-1351	121	10	template	template	NOUN
ijassa-1351	121	11	105	105	NUM
ijassa-1351	121	12	suppose	suppose	VERB
ijassa-1351	121	13	that	that	SCONJ
ijassa-1351	121	14	our	our	PRON
ijassa-1351	121	15	estimate	estimate	NOUN
ijassa-1351	121	16	will	will	AUX
ijassa-1351	121	17	depend	depend	VERB
ijassa-1351	121	18	,	,	PUNCT
ijassa-1351	121	19	as	as	ADV
ijassa-1351	121	20	well	well	ADV
ijassa-1351	121	21	as	as	ADP
ijassa-1351	121	22	the	the	DET
ijassa-1351	121	23	(	(	PUNCT
ijassa-1351	121	24	2.9	2.9	NUM
ijassa-1351	121	25	)	)	PUNCT
ijassa-1351	121	26	expression	expression	NOUN
ijassa-1351	121	27	itself	itself	PRON
ijassa-1351	121	28	,	,	PUNCT
ijassa-1351	121	29	on	on	ADP
ijassa-1351	121	30	the	the	DET
ijassa-1351	121	31	variance	variance	NOUN
ijassa-1351	121	32	of	of	ADP
ijassa-1351	121	33	the	the	DET
ijassa-1351	121	34	average	average	ADJ
ijassa-1351	121	35	response	response	NOUN
ijassa-1351	121	36	time	time	NOUN
ijassa-1351	121	37	in	in	ADP
ijassa-1351	121	38	qs	qs	PROPN
ijassa-1351	121	39	m	m	NOUN
ijassa-1351	121	40	|m	|m	NOUN
ijassa-1351	121	41	|1	|1	PRON
ijassa-1351	121	42	,	,	PUNCT
ijassa-1351	121	43	i.e.	i.e.	X
ijassa-1351	121	44	on	on	ADP
ijassa-1351	121	45	1/(µ−	1/(µ−	NOUN
ijassa-1351	121	46	λ)2	λ)2	NOUN
ijassa-1351	121	47	,	,	PUNCT
ijassa-1351	121	48	and	and	CCONJ
ijassa-1351	121	49	on	on	ADP
ijassa-1351	121	50	the	the	DET
ijassa-1351	121	51	partial	partial	ADJ
ijassa-1351	121	52	sum	sum	NOUN
ijassa-1351	121	53	of	of	ADP
ijassa-1351	121	54	the	the	DET
ijassa-1351	121	55	inverse	inverse	ADJ
ijassa-1351	121	56	square	square	PROPN
ijassa-1351	121	57	series	series	NOUN
ijassa-1351	121	58	.	.	PUNCT
ijassa-1351	122	1	let	let	VERB
ijassa-1351	122	2	us	we	PRON
ijassa-1351	122	3	put	put	VERB
ijassa-1351	122	4	var[rk	var[rk	PROPN
ijassa-1351	122	5	]	]	PUNCT
ijassa-1351	123	1	≈	≈	PROPN
ijassa-1351	123	2	qk	qk	PUNCT
ijassa-1351	123	3	−	−	PROPN
ijassa-1351	123	4	1	1	NUM
ijassa-1351	123	5	(	(	PUNCT
ijassa-1351	123	6	µ−	µ−	PROPN
ijassa-1351	123	7	λ)2	λ)2	NOUN
ijassa-1351	123	8	·	·	PUNCT
ijassa-1351	124	1	σ̃	σ̃	NOUN
ijassa-1351	124	2	+	+	NUM
ijassa-1351	124	3	1	1	NUM
ijassa-1351	124	4	(	(	PUNCT
ijassa-1351	124	5	µ−	µ−	PROPN
ijassa-1351	124	6	λ)2	λ)2	NOUN
ijassa-1351	124	7	,	,	PUNCT
ijassa-1351	124	8	(	(	PUNCT
ijassa-1351	124	9	2.10	2.10	NUM
ijassa-1351	124	10	)	)	PUNCT
ijassa-1351	124	11	where	where	SCONJ
ijassa-1351	124	12	we	we	PRON
ijassa-1351	124	13	assume	assume	VERB
ijassa-1351	124	14	that	that	SCONJ
ijassa-1351	124	15	the	the	DET
ijassa-1351	124	16	estimate	estimate	NOUN
ijassa-1351	124	17	is	be	AUX
ijassa-1351	124	18	sharp	sharp	ADJ
ijassa-1351	124	19	for	for	ADP
ijassa-1351	124	20	k	k	PROPN
ijassa-1351	124	21	=	=	SYM
ijassa-1351	124	22	1	1	X
ijassa-1351	124	23	.	.	PUNCT
ijassa-1351	125	1	next	next	ADV
ijassa-1351	125	2	,	,	PUNCT
ijassa-1351	125	3	to	to	PART
ijassa-1351	125	4	specify	specify	VERB
ijassa-1351	125	5	the	the	DET
ijassa-1351	125	6	expression	expression	NOUN
ijassa-1351	125	7	for	for	ADP
ijassa-1351	125	8	σ̃	σ̃	PROPN
ijassa-1351	125	9	,	,	PUNCT
ijassa-1351	125	10	we	we	PRON
ijassa-1351	125	11	construct	construct	VERB
ijassa-1351	125	12	and	and	CCONJ
ijassa-1351	125	13	analyze	analyze	VERB
ijassa-1351	125	14	plots	plot	NOUN
ijassa-1351	125	15	of	of	ADP
ijassa-1351	125	16	the	the	DET
ijassa-1351	125	17	modified	modify	VERB
ijassa-1351	125	18	variance	variance	NOUN
ijassa-1351	125	19	versus	versus	ADP
ijassa-1351	125	20	ρ	ρ	PROPN
ijassa-1351	125	21	,	,	PUNCT
ijassa-1351	125	22	(	(	PUNCT
ijassa-1351	125	23	qk	qk	ADP
ijassa-1351	125	24	−	−	PROPN
ijassa-1351	125	25	1	1	NUM
ijassa-1351	125	26	)	)	PUNCT
ijassa-1351	125	27	,	,	PUNCT
ijassa-1351	125	28	and	and	CCONJ
ijassa-1351	125	29	(	(	PUNCT
ijassa-1351	125	30	hk	hk	NOUN
ijassa-1351	125	31	−	−	PROPN
ijassa-1351	125	32	1	1	NUM
ijassa-1351	125	33	)	)	PUNCT
ijassa-1351	125	34	.	.	PUNCT
ijassa-1351	126	1	under	under	ADP
ijassa-1351	126	2	the	the	DET
ijassa-1351	126	3	modified	modify	VERB
ijassa-1351	126	4	variance	variance	NOUN
ijassa-1351	126	5	expression	expression	NOUN
ijassa-1351	126	6	,	,	PUNCT
ijassa-1351	126	7	we	we	PRON
ijassa-1351	126	8	mean	mean	VERB
ijassa-1351	126	9	the	the	DET
ijassa-1351	126	10	following	following	NOUN
ijassa-1351	126	11	:	:	PUNCT
ijassa-1351	126	12	σ̃	σ̃	PROPN
ijassa-1351	126	13	=	=	SYM
ijassa-1351	126	14	var[rk	var[rk	NOUN
ijassa-1351	126	15	]	]	X
ijassa-1351	126	16	(	(	PUNCT
ijassa-1351	126	17	µ−	µ−	PROPN
ijassa-1351	126	18	λ)2	λ)2	NOUN
ijassa-1351	126	19	−	−	NOUN
ijassa-1351	126	20	1	1	NUM
ijassa-1351	126	21	qk	qk	NOUN
ijassa-1351	126	22	−	−	PROPN
ijassa-1351	126	23	1	1	NUM
ijassa-1351	126	24	,	,	PUNCT
ijassa-1351	126	25	(	(	PUNCT
ijassa-1351	126	26	2.11	2.11	NUM
ijassa-1351	126	27	)	)	PUNCT
ijassa-1351	126	28	where	where	SCONJ
ijassa-1351	126	29	the	the	DET
ijassa-1351	126	30	values	value	NOUN
ijassa-1351	126	31	of	of	ADP
ijassa-1351	126	32	var[rk	var[rk	NOUN
ijassa-1351	126	33	]	]	PUNCT
ijassa-1351	126	34	were	be	AUX
ijassa-1351	126	35	obtained	obtain	VERB
ijassa-1351	126	36	by	by	ADP
ijassa-1351	126	37	simulation	simulation	NOUN
ijassa-1351	126	38	.	.	PUNCT
ijassa-1351	127	1	1	1	NUM
ijassa-1351	127	2	1.1	1.1	NUM
ijassa-1351	127	3	1.2	1.2	NUM
ijassa-1351	127	4	1.3	1.3	NUM
ijassa-1351	127	5	1.4	1.4	NUM
ijassa-1351	127	6	1.5	1.5	NUM
ijassa-1351	127	7	1.6	1.6	NUM
ijassa-1351	127	8	1.7	1.7	NUM
ijassa-1351	127	9	1.8	1.8	NUM
ijassa-1351	127	10	1.9	1.9	NUM
ijassa-1351	127	11	2	2	NUM
ijassa-1351	127	12	0.35	0.35	NUM
ijassa-1351	127	13	0.4	0.4	NUM
ijassa-1351	127	14	0.45	0.45	NUM
ijassa-1351	127	15	0.5	0.5	NUM
ijassa-1351	127	16	0.55	0.55	NUM
ijassa-1351	127	17	0.6	0.6	NUM
ijassa-1351	127	18	σ	σ	PROPN
ijassa-1351	127	19	qk	qk	PROPN
ijassa-1351	127	20	–	–	PUNCT
ijassa-1351	127	21	1	1	NUM
ijassa-1351	127	22	fig	fig	NOUN
ijassa-1351	127	23	.	.	PUNCT
ijassa-1351	128	1	2.4	2.4	NUM
ijassa-1351	128	2	.	.	PUNCT
ijassa-1351	128	3	dependence	dependence	NOUN
ijassa-1351	128	4	σ̃	σ̃	PROPN
ijassa-1351	128	5	from	from	ADP
ijassa-1351	128	6	(	(	PUNCT
ijassa-1351	128	7	2.11	2.11	NUM
ijassa-1351	128	8	)	)	PUNCT
ijassa-1351	128	9	on	on	ADP
ijassa-1351	128	10	(	(	PUNCT
ijassa-1351	128	11	qk	qk	NOUN
ijassa-1351	128	12	−	−	PROPN
ijassa-1351	128	13	1	1	NUM
ijassa-1351	128	14	)	)	PUNCT
ijassa-1351	128	15	.	.	PUNCT
ijassa-1351	129	1	1	1	NUM
ijassa-1351	129	2	1.1	1.1	NUM
ijassa-1351	129	3	1.2	1.2	NUM
ijassa-1351	129	4	1.3	1.3	NUM
ijassa-1351	129	5	1.4	1.4	NUM
ijassa-1351	129	6	1.5	1.5	NUM
ijassa-1351	129	7	1.6	1.6	NUM
ijassa-1351	129	8	1.7	1.7	NUM
ijassa-1351	129	9	1.8	1.8	NUM
ijassa-1351	129	10	1.9	1.9	NUM
ijassa-1351	129	11	2	2	NUM
ijassa-1351	129	12	0.65	0.65	NUM
ijassa-1351	129	13	1.15	1.15	NUM
ijassa-1351	129	14	1.65	1.65	NUM
ijassa-1351	129	15	2.15	2.15	NUM
ijassa-1351	129	16	2.65	2.65	NUM
ijassa-1351	129	17	σ	σ	PROPN
ijassa-1351	129	18	hk	hk	PROPN
ijassa-1351	129	19	–	–	PUNCT
ijassa-1351	129	20	1	1	NUM
ijassa-1351	129	21	fig	fig	NOUN
ijassa-1351	129	22	.	.	PUNCT
ijassa-1351	130	1	2.5	2.5	NUM
ijassa-1351	130	2	.	.	PUNCT
ijassa-1351	131	1	dependence	dependence	NOUN
ijassa-1351	131	2	σ̃	σ̃	PROPN
ijassa-1351	131	3	from	from	ADP
ijassa-1351	131	4	(	(	PUNCT
ijassa-1351	131	5	2.11	2.11	NUM
ijassa-1351	131	6	)	)	PUNCT
ijassa-1351	131	7	on	on	ADP
ijassa-1351	131	8	(	(	PUNCT
ijassa-1351	131	9	hk	hk	NOUN
ijassa-1351	131	10	−	−	PROPN
ijassa-1351	131	11	1	1	NUM
ijassa-1351	131	12	)	)	PUNCT
ijassa-1351	131	13	.	.	PUNCT
ijassa-1351	132	1	copyright	copyright	NOUN
ijassa-1351	132	2	©	©	PROPN
ijassa-1351	132	3	2023	2023	NUM
ijassa-1351	132	4	assa	assa	NOUN
ijassa-1351	132	5	.	.	PUNCT
ijassa-1351	133	1	adv	adv	PROPN
ijassa-1351	133	2	syst	syst	PROPN
ijassa-1351	133	3	sci	sci	PROPN
ijassa-1351	133	4	appl	appl	PROPN
ijassa-1351	133	5	(	(	PUNCT
ijassa-1351	133	6	2023	2023	NUM
ijassa-1351	133	7	)	)	PUNCT
ijassa-1351	133	8	106	106	NUM
ijassa-1351	133	9	a.v	a.v	PROPN
ijassa-1351	133	10	.	.	PROPN
ijassa-1351	133	11	gorbunova	gorbunova	PROPN
ijassa-1351	133	12	,	,	PUNCT
ijassa-1351	133	13	a.v	a.v	PROPN
ijassa-1351	133	14	.	.	PROPN
ijassa-1351	133	15	lebedev	lebedev	PROPN
ijassa-1351	133	16	1	1	NUM
ijassa-1351	133	17	1.1	1.1	NUM
ijassa-1351	133	18	1.2	1.2	NUM
ijassa-1351	133	19	1.3	1.3	NUM
ijassa-1351	133	20	1.4	1.4	NUM
ijassa-1351	133	21	1.5	1.5	NUM
ijassa-1351	133	22	1.6	1.6	NUM
ijassa-1351	133	23	1.7	1.7	NUM
ijassa-1351	133	24	1.8	1.8	NUM
ijassa-1351	133	25	1.9	1.9	NUM
ijassa-1351	133	26	2	2	NUM
ijassa-1351	133	27	0	0	NUM
ijassa-1351	133	28	0.1	0.1	NUM
ijassa-1351	133	29	0.2	0.2	NUM
ijassa-1351	133	30	0.3	0.3	NUM
ijassa-1351	133	31	0.4	0.4	NUM
ijassa-1351	133	32	0.5	0.5	NUM
ijassa-1351	133	33	0.6	0.6	NUM
ijassa-1351	133	34	0.7	0.7	NUM
ijassa-1351	133	35	0.8	0.8	NUM
ijassa-1351	133	36	0.9	0.9	NUM
ijassa-1351	133	37	1	1	NUM
ijassa-1351	133	38	σ	σ	PROPN
ijassa-1351	133	39	ρ	ρ	NUM
ijassa-1351	133	40	fig	fig	NOUN
ijassa-1351	133	41	.	.	PUNCT
ijassa-1351	134	1	2.6	2.6	NUM
ijassa-1351	134	2	.	.	PUNCT
ijassa-1351	134	3	dependence	dependence	NOUN
ijassa-1351	134	4	σ̃	σ̃	PROPN
ijassa-1351	134	5	from	from	ADP
ijassa-1351	134	6	(	(	PUNCT
ijassa-1351	134	7	2.11	2.11	NUM
ijassa-1351	134	8	)	)	PUNCT
ijassa-1351	134	9	on	on	ADP
ijassa-1351	134	10	ρ	ρ	PROPN
ijassa-1351	134	11	.	.	PUNCT
ijassa-1351	135	1	in	in	ADP
ijassa-1351	135	2	figures	figure	NOUN
ijassa-1351	135	3	2.4	2.4	NUM
ijassa-1351	135	4	and	and	CCONJ
ijassa-1351	135	5	2.5	2.5	NUM
ijassa-1351	135	6	at	at	ADP
ijassa-1351	135	7	fixed	fix	VERB
ijassa-1351	135	8	values	value	NOUN
ijassa-1351	135	9	of	of	ADP
ijassa-1351	135	10	ρ	ρ	NOUN
ijassa-1351	135	11	,	,	PUNCT
ijassa-1351	135	12	σ̃	σ̃	PROPN
ijassa-1351	135	13	is	be	AUX
ijassa-1351	135	14	observed	observe	VERB
ijassa-1351	135	15	to	to	PART
ijassa-1351	135	16	depend	depend	VERB
ijassa-1351	135	17	quadratically	quadratically	ADV
ijassa-1351	135	18	on	on	ADP
ijassa-1351	135	19	(	(	PUNCT
ijassa-1351	135	20	qk	qk	NOUN
ijassa-1351	135	21	−	−	PROPN
ijassa-1351	135	22	1	1	NUM
ijassa-1351	135	23	)	)	PUNCT
ijassa-1351	135	24	and	and	CCONJ
ijassa-1351	135	25	on	on	ADP
ijassa-1351	135	26	(	(	PUNCT
ijassa-1351	135	27	hk	hk	NOUN
ijassa-1351	135	28	−	−	PROPN
ijassa-1351	135	29	1	1	NUM
ijassa-1351	135	30	)	)	PUNCT
ijassa-1351	135	31	,	,	PUNCT
ijassa-1351	135	32	respectively	respectively	ADV
ijassa-1351	135	33	.	.	PUNCT
ijassa-1351	136	1	however	however	ADV
ijassa-1351	136	2	,	,	PUNCT
ijassa-1351	136	3	the	the	DET
ijassa-1351	136	4	analysis	analysis	NOUN
ijassa-1351	136	5	of	of	ADP
ijassa-1351	136	6	the	the	DET
ijassa-1351	136	7	experimental	experimental	ADJ
ijassa-1351	136	8	data	datum	NOUN
ijassa-1351	136	9	for	for	ADP
ijassa-1351	136	10	large	large	ADJ
ijassa-1351	136	11	k	k	PROPN
ijassa-1351	136	12	showed	show	VERB
ijassa-1351	136	13	that	that	SCONJ
ijassa-1351	136	14	the	the	DET
ijassa-1351	136	15	dependence	dependence	NOUN
ijassa-1351	136	16	on	on	ADP
ijassa-1351	136	17	(	(	PUNCT
ijassa-1351	136	18	hk	hk	NOUN
ijassa-1351	136	19	−	−	PROPN
ijassa-1351	136	20	1	1	NUM
ijassa-1351	136	21	)	)	PUNCT
ijassa-1351	136	22	is	be	AUX
ijassa-1351	136	23	closer	close	ADJ
ijassa-1351	136	24	to	to	ADP
ijassa-1351	136	25	the	the	DET
ijassa-1351	136	26	truth	truth	NOUN
ijassa-1351	136	27	since	since	SCONJ
ijassa-1351	136	28	the	the	DET
ijassa-1351	136	29	actual	actual	ADJ
ijassa-1351	136	30	values	value	NOUN
ijassa-1351	136	31	of	of	ADP
ijassa-1351	136	32	the	the	DET
ijassa-1351	136	33	variance	variance	NOUN
ijassa-1351	136	34	grow	grow	VERB
ijassa-1351	136	35	without	without	ADP
ijassa-1351	136	36	limit	limit	NOUN
ijassa-1351	136	37	with	with	ADP
ijassa-1351	136	38	the	the	DET
ijassa-1351	136	39	growth	growth	NOUN
ijassa-1351	136	40	of	of	ADP
ijassa-1351	136	41	k.	k.	PROPN
ijassa-1351	136	42	otherwise	otherwise	ADV
ijassa-1351	136	43	,	,	PUNCT
ijassa-1351	136	44	the	the	DET
ijassa-1351	136	45	dispersion	dispersion	NOUN
ijassa-1351	136	46	values	value	NOUN
ijassa-1351	136	47	would	would	AUX
ijassa-1351	136	48	quickly	quickly	ADV
ijassa-1351	136	49	stabilize	stabilize	VERB
ijassa-1351	136	50	since	since	ADV
ijassa-1351	136	51	,	,	PUNCT
ijassa-1351	136	52	as	as	SCONJ
ijassa-1351	136	53	is	be	AUX
ijassa-1351	136	54	known	know	VERB
ijassa-1351	136	55	,	,	PUNCT
ijassa-1351	136	56	qk	qk	NOUN
ijassa-1351	136	57	has	have	VERB
ijassa-1351	136	58	a	a	DET
ijassa-1351	136	59	finite	finite	ADJ
ijassa-1351	136	60	limit	limit	NOUN
ijassa-1351	136	61	at	at	ADP
ijassa-1351	136	62	k	k	PROPN
ijassa-1351	136	63	→	→	SYM
ijassa-1351	136	64	∞	∞	PROPN
ijassa-1351	136	65	equal	equal	ADJ
ijassa-1351	136	66	to	to	ADP
ijassa-1351	136	67	π2/6	π2/6	NOUN
ijassa-1351	136	68	.	.	PUNCT
ijassa-1351	137	1	further	far	ADV
ijassa-1351	137	2	,	,	PUNCT
ijassa-1351	137	3	in	in	ADP
ijassa-1351	137	4	the	the	DET
ijassa-1351	137	5	figure	figure	NOUN
ijassa-1351	137	6	2.6	2.6	NUM
ijassa-1351	137	7	there	there	PRON
ijassa-1351	137	8	is	be	VERB
ijassa-1351	137	9	an	an	DET
ijassa-1351	137	10	explicit	explicit	ADJ
ijassa-1351	137	11	linear	linear	ADJ
ijassa-1351	137	12	dependence	dependence	NOUN
ijassa-1351	137	13	on	on	ADP
ijassa-1351	137	14	ρ	ρ	PROPN
ijassa-1351	137	15	with	with	ADP
ijassa-1351	137	16	a	a	DET
ijassa-1351	137	17	slope	slope	NOUN
ijassa-1351	137	18	depending	depend	VERB
ijassa-1351	137	19	on	on	ADP
ijassa-1351	137	20	k	k	PROPN
ijassa-1351	137	21	,	,	PUNCT
ijassa-1351	137	22	and	and	CCONJ
ijassa-1351	137	23	the	the	DET
ijassa-1351	137	24	straight	straight	ADJ
ijassa-1351	137	25	lines	line	NOUN
ijassa-1351	137	26	pass	pass	VERB
ijassa-1351	137	27	through	through	ADP
ijassa-1351	137	28	the	the	DET
ijassa-1351	137	29	point	point	NOUN
ijassa-1351	137	30	(	(	PUNCT
ijassa-1351	137	31	0	0	NUM
ijassa-1351	137	32	,	,	PUNCT
ijassa-1351	137	33	1	1	NUM
ijassa-1351	137	34	)	)	PUNCT
ijassa-1351	137	35	.	.	PUNCT
ijassa-1351	138	1	so	so	ADV
ijassa-1351	138	2	let	let	VERB
ijassa-1351	138	3	us	we	PRON
ijassa-1351	138	4	assume	assume	VERB
ijassa-1351	138	5	that	that	SCONJ
ijassa-1351	138	6	σ̃	σ̃	PROPN
ijassa-1351	138	7	=	=	SYM
ijassa-1351	138	8	σ̃(ρ	σ̃(ρ	PROPN
ijassa-1351	138	9	,	,	PUNCT
ijassa-1351	138	10	hk	hk	PROPN
ijassa-1351	138	11	)	)	PUNCT
ijassa-1351	138	12	=	=	SYM
ijassa-1351	139	1	1	1	NUM
ijassa-1351	139	2	+	+	NUM
ijassa-1351	139	3	ρ	ρ	PROPN
ijassa-1351	139	4	(	(	PUNCT
ijassa-1351	139	5	c1	c1	NOUN
ijassa-1351	139	6	+	+	CCONJ
ijassa-1351	139	7	c2(hk	c2(hk	PROPN
ijassa-1351	139	8	−	−	PROPN
ijassa-1351	139	9	1	1	NUM
ijassa-1351	139	10	)	)	PUNCT
ijassa-1351	139	11	+	+	NUM
ijassa-1351	139	12	c3(hk	c3(hk	PROPN
ijassa-1351	139	13	−	−	PROPN
ijassa-1351	139	14	1)2	1)2	NUM
ijassa-1351	139	15	)	)	PUNCT
ijassa-1351	139	16	(	(	PUNCT
ijassa-1351	139	17	2.12	2.12	NUM
ijassa-1351	139	18	)	)	PUNCT
ijassa-1351	139	19	and	and	CCONJ
ijassa-1351	139	20	correspondingly	correspondingly	ADV
ijassa-1351	139	21	,	,	PUNCT
ijassa-1351	139	22	var[rk	var[rk	NOUN
ijassa-1351	139	23	]	]	PUNCT
ijassa-1351	140	1	≈	≈	PROPN
ijassa-1351	140	2	qk	qk	PUNCT
ijassa-1351	140	3	−	−	PROPN
ijassa-1351	140	4	1	1	NUM
ijassa-1351	140	5	(	(	PUNCT
ijassa-1351	140	6	µ−	µ−	PROPN
ijassa-1351	140	7	λ)2	λ)2	NOUN
ijassa-1351	140	8	·	·	PUNCT
ijassa-1351	140	9	(	(	PUNCT
ijassa-1351	140	10	1	1	NUM
ijassa-1351	140	11	+	+	NUM
ijassa-1351	140	12	ρ	ρ	PROPN
ijassa-1351	140	13	(	(	PUNCT
ijassa-1351	140	14	c1	c1	NOUN
ijassa-1351	140	15	+	+	CCONJ
ijassa-1351	140	16	c2(hk	c2(hk	PROPN
ijassa-1351	140	17	−	−	PROPN
ijassa-1351	140	18	1	1	NUM
ijassa-1351	140	19	)	)	PUNCT
ijassa-1351	140	20	+	+	NUM
ijassa-1351	140	21	c3(hk	c3(hk	PROPN
ijassa-1351	140	22	−	−	PROPN
ijassa-1351	140	23	1)2	1)2	NUM
ijassa-1351	140	24	)	)	PUNCT
ijassa-1351	140	25	)	)	PUNCT
ijassa-1351	141	1	+	+	CCONJ
ijassa-1351	141	2	1	1	X
ijassa-1351	141	3	(	(	PUNCT
ijassa-1351	141	4	µ−	µ−	PROPN
ijassa-1351	141	5	λ)2	λ)2	NOUN
ijassa-1351	141	6	.	.	PUNCT
ijassa-1351	142	1	(	(	PUNCT
ijassa-1351	142	2	2.13	2.13	NUM
ijassa-1351	142	3	)	)	PUNCT
ijassa-1351	142	4	then	then	ADV
ijassa-1351	142	5	,	,	PUNCT
ijassa-1351	142	6	similarly	similarly	ADV
ijassa-1351	142	7	,	,	PUNCT
ijassa-1351	142	8	using	use	VERB
ijassa-1351	142	9	the	the	DET
ijassa-1351	142	10	nelder	nelder	ADJ
ijassa-1351	142	11	-	-	PUNCT
ijassa-1351	142	12	mead	mead	NOUN
ijassa-1351	142	13	method	method	NOUN
ijassa-1351	142	14	,	,	PUNCT
ijassa-1351	142	15	we	we	PRON
ijassa-1351	142	16	solve	solve	VERB
ijassa-1351	142	17	the	the	DET
ijassa-1351	142	18	optimization	optimization	NOUN
ijassa-1351	142	19	problem	problem	NOUN
ijassa-1351	142	20	of	of	ADP
ijassa-1351	142	21	minimizing	minimize	VERB
ijassa-1351	142	22	the	the	DET
ijassa-1351	142	23	maximum	maximum	ADJ
ijassa-1351	142	24	approximation	approximation	NOUN
ijassa-1351	142	25	error	error	NOUN
ijassa-1351	142	26	of	of	ADP
ijassa-1351	142	27	the	the	DET
ijassa-1351	142	28	formula	formula	NOUN
ijassa-1351	142	29	(	(	PUNCT
ijassa-1351	142	30	2.13	2.13	NUM
ijassa-1351	142	31	)	)	PUNCT
ijassa-1351	142	32	max	max	NOUN
ijassa-1351	142	33	∣∣∣∣v̂ar[rk	∣∣∣∣v̂ar[rk	NOUN
ijassa-1351	142	34	]	]	PUNCT
ijassa-1351	142	35	−	−	PROPN
ijassa-1351	142	36	var[rk	var[rk	NOUN
ijassa-1351	142	37	]	]	PUNCT
ijassa-1351	142	38	var[rk	var[rk	NOUN
ijassa-1351	142	39	]	]	PUNCT
ijassa-1351	142	40	·	·	PUNCT
ijassa-1351	142	41	100	100	NUM
ijassa-1351	142	42	%	%	NOUN
ijassa-1351	142	43	∣∣∣∣	∣∣∣∣	PROPN
ijassa-1351	142	44	→	→	SYM
ijassa-1351	142	45	min	min	PROPN
ijassa-1351	142	46	.	.	PUNCT
ijassa-1351	143	1	(	(	PUNCT
ijassa-1351	143	2	2.14	2.14	NUM
ijassa-1351	143	3	)	)	PUNCT
ijassa-1351	143	4	as	as	ADP
ijassa-1351	143	5	a	a	DET
ijassa-1351	143	6	result	result	NOUN
ijassa-1351	143	7	,	,	PUNCT
ijassa-1351	143	8	we	we	PRON
ijassa-1351	143	9	obtain	obtain	VERB
ijassa-1351	143	10	the	the	DET
ijassa-1351	143	11	following	follow	VERB
ijassa-1351	143	12	values	value	NOUN
ijassa-1351	143	13	of	of	ADP
ijassa-1351	143	14	the	the	DET
ijassa-1351	143	15	coefficients	coefficient	NOUN
ijassa-1351	143	16	ci	ci	PROPN
ijassa-1351	143	17	c1	c1	PROPN
ijassa-1351	143	18	≈	≈	PROPN
ijassa-1351	143	19	−0.113658	−0.113658	PROPN
ijassa-1351	143	20	,	,	PUNCT
ijassa-1351	143	21	c2	c2	PROPN
ijassa-1351	143	22	≈	≈	PROPN
ijassa-1351	143	23	0.339780	0.339780	NUM
ijassa-1351	143	24	,	,	PUNCT
ijassa-1351	143	25	c3	c3	PROPN
ijassa-1351	143	26	≈	≈	PROPN
ijassa-1351	143	27	0.053745	0.053745	NUM
ijassa-1351	143	28	.	.	PUNCT
ijassa-1351	144	1	(	(	PUNCT
ijassa-1351	144	2	2.15	2.15	NUM
ijassa-1351	144	3	)	)	PUNCT
ijassa-1351	144	4	the	the	DET
ijassa-1351	144	5	figure	figure	NOUN
ijassa-1351	144	6	2.7	2.7	NUM
ijassa-1351	144	7	shows	show	VERB
ijassa-1351	144	8	the	the	DET
ijassa-1351	144	9	results	result	NOUN
ijassa-1351	144	10	obtained	obtain	VERB
ijassa-1351	144	11	using	use	VERB
ijassa-1351	144	12	the	the	DET
ijassa-1351	144	13	(	(	PUNCT
ijassa-1351	144	14	2.13	2.13	NUM
ijassa-1351	144	15	)	)	PUNCT
ijassa-1351	144	16	formula	formula	NOUN
ijassa-1351	144	17	and	and	CCONJ
ijassa-1351	144	18	simulation	simulation	NOUN
ijassa-1351	144	19	modeling	modeling	NOUN
ijassa-1351	144	20	to	to	PART
ijassa-1351	144	21	illustrate	illustrate	VERB
ijassa-1351	144	22	the	the	DET
ijassa-1351	144	23	quality	quality	NOUN
ijassa-1351	144	24	of	of	ADP
ijassa-1351	144	25	the	the	DET
ijassa-1351	144	26	obtained	obtain	VERB
ijassa-1351	144	27	approximation	approximation	NOUN
ijassa-1351	144	28	.	.	PUNCT
ijassa-1351	145	1	for	for	ADP
ijassa-1351	145	2	the	the	DET
ijassa-1351	145	3	standard	standard	ADJ
ijassa-1351	145	4	deviation	deviation	NOUN
ijassa-1351	145	5	of	of	ADP
ijassa-1351	145	6	the	the	DET
ijassa-1351	145	7	response	response	NOUN
ijassa-1351	145	8	time	time	NOUN
ijassa-1351	145	9	for	for	ADP
ijassa-1351	145	10	λ	λ	PROPN
ijassa-1351	145	11	=	=	SYM
ijassa-1351	145	12	1	1	NUM
ijassa-1351	145	13	,	,	PUNCT
ijassa-1351	145	14	ρ	ρ	PROPN
ijassa-1351	145	15	∈	∈	PROPN
ijassa-1351	145	16	{	{	PUNCT
ijassa-1351	145	17	0.1	0.1	NUM
ijassa-1351	145	18	,	,	PUNCT
ijassa-1351	145	19	0.15	0.15	NUM
ijassa-1351	145	20	,	,	PUNCT
ijassa-1351	145	21	0.20	0.20	NUM
ijassa-1351	145	22	,	,	PUNCT
ijassa-1351	145	23	...	...	PUNCT
ijassa-1351	145	24	,	,	PUNCT
ijassa-1351	145	25	0.90	0.90	NUM
ijassa-1351	145	26	}	}	PUNCT
ijassa-1351	145	27	and	and	CCONJ
ijassa-1351	145	28	k	k	X
ijassa-1351	145	29	=	=	SYM
ijassa-1351	145	30	3	3	NUM
ijassa-1351	145	31	,	,	PUNCT
ijassa-1351	145	32	...	...	PUNCT
ijassa-1351	145	33	,	,	PUNCT
ijassa-1351	145	34	20	20	NUM
ijassa-1351	145	35	,	,	PUNCT
ijassa-1351	145	36	we	we	PRON
ijassa-1351	145	37	have	have	VERB
ijassa-1351	145	38	maxape	maxape	NOUN
ijassa-1351	145	39	≈	≈	PROPN
ijassa-1351	145	40	0.564247	0.564247	NUM
ijassa-1351	145	41	%	%	NOUN
ijassa-1351	145	42	,	,	PUNCT
ijassa-1351	145	43	minape	minape	NOUN
ijassa-1351	145	44	≈	≈	PROPN
ijassa-1351	145	45	0.000755	0.000755	NUM
ijassa-1351	145	46	%	%	NOUN
ijassa-1351	145	47	,	,	PUNCT
ijassa-1351	145	48	mape	mape	NOUN
ijassa-1351	145	49	≈	≈	PROPN
ijassa-1351	145	50	0.188812	0.188812	NUM
ijassa-1351	145	51	%	%	NOUN
ijassa-1351	145	52	,	,	PUNCT
ijassa-1351	145	53	while	while	SCONJ
ijassa-1351	145	54	for	for	SCONJ
ijassa-1351	145	55	the	the	DET
ijassa-1351	145	56	formula	formula	NOUN
ijassa-1351	145	57	(	(	PUNCT
ijassa-1351	145	58	2.9	2.9	NUM
ijassa-1351	145	59	)	)	PUNCT
ijassa-1351	145	60	for	for	ADP
ijassa-1351	145	61	the	the	DET
ijassa-1351	145	62	same	same	ADJ
ijassa-1351	145	63	values	value	NOUN
ijassa-1351	145	64	λ	λ	PROPN
ijassa-1351	145	65	,	,	PUNCT
ijassa-1351	145	66	ρ	ρ	PROPN
ijassa-1351	145	67	and	and	CCONJ
ijassa-1351	145	68	k	k	PROPN
ijassa-1351	145	69	is	be	AUX
ijassa-1351	145	70	true	true	ADJ
ijassa-1351	145	71	maxape	maxape	NOUN
ijassa-1351	145	72	≈	≈	PROPN
ijassa-1351	145	73	14.475134	14.475134	NUM
ijassa-1351	145	74	%	%	NOUN
ijassa-1351	145	75	,	,	PUNCT
ijassa-1351	145	76	minape	minape	NOUN
ijassa-1351	145	77	≈	≈	PROPN
ijassa-1351	145	78	0.173239	0.173239	NUM
ijassa-1351	145	79	%	%	NOUN
ijassa-1351	145	80	,	,	PUNCT
ijassa-1351	145	81	mape	mape	NOUN
ijassa-1351	145	82	≈	≈	PROPN
ijassa-1351	145	83	6.055298	6.055298	NUM
ijassa-1351	145	84	%	%	NOUN
ijassa-1351	145	85	.	.	PUNCT
ijassa-1351	146	1	thus	thus	ADV
ijassa-1351	146	2	,	,	PUNCT
ijassa-1351	146	3	our	our	PRON
ijassa-1351	146	4	estimate	estimate	NOUN
ijassa-1351	146	5	improves	improve	VERB
ijassa-1351	146	6	maxape	maxape	NOUN
ijassa-1351	146	7	by	by	ADP
ijassa-1351	146	8	a	a	DET
ijassa-1351	146	9	factor	factor	NOUN
ijassa-1351	146	10	of	of	ADP
ijassa-1351	146	11	25.7	25.7	NUM
ijassa-1351	146	12	and	and	CCONJ
ijassa-1351	146	13	mape	mape	NOUN
ijassa-1351	146	14	by	by	ADP
ijassa-1351	146	15	a	a	DET
ijassa-1351	146	16	factor	factor	NOUN
ijassa-1351	146	17	of	of	ADP
ijassa-1351	146	18	32.1	32.1	NUM
ijassa-1351	146	19	.	.	PUNCT
ijassa-1351	147	1	copyright	copyright	NOUN
ijassa-1351	147	2	©	©	PROPN
ijassa-1351	147	3	2023	2023	NUM
ijassa-1351	147	4	assa	assa	NOUN
ijassa-1351	147	5	.	.	PUNCT
ijassa-1351	148	1	adv	adv	PROPN
ijassa-1351	148	2	syst	syst	PROPN
ijassa-1351	148	3	sci	sci	PROPN
ijassa-1351	148	4	appl	appl	PROPN
ijassa-1351	148	5	(	(	PUNCT
ijassa-1351	148	6	2023	2023	NUM
ijassa-1351	148	7	)	)	PUNCT
ijassa-1351	148	8	assa	assa	NOUN
ijassa-1351	148	9	latex	latex	NOUN
ijassa-1351	148	10	template	template	NOUN
ijassa-1351	148	11	107	107	NUM
ijassa-1351	148	12	0	0	NUM
ijassa-1351	148	13	1	1	NUM
ijassa-1351	148	14	2	2	NUM
ijassa-1351	148	15	3	3	NUM
ijassa-1351	148	16	4	4	NUM
ijassa-1351	148	17	5	5	NUM
ijassa-1351	148	18	6	6	NUM
ijassa-1351	148	19	7	7	NUM
ijassa-1351	148	20	8	8	NUM
ijassa-1351	148	21	9	9	NUM
ijassa-1351	148	22	10	10	NUM
ijassa-1351	148	23	11	11	NUM
ijassa-1351	148	24	12	12	NUM
ijassa-1351	148	25	13	13	NUM
ijassa-1351	148	26	0	0	NUM
ijassa-1351	148	27	1	1	NUM
ijassa-1351	148	28	2	2	NUM
ijassa-1351	148	29	3	3	NUM
ijassa-1351	148	30	4	4	NUM
ijassa-1351	148	31	5	5	NUM
ijassa-1351	148	32	6	6	NUM
ijassa-1351	148	33	7	7	NUM
ijassa-1351	148	34	8	8	NUM
ijassa-1351	148	35	9	9	NUM
ijassa-1351	148	36	10	10	NUM
ijassa-1351	148	37	11	11	NUM
ijassa-1351	148	38	12	12	NUM
ijassa-1351	148	39	13	13	NUM
ijassa-1351	148	40	f	f	NOUN
ijassa-1351	148	41	o	o	X
ijassa-1351	148	42	rm	rm	X
ijassa-1351	148	43	u	u	PROPN
ijassa-1351	148	44	la	la	PROPN
ijassa-1351	148	45	(	(	PUNCT
ijassa-1351	148	46	1	1	NUM
ijassa-1351	148	47	3	3	NUM
ijassa-1351	148	48	)	)	PUNCT
ijassa-1351	148	49	simulation	simulation	NOUN
ijassa-1351	148	50	fig	fig	NOUN
ijassa-1351	148	51	.	.	PUNCT
ijassa-1351	149	1	2.7	2.7	NUM
ijassa-1351	149	2	.	.	PUNCT
ijassa-1351	150	1	the	the	DET
ijassa-1351	150	2	standard	standard	ADJ
ijassa-1351	150	3	deviation	deviation	NOUN
ijassa-1351	150	4	of	of	ADP
ijassa-1351	150	5	the	the	DET
ijassa-1351	150	6	response	response	NOUN
ijassa-1351	150	7	time	time	NOUN
ijassa-1351	150	8	.	.	PUNCT
ijassa-1351	151	1	as	as	ADP
ijassa-1351	151	2	in	in	ADP
ijassa-1351	151	3	the	the	DET
ijassa-1351	151	4	case	case	NOUN
ijassa-1351	151	5	of	of	ADP
ijassa-1351	151	6	the	the	DET
ijassa-1351	151	7	mathematical	mathematical	ADJ
ijassa-1351	151	8	expectation	expectation	NOUN
ijassa-1351	151	9	of	of	ADP
ijassa-1351	151	10	the	the	DET
ijassa-1351	151	11	response	response	NOUN
ijassa-1351	151	12	time	time	NOUN
ijassa-1351	151	13	,	,	PUNCT
ijassa-1351	151	14	the	the	DET
ijassa-1351	151	15	formula	formula	NOUN
ijassa-1351	151	16	for	for	ADP
ijassa-1351	151	17	the	the	DET
ijassa-1351	151	18	standard	standard	ADJ
ijassa-1351	151	19	deviation	deviation	NOUN
ijassa-1351	151	20	of	of	ADP
ijassa-1351	151	21	the	the	DET
ijassa-1351	151	22	response	response	NOUN
ijassa-1351	151	23	time	time	NOUN
ijassa-1351	151	24	turns	turn	VERB
ijassa-1351	151	25	out	out	ADP
ijassa-1351	151	26	to	to	PART
ijassa-1351	151	27	be	be	AUX
ijassa-1351	151	28	good	good	ADJ
ijassa-1351	151	29	not	not	PART
ijassa-1351	151	30	only	only	ADV
ijassa-1351	151	31	for	for	ADP
ijassa-1351	151	32	the	the	DET
ijassa-1351	151	33	maximum	maximum	ADJ
ijassa-1351	151	34	value	value	NOUN
ijassa-1351	151	35	of	of	ADP
ijassa-1351	151	36	k	k	PROPN
ijassa-1351	151	37	=	=	SYM
ijassa-1351	151	38	20	20	NUM
ijassa-1351	151	39	,	,	PUNCT
ijassa-1351	151	40	but	but	CCONJ
ijassa-1351	151	41	also	also	ADV
ijassa-1351	151	42	for	for	ADP
ijassa-1351	151	43	a	a	DET
ijassa-1351	151	44	much	much	ADV
ijassa-1351	151	45	larger	large	ADJ
ijassa-1351	151	46	number	number	NOUN
ijassa-1351	151	47	of	of	ADP
ijassa-1351	151	48	subsystems	subsystem	NOUN
ijassa-1351	151	49	.	.	PUNCT
ijassa-1351	152	1	thus	thus	ADV
ijassa-1351	152	2	,	,	PUNCT
ijassa-1351	152	3	for	for	ADP
ijassa-1351	152	4	k	k	PROPN
ijassa-1351	152	5	=	=	SYM
ijassa-1351	152	6	100	100	NUM
ijassa-1351	152	7	and	and	CCONJ
ijassa-1351	152	8	values	value	NOUN
ijassa-1351	152	9	ρ	ρ	PROPN
ijassa-1351	152	10	∈	∈	PROPN
ijassa-1351	153	1	[	[	X
ijassa-1351	153	2	0.1	0.1	NUM
ijassa-1351	153	3	,	,	PUNCT
ijassa-1351	153	4	0.9	0.9	NUM
ijassa-1351	153	5	]	]	PUNCT
ijassa-1351	153	6	with	with	ADP
ijassa-1351	153	7	a	a	DET
ijassa-1351	153	8	step	step	NOUN
ijassa-1351	153	9	of	of	ADP
ijassa-1351	153	10	0.05	0.05	NUM
ijassa-1351	153	11	we	we	PRON
ijassa-1351	153	12	have	have	VERB
ijassa-1351	153	13	the	the	DET
ijassa-1351	153	14	following	follow	VERB
ijassa-1351	153	15	approximation	approximation	NOUN
ijassa-1351	153	16	errors	error	NOUN
ijassa-1351	153	17	maxape	maxape	NOUN
ijassa-1351	154	1	≈	≈	PROPN
ijassa-1351	154	2	1.211417	1.211417	NUM
ijassa-1351	154	3	%	%	NOUN
ijassa-1351	154	4	,	,	PUNCT
ijassa-1351	154	5	minape	minape	NOUN
ijassa-1351	154	6	≈	≈	PROPN
ijassa-1351	154	7	0.094622	0.094622	NUM
ijassa-1351	154	8	%	%	NOUN
ijassa-1351	154	9	,	,	PUNCT
ijassa-1351	154	10	mape	mape	NOUN
ijassa-1351	154	11	≈	≈	PROPN
ijassa-1351	154	12	0.724898	0.724898	NUM
ijassa-1351	154	13	%	%	NOUN
ijassa-1351	154	14	.	.	PUNCT
ijassa-1351	155	1	for	for	ADP
ijassa-1351	155	2	the	the	DET
ijassa-1351	155	3	value	value	NOUN
ijassa-1351	155	4	k	k	PROPN
ijassa-1351	155	5	=	=	SYM
ijassa-1351	155	6	1000	1000	NUM
ijassa-1351	155	7	,	,	PUNCT
ijassa-1351	155	8	for	for	ADP
ijassa-1351	155	9	the	the	DET
ijassa-1351	155	10	same	same	ADJ
ijassa-1351	155	11	reasons	reason	NOUN
ijassa-1351	155	12	as	as	ADP
ijassa-1351	155	13	in	in	ADP
ijassa-1351	155	14	the	the	DET
ijassa-1351	155	15	case	case	NOUN
ijassa-1351	155	16	of	of	ADP
ijassa-1351	155	17	the	the	DET
ijassa-1351	155	18	formula	formula	NOUN
ijassa-1351	155	19	for	for	ADP
ijassa-1351	155	20	the	the	DET
ijassa-1351	155	21	mathematical	mathematical	ADJ
ijassa-1351	155	22	expectation	expectation	NOUN
ijassa-1351	155	23	,	,	PUNCT
ijassa-1351	155	24	we	we	PRON
ijassa-1351	155	25	present	present	VERB
ijassa-1351	155	26	the	the	DET
ijassa-1351	155	27	results	result	NOUN
ijassa-1351	155	28	of	of	ADP
ijassa-1351	155	29	the	the	DET
ijassa-1351	155	30	approximation	approximation	NOUN
ijassa-1351	155	31	error	error	NOUN
ijassa-1351	155	32	only	only	ADV
ijassa-1351	155	33	under	under	ADP
ijassa-1351	155	34	conditions	condition	NOUN
ijassa-1351	155	35	of	of	ADP
ijassa-1351	155	36	low	low	ADJ
ijassa-1351	155	37	system	system	NOUN
ijassa-1351	155	38	load	load	NOUN
ijassa-1351	155	39	ρ	ρ	NOUN
ijassa-1351	155	40	=	=	PUNCT
ijassa-1351	155	41	{	{	PUNCT
ijassa-1351	155	42	0.1	0.1	NUM
ijassa-1351	155	43	,	,	PUNCT
ijassa-1351	155	44	0.2	0.2	NUM
ijassa-1351	155	45	,	,	PUNCT
ijassa-1351	155	46	0.3	0.3	NUM
ijassa-1351	155	47	,	,	PUNCT
ijassa-1351	155	48	0.4	0.4	NUM
ijassa-1351	155	49	,	,	PUNCT
ijassa-1351	155	50	0.5	0.5	NUM
ijassa-1351	155	51	}	}	PUNCT
ijassa-1351	155	52	maxape	maxape	NOUN
ijassa-1351	155	53	≈	≈	PROPN
ijassa-1351	155	54	1.029874	1.029874	NUM
ijassa-1351	155	55	%	%	NOUN
ijassa-1351	155	56	,	,	PUNCT
ijassa-1351	155	57	minape	minape	NOUN
ijassa-1351	155	58	≈	≈	PROPN
ijassa-1351	155	59	0.203567	0.203567	NUM
ijassa-1351	155	60	%	%	NOUN
ijassa-1351	155	61	,	,	PUNCT
ijassa-1351	155	62	mape	mape	NOUN
ijassa-1351	155	63	≈	≈	PROPN
ijassa-1351	155	64	0.592974	0.592974	NUM
ijassa-1351	155	65	%	%	NOUN
ijassa-1351	155	66	.	.	PUNCT
ijassa-1351	156	1	as	as	ADP
ijassa-1351	156	2	a	a	DET
ijassa-1351	156	3	result	result	NOUN
ijassa-1351	156	4	,	,	PUNCT
ijassa-1351	156	5	a	a	DET
ijassa-1351	156	6	very	very	ADV
ijassa-1351	156	7	good	good	ADJ
ijassa-1351	156	8	approximation	approximation	NOUN
ijassa-1351	156	9	takes	take	VERB
ijassa-1351	156	10	place	place	NOUN
ijassa-1351	156	11	.	.	PUNCT
ijassa-1351	157	1	3	3	X
ijassa-1351	157	2	.	.	X
ijassa-1351	157	3	features	feature	NOUN
ijassa-1351	157	4	of	of	ADP
ijassa-1351	157	5	fork	fork	NOUN
ijassa-1351	157	6	-	-	PUNCT
ijassa-1351	157	7	join	join	NOUN
ijassa-1351	157	8	qs	qs	PROPN
ijassa-1351	157	9	simulation	simulation	NOUN
ijassa-1351	157	10	the	the	DET
ijassa-1351	157	11	fork	fork	NOUN
ijassa-1351	157	12	-	-	PUNCT
ijassa-1351	157	13	join	join	NOUN
ijassa-1351	157	14	queuing	queuing	NOUN
ijassa-1351	157	15	system	system	NOUN
ijassa-1351	157	16	is	be	AUX
ijassa-1351	157	17	one	one	NUM
ijassa-1351	157	18	of	of	ADP
ijassa-1351	157	19	the	the	DET
ijassa-1351	157	20	systems	system	NOUN
ijassa-1351	157	21	that	that	PRON
ijassa-1351	157	22	is	be	AUX
ijassa-1351	157	23	difficult	difficult	ADJ
ijassa-1351	157	24	to	to	PART
ijassa-1351	157	25	study	study	VERB
ijassa-1351	157	26	.	.	PUNCT
ijassa-1351	158	1	exact	exact	ADJ
ijassa-1351	158	2	analytical	analytical	ADJ
ijassa-1351	158	3	results	result	NOUN
ijassa-1351	158	4	are	be	AUX
ijassa-1351	158	5	known	know	VERB
ijassa-1351	158	6	only	only	ADV
ijassa-1351	158	7	for	for	ADP
ijassa-1351	158	8	a	a	DET
ijassa-1351	158	9	small	small	ADJ
ijassa-1351	158	10	number	number	NOUN
ijassa-1351	158	11	of	of	ADP
ijassa-1351	158	12	particular	particular	ADJ
ijassa-1351	158	13	cases	case	NOUN
ijassa-1351	158	14	.	.	PUNCT
ijassa-1351	159	1	in	in	ADP
ijassa-1351	159	2	most	most	ADJ
ijassa-1351	159	3	works	work	NOUN
ijassa-1351	159	4	on	on	ADP
ijassa-1351	159	5	this	this	DET
ijassa-1351	159	6	topic	topic	NOUN
ijassa-1351	159	7	,	,	PUNCT
ijassa-1351	159	8	many	many	ADJ
ijassa-1351	159	9	approximate	approximate	ADJ
ijassa-1351	159	10	methods	method	NOUN
ijassa-1351	159	11	,	,	PUNCT
ijassa-1351	159	12	including	include	VERB
ijassa-1351	159	13	numerical	numerical	ADJ
ijassa-1351	159	14	algorithms	algorithm	NOUN
ijassa-1351	159	15	,	,	PUNCT
ijassa-1351	159	16	have	have	AUX
ijassa-1351	159	17	been	be	AUX
ijassa-1351	159	18	developed	develop	VERB
ijassa-1351	159	19	to	to	PART
ijassa-1351	159	20	analyze	analyze	VERB
ijassa-1351	159	21	the	the	DET
ijassa-1351	159	22	performance	performance	NOUN
ijassa-1351	159	23	characteristics	characteristic	NOUN
ijassa-1351	159	24	of	of	ADP
ijassa-1351	159	25	fork	fork	NOUN
ijassa-1351	159	26	-	-	PUNCT
ijassa-1351	159	27	join	join	NOUN
ijassa-1351	159	28	qs	qs	NOUN
ijassa-1351	159	29	.	.	PUNCT
ijassa-1351	160	1	the	the	DET
ijassa-1351	160	2	effectiveness	effectiveness	NOUN
ijassa-1351	160	3	of	of	ADP
ijassa-1351	160	4	a	a	DET
ijassa-1351	160	5	particular	particular	ADJ
ijassa-1351	160	6	method	method	NOUN
ijassa-1351	160	7	can	can	AUX
ijassa-1351	160	8	be	be	AUX
ijassa-1351	160	9	determined	determine	VERB
ijassa-1351	160	10	by	by	ADP
ijassa-1351	160	11	various	various	ADJ
ijassa-1351	160	12	criteria	criterion	NOUN
ijassa-1351	160	13	.	.	PUNCT
ijassa-1351	161	1	the	the	DET
ijassa-1351	161	2	most	most	ADV
ijassa-1351	161	3	significant	significant	ADJ
ijassa-1351	161	4	among	among	ADP
ijassa-1351	161	5	them	they	PRON
ijassa-1351	161	6	are	be	AUX
ijassa-1351	161	7	economy	economy	NOUN
ijassa-1351	161	8	and	and	CCONJ
ijassa-1351	161	9	high	high	ADJ
ijassa-1351	161	10	accuracy	accuracy	NOUN
ijassa-1351	161	11	.	.	PUNCT
ijassa-1351	162	1	efficiency	efficiency	NOUN
ijassa-1351	162	2	is	be	AUX
ijassa-1351	162	3	understood	understand	VERB
ijassa-1351	162	4	as	as	ADP
ijassa-1351	162	5	the	the	DET
ijassa-1351	162	6	required	require	VERB
ijassa-1351	162	7	amount	amount	NOUN
ijassa-1351	162	8	of	of	ADP
ijassa-1351	162	9	resources	resource	NOUN
ijassa-1351	162	10	:	:	PUNCT
ijassa-1351	162	11	the	the	DET
ijassa-1351	162	12	less	less	ADJ
ijassa-1351	162	13	computer	computer	NOUN
ijassa-1351	162	14	memory	memory	NOUN
ijassa-1351	162	15	is	be	AUX
ijassa-1351	162	16	required	require	VERB
ijassa-1351	162	17	,	,	PUNCT
ijassa-1351	162	18	or	or	CCONJ
ijassa-1351	162	19	the	the	DET
ijassa-1351	162	20	shorter	short	ADJ
ijassa-1351	162	21	the	the	DET
ijassa-1351	162	22	time	time	NOUN
ijassa-1351	162	23	of	of	ADP
ijassa-1351	162	24	the	the	DET
ijassa-1351	162	25	algorithm	algorithm	NOUN
ijassa-1351	162	26	itself	itself	PRON
ijassa-1351	162	27	,	,	PUNCT
ijassa-1351	162	28	the	the	PRON
ijassa-1351	162	29	better	well	ADJ
ijassa-1351	162	30	.	.	PUNCT
ijassa-1351	163	1	regarding	regard	VERB
ijassa-1351	163	2	the	the	DET
ijassa-1351	163	3	accuracy	accuracy	NOUN
ijassa-1351	163	4	of	of	ADP
ijassa-1351	163	5	the	the	DET
ijassa-1351	163	6	method	method	NOUN
ijassa-1351	163	7	,	,	PUNCT
ijassa-1351	163	8	data	datum	NOUN
ijassa-1351	163	9	for	for	ADP
ijassa-1351	163	10	comparison	comparison	NOUN
ijassa-1351	163	11	are	be	AUX
ijassa-1351	163	12	required	require	VERB
ijassa-1351	163	13	here	here	ADV
ijassa-1351	163	14	.	.	PUNCT
ijassa-1351	164	1	the	the	DET
ijassa-1351	164	2	only	only	ADJ
ijassa-1351	164	3	possible	possible	ADJ
ijassa-1351	164	4	tool	tool	NOUN
ijassa-1351	164	5	for	for	ADP
ijassa-1351	164	6	obtaining	obtain	VERB
ijassa-1351	164	7	them	they	PRON
ijassa-1351	164	8	in	in	ADP
ijassa-1351	164	9	this	this	DET
ijassa-1351	164	10	context	context	NOUN
ijassa-1351	164	11	can	can	AUX
ijassa-1351	164	12	only	only	ADV
ijassa-1351	164	13	be	be	AUX
ijassa-1351	164	14	simulation	simulation	NOUN
ijassa-1351	164	15	modeling	modeling	NOUN
ijassa-1351	164	16	.	.	PUNCT
ijassa-1351	165	1	thus	thus	ADV
ijassa-1351	165	2	,	,	PUNCT
ijassa-1351	165	3	the	the	DET
ijassa-1351	165	4	assessment	assessment	NOUN
ijassa-1351	165	5	of	of	ADP
ijassa-1351	165	6	the	the	DET
ijassa-1351	165	7	accuracy	accuracy	NOUN
ijassa-1351	165	8	of	of	ADP
ijassa-1351	165	9	new	new	ADJ
ijassa-1351	165	10	methods	method	NOUN
ijassa-1351	165	11	for	for	ADP
ijassa-1351	165	12	studying	study	VERB
ijassa-1351	165	13	fork	fork	NOUN
ijassa-1351	165	14	-	-	PUNCT
ijassa-1351	165	15	join	join	NOUN
ijassa-1351	165	16	qs	qs	NOUN
ijassa-1351	165	17	directly	directly	ADV
ijassa-1351	165	18	depends	depend	VERB
ijassa-1351	165	19	on	on	ADP
ijassa-1351	165	20	the	the	DET
ijassa-1351	165	21	accuracy	accuracy	NOUN
ijassa-1351	165	22	of	of	ADP
ijassa-1351	165	23	the	the	DET
ijassa-1351	165	24	values	value	NOUN
ijassa-1351	165	25	obtained	obtain	VERB
ijassa-1351	165	26	as	as	ADP
ijassa-1351	165	27	a	a	DET
ijassa-1351	165	28	result	result	NOUN
ijassa-1351	165	29	of	of	ADP
ijassa-1351	165	30	simulation	simulation	NOUN
ijassa-1351	165	31	modeling	modeling	NOUN
ijassa-1351	165	32	.	.	PUNCT
ijassa-1351	166	1	simulation	simulation	NOUN
ijassa-1351	166	2	modeling	modeling	NOUN
ijassa-1351	166	3	is	be	AUX
ijassa-1351	166	4	based	base	VERB
ijassa-1351	166	5	on	on	ADP
ijassa-1351	166	6	the	the	DET
ijassa-1351	166	7	monte	monte	PROPN
ijassa-1351	166	8	carlo	carlo	PROPN
ijassa-1351	166	9	method	method	NOUN
ijassa-1351	166	10	,	,	PUNCT
ijassa-1351	166	11	which	which	PRON
ijassa-1351	166	12	consists	consist	VERB
ijassa-1351	166	13	of	of	ADP
ijassa-1351	166	14	multiple	multiple	ADJ
ijassa-1351	166	15	reproductions	reproduction	NOUN
ijassa-1351	166	16	of	of	ADP
ijassa-1351	166	17	the	the	DET
ijassa-1351	166	18	random	random	ADJ
ijassa-1351	166	19	process	process	NOUN
ijassa-1351	166	20	of	of	ADP
ijassa-1351	166	21	the	the	DET
ijassa-1351	166	22	system	system	NOUN
ijassa-1351	166	23	functioning	function	VERB
ijassa-1351	166	24	and	and	CCONJ
ijassa-1351	166	25	further	further	ADJ
ijassa-1351	166	26	statistical	statistical	ADJ
ijassa-1351	166	27	processing	processing	NOUN
ijassa-1351	166	28	of	of	ADP
ijassa-1351	166	29	the	the	DET
ijassa-1351	166	30	results	result	NOUN
ijassa-1351	166	31	obtained	obtain	VERB
ijassa-1351	166	32	.	.	PUNCT
ijassa-1351	167	1	as	as	ADP
ijassa-1351	167	2	a	a	DET
ijassa-1351	167	3	result	result	NOUN
ijassa-1351	167	4	of	of	ADP
ijassa-1351	167	5	the	the	DET
ijassa-1351	167	6	fork	fork	NOUN
ijassa-1351	167	7	-	-	PUNCT
ijassa-1351	167	8	join	join	NOUN
ijassa-1351	167	9	qs	qs	PROPN
ijassa-1351	167	10	simulation	simulation	NOUN
ijassa-1351	167	11	,	,	PUNCT
ijassa-1351	167	12	we	we	PRON
ijassa-1351	167	13	can	can	AUX
ijassa-1351	167	14	get	get	VERB
ijassa-1351	167	15	a	a	DET
ijassa-1351	167	16	data	data	NOUN
ijassa-1351	167	17	set	set	VERB
ijassa-1351	167	18	or	or	CCONJ
ijassa-1351	167	19	a	a	DET
ijassa-1351	167	20	vector	vector	NOUN
ijassa-1351	167	21	,	,	PUNCT
ijassa-1351	167	22	which	which	PRON
ijassa-1351	167	23	is	be	AUX
ijassa-1351	167	24	a	a	DET
ijassa-1351	167	25	sequence	sequence	NOUN
ijassa-1351	167	26	of	of	ADP
ijassa-1351	167	27	realizations	realization	NOUN
ijassa-1351	167	28	of	of	ADP
ijassa-1351	167	29	a	a	DET
ijassa-1351	167	30	random	random	ADJ
ijassa-1351	167	31	value	value	NOUN
ijassa-1351	167	32	of	of	ADP
ijassa-1351	167	33	the	the	DET
ijassa-1351	167	34	time	time	NOUN
ijassa-1351	167	35	the	the	DET
ijassa-1351	167	36	request	request	NOUN
ijassa-1351	167	37	stays	stay	VERB
ijassa-1351	167	38	in	in	ADP
ijassa-1351	167	39	the	the	DET
ijassa-1351	167	40	system	system	NOUN
ijassa-1351	167	41	.	.	PUNCT
ijassa-1351	168	1	further	far	ADV
ijassa-1351	168	2	,	,	PUNCT
ijassa-1351	168	3	using	use	VERB
ijassa-1351	168	4	these	these	DET
ijassa-1351	168	5	data	datum	NOUN
ijassa-1351	168	6	,	,	PUNCT
ijassa-1351	168	7	it	it	PRON
ijassa-1351	168	8	is	be	AUX
ijassa-1351	168	9	necessary	necessary	ADJ
ijassa-1351	168	10	to	to	PART
ijassa-1351	168	11	construct	construct	VERB
ijassa-1351	168	12	a	a	DET
ijassa-1351	168	13	point	point	NOUN
ijassa-1351	168	14	estimate	estimate	NOUN
ijassa-1351	168	15	copyright	copyright	NOUN
ijassa-1351	168	16	©	©	ADP
ijassa-1351	168	17	2023	2023	NUM
ijassa-1351	168	18	assa	assa	NOUN
ijassa-1351	168	19	.	.	PUNCT
ijassa-1351	169	1	adv	adv	PROPN
ijassa-1351	169	2	syst	syst	PROPN
ijassa-1351	169	3	sci	sci	PROPN
ijassa-1351	169	4	appl	appl	PROPN
ijassa-1351	169	5	(	(	PUNCT
ijassa-1351	169	6	2023	2023	NUM
ijassa-1351	169	7	)	)	PUNCT
ijassa-1351	169	8	108	108	NUM
ijassa-1351	169	9	a.v	a.v	PROPN
ijassa-1351	169	10	.	.	PROPN
ijassa-1351	169	11	gorbunova	gorbunova	PROPN
ijassa-1351	169	12	,	,	PUNCT
ijassa-1351	169	13	a.v	a.v	PROPN
ijassa-1351	169	14	.	.	PROPN
ijassa-1351	169	15	lebedev	lebedev	PROPN
ijassa-1351	169	16	of	of	ADP
ijassa-1351	169	17	the	the	DET
ijassa-1351	169	18	average	average	ADJ
ijassa-1351	169	19	response	response	NOUN
ijassa-1351	169	20	time	time	NOUN
ijassa-1351	169	21	and	and	CCONJ
ijassa-1351	169	22	the	the	DET
ijassa-1351	169	23	corresponding	correspond	VERB
ijassa-1351	169	24	confidence	confidence	NOUN
ijassa-1351	169	25	interval	interval	NOUN
ijassa-1351	169	26	.	.	PUNCT
ijassa-1351	170	1	however	however	ADV
ijassa-1351	170	2	,	,	PUNCT
ijassa-1351	170	3	the	the	DET
ijassa-1351	170	4	main	main	ADJ
ijassa-1351	170	5	difficulty	difficulty	NOUN
ijassa-1351	170	6	in	in	ADP
ijassa-1351	170	7	constructing	construct	VERB
ijassa-1351	170	8	a	a	DET
ijassa-1351	170	9	confidence	confidence	NOUN
ijassa-1351	170	10	interval	interval	NOUN
ijassa-1351	170	11	is	be	AUX
ijassa-1351	170	12	that	that	SCONJ
ijassa-1351	170	13	the	the	DET
ijassa-1351	170	14	data	datum	NOUN
ijassa-1351	170	15	obtained	obtain	VERB
ijassa-1351	170	16	are	be	AUX
ijassa-1351	170	17	correlated	correlate	VERB
ijassa-1351	170	18	.	.	PUNCT
ijassa-1351	171	1	in	in	ADP
ijassa-1351	171	2	particular	particular	ADJ
ijassa-1351	171	3	,	,	PUNCT
ijassa-1351	171	4	it	it	PRON
ijassa-1351	171	5	is	be	AUX
ijassa-1351	171	6	clear	clear	ADJ
ijassa-1351	171	7	that	that	SCONJ
ijassa-1351	171	8	the	the	DET
ijassa-1351	171	9	sojourn	sojourn	NOUN
ijassa-1351	171	10	time	time	NOUN
ijassa-1351	171	11	of	of	ADP
ijassa-1351	171	12	the	the	DET
ijassa-1351	171	13	n	n	ADV
ijassa-1351	171	14	-	-	PUNCT
ijassa-1351	171	15	th	th	X
ijassa-1351	171	16	task	task	NOUN
ijassa-1351	171	17	in	in	ADP
ijassa-1351	171	18	the	the	DET
ijassa-1351	171	19	system	system	NOUN
ijassa-1351	171	20	will	will	AUX
ijassa-1351	171	21	depend	depend	VERB
ijassa-1351	171	22	on	on	ADP
ijassa-1351	171	23	the	the	DET
ijassa-1351	171	24	sojourn	sojourn	NOUN
ijassa-1351	171	25	time	time	NOUN
ijassa-1351	171	26	of	of	ADP
ijassa-1351	171	27	the	the	DET
ijassa-1351	171	28	previous	previous	ADJ
ijassa-1351	171	29	one	one	NUM
ijassa-1351	171	30	,	,	PUNCT
ijassa-1351	171	31	i.e.	i.e.	X
ijassa-1351	171	32	(	(	PUNCT
ijassa-1351	171	33	n−	n−	NOUN
ijassa-1351	171	34	1)-th	1)-th	NUM
ijassa-1351	171	35	task	task	NOUN
ijassa-1351	171	36	,	,	PUNCT
ijassa-1351	171	37	the	the	DET
ijassa-1351	171	38	sojourn	sojourn	NOUN
ijassa-1351	171	39	time	time	NOUN
ijassa-1351	171	40	of	of	ADP
ijassa-1351	171	41	which	which	PRON
ijassa-1351	171	42	,	,	PUNCT
ijassa-1351	171	43	in	in	ADP
ijassa-1351	171	44	turn	turn	NOUN
ijassa-1351	171	45	,	,	PUNCT
ijassa-1351	171	46	depends	depend	VERB
ijassa-1351	171	47	on	on	ADP
ijassa-1351	171	48	the	the	DET
ijassa-1351	171	49	sojourn	sojourn	NOUN
ijassa-1351	171	50	time	time	NOUN
ijassa-1351	171	51	of	of	ADP
ijassa-1351	171	52	the	the	DET
ijassa-1351	171	53	(	(	PUNCT
ijassa-1351	171	54	n−	n−	NOUN
ijassa-1351	171	55	2)-th	2)-th	NUM
ijassa-1351	171	56	task	task	NOUN
ijassa-1351	171	57	,	,	PUNCT
ijassa-1351	171	58	and	and	CCONJ
ijassa-1351	171	59	so	so	ADV
ijassa-1351	171	60	on	on	ADV
ijassa-1351	171	61	.	.	PUNCT
ijassa-1351	172	1	therefore	therefore	ADV
ijassa-1351	172	2	,	,	PUNCT
ijassa-1351	172	3	the	the	DET
ijassa-1351	172	4	question	question	NOUN
ijassa-1351	172	5	of	of	ADP
ijassa-1351	172	6	a	a	DET
ijassa-1351	172	7	sufficient	sufficient	ADJ
ijassa-1351	172	8	number	number	NOUN
ijassa-1351	172	9	of	of	ADP
ijassa-1351	172	10	realizations	realization	NOUN
ijassa-1351	172	11	of	of	ADP
ijassa-1351	172	12	the	the	DET
ijassa-1351	172	13	studied	study	VERB
ijassa-1351	172	14	quantity	quantity	NOUN
ijassa-1351	172	15	during	during	ADP
ijassa-1351	172	16	the	the	DET
ijassa-1351	172	17	duration	duration	NOUN
ijassa-1351	172	18	of	of	ADP
ijassa-1351	172	19	one	one	NUM
ijassa-1351	172	20	run	run	NOUN
ijassa-1351	172	21	of	of	ADP
ijassa-1351	172	22	the	the	DET
ijassa-1351	172	23	simulation	simulation	NOUN
ijassa-1351	172	24	model	model	NOUN
ijassa-1351	172	25	is	be	AUX
ijassa-1351	172	26	quite	quite	ADV
ijassa-1351	172	27	relevant	relevant	ADJ
ijassa-1351	172	28	.	.	PUNCT
ijassa-1351	173	1	of	of	ADP
ijassa-1351	173	2	course	course	NOUN
ijassa-1351	173	3	,	,	PUNCT
ijassa-1351	173	4	in	in	ADP
ijassa-1351	173	5	practice	practice	NOUN
ijassa-1351	173	6	,	,	PUNCT
ijassa-1351	173	7	it	it	PRON
ijassa-1351	173	8	is	be	AUX
ijassa-1351	173	9	possible	possible	ADJ
ijassa-1351	173	10	to	to	PART
ijassa-1351	173	11	experimentally	experimentally	ADV
ijassa-1351	173	12	determine	determine	VERB
ijassa-1351	173	13	the	the	DET
ijassa-1351	173	14	required	require	VERB
ijassa-1351	173	15	size	size	NOUN
ijassa-1351	173	16	of	of	ADP
ijassa-1351	173	17	the	the	DET
ijassa-1351	173	18	sequence	sequence	NOUN
ijassa-1351	173	19	,	,	PUNCT
ijassa-1351	173	20	gradually	gradually	ADV
ijassa-1351	173	21	increasing	increase	VERB
ijassa-1351	173	22	the	the	DET
ijassa-1351	173	23	number	number	NOUN
ijassa-1351	173	24	of	of	ADP
ijassa-1351	173	25	its	its	PRON
ijassa-1351	173	26	elements	element	NOUN
ijassa-1351	173	27	with	with	ADP
ijassa-1351	173	28	each	each	DET
ijassa-1351	173	29	run	run	NOUN
ijassa-1351	173	30	of	of	ADP
ijassa-1351	173	31	the	the	DET
ijassa-1351	173	32	model	model	NOUN
ijassa-1351	173	33	and	and	CCONJ
ijassa-1351	173	34	observing	observe	VERB
ijassa-1351	173	35	how	how	SCONJ
ijassa-1351	173	36	the	the	DET
ijassa-1351	173	37	value	value	NOUN
ijassa-1351	173	38	of	of	ADP
ijassa-1351	173	39	the	the	DET
ijassa-1351	173	40	sample	sample	NOUN
ijassa-1351	173	41	average	average	ADJ
ijassa-1351	173	42	response	response	NOUN
ijassa-1351	173	43	time	time	NOUN
ijassa-1351	173	44	changes	change	NOUN
ijassa-1351	173	45	.	.	PUNCT
ijassa-1351	174	1	if	if	SCONJ
ijassa-1351	174	2	these	these	DET
ijassa-1351	174	3	changes	change	NOUN
ijassa-1351	174	4	become	become	VERB
ijassa-1351	174	5	insignificant	insignificant	ADJ
ijassa-1351	174	6	,	,	PUNCT
ijassa-1351	174	7	the	the	DET
ijassa-1351	174	8	experiment	experiment	NOUN
ijassa-1351	174	9	is	be	AUX
ijassa-1351	174	10	stopped	stop	VERB
ijassa-1351	174	11	,	,	PUNCT
ijassa-1351	174	12	and	and	CCONJ
ijassa-1351	174	13	the	the	DET
ijassa-1351	174	14	final	final	ADJ
ijassa-1351	174	15	result	result	NOUN
ijassa-1351	174	16	is	be	AUX
ijassa-1351	174	17	chosen	choose	VERB
ijassa-1351	174	18	.	.	PUNCT
ijassa-1351	175	1	despite	despite	SCONJ
ijassa-1351	175	2	the	the	DET
ijassa-1351	175	3	fact	fact	NOUN
ijassa-1351	175	4	that	that	SCONJ
ijassa-1351	175	5	the	the	DET
ijassa-1351	175	6	described	describe	VERB
ijassa-1351	175	7	approach	approach	NOUN
ijassa-1351	175	8	to	to	ADP
ijassa-1351	175	9	determining	determine	VERB
ijassa-1351	175	10	the	the	DET
ijassa-1351	175	11	duration	duration	NOUN
ijassa-1351	175	12	of	of	ADP
ijassa-1351	175	13	the	the	DET
ijassa-1351	175	14	run	run	NOUN
ijassa-1351	175	15	of	of	ADP
ijassa-1351	175	16	the	the	DET
ijassa-1351	175	17	simulation	simulation	NOUN
ijassa-1351	175	18	model	model	NOUN
ijassa-1351	175	19	is	be	AUX
ijassa-1351	175	20	the	the	DET
ijassa-1351	175	21	most	most	ADV
ijassa-1351	175	22	common	common	ADJ
ijassa-1351	175	23	,	,	PUNCT
ijassa-1351	175	24	it	it	PRON
ijassa-1351	175	25	requires	require	VERB
ijassa-1351	175	26	a	a	DET
ijassa-1351	175	27	lot	lot	NOUN
ijassa-1351	175	28	of	of	ADP
ijassa-1351	175	29	time	time	NOUN
ijassa-1351	175	30	,	,	PUNCT
ijassa-1351	175	31	but	but	CCONJ
ijassa-1351	175	32	it	it	PRON
ijassa-1351	175	33	does	do	AUX
ijassa-1351	175	34	not	not	PART
ijassa-1351	175	35	guarantee	guarantee	VERB
ijassa-1351	175	36	the	the	DET
ijassa-1351	175	37	result	result	NOUN
ijassa-1351	175	38	due	due	ADP
ijassa-1351	175	39	to	to	ADP
ijassa-1351	175	40	the	the	DET
ijassa-1351	175	41	lack	lack	NOUN
ijassa-1351	175	42	of	of	ADP
ijassa-1351	175	43	knowledge	knowledge	NOUN
ijassa-1351	175	44	about	about	ADP
ijassa-1351	175	45	the	the	DET
ijassa-1351	175	46	confidence	confidence	NOUN
ijassa-1351	175	47	level	level	NOUN
ijassa-1351	175	48	of	of	ADP
ijassa-1351	175	49	the	the	DET
ijassa-1351	175	50	obtained	obtain	VERB
ijassa-1351	175	51	values	value	NOUN
ijassa-1351	175	52	.	.	PUNCT
ijassa-1351	176	1	therefore	therefore	ADV
ijassa-1351	176	2	,	,	PUNCT
ijassa-1351	176	3	this	this	DET
ijassa-1351	176	4	paper	paper	NOUN
ijassa-1351	176	5	proposes	propose	VERB
ijassa-1351	176	6	an	an	DET
ijassa-1351	176	7	approach	approach	NOUN
ijassa-1351	176	8	to	to	ADP
ijassa-1351	176	9	constructing	construct	VERB
ijassa-1351	176	10	confidence	confidence	NOUN
ijassa-1351	176	11	intervals	interval	NOUN
ijassa-1351	176	12	for	for	ADP
ijassa-1351	176	13	the	the	DET
ijassa-1351	176	14	average	average	ADJ
ijassa-1351	176	15	response	response	NOUN
ijassa-1351	176	16	time	time	NOUN
ijassa-1351	176	17	of	of	ADP
ijassa-1351	176	18	a	a	DET
ijassa-1351	176	19	fork	fork	NOUN
ijassa-1351	176	20	-	-	PUNCT
ijassa-1351	176	21	join	join	NOUN
ijassa-1351	176	22	qs	qs	NOUN
ijassa-1351	176	23	under	under	ADP
ijassa-1351	176	24	the	the	DET
ijassa-1351	176	25	conditions	condition	NOUN
ijassa-1351	176	26	of	of	ADP
ijassa-1351	176	27	correlation	correlation	NOUN
ijassa-1351	176	28	of	of	ADP
ijassa-1351	176	29	simulation	simulation	NOUN
ijassa-1351	176	30	data	data	PROPN
ijassa-1351	176	31	.	.	PUNCT
ijassa-1351	177	1	an	an	DET
ijassa-1351	177	2	estimate	estimate	NOUN
ijassa-1351	177	3	of	of	ADP
ijassa-1351	177	4	the	the	DET
ijassa-1351	177	5	correlation	correlation	NOUN
ijassa-1351	177	6	between	between	ADP
ijassa-1351	177	7	realizations	realization	NOUN
ijassa-1351	177	8	of	of	ADP
ijassa-1351	177	9	the	the	DET
ijassa-1351	177	10	random	random	ADJ
ijassa-1351	177	11	value	value	NOUN
ijassa-1351	177	12	of	of	ADP
ijassa-1351	177	13	the	the	DET
ijassa-1351	177	14	fork	fork	NOUN
ijassa-1351	177	15	-	-	PUNCT
ijassa-1351	177	16	join	join	VERB
ijassa-1351	177	17	response	response	NOUN
ijassa-1351	177	18	time	time	NOUN
ijassa-1351	177	19	of	of	ADP
ijassa-1351	177	20	the	the	DET
ijassa-1351	177	21	ri	ri	PROPN
ijassa-1351	177	22	system	system	NOUN
ijassa-1351	177	23	during	during	ADP
ijassa-1351	177	24	the	the	DET
ijassa-1351	177	25	duration	duration	NOUN
ijassa-1351	177	26	of	of	ADP
ijassa-1351	177	27	one	one	NUM
ijassa-1351	177	28	run	run	NOUN
ijassa-1351	177	29	,	,	PUNCT
ijassa-1351	177	30	which	which	PRON
ijassa-1351	177	31	are	be	AUX
ijassa-1351	177	32	at	at	ADP
ijassa-1351	177	33	a	a	DET
ijassa-1351	177	34	distance	distance	NOUN
ijassa-1351	177	35	of	of	ADP
ijassa-1351	177	36	n	n	CCONJ
ijassa-1351	177	37	,	,	PUNCT
ijassa-1351	177	38	n	n	NOUN
ijassa-1351	177	39	=	=	SYM
ijassa-1351	177	40	1	1	NUM
ijassa-1351	177	41	,	,	PUNCT
ijassa-1351	177	42	2	2	NUM
ijassa-1351	177	43	,	,	PUNCT
ijassa-1351	177	44	...	...	PUNCT
ijassa-1351	177	45	is	be	AUX
ijassa-1351	177	46	determined	determine	VERB
ijassa-1351	177	47	by	by	ADP
ijassa-1351	177	48	the	the	DET
ijassa-1351	177	49	expression	expression	NOUN
ijassa-1351	177	50	r̂(n	r̂(n	PUNCT
ijassa-1351	177	51	)	)	PUNCT
ijassa-1351	177	52	=	=	SYM
ijassa-1351	177	53	ê[riri+n]−	ê[riri+n]−	PROPN
ijassa-1351	177	54	ê[r]2	ê[r]2	NUM
ijassa-1351	177	55	v̂ar[r	v̂ar[r	NOUN
ijassa-1351	177	56	]	]	PUNCT
ijassa-1351	177	57	,	,	PUNCT
ijassa-1351	177	58	(	(	PUNCT
ijassa-1351	177	59	3.16	3.16	NUM
ijassa-1351	177	60	)	)	PUNCT
ijassa-1351	177	61	where	where	SCONJ
ijassa-1351	177	62	ê[riri+n	ê[riri+n	ADV
ijassa-1351	177	63	]	]	X
ijassa-1351	177	64	=	=	SYM
ijassa-1351	177	65	1	1	NUM
ijassa-1351	177	66	n	n	NUM
ijassa-1351	177	67	−	−	PROPN
ijassa-1351	177	68	n	n	CCONJ
ijassa-1351	177	69	n−n∑	n−n∑	CCONJ
ijassa-1351	177	70	i=1	i=1	PROPN
ijassa-1351	177	71	ri	ri	PROPN
ijassa-1351	177	72	·	·	PUNCT
ijassa-1351	177	73	ri+n	ri+n	PROPN
ijassa-1351	177	74	,	,	PUNCT
ijassa-1351	177	75	σ̂2	σ̂2	NOUN
ijassa-1351	177	76	=	=	SYM
ijassa-1351	177	77	v̂ar[r	v̂ar[r	PROPN
ijassa-1351	177	78	]	]	PUNCT
ijassa-1351	177	79	=	=	SYM
ijassa-1351	177	80	ê[r2]−	ê[r2]−	NOUN
ijassa-1351	177	81	ê[r]2	ê[r]2	NOUN
ijassa-1351	177	82	,	,	PUNCT
ijassa-1351	177	83	r̂	r̂	NOUN
ijassa-1351	177	84	=	=	SYM
ijassa-1351	177	85	ê[r	ê[r	NUM
ijassa-1351	177	86	]	]	PUNCT
ijassa-1351	178	1	=	=	SYM
ijassa-1351	178	2	1	1	NUM
ijassa-1351	178	3	n	n	NUM
ijassa-1351	178	4	n∑	n∑	NOUN
ijassa-1351	178	5	i=1	i=1	PROPN
ijassa-1351	178	6	ri	ri	PROPN
ijassa-1351	178	7	,	,	PUNCT
ijassa-1351	178	8	ê[r2	ê[r2	PROPN
ijassa-1351	178	9	]	]	PUNCT
ijassa-1351	178	10	=	=	SYM
ijassa-1351	178	11	1	1	NUM
ijassa-1351	178	12	n	n	NUM
ijassa-1351	178	13	n∑	n∑	NOUN
ijassa-1351	178	14	i=1	i=1	PROPN
ijassa-1351	178	15	r2	r2	PROPN
ijassa-1351	179	1	i	i	PRON
ijassa-1351	179	2	.	.	PUNCT
ijassa-1351	180	1	next	next	ADV
ijassa-1351	180	2	,	,	PUNCT
ijassa-1351	180	3	we	we	PRON
ijassa-1351	180	4	calculate	calculate	VERB
ijassa-1351	180	5	the	the	DET
ijassa-1351	180	6	variance	variance	NOUN
ijassa-1351	180	7	of	of	ADP
ijassa-1351	180	8	the	the	DET
ijassa-1351	180	9	response	response	NOUN
ijassa-1351	180	10	time	time	NOUN
ijassa-1351	180	11	estimate	estimate	NOUN
ijassa-1351	180	12	obtained	obtain	VERB
ijassa-1351	180	13	using	use	VERB
ijassa-1351	180	14	simulation	simulation	NOUN
ijassa-1351	180	15	modeling	model	VERB
ijassa-1351	180	16	var[r̂	var[r̂	PROPN
ijassa-1351	180	17	]	]	X
ijassa-1351	181	1	=	=	PUNCT
ijassa-1351	181	2	var	var	NOUN
ijassa-1351	181	3	[	[	PUNCT
ijassa-1351	181	4	1	1	NUM
ijassa-1351	181	5	n	n	NUM
ijassa-1351	181	6	n∑	n∑	NOUN
ijassa-1351	181	7	i=1	i=1	PROPN
ijassa-1351	181	8	ri	ri	X
ijassa-1351	181	9	]	]	PUNCT
ijassa-1351	181	10	=	=	SYM
ijassa-1351	181	11	1	1	NUM
ijassa-1351	181	12	n2	n2	ADJ
ijassa-1351	181	13	var	var	NOUN
ijassa-1351	181	14	[	[	PUNCT
ijassa-1351	181	15	n∑	n∑	NOUN
ijassa-1351	181	16	i=1	i=1	PROPN
ijassa-1351	181	17	ri	ri	X
ijassa-1351	181	18	]	]	PUNCT
ijassa-1351	182	1	=	=	PUNCT
ijassa-1351	182	2	=	=	SYM
ijassa-1351	182	3	1	1	NUM
ijassa-1351	182	4	n2	n2	NOUN
ijassa-1351	182	5	(	(	PUNCT
ijassa-1351	182	6	n∑	n∑	NOUN
ijassa-1351	182	7	i=1	i=1	PROPN
ijassa-1351	182	8	var[ri	var[ri	PROPN
ijassa-1351	182	9	]	]	X
ijassa-1351	182	10	+	+	CCONJ
ijassa-1351	182	11	2	2	NUM
ijassa-1351	182	12	n−1∑	n−1∑	NUM
ijassa-1351	182	13	i=1	i=1	PROPN
ijassa-1351	182	14	n∑	n∑	PROPN
ijassa-1351	182	15	j	j	PROPN
ijassa-1351	183	1	=	=	NOUN
ijassa-1351	183	2	i+1	i+1	NOUN
ijassa-1351	183	3	cov(ri	cov(ri	NOUN
ijassa-1351	183	4	,	,	PUNCT
ijassa-1351	183	5	rj	rj	PROPN
ijassa-1351	183	6	)	)	PUNCT
ijassa-1351	183	7	)	)	PUNCT
ijassa-1351	184	1	=	=	PUNCT
ijassa-1351	185	1	=	=	PUNCT
ijassa-1351	185	2	σ2	σ2	PROPN
ijassa-1351	185	3	n	n	CCONJ
ijassa-1351	185	4	(	(	PUNCT
ijassa-1351	185	5	1	1	NUM
ijassa-1351	185	6	+	+	SYM
ijassa-1351	185	7	2	2	NUM
ijassa-1351	185	8	n	n	NUM
ijassa-1351	185	9	n−1∑	n−1∑	NUM
ijassa-1351	185	10	i=1	i=1	PROPN
ijassa-1351	185	11	n∑	n∑	PROPN
ijassa-1351	185	12	j	j	PROPN
ijassa-1351	186	1	=	=	NOUN
ijassa-1351	186	2	i+1	i+1	X
ijassa-1351	186	3	corr(ri	corr(ri	NOUN
ijassa-1351	186	4	,	,	PUNCT
ijassa-1351	186	5	rj	rj	PROPN
ijassa-1351	186	6	)	)	PUNCT
ijassa-1351	186	7	)	)	PUNCT
ijassa-1351	187	1	=	=	SYM
ijassa-1351	187	2	σ2	σ2	PROPN
ijassa-1351	187	3	n	n	CCONJ
ijassa-1351	187	4	(	(	PUNCT
ijassa-1351	187	5	1	1	NUM
ijassa-1351	187	6	+	+	NUM
ijassa-1351	187	7	2∆n	2∆n	NUM
ijassa-1351	187	8	)	)	PUNCT
ijassa-1351	187	9	,	,	PUNCT
ijassa-1351	187	10	where	where	SCONJ
ijassa-1351	187	11	∆n	∆n	PROPN
ijassa-1351	187	12	=	=	SYM
ijassa-1351	187	13	1	1	NUM
ijassa-1351	187	14	n	n	NUM
ijassa-1351	187	15	n−1∑	n−1∑	NUM
ijassa-1351	187	16	i=1	i=1	PROPN
ijassa-1351	187	17	n∑	n∑	PROPN
ijassa-1351	187	18	j	j	PROPN
ijassa-1351	188	1	=	=	NOUN
ijassa-1351	188	2	i+1	i+1	X
ijassa-1351	188	3	corr(ri	corr(ri	NOUN
ijassa-1351	188	4	,	,	PUNCT
ijassa-1351	188	5	rj	rj	PROPN
ijassa-1351	188	6	)	)	PUNCT
ijassa-1351	188	7	=	=	SYM
ijassa-1351	189	1	1	1	NUM
ijassa-1351	189	2	n	n	DET
ijassa-1351	189	3	n−1∑	n−1∑	NUM
ijassa-1351	189	4	n=1	n=1	PROPN
ijassa-1351	189	5	(	(	PUNCT
ijassa-1351	189	6	n	n	CCONJ
ijassa-1351	189	7	−	−	PROPN
ijassa-1351	189	8	n)r(n	n)r(n	PROPN
ijassa-1351	189	9	)	)	PUNCT
ijassa-1351	189	10	,	,	PUNCT
ijassa-1351	189	11	r(n	r(n	PROPN
ijassa-1351	189	12	)	)	PUNCT
ijassa-1351	189	13	is	be	AUX
ijassa-1351	189	14	the	the	DET
ijassa-1351	189	15	correlation	correlation	NOUN
ijassa-1351	189	16	coefficient	coefficient	NOUN
ijassa-1351	189	17	between	between	ADP
ijassa-1351	189	18	a	a	DET
ijassa-1351	189	19	pair	pair	NOUN
ijassa-1351	189	20	of	of	ADP
ijassa-1351	189	21	elements	element	NOUN
ijassa-1351	189	22	(	(	PUNCT
ijassa-1351	189	23	response	response	NOUN
ijassa-1351	189	24	times	time	NOUN
ijassa-1351	189	25	)	)	PUNCT
ijassa-1351	189	26	separated	separate	VERB
ijassa-1351	189	27	from	from	ADP
ijassa-1351	189	28	each	each	DET
ijassa-1351	189	29	other	other	ADJ
ijassa-1351	189	30	(	(	PUNCT
ijassa-1351	189	31	according	accord	VERB
ijassa-1351	189	32	to	to	ADP
ijassa-1351	189	33	the	the	DET
ijassa-1351	189	34	numbers	number	NOUN
ijassa-1351	189	35	of	of	ADP
ijassa-1351	189	36	serviced	serviced	ADJ
ijassa-1351	189	37	tasks	task	NOUN
ijassa-1351	189	38	)	)	PUNCT
ijassa-1351	189	39	by	by	ADP
ijassa-1351	189	40	a	a	DET
ijassa-1351	189	41	distance	distance	NOUN
ijassa-1351	189	42	of	of	ADP
ijassa-1351	189	43	n.	n.	NOUN
ijassa-1351	189	44	copyright	copyright	NOUN
ijassa-1351	189	45	©	©	PROPN
ijassa-1351	189	46	2023	2023	NUM
ijassa-1351	189	47	assa	assa	NOUN
ijassa-1351	189	48	.	.	PUNCT
ijassa-1351	190	1	adv	adv	PROPN
ijassa-1351	190	2	syst	syst	PROPN
ijassa-1351	190	3	sci	sci	PROPN
ijassa-1351	190	4	appl	appl	PROPN
ijassa-1351	190	5	(	(	PUNCT
ijassa-1351	190	6	2023	2023	NUM
ijassa-1351	190	7	)	)	PUNCT
ijassa-1351	190	8	assa	assa	NOUN
ijassa-1351	190	9	latex	latex	NOUN
ijassa-1351	190	10	template	template	NOUN
ijassa-1351	190	11	109	109	NUM
ijassa-1351	190	12	then	then	ADV
ijassa-1351	190	13	∆n	∆n	PROPN
ijassa-1351	190	14	=	=	SYM
ijassa-1351	190	15	1	1	NUM
ijassa-1351	190	16	n	n	NUM
ijassa-1351	190	17	n−1∑	n−1∑	NUM
ijassa-1351	190	18	n=1	n=1	PROPN
ijassa-1351	190	19	(	(	PUNCT
ijassa-1351	190	20	n	n	CCONJ
ijassa-1351	190	21	−	−	PROPN
ijassa-1351	190	22	n)r(n	n)r(n	PROPN
ijassa-1351	190	23	)	)	PUNCT
ijassa-1351	190	24	=	=	SYM
ijassa-1351	190	25	n−1∑	n−1∑	NUM
ijassa-1351	190	26	n=1	n=1	PROPN
ijassa-1351	190	27	(	(	PUNCT
ijassa-1351	190	28	1−	1−	NUM
ijassa-1351	190	29	n	n	CCONJ
ijassa-1351	190	30	n	n	NOUN
ijassa-1351	190	31	)	)	PUNCT
ijassa-1351	190	32	r(n	r(n	ADJ
ijassa-1351	190	33	)	)	PUNCT
ijassa-1351	190	34	−−−→	−−−→	VERB
ijassa-1351	190	35	n→∞	n→∞	NUM
ijassa-1351	190	36	∞∑	∞∑	NUM
ijassa-1351	190	37	n=1	n=1	ADJ
ijassa-1351	190	38	r(n	r(n	PROPN
ijassa-1351	190	39	)	)	PUNCT
ijassa-1351	190	40	=	=	PUNCT
ijassa-1351	191	1	∆.	∆.	NOUN
ijassa-1351	191	2	the	the	DET
ijassa-1351	191	3	question	question	NOUN
ijassa-1351	191	4	arises	arise	VERB
ijassa-1351	191	5	of	of	ADP
ijassa-1351	191	6	how	how	SCONJ
ijassa-1351	191	7	to	to	PART
ijassa-1351	191	8	estimate	estimate	VERB
ijassa-1351	191	9	the	the	DET
ijassa-1351	191	10	sum	sum	NOUN
ijassa-1351	191	11	of	of	ADP
ijassa-1351	191	12	an	an	DET
ijassa-1351	191	13	infinite	infinite	ADJ
ijassa-1351	191	14	series	series	NOUN
ijassa-1351	191	15	∆	∆	PROPN
ijassa-1351	191	16	,	,	PUNCT
ijassa-1351	191	17	while	while	SCONJ
ijassa-1351	191	18	in	in	ADP
ijassa-1351	191	19	practice	practice	NOUN
ijassa-1351	191	20	,	,	PUNCT
ijassa-1351	191	21	we	we	PRON
ijassa-1351	191	22	can	can	AUX
ijassa-1351	191	23	estimate	estimate	VERB
ijassa-1351	191	24	only	only	ADV
ijassa-1351	191	25	a	a	DET
ijassa-1351	191	26	finite	finite	ADJ
ijassa-1351	191	27	number	number	NOUN
ijassa-1351	191	28	of	of	ADP
ijassa-1351	191	29	autocorrelations	autocorrelation	NOUN
ijassa-1351	191	30	r(n	r(n	PROPN
ijassa-1351	191	31	)	)	PUNCT
ijassa-1351	191	32	.	.	PUNCT
ijassa-1351	192	1	in	in	ADP
ijassa-1351	192	2	the	the	DET
ijassa-1351	192	3	dissertation	dissertation	NOUN
ijassa-1351	192	4	[	[	X
ijassa-1351	192	5	21	21	NUM
ijassa-1351	192	6	]	]	X
ijassa-1351	192	7	it	it	PRON
ijassa-1351	192	8	was	be	AUX
ijassa-1351	192	9	proposed	propose	VERB
ijassa-1351	192	10	to	to	PART
ijassa-1351	192	11	use	use	VERB
ijassa-1351	192	12	for	for	ADP
ijassa-1351	192	13	this	this	PRON
ijassa-1351	192	14	the	the	DET
ijassa-1351	192	15	exponential	exponential	ADJ
ijassa-1351	192	16	asymptotics	asymptotic	NOUN
ijassa-1351	192	17	r(n	r(n	VERB
ijassa-1351	192	18	)	)	PUNCT
ijassa-1351	192	19	∼	∼	NOUN
ijassa-1351	192	20	ae−bn	ae−bn	NOUN
ijassa-1351	192	21	,	,	PUNCT
ijassa-1351	192	22	n	n	X
ijassa-1351	192	23	→	→	SYM
ijassa-1351	192	24	∞	∞	PROPN
ijassa-1351	192	25	,	,	PUNCT
ijassa-1351	192	26	(	(	PUNCT
ijassa-1351	192	27	3.17	3.17	NUM
ijassa-1351	192	28	)	)	PUNCT
ijassa-1351	192	29	observed	observe	VERB
ijassa-1351	192	30	for	for	ADP
ijassa-1351	192	31	the	the	DET
ijassa-1351	192	32	types	type	NOUN
ijassa-1351	192	33	of	of	ADP
ijassa-1351	192	34	qs	qs	ADP
ijassa-1351	192	35	considered	consider	VERB
ijassa-1351	192	36	there	there	ADV
ijassa-1351	192	37	.	.	PUNCT
ijassa-1351	193	1	our	our	PRON
ijassa-1351	193	2	calculations	calculation	NOUN
ijassa-1351	193	3	also	also	ADV
ijassa-1351	193	4	show	show	VERB
ijassa-1351	193	5	good	good	ADJ
ijassa-1351	193	6	agreement	agreement	NOUN
ijassa-1351	193	7	with	with	ADP
ijassa-1351	193	8	the	the	DET
ijassa-1351	193	9	exponential	exponential	ADJ
ijassa-1351	193	10	law	law	NOUN
ijassa-1351	193	11	of	of	ADP
ijassa-1351	193	12	decreasing	decrease	VERB
ijassa-1351	193	13	autocorrelations	autocorrelation	NOUN
ijassa-1351	193	14	(	(	PUNCT
ijassa-1351	193	15	for	for	ADP
ijassa-1351	193	16	large	large	ADJ
ijassa-1351	193	17	ρ	ρ	NOUN
ijassa-1351	193	18	)	)	PUNCT
ijassa-1351	193	19	.	.	PUNCT
ijassa-1351	194	1	for	for	ADP
ijassa-1351	194	2	clarity	clarity	NOUN
ijassa-1351	194	3	,	,	PUNCT
ijassa-1351	194	4	the	the	DET
ijassa-1351	194	5	figure	figure	NOUN
ijassa-1351	194	6	3.8	3.8	NUM
ijassa-1351	194	7	shows	show	VERB
ijassa-1351	194	8	a	a	DET
ijassa-1351	194	9	graph	graph	NOUN
ijassa-1351	194	10	of	of	ADP
ijassa-1351	194	11	the	the	DET
ijassa-1351	194	12	dependence	dependence	NOUN
ijassa-1351	194	13	of	of	ADP
ijassa-1351	194	14	sample	sample	NOUN
ijassa-1351	194	15	autocorrelations	autocorrelation	NOUN
ijassa-1351	194	16	calculated	calculate	VERB
ijassa-1351	194	17	by	by	ADP
ijassa-1351	194	18	the	the	DET
ijassa-1351	194	19	formula	formula	NOUN
ijassa-1351	194	20	(	(	PUNCT
ijassa-1351	194	21	3.16	3.16	NUM
ijassa-1351	194	22	)	)	PUNCT
ijassa-1351	194	23	on	on	ADP
ijassa-1351	194	24	the	the	DET
ijassa-1351	194	25	step	step	NOUN
ijassa-1351	194	26	length	length	NOUN
ijassa-1351	194	27	n	n	CCONJ
ijassa-1351	194	28	at	at	ADP
ijassa-1351	194	29	ρ	ρ	PROPN
ijassa-1351	194	30	=	=	SYM
ijassa-1351	194	31	0.7	0.7	NUM
ijassa-1351	194	32	.	.	NOUN
ijassa-1351	194	33	0	0	NUM
ijassa-1351	194	34	0.1	0.1	NUM
ijassa-1351	194	35	0.2	0.2	NUM
ijassa-1351	194	36	0.3	0.3	NUM
ijassa-1351	194	37	0.4	0.4	NUM
ijassa-1351	194	38	0.5	0.5	NUM
ijassa-1351	194	39	0.6	0.6	NUM
ijassa-1351	194	40	0.7	0.7	NUM
ijassa-1351	194	41	0.8	0.8	NUM
ijassa-1351	194	42	0.9	0.9	NUM
ijassa-1351	194	43	1	1	NUM
ijassa-1351	194	44	0	0	NUM
ijassa-1351	194	45	20	20	NUM
ijassa-1351	194	46	40	40	NUM
ijassa-1351	194	47	60	60	NUM
ijassa-1351	194	48	80	80	NUM
ijassa-1351	194	49	100	100	NUM
ijassa-1351	194	50	r	r	NOUN
ijassa-1351	194	51	(	(	PUNCT
ijassa-1351	194	52	n	n	NOUN
ijassa-1351	194	53	)	)	PUNCT
ijassa-1351	194	54	n	n	CCONJ
ijassa-1351	194	55	k=2	k=2	PROPN
ijassa-1351	194	56	k=10	k=10	PROPN
ijassa-1351	194	57	k=20	k=20	PROPN
ijassa-1351	194	58	fig	fig	PROPN
ijassa-1351	194	59	.	.	PUNCT
ijassa-1351	195	1	3.8	3.8	NUM
ijassa-1351	195	2	.	.	PUNCT
ijassa-1351	196	1	correlation	correlation	NOUN
ijassa-1351	196	2	coefficient	coefficient	NOUN
ijassa-1351	196	3	between	between	ADP
ijassa-1351	196	4	the	the	DET
ijassa-1351	196	5	sojourn	sojourn	NOUN
ijassa-1351	196	6	times	time	NOUN
ijassa-1351	196	7	of	of	ADP
ijassa-1351	196	8	i	i	PROPN
ijassa-1351	196	9	-	-	PUNCT
ijassa-1351	196	10	th	th	X
ijassa-1351	196	11	and	and	CCONJ
ijassa-1351	196	12	(	(	PUNCT
ijassa-1351	196	13	i+	i+	NOUN
ijassa-1351	196	14	n)-th	n)-th	PROPN
ijassa-1351	196	15	tasks	task	NOUN
ijassa-1351	196	16	in	in	ADP
ijassa-1351	196	17	the	the	DET
ijassa-1351	196	18	system	system	NOUN
ijassa-1351	196	19	,	,	PUNCT
ijassa-1351	196	20	ρ	ρ	PROPN
ijassa-1351	196	21	=	=	SYM
ijassa-1351	196	22	0.7	0.7	NUM
ijassa-1351	196	23	,	,	PUNCT
ijassa-1351	196	24	n	n	NOUN
ijassa-1351	196	25	=	=	SYM
ijassa-1351	196	26	1	1	NUM
ijassa-1351	196	27	,	,	PUNCT
ijassa-1351	196	28	2	2	NUM
ijassa-1351	196	29	,	,	PUNCT
ijassa-1351	196	30	...	...	PUNCT
ijassa-1351	197	1	100	100	NUM
ijassa-1351	197	2	.	.	PUNCT
ijassa-1351	198	1	we	we	PRON
ijassa-1351	198	2	can	can	AUX
ijassa-1351	198	3	now	now	ADV
ijassa-1351	198	4	estimate	estimate	VERB
ijassa-1351	198	5	∆	∆	PROPN
ijassa-1351	198	6	by	by	ADP
ijassa-1351	198	7	calculating	calculate	VERB
ijassa-1351	198	8	the	the	DET
ijassa-1351	198	9	values	value	NOUN
ijassa-1351	198	10	of	of	ADP
ijassa-1351	198	11	r̂(n	r̂(n	NOUN
ijassa-1351	198	12	)	)	PUNCT
ijassa-1351	198	13	using	use	VERB
ijassa-1351	198	14	simulation	simulation	NOUN
ijassa-1351	198	15	for	for	ADP
ijassa-1351	198	16	a	a	DET
ijassa-1351	198	17	finite	finite	ADJ
ijassa-1351	198	18	number	number	NOUN
ijassa-1351	198	19	of	of	ADP
ijassa-1351	198	20	steps	step	NOUN
ijassa-1351	198	21	,	,	PUNCT
ijassa-1351	198	22	i.e.	i.e.	X
ijassa-1351	198	23	for	for	ADP
ijassa-1351	198	24	n	n	NOUN
ijassa-1351	198	25	=	=	SYM
ijassa-1351	198	26	1	1	NUM
ijassa-1351	198	27	,	,	PUNCT
ijassa-1351	198	28	2	2	NUM
ijassa-1351	198	29	,	,	PUNCT
ijassa-1351	198	30	...	...	PUNCT
ijassa-1351	198	31	,	,	PUNCT
ijassa-1351	198	32	m	m	PROPN
ijassa-1351	198	33	,	,	PUNCT
ijassa-1351	198	34	∆	∆	PROPN
ijassa-1351	198	35	=	=	PUNCT
ijassa-1351	199	1	+	+	ADJ
ijassa-1351	199	2	∞∑	∞∑	NUM
ijassa-1351	199	3	n=1	n=1	ADP
ijassa-1351	199	4	r(n	r(n	PROPN
ijassa-1351	199	5	)	)	PUNCT
ijassa-1351	199	6	=	=	PUNCT
ijassa-1351	199	7	m∑	m∑	NOUN
ijassa-1351	199	8	n=1	n=1	PROPN
ijassa-1351	199	9	r(n	r(n	PROPN
ijassa-1351	199	10	)	)	PUNCT
ijassa-1351	200	1	+	+	PUNCT
ijassa-1351	201	1	+	+	PUNCT
ijassa-1351	201	2	∞∑	∞∑	NUM
ijassa-1351	201	3	n	n	CCONJ
ijassa-1351	201	4	=	=	NOUN
ijassa-1351	201	5	m+1	m+1	NUM
ijassa-1351	201	6	r(n	r(n	PROPN
ijassa-1351	201	7	)	)	PUNCT
ijassa-1351	201	8	,	,	PUNCT
ijassa-1351	201	9	(	(	PUNCT
ijassa-1351	201	10	3.18	3.18	NUM
ijassa-1351	201	11	)	)	PUNCT
ijassa-1351	201	12	taking	take	VERB
ijassa-1351	201	13	into	into	ADP
ijassa-1351	201	14	account	account	NOUN
ijassa-1351	201	15	the	the	DET
ijassa-1351	201	16	fact	fact	NOUN
ijassa-1351	201	17	that	that	SCONJ
ijassa-1351	201	18	due	due	ADP
ijassa-1351	201	19	to	to	ADP
ijassa-1351	201	20	(	(	PUNCT
ijassa-1351	201	21	3.17	3.17	NUM
ijassa-1351	201	22	)	)	PUNCT
ijassa-1351	201	23	it	it	PRON
ijassa-1351	201	24	is	be	AUX
ijassa-1351	201	25	true	true	ADJ
ijassa-1351	201	26	+	+	PROPN
ijassa-1351	201	27	∞∑	∞∑	NUM
ijassa-1351	201	28	n	n	CCONJ
ijassa-1351	201	29	=	=	NOUN
ijassa-1351	201	30	m+1	m+1	ADJ
ijassa-1351	201	31	r(n	r(n	PROPN
ijassa-1351	201	32	)	)	PUNCT
ijassa-1351	201	33	∼	∼	NOUN
ijassa-1351	201	34	a	a	DET
ijassa-1351	201	35	e−b(m+1	e−b(m+1	NOUN
ijassa-1351	201	36	)	)	PUNCT
ijassa-1351	201	37	1−	1−	NUM
ijassa-1351	201	38	e−b	e−b	PROPN
ijassa-1351	201	39	,	,	PUNCT
ijassa-1351	201	40	m	m	PROPN
ijassa-1351	201	41	→	→	SYM
ijassa-1351	201	42	∞.	∞.	PROPN
ijassa-1351	201	43	(	(	PUNCT
ijassa-1351	201	44	3.19	3.19	NUM
ijassa-1351	201	45	)	)	PUNCT
ijassa-1351	201	46	two	two	NUM
ijassa-1351	201	47	situations	situation	NOUN
ijassa-1351	201	48	are	be	AUX
ijassa-1351	201	49	possible	possible	ADJ
ijassa-1351	201	50	.	.	PUNCT
ijassa-1351	202	1	we	we	PRON
ijassa-1351	202	2	sum	sum	VERB
ijassa-1351	202	3	r̂(n	r̂(n	NOUN
ijassa-1351	202	4	)	)	PUNCT
ijassa-1351	202	5	as	as	ADV
ijassa-1351	202	6	long	long	ADV
ijassa-1351	202	7	as	as	SCONJ
ijassa-1351	202	8	it	it	PRON
ijassa-1351	202	9	is	be	AUX
ijassa-1351	202	10	true	true	ADJ
ijassa-1351	202	11	that	that	SCONJ
ijassa-1351	202	12	r̂(n	r̂(n	PROPN
ijassa-1351	202	13	)	)	PUNCT
ijassa-1351	202	14	⩾	⩾	PROPN
ijassa-1351	203	1	2/	2/	NUM
ijassa-1351	203	2	√	√	NUM
ijassa-1351	203	3	n	n	CCONJ
ijassa-1351	203	4	,	,	PUNCT
ijassa-1351	203	5	otherwise	otherwise	ADV
ijassa-1351	203	6	we	we	PRON
ijassa-1351	203	7	calculate	calculate	VERB
ijassa-1351	203	8	the	the	DET
ijassa-1351	203	9	values	value	NOUN
ijassa-1351	203	10	of	of	ADP
ijassa-1351	203	11	r̂(n	r̂(n	NOUN
ijassa-1351	203	12	)	)	PUNCT
ijassa-1351	203	13	statistically	statistically	ADV
ijassa-1351	203	14	not	not	PART
ijassa-1351	203	15	significant	significant	ADJ
ijassa-1351	203	16	.	.	PUNCT
ijassa-1351	204	1	in	in	ADP
ijassa-1351	204	2	the	the	DET
ijassa-1351	204	3	first	first	ADJ
ijassa-1351	204	4	case	case	NOUN
ijassa-1351	204	5	,	,	PUNCT
ijassa-1351	204	6	the	the	DET
ijassa-1351	204	7	number	number	NOUN
ijassa-1351	204	8	copyright	copyright	NOUN
ijassa-1351	204	9	©	©	PROPN
ijassa-1351	204	10	2023	2023	NUM
ijassa-1351	204	11	assa	assa	NOUN
ijassa-1351	204	12	.	.	PUNCT
ijassa-1351	205	1	adv	adv	PROPN
ijassa-1351	205	2	syst	syst	PROPN
ijassa-1351	205	3	sci	sci	PROPN
ijassa-1351	205	4	appl	appl	PROPN
ijassa-1351	205	5	(	(	PUNCT
ijassa-1351	205	6	2023	2023	NUM
ijassa-1351	205	7	)	)	PUNCT
ijassa-1351	205	8	110	110	NUM
ijassa-1351	205	9	a.v	a.v	PROPN
ijassa-1351	205	10	.	.	PROPN
ijassa-1351	205	11	gorbunova	gorbunova	PROPN
ijassa-1351	205	12	,	,	PUNCT
ijassa-1351	205	13	a.v	a.v	PROPN
ijassa-1351	205	14	.	.	PROPN
ijassa-1351	205	15	lebedev	lebedev	PROPN
ijassa-1351	205	16	of	of	ADP
ijassa-1351	205	17	obtained	obtain	VERB
ijassa-1351	205	18	elements	element	NOUN
ijassa-1351	205	19	r̂(n	r̂(n	NOUN
ijassa-1351	205	20	)	)	PUNCT
ijassa-1351	205	21	,	,	PUNCT
ijassa-1351	205	22	n	n	NOUN
ijassa-1351	205	23	=	=	SYM
ijassa-1351	205	24	1	1	NUM
ijassa-1351	205	25	,	,	PUNCT
ijassa-1351	205	26	2	2	NUM
ijassa-1351	205	27	,	,	PUNCT
ijassa-1351	205	28	...	...	PUNCT
ijassa-1351	205	29	,	,	PUNCT
ijassa-1351	205	30	m	m	PROPN
ijassa-1351	205	31	,	,	PUNCT
ijassa-1351	205	32	may	may	AUX
ijassa-1351	205	33	be	be	AUX
ijassa-1351	205	34	sufficient	sufficient	ADJ
ijassa-1351	205	35	for	for	ADP
ijassa-1351	205	36	summation	summation	NOUN
ijassa-1351	205	37	,	,	PUNCT
ijassa-1351	205	38	i.e.	i.e.	X
ijassa-1351	205	39	,	,	PUNCT
ijassa-1351	205	40	r̂(m	r̂(m	ADJ
ijassa-1351	205	41	)	)	PUNCT
ijassa-1351	205	42	<	<	X
ijassa-1351	205	43	2/	2/	NUM
ijassa-1351	205	44	sqrtn	sqrtn	NOUN
ijassa-1351	205	45	.	.	PUNCT
ijassa-1351	206	1	otherwise	otherwise	ADV
ijassa-1351	206	2	,	,	PUNCT
ijassa-1351	206	3	when	when	SCONJ
ijassa-1351	206	4	r̂(m	r̂(m	ADP
ijassa-1351	206	5	)	)	PUNCT
ijassa-1351	206	6	⩾	⩾	PROPN
ijassa-1351	206	7	2/	2/	NUM
ijassa-1351	206	8	√	√	NUM
ijassa-1351	206	9	n	n	NOUN
ijassa-1351	206	10	,	,	PUNCT
ijassa-1351	206	11	we	we	PRON
ijassa-1351	206	12	will	will	AUX
ijassa-1351	206	13	need	need	VERB
ijassa-1351	206	14	to	to	PART
ijassa-1351	206	15	estimate	estimate	VERB
ijassa-1351	206	16	summation	summation	NOUN
ijassa-1351	206	17	residuals	residual	NOUN
ijassa-1351	206	18	for	for	ADP
ijassa-1351	206	19	n	n	NUM
ijassa-1351	206	20	from	from	ADP
ijassa-1351	206	21	(	(	PUNCT
ijassa-1351	206	22	m+	m+	NOUN
ijassa-1351	206	23	1	1	NUM
ijassa-1351	206	24	)	)	PUNCT
ijassa-1351	206	25	to	to	ADP
ijassa-1351	206	26	+	+	NOUN
ijassa-1351	206	27	∞	∞	PROPN
ijassa-1351	206	28	from	from	ADP
ijassa-1351	206	29	(	(	PUNCT
ijassa-1351	206	30	3.19	3.19	NUM
ijassa-1351	206	31	)	)	PUNCT
ijassa-1351	206	32	.	.	PUNCT
ijassa-1351	207	1	this	this	PRON
ijassa-1351	207	2	can	can	AUX
ijassa-1351	207	3	be	be	AUX
ijassa-1351	207	4	done	do	VERB
ijassa-1351	207	5	by	by	ADP
ijassa-1351	207	6	building	build	VERB
ijassa-1351	207	7	a	a	DET
ijassa-1351	207	8	regression	regression	NOUN
ijassa-1351	207	9	model	model	NOUN
ijassa-1351	207	10	.	.	PUNCT
ijassa-1351	208	1	we	we	PRON
ijassa-1351	208	2	add	add	VERB
ijassa-1351	208	3	the	the	DET
ijassa-1351	208	4	resulting	result	VERB
ijassa-1351	208	5	estimate	estimate	NOUN
ijassa-1351	208	6	for	for	ADP
ijassa-1351	208	7	the	the	DET
ijassa-1351	208	8	tail	tail	NOUN
ijassa-1351	208	9	of	of	ADP
ijassa-1351	208	10	the	the	DET
ijassa-1351	208	11	sum	sum	NOUN
ijassa-1351	208	12	to	to	ADP
ijassa-1351	208	13	the	the	DET
ijassa-1351	208	14	sum	sum	NOUN
ijassa-1351	208	15	over	over	ADP
ijassa-1351	208	16	n	n	ADV
ijassa-1351	208	17	from	from	ADP
ijassa-1351	208	18	1	1	NUM
ijassa-1351	208	19	to	to	PART
ijassa-1351	208	20	m.	m.	NOUN
ijassa-1351	208	21	as	as	ADP
ijassa-1351	208	22	a	a	DET
ijassa-1351	208	23	result	result	NOUN
ijassa-1351	208	24	of	of	ADP
ijassa-1351	208	25	the	the	DET
ijassa-1351	208	26	described	describe	VERB
ijassa-1351	208	27	actions	action	NOUN
ijassa-1351	208	28	,	,	PUNCT
ijassa-1351	208	29	we	we	PRON
ijassa-1351	208	30	will	will	AUX
ijassa-1351	208	31	calculate	calculate	VERB
ijassa-1351	208	32	some	some	DET
ijassa-1351	208	33	estimate	estimate	NOUN
ijassa-1351	208	34	∆̂	∆̂	NOUN
ijassa-1351	208	35	for	for	ADP
ijassa-1351	208	36	∆	∆	PROPN
ijassa-1351	208	37	from	from	ADP
ijassa-1351	208	38	(	(	PUNCT
ijassa-1351	208	39	3.18	3.18	NUM
ijassa-1351	208	40	)	)	PUNCT
ijassa-1351	208	41	.	.	PUNCT
ijassa-1351	209	1	thus	thus	ADV
ijassa-1351	209	2	,	,	PUNCT
ijassa-1351	209	3	for	for	ADP
ijassa-1351	209	4	specific	specific	ADJ
ijassa-1351	209	5	values	value	NOUN
ijassa-1351	209	6	of	of	ADP
ijassa-1351	209	7	the	the	DET
ijassa-1351	209	8	parameters	parameter	NOUN
ijassa-1351	209	9	of	of	ADP
ijassa-1351	209	10	the	the	DET
ijassa-1351	209	11	system	system	NOUN
ijassa-1351	209	12	under	under	ADP
ijassa-1351	209	13	consideration	consideration	NOUN
ijassa-1351	209	14	,	,	PUNCT
ijassa-1351	209	15	for	for	ADP
ijassa-1351	209	16	example	example	NOUN
ijassa-1351	209	17	,	,	PUNCT
ijassa-1351	209	18	for	for	ADP
ijassa-1351	209	19	a	a	DET
ijassa-1351	209	20	certain	certain	ADJ
ijassa-1351	209	21	value	value	NOUN
ijassa-1351	209	22	of	of	ADP
ijassa-1351	209	23	the	the	DET
ijassa-1351	209	24	load	load	NOUN
ijassa-1351	209	25	factor	factor	NOUN
ijassa-1351	209	26	ρ	ρ	PROPN
ijassa-1351	209	27	and	and	CCONJ
ijassa-1351	209	28	the	the	DET
ijassa-1351	209	29	number	number	NOUN
ijassa-1351	209	30	of	of	ADP
ijassa-1351	209	31	subsystems	subsystem	NOUN
ijassa-1351	209	32	k	k	X
ijassa-1351	209	33	:	:	PUNCT
ijassa-1351	209	34	1	1	X
ijassa-1351	209	35	.	.	X
ijassa-1351	209	36	choose	choose	VERB
ijassa-1351	209	37	some	some	DET
ijassa-1351	209	38	value	value	NOUN
ijassa-1351	209	39	m	m	NOUN
ijassa-1351	209	40	;	;	PUNCT
ijassa-1351	209	41	2	2	X
ijassa-1351	209	42	.	.	PUNCT
ijassa-1351	209	43	based	base	VERB
ijassa-1351	209	44	on	on	ADP
ijassa-1351	209	45	the	the	DET
ijassa-1351	209	46	simulation	simulation	NOUN
ijassa-1351	209	47	results	result	VERB
ijassa-1351	209	48	for	for	ADP
ijassa-1351	209	49	a	a	DET
ijassa-1351	209	50	large	large	ADJ
ijassa-1351	209	51	number	number	NOUN
ijassa-1351	209	52	of	of	ADP
ijassa-1351	209	53	implementations	implementation	NOUN
ijassa-1351	209	54	n	n	CCONJ
ijassa-1351	209	55	,	,	PUNCT
ijassa-1351	209	56	we	we	PRON
ijassa-1351	209	57	calculate	calculate	VERB
ijassa-1351	209	58	the	the	DET
ijassa-1351	209	59	set	set	NOUN
ijassa-1351	209	60	of	of	ADP
ijassa-1351	209	61	values	value	NOUN
ijassa-1351	209	62	r̂(n	r̂(n	ADJ
ijassa-1351	209	63	)	)	PUNCT
ijassa-1351	209	64	using	use	VERB
ijassa-1351	209	65	the	the	DET
ijassa-1351	209	66	formula	formula	NOUN
ijassa-1351	209	67	(	(	PUNCT
ijassa-1351	209	68	3.16	3.16	NUM
ijassa-1351	209	69	)	)	PUNCT
ijassa-1351	209	70	,	,	PUNCT
ijassa-1351	209	71	n	n	NOUN
ijassa-1351	209	72	=	=	SYM
ijassa-1351	209	73	1	1	NUM
ijassa-1351	209	74	,	,	PUNCT
ijassa-1351	209	75	2	2	NUM
ijassa-1351	209	76	,	,	PUNCT
ijassa-1351	209	77	...	...	PUNCT
ijassa-1351	209	78	m	m	X
ijassa-1351	209	79	;	;	PUNCT
ijassa-1351	209	80	3	3	X
ijassa-1351	209	81	.	.	X
ijassa-1351	209	82	sum	sum	VERB
ijassa-1351	209	83	the	the	DET
ijassa-1351	209	84	elements	element	NOUN
ijassa-1351	209	85	of	of	ADP
ijassa-1351	209	86	r̂(n	r̂(n	NOUN
ijassa-1351	209	87	)	)	PUNCT
ijassa-1351	209	88	until	until	ADP
ijassa-1351	209	89	r̂(n	r̂(n	PROPN
ijassa-1351	209	90	)	)	PUNCT
ijassa-1351	209	91	<	<	X
ijassa-1351	209	92	2/	2/	NUM
ijassa-1351	209	93	√	√	NUM
ijassa-1351	209	94	n	n	NOUN
ijassa-1351	209	95	,	,	PUNCT
ijassa-1351	209	96	n	n	NOUN
ijassa-1351	209	97	=	=	SYM
ijassa-1351	209	98	1	1	NUM
ijassa-1351	209	99	,	,	PUNCT
ijassa-1351	209	100	2	2	NUM
ijassa-1351	209	101	,	,	PUNCT
ijassa-1351	209	102	...	...	PUNCT
ijassa-1351	209	103	m	m	X
ijassa-1351	209	104	;	;	PUNCT
ijassa-1351	209	105	4	4	X
ijassa-1351	209	106	.	.	X
ijassa-1351	210	1	if	if	SCONJ
ijassa-1351	210	2	r̂(m	r̂(m	ADP
ijassa-1351	210	3	)	)	PUNCT
ijassa-1351	210	4	⩾	⩾	PROPN
ijassa-1351	211	1	2/	2/	NUM
ijassa-1351	211	2	√	√	NUM
ijassa-1351	211	3	n	n	PRON
ijassa-1351	211	4	1	1	NUM
ijassa-1351	211	5	)	)	PUNCT
ijassa-1351	211	6	we	we	PRON
ijassa-1351	211	7	build	build	VERB
ijassa-1351	211	8	a	a	DET
ijassa-1351	211	9	regression	regression	NOUN
ijassa-1351	211	10	model	model	NOUN
ijassa-1351	211	11	of	of	ADP
ijassa-1351	211	12	the	the	DET
ijassa-1351	211	13	form	form	NOUN
ijassa-1351	211	14	(	(	PUNCT
ijassa-1351	211	15	3.17	3.17	NUM
ijassa-1351	211	16	)	)	PUNCT
ijassa-1351	211	17	,	,	PUNCT
ijassa-1351	211	18	which	which	PRON
ijassa-1351	211	19	is	be	AUX
ijassa-1351	211	20	reduced	reduce	VERB
ijassa-1351	211	21	to	to	ADP
ijassa-1351	211	22	a	a	DET
ijassa-1351	211	23	linear	linear	ADJ
ijassa-1351	211	24	one	one	NUM
ijassa-1351	211	25	by	by	ADP
ijassa-1351	211	26	taking	take	VERB
ijassa-1351	211	27	the	the	DET
ijassa-1351	211	28	logarithm	logarithm	NOUN
ijassa-1351	211	29	of	of	ADP
ijassa-1351	211	30	both	both	DET
ijassa-1351	211	31	parts	part	NOUN
ijassa-1351	211	32	of	of	ADP
ijassa-1351	211	33	the	the	DET
ijassa-1351	211	34	expression	expression	NOUN
ijassa-1351	211	35	:	:	PUNCT
ijassa-1351	211	36	ln	ln	PROPN
ijassa-1351	211	37	r(n	r(n	PROPN
ijassa-1351	211	38	)	)	PUNCT
ijassa-1351	211	39	=	=	SYM
ijassa-1351	211	40	ln	ln	ADJ
ijassa-1351	211	41	a−	a−	PROPN
ijassa-1351	211	42	bn+	bn+	NOUN
ijassa-1351	211	43	ε	ε	PROPN
ijassa-1351	211	44	(	(	PUNCT
ijassa-1351	211	45	ε	ε	PROPN
ijassa-1351	211	46	—	—	PUNCT
ijassa-1351	211	47	random	random	ADJ
ijassa-1351	211	48	error	error	NOUN
ijassa-1351	211	49	of	of	ADP
ijassa-1351	211	50	the	the	DET
ijassa-1351	211	51	model	model	NOUN
ijassa-1351	211	52	)	)	PUNCT
ijassa-1351	211	53	;	;	PUNCT
ijassa-1351	211	54	2	2	X
ijassa-1351	211	55	)	)	PUNCT
ijassa-1351	211	56	estimate	estimate	VERB
ijassa-1351	211	57	the	the	DET
ijassa-1351	211	58	parameters	parameter	NOUN
ijassa-1351	211	59	a	a	PRON
ijassa-1351	211	60	and	and	CCONJ
ijassa-1351	211	61	b	b	NOUN
ijassa-1351	211	62	of	of	ADP
ijassa-1351	211	63	the	the	DET
ijassa-1351	211	64	constructed	construct	VERB
ijassa-1351	211	65	regression	regression	NOUN
ijassa-1351	211	66	model	model	NOUN
ijassa-1351	211	67	using	use	VERB
ijassa-1351	211	68	the	the	DET
ijassa-1351	211	69	least	least	ADJ
ijassa-1351	211	70	squares	square	NOUN
ijassa-1351	211	71	method	method	NOUN
ijassa-1351	211	72	;	;	PUNCT
ijassa-1351	211	73	3	3	X
ijassa-1351	211	74	)	)	PUNCT
ijassa-1351	211	75	calculate	calculate	VERB
ijassa-1351	211	76	the	the	DET
ijassa-1351	211	77	estimate	estimate	NOUN
ijassa-1351	211	78	of	of	ADP
ijassa-1351	211	79	the	the	DET
ijassa-1351	211	80	summation	summation	NOUN
ijassa-1351	211	81	tail	tail	NOUN
ijassa-1351	211	82	by	by	ADP
ijassa-1351	211	83	the	the	DET
ijassa-1351	211	84	formula	formula	NOUN
ijassa-1351	211	85	(	(	PUNCT
ijassa-1351	211	86	3.19	3.19	NUM
ijassa-1351	211	87	)	)	PUNCT
ijassa-1351	211	88	,	,	PUNCT
ijassa-1351	211	89	substituting	substitute	VERB
ijassa-1351	211	90	into	into	ADP
ijassa-1351	211	91	it	it	PRON
ijassa-1351	211	92	the	the	DET
ijassa-1351	211	93	values	value	NOUN
ijassa-1351	211	94	of	of	ADP
ijassa-1351	211	95	the	the	DET
ijassa-1351	211	96	obtained	obtain	VERB
ijassa-1351	211	97	estimates	estimate	NOUN
ijassa-1351	211	98	of	of	ADP
ijassa-1351	211	99	the	the	DET
ijassa-1351	211	100	regression	regression	NOUN
ijassa-1351	211	101	parameters	parameter	NOUN
ijassa-1351	211	102	a	a	PRON
ijassa-1351	211	103	and	and	CCONJ
ijassa-1351	211	104	b	b	NOUN
ijassa-1351	211	105	,	,	PUNCT
ijassa-1351	211	106	as	as	ADV
ijassa-1351	211	107	well	well	ADV
ijassa-1351	211	108	as	as	ADP
ijassa-1351	211	109	m	m	NOUN
ijassa-1351	211	110	;	;	PUNCT
ijassa-1351	211	111	4	4	X
ijassa-1351	211	112	)	)	PUNCT
ijassa-1351	211	113	calculate	calculate	VERB
ijassa-1351	211	114	the	the	DET
ijassa-1351	211	115	estimate	estimate	NOUN
ijassa-1351	211	116	∆	∆	PROPN
ijassa-1351	211	117	according	accord	VERB
ijassa-1351	211	118	to	to	ADP
ijassa-1351	211	119	the	the	DET
ijassa-1351	211	120	formula	formula	NOUN
ijassa-1351	211	121	(	(	PUNCT
ijassa-1351	211	122	3.18	3.18	NUM
ijassa-1351	211	123	)	)	PUNCT
ijassa-1351	211	124	,	,	PUNCT
ijassa-1351	211	125	substituting	substitute	VERB
ijassa-1351	211	126	the	the	DET
ijassa-1351	211	127	corresponding	correspond	VERB
ijassa-1351	211	128	values	value	NOUN
ijassa-1351	211	129	into	into	ADP
ijassa-1351	211	130	it	it	PRON
ijassa-1351	211	131	∆̂	∆̂	NOUN
ijassa-1351	211	132	=	=	PUNCT
ijassa-1351	211	133	m∑	m∑	NOUN
ijassa-1351	211	134	n=1	n=1	PUNCT
ijassa-1351	211	135	r̂(n	r̂(n	PROPN
ijassa-1351	211	136	)	)	PUNCT
ijassa-1351	211	137	+	+	NUM
ijassa-1351	211	138	â	â	X
ijassa-1351	211	139	e−b̂(m+1	e−b̂(m+1	NOUN
ijassa-1351	211	140	)	)	PUNCT
ijassa-1351	211	141	1−	1−	NUM
ijassa-1351	211	142	e−b̂	e−b̂	ADJ
ijassa-1351	211	143	;	;	PUNCT
ijassa-1351	211	144	5	5	X
ijassa-1351	211	145	.	.	X
ijassa-1351	212	1	if	if	SCONJ
ijassa-1351	212	2	r̂(n∗	r̂(n∗	VERB
ijassa-1351	212	3	+	+	NOUN
ijassa-1351	212	4	1	1	X
ijassa-1351	212	5	)	)	PUNCT
ijassa-1351	212	6	<	<	X
ijassa-1351	212	7	2/	2/	NUM
ijassa-1351	212	8	√	√	NUM
ijassa-1351	212	9	n	n	NUM
ijassa-1351	212	10	,	,	PUNCT
ijassa-1351	212	11	and	and	CCONJ
ijassa-1351	212	12	n∗	n∗	PROPN
ijassa-1351	212	13	⩽	⩽	PROPN
ijassa-1351	212	14	m	m	PROPN
ijassa-1351	212	15	,	,	PUNCT
ijassa-1351	212	16	we	we	PRON
ijassa-1351	212	17	get	get	VERB
ijassa-1351	212	18	the	the	DET
ijassa-1351	212	19	estimate	estimate	NOUN
ijassa-1351	212	20	∆̂	∆̂	NOUN
ijassa-1351	212	21	=	=	SYM
ijassa-1351	212	22	n∗∑	n∗∑	NUM
ijassa-1351	212	23	n=1	n=1	PROPN
ijassa-1351	212	24	r̂(n	r̂(n	PROPN
ijassa-1351	212	25	)	)	PUNCT
ijassa-1351	212	26	.	.	PUNCT
ijassa-1351	213	1	due	due	ADP
ijassa-1351	213	2	to	to	ADP
ijassa-1351	213	3	the	the	DET
ijassa-1351	213	4	asymptotic	asymptotic	ADJ
ijassa-1351	213	5	normality	normality	NOUN
ijassa-1351	213	6	of	of	ADP
ijassa-1351	213	7	the	the	DET
ijassa-1351	213	8	estimate	estimate	NOUN
ijassa-1351	213	9	of	of	ADP
ijassa-1351	213	10	the	the	DET
ijassa-1351	213	11	mean	mean	NOUN
ijassa-1351	213	12	,	,	PUNCT
ijassa-1351	213	13	we	we	PRON
ijassa-1351	213	14	can	can	AUX
ijassa-1351	213	15	build	build	VERB
ijassa-1351	213	16	asymptotic	asymptotic	ADJ
ijassa-1351	213	17	confidence	confidence	NOUN
ijassa-1351	213	18	intervals	interval	NOUN
ijassa-1351	213	19	for	for	ADP
ijassa-1351	213	20	arbitrary	arbitrary	ADJ
ijassa-1351	213	21	levels	level	NOUN
ijassa-1351	213	22	of	of	ADP
ijassa-1351	213	23	reliability	reliability	NOUN
ijassa-1351	213	24	,	,	PUNCT
ijassa-1351	213	25	for	for	ADP
ijassa-1351	213	26	example	example	NOUN
ijassa-1351	213	27	,	,	PUNCT
ijassa-1351	213	28	by	by	ADP
ijassa-1351	213	29	applying	apply	VERB
ijassa-1351	213	30	the	the	DET
ijassa-1351	213	31	“	"	PUNCT
ijassa-1351	213	32	three	three	NUM
ijassa-1351	213	33	sigma	sigma	NOUN
ijassa-1351	213	34	”	"	PUNCT
ijassa-1351	213	35	rule	rule	NOUN
ijassa-1351	213	36	.	.	PUNCT
ijassa-1351	214	1	then	then	ADV
ijassa-1351	214	2	with	with	ADP
ijassa-1351	214	3	probability	probability	NOUN
ijassa-1351	214	4	p	p	X
ijassa-1351	214	5	=	=	PROPN
ijassa-1351	214	6	0.997	0.997	NUM
ijassa-1351	214	7	,	,	PUNCT
ijassa-1351	214	8	it	it	PRON
ijassa-1351	214	9	will	will	AUX
ijassa-1351	214	10	be	be	AUX
ijassa-1351	214	11	true	true	ADJ
ijassa-1351	214	12	e[r	e[r	NOUN
ijassa-1351	214	13	]	]	X
ijassa-1351	214	14	=	=	SYM
ijassa-1351	214	15	ê[r]±	ê[r]±	PROPN
ijassa-1351	214	16	3σê[r	3σê[r	NUM
ijassa-1351	214	17	]	]	X
ijassa-1351	215	1	≈	≈	PROPN
ijassa-1351	215	2	ê[r]±	ê[r]±	NOUN
ijassa-1351	215	3	3σ√	3σ√	PROPN
ijassa-1351	215	4	n	n	NOUN
ijassa-1351	215	5	√	√	ADP
ijassa-1351	215	6	1	1	NUM
ijassa-1351	215	7	+	+	CCONJ
ijassa-1351	215	8	2∆n	2∆n	NUM
ijassa-1351	215	9	≈	≈	PROPN
ijassa-1351	215	10	ê[r]±	ê[r]±	PROPN
ijassa-1351	215	11	3σ̂√	3σ̂√	NUM
ijassa-1351	215	12	n	n	NOUN
ijassa-1351	215	13	√	√	ADV
ijassa-1351	215	14	1	1	NUM
ijassa-1351	215	15	+	+	NUM
ijassa-1351	215	16	2∆̂.	2∆̂.	NUM
ijassa-1351	215	17	(	(	PUNCT
ijassa-1351	215	18	3.20	3.20	NUM
ijassa-1351	215	19	)	)	PUNCT
ijassa-1351	215	20	as	as	SCONJ
ijassa-1351	215	21	you	you	PRON
ijassa-1351	215	22	can	can	AUX
ijassa-1351	215	23	see	see	VERB
ijassa-1351	215	24	,	,	PUNCT
ijassa-1351	215	25	compared	compare	VERB
ijassa-1351	215	26	to	to	ADP
ijassa-1351	215	27	the	the	DET
ijassa-1351	215	28	case	case	NOUN
ijassa-1351	215	29	of	of	ADP
ijassa-1351	215	30	independent	independent	ADJ
ijassa-1351	215	31	random	random	ADJ
ijassa-1351	215	32	variables	variable	NOUN
ijassa-1351	215	33	,	,	PUNCT
ijassa-1351	215	34	the	the	DET
ijassa-1351	215	35	number	number	NOUN
ijassa-1351	215	36	of	of	ADP
ijassa-1351	215	37	trials	trial	NOUN
ijassa-1351	215	38	n	n	CCONJ
ijassa-1351	215	39	during	during	ADP
ijassa-1351	215	40	one	one	NUM
ijassa-1351	215	41	model	model	NOUN
ijassa-1351	215	42	run	run	NOUN
ijassa-1351	215	43	will	will	AUX
ijassa-1351	215	44	be	be	AUX
ijassa-1351	215	45	required	require	VERB
ijassa-1351	215	46	√	√	NUM
ijassa-1351	215	47	1	1	NUM
ijassa-1351	215	48	+	+	NUM
ijassa-1351	215	49	2∆n	2∆n	NUM
ijassa-1351	215	50	times	time	NOUN
ijassa-1351	215	51	more	more	ADV
ijassa-1351	215	52	due	due	ADJ
ijassa-1351	215	53	to	to	ADP
ijassa-1351	215	54	the	the	DET
ijassa-1351	215	55	existing	exist	VERB
ijassa-1351	215	56	correlation	correlation	NOUN
ijassa-1351	215	57	between	between	ADP
ijassa-1351	215	58	the	the	DET
ijassa-1351	215	59	data	datum	NOUN
ijassa-1351	215	60	.	.	PUNCT
ijassa-1351	216	1	next	next	ADV
ijassa-1351	216	2	,	,	PUNCT
ijassa-1351	216	3	we	we	PRON
ijassa-1351	216	4	construct	construct	VERB
ijassa-1351	216	5	an	an	DET
ijassa-1351	216	6	estimate	estimate	NOUN
ijassa-1351	216	7	for	for	ADP
ijassa-1351	216	8	∆	∆	PROPN
ijassa-1351	216	9	for	for	ADP
ijassa-1351	216	10	a	a	DET
ijassa-1351	216	11	fork	fork	NOUN
ijassa-1351	216	12	-	-	PUNCT
ijassa-1351	216	13	join	join	NOUN
ijassa-1351	216	14	qs	qs	NOUN
ijassa-1351	216	15	with	with	ADP
ijassa-1351	216	16	k	k	PROPN
ijassa-1351	216	17	subsystems	subsystem	NOUN
ijassa-1351	216	18	of	of	ADP
ijassa-1351	216	19	type	type	NOUN
ijassa-1351	216	20	m	m	NOUN
ijassa-1351	216	21	|m	|m	NOUN
ijassa-1351	216	22	|1	|1	NUM
ijassa-1351	216	23	in	in	ADP
ijassa-1351	216	24	the	the	DET
ijassa-1351	216	25	form	form	NOUN
ijassa-1351	216	26	of	of	ADP
ijassa-1351	216	27	some	some	DET
ijassa-1351	216	28	analytic	analytic	ADJ
ijassa-1351	216	29	expression	expression	NOUN
ijassa-1351	216	30	depending	depend	VERB
ijassa-1351	216	31	on	on	ADP
ijassa-1351	216	32	ρ	ρ	PROPN
ijassa-1351	216	33	and	and	CCONJ
ijassa-1351	216	34	k.	k.	NOUN
ijassa-1351	216	35	to	to	PART
ijassa-1351	216	36	do	do	VERB
ijassa-1351	216	37	this	this	PRON
ijassa-1351	216	38	,	,	PUNCT
ijassa-1351	216	39	using	use	VERB
ijassa-1351	216	40	simulation	simulation	NOUN
ijassa-1351	216	41	for	for	ADP
ijassa-1351	216	42	various	various	ADJ
ijassa-1351	216	43	combinations	combination	NOUN
ijassa-1351	216	44	of	of	ADP
ijassa-1351	216	45	pairs	pair	NOUN
ijassa-1351	216	46	of	of	ADP
ijassa-1351	216	47	values	value	NOUN
ijassa-1351	216	48	k	k	X
ijassa-1351	217	1	=	=	SYM
ijassa-1351	217	2	2	2	NUM
ijassa-1351	217	3	,	,	PUNCT
ijassa-1351	217	4	...	...	PUNCT
ijassa-1351	217	5	,	,	PUNCT
ijassa-1351	217	6	20	20	NUM
ijassa-1351	217	7	and	and	CCONJ
ijassa-1351	217	8	ρ	ρ	NUM
ijassa-1351	218	1	=	=	SYM
ijassa-1351	218	2	0.1	0.1	NUM
ijassa-1351	218	3	,	,	PUNCT
ijassa-1351	218	4	0.2	0.2	NUM
ijassa-1351	218	5	,	,	PUNCT
ijassa-1351	218	6	...	...	PUNCT
ijassa-1351	218	7	0.9	0.9	NUM
ijassa-1351	218	8	,	,	PUNCT
ijassa-1351	218	9	according	accord	VERB
ijassa-1351	218	10	to	to	ADP
ijassa-1351	218	11	the	the	DET
ijassa-1351	218	12	algorithm	algorithm	NOUN
ijassa-1351	218	13	described	describe	VERB
ijassa-1351	218	14	above	above	ADV
ijassa-1351	218	15	,	,	PUNCT
ijassa-1351	218	16	we	we	PRON
ijassa-1351	218	17	calculate	calculate	VERB
ijassa-1351	218	18	the	the	DET
ijassa-1351	218	19	values	value	NOUN
ijassa-1351	218	20	∆̂	∆̂	NOUN
ijassa-1351	218	21	=	=	SYM
ijassa-1351	218	22	∆̂(k	∆̂(k	PROPN
ijassa-1351	218	23	,	,	PUNCT
ijassa-1351	218	24	ρ	ρ	NOUN
ijassa-1351	218	25	)	)	PUNCT
ijassa-1351	218	26	.	.	PUNCT
ijassa-1351	219	1	the	the	DET
ijassa-1351	219	2	values	value	NOUN
ijassa-1351	219	3	of	of	ADP
ijassa-1351	219	4	m	m	PRON
ijassa-1351	219	5	were	be	AUX
ijassa-1351	219	6	chosen	choose	VERB
ijassa-1351	219	7	depending	depend	VERB
ijassa-1351	219	8	on	on	ADP
ijassa-1351	219	9	ρ	ρ	PROPN
ijassa-1351	219	10	,	,	PUNCT
ijassa-1351	219	11	namely	namely	ADV
ijassa-1351	219	12	m	m	NOUN
ijassa-1351	219	13	=	=	NOUN
ijassa-1351	219	14	10	10	NUM
ijassa-1351	219	15	,	,	PUNCT
ijassa-1351	219	16	20	20	NUM
ijassa-1351	219	17	,	,	PUNCT
ijassa-1351	219	18	30	30	NUM
ijassa-1351	219	19	,	,	PUNCT
ijassa-1351	219	20	40	40	NUM
ijassa-1351	219	21	,	,	PUNCT
ijassa-1351	219	22	50	50	NUM
ijassa-1351	219	23	,	,	PUNCT
ijassa-1351	219	24	50	50	NUM
ijassa-1351	219	25	,	,	PUNCT
ijassa-1351	219	26	100	100	NUM
ijassa-1351	219	27	,	,	PUNCT
ijassa-1351	219	28	250	250	NUM
ijassa-1351	219	29	,	,	PUNCT
ijassa-1351	219	30	1000	1000	NUM
ijassa-1351	219	31	.	.	PUNCT
ijassa-1351	220	1	note	note	VERB
ijassa-1351	220	2	that	that	SCONJ
ijassa-1351	220	3	here	here	ADV
ijassa-1351	220	4	we	we	PRON
ijassa-1351	220	5	start	start	VERB
ijassa-1351	220	6	the	the	DET
ijassa-1351	220	7	simulation	simulation	NOUN
ijassa-1351	220	8	with	with	ADP
ijassa-1351	220	9	k	k	PROPN
ijassa-1351	220	10	=	=	SYM
ijassa-1351	220	11	2	2	NUM
ijassa-1351	220	12	,	,	PUNCT
ijassa-1351	220	13	since	since	SCONJ
ijassa-1351	220	14	for	for	ADP
ijassa-1351	220	15	this	this	DET
ijassa-1351	220	16	characteristic	characteristic	NOUN
ijassa-1351	220	17	,	,	PUNCT
ijassa-1351	220	18	even	even	ADV
ijassa-1351	220	19	in	in	ADP
ijassa-1351	220	20	this	this	DET
ijassa-1351	220	21	case	case	NOUN
ijassa-1351	220	22	,	,	PUNCT
ijassa-1351	220	23	there	there	PRON
ijassa-1351	220	24	are	be	VERB
ijassa-1351	220	25	still	still	ADV
ijassa-1351	220	26	no	no	DET
ijassa-1351	220	27	exact	exact	ADJ
ijassa-1351	220	28	results	result	NOUN
ijassa-1351	220	29	,	,	PUNCT
ijassa-1351	220	30	just	just	ADV
ijassa-1351	220	31	as	as	SCONJ
ijassa-1351	220	32	there	there	PRON
ijassa-1351	220	33	were	be	VERB
ijassa-1351	220	34	no	no	DET
ijassa-1351	220	35	approximate	approximate	ADJ
ijassa-1351	220	36	ones	one	NOUN
ijassa-1351	220	37	,	,	PUNCT
ijassa-1351	220	38	i.e.	i.e.	X
ijassa-1351	220	39	research	research	NOUN
ijassa-1351	220	40	is	be	AUX
ijassa-1351	220	41	completely	completely	ADV
ijassa-1351	220	42	new	new	ADJ
ijassa-1351	220	43	.	.	PUNCT
ijassa-1351	221	1	copyright	copyright	NOUN
ijassa-1351	221	2	©	©	ADP
ijassa-1351	221	3	2023	2023	NUM
ijassa-1351	221	4	assa	assa	NOUN
ijassa-1351	221	5	.	.	PUNCT
ijassa-1351	222	1	adv	adv	PROPN
ijassa-1351	222	2	syst	syst	PROPN
ijassa-1351	222	3	sci	sci	PROPN
ijassa-1351	222	4	appl	appl	PROPN
ijassa-1351	222	5	(	(	PUNCT
ijassa-1351	222	6	2023	2023	NUM
ijassa-1351	222	7	)	)	PUNCT
ijassa-1351	222	8	assa	assa	NOUN
ijassa-1351	222	9	latex	latex	NOUN
ijassa-1351	222	10	template	template	NOUN
ijassa-1351	222	11	111	111	NUM
ijassa-1351	222	12	-0.05	-0.05	NUM
ijassa-1351	222	13	0.00	0.00	NUM
ijassa-1351	222	14	0.05	0.05	NUM
ijassa-1351	222	15	0.10	0.10	NUM
ijassa-1351	222	16	0.15	0.15	NUM
ijassa-1351	222	17	0.20	0.20	NUM
ijassa-1351	222	18	0.25	0.25	NUM
ijassa-1351	222	19	0.30	0.30	NUM
ijassa-1351	222	20	0.35	0.35	NUM
ijassa-1351	222	21	0.40	0.40	NUM
ijassa-1351	222	22	0.45	0.45	NUM
ijassa-1351	222	23	0.10	0.10	NUM
ijassa-1351	222	24	0.20	0.20	NUM
ijassa-1351	222	25	0.30	0.30	NUM
ijassa-1351	222	26	0.40	0.40	NUM
ijassa-1351	222	27	0.50	0.50	NUM
ijassa-1351	222	28	0.60	0.60	NUM
ijassa-1351	222	29	0.70	0.70	NUM
ijassa-1351	222	30	0.80	0.80	NUM
ijassa-1351	222	31	0.90	0.90	NUM
ijassa-1351	222	32	k=2	k=2	PROPN
ijassa-1351	223	1	k=3	k=3	PROPN
ijassa-1351	223	2	k=4	k=4	X
ijassa-1351	223	3	k=5	k=5	PUNCT
ijassa-1351	223	4	k=6	k=6	X
ijassa-1351	223	5	k=7	k=7	X
ijassa-1351	223	6	k=8	k=8	X
ijassa-1351	224	1	k=9	k=9	PROPN
ijassa-1351	224	2	k=10	k=10	PROPN
ijassa-1351	224	3	k=11	k=11	PROPN
ijassa-1351	224	4	k=12	k=12	PROPN
ijassa-1351	224	5	k=13	k=13	VERB
ijassa-1351	224	6	fig	fig	NOUN
ijassa-1351	224	7	.	.	PUNCT
ijassa-1351	225	1	3.9	3.9	NUM
ijassa-1351	225	2	.	.	PUNCT
ijassa-1351	225	3	dependence	dependence	NOUN
ijassa-1351	226	1	[	[	X
ijassa-1351	226	2	∆̂/(2ρ/(1−	∆̂/(2ρ/(1−	X
ijassa-1351	226	3	ρ2))−	ρ2))−	NOUN
ijassa-1351	226	4	1	1	NUM
ijassa-1351	226	5	]	]	PUNCT
ijassa-1351	226	6	on	on	ADP
ijassa-1351	226	7	ρ	ρ	PROPN
ijassa-1351	226	8	.	.	PUNCT
ijassa-1351	227	1	now	now	ADV
ijassa-1351	227	2	let	let	VERB
ijassa-1351	227	3	us	we	PRON
ijassa-1351	227	4	define	define	VERB
ijassa-1351	227	5	a	a	DET
ijassa-1351	227	6	specific	specific	ADJ
ijassa-1351	227	7	type	type	NOUN
ijassa-1351	227	8	of	of	ADP
ijassa-1351	227	9	functional	functional	ADJ
ijassa-1351	227	10	dependence	dependence	NOUN
ijassa-1351	227	11	by	by	ADP
ijassa-1351	227	12	analyzing	analyze	VERB
ijassa-1351	227	13	the	the	DET
ijassa-1351	227	14	results	result	NOUN
ijassa-1351	227	15	of	of	ADP
ijassa-1351	227	16	constructing	construct	VERB
ijassa-1351	227	17	various	various	ADJ
ijassa-1351	227	18	graphs	graph	NOUN
ijassa-1351	227	19	.	.	PUNCT
ijassa-1351	228	1	in	in	ADP
ijassa-1351	228	2	particular	particular	ADJ
ijassa-1351	228	3	,	,	PUNCT
ijassa-1351	228	4	the	the	DET
ijassa-1351	228	5	plot	plot	NOUN
ijassa-1351	228	6	of	of	ADP
ijassa-1351	228	7	∆̂/(2ρ/(1−	∆̂/(2ρ/(1−	NOUN
ijassa-1351	228	8	ρ2))−	ρ2))−	NUM
ijassa-1351	228	9	1	1	NUM
ijassa-1351	228	10	as	as	ADP
ijassa-1351	228	11	a	a	DET
ijassa-1351	228	12	function	function	NOUN
ijassa-1351	228	13	of	of	ADP
ijassa-1351	228	14	ρ	ρ	PROPN
ijassa-1351	228	15	resembles	resemble	VERB
ijassa-1351	228	16	a	a	DET
ijassa-1351	228	17	bunch	bunch	NOUN
ijassa-1351	228	18	of	of	ADP
ijassa-1351	228	19	straight	straight	ADJ
ijassa-1351	228	20	lines	line	NOUN
ijassa-1351	228	21	with	with	ADP
ijassa-1351	228	22	different	different	ADJ
ijassa-1351	228	23	slopes	slope	NOUN
ijassa-1351	228	24	passing	pass	VERB
ijassa-1351	228	25	through	through	ADP
ijassa-1351	228	26	the	the	DET
ijassa-1351	228	27	point	point	NOUN
ijassa-1351	228	28	(	(	PUNCT
ijassa-1351	228	29	0	0	NUM
ijassa-1351	228	30	,	,	PUNCT
ijassa-1351	228	31	0	0	NUM
ijassa-1351	228	32	)	)	PUNCT
ijassa-1351	228	33	,	,	PUNCT
ijassa-1351	228	34	taking	take	VERB
ijassa-1351	228	35	into	into	ADP
ijassa-1351	228	36	account	account	NOUN
ijassa-1351	228	37	fluctuations	fluctuation	NOUN
ijassa-1351	228	38	caused	cause	VERB
ijassa-1351	228	39	by	by	ADP
ijassa-1351	228	40	random	random	ADJ
ijassa-1351	228	41	errors	error	NOUN
ijassa-1351	228	42	(	(	PUNCT
ijassa-1351	228	43	fig	fig	NOUN
ijassa-1351	228	44	.	.	PUNCT
ijassa-1351	228	45	3.9	3.9	NUM
ijassa-1351	228	46	)	)	PUNCT
ijassa-1351	228	47	.	.	PUNCT
ijassa-1351	229	1	therefore	therefore	ADV
ijassa-1351	229	2	,	,	PUNCT
ijassa-1351	229	3	it	it	PRON
ijassa-1351	229	4	remains	remain	VERB
ijassa-1351	229	5	to	to	PART
ijassa-1351	229	6	find	find	VERB
ijassa-1351	229	7	a	a	DET
ijassa-1351	229	8	formula	formula	NOUN
ijassa-1351	229	9	that	that	PRON
ijassa-1351	229	10	describes	describe	VERB
ijassa-1351	229	11	these	these	DET
ijassa-1351	229	12	lines	line	NOUN
ijassa-1351	229	13	.	.	PUNCT
ijassa-1351	230	1	taking	take	VERB
ijassa-1351	230	2	into	into	ADP
ijassa-1351	230	3	account	account	NOUN
ijassa-1351	230	4	the	the	DET
ijassa-1351	230	5	approximations	approximation	NOUN
ijassa-1351	230	6	obtained	obtain	VERB
ijassa-1351	230	7	in	in	ADP
ijassa-1351	230	8	earlier	early	ADJ
ijassa-1351	230	9	publications	publication	NOUN
ijassa-1351	230	10	for	for	ADP
ijassa-1351	230	11	the	the	DET
ijassa-1351	230	12	average	average	ADJ
ijassa-1351	230	13	response	response	NOUN
ijassa-1351	230	14	time	time	NOUN
ijassa-1351	230	15	of	of	ADP
ijassa-1351	230	16	a	a	DET
ijassa-1351	230	17	fork	fork	NOUN
ijassa-1351	230	18	-	-	PUNCT
ijassa-1351	230	19	join	join	NOUN
ijassa-1351	230	20	system	system	NOUN
ijassa-1351	230	21	in	in	ADP
ijassa-1351	230	22	which	which	PRON
ijassa-1351	230	23	there	there	PRON
ijassa-1351	230	24	is	be	VERB
ijassa-1351	230	25	a	a	DET
ijassa-1351	230	26	partial	partial	ADJ
ijassa-1351	230	27	sum	sum	NOUN
ijassa-1351	230	28	of	of	ADP
ijassa-1351	230	29	the	the	DET
ijassa-1351	230	30	harmonic	harmonic	ADJ
ijassa-1351	230	31	series	series	NOUN
ijassa-1351	230	32	,	,	PUNCT
ijassa-1351	230	33	it	it	PRON
ijassa-1351	230	34	is	be	AUX
ijassa-1351	230	35	natural	natural	ADJ
ijassa-1351	230	36	to	to	PART
ijassa-1351	230	37	assume	assume	VERB
ijassa-1351	230	38	that	that	SCONJ
ijassa-1351	230	39	∆	∆	PROPN
ijassa-1351	230	40	will	will	AUX
ijassa-1351	230	41	similarly	similarly	ADV
ijassa-1351	230	42	depend	depend	VERB
ijassa-1351	230	43	on	on	ADP
ijassa-1351	230	44	k	k	PROPN
ijassa-1351	230	45	not	not	PART
ijassa-1351	230	46	directly	directly	ADV
ijassa-1351	230	47	but	but	CCONJ
ijassa-1351	230	48	through	through	ADP
ijassa-1351	230	49	hk	hk	PROPN
ijassa-1351	230	50	.	.	PUNCT
ijassa-1351	231	1	with	with	ADP
ijassa-1351	231	2	respect	respect	NOUN
ijassa-1351	231	3	to	to	ADP
ijassa-1351	231	4	hk	hk	PROPN
ijassa-1351	231	5	,	,	PUNCT
ijassa-1351	231	6	a	a	DET
ijassa-1351	231	7	dependence	dependence	NOUN
ijassa-1351	231	8	close	close	ADJ
ijassa-1351	231	9	to	to	ADP
ijassa-1351	231	10	linear	linear	PROPN
ijassa-1351	231	11	was	be	AUX
ijassa-1351	231	12	also	also	ADV
ijassa-1351	231	13	observed	observe	VERB
ijassa-1351	231	14	.	.	PUNCT
ijassa-1351	232	1	therefore	therefore	ADV
ijassa-1351	232	2	,	,	PUNCT
ijassa-1351	232	3	suppose	suppose	VERB
ijassa-1351	232	4	that	that	SCONJ
ijassa-1351	232	5	the	the	DET
ijassa-1351	232	6	lines	line	NOUN
ijassa-1351	232	7	can	can	AUX
ijassa-1351	232	8	be	be	AUX
ijassa-1351	232	9	described	describe	VERB
ijassa-1351	232	10	by	by	ADP
ijassa-1351	232	11	the	the	DET
ijassa-1351	232	12	formula	formula	NOUN
ijassa-1351	232	13	c	c	NOUN
ijassa-1351	232	14	·	·	PUNCT
ijassa-1351	232	15	ρ(hk	ρ(hk	NOUN
ijassa-1351	232	16	−	−	NOUN
ijassa-1351	232	17	1	1	NUM
ijassa-1351	232	18	)	)	PUNCT
ijassa-1351	232	19	.	.	PUNCT
ijassa-1351	233	1	finally	finally	ADV
ijassa-1351	233	2	,	,	PUNCT
ijassa-1351	233	3	we	we	PRON
ijassa-1351	233	4	get	get	VERB
ijassa-1351	233	5	an	an	DET
ijassa-1351	233	6	expression	expression	NOUN
ijassa-1351	233	7	for	for	ADP
ijassa-1351	233	8	the	the	DET
ijassa-1351	233	9	∆	∆	ADJ
ijassa-1351	233	10	estimate	estimate	NOUN
ijassa-1351	233	11	of	of	ADP
ijassa-1351	233	12	the	the	DET
ijassa-1351	233	13	following	follow	VERB
ijassa-1351	233	14	form	form	NOUN
ijassa-1351	233	15	:	:	PUNCT
ijassa-1351	233	16	∆(k	∆(k	PROPN
ijassa-1351	233	17	,	,	PUNCT
ijassa-1351	233	18	ρ	ρ	NOUN
ijassa-1351	233	19	)	)	PUNCT
ijassa-1351	234	1	≈	≈	PROPN
ijassa-1351	234	2	2ρ	2ρ	NOUN
ijassa-1351	234	3	(	(	PUNCT
ijassa-1351	234	4	1−	1−	NUM
ijassa-1351	234	5	ρ)2	ρ)2	NOUN
ijassa-1351	234	6	(	(	PUNCT
ijassa-1351	234	7	1	1	NUM
ijassa-1351	234	8	+	+	CCONJ
ijassa-1351	234	9	c	c	X
ijassa-1351	234	10	·	·	PUNCT
ijassa-1351	234	11	ρ(hk	ρ(hk	NOUN
ijassa-1351	234	12	−	−	NOUN
ijassa-1351	234	13	1	1	NUM
ijassa-1351	234	14	)	)	PUNCT
ijassa-1351	234	15	)	)	PUNCT
ijassa-1351	234	16	,	,	PUNCT
ijassa-1351	234	17	(	(	PUNCT
ijassa-1351	234	18	3.21	3.21	NUM
ijassa-1351	234	19	)	)	PUNCT
ijassa-1351	234	20	where	where	SCONJ
ijassa-1351	234	21	c	c	NOUN
ijassa-1351	234	22	is	be	AUX
ijassa-1351	234	23	some	some	DET
ijassa-1351	234	24	coefficient	coefficient	NOUN
ijassa-1351	234	25	whose	whose	DET
ijassa-1351	234	26	value	value	NOUN
ijassa-1351	234	27	is	be	AUX
ijassa-1351	234	28	to	to	PART
ijassa-1351	234	29	be	be	AUX
ijassa-1351	234	30	found	find	VERB
ijassa-1351	234	31	.	.	PUNCT
ijassa-1351	235	1	the	the	DET
ijassa-1351	235	2	search	search	NOUN
ijassa-1351	235	3	for	for	ADP
ijassa-1351	235	4	the	the	DET
ijassa-1351	235	5	c	c	PROPN
ijassa-1351	235	6	coefficient	coefficient	NOUN
ijassa-1351	235	7	is	be	AUX
ijassa-1351	235	8	carried	carry	VERB
ijassa-1351	235	9	out	out	ADP
ijassa-1351	235	10	using	use	VERB
ijassa-1351	235	11	the	the	DET
ijassa-1351	235	12	nelder	nelder	ADJ
ijassa-1351	235	13	-	-	PUNCT
ijassa-1351	235	14	mead	mead	NOUN
ijassa-1351	235	15	optimization	optimization	NOUN
ijassa-1351	235	16	method	method	NOUN
ijassa-1351	235	17	.	.	PUNCT
ijassa-1351	236	1	thus	thus	ADV
ijassa-1351	236	2	,	,	PUNCT
ijassa-1351	236	3	we	we	PRON
ijassa-1351	236	4	get	get	VERB
ijassa-1351	236	5	c	c	NOUN
ijassa-1351	236	6	≈	≈	PROPN
ijassa-1351	236	7	0.186722	0.186722	NUM
ijassa-1351	236	8	.	.	PUNCT
ijassa-1351	237	1	to	to	PART
ijassa-1351	237	2	verify	verify	VERB
ijassa-1351	237	3	the	the	DET
ijassa-1351	237	4	quality	quality	NOUN
ijassa-1351	237	5	of	of	ADP
ijassa-1351	237	6	the	the	DET
ijassa-1351	237	7	obtained	obtain	VERB
ijassa-1351	237	8	approximation	approximation	NOUN
ijassa-1351	237	9	,	,	PUNCT
ijassa-1351	237	10	we	we	PRON
ijassa-1351	237	11	construct	construct	VERB
ijassa-1351	237	12	the	the	DET
ijassa-1351	237	13	corresponding	corresponding	ADJ
ijassa-1351	237	14	graph	graph	NOUN
ijassa-1351	237	15	(	(	PUNCT
ijassa-1351	237	16	fig	fig	NOUN
ijassa-1351	237	17	.	.	PUNCT
ijassa-1351	237	18	3.10	3.10	NUM
ijassa-1351	237	19	)	)	PUNCT
ijassa-1351	237	20	and	and	CCONJ
ijassa-1351	237	21	analyze	analyze	VERB
ijassa-1351	237	22	the	the	DET
ijassa-1351	237	23	approximation	approximation	NOUN
ijassa-1351	237	24	errors	error	NOUN
ijassa-1351	237	25	.	.	PUNCT
ijassa-1351	238	1	let	let	VERB
ijassa-1351	238	2	ape	ape	NOUN
ijassa-1351	238	3	=	=	SYM
ijassa-1351	238	4	∆̂−∆	∆̂−∆	PROPN
ijassa-1351	238	5	∆	∆	X
ijassa-1351	238	6	·	·	PUNCT
ijassa-1351	238	7	100	100	NUM
ijassa-1351	238	8	%	%	NOUN
ijassa-1351	238	9	,	,	PUNCT
ijassa-1351	238	10	then	then	ADV
ijassa-1351	238	11	we	we	PRON
ijassa-1351	238	12	get	get	VERB
ijassa-1351	238	13	maxape	maxape	NOUN
ijassa-1351	238	14	≈	≈	PROPN
ijassa-1351	238	15	5.27449	5.27449	NUM
ijassa-1351	238	16	%	%	NOUN
ijassa-1351	238	17	,	,	PUNCT
ijassa-1351	238	18	minape	minape	NOUN
ijassa-1351	238	19	≈	≈	PROPN
ijassa-1351	238	20	0.013941	0.013941	NUM
ijassa-1351	238	21	%	%	NOUN
ijassa-1351	238	22	,	,	PUNCT
ijassa-1351	238	23	where	where	SCONJ
ijassa-1351	238	24	the	the	DET
ijassa-1351	238	25	average	average	ADJ
ijassa-1351	238	26	value	value	NOUN
ijassa-1351	238	27	of	of	ADP
ijassa-1351	238	28	the	the	DET
ijassa-1351	238	29	modules	module	NOUN
ijassa-1351	238	30	of	of	ADP
ijassa-1351	238	31	relative	relative	ADJ
ijassa-1351	238	32	approximation	approximation	NOUN
ijassa-1351	238	33	errors	error	NOUN
ijassa-1351	238	34	mape	mape	NOUN
ijassa-1351	238	35	≈	≈	PROPN
ijassa-1351	238	36	0.835525	0.835525	NUM
ijassa-1351	238	37	%	%	NOUN
ijassa-1351	238	38	,	,	PUNCT
ijassa-1351	238	39	copyright	copyright	NOUN
ijassa-1351	238	40	©	©	PROPN
ijassa-1351	238	41	2023	2023	NUM
ijassa-1351	238	42	assa	assa	NOUN
ijassa-1351	238	43	.	.	PUNCT
ijassa-1351	239	1	adv	adv	PROPN
ijassa-1351	239	2	syst	syst	PROPN
ijassa-1351	239	3	sci	sci	PROPN
ijassa-1351	239	4	appl	appl	PROPN
ijassa-1351	239	5	(	(	PUNCT
ijassa-1351	239	6	2023	2023	NUM
ijassa-1351	239	7	)	)	PUNCT
ijassa-1351	239	8	112	112	NUM
ijassa-1351	239	9	a.v	a.v	PROPN
ijassa-1351	239	10	.	.	PROPN
ijassa-1351	239	11	gorbunova	gorbunova	PROPN
ijassa-1351	239	12	,	,	PUNCT
ijassa-1351	239	13	a.v	a.v	PROPN
ijassa-1351	239	14	.	.	PROPN
ijassa-1351	239	15	lebedev	lebedev	PROPN
ijassa-1351	239	16	0	0	NUM
ijassa-1351	240	1	50	50	NUM
ijassa-1351	240	2	100	100	NUM
ijassa-1351	240	3	150	150	NUM
ijassa-1351	240	4	200	200	NUM
ijassa-1351	240	5	250	250	NUM
ijassa-1351	240	6	0	0	NUM
ijassa-1351	240	7	50	50	NUM
ijassa-1351	240	8	100	100	NUM
ijassa-1351	240	9	150	150	NUM
ijassa-1351	240	10	200	200	NUM
ijassa-1351	240	11	250	250	NUM
ijassa-1351	240	12	f	f	NOUN
ijassa-1351	240	13	o	o	X
ijassa-1351	240	14	rm	rm	NOUN
ijassa-1351	240	15	u	u	PROPN
ijassa-1351	240	16	la	la	X
ijassa-1351	240	17	(	(	PUNCT
ijassa-1351	240	18	2	2	NUM
ijassa-1351	240	19	1	1	NUM
ijassa-1351	240	20	)	)	PUNCT
ijassa-1351	240	21	simulation	simulation	NOUN
ijassa-1351	240	22	fig	fig	NOUN
ijassa-1351	240	23	.	.	PUNCT
ijassa-1351	241	1	3.10	3.10	NUM
ijassa-1351	241	2	.	.	PUNCT
ijassa-1351	242	1	∆	∆	PROPN
ijassa-1351	242	2	coefficient	coefficient	NOUN
ijassa-1351	242	3	:	:	PUNCT
ijassa-1351	242	4	comparison	comparison	NOUN
ijassa-1351	242	5	of	of	ADP
ijassa-1351	242	6	simulation	simulation	NOUN
ijassa-1351	242	7	results	result	VERB
ijassa-1351	242	8	with	with	ADP
ijassa-1351	242	9	the	the	DET
ijassa-1351	242	10	formula	formula	NOUN
ijassa-1351	242	11	(	(	PUNCT
ijassa-1351	242	12	3.21	3.21	NUM
ijassa-1351	242	13	)	)	PUNCT
ijassa-1351	242	14	.	.	PUNCT
ijassa-1351	243	1	which	which	PRON
ijassa-1351	243	2	indicates	indicate	VERB
ijassa-1351	243	3	the	the	DET
ijassa-1351	243	4	good	good	ADJ
ijassa-1351	243	5	quality	quality	NOUN
ijassa-1351	243	6	of	of	ADP
ijassa-1351	243	7	the	the	DET
ijassa-1351	243	8	resulting	result	VERB
ijassa-1351	243	9	expression	expression	NOUN
ijassa-1351	243	10	.	.	PUNCT
ijassa-1351	244	1	in	in	ADP
ijassa-1351	244	2	this	this	DET
ijassa-1351	244	3	case	case	NOUN
ijassa-1351	244	4	,	,	PUNCT
ijassa-1351	244	5	we	we	PRON
ijassa-1351	244	6	can	can	AUX
ijassa-1351	244	7	assume	assume	VERB
ijassa-1351	244	8	that	that	SCONJ
ijassa-1351	244	9	the	the	DET
ijassa-1351	244	10	formula	formula	NOUN
ijassa-1351	244	11	(	(	PUNCT
ijassa-1351	244	12	3.21	3.21	NUM
ijassa-1351	244	13	)	)	PUNCT
ijassa-1351	244	14	can	can	AUX
ijassa-1351	244	15	be	be	AUX
ijassa-1351	244	16	successfully	successfully	ADV
ijassa-1351	244	17	used	use	VERB
ijassa-1351	244	18	to	to	PART
ijassa-1351	244	19	construct	construct	VERB
ijassa-1351	244	20	confidence	confidence	NOUN
ijassa-1351	244	21	intervals	interval	NOUN
ijassa-1351	244	22	not	not	PART
ijassa-1351	244	23	only	only	ADV
ijassa-1351	244	24	in	in	ADP
ijassa-1351	244	25	the	the	DET
ijassa-1351	244	26	region	region	NOUN
ijassa-1351	244	27	2	2	NUM
ijassa-1351	244	28	⩽	⩽	NOUN
ijassa-1351	244	29	k	k	PROPN
ijassa-1351	244	30	⩽	⩽	PROPN
ijassa-1351	244	31	20	20	NUM
ijassa-1351	244	32	,	,	PUNCT
ijassa-1351	244	33	but	but	CCONJ
ijassa-1351	244	34	also	also	ADV
ijassa-1351	244	35	for	for	ADP
ijassa-1351	244	36	large	large	ADJ
ijassa-1351	244	37	values	value	NOUN
ijassa-1351	244	38	of	of	ADP
ijassa-1351	244	39	k.	k.	PROPN
ijassa-1351	244	40	we	we	PRON
ijassa-1351	244	41	also	also	ADV
ijassa-1351	244	42	note	note	VERB
ijassa-1351	244	43	that	that	SCONJ
ijassa-1351	244	44	the	the	DET
ijassa-1351	244	45	values	value	NOUN
ijassa-1351	244	46	of	of	ADP
ijassa-1351	244	47	∆	∆	PROPN
ijassa-1351	244	48	observed	observe	VERB
ijassa-1351	244	49	in	in	ADP
ijassa-1351	244	50	the	the	DET
ijassa-1351	244	51	studied	study	VERB
ijassa-1351	244	52	range	range	NOUN
ijassa-1351	244	53	of	of	ADP
ijassa-1351	244	54	parameters	parameter	NOUN
ijassa-1351	244	55	reach	reach	VERB
ijassa-1351	244	56	approximately	approximately	ADV
ijassa-1351	244	57	252	252	NUM
ijassa-1351	244	58	,	,	PUNCT
ijassa-1351	244	59	which	which	PRON
ijassa-1351	244	60	means	mean	VERB
ijassa-1351	244	61	,	,	PUNCT
ijassa-1351	244	62	in	in	ADP
ijassa-1351	244	63	this	this	DET
ijassa-1351	244	64	case	case	NOUN
ijassa-1351	244	65	,	,	PUNCT
ijassa-1351	244	66	an	an	DET
ijassa-1351	244	67	increase	increase	NOUN
ijassa-1351	244	68	in	in	ADP
ijassa-1351	244	69	the	the	DET
ijassa-1351	244	70	required	require	VERB
ijassa-1351	244	71	number	number	NOUN
ijassa-1351	244	72	of	of	ADP
ijassa-1351	244	73	trials	trial	NOUN
ijassa-1351	244	74	n	n	X
ijassa-1351	244	75	by	by	ADP
ijassa-1351	244	76	more	more	ADJ
ijassa-1351	244	77	than	than	ADP
ijassa-1351	244	78	22	22	NUM
ijassa-1351	244	79	times	time	NOUN
ijassa-1351	244	80	compared	compare	VERB
ijassa-1351	244	81	to	to	ADP
ijassa-1351	244	82	the	the	DET
ijassa-1351	244	83	case	case	NOUN
ijassa-1351	244	84	of	of	ADP
ijassa-1351	244	85	independent	independent	ADJ
ijassa-1351	244	86	trials	trial	NOUN
ijassa-1351	244	87	(	(	PUNCT
ijassa-1351	244	88	to	to	PART
ijassa-1351	244	89	achieve	achieve	VERB
ijassa-1351	244	90	the	the	DET
ijassa-1351	244	91	same	same	ADJ
ijassa-1351	244	92	accuracy	accuracy	NOUN
ijassa-1351	244	93	of	of	ADP
ijassa-1351	244	94	the	the	DET
ijassa-1351	244	95	estimate	estimate	NOUN
ijassa-1351	244	96	average	average	ADJ
ijassa-1351	244	97	response	response	NOUN
ijassa-1351	244	98	time	time	NOUN
ijassa-1351	244	99	)	)	PUNCT
ijassa-1351	244	100	,	,	PUNCT
ijassa-1351	244	101	and	and	CCONJ
ijassa-1351	244	102	this	this	DET
ijassa-1351	244	103	effect	effect	NOUN
ijassa-1351	244	104	can	can	AUX
ijassa-1351	244	105	not	not	PART
ijassa-1351	244	106	be	be	AUX
ijassa-1351	244	107	neglected	neglect	VERB
ijassa-1351	244	108	.	.	PUNCT
ijassa-1351	245	1	the	the	DET
ijassa-1351	245	2	algorithm	algorithm	NOUN
ijassa-1351	245	3	presented	present	VERB
ijassa-1351	245	4	above	above	ADV
ijassa-1351	245	5	can	can	AUX
ijassa-1351	245	6	be	be	AUX
ijassa-1351	245	7	used	use	VERB
ijassa-1351	245	8	to	to	PART
ijassa-1351	245	9	build	build	VERB
ijassa-1351	245	10	confidence	confidence	NOUN
ijassa-1351	245	11	intervals	interval	NOUN
ijassa-1351	245	12	of	of	ADP
ijassa-1351	245	13	the	the	DET
ijassa-1351	245	14	form	form	NOUN
ijassa-1351	245	15	(	(	PUNCT
ijassa-1351	245	16	3.20	3.20	NUM
ijassa-1351	245	17	)	)	PUNCT
ijassa-1351	245	18	to	to	PART
ijassa-1351	245	19	estimate	estimate	VERB
ijassa-1351	245	20	the	the	DET
ijassa-1351	245	21	average	average	ADJ
ijassa-1351	245	22	response	response	NOUN
ijassa-1351	245	23	time	time	NOUN
ijassa-1351	245	24	not	not	PART
ijassa-1351	245	25	only	only	ADV
ijassa-1351	245	26	in	in	ADP
ijassa-1351	245	27	the	the	DET
ijassa-1351	245	28	case	case	NOUN
ijassa-1351	245	29	of	of	ADP
ijassa-1351	245	30	subsystems	subsystem	NOUN
ijassa-1351	245	31	of	of	ADP
ijassa-1351	245	32	the	the	DET
ijassa-1351	245	33	m	m	NOUN
ijassa-1351	245	34	|m	|m	NOUN
ijassa-1351	245	35	|1	|1	DET
ijassa-1351	245	36	type	type	NOUN
ijassa-1351	245	37	but	but	CCONJ
ijassa-1351	245	38	also	also	ADV
ijassa-1351	245	39	in	in	ADP
ijassa-1351	245	40	more	more	ADJ
ijassa-1351	245	41	complex	complex	ADJ
ijassa-1351	245	42	cases	case	NOUN
ijassa-1351	245	43	,	,	PUNCT
ijassa-1351	245	44	for	for	ADP
ijassa-1351	245	45	example	example	NOUN
ijassa-1351	245	46	,	,	PUNCT
ijassa-1351	245	47	for	for	ADP
ijassa-1351	245	48	subsystems	subsystem	NOUN
ijassa-1351	245	49	of	of	ADP
ijassa-1351	245	50	the	the	DET
ijassa-1351	245	51	type	type	NOUN
ijassa-1351	245	52	g|g|1	g|g|1	NOUN
ijassa-1351	245	53	and	and	CCONJ
ijassa-1351	245	54	others	other	NOUN
ijassa-1351	245	55	.	.	PUNCT
ijassa-1351	246	1	as	as	SCONJ
ijassa-1351	246	2	regards	regard	VERB
ijassa-1351	246	3	the	the	DET
ijassa-1351	246	4	method	method	NOUN
ijassa-1351	246	5	of	of	ADP
ijassa-1351	246	6	constructing	construct	VERB
ijassa-1351	246	7	a	a	DET
ijassa-1351	246	8	functional	functional	ADJ
ijassa-1351	246	9	dependence	dependence	NOUN
ijassa-1351	246	10	for	for	ADP
ijassa-1351	246	11	the	the	DET
ijassa-1351	246	12	coefficient	coefficient	NOUN
ijassa-1351	246	13	∆	∆	PROPN
ijassa-1351	246	14	,	,	PUNCT
ijassa-1351	246	15	more	more	ADV
ijassa-1351	246	16	laborious	laborious	ADJ
ijassa-1351	246	17	work	work	NOUN
ijassa-1351	246	18	is	be	AUX
ijassa-1351	246	19	possible	possible	ADJ
ijassa-1351	246	20	here	here	ADV
ijassa-1351	246	21	on	on	ADP
ijassa-1351	246	22	the	the	DET
ijassa-1351	246	23	selection	selection	NOUN
ijassa-1351	246	24	of	of	ADP
ijassa-1351	246	25	the	the	DET
ijassa-1351	246	26	type	type	NOUN
ijassa-1351	246	27	of	of	ADP
ijassa-1351	246	28	dependence	dependence	NOUN
ijassa-1351	246	29	in	in	ADP
ijassa-1351	246	30	each	each	DET
ijassa-1351	246	31	specific	specific	ADJ
ijassa-1351	246	32	case	case	NOUN
ijassa-1351	246	33	,	,	PUNCT
ijassa-1351	246	34	i.e.	i.e.	X
ijassa-1351	246	35	,	,	PUNCT
ijassa-1351	246	36	for	for	ADP
ijassa-1351	246	37	specific	specific	ADJ
ijassa-1351	246	38	distributions	distribution	NOUN
ijassa-1351	246	39	of	of	ADP
ijassa-1351	246	40	input	input	NOUN
ijassa-1351	246	41	flow	flow	NOUN
ijassa-1351	246	42	and	and	CCONJ
ijassa-1351	246	43	service	service	NOUN
ijassa-1351	246	44	times	time	NOUN
ijassa-1351	246	45	.	.	PUNCT
ijassa-1351	247	1	in	in	ADP
ijassa-1351	247	2	particular	particular	ADJ
ijassa-1351	247	3	,	,	PUNCT
ijassa-1351	247	4	dependence	dependence	NOUN
ijassa-1351	247	5	on	on	ADP
ijassa-1351	247	6	hk	hk	PROPN
ijassa-1351	247	7	naturally	naturally	ADV
ijassa-1351	247	8	arises	arise	VERB
ijassa-1351	247	9	for	for	ADP
ijassa-1351	247	10	an	an	DET
ijassa-1351	247	11	exponential	exponential	ADJ
ijassa-1351	247	12	distribution	distribution	NOUN
ijassa-1351	247	13	,	,	PUNCT
ijassa-1351	247	14	and	and	CCONJ
ijassa-1351	247	15	for	for	ADP
ijassa-1351	247	16	example	example	NOUN
ijassa-1351	247	17	,	,	PUNCT
ijassa-1351	247	18	in	in	ADP
ijassa-1351	247	19	the	the	DET
ijassa-1351	247	20	case	case	NOUN
ijassa-1351	247	21	of	of	ADP
ijassa-1351	247	22	distributions	distribution	NOUN
ijassa-1351	247	23	with	with	ADP
ijassa-1351	247	24	heavy	heavy	ADJ
ijassa-1351	247	25	(	(	PUNCT
ijassa-1351	247	26	power	power	NOUN
ijassa-1351	247	27	-	-	PUNCT
ijassa-1351	247	28	law	law	NOUN
ijassa-1351	247	29	)	)	PUNCT
ijassa-1351	247	30	tails	tail	NOUN
ijassa-1351	247	31	(	(	PUNCT
ijassa-1351	247	32	for	for	ADP
ijassa-1351	247	33	example	example	NOUN
ijassa-1351	247	34	,	,	PUNCT
ijassa-1351	247	35	as	as	ADP
ijassa-1351	247	36	in	in	ADP
ijassa-1351	247	37	[	[	X
ijassa-1351	247	38	12	12	NUM
ijassa-1351	247	39	]	]	NUM
ijassa-1351	247	40	)	)	PUNCT
ijassa-1351	247	41	,	,	PUNCT
ijassa-1351	247	42	dependence	dependence	NOUN
ijassa-1351	247	43	on	on	ADP
ijassa-1351	247	44	some	some	DET
ijassa-1351	247	45	degree	degree	NOUN
ijassa-1351	247	46	of	of	ADP
ijassa-1351	247	47	k	k	PROPN
ijassa-1351	247	48	will	will	AUX
ijassa-1351	247	49	be	be	AUX
ijassa-1351	247	50	natural	natural	ADJ
ijassa-1351	247	51	.	.	PUNCT
ijassa-1351	248	1	however	however	ADV
ijassa-1351	248	2	,	,	PUNCT
ijassa-1351	248	3	the	the	DET
ijassa-1351	248	4	general	general	ADJ
ijassa-1351	248	5	approach	approach	NOUN
ijassa-1351	248	6	to	to	ADP
ijassa-1351	248	7	constructing	construct	VERB
ijassa-1351	248	8	an	an	DET
ijassa-1351	248	9	estimate	estimate	NOUN
ijassa-1351	248	10	for	for	ADP
ijassa-1351	248	11	∆	∆	PROPN
ijassa-1351	248	12	,	,	PUNCT
ijassa-1351	248	13	described	describe	VERB
ijassa-1351	248	14	by	by	ADP
ijassa-1351	248	15	the	the	DET
ijassa-1351	248	16	example	example	NOUN
ijassa-1351	248	17	of	of	ADP
ijassa-1351	248	18	deriving	derive	VERB
ijassa-1351	248	19	the	the	DET
ijassa-1351	248	20	(	(	PUNCT
ijassa-1351	248	21	3.21	3.21	NUM
ijassa-1351	248	22	)	)	PUNCT
ijassa-1351	248	23	expression	expression	NOUN
ijassa-1351	248	24	,	,	PUNCT
ijassa-1351	248	25	can	can	AUX
ijassa-1351	248	26	be	be	AUX
ijassa-1351	248	27	applied	apply	VERB
ijassa-1351	248	28	to	to	ADP
ijassa-1351	248	29	other	other	ADJ
ijassa-1351	248	30	types	type	NOUN
ijassa-1351	248	31	of	of	ADP
ijassa-1351	248	32	qs	qs	ADP
ijassa-1351	248	33	fork	fork	NOUN
ijassa-1351	248	34	-	-	PUNCT
ijassa-1351	248	35	join	join	NOUN
ijassa-1351	248	36	subsystems	subsystem	NOUN
ijassa-1351	248	37	.	.	PUNCT
ijassa-1351	249	1	4	4	X
ijassa-1351	249	2	.	.	X
ijassa-1351	249	3	conclusion	conclusion	VERB
ijassa-1351	249	4	the	the	DET
ijassa-1351	249	5	paper	paper	NOUN
ijassa-1351	249	6	presents	present	VERB
ijassa-1351	249	7	an	an	DET
ijassa-1351	249	8	approach	approach	NOUN
ijassa-1351	249	9	to	to	ADP
ijassa-1351	249	10	obtaining	obtain	VERB
ijassa-1351	249	11	more	more	ADV
ijassa-1351	249	12	accurate	accurate	ADJ
ijassa-1351	249	13	than	than	ADP
ijassa-1351	249	14	known	know	VERB
ijassa-1351	249	15	estimates	estimate	NOUN
ijassa-1351	249	16	for	for	ADP
ijassa-1351	249	17	the	the	DET
ijassa-1351	249	18	expectation	expectation	NOUN
ijassa-1351	249	19	and	and	CCONJ
ijassa-1351	249	20	response	response	NOUN
ijassa-1351	249	21	time	time	NOUN
ijassa-1351	249	22	variance	variance	NOUN
ijassa-1351	249	23	of	of	ADP
ijassa-1351	249	24	a	a	DET
ijassa-1351	249	25	fork	fork	NOUN
ijassa-1351	249	26	-	-	PUNCT
ijassa-1351	249	27	join	join	NOUN
ijassa-1351	249	28	system	system	NOUN
ijassa-1351	249	29	with	with	ADP
ijassa-1351	249	30	k	k	PROPN
ijassa-1351	249	31	subsystems	subsystems	PROPN
ijassa-1351	249	32	m	m	VERB
ijassa-1351	249	33	|m	|m	NOUN
ijassa-1351	249	34	|1	|1	X
ijassa-1351	249	35	.	.	PUNCT
ijassa-1351	250	1	as	as	SCONJ
ijassa-1351	250	2	shown	show	VERB
ijassa-1351	250	3	by	by	ADP
ijassa-1351	250	4	the	the	DET
ijassa-1351	250	5	numerical	numerical	ADJ
ijassa-1351	250	6	experiment	experiment	NOUN
ijassa-1351	250	7	,	,	PUNCT
ijassa-1351	250	8	the	the	DET
ijassa-1351	250	9	obtained	obtain	VERB
ijassa-1351	250	10	analytical	analytical	ADJ
ijassa-1351	250	11	formulas	formula	NOUN
ijassa-1351	250	12	are	be	AUX
ijassa-1351	250	13	valid	valid	ADJ
ijassa-1351	250	14	for	for	ADP
ijassa-1351	250	15	a	a	DET
ijassa-1351	250	16	wide	wide	ADJ
ijassa-1351	250	17	range	range	NOUN
ijassa-1351	250	18	of	of	ADP
ijassa-1351	250	19	values	value	NOUN
ijassa-1351	250	20	of	of	ADP
ijassa-1351	250	21	the	the	DET
ijassa-1351	250	22	parameters	parameter	NOUN
ijassa-1351	250	23	included	include	VERB
ijassa-1351	250	24	in	in	ADP
ijassa-1351	250	25	them	they	PRON
ijassa-1351	250	26	.	.	PUNCT
ijassa-1351	251	1	the	the	DET
ijassa-1351	251	2	considered	consider	VERB
ijassa-1351	251	3	approach	approach	NOUN
ijassa-1351	251	4	can	can	AUX
ijassa-1351	251	5	be	be	AUX
ijassa-1351	251	6	used	use	VERB
ijassa-1351	251	7	to	to	PART
ijassa-1351	251	8	construct	construct	VERB
ijassa-1351	251	9	good	good	ADJ
ijassa-1351	251	10	quality	quality	NOUN
ijassa-1351	251	11	estimates	estimate	NOUN
ijassa-1351	251	12	in	in	ADP
ijassa-1351	251	13	more	more	ADJ
ijassa-1351	251	14	complex	complex	ADJ
ijassa-1351	251	15	cases	case	NOUN
ijassa-1351	251	16	.	.	PUNCT
ijassa-1351	252	1	for	for	ADP
ijassa-1351	252	2	example	example	NOUN
ijassa-1351	252	3	,	,	PUNCT
ijassa-1351	252	4	when	when	SCONJ
ijassa-1351	252	5	the	the	DET
ijassa-1351	252	6	subsystems	subsystem	NOUN
ijassa-1351	252	7	are	be	AUX
ijassa-1351	252	8	queuing	queue	VERB
ijassa-1351	252	9	systems	system	NOUN
ijassa-1351	252	10	of	of	ADP
ijassa-1351	252	11	the	the	DET
ijassa-1351	252	12	form	form	NOUN
ijassa-1351	252	13	g|g|1	g|g|1	NOUN
ijassa-1351	252	14	,	,	PUNCT
ijassa-1351	252	15	which	which	PRON
ijassa-1351	252	16	can	can	AUX
ijassa-1351	252	17	be	be	AUX
ijassa-1351	252	18	the	the	DET
ijassa-1351	252	19	subject	subject	NOUN
ijassa-1351	252	20	of	of	ADP
ijassa-1351	252	21	further	further	ADJ
ijassa-1351	252	22	research	research	NOUN
ijassa-1351	252	23	.	.	PUNCT
ijassa-1351	253	1	in	in	ADP
ijassa-1351	253	2	addition	addition	NOUN
ijassa-1351	253	3	,	,	PUNCT
ijassa-1351	253	4	the	the	DET
ijassa-1351	253	5	article	article	NOUN
ijassa-1351	253	6	describes	describe	VERB
ijassa-1351	253	7	the	the	DET
ijassa-1351	253	8	essential	essential	ADJ
ijassa-1351	253	9	aspects	aspect	NOUN
ijassa-1351	253	10	of	of	ADP
ijassa-1351	253	11	fork	fork	NOUN
ijassa-1351	253	12	-	-	PUNCT
ijassa-1351	253	13	join	join	NOUN
ijassa-1351	253	14	qs	qs	NOUN
ijassa-1351	253	15	simulation	simulation	NOUN
ijassa-1351	253	16	and	and	CCONJ
ijassa-1351	253	17	the	the	DET
ijassa-1351	253	18	evaluation	evaluation	NOUN
ijassa-1351	253	19	of	of	ADP
ijassa-1351	253	20	its	its	PRON
ijassa-1351	253	21	results	result	NOUN
ijassa-1351	253	22	,	,	PUNCT
ijassa-1351	253	23	which	which	PRON
ijassa-1351	253	24	is	be	AUX
ijassa-1351	253	25	an	an	DET
ijassa-1351	253	26	integral	integral	ADJ
ijassa-1351	253	27	part	part	NOUN
ijassa-1351	253	28	of	of	ADP
ijassa-1351	253	29	the	the	DET
ijassa-1351	253	30	organization	organization	NOUN
ijassa-1351	253	31	of	of	ADP
ijassa-1351	253	32	a	a	DET
ijassa-1351	253	33	numerical	numerical	ADJ
ijassa-1351	253	34	experiment	experiment	NOUN
ijassa-1351	253	35	to	to	PART
ijassa-1351	253	36	check	check	VERB
ijassa-1351	253	37	the	the	DET
ijassa-1351	253	38	quality	quality	NOUN
ijassa-1351	253	39	of	of	ADP
ijassa-1351	253	40	approximation	approximation	NOUN
ijassa-1351	253	41	of	of	ADP
ijassa-1351	253	42	any	any	DET
ijassa-1351	253	43	approximation	approximation	NOUN
ijassa-1351	253	44	.	.	PUNCT
ijassa-1351	254	1	an	an	DET
ijassa-1351	254	2	algorithm	algorithm	NOUN
ijassa-1351	254	3	for	for	ADP
ijassa-1351	254	4	copyright	copyright	NOUN
ijassa-1351	254	5	©	©	PROPN
ijassa-1351	254	6	2023	2023	NUM
ijassa-1351	254	7	assa	assa	NOUN
ijassa-1351	254	8	.	.	PUNCT
ijassa-1351	255	1	adv	adv	PROPN
ijassa-1351	255	2	syst	syst	PROPN
ijassa-1351	255	3	sci	sci	PROPN
ijassa-1351	255	4	appl	appl	PROPN
ijassa-1351	255	5	(	(	PUNCT
ijassa-1351	255	6	2023	2023	NUM
ijassa-1351	255	7	)	)	PUNCT
ijassa-1351	255	8	assa	assa	NOUN
ijassa-1351	255	9	latex	latex	NOUN
ijassa-1351	255	10	template	template	NOUN
ijassa-1351	255	11	113	113	NUM
ijassa-1351	255	12	constructing	construct	VERB
ijassa-1351	255	13	confidence	confidence	NOUN
ijassa-1351	255	14	intervals	interval	NOUN
ijassa-1351	255	15	for	for	ADP
ijassa-1351	255	16	sample	sample	NOUN
ijassa-1351	255	17	estimates	estimate	NOUN
ijassa-1351	255	18	obtained	obtain	VERB
ijassa-1351	255	19	by	by	ADP
ijassa-1351	255	20	simulating	simulate	VERB
ijassa-1351	255	21	the	the	DET
ijassa-1351	255	22	functioning	functioning	NOUN
ijassa-1351	255	23	of	of	ADP
ijassa-1351	255	24	a	a	DET
ijassa-1351	255	25	fork	fork	NOUN
ijassa-1351	255	26	-	-	PUNCT
ijassa-1351	255	27	join	join	NOUN
ijassa-1351	255	28	qs	qs	NOUN
ijassa-1351	255	29	is	be	AUX
ijassa-1351	255	30	presented	present	VERB
ijassa-1351	255	31	,	,	PUNCT
ijassa-1351	255	32	and	and	CCONJ
ijassa-1351	255	33	some	some	DET
ijassa-1351	255	34	recommendations	recommendation	NOUN
ijassa-1351	255	35	are	be	AUX
ijassa-1351	255	36	also	also	ADV
ijassa-1351	255	37	given	give	VERB
ijassa-1351	255	38	.	.	PUNCT
ijassa-1351	256	1	references	reference	NOUN
ijassa-1351	256	2	1	1	NUM
ijassa-1351	256	3	.	.	PUNCT
ijassa-1351	257	1	nguyen	nguyen	NOUN
ijassa-1351	257	2	,	,	PUNCT
ijassa-1351	257	3	m.	m.	NOUN
ijassa-1351	257	4	,	,	PUNCT
ijassa-1351	257	5	alesawi	alesawi	PROPN
ijassa-1351	257	6	,	,	PUNCT
ijassa-1351	257	7	s.	s.	PROPN
ijassa-1351	257	8	,	,	PUNCT
ijassa-1351	257	9	li	li	PROPN
ijassa-1351	257	10	,	,	PUNCT
ijassa-1351	257	11	n.	n.	NOUN
ijassa-1351	257	12	,	,	PUNCT
ijassa-1351	257	13	che	che	PROPN
ijassa-1351	257	14	,	,	PUNCT
ijassa-1351	257	15	h.	h.	PROPN
ijassa-1351	257	16	&	&	CCONJ
ijassa-1351	257	17	jiang	jiang	PROPN
ijassa-1351	257	18	,	,	PUNCT
ijassa-1351	257	19	h.	h.	PROPN
ijassa-1351	257	20	(	(	PUNCT
ijassa-1351	257	21	2020	2020	NUM
ijassa-1351	257	22	)	)	PUNCT
ijassa-1351	257	23	.	.	PUNCT
ijassa-1351	258	1	a	a	DET
ijassa-1351	258	2	black	black	ADJ
ijassa-1351	258	3	-	-	PUNCT
ijassa-1351	258	4	box	box	NOUN
ijassa-1351	258	5	forkjoin	forkjoin	NOUN
ijassa-1351	258	6	latency	latency	NOUN
ijassa-1351	258	7	prediction	prediction	NOUN
ijassa-1351	258	8	model	model	NOUN
ijassa-1351	258	9	for	for	ADP
ijassa-1351	258	10	data	data	NOUN
ijassa-1351	258	11	-	-	PUNCT
ijassa-1351	258	12	intensive	intensive	ADJ
ijassa-1351	258	13	applications	application	NOUN
ijassa-1351	258	14	,	,	PUNCT
ijassa-1351	258	15	ieee	ieee	NOUN
ijassa-1351	258	16	transactions	transaction	NOUN
ijassa-1351	258	17	on	on	ADP
ijassa-1351	258	18	parallel	parallel	ADJ
ijassa-1351	258	19	and	and	CCONJ
ijassa-1351	258	20	distributed	distributed	ADJ
ijassa-1351	258	21	systems	system	NOUN
ijassa-1351	258	22	,	,	PUNCT
ijassa-1351	258	23	31(9	31(9	NUM
ijassa-1351	258	24	)	)	PUNCT
ijassa-1351	258	25	,	,	PUNCT
ijassa-1351	258	26	1983	1983	NUM
ijassa-1351	258	27	-	-	SYM
ijassa-1351	258	28	2000	2000	NUM
ijassa-1351	258	29	.	.	PUNCT
ijassa-1351	259	1	2	2	X
ijassa-1351	259	2	.	.	X
ijassa-1351	259	3	peng	peng	PROPN
ijassa-1351	259	4	,	,	PUNCT
ijassa-1351	259	5	p.	p.	PROPN
ijassa-1351	259	6	,	,	PUNCT
ijassa-1351	259	7	soljanin	soljanin	PROPN
ijassa-1351	259	8	,	,	PUNCT
ijassa-1351	259	9	e.	e.	PROPN
ijassa-1351	259	10	&	&	CCONJ
ijassa-1351	259	11	whiting	whiting	PROPN
ijassa-1351	259	12	,	,	PUNCT
ijassa-1351	259	13	p.	p.	NOUN
ijassa-1351	259	14	(	(	PUNCT
ijassa-1351	259	15	2022	2022	NUM
ijassa-1351	259	16	)	)	PUNCT
ijassa-1351	259	17	.	.	PUNCT
ijassa-1351	260	1	diversity	diversity	NOUN
ijassa-1351	260	2	/	/	SYM
ijassa-1351	260	3	parallelism	parallelism	NOUN
ijassa-1351	260	4	trade	trade	NOUN
ijassa-1351	260	5	-	-	PUNCT
ijassa-1351	260	6	off	off	NOUN
ijassa-1351	260	7	in	in	ADP
ijassa-1351	260	8	distributed	distribute	VERB
ijassa-1351	260	9	systems	system	NOUN
ijassa-1351	260	10	with	with	ADP
ijassa-1351	260	11	redundancy	redundancy	NOUN
ijassa-1351	260	12	ieee	ieee	NOUN
ijassa-1351	260	13	transactions	transaction	NOUN
ijassa-1351	260	14	on	on	ADP
ijassa-1351	260	15	information	information	NOUN
ijassa-1351	260	16	theory	theory	NOUN
ijassa-1351	260	17	,	,	PUNCT
ijassa-1351	260	18	68(2	68(2	NOUN
ijassa-1351	260	19	)	)	PUNCT
ijassa-1351	260	20	,	,	PUNCT
ijassa-1351	260	21	1279	1279	NUM
ijassa-1351	260	22	-	-	SYM
ijassa-1351	260	23	1295	1295	NUM
ijassa-1351	260	24	.	.	PUNCT
ijassa-1351	261	1	3	3	X
ijassa-1351	261	2	.	.	X
ijassa-1351	261	3	samyukta	samyukta	NOUN
ijassa-1351	261	4	sethuraman	sethuraman	NOUN
ijassa-1351	261	5	(	(	PUNCT
ijassa-1351	261	6	2022	2022	NUM
ijassa-1351	261	7	)	)	PUNCT
ijassa-1351	261	8	.	.	PUNCT
ijassa-1351	262	1	analysis	analysis	NOUN
ijassa-1351	262	2	of	of	ADP
ijassa-1351	262	3	fork	fork	NOUN
ijassa-1351	262	4	-	-	PUNCT
ijassa-1351	262	5	join	join	NOUN
ijassa-1351	262	6	systems	system	NOUN
ijassa-1351	262	7	:	:	PUNCT
ijassa-1351	262	8	network	network	NOUN
ijassa-1351	262	9	of	of	ADP
ijassa-1351	262	10	queues	queue	NOUN
ijassa-1351	262	11	with	with	ADP
ijassa-1351	262	12	precedence	precedence	NOUN
ijassa-1351	262	13	constraints	constraint	NOUN
ijassa-1351	262	14	.	.	PUNCT
ijassa-1351	263	1	boca	boca	PROPN
ijassa-1351	263	2	-	-	PUNCT
ijassa-1351	263	3	raton	raton	PROPN
ijassa-1351	263	4	,	,	PUNCT
ijassa-1351	263	5	fl	fl	PROPN
ijassa-1351	263	6	:	:	PUNCT
ijassa-1351	263	7	crc	crc	NOUN
ijassa-1351	263	8	press	press	NOUN
ijassa-1351	263	9	.	.	PUNCT
ijassa-1351	264	1	4	4	X
ijassa-1351	264	2	.	.	X
ijassa-1351	264	3	de	de	PROPN
ijassa-1351	264	4	oliveira	oliveira	PROPN
ijassa-1351	264	5	,	,	PUNCT
ijassa-1351	264	6	d.	d.	PROPN
ijassa-1351	264	7	c.	c.	PROPN
ijassa-1351	264	8	m.	m.	PROPN
ijassa-1351	264	9	,	,	PUNCT
ijassa-1351	264	10	liu	liu	PROPN
ijassa-1351	264	11	,	,	PUNCT
ijassa-1351	264	12	j.	j.	PROPN
ijassa-1351	264	13	&	&	CCONJ
ijassa-1351	264	14	pacitti	pacitti	PROPN
ijassa-1351	264	15	,	,	PUNCT
ijassa-1351	264	16	e.	e.	PROPN
ijassa-1351	264	17	(	(	PUNCT
ijassa-1351	264	18	2019	2019	NUM
ijassa-1351	264	19	)	)	PUNCT
ijassa-1351	264	20	.	.	PUNCT
ijassa-1351	265	1	data	datum	NOUN
ijassa-1351	265	2	-	-	PUNCT
ijassa-1351	265	3	intensive	intensive	ADJ
ijassa-1351	265	4	workflow	workflow	NOUN
ijassa-1351	265	5	management	management	NOUN
ijassa-1351	265	6	:	:	PUNCT
ijassa-1351	265	7	for	for	ADP
ijassa-1351	265	8	clouds	cloud	NOUN
ijassa-1351	265	9	and	and	CCONJ
ijassa-1351	265	10	data	datum	NOUN
ijassa-1351	265	11	-	-	PUNCT
ijassa-1351	265	12	intensive	intensive	ADJ
ijassa-1351	265	13	and	and	CCONJ
ijassa-1351	265	14	scalable	scalable	ADJ
ijassa-1351	265	15	computing	compute	VERB
ijassa-1351	265	16	environments	environment	NOUN
ijassa-1351	265	17	.	.	PUNCT
ijassa-1351	266	1	san	san	PROPN
ijassa-1351	266	2	rafael	rafael	PROPN
ijassa-1351	266	3	,	,	PUNCT
ijassa-1351	266	4	ca	ca	PROPN
ijassa-1351	266	5	:	:	PUNCT
ijassa-1351	266	6	morgan	morgan	PROPN
ijassa-1351	266	7	&	&	CCONJ
ijassa-1351	266	8	claypool	claypool	PROPN
ijassa-1351	266	9	publishers	publisher	NOUN
ijassa-1351	266	10	.	.	PUNCT
ijassa-1351	267	1	5	5	X
ijassa-1351	267	2	.	.	X
ijassa-1351	267	3	khalid	khalid	PROPN
ijassa-1351	267	4	,	,	PUNCT
ijassa-1351	267	5	m.	m.	PROPN
ijassa-1351	267	6	&	&	CCONJ
ijassa-1351	267	7	yousaf	yousaf	PROPN
ijassa-1351	267	8	,	,	PUNCT
ijassa-1351	267	9	m.	m.	NOUN
ijassa-1351	267	10	m.	m.	NOUN
ijassa-1351	267	11	(	(	PUNCT
ijassa-1351	267	12	2021	2021	NUM
ijassa-1351	267	13	)	)	PUNCT
ijassa-1351	267	14	.	.	PUNCT
ijassa-1351	268	1	a	a	DET
ijassa-1351	268	2	comparative	comparative	ADJ
ijassa-1351	268	3	analysis	analysis	NOUN
ijassa-1351	268	4	of	of	ADP
ijassa-1351	268	5	big	big	ADJ
ijassa-1351	268	6	data	datum	NOUN
ijassa-1351	268	7	frameworks	framework	NOUN
ijassa-1351	268	8	:	:	PUNCT
ijassa-1351	268	9	an	an	DET
ijassa-1351	268	10	adoption	adoption	NOUN
ijassa-1351	268	11	perspective	perspective	NOUN
ijassa-1351	268	12	,	,	PUNCT
ijassa-1351	268	13	applied	apply	VERB
ijassa-1351	268	14	sciences	science	NOUN
ijassa-1351	268	15	,	,	PUNCT
ijassa-1351	268	16	11(22	11(22	PROPN
ijassa-1351	268	17	)	)	PUNCT
ijassa-1351	268	18	,	,	PUNCT
ijassa-1351	268	19	11033	11033	NUM
ijassa-1351	268	20	.	.	PUNCT
ijassa-1351	269	1	6	6	NUM
ijassa-1351	269	2	.	.	X
ijassa-1351	269	3	nelson	nelson	PROPN
ijassa-1351	269	4	,	,	PUNCT
ijassa-1351	269	5	r.	r.	PROPN
ijassa-1351	269	6	&	&	CCONJ
ijassa-1351	269	7	tantawi	tantawi	PROPN
ijassa-1351	269	8	,	,	PUNCT
ijassa-1351	269	9	a.	a.	PROPN
ijassa-1351	269	10	n.	n.	PROPN
ijassa-1351	269	11	(	(	PUNCT
ijassa-1351	269	12	1988	1988	NUM
ijassa-1351	269	13	)	)	PUNCT
ijassa-1351	269	14	.	.	PUNCT
ijassa-1351	270	1	approximate	approximate	ADJ
ijassa-1351	270	2	analysis	analysis	NOUN
ijassa-1351	270	3	of	of	ADP
ijassa-1351	270	4	fork	fork	NOUN
ijassa-1351	270	5	/	/	SYM
ijassa-1351	270	6	join	join	NOUN
ijassa-1351	270	7	synchronization	synchronization	NOUN
ijassa-1351	270	8	in	in	ADP
ijassa-1351	270	9	parallel	parallel	ADJ
ijassa-1351	270	10	queues	queue	NOUN
ijassa-1351	270	11	,	,	PUNCT
ijassa-1351	270	12	ieee	ieee	NOUN
ijassa-1351	270	13	transactions	transaction	NOUN
ijassa-1351	270	14	on	on	ADP
ijassa-1351	270	15	computers	computer	NOUN
ijassa-1351	270	16	,	,	PUNCT
ijassa-1351	270	17	37(6	37(6	NUM
ijassa-1351	270	18	)	)	PUNCT
ijassa-1351	270	19	,	,	PUNCT
ijassa-1351	270	20	739–743	739–743	NUM
ijassa-1351	270	21	.	.	PUNCT
ijassa-1351	271	1	7	7	X
ijassa-1351	271	2	.	.	X
ijassa-1351	271	3	varki	varki	NOUN
ijassa-1351	271	4	,	,	PUNCT
ijassa-1351	271	5	e.	e.	PROPN
ijassa-1351	271	6	,	,	PUNCT
ijassa-1351	271	7	merchant	merchant	NOUN
ijassa-1351	271	8	,	,	PUNCT
ijassa-1351	271	9	a.	a.	PROPN
ijassa-1351	271	10	&	&	CCONJ
ijassa-1351	271	11	chen	chen	PROPN
ijassa-1351	271	12	,	,	PUNCT
ijassa-1351	271	13	h.	h.	PROPN
ijassa-1351	271	14	(	(	PUNCT
ijassa-1351	271	15	2002	2002	NUM
ijassa-1351	271	16	)	)	PUNCT
ijassa-1351	271	17	.	.	PUNCT
ijassa-1351	272	1	the	the	DET
ijassa-1351	272	2	m	m	PROPN
ijassa-1351	272	3	/	/	SYM
ijassa-1351	272	4	m/1	m/1	NOUN
ijassa-1351	272	5	fork	fork	NOUN
ijassa-1351	272	6	-	-	PUNCT
ijassa-1351	272	7	join	join	NOUN
ijassa-1351	272	8	queue	queue	NOUN
ijassa-1351	272	9	with	with	ADP
ijassa-1351	272	10	variable	variable	ADJ
ijassa-1351	272	11	subtasks	subtask	NOUN
ijassa-1351	272	12	,	,	PUNCT
ijassa-1351	272	13	[	[	X
ijassa-1351	272	14	online	online	X
ijassa-1351	272	15	]	]	X
ijassa-1351	272	16	.	.	PUNCT
ijassa-1351	273	1	available	available	ADJ
ijassa-1351	273	2	:	:	PUNCT
ijassa-1351	273	3	http://www.cs.unh.edu/	http://www.cs.unh.edu/	PROPN
ijassa-1351	273	4	varki	varki	VERB
ijassa-1351	273	5	/	/	SYM
ijassa-1351	273	6	publication/2002nov	publication/2002nov	NOUN
ijassa-1351	273	7	-	-	SYM
ijassa-1351	273	8	open.pdf	open.pdf	PROPN
ijassa-1351	273	9	.	.	NOUN
ijassa-1351	273	10	8	8	NUM
ijassa-1351	273	11	.	.	X
ijassa-1351	273	12	varma	varma	PROPN
ijassa-1351	273	13	,	,	PUNCT
ijassa-1351	273	14	s.	s.	PROPN
ijassa-1351	273	15	&	&	CCONJ
ijassa-1351	273	16	makowski	makowski	PROPN
ijassa-1351	273	17	,	,	PUNCT
ijassa-1351	273	18	a.	a.	NOUN
ijassa-1351	273	19	m.	m.	NOUN
ijassa-1351	273	20	(	(	PUNCT
ijassa-1351	273	21	1994	1994	NUM
ijassa-1351	273	22	)	)	PUNCT
ijassa-1351	273	23	.	.	PUNCT
ijassa-1351	274	1	interpolation	interpolation	NOUN
ijassa-1351	274	2	approximations	approximation	NOUN
ijassa-1351	274	3	for	for	ADP
ijassa-1351	274	4	symmetric	symmetric	ADJ
ijassa-1351	274	5	fork	fork	NOUN
ijassa-1351	274	6	-	-	PUNCT
ijassa-1351	274	7	join	join	NOUN
ijassa-1351	274	8	queues	queue	NOUN
ijassa-1351	274	9	,	,	PUNCT
ijassa-1351	274	10	performance	performance	NOUN
ijassa-1351	274	11	evaluation	evaluation	NOUN
ijassa-1351	274	12	,	,	PUNCT
ijassa-1351	274	13	20	20	NUM
ijassa-1351	274	14	,	,	PUNCT
ijassa-1351	274	15	245–265	245–265	NUM
ijassa-1351	274	16	.	.	NOUN
ijassa-1351	275	1	9	9	NUM
ijassa-1351	275	2	.	.	X
ijassa-1351	275	3	kemper	kemper	PROPN
ijassa-1351	275	4	,	,	PUNCT
ijassa-1351	275	5	b.	b.	PROPN
ijassa-1351	275	6	&	&	CCONJ
ijassa-1351	275	7	mandjes	mandjes	PROPN
ijassa-1351	275	8	,	,	PUNCT
ijassa-1351	275	9	m.	m.	NOUN
ijassa-1351	275	10	(	(	PUNCT
ijassa-1351	275	11	2012	2012	NUM
ijassa-1351	275	12	)	)	PUNCT
ijassa-1351	275	13	.	.	PUNCT
ijassa-1351	276	1	mean	mean	VERB
ijassa-1351	276	2	sojourn	sojourn	NOUN
ijassa-1351	276	3	time	time	NOUN
ijassa-1351	276	4	in	in	ADP
ijassa-1351	276	5	two	two	NUM
ijassa-1351	276	6	-	-	PUNCT
ijassa-1351	276	7	queue	queue	NOUN
ijassa-1351	276	8	fork	fork	NOUN
ijassa-1351	276	9	-	-	PUNCT
ijassa-1351	276	10	join	join	NOUN
ijassa-1351	276	11	systems	system	NOUN
ijassa-1351	276	12	:	:	PUNCT
ijassa-1351	276	13	bounds	bound	NOUN
ijassa-1351	276	14	and	and	CCONJ
ijassa-1351	276	15	approximations	approximation	NOUN
ijassa-1351	276	16	,	,	PUNCT
ijassa-1351	276	17	or	or	CCONJ
ijassa-1351	276	18	spectrum	spectrum	NOUN
ijassa-1351	276	19	,	,	PUNCT
ijassa-1351	276	20	34	34	NUM
ijassa-1351	276	21	,	,	PUNCT
ijassa-1351	276	22	723–742	723–742	NUM
ijassa-1351	276	23	.	.	PUNCT
ijassa-1351	276	24	10	10	NUM
ijassa-1351	276	25	.	.	PUNCT
ijassa-1351	277	1	david	david	PROPN
ijassa-1351	277	2	,	,	PUNCT
ijassa-1351	277	3	h.	h.	PROPN
ijassa-1351	277	4	a.	a.	PROPN
ijassa-1351	277	5	&	&	CCONJ
ijassa-1351	277	6	nadaraja	nadaraja	PROPN
ijassa-1351	277	7	,	,	PUNCT
ijassa-1351	277	8	h.	h.	PROPN
ijassa-1351	277	9	n.	n.	PROPN
ijassa-1351	277	10	(	(	PUNCT
ijassa-1351	277	11	2003	2003	NUM
ijassa-1351	277	12	)	)	PUNCT
ijassa-1351	277	13	.	.	PUNCT
ijassa-1351	278	1	order	order	NOUN
ijassa-1351	278	2	statistics	statistic	NOUN
ijassa-1351	278	3	.	.	PUNCT
ijassa-1351	279	1	hoboken	hoboken	PROPN
ijassa-1351	279	2	,	,	PUNCT
ijassa-1351	279	3	nj	nj	PROPN
ijassa-1351	279	4	:	:	PUNCT
ijassa-1351	279	5	john	john	PROPN
ijassa-1351	279	6	wiley	wiley	PROPN
ijassa-1351	279	7	&	&	CCONJ
ijassa-1351	279	8	sons	son	NOUN
ijassa-1351	279	9	.	.	PUNCT
ijassa-1351	280	1	11	11	NUM
ijassa-1351	280	2	.	.	X
ijassa-1351	280	3	gorbunova	gorbunova	PROPN
ijassa-1351	280	4	,	,	PUNCT
ijassa-1351	280	5	a.	a.	PROPN
ijassa-1351	280	6	v.	v.	PROPN
ijassa-1351	280	7	&	&	CCONJ
ijassa-1351	280	8	vishnevsky	vishnevsky	PROPN
ijassa-1351	280	9	,	,	PUNCT
ijassa-1351	280	10	v.	v.	ADP
ijassa-1351	280	11	m.	m.	NOUN
ijassa-1351	280	12	(	(	PUNCT
ijassa-1351	280	13	2020	2020	NUM
ijassa-1351	280	14	)	)	PUNCT
ijassa-1351	280	15	.	.	PUNCT
ijassa-1351	281	1	estimating	estimate	VERB
ijassa-1351	281	2	the	the	DET
ijassa-1351	281	3	response	response	NOUN
ijassa-1351	281	4	time	time	NOUN
ijassa-1351	281	5	of	of	ADP
ijassa-1351	281	6	a	a	DET
ijassa-1351	281	7	cloud	cloud	NOUN
ijassa-1351	281	8	computing	compute	VERB
ijassa-1351	281	9	system	system	NOUN
ijassa-1351	281	10	with	with	ADP
ijassa-1351	281	11	the	the	DET
ijassa-1351	281	12	help	help	NOUN
ijassa-1351	281	13	of	of	ADP
ijassa-1351	281	14	neural	neural	ADJ
ijassa-1351	281	15	networks	network	NOUN
ijassa-1351	281	16	,	,	PUNCT
ijassa-1351	281	17	advances	advance	NOUN
ijassa-1351	281	18	in	in	ADP
ijassa-1351	281	19	systems	system	NOUN
ijassa-1351	281	20	science	science	NOUN
ijassa-1351	281	21	and	and	CCONJ
ijassa-1351	281	22	applications	application	NOUN
ijassa-1351	281	23	,	,	PUNCT
ijassa-1351	281	24	20(3	20(3	NOUN
ijassa-1351	281	25	)	)	PUNCT
ijassa-1351	281	26	,	,	PUNCT
ijassa-1351	281	27	105–112	105–112	NUM
ijassa-1351	281	28	.	.	PUNCT
ijassa-1351	282	1	12	12	NUM
ijassa-1351	282	2	.	.	PUNCT
ijassa-1351	282	3	gorbunova	gorbunova	PROPN
ijassa-1351	282	4	,	,	PUNCT
ijassa-1351	282	5	a.	a.	PROPN
ijassa-1351	282	6	v.	v.	PROPN
ijassa-1351	282	7	&	&	CCONJ
ijassa-1351	282	8	lebedev	lebedev	PROPN
ijassa-1351	282	9	,	,	PUNCT
ijassa-1351	282	10	a.	a.	PROPN
ijassa-1351	282	11	v.	v.	PROPN
ijassa-1351	282	12	(	(	PUNCT
ijassa-1351	282	13	2022	2022	NUM
ijassa-1351	282	14	)	)	PUNCT
ijassa-1351	282	15	.	.	PUNCT
ijassa-1351	283	1	response	response	NOUN
ijassa-1351	283	2	time	time	NOUN
ijassa-1351	283	3	estimate	estimate	NOUN
ijassa-1351	283	4	for	for	ADP
ijassa-1351	283	5	a	a	DET
ijassa-1351	283	6	fork	fork	NOUN
ijassa-1351	283	7	-	-	PUNCT
ijassa-1351	283	8	join	join	NOUN
ijassa-1351	283	9	system	system	NOUN
ijassa-1351	283	10	with	with	ADP
ijassa-1351	283	11	pareto	pareto	ADJ
ijassa-1351	283	12	distributed	distribute	VERB
ijassa-1351	283	13	service	service	NOUN
ijassa-1351	283	14	time	time	NOUN
ijassa-1351	283	15	as	as	ADP
ijassa-1351	283	16	a	a	DET
ijassa-1351	283	17	model	model	NOUN
ijassa-1351	283	18	of	of	ADP
ijassa-1351	283	19	a	a	DET
ijassa-1351	283	20	cloud	cloud	NOUN
ijassa-1351	283	21	computing	compute	VERB
ijassa-1351	283	22	system	system	NOUN
ijassa-1351	283	23	using	use	VERB
ijassa-1351	283	24	neural	neural	ADJ
ijassa-1351	283	25	networks	network	NOUN
ijassa-1351	283	26	,	,	PUNCT
ijassa-1351	283	27	communications	communication	NOUN
ijassa-1351	283	28	in	in	ADP
ijassa-1351	283	29	computer	computer	NOUN
ijassa-1351	283	30	and	and	CCONJ
ijassa-1351	283	31	information	information	NOUN
ijassa-1351	283	32	science	science	NOUN
ijassa-1351	283	33	,	,	PUNCT
ijassa-1351	283	34	1552	1552	NUM
ijassa-1351	283	35	,	,	PUNCT
ijassa-1351	283	36	318–332	318–332	NUM
ijassa-1351	283	37	.	.	PUNCT
ijassa-1351	284	1	13	13	NUM
ijassa-1351	284	2	.	.	PUNCT
ijassa-1351	285	1	vishnevsky	vishnevsky	ADJ
ijassa-1351	285	2	,	,	PUNCT
ijassa-1351	285	3	v.	v.	ADP
ijassa-1351	285	4	m.	m.	PROPN
ijassa-1351	285	5	&	&	CCONJ
ijassa-1351	285	6	gorbunova	gorbunova	PROPN
ijassa-1351	285	7	,	,	PUNCT
ijassa-1351	285	8	a.	a.	PROPN
ijassa-1351	285	9	v.	v.	PROPN
ijassa-1351	285	10	(	(	PUNCT
ijassa-1351	285	11	2022	2022	NUM
ijassa-1351	285	12	)	)	PUNCT
ijassa-1351	285	13	.	.	PUNCT
ijassa-1351	286	1	application	application	NOUN
ijassa-1351	286	2	of	of	ADP
ijassa-1351	286	3	machine	machine	NOUN
ijassa-1351	286	4	learning	learn	VERB
ijassa-1351	286	5	methods	method	NOUN
ijassa-1351	286	6	to	to	ADP
ijassa-1351	286	7	solving	solve	VERB
ijassa-1351	286	8	problems	problem	NOUN
ijassa-1351	286	9	of	of	ADP
ijassa-1351	286	10	queuing	queue	VERB
ijassa-1351	286	11	theory	theory	NOUN
ijassa-1351	286	12	,	,	PUNCT
ijassa-1351	286	13	communications	communication	NOUN
ijassa-1351	286	14	in	in	ADP
ijassa-1351	286	15	computer	computer	NOUN
ijassa-1351	286	16	and	and	CCONJ
ijassa-1351	286	17	information	information	NOUN
ijassa-1351	286	18	science	science	NOUN
ijassa-1351	286	19	,	,	PUNCT
ijassa-1351	286	20	1605	1605	NUM
ijassa-1351	286	21	,	,	PUNCT
ijassa-1351	286	22	304–316	304–316	NUM
ijassa-1351	286	23	.	.	PUNCT
ijassa-1351	286	24	14	14	NUM
ijassa-1351	286	25	.	.	PUNCT
ijassa-1351	287	1	thomasian	thomasian	ADJ
ijassa-1351	287	2	,	,	PUNCT
ijassa-1351	287	3	a.	a.	NOUN
ijassa-1351	287	4	(	(	PUNCT
ijassa-1351	287	5	2014	2014	NUM
ijassa-1351	287	6	)	)	PUNCT
ijassa-1351	287	7	.	.	PUNCT
ijassa-1351	288	1	analysis	analysis	NOUN
ijassa-1351	288	2	of	of	ADP
ijassa-1351	288	3	fork	fork	NOUN
ijassa-1351	288	4	/	/	SYM
ijassa-1351	288	5	join	join	NOUN
ijassa-1351	288	6	and	and	CCONJ
ijassa-1351	288	7	related	related	ADJ
ijassa-1351	288	8	queueing	queueing	NOUN
ijassa-1351	288	9	systems	system	NOUN
ijassa-1351	288	10	,	,	PUNCT
ijassa-1351	288	11	acm	acm	PROPN
ijassa-1351	288	12	computing	computing	NOUN
ijassa-1351	288	13	surveys	survey	NOUN
ijassa-1351	288	14	(	(	PUNCT
ijassa-1351	288	15	csur	csur	NOUN
ijassa-1351	288	16	)	)	PUNCT
ijassa-1351	288	17	,	,	PUNCT
ijassa-1351	288	18	47(2	47(2	PROPN
ijassa-1351	288	19	)	)	PUNCT
ijassa-1351	288	20	,	,	PUNCT
ijassa-1351	288	21	17:1–17:71	17:1–17:71	NUM
ijassa-1351	288	22	.	.	PUNCT
ijassa-1351	288	23	15	15	NUM
ijassa-1351	288	24	.	.	X
ijassa-1351	289	1	qiu	qiu	PROPN
ijassa-1351	289	2	,	,	PUNCT
ijassa-1351	289	3	z.	z.	PROPN
ijassa-1351	289	4	,	,	PUNCT
ijassa-1351	289	5	perez	perez	PROPN
ijassa-1351	289	6	,	,	PUNCT
ijassa-1351	289	7	j.	j.	PROPN
ijassa-1351	289	8	f.	f.	PROPN
ijassa-1351	289	9	&	&	CCONJ
ijassa-1351	289	10	harrison	harrison	PROPN
ijassa-1351	289	11	,	,	PUNCT
ijassa-1351	289	12	p.	p.	NOUN
ijassa-1351	289	13	g.	g.	PROPN
ijassa-1351	289	14	(	(	PUNCT
ijassa-1351	289	15	2015	2015	NUM
ijassa-1351	289	16	)	)	PUNCT
ijassa-1351	289	17	.	.	PUNCT
ijassa-1351	290	1	beyond	beyond	ADP
ijassa-1351	290	2	the	the	DET
ijassa-1351	290	3	mean	mean	NOUN
ijassa-1351	290	4	in	in	ADP
ijassa-1351	290	5	fork	fork	NOUN
ijassa-1351	290	6	-	-	PUNCT
ijassa-1351	290	7	join	join	NOUN
ijassa-1351	290	8	queues	queue	NOUN
ijassa-1351	290	9	:	:	PUNCT
ijassa-1351	290	10	efficient	efficient	ADJ
ijassa-1351	290	11	approximation	approximation	NOUN
ijassa-1351	290	12	for	for	ADP
ijassa-1351	290	13	response	response	NOUN
ijassa-1351	290	14	-	-	PUNCT
ijassa-1351	290	15	time	time	NOUN
ijassa-1351	290	16	tails	tail	NOUN
ijassa-1351	290	17	,	,	PUNCT
ijassa-1351	290	18	performance	performance	NOUN
ijassa-1351	290	19	evaluation	evaluation	NOUN
ijassa-1351	290	20	,	,	PUNCT
ijassa-1351	290	21	91	91	NUM
ijassa-1351	290	22	,	,	PUNCT
ijassa-1351	290	23	99–116	99–116	PROPN
ijassa-1351	290	24	.	.	PUNCT
ijassa-1351	291	1	16	16	NUM
ijassa-1351	291	2	.	.	PUNCT
ijassa-1351	292	1	wang	wang	PROPN
ijassa-1351	292	2	,	,	PUNCT
ijassa-1351	292	3	w.	w.	PROPN
ijassa-1351	292	4	,	,	PUNCT
ijassa-1351	292	5	harchol	harchol	NOUN
ijassa-1351	292	6	-	-	PUNCT
ijassa-1351	292	7	balter	balter	NOUN
ijassa-1351	292	8	,	,	PUNCT
ijassa-1351	292	9	m.	m.	NOUN
ijassa-1351	292	10	,	,	PUNCT
ijassa-1351	292	11	jiang	jiang	PROPN
ijassa-1351	292	12	,	,	PUNCT
ijassa-1351	292	13	h.	h.	PROPN
ijassa-1351	292	14	,	,	PUNCT
ijassa-1351	292	15	scheller	scheller	NOUN
ijassa-1351	292	16	-	-	PUNCT
ijassa-1351	292	17	wolf	wolf	PROPN
ijassa-1351	292	18	,	,	PUNCT
ijassa-1351	292	19	a.	a.	PROPN
ijassa-1351	292	20	&	&	CCONJ
ijassa-1351	292	21	srikant	srikant	PROPN
ijassa-1351	292	22	,	,	PUNCT
ijassa-1351	292	23	r.	r.	PROPN
ijassa-1351	292	24	(	(	PUNCT
ijassa-1351	292	25	2019	2019	NUM
ijassa-1351	292	26	)	)	PUNCT
ijassa-1351	292	27	.	.	PUNCT
ijassa-1351	293	1	delay	delay	NOUN
ijassa-1351	293	2	asymptotics	asymptotic	NOUN
ijassa-1351	293	3	and	and	CCONJ
ijassa-1351	293	4	bounds	bound	NOUN
ijassa-1351	293	5	for	for	ADP
ijassa-1351	293	6	multitask	multitask	ADJ
ijassa-1351	293	7	parallel	parallel	ADJ
ijassa-1351	293	8	jobs	job	NOUN
ijassa-1351	293	9	,	,	PUNCT
ijassa-1351	293	10	queueing	queue	VERB
ijassa-1351	293	11	syst	syst	NOUN
ijassa-1351	293	12	.	.	PROPN
ijassa-1351	293	13	,	,	PUNCT
ijassa-1351	293	14	91	91	NUM
ijassa-1351	293	15	,	,	PUNCT
ijassa-1351	293	16	207–239	207–239	NUM
ijassa-1351	293	17	.	.	NOUN
ijassa-1351	293	18	17	17	NUM
ijassa-1351	293	19	.	.	PUNCT
ijassa-1351	293	20	gorbunova	gorbunova	PROPN
ijassa-1351	293	21	,	,	PUNCT
ijassa-1351	293	22	a.	a.	PROPN
ijassa-1351	293	23	v.	v.	PROPN
ijassa-1351	293	24	&	&	CCONJ
ijassa-1351	293	25	lebedev	lebedev	PROPN
ijassa-1351	293	26	,	,	PUNCT
ijassa-1351	293	27	a.	a.	PROPN
ijassa-1351	293	28	v.	v.	PROPN
ijassa-1351	293	29	(	(	PUNCT
ijassa-1351	293	30	2020	2020	NUM
ijassa-1351	293	31	)	)	PUNCT
ijassa-1351	293	32	.	.	PUNCT
ijassa-1351	294	1	bivariate	bivariate	ADJ
ijassa-1351	294	2	distributions	distribution	NOUN
ijassa-1351	294	3	of	of	ADP
ijassa-1351	294	4	maximum	maximum	ADJ
ijassa-1351	294	5	remaining	remain	VERB
ijassa-1351	294	6	service	service	NOUN
ijassa-1351	294	7	times	time	NOUN
ijassa-1351	294	8	in	in	ADP
ijassa-1351	294	9	fork	fork	NOUN
ijassa-1351	294	10	-	-	PUNCT
ijassa-1351	294	11	join	join	VERB
ijassa-1351	294	12	infinite	infinite	ADJ
ijassa-1351	294	13	-	-	PUNCT
ijassa-1351	294	14	server	server	NOUN
ijassa-1351	294	15	queues	queue	NOUN
ijassa-1351	294	16	,	,	PUNCT
ijassa-1351	294	17	problems	problem	NOUN
ijassa-1351	294	18	of	of	ADP
ijassa-1351	294	19	information	information	NOUN
ijassa-1351	294	20	transmission	transmission	NOUN
ijassa-1351	294	21	,	,	PUNCT
ijassa-1351	294	22	56(1	56(1	NUM
ijassa-1351	294	23	)	)	PUNCT
ijassa-1351	294	24	,	,	PUNCT
ijassa-1351	294	25	73–90	73–90	NUM
ijassa-1351	294	26	.	.	PUNCT
ijassa-1351	295	1	18	18	NUM
ijassa-1351	295	2	.	.	PUNCT
ijassa-1351	296	1	nelder	nelder	PROPN
ijassa-1351	296	2	,	,	PUNCT
ijassa-1351	296	3	j.	j.	PROPN
ijassa-1351	296	4	a.	a.	PROPN
ijassa-1351	296	5	&	&	CCONJ
ijassa-1351	296	6	mead	mead	PROPN
ijassa-1351	296	7	,	,	PUNCT
ijassa-1351	296	8	r.	r.	PROPN
ijassa-1351	296	9	(	(	PUNCT
ijassa-1351	296	10	1965	1965	NUM
ijassa-1351	296	11	)	)	PUNCT
ijassa-1351	296	12	.	.	PUNCT
ijassa-1351	297	1	a	a	DET
ijassa-1351	297	2	simplex	simplex	NOUN
ijassa-1351	297	3	method	method	NOUN
ijassa-1351	297	4	for	for	ADP
ijassa-1351	297	5	function	function	NOUN
ijassa-1351	297	6	minimization	minimization	NOUN
ijassa-1351	297	7	,	,	PUNCT
ijassa-1351	297	8	computer	computer	NOUN
ijassa-1351	297	9	journal	journal	NOUN
ijassa-1351	297	10	,	,	PUNCT
ijassa-1351	297	11	7	7	NUM
ijassa-1351	297	12	,	,	PUNCT
ijassa-1351	297	13	308–313	308–313	NUM
ijassa-1351	297	14	.	.	NOUN
ijassa-1351	297	15	19	19	NUM
ijassa-1351	297	16	.	.	NOUN
ijassa-1351	297	17	kochenderfer	kochenderfer	NOUN
ijassa-1351	297	18	,	,	PUNCT
ijassa-1351	297	19	m.	m.	PROPN
ijassa-1351	297	20	j.	j.	PROPN
ijassa-1351	297	21	&	&	CCONJ
ijassa-1351	297	22	wheeler	wheeler	NOUN
ijassa-1351	297	23	,	,	PUNCT
ijassa-1351	297	24	t.	t.	NOUN
ijassa-1351	297	25	a.	a.	NOUN
ijassa-1351	297	26	(	(	PUNCT
ijassa-1351	297	27	2019	2019	NUM
ijassa-1351	297	28	)	)	PUNCT
ijassa-1351	297	29	.	.	PUNCT
ijassa-1351	298	1	algorithms	algorithm	NOUN
ijassa-1351	298	2	for	for	ADP
ijassa-1351	298	3	optimization	optimization	NOUN
ijassa-1351	298	4	.	.	PUNCT
ijassa-1351	299	1	cambridge	cambridge	PROPN
ijassa-1351	299	2	,	,	PUNCT
ijassa-1351	299	3	uk	uk	PROPN
ijassa-1351	299	4	:	:	PUNCT
ijassa-1351	299	5	mit	mit	PROPN
ijassa-1351	299	6	press	press	NOUN
ijassa-1351	299	7	.	.	PUNCT
ijassa-1351	300	1	copyright	copyright	NOUN
ijassa-1351	300	2	©	©	PROPN
ijassa-1351	300	3	2023	2023	NUM
ijassa-1351	300	4	assa	assa	NOUN
ijassa-1351	300	5	.	.	PUNCT
ijassa-1351	301	1	adv	adv	PROPN
ijassa-1351	301	2	syst	syst	PROPN
ijassa-1351	301	3	sci	sci	PROPN
ijassa-1351	301	4	appl	appl	PROPN
ijassa-1351	301	5	(	(	PUNCT
ijassa-1351	301	6	2023	2023	NUM
ijassa-1351	301	7	)	)	PUNCT
ijassa-1351	301	8	114	114	NUM
ijassa-1351	301	9	a.v	a.v	PROPN
ijassa-1351	301	10	.	.	PROPN
ijassa-1351	301	11	gorbunova	gorbunova	PROPN
ijassa-1351	301	12	,	,	PUNCT
ijassa-1351	301	13	a.v	a.v	PROPN
ijassa-1351	301	14	.	.	PROPN
ijassa-1351	301	15	lebedev	lebedev	PROPN
ijassa-1351	301	16	20	20	NUM
ijassa-1351	301	17	.	.	PUNCT
ijassa-1351	302	1	gorbunova	gorbunova	PROPN
ijassa-1351	302	2	,	,	PUNCT
ijassa-1351	302	3	a.	a.	PROPN
ijassa-1351	302	4	,	,	PUNCT
ijassa-1351	302	5	zaryadov	zaryadov	PROPN
ijassa-1351	302	6	,	,	PUNCT
ijassa-1351	302	7	i	i	PRON
ijassa-1351	302	8	,	,	PUNCT
ijassa-1351	302	9	matushenko	matushenko	PROPN
ijassa-1351	302	10	,	,	PUNCT
ijassa-1351	302	11	s.	s.	PROPN
ijassa-1351	302	12	,	,	PUNCT
ijassa-1351	302	13	sopin	sopin	PROPN
ijassa-1351	302	14	,	,	PUNCT
ijassa-1351	302	15	e.	e.	PROPN
ijassa-1351	302	16	(	(	PUNCT
ijassa-1351	302	17	2016	2016	NUM
ijassa-1351	302	18	)	)	PUNCT
ijassa-1351	302	19	.	.	PUNCT
ijassa-1351	303	1	the	the	DET
ijassa-1351	303	2	estimation	estimation	NOUN
ijassa-1351	303	3	of	of	ADP
ijassa-1351	303	4	probability	probability	NOUN
ijassa-1351	303	5	characteristics	characteristic	NOUN
ijassa-1351	303	6	of	of	ADP
ijassa-1351	303	7	cloud	cloud	NOUN
ijassa-1351	303	8	computing	computing	NOUN
ijassa-1351	303	9	systems	system	NOUN
ijassa-1351	303	10	with	with	ADP
ijassa-1351	303	11	splitting	splitting	NOUN
ijassa-1351	303	12	of	of	ADP
ijassa-1351	303	13	requests	request	NOUN
ijassa-1351	303	14	,	,	PUNCT
ijassa-1351	303	15	communications	communication	NOUN
ijassa-1351	303	16	in	in	ADP
ijassa-1351	303	17	computer	computer	NOUN
ijassa-1351	303	18	and	and	CCONJ
ijassa-1351	303	19	information	information	NOUN
ijassa-1351	303	20	science	science	NOUN
ijassa-1351	303	21	,	,	PUNCT
ijassa-1351	303	22	678	678	NUM
ijassa-1351	303	23	,	,	PUNCT
ijassa-1351	303	24	418–429	418–429	NUM
ijassa-1351	303	25	.	.	PUNCT
ijassa-1351	303	26	21	21	NUM
ijassa-1351	303	27	.	.	X
ijassa-1351	304	1	zaharenkova	zaharenkova	PROPN
ijassa-1351	304	2	,	,	PUNCT
ijassa-1351	304	3	e.	e.	PROPN
ijassa-1351	304	4	(	(	PUNCT
ijassa-1351	304	5	2019	2019	NUM
ijassa-1351	304	6	)	)	PUNCT
ijassa-1351	304	7	.	.	PUNCT
ijassa-1351	305	1	analitiko	analitiko	ADJ
ijassa-1351	305	2	-	-	PUNCT
ijassa-1351	305	3	statisticheskie	statisticheskie	NOUN
ijassa-1351	305	4	metody	metody	ADJ
ijassa-1351	305	5	rascheta	rascheta	NOUN
ijassa-1351	306	1	i	i	PRON
ijassa-1351	306	2	optimizacii	optimizacii	PROPN
ijassa-1351	307	1	sistem	sistem	PROPN
ijassa-1351	308	1	i	i	PRON
ijassa-1351	308	2	setej	setej	VERB
ijassa-1351	308	3	massovogo	massovogo	AUX
ijassa-1351	308	4	obsluzhivanija	obsluzhivanija	VERB
ijassa-1351	308	5	so	so	ADV
ijassa-1351	308	6	stepennymi	stepennymi	VERB
ijassa-1351	308	7	hvostami	hvostami	NOUN
ijassa-1351	308	8	raspredelenij	raspredelenij	NOUN
ijassa-1351	309	1	[	[	X
ijassa-1351	309	2	analytical	analytical	ADJ
ijassa-1351	309	3	and	and	CCONJ
ijassa-1351	309	4	statistical	statistical	ADJ
ijassa-1351	309	5	methods	method	NOUN
ijassa-1351	309	6	for	for	ADP
ijassa-1351	309	7	calculating	calculate	VERB
ijassa-1351	309	8	and	and	CCONJ
ijassa-1351	309	9	optimizing	optimize	VERB
ijassa-1351	309	10	queuing	queuing	NOUN
ijassa-1351	309	11	systems	system	NOUN
ijassa-1351	309	12	and	and	CCONJ
ijassa-1351	309	13	networks	network	NOUN
ijassa-1351	309	14	with	with	ADP
ijassa-1351	309	15	power	power	NOUN
ijassa-1351	309	16	tails	tail	NOUN
ijassa-1351	309	17	of	of	ADP
ijassa-1351	309	18	distributions	distribution	NOUN
ijassa-1351	309	19	]	]	PUNCT
ijassa-1351	309	20	.	.	PUNCT
ijassa-1351	310	1	ph	ph	PROPN
ijassa-1351	310	2	.	.	PROPN
ijassa-1351	310	3	d.	d.	PROPN
ijassa-1351	310	4	thesis	thesis	PROPN
ijassa-1351	310	5	,	,	PUNCT
ijassa-1351	310	6	omsk	omsk	PROPN
ijassa-1351	310	7	,	,	PUNCT
ijassa-1351	310	8	[	[	X
ijassa-1351	310	9	in	in	ADP
ijassa-1351	310	10	russian	russian	NOUN
ijassa-1351	310	11	]	]	PUNCT
ijassa-1351	310	12	.	.	PUNCT
ijassa-1351	311	1	copyright	copyright	NOUN
ijassa-1351	311	2	©	©	PROPN
ijassa-1351	311	3	2023	2023	NUM
ijassa-1351	311	4	assa	assa	NOUN
ijassa-1351	311	5	.	.	PUNCT
ijassa-1351	312	1	adv	adv	PROPN
ijassa-1351	312	2	syst	syst	PROPN
ijassa-1351	312	3	sci	sci	PROPN
ijassa-1351	312	4	appl	appl	PROPN
ijassa-1351	312	5	(	(	PUNCT
ijassa-1351	312	6	2023	2023	NUM
ijassa-1351	312	7	)	)	PUNCT
ijassa-1351	312	8	introduction	introduction	NOUN
ijassa-1351	312	9	evaluation	evaluation	NOUN
ijassa-1351	312	10	of	of	ADP
ijassa-1351	312	11	the	the	DET
ijassa-1351	312	12	main	main	ADJ
ijassa-1351	312	13	performance	performance	NOUN
ijassa-1351	312	14	characteristics	characteristic	NOUN
ijassa-1351	312	15	of	of	ADP
ijassa-1351	312	16	fork	fork	NOUN
ijassa-1351	312	17	-	-	PUNCT
ijassa-1351	312	18	join	join	VERB
ijassa-1351	312	19	qs	qs	ADP
ijassa-1351	312	20	average	average	ADJ
ijassa-1351	312	21	response	response	NOUN
ijassa-1351	312	22	time	time	NOUN
ijassa-1351	312	23	response	response	NOUN
ijassa-1351	312	24	time	time	NOUN
ijassa-1351	312	25	standard	standard	ADJ
ijassa-1351	312	26	deviation	deviation	NOUN
ijassa-1351	312	27	features	feature	NOUN
ijassa-1351	312	28	of	of	ADP
ijassa-1351	312	29	fork	fork	NOUN
ijassa-1351	312	30	-	-	PUNCT
ijassa-1351	312	31	join	join	NOUN
ijassa-1351	312	32	qs	qs	PROPN
ijassa-1351	312	33	simulation	simulation	NOUN
ijassa-1351	312	34	conclusion	conclusion	NOUN