Standby Redundancy Allocation for a Coherent System under Its Signature Point Process Representation

Size: px
Start display at page:

Download "Standby Redundancy Allocation for a Coherent System under Its Signature Point Process Representation"

Transcription

1 merca Joural of Operao Reearch, 26, 6, hp:// ISSN Ole: ISSN Pr: Sadby Redudacy llocao for a Cohere Syem uder I Sgaure Po Proce Repreeao Vaderle da Coa ueo Deparme of Sac, São Paulo Uvery, São Paulo, razl How o ce h paper: da Coa ueo, V. (26) Sadby Redudacy llocao for a Cohere Syem uder I Sgaure Po Proce Repreeao. merca Joural of Operao Reearch, 6, hp://dx.do.org/.4236/ajor Receved: Sepember 2, 26 cceped: November 2, 26 Publhed: November 24, 26 brac Wllg o work relably heory a geeral e up, uder ochacally depedece codo, we ed o characerze a o decally pare adby redudacy operao hrough compeaor raform uder a complee formao level, he phyc approach, ha, obervg compoe lfeme. We ed o opmze yem relably uder adby redudacy allocao of compoe, parcularly, uder mmal adby redudacy. o ge reul, we wll ue a cohere yem repreeao hrough a gaure po proce. Copyrgh 26 by auhor ad Scefc Reearch Publhg Ic. h work lceed uder he Creave Commo rbuo Ieraoal Lcee (CC Y 4.). hp://creavecommo.org/lcee/by/4./ Ope cce Keyword Relably, Margale Mehod Relably heory, Sgaure Po Proce, Sadby Redudacy, Cohere Syem. Iroduco I relably heory he ma applcao of redudacy o allocae a reduda pare a yem compoe poo order o opmze yem relably. For ace, ee []-[8], amog oher. here are wo commo ype of redudacy ued relably heory, amely acve redudacy, whch ochacally lead o coder maxmum of radom varable ad adby redudacy, whch ochacally lead o coder covoluo of radom varable. For a k-ou-of- yem, [] coder lkelhood rao orderg ad gve uffce codo o eure ha a ere yem he allocao of a adby pare hould go o he weake compoe whle a parallel yem hould go o he roge. Referece [2] coder he ame problem wh aoher crero of opmaly ad ge he DOI:.4236/ajor November 24, 26

2 V. da Coa ueo ame reul. I boh above paper, he compoe lfeme are ochacally depede ad he obervao are a yem level. Few paper aaed o he cae where he compoe are ochacally depede. Referece [7] aalyze redudace for a k-ou-of- yem of depede compoe. Referece [6] ude acve redudacy allocao for a k-ou-of- yem of depede compoe whou mulaeou falure. Referece [5] work a parcular form of adby redudacy, called mmal adby redudacy, whch gve he compoe a addoal lfeme a had ju before he falure. For he cae of depede compoe, [5] oberve he yem a compoe level ad ue he revere rule of order 2 (RR2) propery bewee compeaor procee o vegae he problem of where o allocae a pare a k-ou-of- yem. I h paper, we ed o aalyze a o decally pare adby redudacy allocao for a cohere yem of depede compoe whou mulaeou falure, a compoe level, uder a cohere yem gaure po proce repreeao ad prove ha opmal o perform adby redudacy o he weake compoe of a cohere yem order o opmze yem relably. I Seco 2 we characerze a o decally pare adby redudacy hrough compeaor raform for depede compoe. I Seco 3 we reume mahemacal deal of gaure po proce repreeao of a cohere yem ad Seco 4 we vegae he be adby redudacy allocao a depede compoe cohere yem order o opmze yem relably. 2. No Idecally Spare Sadby Operao hrough Compeaor raform We oberve ha each compoe adby redudacy ha wo phae, adby ad operao uder whch hey ca fal. Depedg o compoe falure characerc durg hee phae, adby redudacy clafed o he followg hree ype: ) Ho adby: Each compoe ha he ame falure rae regardle of wheher adby or operao. Sce he falure rae of oe compoe uque ad o affeced by he oher compoe, he ho adby redudacy co of ochacally depede compoe. 2) Warm adby: adby compoe ca fal, bu ha maller falure rae ha he prcpal compoe. Falure characerc of he compoe are affeced by he oher, ad warm adby duce depede compoe falure. 3) Cold adby: Compoe doe o fal whe hey are adby. he compoe have o-zero falure rae oly whe hey are operao. falure of oe prcpal compoe force a adby compoe o ar operao ad o have a o-zero falure rae. hu, falure characerc of oe compoe are affeced by he oher, ad he cold adby redudacy reul muually depede compoe falure. I wha follow, we coder o oberve wo lfeme ad S, whch are fe po- 49

3 V. da Coa ueo ve radom varable defed a complee probably pace ( Ω,,P) hrough he famly of ub -algebra ( ) of where σ { { }, { }, > > } S afe Dellachere codo of rgh couy ad compleee. We aume ha P( S ), ha, he lfeme ca be depede bu mulaeou falure are ruled ou. I our geeral e up ad order o mplfy he oao, h paper we aume ha relao uch a,, <,, bewee radom varable ad meaurable e, alway hold wh probably oe, whch mea ha he erm P-a.., uppreed. We recall ha a pove radom varable a -oppg me f, for every, { }. he -oppg me called predcable f a creag equece ( ), of -oppg me, < ex uch ha, a ad a -oppg me oally acceble f P ( S) for all predcable -oppg me S. For a mahemacal ba of ochac procee appled o relably heory ee he book of [9] ad []. Geerally, adby redudacy gve o he compoe a addoal lfeme. I our coex he adby operao of S by defed a he mproveme of S by ( S ) SR SR ad deoed by S, S S ( S ) where ( S) S he e { > S}, SR ad equal o he e { S}. We remark ha, he S lfeme erpreao max, S, whch ha a ull falure rae up o me dffere of a parallel yem lfeme, { } m {, S }. he lfeme SR S ha he falure rae of S before falure. ( { }) Furhermore, relao o σ { },, ad ug he Doob-Meyer decompoo, we coder he predcable compeaor procee ( ) S >, uch ha { } a zero mea uformly egral margale. lo, relao o ( σ { { }, } ), we coder he predcable compeaor procee ( ) >, uch ha { } S a zero mea uformly egral margale. he compeaor proce expreed erm of codoal probably, gve he avalable formao ad geeralze he clacal oo of hazard. Iuvely h correpod o produce wheher he falure goe o occur ow, o he ba of all obervao avalable up o, bu o cludg, he pree. he well kow equvalece bewee drbuo fuco ad compeaor procee follow from [] ad we have l F( ), l G( S). herefore P { > } e ad P{ S > } e. I he cae of depede lfeme, he urvval fuco of he mproved lfeme by SR S { ( ) > } ( ) P S S ( ) { } ( ) P S > P > e d e e e. herefore he -compeaor of SR { S } 49

4 V. da Coa ueo e d ed e e e d e d. e e e e SR S l e e I h faho ad preervg he depedece cae erpreao, we defe, for depede lfeme, he raformao of ad, -compeaor of { S SR },, wh ad e e e α d, α e e e β d, β We oberve ha < α < ad < β < mplyg a mproveme of he lfeme. a he um of he compeaor ad geg Followg h hkg, a a predcable compeaor uque we are gog o fd a probably meaure uder whch C he a -compeaor of o proceed we coder he compeaor raform e e e e e e e e e d d d.. SR { S } o prove he ma heorem of h eco we are gog o ue he followg Lemma: Lemma 2. Uder h eco aumpo, he followg proce e e e L { } e d e e a oegave -margale wh E L. Proof We coder he -oppg me defed by I uffce o prove ha he proce L { } V f : or. e e e a bouded -margale. Noe ha, for ay -oppg me e d e e e { } e V V d e e e V V we ca wre L V e e d V e e N where N { }. he procedure eay: V < we have O he e { } L V Oherwe, o he e { V } V e e d V d e e e e e e d e. e e 492

5 V. da Coa ueo he egrad e d e e e d e e V e L e d N V e e e e. e e e d e e e e e e a -predcable proce ad N a -margale, wh E L ad we ge he reul. Secodly, we coder he compeaor raform e e e d d d e e e e e e ad wh he ame argume ued o prove Lemma 2. we ca prove Lemma 2.2: Lemma 2.2 Uder h eco aumpo, he followg proce { } e S d e e L a -margale S e L e S S e e a oegave -margale wh E L. Now, we ca wre he ma heorem: heorem 2.3 Uder h eco aumpo, he followg proce { } { S } L L L e e α β S a oegave local -margale wh E[ L ]. Proof. Ug Lemma 2., Lemma 2.2 ad he Selje dffereao rule we have L L L dl L d L L L. by aumpo ad are couou wh P( S ), we have L L. herefore L L a oegave local -margale wh E L L ad he heorem proved. We are lookg for a probably meaure Q, uch ha, uder Q, C become he a -compeaor of { S SR } wh repec o h modfed probably meaure. Uder cera codo, poble o fd Q. Ideed aume ha he proce L uformly egrable. he follow from Graov heorem, ee [], a well kow reul o po proce margale, ha he dered meaure Q gve by he Rado dq Nkody dervave L. he radom varable L gve by dp L { } { S S } e e S e e e e e e S S ( S ) ( S ) ( e ) ( e ) ( S ) ( S ) e e 493

6 V. da Coa ueo where S m { S, }. Remark 2.4. I referece o he fr paragraph of h eco, he above eg we ca defy he meaure L wh warm adby whch cae he compoe adby ca fal before he compoe operao. I he cae of cold adby redudacy, doe o fal before S, we ca coder S < ad we have S S e e L S S. e e I he cae where ad S are decally drbued, we have ad he compeaor raform gve by e 2 2e 2e 2 e 2 d d whch ca be ued o defe a adby redudacy hrough compeaor raform whe he adby compoe ad he compoe operao are ochacally depede bu decally drbued a [6]. 3. Reul Sgaure Po Proce { } Due mporace we pree hee reul h eco whch appear [2]. I our geeral eup, we coder he vecor (, 2,, ) of compoe lfeme whch are fe ad pove radom varable defed a complee probably pace ( Ω,,P) wh P ( j) for all j,, j C {,, }, he dex e of compoe. herefore, he lfeme ca be depede bu mulaeou falure are ruled ou. he evoluo of compoe me defe a marked po proce gve hrough he falure me ad he correpodg mark. We deoe < ( 2) < < he ordered lfeme, 2,, a hey appear me ad by X j: j he correpodg mark. a coveo we e ( 2) ad X X 2 e where e a fcou mark o C he dex e of he compoe. he equece (, X ) defe a marked po proce. he mahemacal decrpo of our obervao, he complee formao level,, where gve by a famly of ub σ algebra of, deoed by ( ) σ, X j,, j C, < { > }, afe he Dellachere codo of rgh couy ad compleee. Iuvely, a each me he oberver kow f he eve {, X j} have eher occurred or o ad f had, he kow exacly he value ad he mark X. We coder, coveely, he lfeme, j defed by he falure eve X j wh her ub-drbuo fuco, uable adardzed {, } j ( ) F P X, j., 494

7 V. da Coa ueo he behavor of he po proce P ( I ), a he formao flow cououly me gve by he followg heorem: heorem 3. Le, 2,, be he compoe lfeme of a cohere yem wh lfeme. he, P ( ). k j {, } {, } k k j K J { ( k) } { ( k) } Proof. From he oal probably rule we have P ( I ) P( { } { k I ) E k k I { ( k) } { ( k) } ad ( k ) are -oppg me ad well kow ha he eve ( k ) k where I : I,, { } { { } k k } { } k { ( k) } we coclude ha I - meaurable. herefore P ( I ) E k I { } { } k k k { ( k) } { ( k) }. he above decompoo allow u o defe he gaure proce a compoe level. Defo 3.2 he vecor, k, j { ( k ), j } defed a he marked po gaure proce of he yem ΦΦ. Remark 3.3 We oe ha he above repreeao ca be e wo way. We would prefer he oe whch preerve he compoe dex becaue, by example, we could alk abou he relably mporace of compoe j for he yem relably a he k-h falure. lo, a P ( j) for all, j, he colleco {{, }, k, j k j } form a paro of Ω ad {, }. herefore k k j P ( > ) k j k j { ( k), j} ( k), j K, J k j {, } k j ( K), J k j ( k), j K, J> { } { } { } { } { } Remark 3.4 Ug Remark 3.3 we ca calculae he yem relably a P ( > ) E P ( > ) E k j { ( k), j} { ( K), J> } P > k j ({ ( k), j} { ( K), J }) If he compoe lfeme are couou, depede ad decally drbued we have, ( k) k ( ( k) ) P> P P >, 495

8 V. da Coa ueo recoverg he clacal reul a [3]. Remark 3.5 he marked N (, j) { X, j} a j -meaurable, egrable, ad ( ) ( ),. -ub-margale, ha, {, } (, ) E N j N j for all Follow ha, from Doob-Meyer decompoo, here ex a uque proce, (, j), ( ), ha M (, j) N (, j) (, j) -margale. We aume ha (, j) predcable N, j, uch -compeaor of ( ) j, called he a zero mea uformly egrable are aboluely couou -compeaor procee ad ha, j are oally acceble -oppg me. he -compeaor of { } where he yem lfeme e he followg heorem: heorem 3.6 Le, 2,,, be he compoe lfeme of a cohere yem wh lfeme. he, uder he above hypohe ad oao, he -ub-margale P ( ), ha he -compeaor Proof. We coder he proce { ( k), j} k j ( ) d k, j. w,. { } k, j ( k), j { } ( w ) I lef couou ad -predcable. herefore { } k, j d M k, j a a -margale. a fe um of { ( k), j} k j ( ) d M k, j -margale a { } ( ) k, j ( k), j k j k j { } -margale ( ) d N k, j d k, j. -margale. he compeaor uque we ge he reul. 4. Sadby Redudacy a Cohere Syem of Depede Compoe We are cocered wh he problem of where o allocae a pare compoe ug adby redudacy a cohere yem order o opmze yem relably mproveme. We le Φ ( ) be he lfeme of a cohere yem wh compoe lfeme ( ), P ( ), for all j,, j uder he hypo-,,, 2 j he ad oao of Seco 3. Furhermore, le Φ (,,, S,,, ) be he yem lfeme reulg from a adby redudacy operao of compoe hrough a pare wh lfeme S, o decally drbued a. I parcular we cou h yem falure hrough N { a coug proce wh } -compeaor,. o compare he yem lfeme reulg from redudacy operao we are gog o compare he compoe po procee compeaor hrough cumula- 496

9 V. da Coa ueo ve hazard order a [4] Defo 4. Coder wo po procee, lfeme vecor defed a complee probably pace N correpodg o he compoe Ω,, P ad N S, relao o he compoe lfeme vecor S pobly defed o a dffere probably pace, wh correpodg couou compeaor procee [, [ o ;,,, [, [ m o S S ;,,, m m m whch are, max, m ad m, ( m) for all < < <, < < < ad,, we ay ha S maller ha he cumulave hazard order, deoed by S. ch lo, we are gog o ue he followg reul from [5]. heorem 4.2 Coder wo po procee, N correpodg o he compoe lfeme vecor defed a complee probably pace ( Ω,, P ) ad N S, correpodg o he compoe lfeme vecor S pobly defed o a dffere probably pace. If S maller ha cumulave hazard order, S, ch he P almo urely, couou. If for all { } ψ EP ψ N EP N S for all decreag real ad rgh couou fuco wh lef had lm ψψ, whch mple N N. S 4.. Mmal Sadby Redudacy a Cohere Syem of Depede Compoe I h fr ubeco we reume he reul from [5] edg o pree a geeralzao of he ma heorem from a k-ou-of- yem o cohere yem. Iuvely, a mmal adby redudacy gve o he compoe a addoal lfeme a had ju before he falure. I a radom evrome where he compoe affeced by he behavor of oher compoe, [5] fd a compeaor approach for mmal adby redudacy coderg he Graov heorem argume where he compoe compeaor N raformed hrough proce of wh α ad j α d, α for j. he reul : uder he meaure Q defed by he Rado Nkod dervave dq dp, he compoe compeaor raform of N,. Oberve ha d l ( ), 497

10 V. da Coa ueo ad, he aboluely couou cae, where l P ( ) recover, he depedece cae, he clacal expreo >, [], we ca ( > ) P S F F l F. Recoverg our eg, le Φ (,,, S,,, ), he yem lfeme reulg from a mmal adby redudacy operao of he lfeme, of compoe. We cou h yem falure hrough N { a coug proce wh } -compeaor,. Φ be he lfeme of a cohere yem wh com- heorem 4.. Le be le poe lfeme ( ), 2,,, P ( j), for all j,, j. Uder a mmal adby redudacy operao, he hypohe ad oao of Seco 3, f, j j < j, he N N, < j. Proof From heorem 3.6 we have o compare yem compeaor expecao value o he form { } ( ) { } ( ) k, j k, { ( k), j} k j k k j ( ) k, j k, k, j. for where he oao (( k), j ) mea he rerco of erval ] ] ad j 2., k k. Clearly, uffce o prove for { } ( ) ( ) k, { k, j} k k j 2 ( ) { ( k),} { ( k),2} k k { ( k), j} k j 3 ( ) 2 ( ( )) ( ) ( ) k, l k, k, j ( ) ( ) k, k,2 l k,2 k, j ( ) ( ) l k, l k,2 k, k,2. he fal reul follow from heorem Sadby Redudacy a Cohere Syem of Depede Compoe j, o he I wha follow we coder a uque pare wh lfeme S, a Seco 2, wh compeaor procee ( ), uch ha { } S a zero mea uformly egral margale, o be allocaed bewee he compoe, order o opmze yem relably: heorem 4.2. Le be le Φ ( ) be he lfeme of a cohere yem wh compoe lfeme ( ), P ( ), for all j,, j. U-, 2,, j der adby redudacy ad he hypohe ad oao of Seco 3, f, j j < j, he N N, < j. Proof. Follow, from Seco 2, ha he adby redudacy hrough compeaor raform of he compoe by a pare wh compeaor SR S e d ed l e e. e e 498

11 V. da Coa ueo Clearly, uffce o prove for ad j 2. (( k), ) { } ( ) k, { k, j} k k j 2 (( k),2) { } (( k) ) { } (( k) ) k, k,2 k k 2 { } (( k), j) k, j k j 3 k, l e e k, j,, 2 l e e ( ( )) ( ) ( ) ( ) l k, l k,2 k, k,2. he fal reul follow from heorem 4.2. by hypohe, ( j), < j we are coderg compoe weaker ha compoe j he ee ha he hazard proce for falure of compoe larger ha he hazard proce for falure of compoe j, alo mple ha ochacally le ha j. herefore, uder heorem 4.2. we uderad ha, a compoe level, opmal o perform acve redudacy allocao o he weake compoe of a cohere yem of couou depede compoe wh o mulaeou falure. We ca, alo coder wo pare wh lfeme S ad S 2, { S } wh -compeaor ad { S 2 } wh -compeaor ( 2), o be allocaed bewee he compoe, order o opmze yem relably. he followg corollary ca be ealy proved ug he ame argume of heorem Corollary 4.2. Le be le Φ ( ) be he lfeme of a cohere yem wh compoe lfeme ( ), P ( ), for all j,, j. Uder, 2,, j adby redudacy ad he hypohe ad oao of Seco 3, f j j j 2, he N N, < j, where, < ad Φ ( S ) 5. Cocluo,,,,,,. effce mehod o opmze he relably of a cohere yem o add redudacy compoe o he yem. herefore very gfca o kow abou he allocao whch be opmze yem relably. I he la decade, may reearcher devoed hemelve o h opc, geeral aalyzg k-ou-of- yem ad followg a aural ad clacal approach: coderg ha he compoe lfeme were ochacally depede ad o obervg he yem a level hrough σ { { } > } Few paper aemp o he cae where he compoe are ochacally depede whou mulaeou falure. [5] ad [6] coder ochacally depede compoe lfeme ad oberve he complee formao a compoe level σ { { },, } > 499

12 V. da Coa ueo geg reul for k-ou-of- yem. Wh rece reul gaure heory ad exeo o a gaure po proce, we geeralze reul from k-ou-of- o cohere yem, parcularly for mmal adby redudacy ad adby redudacy. I alo mpora o oe he characerzao of adby operao reul wh o decally pare. he dcuo abou h ew approach ad he clacal oe ca be e comparg reul of P ( > ) wh P ( > ). We coclude ha, a compoe level, opmal o perform acve redudacy allocao o he weake compoe of a cohere yem of couou depede compoe wh o mulaeou falure whe ug he hazard rae orderg bewee he compoe lfeme. ckowledgeme h work wa parally uppored by São Paulo Reearch Foudao (FPESP), gra 25/ Referece [] olad, P.J., El Neweh, E. ad Procha, F. (992) Sochac Order for Redudacy llocao Sere ad Parallel Syem. dvaced ppled Probably, 4, 6-7. hp://do.org/.7/s [2] Sgh, H. ad Mra, N. (994) O Redudacy llocao Syem. Joural of ppled Probably, 3, 4-4. hp://do.org/.7/s [3] Kuo, W., Praad, V.R. lma, F. ad Hwag, L. (2) Opmal Relably Deg. Cambrdge Uvery Pre, Cambrdge [4] Praad, V.R., Kuo, W. ad Km, K.M. (999) Opmal llocao of Idecal, Mul Fucoal Spear a Sere Syem. IEEE raaco o Relably, 48, hp://do.org/.9/ [5] ueo, V.C. (25) Mmal Sadby Redudacy llocao a k-ou-of-:f Syem of Depede Compoe. Europea Joural of Operaoal Reearch, 65, hp://do.org/.6/j.ejor [6] ueo, V.C. ad Carmo, I.M. (27) cve Redudacy llocao for a k-ou-of-:f Syem of Depede Compoe. Europea Joural of Operaoal Reearch, 76, 4-5. hp://do.org/.6/j.ejor [7] elzuce, F. Marez-Puera, H. ad Ruz, J.M. (23) O llocao of Reduda Compoe for Syem wh Depede Compoe. Europea Joural of Operaoal Reearch, 23, hp://do.org/.6/j.ejor [8] Zhao, P., Cha, P.S. ad L, L. (25) Redudacy llocao a Compoe Level veru Syem Level. Europea Joural of Operaoal Reearch, 24, hp://do.org/.6/j.ejor [9] ve,. ad Jee, U. (999) Sochac Model Relably. Sprger Verlag, New York. hp://do.org/.7/b97596 [] remaud, P. (98) Po Procee ad Queue: Margale Dyamc. Sprger Verlag, New York. hp://do.org/.7/ [] rja, E. ad Yah,. (988) Noe o Radom Iee ad Codoal Survval Fuco. Joural of ppled Probably, 25,

13 V. da Coa ueo hp://do.org/.7/s [2] ueo, V.C. (26) Sgaure Po Procee. Lamber cademc Publhg, Saarbrucke, Germay. [3] Samaego, F.J. (985) O Cloure of he IFR Cla uder Formao of Cohere Syem. IEEE raaco o Relably, 34, hp://do.org/.9/r [4] Shaked, M. ad Shahkumar, J.G. (994) Sochac Order ad her pplcao. cademc Pre, New York. [5] Kweck,. ad Szekl, R. (99) Compeaor Codo for Sochac Orderg of Po Procee. Joural of ppled Probably, 28, hp://do.org/.7/s Subm or recommed ex maucrp o SCIRP ad we wll provde be ervce for you: ccepg pre-ubmo qure hrough Emal, Facebook, LkedI, wer, ec. wde eleco of joural (cluve of 9 ubjec, more ha 2 joural) Provdg 24-hour hgh-qualy ervce Uer-fredly ole ubmo yem Far ad wf peer-revew yem Effce ypeeg ad proofreadg procedure Dplay of he reul of dowload ad v, a well a he umber of ced arcle Maxmum demao of your reearch work Subm your maucrp a: hp://paperubmo.crp.org/ Or coac ajor@crp.org 5

The Signal, Variable System, and Transformation: A Personal Perspective

The Signal, Variable System, and Transformation: A Personal Perspective The Sgal Varable Syem ad Traformao: A Peroal Perpecve Sherv Erfa 35 Eex Hall Faculy of Egeerg Oule Of he Talk Iroduco Mahemacal Repreeao of yem Operaor Calculu Traformao Obervao O Laplace Traform SSB A

More information

Competitive Facility Location Problem with Demands Depending on the Facilities

Competitive Facility Location Problem with Demands Depending on the Facilities Aa Pacc Maageme Revew 4) 009) 5-5 Compeve Facl Locao Problem wh Demad Depedg o he Facle Shogo Shode a* Kuag-Yh Yeh b Hao-Chg Ha c a Facul of Bue Admrao Kobe Gau Uver Japa bc Urba Plag Deparme Naoal Cheg

More information

Efficient Estimators for Population Variance using Auxiliary Information

Efficient Estimators for Population Variance using Auxiliary Information Global Joural of Mahemacal cece: Theor ad Praccal. IN 97-3 Volume 3, Number (), pp. 39-37 Ieraoal Reearch Publcao Houe hp://www.rphoue.com Effce Emaor for Populao Varace ug Aular Iformao ubhah Kumar Yadav

More information

Reliability Equivalence of a Parallel System with Non-Identical Components

Reliability Equivalence of a Parallel System with Non-Identical Components Ieraoa Mahemaca Forum 3 8 o. 34 693-7 Reaby Equvaece of a Parae Syem wh No-Ideca ompoe M. Moaer ad mmar M. Sarha Deparme of Sac & O.R. oege of Scece Kg Saud Uvery P.O.ox 455 Ryadh 45 Saud raba aarha@yahoo.com

More information

Lecture 3 Topic 2: Distributions, hypothesis testing, and sample size determination

Lecture 3 Topic 2: Distributions, hypothesis testing, and sample size determination Lecure 3 Topc : Drbuo, hypohe eg, ad ample ze deermao The Sude - drbuo Coder a repeaed drawg of ample of ze from a ormal drbuo of mea. For each ample, compue,,, ad aoher ac,, where: The ac he devao of

More information

The Poisson Process Properties of the Poisson Process

The Poisson Process Properties of the Poisson Process Posso Processes Summary The Posso Process Properes of he Posso Process Ierarrval mes Memoryless propery ad he resdual lfeme paradox Superposo of Posso processes Radom seleco of Posso Pos Bulk Arrvals ad

More information

The MacWilliams Identity of the Linear Codes over the Ring F p +uf p +vf p +uvf p

The MacWilliams Identity of the Linear Codes over the Ring F p +uf p +vf p +uvf p Reearch Joural of Aled Scece Eeer ad Techoloy (6): 28-282 22 ISSN: 2-6 Maxwell Scefc Orazao 22 Submed: March 26 22 Acceed: Arl 22 Publhed: Auu 5 22 The MacWllam Idey of he Lear ode over he R F +uf +vf

More information

Some Improved Estimators for Population Variance Using Two Auxiliary Variables in Double Sampling

Some Improved Estimators for Population Variance Using Two Auxiliary Variables in Double Sampling Vplav Kumar gh Rajeh gh Deparme of ac Baara Hdu Uver Varaa-00 Ida Flore maradache Uver of ew Meco Gallup UA ome Improved Emaor for Populao Varace Ug Two Aular Varable Double amplg Publhed : Rajeh gh Flore

More information

The Mean Residual Lifetime of (n k + 1)-out-of-n Systems in Discrete Setting

The Mean Residual Lifetime of (n k + 1)-out-of-n Systems in Discrete Setting Appled Mahemacs 4 5 466-477 Publshed Ole February 4 (hp//wwwscrporg/oural/am hp//dxdoorg/436/am45346 The Mea Resdual Lfeme of ( + -ou-of- Sysems Dscree Seg Maryam Torab Sahboom Deparme of Sascs Scece ad

More information

Analysis of a Stochastic Lotka-Volterra Competitive System with Distributed Delays

Analysis of a Stochastic Lotka-Volterra Competitive System with Distributed Delays Ieraoal Coferece o Appled Maheac Sulao ad Modellg (AMSM 6) Aaly of a Sochac Loa-Volerra Copeve Sye wh Drbued Delay Xagu Da ad Xaou L School of Maheacal Scece of Togre Uvery Togre 5543 PR Cha Correpodg

More information

Reliability Analysis. Basic Reliability Measures

Reliability Analysis. Basic Reliability Measures elably /6/ elably Aaly Perae faul Πelably decay Teporary faul ΠOfe Seady ae characerzao Deg faul Πelably growh durg eg & debuggg A pace hule Challeger Lauch, 986 Ocober 6, Bac elably Meaure elably:

More information

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall 8. Queueg sysems lec8. S-38.45 - Iroduco o Teleraffc Theory - Fall 8. Queueg sysems Coes Refresher: Smle eleraffc model M/M/ server wag laces M/M/ servers wag laces 8. Queueg sysems Smle eleraffc model

More information

New approach for numerical solution of Fredholm integral equations system of the second kind by using an expansion method

New approach for numerical solution of Fredholm integral equations system of the second kind by using an expansion method Ieraoal Reearch Joural o Appled ad Bac Scece Avalable ole a wwwrabcom ISSN 5-88X / Vol : 8- Scece xplorer Publcao New approach or umercal oluo o Fredholm eral equao yem o he ecod d by u a expao mehod Nare

More information

Nonsynchronous covariation process and limit theorems

Nonsynchronous covariation process and limit theorems Sochac Procee ad her Applcao 121 (211) 2416 2454 www.elever.com/locae/pa Noychroou covarao proce ad lm heorem Takak Hayah a,, Nakahro Yohda b a Keo Uvery, Graduae School of Bue Admrao, 4-1-1 Hyoh, Yokohama

More information

Parameters Estimation in a General Failure Rate Semi-Markov Reliability Model

Parameters Estimation in a General Failure Rate Semi-Markov Reliability Model Joura of Saca Theory ad Appcao Vo. No. (Sepember ) - Parameer Emao a Geera Faure Rae Sem-Marov Reaby Mode M. Fahzadeh ad K. Khorhda Deparme of Sac Facuy of Mahemaca Scece Va-e-Ar Uvery of Rafaja Rafaja

More information

Key words: Fractional difference equation, oscillatory solutions,

Key words: Fractional difference equation, oscillatory solutions, OSCILLATION PROPERTIES OF SOLUTIONS OF FRACTIONAL DIFFERENCE EQUATIONS Musafa BAYRAM * ad Ayd SECER * Deparme of Compuer Egeerg, Isabul Gelsm Uversy Deparme of Mahemacal Egeerg, Yldz Techcal Uversy * Correspodg

More information

CS344: Introduction to Artificial Intelligence

CS344: Introduction to Artificial Intelligence C344: Iroduco o Arfcal Iellgece Puhpa Bhaacharyya CE Dep. IIT Bombay Lecure 3 3 32 33: Forward ad bacward; Baum elch 9 h ad 2 March ad 2 d Aprl 203 Lecure 27 28 29 were o EM; dae 2 h March o 8 h March

More information

Cyclically Interval Total Colorings of Cycles and Middle Graphs of Cycles

Cyclically Interval Total Colorings of Cycles and Middle Graphs of Cycles Ope Joural of Dsree Mahemas 2017 7 200-217 hp://wwwsrporg/joural/ojdm ISSN Ole: 2161-7643 ISSN Pr: 2161-7635 Cylally Ierval Toal Colorgs of Cyles Mddle Graphs of Cyles Yogqag Zhao 1 Shju Su 2 1 Shool of

More information

ESTIMATION AND TESTING

ESTIMATION AND TESTING CHAPTER ESTIMATION AND TESTING. Iroduco Modfcao o he maxmum lkelhood (ML mehod of emao cera drbuo o overcome erave oluo of ML equao for he parameer were uggeed by may auhor (for example Tku (967; Mehrora

More information

(1) Cov(, ) E[( E( ))( E( ))]

(1) Cov(, ) E[( E( ))( E( ))] Impac of Auocorrelao o OLS Esmaes ECON 3033/Evas Cosder a smple bvarae me-seres model of he form: y 0 x The four key assumpos abou ε hs model are ) E(ε ) = E[ε x ]=0 ) Var(ε ) =Var(ε x ) = ) Cov(ε, ε )

More information

A Remark on Generalized Free Subgroups. of Generalized HNN Groups

A Remark on Generalized Free Subgroups. of Generalized HNN Groups Ieraoal Mahemacal Forum 5 200 o 503-509 A Remar o Geeralzed Free Subroup o Geeralzed HNN Group R M S Mahmood Al Ho Uvery Abu Dhab POBo 526 UAE raheedmm@yahoocom Abrac A roup ermed eeralzed ree roup a ree

More information

Continuous Time Markov Chains

Continuous Time Markov Chains Couous me Markov chas have seay sae probably soluos f a oly f hey are ergoc, us lke scree me Markov chas. Fg he seay sae probably vecor for a couous me Markov cha s o more ffcul ha s he scree me case,

More information

The Linear Regression Of Weighted Segments

The Linear Regression Of Weighted Segments The Lear Regresso Of Weghed Segmes George Dael Maeescu Absrac. We proposed a regresso model where he depede varable s made o up of pos bu segmes. Ths suao correspods o he markes hroughou he da are observed

More information

Fault Tolerant Computing. Fault Tolerant Computing CS 530 Reliability Analysis

Fault Tolerant Computing. Fault Tolerant Computing CS 530 Reliability Analysis Probably /4/6 CS 5 elably Aaly Yahwa K. Malaya Colorado Sae very Ocober 4, 6 elably Aaly: Oule elably eaure: elably, avalably, Tra. elably, T M MTTF ad (, MTBF Bac Cae Sgle u wh perae falure, falure rae

More information

Fault Tolerant Computing. Fault Tolerant Computing CS 530 Probabilistic methods: overview

Fault Tolerant Computing. Fault Tolerant Computing CS 530 Probabilistic methods: overview Probably 1/19/ CS 53 Probablsc mehods: overvew Yashwa K. Malaya Colorado Sae Uversy 1 Probablsc Mehods: Overvew Cocree umbers presece of uceray Probably Dsjo eves Sascal depedece Radom varables ad dsrbuos

More information

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state)

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state) Pro. O. B. Wrgh, Auum Quaum Mechacs II Lecure Tme-depede perurbao heory Tme-depede perurbao heory (degeerae or o-degeerae sarg sae) Cosder a sgle parcle whch, s uperurbed codo wh Hamloa H, ca exs a superposo

More information

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF EDA/DIT6 Real-Tme Sysems, Chalmers/GU, 0/0 ecure # Updaed February, 0 Real-Tme Sysems Specfcao Problem: Assume a sysem wh asks accordg o he fgure below The mg properes of he asks are gve he able Ivesgae

More information

Practice Final Exam (corrected formulas, 12/10 11AM)

Practice Final Exam (corrected formulas, 12/10 11AM) Ecoomc Meze. Ch Fall Socal Scece 78 Uvery of Wco-Mado Pracce Fal Eam (correced formula, / AM) Awer all queo he (hree) bluebook provded. Make cera you wre your ame, your ude I umber, ad your TA ame o all

More information

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA QR facorzao Ay x real marx ca be wre as AQR, where Q s orhogoal ad R s upper ragular. To oba Q ad R, we use he Householder rasformao as follows: Le P, P, P -, be marces such ha P P... PPA ( R s upper ragular.

More information

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables Joural of Sceces Islamc epublc of Ira 6(: 63-67 (005 Uvers of ehra ISSN 06-04 hp://scecesuacr Some Probabl Iequales for Quadrac Forms of Negavel Depede Subgaussa adom Varables M Am A ozorga ad H Zare 3

More information

14. Poisson Processes

14. Poisson Processes 4. Posso Processes I Lecure 4 we roduced Posso arrvals as he lmg behavor of Bomal radom varables. Refer o Posso approxmao of Bomal radom varables. From he dscusso here see 4-6-4-8 Lecure 4 " arrvals occur

More information

A moment closure method for stochastic reaction networks

A moment closure method for stochastic reaction networks THE JOURNAL OF CHEMICAL PHYSICS 3, 347 29 A mome cloure mehod for ochac reaco ewor Chag Hyeog Lee,,a Kyeog-Hu Km, 2,b ad Plwo Km 3,c Deparme of Mahemacal Scece, Worceer Polyechc Iue, Iue Road, Worceer,

More information

BEST PATTERN OF MULTIPLE LINEAR REGRESSION

BEST PATTERN OF MULTIPLE LINEAR REGRESSION ERI COADA GERMAY GEERAL M.R. SEFAIK AIR FORCE ACADEMY ARMED FORCES ACADEMY ROMAIA SLOVAK REPUBLIC IERAIOAL COFERECE of SCIEIFIC PAPER AFASES Brov 6-8 M BES PAER OF MULIPLE LIEAR REGRESSIO Corel GABER PEROLEUM-GAS

More information

Calibration Approach Based Estimators of Finite Population Mean in Two - Stage Stratified Random Sampling

Calibration Approach Based Estimators of Finite Population Mean in Two - Stage Stratified Random Sampling I.J.Curr.crobol.App.Sc (08) 7(): 808-85 Ieraoal Joural of Curre crobolog ad Appled Scece ISS: 39-7706 olue 7 uber 0 (08) Joural hoepage: hp://www.jca.co Orgal Reearch Arcle hp://do.org/0.0546/jca.08.70.9

More information

Research Article Centralized Fuzzy Data Association Algorithm of Three-sensor Multi-target Tracking System

Research Article Centralized Fuzzy Data Association Algorithm of Three-sensor Multi-target Tracking System Reearch Joural of Appled Scece, Egeerg ad echology 7(6): 55-6, 4 DOI:.96/rjae.7.89 ISSN: 4-7459; e-issn: 4-7467 4 Maxwell Scefc Publcao Corp. Submed: Aprl, Acceped: May 8, Publhed: February 5, 4 Reearch

More information

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits.

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits. ose ad Varably Homewor # (8), aswers Q: Power spera of some smple oses A Posso ose A Posso ose () s a sequee of dela-fuo pulses, eah ourrg depedely, a some rae r (More formally, s a sum of pulses of wdh

More information

Supplement Material for Inverse Probability Weighted Estimation of Local Average Treatment Effects: A Higher Order MSE Expansion

Supplement Material for Inverse Probability Weighted Estimation of Local Average Treatment Effects: A Higher Order MSE Expansion Suppleme Maeral for Iverse Probably Weged Esmao of Local Average Treame Effecs: A Hger Order MSE Expaso Sepe G. Doald Deparme of Ecoomcs Uversy of Texas a Aus Yu-C Hsu Isue of Ecoomcs Academa Sca Rober

More information

Midterm Exam. Tuesday, September hour, 15 minutes

Midterm Exam. Tuesday, September hour, 15 minutes Ecoomcs of Growh, ECON560 Sa Fracsco Sae Uvers Mchael Bar Fall 203 Mderm Exam Tuesda, Sepember 24 hour, 5 mues Name: Isrucos. Ths s closed boo, closed oes exam. 2. No calculaors of a d are allowed. 3.

More information

The algebraic immunity of a class of correlation immune H Boolean functions

The algebraic immunity of a class of correlation immune H Boolean functions Ieraoal Coferece o Advaced Elecroc Scece ad Techology (AEST 06) The algebrac mmuy of a class of correlao mmue H Boolea fucos a Jgla Huag ad Zhuo Wag School of Elecrcal Egeerg Norhwes Uversy for Naoales

More information

International Journal Of Engineering And Computer Science ISSN: Volume 5 Issue 12 Dec. 2016, Page No.

International Journal Of Engineering And Computer Science ISSN: Volume 5 Issue 12 Dec. 2016, Page No. www.jecs. Ieraoal Joural Of Egeerg Ad Compuer Scece ISSN: 19-74 Volume 5 Issue 1 Dec. 16, Page No. 196-1974 Sofware Relably Model whe mulple errors occur a a me cludg a faul correco process K. Harshchadra

More information

Moments of Order Statistics from Nonidentically Distributed Three Parameters Beta typei and Erlang Truncated Exponential Variables

Moments of Order Statistics from Nonidentically Distributed Three Parameters Beta typei and Erlang Truncated Exponential Variables Joural of Mahemacs ad Sascs 6 (4): 442-448, 200 SSN 549-3644 200 Scece Publcaos Momes of Order Sascs from Nodecally Dsrbued Three Parameers Bea ype ad Erlag Trucaed Expoeal Varables A.A. Jamoom ad Z.A.

More information

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters Leas Squares Fg LSQF wh a complcaed fuco Theeampleswehavelookedasofarhavebeelearheparameers ha we have bee rg o deerme e.g. slope, ercep. For he case where he fuco s lear he parameers we ca fd a aalc soluo

More information

ELEC 6041 LECTURE NOTES WEEK 3 Dr. Amir G. Aghdam Concordia University

ELEC 6041 LECTURE NOTES WEEK 3 Dr. Amir G. Aghdam Concordia University ecre Noe Prepared b r G. ghda EE 64 ETUE NTE WEE r. r G. ghda ocorda Uer eceraled orol e - Whe corol heor appled o a e ha co of geographcall eparaed copoe or a e cog of a large ber of p-op ao ofe dered

More information

Complementary Tree Paired Domination in Graphs

Complementary Tree Paired Domination in Graphs IOSR Joural of Mahemacs (IOSR-JM) e-issn: 2278-5728, p-issn: 239-765X Volume 2, Issue 6 Ver II (Nov - Dec206), PP 26-3 wwwosrjouralsorg Complemeary Tree Pared Domao Graphs A Meeaksh, J Baskar Babujee 2

More information

Brownian Motion and Stochastic Calculus. Brownian Motion and Stochastic Calculus

Brownian Motion and Stochastic Calculus. Brownian Motion and Stochastic Calculus Browa Moo Sochasc Calculus Xogzh Che Uversy of Hawa a Maoa earme of Mahemacs Seember, 8 Absrac Ths oe s abou oob decomoso he bascs of Suare egrable margales Coes oob-meyer ecomoso Suare Iegrable Margales

More information

Fully Fuzzy Linear Systems Solving Using MOLP

Fully Fuzzy Linear Systems Solving Using MOLP World Appled Sceces Joural 12 (12): 2268-2273, 2011 ISSN 1818-4952 IDOSI Publcaos, 2011 Fully Fuzzy Lear Sysems Solvg Usg MOLP Tofgh Allahvraloo ad Nasser Mkaelvad Deparme of Mahemacs, Islamc Azad Uversy,

More information

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending CUIC SLINE CURVES Cubc Sples Marx formulao Normalsed cubc sples Alerae ed codos arabolc bledg AML7 CAD LECTURE CUIC SLINE The ame sple comes from he physcal srume sple drafsme use o produce curves A geeral

More information

Probability Bracket Notation and Probability Modeling. Xing M. Wang Sherman Visual Lab, Sunnyvale, CA 94087, USA. Abstract

Probability Bracket Notation and Probability Modeling. Xing M. Wang Sherman Visual Lab, Sunnyvale, CA 94087, USA. Abstract Probably Bracke Noao ad Probably Modelg Xg M. Wag Sherma Vsual Lab, Suyvale, CA 94087, USA Absrac Ispred by he Drac oao, a ew se of symbols, he Probably Bracke Noao (PBN) s proposed for probably modelg.

More information

Continuous Indexed Variable Systems

Continuous Indexed Variable Systems Ieraoal Joural o Compuaoal cece ad Mahemacs. IN 0974-389 Volume 3, Number 4 (20), pp. 40-409 Ieraoal Research Publcao House hp://www.rphouse.com Couous Idexed Varable ysems. Pouhassa ad F. Mohammad ghjeh

More information

Available online Journal of Scientific and Engineering Research, 2014, 1(1): Research Article

Available online  Journal of Scientific and Engineering Research, 2014, 1(1): Research Article Avalable ole wwwjsaercom Joural o Scec ad Egeerg Research, 0, ():0-9 Research Arcle ISSN: 39-630 CODEN(USA): JSERBR NEW INFORMATION INEUALITIES ON DIFFERENCE OF GENERALIZED DIVERGENCES AND ITS APPLICATION

More information

θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions:

θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions: Paramerc coug process models Cosder coug processes: N,,..., ha cou he occurreces of a eve of eres for dvduals Iesy processes: Lelhood λ ( ;,,..., N { } λ < Log-lelhood: l( log L( Score fucos: U ( l( log

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signal & Syem Prof. Mark Fowler Noe Se #27 C-T Syem: Laplace Tranform Power Tool for yem analyi Reading Aignmen: Secion 6.1 6.3 of Kamen and Heck 1/18 Coure Flow Diagram The arrow here how concepual

More information

Fault Diagnosis in Stationary Rotor Systems through Correlation Analysis and Artificial Neural Network

Fault Diagnosis in Stationary Rotor Systems through Correlation Analysis and Artificial Neural Network Faul Dago Saoary oor Syem hrough Correlao aly ad rfcal Neural Newor leadre Carlo duardo a ad obo Pederva b a Federal Uvery of Ma Gera (UFMG). Deparme of Mechacal geerg (DMC) aceduard@homal.com b Sae Uvery

More information

Second Quantization for Fermions

Second Quantization for Fermions 9 Chaper Secod Quazao for Fermo Maro Pr Iuo Superor de Ceca y Tecología Nucleare, Ave Salvador Allede y Luace, Qua de lo Molo, La Habaa 6, Cuba. The objec of quaum chemry co of eracg may parcle yem of

More information

Mixed Integral Equation of Contact Problem in Position and Time

Mixed Integral Equation of Contact Problem in Position and Time Ieraoal Joural of Basc & Appled Sceces IJBAS-IJENS Vol: No: 3 ed Iegral Equao of Coac Problem Poso ad me. A. Abdou S. J. oaquel Deparme of ahemacs Faculy of Educao Aleadra Uversy Egyp Deparme of ahemacs

More information

Partial Molar Properties of solutions

Partial Molar Properties of solutions Paral Molar Properes of soluos A soluo s a homogeeous mxure; ha s, a soluo s a oephase sysem wh more ha oe compoe. A homogeeous mxures of wo or more compoes he gas, lqud or sold phase The properes of a

More information

Linear Approximating to Integer Addition

Linear Approximating to Integer Addition Lear Approxmatg to Iteger Addto L A-Pg Bejg 00085, P.R. Cha apl000@a.com Abtract The teger addto ofte appled cpher a a cryptographc mea. I th paper we wll preet ome reult about the lear approxmatg for

More information

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China,

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China, Mahemacal ad Compuaoal Applcaos Vol. 5 No. 5 pp. 834-839. Assocao for Scefc Research VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS Hoglag Lu Aguo Xao Yogxag Zhao School of Mahemacs

More information

A note on Turán number Tk ( 1, kn, )

A note on Turán number Tk ( 1, kn, ) A oe o Turá umber T (,, ) L A-Pg Beg 00085, P.R. Cha apl000@sa.com Absrac: Turá umber s oe of prmary opcs he combaorcs of fe ses, hs paper, we wll prese a ew upper boud for Turá umber T (,, ). . Iroduco

More information

Nilpotent Elements in Skew Polynomial Rings

Nilpotent Elements in Skew Polynomial Rings Joural of Scece, Ilac epublc of Ira 8(): 59-74 (07) Uvery of Tehra, ISSN 06-04 hp://cece.u.ac.r Nlpoe Elee Sew Polyoal g M. Az ad A. Mouav * Depare of Pure Maheac, Faculy of Maheacal Scece, Tarba Modare

More information

Deterioration-based Maintenance Management Algorithm

Deterioration-based Maintenance Management Algorithm Aca Polyechca Hugarca Vol. 4 No. 2007 Deerorao-baed Maeace Maageme Algorhm Koréla Ambru-Somogy Iue of Meda Techology Budape Tech Doberdó ú 6 H-034 Budape Hugary a_omogy.korela@rkk.bmf.hu Abrac: The Road

More information

CS473-Algorithms I. Lecture 12b. Dynamic Tables. CS 473 Lecture X 1

CS473-Algorithms I. Lecture 12b. Dynamic Tables. CS 473 Lecture X 1 CS473-Algorthm I Lecture b Dyamc Table CS 473 Lecture X Why Dyamc Table? I ome applcato: We do't kow how may object wll be tored a table. We may allocate pace for a table But, later we may fd out that

More information

On cartesian product of fuzzy primary -ideals in -LAsemigroups

On cartesian product of fuzzy primary -ideals in -LAsemigroups Joural Name Orgal Research aper O caresa produc o uzzy prmary -deals -Lsemgroups aroe Yarayog Deparme o Mahemacs, Faculy o cece ad Techology, bulsogram Rajabha Uvers, hsauloe 65000, Thalad rcle hsory Receved:

More information

Cyclone. Anti-cyclone

Cyclone. Anti-cyclone Adveco Cycloe A-cycloe Lorez (963) Low dmesoal aracors. Uclear f hey are a good aalogy o he rue clmae sysem, bu hey have some appealg characerscs. Dscusso Is he al codo balaced? Is here a al adjusme

More information

MODERN CONTROL SYSTEMS

MODERN CONTROL SYSTEMS MODERN CONTROL SYSTEMS Lecure 9, Sae Space Repreeaio Emam Fahy Deparme of Elecrical ad Corol Egieerig email: emfmz@aa.edu hp://www.aa.edu/cv.php?dip_ui=346&er=6855 Trafer Fucio Limiaio TF = O/P I/P ZIC

More information

Reliability Analysis of Sparsely Connected Consecutive-k Systems: GERT Approach

Reliability Analysis of Sparsely Connected Consecutive-k Systems: GERT Approach Relably Aalyss of Sparsely Coece Cosecuve- Sysems: GERT Approach Pooa Moha RMSI Pv. L Noa-2131 poalovely@yahoo.com Mau Agarwal Deparme of Operaoal Research Uversy of Delh Delh-117, Ia Agarwal_maulaa@yahoo.com

More information

The Theory of Membership Degree of Γ-Conclusion in Several n-valued Logic Systems *

The Theory of Membership Degree of Γ-Conclusion in Several n-valued Logic Systems * erca Joural of Operao eearch 0 47-5 hp://ddoorg/046/ajor007 Publhed Ole Jue 0 (hp://wwwscporg/joural/ajor) The Theory of Meberhp Degree of Γ-Cocluo Several -Valued Logc Sye Jacheg Zhag Depare of Maheac

More information

Interval Estimation. Consider a random variable X with a mean of X. Let X be distributed as X X

Interval Estimation. Consider a random variable X with a mean of X. Let X be distributed as X X ECON 37: Ecoomercs Hypohess Tesg Iervl Esmo Wh we hve doe so fr s o udersd how we c ob esmors of ecoomcs reloshp we wsh o sudy. The queso s how comforble re we wh our esmors? We frs exme how o produce

More information

Research Article Almost Automorphic Solutions for Fuzzy Cohen-Grossberg Neural Networks with Mixed Time Delays

Research Article Almost Automorphic Solutions for Fuzzy Cohen-Grossberg Neural Networks with Mixed Time Delays Hdaw Publhg Corporao Mahemacal Problem Egeerg Volume 15, Arcle ID 8167, 14 page hp://dx.do.org/1.1155/15/8167 Reearch Arcle Almo Auomorphc Soluo for Fuzzy Cohe-Groberg Neural Nework wh Mxed Tme Delay Yogku

More information

For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body.

For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body. The kecs of rgd bodes reas he relaoshps bewee he exeral forces acg o a body ad he correspodg raslaoal ad roaoal moos of he body. he kecs of he parcle, we foud ha wo force equaos of moo were requred o defe

More information

Upper Bound For Matrix Operators On Some Sequence Spaces

Upper Bound For Matrix Operators On Some Sequence Spaces Suama Uer Bou formar Oeraors Uer Bou For Mar Oeraors O Some Sequece Saces Suama Dearme of Mahemacs Gaah Maa Uersy Yogyaara 558 INDONESIA Emal: suama@ugmac masomo@yahoocom Isar D alam aer aa susa masalah

More information

The Lattice of Fully Invariant Subgroups of the Cotorsion Hull

The Lattice of Fully Invariant Subgroups of the Cotorsion Hull Advace Pure Mahemac 3 3 67-679 Publhed Ole November 3 (h://wwwcrorg/oural/am) h://dxdoorg/436/am3389 he Lace of Fully Ivara Subgrou of he Cooro Hull arel Kemoldze Dearme of Mahemac Aa ereel Sae Uvery Kua

More information

with finite mean t is a conditional probability of having n, n 0 busy servers in the model at moment t, if at starting time t = 0 the model is empty.

with finite mean t is a conditional probability of having n, n 0 busy servers in the model at moment t, if at starting time t = 0 the model is empty. INFINITE-SERVER M G QUEUEING MODELS WITH CATASTROPHES K Kerobya The fe-erver qeeg model M G, BM G, BM G wh homogeeo ad o-homogeeo arrval of comer ad caarophe are codered The probably geerag fco (PGF) of

More information

4. THE DENSITY MATRIX

4. THE DENSITY MATRIX 4. THE DENSTY MATRX The desy marx or desy operaor s a alerae represeao of he sae of a quaum sysem for whch we have prevously used he wavefuco. Alhough descrbg a quaum sysem wh he desy marx s equvale o

More information

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction refeed Soluos for R&D o Desg Deermao of oe Equao arameers Soluos for R&D o Desg December 4, 0 refeed orporao Yosho Kumagae refeed Iroduco hyscal propery daa s exremely mpora for performg process desg ad

More information

The Properties of Probability of Normal Chain

The Properties of Probability of Normal Chain I. J. Coep. Mah. Sceces Vol. 8 23 o. 9 433-439 HIKARI Ld www.-hkar.co The Properes of Proaly of Noral Cha L Che School of Maheacs ad Sascs Zheghou Noral Uversy Zheghou Cy Hea Provce 4544 Cha cluu6697@sa.co

More information

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse P a g e Vol Issue7Ver,oveber Global Joural of Scece Froer Research Asypoc Behavor of Soluos of olear Delay Dffereal Equaos Wh Ipulse Zhag xog GJSFR Classfcao - F FOR 3 Absrac Ths paper sudes he asypoc

More information

Bianchi Type II Stiff Fluid Tilted Cosmological Model in General Relativity

Bianchi Type II Stiff Fluid Tilted Cosmological Model in General Relativity Ieraoal Joural of Mahemacs esearch. IN 0976-50 Volume 6, Number (0), pp. 6-7 Ieraoal esearch Publcao House hp://www.rphouse.com Bach ype II ff Flud led Cosmologcal Model Geeral elay B. L. Meea Deparme

More information

Final Exam Applied Econometrics

Final Exam Applied Econometrics Fal Eam Appled Ecoomercs. 0 Sppose we have he followg regresso resl: Depede Varable: SAT Sample: 437 Iclded observaos: 437 Whe heeroskedasc-cosse sadard errors & covarace Varable Coeffce Sd. Error -Sasc

More information

The textbook expresses the stock price as the present discounted value of the dividend paid and the price of the stock next period.

The textbook expresses the stock price as the present discounted value of the dividend paid and the price of the stock next period. ublc Affars 974 Meze D. Ch Fall Socal Sceces 748 Uversy of Wscos-Madso Sock rces, News ad he Effce Markes Hypohess (rev d //) The rese Value Model Approach o Asse rcg The exbook expresses he sock prce

More information

arxiv:math/ v1 [math.fa] 1 Feb 1994

arxiv:math/ v1 [math.fa] 1 Feb 1994 arxiv:mah/944v [mah.fa] Feb 994 ON THE EMBEDDING OF -CONCAVE ORLICZ SPACES INTO L Care Schü Abrac. I [K S ] i wa how ha Ave ( i a π(i) ) π i equivale o a Orlicz orm whoe Orlicz fucio i -cocave. Here we

More information

Economics 8723 Macroeconomic Theory Problem Set 3 Sketch of Solutions Professor Sanjay Chugh Spring 2017

Economics 8723 Macroeconomic Theory Problem Set 3 Sketch of Solutions Professor Sanjay Chugh Spring 2017 Deparme of Ecoomic The Ohio Sae Uiveriy Ecoomic 8723 Macroecoomic Theory Problem Se 3 Skech of Soluio Profeor Sajay Chugh Sprig 27 Taylor Saggered Nomial Price-Seig Model There are wo group of moopoliically-compeiive

More information

-distributed random variables consisting of n samples each. Determine the asymptotic confidence intervals for

-distributed random variables consisting of n samples each. Determine the asymptotic confidence intervals for Assgme Sepha Brumme Ocober 8h, 003 9 h semeser, 70544 PREFACE I 004, I ed o sped wo semesers o a sudy abroad as a posgraduae exchage sude a he Uversy of Techology Sydey, Ausrala. Each opporuy o ehace my

More information

PARAMETER OPTIMIZATION FOR ACTIVE SHAPE MODELS. Contact:

PARAMETER OPTIMIZATION FOR ACTIVE SHAPE MODELS. Contact: PARAMEER OPIMIZAION FOR ACIVE SHAPE MODELS Chu Che * Mg Zhao Sa Z.L Jaju Bu School of Compuer Scece ad echology, Zhejag Uvery, Hagzhou, Cha Mcroof Reearch Cha, Bejg Sgma Ceer, Bejg, Cha Coac: chec@zju.edu.c

More information

Chapter 8. Simple Linear Regression

Chapter 8. Simple Linear Regression Chaper 8. Smple Lear Regresso Regresso aalyss: regresso aalyss s a sascal mehodology o esmae he relaoshp of a respose varable o a se of predcor varable. whe here s jus oe predcor varable, we wll use smple

More information

On Metric Dimension of Two Constructed Families from Antiprism Graph

On Metric Dimension of Two Constructed Families from Antiprism Graph Mah S Le 2, No, -7 203) Mahemaal Sees Leers A Ieraoal Joural @ 203 NSP Naural Sees Publhg Cor O Mer Dmeso of Two Cosrued Famles from Aprm Graph M Al,2, G Al,2 ad M T Rahm 2 Cere for Mahemaal Imagg Tehques

More information

Comparison of the Bayesian and Maximum Likelihood Estimation for Weibull Distribution

Comparison of the Bayesian and Maximum Likelihood Estimation for Weibull Distribution Joural of Mahemacs ad Sascs 6 (2): 1-14, 21 ISSN 1549-3644 21 Scece Publcaos Comarso of he Bayesa ad Maxmum Lkelhood Esmao for Webull Dsrbuo Al Omar Mohammed Ahmed, Hadeel Salm Al-Kuub ad Noor Akma Ibrahm

More information

Speech, NLP and the Web

Speech, NLP and the Web peech NL ad he Web uhpak Bhaacharyya CE Dep. IIT Bombay Lecure 38: Uuperved learg HMM CFG; Baum Welch lecure 37 wa o cogve NL by Abh Mhra Baum Welch uhpak Bhaacharyya roblem HMM arg emac ar of peech Taggg

More information

General Complex Fuzzy Transformation Semigroups in Automata

General Complex Fuzzy Transformation Semigroups in Automata Joural of Advaces Compuer Research Quarerly pissn: 345-606x eissn: 345-6078 Sar Brach Islamc Azad Uversy Sar IRIra Vol 7 No May 06 Pages: 7-37 wwwacrausaracr Geeral Complex uzzy Trasformao Semgroups Auomaa

More information

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n 0. Sere I th ecto, we wll troduce ere tht wll be dcug for the ret of th chpter. Wht ere? If we dd ll term of equece, we get whch clled fte ere ( or jut ere) d deoted, for hort, by the ymbol or Doe t mke

More information

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations Joural of aheacs ad copuer Scece (4 39-38 Soluo of Ipulsve Dffereal Equaos wh Boudary Codos Ters of Iegral Equaos Arcle hsory: Receved Ocober 3 Acceped February 4 Avalable ole July 4 ohse Rabba Depare

More information

Extremal graph theory II: K t and K t,t

Extremal graph theory II: K t and K t,t Exremal graph heory II: K ad K, Lecure Graph Theory 06 EPFL Frak de Zeeuw I his lecure, we geeralize he wo mai heorems from he las lecure, from riagles K 3 o complee graphs K, ad from squares K, o complee

More information

Redundancy System Fault Sampling Under Imperfect Maintenance

Redundancy System Fault Sampling Under Imperfect Maintenance A publcao of CHEMICAL EGIEERIG TRASACTIOS VOL. 33, 03 Gues Edors: Erco Zo, Pero Barald Copyrgh 03, AIDIC Servz S.r.l., ISB 978-88-95608-4-; ISS 974-979 The Iala Assocao of Chemcal Egeerg Ole a: www.adc./ce

More information

1 Notes on Little s Law (l = λw)

1 Notes on Little s Law (l = λw) Copyrigh c 26 by Karl Sigma Noes o Lile s Law (l λw) We cosider here a famous ad very useful law i queueig heory called Lile s Law, also kow as l λw, which assers ha he ime average umber of cusomers i

More information

FORCED VIBRATION of MDOF SYSTEMS

FORCED VIBRATION of MDOF SYSTEMS FORCED VIBRAION of DOF SSES he respose of a N DOF sysem s govered by he marx equao of moo: ] u C] u K] u 1 h al codos u u0 ad u u 0. hs marx equao of moo represes a sysem of N smulaeous equaos u ad s me

More information

National Conference on Recent Trends in Synthesis and Characterization of Futuristic Material in Science for the Development of Society

National Conference on Recent Trends in Synthesis and Characterization of Futuristic Material in Science for the Development of Society ABSTRACT Naoa Coferece o Rece Tred Syhe ad Characerzao of Fuurc Maera Scece for he Deveome of Socey (NCRDAMDS-208) I aocao wh Ieraoa Joura of Scefc Reearch Scece ad Techoogy Some New Iegra Reao of I- Fuco

More information

IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS

IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS Vol.7 No.4 (200) p73-78 Joural of Maageme Scece & Sascal Decso IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS TIANXIANG YAO AND ZAIWU GONG College of Ecoomcs &

More information

Laplace Transform. Definition of Laplace Transform: f(t) that satisfies The Laplace transform of f(t) is defined as.

Laplace Transform. Definition of Laplace Transform: f(t) that satisfies The Laplace transform of f(t) is defined as. Lplce Trfor The Lplce Trfor oe of he hecl ool for olvg ordry ler dfferel equo. - The hoogeeou equo d he prculr Iegrl re olved oe opero. - The Lplce rfor cover he ODE o lgerc eq. σ j ple do. I he pole o

More information

FALL HOMEWORK NO. 6 - SOLUTION Problem 1.: Use the Storage-Indication Method to route the Input hydrograph tabulated below.

FALL HOMEWORK NO. 6 - SOLUTION Problem 1.: Use the Storage-Indication Method to route the Input hydrograph tabulated below. Jorge A. Ramírez HOMEWORK NO. 6 - SOLUTION Problem 1.: Use he Sorage-Idcao Mehod o roue he Ipu hydrograph abulaed below. Tme (h) Ipu Hydrograph (m 3 /s) Tme (h) Ipu Hydrograph (m 3 /s) 0 0 90 450 6 50

More information

Other Topics in Kernel Method Statistical Inference with Reproducing Kernel Hilbert Space

Other Topics in Kernel Method Statistical Inference with Reproducing Kernel Hilbert Space Oher Topcs Kerel Mehod Sascal Iferece wh Reproducg Kerel Hlber Space Kej Fukumzu Isue of Sascal Mahemacs, ROIS Deparme of Sascal Scece, Graduae Uversy for Advaced Sudes Sepember 6, 008 / Sascal Learg Theory

More information