Distribution of Mass and Energy in Closed Model of the Universe
|
|
- Shon Phillips
- 5 years ago
- Views:
Transcription
1 Ieraial Jural f Asrmy ad Asrysics, 05, 5, 9-0 Publised Olie December 05 i SciRes ://wwwscirrg/jural/ijaa ://dxdirg/046/ijaa05540 Disribui f Mass ad Eergy i Clsed Mdel f e Uiverse Fadel A Bukari Dearme f Asrmy, Faculy f Sciece, Kig Abdulaziz Uiversiy, Jedda, Saudi Arabia Received February 05; acceed December 05; ublised 5 December 05 Cyrig 05 by aur ad Scieific Researc Publisig Ic Tis wrk is licesed uder e Creaive Cmms Aribui Ieraial Licese (CC BY) ://creaivecmmsrg/liceses/by/40/ Absrac Te uiverse s riz disace ad vlume are csruced i e clsed csmic mdel Te uiverse riz disace disribui icreases csaly fr < me ad decreases fr > me Hwever, e uiverse s riz vlume sws a sudde reduci i e rage = 05 Gyr me due e cage f e uiverse sace frm fla curved e clsed i e ierval 56 Gyr me O e er ad, is disribui exibis a abru rise i e rage = me due e cage f e uiverse sace frm clsed e curved fla i e ierval Gyr Te mass f radiai, maer ad dark eergy wii e riz vlume f e uiverse are als ivesigaed Tese disribuis reveal similar iceable cages as e uiverse s riz vlume disribui fr e same reass Te mass f radiai dmiaes u = 55 yr, e e mass f maer becmes larger Aferwards, b disribuis f radiai ad maer decrease wile e disribui f dark eergy rises uil = 0007 Gyr, were e mass f dark eergy revails u = me Hece, e disribui f dark eergy reduces uil = 4089 Gyr, were e mass f maer becmes rmie agai A = 5646 Gyr e masses f b maer ad radiai becme areciably ig suc a e iercluser sace will vais ad clusers f galaxies ierfere wi eac er Furermre, ly e iergalacic medium will disaear, bu als galaxies will cllide ad merge wi eac er frm exremely dese ad clse csmlgical bdies Tese very dese bdies will uderg furer successive cllisis ad mergers uder e aci f ceral graviy, were e iersellar medium will vais ad e uiverse wuld devel big cruc a bc = 565 Gyr I is ieresig e a e riz disace f e uiverse i e clsed mdel a = me is i very gd agreeme wi e maximum riz disaces i e five geeral csmic mdels Keywrds Dark Eergy, Radiai, Clsed Csmic Mdel Hw cie is aer: Bukari, FA (05) Disribui f Mass ad Eergy i Clsed Mdel f e Uiverse Ieraial Jural f Asrmy ad Asrysics, 5, 9-0 ://dxdirg/046/ijaa05540
2 F A Bukari Irduci Te disribui f desiy arameers f radiai, maer ad dark eergy i e clsed csmic mdel were ivesigaed i a revius sudy [], were we discvered e mai ecs f e uiverse isry i is mdel I is wry w sudy e disribuis f equivale mass f radiai, mass f maer ad equivale mass f dark eergy wii e riz vlume f e uiverse ge deeer sig f e uiverse evlui i e clsed mdel Te reas fr csiderig e equivale mass f radiai i is sudy is e sigifica value f e radiai desiy arameer i e early uiverse ad befre e big cruc as we ave see i [] Terefre, i is vial devel e disribuis f e riz disace ad riz vlume f e uiverse i e clsed mdel a varius ime rages deedig e bases reseed i [] Descrii f medlgy is illusraed i Seci, wile algrim wuld be sw i Seci Resuls ad discussi are dislayed i Seci 4 Cclusi is give i Seci 5 Medlgy I is bvius frm [] a e riz disace ad riz vlume f e uiverse i clsed csmic mdel a e rese ime are resecively c 4 d( ) = S, ( ), ( ), ( ) d 0 a S m a a S Λ r a a a H Ω + Ω + Ω () a 8π V( ) = d ( ) () were Ω Λ,, Ω m, ad Ω r, are give by Λ, Ω Λ, = () c c, c, m, Ω m, = (4) ρ Ω = r, r, c c, ( ) H c, = (6) 8πG 4 H H ( ) = s Ω Λ, ( a ) + s Ω m, ( a a ) + s Ω r, ( a a ) a H( ) H ( ) were s =, S = H H ( ) Λ ( a ) H H =, m, r, a Ω +Ω +Ω a a (8) Λ, Ω Λ, = (9) c ρ c, c, m, Ω m, = (0) ρ Ω = () r, r, c ρc, (5) (7) 9
3 F A Bukari were is e csmic ime i Gyr ρ Λ, Λ, = ρ c, ΩΛ, c Ωm, ρλ, m, = ρc, + a c r, Ωr, ρλ, = ρ c, + 4 c a c ρλ, ρλ, 00 = c c c () () (4) (5) H ρ c, = (6) 8πG Te riz disace f e uiverse i e clsed csmic mdel a ay give ime is give by c a 4 ( ) = Ω, ( ), ( ), ( ) d 0 Λ + Ω m + Ωr H a d S a S a a S a a a (7-a) Csequely, e cage i e riz disace f e uiverse i e ime ierval bewee w isas f scale facrs a, a is wrie as c a ( ) 4, ( ) m, ( ) r, ( ) d H a Λ a d = S Ω a + S Ω a a + S Ω a a a (7-b) Te riz vlume f e uiverse i e clsed mdel a ay give ime is exressed as ( ) ( ( ) ) V = f d, k (8) Equai (8) idicaes a e riz vlume f e uiverse a is a fuci f d ( ) ad e curvaure f sace k a Sice is curvaure culd be fla, e ad clsed frm e big bag big cruc as evide frm Table i [] Tus, e lw f V ( ) ca be deermied accrdig e value f k a, as exlaied i e fllwig cases: () Fla sace ( k = 0 ) We ave see i [] a e riz vlume f e uiverse a ime i is case is give by 8π V( ) = d ( ) (9) Terefre, i is bvius frm Table i [] a Equai (9) is used i e ime iervals 0075 < 56 Gyr, 98 < 4075 Gyr, ad 548 < bc () Clsed sace ( k = + ) We recall e equai f rer disace f exragalacic bjec were Ad e vlume f sace wii d ( ) ( ) ( ) ( ) 65 Gyr, d = R f r (0) si r k = + r dr f ( r) = = r 0 0 k = () kr si r k = is exressed as r V R r kr r ( ) ( ) π π = dφ siθdθ d () 9
4 F A Bukari were R( ), r, r, θ ad φ are defied as i [] [4] Fr k = +, Equais (), (0) ad () yield Hece Equai () gives Assume ( ) ( ) si d = R r () r r dr V ( ) = 8π R ( ) (4) 0 r Subsiuig by (5) i (4) we ge Le Subsiuig by (7) i (6) we ave Subsiuig by () i (8) yields Suse r =, ece r r r = si α, d = csαd α, csα = (5) si r ( ) = ( ) ( ) V 4πR cs α d α (6) 0 β = α, dβ = d α (7) r r V( ) = 4πR ( )( si r) ( si r) ( si r ) r r V( ) = 4π d( ) ( ) ( si r si r ) π α = ad Equai (9) becmes (8) (9) 6 V( ) = d( ) (0) π Tus, e riz vlume f e uiverse i e clsed csmic mdel a ime i is case is exressed as 6 V( ) = d ( ) () π I is evide frm Table i [] a Equai () is used i w ime iervals exedig rug 56 < 98 Gyr () Oe sace ( k = ) Equais (), (0) ad () give Assume Subsiuig by (4) i () we ave ( ) ( ) si d = R r () r r dr V ( ) = 8π R ( ) () 0 + r r r r = si ξ, d = csξd ξ, csξ = + (4) si r ( ) = ( ) ( ) V 4πR cs ξ d ξ (5) 0 94
5 F A Bukari Le Subsiuig by (6) i (5) we ge Subsiuig by () i (7) yields We r =, Equai (8) reduces η = ξ, dη = d ξ (6) ( r) ( si r) ( si r) r cs si V( ) = 4πR ( )( si r) ( r) ( si r) ( si r) r cs si V( ) = 4π d( ) ( ) ( ) (7) (8) V = 98π d (9) Terefre, e riz vlume f e uiverse i clsed csmic mdel a ime i is case is wrie as ( ) ( ) V = 98π d (40) I is clear frm Table i [] a Equai (40) is used i e ime iervals 65< 0075 Gyr, 4075< 548 Gyr Te al desiy f e uiverse i e clsed csmic mdel a ime is Subsiuig by ()-(5) i (4) we ge were r, Λ, ( ) = m, + + (4) c c ( ) = c, Ω m, + c, Ω r, + c, Ω, Λ ( ) ρ ( ) = Ω (4) c, ( ),,, Ω =Ω +Ω +Ω (4) m r Λ Frm Equai (9), (0), (40) ad (4) e al mass f e uiverse wii e riz vlume i clsed csmic mdel a ime is ( ) ( ) ( ) M = V (44) Te masses f maer, radiai ad dark eergy wii e riz vlume f e uiverse i clsed csmic mdel a ime are resecively ( ) m, m, = M M ( ) Ω Ω ( ) r, r, = M M ( ) Ω Ω ( ), Λ, = M M Te ime ierval bewee w isas wi scale facrs a, a durig e uiverse exasi is give by Equai (6) i [4] [5] as Ω Λ Ω ( ) Δ a =, ( a ) m, r, d a a Λ H Ω +Ω +Ω a a (45) (46) (47) (48) 95
6 F A Bukari Hwever, durig e uiverse craci if a < a e mdulus f e rig ad side f (50) suld be ake Algrim I deermiai f e disribuis f ( ), ( ), ( ), m,, r, ad Λ, d V M M M M we use e fllwig ses: () Sage f e uiverse exasi a) Se = 0, d = 0 ad iser e value f amax = 00988, J = 000 fr 05 Gyr, a max = 75587, J = 600 fr 05 < me amax b) Calculae DA = DBLE J ( ) c) Sar geeral DO l I =, J wic icludes e fllwig sub ses: a = DA I, a = DA I d) ( ) e) Cmue ew value f csmic ime umerically usig (48), were = + Δ f) Obai ew value f e uiverse riz disace d umerically usig (7-b), were d = d + Δd g) Deermie e crresdig values f V usig (9), () ad (40), i addii e values f H ( ), c,, Ω m,, Ω r,, Ω Λ,, Ω ( ), ( ), M( ), Mm,, Mr, ad M Λ, usig (7), (6), (4), (5), (), (4), (4), (44), (45), (46) ad (47) resecively ) Ciue e geeral DO l () Sage f e uiverse craci a) Se = me = 6857 Gyr, d = d ( me ) = 8694 Gc, ad iser e values f amax = 75587, J = 600 fr me < *, * = bc 05 Gr y, amax = 00959, J = 90 fr > * amax b) Evaluae DA = DBLE J ( ) c) Sar geeral DO l I =, J wic icludes e fllwig sub ses: J = J I +, a = DA J, a = DA J d) Se ( ) e) Obai ew value f csmic ime umerically usig (48), were = + Δ f) Cmue ew value f e uiverse riz disace d umerically usig (7-b), were d = d Δd Sub ses (g) ad () are similar (g), () meied abve i e sage f e uiverse exasi 4 Resuls ad Discussi Te disribui f e uiverse riz disace i e clsed csmic mdel uil = 05 Gyr is sw i Figure (a) Te disribui icreases quie slwly u = Myr, e e disribui sars raisig raidly Hwever, e disribui f e uiverse riz disace i e rage = 05 Gyr - me icreases very fas uil abu = 577 Gyr Aferwards, i raises gradually as idicaed i Figure (b) Furermre, e disribui f e uiverse riz disace i e rage = me - *, were * = bc - 05 Gyr, decreases quie slwly u = Gyr, ece i decreases relaively fas as reseed i Figure (c) Nevereless, e disribui f e uiverse riz disace i e rage = - * decreases slwly uil = 547 Gyr, = bc Gyr, e i sars reduci sarly wards = bc as dislayed i Figure (d) Te disribui f e uiverse riz vlume i e clsed csmic mdel u = 05 Gyr is sw i Figure (a) Te disribui icreases very slwly uil = Myr Aferwards, e disribui sars raisig areciably Durig is csmic ime rage e sace f uiverse is fla Te disribui f e uiverse riz vlume ciues raisig u = 48 Gyr, ece e disribui suddely decreases uil = Gyr, e i icreases gradually u = me as see is Figure (b) Te sar decrease f e disribui i e rage 48 < < Gyr because e sace f e uiverse cages frm fla curved e clsed i e ierval 56 Gyr me Te disribui f e uiverse riz vlume i e rage = me - * is disclsed i Figure (c) Te disribui decreases uil = Gyr, ece i sws abru raisig u = Gyr, ece i reduces agai uil = * Te abru icrease f e disribui i e rage < < Gyr is due 96
7 F A Bukari (a) (b) (c) Figure (a) Te disribui f e uiverse riz disace i e clsed csmic mdel u = 05 Gyr; (b) Te disribui f e uiverse riz disace i e clsed csmic mdel i e rage = 05 Gyr - me ; (c) Te disribui f e uiverse riz disace i e clsed csmic mdel i e rage = me - * ; (d) Te disribui f e uiverse riz disace i e clsed csmic mdel i e rage = * - (d) (a) (b) 97
8 F A Bukari (c) Figure (a) Te disribui f e uiverse riz vlume i e clsed csmic mdel u = 05 Gyr; (b) Te disribui f e uiverse riz vlume i e clsed csmic mdel i e rage = 05 Gyr - me ; (c) Te disribui f e uiverse riz vlume i e clsed csmic mdel i e rage = me - * ; (d) Te disribui f e uiverse riz vlume i e clsed csmic mdel i e rage = * - e fac a e uiverse sace cages frm clsed e curved fla i e ierval Gyr Te disribui f e uiverse riz vlume i e rage = - * is reseed i Figure (d), wic is reducig gradually wards = bc Te disribui f mass ad eergy wii e riz vlume f e uiverse i e clsed csmic mdel uil = 05 Gyr is sw i Figure (a) Te disribuis f radiai ad al mass decrease very slwly u = 4596 yr ad = 606 yr resecively, e ey reduce mre raidly Hwever, e disribui f maer icreases s slwly uil = 86 yr ad i decreases raidly aferwards Tis disribui iersecs wi e disribui f radiai a = 55 yr ad cicides wi e disribui f al mass a = 89 Myr Te disribui f dark eergy icreases ciuusly wards = 05 Gyr Te disribui f mass ad eergy wii e riz vlume f e uiverse i e clsed mdel i e rage = 05 Gyr - me is illusraed i Figure (b) I is iceable a e disribui f radiai iersecs e disribui f dark eergy a = 0668 Gyr, ece i reduces very fas u = 047 Gyr Aferwards, i raises gradually uil = 4965 Gyr, e i decreases abruly u = 697Gyr, were i sars icreasig agai wards me Te disribui f maer decreases u = 794 Gyr, ece i raises very slwly wards me Tis disribui cicides wi e disribui f al mass u = 985 Gyr, ad iersecs wi e dark eergy disribui a = 0007 Gyr Te maer disribui idicaes bvius decrease i e rage = Gyr Te disribui f dark maer icreases uil = 4965 Gyr, ece i als sws marked decrease u = 697 Gyr Aferwards, i raises sligly wards me Te al mass disribui reduces u = 4965 Gyr, e i decreases abruly uil = 697 Gyr Hece, is disribui icreases gradually wards me Te iceable decrease f all fur disribuis i e rage abu 495 < < 697 Gyr is due e cage f e uiverse sace frm fla curved e clsed i e rage 56 me Te disribui f mass ad eergy wii e riz vlume f e uiverse i e clsed mdel i e rage = me - * is illusraed i Figure (c) Te disribui f radiai reduces very slwly uil = 7989 Gyr, e i raises suddely u = 4040 Gyr Hece, is disribui decreases agai uil = Gyr were i iersecs wi e disribui f dark eergy, e i sars raisig wards * Te maer disribui icreases s slwly u = 7989 Gyr, ece i exibis marked raise uil = 4040 Gyr ad iersecs wi e dark eergy disribui a = 4089 Gyr Aferwards, e disribui f maer sws subsaial icrease wards * ad cicides wi e al mass disribui a = 590 Gyr ece fr Te dark eergy disribui reduces gradually uil = 7989 Gyr were i dislays usadig raise u = 4040 Gyr, ece i decreases agai wards * Te al mass disribui reduces als gradually uil = 7989 Gyr, e i exibis bvius icrease u = 4040 Gyr Aferwards, i raises very fas as e maer disribui Te rmie icrease f e fur disribuis i e ierval abu 7989 < < 4040 Gyr is wig e cage f e uiverse sace frm clsed e curved (d) 98
9 F A Bukari (a) (b) (c) Figure (a) Te disribui f mass ad eergy i e clsed csmic mdel u = 05 Gyr; (b) Te disribui f mass ad eergy i e clsed csmic mdel i e rage = 05 Gyr - me ; (c) Te disribui f mass ad eergy i e clsed csmic mdel i e rage = me - * ; (d) Te disribui f e mass ad eergy i e clsed csmic mdel i e rage = * - fla i e rage Gyr Te disribui f mass ad eergy wii e riz vlume f e uiverse i e clsed mdel i e rage = * is dislayed i Figure (d) Te radiai disribui icreases quie slwly uil = 550 Gyr, ece i sars raisig areciably fas Te disribui f b maer ad al mass cicide eac er ad lie ver e radiai disribui Te w disribuis icrease gradually u = 5574 Gyr, e ey raise u Hwever, e dark eergy disribui decreases s slwly uil = 5574 Gyr, aferwards i reduces subsaially Esimais f d( ), V( ), Mr( ), Mm( ), M () ad e equivale umber f e Cma-like clusers e mass f maer wii e uiverse riz vlume NCOMA ( ) i e clsed csmic mdel a secial imes are reseed i Table I is ieresig e a a = = bc Gyr, e riz vlume f e uiverse V ( ) 0000( 0 Gc) = 6 Sice e radius f e Cma cluser is r COMA = 6 Mc [5], e V ( ) = VCOMA, were V COMA is e Cma cluser vlume Hwever, e mass f maer wii e riz vlume f e uiverse a = is Mm ( ) = MCOMA Tis idicaes very clearly a e iercluser medium will disaear a = ad galaxy clusers will ierfere wi eac er Furermre, e radius f e Milky Way galaxy is r Mw = 50 Kc [6] Tus, V ( ) = VMW, were V MW is e Milky Way galaxy vlume Nevereless, i is fud a Mm ( ) = MMW Terefre, ly e iergalacic saces will vais a 6 =, bu als galaxies will cllide ad merge wi eac er frm exremely dese ad clse csmlgical bdies Tese very dese bdies will uderg furer successive cllisis ad mergers uder e aci f ceral graviy, were e iersellar medium will vais ad e uiverse wuld devel big cruc a bc = 565 Gyr I is als ieresig e frm Table a e riz disace f e uiverse a maximum exasi is d ( me ) = 869 Gc Tis riz disace is i very gd agreeme wi e maximum value f e uiverse riz disace i e bserved geeral csmic mdel A, d ( ) = 900 Gc, were = 4 Gyr (d) 99
10 F A Bukari Table Esimais f e riz disace, riz vlume, mass f radiai, mass f maer, mass f dark eergy ad e equivale umber f e Cma-like clusers e mass f maer wii e uiverse riz vlume i e clsed csmic mdel a secial imes d ( ) Gc V ( ) lg ( Mr M ) lg ( Mm M ) lg ( M M ) N ( ) COMA rm (55) yr u u m (0007) Gyr (7) Gyr me (685) Gyr u u u u u u 4 m (4089) Gyr (5646) Gyr u u u u were = Gyr, u = (Gc), u = (0 Gc), bc u = 0 ad 8 u = 0 4 Te value f d ( ) is als i ig agreeme wi e values f d ( ) mdels as sw frm Table i [7] 5 Cclusis me i e er fur geeral csmic I is aer we ave ivesigaed e disribuis f e uiverse riz disace ad e uiverse riz vlume i e clsed csmic mdel I is fud a e uiverse riz disace disribui icreases csaly fr < me ad decreases fr > me Hwever, e uiverse riz vlume disribui sws sudde reduci i e rage = 05 Gyr - me due e cage f e uiverse sace frm fla curved e clsed i e ierval 56 Gyr me O e er ad, is disribui exibis abru raise i e rage = me - * because f e cage f e uiverse sace frm clsed e curved fla i e ierval Gyr Disribuis f mass f radiai, maer ad dark eergy wii e riz vlume f e uiverse were als ivesigaed i e clsed csmic mdel Tese disribuis reveal similar iceable cages as e uiverse riz vlume disribui fr e same reass Te mass f radiai dmiaes u = 55 yr, e e mass f maer becmes larger Aferwards, b disribuis f radiai ad maer decrease wile e disribui f dark eergy rises uil = 0007 Gyr, were e mass f dark eergy revails u = me Hece, e disribui f dark eergy reduces uil = 4089 Gyr were e mass f maer becmes rmie agai A = 5646 Gyr e masses f b maer ad radiai becme areciably ig suc a e iercluser sace will vais ad clusers f galaxies will ierfere wi eac er Furermre, ly e iergalacic medium will disaear, bu als galaxies will cllide ad merge wi eac er frm exremely dese ad clse csmlgical bdies Tese very dese bdies will uderg furer successive cllisis ad mergers uder e aci f ceral graviy, were e iersellar medium will vais ad e uiverse wuld devel big cruc a = 565Gyr Refereces bc [] Bukari, FA (0) A Clsed Mdel f e Uiverse Ieraial Jural f Asrmy ad Asrysics,, ://dxdirg/046/ijaa00 [] Bukari, FA (0) Csmlgical Disaces i Clsed Mdel f e Uiverse Ieraial Jural f Asrmy ad Asrysics,, 99-0 ://dxdirg/046/ijaa00 [] Bukari, FA (0) Csmlgical Disaces i Five Geeral Csmic Mdels Ieraial Jural f Asrmy 00
11 F A Bukari ad Asrysics,, 8-88 ://dxdirg/046/ijaa00 [4] Bukari, FA (0) Five Geeral Csmic Mdels Jural f Kig Abdulaziz Uiversiy: Sciece, 5 [5] Ryde, B (00) Irduci Csmlgy Addis & Wesley, Bs [6] Sceider, P (00) Exragalacic Asrmy ad Csmlgy Sriger, New Yrk [7] Bukari, FA (05) Disribui f Mass ad Eergy i Five Geeral Csmic Mdels Ieraial Jural f Asrmy ad Asrysics, 5, 0-7 ://dxdirg/046/ijaa
Distribution of Mass and Energy in Five General Cosmic Models
Inerninl Jurnl f Asrnmy nd Asrpysics 05 5 0-7 Publised Online Mrc 05 in SciRes p://wwwscirprg/jurnl/ij p://dxdirg/0436/ij055004 Disribuin f Mss nd Energy in Five Generl Csmic Mdels Fdel A Bukri Deprmen
More informationThabet Abdeljawad 1. Çankaya Üniversitesi Fen-Edebiyat Fakültesi, Journal of Arts and Sciences Say : 9 / May s 2008
Çaaya Üiversiesi Fe-Edebiya Faülesi, Jural Ars ad Scieces Say : 9 / May s 008 A Ne e Cai Rule ime Scales abe Abdeljawad Absrac I is w, i eeral, a e cai rule eeral ime scale derivaives des beave well as
More informationSingle Platform Emitter Location
Sigle Plarm Emier Lcai AOADF FOA Ierermeery TOA SBI LBI Emier Lcai is Tw Esimai Prblems i Oe: Esimae Sigal Parameers a Deed Emier s Lcai: a Time--Arrival TOA Pulses b Pase Ierermeery: Pase is measured
More informationCosmological Distances in Closed Model of the Universe
Inerninl Jurnl f srnmy n srpysics 3 3 99-3 p://xirg/436/ij333 Publise Online June 3 (p://wwwscirprg/jurnl/ij) Csmlgicl Disnces in Clse el f e Universe Fel Bukri Deprmen f srnmy Fculy f Science King bulziz
More informationResearch & Reviews: Journal of Statistics and Mathematical Sciences
Research & Reviews: Jural f Saisics ad Mahemaical Scieces iuus Depedece f he Slui f A Schasic Differeial Equai Wih Nlcal diis El-Sayed AMA, Abd-El-Rahma RO, El-Gedy M Faculy f Sciece, Alexadria Uiversiy,
More informationNumerical Solution of Parabolic Volterra Integro-Differential Equations via Backward-Euler Scheme
America Joural of Compuaioal ad Applied Maemaics, (6): 77-8 DOI:.59/.acam.6. Numerical Soluio of Parabolic Volerra Iegro-Differeial Equaios via Bacward-Euler Sceme Ali Filiz Deparme of Maemaics, Ada Mederes
More informationMulti-objective Programming Approach for. Fuzzy Linear Programming Problems
Applied Mathematical Scieces Vl. 7 03. 37 8-87 HIKARI Ltd www.m-hikari.cm Multi-bective Prgrammig Apprach fr Fuzzy Liear Prgrammig Prblems P. Padia Departmet f Mathematics Schl f Advaced Scieces VIT Uiversity
More informationCalculus Limits. Limit of a function.. 1. One-Sided Limits...1. Infinite limits 2. Vertical Asymptotes...3. Calculating Limits Using the Limit Laws.
Limi of a fucio.. Oe-Sided..... Ifiie limis Verical Asympoes... Calculaig Usig he Limi Laws.5 The Squeeze Theorem.6 The Precise Defiiio of a Limi......7 Coiuiy.8 Iermediae Value Theorem..9 Refereces..
More informationBIBECHANA A Multidisciplinary Journal of Science, Technology and Mathematics
Biod Prasad Dhaal / BIBCHANA 9 (3 5-58 : BMHSS,.5 (Olie Publicaio: Nov., BIBCHANA A Mulidisciliary Joural of Sciece, Techology ad Mahemaics ISSN 9-76 (olie Joural homeage: h://ejol.ifo/idex.h/bibchana
More informationPrakash Chandra Rautaray 1, Ellipse 2
Prakash Chadra Rauara, Ellise / Ieraioal Joural of Egieerig Research ad Alicaios (IJERA) ISSN: 48-96 www.ijera.com Vol. 3, Issue, Jauar -Februar 3,.36-337 Degree Of Aroimaio Of Fucios B Modified Parial
More informationBig O Notation for Time Complexity of Algorithms
BRONX COMMUNITY COLLEGE of he Ciy Uiversiy of New York DEPARTMENT OF MATHEMATICS AND COMPUTER SCIENCE CSI 33 Secio E01 Hadou 1 Fall 2014 Sepember 3, 2014 Big O Noaio for Time Complexiy of Algorihms Time
More informationCalculus BC 2015 Scoring Guidelines
AP Calculus BC 5 Scorig Guidelies 5 The College Board. College Board, Advaced Placeme Program, AP, AP Ceral, ad he acor logo are regisered rademarks of he College Board. AP Ceral is he official olie home
More informationMATH 507a ASSIGNMENT 4 SOLUTIONS FALL 2018 Prof. Alexander. g (x) dx = g(b) g(0) = g(b),
MATH 57a ASSIGNMENT 4 SOLUTIONS FALL 28 Prof. Alexader (2.3.8)(a) Le g(x) = x/( + x) for x. The g (x) = /( + x) 2 is decreasig, so for a, b, g(a + b) g(a) = a+b a g (x) dx b so g(a + b) g(a) + g(b). Sice
More informationChapter 2: Time-Domain Representations of Linear Time-Invariant Systems. Chih-Wei Liu
Caper : Time-Domai Represeaios of Liear Time-Ivaria Sysems Ci-Wei Liu Oulie Iroucio Te Covoluio Sum Covoluio Sum Evaluaio Proceure Te Covoluio Iegral Covoluio Iegral Evaluaio Proceure Iercoecios of LTI
More informationApplication of Fixed Point Theorem of Convex-power Operators to Nonlinear Volterra Type Integral Equations
Ieraioal Mahemaical Forum, Vol 9, 4, o 9, 47-47 HIKRI Ld, wwwm-hikaricom h://dxdoiorg/988/imf4333 licaio of Fixed Poi Theorem of Covex-ower Oeraors o Noliear Volerra Tye Iegral Equaios Ya Chao-dog Huaiyi
More information1. Solve by the method of undetermined coefficients and by the method of variation of parameters. (4)
7 Differeial equaios Review Solve by he mehod of udeermied coefficies ad by he mehod of variaio of parameers (4) y y = si Soluio; we firs solve he homogeeous equaio (4) y y = 4 The correspodig characerisic
More informationEssential Microeconomics EXISTENCE OF EQUILIBRIUM Core ideas: continuity of excess demand functions, Fixed point theorems
Essetial Microecoomics -- 5.3 EXISTENCE OF EQUILIBRIUM Core ideas: cotiuity of excess demad fuctios, Fixed oit teorems Two commodity excage ecoomy 2 Excage ecoomy wit may commodities 5 Discotiuous demad
More informationChapter 6 - Work and Energy
Caper 6 - Work ad Eergy Rosedo Pysics 1-B Eploraory Aciviy Usig your book or e iere aswer e ollowig quesios: How is work doe? Deie work, joule, eergy, poeial ad kieic eergy. How does e work doe o a objec
More informationECE 340 Lecture 15 and 16: Diffusion of Carriers Class Outline:
ECE 340 Lecure 5 ad 6: iffusio of Carriers Class Oulie: iffusio rocesses iffusio ad rif of Carriers Thigs you should kow whe you leave Key Quesios Why do carriers diffuse? Wha haes whe we add a elecric
More informationThe Connection between the Basel Problem and a Special Integral
Applied Mahemaics 4 5 57-584 Published Olie Sepember 4 i SciRes hp://wwwscirporg/joural/am hp://ddoiorg/436/am45646 The Coecio bewee he Basel Problem ad a Special Iegral Haifeg Xu Jiuru Zhou School of
More informationOn The Eneström-Kakeya Theorem
Applied Mahemaics,, 3, 555-56 doi:436/am673 Published Olie December (hp://wwwscirporg/oural/am) O The Eesröm-Kakeya Theorem Absrac Gulsha Sigh, Wali Mohammad Shah Bharahiar Uiversiy, Coimbaore, Idia Deparme
More informationA L A BA M A L A W R E V IE W
A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N
More informationECE-314 Fall 2012 Review Questions
ECE-34 Fall 0 Review Quesios. A liear ime-ivaria sysem has he ipu-oupu characerisics show i he firs row of he diagram below. Deermie he oupu for he ipu show o he secod row of he diagram. Jusify your aswer.
More informationQuantum Mechanics for Scientists and Engineers. David Miller
Quatum Mechaics fr Scietists ad Egieers David Miller Time-depedet perturbati thery Time-depedet perturbati thery Time-depedet perturbati basics Time-depedet perturbati thery Fr time-depedet prblems csider
More informationDepartment of Mathematical and Statistical Sciences University of Alberta
MATH 4 (R) Wier 008 Iermediae Calculus I Soluios o Problem Se # Due: Friday Jauary 8, 008 Deparme of Mahemaical ad Saisical Scieces Uiversiy of Albera Quesio. [Sec.., #] Fid a formula for he geeral erm
More informationINVESTMENT PROJECT EFFICIENCY EVALUATION
368 Miljeko Crjac Domiika Crjac INVESTMENT PROJECT EFFICIENCY EVALUATION Miljeko Crjac Professor Faculy of Ecoomics Drsc Domiika Crjac Faculy of Elecrical Egieerig Osijek Summary Fiacial efficiecy of ivesme
More informationExercise 3 Stochastic Models of Manufacturing Systems 4T400, 6 May
Exercise 3 Sochasic Models of Maufacurig Sysems 4T4, 6 May. Each week a very popular loery i Adorra pris 4 ickes. Each ickes has wo 4-digi umbers o i, oe visible ad he oher covered. The umbers are radomly
More informationIntroduction to Astrophysics Tutorial 2: Polytropic Models
Itroductio to Astrophysics Tutorial : Polytropic Models Iair Arcavi 1 Summary of the Equatios of Stellar Structure We have arrived at a set of dieretial equatios which ca be used to describe the structure
More information8.0 Negative Bias Temperature Instability (NBTI)
EE650R: Reliability Physics f Naelectric Devices Lecture 8: Negative Bias Temerature Istability Date: Se 27 2006 Class Ntes: Vijay Rawat Reviewed by: Saakshi Gagwal 8.0 Negative Bias Temerature Istability
More informationThe universal vector. Open Access Journal of Mathematical and Theoretical Physics [ ] Introduction [ ] ( 1)
Ope Access Joural of Mahemaical ad Theoreical Physics Mii Review The uiversal vecor Ope Access Absrac This paper akes Asroheology mahemaics ad pus some of i i erms of liear algebra. All of physics ca be
More informationECE 570 Session 7 IC 752-E Computer Aided Engineering for Integrated Circuits. Transient analysis. Discuss time marching methods used in SPICE
ECE 570 Sessio 7 IC 75-E Compuer Aided Egieerig for Iegraed Circuis Trasie aalysis Discuss ime marcig meods used i SPICE. Time marcig meods. Explici ad implici iegraio meods 3. Implici meods used i circui
More informationAn interesting result about subset sums. Nitu Kitchloo. Lior Pachter. November 27, Abstract
A ieresig resul abou subse sums Niu Kichloo Lior Pacher November 27, 1993 Absrac We cosider he problem of deermiig he umber of subses B f1; 2; : : :; g such ha P b2b b k mod, where k is a residue class
More informationOutline. simplest HMM (1) simple HMMs? simplest HMM (2) Parameter estimation for discrete hidden Markov models
Oulie Parameer esimaio for discree idde Markov models Juko Murakami () ad Tomas Taylor (2). Vicoria Uiversiy of Welligo 2. Arizoa Sae Uiversiy Descripio of simple idde Markov models Maximum likeliood esimae
More informationNeutron Slowing Down Distances and Times in Hydrogenous Materials. Erin Boyd May 10, 2005
Neu Slwig Dw Disaces ad Times i Hydgeus Maeials i Byd May 0 005 Oulie Backgud / Lecue Maeial Neu Slwig Dw quai Flux behavi i hydgeus medium Femi eame f calculaig slwig dw disaces ad imes. Bief deivai f
More informationComputation of Hahn Moments for Large Size Images
Joural of Computer Sciece 6 (9): 37-4, ISSN 549-3636 Sciece Publicatios Computatio of Ha Momets for Large Size Images A. Vekataramaa ad P. Aat Raj Departmet of Electroics ad Commuicatio Egieerig, Quli
More informationExamination No. 3 - Tuesday, Nov. 15
NAME (lease rit) SOLUTIONS ECE 35 - DEVICE ELECTRONICS Fall Semester 005 Examiati N 3 - Tuesday, Nv 5 3 4 5 The time fr examiati is hr 5 mi Studets are allwed t use 3 sheets f tes Please shw yur wrk, artial
More informationDavid Randall. ( )e ikx. k = u x,t. u( x,t)e ikx dx L. x L /2. Recall that the proof of (1) and (2) involves use of the orthogonality condition.
! Revised April 21, 2010 1:27 P! 1 Fourier Series David Radall Assume ha u( x,) is real ad iegrable If he domai is periodic, wih period L, we ca express u( x,) exacly by a Fourier series expasio: ( ) =
More information10/ Statistical Machine Learning Homework #1 Solutions
Caregie Mello Uiversity Departet of Statistics & Data Sciece 0/36-70 Statistical Macie Learig Hoework # Solutios Proble [40 pts.] DUE: February, 08 Let X,..., X P were X i [0, ] ad P as desity p. Let p
More information1 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 information2 f(x) dx = 1, 0. 2f(x 1) dx d) 1 4t t6 t. t 2 dt i)
Mah PracTes Be sure o review Lab (ad all labs) There are los of good quesios o i a) Sae he Mea Value Theorem ad draw a graph ha illusraes b) Name a impora heorem where he Mea Value Theorem was used i he
More informationMoment Generating Function
1 Mome Geeraig Fucio m h mome m m m E[ ] x f ( x) dx m h ceral mome m m m E[( ) ] ( ) ( x ) f ( x) dx Mome Geeraig Fucio For a real, M () E[ e ] e k x k e p ( x ) discree x k e f ( x) dx coiuous Example
More informationA NOTE ON AN R- MODULE WITH APPROXIMATELY-PURE INTERSECTION PROPERTY
Joural of Al-ahrai Uiversity Vol.13 (3), September, 2010, pp.170-174 Sciece A OTE O A R- ODULE WIT APPROXIATELY-PURE ITERSECTIO PROPERTY Uhood S. Al-assai Departmet of Computer Sciece, College of Sciece,
More informationA Two-Level Quantum Analysis of ERP Data for Mock-Interrogation Trials. Michael Schillaci Jennifer Vendemia Robert Buzan Eric Green
A Two-Level Quaum Aalysis of ERP Daa for Mock-Ierrogaio Trials Michael Schillaci Jeifer Vedemia Rober Buza Eric Gree Oulie Experimeal Paradigm 4 Low Workload; Sigle Sessio; 39 8 High Workload; Muliple
More informationare specified , are linearly independent Otherwise, they are linearly dependent, and one is expressed by a linear combination of the others
Chater 3. Higher Order Liear ODEs Kreyszig by YHLee;4; 3-3. Hmgeeus Liear ODEs The stadard frm f the th rder liear ODE ( ) ( ) = : hmgeeus if r( ) = y y y y r Hmgeeus Liear ODE: Suersiti Pricile, Geeral
More information12 th Mathematics Objective Test Solutions
Maemaics Objecive Tes Soluios Differeiaio & H.O.D A oes idividual is saisfied wi imself as muc as oer are saisfied wi im. Name: Roll. No. Bac [Moda/Tuesda] Maimum Time: 90 Miues [Eac rig aswer carries
More informationProcedia - Social and Behavioral Sciences 230 ( 2016 ) Joint Probability Distribution and the Minimum of a Set of Normalized Random Variables
Available olie a wwwsciecedireccom ScieceDirec Procedia - Social ad Behavioral Scieces 30 ( 016 ) 35 39 3 rd Ieraioal Coferece o New Challeges i Maageme ad Orgaizaio: Orgaizaio ad Leadership, May 016,
More informationHº = -690 kj/mol for ionization of n-propylene Hº = -757 kj/mol for ionization of isopropylene
Prblem 56. (a) (b) re egative º values are a idicati f mre stable secies. The º is mst egative fr the i-ryl ad -butyl is, bth f which ctai a alkyl substituet bded t the iized carb. Thus it aears that catis
More informationLinear System Theory
Naioal Tsig Hua Uiversiy Dearme of Power Mechaical Egieerig Mid-Term Eamiaio 3 November 11.5 Hours Liear Sysem Theory (Secio B o Secio E) [11PME 51] This aer coais eigh quesios You may aswer he quesios
More informationChapter 3.1: Polynomial Functions
Ntes 3.1: Ply Fucs Chapter 3.1: Plymial Fuctis I Algebra I ad Algebra II, yu ecutered sme very famus plymial fuctis. I this secti, yu will meet may ther members f the plymial family, what sets them apart
More informationSUMMATION OF INFINITE SERIES REVISITED
SUMMATION OF INFINITE SERIES REVISITED I several aricles over he las decade o his web page we have show how o sum cerai iiie series icludig he geomeric series. We wa here o eed his discussio o he geeral
More informationSolutions. Definitions pertaining to solutions
Slutis Defiitis pertaiig t slutis Slute is the substace that is disslved. It is usually preset i the smaller amut. Slvet is the substace that des the disslvig. It is usually preset i the larger amut. Slubility
More informationExtremal 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 informationOn two general nonlocal differential equations problems of fractional orders
Malaya Journal of Maemaik, Vol. 6, No. 3, 478-482, 28 ps://doi.org/.26637/mjm63/3 On wo general nonlocal differenial equaions problems of fracional orders Abd El-Salam S. A. * and Gaafar F. M.2 Absrac
More informationSome inequalities for q-polygamma function and ζ q -Riemann zeta functions
Aales Mahemaicae e Iformaicae 37 (1). 95 1 h://ami.ekf.hu Some iequaliies for q-olygamma fucio ad ζ q -Riema zea fucios Valmir Krasiqi a, Toufik Masour b Armed Sh. Shabai a a Dearme of Mahemaics, Uiversiy
More informationB. Maddah INDE 504 Simulation 09/02/17
B. Maddah INDE 54 Simulaio 9/2/7 Queueig Primer Wha is a queueig sysem? A queueig sysem cosiss of servers (resources) ha provide service o cusomers (eiies). A Cusomer requesig service will sar service
More informationSTK4080/9080 Survival and event history analysis
STK48/98 Survival ad eve hisory aalysis Marigales i discree ime Cosider a sochasic process The process M is a marigale if Lecure 3: Marigales ad oher sochasic processes i discree ime (recap) where (formally
More informationModern Physics. Unit 15: Nuclear Structure and Decay Lecture 15.2: The Strong Force. Ron Reifenberger Professor of Physics Purdue University
Mder Physics Uit 15: Nuclear Structure ad Decay Lecture 15.: The Strg Frce R Reifeberger Prfessr f Physics Purdue Uiversity 1 Bidig eergy er ucle - the deuter Eergy (MeV) ~0.4fm B.E. A =.MeV/ = 1.1 MeV/ucle.
More informationDynamic h-index: the Hirsch index in function of time
Dyamic h-idex: he Hirsch idex i fucio of ime by L. Egghe Uiversiei Hassel (UHassel), Campus Diepebeek, Agoralaa, B-3590 Diepebeek, Belgium ad Uiversiei Awerpe (UA), Campus Drie Eike, Uiversieisplei, B-260
More informationExtended Laguerre Polynomials
I J Coemp Mah Scieces, Vol 7, 1, o, 189 194 Exeded Laguerre Polyomials Ada Kha Naioal College of Busiess Admiisraio ad Ecoomics Gulberg-III, Lahore, Pakisa adakhaariq@gmailcom G M Habibullah Naioal College
More informationUsing Linnik's Identity to Approximate the Prime Counting Function with the Logarithmic Integral
Usig Lii's Ideiy o Approimae he Prime Couig Fucio wih he Logarihmic Iegral Naha McKezie /26/2 aha@icecreambreafas.com Summary:This paper will show ha summig Lii's ideiy from 2 o ad arragig erms i a cerai
More informationMinimax Regret Treatment Choice with Incomplete Data and Many Treatments
Mii Regre Treame Chice wih Icmplee Daa ad May Treames Jörg Sye New Yrk Uiversiy Jauary 27, 2006 Absrac This e adds he rece research prjec reame chice uder ambiguiy. I geeralize Maski s i press aalysis
More informationLONGITUDINAL VIBRATIONS OF THE SUGAR BEET ROOT CROP BODY AT VIBRATIONAL EXTRACTION FROM SOIL
TEKA Km. M. Eerg. Rl., 005, 5, 5 5 LONGITDINAL VIBRATION OF THE GAR BEET ROOT CROP BODY AT VIBRATIONAL EXTRACTION FROM OIL Vldmr Bulgakv, Jausz Nwak, Wjciec Przsupa Naial Agraria iversi, kraie Agriculural
More informationThe Eigen Function of Linear Systems
1/25/211 The Eige Fucio of Liear Sysems.doc 1/7 The Eige Fucio of Liear Sysems Recall ha ha we ca express (expad) a ime-limied sigal wih a weighed summaio of basis fucios: v ( ) a ψ ( ) = where v ( ) =
More informationANSWER KEY WITH SOLUTION PAPER - 2 MATHEMATICS SECTION A 1. B 2. B 3. D 4. C 5. B 6. C 7. C 8. B 9. B 10. D 11. C 12. C 13. A 14. B 15.
TARGET IIT-JEE t [ACCELERATION] V0 to V BATCH ADVANCED TEST DATE : - 09-06 ANSWER KEY WITH SOLUTION PAPER - MATHEMATICS SECTION A. B. B. D. C 5. B 6. C 7. C 8. B 9. B 0. D. C. C. A. B 5. C 6. D 7. A 8.
More informationBounds for the Positive nth-root of Positive Integers
Pure Mathematical Scieces, Vol. 6, 07, o., 47-59 HIKARI Ltd, www.m-hikari.com https://doi.org/0.988/pms.07.7 Bouds for the Positive th-root of Positive Itegers Rachid Marsli Mathematics ad Statistics Departmet
More informationStudy of Energy Eigenvalues of Three Dimensional. Quantum Wires with Variable Cross Section
Adv. Studies Ther. Phys. Vl. 3 009. 5 3-0 Study f Eergy Eigevalues f Three Dimesial Quatum Wires with Variale Crss Secti M.. Sltai Erde Msa Departmet f physics Islamic Aad Uiversity Share-ey rach Ira alrevahidi@yah.cm
More informationENGI 4421 Central Limit Theorem Page Central Limit Theorem [Navidi, section 4.11; Devore sections ]
ENGI 441 Cetral Limit Therem Page 11-01 Cetral Limit Therem [Navidi, secti 4.11; Devre sectis 5.3-5.4] If X i is t rmally distributed, but E X i, V X i ad is large (apprximately 30 r mre), the, t a gd
More informationTheoretical and Experimental Study of the Rheological Behaviour of Non-Newtonian Fluids Using Falling Cylinder Rheometer
Thereical ad Experieal Sudy f he helgical Behaviur f N-Newia Fluids Usig Fallig Cylider heeer S.Gh. Eead,. Bagheri ad S.Zeiali. Heris Cheical Egieerig Depare Isfaha Uiversiy f Techlgy 8454 Isfaha, Ira
More informationLIMITS MULTIPLE CHOICE QUESTIONS. (a) 1 (b) 0 (c) 1 (d) does not exist. (a) 0 (b) 1/4 (c) 1/2 (d) 1/8. (a) 1 (b) e (c) 0 (d) none of these
DSHA CLASSES Guidig you to Success LMTS MULTPLE CHOCE QUESTONS.... 5. Te value of + LEVEL (Objective Questios) (a) e (b) e (c) e 5 (d) e 5 (a) (b) (c) (d) does ot et (a) (b) / (c) / (d) /8 (a) (b) (c)
More information12 Getting Started With Fourier Analysis
Commuicaios Egieerig MSc - Prelimiary Readig Geig Sared Wih Fourier Aalysis Fourier aalysis is cocered wih he represeaio of sigals i erms of he sums of sie, cosie or complex oscillaio waveforms. We ll
More informationA note on deviation inequalities on {0, 1} n. by Julio Bernués*
A oe o deviaio iequaliies o {0, 1}. by Julio Berués* Deparameo de Maemáicas. Faculad de Ciecias Uiversidad de Zaragoza 50009-Zaragoza (Spai) I. Iroducio. Le f: (Ω, Σ, ) IR be a radom variable. Roughly
More informationDANIELL AND RIEMANN INTEGRABILITY
DANIELL AND RIEMANN INTEGRABILITY ILEANA BUCUR We itroduce the otio of Riema itegrable fuctio with respect to a Daiell itegral ad prove the approximatio theorem of such fuctios by a mootoe sequece of Jorda
More informationK3 p K2 p Kp 0 p 2 p 3 p
Mah 80-00 Mo Ar 0 Chaer 9 Fourier Series ad alicaios o differeial equaios (ad arial differeial equaios) 9.-9. Fourier series defiiio ad covergece. The idea of Fourier series is relaed o he liear algebra
More informationA Generalized Cost Malmquist Index to the Productivities of Units with Negative Data in DEA
Proceedigs of he 202 Ieraioal Coferece o Idusrial Egieerig ad Operaios Maageme Isabul, urey, July 3 6, 202 A eeralized Cos Malmquis Ide o he Produciviies of Uis wih Negaive Daa i DEA Shabam Razavya Deparme
More informationMathematical Statistics. 1 Introduction to the materials to be covered in this course
Mahemaical Saisics Iroducio o he maerials o be covered i his course. Uivariae & Mulivariae r.v s 2. Borl-Caelli Lemma Large Deviaios. e.g. X,, X are iid r.v s, P ( X + + X where I(A) is a umber depedig
More informationA New Method for Finding an Optimal Solution. of Fully Interval Integer Transportation Problems
Applied Matheatical Scieces, Vl. 4, 200,. 37, 89-830 A New Methd fr Fidig a Optial Sluti f Fully Iterval Iteger Trasprtati Prbles P. Padia ad G. Nataraja Departet f Matheatics, Schl f Advaced Scieces,
More information3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,
3. Z Trasform Referece: Etire Chapter 3 of text. Recall that the Fourier trasform (FT) of a DT sigal x [ ] is ω ( ) [ ] X e = j jω k = xe I order for the FT to exist i the fiite magitude sese, S = x [
More informationFurther Methods for Advanced Mathematics (FP2) WEDNESDAY 9 JANUARY 2008
ADVANCED GCE 7/ MATHEMATICS (MEI) Furter Metods for Advaced Matematics (F) WEDNESDAY 9 JANUARY 8 Additioal materials: Aswer Booklet (8 pages) Grap paper MEI Eamiatio Formulae ad Tables (MF) Afteroo Time:
More informationF D D D D F. smoothed value of the data including Y t the most recent data.
Module 2 Forecasig 1. Wha is forecasig? Forecasig is defied as esimaig he fuure value ha a parameer will ake. Mos scieific forecasig mehods forecas he fuure value usig pas daa. I Operaios Maageme forecasig
More informationSampling Example. ( ) δ ( f 1) (1/2)cos(12πt), T 0 = 1
Samplig Example Le x = cos( 4π)cos( π). The fudameal frequecy of cos 4π fudameal frequecy of cos π is Hz. The ( f ) = ( / ) δ ( f 7) + δ ( f + 7) / δ ( f ) + δ ( f + ). ( f ) = ( / 4) δ ( f 8) + δ ( f
More informationAdditional Exercises for Chapter What is the slope-intercept form of the equation of the line given by 3x + 5y + 2 = 0?
ddiional Eercises for Caper 5 bou Lines, Slopes, and Tangen Lines 39. Find an equaion for e line roug e wo poins (, 7) and (5, ). 4. Wa is e slope-inercep form of e equaion of e line given by 3 + 5y +
More informationFermat Numbers in Multinomial Coefficients
1 3 47 6 3 11 Joural of Ieger Sequeces, Vol. 17 (014, Aricle 14.3. Ferma Numbers i Muliomial Coefficies Shae Cher Deparme of Mahemaics Zhejiag Uiversiy Hagzhou, 31007 Chia chexiaohag9@gmail.com Absrac
More informationTurbulent entry length. 7.3 Turbulent pipe flow. Turbulent entry length. Illustrative experiment. The Reynolds analogy and heat transfer
Turulet etry legt 7.3 Turulet ie l Etry legts x e ad x et are geerally srter turulet l ta lamar l Termal etry legts, x et /, r a case it q cst imsed a ydrdyamically ully develed l 7.3 Turulet ie l ill
More informationPHYSICS 116A Homework 2 Solutions
PHYSICS 6A Homework 2 Solutios I. [optioal] Boas, Ch., 6, Qu. 30 (proof of the ratio test). Just follow the hits. If ρ, the ratio of succcessive terms for is less tha, the hits show that the terms of the
More informationALLOCATING SAMPLE TO STRATA PROPORTIONAL TO AGGREGATE MEASURE OF SIZE WITH BOTH UPPER AND LOWER BOUNDS ON THE NUMBER OF UNITS IN EACH STRATUM
ALLOCATING SAPLE TO STRATA PROPORTIONAL TO AGGREGATE EASURE OF SIZE WIT BOT UPPER AND LOWER BOUNDS ON TE NUBER OF UNITS IN EAC STRATU Lawrece R. Erst ad Cristoper J. Guciardo Erst_L@bls.gov, Guciardo_C@bls.gov
More information[1 & α(t & T 1. ' ρ 1
NAME 89.304 - IGNEOUS & METAMORPHIC PETROLOGY DENSITY & VISCOSITY OF MAGMAS I. Desity The desity (mass/vlume) f a magma is a imprtat parameter which plays a rle i a umber f aspects f magma behavir ad evluti.
More information8.3 Perturbation theory
8.3 Perturbatio theory Slides: Video 8.3.1 Costructig erturbatio theory Text referece: Quatu Mechaics for Scietists ad gieers Sectio 6.3 (u to First order erturbatio theory ) Perturbatio theory Costructig
More informationPipe Networks - Hardy Cross Method Page 1. Pipe Networks
Pie Netwrks - Hardy Crss etd Page Pie Netwrks Itrducti A ie etwrk is a itercected set f ies likig e r mre surces t e r mre demad (delivery) its, ad ca ivlve ay umber f ies i series, bracig ies, ad arallel
More informationDEGENERACY AND ALL THAT
DEGENERACY AND ALL THAT Te Nature of Termodyamics, Statistical Mecaics ad Classical Mecaics Termodyamics Te study of te equilibrium bulk properties of matter witi te cotext of four laws or facts of experiece
More informationx 2 x 3 x b 0, then a, b, c log x 1 log z log x log y 1 logb log a dy 4. dx As tangent is perpendicular to the x axis, slope
The agle betwee the tagets draw t the parabla y = frm the pit (-,) 5 9 6 Here give pit lies the directri, hece the agle betwee the tagets frm that pit right agle Ratig :EASY The umber f values f c such
More informationAn S-type upper bound for the largest singular value of nonnegative rectangular tensors
Ope Mat. 06 4 95 933 Ope Matematics Ope Access Researc Article Jiaxig Za* ad Caili Sag A S-type upper bud r te largest sigular value egative rectagular tesrs DOI 0.55/mat-06-0085 Received August 3, 06
More informationALE 26. Equilibria for Cell Reactions. What happens to the cell potential as the reaction proceeds over time?
Name Chem 163 Secti: Team Number: AL 26. quilibria fr Cell Reactis (Referece: 21.4 Silberberg 5 th editi) What happes t the ptetial as the reacti prceeds ver time? The Mdel: Basis fr the Nerst quati Previusly,
More informationThe analysis of the method on the one variable function s limit Ke Wu
Ieraioal Coferece o Advaces i Mechaical Egieerig ad Idusrial Iformaics (AMEII 5) The aalysis of he mehod o he oe variable fucio s i Ke Wu Deparme of Mahemaics ad Saisics Zaozhuag Uiversiy Zaozhuag 776
More informationIJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 2 Issue 12, December
IJISET - Iteratial Jural f Ivative Sciece, Egieerig & Techlgy, Vl Issue, December 5 wwwijisetcm ISSN 48 7968 Psirmal ad * Pararmal mpsiti Operatrs the Fc Space Abstract Dr N Sivamai Departmet f athematics,
More informationAtomic Physics 4. Name: Date: 1. The de Broglie wavelength associated with a car moving with a speed of 20 m s 1 is of the order of. A m.
Name: Date: Atomic Pysics 4 1. Te de Broglie wavelegt associated wit a car movig wit a speed of 0 m s 1 is of te order of A. 10 38 m. B. 10 4 m. C. 10 4 m. D. 10 38 m.. Te diagram below sows tree eergy
More informationANALYSIS OF THE CHAOS DYNAMICS IN (X n,x n+1) PLANE
ANALYSIS OF THE CHAOS DYNAMICS IN (X,X ) PLANE Soegiao Soelisioo, The Houw Liog Badug Isiue of Techolog (ITB) Idoesia soegiao@sude.fi.ib.ac.id Absrac I he las decade, sudies of chaoic ssem are more ofe
More informationThe Metric and The Dynamics
The Metric and The Dynamics r τ c t a () t + r + Sin φ ( kr ) The RW metric tell us where in a 3 dimension space is an event and at which proper time. The coordinates of the event do not change as a function
More informationd y f f dy Numerical Solution of Ordinary Differential Equations Consider the 1 st order ordinary differential equation (ODE) . dx
umerical Solutio o Ordiar Dieretial Equatios Cosider te st order ordiar dieretial equatio ODE d. d Te iitial coditio ca be tae as. Te we could use a Talor series about ad obtai te complete solutio or......!!!
More informationFresnel Dragging Explained
Fresel Draggig Explaied 07/05/008 Decla Traill Decla@espace.e.au The Fresel Draggig Coefficie required o explai he resul of he Fizeau experime ca be easily explaied by usig he priciples of Eergy Field
More informationLIMITS AND DERIVATIVES
Capter LIMITS AND DERIVATIVES. Overview.. Limits of a fuctio Let f be a fuctio defied i a domai wic we take to be a iterval, say, I. We sall study te cocept of it of f at a poit a i I. We say f ( ) is
More information