Derivation of an Analytic Expression for the Mass of an Individual Fish Larvae in an Uncapped Rate Stochastic Situation.
|
|
- Evangeline Mason
- 6 years ago
- Views:
Transcription
1 New Yrk Science Jurnal 01;5(1) hp:// Derivain f an Analyic Exprein fr he Ma f an Individual Fih Larvae in an Uncapped Rae Schaic Siuain. 1 ADEWOLE Olukrede.O and ALLI Sulaimn.G 1 Deparmen f Phyic, Univeriy f Ibadan, Nigeria. Deparmen f Mahemaic & Saiic, The Plyechnic, Ibadan, Nigeria. Crrepndence viz; kredeadewle@yah.cm ABSTRACT: There i need vividly examine he impac f chaic variain in divere prcee a may apply a ypical grwh mdel. A capped rae chaic prce culd be decribed a bunded by me limi and hrugh delineain f he variu facr affecing he grwh f fih larvae i highly eenial. The change in ma f fih larvae wa cnidered due phyilgical and meablic pahway and her relevan facr vividly examine he cncep f chaic prce a applicable he capped rae mdel, and delineae an analyically derived exprein fr he ma f an individual larvae baed n relevan chaic differenial frmulain in an uncapped rae chaic prce inundaing he I lemma. The uncapped rae iuain i nly a remval f a maximum r imped limi frm a capped rae chaic prce. [ADEWOLE Olukrede.O and ALLI Sulaimn.G. Derivain f an Analyic Exprein fr he Ma f an Individual Fih Larvae in an Uncapped Rae Schaic Siuain. N Y Sci J 01;5(1):86-91]. (ISSN: ). hp:// 13 Keywrd: Schaic prce, uncapped rae, I lemma. 1.0 INTRODUCTION Va number f mahemaical funcin are knwn ake divere frm and f variu uiabiliy a number f daily life applicain, ranging frm bilgical, chemical phyical prcee. A number f prcee defined by me relevan mahemaical funcin and equain can be mdeled. A funcin can be defined uch ha i value d n exceed me capped r maximum imped value. Inereingly, deerminiic and chaic prcee are w well encunered cae, invariably, capped rae prce n pracical grund huld incrprae me chaic variain parameer. The fih recruimen larvae have been cnidered in hi cae. An individual larva find ielf in a precariu iuain, larvae exi in a highly chaic and pachy envirnmen and pe nly limied lcmry and enry abiliy. Larva are mall relaive he paial cale f prey heergeneiy and he urbulen fluid flw a hee paial cale (Pichfrd and Brindley, 001). They al have nly lcal knwledge f heir immediae envirnmen, limied by a viual percepive diance f arund ne bdy lengh (Pichfrd e al, 003), and hey are ubjec maive mraliy, wih a newly hached individual prbabiliy f urvival meamrphi being O(1%) r le (Chamber and Trippel, 1997) driven by ypical mraliy f 10% per day in he larva age (Cuhing and Hrwd,1994). There are phyilgical limi n hw fa an individual can grw, imped by facr uch a gu ize and meablim. A iny minriy f larvae even under favurable cndiin urvive adulhd, hu average larva i m definiely dead pracically. M = min [prey encunered x cnverin efficiency meablic c maximum grwh rae] = min [f 1 (M) Z(M) f (M); g(m)] 1.0 where M repreen he ma f an individual, Z(M) i he rae a which prey i encunered and digeed (dependen n lcal prey cncenrain), f 1 (M) decribe he efficiency f cnvering prey in ma, f (M) repreen meablic c and g(m) i he maximal rae a which individual can grw. Grwh rae deermine he durain f he perid during which larvae are vulnerable gape-limied predar (Fgary e al, 1991). Equain (1.0) abve cnciely decribe a general mdel fr an individual change in ma, M during ime inerval,. Schaic and deerminiic prcee are frequenly encunered in va number f daily applicain including phyical, chemical and bilgical ec. Preciely, he grwh f fih larvae i he ubjec f hi dicuin. The cncep f chaic even r prce cann be aken wih leviy a i pan acr m apec f life and applicain. Variu frm f variain are encunered in ne r mre prcee, indeed in cience, finance menin a few, we cann bu menin chaic prce. A capped rae prce hugh ha a maximum r limi imped bu pracically, here are me flucuain ha wrh being cnidered. 86
2 New Yrk Science Jurnal 01;5(1) hp:// In real ene, flucuain r variain exi, which ake differen frm, uually randm appearing a nie. Fr inance, grwh f an individual i influenced by inernal and exernal facr. Inernal facr are baically, phyilgical and meablic pahway. The exernal facr wuld include facr like prey, predar, which are bilgical and phyical facr like emperaure, humidiy, ph, aliniy, ligh ineniy ec. In a grwh mdel, an individual i expeced grw cninuuly, realiically peaking, here i a limi r maximum grwh limi. If he change in ma i cnidered wih ime, iniially he grwh rae depend n he phyilgical and meablic pahway uch a rae f cnverin f fd ma and amun f fd cnverin uilized. Hwever, here i a maximum r capped grwh limi he individual can aain. An ideal l fr hi wrk i he Cuhing-Hrwd mdel f larval fih grwh (Cuhing & Hrwd, 1994). Accrding he grwh/mraliy hyphei (Cuhing and Hrwd, 1994; Rice e al, 1993), larvae which grw quickly hrugh a mraliy windw have a urvival advanage ver he ha d n (Campana, 1996). Fcung n he fih larvae recruimen in hi udy, he capped rae chaic prce ha been cnidered and he ma change cnidered in cnnance wih phyilgical facr, meablic c and ime wih her relevan facr. Even when a prce i capped, here i expedien need incrprae me chaiciy hereby unveiling a chaic paern..0 Mehdlgy The I inerpreain ha been applied in delineaing he capped rae prce in fih larvae recruimen wih cniderain f me chaic variable deermining he change in ma f an individual fih larvae. The mdel applied in hi wrk i he Cuhing-Hrwd mdel (1994) wih numerical reamen. The change in ma f he individual by hi mdel i given by: M = min [(b(m) Z(M) C(M) x G(M)]. An analyic exprein fr he ma f an individual larvae ha been derived. 3.0 Dicuin Many mahemaical mdel which aemp decribe hi prce ue cninuu apprximain pecifically, an rdinary differenial equain (ODE) i derived. There i an exigen need incrprae chaically in he ODE when uncerainy play a ignifican rle in he prce, fr example when prey are diribued pachly r he predar ha a high mraliy rik. Hwever, he chaic generalizain fen rely n infinieimally mall ime ep, n applicable bilgical yem. N including he unpredicable envirnmen nie in fiherie mdel can lead (and ha lead) errneu predicin f behavir f explied ck, and may have cnribued he deerirain f hee ck (Keyl and Wlff, 008). Deerminiic mdel f recruimen can prvide impran inigh in fih ppulain dynamic in he face f expliain (Fgary, 1993). Hwever, becaue he key naural phenmena are inherenly chaic, deerminiic mdel can be argued be inapprpriae fr qualifying recruimen. Raher, chaic mdel huld be cnruced arrive a recruimen prbabiliy (Pichfrd and Brindley, 001) and inveigae recruimen variabiliy (Frgary, 1991, 1993). There are phyilgical limi n hw fa an individual can grw, imped by facr uch a gu ize and meablim, a much a 99.9% f larvae die befre reaching meamrphi (Campana, 1996), and rapid grwh hrugh he larva age i hugh increae urvival prbabiliie due an increaed abiliy frage fr prey and avid predar (Cuhing and Hrwd, 1994). Tw naïve apprache chaic prce cmprie, he andard Weiner prce and Pin prce. Where M() i defined a a diffuin prce wih cnan drif; dm() = d + dw()..0.0 W() i a andard Weiner prce (Grimme and Sirzaker, 001). Wih inananeu mean zer, Anher apprach; dm() = dn () Ue a Pin nie prce (Feller, 1950). A in equain.0, M() al ha expecain in equain.0.1. Thee w chaic prce culd be applied in principle generalize equain (1.0) excep where capped rae mdel are cncerned, which culd generae n leading reul (Jame e al, 005). A a reul f he chaic prce incrpraed, a chaic differenial equain ha a luin, which ielf i a chaic prce. An earlier wrk relaed Brwnian min wa credied Bachelier, 1900 in Thery f peculain and laer fllwed up by Langevin I and Sranvich. 3.1 Furher Dicuin Cnidering he uncapped deerminiic cae dm =( (f 1 (M) z(m) f (M))d...0. If z(m) i n lnger deerminiic, he infinieimal rae z(m) wuld be replaced by z(m)d + z (M)dW() where z(m) i an average value and z (M) meaure he ineniy f he chaic perurbain by a Weiner prce. Hence he SDE bained i; dm = f 1 (M) z(m) d + z (M) dw() f (M)d
3 New Yrk Science Jurnal 01;5(1) hp:// Equain.0.3 can be lved analyically r numerically depending n he frm f he variu funcin. Schaic differenial equain are ued exenively fr inance in Phyic a Langevin equain, prbabiliy hery and financial mahemaic, numerical luin ec. A ypical chaic differenial equain i f he frm d = (, ) d + (,)db where B dene a Weiner prce (andard Brwnian min). Fr funcin fεn, he I inegral i F[f](ω)= T f(,ω)db (ω)..0.6 S In inegral frm, he equain i; + = (, u) du ( u, u) dbu..0.5 Fr funcin fεn, he I inegral i F[f](ω)= T f(,ω)db (ω)..0.6 S where B i 1-dimeninal Brwnian min. The Sranvich inegral, i an alernaive he I inegral. Unlike he I calculu, he chain rule f rdinary calculu applie Sranvich chaic inergral and he w can be cnvered viz he her fr cnvenience a demanded. A cmparin f I and Sranvich inegral culd be dne. The whie nie equain; dx b(, ) (, ) W d ha he luin given a: b(, x) d (, ) db.0.8 Adping he Sranvich equain a m apprpriae in me cae, fr -cninuuly differeniable prcee B (n) uch ha: B (n) (,ω) B(,ω) a n. Unifrmly (in ) in bunded inerval. Fr (n) each ω, le, (ω) be he luin f he crrepnding deerminiic differenial equain. ( n) dx db b(, ) (, ) d d (n) (ω) cnverge me funcin (ω) and (n) (ω) (ω) a n, unifrmly (in ) in bunded inerval. The luin here, i.e. f he Sranvich SDE = + b (, ) d (, ) db..10 Cincide wih he luin f he equain given by:.0.8. Thu, he luin f he mdified I equain i; = + 1 b (, ) d (, ) (, ) d (, ) db..11 where dene he derivaive f (, x) wih repec (Sranvich, 1966). Thu, he Sranvich inerpreain given by.11 huld be mre reanably adped cmpared he I inerpreain; = + b (, ) d (, ) db.1 which i he reul f he whie nie equain,.0.7. Cnverin beween he I and Sranvich inegral may be perfrmed uing he frmula; T 1 T T 1 ( ) dw ( ) d ( ) dw..1(b) Where i me prce, i a cninuuly differeniable funcin wih derivaive, 1 and he la i an I inegral. W() i ued in deriving a chaic differenial equain. The change in an a f he fih larva i cnidered in he curren udy. Each individual larva hache wih ma, M and grw accrding he equain; M = min ((f 1 (M) z(m) f (M); G(M)).13 Where f 1 (M) i he larva efficiency, a cnvering fd in bima, f (M) i he meablic c. Equain.13 i n lnger an ODE and becme a chaic differenial equain, SDE when he prey cnac rae Z i defined a a randm variable repreening a heergeneu fd upply. Wih he defining funcin f he rae f change i n mh in he minimum funcin f equain.13, Z fllw a Gauian diribuin. SDE are lved analyically and cmpuainally r numerically. The curren udy adped he numerical mehd f luin bain reul n he change in ma, M f fih larva recruimen fr w cae; capped rae and uncapped rae chaic prcee. The uncapped deerminiic cae i; dm = (f 1 (M) z(m) f (M))d..14 If Z i n lnger deerminiic; he infinieimal rae z(m) d huld be replaced by z(m) d + (M)dW () where z(m) i an average value and z (M) meaure he ineniy f he chaic perurbain; aumed be given by a Weiner prce. The SDE hu becme; dm = f 1 (M) z(m) d + (M)dW() f (M) d.14(b). Thi frm f he SDE can be lve analyical r numerically depending n he frm f he funcin. 88
4 New Yrk Science Jurnal 01;5(1) hp:// The ime mauriy in hi cae ha been exenively udied and me analyical luin have been fund, (Tarlin and Taylr, 1981, Grimme and Sirzaker, 001). The deerminiic capped rae cae i; dm = min( (f 1 (M) z(m) f (M), g(m))d..15 quie differen frm he uncapped chaic cae. Equain,.0.5 characeriic he behaviur f he cninuu ime chaic prce a he um f an rdinary Lebeque inegral and an I inegral. A plauible bu very helpful inerpreain f he chaic differenial equain i ha in a mall ime inerval f lengh d, he chaic prce change i value by an amun ha i nrmally diribued wih expecain (, ) and variance (,).The incremen f he Weiner prce are independen and nrmally diribued, hu hi i independen f he pa behaviur f he prce. The funcin i referred a he drif cefficien, i called he diffuin cefficien and he chaic prce i called he diffuin prce. 3. Significance f he udy A ypical ecnmic cenari i dynamic fen characerized by a number f variable. Sme f he variable are predicable a cniderable exen while her are nn-predicable fen characerized by chaic variain. The cncep f mahemaical mdeling kep n gaining grund in recen ime. A ypical mdel invlve cerain reanable aumpin and cniderain f variable ha culd be rarely aic bu uually dynamic ver a ime pace. The cncep f mdelling ha gained prminence in cienific ue and nw becme f exigen need in m her recen daily applicain, even ck exchange. Mahemaical funcin and aiical prbabiliy diribuin funcin are fen vial l in delineaing he cncep f capped-rae mdel in addiin her mdelling applicain. The idea i impe a maximum value n a mahemaical funcin ha purpr explain he eenial behaviur f he iuain in perue. Delineaing he uncapped rae chaic prce baed and frmulain f a mdel fr he ma f an individual fih larva cnidering he Wiener frmulain viz a chaic differenial equain becme exigen in explring he bilgical iuain. 4.0 POPULATION GROWTH MODEL The ppulain grwh mdel i dn = α N ; N given....1 d Where α = r +.W ; W whie nie, cnan. Auming r = r = cnan. By he I inerrelain, (,x) = x viz; = + b (, ) d (, ) d. Fr he chaic differenial equain; d = b (, ) + (, ); b (, x), x ϵ R, (, x) ϵ R. d.b where W i 1-dimeninal whie nie dn = rn d + db implie, dn N r B ( B 0)..3 uing he I frmula fr he equain g(,x) = lnx; x>.4 d(lnn ) = we have; 1. dn + 1 / N dn = 1 d N Hence; dn 1 d (ln N ) d N 1 N dn And hu; ln N 1 r B N r N = N exp 1 r B.7...8(b) Hwever, he ranvich inerpreain give; dn rn d N 0 db.9 Wih he luin; N = N exp (r + B )..30 The mehd f luin culd be analyical r numerical depending n he frm f he variu funcin and luin, where; M = min [f 1 (M) z(m) f (M)g (M)].31 i.e. M = min (prey cunered x cnverin efficiency meablic c x grwh rae) Remving he grwh rae, i.e. he uncapped rae chaic iuain; dm = f 1 (M) z(m)d f (M)d If z(m) i chaic hen; dm = f 1 (M) z(m) d + z (M) dw() f (M) d...3 where z(m) in.3 i an average value. z (M) meaure he ineniy f he chaic perurbain driven by Weiner prce. Frm.3; dm = f 1 (M) z(m)d + z (M)(M)dW() f (M)d.3b 89
5 New Yrk Science Jurnal 01;5(1) hp:// T lve i analyically, le W = 0; M(0) = M dm = [f 1 (M) z(m) f (M)]d + z (M)dW().33 z (M) = M, Okendal.v. 5.1 uing I inerpreain. dm = [f 1 (M) z(m) f (M)d + MdW()...34 Fr a mh grwh funcin i.e. an uncapped rae, i can be hwn uing a generalizain f he cenral limi herem ha hi frmulain i equivalen he SDE wih z (M) = z (M ), prvided he number f fd iem cnumed i large (Feller, 1950, Whi, 00). Fr inance, Binmial cnverge Pin a N. Fr large N and = z(m) a he mean arrival rae, a, G(M) like Pin: uppreed. ln M 1 r W M And hu; M = M exp x e..35 r 1 W behave viz inegrain f rdinary calculu and cmparin wih he I inerpreain frm he grwh mdel in.8. A an exenin f he prblem in vgue, he uncapped rae chaic prce ha been added having menined he change in ma f he fih larval recruimen al fr he capped rae chaic prce. The uncapped rae chaic cae differ by ju a remval f he grwh rae. The ime mauriy in hi cae ha been udied exenively and me analyical luin have been fund (Karlin and Taylr, 1981; Grimme and Sirzaker, 001). Having adaped he change in ma fr fih larva recruimen viz he ppulain grwh mdel, we deduced an exprein previuly aed in cmparin wih he I inerpreain fr he individual ma, M grw and becme M viz; M = M exp 1 r W ] viz inegrain f rdinary calculu. 4.1 Schaic Differenial Equain Equain (1.0) abve becme a chaic differenial equain (SDE) and n lnger an ODE when he prey encunered rae, Z i defined a a randm variable repreening a heergeneu fd upply. Schaic differenial equain incrprae Whie nie, which can be een a he derivaive f Brwnian min r he Weiner prce. I can al incrprae her ype f randm flucuain uch a jump prce. Firly, he uncapped deerminiic cae i; dm = (f 1 (M) Z(M) f (M))d (.18) If Z(M) i n lnger deerminiic, he infinieimal rae Z(M)d huld be replaced by Z(M)d + z (M) dw(), where Z(M) i an average value and z (M) meaure he ineniy f he chaic perurbain (aumed be driven by a Wiener prce). The SDE i; dm = f 1 (M) Z(M)d + z (M)dW() f (M)d...(.19) The SDE can be lved analyically r numerically depending n he frm f he variu funcin. Fr he capped rae, we have; dm = min (f 1 (M) Z(M) f (M); g(m)d (.0) When meablic c, f (M) = 0, he ime mauriy i imply he Nh arrival f he Pin prce, where N i calculaed frm M ma and f 1 (M). In he cae where f (M) 0, he prblem can be aken a ha f a randm walk hiing a mving barrier. Frm he cenral limi herem, hi i equivalen he SDE wih z (M) = Z(M), prvided he number f fd iem cnumed i large (Feller, 1950; Whi, 00). The change in ma i very eniive he ime inerval chen when n limiing prce i reached a CONCLUSION I i a wrhwhile ak explring a grwh mdel, preciely here fih recruimen larvae. The grwh mdel plauibly, culd be aumed be capped. Hwever, he aainmen f capped rae chaic iuain migh n be ufficien pracically due me chaic r randm flucuain in real life prcee, hu cniderain f an uncapped rae iuain becme expedien. The chaic variain in uncapped rae iuain and he Wiener driven nie are pracically ineviable. Fr a ypical grwh mdel, change in ma i cnidered wih repec he individual ma and al vial fr cniderain are phyical and phyilgical facr, epecially in an uncapped rae chaic iuain. Specifically, meablic c, mean prey arrival rae, cnverin efficiency f fd, ime inerval were cnidered here. Hwever, cnidering an I Inerpreain, an analyical exprein ha been derived fr deermining he ma f an individual fih larvae in an uncapped rae chaic prce r iuain. REFERENCES 1. Abramvich M & Segun IA. Handbk f Mahemaical funcin, 3rd edn. New Yrk: Dver
6 New Yrk Science Jurnal 01;5(1) hp:// Cuhing DN, Hrwd JW. The grwh and deah f fih larvae. J.Plankn Re. 1994:16: Chamber RC and Trippel AE. Early Life Hiry and Recruimen in Fih Ppulain: Lndn, Chapman and Hall Feller W. Prbabiliy hery and i applicain. New Yrk: Wiley Fgary, M.J. Recruimen in randmly varying envirnmen. ICES Jurnal f Marine Science. 1991: 50: Fgary MJ, Sieenwine MP and Chen EB. Recruimen variabiliy and he dynamic f explied marine ppulain. TRENDS in eclgy and evluin. 1991:6(8): Grimme GR & Sirzaker DR. Prbabiliy and randm prcee. 3 rd ediin, Oxfrd Univeriy Pre, Jhnn NL, Krz S. Cninuu univarae diribuin I. Bn, MA; Hughn Mifflin Cmpany Jame A, Baxer PD, Pichfrd JW. Mdelling predain a a capped rae chaic prce, wih applicain fih recruimen. Jurnal f The Ryal Sciey..005: Karlin S, Taylr H. A ecnd cure n chaic prcee. New Yrk: Academic pre, New Yrk. 1981: Økendal B. Schaic differenial equain. An inrducin wih applicain, 6h edn. New Yrk: Springer, Pichfrd J, Brindley, J. Prey pachne, predar urvival and fih recruimen. Bull. Mah. Bil. 011:63: (di:10/006/buin,001.30). 13. Sranvich. A new repreenain fr chaic inegral and inegrain: SIAM J.Cnrl. 1966:4: Whi W. Schaic prce limi. In Springer erie in perainal reearch. New Yrk: Springer /4/01 91
a. (1) Assume T = 20 ºC = 293 K. Apply Equation 2.22 to find the resistivity of the brass in the disk with
Aignmen #5 EE7 / Fall 0 / Aignmen Sluin.7 hermal cnducin Cnider bra ally wih an X amic fracin f Zn. Since Zn addiin increae he number f cnducin elecrn, we have cale he final ally reiiviy calculaed frm
More information10.7 Temperature-dependent Viscoelastic Materials
Secin.7.7 Temperaure-dependen Viscelasic Maerials Many maerials, fr example plymeric maerials, have a respnse which is srngly emperaure-dependen. Temperaure effecs can be incrpraed in he hery discussed
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.070J Fall 2013 Lecture 15 10/30/2013. Ito integral for simple processes
MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.65/15.7J Fall 13 Lecure 15 1/3/13 I inegral fr simple prcesses Cnen. 1. Simple prcesses. I ismery. Firs 3 seps in cnsrucing I inegral fr general prcesses 1 I inegral
More informationIntroduction. If there are no physical guides, the motion is said to be unconstrained. Example 2. - Airplane, rocket
Kinemaic f Paricle Chaper Inrducin Kinemaic: i he branch f dynamic which decribe he min f bdie wihu reference he frce ha eiher caue he min r are generaed a a reul f he min. Kinemaic i fen referred a he
More informationBrace-Gatarek-Musiela model
Chaper 34 Brace-Gaarek-Musiela mdel 34. Review f HJM under risk-neural IP where f ( T Frward rae a ime fr brrwing a ime T df ( T ( T ( T d + ( T dw ( ( T The ineres rae is r( f (. The bnd prices saisfy
More informationMachine Learning for Signal Processing Prediction and Estimation, Part II
Machine Learning fr Signal Prceing Predicin and Eimain, Par II Bhikha Raj Cla 24. 2 Nv 203 2 Nv 203-755/8797 Adminirivia HW cre u Sme uden wh g really pr mark given chance upgrade Make i all he way he
More informationVariation of Mean Hourly Insolation with Time at Jos
OR Jurnal f Envirnmenal cience, Txiclgy and Fd Technlgy (OR-JETFT) e-n: 319-40,p- N: 319-399.Vlume 9, ue 7 Ver. (July. 015), PP 01-05 www.irjurnal.rg Variain f Mean urly nlain wih Time a J 1 Ad Mua, Babangida
More informationCHAPTER 2 Describing Motion: Kinematics in One Dimension
CHAPTER Decribing Min: Kinemaic in One Dimenin hp://www.phyicclarm.cm/cla/dkin/dkintoc.hml Reference Frame and Diplacemen Average Velciy Inananeu Velciy Accelerain Min a Cnan Accelerain Slving Prblem Falling
More informationCHAPTER 2 Describing Motion: Kinematics in One Dimension
CHAPTER Decribing Min: Kinemaic in One Dimenin hp://www.phyicclarm.cm/cla/dkin/dkintoc.hml Reference Frame and Diplacemen Average Velciy Inananeu Velciy Accelerain Min a Cnan Accelerain Slving Prblem Falling
More informationThe Components of Vector B. The Components of Vector B. Vector Components. Component Method of Vector Addition. Vector Components
Upcming eens in PY05 Due ASAP: PY05 prees n WebCT. Submiing i ges yu pin ward yur 5-pin Lecure grade. Please ake i seriusly, bu wha cuns is wheher r n yu submi i, n wheher yu ge hings righ r wrng. Due
More informationVisco-elastic Layers
Visc-elasic Layers Visc-elasic Sluins Sluins are bained by elasic viscelasic crrespndence principle by applying laplace ransfrm remve he ime variable Tw mehds f characerising viscelasic maerials: Mechanical
More informationSection 11 Basics of Time-Series Regression
Secin Baic f ime-serie Regrein Wha differen abu regrein uing ime-erie daa? Dynamic effec f X n Y Ubiquiu aucrrelain f errr erm Difficulie f nnainary Y and X Crrelain i cmmn ju becaue bh variable fllw rend
More information(V 1. (T i. )- FrC p. ))= 0 = FrC p (T 1. (T 1s. )+ UA(T os. (T is
. Yu are repnible fr a reacr in which an exhermic liqui-phae reacin ccur. The fee mu be preheae he hrehl acivain emperaure f he caaly, bu he pruc ream mu be cle. T reuce uiliy c, yu are cniering inalling
More informationOn the Stability and Boundedness of Solutions of Certain Non-Autonomous Delay Differential Equation of Third Order
Applie Mahemaic, 6, 7, 457-467 Publihe Online March 6 in SciRe. hp://www.cirp.rg/jurnal/am hp://.i.rg/.436/am.6.764 On he Sabili an Bunene f Sluin f Cerain Nn-Aunmu Dela Differenial Equain f Thir Orer
More informationGAMS Handout 2. Utah State University. Ethan Yang
Uah ae Universiy DigialCmmns@UU All ECAIC Maerials ECAIC Repsiry 2017 GAM Handu 2 Ehan Yang yey217@lehigh.edu Fllw his and addiinal wrs a: hps://digialcmmns.usu.edu/ecsaic_all Par f he Civil Engineering
More informationTHE DETERMINATION OF CRITICAL FLOW FACTORS FOR NATURAL GAS MIXTURES. Part 3: The Calculation of C* for Natural Gas Mixtures
A REPORT ON THE DETERMINATION OF CRITICAL FLOW FACTORS FOR NATURAL GAS MIXTURES Par 3: The Calculain f C* fr Naural Gas Mixures FOR NMSPU Deparmen f Trade and Indusry 151 Buckingham Palace Rad Lndn SW1W
More informationImpact Switch Study Modeling & Implications
L-3 Fuzing & Ordnance Sysems Impac Swich Sudy Mdeling & Implicains Dr. Dave Frankman May 13, 010 NDIA 54 h Annual Fuze Cnference This presenain cnsiss f L-3 Crprain general capabiliies infrmain ha des
More informationu(t) Figure 1. Open loop control system
Open loop conrol v cloed loop feedbac conrol The nex wo figure preen he rucure of open loop and feedbac conrol yem Figure how an open loop conrol yem whoe funcion i o caue he oupu y o follow he reference
More informationName Student ID. A student uses a voltmeter to measure the electric potential difference across the three boxes.
Name Student ID II. [25 pt] Thi quetin cnit f tw unrelated part. Part 1. In the circuit belw, bulb 1-5 are identical, and the batterie are identical and ideal. Bxe,, and cntain unknwn arrangement f linear
More informationINFLUENCE OF WIND VELOCITY TO SUPPLY WATER TEMPERATURE IN HOUSE HEATING INSTALLATION AND HOT-WATER DISTRICT HEATING SYSTEM
Dr. Branislav Zivkvic, B. Eng. Faculy f Mechanical Engineering, Belgrade Universiy Predrag Zeknja, B. Eng. Belgrade Municipal DH Cmpany Angelina Kacar, B. Eng. Faculy f Agriculure, Belgrade Universiy INFLUENCE
More informationTo become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship
Laplace Tranform (Lin & DeCarlo: Ch 3) ENSC30 Elecric Circui II The Laplace ranform i an inegral ranformaion. I ranform: f ( ) F( ) ime variable complex variable From Euler > Lagrange > Laplace. Hence,
More informationProductivity changes of units: A directional measure of cost Malmquist index
Available nline a hp://jnrm.srbiau.ac.ir Vl.1, N.2, Summer 2015 Jurnal f New Researches in Mahemaics Science and Research Branch (IAU Prduciviy changes f unis: A direcinal measure f cs Malmquis index G.
More informationINVESTIGATING THE EFFECT OF FRP CONFIGURATION ON THE ULTIMATE TORSIONAL CAPACITY OF FRP STRENGHTNED REINFORCED CONCRETE BEAMS
INVESTIGTING THE EFFECT OF FRP CONFIGURTION ON THE ULTIMTE TORSIONL CPCITY OF FRP STRENGHTNED REINFORCED CONCRETE BEMS M. meli 1 * and H.R. Rnagh 2 1 Cenre r Buil Inrarucure Reearch, Faculy Engineering,
More information5.1 Angles and Their Measure
5. Angles and Their Measure Secin 5. Nes Page This secin will cver hw angles are drawn and als arc lengh and rains. We will use (hea) represen an angle s measuremen. In he figure belw i describes hw yu
More informationAn application of nonlinear optimization method to. sensitivity analysis of numerical model *
An applicain f nnlinear pimizain mehd sensiiviy analysis f numerical mdel XU Hui 1, MU Mu 1 and LUO Dehai 2 (1. LASG, Insiue f Amspheric Physics, Chinese Academy f Sciences, Beijing 129, China; 2. Deparmen
More informationPRINCE SULTAN UNIVERSITY Department of Mathematical Sciences Final Examination Second Semester (072) STAT 271.
PRINCE SULTAN UNIVERSITY Deparmen f Mahemaical Sciences Final Examinain Secnd Semeser 007 008 (07) STAT 7 Suden Name Suden Number Secin Number Teacher Name Aendance Number Time allwed is ½ hurs. Wrie dwn
More informationAP Physics 1 MC Practice Kinematics 1D
AP Physics 1 MC Pracice Kinemaics 1D Quesins 1 3 relae w bjecs ha sar a x = 0 a = 0 and mve in ne dimensin independenly f ne anher. Graphs, f he velciy f each bjec versus ime are shwn belw Objec A Objec
More informationConvex Stochastic Duality and the Biting Lemma
Jurnal f Cnvex Analysis Vlume 9 (2002), N. 1, 237 244 Cnvex Schasic Dualiy and he Biing Lemma Igr V. Evsigneev Schl f Ecnmic Sudies, Universiy f Mancheser, Oxfrd Rad, Mancheser, M13 9PL, UK igr.evsigneev@man.ac.uk
More informationEE202 Circuit Theory II
EE202 Circui Theory II 2017-2018, Spring Dr. Yılmaz KALKAN I. Inroducion & eview of Fir Order Circui (Chaper 7 of Nilon - 3 Hr. Inroducion, C and L Circui, Naural and Sep epone of Serie and Parallel L/C
More informationAn Introduction to Wavelet Analysis. with Applications to Vegetation Monitoring
An Inrducin Wavele Analysis wih Applicains Vegeain Mniring Dn Percival Applied Physics Labrary, Universiy f Washingn Seale, Washingn, USA verheads fr alk available a hp://saff.washingn.edu/dbp/alks.hml
More informationChem. 6C Midterm 1 Version B October 19, 2007
hem. 6 Miderm Verin Ocber 9, 007 Name Suden Number ll wr mu be hwn n he exam fr parial credi. Pin will be aen ff fr incrrec r n uni. Nn graphing calcular and ne hand wrien 5 ne card are allwed. Prblem
More informationMotion Along a Straight Line
PH 1-3A Fall 010 Min Alng a Sraigh Line Lecure Chaper (Halliday/Resnick/Walker, Fundamenals f Physics 8 h ediin) Min alng a sraigh line Sudies he min f bdies Deals wih frce as he cause f changes in min
More informationRamsey model. Rationale. Basic setup. A g A exogenous as in Solow. n L each period.
Ramsey mdel Rainale Prblem wih he Slw mdel: ad-hc assumpin f cnsan saving rae Will cnclusins f Slw mdel be alered if saving is endgenusly deermined by uiliy maximizain? Yes, bu we will learn a l abu cnsumpin/saving
More informationIntroduction to SLE Lecture Notes
Inroducion o SLE Lecure Noe May 13, 16 - The goal of hi ecion i o find a ufficien condiion of λ for he hull K o be generaed by a imple cure. I urn ou if λ 1 < 4 hen K i generaed by a imple curve. We will
More informationA Theoretical Model of a Voltage Controlled Oscillator
A Theoreical Model of a Volage Conrolled Ocillaor Yenming Chen Advior: Dr. Rober Scholz Communicaion Science Iniue Univeriy of Souhern California UWB Workhop, April 11-1, 6 Inroducion Moivaion The volage
More informationPhysics Courseware Physics I Constant Acceleration
Physics Curseware Physics I Cnsan Accelerain Equains fr cnsan accelerain in dimensin x + a + a + ax + x Prblem.- In he 00-m race an ahlee acceleraes unifrmly frm res his p speed f 0m/s in he firs x5m as
More information7 The Itô/Stratonovich dilemma
7 The Iô/Sraonovich dilemma The dilemma: wha does he idealizaion of dela-funcion-correlaed noise mean? ẋ = f(x) + g(x)η() η()η( ) = κδ( ). (1) Previously, we argued by a limiing procedure: aking noise
More informationA Note on the Approximation of the Wave Integral. in a Slightly Viscous Ocean of Finite Depth. due to Initial Surface Disturbances
Applied Mahemaical Sciences, Vl. 7, 3, n. 36, 777-783 HIKARI Ld, www.m-hikari.cm A Ne n he Apprximain f he Wave Inegral in a Slighly Viscus Ocean f Finie Deph due Iniial Surface Disurbances Arghya Bandypadhyay
More informationRough Paths and its Applications in Machine Learning
Pah ignaure Machine learning applicaion Rough Pah and i Applicaion in Machine Learning July 20, 2017 Rough Pah and i Applicaion in Machine Learning Pah ignaure Machine learning applicaion Hiory and moivaion
More informationKinematics Review Outline
Kinemaics Review Ouline 1.1.0 Vecrs and Scalars 1.1 One Dimensinal Kinemaics Vecrs have magniude and direcin lacemen; velciy; accelerain sign indicaes direcin + is nrh; eas; up; he righ - is suh; wes;
More informationTP B.2 Rolling resistance, spin resistance, and "ball turn"
echnical proof TP B. olling reiance, pin reiance, and "ball urn" upporing: The Illuraed Principle of Pool and Billiard hp://billiard.coloae.edu by Daid G. Alciaore, PhD, PE ("Dr. Dae") echnical proof originally
More informationExplicit form of global solution to stochastic logistic differential equation and related topics
SAISICS, OPIMIZAION AND INFOMAION COMPUING Sa., Opim. Inf. Compu., Vol. 5, March 17, pp 58 64. Publihed online in Inernaional Academic Pre (www.iapre.org) Explici form of global oluion o ochaic logiic
More information21.9 Magnetic Materials
21.9 Magneic Maerials The inrinsic spin and rbial min f elecrns gives rise he magneic prperies f maerials è elecrn spin and rbis ac as iny curren lps. In ferrmagneic maerials grups f 10 16-10 19 neighbring
More informationLaplace Transform. Inverse Laplace Transform. e st f(t)dt. (2)
Laplace Tranform Maoud Malek The Laplace ranform i an inegral ranform named in honor of mahemaician and aronomer Pierre-Simon Laplace, who ued he ranform in hi work on probabiliy heory. I i a powerful
More informationPHY305F Electronics Laboratory I. Section 2. AC Circuit Basics: Passive and Linear Components and Circuits. Basic Concepts
PHY305F Elecrnics abrary I Secin ircui Basics: Passie and inear mpnens and ircuis Basic nceps lernaing curren () circui analysis deals wih (sinusidally) ime-arying curren and lage signals whse ime aerage
More informationPhysics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution
Physics 7b: Saisical Mechanics Fokker-Planck Equaion The Langevin equaion approach o he evoluion of he velociy disribuion for he Brownian paricle migh leave you uncomforable. A more formal reamen of his
More informationFractional Ornstein-Uhlenbeck Bridge
WDS'1 Proceeding of Conribued Paper, Par I, 21 26, 21. ISBN 978-8-7378-139-2 MATFYZPRESS Fracional Ornein-Uhlenbeck Bridge J. Janák Charle Univeriy, Faculy of Mahemaic and Phyic, Prague, Czech Republic.
More information, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max
ecure 8 7. Sabiliy Analyi For an n dimenional vecor R n, he and he vecor norm are defined a: = T = i n i (7.) I i eay o how ha hee wo norm aify he following relaion: n (7.) If a vecor i ime-dependen, hen
More information6.8 Laplace Transform: General Formulas
48 HAP. 6 Laplace Tranform 6.8 Laplace Tranform: General Formula Formula Name, ommen Sec. F() l{ f ()} e f () d f () l {F()} Definiion of Tranform Invere Tranform 6. l{af () bg()} al{f ()} bl{g()} Lineariy
More informationUnit-I (Feedback amplifiers) Features of feedback amplifiers. Presentation by: S.Karthie, Lecturer/ECE SSN College of Engineering
Uni-I Feedback ampliiers Feaures eedback ampliiers Presenain by: S.Karhie, Lecurer/ECE SSN Cllege Engineering OBJECTIVES T make he sudens undersand he eec negaive eedback n he llwing ampliier characerisics:
More informationStability in Distribution for Backward Uncertain Differential Equation
Sabiliy in Diribuion for Backward Uncerain Differenial Equaion Yuhong Sheng 1, Dan A. Ralecu 2 1. College of Mahemaical and Syem Science, Xinjiang Univeriy, Urumqi 8346, China heng-yh12@mail.inghua.edu.cn
More informationEECE 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 informationCHAPTER 7: SECOND-ORDER CIRCUITS
EEE5: CI RCUI T THEORY CHAPTER 7: SECOND-ORDER CIRCUITS 7. Inroducion Thi chaper conider circui wih wo orage elemen. Known a econd-order circui becaue heir repone are decribed by differenial equaion ha
More informationMathematische Annalen
Mah. Ann. 39, 33 339 (997) Mahemaiche Annalen c Springer-Verlag 997 Inegraion by par in loop pace Elon P. Hu Deparmen of Mahemaic, Norhweern Univeriy, Evanon, IL 628, USA (e-mail: elon@@mah.nwu.edu) Received:
More informationBAYESIAN MOBILE LOCATION IN CELLULAR NETWORKS
BAYESIAN MOBILE LOCATION IN CELLULAR NETWORKS Mhamed Khalaf-Allah Iniue f Cmmunicain Engineering, Univeriy f Hannver Appelrae 9A, D-3067, Hannver, Germany phne: + 49 5 762 2845, fax: + 49 5 762 3030, email:
More informationSuccessive ApproxiInations and Osgood's Theorenl
Revisa de la Unin Maemaica Argenina Vlumen 40, Niimers 3 y 4,1997. 73 Successive ApprxiInains and Osgd's Therenl Calix P. Caldern Virginia N. Vera de Seri.July 29, 1996 Absrac The Picard's mehd fr slving
More informationChapter 7: Inverse-Response Systems
Chaper 7: Invere-Repone Syem Normal Syem Invere-Repone Syem Baic Sar ou in he wrong direcion End up in he original eady-ae gain value Two or more yem wih differen magniude and cale in parallel Main yem
More informationAssignment 16. Malaria does not affect the red cell count in the lizards.
ignmen 16 7.3.5 If he null hypohei i no rejeced ha he wo ample are differen, hen he Type of Error would be ype II 7.3.9 Fale. The cieni rejeced baed on a bad calculaion, no baed upon ample ha yielded an
More information18.03SC Unit 3 Practice Exam and Solutions
Sudy Guide on Sep, Dela, Convoluion, Laplace You can hink of he ep funcion u() a any nice mooh funcion which i for < a and for > a, where a i a poiive number which i much maller han any ime cale we care
More informationLecture 3: Resistive forces, and Energy
Lecure 3: Resisive frces, and Energy Las ie we fund he velciy f a prjecile ving wih air resisance: g g vx ( ) = vx, e vy ( ) = + v + e One re inegrain gives us he psiin as a funcin f ie: dx dy g g = vx,
More informationDiscussion Session 2 Constant Acceleration/Relative Motion Week 03
PHYS 100 Dicuion Seion Conan Acceleraion/Relaive Moion Week 03 The Plan Today you will work wih your group explore he idea of reference frame (i.e. relaive moion) and moion wih conan acceleraion. You ll
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Civil and Environmental Engineering
MASSACHUSETTS INSTITUTE OF TECHNOLOGY Deparmen of Civil and Environmenal Engineering 1.731 Waer Reource Syem Lecure 17 River Bain Planning Screening Model Nov. 7 2006 River Bain Planning River bain planning
More informationStochastic Model for Cancer Cell Growth through Single Forward Mutation
Journal of Modern Applied Saisical Mehods Volume 16 Issue 1 Aricle 31 5-1-2017 Sochasic Model for Cancer Cell Growh hrough Single Forward Muaion Jayabharahiraj Jayabalan Pondicherry Universiy, jayabharahi8@gmail.com
More informationand Sun (14) and Due and Singlen (19) apply he maximum likelihd mehd while Singh (15), and Lngsa and Schwarz (12) respecively emply he hreesage leas s
A MONTE CARLO FILTERING APPROACH FOR ESTIMATING THE TERM STRUCTURE OF INTEREST RATES Akihik Takahashi 1 and Seish Sa 2 1 The Universiy f Tky, 3-8-1 Kmaba, Megur-ku, Tky 153-8914 Japan 2 The Insiue f Saisical
More informationLecture #31, 32: The Ornstein-Uhlenbeck Process as a Model of Volatility
Saisics 441 (Fall 214) November 19, 21, 214 Prof Michael Kozdron Lecure #31, 32: The Ornsein-Uhlenbeck Process as a Model of Volailiy The Ornsein-Uhlenbeck process is a di usion process ha was inroduced
More informationNelson Primary School Written Calculation Policy
Addiin Fundain Y1 Y2 Children will engage in a wide variey f sngs, rhymes, games and aciviies. They will begin relae addiin cmbining w grups f bjecs. They will find ne mre han a given number. Cninue develp
More informationLinear Motion, Speed & Velocity
Add Iporan Linear Moion, Speed & Velociy Page: 136 Linear Moion, Speed & Velociy NGSS Sandard: N/A MA Curriculu Fraework (2006): 1.1, 1.2 AP Phyic 1 Learning Objecive: 3.A.1.1, 3.A.1.3 Knowledge/Underanding
More informationLecture 4 ( ) Some points of vertical motion: Here we assumed t 0 =0 and the y axis to be vertical.
Sme pins f erical min: Here we assumed and he y axis be erical. ( ) y g g y y y y g dwnwards 9.8 m/s g Lecure 4 Accelerain The aerage accelerain is defined by he change f elciy wih ime: a ; In analgy,
More informationTemperature control for simulated annealing
PHYSICAL REVIEW E, VOLUME 64, 46127 Temperaure conrol for imulaed annealing Toyonori Munakaa 1 and Yauyuki Nakamura 2 1 Deparmen of Applied Mahemaic and Phyic, Kyoo Univeriy, Kyoo 66, Japan 2 Deparmen
More informationELEG 205 Fall Lecture #10. Mark Mirotznik, Ph.D. Professor The University of Delaware Tel: (302)
EEG 05 Fall 07 ecure #0 Mark Mirznik, Ph.D. Prfessr The Universiy f Delaware Tel: (3083-4 Email: mirzni@ece.udel.edu haper 7: apacirs and Inducrs The apacir Symbl Wha hey really lk like The apacir Wha
More informationMotion In One Dimension. Graphing Constant Speed
Moion In One Dimenion PLATO AND ARISTOTLE GALILEO GALILEI LEANING TOWER OF PISA Graphing Conan Speed Diance v. Time for Toy Car (0-5 ec.) be-fi line (from TI calculaor) d = 207.7 12.6 Diance (cm) 1000
More informationPhysics 240: Worksheet 16 Name
Phyic 4: Workhee 16 Nae Non-unifor circular oion Each of hee proble involve non-unifor circular oion wih a conan α. (1) Obain each of he equaion of oion for non-unifor circular oion under a conan acceleraion,
More informationSynchronous Rectified Soft-Switched Phase-Shift Full-Bridge Converter with Primary Energy Storage Inductor
Synchrnu ecified Sf-Swiched Phae-Shif Full-Bridge Cnverer wih Primary Energy Srage Inducr Chen Zha, Xinke Wu, Wei Ya, Zhaming Qian (IEEE Senir Member Zhejiang Univeriy Ineril Crprain Jin Labrary Cllege
More informationSubject: Turbojet engines (continued); Design parameters; Effect of mass flow on thrust.
16.50 Leure 19 Subje: Turbje engines (ninued; Design parameers; Effe f mass flw n hrus. In his haper we examine he quesin f hw hse he key parameers f he engine bain sme speified perfrmane a he design ndiins,
More informationLabQuest 24. Capacitors
Capaciors LabQues 24 The charge q on a capacior s plae is proporional o he poenial difference V across he capacior. We express his wih q V = C where C is a proporionaliy consan known as he capaciance.
More informationTopic 3. Single factor ANOVA [ST&D Ch. 7]
Topic 3. Single facor ANOVA [ST&D Ch. 7] "The analyi of variance i more han a echnique for aiical analyi. Once i i underood, ANOVA i a ool ha can provide an inigh ino he naure of variaion of naural even"
More informationMoney in OLG Models. 1. Introduction. Econ604. Spring Lutz Hendricks
Mne in OLG Mdels Ecn604. Spring 2005. Luz Hendricks. Inrducin One applicain f he mdels sudied in his curse ha will be pursued hrughu is mne. The purpse is w-fld: I prvides an inrducin he ke mdels f mne
More informationA Risk-Averse Insider and Asset Pricing in Continuous Time
Managemen Science and Financial Engineering Vol 9, No, May 3, pp-6 ISSN 87-43 EISSN 87-36 hp://dxdoiorg/7737/msfe39 3 KORMS A Rik-Avere Inider and Ae Pricing in oninuou Time Byung Hwa Lim Graduae School
More informationCHAPTER 7 CHRONOPOTENTIOMETRY. In this technique the current flowing in the cell is instantaneously stepped from
CHAPTE 7 CHONOPOTENTIOMETY In his echnique he curren flwing in he cell is insananeusly sepped frm zer sme finie value. The sluin is n sirred and a large ecess f suppring elecrlye is presen in he sluin;
More informationActa Scientiarum. Technology ISSN: Universidade Estadual de Maringá Brasil
Aca cieniarum. Technlgy IN: 86-2563 eduem@uem.br Universidade Esadual de Maringá Brasil hang, Hsu Yang A mehdlgy fr analysis f defecive pipeline by inrducing sress cncenrain facr in beam-pipe finie elemen
More informationStat13 Homework 7. Suggested Solutions
Sa3 Homework 7 hp://www.a.ucla.edu/~dinov/coure_uden.hml Suggeed Soluion Queion 7.50 Le denoe infeced and denoe noninfeced. H 0 : Malaria doe no affec red cell coun (µ µ ) H A : Malaria reduce red cell
More informationBusiness Cycles. Approaches to business cycle modeling
Business Cycles 73 Business Cycles Appraches business cycle mdeling Definiin: Recurren paern f dwnswings and upswings: Acrss many indusries Wih cmmn paern f c-mvemen amng majr variables Oupu Emplymen Invesmen
More informationResearch Article On Double Summability of Double Conjugate Fourier Series
Inernaional Journal of Mahemaic and Mahemaical Science Volume 22, Aricle ID 4592, 5 page doi:.55/22/4592 Reearch Aricle On Double Summabiliy of Double Conjugae Fourier Serie H. K. Nigam and Kuum Sharma
More informationNotes on cointegration of real interest rates and real exchange rates. ρ (2)
Noe on coinegraion of real inere rae and real exchange rae Charle ngel, Univeriy of Wiconin Le me ar wih he obervaion ha while he lieraure (mo prominenly Meee and Rogoff (988) and dion and Paul (993))
More informationNGSS High School Physics Domain Model
NGSS High Schl Physics Dmain Mdel Mtin and Stability: Frces and Interactins HS-PS2-1: Students will be able t analyze data t supprt the claim that Newtn s secnd law f mtin describes the mathematical relatinship
More informationSchool and Workshop on Market Microstructure: Design, Efficiency and Statistical Regularities March 2011
2229-12 School and Workshop on Marke Microsrucure: Design, Efficiency and Saisical Regulariies 21-25 March 2011 Some mahemaical properies of order book models Frederic ABERGEL Ecole Cenrale Paris Grande
More informationAlgorithmic Discrete Mathematics 6. Exercise Sheet
Algorihmic Dicree Mahemaic. Exercie Shee Deparmen of Mahemaic SS 0 PD Dr. Ulf Lorenz 7. and 8. Juni 0 Dipl.-Mah. David Meffer Verion of June, 0 Groupwork Exercie G (Heap-Sor) Ue Heap-Sor wih a min-heap
More informationChapter 9 Compressible Flow 667
Chapter 9 Cmpreible Flw 667 9.57 Air flw frm a tank thrugh a nzzle int the tandard atmphere, a in Fig. P9.57. A nrmal hck tand in the exit f the nzzle, a hwn. Etimate (a) the tank preure; and (b) the ma
More informationPhysics 111. Exam #1. September 28, 2018
Physics xam # Sepember 8, 08 ame Please read and fllw hese insrucins carefully: Read all prblems carefully befre aemping slve hem. Yur wrk mus be legible, and he rganizain clear. Yu mus shw all wrk, including
More informationU T,0. t = X t t T X T. (1)
Gauian bridge Dario Gabarra 1, ommi Soinen 2, and Eko Valkeila 3 1 Deparmen of Mahemaic and Saiic, PO Box 68, 14 Univeriy of Helinki,Finland dariogabarra@rnihelinkifi 2 Deparmen of Mahemaic and Saiic,
More informationPhysics 20 Lesson 9H Rotational Kinematics
Phyc 0 Len 9H Ranal Knemac In Len 1 9 we learned abu lnear mn knemac and he relanhp beween dplacemen, velcy, acceleran and me. In h len we wll learn abu ranal knemac. The man derence beween he w ype mn
More informationESTIMATES FOR THE DERIVATIVE OF DIFFUSION SEMIGROUPS
Elec. Comm. in Probab. 3 (998) 65 74 ELECTRONIC COMMUNICATIONS in PROBABILITY ESTIMATES FOR THE DERIVATIVE OF DIFFUSION SEMIGROUPS L.A. RINCON Deparmen of Mahemaic Univeriy of Wale Swanea Singleon Par
More information11. HAFAT İş-Enerji Power of a force: Power in the ability of a force to do work
MÜHENDİSLİK MEKNİĞİ. HFT İş-Eneji Pwe f a fce: Pwe in he abiliy f a fce d wk F: The fce applied n paicle Q P = F v = Fv cs( θ ) F Q v θ Pah f Q v: The velciy f Q ÖRNEK: İŞ-ENERJİ ω µ k v Calculae he pwe
More informationRAMIFICATIONS of POSITION SERVO LOOP COMPENSATION
RAMIFICATIONS f POSITION SERO LOOP COMPENSATION Gerge W. Yunk, P.E. Lfe Fellw IEEE Indural Cnrl Cnulg, Inc. Fnd du Lac, Wcn Fr many year dural pg er dre dd n ue er cmpena he frward p lp. Th wa referred
More informationModeling the Evolution of Demand Forecasts with Application to Safety Stock Analysis in Production/Distribution Systems
Modeling he Evoluion of Demand oreca wih Applicaion o Safey Sock Analyi in Producion/Diribuion Syem David Heah and Peer Jackon Preened by Kai Jiang Thi ummary preenaion baed on: Heah, D.C., and P.L. Jackon.
More informationAngular Motion, Speed and Velocity
Add Imporan Angular Moion, Speed and Velociy Page: 163 Noe/Cue Here Angular Moion, Speed and Velociy NGSS Sandard: N/A MA Curriculum Framework (006): 1.1, 1. AP Phyic 1 Learning Objecive: 3.A.1.1, 3.A.1.3
More informationū(e )(1 γ 5 )γ α v( ν e ) v( ν e )γ β (1 + γ 5 )u(e ) tr (1 γ 5 )γ α ( p ν m ν )γ β (1 + γ 5 )( p e + m e ).
PHY 396 K. Soluion for problem e #. Problem (a: A poin of noaion: In he oluion o problem, he indice µ, e, ν ν µ, and ν ν e denoe he paricle. For he Lorenz indice, I hall ue α, β, γ, δ, σ, and ρ, bu never
More informationBasic Circuit Elements Professor J R Lucas November 2001
Basic Circui Elemens - J ucas An elecrical circui is an inerconnecion of circui elemens. These circui elemens can be caegorised ino wo ypes, namely acive and passive elemens. Some Definiions/explanaions
More informationHow to Solve System Dynamic s Problems
How o Solve Sye Dynaic Proble A ye dynaic proble involve wo or ore bodie (objec) under he influence of everal exernal force. The objec ay uliaely re, ove wih conan velociy, conan acceleraion or oe cobinaion
More informationResearch Article Existence and Uniqueness of Solutions for a Class of Nonlinear Stochastic Differential Equations
Hindawi Publihing Corporaion Abrac and Applied Analyi Volume 03, Aricle ID 56809, 7 page hp://dx.doi.org/0.55/03/56809 Reearch Aricle Exience and Uniquene of Soluion for a Cla of Nonlinear Sochaic Differenial
More information