Abstract: 1. Introduction: components such as damping from the water viscosity and different masses for large manipulated objects.
|
|
- Brooke Sharp
- 5 years ago
- Views:
Transcription
1 Dynamc Smulaon for ero-gravy Acves Norman I. Badler, Dmrs N. Meaxas, Gang Huang, Ambarsh Goswam, Sueung Huh Unversy of Pennsylvana, Phladelpha, USA Absrac: Worng and ranng for space acves s dffcul n erresral envronmens. We approach hs crucal aspec of space human facors hrough D compuer graphcs dynamcs smulaon of crewmembers, her ass, and physcs-based movemen modelng. Such vrual crewmembers may be used o desgn ass and analyze her physcal worload o mze success and safey whou expensve physcal mocups or parally realsc neural-buoyancy ans. Among he sofware ools we have developed are mehods for fully arculaed D human models and dynamc smulaon. We are developng a fas recursve dynamcs algorhm for dynamcally smulang arculaed D human models, whch comprses nemac chans -- seral, closed-loop, and ree-srucure -- as well as he neral properes of he segmens. Moon plannng s done by frs solvng he nverse nemac problem o generae possble raecores, and hen by solvng he resulng nonlnear opmal conrol problem. For example, he mnmzaon of he orques durng a smulaon under ceran consrans s usually appled and has s orgn n he bomechancs leraure. Examples of space acves shown are zero-gravy self orenaon and ladder raversal. Energy expendure s compued for he raversal as. Keywords: dynamc smulaon, D compuer graphcs smulaon, arculaed body, human model, opmal conrol, moon plannng.. Inroducon: Worng and ranng for space acves s dffcul n erresral envronmens. There s a grea demand for human facors regardng he dynamc ably of he human body n space. In compuer graphcs (CG and vrual realy (VR such human facors would be helpful o creae realsc human anmaons, and desgn ass o mze success and safey whou always havng o resor o expensve physcal mocups or parally realsc neural-buoyancy ans. The laer accommodaes some of he -gravy experence bu adds unrealsc dynamc componens such as dampng from he waer vscosy and dfferen masses for large manpulaed obecs. There are many forward and nverse dynamcs smulaon echnques for smulang human behavor ha have been mplemened by CG researchers [4][9][], bu hey are no compuaonally effcen and smulaons canno be done n real me. Some conrol echnques have also been used, such as feedbac conrol o follow he desred raecores generaed by nverse nemacs [4] and he spaceme consran mehod based on opmzaon heory []. However, hey do no address explcly eher he orque opmzaon problem or dynamcs ha deal wh he varous opologcal confguraons of he arculaed body. Ths paper frs presens an effcen way o conver he geomery of an arculaed body o a dynamc ree srucured model, whch s suable for dynamc smulaon and moon plannng. In he dynamc ree, each on has only one degree of freedom, whch gves only one paren ln and one chld ln. Each ln has s own roo on, and up o hree branch ons. The ln can be a dummy ln, whch has no mass, lengh and nera. The roo of he dynamc ree usually s a base on fxed o he reference frame. Each leaf of he dynamc ree mus be ln, hough he ln can be a dummy ln. Jon Paren Ln Jon Chld Ln Ln Roo Jon Jon Ln Branch Jon Ln Ln Branch Jon Ln Branch Jon Fgure. The Relaonshp beween Jons and Lns Secon of he paper shows a smple ype of funcon ha we used for smulang he moons, and s properes for nemac and dynamc smulaon. All he dynamc smulaons n hs paper use hs funcon, whch we call nemac moon funcon, o specfy he moon of each on or he body.
2 In Secon an effcen recursve dynamcs mehod for he dynamc ree based on Feahersones mehod [] s suded and used o dynamcally smulae asronau self-orenaon (Secon 4 and ladder raversal n -gravy (Secon 5. Furhermore, n Secon we presen an opmal conrol algorhm based on hs effcen recursve dynamcs mehod and graden mehod o fnd he local mnmum on-orque moon under specfed consrans []. From he bomechancs pon of vew, he mnmum onorque moon s he opmal moon under ceran condons for human body, for example he moon o do wegh lfng n seconds. Fnally, n Secon 7 we oulne some energy expendure models ha can be evaluaed based on he compued on orques.. Dynamc Model for an Arculaed Body: Physcal properes: he number of degrees freedom of he on, he on ype, (such as -on, -on, and -on, ec. he on lms, he on orque lms, he dampng coeffcens for he on. Noe: each on has s own on coordnae frame called on prvae coordnae frame, whch s dfferen from he on local coordnae frame defned n he ree srucure, n whch he on roaon axs s always he z-axs. For example: n he on prvae coordnae frame, he z-axs and he y-axs are on roaon axes, and he x- axs s defned n he rgh-hand sense. In he on local coordnae frame boh roaon axes are defned as he z-axs. By roang he frs z-axs 9 degrees concdes wh he second z-axs. (See Fg.. Jon The physcally based smulaon of human moon s obaned from nemac and dynamc calculaons. The effcency of he compuaon depends on he algorhms used for hese calculaons. O Jon Type: -Jon An arculaed body can be represened opologcally as a ree whose lns represen s maor pars. Bascally, hs means here are no nemac loops and ha no par of he arculaed body s enrely dsconneced from he res. An mmoble ln (or an appropraely chosen ln f none of he lns s mmoble s consdered as he roo of he dynamc ree, and he ouermos lns are s leaves. Two lns conneced by a on are he paren and chld lns of he on, dependng on wheher he ln s more proxmal or dsal o he roo. The on s called he roo on of s chld ln. The ons wh he same paren ln are called he branch ons of he ln. The base ln s he ln connecng he fxed pon o he roo on of he dynamc ree. Every ln excep he base ln has exacly one roo on, bu may have up o hree branch ons f modelng humans. We represen he arculaed body as a ree srucure. Each on has he followng properes: Tree srucure properes: he ndex for he on, he ndex for s paren and chld lns. Noe he base ln s defned as he null ln, and he on conneced o he null ln s on. (See Fg.. O 9 Fgure. Jon Prvae Coordnae frame O for -on, Jon Local Coordnae frame O for o- z he roaon axs, and O for o-y he roaon axs Each ln has he followng geomerc and dynamc properes: Tree srucure properes: he ndex for he ln, he ndex for s roo on, he number of he branch ons, he ndex for each branch on. Noe a leaf ln has no branch on, we defne as he null on. Dynamc properes: he mass, he cener of mass n he lns roo on coordnae frame, he prncpal neral marx, and he roaon marx from he lns roo on coordnae frame o s prncpal coordnae frame. Denav-Harenberg noaon [] parameers for each par of he lns roo We consder only mulple-degree-of-freedom on wh orhogonal roaon axs.
3 and branch on (See Fg. : he lengh of he common normal a ; he dsance beween he orgn O and he pon H ; he angle α beween he lns roo on axs and branch on axs n he rgh-hand sense; he angle θ beween he lns roo on coordnae frame x -axs and he common normal, whch s he x-axs of he lns branch on coordnae frame, measured abou s roo on z-axs n he rgh-hand sense. If a lns roo on s a mulple-degree-offreedom on, he lns roo on z-axs s he las roaon axs n he on prvae coordnae frame. For example f he on ype s -on, he y-axs n he on prvae coordnae frame s he lns roo on z-axs we are usng. In he same manner, f a lns branch on s a mulple-degree-of-freedom on, he lns branch on axs s he frs roaon axs n he on prvae coordnae frame. Jon - Ln - H z Jon O y a x θ Ln Fgure. Denav-Harenberg Noaon y O α z Jon x Jon The numberng scheme we use for he arculaed body s ha each ln has he same ndex number as he lns roo on. The ndex of a lns roo on s less han he ndex of he lns lefmos branch on. The ndex of a lns lef branch on s less han he ndex of he lns rgh branch on. (The numberng on Fg. 4 follows hs scheme. Thus, we defne he arculaed body as a lef-rgh ree-le srucure. Base Null Ln J J: Jon L: Ln : D on : D on : D on L J Fgure 4. Numberng Scheme for Arculaed Tree L We now presen a mehod o effcenly represen an arculaed ree usng a dynamc ree represenaon. Mulple-degree-of-freedom ons can be synheszed from he approprae number of sngle-degree-of-freedom ons. A movng arculaed body could be reaed as a dynamc ree srucure by nroducng a fcous, unpowered on beween he roo and some fxed pon. If he roo of he dynamc ree has complee moon freedom hen he on has sx degrees of freedom. The arculaed body defned as an arculaed ree srucure s convered o a dynamc ree by represenng every mulple-degree-of-freedom on wh he approprae number of sngledegree-of-freedom ons. Based on our mehod, we add dummy lns no a mulple-degree-offreedom on, such ha every on n he dynamc ree s a sngle-degree-of-freedom on. The dummy ln s defned as he ln wh no lengh, no mass, and no nera. Beween he wo consecuve generaed sngle-degree-of-freedom ons here s a roaon marx, whch defnes he ransformaon marx beween he wo new on local coordnaes. Therefore a wo-degreeof-freedom on wll generae wo sngle-degreeof-freedom ons, such ha he z-axes n boh of he on local coordnaes are parallel o he orgnal on roaon axes. The numberng scheme for he dynamc ree s he same for he arculaed ree. (See Fg. 5. The on coordnae frame s aached o ln. J L 4 L 7 J 4 L J J 7 J 5 L L 5 J L Srcly speang, he par s he sngle-degree-of-freedom roo on and he sngle-degree-of-freedom branch on.
4 (snce Base Null Ln J J: Jon L: Ln L J J L L J J 5 J 4 L 4 L J 7 L 7 J L L5 J 8 L 8 J 9 L 9 J L mos human moon sars wh zero velocy and zero acceleraon, and ends wh zero velocy and zero acceleraon as well. To sasfy hese boundary condons, we choose he smples ype of funcon. Is dervave (namely, velocy funcon s n he form of: x( C ( ( e C s a consan ha can be calculaed from he nal and endng posons, s he sarng me, and e s he endng me. J Fgure 5. Numberng Scheme for Dynamc Tree, whch s generaed from Arculaed ree n Fg. 4. Jon O Jon Type: -Jon Jon + O + Dummy Ln O L T + Fgure. Two-degree-of-freedom -on convered o wo sngle-degree-of-freedom ons and one dummy ln. (Compare wh Fg.. If on n arculaed ree can generae on, dummy ln, and on + n dynamc ree, T s he ransformaon marx beween he on + local coordnae frame and he on + local coordnae frame.. Knemac Moon Funcon: In our smulaon we would le o assess he feasbly of connuous moon. Therefore, we frs need o generae hese moons and hen use nverse dynamcs o compue he on orques. The human moon smulaon s carred ou based on nemac calculaons, and he on orques are obaned by nverse dynamcs. The ssue s wha nd of funcon we should use o specfy he moon of ons or bodes. There are an nfne number of funcons we could choose for he moon smulaon, for example lnear funcons and quadrac funcons. However, For smplcy, we se, e T, and x (, x ( T. The nemac moon funcon s x( C ( T Ths funcon obvously sasfes he velocy and acceleraon consrans. Namely, x(, x( T, x(, x( T. We negrae he velocy funcon o oban he moon funcon: x( C T T + 5 x T, we ge From ( C T 5 So he funcon for he moon smulaon s x ( ( T 5T + ( 5 T The varable x ( can represen a poson vecor (he hree componens have dfferen parameers of he nemac moon funcon or on θ for a revolue on. varable (for example ( Now we sudy a more complcaed moon problem, n whch he moon funcon should sasfy he consran ha he mum speed durng he moon should have an upper bound V. Frs we solve he funcon for he moon smulaon as above, and hen chec f 5 V x( T he nemac moon 8T funcon reaches s mum a he mddle of he moon. If s sasfed, he funcon we calculaed s he fnal funcon for he moon smulaon. If s no sasfed, we wll change he moon o hree phases. The frs phase s he acceleraon phase, n whch he moon speeds up o V n seconds. The second phase s he consan speed phase, n whch he moon eeps he speed a V for seconds. The hrd phase
5 s he deceleraon phase, n whch he moon slows down o zero velocy n seconds. Thus, T, T V V x x V ( (, [, ( V (, [, + x + 4 ( ( T T ( + ( + ( T ( + ( + T + V ( [ T ],, Noe T Self Orenaon: People re-oren hemselves easly on earh snce gravy assures a force componen and herefore an expecaon of frcon wh he supporng surface. A space waler can move and mae urns f equpped wh SAFER (Smplfed Ad for Exravehcular acvy Rescue, whch produces sx degrees of freedom n movemen. Bu how can an asronau maes urns when floang nsde he vehcle wh no exernal force and orque acng on her body and no hand or foo resrans? In hs secon, we descrbe he dynamc heory -- based on he conservaon of momenum and Feahersones nverse recursve dynamcs -- whch allows he asronau o do a self-orenaon. Then we do he smulaon and calculae he on orques durng he smulaed moon. A -gravy self-orenaon moon can be compleed n hree seps: leg lfng, leg wsng, and leg closng. Fgure 7. Sandng Posure Fgure 8. Leg Lfng Fgure 9. Leg Twsng Fgure. Leg Closng For he purpose of hs smulaon, we use a smplfed arculaed body whch ncludes wo ons (he lef and rgh hp ons and hree lns (he orso ln, he lef and rgh leg lns, whch can be convered o a dynamc ree wh sx ons and seven lns. (See Fg.. The O frame s he reference frame. The orso ln coordnae frame O s aached o he cener of mass of he orso. The rgh hp on prvae coordnae frame O and he lef hp on prvae coordnae frame O are aached o he rgh and lef leg lns, respecvely. C and C are he cener of mass of he rgh and lef legs, respecvely. O Torso Ln O O O J4 J5 L L L L C C Jon has degree of freedoms, and s defned a he cener of he mass Rgh Leg Ln Lef Leg Ln of he orso ln J L5 L4 L J J J Fgure. Coordnae frames for Arculaed Body and s Dynamc Tree. Noe: L, L, L4, and L5 are dummy lns Snce he asronau s floang nsde he vehcle, here s no exernal force and orque exered on he asronau, and so spaal momenum (.e. lnear and angular momenum of he human body s conserved durng he moon. The dynamc noaons we use n hs paper are based on hose n Feahersones boo. The conservaon of momenum s expressed as: I ˆ vˆ + Iˆ vˆ + Iˆ vˆ cons ˆ Î ( s he spaal nera for each ln n he reference frame. vˆ ( s he spaal velocy for each ln n he reference frame. The spaal veloces ˆv and ˆv of he lef and rgh leg lns can be wren as:
6 J vˆ vˆ + Sˆq + Sˆ q + Sˆq vˆ vˆ + Sˆ q + Sˆ q + Sˆ q J5 ] fˆ Iˆ aˆ + vˆ ˆ Iˆ vˆ aˆ aˆ + Sˆq + Sˆ q + Sˆ q + vˆ ˆ Sˆq + Sˆ q + Sˆ q + Sˆ q ˆ Sˆ q + Sˆ q + Sˆ q ˆ Sˆ q ( ( The on orque abou each on axs s hus: Q SˆS fˆ, Q Sˆ S fˆ, L4 -Jon L J7 -Jon L5 J -Jon Fgure. Smplfed Arculaed Tree wh degrees of freedom (All he frame are on prvae coordnae frames. ( for he orso ln. d ˆ fˆ I vˆ Iˆ aˆ + vˆ ˆ Iˆ vˆ d In order o ge he lef-hp on orque, he spaal force fˆ s compued as -Jon L Le fˆ be he resulan spaal force exered on he orso ln hrough he rgh and lef hp ons. fˆ gves he overall rae change of momenum J J4 ( -Jon L can ge he poson and orenaon of he orso ln and he spaal acceleraon of as well. J Iˆ Sˆq + Sˆ q + Sˆ q + Iˆ Sˆ4 q4 + Sˆ5 q5 + Sˆ q By negrang v or ang s dervaves, we -Jon The spaal velocy v s obaned by solvng he above equaons: vˆ Iˆ + Iˆ + Iˆ [( L J q ( ( s he specfed funcon for moon smulaon durng each sep, compued from (. S ( s he spaal vecor for he axs of on. ( -Jon -Jon L A dynamc ree wh ons and lns can be generaed from he arculaed ree easly. We add a dummy ln o he lef wrs z-on f he rgh wrs y-on s he roo on for he dynamc ree. In order o smplfy he smulaon, we assume here are no dynamc closed loops durng he moon. Namely, f he rgh hand grabs he bar hen he lef hand mus be free, hs s smplfcaon s based on how asronaus raverse ladders. We can dvde he moon no wo nds of moon perods: Sarng/endng moon perod, Mddle moon perod. The sarng moon perod begns wh boh hands on he bar, bu only one grabbng (say rgh hand, and ends wh he free hand (lef hand on he fron bar. The endng moon perod s he reverse of he sarng moon perod. The mddle moon perod sars wh one hand grabbng bar (say rgh hand and he oher hand (lef hand on bar (-, and ends wh he oher hand (lef hand on bar (+. (See Fg.,4. Q SˆS fˆ. 5. Ladder Traversal: Snce an asronau floas n space (-gravy, s hard o eep balance among he lmbs when raversng a ladder. By leng he legs floa free and only usng he hands o grab he bars, he asronau can conrol her body moon. In hs Secon we do he dynamc smulaon and calculae he on orques, so we can compue he mum possble worload for an asronau raversng a ladder. In he fuure, we plan o use compuer vson echnques o capure an acual asronaus movemen for dealed comparson. The arculaed ree we used o smplfy he asronau body consss of egh ons and 7 lns. (See Fg.. Fgure. Endng Posure, whch s he same as sarng posure (a (b (c (d (e (f
7 (g Fgure 4. Anmaon Sequence of Ladder Traversal n one perod The nemac moon funcons are compued n wo levels. The global moon plannng level gves he smulaed moon for he orso ln by he mehod we descrbed n Secon. The perodc moon plannng level gves he smulaed moons for each on durng ha perod. These funcons are calculaed by gvng he nal and fnal posons for on-varables and he mum speed consrans. The nal and fnal on-varables are compued based on nverse nemacs, wh he poson and orenaon of he orso ln specfed, and he hands posons are nown a each perods nal and fnal sages. The velocy of he orso ln (obaned from he perodc moon plannng level n he drecon of moon should be conssen wh he one compued from he global moon plannng level. Once we have he funcons of he smulaed moon for each on, we calculae he on orques. The above compues nemacs. In order o compue he on orques we use an effcen calculaon scheme, whch s smlar o Feahersones and can be obaned by performng hese calculaons pernen o ln n on -coordnae frame. The equaons n on -coordnae frame, whch s aached o ln, s as follows: vˆ ˆ vˆ + Sˆ q, ( v ˆ. paren. paren. paren. paren fˆ ˆ a v ˆ I ˆ + ˆ ˆ Ivˆ, ˆ. paren aˆ ˆ aˆ + vˆ ˆ Sˆ q + Sˆ q, ( a ˆ fˆ ˆ ˆ fˆ, (f { chld} f + {. chld } S Sˆ fˆ Q.. Opmal Conrol: ˆ. paren., fˆ fˆ The above smulaons are done n real me. Bu we also neres n opmzed moon of he human moon under ceran specfed consrans, whch can no be done n real me. The opmal conrol problem s formulaed by mnmzng he on orques, snce s suable n space applcaons. The problem can be saed as []: Opmze: DOF f mn [ τ (, q ] d q Subec o all he gven consrans DOF s he oal degrees-of-freedom of τ, s he on orque a he arculaed body. ( q me when he funcons of he smulaed moon are expressed n B-Splne funcons [] wh he conrol pons q. The nonlnear programmng mehod requres he explc calculaon of he graden. We defne he opmzaon funcon based on a gven se of conrol pons q and he wegh coeffcens λ for all he consrans: F DOF f n ( q, λ [ τ (, q ] d + λc (, q n s he oal number of consrans. We opmze F ( λ mehod: q ( l ( l δq [ F( q, λ ] ( + ( + m n m n δλ ( m+ n DOF N, by usng he graden ( l ( l ( F( q, λ ( m+ n m, N s he number of B-splne conrol pons for each ons smulaed moon funcon n B-splne form. Lo and Meaxas [] gve he deals on how o compue he graden F, λ. By of he opmzaon funcon ( solvng he above lnear equaon sysem, we oban δ q and δλ. And we have he new se of he conrol pons and he wegh coeffcens: ( l ( l q + q + δq, ( l + ( l λ δλ. λ + If he eraon ndex l s larger han he specfed mum eraon mes, or δ q δ << and δλ <<, q δλ we choose ( l + q as he fnal conrol pons for each ons B-splne nemac moon funcon. 7. Energy Expendure: I s commonly suggesed ha slled human movemens opmze ceran crera, whch are relaed o he energy expendure []. Among he suggesed crera, we eleced o measure he vrual human's energy expendure based on he followng quanes: q
8 a he weghed sum of he absolue values of he on orque, b he change of he oal mechancal energy of he body, c he mechancal power generaed or ransferred n he ons, and d he rae of sudden change n movemen (er. The weghed sum of he absolue values of he on orque The me negral of he on orque has been suggesed as a useful measure of he energy expendure when s appropraely weghed for he negave and posve wor condons [,]. Among many suggesons, Wllams[4] and Perrynows e al. [5] have repored ha he negave wor s approxmaely hree mes more effcen han he posve wor. For a gven on, he wor s posve when he orque and he angular velocy have he same drecon, and negave oherwse. The posve on wor corresponds o he concenrc muscle acvy and he negave on wor corresponds o he eccenrc muscle acvy. So he sum of he weghed absolue on momens s used as our energy expendure measure he absolue on momen s defned as ρ τ f τ *ω o τ oherwse ω τ refers o he orque of he on and refers o he angular velocy of he on. Fg. 5 shows he weghed sum of he absolue on orque whou any shoulder consran he hgh pch denoes he me when he asronau ouches he ladder. Fgure 5. Weghed Sum of he absolue on orques The change of he oal mechancal energy of he body E TKE + RKE ( refers o he Translaonal Knec TKE Energy of he on and RKE he Roaonal Knec Energy of he on. The mechancal power generaed or absorbed a he ons P τ ( ω ω + τ refers o he orque of he on and refers o he angular velocy of he on. ω The mechancal power ransferred a he ons P ι ω ι p τ * f τ *ω τ τ * ω p oherwse o refers o he orque of he on and ω refers o he angular velocy of he on. Ths creron ncorporaes boh concenrc and eccenrc muscle acves. The rae of sudden change n movemen(jer A J J refers o he me dervave of acceleraon of he on (er. The er s shown o be mnmzed for a ceran class of acves [7]. 8. Concluson: Dynamcally correc human moon smulaon requres a proper dynamc ree model effcenly creaed from a smplfed arculaed ree. I also requres he generaon of an arculaed body movemen paern from a sarng posure o a fnal posure. The man focus of hs paper s o smulae self-orenaon and ladder raversal of an asronau n -gravy. These and oher dynamc smulaons may be used for boh vsualzaon and analyss of - or mcro-gray ass. We mplemened he mehods developed here o generae he dynamc ree, smulae he
9 desred moons, and compue he energy expendure funcons. These procedures wll be useful n he fuure analyss and safey evaluaon of novel space acves. Acnowledgmens: Ths research s parally suppored by NASA NRA NAG 5-99 and ONR IP N o he second auhor. Bblography: [] G. Engeln-Mullges, F. Uhlg. Numercal Algorhms wh C. Sprnger, 99 [] R. Feahersone. Robo Dynamcs Algorhm. Kluwer Academc Publshers, Boson, 987 [] R. Flecher. Praccal Mehods of Opmzaon. John Wley & Sons, Ld. 98 [4] J.K. Hodgns, W.L. Wooen, D.C. Brogan, and J.F. OBren. Anmaon of Human Ahlecs. In Proc. SIGGRAPH 95, pages 7-78, Augus 995 [5] K.W. Llly. Effcen Dynamc Smulaon of Roboc Mechansms. Kluwer Academc Publshers, Boson, 99 [] J. Lo. Ph.D. Thess: Recursve Dynamcs and Opmal Conrol Technques for Human Moon Plannng. Mechancal Engneerng and Appled Mechancs, Unversy of Pennsylvana, 998 [7] J. Lo and D. Meaxas. Effcen Human Moon Plannng Usng Recursve Dynamcs and Opmal Conrol Technques. Proc. Of he Second Symposum on Mulbody Dynamcs and Vbraon a he 7 h Bennal Conference on Mechancal Vbraon and Nose, Las Vegas, NV, Sep. -5, 999 [8] J. Lo and D. Meaxas. Recursve Dynamcs and Opmal Conrol Technques for Human Moon Plannng. Proc. Of Compuer Anmaon Conference, CA99. Geneva, Swzerland, May -9, 999 [9] A.J. Sewar and J.F. Cremer. Beyond eyframng: An algorhmc approach o anmaon. In Proc. Of Graphcs Inerface, pages 7-8, 99 [] H.W. Sone. Knemac Modelng, Idenfcaon, and Conrol of Roboc Manpulaors. Kluwer Academc Publshers, Boson, 987 [] J. Wlhelms and B. Barsy. Usng Dynamc Analyss o Anmae Arculaed Bodes such as Humans and Robos. In Graphcs Inerface, 985 [] A. Wn and M. Kass. Spaceme Consrans. ACM Compuer Graphcs, (4, 988 [] R.N. Marshall, G.A. Wood and L.S. Jennngs. Performance obecves n human movemen: A revew and applcaon o he sance phase of normal walng. Human Movemen Scence 8 ( [4] K.R. Wllams and P.R. Cavanagh. A model for he calculaon of mechancal power durng dsance runnng. Journal of Bomechancs, 5-8, 98 [5] M.R. Perrynows, D.A. Wner and R.W. Norman. Transfers of mechancal energy whn he oal body and mechancal durng readmll walng. Ergonomcs, 98, 47-5 [] J.G. Andrews. Bomechancal measures of muscular effor. Medcne and Scence n Spors and exercse 5, 99-7 [7] N. Hogan. An organzng prncple for a class of volunary movemens. Journal of Neuroscence 4,
2.1 Constitutive Theory
Secon.. Consuve Theory.. Consuve Equaons Governng Equaons The equaons governng he behavour of maerals are (n he spaal form) dρ v & ρ + ρdv v = + ρ = Conservaon of Mass (..a) d x σ j dv dvσ + b = ρ v& +
More informationOn One Analytic Method of. Constructing Program Controls
Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna
More information( ) () we define the interaction representation by the unitary transformation () = ()
Hgher Order Perurbaon Theory Mchael Fowler 3/7/6 The neracon Represenaon Recall ha n he frs par of hs course sequence, we dscussed he chrödnger and Hesenberg represenaons of quanum mechancs here n he chrödnger
More informationV.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS
R&RATA # Vol.) 8, March FURTHER AALYSIS OF COFIDECE ITERVALS FOR LARGE CLIET/SERVER COMPUTER ETWORKS Vyacheslav Abramov School of Mahemacal Scences, Monash Unversy, Buldng 8, Level 4, Clayon Campus, Wellngon
More informationCS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4
CS434a/54a: Paern Recognon Prof. Olga Veksler Lecure 4 Oulne Normal Random Varable Properes Dscrmnan funcons Why Normal Random Varables? Analycally racable Works well when observaon comes form a corruped
More informationHEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD
Journal of Appled Mahemacs and Compuaonal Mechancs 3, (), 45-5 HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Sansław Kukla, Urszula Sedlecka Insue of Mahemacs,
More informationVariants of Pegasos. December 11, 2009
Inroducon Varans of Pegasos SooWoong Ryu bshboy@sanford.edu December, 009 Youngsoo Cho yc344@sanford.edu Developng a new SVM algorhm s ongong research opc. Among many exng SVM algorhms, we wll focus on
More informationCubic Bezier Homotopy Function for Solving Exponential Equations
Penerb Journal of Advanced Research n Compung and Applcaons ISSN (onlne: 46-97 Vol. 4, No.. Pages -8, 6 omoopy Funcon for Solvng Eponenal Equaons S. S. Raml *,,. Mohamad Nor,a, N. S. Saharzan,b and M.
More informationVEHICLE DYNAMIC MODELING & SIMULATION: COMPARING A FINITE- ELEMENT SOLUTION TO A MULTI-BODY DYNAMIC SOLUTION
21 NDIA GROUND VEHICLE SYSTEMS ENGINEERING AND TECHNOLOGY SYMPOSIUM MODELING & SIMULATION, TESTING AND VALIDATION (MSTV) MINI-SYMPOSIUM AUGUST 17-19 DEARBORN, MICHIGAN VEHICLE DYNAMIC MODELING & SIMULATION:
More informationSolution in semi infinite diffusion couples (error function analysis)
Soluon n sem nfne dffuson couples (error funcon analyss) Le us consder now he sem nfne dffuson couple of wo blocks wh concenraon of and I means ha, n a A- bnary sysem, s bondng beween wo blocks made of
More informationTHE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS
THE PREICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS INTROUCTION The wo dmensonal paral dfferenal equaons of second order can be used for he smulaon of compeve envronmen n busness The arcle presens he
More informationGENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim
Korean J. Mah. 19 (2011), No. 3, pp. 263 272 GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS Youngwoo Ahn and Kae Km Absrac. In he paper [1], an explc correspondence beween ceran
More informationHomework 8: Rigid Body Dynamics Due Friday April 21, 2017
EN40: Dynacs and Vbraons Hoework 8: gd Body Dynacs Due Frday Aprl 1, 017 School of Engneerng Brown Unversy 1. The earh s roaon rae has been esaed o decrease so as o ncrease he lengh of a day a a rae of
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 0 Canoncal Transformaons (Chaper 9) Wha We Dd Las Tme Hamlon s Prncple n he Hamlonan formalsm Dervaon was smple δi δ Addonal end-pon consrans pq H( q, p, ) d 0 δ q ( ) δq ( ) δ
More informationThe Finite Element Method for the Analysis of Non-Linear and Dynamic Systems
Swss Federal Insue of Page 1 The Fne Elemen Mehod for he Analyss of Non-Lnear and Dynamc Sysems Prof. Dr. Mchael Havbro Faber Dr. Nebojsa Mojslovc Swss Federal Insue of ETH Zurch, Swzerland Mehod of Fne
More informationCHAPTER 10: LINEAR DISCRIMINATION
CHAPER : LINEAR DISCRIMINAION Dscrmnan-based Classfcaon 3 In classfcaon h K classes (C,C,, C k ) We defned dscrmnan funcon g j (), j=,,,k hen gven an es eample, e chose (predced) s class label as C f g
More informationLinear Response Theory: The connection between QFT and experiments
Phys540.nb 39 3 Lnear Response Theory: The connecon beween QFT and expermens 3.1. Basc conceps and deas Q: ow do we measure he conducvy of a meal? A: we frs nroduce a weak elecrc feld E, and hen measure
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm H ( q, p, ) = q p L( q, q, ) H p = q H q = p H = L Equvalen o Lagrangan formalsm Smpler, bu
More informationComb Filters. Comb Filters
The smple flers dscussed so far are characered eher by a sngle passband and/or a sngle sopband There are applcaons where flers wh mulple passbands and sopbands are requred Thecomb fler s an example of
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm Hqp (,,) = qp Lqq (,,) H p = q H q = p H L = Equvalen o Lagrangan formalsm Smpler, bu wce as
More informationScattering at an Interface: Oblique Incidence
Course Insrucor Dr. Raymond C. Rumpf Offce: A 337 Phone: (915) 747 6958 E Mal: rcrumpf@uep.edu EE 4347 Appled Elecromagnecs Topc 3g Scaerng a an Inerface: Oblque Incdence Scaerng These Oblque noes may
More informationLecture 6: Learning for Control (Generalised Linear Regression)
Lecure 6: Learnng for Conrol (Generalsed Lnear Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure 6: RLSC - Prof. Sehu Vjayakumar Lnear Regresson
More information[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5
TPG460 Reservor Smulaon 08 page of 5 DISCRETIZATIO OF THE FOW EQUATIOS As we already have seen, fne dfference appromaons of he paral dervaves appearng n he flow equaons may be obaned from Taylor seres
More informationCH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC
CH.3. COMPATIBILITY EQUATIONS Connuum Mechancs Course (MMC) - ETSECCPB - UPC Overvew Compably Condons Compably Equaons of a Poenal Vecor Feld Compably Condons for Infnesmal Srans Inegraon of he Infnesmal
More informationLecture 18: The Laplace Transform (See Sections and 14.7 in Boas)
Lecure 8: The Lalace Transform (See Secons 88- and 47 n Boas) Recall ha our bg-cure goal s he analyss of he dfferenal equaon, ax bx cx F, where we emloy varous exansons for he drvng funcon F deendng on
More informationFTCS Solution to the Heat Equation
FTCS Soluon o he Hea Equaon ME 448/548 Noes Gerald Reckenwald Porland Sae Unversy Deparmen of Mechancal Engneerng gerry@pdxedu ME 448/548: FTCS Soluon o he Hea Equaon Overvew Use he forward fne d erence
More informationLecture VI Regression
Lecure VI Regresson (Lnear Mehods for Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure VI: MLSC - Dr. Sehu Vjayakumar Lnear Regresson Model M
More informationApproximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy
Arcle Inernaonal Journal of Modern Mahemacal Scences, 4, (): - Inernaonal Journal of Modern Mahemacal Scences Journal homepage: www.modernscenfcpress.com/journals/jmms.aspx ISSN: 66-86X Florda, USA Approxmae
More informationVolatility Interpolation
Volaly Inerpolaon Prelmnary Verson March 00 Jesper Andreasen and Bran Huge Danse Mares, Copenhagen wan.daddy@danseban.com brno@danseban.com Elecronc copy avalable a: hp://ssrn.com/absrac=69497 Inro Local
More informationIntroduction to. Computer Animation
Inroducon o 1 Movaon Anmaon from anma (la.) = soul, spr, breah of lfe Brng mages o lfe! Examples Characer anmaon (humans, anmals) Secondary moon (har, cloh) Physcal world (rgd bodes, waer, fre) 2 2 Anmaon
More informationJ i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes.
umercal negraon of he dffuson equaon (I) Fne dfference mehod. Spaal screaon. Inernal nodes. R L V For hermal conducon le s dscree he spaal doman no small fne spans, =,,: Balance of parcles for an nernal
More informationM. Y. Adamu Mathematical Sciences Programme, AbubakarTafawaBalewa University, Bauchi, Nigeria
IOSR Journal of Mahemacs (IOSR-JM e-issn: 78-578, p-issn: 9-765X. Volume 0, Issue 4 Ver. IV (Jul-Aug. 04, PP 40-44 Mulple SolonSoluons for a (+-dmensonalhroa-sasuma shallow waer wave equaon UsngPanlevé-Bӓclund
More informationImplementation of Quantized State Systems in MATLAB/Simulink
SNE T ECHNICAL N OTE Implemenaon of Quanzed Sae Sysems n MATLAB/Smulnk Parck Grabher, Mahas Rößler 2*, Bernhard Henzl 3 Ins. of Analyss and Scenfc Compung, Venna Unversy of Technology, Wedner Haupsraße
More information. The geometric multiplicity is dim[ker( λi. number of linearly independent eigenvectors associated with this eigenvalue.
Lnear Algebra Lecure # Noes We connue wh he dscusson of egenvalues, egenvecors, and dagonalzably of marces We wan o know, n parcular wha condons wll assure ha a marx can be dagonalzed and wha he obsrucons
More informationA NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION
S19 A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION by Xaojun YANG a,b, Yugu YANG a*, Carlo CATTANI c, and Mngzheng ZHU b a Sae Key Laboraory for Geomechancs and Deep Underground Engneerng, Chna Unversy
More informationChapter Lagrangian Interpolation
Chaper 5.4 agrangan Inerpolaon Afer readng hs chaper you should be able o:. dere agrangan mehod of nerpolaon. sole problems usng agrangan mehod of nerpolaon and. use agrangan nerpolans o fnd deraes and
More informationDynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005
Dynamc Team Decson Theory EECS 558 Proec Shruvandana Sharma and Davd Shuman December 0, 005 Oulne Inroducon o Team Decson Theory Decomposon of he Dynamc Team Decson Problem Equvalence of Sac and Dynamc
More informationChapters 2 Kinematics. Position, Distance, Displacement
Chapers Knemacs Poson, Dsance, Dsplacemen Mechancs: Knemacs and Dynamcs. Knemacs deals wh moon, bu s no concerned wh he cause o moon. Dynamcs deals wh he relaonshp beween orce and moon. The word dsplacemen
More informationSymbolic Equation of Motion and Linear Algebra Models for High- Speed Ground Vehicle Simulations.
Symbolc Equaon of Moon and Lnear Algebra Models for Hgh- Speed Ground Vehcle Smulaons. y: James. D. Turner, Ph.D., ADS and Smulaon Cener, 2401 Oakdale lvd., Iowa Cy, Iowa, 52242. Absrac. Synhec envronmen
More informationMotion in Two Dimensions
Phys 1 Chaper 4 Moon n Two Dmensons adzyubenko@csub.edu hp://www.csub.edu/~adzyubenko 005, 014 A. Dzyubenko 004 Brooks/Cole 1 Dsplacemen as a Vecor The poson of an objec s descrbed by s poson ecor, r The
More informationLecture 11 SVM cont
Lecure SVM con. 0 008 Wha we have done so far We have esalshed ha we wan o fnd a lnear decson oundary whose margn s he larges We know how o measure he margn of a lnear decson oundary Tha s: he mnmum geomerc
More informationChapter 6: AC Circuits
Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.
More informationP R = P 0. The system is shown on the next figure:
TPG460 Reservor Smulaon 08 page of INTRODUCTION TO RESERVOIR SIMULATION Analycal and numercal soluons of smple one-dmensonal, one-phase flow equaons As an nroducon o reservor smulaon, we wll revew he smples
More informationRelative controllability of nonlinear systems with delays in control
Relave conrollably o nonlnear sysems wh delays n conrol Jerzy Klamka Insue o Conrol Engneerng, Slesan Techncal Unversy, 44- Glwce, Poland. phone/ax : 48 32 37227, {jklamka}@a.polsl.glwce.pl Keywor: Conrollably.
More informationMEEN Handout 4a ELEMENTS OF ANALYTICAL MECHANICS
MEEN 67 - Handou 4a ELEMENTS OF ANALYTICAL MECHANICS Newon's laws (Euler's fundamenal prncples of moon) are formulaed for a sngle parcle and easly exended o sysems of parcles and rgd bodes. In descrbng
More informationRobustness Experiments with Two Variance Components
Naonal Insue of Sandards and Technology (NIST) Informaon Technology Laboraory (ITL) Sascal Engneerng Dvson (SED) Robusness Expermens wh Two Varance Componens by Ana Ivelsse Avlés avles@ns.gov Conference
More informationFI 3103 Quantum Physics
/9/4 FI 33 Quanum Physcs Aleander A. Iskandar Physcs of Magnesm and Phooncs Research Grou Insu Teknolog Bandung Basc Conces n Quanum Physcs Probably and Eecaon Value Hesenberg Uncerany Prncle Wave Funcon
More informationIn the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!") i+1,q - [(!
ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL The frs hng o es n wo-way ANOVA: Is here neracon? "No neracon" means: The man effecs model would f. Ths n urn means: In he neracon plo (wh A on he horzonal
More informationOrdinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s
Ordnary Dfferenal Equaons n Neuroscence wh Malab eamples. Am - Gan undersandng of how o se up and solve ODE s Am Undersand how o se up an solve a smple eample of he Hebb rule n D Our goal a end of class
More information3. OVERVIEW OF NUMERICAL METHODS
3 OVERVIEW OF NUMERICAL METHODS 3 Inroducory remarks Ths chaper summarzes hose numercal echnques whose knowledge s ndspensable for he undersandng of he dfferen dscree elemen mehods: he Newon-Raphson-mehod,
More informationAn introduction to Support Vector Machine
An nroducon o Suppor Vecor Machne 報告者 : 黃立德 References: Smon Haykn, "Neural Neworks: a comprehensve foundaon, second edon, 999, Chaper 2,6 Nello Chrsann, John Shawe-Tayer, An Inroducon o Suppor Vecor Machnes,
More information10. A.C CIRCUITS. Theoretically current grows to maximum value after infinite time. But practically it grows to maximum after 5τ. Decay of current :
. A. IUITS Synopss : GOWTH OF UNT IN IUIT : d. When swch S s closed a =; = d. A me, curren = e 3. The consan / has dmensons of me and s called he nducve me consan ( τ ) of he crcu. 4. = τ; =.63, n one
More informationDual Approximate Dynamic Programming for Large Scale Hydro Valleys
Dual Approxmae Dynamc Programmng for Large Scale Hydro Valleys Perre Carpener and Jean-Phlppe Chanceler 1 ENSTA ParsTech and ENPC ParsTech CMM Workshop, January 2016 1 Jon work wh J.-C. Alas, suppored
More information. The geometric multiplicity is dim[ker( λi. A )], i.e. the number of linearly independent eigenvectors associated with this eigenvalue.
Mah E-b Lecure #0 Noes We connue wh he dscusson of egenvalues, egenvecors, and dagonalzably of marces We wan o know, n parcular wha condons wll assure ha a marx can be dagonalzed and wha he obsrucons are
More informationAn Inverse Dynamic Model of the Gough-Stewart Platform
An Inverse Dynamc Model of he Gough-Sewar Plaform GEORGES FRIED, KARIM DJOANI, DIANE BOROJENI, SOHAIL IQBAL nversy of PARIS XII LISSI-SCTIC Laboraory 120-122 rue Paul Aramango, 94400 Vry sur Sene FRANCE
More informationLet s treat the problem of the response of a system to an applied external force. Again,
Page 33 QUANTUM LNEAR RESPONSE FUNCTON Le s rea he problem of he response of a sysem o an appled exernal force. Agan, H() H f () A H + V () Exernal agen acng on nernal varable Hamlonan for equlbrum sysem
More informationExistence and Uniqueness Results for Random Impulsive Integro-Differential Equation
Global Journal of Pure and Appled Mahemacs. ISSN 973-768 Volume 4, Number 6 (8), pp. 89-87 Research Inda Publcaons hp://www.rpublcaon.com Exsence and Unqueness Resuls for Random Impulsve Inegro-Dfferenal
More informationEEL 6266 Power System Operation and Control. Chapter 5 Unit Commitment
EEL 6266 Power Sysem Operaon and Conrol Chaper 5 Un Commmen Dynamc programmng chef advanage over enumeraon schemes s he reducon n he dmensonaly of he problem n a src prory order scheme, here are only N
More informationOn computing differential transform of nonlinear non-autonomous functions and its applications
On compung dfferenal ransform of nonlnear non-auonomous funcons and s applcaons Essam. R. El-Zahar, and Abdelhalm Ebad Deparmen of Mahemacs, Faculy of Scences and Humanes, Prnce Saam Bn Abdulazz Unversy,
More informationPlanar truss bridge optimization by dynamic programming and linear programming
IABSE-JSCE Jon Conference on Advances n Brdge Engneerng-III, Augus 1-, 015, Dhaka, Bangladesh. ISBN: 978-984-33-9313-5 Amn, Oku, Bhuyan, Ueda (eds.) www.abse-bd.org Planar russ brdge opmzaon by dynamc
More informationGraduate Macroeconomics 2 Problem set 5. - Solutions
Graduae Macroeconomcs 2 Problem se. - Soluons Queson 1 To answer hs queson we need he frms frs order condons and he equaon ha deermnes he number of frms n equlbrum. The frms frs order condons are: F K
More informationPendulum Dynamics. = Ft tangential direction (2) radial direction (1)
Pendulum Dynams Consder a smple pendulum wh a massless arm of lengh L and a pon mass, m, a he end of he arm. Assumng ha he fron n he sysem s proporonal o he negave of he angenal veloy, Newon s seond law
More informationSingle-loop System Reliability-Based Design & Topology Optimization (SRBDO/SRBTO): A Matrix-based System Reliability (MSR) Method
10 h US Naonal Congress on Compuaonal Mechancs Columbus, Oho 16-19, 2009 Sngle-loop Sysem Relably-Based Desgn & Topology Opmzaon (SRBDO/SRBTO): A Marx-based Sysem Relably (MSR) Mehod Tam Nguyen, Junho
More informationOutline. Probabilistic Model Learning. Probabilistic Model Learning. Probabilistic Model for Time-series Data: Hidden Markov Model
Probablsc Model for Tme-seres Daa: Hdden Markov Model Hrosh Mamsuka Bonformacs Cener Kyoo Unversy Oulne Three Problems for probablsc models n machne learnng. Compung lkelhood 2. Learnng 3. Parsng (predcon
More informationOnline Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading
Onlne Supplemen for Dynamc Mul-Technology Producon-Invenory Problem wh Emssons Tradng by We Zhang Zhongsheng Hua Yu Xa and Baofeng Huo Proof of Lemma For any ( qr ) Θ s easy o verfy ha he lnear programmng
More informationModeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts
nernaonal ournal of Appled Engneerng Research SSN 0973-4562 Volume 13, Number 10 (2018) pp. 8708-8713 Modelng and Solvng of Mul-Produc nvenory Lo-Szng wh Suppler Selecon under Quany Dscouns Naapa anchanaruangrong
More information5th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2015)
5h Inernaonal onference on Advanced Desgn and Manufacurng Engneerng (IADME 5 The Falure Rae Expermenal Sudy of Specal N Machne Tool hunshan He, a, *, La Pan,b and Bng Hu 3,c,,3 ollege of Mechancal and
More informatione-journal Reliability: Theory& Applications No 2 (Vol.2) Vyacheslav Abramov
June 7 e-ournal Relably: Theory& Applcaons No (Vol. CONFIDENCE INTERVALS ASSOCIATED WITH PERFORMANCE ANALYSIS OF SYMMETRIC LARGE CLOSED CLIENT/SERVER COMPUTER NETWORKS Absrac Vyacheslav Abramov School
More informationTight results for Next Fit and Worst Fit with resource augmentation
Tgh resuls for Nex F and Wors F wh resource augmenaon Joan Boyar Leah Epsen Asaf Levn Asrac I s well known ha he wo smple algorhms for he classc n packng prolem, NF and WF oh have an approxmaon rao of
More informationTSS = SST + SSE An orthogonal partition of the total SS
ANOVA: Topc 4. Orhogonal conrass [ST&D p. 183] H 0 : µ 1 = µ =... = µ H 1 : The mean of a leas one reamen group s dfferen To es hs hypohess, a basc ANOVA allocaes he varaon among reamen means (SST) equally
More informationDensity Matrix Description of NMR BCMB/CHEM 8190
Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon If we say wh one bass se, properes vary only because of changes n he coeffcens weghng each bass se funcon x = h< Ix > - hs s how we calculae
More information(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function
MACROECONOMIC THEORY T J KEHOE ECON 87 SPRING 5 PROBLEM SET # Conder an overlappng generaon economy le ha n queon 5 on problem e n whch conumer lve for perod The uly funcon of he conumer born n perod,
More informationMath 128b Project. Jude Yuen
Mah 8b Proec Jude Yuen . Inroducon Le { Z } be a sequence of observed ndependen vecor varables. If he elemens of Z have a on normal dsrbuon hen { Z } has a mean vecor Z and a varancecovarance marx z. Geomercally
More informationDensity Matrix Description of NMR BCMB/CHEM 8190
Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon Alernae approach o second order specra: ask abou x magnezaon nsead of energes and ranson probables. If we say wh one bass se, properes vary
More informationHow about the more general "linear" scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )?
lmcd Lnear ransformaon of a vecor he deas presened here are que general hey go beyond he radonal mar-vecor ype seen n lnear algebra Furhermore, hey do no deal wh bass and are equally vald for any se of
More informationNATIONAL UNIVERSITY OF SINGAPORE PC5202 ADVANCED STATISTICAL MECHANICS. (Semester II: AY ) Time Allowed: 2 Hours
NATONAL UNVERSTY OF SNGAPORE PC5 ADVANCED STATSTCAL MECHANCS (Semeser : AY 1-13) Tme Allowed: Hours NSTRUCTONS TO CANDDATES 1. Ths examnaon paper conans 5 quesons and comprses 4 prned pages.. Answer all
More informationPHYS 1443 Section 001 Lecture #4
PHYS 1443 Secon 001 Lecure #4 Monda, June 5, 006 Moon n Two Dmensons Moon under consan acceleraon Projecle Moon Mamum ranges and heghs Reerence Frames and relae moon Newon s Laws o Moon Force Newon s Law
More informationComputing Relevance, Similarity: The Vector Space Model
Compung Relevance, Smlary: The Vecor Space Model Based on Larson and Hears s sldes a UC-Bereley hp://.sms.bereley.edu/courses/s0/f00/ aabase Managemen Sysems, R. Ramarshnan ocumen Vecors v ocumens are
More informationHandout # 6 (MEEN 617) Numerical Integration to Find Time Response of SDOF mechanical system Y X (2) and write EOM (1) as two first-order Eqs.
Handou # 6 (MEEN 67) Numercal Inegraon o Fnd Tme Response of SDOF mechancal sysem Sae Space Mehod The EOM for a lnear sysem s M X DX K X F() () X X X X V wh nal condons, a 0 0 ; 0 Defne he followng varables,
More informationNotes on the stability of dynamic systems and the use of Eigen Values.
Noes on he sabl of dnamc ssems and he use of Egen Values. Source: Macro II course noes, Dr. Davd Bessler s Tme Seres course noes, zarads (999) Ineremporal Macroeconomcs chaper 4 & Techncal ppend, and Hamlon
More informationTesting a new idea to solve the P = NP problem with mathematical induction
Tesng a new dea o solve he P = NP problem wh mahemacal nducon Bacground P and NP are wo classes (ses) of languages n Compuer Scence An open problem s wheher P = NP Ths paper ess a new dea o compare he
More informationResponse of MDOF systems
Response of MDOF syses Degree of freedo DOF: he nu nuber of ndependen coordnaes requred o deerne copleely he posons of all pars of a syse a any nsan of e. wo DOF syses hree DOF syses he noral ode analyss
More informationISSN MIT Publications
MIT Inernaonal Journal of Elecrcal and Insrumenaon Engneerng Vol. 1, No. 2, Aug 2011, pp 93-98 93 ISSN 2230-7656 MIT Publcaons A New Approach for Solvng Economc Load Dspach Problem Ansh Ahmad Dep. of Elecrcal
More informationAC : FLEXIBLE MULTIBODY DYNAMICS EXPLICIT SOLVER FOR REAL-TIME SIMULATION OF AN ONLINE VIRTUAL DYNAMICS LAB
AC 2012-5478: FLEXIBLE MULTIBODY DYNAMICS EXPLICIT SOLVER FOR REAL-TIME SIMULATION OF AN ONLINE VIRTUAL DYNAMICS LAB Mr. Haem M. Wasfy, Advanced Scence and Auomaon Corp. Haem Wasfy s he Presden of Advanced
More informationDiscrete Markov Process. Introduction. Example: Balls and Urns. Stochastic Automaton. INTRODUCTION TO Machine Learning 3rd Edition
EHEM ALPAYDI he MI Press, 04 Lecure Sldes for IRODUCIO O Machne Learnng 3rd Edon alpaydn@boun.edu.r hp://www.cmpe.boun.edu.r/~ehem/ml3e Sldes from exboo resource page. Slghly eded and wh addonal examples
More informationELASTIC MODULUS ESTIMATION OF CHOPPED CARBON FIBER TAPE REINFORCED THERMOPLASTICS USING THE MONTE CARLO SIMULATION
THE 19 TH INTERNATIONAL ONFERENE ON OMPOSITE MATERIALS ELASTI MODULUS ESTIMATION OF HOPPED ARBON FIBER TAPE REINFORED THERMOPLASTIS USING THE MONTE ARLO SIMULATION Y. Sao 1*, J. Takahash 1, T. Masuo 1,
More informationLecture 9: Dynamic Properties
Shor Course on Molecular Dynamcs Smulaon Lecure 9: Dynamc Properes Professor A. Marn Purdue Unversy Hgh Level Course Oulne 1. MD Bascs. Poenal Energy Funcons 3. Inegraon Algorhms 4. Temperaure Conrol 5.
More informationAdvanced Macroeconomics II: Exchange economy
Advanced Macroeconomcs II: Exchange economy Krzyszof Makarsk 1 Smple deermnsc dynamc model. 1.1 Inroducon Inroducon Smple deermnsc dynamc model. Defnons of equlbrum: Arrow-Debreu Sequenal Recursve Equvalence
More informationPerformance Analysis for a Network having Standby Redundant Unit with Waiting in Repair
TECHNI Inernaonal Journal of Compung Scence Communcaon Technologes VOL.5 NO. July 22 (ISSN 974-3375 erformance nalyss for a Nework havng Sby edundan Un wh ang n epar Jendra Sngh 2 abns orwal 2 Deparmen
More informationAnisotropic Behaviors and Its Application on Sheet Metal Stamping Processes
Ansoropc Behavors and Is Applcaon on Shee Meal Sampng Processes Welong Hu ETA-Engneerng Technology Assocaes, Inc. 33 E. Maple oad, Sue 00 Troy, MI 48083 USA 48-79-300 whu@ea.com Jeanne He ETA-Engneerng
More informationCS286.2 Lecture 14: Quantum de Finetti Theorems II
CS286.2 Lecure 14: Quanum de Fne Theorems II Scrbe: Mara Okounkova 1 Saemen of he heorem Recall he las saemen of he quanum de Fne heorem from he prevous lecure. Theorem 1 Quanum de Fne). Le ρ Dens C 2
More informationA Principled Approach to MILP Modeling
A Prncpled Approach o MILP Modelng John Hooer Carnege Mellon Unvers Augus 008 Slde Proposal MILP modelng s an ar, bu need no be unprncpled. Slde Proposal MILP modelng s an ar, bu need no be unprncpled.
More informationPart II CONTINUOUS TIME STOCHASTIC PROCESSES
Par II CONTINUOUS TIME STOCHASTIC PROCESSES 4 Chaper 4 For an advanced analyss of he properes of he Wener process, see: Revus D and Yor M: Connuous marngales and Brownan Moon Karazas I and Shreve S E:
More informationLearning Objectives. Self Organization Map. Hamming Distance(1/5) Introduction. Hamming Distance(3/5) Hamming Distance(2/5) 15/04/2015
/4/ Learnng Objecves Self Organzaon Map Learnng whou Exaples. Inroducon. MAXNET 3. Cluserng 4. Feaure Map. Self-organzng Feaure Map 6. Concluson 38 Inroducon. Learnng whou exaples. Daa are npu o he syse
More informationDynamic Model of the Axially Moving Viscoelastic Belt System with Tensioner Pulley Yanqi Liu1, a, Hongyu Wang2, b, Dongxing Cao3, c, Xiaoling Gai1, d
Inernaonal Indsral Informacs and Comper Engneerng Conference (IIICEC 5) Dynamc Model of he Aally Movng Vscoelasc Bel Sysem wh Tensoner Plley Yanq L, a, Hongy Wang, b, Dongng Cao, c, Xaolng Ga, d Bejng
More informationGenetic Algorithm in Parameter Estimation of Nonlinear Dynamic Systems
Genec Algorhm n Parameer Esmaon of Nonlnear Dynamc Sysems E. Paeraks manos@egnaa.ee.auh.gr V. Perds perds@vergna.eng.auh.gr Ah. ehagas kehagas@egnaa.ee.auh.gr hp://skron.conrol.ee.auh.gr/kehagas/ndex.hm
More informationSupplementary Material to: IMU Preintegration on Manifold for E cient Visual-Inertial Maximum-a-Posteriori Estimation
Supplemenary Maeral o: IMU Prenegraon on Manfold for E cen Vsual-Ineral Maxmum-a-Poseror Esmaon echncal Repor G-IRIM-CP&R-05-00 Chrsan Forser, Luca Carlone, Fran Dellaer, and Davde Scaramuzza May 0, 05
More informationReactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times
Reacve Mehods o Solve he Berh AllocaonProblem wh Sochasc Arrval and Handlng Tmes Nsh Umang* Mchel Berlare* * TRANSP-OR, Ecole Polyechnque Fédérale de Lausanne Frs Workshop on Large Scale Opmzaon November
More informationThis document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore.
Ths documen s downloaded from DR-NTU, Nanyang Technologcal Unversy Lbrary, Sngapore. Tle A smplfed verb machng algorhm for word paron n vsual speech processng( Acceped verson ) Auhor(s) Foo, Say We; Yong,
More informationMANY real-world applications (e.g. production
Barebones Parcle Swarm for Ineger Programmng Problems Mahamed G. H. Omran, Andres Engelbrech and Ayed Salman Absrac The performance of wo recen varans of Parcle Swarm Opmzaon (PSO) when appled o Ineger
More information