Guaranteed Strategies to Search for Mobile Evaders in the Plane (Draft)

Size: px
Start display at page:

Download "Guaranteed Strategies to Search for Mobile Evaders in the Plane (Draft)"

Transcription

1 Guaraneed Sraegie o Search for Mobile Evader in he Plane (Draf) Timohy G. McGee and J. Karl Hedrick Abrac Thi paper udie everal problem of earch in he wo-dimenional plane for a mobile inruder or evader. In each cae, boh he earcher and evader are aumed o have bounded velociie, wih he velociy of he earcher greaer han ha of he evader. The earcher ha a enor wih a circular fooprin which allow i o deec he evader if i diance i le han he enor radiu. Unlike much of he pa work done in earch heory, he propoed raegie make no aumpion abou he moion of he evader, and are guaraneed o ucceed for any rajecory of he evader. The hree problem formulaion udied include he earch for mobile arge hrough a linear corridor, he earch for or bounding of a mobile arge which ar inide of a circular region, and he prevenion of a mobile arge from enering a circular region. The exenion of he propoed raegie for muliple earcher i alo dicued. I. INTRODUCTION Thi paper udie everal problem of earch in he wo-dimenional plane for a mobile inruder or evader. I i aumed ha he earcher and he evading arge have maximum velociie, and, wih >. No rericion are placed on he maximum urning rae of eiher pary. The earcher i aumed o have a enor wih a circular fooprin of radiu R which will deec he arge if he arge i inide of he enor fooprin. Unlike much of he pa work done in earch heory, he propoed raegie make no aumpion abou he moion of he evader, and are guaraneed o ucceed for any rajecory of he evader. The problem formulaion given, alhough abraced, have poenial applicaion for a wide variey of pracical problem including border and harbor parol, convoy proecion, and earch and recue operaion. The fir problem involve he earch for mobile arge hrough a corridor bounded by parallel line. The econd problem explore how o earch for or rap a mobile arge whoe iniial poiion i known o be wihin a circle of known radiu greaer han he enor radiu. The final problem, which i very imilar o he econd, explore how o creae a perimeer around a fixed poin in he plane in order o preven inruder from approaching he poin wihou being deeced. The major conribuion of hi paper i a raegy for earching he circular region, which i an improvemen o a imilar raegy oulined in [15]. While he proof of opimal raegie i difficul for hee problem, i i argued ha he opimal raegy mu be cloe o he propoed oluion. Thi i done by reducing he Thi work wa uppored by ONR gran #N C-0187, SPO # , and a Berkeley Fellowhip for Mr. McGee T. McGee i a graduae uden in Mechanical Engineering, Univeriy of California, Berkeley, CA 9470, USA mcgee@me.berkeley.edu J.K. Hedrick i a profeor in Mechanical Engineering, Univeriy of California, Berkeley, CA 9470, USA khedrick@me.berkeley.edu earch problem o he impler problem of ravelling around an expanding circle for which he opimal oluion can be found. I i alo hown how hee raegie can be execued by eam of muliple earcher o improve performance. There ha a large amoun of reearch ino earch heory daing back o WWII, including everal book devoed o he opic [7], [], [11]. Many earch problem are alo cloely relaed o game heory [10]. One major group of problem involve he earch for aionary or quai-aionary arge. Baeza-Yae oulined opimal mehod for earching for aionary poin or line in planar grid [6]. Several reearcher have udied opimal rajecorie o compleely cover an area wih a enor or ool wih minimal overlap beween pae [9], [1], [5], [13]. Search problem wih mobile arge can be furher claified by he inenion and informaion of he arge. In he rendezvou earch problem, boh player cooperae o find one anoher [3]. In he helicoper and ubmarine problem, fir propoed by Dankin [8], a helicoper earche for an evading ubmarine ha doe no know he poiion of he earcher. Several oher reearcher have udied he ame problem [18], [16], [19]. Anoher udy examine guaraneed earch raegie for an evader in an complex encloed workpace by a earcher wih a line of igh enor [1]. More recenly, earch wih eam of cooperaing agen ha become an acive reearch opic [14], [17], [4]. II. SEARCH OF A CORRIDOR The fir planar earch problem conidered i he parol of a corridor beween parallel border eparaed by widh W. Thi problem wa olved by Koopman [11] in he 1940 in order o deermine opimal parol raegie for aircraf earching for hip in a channel. I i reviewed here ince he concep ued o olve hi problem are laer hown o be applicable o more difficul earch problem in he plane. The corridor earch problem aume ha a he iniial ime, he e of all poible poiion of he arge, which we hall refer o a he arge e, i he area o one ide of a line perpendicular o he border of he corridor. The earcher begin on one of he corridor border wih i circular enor angen o he boundary of he arge e a hown in Fig. 1a. Since he evader i mobile, he arge e grow normal o i boundary a he maximum velociy of he evader,. Thu, in order o keep i enor angen o he border of he arge e, he earcher mu ravel a an angle o he normal of he arge e (Fig. 1b), where i calculaed a: V = arcin (1)

2 V problem could have applicaion for embargoe, parolling jail perimeer, or earch for mobile arge. Auming he arge i iniially inide a circle of radiu R o, and he earcher i ouide of hi circle wih i enor angen o arge e, we explore how he earcher hould ravel o guaranee ha he arge e i bounded for he large poible iniial circle wih radiu R o. For all circle maller han hi, he bounding raegy hould alo provide a mehod o hrink he area arge e o zero in order o guaranee capure. Thi i analogou o he advancing barrier for he channel parol problem. Fig. 1. V Corridor Parol Sraegy. By following hi raegy, when he earcher reache he oppoie border, he boundary of he arge e i ill a line perpendicular o he border, alhough he earcher i now ouide of he arge e (Fig. 1c). The earcher nex ravel parallel o he border unil i i again over he arge e, and i enor i angen o he boundary of he arge e (Fig. 1d). The earcher hen repea he ame maneuver o reurn o he oppoie border, compleing one cycle of he maneuver. The ime required for he earcher o complee each half cycle, 1, i he um of he ime required o cro he corridor and he ime o ravel up he border. 1 = W co () + R + = W V + R + () If he ravel ime of he earcher for each half cycle i equal o he ime required for he evader o ravel he widh of he earch enor, he boundary of he arge e a he beginning of each half cycle will remain aionary. W + R = R (3) V V + Koopman referred o hi cae a a ymmeric barrier. Solving for he widh of he corridor in hi cae give he maximum widh of a corridor ha can be parolled: 1 1 V W = R V + V (4) If he corridor widh i larger han W, he ize of he arge e will grow afer each cycle, and i canno be guaraneed ha he arge will be deeced. If he widh i le han W, he arge e will hrink, allowing i o be earched. Koopman called hee cae rereaing elemen barrier and advancing elemen barrier repecively. III. CIRCULAR BARRIERS AGAINST FLEEING EVADERS Anoher problem o conider i how o earch for or bound an evader ha ar wihin a known circular region. Thi A. Upper Bound for R o Since he opimal oluion for he guaraneed earch of an expanding dik i unknown [7], a good fir ep o exploring hi problem i o e bound on R o. One uch bound can be found by auming ha he earcher can apply i maximum earch rae arbirarily in he plane. For he problem under conideraion, he maximum earch rae i he produc of he earch velociy, and he widh of he enor, R. The growh rae of he arge e can be calculaed a he produc of i perimeer, πr o, and he velociy of he arge,. The maximum radiu of he arge e for hi unconrained problem, which ac a an upper bound for our problem, can hen be found by eing he earch rae equal o he growh rae of he arge e. B. Circular Search Paern R o R π (5) One imple raegy o bound an evader, which ha been offered by everal reearcher [11], [16], i o ravel a imple circular paern. Boh of hee udie calculae he large circle ha can be bounded uing a circular paern o be: R o = R ( /π 1) (6) Thi equaion i found by eing he ime for he earcher o ravel around hi circle π(r o + R )/ o be equal o he ime i ake he evader o ravel acro he diameer of he earch enor R /. One limiaion of hi calculaion, however, i ha i aume ha he evader i ravelling radially from he cener of he circle. The opimal pah of he evader i acually o ravel a a ligh angle, γ op o he radiu of he circle a illuraed in Fig.. Thi opimal angle γ op Fig.. Searcher Pah γ op Evader Pah Opimal Evaion Sraegy Again Circular Search Pah.

3 can be calculaed by maximizing he quaniy dr /dθ rel : dr dθ rel = R θ p θ = co (γ) /R p in (γ)/r (7) where R i he radiu of he evading arge, R p i he radiu of he earcher, and θ rel i he relaive angle beween he earcher and evader. The opimal choice of γ o maximize dr /dθ rel i: V R p γ op = arcin (8) R Alhough ravelling a γ op reduce he radial velociy of he arge, i force he earcher o ravel more han a full circle o cach he arge. Thu if he evader follow he pah pecified by Eq. 8, i can ecape he circle defined by Eq. 6. Alhough he circular earch pah i imple, i i no opimal, and i doen lend ielf o a mehod of reducing he arge e for R o < Ro. C. Propoed Paern o Search Expanding Dik The goal of he earch of he expanding dik problem can be reexpreed a he reducion of he area of he arge e, A T S, o zero in he minimum ime. Since an analyical oluion o hi problem i difficul becaue of he parial informaion of he evader poiion, an approach i aken o develop a raegy baed on inigh from imilar problem. Since inuiion can ofen be wrong, he performance of he developed raegy i compared again he heoreical bound on he opimal raegy in Eq. 6. Fir, we explore he inananeou rae of change of he arge e area which can be calculaed a he difference beween he growh rae of he arge e reuling from poible arge moion and he reducion of he arge e area by he moion of he earcher: A T S = P T S L S (9) where P T S i he perimeer of he arge e and L S i he widh of he enor fooprin perpendicular o he velociy of he earcher ha i over he arge e. The maximum value of L S i he widh of he enor, R. While minimizing A T S i difficul becaue P T S and L S are complicaed funcion of he choen rajecory, everal imporan properie for a well deigned raegy can be inferred from Eq. 9. Propery 1: The well deigned earch raegy hould ravel along he perimeer of he arge e. In order o minimize he value of A T S, he earch raegy hould alo minimize he perimeer of he arge e, P T S. If he earcher were o ravel ino he arge e a oppoed o along he perimeer, i would creae a channel ha would grealy increae he perimeer of he arge e. Thi propery eliminae divide and conquer ype raegie from being conidered for earch of he circle. Propery : The arge e hould remain near circular when he well deigned earch raegy i applied. For any given planar area, he hape encloing ha area wih he malle perimeer i he circle. Thu earch raegie ha preerve he circular hape of he arge e will be uperior o hoe ha do no. Thi propery eliminae raegie uch a line weep from being conidered. Fig. 3. θ = 0 Minimum lengh pah around expanding circle. Propery 3: The ouer edge of he earch enor hould be angen o he boundary of he arge e during mo of he well deigned earch. From Propery 1, i wa found ha he earcher hould ravel along he perimeer of he arge e. If he earch enor i angen o he boundary of he arge e, L S will equal i maximum value. In order o develop a earch raegy which accoun for he above properie, we conider a implified problem. Conider a mobile agen, ravelling a a conan peed,, ha mu ravel around an expanding circle in he plane. The radiu of he circle expand linearly in ime a a rae of. A he iniial ime, he agen i a θ = 0, and i diance from he cener of he circle i greaer han he iniial radiu of he circle. The minimum lengh (and hu ime) pah ha he agen can ake o ravel around he expanding circle i o fir ravel a raigh line ha will inerec he expanding circle angenially and hen o ravel along he perimeer of he expanding circle. Thi pah i illuraed in Fig. 3. The oluion o hi implified problem can be lighly modified o produce he improved earch mehod, illuraed in Fig. 4. Thi earch raegy coni of alernaing raigh line and ouward piral maneuver of he earcher, which reul from a ingle rule ha govern he velociy direcion of he earcher. A he iniial ime, he earcher begin ouide of he arge e wih i enor radiu angen o he circular arge e. From hi poin forward, a each inance in ime, a line i drawn which i angen o boh he earch enor and he ouide of he arge e, a hown by he doed line in Fig. 4a. The earcher hen ravel a an angle o hi line, which i he ame lead angle calculaed in Eq. 1. During he fir porion of he earch, hi produce a linear moion of he earcher. Once he ouide of he enor fooprin become angen o he circular porion of he arge e (Fig. 4b), he angen line o he earch enor and he arge e i angen o boh a he ame poin. A he earcher coninue o ravel a a lead angle o hi angen line, i will ravel along an ouward piral uch ha he radial velociy of he earcher i equal o he arge velociy: R p = in () = (10) θ p = V co () V = (11) R p R p where R p and θ p are he radiu and angle of he earcher wih repec o he cener of he arge e.

4 A D R 3 B R 1 R C Fig. 5. Secion of arge e. P * P * Fig. 4. Propoed paern. Fig. 6. Marginal improvemen o raegy. The earcher coninue hi piral maneuver (Fig. 4c) unil i reache he mall arc which connec he circular and linear porion of he arge e (Fig. 4d). A hi poin, he earch ravel along a maller ouward piral uing he ame lead angle raegy. Following he earch raegy decribed above will produce a arge e whoe perimeer can be divided ino four ecion a hown in Fig. 5. The fir ecion, A-B, i a linear ecion. The econd ecion of he perimeer, B-C, define he arc of a circle whoe radiu, (R 1 ), i equal o he radiu of he earcher minu he enor radiu. The hird ecion of he perimeer, C-D, define he arc of a circle whoe radiu, (R ), i equal o he radiu of he earcher plu he enor radiu. The final ecion of he perimeer, D-A, i he arc of a maller circle which connec he linear ecion, A-B, and he larger circle, C- D. During he iniial age of a earch, while he arge e i large enough, he radiu of he D-A ecion, R 3, will be greaer han he radiu of he earch enor, R, when he earcher reache hi ecion of he perimeer. During hee cae, he ouide of he earch enor will alway be angen o he edge of he arge e and he earch pah will be differeniable. When he arge e ge maller however, he earch enor will compleely cover he D-A ecion of he perimeer. In hee cae, he rule decribed above will produce a harp change in he direcion of he earcher. When hi condiion occur, here i a modificaion o he earch raegy ha can lighly improve performance. The diameer of he enor which i perpendicular he line angen o he enor and arge e can be ued o define he poin P a illuraed in Fig. 6a. Whenever hi poin P i ouide he arge e, he earcher can improve performance by ravelling radially inward oward he cener of he arge e unil P ouche he arge e (Fig. 6b). Thi modificaion can alo be ued a he beginning of he earch effor (Fig. 4a). Alhough hi modificaion can provide a mall improvemen, i complicae he moion and will no conidered when calculaing he performance of he propoed mehod. In order o deermine he large iniial radiu of he arge e ha can be bounded, Ro, uing he propoed paern, i aumed ha R 3 in Fig. 5 i equal o zero. Thi conervaive aumpion reul in a lighly maller R o han i acually achievable, alhough i grealy implifie he calculaion. The pah of he earcher can now be divided ino wo porion: he raigh ecion and he ouward piral. Conider he ime,, required by he earcher o ravel he raigh porion of he earch, auming he earcher ar a R o + R. Thi ime can be calculaed a: = R o R co = R o R V (1) Thi ime i he raio of he diance R o R, hown in Fig. 7, o he velociy of he earcher parallel o hi line egmen. The radiu of he earcher immediaely afer ravelling he raigh maneuver, R p, can be calculaed: R p = R o R + (13) The radiu of he earcher afer he piral maneuver can hen be calculaed by inegraing Eq. 10 and 11 : (θ f β) R p (θ f ) = R p exp V (14) where θ f = π in he cae of a ingle earcher, and β, illuraed in Fig 7, i he angle of he arge e ravered during he raigh maneuver: Ro R β = co 1 (15) R o + R

5 R o R β R o +R R o R Fig. 7. Calculaing lengh of raigh ecion. The radiu of he large boundable circle, uing he propoed piral earch can hen be calculaed by enforcing ha he earcher finihe a cycle of he earch where i ared: R (θ f ) = R o + R. (16) Combining Eq yield an expreion ha can be olved for R o: (R o R + R or R o + R = V ( ) (θ f co 1 ((R o R )/(R o + R ))) exp (17) V For = 0, = 1, and R = 100, a circular paern can bound R o = 536, while he propoed raegy can bound R o = 65. The heoreical upper bound from Eq. 6 i 636. IV. CIRCULAR BARRIERS AGAINST INTRUDERS The hird problem conidered i how o preven an inruder from enering a circular region wihou being deeced. Thi problem i eenially he revere of he circular barrier problem decribed above. Auming he arge i iniially ouide he circle R o, and he earcher i inide of hi circle wih i enor angen o R o, we explore how he earcher hould ravel o guaranee ha he inruder minimum diance from he cener of he circle i bounded. The goal i o find a raegy o guaranee bounding for he large iniial circle Ro. For all circle maller han hi, he bounding raegy hould alo provide a mehod o expand he cleared area o i maximum. The raegy of Secion III can be revered o expand he cleared area. Thi i done by defining he lead angle oward he cener of he cleared region, which produce inward piral raher han ouward piral. Thi raegy i illuraed in Fig.8. The applicaion of hi raegy will reul in a able final rajecory, analogou o a able limi cycle, around he cleared area. For large iniial radii of he cleared area, R o, he cleared area will hrink ince he earcher canno clear he perimeer fa enough. For mall iniial radii of he cleared area, he cleared area will be enlarged ince he earcher can clear area faer han he poible invader moion fill i in. Thi exience of a able final rajecory i differen from he unable rajecorie of III. When earching for a arge on he inide of an expanding circular region, if R o i larger han Ro, he arge e will ) Fig. 8. Propoed paern for inruder. increae indefiniely, while if R o i maller han Ro, he arge e will hrink o zero area. Thi i analogou o an unable limi cycle. V. MULTIPLE SEARCHERS The raegie decribed above can be eaily exended o muliple earcher. For he earch of he corridor [11], muliple earcher can ravel abrea, effecively increaing he widh of he earch enor. Unlike he corridor cae, for he earch of he expanding or collaping circular region, muliple earcher canno ravel abrea unle hey are able o vary heir velociie o ha heir angular velociie around he perimeer are equal. Conidering he earch of he expanding circle for muliple earcher, Eq. 9 become: A T S = P T S n L S i (18) where, n i he number of earcher. Thi ugge ha he ame hree properie oulined in Secion III for a ingle earch apply o he muliple earcher cae. If he muliple earcher are equally paced around he perimeer of he arge e, he implified problem of ravering an expanding circle for a ingle earcher hown in Fig. 3 can be modified o find he opimal pah for a ingle earcher o ravel from θ = 0 wih repec o he expanding circle o θ = π/n. Thu, he ame conrol law from he ingle vehicle cae i direcly applicable o he muliple vehicle cae. Thi raegy will produce a arge e hape imilar o Fig. 5, only inead of a ingle raigh line ecion, here will be a raigh line for each earcher. Thi i illuraed in Fig. 9 which illurae hree earcher in he expanding circle cae. In order o calculae R o for muliple earcher, Eq. 14 can be modified by eing θ f = π/n. Thi impoe he conrain ha each earcher will finih he cycle where he earcher in fron of i ared. In order o furher udy he effec of i=1

6 VI. CONCLUSIONS Guaraneed raegie for everal problem of earch in he wo-dimenional plane for a mobile inruder or evader have been preened. The propoed raegie make no aumpion abou he moion of he evader, and guaranee ha he earcher will ravel wihin enor range of he evader for any rajecory of he evader. The hree problem formulaion udied include he earch for mobile arge hrough a channel bounded by parallel line, he earch for or bounding of a mobile arge which ar inide of a circular region, and he prevenion of a mobile arge from enering a circular region. While no opimaliy proof for earch of he circular region exi, he propoed raegie are hown o perform cloe o a heoreical bound on he problem. The applicaion of he raegy for muliple earcher i alo preened. κ(n) Fig Fig. 10. Search wih muliple earcher Number of Searcher Cooperaion gain, κ for muliple earcher. cooperaing earcher, we define a cooperaion gain, κ(n): κ(n) = R o(n) nr o(1) (19) where R o(n) i he maximum boundable radiu wih n earcher. Figure 10 illurae, ha κ(n) i monoonically increaing ignifying ha n earcher can bound a circle wih a radiu greaer han n ime he radiu ha can be bound by a ingle earcher. Furher, a n increae, κ(n) approache he raio of he heoreical upper bound in Eq. 6 o R o(1): lim n κ(n) = R [R πv o(1)] 1 (0) Thu, a he number of earcher increae,he maximum boundable radiu approache he heoreical upper bound. I hould alo be noed ha ince he radiu of he maximum boundable circle i roughly proporional o he number of earcher, he maximum boundable area i roughly proporional o he quare of he number of earcher. REFERENCES [1] V. Ablavky and M. Snorraon, Opimal earch for a moving arge: A geomeric approach, in AIAA Guidance, Navigaion, and Conrol Conference and Exhibi, 000. [] S. Alpern and S. Gal, The Theory of Search Game and Rendezvou. Boon, Maachue: Kluwer Academic Publiher, 003. [3] E. Anderon and S. Fekee, Two dimenional rendezvou earch, Operaion Reearch, vol. 49, 001. [4] A. Anoniade, H. J. Kim, and S. Sary, Purui-evaion raegie for eam of muliple agen wih incomplee informaion, in Proceeding of he 4nd IEEE Conference on Deciion and Conrol, 003. [5] E. M. Arkin, S. P. Fekee, and J. S. Michell, Approximaion algorihm for lawn mowing and milling, Compuaional Geomery, vol. 17, 000. [6] R. A. Baeza-Yae, J. C. Culberon, and G. J. Rawlin, Searching in he plane, Informaion and Compuaion, vol. 106, [7] D. Chudnovky and G. C. (ed), Search Theory: Some Recen Developmen. New York, New York: Marcel Dekker, [8] J. M. Dankin, A helicoper veru ubmarine earch game, Operaion Reearch, vol. 16, [9] W. H. Huang, Opimal line-weep-baed decompoiion for coverage algorihm, in Proceeding of he 001 IEEE Inernaional Conference on Roboic and Auomaion, 001. [10] R. Iaac, Differenial Game. Mineola, New York: Dover Publicaion, [11] B. Koopman, Search and Screening: General Principle wih Hiorical Applicaion. New York, New York: Pergamon Pre, [1] S. LaValle, D. Lin, L. Guiba, J. Laombe, and R. Mowani, Finding an unpredicable arge in a workpace wih obacle, in Proc. of he IEEE Inernaional Conference on Roboic and Auomaion, [13] B. M. More, M. Collin, J. Saia, and L. Yu, Ice rink and cruie mile: Sweeking a imple polygon, in Proceeding of he 1 Workhop of Algorihm Engineering, [14] M. M. Polycarpou, Y. Yang, and K. M. Paino, A cooperaive earch framework for diribued agen, in Proceeding of he IEEE Inernaional Sympoium on Inelligen Conrol, 001. [15] I. Shevchenko, Succeive purui wih a bounded deecion domain, Journal of Opimizaion Theory and Applicaion, vol. 95, [16] L. Thoma and A. Wahburn, Dynamic earch game, Operaion Reearch, vol. 39, [17] R. Vidal, O. Shakernia, H. J. Kim, D. H. Shim, and S. Sary, Probabaliic purui-evaion game: Thoery, implemenaion, and experimenal evaluaion, IEEE Tranacion on Roboic and Auomaion, vol. 18, 00. [18] A. Wahburn and R. Hohzaki, The dieel ubmarine flaming daum problem, Miliary Operaion Reearch, vol. 6, 001. [19] A. R. Wahburn, Search-evaion game in a fixed region, Operaion Reearch, vol. 8, 1980.

13.1 Accelerating Objects

13.1 Accelerating Objects 13.1 Acceleraing Objec A you learned in Chaper 12, when you are ravelling a a conan peed in a raigh line, you have uniform moion. However, mo objec do no ravel a conan peed in a raigh line o hey do no

More information

Introduction to Congestion Games

Introduction to Congestion Games Algorihmic Game Theory, Summer 2017 Inroducion o Congeion Game Lecure 1 (5 page) Inrucor: Thoma Keelheim In hi lecure, we ge o know congeion game, which will be our running example for many concep in game

More information

Discussion Session 2 Constant Acceleration/Relative Motion Week 03

Discussion 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 information

Angular Motion, Speed and Velocity

Angular 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 information

Physics 240: Worksheet 16 Name

Physics 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 information

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship

To 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 information

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V ME 352 VETS 2. VETS Vecor algebra form he mahemaical foundaion for kinemaic and dnamic. Geomer of moion i a he hear of boh he kinemaic and dnamic of mechanical em. Vecor anali i he imehonored ool for decribing

More information

CHAPTER 7: SECOND-ORDER CIRCUITS

CHAPTER 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 information

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow.

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow. CSE 202: Deign and Analyi of Algorihm Winer 2013 Problem Se 3 Inrucor: Kamalika Chaudhuri Due on: Tue. Feb 26, 2013 Inrucion For your proof, you may ue any lower bound, algorihm or daa rucure from he ex

More information

1 Motivation and Basic Definitions

1 Motivation and Basic Definitions CSCE : Deign and Analyi of Algorihm Noe on Max Flow Fall 20 (Baed on he preenaion in Chaper 26 of Inroducion o Algorihm, 3rd Ed. by Cormen, Leieron, Rive and Sein.) Moivaion and Baic Definiion Conider

More information

arxiv: v1 [cs.cg] 21 Mar 2013

arxiv: v1 [cs.cg] 21 Mar 2013 On he rech facor of he Thea-4 graph Lui Barba Proenji Boe Jean-Lou De Carufel André van Renen Sander Verdoncho arxiv:1303.5473v1 [c.cg] 21 Mar 2013 Abrac In hi paper we how ha he θ-graph wih 4 cone ha

More information

6.8 Laplace Transform: General Formulas

6.8 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 information

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method ME 352 GRHICL VELCITY NLYSIS 52 GRHICL VELCITY NLYSIS olygon Mehod Velociy analyi form he hear of kinemaic and dynamic of mechanical yem Velociy analyi i uually performed following a poiion analyi; ie,

More information

Motion In One Dimension. Graphing Constant Speed

Motion 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 information

TP B.2 Rolling resistance, spin resistance, and "ball turn"

TP 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 information

Notes on cointegration of real interest rates and real exchange rates. ρ (2)

Notes 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 information

Randomized Perfect Bipartite Matching

Randomized Perfect Bipartite Matching Inenive Algorihm Lecure 24 Randomized Perfec Biparie Maching Lecurer: Daniel A. Spielman April 9, 208 24. Inroducion We explain a randomized algorihm by Ahih Goel, Michael Kapralov and Sanjeev Khanna for

More information

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2)

Laplace 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 information

Buckling of a structure means failure due to excessive displacements (loss of structural stiffness), and/or

Buckling of a structure means failure due to excessive displacements (loss of structural stiffness), and/or Buckling Buckling of a rucure mean failure due o exceive diplacemen (lo of rucural iffne), and/or lo of abiliy of an equilibrium configuraion of he rucure The rule of humb i ha buckling i conidered a mode

More information

ARTIFICIAL INTELLIGENCE. Markov decision processes

ARTIFICIAL INTELLIGENCE. Markov decision processes INFOB2KI 2017-2018 Urech Univeriy The Neherland ARTIFICIAL INTELLIGENCE Markov deciion procee Lecurer: Silja Renooij Thee lide are par of he INFOB2KI Coure Noe available from www.c.uu.nl/doc/vakken/b2ki/chema.hml

More information

ANALYSIS OF SOME SAFETY ASSESSMENT STANDARD ON GROUNDING SYSTEMS

ANALYSIS OF SOME SAFETY ASSESSMENT STANDARD ON GROUNDING SYSTEMS ANAYSIS OF SOME SAFETY ASSESSMENT STANDARD ON GROUNDING SYSTEMS Shang iqun, Zhang Yan, Cheng Gang School of Elecrical and Conrol Engineering, Xi an Univeriy of Science & Technology, 710054, Xi an, China,

More information

Main Reference: Sections in CLRS.

Main Reference: Sections in CLRS. Maximum Flow Reied 09/09/200 Main Reference: Secion 26.-26. in CLRS. Inroducion Definiion Muli-Source Muli-Sink The Ford-Fulkeron Mehod Reidual Nework Augmening Pah The Max-Flow Min-Cu Theorem The Edmond-Karp

More information

CSC 364S Notes University of Toronto, Spring, The networks we will consider are directed graphs, where each edge has associated with it

CSC 364S Notes University of Toronto, Spring, The networks we will consider are directed graphs, where each edge has associated with it CSC 36S Noe Univeriy of Torono, Spring, 2003 Flow Algorihm The nework we will conider are direced graph, where each edge ha aociaed wih i a nonnegaive capaciy. The inuiion i ha if edge (u; v) ha capaciy

More information

Chapter 7: Inverse-Response Systems

Chapter 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 information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

NEUTRON DIFFUSION THEORY

NEUTRON DIFFUSION THEORY NEUTRON DIFFUSION THEORY M. Ragheb 4//7. INTRODUCTION The diffuion heory model of neuron ranpor play a crucial role in reacor heory ince i i imple enough o allow cienific inigh, and i i ufficienly realiic

More information

Algorithmic Discrete Mathematics 6. Exercise Sheet

Algorithmic 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 information

Network Flows: Introduction & Maximum Flow

Network Flows: Introduction & Maximum Flow CSC 373 - lgorihm Deign, nalyi, and Complexiy Summer 2016 Lalla Mouaadid Nework Flow: Inroducion & Maximum Flow We now urn our aenion o anoher powerful algorihmic echnique: Local Search. In a local earch

More information

CS4445/9544 Analysis of Algorithms II Solution for Assignment 1

CS4445/9544 Analysis of Algorithms II Solution for Assignment 1 Conider he following flow nework CS444/944 Analyi of Algorihm II Soluion for Aignmen (0 mark) In he following nework a minimum cu ha capaciy 0 Eiher prove ha hi aemen i rue, or how ha i i fale Uing he

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

, 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 information

Stability in Distribution for Backward Uncertain Differential Equation

Stability 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 information

EECE 301 Signals & Systems Prof. Mark Fowler

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

More information

KINEMATICS IN ONE DIMENSION

KINEMATICS IN ONE DIMENSION KINEMATICS IN ONE DIMENSION PREVIEW Kinemaics is he sudy of how hings move how far (disance and displacemen), how fas (speed and velociy), and how fas ha how fas changes (acceleraion). We say ha an objec

More information

Rectilinear Kinematics

Rectilinear Kinematics Recilinear Kinemaic Coninuou Moion Sir Iaac Newon Leonard Euler Oeriew Kinemaic Coninuou Moion Erraic Moion Michael Schumacher. 7-ime Formula 1 World Champion Kinemaic The objecie of kinemaic i o characerize

More information

EF 151 Exam #1, Spring, 2009 Page 1 of 6

EF 151 Exam #1, Spring, 2009 Page 1 of 6 EF 5 Exam #, Spring, 009 Page of 6 Name: Guideline: Aume 3 ignifican figure for all given number unle oherwie aed Show all of your work no work, no credi Wrie your final anwer in he box provided Include

More information

15. Vector Valued Functions

15. Vector Valued Functions 1. Vecor Valued Funcions Up o his poin, we have presened vecors wih consan componens, for example, 1, and,,4. However, we can allow he componens of a vecor o be funcions of a common variable. For example,

More information

Exponential Sawtooth

Exponential Sawtooth ECPE 36 HOMEWORK 3: PROPERTIES OF THE FOURIER TRANSFORM SOLUTION. Exponenial Sawooh: The eaie way o do hi problem i o look a he Fourier ranform of a ingle exponenial funcion, () = exp( )u(). From he able

More information

EE202 Circuit Theory II

EE202 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 information

u(t) Figure 1. Open loop control system

u(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 information

Performance Comparison of LCMV-based Space-time 2D Array and Ambiguity Problem

Performance Comparison of LCMV-based Space-time 2D Array and Ambiguity Problem Inernaional journal of cience Commerce and umaniie Volume No 2 No 3 April 204 Performance Comparion of LCMV-baed pace-ime 2D Arra and Ambigui Problem 2 o uan Chang and Jin hinghia Deparmen of Communicaion

More information

CS 473G Lecture 15: Max-Flow Algorithms and Applications Fall 2005

CS 473G Lecture 15: Max-Flow Algorithms and Applications Fall 2005 CS 473G Lecure 1: Max-Flow Algorihm and Applicaion Fall 200 1 Max-Flow Algorihm and Applicaion (November 1) 1.1 Recap Fix a direced graph G = (V, E) ha doe no conain boh an edge u v and i reveral v u,

More information

Introduction to SLE Lecture Notes

Introduction 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 information

In this chapter the model of free motion under gravity is extended to objects projected at an angle. When you have completed it, you should

In this chapter the model of free motion under gravity is extended to objects projected at an angle. When you have completed it, you should Cambridge Universiy Press 978--36-60033-7 Cambridge Inernaional AS and A Level Mahemaics: Mechanics Coursebook Excerp More Informaion Chaper The moion of projeciles In his chaper he model of free moion

More information

Graphs III - Network Flow

Graphs III - Network Flow Graph III - Nework Flow Flow nework eup graph G=(V,E) edge capaciy w(u,v) 0 - if edge doe no exi, hen w(u,v)=0 pecial verice: ource verex ; ink verex - no edge ino and no edge ou of Aume every verex v

More information

Linear Motion, Speed & Velocity

Linear 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 information

1. VELOCITY AND ACCELERATION

1. VELOCITY AND ACCELERATION 1. VELOCITY AND ACCELERATION 1.1 Kinemaics Equaions s = u + 1 a and s = v 1 a s = 1 (u + v) v = u + as 1. Displacemen-Time Graph Gradien = speed 1.3 Velociy-Time Graph Gradien = acceleraion Area under

More information

The Residual Graph. 12 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm

The Residual Graph. 12 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm Augmening Pah Algorihm Greedy-algorihm: ar wih f (e) = everywhere find an - pah wih f (e) < c(e) on every edge augmen flow along he pah repea a long a poible The Reidual Graph From he graph G = (V, E,

More information

Selfish Routing and the Price of Anarchy. Tim Roughgarden Cornell University

Selfish Routing and the Price of Anarchy. Tim Roughgarden Cornell University Selfih Rouing and he Price of Anarchy Tim Roughgarden Cornell Univeriy 1 Algorihm for Self-Inereed Agen Our focu: problem in which muliple agen (people, compuer, ec.) inerac Moivaion: he Inerne decenralized

More information

Please Complete Course Survey. CMPSCI 311: Introduction to Algorithms. Approximation Algorithms. Coping With NP-Completeness. Greedy Vertex Cover

Please Complete Course Survey. CMPSCI 311: Introduction to Algorithms. Approximation Algorithms. Coping With NP-Completeness. Greedy Vertex Cover Pleae Complee Coure Survey CMPSCI : Inroducion o Algorihm Dealing wih NP-Compleene Dan Sheldon hp: //owl.oi.uma.edu/parner/coureevalsurvey/uma/ Univeriy of Maachue Slide Adaped from Kevin Wayne La Compiled:

More information

18 Extensions of Maximum Flow

18 Extensions of Maximum Flow Who are you?" aid Lunkwill, riing angrily from hi ea. Wha do you wan?" I am Majikhie!" announced he older one. And I demand ha I am Vroomfondel!" houed he younger one. Majikhie urned on Vroomfondel. I

More information

How to Solve System Dynamic s Problems

How 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 information

Additional Methods for Solving DSGE Models

Additional Methods for Solving DSGE Models Addiional Mehod for Solving DSGE Model Karel Meren, Cornell Univeriy Reference King, R. G., Ploer, C. I. & Rebelo, S. T. (1988), Producion, growh and buine cycle: I. he baic neoclaical model, Journal of

More information

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still. Lecure - Kinemaics in One Dimension Displacemen, Velociy and Acceleraion Everyhing in he world is moving. Nohing says sill. Moion occurs a all scales of he universe, saring from he moion of elecrons in

More information

IB Physics Kinematics Worksheet

IB Physics Kinematics Worksheet IB Physics Kinemaics Workshee Wrie full soluions and noes for muliple choice answers. Do no use a calculaor for muliple choice answers. 1. Which of he following is a correc definiion of average acceleraion?

More information

16 Max-Flow Algorithms and Applications

16 Max-Flow Algorithms and Applications Algorihm A proce canno be underood by opping i. Underanding mu move wih he flow of he proce, mu join i and flow wih i. The Fir Law of Mena, in Frank Herber Dune (196) There a difference beween knowing

More information

Vehicle Arrival Models : Headway

Vehicle Arrival Models : Headway Chaper 12 Vehicle Arrival Models : Headway 12.1 Inroducion Modelling arrival of vehicle a secion of road is an imporan sep in raffic flow modelling. I has imporan applicaion in raffic flow simulaion where

More information

Admin MAX FLOW APPLICATIONS. Flow graph/networks. Flow constraints 4/30/13. CS lunch today Grading. in-flow = out-flow for every vertex (except s, t)

Admin MAX FLOW APPLICATIONS. Flow graph/networks. Flow constraints 4/30/13. CS lunch today Grading. in-flow = out-flow for every vertex (except s, t) /0/ dmin lunch oday rading MX LOW PPLIION 0, pring avid Kauchak low graph/nework low nework direced, weighed graph (V, ) poiive edge weigh indicaing he capaciy (generally, aume ineger) conain a ingle ource

More information

EE Control Systems LECTURE 2

EE Control Systems LECTURE 2 Copyrigh F.L. Lewi 999 All righ reerved EE 434 - Conrol Syem LECTURE REVIEW OF LAPLACE TRANSFORM LAPLACE TRANSFORM The Laplace ranform i very ueful in analyi and deign for yem ha are linear and ime-invarian

More information

Selfish Routing. Tim Roughgarden Cornell University. Includes joint work with Éva Tardos

Selfish Routing. Tim Roughgarden Cornell University. Includes joint work with Éva Tardos Selfih Rouing Tim Roughgarden Cornell Univeriy Include join work wih Éva Tardo 1 Which roue would you chooe? Example: one uni of raffic (e.g., car) wan o go from o delay = 1 hour (no congeion effec) long

More information

The Residual Graph. 11 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm

The Residual Graph. 11 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm Augmening Pah Algorihm Greedy-algorihm: ar wih f (e) = everywhere find an - pah wih f (e) < c(e) on every edge augmen flow along he pah repea a long a poible The Reidual Graph From he graph G = (V, E,

More information

Path Planning on Grids: The Effect of Vertex Placement on Path Length

Path Planning on Grids: The Effect of Vertex Placement on Path Length Proceeding, The Elevenh AAAI Conference on Arificial Inelligence and Ineracive Digial Enerainmen (AIIDE-15) Pah Planning on Grid: The Effec of Verex Placemen on Pah Lengh Jame Bailey Craig Tovey School

More information

Geometric Path Problems with Violations

Geometric Path Problems with Violations Click here o view linked Reference 1 1 1 0 1 0 1 0 1 0 1 Geomeric Pah Problem wih Violaion Anil Mahehwari 1, Subha C. Nandy, Drimi Paanayak, Saanka Roy and Michiel Smid 1 1 School of Compuer Science, Carleon

More information

EF 151 Exam #2 - Spring, 2014 Page 1 of 6

EF 151 Exam #2 - Spring, 2014 Page 1 of 6 EF 5 Exam # - Spring, 04 Page of 6 Name: Secion: Inrucion: Pu your name and ecion on he exam. Do no open he e unil you are old o do o. Wrie your final anwer in he box proided If you finih wih le han 5

More information

Final Spring 2007

Final Spring 2007 .615 Final Spring 7 Overview The purpose of he final exam is o calculae he MHD β limi in a high-bea oroidal okamak agains he dangerous n = 1 exernal ballooning-kink mode. Effecively, his corresponds o

More information

An Inventory Replenishment Model for Deteriorating Items with Time-varying Demand and Shortages using Genetic Algorithm

An Inventory Replenishment Model for Deteriorating Items with Time-varying Demand and Shortages using Genetic Algorithm An Invenory Replenihmen odel for Deerioraing Iem wih ime-varying Demand and Shorage uing Geneic Algorihm An Invenory Replenihmen odel for Deerioraing Iem wih ime-varying Demand and Shorage uing Geneic

More information

Lecture 21: Bezier Approximation and de Casteljau s Algorithm. and thou shalt be near unto me Genesis 45:10

Lecture 21: Bezier Approximation and de Casteljau s Algorithm. and thou shalt be near unto me Genesis 45:10 Lecure 2: Bezier Approximaion and de Caeljau Algorihm and hou hal be near uno me Genei 45:0. Inroducion In Lecure 20, we ued inerpolaion o pecify hape. Bu inerpolaion i no alway a good way o decribe he

More information

Random Walk with Anti-Correlated Steps

Random Walk with Anti-Correlated Steps Random Walk wih Ani-Correlaed Seps John Noga Dirk Wagner 2 Absrac We conjecure he expeced value of random walks wih ani-correlaed seps o be exacly. We suppor his conjecure wih 2 plausibiliy argumens and

More information

Classification of 3-Dimensional Complex Diassociative Algebras

Classification of 3-Dimensional Complex Diassociative Algebras Malayian Journal of Mahemaical Science 4 () 41-54 (010) Claificaion of -Dimenional Complex Diaociaive Algebra 1 Irom M. Rihiboev, Iamiddin S. Rahimov and Wiriany Bari 1,, Iniue for Mahemaical Reearch,,

More information

What is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models

What is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models Wha i maximum Likelihood? Hiory Feaure of ML mehod Tool ued Advanage Diadvanage Evoluionary model Maximum likelihood mehod creae all he poible ree conaining he e of organim conidered, and hen ue he aiic

More information

!!"#"$%&#'()!"#&'(*%)+,&',-)./0)1-*23)

!!#$%&#'()!#&'(*%)+,&',-)./0)1-*23) "#"$%&#'()"#&'(*%)+,&',-)./)1-*) #$%&'()*+,&',-.%,/)*+,-&1*#$)()5*6$+$%*,7&*-'-&1*(,-&*6&,7.$%$+*&%'(*8$&',-,%'-&1*(,-&*6&,79*(&,%: ;..,*&1$&$.$%&'()*1$$.,'&',-9*(&,%)?%*,('&5

More information

Displacement ( x) x x x

Displacement ( x) x x x Kinemaics Kinemaics is he branch of mechanics ha describes he moion of objecs wihou necessarily discussing wha causes he moion. 1-Dimensional Kinemaics (or 1- Dimensional moion) refers o moion in a sraigh

More information

Lecture 5 Buckling Buckling of a structure means failure due to excessive displacements (loss of structural stiffness), and/or

Lecture 5 Buckling Buckling of a structure means failure due to excessive displacements (loss of structural stiffness), and/or AOE 204 Inroducion o Aeropace Engineering Lecure 5 Buckling Buckling of a rucure mean failure due o exceive diplacemen (lo of rucural iffne), and/or lo of abiliy of an equilibrium configuraion of he rucure

More information

FLAT CYCLOTOMIC POLYNOMIALS OF ORDER FOUR AND HIGHER

FLAT CYCLOTOMIC POLYNOMIALS OF ORDER FOUR AND HIGHER #A30 INTEGERS 10 (010), 357-363 FLAT CYCLOTOMIC POLYNOMIALS OF ORDER FOUR AND HIGHER Nahan Kaplan Deparmen of Mahemaic, Harvard Univeriy, Cambridge, MA nkaplan@mah.harvard.edu Received: 7/15/09, Revied:

More information

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum MEE Engineering Mechanics II Lecure 4 Lecure 4 Kineics of a paricle Par 3: Impulse and Momenum Linear impulse and momenum Saring from he equaion of moion for a paricle of mass m which is subjeced o an

More information

Designing Information Devices and Systems I Spring 2019 Lecture Notes Note 17

Designing Information Devices and Systems I Spring 2019 Lecture Notes Note 17 EES 16A Designing Informaion Devices and Sysems I Spring 019 Lecure Noes Noe 17 17.1 apaciive ouchscreen In he las noe, we saw ha a capacior consiss of wo pieces on conducive maerial separaed by a nonconducive

More information

Research Article An Upper Bound on the Critical Value β Involved in the Blasius Problem

Research Article An Upper Bound on the Critical Value β Involved in the Blasius Problem Hindawi Publihing Corporaion Journal of Inequaliie and Applicaion Volume 2010, Aricle ID 960365, 6 page doi:10.1155/2010/960365 Reearch Aricle An Upper Bound on he Criical Value Involved in he Blaiu Problem

More information

Curvature. Institute of Lifelong Learning, University of Delhi pg. 1

Curvature. Institute of Lifelong Learning, University of Delhi pg. 1 Dicipline Coure-I Semeer-I Paper: Calculu-I Leon: Leon Developer: Chaianya Kumar College/Deparmen: Deparmen of Mahemaic, Delhi College of r and Commerce, Univeriy of Delhi Iniue of Lifelong Learning, Univeriy

More information

CHAPTER 7: UNCERTAINTY

CHAPTER 7: UNCERTAINTY Eenial Microeconomic - ecion 7-3, 7-4 CHPTER 7: UNCERTINTY Fir and econd order ochaic dominance 2 Mean preerving pread 8 Condiional ochaic Dominance 0 Monoone Likelihood Raio Propery 2 Coninuou diribuion

More information

A STUDY ON COMPLICATED ROLL MOTION OF A SHIP EQUIPPED WITH AN ANTI-ROLLING TANK

A STUDY ON COMPLICATED ROLL MOTION OF A SHIP EQUIPPED WITH AN ANTI-ROLLING TANK 607 A STUDY ON COMPLICATED ROLL MOTION OF A SHIP EQUIPPED WITH AN ANTI-ROLLING TANK Harukuni Taguchi, Hirohi Sawada and Kauji Tanizawa Naional Mariime Reearch Iniue (JAPAN) Abrac Nonlinear roll moion of

More information

WEEK-3 Recitation PHYS 131. of the projectile s velocity remains constant throughout the motion, since the acceleration a x

WEEK-3 Recitation PHYS 131. of the projectile s velocity remains constant throughout the motion, since the acceleration a x WEEK-3 Reciaion PHYS 131 Ch. 3: FOC 1, 3, 4, 6, 14. Problems 9, 37, 41 & 71 and Ch. 4: FOC 1, 3, 5, 8. Problems 3, 5 & 16. Feb 8, 018 Ch. 3: FOC 1, 3, 4, 6, 14. 1. (a) The horizonal componen of he projecile

More information

Interpretation of special relativity as applied to earth-centered locally inertial

Interpretation of special relativity as applied to earth-centered locally inertial Inerpreaion of special relaiviy as applied o earh-cenered locally inerial coordinae sysems in lobal osiioning Sysem saellie experimens Masanori Sao Honda Elecronics Co., Ld., Oyamazuka, Oiwa-cho, Toyohashi,

More information

Average Case Lower Bounds for Monotone Switching Networks

Average Case Lower Bounds for Monotone Switching Networks Average Cae Lower Bound for Monoone Swiching Nework Yuval Filmu, Toniann Piai, Rober Robere, Sephen Cook Deparmen of Compuer Science Univeriy of Torono Monoone Compuaion (Refreher) Monoone circui were

More information

Mon Apr 2: Laplace transform and initial value problems like we studied in Chapter 5

Mon Apr 2: Laplace transform and initial value problems like we studied in Chapter 5 Mah 225-4 Week 2 April 2-6 coninue.-.3; alo cover par of.4-.5, EP 7.6 Mon Apr 2:.-.3 Laplace ranform and iniial value problem like we udied in Chaper 5 Announcemen: Warm-up Exercie: Recall, The Laplace

More information

EXERCISES FOR SECTION 1.5

EXERCISES FOR SECTION 1.5 1.5 Exisence and Uniqueness of Soluions 43 20. 1 v c 21. 1 v c 1 2 4 6 8 10 1 2 2 4 6 8 10 Graph of approximae soluion obained using Euler s mehod wih = 0.1. Graph of approximae soluion obained using Euler

More information

Price of Stability and Introduction to Mechanism Design

Price of Stability and Introduction to Mechanism Design Algorihmic Game Theory Summer 2017, Week 5 ETH Zürich Price of Sabiliy and Inroducion o Mechanim Deign Paolo Penna Thi i he lecure where we ar deigning yem which involve elfih player. Roughly peaking,

More information

CHAPTER 12 DIRECT CURRENT CIRCUITS

CHAPTER 12 DIRECT CURRENT CIRCUITS CHAPTER 12 DIRECT CURRENT CIUITS DIRECT CURRENT CIUITS 257 12.1 RESISTORS IN SERIES AND IN PARALLEL When wo resisors are conneced ogeher as shown in Figure 12.1 we said ha hey are conneced in series. As

More information

CONTROL SYSTEMS. Chapter 10 : State Space Response

CONTROL SYSTEMS. Chapter 10 : State Space Response CONTROL SYSTEMS Chaper : Sae Space Repone GATE Objecive & Numerical Type Soluion Queion 5 [GATE EE 99 IIT-Bombay : Mark] Conider a econd order yem whoe ae pace repreenaion i of he form A Bu. If () (),

More information

Flow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001

Flow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001 CS 545 Flow Nework lon Efra Slide courey of Charle Leieron wih mall change by Carola Wenk Flow nework Definiion. flow nework i a direced graph G = (V, E) wih wo diinguihed verice: a ource and a ink. Each

More information

QoS-Oriented Distributed Opportunistic Scheduling for Wireless Networks with Hybrid Links

QoS-Oriented Distributed Opportunistic Scheduling for Wireless Networks with Hybrid Links Globecom 2013 - Wirele Neworking Sympoium QoS-Oriened Diribued Opporuniic Scheduling for Wirele Nework wih Hybrid Link Wenguang Mao, Shanhan Wu, and Xudong Wang UM-SJU Join Iniue, Shanghai Jiao ong Univeriy,

More information

Implementation of 64-Point FFT Processor Based on Radix-2 Using Verilog

Implementation of 64-Point FFT Processor Based on Radix-2 Using Verilog Inernaional Journal of Engineering Reearch & Technology (IJERT) Implemenaion of 64-oin roceor Baed on Radix-2 Uing Verilog T.TIRUALA KOTESWARA RAO 1, S. SARATH CHANDRA 2 Suden of. Tech Deparmen of Elecronic

More information

ESTIMATES FOR THE DERIVATIVE OF DIFFUSION SEMIGROUPS

ESTIMATES 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 information

NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY

NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY Ian Crawford THE INSTITUTE FOR FISCAL STUDIES DEPARTMENT OF ECONOMICS, UCL cemmap working paper CWP02/04 Neceary and Sufficien Condiion for Laen

More information

Network Flows UPCOPENCOURSEWARE number 34414

Network Flows UPCOPENCOURSEWARE number 34414 Nework Flow UPCOPENCOURSEWARE number Topic : F.-Javier Heredia Thi work i licened under he Creaive Common Aribuion- NonCommercial-NoDeriv. Unpored Licene. To view a copy of hi licene, vii hp://creaivecommon.org/licene/by-nc-nd/./

More information

Maximum Flow in Planar Graphs

Maximum Flow in Planar Graphs Maximum Flow in Planar Graph Planar Graph and i Dual Dualiy i defined for direced planar graph a well Minimum - cu in undireced planar graph An - cu (undireced graph) An - cu The dual o he cu Cu/Cycle

More information

Non-uniform circular motion *

Non-uniform circular motion * OpenSax-CNX module: m14020 1 Non-uniform circular moion * Sunil Kumar Singh This work is produced by OpenSax-CNX and licensed under he Creaive Commons Aribuion License 2.0 Wha do we mean by non-uniform

More information

Essential Microeconomics : OPTIMAL CONTROL 1. Consider the following class of optimization problems

Essential Microeconomics : OPTIMAL CONTROL 1. Consider the following class of optimization problems Essenial Microeconomics -- 6.5: OPIMAL CONROL Consider he following class of opimizaion problems Max{ U( k, x) + U+ ( k+ ) k+ k F( k, x)}. { x, k+ } = In he language of conrol heory, he vecor k is he vecor

More information

Stat13 Homework 7. Suggested Solutions

Stat13 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 information

A Theoretical Analysis on Dynamic Marginal Cost Pricing. Masao Kuwahara Institute of Industrial Science, University of Tokyo.

A Theoretical Analysis on Dynamic Marginal Cost Pricing. Masao Kuwahara Institute of Industrial Science, University of Tokyo. A Theoreical Analyi on Dynamic Marginal Co Pricing Maao Kuahara Iniue of Indurial Science, Univeriy of Tokyo Abrac Thi udy exend he aic marginal co analyi o he dynamic one o ha he dynamic boleneck phenomena

More information

Robotics I. April 11, The kinematics of a 3R spatial robot is specified by the Denavit-Hartenberg parameters in Tab. 1.

Robotics I. April 11, The kinematics of a 3R spatial robot is specified by the Denavit-Hartenberg parameters in Tab. 1. Roboics I April 11, 017 Exercise 1 he kinemaics of a 3R spaial robo is specified by he Denavi-Harenberg parameers in ab 1 i α i d i a i θ i 1 π/ L 1 0 1 0 0 L 3 0 0 L 3 3 able 1: able of DH parameers of

More information

Explicit form of global solution to stochastic logistic differential equation and related topics

Explicit 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 information