Nurturing a New Low Carbon Sector under Uncertainty of Fuel Economy and Renewable Sources Development

Size: px
Start display at page:

Download "Nurturing a New Low Carbon Sector under Uncertainty of Fuel Economy and Renewable Sources Development"

Transcription

1 Nururng a New Low Carbon Seor under Unerany of Fuel Eonomy and Renewable Soures Developmen a Nmura a, Hrosh aamor b, Da Yamasa, Wang d, and Ryuh Yooyama e a Fauly of Eonoms, Hose Unversy b Waseda Unversy Envronmenal Researh Insue Dep. of Envronmen and Energy Engneerng, Waseda Unversy d Dep. of Envronmen and Energy Engneerng, Waseda Unversy e Dep. of Envronmen and Energy Engneerng, Waseda Unversy Absra: hs paper explores avenues for nururng a new energy-savng seor under uneran developmen of renewable energy soures and energy sorage fales. In parular, we addresses desgnng a smar-grd sheme ha would mae rowds of EV users he par of he energy managemen opmzers of a smar ommuny. A olleed mass of eleral vehles provdes he apay as ushons for absorbng erra energy dsurbanes aused by renewable soures. he man nsrumen s o exerse he dynam prng and ndue varous ypes of users, nludng EV users, o respond o he elery pre drven her own nenves. hs sudy ams o draw on he dynamsm of ompeve mare mehansms. Keywords: hargng nfrasruure; renewable energy rs; smar-grd. A Model of Energy Managemen n he Smar Communy Fgure shows an mage of he smar ommuny, he energy managemen of whh s o be suded n hs paper. Energy n he form of elery s of man onern. Up o oday, elery has radonally been suppled by an eler power ompany or a uly ompany ha serve as a regonal monopols. Whle he eler power ompany enjoys he monopoly poson, operaons have been regulaed n many ways. In parular, under hs sheme, he pre of elery was under rgd onrol by he governmen. Wh elery pre fxed, he demand ypally fluuaes n erra manners. I has been he uly ompanes msson and responsbly ha hey are prepared o mee whaever hgh demand for elery wh suffen apay a hand. hs requres for he elery ompany o nves heavly n apay n preparaon for he pea demand. hs seems o be a soure of neffeny n he frm s operaon, beause mos generaon fales reman dle n low demand perods. In onras o he radonal prae, Fgure shows a new ype of busness players n eler power enerprses, alled he Load Servng Eny (LSE), or somemes he Elery Aggregaor. he frms n he aegory of wha s alled he PPS (Power Produer and Suppler) are mos lely o ener hs new enerprse. An mporan dfferene beween he LSE and he eler uly ompany s ha he LSE sees o

2 rade elery wh pre responsve users n he ommuny. he LSE may have s own generaon faly suh as a gas urbne generaor or some renewable generaon fales as seen n Fgure. I may also have a onra wh some ousde soures le an eler uly or anoher PPS frm o proure elery for a pre-arranged pre when needed. I s wdely nown ha here are que dfferen ypes of elery users n he ommuny. Some ype of users adjuss he quany of elery hey use respondng o he pre hanges, and some users do no. hs paper presens a model of energy managemen wh an LSE as a busness oordnaor n a ommuny. Fgure An mage of smar Communy. Demand Response Charaerss of Varous Elery Users n he Communy hs seon onsders a model of he smar ommuny as shown n Fgure 2. A load servng eny (LSE) aggregaes and oordnaes, a day n advane, demands for elery of varous ypes of users n he ommuny for eah perod of he nex day. he purpose of he LSE s o aheve effen energy supply and onsumpon va sgnalng elery pre for eah perod, o whh users adap her onsumpons. 2

3 Fgure 2 A Model of Daly Arrangemens of Dynam Prng and Consumpons he onsumpon behavor of eah user ype s modeled by her demand funon for elery: α q = A p, =, 2,, () where he oeffen α sands for he pre elasy of onsumpon of ype users and he oeffen A represens he demand shf parameer. he dynam demand hanges over perods n a day are represened by hangng values of A. he nverse demand funon of () s as follows. h p = M q, =, 2,, where M = / A, h = / α (2) he heory of Eonoms spulaes ha he nverse demand funon represens he margnal value, or uly funon, namely, where ( ) du ( q ) h M q dq = (3) U q s he value funon of he ype users onsumng elery n he amoun of hus, we an derve he value funon by ang he negral of (3): q h M γ U ( q ) = M,, 2,, 0 x dx = q = γ where γ = h + q. (4) 3

4 Fgure 3 Demand funon and Uly funon For smply, we onsder hree ypes of ypal elery users as desrbed below. ype A Users hs ype of users are pre responsve, for example, wh he elasy ofα A =.5. he seond row of able shows he demand level qa () of ype A users for pre p = 0 (Yen/Wh),, 2,, 6 A are deermned from () as: =. he orrespondng demand shf parameers ( ) α ( ) da A = q / p, =, 2,, (5) he seond row shows he demand shf hus deermned. able Demand for pre 0 (yen/wh) and Shf Parameers: ype A Perod Demand D for p= A a Fgure 2 draws he urve of he nverse demand funon derved from () for eah perod. 4

5 Fgure 4 Demand urve and elasy of ype A ype B Users hs ype of users are pre rresponsve wh he elasy, for example, of α B = 0.2 able 2 shows he demand level qb () of ype B users for pre p = 0 (Yen/Wh), =, 2,, 6, and he orrespondng demand shf parameers A b. able 2 Demand for pre 0 (yen/wh) and Shf Parameers: ype B Perod Demand D for p= A b Fgure 5 draws he urve of he nverse demand funon for eah perod. As seen n he fgure, he urves are lose o veral lnes around he pre of p = 0 (yen/wr), ndang ha he demands q ( ) b s are pre nelas for he ype B users. ype C Users Fgure 5 A Dynam Demand Shf of ype B Users 5

6 he onsumpon behavor of hs ype s drven by a preferene dfferen from he demand funon of A and B. hese users see o mnmze he oal os of onsumpon upon q ahevng he oal onsumpon = beng equal o Q ( = ) w = max K q Q pq C = (6) where q () s he elery onsumpon n perod, and Q s he oal onsumpon durng a day. he parameer p s he pre of elery n perod. Elery vehle users ypal belong o hs group. hese users smply wsh he oal onsumpon o be Q, and hey are ndfferen abou when o onsume durng he day as far as her oal onsumpon s Q. For he ype C users, we anno draw he demand urve perod-wse ndependenly. her enre demand = ( d, d2,, d ) pres = ( p, p2,, p ) veor = ( p p p ) follows: d over he all perods depends upon he veor of he enre p. In oher words, he demand n eah perod s a funon of he p, 2,,, d ( p), =, 2,,. hs funonal relaonshp s wren as ( ) ( d ( ), d ( ),, d ( )) d p p p p 2 From he ommuny s sand pon, hese users onrbue grealy o mgang demand and supply runh of he pea perods. ype D users: Iner-emporal arbragers hs ype of users as le baeres wh some sorage apay for energy. ypally, we magne eler vehle users purhasng elery n low pre perods and sellng n hgher pre perods. Whle hey are ang drven by her own benefs, her arbrage ype of behavors onrbue grealy o smooh ou erra fluuaon of pres whn a span of dfferen perods. + S = S + s s, =, 2,, + s, s, S 0, S S S : Level of energy harge of he sorage faly a he end of perod. s + : Amoun of dsharge of elery durng perod. s : Amoun of harge of elery durng perod hese users objeve s defned by 6

7 I s also o be noed here ha hs welfare maxmzaon problem s for a gven pre veor p. 2. Dynam Prng for he Energy Managemen n he Communy 2. Welfare Maxmzaon of All he Agens n he Communy Le q ( q, q2,, q ), = AB, be he veor of energy onsumpon of ype users. Gven a pre veor p = ( p, p2,, p ), hese wo ypes of users see o maxmze ( p) ( q p) W = max w,, :, = AB, q q where w ( q : p) = U ( q ) p q = (7) where p qa sands for he nner produ of a par of veors p and q a. he frs order ondon of (7) s where ( q ) ( q ) du dq p = 0, = AB,, =, 2,, (8) du / dq sands for he margnal uly funon represened by he nverse demand funon (3). Communy Welfare hs subseon desrbes he welfare ha eah ype of users sees o maxmze respondng o a gven pre veor p. hese users adjus her onsumpon levels qa, qb, q, qd o maxmze her welfares ha are defned below. w q : p = max U q pq, = AB, q =. ype A and B: ( ) ( ). ype C: w ( ) U ( ) q : p = max q pq, where he uly funon of hs ype of users C q are n he followng form ( q ) = ( ) 2 U K q Q =, he oeffen K s very large posve number so U q s maxmzed when ha ( ) Q. q = w ps ps + + D, ; = max s s S = =. ype D: ( s s p ) +,, 7

8 v. Welfare of he ommuny (LSE) s wl( x: p) = max p x C ( x), where ( ) he oal os of supplyng x n perod. = x C x s he ommuny welfare maxmzaon s now wren as follows. COM ( q s x p) = w ( q p) + w ( q p) + w ( q p) W,, ; ; ; ; A a B b C + ( s, s ; p) w ( x; p) + w + D d d L ( q ( ) ) ( q ( ) ) C( x ) = max U + U a a b b q, s, x = = = subje o : mare learng ondon : q + q + q + q = x a b d (9) where x sands for he supply veor of elery ha he LSE needs o proure by generaon from renewable soures, or by generaon from s own plan or by ousourng. As seen n (9), summng up all he welfares of he all agens nvolved n he sysem resuls n dsappearane of he pre veorp from he problem. he os erm C( x ) = depends upon he supply managemen on he par of he LSE, he oordnaor of he ommuny. he nex seon models he plannng and operaonal deson problem of he supply-sde LSE. 2.2 Plannng and Operaonal Deson Problem of he Supply-sde LSE We onsder a day-ahead plannng problem of he LSE. However, adjusng o he real-me realzaon of uneran generaon from renewable soures, he problem nvolves some real-me deson varables as well. 8

9 Fgure 6 A Day-Ahead Coordnaon of Energy Managemen n a Communy Nomenlaure General Parameers : oal number of perods n a day : Number of hours n a perod, = 24 / p Mare pre of elery n perod. hs s deermned a day-ahead by onra. [0 3 yen/mwh] () LSE s varables and parameers relaed o long erm deson G : Generaon apay o onsru (MW): deson varable I C : Invesmen os per apay of generaon (0 6 yen/mw) h : Hpurly equvalen of Invesmen os per apay (0 3 yen/mw/h) () LSE s annual deson varables and parameer z : Capay onra for ousourng (MW) C z : Conra os per ousourng apay (0 6 yen/mw) z Daly equvalen of onra os per ousourng apay (0 6 yen/day) A Day-ahead Varables, Conra Desons () Users Deson Varables q : Elery demand level of user ype n perod [MW/hr.] α : Demand elasy of user ype, = ab, A : Demand shf parameer of user ype n perod () LSE s Deson Varables 9

10 x : Supply level n perod [MW/hr.] z : Capay onra for ousourng n perod. [MWh] a : Capay pre for ousourng n perod. [MWh] LSE s Real-me Deson Varables and Parameers n he Curren Day Desons depend on he realzaon of he sae of naure ω Sae of naure n perod, e.g., = : fne weaher, = : loudy weaher r ρ g g y y o o Renewable energy generaon level forω n perod [MW/hr.] Probably of realzaon of sae Generaon level by LSE s plan [MW/hr.] Margnal os of generaon by LSE s plan, [0 3 yen/mw/hr.] Elery os per MW/hr. for ousoung n perod [0 3 yen/mwh] Ousourng level per hour [MW/hr.] Purhasng amoun exeedng he onra apay z [MW/hr.] Purhasng os n he onra over-run [0 3 yen/mwh] 0

11 Fgure 7 Long-erm deson and shor-erm deson Long-erm Invesmen Deson on he Generang Plan he LSE maes a long-erm deson on he apay G (MW) of s own generaon plan. I oss I (0 6 yen/mw) per one Megawa of apay o onsru a generang faly of s own. Assumng ha he plan wll be n operaon for n = 8 year and he apal os for he nvesmen s = 0.08 (8%). he apal os I s ransformed o annual equvalen I a by ( + ) n ( ) ( ) Ia= I Fn,, Fn, = = = (.07 ) n 8 (0) where Fn, s he annual equvalen os faor. he annual os I (0 6 yen/mw/yr.) s furher ransformed o he hourly equvalen nvesmen os I h = H by 3 (0 3 yen/mw/h) () hus, f he LSE or he ommuny dedes o onsru G megawa of plan, wll os yen) hourly. he generaon levels, g, =, 2,,, are onsraned by H G (03 g G, =, 2,, (2) Capay Prouremen from Exernal Supplers: An annual deson on onra wh he ousde soure of supply he LSE purhases a apay on a onra annually. he apay are expressed by z (MW). hs s a deson varable made one n a year. In oher words, he LSE an purhase hourly up o he amoun z (MW), whh s proured a he begnnng of he year for he apay pre of C a (0 6 yen/mw). hs os of purhasng a un of apay s ransformed o he apay os per day by 3 ( C / 365) 0 a = a (0 3 yen/mw/day). Le ( y y y ), 2,, (3) y = be he veor of he real-me purhase from he ousde soure. hen, he deson varables are onsraned by y s y z, =, 2,, (4)

12 he os y (0 3 yen/mw/h) appled o y s onsderably low ompared wh he os o (0 3 yen/mw/h) appled o O whh s he purhase n he amoun of he apay over-run. 2.3 he Cos Mnmzaon of he Supply-sde LSE Le hs subseon desrbes he os mnmzaon problem o mee a gven supply veor x = ( x, x2,, x ). he LSE has s own generang plan. he un os of generaon s H (0 3 yen/mw/h). he varable os of generaon ( ) ( ), g C g for he generaon level of g [MW/hr.] s C g = C g where C =, = he number of hours n a perod. g g ( g g g ) g =, 2,, (5) be he veor of generaons for all he perods n he urren day. he deson on g depends upon he realzaon of he renewable generaon r. In meeng he power demand x n perod, he LSE aemps o supply wh he purhase y under he day-ahead apay onra and wh he generaon from he renewables r. he balane g needs o be generaed by s own osly plan. Boh he self-generaon g and he purhase from ousoure y are bounded by he longer erm deson and onra. herefore, he requremen and onsrans for perods are wren as r + g + y + o = x, y z, g G, =, 2,, (6) where he supply level x s no a random varable sne s predeermned a day-ahead, whle oher varables are real-me random varables dependng upon he realzaon of he renewable energy avalably r. he os funon ( ) C x n (9) s expressed as follows. C x G z g y o ( ) = h + z + E( g + y + o ) (7) = hs s he expeed os for one day. Sne g, y, o are nerdependen varables resulng from he real-me deson, he expeed value operaon E[ ] anno be dsrbued among erms whn he brae. o smplfy hs operaon, we assume ha he random varables r aes a value ou of wo possble values as follows. Energy generaon by renewable soure 2

13 he LSE owns a renewable generaon plan, and he renewable generaon levels durng a day are represened by ( r r r ) r =, 2,,. (8) he generaon level r n perod has a bnomal dsrbuon as follows: he os funon C ( x) = probably r r r =, =, 2,, 2 r r n (9) resuls from he followng mnmzaon: ( ) mn ( ) 2 z z g g g, y, o C x = z+ G ρ g + ρ g subje o :onsrans on generaon wh he LSE plan y ( ) ( ( ) ) o ( ) ρy + ρ y + ρo + ρ o r + g + y + o = x, y z, =, 2, =, 2,, g G, =, 2, =, 2,, g, y, o 0, =, 2, =, 2,, x 0, =, 2,, Referenes [Chang, 2005] A. C. Chang and K. Wanwrgh. Fundamenal Mehods of Mahemaal Eonoms, Fourh ed... MGraw Hll Irwn, [Chen, 202] Ljun Chen, Na L, Lbn Jang and Seven H. Low, Opmal Demand Response: Problem Formulaon and Deermns Case. In A. Charabory and M. D. Il (edd.) Conrol and Opmzaon Mehods for Eler Smar Grds, Sprnger, 202. [Green, 2000] Rhard Green. Compeon n Generaon: he Eonom Foundaons. Proeedngs of he IEEE, Vol.88, No.2, Feb., [Hobbs, 2004] B. Hobbs and U. Helman, Complemenary-Based Equlbrum modelng for Eler Power Mares. In Bunn, D. W. (eds.), Modelng Pres n Compeve Elery Mares, John & Sons, Ld., pp.69 97,

14 [Prhard, 200] G. Prhard, G. Zaer, and A. Phlpo. A Sngle-Selemen, Energy-Only Eler Power Mare for Unpredable and Inermen Parpans. Operaons Researh, Vol. 58, No. 4, 20 29, 200. [Shwarz, 2002] P. E. Shwarz,. M. aylor, M. Brmngham, and S. L. Dardan. Indusral Response o Elery Real-me Pres: Shor Run and Long Run. Eonom Inqurey, Vol.40, No.4, pp , [Zhao, 202] J. Zhao, B.F. Hobbs and J. Pang, Long-Run Equlbrum Modelng of Allowane Alloaon Sysems n Eler Power Mare. Operaons Researh, vol.58, No.3, pp , 200. [Wang, 202] G. Wang, M. Negree-Pne, A. Kowl, E. Shafeepoorfard, S. Meyn and U. V. Shanbhag. Dynam Compeve Equlbrum n Elery Mares. In A. Charabory and M. D. Il (eds.) Conrol and Opmzaon Mehods for Eler Smar Grds, Sprnger,

Problem Set 3 EC2450A. Fall ) Write the maximization problem of the individual under this tax system and derive the first-order conditions.

Problem Set 3 EC2450A. Fall ) Write the maximization problem of the individual under this tax system and derive the first-order conditions. Problem Se 3 EC450A Fall 06 Problem There are wo ypes of ndvduals, =, wh dfferen ables w. Le be ype s onsumpon, l be hs hours worked and nome y = w l. Uly s nreasng n onsumpon and dereasng n hours worked.

More information

Lecture Notes 4: Consumption 1

Lecture Notes 4: Consumption 1 Leure Noes 4: Consumpon Zhwe Xu (xuzhwe@sju.edu.n) hs noe dsusses households onsumpon hoe. In he nex leure, we wll dsuss rm s nvesmen deson. I s safe o say ha any propagaon mehansm of maroeonom model s

More information

ECON 8105 FALL 2017 ANSWERS TO MIDTERM EXAMINATION

ECON 8105 FALL 2017 ANSWERS TO MIDTERM EXAMINATION MACROECONOMIC THEORY T. J. KEHOE ECON 85 FALL 7 ANSWERS TO MIDTERM EXAMINATION. (a) Wh an Arrow-Debreu markes sruure fuures markes for goods are open n perod. Consumers rade fuures onras among hemselves.

More information

Computational results on new staff scheduling benchmark instances

Computational results on new staff scheduling benchmark instances TECHNICAL REPORT Compuaonal resuls on new saff shedulng enhmark nsanes Tm Curos Rong Qu ASAP Researh Group Shool of Compuer Sene Unersy of Nongham NG8 1BB Nongham UK Frs pulshed onlne: 19-Sep-2014 las

More information

Graduate Macroeconomics 2 Problem set 5. - Solutions

Graduate 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 information

Pendulum Dynamics. = Ft tangential direction (2) radial direction (1)

Pendulum 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 information

A Game-theoretical Approach for Job Shop Scheduling Considering Energy Cost in Service Oriented Manufacturing

A Game-theoretical Approach for Job Shop Scheduling Considering Energy Cost in Service Oriented Manufacturing 06 Inernaonal Conferene on Appled Mehans, Mehanal and Maerals Engneerng (AMMME 06) ISBN: 978--60595-409-7 A Game-heoreal Approah for Job Shop Shedulng Consderng Energy Cos n Serve Orened Manufaurng Chang-le

More information

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS

THE 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 information

Output equals aggregate demand, an equilibrium condition Definition of aggregate demand Consumption function, c

Output equals aggregate demand, an equilibrium condition Definition of aggregate demand Consumption function, c Eonoms 435 enze D. Cnn Fall Soal Senes 748 Unversy of Wsonsn-adson Te IS-L odel Ts se of noes oulnes e IS-L model of naonal nome and neres rae deermnaon. Ts nvolves exendng e real sde of e eonomy (desred

More information

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION INTERNATIONAL TRADE T. J. KEHOE UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 27 EXAMINATION Please answer wo of he hree quesons. You can consul class noes, workng papers, and arcles whle you are workng on he

More information

Sequential Unit Root Test

Sequential Unit Root Test Sequenal Un Roo es Naga, K, K Hom and Y Nshyama 3 Deparmen of Eonoms, Yokohama Naonal Unversy, Japan Deparmen of Engneerng, Kyoo Insue of ehnology, Japan 3 Insue of Eonom Researh, Kyoo Unversy, Japan Emal:

More information

Citation 2006 Ieee Power Engineering Society General Meeting, Pes, 2006

Citation 2006 Ieee Power Engineering Society General Meeting, Pes, 2006 Tle Reave power plannng and s os alloaon for dsrbuon sysems wh dsrbued generaon Auhor(s) Chen, L; Zhong, J; Gan, D Caon 6 eee Power Engneerng Soey General Meeng, Pes, 6 ssued Dae 6 URL hp://hdl.handle.ne/7/459

More information

Lecture 2 M/G/1 queues. M/G/1-queue

Lecture 2 M/G/1 queues. M/G/1-queue Lecure M/G/ queues M/G/-queue Posson arrval process Arbrary servce me dsrbuon Sngle server To deermne he sae of he sysem a me, we mus now The number of cusomers n he sysems N() Tme ha he cusomer currenly

More information

Chapter 6: AC Circuits

Chapter 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 information

Optimal Replenishment Policy for Hi-tech Industry with Component Cost and Selling Price Reduction

Optimal Replenishment Policy for Hi-tech Industry with Component Cost and Selling Price Reduction Opmal Replenshmen Poly for H-eh Indusry wh Componen Cos and Sellng Pre Reduon P.C. Yang 1, H.M. Wee, J.Y. Shau, and Y.F. seng 1 1 Indusral Engneerng & Managemen Deparmen, S. John s Unversy, amsu, ape 5135

More information

Let s treat the problem of the response of a system to an applied external force. Again,

Let 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 information

Superstructure-based Optimization for Design of Optimal PSA Cycles for CO 2 Capture

Superstructure-based Optimization for Design of Optimal PSA Cycles for CO 2 Capture Supersruure-asedOpmaonforDesgnof OpmalPSACylesforCO 2 Capure R. S. Kamah I. E. Grossmann L.. Begler Deparmen of Chemal Engneerng Carnege Mellon Unversy Psurgh PA 523 Marh 2 PSA n Nex Generaon Power Plans

More information

Mechanics Physics 151

Mechanics 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 information

Solution in semi infinite diffusion couples (error function analysis)

Solution 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 information

On One Analytic Method of. Constructing Program Controls

On 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

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS

V.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 information

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s

Ordinary 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 information

WELFARE MEASUREMENT, INVOLUNTARY UNEMPLOYMENT, AND HETEROGENEITY

WELFARE MEASUREMENT, INVOLUNTARY UNEMPLOYMENT, AND HETEROGENEITY row_42 559..571 Revew of Inome and Wealh Seres 56, umber 3, Sepember 21 WELFARE EASUREET, IVOLUTARY UEPLOYET, AD HETEROGEEITY by Thomas Aronsson* Umeå Unversy Ths paper onerns welfare measuremen n an eonomy

More information

Regularization and Stabilization of the Rectangle Descriptor Decentralized Control Systems by Dynamic Compensator

Regularization and Stabilization of the Rectangle Descriptor Decentralized Control Systems by Dynamic Compensator www.sene.org/mas Modern Appled ene Vol. 5, o. 2; Aprl 2 Regularzaon and ablzaon of he Reangle Desrpor Deenralzed Conrol ysems by Dynam Compensaor Xume Tan Deparmen of Eleromehanal Engneerng, Heze Unversy

More information

( ) () we define the interaction representation by the unitary transformation () = ()

( ) () 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 information

)-interval valued fuzzy ideals in BF-algebras. Some properties of (, ) -interval valued fuzzy ideals in BF-algebra, where

)-interval valued fuzzy ideals in BF-algebras. Some properties of (, ) -interval valued fuzzy ideals in BF-algebra, where Inernaonal Journal of Engneerng Advaned Researh Tehnology (IJEART) ISSN: 454-990, Volume-, Issue-4, Oober 05 Some properes of (, )-nerval valued fuzzy deals n BF-algebras M. Idrees, A. Rehman, M. Zulfqar,

More information

Political Economy of Institutions and Development: Problem Set 2 Due Date: Thursday, March 15, 2019.

Political Economy of Institutions and Development: Problem Set 2 Due Date: Thursday, March 15, 2019. Polcal Economy of Insuons and Developmen: 14.773 Problem Se 2 Due Dae: Thursday, March 15, 2019. Please answer Quesons 1, 2 and 3. Queson 1 Consder an nfne-horzon dynamc game beween wo groups, an ele and

More information

Mechanics Physics 151

Mechanics 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 information

Mechanics Physics 151

Mechanics 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 information

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD

HEAT 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 information

EEL 6266 Power System Operation and Control. Chapter 5 Unit Commitment

EEL 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 information

The Dynamic Programming Models for Inventory Control System with Time-varying Demand

The Dynamic Programming Models for Inventory Control System with Time-varying Demand The Dynamc Programmng Models for Invenory Conrol Sysem wh Tme-varyng Demand Truong Hong Trnh (Correspondng auhor) The Unversy of Danang, Unversy of Economcs, Venam Tel: 84-236-352-5459 E-mal: rnh.h@due.edu.vn

More information

COMPUTER SCIENCE 349A SAMPLE EXAM QUESTIONS WITH SOLUTIONS PARTS 1, 2

COMPUTER SCIENCE 349A SAMPLE EXAM QUESTIONS WITH SOLUTIONS PARTS 1, 2 COMPUTE SCIENCE 49A SAMPLE EXAM QUESTIONS WITH SOLUTIONS PATS, PAT.. a Dene he erm ll-ondoned problem. b Gve an eample o a polynomal ha has ll-ondoned zeros.. Consder evaluaon o anh, where e e anh. e e

More information

Method of Characteristics for Pure Advection By Gilberto E. Urroz, September 2004

Method of Characteristics for Pure Advection By Gilberto E. Urroz, September 2004 Mehod of Charaerss for Pre Adveon By Glbero E Urroz Sepember 004 Noe: The followng noes are based on lass noes for he lass COMPUTATIONAL HYDAULICS as agh by Dr Forres Holly n he Sprng Semeser 985 a he

More information

Robustness Experiments with Two Variance Components

Robustness 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 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

[ ] 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 information

Modeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts

Modeling 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 information

Electromagnetic waves in vacuum.

Electromagnetic waves in vacuum. leromagne waves n vauum. The dsovery of dsplaemen urrens enals a peular lass of soluons of Maxwell equaons: ravellng waves of eler and magne felds n vauum. In he absene of urrens and harges, he equaons

More information

Dual Approximate Dynamic Programming for Large Scale Hydro Valleys

Dual 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

2/20/2013. EE 101 Midterm 2 Review

2/20/2013. EE 101 Midterm 2 Review //3 EE Mderm eew //3 Volage-mplfer Model The npu ressance s he equalen ressance see when lookng no he npu ermnals of he amplfer. o s he oupu ressance. I causes he oupu olage o decrease as he load ressance

More information

Appendix H: Rarefaction and extrapolation of Hill numbers for incidence data

Appendix H: Rarefaction and extrapolation of Hill numbers for incidence data Anne Chao Ncholas J Goell C seh lzabeh L ander K Ma Rober K Colwell and Aaron M llson 03 Rarefacon and erapolaon wh ll numbers: a framewor for samplng and esmaon n speces dversy sudes cology Monographs

More information

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005

Dynamic 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 information

Reactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times

Reactive 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 information

Math 128b Project. Jude Yuen

Math 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 information

Volatility Interpolation

Volatility 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 information

Variants of Pegasos. December 11, 2009

Variants 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 information

Department of Economics University of Toronto

Department of Economics University of Toronto Deparmen of Economcs Unversy of Torono ECO408F M.A. Economercs Lecure Noes on Heeroskedascy Heeroskedascy o Ths lecure nvolves lookng a modfcaons we need o make o deal wh he regresson model when some of

More information

Origin of the inertial mass (II): Vector gravitational theory

Origin of the inertial mass (II): Vector gravitational theory Orn of he neral mass (II): Veor ravaonal heory Weneslao Seura González e-mal: weneslaoseuraonzalez@yahoo.es Independen Researher Absra. We dedue he nduve fores of a veor ravaonal heory and we wll sudy

More information

, t 1. Transitions - this one was easy, but in general the hardest part is choosing the which variables are state and control variables

, t 1. Transitions - this one was easy, but in general the hardest part is choosing the which variables are state and control variables Opmal Conrol Why Use I - verss calcls of varaons, opmal conrol More generaly More convenen wh consrans (e.g., can p consrans on he dervaves More nsghs no problem (a leas more apparen han hrogh calcls of

More information

WORKING PAPER SERIES

WORKING PAPER SERIES WORKING PAPER SERIES 08 206 Fsal poly reforms n a general equlbrum model h mperfeons Panagoa Kolous, Naasha Maoul, Aposols Phlppopoulos Πατησίων 76, 04 34 Αθήνα. Tηλ.: 20 8203303 5 / Fax: 20 8238249 76,

More information

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function

(,,, ) (,,, ). 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 information

Linear Quadratic Regulator (LQR) - State Feedback Design

Linear Quadratic Regulator (LQR) - State Feedback Design Linear Quadrai Regulaor (LQR) - Sae Feedbak Design A sysem is expressed in sae variable form as x = Ax + Bu n m wih x( ) R, u( ) R and he iniial ondiion x() = x A he sabilizaion problem using sae variable

More information

SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β

SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β SARAJEVO JOURNAL OF MATHEMATICS Vol.3 (15) (2007), 137 143 SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β M. A. K. BAIG AND RAYEES AHMAD DAR Absrac. In hs paper, we propose

More information

On the Boyd- Kuramoto Model : Emergence in a Mathematical Model for Adversarial C2 Systems

On the Boyd- Kuramoto Model : Emergence in a Mathematical Model for Adversarial C2 Systems On he oyd- Kuramoo Model : Emergence n a Mahemacal Model for Adversaral C2 Sysems Alexander Kallonas DSTO, Jon Operaons Dvson C2 Processes: many are cycles! oyd s Observe-Oren-Decde-Ac Loop: Snowden s

More information

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4

CS434a/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 information

Linear Response Theory: The connection between QFT and experiments

Linear 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 information

WiH Wei He

WiH Wei He Sysem Idenfcaon of onlnear Sae-Space Space Baery odels WH We He wehe@calce.umd.edu Advsor: Dr. Chaochao Chen Deparmen of echancal Engneerng Unversy of aryland, College Par 1 Unversy of aryland Bacground

More information

CS286.2 Lecture 14: Quantum de Finetti Theorems II

CS286.2 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 information

Coordination and Concurrent Negotiation for Multiple Web Services Procurement

Coordination and Concurrent Negotiation for Multiple Web Services Procurement Proeedngs of he Inernaonal MulConferene of Engneers and Compuer Senss 009 Vol I IMECS 009, Marh 8-0, 009, Hong Kong Coordnaon and Conurren Negoaon for Mulple Web Serves Prouremen Benyun Sh, and Kwang Mong

More information

Development of a New Optimal Multilevel Thresholding Using Improved Particle Swarm Optimization Algorithm for Image Segmentation

Development of a New Optimal Multilevel Thresholding Using Improved Particle Swarm Optimization Algorithm for Image Segmentation Inernaonal Journal of Elerons Engneerng, (1), 010, pp. 63-67 Developmen of a New Opmal Mullevel Thresholdng Usng Improved Parle Swarm Opmzaon Algorhm for Image Segmenaon P.D. Sahya 1 & R. Kayalvzh 1 Deparmen

More information

National Exams December 2015 NOTES: 04-BS-13, Biology. 3 hours duration

National Exams December 2015 NOTES: 04-BS-13, Biology. 3 hours duration Naonal Exams December 205 04-BS-3 Bology 3 hours duraon NOTES: f doub exss as o he nerpreaon of any queson he canddae s urged o subm wh he answer paper a clear saemen of any assumpons made 2 Ths s a CLOSED

More information

II. Light is a Ray (Geometrical Optics)

II. Light is a Ray (Geometrical Optics) II Lgh s a Ray (Geomercal Opcs) IIB Reflecon and Refracon Hero s Prncple of Leas Dsance Law of Reflecon Hero of Aleandra, who lved n he 2 nd cenury BC, posulaed he followng prncple: Prncple of Leas Dsance:

More information

Optimal Buyer-Seller Inventory Models in Supply Chain

Optimal Buyer-Seller Inventory Models in Supply Chain Inernaonal Conference on Educaon echnology and Informaon Sysem (ICEIS 03 Opmal Buyer-Seller Invenory Models n Supply Chan Gaobo L Shandong Women s Unversy, Jnan, 50300,Chna emal: lgaobo_979@63.com Keywords:

More information

Electrical and current self-induction

Electrical and current self-induction Elecrical and curren self-inducion F. F. Mende hp://fmnauka.narod.ru/works.hml mende_fedor@mail.ru Absrac The aricle considers he self-inducance of reacive elemens. Elecrical self-inducion To he laws of

More information

Optimal Adaptive Data Transmission over a Fading Channel with Deadline and Power Constraints

Optimal Adaptive Data Transmission over a Fading Channel with Deadline and Power Constraints Opmal Adapve Daa Transmsson over a Fadng Channel wh Deadlne and Power Consrans Muraza Zafer and yan Modano aboraory for Informaon and Deson Sysems Massahuses Insue of Tehnology Cambrdge, MA 239, USA emal:{muraza,modano}@m.edu

More information

The Maxwell equations as a Bäcklund transformation

The Maxwell equations as a Bäcklund transformation ADVANCED ELECTROMAGNETICS, VOL. 4, NO. 1, JULY 15 The Mawell equaons as a Bäklund ransformaon C. J. Papahrsou Deparmen of Physal Senes, Naval Aademy of Greee, Praeus, Greee papahrsou@snd.edu.gr Absra Bäklund

More information

by Lauren DeDieu Advisor: George Chen

by Lauren DeDieu Advisor: George Chen b Laren DeDe Advsor: George Chen Are one of he mos powerfl mehods o nmercall solve me dependen paral dfferenal eqaons PDE wh some knd of snglar shock waves & blow-p problems. Fed nmber of mesh pons Moves

More information

Inventory Balancing in Disassembly Line: A Multiperiod Problem

Inventory Balancing in Disassembly Line: A Multiperiod Problem Invenory Balancng n Dsassembly Lne: A Mulperod Problem [007-0662] Badr O. Johar and Surendra M. Gupa * Laboraory for Responsble Manufacurng 334 SN Deparmen of MIE Norheasern Unversy 360 Hunngon Avenue

More information

Epistemic Game Theory: Online Appendix

Epistemic Game Theory: Online Appendix Epsemc Game Theory: Onlne Appendx Edde Dekel Lucano Pomao Marcano Snscalch July 18, 2014 Prelmnares Fx a fne ype srucure T I, S, T, β I and a probably µ S T. Le T µ I, S, T µ, βµ I be a ype srucure ha

More information

Example: MOSFET Amplifier Distortion

Example: MOSFET Amplifier Distortion 4/25/2011 Example MSFET Amplfer Dsoron 1/9 Example: MSFET Amplfer Dsoron Recall hs crcu from a prevous handou: ( ) = I ( ) D D d 15.0 V RD = 5K v ( ) = V v ( ) D o v( ) - K = 2 0.25 ma/v V = 2.0 V 40V.

More information

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

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

More information

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim

GENERATING 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 information

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes.

J 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 information

Including the ordinary differential of distance with time as velocity makes a system of ordinary differential equations.

Including the ordinary differential of distance with time as velocity makes a system of ordinary differential equations. Soluons o Ordnary Derenal Equaons An ordnary derenal equaon has only one ndependen varable. A sysem o ordnary derenal equaons consss o several derenal equaons each wh he same ndependen varable. An eample

More information

Linear Circuit Elements

Linear Circuit Elements 1/25/2011 inear ircui Elemens.doc 1/6 inear ircui Elemens Mos microwave devices can be described or modeled in erms of he hree sandard circui elemens: 1. ESISTANE () 2. INDUTANE () 3. APAITANE () For he

More information

CS 268: Packet Scheduling

CS 268: Packet Scheduling Pace Schedulng Decde when and wha pace o send on oupu ln - Usually mplemened a oupu nerface CS 68: Pace Schedulng flow Ion Soca March 9, 004 Classfer flow flow n Buffer managemen Scheduler soca@cs.bereley.edu

More information

2 Aggregate demand in partial equilibrium static framework

2 Aggregate demand in partial equilibrium static framework Unversy of Mnnesoa 8107 Macroeconomc Theory, Sprng 2009, Mn 1 Fabrzo Perr Lecure 1. Aggregaon 1 Inroducon Probably so far n he macro sequence you have deal drecly wh represenave consumers and represenave

More information

Optimal environmental charges under imperfect compliance

Optimal environmental charges under imperfect compliance ISSN 1 746-7233, England, UK World Journal of Modellng and Smulaon Vol. 4 (28) No. 2, pp. 131-139 Opmal envronmenal charges under mperfec complance Dajn Lu 1, Ya Wang 2 Tazhou Insue of Scence and Technology,

More information

Quality of Imports Relative to Exports, and the Transmission of Sustained Growth through the Terms of Trade

Quality of Imports Relative to Exports, and the Transmission of Sustained Growth through the Terms of Trade Qualy of Impors Relave o Expors, and he Transmsson of Susaned Growh hrough he Terms of Trade Carmen D. Álvarez-Albelo Unversdad de La Laguna and CREB Móna Pgem-Vgo Unversa de Barelona and CREB ABSTRACT:

More information

CHAPTER 5: MULTIVARIATE METHODS

CHAPTER 5: MULTIVARIATE METHODS CHAPER 5: MULIVARIAE MEHODS Mulvarae Daa 3 Mulple measuremens (sensors) npus/feaures/arbues: -varae N nsances/observaons/eamples Each row s an eample Each column represens a feaure X a b correspons o he

More information

Computing Relevance, Similarity: The Vector Space Model

Computing 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 information

Comb Filters. Comb Filters

Comb 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 information

Brander and Lewis (1986) Link the relationship between financial and product sides of a firm.

Brander and Lewis (1986) Link the relationship between financial and product sides of a firm. Brander and Lews (1986) Lnk the relatonshp between fnanal and produt sdes of a frm. The way a frm fnanes ts nvestment: (1) Debt: Borrowng from banks, n bond market, et. Debt holders have prorty over a

More information

Markup Variation and Endogenous Fluctuations in the Price of Investment Goods

Markup Variation and Endogenous Fluctuations in the Price of Investment Goods Markup Varaon and Endogenous Fluuaons n he Pre of Invesmen Goods Max Floeoo Sanford Unversy Nr Jamovh Sanford Unversy and NBER February 2009 Seh Pru Federal Reserve Board of Governors Absra The wo seor

More information

10. A.C CIRCUITS. Theoretically current grows to maximum value after infinite time. But practically it grows to maximum after 5τ. Decay of current :

10. 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 information

THERMODYNAMICS 1. The First Law and Other Basic Concepts (part 2)

THERMODYNAMICS 1. The First Law and Other Basic Concepts (part 2) Company LOGO THERMODYNAMICS The Frs Law and Oher Basc Conceps (par ) Deparmen of Chemcal Engneerng, Semarang Sae Unversy Dhon Harano S.T., M.T., M.Sc. Have you ever cooked? Equlbrum Equlbrum (con.) Equlbrum

More information

Cubic Bezier Homotopy Function for Solving Exponential Equations

Cubic 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 information

Complex Dynamics Analysis for Cournot Game with Bounded Rationality in Power Market

Complex Dynamics Analysis for Cournot Game with Bounded Rationality in Power Market J. Elecromagnec Analyss & Applcaons 9 : 48- Publshed Onlne March 9 n ScRes (www.scrp.org/journal/jemaa Complex Dynamcs Analyss for Courno Game wh Bounded Raonaly n Power Marke Hongmng Yang Yongx Zhang

More information

Lorentz Transformation Properties of Currents for the Particle-Antiparticle Pair Wave Functions

Lorentz Transformation Properties of Currents for the Particle-Antiparticle Pair Wave Functions Open Aess Library Journal 17, Volume 4, e373 ISSN Online: 333-971 ISSN Prin: 333-975 Lorenz Transformaion Properies of Currens for he Parile-Aniparile Pair Wave Funions Raja Roy Deparmen of Eleronis and

More information

Amit Mehra. Indian School of Business, Hyderabad, INDIA Vijay Mookerjee

Amit Mehra. Indian School of Business, Hyderabad, INDIA Vijay Mookerjee RESEARCH ARTICLE HUMAN CAPITAL DEVELOPMENT FOR PROGRAMMERS USING OPEN SOURCE SOFTWARE Ami Mehra Indian Shool of Business, Hyderabad, INDIA {Ami_Mehra@isb.edu} Vijay Mookerjee Shool of Managemen, Uniersiy

More information

Decentralized Trading and Demand Side Response in Inter-Intelligent Renewable Energy Network

Decentralized Trading and Demand Side Response in Inter-Intelligent Renewable Energy Network Decenralzed Tradng and Demand Sde Response n Iner-Inellgen Renewable Energy Nework Tadahro Tanguch Deparmen of Informaon Scence & Engneerng Rsumekan Unversy Shga, Japan Emal: anguch@rsume.ac.jp Shro Yano

More information

EP2200 Queuing theory and teletraffic systems. 3rd lecture Markov chains Birth-death process - Poisson process. Viktoria Fodor KTH EES

EP2200 Queuing theory and teletraffic systems. 3rd lecture Markov chains Birth-death process - Poisson process. Viktoria Fodor KTH EES EP Queung heory and eleraffc sysems 3rd lecure Marov chans Brh-deah rocess - Posson rocess Vora Fodor KTH EES Oulne for oday Marov rocesses Connuous-me Marov-chans Grah and marx reresenaon Transen and

More information

FI 3103 Quantum Physics

FI 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 information

Comparison of Differences between Power Means 1

Comparison of Differences between Power Means 1 In. Journal of Mah. Analyss, Vol. 7, 203, no., 5-55 Comparson of Dfferences beween Power Means Chang-An Tan, Guanghua Sh and Fe Zuo College of Mahemacs and Informaon Scence Henan Normal Unversy, 453007,

More information

e-journal Reliability: Theory& Applications No 2 (Vol.2) Vyacheslav Abramov

e-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 information

Scattering at an Interface: Oblique Incidence

Scattering 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 information

Problem 1 / 25 Problem 2 / 15 Problem 3 / 15 Problem 4 / 20 Problem 5 / 25 TOTAL / 100

Problem 1 / 25 Problem 2 / 15 Problem 3 / 15 Problem 4 / 20 Problem 5 / 25 TOTAL / 100 Deparmen of Appled Economcs Johns Hopkns Unversy Economcs 60 Macroeconomc Theory and Polcy Fnal Exam Suggesed Soluons Professor Sanjay Chugh Fall 009 NAME: The Exam has a oal of fve (5) problems and pages

More information

How about the more general "linear" scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )?

How 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 information

Fuzzy Goal Programming for Solving Fuzzy Regression Equations

Fuzzy Goal Programming for Solving Fuzzy Regression Equations Proeedngs of he h WSEAS Inernaonal Conferene on SYSEMS Voulagmen Ahens Greee July () Fuzzy Goal Programmng for Solvng Fuzzy Regresson Equaons RueyChyn saur Dearmen of Fnane Hsuan Chuang Unversy 8 Hsuan

More information

ME 160 Introduction to Finite Element Method. Chapter 5 Finite Element Analysis in Heat Conduction Analysis of Solid Structures

ME 160 Introduction to Finite Element Method. Chapter 5 Finite Element Analysis in Heat Conduction Analysis of Solid Structures San Jose Sae Unvers Deparmen o Mehanal Engneerng ME 6 Inroduon o Fne Elemen Mehod Chaper 5 Fne Elemen Analss n Hea Conduon Analss o Sold Sruures Insruor a-ran Hsu Proessor Prnpal reerenes: ) he Fne Elemen

More information