An Electricity Trade Model for Microgrid Communities in Smart Grid


 Marvin Davidson
 3 years ago
 Views:
Transcription
1 An Electrcty Trade Model for Mcrogrd Countes n Sart Grd Tansong Cu, Yanzh Wang, Shahn Nazaran and Massoud Pedra Unversty of Southern Calforna Departent of Electrcal Engneerng Los Angeles, CA, USA {tcu, yanzhwa, shahn, Abstract Dstrbuted crogrd network s the ajor trend of future sart grd, whch contans varous knds of renewable power generaton centers and a sall group of energy users. In the dstrbuted power syste, each crogrd acts as a prosuer (producer and consuer) and axzes ts own socal welfare. In addton, dfferent crogrds can nteract aong each other through tradng over a arketplace. In ths paper, two odels are ntroduced for crogrds to deal wth the welfare axzaton probles. In the frst odel, a crogrd s consdered as a closed econoy group and decdes the optal power generaton dstrbuton n ters of te. In the second odel, each crogrd can trade wth ts neghborhoods and thus acheve a welfare ncrease fro akng use of ts coparatve advantage on power generaton durng a certan perod of te. For each odel, an effcent soluton s presented. Experental result shows the accuracy and effcency of our presented solutons. I. INTRODUCTION The current sart grd technology s undergong a transforaton fro a centralzed, producercontrolled network to one that s ore dstrbuted and consuernteractve [1][2]. Wth the ntroducton of the decentralzed network archtecture, the entre busness odel wll be changed together wth the relatonshp of all stakeholders, nvolvng and affectng utltes, regulators, energy servce provders, technology and autoaton vendors and all consuers of electrc power [2]. Aong all the changes n sart grd, the transforaton of the power generaton network s of the ost crtcal,.e., nstead of beng generated by a few faroff hghcapacty generators and transtted to end users, electrcal energy s ncreasngly beng produced by sallscale generators located closer to pontsofuse [3]. Ths dstrbuted power generaton center has ade t easer to ake use of all knds of renewable energy sources and sgnfcantly reduced the energy transsson cost. However, the nablty to control the ncreased nuber of dstrbuted energy sources can create huge dffcultes n operatng and controllng the dstrbuton network. To solve ths proble, the dea of crogrd s ntroduced [4]. A crogrd can be vewed as a prosuer (producer and consuer) [3]. It contans one or ultple knds of renewable power generaton centers and a sngle or a sall group of energy users, and offers the possblty of coordnatng the dstrbuted resources n a ore ntellgent way so that they can behave as a controlled entty. In ths way, dstrbuted resources can provde ther full advantages n a ore consstent way. Generally for each crogrd, as electrcty ust be used as t s beng generated, the usual practce s to atch supply to deand [5]. Ths s a challengng proble because of the followng reasons: frst, the power deand depends on exogenous factors and vares draatcally [6]; second, each energy user can have ts own utlty preference of energy usage at dfferent te slots; thrd, due to the varous types of power generaton centers, the power generaton cost wll also vary as a functon of te and weather factors, e.g., for a solar energy center, the power generaton cost wll be uch cheaper n the day te than durng the nght te. Under a certan resource constrant, t s necessary to decde the aount of energy generaton and consupton at each te so that the socal welfare of the crogrd can be axzed [7]. In addton, the arket dea has been n the heart of ajor roadaps for crogrd structures [36]. The nterconnect network enables the surplus generaton fro one crogrd to be used to eet the local deand n ts neghborhood. In the classc econoc study, trade s always benefcal to both sdes and thus should be encouraged [8]. By tradng wth each other, each crogrd can ake use of ts coparatve advantage and acheve an ncrease of socal welfare. Prevous papers such as [3] have studed structure of the energy tradng platfor n sart grd neghborhoods. However, they faled to provde an analyss on soe of the econoc factors such as what s the optal energy tradng volue or what deternes the relatve energy prce. To gve a detaled study on the above probles, two odels are ntroduced n ths paper. The frst odel deals wth the local welfare axzaton proble where a crogrd s consdered as a closed econoy group and decdes the optal power generaton dstrbuton n ters of te. In the second odel, each crogrd can trade wth ts neghborhoods and thus acheve a welfare ncrease fro akng use of ts coparatve advantage on power generaton durng a certan perod of te. A odfed Rcardan odel s used to study the econoc factors n the trade process [9]. The reander of ths paper s organzed as follows. In the next secton, we present our local welfare axzaton odel for each crogrd. In secton Secton III, the electrcty trade odel s ntroduced for crogrd neghborhoods. Secton IV reports the experental results and the paper s concluded n Secton V.
2 II. MODEL OF LOCAL WELFARE MAXIMIZATION In the frst odel, we start wth the assupton that a crogrd s a closed econoy group n ters of energy (.e., no energy tradng s allowed) and decdes the optal energy generaton dstrbuton n ters of te. A slotted te odel s assued,.e., all syste cost paraeters and constrants as well as energy generaton and consupton decsons are provded for dscrete te ntervals of constant length. We use C and P to represent the energy generaton and consupton levels (wth a unfed energy unt) at te slot where {1, 2,..., T }. T s the total nuber of equalszed te slots that we dvde one operatng perod nto. For exaple, f we set one operatng perod to be a day and T = 24, a day s dvded nto 24 te slots, each wth duraton of one hour. Econosts have agreed that users consue coonaltes (such as energy) at each te because ths energy consupton provdes satsfacton, or utlty, whch represents the level of a knd of socal welfare [9]. It s coonly odeled and verfed n econoc study that the relatonshp between the utlty derved fro the level of energy consupton at each te follows the for [9]:, (1) where s the preference factor at each te slot and we have 0 < < 1 for all. A hgher eans the users n ths crogrd prefer to consue ore energy at the correspondng te slot. Equaton (1) also reflects three characterstcs of the relatonshp between the utlty and energy consupton level: 1. As > 0, the utlty s an ncreasng functon of C, whch eans the overall satsfacton level wll be ncreased f users can consue ore energy at any te slot. 2. As < 1, the argnal utlty, U/ C = j Cαj j 1, s a decreasng functon of C. Ths eans f the energy consupton at one te slot s already at a very hgh level (.e., uch ore than necessary), users satsfacton level wll not ncrease too uch f we further ncrease the energy producton level at that te. As a result, to satsfy the energy users n the crogrd, t s better to ncrease the energy producton at the ore necessary te slots, whch s realstc. 3. The utlty functon drops to 0 f C = 0 for any 1 T, whch eans the level of satsfacton wll be very low f power outage occurs durng any perod of te. On the other hand, the generaton centers should decde the energy generaton dstrbuton n ters of te so that the total utlty of the crogrd s axzed. It s also coonly odeled n econocs that under a gven resource constrant, the energy generaton producton possbltes should follow the gven nequaton [9]: β P I, (2) where β s the nuber of resource unts that are needed to generate one unt of energy at each te slot and I s the total nuber of resource unts that s allowed to use durng one operatng perod. Notce that β s deterned by the type of energy generaton centers as well as the level of technology, and ght not be constant for dfferent values. Gven the odels for energy generaton and consupton, we need to deterne the relatonshp between the two. Unlke other coon fors of energy such as checal or knetc, electrcal energy should be used as t s beng generated. If storage s requred, electrcal energy wll typcally be converted edately nto another for of energy such as potental, knetc, or electrochecal[1][2]. In ost of the recent crogrd structures, energy storage s not used because of the hgh cost[3][4]. In addton, as stated at the begnnng of ths secton, the crogrd s assued to be a closed econoy group n ters of energy n ths odel. Therefore, no energy trade s consdered n ths odel. Based on the above assuptons, the energy generaton and consupton level should be the sae at every te nsde the crogrd,.e., C = P for each. Usng the above defntons and assuptons, the local welfare axzaton proble for one crogrd can be odeled as follows: Local Welfare Maxzaton Proble for a Mcrogrd Fnd the optal energy generaton P for 1 T. Maxze: β P I P 0 1 T C = P 1 T The geoetry optzaton dea [12] can be used to nuercally solve ths proble. Property 1: At the optal soluton pont of the above local welfare axzaton proble, we have: U/ C β P = I, (3) = U β C = D 1 T, (4) where D s the sae value for all, whch results n the optal soluton gven by: P = C = T β =1 α I 1 T. (5) Proof: It can be easly deterned that only when we ake full use of the energy generaton resources can we acheve the
3 axal utlty functon. In addton, assue at the optal soluton pont, there exsts a par of te slots {, j} that U/ C > U/ Cj I/ P j. We wll be able to fnd a new possble soluton wth C = C + σ/β and C j = C j σ/β j, where σ s a very sall value wth the sae unt of total resource I. As we have U/ C > U/ Cj I/ P j, t can be proven that U(C 1, C 2,..., C, C j,...) > U(C 1, C 2,..., C, C j,...), whch conflcts the optalty of the soluton. As a result, the optal soluton wll occur only when U/ C s the sae for every. It can be observed fro the soluton that for a closed crogrd, we need to spend a lot of resources to generate a certan aount of energy at the loweffcency power generaton te,.e., when β s large. In order to solve ths proble and also ake better use of ts hgheffcency te, a crogrd can choose to trade wth ts neghborhood, whch s dscussed n the next secton. III. MODEL OF WELFARE MAXIMIZATION WITH NEIGHBORHOOD TRADING In nternatonal econoc studes, countres engage n nternatonal trade because they are dfferent fro each other and both of the can beneft fro the dfferences by reachng an arrangeent n whch each does the thngs t does relatvely well [9]. Slarly, by buldng the nterconnect power network, each crogrd can perfor energy trade wth ts neghborhood n order to acheve a welfare ncrease. Bascally, an energy trade contract contans two steps: Frst, both crogrds get together to ake ther energy generaton decsons n order to acheve a axal overall utlty functon; Second, both sdes decde the dstrbuton of the beneft fro trade n a far way. The second step can be perfored usng a far beneft dstrbuton law that the rato between the utlty functon after trade and the axal utlty functon before trade (.e., U trade /U local,ax ) s the sae for both sdes, whch s relatvely easy and s not dscussed n detal n ths secton because of space lt (but s used and shown n experental result secton). In ths secton, we focus on the frst step to deal wth the total welfare axzaton proble for the two crogrds. A odfed Rcardan odel s used n ths secton [9]. In subsecton A, we start wth a splfed odel wth only two te slots n order to study the characterstcs of the optal soluton of the welfare axzaton proble. The odel s then extended to a ore general case n subsecton B. A. Tradng wth Two Te Slots In ths odel, we assue that the target crogrd and ts neghborhood has dfferent energy generaton cost as well as the resource. We denote the target crogrd s total resource by I s, the energy generaton at each te slot by P s, and the nuber of resource unts that are needed to generate one unt of energy at each te slot by β s,. Slarly, we have I n, P n, and β n, for ts neghborhood. As before, C denotes the total energy consupton at te slot and denotes the correspondng preference factor. The preference factor s assued to be the sae for both crogrds because they lve close to each other. Usng the above defntons and assuptons, the total welfare axzaton proble for these two crogrd can be odeled as follows: Total Welfare Maxzaton Proble for Two Mcrogrds Fnd the optal energy generaton P s, and P n, for 1 T. Maxze: β s, P s, = I s β n, P n, = I n P s, 0, P n, 0 1 T C = P s, + P n, 1 T Notce that we have sply used = nstead of n the frst two constrants because we have already proven that the axal utlty can be acheved only when each crogrd has ade full use of ts resources. In ths subsecton, we focus on a splfed stuaton that T = 2. Econosts have used the dea of coparatve advantage to analyze the otve of tradng. Coparatve advantage refers to the ablty of a party to produce a partcular good or servce at a lower argnal and opportunty cost over another. For energy generaton centers n a crogrd, the coparatve advantage coes fro the ablty of generatng energy at a partcular te slot at a lower opportunty cost over the energy generaton centers n another crogrd. For convenence, assue we have relabeled the te slots to ake β s,1 /β n,1 < β s,2 /β n,2. Based on the defnton, the target crogrd has coparatve advantage on energy generaton at te slot 1, and the neghborhood crogrd has coparatve advantage on energy generaton at te slot 2. Notce that coparatve advantage s deterned by the rato of β s, /β n, nstead of the absolute values, whch eans even though a crogrd has a hgher energy generaton cost at every te slot, t can stll have coparatve advantage at soe of the te slots. As we have stated before that energy tradng enables both crogrds to ake better use of ts coparatve advantage at a specal te slot, we are able to analyze the optal soluton. Property 2: At the optal soluton pont of the above total welfare axzaton proble wth T = 2, f β s,1 /β n,1 < β s,2 /β n,2, we have ether P n,1 = 0 or P s,2 = 0 (or both). Proof: Assue we have both P n,1 > 0 and P s,2 > 0 at the optal soluton pont, we wll be able to fnd a new possble
4 soluton wth P s,1 = P s,1 + σ s /β s,1, P s,2 = P s,2 σ s /β s,2, P n,1 = P n,1 σ n /β n,1 and P n,2 = P n,2 + σ n /β n,2, where σ s and σ n are a very sall values wth the sae unt of total resource I s or I n. As β s,1 /β n,1 < β s,2 /β n,2, there should exsts a par of {σ s, σ n } that β s,1 /β n,1 < σ s /σ n < β s,2 /β n,2. In ths case, we wll have both P s,1 + P n,1 > P s,1 + P n,1 and P s,2 +P n,2 > P s,2 +P n,2, whch leads to a hgher total utlty and conflcts the optalty of the soluton. Based on ths property, at least one crogrd wll be specfed n generatng energy at one te slot at the optal soluton pont. And thus the optal soluton of the total welfare axzaton proble wth T = 2 can be acheved by coparng the partal optal soluton at P n,1 = 0 or P s,2 = 0. Notce that there s another specal stuaton where β s,1 /β n,1 = β s,2 /β n,2. It can be proven that there are ultple optal soluton ponts n ths case and one of the optal soluton can be acheved when each of the two crogrds sply axzes ts own utlty as n secton II, whch eans none of the two crogrds can gan fro trade. Ths case s not dscussed n detal because of space lt but s verfed n the experental result secton. B. Tradng wth Multple Te Slots When we extend the proble to a ore general case wth T > 2, the dea of coparatve advantage can stll be used to analyze the characterstcs of the optal soluton. Slarly for convenence, assue we have already relabeled the te slots so that we have β s,1 /β n,1 < β s,2 /β n,2 < β s,3 /β n,3 <... < β s,t /β n,t. We can also coe up wth the property as follows: Property 3: At the optal soluton pont of the total welfare axzaton proble wth T > 2, f β s,1 /β n,1 < β s,2 /β n,2 < β s,3 /β n,3 <... < β s,t /β n,t, there exsts a te slot t that we have P n, = 0 for 1 < t and P s, = 0 for t < T. In other words, there s at ost one (probably zero) te slot n whch the energy s generated by both crogrds. Proof: When there already exsts a te slot t wth both P n,t > 0 and P s,t > 0, f there exsts another te slot 1 < t wth P n, > 0, we wll have β s, /β n, < β s,t /β n,t together wth P n, > 0 and P s,t > 0. We can fnd a better soluton accordng to the proof of Property 2. Slarly, there should not exst another te slot t < T wth P s, > 0. Assue we have already known the value of t, based on the analyss n secton II, we also have the followng property: Property 4: At the optal soluton pont of the above proble wth T > 2, U/ Ps, β s, s the sae for each 1 < t and U/ Pn, β n, s the sae for t < T. Proof: Based on Property 3, we have P n, = 0 for 1 < t and P s, = 0 for t < T, whch eans C = P s, for 1 < t and C = P n, for t < T. Thus Property 4 can be concluded accordng to the proof of Property 1. Property 3 and 4 can be used to deterne the energy generaton at all the other te slots when P s,t and P n,t are gven: P s, = t 1 β s, =1 α (I β s,t P s,t ) 1 < t.(6) P n, = T β n, =t+1 α (I β n,t P n,t ) t < T.(7) As a result, gven the value of t, the total welfare axzaton proble wth T > 2 can be splfed as follows: Total Welfare Maxzaton Proble wth a Gven t Fnd the optal energy generaton P s,t and P n,t. Maxze: =t+1 t 1 [ t 1 β s, =1 α (I β s,t P s,t )] α [ T β n, =t+1 α (I β n,t P n,t )] α (P s,t + P n,t ) αt 0 P s,t I s /β s,t 0 P n,t I n /β n,t There are only two varables n the above proble and they can be easly solved usng geoetry optzaton wth the help of atlab. The reanng proble s to deterne the value of t, and a straghtforward algorth s to swtch t fro 1 to T wth a coplexty of O(n). However, t can be proven that the axal utlty s a concave functon of t. In addton, t can be guaranteed that the optal t value s already acheved when we end up wth both P s,t > 0 and P n,t > 0 n solvng the aboveentoned optzaton proble. Detaled proof s otted n ths paper because of space lt. Usng these propertes, we can ternate our algorth once we have U(t) U(t 1) or both P s,t and P n,t are greater than zero. A specal case s that at the optal soluton pont, there s no te slot n whch the energy s generated by both copanes. Ths stuaton s already ncluded n our algorth and wll end up wth P s,t = 0 or P n,t = 0. IV. EXPERIMENTAL RESULTS To deonstrate the effectveness of the proposed solutons, cases correspondng to the aforesad odels are exaned. The proposed solutons have been pleented usng Matlab and tested for rando cases. In the frst sulaton, we focus on the case T = 2. The preference factor of each te slot s set to be 0.3 and 0.7. Before tradng, both the target crogrd and the neghborhood crogrd are consdered to be closed econoc groups and axze ther own utlty functons. When the crogrds open up to trade, they frst get together to decde the optal energy generaton at each te slot so that the total welfare can be axzed. After that, they dstrbute the total energy consupton n a far way, followng the rule that the rato
5 between the utlty functon after trade and the axal utlty functon before trade s the sae for both sdes. The odel s tested for rando cases wth dfferent energy generaton cost and total resource cobnatons. The detaled sulaton result s presented n Table I. TABLE I SIMULATION RESULTS FOR DIFFERENT CASES UNDER T = 2 before trade after trade U case grd β 1 β 2 I trade P 1 P 2 P 1 P 2 U local s n s n s n s n s n s n It can be observed fro the above table that n case 1, as we have β s,1 /β n,1 = β s,2 /β n,2, there s no coparatve advantage between the two crogrds. As a result, the optal soluton can be acheved when each of the two crogrds sply axzes ts own utlty as and none of the two crogrds can gan fro trade. Fro case 2 to case 6, as long as there s a dfference between β s,1 /β n,1 and β s,2 /β n,2, both crogrds can ake use of ts coparatve advantage and acheve a welfare ncrease fro tradng wth each other. The hgher ths dfference, the ore they can gan fro trade. In addton, copare case 2 and case 3, we can also observe that the total energy generaton resource wll also affect the cooperatve energy generaton decson for both crogrds. In case 2, the resource of the neghborhood crogrd s relatvely lted so the target crogrd needs to generate energy at both te slots. But n case 3, both crogrds have enough resources so that each of the turns out to be specfed n energy generaton at ts own advantageous te slot. In the second sulaton, we analyze the general case wth total te slot T = 6. We set β s,1 /β n,1 < β s,2 /β n,2 < β s,3 /β n,3 <... < β s,6 /β n,6 and test our odel under cases wth total resource cobnatons. The fnal result of cooperatve energy generaton at each te slot s shown n Table II TABLE II COOPERATIVE ENERGY GENERATION RESULTS UNDER T = 6 grd I P 1 P 2 P 3 P 4 P 5 P 6 U trade U local s n s n s n Our soluton s verfed n the above table. Case 1 and case 3 are the two extree cases n whch one crogrd s totally specfed n energy generaton at only one te slot, whle the other crogrd generates energy at every te slot. In case 2, as the two crogrds have relatvely the sae aount of resources, energy turns out to be generated by one certan crogrd wth a coparatve advantage at that te slot. No atter n whch case, both of the crogrds can acheve a welfare ncrease after openng up to trade. Another observaton fro the above experental results s that even f a crogrd has a uch better technology,.e., β s, s saller than ts neghborhood at any te slot, t wll stll beneft fro tradng wth other crogrds. And also, a crogrd wth less energy generaton resources s ore lkely to be specfed n generatng energy at a sngle te slot. V. CONCLUSION Two odels are presented n ths paper to deal wth the welfare axzaton probles for crogrds. In each odel, a crogrd s consdered to be a prosuer to have both energy generaton and consupton. In the frst odel, a closed econoy group s consdered for each crogrd and optal power generaton dstrbuton s solved. In the second odel, the crogrd cooperates wth ts neghborhood through energy tradng and a welfare ncrease s acheved for both sdes. The dea of coparatve advantage s used for crogrds n akng decsons on energy generaton. For each odel, an effcent soluton s presented. The accuracy and effcency of our presented solutons are verfed by experental results. REFERENCES [1] The Sart Grd: An Introducton, The US Departent of Energy, [2] L. Chen, S. Low, and J. Doyle, Two arket odels for deand response n power networks, Proc. of Sart Grd Councatons Conf., [3] D. Ilc, P.G. Da Slva, S.Karnouskos, M. Greseer, An energy arket for tradng electrcty n sart grd neghbourhoods, 6th IEEE Internatonal Conference on Dgtal Ecosystes Technologes (DEST), [4] MICROGRIDS: Large Scale Integraton of McroGeneraton to Low Voltage Grds, EU Contract ENK5CT , Techncal Annex, May [5] T. Cu, Y. Wang, S. Yue, S. Nazaran, and M. Pedra, A Gae Theoretc Prce Deternaton Algorth for Utlty Copanes Servng a County n Sart Grd, Proc. of IEEE PES Innovatve Sart Grd Technologes (ISGT) Conference, Feb [6] T. Saad, Technology Developents and R&D Challenges for Sart Grd Applcatons n Hoes, Buldngs, and Industry, Presentaton sldes avalable onlne. [7] P. Saad, H. MohsenanRad, R. Schober, V. Wong, and J. Jatskevch, Optal realte prcng algorth based on utlty axzaton for sart grd, Proc. of Sart Grd Councatons Conf., [8] N. Gregory Mankw, Prncple of Econocs, Dryden Press, [9] P. Krugan, M. Obstfeld, and M. Meltz, Internatonal Econocs: Theory and Polcy, Addson Wesley, [10] W. Saad, H. Zhu, H. V. Poor, and T. Basar, GaeTheoretc Methods for the Sart Grd: An Overvew of Mcrogrd Systes, DeandSde Manageent, and Sart Grd Councatons, IEEE Sgnal Processng Magazne, [11] Y. Narahar, D. Garg, R. Narayana, and H. Prakash, Gae Theoretc Probles n Network Econocs and Mechans Desgn Solutons, Advanced Inforaton and Knowledge Process, [12] S. P. Boyd and L. Vandenberghe, Convex optzaton, Cabrdge unversty press, 2004.
BANDWIDTH ALLOCATION AND PRICING PROBLEM FOR A DUOPOLY MARKET
Yugoslav Journal of Operatons Research (0), Nuber, 6578 DOI: 0.98/YJOR0065Y BANDWIDTH ALLOCATION AND PRICING PROBLEM FOR A DUOPOLY MARKET PengSheng YOU Graduate Insttute of Marketng and Logstcs/Transportaton,
More informationInstitute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic
Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange
More informationStochastic Models of Load Balancing and Scheduling in Cloud Computing Clusters
Stochastc Models of Load Balancng and Schedulng n Cloud Coputng Clusters Sva Theja Magulur and R. Srkant Departent of ECE and CSL Unversty of Illnos at UrbanaChapagn sva.theja@gal.co; rsrkant@llnos.edu
More informationINTRODUCTION TO MERGERS AND ACQUISITIONS: FIRM DIVERSIFICATION
XV. INTODUCTION TO MEGES AND ACQUISITIONS: FIM DIVESIFICATION In the ntroducton to Secton VII, t was noted that frs can acqure assets by ether undertakng nternallygenerated new projects or by acqurng
More informationCONSTRUCTION OF A COLLABORATIVE VALUE CHAIN IN CLOUD COMPUTING ENVIRONMENT
CONSTRUCTION OF A COLLAORATIVE VALUE CHAIN IN CLOUD COMPUTING ENVIRONMENT Png Wang, School of Econoy and Manageent, Jangsu Unversty of Scence and Technology, Zhenjang Jangsu Chna, sdwangp1975@163.co Zhyng
More informationStochastic Models of Load Balancing and Scheduling in Cloud Computing Clusters
Stochastc Models of Load Balancng and Schedulng n Cloud Coputng Clusters Sva Theja Magulur and R. Srkant Departent of ECE and CSL Unversty of Illnos at UrbanaChapagn sva.theja@gal.co; rsrkant@llnos.edu
More informationAn Alternative Way to Measure Private Equity Performance
An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate
More informationII. THE QUALITY AND REGULATION OF THE DISTRIBUTION COMPANIES I. INTRODUCTION
Fronter Methodology to fx Qualty goals n Electrcal Energy Dstrbuton Copanes R. Rarez 1, A. Sudrà 2, A. Super 3, J.Bergas 4, R.Vllafáfla 5 12 345  CITCEA  UPC UPC., Unversdad Poltécnca de Cataluña,
More informationBasic Queueing Theory M/M/* Queues. Introduction
Basc Queueng Theory M/M/* Queues These sldes are created by Dr. Yh Huang of George Mason Unversty. Students regstered n Dr. Huang's courses at GMU can ake a sngle achnereadable copy and prnt a sngle copy
More informationStochastic Models of Load Balancing and Scheduling in Cloud Computing Clusters
01 Proceedngs IEEE INFOCOM Stochastc Models of Load Balancng and Schedulng n Cloud Coputng Clusters Sva heja Magulur and R. Srkant Departent of ECE and CSL Unversty of Illnos at UrbanaChapagn sva.theja@gal.co;
More informationDEFINING %COMPLETE IN MICROSOFT PROJECT
CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMISP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,
More informationHow Much to Bet on Video Poker
How Much to Bet on Vdeo Poker Trstan Barnett A queston that arses whenever a gae s favorable to the player s how uch to wager on each event? Whle conservatve play (or nu bet nzes large fluctuatons, t lacks
More informationMaximizing profit using recommender systems
Maxzng proft usng recoender systes Aparna Das Brown Unversty rovdence, RI aparna@cs.brown.edu Clare Matheu Brown Unversty rovdence, RI clare@cs.brown.edu Danel Rcketts Brown Unversty rovdence, RI danel.bore.rcketts@gal.co
More informationTransformation of Commercial Flows into Physical Flows of Electricity
Transforaton of Coercal Flows nto Physcal Flows of Electrcty Marek ADAMEC, Mchaela INDRAKOVA, Pavel PAVLATKA Dept. of Econocs, Manageent and Huantes, Czech Techncal Unversty, Zkova 4, 166 27 Praha, Czech
More informationResearch Article Load Balancing for Future Internet: An Approach Based on Game Theory
Appled Matheatcs, Artcle ID 959782, 11 pages http://dx.do.org/10.1155/2014/959782 Research Artcle Load Balancng for Future Internet: An Approach Based on Gae Theory Shaoy Song, Tngje Lv, and Xa Chen School
More informationRevenue Maximization Using Adaptive Resource Provisioning in Cloud Computing Environments
202 ACM/EEE 3th nternatonal Conference on Grd Coputng evenue Maxzaton sng Adaptve esource Provsonng n Cloud Coputng Envronents Guofu Feng School of nforaton Scence, Nanng Audt nversty, Nanng, Chna nufgf@gal.co
More informationbenefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).
REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or
More informationThe OC Curve of Attribute Acceptance Plans
The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4
More informationNear Optimal Online Algorithms and Fast Approximation Algorithms for Resource Allocation Problems
Near Optal Onlne Algorths and Fast Approxaton Algorths for Resource Allocaton Probles Nkhl R Devanur Kaal Jan Balasubraanan Svan Chrstopher A Wlkens Abstract We present algorths for a class of resource
More informationOn the Optimal Control of a Cascade of HydroElectric Power Stations
On the Optmal Control of a Cascade of HydroElectrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;
More informationELE427  Testing Linear Sensors. Linear Regression, Accuracy, and Resolution.
ELE47  Testng Lnear Sensors Lnear Regresson, Accurac, and Resoluton. Introducton: In the frst three la eperents we wll e concerned wth the characterstcs of lnear sensors. The asc functon of these sensors
More informationThe Subtraction Rule and its Effects on Pricing in the Electricity Industry
Dscusson Paer No 04 The Subtracton Rule and ts Effects on Prcng n the Electrcty Industry Walter Elberfeld Dscusson Paer No 04 The Subtracton Rule and ts Effects on Prcng n the Electrcty Industry Walter
More informationStudy on Model of Risks Assessment of Standard Operation in Rural Power Network
Study on Model of Rsks Assessment of Standard Operaton n Rural Power Network Qngj L 1, Tao Yang 2 1 Qngj L, College of Informaton and Electrcal Engneerng, Shenyang Agrculture Unversty, Shenyang 110866,
More informationScan Detection in HighSpeed Networks Based on Optimal Dynamic Bit Sharing
Scan Detecton n HghSpeed Networks Based on Optal Dynac Bt Sharng Tao L Shgang Chen Wen Luo Mng Zhang Departent of Coputer & Inforaton Scence & Engneerng, Unversty of Florda Abstract Scan detecton s one
More informationCapacity Planning for Virtualized Servers
Capacty Plannng for Vrtualzed Servers Martn Bchler, Thoas Setzer, Benjan Spetkap Departent of Inforatcs, TU München 85748 Garchng/Munch, Gerany (bchler setzer benjan.spetkap)@n.tu.de Abstract Today's data
More informationA hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm
Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):18841889 Research Artcle ISSN : 09757384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel
More informationFeasibility of Using Discriminate Pricing Schemes for Energy Trading in Smart Grid
Feasblty of Usng Dscrmnate Prcng Schemes for Energy Tradng n Smart Grd Wayes Tushar, Chau Yuen, Bo Cha, Davd B. Smth, and H. Vncent Poor Sngapore Unversty of Technology and Desgn, Sngapore 138682. Emal:
More informationOnline Algorithms for Uploading Deferrable Big Data to The Cloud
Onlne lgorths for Uploadng Deferrable Bg Data to The Cloud Lnquan Zhang, Zongpeng L, Chuan Wu, Mnghua Chen Unversty of Calgary, {lnqzhan,zongpeng}@ucalgary.ca The Unversty of Hong Kong, cwu@cs.hku.hk The
More informationA Secure PasswordAuthenticated Key Agreement Using Smart Cards
A Secure PasswordAuthentcated Key Agreement Usng Smart Cards Ka Chan 1, WenChung Kuo 2 and JnChou Cheng 3 1 Department of Computer and Informaton Scence, R.O.C. Mltary Academy, Kaohsung 83059, Tawan,
More informationStudy on CET4 Marks in China s Graded English Teaching
Study on CET4 Marks n Chna s Graded Englsh Teachng CHE We College of Foregn Studes, Shandong Insttute of Busness and Technology, P.R.Chna, 264005 Abstract: Ths paper deploys Logt model, and decomposes
More informationNaglaa Raga Said Assistant Professor of Operations. Egypt.
Volue, Issue, Deceer ISSN: 77 8X Internatonal Journal of Adanced Research n Coputer Scence and Software Engneerng Research Paper Aalale onlne at: www.jarcsse.co Optal Control Theory Approach to Sole Constraned
More informationUSING ECASH IN THE NEW ECONOMY: AN ECONOMIC ANALYSIS OF MICROPAYMENT SYSTEMS
Journal of Electronc Coerce Research, VOL. 5, NO.4, 004 USING ECASH IN THE NEW ECONOMY: AN ECONOMIC ANALYSIS OF MICROPAYMENT SYSTEMS Mchelle Baddeley Gonvlle & Caus College and Faculty of Econocs and
More informationGroup Solvency Optimization Model for Insurance Companies Using Copula Functions
Internatonal Conference on Econocs, Busness and Marketng Manageent IPEDR vol.9 () () IACSIT Press, Sngapore Group Solvency Optzaton Model for Insurance Copanes Usng Copula Functons Masayasu Kanno + Faculty
More informationDynamic Pricing for Smart Grid with Reinforcement Learning
Dynamc Prcng for Smart Grd wth Renforcement Learnng ByungGook Km, Yu Zhang, Mhaela van der Schaar, and JangWon Lee Samsung Electroncs, Suwon, Korea Department of Electrcal Engneerng, UCLA, Los Angeles,
More informationCalculating the high frequency transmission line parameters of power cables
< ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,
More informationTwoPhase Traceback of DDoS Attacks with Overlay Network
4th Internatonal Conference on Sensors, Measureent and Intellgent Materals (ICSMIM 205) TwoPhase Traceback of DDoS Attacks wth Overlay Network Zahong Zhou, a, Jang Wang2, b and X Chen3, c 2 School of
More informationAn Analytical Model of Web Server Load Distribution by Applying a Minimum Entropy Strategy
Internatonal Journal of Coputer and Councaton Engneerng, Vol. 2, No. 4, July 203 An Analytcal odel of Web Server Load Dstrbuton by Applyng a nu Entropy Strategy Teeranan Nandhakwang, Settapong alsuwan,
More informationINVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMAHDR NETWORKS
21 22 September 2007, BULGARIA 119 Proceedngs of the Internatonal Conference on Informaton Technologes (InfoTech2007) 21 st 22 nd September 2007, Bulgara vol. 2 INVESTIGATION OF VEHICULAR USERS FAIRNESS
More informationTo manage leave, meeting institutional requirements and treating individual staff members fairly and consistently.
Corporate Polces & Procedures Human Resources  Document CPP216 Leave Management Frst Produced: Current Verson: Past Revsons: Revew Cycle: Apples From: 09/09/09 26/10/12 09/09/09 3 years Immedately Authorsaton:
More informationA Novel Dynamic RoleBased Access Control Scheme in User Hierarchy
Journal of Coputatonal Inforaton Systes 6:7(200) 24232430 Avalable at http://www.jofcs.co A Novel Dynac RoleBased Access Control Schee n User Herarchy Xuxa TIAN, Zhongqn BI, Janpng XU, Dang LIU School
More informationCan Auto Liability Insurance Purchases Signal Risk Attitude?
Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? ChuShu L Department of Internatonal Busness, Asa Unversty, Tawan ShengChang
More informationA Fuzzy Optimization Framework for COTS Products Selection of Modular Software Systems
Internatonal Journal of Fuy Systes, Vol. 5, No., June 0 9 A Fuy Optaton Fraework for COTS Products Selecton of Modular Software Systes Pankaj Gupta, Hoang Pha, Mukesh Kuar Mehlawat, and Shlp Vera Abstract
More informationCHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol
CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK Sample Stablty Protocol Background The Cholesterol Reference Method Laboratory Network (CRMLN) developed certfcaton protocols for total cholesterol, HDL
More informationA metafrontier study of securities broker and dealer efficiency under zerosum gains
ChnY Fang (Tawan), JnL Hu (Tawan) Investent Manageent and Fnancal Innovatons, Volue 6, Issue 3, 2009 A etafronter study of securtes broer and dealer effcency under zerosu gans Abstract Ths paper studes
More information"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *
Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC
More informationA Hybrid Approach to Evaluate the Performance of Engineering Schools
A Hybrd Approach to Evaluate the Perforance of Engneerng Schools School of Engneerng Unversty of Brdgeport Brdgeport, CT 06604 ABSTRACT Scence and engneerng (S&E) are two dscplnes that are hghly receptve
More informationFault tolerance in cloud technologies presented as a service
Internatonal Scentfc Conference Computer Scence 2015 Pavel Dzhunev, PhD student Fault tolerance n cloud technologes presented as a servce INTRODUCTION Improvements n technques for vrtualzaton and performance
More informationGanesh Subramaniam. American Solutions Inc., 100 Commerce Dr Suite # 103, Newark, DE 19713, USA
238 Int. J. Sulaton and Process Modellng, Vol. 3, No. 4, 2007 Sulatonbased optsaton for ateral dspatchng n VendorManaged Inventory systes Ganesh Subraana Aercan Solutons Inc., 100 Coerce Dr Sute # 103,
More informationVirtual machine resource allocation algorithm in cloud environment
COMPUTE MOELLIN & NEW TECHNOLOIES 2014 1(11) 27924 Le Zheng Vrtual achne resource allocaton algorth n cloud envronent 1, 2 Le Zheng 1 School of Inforaton Engneerng, Shandong Youth Unversty of Poltcal
More informationSecure Cloud Storage Service with An Efficient DOKS Protocol
Secure Cloud Storage Servce wth An Effcent DOKS Protocol ZhengTao Jang Councaton Unversty of Chna z.t.ang@163.co Abstract Storage servces based on publc clouds provde custoers wth elastc storage and ondeand
More informationEfficient Bandwidth Management in Broadband Wireless Access Systems Using CACbased Dynamic Pricing
Effcent Bandwdth Management n Broadband Wreless Access Systems Usng CACbased Dynamc Prcng Bader AlManthar, Ndal Nasser 2, Najah Abu Al 3, Hossam Hassanen Telecommuncatons Research Laboratory School of
More informationTraffic Demand Forecasting for EGCS with Grey Theory Based Multi Model Method
IJCSI Internatonal Journal of Coputer Scence Issues, Vol., Issue, No, January 3 ISSN (Prnt): 694784 ISSN (Onlne): 69484 www.ijcsi.org 6 Traffc Deand Forecastng for EGCS wth Grey Theory Based Mult Model
More informationResearch Article Enhanced TwoStep Method via Relaxed Order of αsatisfactory Degrees for Fuzzy Multiobjective Optimization
Hndaw Publshng Corporaton Mathematcal Problems n Engneerng Artcle ID 867836 pages http://dxdoorg/055/204/867836 Research Artcle Enhanced TwoStep Method va Relaxed Order of αsatsfactory Degrees for Fuzzy
More informationQuality of Service Analysis and Control for Wireless Sensor Networks
Qualty of ervce Analyss and Control for Wreless ensor Networs Jaes Kay and Jeff Frol Unversty of Veront ay@uv.edu, frol@eba.uv.edu Abstract hs paper nvestgates wreless sensor networ spatal resoluton as
More informationPowerofTwo Policies for Single Warehouse MultiRetailer Inventory Systems with Order Frequency Discounts
Powerofwo Polces for Sngle Warehouse MultRetaler Inventory Systems wth Order Frequency Dscounts José A. Ventura Pennsylvana State Unversty (USA) Yale. Herer echnon Israel Insttute of echnology (Israel)
More informationA Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy Scurve Regression
Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy Scurve Regresson ChengWu Chen, Morrs H. L. Wang and TngYa Hseh Department of Cvl Engneerng, Natonal Central Unversty,
More informationWeb Servicebased Business Process Automation Using Matching Algorithms
Web Servcebased Busness Process Autoaton Usng Matchng Algorths Yanggon K and Juhnyoung Lee 2 Coputer and Inforaton Scences, Towson Uversty, Towson, MD 2252, USA, yk@towson.edu 2 IBM T. J. Watson Research
More informationModule 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..
More informationSPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:
SPEE Recommended Evaluaton Practce #6 efnton of eclne Curve Parameters Background: The producton hstores of ol and gas wells can be analyzed to estmate reserves and future ol and gas producton rates and
More informationAddendum to: Importing SkillBiased Technology
Addendum to: Importng SkllBased Technology Arel Bursten UCLA and NBER Javer Cravno UCLA August 202 Jonathan Vogel Columba and NBER Abstract Ths Addendum derves the results dscussed n secton 3.3 of our
More informationCommunication Networks II Contents
8 / 1  Communcaton Networs II (Görg)  www.comnets.unbremen.de Communcaton Networs II Contents 1 Fundamentals of probablty theory 2 Traffc n communcaton networs 3 Stochastc & Marovan Processes (SP
More informationBERNSTEIN POLYNOMIALS
OnLne Geometrc Modelng Notes BERNSTEIN POLYNOMIALS Kenneth I. Joy Vsualzaton and Graphcs Research Group Department of Computer Scence Unversty of Calforna, Davs Overvew Polynomals are ncredbly useful
More informationVRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT09105, Phone: (3705) 2127472, Fax: (3705) 276 1380, Email: info@teltonika.
VRT012 User s gude V0.1 Thank you for purchasng our product. We hope ths userfrendly devce wll be helpful n realsng your deas and brngng comfort to your lfe. Please take few mnutes to read ths manual
More informationFeature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College
Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure
More informationPricing Model of Cloud Computing Service with Partial Multihoming
Prcng Model of Cloud Computng Servce wth Partal Multhomng Zhang Ru 1 Tang Bngyong 1 1.Glorous Sun School of Busness and Managment Donghua Unversty Shangha 251 Chna Emal:ru528369@mal.dhu.edu.cn Abstract
More informationThe Development of Web Log Mining Based on ImproveKMeans Clustering Analysis
The Development of Web Log Mnng Based on ImproveKMeans Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.
More informationA Statistical Model for Detecting Abnormality in StaticPriority Scheduling Networks with Differentiated Services
A Statstcal odel for Detectng Abnoralty n StatcProrty Schedulng Networks wth Dfferentated Servces ng L 1 and We Zhao 1 School of Inforaton Scence & Technology, East Chna Noral Unversty, Shangha 0006,
More informationMultiplePeriod Attribution: Residuals and Compounding
MultplePerod Attrbuton: Resduals and Compoundng Our revewer gave these authors full marks for dealng wth an ssue that performance measurers and vendors often regard as propretary nformaton. In 1994, Dens
More informationLecture 3: Annuity. Study annuities whose payments form a geometric progression or a arithmetic progression.
Lecture 3: Annuty Goals: Learn contnuous annuty and perpetuty. Study annutes whose payments form a geometrc progresson or a arthmetc progresson. Dscuss yeld rates. Introduce Amortzaton Suggested Textbook
More informationTourism Demand Forecasting by Improved SVR Model
Internatonal Journal of u and e Servce, Scence and Technology, pp4034 http://dxdoorg/0457/junesst058538 Tours Deand Forecastng by Iproved SVR Model L Me Departent of Socal Servces,Zhengzhou Tours College,Henan,PRChna
More informationRESEARCH ON DUALSHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.
ICSV4 Carns Australa 9 July, 007 RESEARCH ON DUALSHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract
More informationSUPPLIER FINANCING AND STOCK MANAGEMENT. A JOINT VIEW.
SUPPLIER FINANCING AND STOCK MANAGEMENT. A JOINT VIEW. Lucía Isabel García Cebrán Departamento de Economía y Dreccón de Empresas Unversdad de Zaragoza Gran Vía, 2 50.005 Zaragoza (Span) Phone: 976761000
More informationAnswer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy
4.02 Quz Solutons Fall 2004 MultpleChoce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multplechoce questons. For each queston, only one of the answers s correct.
More informationA system for realtime calculation and monitoring of energy performance and carbon emissions of RET systems and buildings
A system for realtme calculaton and montorng of energy performance and carbon emssons of RET systems and buldngs Dr PAAIOTIS PHILIMIS Dr ALESSADRO GIUSTI Dr STEPHE GARVI CE Technology Center Democratas
More informationProblem Set 3. a) We are asked how people will react, if the interest rate i on bonds is negative.
Queston roblem Set 3 a) We are asked how people wll react, f the nterest rate on bonds s negatve. When
More informationEE201 Circuit Theory I 2015 Spring. Dr. Yılmaz KALKAN
EE201 Crcut Theory I 2015 Sprng Dr. Yılmaz KALKAN 1. Basc Concepts (Chapter 1 of Nlsson  3 Hrs.) Introducton, Current and Voltage, Power and Energy 2. Basc Laws (Chapter 2&3 of Nlsson  6 Hrs.) Voltage
More informationInventory Control in a MultiSupplier System
3th Intl Workng Senar on Producton Econocs (WSPE), Igls, Autrche, pp.56 Inventory Control n a MultSuppler Syste Yasen Arda and JeanClaude Hennet LAASCRS, 7 Avenue du Colonel Roche, 3077 Toulouse Cedex
More information2008/8. An integrated model for warehouse and inventory planning. Géraldine Strack and Yves Pochet
2008/8 An ntegrated model for warehouse and nventory plannng Géraldne Strack and Yves Pochet CORE Voe du Roman Pays 34 B1348 LouvanlaNeuve, Belgum. Tel (32 10) 47 43 04 Fax (32 10) 47 43 01 Emal: corestatlbrary@uclouvan.be
More information7.5. Present Value of an Annuity. Investigate
7.5 Present Value of an Annuty Owen and Anna are approachng retrement and are puttng ther fnances n order. They have worked hard and nvested ther earnngs so that they now have a large amount of money on
More informationFinn Roar Aune, Hanne Marit Dalen and Cathrine Hagem
Dscusson Papers No. 630, September 2010 Statstcs Norway, Research Department Fnn Roar Aune, Hanne Mart Dalen and Cathrne Hagem Implementng the EU renewable target through green certfcate markets Abstract:
More informationThe Application of Fractional Brownian Motion in Option Pricing
Vol. 0, No. (05), pp. 738 http://dx.do.org/0.457/jmue.05.0..6 The Applcaton of Fractonal Brownan Moton n Opton Prcng Qngxn Zhou School of Basc Scence,arbn Unversty of Commerce,arbn zhouqngxn98@6.com
More informationAn Enhanced KAnonymity Model against Homogeneity Attack
JOURNAL OF SOFTWARE, VOL. 6, NO. 10, OCTOBER 011 1945 An Enhanced KAnont Model aganst Hoogenet Attack Qan Wang College of Coputer Scence of Chongqng Unverst, Chongqng, Chna Eal: wangqan@cqu.edu.cn Zhwe
More informationWeek 6 Market Failure due to Externalities
Week 6 Market Falure due to Externaltes 1. Externaltes n externalty exsts when the acton of one agent unavodably affects the welfare of another agent. The affected agent may be a consumer, gvng rse to
More informationAllocating Collaborative Profit in LessthanTruckload Carrier Alliance
J. Servce Scence & Management, 2010, 3: 143149 do:10.4236/jssm.2010.31018 Publshed Onlne March 2010 (http://www.scrp.org/journal/jssm) 143 Allocatng Collaboratve Proft n LessthanTruckload Carrer Allance
More informationMoving Beyond Open Markets for Water Quality Trading: The Gains from Structured Bilateral Trades
Movng Beyond Open Markets for Water Qualty Tradng: The Gans from Structured Blateral Trades Tanl Zhao Yukako Sado Rchard N. Bosvert Gregory L. Poe Cornell Unversty EAERE Preconference on Water Economcs
More informationAnalysis of Clock Synchronization Approaches for Residential Ethernet
Analyss of Clock Synchronzaton Approaches for Resdental Ethernet Geoffrey M. Garner (Consultant) Kees den Hollander SAIT, Sasung Electroncs ggarner@cocast.net, denhollander.c.@sasung.co Abstract Resdental
More informationCAPITAL GAINS AND THE CAPITAL ASSET PRICING MODEL. WORKING PAPER SERIES Working Paper No. 1
CAPITAL GAINS AN THE CAPITAL ASSET PRING MOEL WORKING PAPER SERIES Workng Paper No. 1 Martn Lally School of Econocs and nance aculty of Coerce and Adnstraton Vctora Unversty of Wellngton Tony van Zl School
More informationINVENTORY CONTROL FOR HIGH TECHNOLOGY CAPITAL EQUIPMENT FIRMS. Hari Shreeram Abhyankar. B.S. Mathematics B.S. Economics Purdue University.
INVENTORY CONTRO FOR IG TECNOOGY CAPITA EQUIPMENT FIRM by ar hreera Abhyankar B.. Matheatcs B.. Econocs Purdue Unversty. 99 M.. Industral Engneerng Purdue Unversty. 994 ubtted to the loan chool of Manageent
More informationSimple Interest Loans (Section 5.1) :
Chapter 5 Fnance The frst part of ths revew wll explan the dfferent nterest and nvestment equatons you learned n secton 5.1 through 5.4 of your textbook and go through several examples. The second part
More informationEfficient Project Portfolio as a tool for Enterprise Risk Management
Effcent Proect Portfolo as a tool for Enterprse Rsk Management Valentn O. Nkonov Ural State Techncal Unversty Growth Traectory Consultng Company January 5, 27 Effcent Proect Portfolo as a tool for Enterprse
More informationSection 5.4 Annuities, Present Value, and Amortization
Secton 5.4 Annutes, Present Value, and Amortzaton Present Value In Secton 5.2, we saw that the present value of A dollars at nterest rate per perod for n perods s the amount that must be deposted today
More informationWhat is Candidate Sampling
What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble
More informationNear Optimal Online Algorithms and Fast Approximation Algorithms for Resource Allocation Problems
Near Optal Onlne Algorths and Fast Approxaton Algorths for Resource Allocaton Probles ABSTRACT Nhl R Devanur Mcrosoft Research Redond WA USA ndev@crosoftco Balasubraanan Svan Coputer Scences Dept Unv of
More informationMAPP. MERIS level 3 cloud and water vapour products. Issue: 1. Revision: 0. Date: 9.12.1998. Function Name Organisation Signature Date
Ttel: Project: Doc. No.: MERIS level 3 cloud and water vapour products MAPP MAPPATBDClWVL3 Issue: 1 Revson: 0 Date: 9.12.1998 Functon Name Organsaton Sgnature Date Author: Bennartz FUB Preusker FUB Schüller
More informationInternational Journal of Information Management
Internatonal Journal of Inforaton Manageent 32 (2012) 409 418 Contents lsts avalable at ScVerse ScenceDrect Internatonal Journal of Inforaton Manageent j our nal ho e p age: www.elsever.co/locate/jnfogt
More informationInternational Journal of Industrial Engineering Computations
Internatonal Journal of Industral ngneerng Coputatons 3 (2012) 393 402 Contents lsts avalable at GrowngScence Internatonal Journal of Industral ngneerng Coputatons hoepage: www.growngscence.co/jec Suppler
More informationJoint Resource Allocation and BaseStation. Assignment for the Downlink in CDMA Networks
Jont Resource Allocaton and BaseStaton 1 Assgnment for the Downlnk n CDMA Networks Jang Won Lee, Rav R. Mazumdar, and Ness B. Shroff School of Electrcal and Computer Engneerng Purdue Unversty West Lafayette,
More informationDynamic Resource Allocation in Clouds: Smart Placement with Live Migration
Dynac Resource Allocaton n Clouds: Sart Placeent wth Lve Mgraton Mahlouf Had Ingéneur de Recherche ahlouf.had@rtsystex.fr Avec : Daal Zeghlache (TSP) daal.zeghlache@telecosudpars.eu FONDATION DE COOPERATION
More informationRiskbased Fatigue Estimate of Deep Water Risers  Course Project for EM388F: Fracture Mechanics, Spring 2008
Rskbased Fatgue Estmate of Deep Water Rsers  Course Project for EM388F: Fracture Mechancs, Sprng 2008 Chen Sh Department of Cvl, Archtectural, and Envronmental Engneerng The Unversty of Texas at Austn
More informationDownlink Power Allocation for Multiclass. Wireless Systems
Downlnk Power Allocaton for Multclass 1 Wreless Systems JangWon Lee, Rav R. Mazumdar, and Ness B. Shroff School of Electrcal and Computer Engneerng Purdue Unversty West Lafayette, IN 47907, USA {lee46,
More information