Based on PSO cloud computing server points location searching

Size: px
Start display at page:

Download "Based on PSO cloud computing server points location searching"

Transcription

1 Iteratoa Worshop o Coud Coput ad Iforato Securty (CCIS 13) Based o PSO coud coput server pots ocato search Che Hua-sha Iforato Techooy Ceter Shaha Iteratoa Studes Uversty Shaha, cha, E-a: huasha@shsu.edu.c She jaje Coputer ceter of Schoo of Iforato Scece & Techooy East cha ora uversty Shaha, cha, E-a: @ecu.c Abstract: A to probe of how to optze the coud coput ocato, a proved PSO aorth s desed to hade ths probe, us the proved PSO aorth servers ocato ad coucato cost ca be optzed uder coud coput stuato. Thouh theoretca dervato, the correctess of proved PSO aorth s proofed. The correctess of theoretca dervato s aso verfed by the experet. Keyword: coud coput, partce swar optzato, coucato cost I Itroducto Wth the deveopet of the coud coput, ad ore ad ore appcato s upoad to the coud se, however the how to ocate the coud coput server ode rea a questo to debate. I the paper, a proved PSO aorth s preseted to hade ths probe. Thouh the theoretca devato, the correctess of the aorth s proofed. The correctess of the theoretca devato s verfed by the experet. The paper s orazed as foow: I secod secto of paper, the reated wor w troduced. I the thrd secto of paper proved PSO aorth w be preseted. The experet ad ts resut w appear forth secto. The ffth secto s the resut. II reated wor.1 coud coput Coud coput [1] s hot topc both research ad appcato deveopet. May paper dscus about ths topc []-[1], for exape soe paper are ore focus to the defto of the coud coput other are appcato estabsh ad the ode. It s true that the coud coput w becoe a coputer oraze for of ext eerato. The coud coput aso cost vary probe, for exape how to fd the resource optzato cost ad how to ae the fredy ferece the the coud stuato.. partce swar optzato Stadard PSO aorth s frst preseted by Keedy, Eberhart 1995 [13]. After stadard PSO aorth, there are a ot of proveet, ad severa appcato ad case have aready bee soved by the PSO aorth...1 the fucto of the stadard PSO aorth as: as: The posto ad veocty of swar as foow: X ( x 1, x,.., x D) (1 ) V (v1, v,..,vd) (1) The optzato vaue of the partce s ared p ( x x,..., x ) (), 1 The optzato vaue of the swar s ared p ( x1, x,.., x) (3) Each partce w chae posto ad veocty the every step based o the foow fucto: v x 1 1 v x c ( p v 1 1 x ) c ( p d x.. The descrpto of the stadard PSO aorth The step of stadard PSO aorth as foow: ) (4) Step 1: taze the swar cude the posto ad veocty Step : us the PSO aorth to fd the optzato vaue. partce( Step.1: fd the optzato vaue of each p ) ad optzato vaue of swar( p ). 13. The authors - Pubshed by Atats Press 341

2 Step.: update the posto ad veocty based o fucto 4. partce. Step.3: cacuate the taret fucto vaue of each Step.4: f step uber ber tha axu step uber or the optzato vaue s reached o to step 3,ese o to step.1. Step 3: Prt the optzato vaue The proved PSO aorth have bee preseted by vary papers [14]-[5], for exape how to cobe the PSO aorth wth SVM aorth wth optzato paraeters ad how to use dfferet d of proved PSO aorth to sove vary probes. III Iproved PSO aorth ad aorth's characters 3.1 The assupto ad defto of PSO aorth Assupto 1: The coucato cost s crease wth the dstace betwee the odes. Assupto : Oe coud server oy ca ocate severa dfferet pace whch s cose to each other. Assupto 3: The ceter data base ca coect a aets data after coucated wth a aets, ad oy after t coucate wth a aets. Assupto 4: Oe cty ca have severa dfferet server odes. Defto 1: the uber of server whch coucate wth ceter base each cty ode s caed as the coucato uber. Defto : the cty server ode whch s cosest to the ceter data base s caed as cosest dstace betwee cty ad partce ared as s j ar ( p ) (5) j s posto of cty ode j. p s partce. Defto 3 the varabe rae of the partce s caed as the partce rae. ared as j RP. Note: the partce rae shoud cude a the server ode of oe cty. Defto 4: the dstace betwee the cty server j ad the ceter data base s caed as the coucato eth betwee the cty server j ad the ceter data base, ared as: j j sd (6) j s the cty server j, sd the ceter data base. The u the coucato eth betwee the cty server j ad the ceter data base s caed the u coucato eth betwee cty ad data base, ared as sd (7) j 1 j s the cty server j, sd the ceter data base. Defto 5: the tota coucato eth s caed as the tota coucato eth, ared as j j 1 j1 1 s the tota dstace, j (8) s the coucato eth betwee the cty server j ad the ceter data base. The u vaue of tota coucato eth s caed as the u coucato eth. ared as M (9) 3. The descrpto of proved PSO aorth foow: The descrpto of proved PSO aorth as Step 1: taze the swar cude the posto ad veocty. Step : us PSO to fd the u su dstace of the Step.1: fd the optzato vaue of each partce ( p ) ad optzato vaue of swar( p ). Step.: update the posto ad veocty based o fucto 4. Step.3: chec a partce ocato, ad f the partce outse of reo fx t. partce. Step.4: cacuate the taret fucto vaue of each Step.5 f the step uber s ber tha axu step uber or the optzato vaue o to step 3,ese o 34

3 to step.1. whch Step.6:search the pot whch s se of se Step 3: prt the resut server ode Fro step.1 to step.4, the process of proveet PSO aorth s as sae as the stadard PSO aorth. The a dfferece betwee the proveet PSO 3.3 The character of proved PSO aorth Theore 1: f every seected ode s cosest to the ceter data base the tota coucato w becoe the u coucato eth. If the tota coucato u coucato eth, accord to the fucto 9 ad fucto 8: M ad because a the j the u vaue of fucto equa to: 1 j1 1 1 j1 1 j depedet wth each other, j 1 j1 1 So f ad oy f a the the coucato eth betwee the cty server j ad the ceter data base s u, the optzato vaue w be reached. Iferece 1: f the proveet PSO ca fd the cose pot every cty the u tota coucato eth w be foud. As the theore 1 f a the u coucato eth betwee cty ad data base s reached, the u tota coucato eth w be foud, so f a the u coucato eth s foud by PSO aorth, the u tota coucato eth. tota coucato eth w be Theore : f the partce rae s sa eouh, the tota coucato eth w chae a tte betwee dfferet rouds of experet. If the the partce rae s sa eouh that oe sty oo e oe pot copar wth the dstace betwee j the ctys s very sa ad oo e a pot. So the dstace dfferet betwee the dfferet experet roud w be cose. Iferece : f the partce rae s sa eouh, the tota coucato eth crease wth coucato uber, t s cose to drect rato. Accord to the theore, f the partce rae s sa eouh that the dfferet betwee the experet roud w be very sa. So f the coucato uber s, t s equa to te experet of search cosest cty aet pot to the ceter data base. 1 j1 1 w1 w1 1 j1 1 w1 w eth, w jw jw jw s the w roud of the tota coucato s coucato eth betwee the cty server j ad the ceter data base roud w ad The... 1 s roud tota coucato eth. So the tota eth of the coucato eth s cose to the su of te of the tota eth of coucato eth whe coucato uber s 1. ad w1 So the theore s proofed w1... IV 4.1 The experet data Experet The data atera of ths experet s coe fro 343

4 ad the experet data s estabshed as foows: Step1: seect severa dfferet severa data-sets of TSP fro the TSP database, ad use oe pot represets a server ode of the coud. The data-set represets oe cty. Step: each ode pus a offset whch far ber tha the coordate of dataset s ode coordate, ad ae sure the sae dataset ode hav sae offset. Step3: ae sure a dataset s far away fro each other, or o to step. Step 4: set the ocato of ceter data base. The seected dataset ad offset as foows: Tabe1 data of experece Coud Dataset Coordate The TSP ae offset eth 1 e51 (,) 46 e51 (,) 46 3 e76 (1,1) e11 (,5) 69 5 e51 (,) 46 6 e51 (5,) 46 As tabe 1 shows the a cty s created by 3 dfferet data sets, ad offset s far arer tha TSP eth. The coordate of the ceter data base s ocato s (16, 1) ad (6, 7). 4. The experet resut Fure 1 shows the ode of cty ad ceter base ocato Fure show the proved PSO aorth resut of uder stuato oe server ode each cty. the dstace of the coucato x 14 1 tota dstace of coucato eth betwee experet roud experet uber Fure Tota dstace of coucato eth betwee experet roud ceter base1 ceter base The fure shows the tota coucato eth betwee roud ubers. The coucato eth betwee the dfferet experet roud s cose to each other because the stabty of proved PSO aorth ad the reo s ft for the experet whch fts theore. Fure 3 shows the reatoshp betwee the coucato uber ad the coucato eth. 15 x 14 the reatoshp betwee the coucato uber ad coucato eth ceter base 1 ceter base 5 15 the ode ocato of the coud cty 1 cty cty 3 cty 4 cty 5 cty 6 ceter base1 ceter base the coucato eth 1 5 y x Fure 1 the ode ocato of the coud Fure 1 shows the ode of the experet ad the two ceter base. The reaso why the cty 1oos e oe pot s that se dstace of cty s far saer tha the dstace betwee the cty uber of each cty coucato ode Fure 3 the reatoshp betwee the coucato uber ad coucato eth Fure 3 show the reatoshp betwee coucato ode uber of each cty ad the tota coucato. The fure shows the coucato eth wth the crease of the ode uber of each cty, ad t s aost e to be drect rato whch s fts wth ferece. 344

5 V cocuso The proveet PSO aorth s preseted to hade the probe of coud coput server pots ocato. Thouh theoretca dervato, the correctess of the aorth. The correctess of the theoretca dervato s verfed by the experet. Referece [1] M. Arbrust, A. Fox, R. Grffth. A vew of coud coput. Coucatos of the ac. Vo. 53, ss. 4, apr 1, pp [] D. Nur, R. Wos, C. Grzeorczy. The eucayptus ope-source coud-coput syste. custer coput ad the r, 9. ccr '9. 9th pp [3] L. youseff, M. Butrco, D. D. Sva. Toward a ufed otooy of coud coput. Gr coput evroets worshop, 8. ce '8 pp. 1-1 [4] qa wa, u re, wej ou. Prvacy-preserv pubc audt for data storae securty coud coput.foco, 1 proceeds eee. pp. 1-9 [5] L. Wa, G. Laszews, A. Youe. Coud coput: a perspectve study.ew eerato coput. Vo. 8, ss., 1, pp [6] M. D. D. Assução, A. D. Costazo. Evauat the cost-beeft of us coud coput to exted the capacty of custers. Hp '9 proceeds of the 18th ac teratoa syposu o hh perforace dstrbuted coput pp [7] K. Kuar, Y. H. Lu. Coud coput for obe users: ca offoad coputato save eery?. Coputer. Vo. 43, ss. 4, 1, pp [8]. Suta.coud coput for educato: a ew daw?. Iteratoa joura of forato aaeet 1. pp [9] H. Taab, J. B.d. Josh,.-j. Ah. Securty ad prvacy chaees coud coput evroets. Ieee securty ad prvacy. Vo. 8, ss. 6, 1, pp [1] S. Subash, V. Kavtha. A survey o securty ssues servce devery odes ofcouoput. Joura of etwor ad coputer appcatos. Vo , pp. 1 1 [11] Q. Zha, L. Che, R. Boutaba. Coud coput: state-of-the-art ad research chaees. Joura of teret servces ad appcatos. 1, vo. 1, ss. 1. pp [1] Q. Wa, C. Wa, K. Re, W. J. Lo, J. L. Eab pubc audtabty ad data dyacs for storae securty coud coput. Ieee trasactos o parae ad dstrbuted systes, vo., o. 5, ay 11 pp [13] eedy j, eberhart r c. Partce swar optzato[c]//proceeds of eee teratoa coferece o eura etwors.pscataway ew jersey : sttute of eectrca ad eectrocs eeers,c. 1995: [14] M. Mada, A. Muhopadhyay. A utobjectve pso-based approach for etfy o-redudat ee arers fro croarray ee expresso data. Coput, coucato ad appcatos (ccca). pp. 1-6 [15] b. Lu,. Wa, ad y. H. J. A effectve pso-based eetc aorth for fow shop schedu. Ieee trasactos o systes, a, ad cyberetcs part b: cyberetcs, vo. 37, ss. 1, feb. 7. pp [16]. Messerscht, a. P. Eebrech. Lear to pay aes us a pso-based copettve ear approach. Evoutoary coputato, vo. 8, ss. 3, ju. 4. pp [17] K. W. Chau. appcato of a pso-based eura etwor aayss of outcoes of costructo cas. Autoato costructo. vo. 16, 7, pp [18] Mohaed Ahed Mohades. Mode oba soar radato us Partce Swar Optzato (PSO). Soar Eery. vo. 86, ss. 11, ov. 1, pp [19] J. Yu, S. Wa,. X. Evov artfca eura etwors us a proved pso ad dpso. Neurocoput. vo. 71, 8, pp [] C.-L. Hua, J.-F. Du. A dstrbuted pso sv hybr syste wth feature seecto ad paraeter optzato. Apped soft coput. vo. 8, ss. 4, septeber 8, pp [1] M. Mada, A. Muhopadhyay. A utobjectve PSO-based approach for etfy o-redudat ee arers fro croarray ee expresso data. Coput. Coucato ad Appcatos (ICCCA). pp. 1-6 [] Archaa Saraa,Rab Kuar Mahapatrab,Sba Prasada Parah.DEPSO ad PSO-QI dta fter des. Expert Systes wth Appcatos. Vo. 38, Iss. 9, Sep. 11.pp [3] J. L. Feradez-Martıez, E. G.-Gozao Stochastc Stabty Aayss of the Lear Cotuous ad Dscrete PSO Modes. Evoutoary Coputato. Vo. 15, Iss. 3,Ju. 11. pp [4].A. Sara a, R. K. Mahapatra b, S. Prasada Parah. DEPSO ad PSO-QI dta fter des. Expert Systes wth Appcatos. Vo. 38, 11. pp [5] A. Chadera,A. Chatterjeec, P. Sarrya,. A ew soca ad oetu copoet adaptve PSO aorth for ae seetato. Expert Systes wth Appcatos. Expert Systes wth Appcatos. Vo. 38, 11. pp

Measuring the Quality of Credit Scoring Models

Measuring the Quality of Credit Scoring Models Measur the Qualty of Credt cor Models Mart Řezáč Dept. of Matheatcs ad tatstcs, Faculty of cece, Masaryk Uversty CCC XI, Edurh Auust 009 Cotet. Itroducto 3. Good/ad clet defto 4 3. Measur the qualty 6

More information

STOCK INVESTMENT MANAGEMENT UNDER UNCERTAINTY. Madalina Ecaterina ANDREICA 1 Marin ANDREICA 2

STOCK INVESTMENT MANAGEMENT UNDER UNCERTAINTY. Madalina Ecaterina ANDREICA 1 Marin ANDREICA 2 "AROACHES IN ORGANISATIONA MANAGEMENT" 15-16 Noveber 01, BCHAREST, ROMANIA STOCK INVESTMENT MANAGEMENT NDER NCERTAINTY Madaa Ecatera ANDREICA 1 Mar ANDREICA ABSTRACT Ths paper presets a stock vestet aageet

More information

A Study of Unrelated Parallel-Machine Scheduling with Deteriorating Maintenance Activities to Minimize the Total Completion Time

A Study of Unrelated Parallel-Machine Scheduling with Deteriorating Maintenance Activities to Minimize the Total Completion Time Joural of Na Ka, Vol. 0, No., pp.5-9 (20) 5 A Study of Urelated Parallel-Mache Schedulg wth Deteroratg Mateace Actvtes to Mze the Total Copleto Te Suh-Jeq Yag, Ja-Yuar Guo, Hs-Tao Lee Departet of Idustral

More information

APPENDIX III THE ENVELOPE PROPERTY

APPENDIX III THE ENVELOPE PROPERTY Apped III APPENDIX III THE ENVELOPE PROPERTY Optmzato mposes a very strog structure o the problem cosdered Ths s the reaso why eoclasscal ecoomcs whch assumes optmzg behavour has bee the most successful

More information

Decision Science Letters

Decision Science Letters Decso Scece Letters 1 (2012) 11 22 Cotets sts avaabe at GrowgScece Decso Scece Letters hoepage: www.growgscece.co/ds A Fuzzy-MOORA approach for ERP syste seecto Prasad Karade a ad Shakar Chakraborty b*

More information

The simple linear Regression Model

The simple linear Regression Model The smple lear Regresso Model Correlato coeffcet s o-parametrc ad just dcates that two varables are assocated wth oe aother, but t does ot gve a deas of the kd of relatoshp. Regresso models help vestgatg

More information

1. The Time Value of Money

1. The Time Value of Money Corporate Face [00-0345]. The Tme Value of Moey. Compoudg ad Dscoutg Captalzato (compoudg, fdg future values) s a process of movg a value forward tme. It yelds the future value gve the relevat compoudg

More information

Abraham Zaks. Technion I.I.T. Haifa ISRAEL. and. University of Haifa, Haifa ISRAEL. Abstract

Abraham Zaks. Technion I.I.T. Haifa ISRAEL. and. University of Haifa, Haifa ISRAEL. Abstract Preset Value of Autes Uder Radom Rates of Iterest By Abraham Zas Techo I.I.T. Hafa ISRAEL ad Uversty of Hafa, Hafa ISRAEL Abstract Some attempts were made to evaluate the future value (FV) of the expected

More information

Green Master based on MapReduce Cluster

Green Master based on MapReduce Cluster Gree Master based o MapReduce Cluster Mg-Zh Wu, Yu-Chag L, We-Tsog Lee, Yu-Su L, Fog-Hao Lu Dept of Electrcal Egeerg Tamkag Uversty, Tawa, ROC Dept of Electrcal Egeerg Tamkag Uversty, Tawa, ROC Dept of

More information

Angles formed by 2 Lines being cut by a Transversal

Angles formed by 2 Lines being cut by a Transversal Chapter 4 Anges fored by 2 Lines being cut by a Transversa Now we are going to nae anges that are fored by two ines being intersected by another ine caed a transversa. 1 2 3 4 t 5 6 7 8 If I asked you

More information

Polyphase Filters. Section 12.4 Porat 1/39

Polyphase Filters. Section 12.4 Porat 1/39 Polyphase Flters Secto.4 Porat /39 .4 Polyphase Flters Polyphase s a way of dog saplg-rate coverso that leads to very effcet pleetatos. But ore tha that, t leads to very geeral vewpots that are useful

More information

Fuzzy Task Assignment Model of Web Services Supplier in Collaborative Development Environment

Fuzzy Task Assignment Model of Web Services Supplier in Collaborative Development Environment , pp.199-210 http://dx.do.org/10.14257/uesst.2015.8.6.19 Fuzzy Task Assget Model of Web Servces Suppler Collaboratve Developet Evroet Su Ja 1,2, Peg Xu-ya 1, *, Xu Yg 1,3, Wag Pe-e 2 ad Ma Na- 4,2 1. College

More information

6.7 Network analysis. 6.7.1 Introduction. References - Network analysis. Topological analysis

6.7 Network analysis. 6.7.1 Introduction. References - Network analysis. Topological analysis 6.7 Network aalyss Le data that explctly store topologcal formato are called etwork data. Besdes spatal operatos, several methods of spatal aalyss are applcable to etwork data. Fgure: Network data Refereces

More information

Numerical Comparisons of Quality Control Charts for Variables

Numerical Comparisons of Quality Control Charts for Variables Global Vrtual Coferece Aprl, 8. - 2. 203 Nuercal Coparsos of Qualty Cotrol Charts for Varables J.F. Muñoz-Rosas, M.N. Pérez-Aróstegu Uversty of Graada Facultad de Cecas Ecoócas y Epresarales Graada, pa

More information

Optimal multi-degree reduction of Bézier curves with constraints of endpoints continuity

Optimal multi-degree reduction of Bézier curves with constraints of endpoints continuity Computer Aded Geometrc Desg 19 (2002 365 377 wwwelsevercom/locate/comad Optmal mult-degree reducto of Bézer curves wth costrats of edpots cotuty Guo-Dog Che, Guo-J Wag State Key Laboratory of CAD&CG, Isttute

More information

Numerical Methods with MS Excel

Numerical Methods with MS Excel TMME, vol4, o.1, p.84 Numercal Methods wth MS Excel M. El-Gebely & B. Yushau 1 Departmet of Mathematcal Sceces Kg Fahd Uversty of Petroleum & Merals. Dhahra, Saud Araba. Abstract: I ths ote we show how

More information

Energy Density / Energy Flux / Total Energy in 3D

Energy Density / Energy Flux / Total Energy in 3D Lecture 5 Phys 75 Energy Density / Energy Fux / Tota Energy in D Overview and Motivation: In this ecture we extend the discussion of the energy associated with wave otion to waves described by the D wave

More information

IDENTIFICATION OF THE DYNAMICS OF THE GOOGLE S RANKING ALGORITHM. A. Khaki Sedigh, Mehdi Roudaki

IDENTIFICATION OF THE DYNAMICS OF THE GOOGLE S RANKING ALGORITHM. A. Khaki Sedigh, Mehdi Roudaki IDENIFICAION OF HE DYNAMICS OF HE GOOGLE S RANKING ALGORIHM A. Khak Sedgh, Mehd Roudak Cotrol Dvso, Departmet of Electrcal Egeerg, K.N.oos Uversty of echology P. O. Box: 16315-1355, ehra, Ira sedgh@eetd.ktu.ac.r,

More information

A Comparative Study for Email Classification

A Comparative Study for Email Classification A Coparatve Study for Eal Classfcato Seogwook You ad Des McLeod Uversty of Souther Calfora, Los Ageles, CA 90089 USA Abstract - Eal has becoe oe of the fastest ad ost ecoocal fors of coucato. However,

More information

A Fair Non-repudiation Protocol without TTP on Conic Curve over Ring

A Fair Non-repudiation Protocol without TTP on Conic Curve over Ring Far No-reudato Protocol wthout TTP o Coc Curve over Rg Z L Zhahu, Fa Ka, 3L Hu, Zheg Ya Far No-reudato Protocol wthout TTP o Coc Curve over Rg Z 1 L Zhahu, Fa Ka, 3 L Hu, 4 Zheg Ya 1State Key Laboratory

More information

SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN

SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN Wojcech Zelńsk Departmet of Ecoometrcs ad Statstcs Warsaw Uversty of Lfe Sceces Nowoursyowska 66, -787 Warszawa e-mal: wojtekzelsk@statystykafo Zofa Hausz,

More information

STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ " 1

STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ  1 STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS Recall Assumpto E(Y x) η 0 + η x (lear codtoal mea fucto) Data (x, y ), (x 2, y 2 ),, (x, y ) Least squares estmator ˆ E (Y x) ˆ " 0 + ˆ " x, where ˆ

More information

ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN

ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN Colloquum Bometrcum 4 ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN Zofa Hausz, Joaa Tarasńska Departmet of Appled Mathematcs ad Computer Scece Uversty of Lfe Sceces Lubl Akademcka 3, -95 Lubl

More information

Lecture 7. Norms and Condition Numbers

Lecture 7. Norms and Condition Numbers Lecture 7 Norms ad Codto Numbers To dscuss the errors umerca probems vovg vectors, t s usefu to empo orms. Vector Norm O a vector space V, a orm s a fucto from V to the set of o-egatve reas that obes three

More information

Developing a Fuzzy Search Engine Based on Fuzzy Ontology and Semantic Search

Developing a Fuzzy Search Engine Based on Fuzzy Ontology and Semantic Search 0 IEEE Iteratoal Coferece o Fuzzy Systes Jue 7-30, 0, Tape, Tawa Developg a Fuzzy Search Ege Based o Fuzzy Otology ad Seatc Search Le-Fu La Chao-Ch Wu Pe-Yg L Dept. of Coputer Scece ad Iforato Egeerg Natoal

More information

A Covariance Analysis Model for DDoS Attack Detection*

A Covariance Analysis Model for DDoS Attack Detection* A Covarace Aayss Mode or DDoS Attac Detecto* Shuyua J Deartmet o Comutg HogKog Poytechc Uversty HogKog Cha cssy@com.oyu.edu.h Dae S. Yeug Deartmet o Comutg HogKog Poytechc Uversty HogKog Cha csdae@et.oyu.edu.h

More information

Chapter Eight. f : R R

Chapter Eight. f : R R Chapter Eght f : R R 8. Itroducto We shall ow tur our atteto to the very mportat specal case of fuctos that are real, or scalar, valued. These are sometmes called scalar felds. I the very, but mportat,

More information

ANOVA Notes Page 1. Analysis of Variance for a One-Way Classification of Data

ANOVA Notes Page 1. Analysis of Variance for a One-Way Classification of Data ANOVA Notes Page Aalss of Varace for a Oe-Wa Classfcato of Data Cosder a sgle factor or treatmet doe at levels (e, there are,, 3, dfferet varatos o the prescrbed treatmet) Wth a gve treatmet level there

More information

Preprocess a planar map S. Given a query point p, report the face of S containing p. Goal: O(n)-size data structure that enables O(log n) query time.

Preprocess a planar map S. Given a query point p, report the face of S containing p. Goal: O(n)-size data structure that enables O(log n) query time. Computatoal Geometry Chapter 6 Pot Locato 1 Problem Defto Preprocess a plaar map S. Gve a query pot p, report the face of S cotag p. S Goal: O()-sze data structure that eables O(log ) query tme. C p E

More information

Generalized solutions for the joint replenishment problem with correction factor

Generalized solutions for the joint replenishment problem with correction factor Geerzed soutos for the ot repeshet proe wth correcto fctor Astrct Erc Porrs, Roert Deer Ecooetrc Isttute, erge Isttute, Ersus Uversty Rotterd, P.O. Box 73, 3 DR Rotterd, he etherds Ecooetrc Isttute Report

More information

A New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree

A New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree , pp.277-288 http://dx.do.org/10.14257/juesst.2015.8.1.25 A New Bayesa Network Method for Computg Bottom Evet's Structural Importace Degree usg Jotree Wag Yao ad Su Q School of Aeroautcs, Northwester Polytechcal

More information

Online Appendix: Measured Aggregate Gains from International Trade

Online Appendix: Measured Aggregate Gains from International Trade Ole Appedx: Measured Aggregate Gas from Iteratoal Trade Arel Burste UCLA ad NBER Javer Cravo Uversty of Mchga March 3, 2014 I ths ole appedx we derve addtoal results dscussed the paper. I the frst secto,

More information

A Parallel Transmission Remote Backup System

A Parallel Transmission Remote Backup System 2012 2d Iteratoal Coferece o Idustral Techology ad Maagemet (ICITM 2012) IPCSIT vol 49 (2012) (2012) IACSIT Press, Sgapore DOI: 107763/IPCSIT2012V495 2 A Parallel Trasmsso Remote Backup System Che Yu College

More information

Report 52 Fixed Maturity EUR Industrial Bond Funds

Report 52 Fixed Maturity EUR Industrial Bond Funds Rep52, Computed & Prted: 17/06/2015 11:53 Report 52 Fxed Maturty EUR Idustral Bod Fuds From Dec 2008 to Dec 2014 31/12/2008 31 December 1999 31/12/2014 Bechmark Noe Defto of the frm ad geeral formato:

More information

Assigning Tasks in a 24-Hour Software Development Model

Assigning Tasks in a 24-Hour Software Development Model Assigning Tasks in a -Hour Software Deveopent Mode Pankaj Jaote, Gourav Jain Departent of Coputer Science & Engineering Indian Institute of Technoogy, Kanpur, INDIA 006 Eai:{jaote, gauravj}@iitk.ac.in

More information

Security Analysis of RAPP: An RFID Authentication Protocol based on Permutation

Security Analysis of RAPP: An RFID Authentication Protocol based on Permutation Securty Aalyss of RAPP: A RFID Authetcato Protocol based o Permutato Wag Shao-hu,,, Ha Zhje,, Lu Sujua,, Che Da-we, {College of Computer, Najg Uversty of Posts ad Telecommucatos, Najg 004, Cha Jagsu Hgh

More information

10/19/2011. Financial Mathematics. Lecture 24 Annuities. Ana NoraEvans 403 Kerchof AnaNEvans@virginia.edu http://people.virginia.

10/19/2011. Financial Mathematics. Lecture 24 Annuities. Ana NoraEvans 403 Kerchof AnaNEvans@virginia.edu http://people.virginia. Math 40 Lecture 24 Autes Facal Mathematcs How ready do you feel for the quz o Frday: A) Brg t o B) I wll be by Frday C) I eed aother week D) I eed aother moth Aa NoraEvas 403 Kerchof AaNEvas@vrga.edu http://people.vrga.edu/~as5k/

More information

Load and Resistance Factor Design (LRFD)

Load and Resistance Factor Design (LRFD) 53:134 Structural Desg II Load ad Resstace Factor Desg (LRFD) Specfcatos ad Buldg Codes: Structural steel desg of buldgs the US s prcpally based o the specfcatos of the Amerca Isttute of Steel Costructo

More information

Finance 360 Problem Set #6 Solutions

Finance 360 Problem Set #6 Solutions Finance 360 Probem Set #6 Soutions 1) Suppose that you are the manager of an opera house. You have a constant margina cost of production equa to $50 (i.e. each additiona person in the theatre raises your

More information

Automated Alignment and Extraction of Bilingual Ontology for Cross-Language Domain-Specific Applications

Automated Alignment and Extraction of Bilingual Ontology for Cross-Language Domain-Specific Applications Automated Agmet ad Extracto of gua Otoogy for Cross-Laguage Doma-Specfc Appcatos Ju-Feg Yeh, Chug-Hse Wu, Mg-Ju Che ad Lag-Chh Yu Departmet of Computer Scece ad Iformato Egeerg Natoa Cheg Kug Uversty,

More information

The Gompertz-Makeham distribution. Fredrik Norström. Supervisor: Yuri Belyaev

The Gompertz-Makeham distribution. Fredrik Norström. Supervisor: Yuri Belyaev The Gompertz-Makeham dstrbuto by Fredrk Norström Master s thess Mathematcal Statstcs, Umeå Uversty, 997 Supervsor: Yur Belyaev Abstract Ths work s about the Gompertz-Makeham dstrbuto. The dstrbuto has

More information

Applications of Support Vector Machine Based on Boolean Kernel to Spam Filtering

Applications of Support Vector Machine Based on Boolean Kernel to Spam Filtering Moder Appled Scece October, 2009 Applcatos of Support Vector Mache Based o Boolea Kerel to Spam Flterg Shugag Lu & Keb Cu School of Computer scece ad techology, North Cha Electrc Power Uversty Hebe 071003,

More information

ECONOMIC CHOICE OF OPTIMUM FEEDER CABLE CONSIDERING RISK ANALYSIS. University of Brasilia (UnB) and The Brazilian Regulatory Agency (ANEEL), Brazil

ECONOMIC CHOICE OF OPTIMUM FEEDER CABLE CONSIDERING RISK ANALYSIS. University of Brasilia (UnB) and The Brazilian Regulatory Agency (ANEEL), Brazil ECONOMIC CHOICE OF OPTIMUM FEEDER CABE CONSIDERING RISK ANAYSIS I Camargo, F Fgueredo, M De Olvera Uversty of Brasla (UB) ad The Brazla Regulatory Agecy (ANEE), Brazl The choce of the approprate cable

More information

A particle swarm optimization to vehicle routing problem with fuzzy demands

A particle swarm optimization to vehicle routing problem with fuzzy demands A partcle swarm optmzato to vehcle routg problem wth fuzzy demads Yag Peg, Ye-me Qa A partcle swarm optmzato to vehcle routg problem wth fuzzy demads Yag Peg 1,Ye-me Qa 1 School of computer ad formato

More information

Mean number of years to complete the program 5.9 5.4 5.6 7.4 5.7 6.0 6.6 6.0

Mean number of years to complete the program 5.9 5.4 5.6 7.4 5.7 6.0 6.6 6.0 Te to Copeto for PsyD Graduates Year wc Degrees were Coferred Outcoe Tota Tota uber of studets wt doctora degree coferred o trascrpt 12 14 11 11 12 19 8 87 Mea uber of years to copete te progra 5.9 5.4

More information

An SVR-Based Data Farming Technique for Web Application

An SVR-Based Data Farming Technique for Web Application A SVR-Based Data Farmg Techque for Web Appcato Ja L 1 ad Mjg Peg 2 1 Schoo of Ecoomcs ad Maagemet, Behag Uversty 100083 Bejg, P.R. Cha Ja@wyu.c 2 Isttute of Systems Scece ad Techoogy, Wuy Uversty, Jagme

More information

AP Statistics 2006 Free-Response Questions Form B

AP Statistics 2006 Free-Response Questions Form B AP Statstcs 006 Free-Respose Questos Form B The College Board: Coectg Studets to College Success The College Board s a ot-for-proft membershp assocato whose msso s to coect studets to college success ad

More information

A DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS

A DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS L et al.: A Dstrbuted Reputato Broker Framework for Web Servce Applcatos A DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS Kwe-Jay L Departmet of Electrcal Egeerg ad Computer Scece

More information

CHAPTER 2. Time Value of Money 6-1

CHAPTER 2. Time Value of Money 6-1 CHAPTER 2 Tme Value of Moey 6- Tme Value of Moey (TVM) Tme Les Future value & Preset value Rates of retur Autes & Perpetutes Ueve cash Flow Streams Amortzato 6-2 Tme les 0 2 3 % CF 0 CF CF 2 CF 3 Show

More information

DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT

DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT ESTYLF08, Cuecas Meras (Meres - Lagreo), 7-9 de Septembre de 2008 DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT José M. Mergó Aa M. Gl-Lafuete Departmet of Busess Admstrato, Uversty of Barceloa

More information

Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), January Edition, 2011

Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), January Edition, 2011 Cyber Jourals: Multdscplary Jourals cece ad Techology, Joural of elected Areas Telecommucatos (JAT), Jauary dto, 2011 A ovel rtual etwork Mappg Algorthm for Cost Mmzg ZHAG hu-l, QIU Xue-sog tate Key Laboratory

More information

An Approach to Evaluating the Computer Network Security with Hesitant Fuzzy Information

An Approach to Evaluating the Computer Network Security with Hesitant Fuzzy Information A Approach to Evaluatg the Computer Network Securty wth Hestat Fuzzy Iformato Jafeg Dog A Approach to Evaluatg the Computer Network Securty wth Hestat Fuzzy Iformato Jafeg Dog, Frst ad Correspodg Author

More information

Application of GA with SVM for Stock Price Prediction in Financial Market

Application of GA with SVM for Stock Price Prediction in Financial Market Iteratoa Joura of Scece ad Research (IJSR) ISSN (Oe): 39-7064 Impact Factor (0): 3.358 Appcato of GA wth SVM for Stock Prce Predcto Faca Market Om Prakash Jea, Dr. Sudarsa Padhy Departmet of Computer Scece

More information

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability Egeerg, 203, 5, 4-8 http://dx.do.org/0.4236/eg.203.59b003 Publshed Ole September 203 (http://www.scrp.org/joural/eg) Mateace Schedulg of Dstrbuto System wth Optmal Ecoomy ad Relablty Syua Hog, Hafeg L,

More information

Statistical Pattern Recognition (CE-725) Department of Computer Engineering Sharif University of Technology

Statistical Pattern Recognition (CE-725) Department of Computer Engineering Sharif University of Technology I The Name of God, The Compassoate, The ercful Name: Problems' eys Studet ID#:. Statstcal Patter Recogto (CE-725) Departmet of Computer Egeerg Sharf Uversty of Techology Fal Exam Soluto - Sprg 202 (50

More information

Analyses of Integrity Monitoring Techniques for a Global Navigation Satellite System (GNSS-2)

Analyses of Integrity Monitoring Techniques for a Global Navigation Satellite System (GNSS-2) Aalyses of Iterty Motor echques for a Global Navato Satellte System (GNSS-) heodor Z ad Berd Essfeller Isttute of Geodesy ad Navato (IfEN), Uversty FAF Much D-85577 Neubber, Germay Erw Löhert ad Robert

More information

A Methodology to Improve Cash Demand Forecasting for ATM Network

A Methodology to Improve Cash Demand Forecasting for ATM Network Iteratoal Joural of Coputer ad Electrcal Egeerg, Vol. 5, o., August 03 A Methodolog to Iprove Cash Dead Forecastg for ATM etwork Saad M. Darwsh Abstract Developg cash dead forecastg odel for ATM etwork

More information

ECONOMICS. Calculating loan interest no. 3.758

ECONOMICS. Calculating loan interest no. 3.758 F A M & A N H S E E S EONOMS alculatig loa iterest o. 3.758 y Nora L. Dalsted ad Paul H. Gutierrez Quick Facts... The aual percetage rate provides a coo basis to copare iterest charges associated with

More information

De-Duplication Scheduling Strategy in Real-Time Data Warehouse

De-Duplication Scheduling Strategy in Real-Time Data Warehouse Sed Orders for Reprts to reprts@bethascece.ae he Ope Cyberetcs & Systecs Joural, 25, 9, 37-43 37 Ope Access De-Duplcato Schedulg Strategy Real-e Data Warehouse Hu Lu, Je Sog 2,*, JBoWu 2, ad Yu-B Bao 3

More information

Fractal-Structured Karatsuba`s Algorithm for Binary Field Multiplication: FK

Fractal-Structured Karatsuba`s Algorithm for Binary Field Multiplication: FK Fractal-Structured Karatsuba`s Algorthm for Bary Feld Multplcato: FK *The authors are worg at the Isttute of Mathematcs The Academy of Sceces of DPR Korea. **Address : U Jog dstrct Kwahadog Number Pyogyag

More information

Performance Measurement Model of Multi-Source Data Fusion Based on Network Situation Awareness

Performance Measurement Model of Multi-Source Data Fusion Based on Network Situation Awareness Leag GUO agx CHEN Chao GAO We XIONG Huazhog Uversty of Scece ad Techology Ar orce Radar Acadey Perforace Measureet Model of Mult-Source Data uso Based o Networ Stuato Awareess Abstract. I order to solve

More information

Load Balancing via Random Local Search in Closed and Open systems

Load Balancing via Random Local Search in Closed and Open systems Load Balacg va Rado Local Search Closed ad Ope systes A. Gaesh Dept. of Matheatcs Uversty of Brstol, UK a.gaesh@brstol.ac.u A. Proutere Mcrosoft Research Cabrdge, UK aproute@crosoft.co S. Llethal Stats

More information

FINANCIAL MATHEMATICS 12 MARCH 2014

FINANCIAL MATHEMATICS 12 MARCH 2014 FINNCIL MTHEMTICS 12 MRCH 2014 I ths lesso we: Lesso Descrpto Make use of logarthms to calculate the value of, the tme perod, the equato P1 or P1. Solve problems volvg preset value ad future value autes.

More information

Models for Selecting an ERP System with Intuitionistic Trapezoidal Fuzzy Information

Models for Selecting an ERP System with Intuitionistic Trapezoidal Fuzzy Information JOURNAL OF SOFWARE, VOL 5, NO 3, MARCH 00 75 Models for Selectg a ERP System wth Itutostc rapezodal Fuzzy Iformato Guwu We, Ru L Departmet of Ecoomcs ad Maagemet, Chogqg Uversty of Arts ad Sceces, Yogchua,

More information

CHAPTER FIVE Network Hydraulics

CHAPTER FIVE Network Hydraulics . ETWOR YDRAULICSE CATER IVE Network ydrauics The fudameta reatioships of coservatio of mass ad eergy mathematicay describe the fow ad pressure distributio withi a pipe etwork uder steady state coditios.

More information

A Key-Policy Attribute-Based Broadcast Encryption

A Key-Policy Attribute-Based Broadcast Encryption 444 The Iteratoa rab Joura of Iformato Techooy Vo. 0 o. 5 September 0 Key-Pocy ttrbute-base Broacast Ecrypto J Su Yupu Hu a Leyou ha Departmet of ppcato Mathematcs X a Uversty of Techooy Cha Key Lab of

More information

Multi-Channel Pricing for Financial Services

Multi-Channel Pricing for Financial Services 0-7695-435-9/0 $7.00 (c) 00 IEEE Proceedgs of the 35th Aual Hawa Iteratoal Coferece o yste ceces (HIC-35 0) 0-7695-435-9/0 $7.00 00 IEEE Proceedgs of the 35th Hawa Iteratoal Coferece o yste ceces - 00

More information

A 360 Degree Feedback Model for Performance Appraisal Based on Fuzzy AHP and TOPSIS

A 360 Degree Feedback Model for Performance Appraisal Based on Fuzzy AHP and TOPSIS Iteratoal Joural of Ecooy, aaeet ad Socal Sceces, () Noveber 03, Paes: 969-976 TI Jourals Iteratoal Joural of Ecooy, aaeet ad Socal Sceces www.tourals.co ISSN 306-776 A 360 Deree Feedback odel for Perforace

More information

Classic Problems at a Glance using the TVM Solver

Classic Problems at a Glance using the TVM Solver C H A P T E R 2 Classc Problems at a Glace usg the TVM Solver The table below llustrates the most commo types of classc face problems. The formulas are gve for each calculato. A bref troducto to usg the

More information

CH. V ME256 STATICS Center of Gravity, Centroid, and Moment of Inertia CENTER OF GRAVITY AND CENTROID

CH. V ME256 STATICS Center of Gravity, Centroid, and Moment of Inertia CENTER OF GRAVITY AND CENTROID CH. ME56 STTICS Ceter of Gravt, Cetrod, ad Momet of Ierta CENTE OF GITY ND CENTOID 5. CENTE OF GITY ND CENTE OF MSS FO SYSTEM OF PTICES Ceter of Gravt. The ceter of gravt G s a pot whch locates the resultat

More information

Near Neighbor Distribution in Sets of Fractal Nature

Near Neighbor Distribution in Sets of Fractal Nature Iteratoal Joural of Computer Iformato Systems ad Idustral Maagemet Applcatos. ISS 250-7988 Volume 5 (202) 3 pp. 59-66 MIR Labs, www.mrlabs.et/jcsm/dex.html ear eghbor Dstrbuto Sets of Fractal ature Marcel

More information

Average Price Ratios

Average Price Ratios Average Prce Ratos Morgstar Methodology Paper August 3, 2005 2005 Morgstar, Ic. All rghts reserved. The formato ths documet s the property of Morgstar, Ic. Reproducto or trascrpto by ay meas, whole or

More information

How do bookmakers (or FdJ 1 ) ALWAYS manage to win?

How do bookmakers (or FdJ 1 ) ALWAYS manage to win? How do bookakers (or FdJ ALWAYS aage to w? Itroducto otatos & varables Bookaker's beeft eected value 4 4 Bookaker's strateges5 4 The hoest bookaker 6 4 "real lfe" bookaker 6 4 La FdJ 8 5 How ca we estate

More information

Impact of Interference on the GPRS Multislot Link Level Performance

Impact of Interference on the GPRS Multislot Link Level Performance Impact of Iterferece o the GPRS Multslot Lk Level Performace Javer Gozalvez ad Joh Dulop Uversty of Strathclyde - Departmet of Electroc ad Electrcal Egeerg - George St - Glasgow G-XW- Scotlad Ph.: + 8

More information

The analysis of annuities relies on the formula for geometric sums: r k = rn+1 1 r 1. (2.1) k=0

The analysis of annuities relies on the formula for geometric sums: r k = rn+1 1 r 1. (2.1) k=0 Chapter 2 Autes ad loas A auty s a sequece of paymets wth fxed frequecy. The term auty orgally referred to aual paymets (hece the ame), but t s ow also used for paymets wth ay frequecy. Autes appear may

More information

Project 3 Weight analysis

Project 3 Weight analysis The Faculty of Power ad Aeroautcal Egeerg Arcraft Desg Departet Project 3 Weght aalyss Ths project cossts of two parts. Frst part cludes fuselage teror (cockpt) coceptual desg. Secod part cludes etoed

More information

OPTIMAL KNOWLEDGE FLOW ON THE INTERNET

OPTIMAL KNOWLEDGE FLOW ON THE INTERNET İstabul Tcaret Üverstes Fe Blmler Dergs Yıl: 5 Sayı:0 Güz 006/ s. - OPTIMAL KNOWLEDGE FLOW ON THE INTERNET Bura ORDİN *, Urfat NURİYEV ** ABSTRACT The flow roblem ad the mmum sag tree roblem are both fudametal

More information

Banking (Early Repayment of Housing Loans) Order, 5762 2002 1

Banking (Early Repayment of Housing Loans) Order, 5762 2002 1 akg (Early Repaymet of Housg Loas) Order, 5762 2002 y vrtue of the power vested me uder Secto 3 of the akg Ordace 94 (hereafter, the Ordace ), followg cosultato wth the Commttee, ad wth the approval of

More information

POSTRACK: A Low Cost Real-Time Motion Tracking System for VR Application

POSTRACK: A Low Cost Real-Time Motion Tracking System for VR Application POSTRACK: A Low Cost Real-Te Moto Trackg Syste for VR Applcato Jaeyog Chug, Nagyu K, Gerard Joughyu K, ad Cha-Mo Park VR Laboratory, Departet of Coputer Scece ad Egeerg, Pohag Uversty of Scece ad Techology

More information

Chapter 3 0.06 = 3000 ( 1.015 ( 1 ) Present Value of an Annuity. Section 4 Present Value of an Annuity; Amortization

Chapter 3 0.06 = 3000 ( 1.015 ( 1 ) Present Value of an Annuity. Section 4 Present Value of an Annuity; Amortization Chapter 3 Mathematcs of Face Secto 4 Preset Value of a Auty; Amortzato Preset Value of a Auty I ths secto, we wll address the problem of determg the amout that should be deposted to a accout ow at a gve

More information

Questions? Ask Prof. Herz, herz@ucsd.edu. General Classification of adsorption

Questions? Ask Prof. Herz, herz@ucsd.edu. General Classification of adsorption Questos? Ask rof. Herz, herz@ucsd.edu Geeral Classfcato of adsorpto hyscal adsorpto - physsorpto - dsperso forces - Va der Waals forces - weak - oly get hgh fractoal coerage of surface at low temperatures

More information

Load Balancing Algorithm based Virtual Machine Dynamic Migration Scheme for Datacenter Application with Optical Networks

Load Balancing Algorithm based Virtual Machine Dynamic Migration Scheme for Datacenter Application with Optical Networks 0 7th Iteratoal ICST Coferece o Commucatos ad Networkg Cha (CHINACOM) Load Balacg Algorthm based Vrtual Mache Dyamc Mgrato Scheme for Dataceter Applcato wth Optcal Networks Xyu Zhag, Yogl Zhao, X Su, Ruyg

More information

Investigation of Atwood s machines as Series and Parallel networks

Investigation of Atwood s machines as Series and Parallel networks Ivestiatio of Atwood s achies as Series ad Parallel etworks Jafari Matehkolaee, Mehdi; Bavad, Air Ahad Islaic Azad uiversity of Shahrood, Shahid Beheshti hih school i Sari, Mazadara, Ira ehdisaraviaria@yahoo.co

More information

Case Study. Normal and t Distributions. Density Plot. Normal Distributions

Case Study. Normal and t Distributions. Density Plot. Normal Distributions Case Study Normal ad t Distributios Bret Halo ad Bret Larget Departmet of Statistics Uiversity of Wiscosi Madiso October 11 13, 2011 Case Study Body temperature varies withi idividuals over time (it ca

More information

Finite Production Rate Model With Quality Assurance, Multi-customer and Discontinuous Deliveries

Finite Production Rate Model With Quality Assurance, Multi-customer and Discontinuous Deliveries Fte Producto Rate Model Wth ualty Assurace, Mult-custoer ad Dscotuous Delveres Yua-Shy Peter Chu, L-We L, Fa-Yu Pa 3, Sga Wag Chu * Departet of Idustral Egeerg Chaoyag Uversty of Techology, Tachug 43,

More information

AnySee: Peer-to-Peer Live Streaming

AnySee: Peer-to-Peer Live Streaming ysee: Peer-to-Peer Lve Streamg School of Computer Scece ad Techology Huazhog Uversty of Scece ad Techology Wuha, 40074, Cha {xflao, hj, dfdeg }@hust.edu.c Xaofe Lao, Ha J, *Yuhao Lu, *Loel M. N, ad afu

More information

Research on Single and Mixed Fleet Strategy for Open Vehicle Routing Problem

Research on Single and Mixed Fleet Strategy for Open Vehicle Routing Problem 276 JOURNAL OF SOFTWARE, VOL 6, NO, OCTOBER 2 Research on Snge and Mxed Feet Strategy for Open Vehce Routng Probe Chunyu Ren Heongjang Unversty /Schoo of Inforaton scence and technoogy, Harbn, Chna Ea:

More information

Projection model for Computer Network Security Evaluation with interval-valued intuitionistic fuzzy information. Qingxiang Li

Projection model for Computer Network Security Evaluation with interval-valued intuitionistic fuzzy information. Qingxiang Li Iteratoal Joural of Scece Vol No7 05 ISSN: 83-4890 Proecto model for Computer Network Securty Evaluato wth terval-valued tutostc fuzzy formato Qgxag L School of Software Egeerg Chogqg Uversty of rts ad

More information

ON SLANT HELICES AND GENERAL HELICES IN EUCLIDEAN n -SPACE. Yusuf YAYLI 1, Evren ZIPLAR 2. yayli@science.ankara.edu.tr. evrenziplar@yahoo.

ON SLANT HELICES AND GENERAL HELICES IN EUCLIDEAN n -SPACE. Yusuf YAYLI 1, Evren ZIPLAR 2. yayli@science.ankara.edu.tr. evrenziplar@yahoo. ON SLANT HELICES AND ENERAL HELICES IN EUCLIDEAN -SPACE Yusuf YAYLI Evre ZIPLAR Departmet of Mathematcs Faculty of Scece Uversty of Akara Tadoğa Akara Turkey yayl@sceceakaraedutr Departmet of Mathematcs

More information

The Digital Signature Scheme MQQ-SIG

The Digital Signature Scheme MQQ-SIG The Dgtal Sgature Scheme MQQ-SIG Itellectual Property Statemet ad Techcal Descrpto Frst publshed: 10 October 2010, Last update: 20 December 2010 Dalo Glgorosk 1 ad Rue Stesmo Ødegård 2 ad Rue Erled Jese

More information

A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining

A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining A Fast Clusterg Algorth to Cluster Very Large Categorcal Data Sets Data Mg Zhexue Huag * Cooperatve Research Cetre for Advaced Coputatoal Systes CSIRO Matheatcal ad Iforato Sceces GPO Box 664, Caberra

More information

An Effectiveness of Integrated Portfolio in Bancassurance

An Effectiveness of Integrated Portfolio in Bancassurance A Effectveess of Itegrated Portfolo Bacassurace Taea Karya Research Ceter for Facal Egeerg Isttute of Ecoomc Research Kyoto versty Sayouu Kyoto 606-850 Japa arya@eryoto-uacp Itroducto As s well ow the

More information

Report 19 Euroland Corporate Bonds

Report 19 Euroland Corporate Bonds Rep19, Computed & Prted: 17/06/2015 11:38 Report 19 Eurolad Corporate Bods From Dec 1999 to Dec 2014 31/12/1999 31 December 1999 31/12/2014 Bechmark 100% IBOXX Euro Corp All Mats. TR Defto of the frm ad

More information

11 - KINETIC THEORY OF GASES Page 1

11 - KINETIC THEORY OF GASES Page 1 - KIETIC THEORY OF GASES Page Introduction The constituent partices of the atter ike atos, oecues or ions are in continuous otion. In soids, the partices are very cose and osciate about their ean positions.

More information

10.5 Future Value and Present Value of a General Annuity Due

10.5 Future Value and Present Value of a General Annuity Due Chapter 10 Autes 371 5. Thomas leases a car worth $4,000 at.99% compouded mothly. He agrees to make 36 lease paymets of $330 each at the begg of every moth. What s the buyout prce (resdual value of the

More information

DISTANCE MEASURE FOR ORDINAL DATA *

DISTANCE MEASURE FOR ORDINAL DATA * ARGUMENTA OECONOMICA No (8) 999 PL ISSN 33-5835 Mre Wes DISTANCE MEASURE FOR ORDINAL DATA * The study cosders the proe of costructo esures of srty for ord dt. The ord chrcter of the dt requred the ppcto

More information

The impact of service-oriented architecture on the scheduling algorithm in cloud computing

The impact of service-oriented architecture on the scheduling algorithm in cloud computing Iteratoal Research Joural of Appled ad Basc Sceces 2015 Avalable ole at www.rjabs.com ISSN 2251-838X / Vol, 9 (3): 387-392 Scece Explorer Publcatos The mpact of servce-oreted archtecture o the schedulg

More information

Identification of Coherent Groups of Generators Based on Fuzzy Algorithm

Identification of Coherent Groups of Generators Based on Fuzzy Algorithm Proceedgs of the 4 th Iteratoal Mddle East Power Systes Coferece (MEPCON 0), Caro Uversty, Egypt, Deceber 9-, 00, Paper ID 303. Idetfcato of Coheret Groups of Geerators Based o Fuzzy Algorth Mahd M. M.

More information

Simple Linear Regression

Simple Linear Regression Smple Lear Regresso Regresso equato a equato that descrbes the average relatoshp betwee a respose (depedet) ad a eplaator (depedet) varable. 6 8 Slope-tercept equato for a le m b (,6) slope. (,) 6 6 8

More information

RQM: A new rate-based active queue management algorithm

RQM: A new rate-based active queue management algorithm : A ew rate-based actve queue maagemet algorthm Jeff Edmods, Suprakash Datta, Patrck Dymod, Kashf Al Computer Scece ad Egeerg Departmet, York Uversty, Toroto, Caada Abstract I ths paper, we propose a ew

More information