Security Analysis of RAPP: An RFID Authentication Protocol based on Permutation
|
|
- Duane Robbins
- 8 years ago
- Views:
Transcription
1 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 Techology Research ey Laboratory for Wreless Sesor Networks, Najg, Jagsu 000, Cha Network ad Data Securty ey Laboratory of Schua Provce } Abstract Oe of the key problems Rado Frequecy IdetfcatoRFID s securty ad prvacy May RFID authetcato protocols have bee proposed to preserve securty ad prvacy of the system Nevertheless, most of these protocols are aalyzed ad t s show that they ca ot provde securty agast some RFID attacks RAPP s a ew ultralghtweght authetcato protocol wth permutato I RAPP, oly three operatos are volved: btwse XOR, left rotato ad permutato I ths paper, we gve a actve attack o RAPP We frst collect some authetcato messages through mpersoatg vald tag ad readers; 0 The we forge vald reader to commucate wth the tag about tmes Usg the property of the left rotato ad permutato operato, we ca deduce the relatoshp of bts of radom umber or secret keys at dfferet postos, thus obta all the secret shared by the reader ad the tag eywords: RFID; Lghtweght Authetcato; Permutato; Prvacy; Actve Attack Itroducto Rado Frequecy Idetfcato RFID systems are used for automated detfcato of objects ad people Applcatos that use RFID techology clude warehouse maagemet, logstcs, ralroad car trackg, product detfcato, lbrary books check-/check-out, asset trackg, passport ad credt cards, etc Most of the RFID systems comprse of three ettes: the tag, the reader ad the back-ed database The tag s a hghly costraed mcrochp wth atea that stores the uque tag detfer ad other related formato about a object The reader s a devce that ca read/modfy the stored formato of the tags ad trasfer these data to a back-ed database, wth or wthout modfcato Back ed database stores ths formato ad wll keep track of the data echaged by the reader [ Oe of the key problems RFID s prvacy ad securty It s typcally crtcal to the commucato betwee the reader ad the tag because wreless trasmssos are more vulerable to malcous adversares The possble securty threats to RFID systems clude deal of servce DoS, ma the mddle MIM, couterfetg, spoofg, eavesdroppg, traffc aalyss, traceablty, de-sychrozato etc A effectve ad fleble way to assure prvacy ad securty s to adopt authetcato protocols The low cost deploymet demad for RFID tags forces the lack of resources for performg true cryptographc operatos to provde securty It s worthwhle to study ultralghtweght authetcato protocols whch requre tags to volve oly smple btwse operatos such as btwse XOR, btwse OR, btwse AND ad rotato Provdg lght weght securty RFID systems s ot a trval task Several ultralghtweght protocols have already bee proposed However, they all have certa flaws ad vulerabltes Vajda ad LButtya [ have proposed a set of etremely lghtweght challege respose authetcato algorthms These ca be used for authetcatg the tags, but they may be easly attacked by a powerful adversary Juels [ proposed a soluto based o the use of pseudoyms, wthout usg ay hash fucto But after a set of authetcato sessos, the lst of pseudoyms wll eed to be reused or updated through a out-of-bad chael, whch lmts the practcalty of ths scheme Pers-Lopez et al proposed a famly of ultralghtweght mutual authetcato protocols eg, [4 ad [ But later t was reported that these protocols are vulerable to desychrozato attack ad full-dsclosure attack [ I addto to ths there are other lghtweght mutual authetcato protocols proposed the lterature ad attacks have bee successfully mouted o all of these as demostrated lterature [-0 Che troduced aother ultralghtweght protocol called SASI [ to provde strog authetcato ad strog tegrty However, vulerabltes have also bee llustrated such as tag traceablty, de-sychrozato ad secret dsclosure attack [- [ preseted Gossamer protocol whch s spred by SASI ad tres to be devod of the weakess of SASI Noetheless, the de-sychrozato attack [4 stll works Recetly, Yu Ta etal[ propose a ew ultralghtweght RFID authetcato protocol wth permutato called RAPP They troduce the permutato operato to break the orders of the bts Moreover, ther scheme, the last messages are set by the reader rather tha by the tag to resst de-sychrozato attacks Ths also ecoomzes the storage of the tag Tags RAPP volve three operatos: btwse XOR, left rotato ad permutato I ths paper, we gve a securty aalyss of ths ew proposed protocol RAPP A actve attack s proposed, whch we frst collect some authetcato messages through mpersoatg vald tag ad reader; The we forge vald
2 0 reader to commucate wth the tag The aalyss shows whe queryg about tmes wth the tag, we ca deduce all the secrets shared by the reader ad the tag utlzg the property of the left rotato ad permutato operatos The rest of the paper s orgazed as follows: RAPP s brefly llustrated secto Secto descrbes the detal securty aalyss of ths ew protocol wth permutato, ad shows how to etract all the secrets shared by the reader ad the tag Secto 4 gves the complety of the attack ad a eample of our attack wth reduced legth s preseted Cocluso s gve secto RAPP Scheme I ths secto, we gve a bref descrpto of RAPP I ths protocol, costly operatos such as multplcatos ad hash evaluatos are ot used at all, ad radom umber geerato s oly doe at the reader s sde All the varables the protocol are 9 bt Frequetly used otatos ths paper are lsted below: ID : Tag s uque detfer IDS : th Tag s dyamc pseudoym at the successful ru of protocol th,, : Secret keys shared at the successful ru of protocol, : Pseudoradom umbers geerated by Reader A, B, C, D, E : Messages trasferred betwee Reader ad Tag Btwse XOR operato I RAPP, the tags ad readers oly volve operatos: btwse XOR, left rotato Rot, y ad permutato Per, y Suppose ad y are two 9-bt strgs, Rot, y s defed to left rotate by wty bts, where wty s the Hammg weght of y The permutato operato Per, y s defed as follows: Defto : Suppose ad y are two 9-bt strgs, where, 9 { 0,},,,, 9; y y yy, 9 y { 0,},,,, 9 Moreover, the Hammg weght of y, wty, s m 0 m 9 ad y y y, y 0 k k k m k y + k y, m m+ k 9 where k 9 ad < k < < km km + < km+ < < k9 9 The, the permutato of accordg to y, deoted as Per, y, s Pert, y k k k m k 9 k 9 k m+ k m + th I RAPP, every tag shares a fed ad uque detfer ID wth the reader At the authetcato, the tag + ad the reader share a pseudoym IDS ad three secrets,,, whch wll update to IDS, + + +,, f authetcato s successful Every authetcato cotas three rouds: tag detfcato, mutual authetcato ad IDS, secrets updatg, whch s preseted as follows: I Tag Idetfcato After recevg the Hello message from the reader, the tag seds the IDS to the reader, whch wll look up the tags the database wth the same pseudoym ad get the correspodg formato II Mutual Authetcato The reader ad tag wll authetcate to each other through the followg step: Step Reader frst geerates a radom umber, computes ad seds the tag the messages A, B as equato ad The tag ca deduce the radom umber through message A, ad make sure whether the reader s vald va checkg the correctess of message B : A Per, B Per, Rot, Per, Step If the reader s vald, the tag seds back the aswer message C to authetcate hmself: C Per, ID Step After authetcatg the valdty of the tag, Reader geerates aother radom umber, computes ad seds the tag the messages D, E as follow The tag ca deduce the radom umber through message D, ad make sure that s ot chaged va checkg the correctess of message E : D Per, 4 E Per, Rot, Per, III IDS ad Secrets Updatg After authetcatg successfully, the reader ad tag wll update the pseudoym IDS ad secrets the follow way: IDS Per IDS, Per, Per, Per, IDS 9
3 Securty Aalyss of RAPP I the secto, we gve the securty aalyss of the RAPP ad some superscrpts are omtted for coveece the followg paper We deote by [ the bt at posto ad, the strg wth the same bt as 0 + ecept for the bts posto ad +, meas the strg wth all the bts are 0 ecept that the bt posto ad + s As to the operatos Per, ad Rot,, we ca get the followg observatos: Observato As to ay two 9-bt strgs, y ad z, t s easy to see that operato Per, has the property: Per, y Per z, y Per z, y Observato As to ay,,,9, f ad are dfferet, ad have the same hammg [ [,, wt + [ [, wt, wt [ [,,, Rot, 0s, s+ weght If [ [ 0, wt ; ad f Observato As to ay,,,9, f ad are dfferet, Rot for some bt posto s That s to say Rot,,, s almost the same as Rot, ecept for the bts posto s ad s + I addto, there s oly oe dfferet umber the sequece of umber satsfyg [ Rot,,, from that of [ Rot,, ad also oe dfferet posto umber the sequece of umber j satsfyg [ + j Rot,,, 0 from that of [ Rot, 0 j Observato 4 From the observato, we ca see as to ay,,, 9, f [ ad [ are dfferet, Per y, Rot,,, ether equals to Per y, Rot,, or has dfferet bts postos, e Per y, Rot,,, Per y, Rot, 0s, t wth bt posto s ad t Eample: Gve 000, we ca get, 000, 4, 0, wt, wt, wt 4, wt + Rot, 000, Rot,,, 000 ad Rot 4,, 4, 0 Rot,,, has the dfferet bts from Rot, at bt posto ad, whle Rot 4,, 4, has 4 dfferet bts from Rot, At posto,,, 4,, the bt of Rot,,, s, ad posto,,, the bt of Rot,,, s 0; whle the bt of Rot, s at the posto,,,4,, ad 0 at the posto,, I the followg, we wll llustrate how to deduce all the secrets shared betwee the tag ad reader Our attack belogs to actve attack, that the adversary ca mpersoate a legal tag or reader to commucate wth the correspodg reader or tag We frst show how to recover the radom umber geerated by the reader; The the secret key s deduced ad secret key s obtaed by aalyzg some lear equatos; All the other secrets cludg ad ID ca be recovered the ed Recovery of radom umber I our attack, the adversary frst forges a legal reader to commucate wth the tag to obta ts pseudoym IDS ; The he forges as the legal tag to authetcate hmself After recevg the pseudoym IDS, the reader geerates radom umber to compute messages A ad B as equato ad : A Per ; B Per, Rot, Per, To recover the radom umber, the adversary forge a legal reader to lauch the authetcato wth the vald tag Ad for ay umber used by adversary s,,,,9, the adversary calculates the message A ' A,,, ad t s easy to kow the radom From the observato, we ca see the vald message B ' must satsfy: B' B Per, Rot, Per, Per, Rot, Per,,,, Per, Rot, Per, Rot, Per0,,,, From the observato, ad 4, we ca see: If [ ad [ are dfferet, Per, Rot, Per,, ether equals Rot,, to 0 or 0 s, t wth ukow posto s ad t, ad Per 0,, equals to 0 u, v wth ukow bt posto u ad v That s to say, ths codtos, wt B' B 4 If [ ad [ are the same, the permutato of accordg to Rot, behaves,, radomly compared wth Rot, So t s hard to predcate the chages ad wll be bgger wt B' B tha 4 wth overwhelmg probablty
4 From the above aalyss, we proceed the followg algorthm to deduce the radom umber : Algorthm Recovery of the radom umber for to 9 wth all the possble u < v < 9, the adversary seds the tag A', B' A,, B 0u, v f tag seds back the message ', we coclude [ C [ Otherwse A', B' A,, B 0s, t 0u, v s sed wth all the possble s < t < 9, u < v < 9 f tag seds back the message ', we coclude [ [ Otherwse we coclude [ Recovery of secret key C [ It s easy to see we do ot deduce the actual value of radom umber but the relatoshp of adjog bt So we ca always obta possble radom umbers, oe startg wth the bt, ad the other wth bt 0 I fact, the two possble radom umbers are ad After obtag the radom umber, we ca get Per, A To recover the secret key, we use the followg observato: Observato As to ay,,,9, f [ ad [ are dfferet, Per y,, ether equals to Per y,, or has dfferet bts at postos The adversary frst seds the actual message A, B to the tag, ad receves the respose message C From the Algorthm, f [ ad [ are dfferet, the adversary ca forge vald message A', B' ad tag seds back message C', whch satsfes: C C Per, ID Per, ID Per, ',,,, Per, Per, Per,,, [ [ wt C C' [ [ C C' From the observato, we ca see f ad are dfferet, must equal to ; whle f equals to, wt wll be larger tha wth overwhelmg probablty However, as show Algorthm, we ca ot obta all the relatoshp of adjog bt of, because f [ ad [ are the same, we ca ot forge vald message to obta So, the adversary ca forge A ', B' C' tag ad the reader aga to commucate wth the correspodg vald oes obta other authetcato messages r r r A, B, C, r,,, l The value of l wll be dscussed secto 4 Because Per, s kow, the radom umbers r r r, r,,, l ca be computed as A Per, Thus we preset the followg Algorthm to recover the secret key Algorthm Recovery of the secret key for to 9 f [ [ f wt C C', we coclude [, whch meas [ Otherwse, we coclude [, whch meas [ [ t t Otherwse fd the value t : [ [, ad call the Algorthm to obta f wt C t C t ', we coclude [ [ Otherwse, we coclude [ [ [ [ [ t C ' Recovery of secret key We should ote that just as Algorthm, Algorthm s utlzed to obta the relatoshp of adjog bt of As to each possble radom umber ad, there are possble secret key ad So there are 4 possble combatos,,,,, ad, We should try all these 4 possble combatos We use the varable ad to show how to recover the secret key From the equato C, we ca obta: C Per, ID Per, Per, ID
5 e Per, C Per, ID As to dfferet s ad t, we ca get : s t t s s s t t Per, Per, C C Per, Per, Secret key ad all the radom umbers are kow, so the rght part of the above equato,,,, l s t ca be computed Per ad are two dfferet permutatos of secret key, Per, Thus the left part of the equato volves the relatoshp of bt at dfferet bt posto ad the lear equatos ca be set up However we do ot solve the lear equatos, we ca obta the relatoshp of bt of at dfferet postos from the equatos 4 Recovery of all the other secrets After obtag the radom umber ad secret keys ad, the detfer ID ca be deduced usg equato, ad the secret key of ca be computed through the equato I addto, we ca use the r r r messages A, B, C, r,,, m to check whether the possble guessg s rght or ot 4 Epermet Results I ths secto, we frst gve a attack eample wth all the varables havg 4 bts, ad the the geeral complety of our attack s aalyzed 4 A Eample wth Reduced Legth Here we gve a eample wth reduced legth We take the detfer ID 0ca, three secrets keys a a e f b, ad the frst radom umber chose Thus we ca , 0 4, cb compute: Per, , Rot, , Per, Per, Rot, So the messages the reader geerated are: A , B , The attack procedure s preset brefly as follows: Step Recovery the radom umber whe, we kow ow 00b, Rot,,,, , Per, Rot, , ad Per,,,, The message B ' should equal to , ad wt B B' So as to the Algorthm, the adversary ca ot compute the vald B ' to authetcate hmself We ca coclude [ [ I the table, as from to, we lst the correspodg values wth the ew radom umber We ca, see whe,,,,, wt B B' 4, ad we ca forge a vald B ' from the Algorthm So [ [ whe,,,, Table part of the values wth ew radom umber, Per,,, Rot, Per,,, 00b ab fb deb cab c0b B ' wt B B'
6 0cb c9b cdb cb cb c0fb Fally We ca coclude that [ [ [ [ 4 [ [ [ [ [ 9 [ 0 [ [ [ [ [ [ [ [ [ [ [ [ [ [ So the two possble radom umbers are ad Step Recovery the secret key As to the orgal message A ad B, we kow , , Per, ,ad the respose message sed by the tag s C As to the algorthm, we kow whe,,,,, the adversary ca forge vald authetcato message A ' ad B ', ad the tag wll sed back C' Take,, as a eample, we show how to deduce the relatoshp of : : , ,,,,, Per, , ad C' Because wt C C', we coclude [ Because, [ [ [ [ [ : , ,,,,, Per, , ad C' Because wt C C', we coclude [ Because, [ [ [ [ [ : , ,,,,, Per, , ad C' Because wt C C', we coclude [ Because, [ [ [ [ [ To obta all the relatoshp of bt cojog posto, we eed to collect other radom umbers ad we do ot show ths detal here The relatoshp of bt at dfferet posto that we ca get s: [ [ [ [ [ [ [ [ [ [ [ [ [ [ 4 [ [ [ [ [ 9 [ 0 [ [ [ [ 4 So the two possble secret key are ad Step Recovery the secret key Here we get 4 possble combatos,,,,, ad, Suppose we get aother authetcato messages A, B ad C from the vald reader ad tag The ew radom umber chose s r 049a, ad A , B ad C We oly choose, as a eample Now We kow Per, , ad we ca get the ew radom umber s r 049a Set ad r, the we have: C C' Per, Per, r,,4,,,9,0,,,,9,,4,,,0,,,4,,,,,,4,,,9,0,,,,,9,4,,,,0,4,,,,,,, meas the permutato of accordg to,,4,,,,, So we ca,,4,,,9,0,,,,9,,4,,,0,,,4,,,,, get [, Because, so Thus we ca [ [ [ [ r [ [,[ r [ [ get the relatoshp of bt at dfferet postos the same way Usually we ca ot get all the relatoshp we eed I the eample, we ca ot get the relatoshp of bt wth posto 9 ad 0 At that tme, we eed to choose aother messages to try the above procedure to get the relatoshp of bt posto 9 or 0 wth other bt postos As the computato of the other secret ad detfer s straghtforward, we do ot dscuss here
7 4 Complety Aalyss of the Attack Here we wll aalyss the complety of our attack There are two factors we should cosder: The umber l of authetcato messages that the adversary eed to collect through mpersoatg vald tag or reader If the umber s chose radomly, we kow for ay,,, 9, pr [ [ 0 For l radom l umber, the probablty that the bt at posto equals to the bt at posto + s 0 Take l 0, 0 l That s to say, whe collectg 0 authetcato messages, we ca fd [ wth [ overwhelmg probablty for ay,,,9 the umber we eed to query the tag To recover the radom umber ad secret key, we eed to sed the forged messages A', B' to the tag to deduce the relatoshp of bt dfferet postos From the Algorthm ad 0 algorthm, we ca coclude the umber s about 4 C C 9 9 Cocluso I ths paper, we gve a actve attack o RAPP, a ew ultralghtweght authetcato protocol wth permutato We frst collect some authetcato messages through mpersoatg vald tag ad readers; The we forge vald reader to 0 commucate wth the tag about tmes Usg the property of the left rotato ad permutato operato, we ca deduce relatoshp of bts of radom umber or secret keys at dfferet postos, thus obta all the secret shared by the reader ad the tag I practce, the umber eeded to query the tag s much larger How to reduce the aalyss complety wll be cosdered the future work Ackowledgemets Ths work s supported by the Prorty Academc Program Developmet of Jagsu Hgher Educato IsttutosPAPD, Natoal Natural Scece Fuds Grat No090 ad Najg Uversty of Post ad Telecommucato Fuds Grat NoNY00 REFERENCE Hut, VD, Pugla, A, Pugla, M: RFID: A Gude to Rado Frequecy Idetfcato Wley-Iter scece 00 Vajda, I, Buttya, L: Lghtweght authetcato protocols for low-cost RFID tags I: Proc of UBICOMP Juels, A: Mmalst Cryptography for Low-Cost RFID Tags Eteded Abstract I: Bludo, C, Cmato, S eds SCN 004 LNCS, vol, pp 49 4 Sprger, Hedelberg 00 4 P Pers-Lopez, J C Heradez-Castro, J M E Tapador, ad A Rbagorda LMAP: a real lghtweght mutual authetcato protocol for low-cost RFID tags Proc 00 Workshop RFID Securty P Pers-Lopez, J C Heradez-Castro, J M E Tapador, ad A Rbagorda MAP: a mmalst mutualauthetcato protocol for lowcost RFID tags Proc 00 Iteratoal Coferece o Ubqutous Itellgece ad Computg, pp 9 9 T L ad G Wag Securty aalyss of two ultra-lghtweght RFID authetcato protocols Proc 00 IFIP RC- Iteratoal Iformato Securty Coferece, pp 09 0 Sadgha, Jall, R: Afmap: Aoymous forward-secure mutual authetcato protocols for rfd systems I: Thrd IEEE Iteratoal Coferece o Emergg Securty Iformato, Systems ad Techologes SECURWARE 009, pp 009 Sadgha, Jall, R: Flmap: A fast lghtweght mutual authetcato protocol for rfd systems I: th IEEE Iteratoal Coferece o Networks ICON 00, New Delh, Ida, pp 00 9 Safkha, M, Nader, M, Bagher, N: Cryptaalyss of AFMAP IEICE Electrocs Epress, Bárász, M, Boros, B, Lget, P, Lója,, Nagy, D: Passve Attack Agast the MAP Mutual Authetcato Protocol for RFID Tags I: Frst Iteratoal EURASIP Workshop o RFID Techology, Vea, Austra 00 Che, H-Y: SASI: A New Ultralghtweght RFID Authetcato Protocol Provdg Strog Authetcato ad Strog Itegrty IEEE Trasactos o Depedable ad Secure Computg 44, T Cao, E Berto, ad H Le Securty aalyss of the SASI protocol IEEE Tras Depedable ad Secure Computg, vol, o, pp, Ja-Mar 009 R C-W Pha Cryptaalyss of a ew ultralghtweght RFID authetcao protocol SASI IEEE Tras Depedable ad Secure Computg, vol, o 4, pp 0, Oct-Dec H-M Su, W-C Tg, ad -H Wag O the securty of Che s ultralghtweght RFID authetcato protocol IEEE Tras Depedable ad Secure Computg, vol, o, pp, Mar-Apr 0 P D Arco ad A De Sats O ultralghtweght RFID authetcato protocols IEEE Tras Depedable ad Secure Computg, vol, o 4, pp 4, July-Aug 0 P Pers-Lopez, J C Heradez-Castro, J M E Tapador, ad A Rbagorda, Advaces ultralghtweght cryptography for low-cost RFID tags: Gossamer protocol, Proc 00 Iteratoal Workshop o Iformato Securty Applcatos, pp Y Ta, G Che, ad J L A New Ultralghtweght RFID Authetcato Protocol wth Permutato IEEE Commucatos Letters, Vol, No, May 0, pp0-0
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 informationIDENTIFICATION 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 informationADAPTATION 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 informationMaintenance 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 informationAn 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 informationAPPENDIX 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 informationA 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 informationOptimal 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 informationGreen 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 informationPreprocess 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 informationProjection 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 informationModels 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 informationApplications 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 informationAverage 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 informationFractal-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 information6.7 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 informationChapter 3. AMORTIZATION OF LOAN. SINKING FUNDS R =
Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS Objectves of the Topc: Beg able to formalse ad solve practcal ad mathematcal problems, whch the subjects of loa amortsato ad maagemet of cumulatve fuds are
More informationA 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 informationChapter 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 informationOn formula to compute primes and the n th prime
Joural's Ttle, Vol., 00, o., - O formula to compute prmes ad the th prme Issam Kaddoura Lebaese Iteratoal Uversty Faculty of Arts ad ceces, Lebao Emal: ssam.addoura@lu.edu.lb amh Abdul-Nab Lebaese Iteratoal
More informationSTATISTICAL 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 informationOptimal Packetization Interval for VoIP Applications Over IEEE 802.16 Networks
Optmal Packetzato Iterval for VoIP Applcatos Over IEEE 802.16 Networks Sheha Perera Harsha Srsea Krzysztof Pawlkowsk Departmet of Electrcal & Computer Egeerg Uversty of Caterbury New Zealad sheha@elec.caterbury.ac.z
More informationSHAPIRO-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 informationNumerical 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 informationA 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 informationFast, Secure Encryption for Indexing in a Column-Oriented DBMS
Fast, Secure Ecrypto for Idexg a Colum-Oreted DBMS Tgja Ge, Sta Zdok Brow Uversty {tge, sbz}@cs.brow.edu Abstract Networked formato systems requre strog securty guaratees because of the ew threats that
More information10.5 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 informationAbraham 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 informationCredibility Premium Calculation in Motor Third-Party Liability Insurance
Advaces Mathematcal ad Computatoal Methods Credblty remum Calculato Motor Thrd-arty Lablty Isurace BOHA LIA, JAA KUBAOVÁ epartmet of Mathematcs ad Quattatve Methods Uversty of ardubce Studetská 95, 53
More informationAn 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 informationAutomated Event Registration System in Corporation
teratoal Joural of Advaces Computer Scece ad Techology JACST), Vol., No., Pages : 0-0 0) Specal ssue of CACST 0 - Held durg 09-0 May, 0 Malaysa Automated Evet Regstrato System Corporato Zafer Al-Makhadmee
More informationThe 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 informationOnline 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 informationT = 1/freq, T = 2/freq, T = i/freq, T = n (number of cash flows = freq n) are :
Bullets bods Let s descrbe frst a fxed rate bod wthout amortzg a more geeral way : Let s ote : C the aual fxed rate t s a percetage N the otoal freq ( 2 4 ) the umber of coupo per year R the redempto of
More informationAN ALGORITHM ABOUT PARTNER SELECTION PROBLEM ON CLOUD SERVICE PROVIDER BASED ON GENETIC
Joural of Theoretcal ad Appled Iformato Techology 0 th Aprl 204. Vol. 62 No. 2005-204 JATIT & LLS. All rghts reserved. ISSN: 992-8645 www.jatt.org E-ISSN: 87-395 AN ALGORITHM ABOUT PARTNER SELECTION PROBLEM
More informationResearch on the Evaluation of Information Security Management under Intuitionisitc Fuzzy Environment
Iteratoal Joural of Securty ad Its Applcatos, pp. 43-54 http://dx.do.org/10.14257/sa.2015.9.5.04 Research o the Evaluato of Iformato Securty Maagemet uder Itutostc Fuzzy Evromet LI Feg-Qua College of techology,
More informationStudy on prediction of network security situation based on fuzzy neutral network
Avalable ole www.ocpr.com Joural of Chemcal ad Pharmaceutcal Research, 04, 6(6):00-06 Research Artcle ISS : 0975-7384 CODE(USA) : JCPRC5 Study o predcto of etwork securty stuato based o fuzzy eutral etwork
More informationAn IG-RS-SVM classifier for analyzing reviews of E-commerce product
Iteratoal Coferece o Iformato Techology ad Maagemet Iovato (ICITMI 205) A IG-RS-SVM classfer for aalyzg revews of E-commerce product Jaju Ye a, Hua Re b ad Hagxa Zhou c * College of Iformato Egeerg, Cha
More informationA 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 informationStatistical 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 informationConstrained Cubic Spline Interpolation for Chemical Engineering Applications
Costraed Cubc Sple Iterpolato or Chemcal Egeerg Applcatos b CJC Kruger Summar Cubc sple terpolato s a useul techque to terpolate betwee kow data pots due to ts stable ad smooth characterstcs. Uortuatel
More informationLow-Cost Side Channel Remote Traffic Analysis Attack in Packet Networks
Low-Cost Sde Chael Remote Traffc Aalyss Attack Packet Networks Sach Kadloor, Xu Gog, Negar Kyavash, Tolga Tezca, Nkta Borsov ECE Departmet ad Coordated Scece Lab. IESE Departmet ad Coordated Scece Lab.
More informationModeling of Router-based Request Redirection for Content Distribution Network
Iteratoal Joural of Computer Applcatos (0975 8887) Modelg of Router-based Request Redrecto for Cotet Dstrbuto Network Erw Harahap, Jaaka Wjekoo, Rajtha Teekoo, Fumto Yamaguch, Shch Ishda, Hroak Nsh Hroak
More informationIP Network Topology Link Prediction Based on Improved Local Information Similarity Algorithm
Iteratoal Joural of Grd Dstrbuto Computg, pp.141-150 http://dx.do.org/10.14257/jgdc.2015.8.6.14 IP Network Topology Lk Predcto Based o Improved Local Iformato mlarty Algorthm Che Yu* 1, 2 ad Dua Zhem 1
More informationProceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds.
Proceedgs of the 21 Wter Smulato Coferece B. Johasso, S. Ja, J. Motoya-Torres, J. Huga, ad E. Yücesa, eds. EMPIRICAL METHODS OR TWO-ECHELON INVENTORY MANAGEMENT WITH SERVICE LEVEL CONSTRAINTS BASED ON
More informationLoad 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 informationThe 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 informationClassic 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 informationThe 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 informationFault Tree Analysis of Software Reliability Allocation
Fault Tree Aalyss of Software Relablty Allocato Jawe XIANG, Kokch FUTATSUGI School of Iformato Scece, Japa Advaced Isttute of Scece ad Techology - Asahda, Tatsuokuch, Ishkawa, 92-292 Japa ad Yaxag HE Computer
More informationThe 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 informationApproximation Algorithms for Scheduling with Rejection on Two Unrelated Parallel Machines
(ICS) Iteratoal oural of dvaced Comuter Scece ad lcatos Vol 6 No 05 romato lgorthms for Schedulg wth eecto o wo Urelated Parallel aches Feg Xahao Zhag Zega Ca College of Scece y Uversty y Shadog Cha 76005
More informationMaximization of Data Gathering in Clustered Wireless Sensor Networks
Maxmzato of Data Gatherg Clustere Wreless Sesor Networks Taq Wag Stuet Member I We Hezelma Seor Member I a Alreza Seye Member I Abstract I ths paper we vestgate the maxmzato of the amout of gathere ata
More informationANOVA 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 informationCompressive Sensing over Strongly Connected Digraph and Its Application in Traffic Monitoring
Compressve Sesg over Strogly Coected Dgraph ad Its Applcato Traffc Motorg Xao Q, Yogca Wag, Yuexua Wag, Lwe Xu Isttute for Iterdscplary Iformato Sceces, Tsghua Uversty, Bejg, Cha {qxao3, kyo.c}@gmal.com,
More informationTHE McELIECE CRYPTOSYSTEM WITH ARRAY CODES. MATRİS KODLAR İLE McELIECE ŞİFRELEME SİSTEMİ
SAÜ e Blmler Dergs, 5 Clt, 2 Sayı, THE McELIECE CRYPTOSYSTEM WITH ARRAY CODES Vedat ŞİAP* *Departmet of Mathematcs, aculty of Scece ad Art, Sakarya Uversty, 5487, Serdva, Sakarya-TURKEY vedatsap@gmalcom
More informationIntegrating Production Scheduling and Maintenance: Practical Implications
Proceedgs of the 2012 Iteratoal Coferece o Idustral Egeerg ad Operatos Maagemet Istabul, Turkey, uly 3 6, 2012 Itegratg Producto Schedulg ad Mateace: Practcal Implcatos Lath A. Hadd ad Umar M. Al-Turk
More informationA Real-time Visual Tracking System in the Robot Soccer Domain
Proceedgs of EUEL obotcs-, Salford, Eglad, th - th Aprl A eal-tme Vsual Trackg System the obot Soccer Doma Bo L, Edward Smth, Huosheg Hu, Lbor Spacek Departmet of Computer Scece, Uversty of Essex, Wvehoe
More informationRESEARCH ON PERFORMANCE MODELING OF TRANSACTIONAL CLOUD APPLICATIONS
Joural of Theoretcal ad Appled Iformato Techology 3 st October 22. Vol. 44 No.2 25-22 JATIT & LLS. All rghts reserved. ISSN: 992-8645 www.jatt.org E-ISSN: 87-395 RESEARCH ON PERFORMANCE MODELING OF TRANSACTIONAL
More informationSoftware Reliability Index Reasonable Allocation Based on UML
Sotware Relablty Idex Reasoable Allocato Based o UML esheg Hu, M.Zhao, Jaeg Yag, Guorog Ja Sotware Relablty Idex Reasoable Allocato Based o UML 1 esheg Hu, 2 M.Zhao, 3 Jaeg Yag, 4 Guorog Ja 1, Frst Author
More informationCurve Fitting and Solution of Equation
UNIT V Curve Fttg ad Soluto of Equato 5. CURVE FITTING I ma braches of appled mathematcs ad egeerg sceces we come across epermets ad problems, whch volve two varables. For eample, t s kow that the speed
More informationAgent-based modeling and simulation of multiproject
Aget-based modelg ad smulato of multproject schedulg José Alberto Araúzo, Javer Pajares, Adolfo Lopez- Paredes Socal Systems Egeerg Cetre (INSISOC) Uversty of Valladold Valladold (Spa) {arauzo,pajares,adolfo}ssoc.es
More informationBanking (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 informationA 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 informationSimple 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 informationProactive Detection of DDoS Attacks Utilizing k-nn Classifier in an Anti-DDos Framework
World Academy of Scece, Egeerg ad Techology Iteratoal Joural of Computer, Electrcal, Automato, Cotrol ad Iformato Egeerg Vol:4, No:3, 2010 Proactve Detecto of DDoS Attacks Utlzg k-nn Classfer a At-DDos
More informationSuspicious Transaction Detection for Anti-Money Laundering
Vol.8, No. (014), pp.157-166 http://dx.do.org/10.1457/jsa.014.8..16 Suspcous Trasacto Detecto for At-Moey Lauderg Xgrog Luo Vocatoal ad techcal college Esh Esh, Hube, Cha es_lxr@16.com Abstract Moey lauderg
More informationApplication of Grey Relational Analysis in Computer Communication
Applcato of Grey Relatoal Aalyss Computer Commucato Network Securty Evaluato Jgcha J Applcato of Grey Relatoal Aalyss Computer Commucato Network Securty Evaluato *1 Jgcha J *1, Frst ad Correspodg Author
More informationWeb Service Composition Optimization Based on Improved Artificial Bee Colony Algorithm
JOURNAL OF NETWORKS, VOL. 8, NO. 9, SEPTEMBER 2013 2143 Web Servce Composto Optmzato Based o Improved Artfcal Bee Coloy Algorthm Ju He The key laboratory, The Academy of Equpmet, Beg, Cha Emal: heu0123@sa.com
More informationA Fast Algorithm for Computing the Deceptive Degree of an Objective Function
IJCSNS Iteratoal Joural of Computer See ad Networ Seurty, VOL6 No3B, Marh 6 A Fast Algorthm for Computg the Deeptve Degree of a Objetve Futo LI Yu-qag Eletro Tehque Isttute, Zhegzhou Iformato Egeerg Uversty,
More informationHow To Balance Load On A Weght-Based Metadata Server Cluster
WLBS: A Weght-based Metadata Server Cluster Load Balacg Strategy J-L Zhag, We Qa, Xag-Hua Xu *, Ja Wa, Yu-Yu Y, Yog-Ja Re School of Computer Scece ad Techology Hagzhou Daz Uversty, Cha * Correspodg author:xhxu@hdu.edu.c
More informationAn Application of Graph Theory in the Process of Mutual Debt Compensation
Acta Poltechca Hugarca ol. 12 No. 3 2015 A Applcato of Graph Theor the Process of Mutual Debt Compesato ladmír Gazda Des Horváth Marcel Rešovský Techcal Uverst of Košce Facult of Ecoomcs; Němcove 32 040
More informationEfficient Traceback of DoS Attacks using Small Worlds in MANET
Effcet Traceback of DoS Attacks usg Small Worlds MANET Yog Km, Vshal Sakhla, Ahmed Helmy Departmet. of Electrcal Egeerg, Uversty of Souther Calfora, U.S.A {yogkm, sakhla, helmy}@ceg.usc.edu Abstract Moble
More informationFINANCIAL 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 informationNetwork dimensioning for elastic traffic based on flow-level QoS
Network dmesog for elastc traffc based o flow-level QoS 1(10) Network dmesog for elastc traffc based o flow-level QoS Pas Lassla ad Jorma Vrtamo Networkg Laboratory Helsk Uversty of Techology Itroducto
More informationof the relationship between time and the value of money.
TIME AND THE VALUE OF MONEY Most agrbusess maagers are famlar wth the terms compoudg, dscoutg, auty, ad captalzato. That s, most agrbusess maagers have a tutve uderstadg that each term mples some relatoshp
More informationNumerical 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 informationA 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 informationON 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 informationOn Error Detection with Block Codes
BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 9, No 3 Sofa 2009 O Error Detecto wth Block Codes Rostza Doduekova Chalmers Uversty of Techology ad the Uversty of Gotheburg,
More informationMDM 4U PRACTICE EXAMINATION
MDM 4U RCTICE EXMINTION Ths s a ractce eam. It does ot cover all the materal ths course ad should ot be the oly revew that you do rearato for your fal eam. Your eam may cota questos that do ot aear o ths
More informationANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS. Janne Peisa Ericsson Research 02420 Jorvas, Finland. Michael Meyer Ericsson Research, Germany
ANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS Jae Pesa Erco Research 4 Jorvas, Flad Mchael Meyer Erco Research, Germay Abstract Ths paper proposes a farly complex model to aalyze the performace of
More information1. 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 informationDIGITAL AUDIO WATERMARKING: SURVEY
DIGITAL AUDIO WATERMARKING: SURVEY MIKDAM A. T. ALSALAMI * MARWAN M. AL-AKAIDI ** * Computer Scece Dept. Zara Prvate Uversty / Jorda ** School of Egeerg ad Techology - De Motfort Uversty / UK Abstract:
More informationResearch on Cloud Computing and Its Application in Big Data Processing of Railway Passenger Flow
325 A publcato of CHEMICAL ENGINEERING TRANSACTIONS VOL. 46, 2015 Guest Edtors: Peyu Re, Yacag L, Hupg Sog Copyrght 2015, AIDIC Servz S.r.l., ISBN 978-88-95608-37-2; ISSN 2283-9216 The Itala Assocato of
More informationVIDEO REPLICA PLACEMENT STRATEGY FOR STORAGE CLOUD-BASED CDN
Joural of Theoretcal ad Appled Iformato Techology 31 st Jauary 214. Vol. 59 No.3 25-214 JATIT & S. All rghts reserved. ISSN: 1992-8645 www.att.org E-ISSN: 1817-3195 VIDEO REPICA PACEMENT STRATEGY FOR STORAGE
More informationBayesian Network Representation
Readgs: K&F 3., 3.2, 3.3, 3.4. Bayesa Network Represetato Lecture 2 Mar 30, 20 CSE 55, Statstcal Methods, Sprg 20 Istructor: Su-I Lee Uversty of Washgto, Seattle Last tme & today Last tme Probablty theory
More informationHow To Value An Annuity
Future Value of a Auty After payg all your blls, you have $200 left each payday (at the ed of each moth) that you wll put to savgs order to save up a dow paymet for a house. If you vest ths moey at 5%
More informationThe Analysis of Development of Insurance Contract Premiums of General Liability Insurance in the Business Insurance Risk
The Aalyss of Developmet of Isurace Cotract Premums of Geeral Lablty Isurace the Busess Isurace Rsk the Frame of the Czech Isurace Market 1998 011 Scetfc Coferece Jue, 10. - 14. 013 Pavla Kubová Departmet
More informationSTOCHASTIC approximation algorithms have several
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 60, NO 10, OCTOBER 2014 6609 Trackg a Markov-Modulated Statoary Degree Dstrbuto of a Dyamc Radom Graph Mazyar Hamd, Vkram Krshamurthy, Fellow, IEEE, ad George
More informationA Single Machine Scheduling with Periodic Maintenance
A Sgle Mache Schedulg wth Perodc Mateace Fracsco Ágel-Bello Ada Álvarez 2 Joaquí Pacheco 3 Irs Martíez Ceter for Qualty ad Maufacturg, Tecológco de Moterrey, Eugeo Garza Sada 250, 64849 Moterrey, NL, Meco
More informationReport 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 informationImpact 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 informationDynamic Service and Data Migration in the Clouds
2009 33rd Aual IEEE Iteratoal Computer Software ad Applcatos Coferece Dyamc Servce ad Data Mgrato the Clouds We Hao Departmet of Computer Scece Norther Ketucky Uversty haow1@ku.edu Abstract Cloud computg
More informationOPTIMAL 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 informationTESTING AND SECURITY IN DISTRIBUTED ECONOMETRIC APPLICATIONS REENGINEERING VIA SOFTWARE EVOLUTION
TESTING AND SECURITY IN DISTRIBUTED ECONOMETRIC APPLICATIONS REENGINEERING VIA SOFTWARE EVOLUTION Cosm TOMOZEI 1 Assstat-Lecturer, PhD C. Vasle Alecsadr Uversty of Bacău, Romaa Departmet of Mathematcs
More informationRQM: 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 informationManaging Interdependent Information Security Risks: Cyberinsurance, Managed Security Services, and Risk Pooling Arrangements
Maagg Iterdepedet Iformato Securty Rsks: Cybersurace, Maaged Securty Servces, ad Rsk Poolg Arragemets Xa Zhao Assstat Professor Departmet of Iformato Systems ad Supply Cha Maagemet Brya School of Busess
More informationCapacitated Production Planning and Inventory Control when Demand is Unpredictable for Most Items: The No B/C Strategy
SCHOOL OF OPERATIONS RESEARCH AND INDUSTRIAL ENGINEERING COLLEGE OF ENGINEERING CORNELL UNIVERSITY ITHACA, NY 4853-380 TECHNICAL REPORT Jue 200 Capactated Producto Plag ad Ivetory Cotrol whe Demad s Upredctable
More informationChapter 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