Term-based composition of security protocols

Size: px
Start display at page:

Download "Term-based composition of security protocols"

Transcription

1 Term-sed composiion of securiy proocols B Genge P Hller R Ovidiu I Ign Peru ior Universiy of Trgu ures Romni genge@upmro phller@upmro oroi@engineeringupmro Technicl Universiy of Cluj poc Romni IosifIgn@csuclujro Asrc-In he conex of securiy proocol prllel composiion where messges elonging o differen proocols cn inersec ech oher we inroduce new prdigm: ermsed composiion (ie he composiion of messge componens lso nown s erms Firs we cree proocol specificion model y exending he originl srnd spces Then we provide erm composiion lgorihm sed on which new erms cn e consruced To ensure h securiy properies re minined we inroduce he concep of erm connecions o express he exising connecions eween erms nd encrypion conexs We illusre he proposed composiion process y using wo exising proocols I ITRODUCTIO Securiy proocols re communicion proocols in which pricipns use encrypion o send ech oher encoded informion Wih he rpid growh of he Inerne nd despere need o secure communicion in he ls few decdes he enion of mny reserchers hs een led owrds he nlysis of securiy proocols [] [] [3] [4] [5] [6] Recenly here hve een severl proposls developed o help he process of securiy proocol design using forml mehods nd ools [7] [8] [9] [0] [] [] [3] os of he proposed echniques use modulr pproch in he design process where he user is given se of smll proocols from which more complex proocols cn e consruced process lso nown s composiion [9] [0] [] In he exising composiion echniques uhors minly del wih he sequenil nd prllel composiion of securiy properies viewed s se of informion rnsmied over messges However he composiion of messge componens hs no een ddressed in proper mnner mening h users hve o solve he prolem of creing new messges on heir own Solving his prolem pprenly insignificn cn led o proocols which execue in hlf he ime he originl composed proocols do In ddiion he composiion process cn led o muliple resuls which mus e crefully nlyzed on messge level o increse proocol performnce In his pper we inroduce novel composiion prdigm: erm-sed composiion The composiion prolem is ddressed he messge level sed on syncicl consrucions nd nlysis This new prdigm is ddressed in he conex of prllel composiion where proocol messges inersec ech oher The resuling proocol conins no only se of unified messges u lso unified se of securiy properies (eg secrecy uhenicion inegriy The pper is srucured s follows Secion II inroduces he concep of -srnds used o model securiy proocols Securiy requiremens re ddressed in secion III In secion IV we presen he prolem of genering proocols using prllel composiion nd erm-sed composiion nd we propose erm composiion lgorihm We exemplify he composiion process y composing wo proocols II KOWLEDGE STRADS In his secion we riefly presen he concep of nowledge srnds (-srnds For more deiled presenion he reder is direced o consul he uhors previous wor [6] [7] A srnd is sequence of rnsmission nd recepion evens used o model proocol pricipns A collecion of srnds is clled srnd spce The srnd spce model ws inroduced y Freg Herzog nd Gumn in [5] nd exended y he uhors wih pricipn nowledge specilized sic ses nd explici erm consrucion in [5] [6] The resuling model is clled -srnd spce The res of his secion formlly defines he -srnd nd - srnd spce conceps By nlyzing he proocol specificions from he SPORE lirry [0] we cn conclude h proocol pricipns communice y exchnging erms consruced from elemens elonging o he following ses: R denoing he se of pricipn nmes; denoing he se of nonces (ie numer once used nd K denoing he se of crypogrphic eys If required oher ses cn e esily dded wihou ffecing he oher componens To denoe he encrypion ype used o cree crypogrphic erms we define he following funcion nmes: Funcme ::= s (secre ey ( p (pulic ey pv (prive ey h (hsh The ove-defined sic ses nd funcion nmes re used in he definiion of erms where we lso inroduce consrucors for piring nd encrypion: T :: = R K ( T T { T } ( Funcme( T where he symol is used o denoe n empy erm We use he symolt o denoe he se of ll suses of erms /08/$ IEEE

2 The composiion process of wo erms nd ino noher erm implies h hs su-erms The su-erm relion is inducively defined s follows Definiion The su-erm relion is he smlles relion on erms such h: ; if or ; { } f ( 3 ( if or Before defining he concep of nowledge srnds we need o define noher elemen: clssifiers As suggesed y heir nmes clssifiers re used o clssify or cegorize nowledge srnds The cegories re creed sed on he ype of operion modeled y given nowledge srnd Formlly clssifiers re defined s: C :: C = R C ( Pricipn clssifier ( emory clssifier To denoe he rnsmission nd recepion of erms we use signed erms The occurrence of erm wih posiive sign denoes rnsmission while he occurrence of erm wih negive sign denoes recepion The se of rnsmission nd recepion sequences is denoed y ( ±T Definiion A -srnd (ie nowledge srnd is uple K c r s where K T denoes he nowledge corresponding o he modeled pricipn c C denoes he clssifier r R denoes he pricipn nme nd ( s ±T denoes he sequence of rnsmissions nd recepions A se of -srnds is clled -srnd spce The se of ll -srnd spces is denoed y Σ Le ς e - srnd spce nd s ς -srnd hen: We define he following mpping funcions: now s o mp he nowledge componen; ( clss ( s o mp he clssifier componen; pr ( s o mp he nme componen; srnd ( s o mp he erm sequence componen; A node is ny rnsmission or recepion of erm wrien s n = srnd ( s i where i is n ineger sisfying he condiion i lengh( s We define he erm( n funcion o mp he erm corresponding o given node; 3 Le n = srnd ( s i nd ( n = srnd s i + e wo consecuive nodes from he sme -srnd Then here exiss n edge n n in he sme -srnd; 4 Le n n e wo nodes If n is posiive node nd n is negive node elonging o differen - srnds hen here exiss n edge n n We define he sign( n funcion o mp he sign of given node (3 Fig shows n exmple specificion of Lowe s BA Concree Secure RPC [4] proocol in he descried - srnd spce model III SECURITY REQUIREETS The composiion of securiy proocols cn no e mde y simply dding messges o one proocol By inspecing he rher lrge numer of repored cs in he lierure [4] [8] [0] we cn gree h ny modificion rough upon proocol cn influence is exising securiy properies Bsed on hese concerns he uhors hve developed in previous pper [7] frmewor for verifying he composiliy of securiy proocols The mehod developed y he uhors requires he execuion of wo seps Firs we mus verify if secre erms from one proocol cn e found in insecure erms in he oher proocol By he concep insecure we men erms encryped wih insecure eys (eg session eys or erms h re sen ou clerly Second we mus verify if erms encryped wih he sme ey re srucurlly independen In oher words we mus verify if pricipns sed on erm srucures nd nowledge cn disinguish eween he given erms The firs requiremen is fulfilled y conducing syncicl verificion of he given proocol erms The proocol model used is he one presened in he previous secion Alongside he specificion he user hs o provide he erms considered o e secre for ech proocol For he second requiremen o e fulfilled we mus consruc he cnonicl specificion model proposed y he uhors in he sme pper This model elimines insniion-sed informion (eg A B K leving only essenil informion needed in he srucurl independence verificion process (eg n r r IV COPOSITIO A Genering proocols By using prllel composiion we cn produce severl disinc proocols For exmple given wo proocols P nd P ech of hem wih wo messges he proocols h cn e consruced re lised in Tle where Pi nd i j denoe messge indexes corresponding o Pj he wo proocols nd PxiPyj x y { } denoes concenion P P P P P P TLE I PROTOCOL AD ESSAGE SEQUECES GEERATED USIG PARALLEL ESSAGE COPOSITIO Wihou erm Wih erm composiion composiion P P P P P P P P P P - - P P P P P P P P P P -

3 A { A B K } B { B A K K } Figure Lowe s BA Concree Andrew Secure RPC represenion in he -srnd spce model ore formlly given wo proocols modeled in he - srnd spce ς ς Σ we genere new proocols using operions such s messge inerclion nd erm concenion essge inerclion denoes he process y which severl messges elonging o differen proocols re comined ogeher mininig he sme ime heir originl order of ppernce On he oher hnd erm concenion simply concenes wo erms wihou performing ny opimisions on he resuling erm The genered proocols re denoed y he se GenProPirs Ech elemen of his se conins sequence of erm pirs x y i j where he firs componen denoes erms rnsmied in he firs proocol nd he second componen denoes erms rnsmied in he second proocol ore formlly xi senterms ( ς y j senterms ( ς i senterms ( ς ( = j = senterms ς where senterms : Σ T is funcion mpping he se of sen erms in given proocol specificion defined s: senterms A { K B } s ( K { } s ( K = s ς i= lengh( srnd ( s ni = srnd ( s i sign( ni =+ ( ς erm( ni {} (4 This funcion lso mpps empy componens denoed y o model siuions where he second operion (ie erm concenion is no pplied As finl sep for he proocol generion process we mus chec h concened messges hve he sme source nd desinion pricipns If we find les one messge h does no sisfy his requiremen he enire proocol is removed from he lis B Securiy propery definiion The erm composiion process consrucs ll possile cominions of erms using wo given erms y modifying exising erms In he conex of securiy proocols hese cominions mus no desroy exising securiy properies In order o provide correc composiion we mus define he concep of securiy propery Becuse securiy proocols consis of pricipns exchnging erms securiy properies re creed y he rnsmied nd received erms ore specificlly i is he crypogrphic conex of ech erm in conjuncion wih he exchnge of erms from which securiy properies re consruced To formlly define securiy properies we inroduce wo new conceps: pril nd complee erm connecion Connecions eween erms denoe he exisence of se of common erms Pril connecions denoe he connecions eween free (ie unencryped erm nd n encryped one while complee connecions denoe he connecions eween wo encryped erms To express he exisence of pril nd complee connecion we inroduce wo operors ( ( _ _ : ± T T Σ ± T T Σ nd P ( ( _ _ : ± T T Σ ± T T Σ respecively C These operors denoe he connecion eween one node erm nd -srnd o noher node erm nd -srnd The firs componen of hese operors is clled pre-condiion nd he second is clled pos-condiion We define he following funcions cnode cerm csrnd o mp he node erm nd -srnd corresponding o pre-condiion or pos-condiion We sy h here is pril connecion eween wo erms nd if is su-erm of is no encryped nd hs crypogrphic consrucion or vicevers Formlly n s P n s if where (5 ( { } ( = { } ( f f ( = { } ( { } f f ( erm ( n erm( n n { ni i lengh ( srnd ( s } n ni i lengh( srnd ( s A complee connecion eween wo erms nd exiss only if is n encryped su-erm of nd hs crypogrphic consrucion or he non-crypogrphic componen of is su-erm of Formlly n s C n s if or where (6 = ( = { } f ( erm ( n erm( n { i ( ( } i ( ( f n n i lengh srnd s n n i lengh srnd s Definiion 3 A securiy propery ξ is collecion of pril nd complee connecions By he definiion given ove securiy propery is se of connecions eween erms This definiion is similr o he definiion of uhenicon ess given y Gumn in [0] The difference is h we define connecions no only eween erms rnsmied y differen nodes u lso eween su-erms This llows us o define complex securiy properies such s uhenicion u lso oher more sule ones such s secrecy By using erm connecions we cn model dependencies eween erms This ey spec is vil in he process of erm composiion ecuse y modifying one erm we mus

4 lso modify oher dependen erms o minin exising securiy properies C odeling dynmic nowledge As opposed o he sic (ie iniil nowledge here is noher ype of nowledge h cn e consruced y proocol pricipns: dynmic nowledge This ype of nowledge grows wih every erm h is received Dynmic nowledge is modeled s -srnd h communices wih he pricipn s -srnd using erm rnsmissions nd recepions Pricipns re modeled s pir of -srnds consising of one min pricipn -srnd nd memory - srnd modeling dynmic nowledge In he composiion process erms cn e modified For exmple hey cn e included in crypogrphic conex h cn no e creed y pricipn ecuse he given node crypogrphic eys hve no ye een received By modeling dynmic nowledge we re le o decide if he erms h mus e rnsmied y node cn e consruced In order o provide persisen model of he dynmic nowledge we consider h erms from his nowledge re sored in memory region h cn only e ccessed y he corresponding pricipn This memory region s menioned erlier is modeled s -srnd However ecuse communicion eween ech pricipn nd is ched memory mus e prive we consider n encryped communicion model using new funcion ype m nd ey The funcion is he sme while he ey is unique for ech user ex we propose n lgorihm for creing memory - srnds idenified y he clssc Given n iniil - srnd s h models he operions corresponding o pricipn y running he lgorihm we genere wo new -srnds pricipn -srnd s nd memory - srnd s The newly genered pricipn -srnd ddiionlly conins nodes modeling communicion wih he ched memory -srnd Receiving erm from he memory -srnd corresponds o he dynmic nowledge The erms received y memory -srnds re decoded rnsformed ino new nowledge nd dded o he exising nowledge The proposed lgorihm mes use of he genknow : T T T funcion o genere new nowledge sed on exising nowledge (sored s erm nd new received erm Algorihm emory -srnd generion: Genere memory communicion encrypion ey K m Iniilize he new -srnds: s = { now( s Km} C R r s = { now( s Km} C r For every posiive node n = srnd ( s i dd posiive node o s : ( C ( s now s r srnd s n = R 3 For every negive node n = srnd ( s i dd negive node o s nd genere new nowledge: ( C R ( { ( } ( s = now s r srnd s n + erm n m K m ( C ( { ( } ( s = now s r srnd s erm n m K m Le n e he ls posiive node from s Le = now( s K = now s K nd ( Le now = genknow( erm( n erm( n ( ( s = K C r srnd s R now m K m ( ( s = K C r srnd s + now m K m D Term composiion lgorihm In he proocol generion process descried secion A erms h re concened mus e composed in order o genere more performn proocols The composiion process cn ler erms minining he sme ime exising securiy properies Firs we consruc he connecion sequences eween proocol erms for he involved proocols Then we iniilize new -srnd spce y creing -srnds corresponding o pricipns The iniilizion process lso crees unified sic nowledge ses for every pricipn ex for every pir of concened erms resuled in he proocol generion phse we run he composiion lgorihm By modifying one erm we mus ensure h he erms from he connecion sequence re lso modified We ensure h pril connecions re minined y no modifying he crypogrphic conex of erms inining complee connecions however requires susequen modificion of dependen erms Afer performing ech erm composiion he memory - srnd lgorihm from secion C is run o consruc he memory -srnds Then for every erm rnsmied y pricipn -srnd we use he Consrucle : T T T predice o verify if he rnsmied erm cn e consruced from he exising sic nd dynmic nowledge senterms ς For wo concened erms ( ( ( senterms ς he composiion lgorihm is he following Algorihm Composiion: Consruc connecion sequences s securiy properies: ξ = n s n s s s ς Le { C P } Le ξ = { n s C P n s s s ς } Iniilize new -srnd spce: Le ς e he resuling -srnd spce For ech s ς ς do If ( s ς role( s role( s Le s = now( s role( s C R ς = ς { s } <> hen Le s ς : role( s role( s = nd s = K r c s

5 { K ( } s = now s r c s EndFor 3 Compose wo erms: = Le = { } f ( { } f ( erm( n erm( n If f = f = hen If / ( c C c ξ : ( cerm( c = cnode( c = n ( cerm ( c = cnode( c = n hen = { } f ( / c c ξ If ( C : ( cerm( c cnode( c n = { } f ( = = erm connecion sequence = { } f erm connecion sequence 4 Genere memory Algorihm o consruc ς iniilized sep 5 Verify erm generion s s ς : clss s = C clss s = C Le ( R ( pr ( s = pr ( s Le n n e he ls posiive node from s nd s respecively If ( ( ( ( Consrucle erm n now s erm n ς V COPOSITIO EXAPLE To illusre he composiion process we use wo proocols: Woo nd Lm Pi3 [6] nd Lowe s modified version of he Yhlom [8 9] proocol The -srnd represenion of he wo proocols cn e seen in Fig nd Fig 3 We use ς o model he -srnd spce corresponding o he Woo nd Lm Pi3 nd ς o model he - srnd spce corresponding o Lowe s Yhlom proocol The firs sep owrds he composiion of hese proocols consiss in verifying he ey-secrecy independence securiy requiremen formuled y he uhors in [7] To chieve his we specify he secre erms for he wo involved proocols For he firs proocol hese re no secre erms while he secre erms for he K (we consider h second proocol re pricipn nmes re pulic B { A B S K } A { A B S K } A s K Figure Woo nd Lm Pi3 represenion in he -srnd spce model A A B S K A { } s ( K A { A B S } s ( K Figure 3 Lowe s modified version of Yhlom s represenion in he - srnd spce model Becuse ( : senterms ς nd is no encryped he firs requiremen is no sisfied To llow he composiion of he wo proocols in he firs proocol mus e differen from in he second proocol We emphsize his spec y replcing wih in ς Becuse of spce considerions we only consruc complee connecions which ply crucil role in he composiion process In proocol ς we hve only one complee connecion: ( s K s ( K + s { A { } s ( K } s ( K ( B A B S K A C ( s K s ( K s ( K + A s B Becuse of erm srucure vrieies in proocol ς here re no complee connecions By using he seps descried in secion IVB we genere ll possile sequences of proocols resuling ol numer of 683 proocols Afer filering proocols for which concened erms hve differen source-desinion pricipns here remin ol numer of 408 proocols For ech proocol we cn pply he erm composiion lgorihm resuling new se of proocols One of he resuling proocols is shown in Fig 4 In order o selec he mos performn proocols we cn pply he minimum numer of messges principle A B S K S K K A { } s ( K { B K } s ( K { A K } ( S A B S K K s K

6 B { A B S K } A { A B S K } A { } s ( K Figure 4 Composed proocol or we cn consruc performnce evluion mehod which we consider o e pr of fuure wor As we cn see from Fig 4 he complee connecion is lso minined in he composed proocol In ddiion he second securiy requiremen formuled y he uhors in [7] ie messge independence is lso sisfied ecuse messges hve differen crypogrphicl srucures VI COCLUSIOS AD FUTURE WORK In his pper we proposed mehod for composing securiy proocol erms To define securiy properies emedded in proocols we inroduced he concep of pril nd complee connecions Our pproch modifies erms only in he sense of exending hem wih new componens hus preserving pril connecions Complee connecions re minined y modifying ll susequen erms dependen of he modified erm As fuure wor we inend o exend he proposed erm composiion lgorihm wih performnce-reled informion This would give users he possiiliy o choose he es suied proocol for given environmen However his is rher difficul o chieve sed only on informl specificions This is why we inend o consruc performnce evluion model h llows us o compre proocol performnce rher hn giving n exc ehvior in specific environmen { A { } s ( K } s ( K { A B S } s ( K { A K } s ( K S A B S K K { B K } ( s K REFERECES [] Adi A D Gordon A Clculus for Crypogrphic Proocols: he spi-clculus In Fourh AC Conference on Compuer nd Communicions Securiy AC Press pp [] Andrew D Gordon Aln Jeffrey Auheniciy y Typing for Securiy Proocols Journl of Compuer Securiy (4 pp [3] Cremers C Scyher documenion 004 ville hp://wwwwinuenl/~cremers/scyher [4] Cherine edows A Procedure for Verifying Securiy Agins Type Confusion Acs 6h IEEE Compuer Securiy Foundions Worshop (CSFW'03 p [5] Genge Bel Iosif Ign An Asrc odel for Securiy Proocol Anlysis WSE TRASACTIOS on COPUTERS Issue Volume 6 pp [6] Genge Bel Iosif Ign A yped specificion for securiy proocols Proceedings of he 5h WSE In Conf on D ewors Communicions nd Compuers Buchres Romni Ocoer 6-7 pp [7] Cs J F Cremers Composiionliy of Securiy Proocols: A Reserch Agend Elecr oes Theor Compu Sci 4 pp [8] S Andov Cs JF Cremers K Gjoseen S uw S jolsnes nd S Rdomirovic A frmewor for composiionl verificion of securiy proocols vier o pper 007 [9] Levene Buyn Building locs for secure services: Auheniced ey rnspor nd Rionl exchnge proocols Thesis 00 [0] Joshu D Gumn Securiy proocol design vi uhenicion ess In Proceedings of he 5h IEEE Compuer Securiy Foundions Worshop IEEE CS Press June 00 [] Hyun-Jin Choi Securiy proocol design y composiion Cmridge Universiy UK Technicl repor r 657 UCA-CL-TR- 657 ISS [] Rn Cnei Tl Rin Universl Composiion wih Join Se In Proceedings of CRYPTO 003 Lecure oes in Compuer Science vol 79 Springer Verlg ew Yor pp [3] A D A Dere J C ichell A Roy Proocol Composiion Logic (PCL Elecronic oes in Theoreicl Compuer Science Volume 7 April pp [4] Gvin Lowe Some new cs upon securiy proocols In Proceedings of he 9 h Compuer Securiy Foundions Worshop IEEE Compuer Sociey Press pp [5] F Jvier Thyer Freg Jonhn C Herzog Joshu D Gumn Srnd spces: Proving securiy proocols correc Journl of Compuer Securiy [6] TYC Woo nd S S Lm A lesson on uhenicion proocol design Opering Sysems Review 994 [7] Genge Bel Iosif Ign Verifying he Independence of Securiy Proocols IEEE 3 rd Inernionl Conference on Inelligen Compuer Communicion nd Processing Cluj-poc Romni pp [8] Gvin Lowe Towrds compleeness resul for model checing of securiy proocols Technicl Repor 998/6 Dep of hemics nd Compuer Science Universiy of Leiceser 998 [9] Lwrence J Pulson Relions eween secres: Two forml nlyses of he Yhlom proocol Journl of Compuer Science 00 [0] --- SPORE Securiy Proocol Open Reposiory hp://wwwlsvens-cchnfr/spore

Example What is the minimum bandwidth for transmitting data at a rate of 33.6 kbps without ISI?

Example What is the minimum bandwidth for transmitting data at a rate of 33.6 kbps without ISI? Emple Wh is he minimum ndwidh for rnsmiing d re of 33.6 kps wihou ISI? Answer: he minimum ndwidh is equl o he yquis ndwidh. herefore, BW min W R / 33.6/ 6.8 khz oe: If % roll-off chrcerisic is used, ndwidh

More information

Dynamic Magnification Factor of SDOF Oscillators under. Harmonic Loading

Dynamic Magnification Factor of SDOF Oscillators under. Harmonic Loading Dynmic Mgnificion Fcor of SDOF Oscillors under Hrmonic Loding Luis Mrí Gil-Mrín, Jun Frncisco Cronell-Márquez, Enrique Hernández-Mones 3, Mrk Aschheim 4 nd M. Psds-Fernández 5 Asrc The mgnificion fcor

More information

Improper Integrals. Dr. Philippe B. laval Kennesaw State University. September 19, 2005. f (x) dx over a finite interval [a, b].

Improper Integrals. Dr. Philippe B. laval Kennesaw State University. September 19, 2005. f (x) dx over a finite interval [a, b]. Improper Inegrls Dr. Philippe B. lvl Kennesw Se Universiy Sepember 9, 25 Absrc Noes on improper inegrls. Improper Inegrls. Inroducion In Clculus II, sudens defined he inegrl f (x) over finie inervl [,

More information

Phys222 W12 Quiz 2: Chapters 23, 24. Name: = 80 nc, and q = 30 nc in the figure, what is the magnitude of the total electric force on q?

Phys222 W12 Quiz 2: Chapters 23, 24. Name: = 80 nc, and q = 30 nc in the figure, what is the magnitude of the total electric force on q? Nme: 1. A pricle (m = 5 g, = 5. µc) is relesed from res when i is 5 cm from second pricle (Q = µc). Deermine he mgniude of he iniil ccelerion of he 5-g pricle.. 54 m/s b. 9 m/s c. 7 m/s d. 65 m/s e. 36

More information

One Practical Algorithm for Both Stochastic and Adversarial Bandits

One Practical Algorithm for Both Stochastic and Adversarial Bandits One Prcicl Algorihm for Boh Sochsic nd Adversril Bndis Yevgeny Seldin Queenslnd Universiy of Technology, Brisbne, Ausrli Aleksndrs Slivkins Microsof Reserch, New York NY, USA YEVGENY.SELDIN@GMAIL.COM SLIVKINS@MICROSOFT.COM

More information

STRATEGIC PLANNING COMMITTEE Wednesday, February 17, 2010

STRATEGIC PLANNING COMMITTEE Wednesday, February 17, 2010 em: STATEGC PLANNNG COMMTTEE Wednesdy, Februry 17, 2010 SUBJECT: EQUEST FO APPOVAL TO NAME THE WALKWAY FOM DADE AVENUE TO PAKNG GAAGE 2 DVESTY WAY ON THE BOCA ATON CAMPUS. POPOSED COMMTTEE ACTON Provide

More information

Influence of Network Load on the Performance of Opportunistic Scanning

Influence of Network Load on the Performance of Opportunistic Scanning Influence of Nework Lod on he Performnce of Opporunisic Scnning Mrc Emmelmnn, Sven Wiehöler, nd Hyung-Tek Lim Technicl Universiy Berlin Telecommunicion Neworks Group TKN Berlin, Germny Emil: emmelmnn@ieee.org,

More information

Reuse-Based Test Traceability: Automatic Linking of Test Cases and Requirements

Reuse-Based Test Traceability: Automatic Linking of Test Cases and Requirements Inernionl Journl on Advnces in Sofwre, vol 7 no 3&4, yer 2014, hp://www.irijournls.org/sofwre/ Reuse-Bsed Tes Trcebiliy: Auomic Linking of Tes Cses nd Requiremens 469 Thoms Nock, Thoms Krbe Technische

More information

Efficient One-time Signature Schemes for Stream Authentication *

Efficient One-time Signature Schemes for Stream Authentication * JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 611-64 (006) Efficien One-ime Signaure Schemes for Sream Auhenicaion * YONGSU PARK AND YOOKUN CHO + College of Informaion and Communicaions Hanyang Universiy

More information

The Application of Multi Shifts and Break Windows in Employees Scheduling

The Application of Multi Shifts and Break Windows in Employees Scheduling The Applicaion of Muli Shifs and Brea Windows in Employees Scheduling Evy Herowai Indusrial Engineering Deparmen, Universiy of Surabaya, Indonesia Absrac. One mehod for increasing company s performance

More information

Detecting Network Intrusions via Sampling : A Game Theoretic Approach

Detecting Network Intrusions via Sampling : A Game Theoretic Approach Deecing Nework Inrusions vi Smpling : A Gme Theoreic Approch Murli Kodilm T. V. Lkshmn Bell Lborories Lucen Technologies 101 Crwfords Corner Rod Holmdel, NJ 07733, USA {murlik, lkshmn}@bell-lbs.com Absrc

More information

Single-machine Scheduling with Periodic Maintenance and both Preemptive and. Non-preemptive jobs in Remanufacturing System 1

Single-machine Scheduling with Periodic Maintenance and both Preemptive and. Non-preemptive jobs in Remanufacturing System 1 Absrac number: 05-0407 Single-machine Scheduling wih Periodic Mainenance and boh Preempive and Non-preempive jobs in Remanufacuring Sysem Liu Biyu hen Weida (School of Economics and Managemen Souheas Universiy

More information

TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS

TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS RICHARD J. POVINELLI AND XIN FENG Deparmen of Elecrical and Compuer Engineering Marquee Universiy, P.O.

More information

A Multi-agent Trading Platform for Electricity Contract Market

A Multi-agent Trading Platform for Electricity Contract Market 1 A Muli-gen Trding Plform for Elecriciy Conrc Mrke Yun Ji-hi, Yu Shun-kun nd Hu Zho-gung Absrc-- An gen-bsed negoiion plform for power genering nd power consuming (purchsing) compnies in conrc elecriciy

More information

Regular Sets and Expressions

Regular Sets and Expressions Regulr Sets nd Expressions Finite utomt re importnt in science, mthemtics, nd engineering. Engineers like them ecuse they re super models for circuits (And, since the dvent of VLSI systems sometimes finite

More information

Inductance and Transient Circuits

Inductance and Transient Circuits Chaper H Inducance and Transien Circuis Blinn College - Physics 2426 - Terry Honan As a consequence of Faraday's law a changing curren hrough one coil induces an EMF in anoher coil; his is known as muual

More information

Reasoning to Solve Equations and Inequalities

Reasoning to Solve Equations and Inequalities Lesson4 Resoning to Solve Equtions nd Inequlities In erlier work in this unit, you modeled situtions with severl vriles nd equtions. For exmple, suppose you were given usiness plns for concert showing

More information

PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE

PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE Profi Tes Modelling in Life Assurance Using Spreadshees PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE Erik Alm Peer Millingon 2004 Profi Tes Modelling in Life Assurance Using Spreadshees

More information

Module 4. Single-phase AC circuits. Version 2 EE IIT, Kharagpur

Module 4. Single-phase AC circuits. Version 2 EE IIT, Kharagpur Module 4 Single-phase A circuis ersion EE T, Kharagpur esson 5 Soluion of urren in A Series and Parallel ircuis ersion EE T, Kharagpur n he las lesson, wo poins were described:. How o solve for he impedance,

More information

Principal components of stock market dynamics. Methodology and applications in brief (to be updated ) Andrei Bouzaev, bouzaev@ya.

Principal components of stock market dynamics. Methodology and applications in brief (to be updated ) Andrei Bouzaev, bouzaev@ya. Principal componens of sock marke dynamics Mehodology and applicaions in brief o be updaed Andrei Bouzaev, bouzaev@ya.ru Why principal componens are needed Objecives undersand he evidence of more han one

More information

Human Body Tracking with Auxiliary Measurements

Human Body Tracking with Auxiliary Measurements IEEE Inernionl Workshop on Anlysis nd Modeling of Fces nd Gesures, 003. Humn Body Trcking wih Auxiliry Mesuremens Mun Wi Lee, Isc Cohen Insiue for Roboics nd Inelligen Sysems Inegred Medi Sysems Cener

More information

USE OF EDUCATION TECHNOLOGY IN ENGLISH CLASSES

USE OF EDUCATION TECHNOLOGY IN ENGLISH CLASSES USE OF EDUCATION TECHNOLOGY IN ENGLISH CLASSES Mehme Nuri GÖMLEKSİZ Absrac Using educaion echnology in classes helps eachers realize a beer and more effecive learning. In his sudy 150 English eachers were

More information

Appendix A: Area. 1 Find the radius of a circle that has circumference 12 inches.

Appendix A: Area. 1 Find the radius of a circle that has circumference 12 inches. Appendi A: Area worked-ou s o Odd-Numbered Eercises Do no read hese worked-ou s before aemping o do he eercises ourself. Oherwise ou ma mimic he echniques shown here wihou undersanding he ideas. Bes wa

More information

Duration and Convexity ( ) 20 = Bond B has a maturity of 5 years and also has a required rate of return of 10%. Its price is $613.

Duration and Convexity ( ) 20 = Bond B has a maturity of 5 years and also has a required rate of return of 10%. Its price is $613. Graduae School of Business Adminisraion Universiy of Virginia UVA-F-38 Duraion and Convexiy he price of a bond is a funcion of he promised paymens and he marke required rae of reurn. Since he promised

More information

3.1. Overview Serial Devices to Ethernet Gateway

3.1. Overview Serial Devices to Ethernet Gateway Overview Progrmmble Server (Seril-o-) Overview Overview.. Overview Seril o Gewy he CP DAS Progrmmble Server i deigned o bring nework conneciviy o your eril device. he progrmmble feure llow developer o

More information

Task is a schedulable entity, i.e., a thread

Task is a schedulable entity, i.e., a thread Real-Time Scheduling Sysem Model Task is a schedulable eniy, i.e., a hread Time consrains of periodic ask T: - s: saring poin - e: processing ime of T - d: deadline of T - p: period of T Periodic ask T

More information

Math 135 Circles and Completing the Square Examples

Math 135 Circles and Completing the Square Examples Mth 135 Circles nd Completing the Squre Exmples A perfect squre is number such tht = b 2 for some rel number b. Some exmples of perfect squres re 4 = 2 2, 16 = 4 2, 169 = 13 2. We wish to hve method for

More information

Chapter 8: Regression with Lagged Explanatory Variables

Chapter 8: Regression with Lagged Explanatory Variables Chaper 8: Regression wih Lagged Explanaory Variables Time series daa: Y for =1,..,T End goal: Regression model relaing a dependen variable o explanaory variables. Wih ime series new issues arise: 1. One

More information

ANALYSIS AND COMPARISONS OF SOME SOLUTION CONCEPTS FOR STOCHASTIC PROGRAMMING PROBLEMS

ANALYSIS AND COMPARISONS OF SOME SOLUTION CONCEPTS FOR STOCHASTIC PROGRAMMING PROBLEMS ANALYSIS AND COMPARISONS OF SOME SOLUTION CONCEPTS FOR STOCHASTIC PROGRAMMING PROBLEMS R. Caballero, E. Cerdá, M. M. Muñoz and L. Rey () Deparmen of Applied Economics (Mahemaics), Universiy of Málaga,

More information

4 Convolution. Recommended Problems. x2[n] 1 2[n]

4 Convolution. Recommended Problems. x2[n] 1 2[n] 4 Convoluion Recommended Problems P4.1 This problem is a simple example of he use of superposiion. Suppose ha a discree-ime linear sysem has oupus y[n] for he given inpus x[n] as shown in Figure P4.1-1.

More information

Technical Report. Resource Sharing Under a Server-based Semi- Partitioned Scheduling Approach. Alexandre Esper Eduardo Tovar

Technical Report. Resource Sharing Under a Server-based Semi- Partitioned Scheduling Approach. Alexandre Esper Eduardo Tovar Technical Repor Resource Sharing Under a Server-based Semi- Pariioned Scheduling Approach Alexandre Esper Eduardo Tovar CISTER-TR-4008 0-08-04 Technical Repor CISTER-TR-4008 Resource Sharing Under a Server-based

More information

Distributing Human Resources among Software Development Projects 1

Distributing Human Resources among Software Development Projects 1 Disribuing Human Resources among Sofware Developmen Proecs Macario Polo, María Dolores Maeos, Mario Piaini and rancisco Ruiz Summary This paper presens a mehod for esimaing he disribuion of human resources

More information

Term Structure of Prices of Asian Options

Term Structure of Prices of Asian Options Term Srucure of Prices of Asian Opions Jirô Akahori, Tsuomu Mikami, Kenji Yasuomi and Teruo Yokoa Dep. of Mahemaical Sciences, Risumeikan Universiy 1-1-1 Nojihigashi, Kusasu, Shiga 525-8577, Japan E-mail:

More information

Individual Health Insurance April 30, 2008 Pages 167-170

Individual Health Insurance April 30, 2008 Pages 167-170 Individual Healh Insurance April 30, 2008 Pages 167-170 We have received feedback ha his secion of he e is confusing because some of he defined noaion is inconsisen wih comparable life insurance reserve

More information

Evolutionary building of stock trading experts in real-time systems

Evolutionary building of stock trading experts in real-time systems Evoluionary building of sock rading expers in real-ime sysems Jerzy J. Korczak Universié Louis Paseur Srasbourg, France Email: jjk@dp-info.u-srasbg.fr Absrac: This paper addresses he problem of consrucing

More information

Automatic measurement and detection of GSM interferences

Automatic measurement and detection of GSM interferences Auomaic measuremen and deecion of GSM inerferences Poor speech qualiy and dropped calls in GSM neworks may be caused by inerferences as a resul of high raffic load. The radio nework analyzers from Rohde

More information

Optimal Contracts in a Continuous-Time Delegated Portfolio Management Problem

Optimal Contracts in a Continuous-Time Delegated Portfolio Management Problem Opiml Conrcs in Coninuous-ime Deleged Porfolio Mngemen Problem Hui Ou-Yng Duke Universiy nd Universiy of Norh Crolin his ricle sudies he conrcing problem beween n individul invesor nd professionl porfolio

More information

Measuring macroeconomic volatility Applications to export revenue data, 1970-2005

Measuring macroeconomic volatility Applications to export revenue data, 1970-2005 FONDATION POUR LES ETUDES ET RERS LE DEVELOPPEMENT INTERNATIONAL Measuring macroeconomic volailiy Applicaions o expor revenue daa, 1970-005 by Joël Cariolle Policy brief no. 47 March 01 The FERDI is a

More information

The Roos of Lisp paul graham Draf, January 18, 2002. In 1960, John McCarhy published a remarkable paper in which he did for programming somehing like wha Euclid did for geomery. 1 He showed how, given

More information

Multiprocessor Systems-on-Chips

Multiprocessor Systems-on-Chips Par of: Muliprocessor Sysems-on-Chips Edied by: Ahmed Amine Jerraya and Wayne Wolf Morgan Kaufmann Publishers, 2005 2 Modeling Shared Resources Conex swiching implies overhead. On a processing elemen,

More information

MTH6121 Introduction to Mathematical Finance Lesson 5

MTH6121 Introduction to Mathematical Finance Lesson 5 26 MTH6121 Inroducion o Mahemaical Finance Lesson 5 Conens 2.3 Brownian moion wih drif........................... 27 2.4 Geomeric Brownian moion........................... 28 2.5 Convergence of random

More information

ACCOUNTING, ECONOMICS AND FINANCE. School Working Papers Series 2004 SWP 2004/08

ACCOUNTING, ECONOMICS AND FINANCE. School Working Papers Series 2004 SWP 2004/08 FACULTY OF BUSINESS AND LAW School of ACCOUNTING, ECONOMICS AND FINANCE School Workin Ppers Series 4 SWP 4/8 STRUCTURAL EFFECTS AND SPILLOVERS IN HSIF, HSI AND S&P5 VOLATILITY Gerrd Gnnon* Deprmen of Accounin,

More information

EQUATIONS OF LINES AND PLANES

EQUATIONS OF LINES AND PLANES EQUATIONS OF LINES AND PLANES MATH 195, SECTION 59 (VIPUL NAIK) Corresponding mteril in the ook: Section 12.5. Wht students should definitely get: Prmetric eqution of line given in point-direction nd twopoint

More information

Photo Modules for PCM Remote Control Systems

Photo Modules for PCM Remote Control Systems Phoo Modules for PCM Remoe Conrol Sysems Available ypes for differen carrier frequencies Type fo Type fo TSOP173 3 khz TSOP1733 33 khz TSOP1736 36 khz TSOP1737 36.7 khz TSOP1738 38 khz TSOP174 4 khz TSOP1756

More information

Information Technology Investment and Adoption: A Rational Expectations Perspective

Information Technology Investment and Adoption: A Rational Expectations Perspective Informion Technology Invesmen nd Adopion: A Rionl Expecions Perspecive Yoris A. Au Rober J. Kuffmn Docorl Progrm, Informion nd Decision Co-Direcor, MIS Reserch Cener nd Sciences, Crlson School of Mngemen,

More information

Option Put-Call Parity Relations When the Underlying Security Pays Dividends

Option Put-Call Parity Relations When the Underlying Security Pays Dividends Inernaional Journal of Business and conomics, 26, Vol. 5, No. 3, 225-23 Opion Pu-all Pariy Relaions When he Underlying Securiy Pays Dividends Weiyu Guo Deparmen of Finance, Universiy of Nebraska Omaha,

More information

IR Receiver Module for Light Barrier Systems

IR Receiver Module for Light Barrier Systems IR Receiver Module for Ligh Barrier Sysems MECHANICAL DATA Pinning: 1 = OUT, 2 = GND, 3 = V S 19026 APPLICATIONS Reflecive sensors for hand dryers, owel or soap dispensers, waer fauces, oile flush Vending

More information

Chapter 1.6 Financial Management

Chapter 1.6 Financial Management Chaper 1.6 Financial Managemen Par I: Objecive ype quesions and answers 1. Simple pay back period is equal o: a) Raio of Firs cos/ne yearly savings b) Raio of Annual gross cash flow/capial cos n c) = (1

More information

Time Series Analysis Using SAS R Part I The Augmented Dickey-Fuller (ADF) Test

Time Series Analysis Using SAS R Part I The Augmented Dickey-Fuller (ADF) Test ABSTRACT Time Series Analysis Using SAS R Par I The Augmened Dickey-Fuller (ADF) Tes By Ismail E. Mohamed The purpose of his series of aricles is o discuss SAS programming echniques specifically designed

More information

Outline. Numerical Analysis Boundary Value Problems & PDE. Exam. Boundary Value Problems. Boundary Value Problems. Solution to BVProblems

Outline. Numerical Analysis Boundary Value Problems & PDE. Exam. Boundary Value Problems. Boundary Value Problems. Solution to BVProblems Oulie Numericl Alysis oudry Vlue Prolems & PDE Lecure 5 Jeff Prker oudry Vlue Prolems Sooig Meod Fiie Differece Meod ollocio Fiie Eleme Fll, Pril Differeil Equios Recp of ove Exm You will o e le o rig

More information

Towards Incentive-Compatible Reputation Management

Towards Incentive-Compatible Reputation Management Towards Incenive-Compaible Repuaion Managemen Radu Jurca, Boi Falings Arificial Inelligence Laboraory Swiss Federal Insiue of Technology (EPFL) IN-Ecublens, 115 Lausanne, Swizerland radu.jurca@epfl.ch,

More information

GUIDE GOVERNING SMI RISK CONTROL INDICES

GUIDE GOVERNING SMI RISK CONTROL INDICES GUIDE GOVERNING SMI RISK CONTROL IND ICES SIX Swiss Exchange Ld 04/2012 i C O N T E N T S 1. Index srucure... 1 1.1 Concep... 1 1.2 General principles... 1 1.3 Index Commission... 1 1.4 Review of index

More information

17 Laplace transform. Solving linear ODE with piecewise continuous right hand sides

17 Laplace transform. Solving linear ODE with piecewise continuous right hand sides 7 Laplace ransform. Solving linear ODE wih piecewise coninuous righ hand sides In his lecure I will show how o apply he Laplace ransform o he ODE Ly = f wih piecewise coninuous f. Definiion. A funcion

More information

Pricing Fixed-Income Derivaives wih he Forward-Risk Adjused Measure Jesper Lund Deparmen of Finance he Aarhus School of Business DK-8 Aarhus V, Denmark E-mail: jel@hha.dk Homepage: www.hha.dk/~jel/ Firs

More information

INTRODUCTION TO FORECASTING

INTRODUCTION TO FORECASTING INTRODUCTION TO FORECASTING INTRODUCTION: Wha is a forecas? Why do managers need o forecas? A forecas is an esimae of uncerain fuure evens (lierally, o "cas forward" by exrapolaing from pas and curren

More information

Botnet Detection by Monitoring Group Activities in DNS Traffic

Botnet Detection by Monitoring Group Activities in DNS Traffic Bone Deecion by Monioring Group Aciviies in DNS Traffic Hyunsang Choi, Hanwoo Lee, Heejo Lee, Hyogon Kim Korea Universiy {realchs, hanwoo, heejo, hyogon}@orea.ac.r Absrac Recen malicious aemps are inended

More information

Life insurance cash flows with policyholder behaviour

Life insurance cash flows with policyholder behaviour Life insurance cash flows wih policyholder behaviour Krisian Buchard,,1 & Thomas Møller, Deparmen of Mahemaical Sciences, Universiy of Copenhagen Universiesparken 5, DK-2100 Copenhagen Ø, Denmark PFA Pension,

More information

DETERMINISTIC INVENTORY MODEL FOR ITEMS WITH TIME VARYING DEMAND, WEIBULL DISTRIBUTION DETERIORATION AND SHORTAGES KUN-SHAN WU

DETERMINISTIC INVENTORY MODEL FOR ITEMS WITH TIME VARYING DEMAND, WEIBULL DISTRIBUTION DETERIORATION AND SHORTAGES KUN-SHAN WU Yugoslav Journal of Operaions Research 2 (22), Number, 6-7 DEERMINISIC INVENORY MODEL FOR IEMS WIH IME VARYING DEMAND, WEIBULL DISRIBUION DEERIORAION AND SHORAGES KUN-SHAN WU Deparmen of Bussines Adminisraion

More information

Caring for trees and your service

Caring for trees and your service Caring for rees and your service Line clearing helps preven ouages FPL is commied o delivering safe, reliable elecric service o our cusomers. Trees, especially palm rees, can inerfere wih power lines and

More information

TSG-RAN Working Group 1 (Radio Layer 1) meeting #3 Nynashamn, Sweden 22 nd 26 th March 1999

TSG-RAN Working Group 1 (Radio Layer 1) meeting #3 Nynashamn, Sweden 22 nd 26 th March 1999 TSG-RAN Working Group 1 (Radio Layer 1) meeing #3 Nynashamn, Sweden 22 nd 26 h March 1999 RAN TSGW1#3(99)196 Agenda Iem: 9.1 Source: Tile: Documen for: Moorola Macro-diversiy for he PRACH Discussion/Decision

More information

How To Understand The Rules Of The Game Of Chess

How To Understand The Rules Of The Game Of Chess Insiue for Sofware Technology Qualiy Assurance in Sofware Developmen Qualiässicherung in der Sofwareenwicklung A.o.Univ.-Prof. Dipl.-Ing. Dr. Bernhard Aichernig Insiue for Sofware Technology Graz Universiy

More information

Lec 2: Gates and Logic

Lec 2: Gates and Logic Lec 2: Gtes nd Logic Kvit Bl CS 34, Fll 28 Computer Science Cornell University Announcements Clss newsgroup creted Posted on we-pge Use it for prtner finding First ssignment is to find prtners Due this

More information

SEASONAL ADJUSTMENT. 1 Introduction. 2 Methodology. 3 X-11-ARIMA and X-12-ARIMA Methods

SEASONAL ADJUSTMENT. 1 Introduction. 2 Methodology. 3 X-11-ARIMA and X-12-ARIMA Methods SEASONAL ADJUSTMENT 1 Inroducion 2 Mehodology 2.1 Time Series and Is Componens 2.1.1 Seasonaliy 2.1.2 Trend-Cycle 2.1.3 Irregulariy 2.1.4 Trading Day and Fesival Effecs 3 X-11-ARIMA and X-12-ARIMA Mehods

More information

Map Task Scheduling in MapReduce with Data Locality: Throughput and Heavy-Traffic Optimality

Map Task Scheduling in MapReduce with Data Locality: Throughput and Heavy-Traffic Optimality Map Task Scheduling in MapReduce wih Daa Localiy: Throughpu and Heavy-Traffic Opimaliy Weina Wang, Kai Zhu and Lei Ying Elecrical, Compuer and Energy Engineering Arizona Sae Universiy Tempe, Arizona 85287

More information

STABILITY OF LOAD BALANCING ALGORITHMS IN DYNAMIC ADVERSARIAL SYSTEMS

STABILITY OF LOAD BALANCING ALGORITHMS IN DYNAMIC ADVERSARIAL SYSTEMS STABILITY OF LOAD BALANCING ALGORITHMS IN DYNAMIC ADVERSARIAL SYSTEMS ELLIOT ANSHELEVICH, DAVID KEMPE, AND JON KLEINBERG Absrac. In he dynamic load balancing problem, we seek o keep he job load roughly

More information

CLASSIFICATION OF REINSURANCE IN LIFE INSURANCE

CLASSIFICATION OF REINSURANCE IN LIFE INSURANCE CLASSIFICATION OF REINSURANCE IN LIFE INSURANCE Kaarína Sakálová 1. Classificaions of reinsurance There are many differen ways in which reinsurance may be classified or disinguished. We will discuss briefly

More information

STABILITY OF LOAD BALANCING ALGORITHMS IN DYNAMIC ADVERSARIAL SYSTEMS

STABILITY OF LOAD BALANCING ALGORITHMS IN DYNAMIC ADVERSARIAL SYSTEMS SIAM J. COMPUT. Vol. 37, No. 5, pp. 1656 1673 c 2008 Sociey for Indusrial and Applied Mahemaics STABILITY OF LOAD BALANCING ALGORITHMS IN DYNAMIC ADVERSARIAL SYSTEMS ELLIOT ANSHELEVICH, DAVID KEMPE, AND

More information

Stochastic Optimal Control Problem for Life Insurance

Stochastic Optimal Control Problem for Life Insurance Sochasic Opimal Conrol Problem for Life Insurance s. Basukh 1, D. Nyamsuren 2 1 Deparmen of Economics and Economerics, Insiue of Finance and Economics, Ulaanbaaar, Mongolia 2 School of Mahemaics, Mongolian

More information

Department of Health & Human Services (DHHS) Centers for Medicare & Medicaid Services (CMS) Transmittal 1151 Date: November 16, 2012

Department of Health & Human Services (DHHS) Centers for Medicare & Medicaid Services (CMS) Transmittal 1151 Date: November 16, 2012 nul ysem ub 100-20 One-Time Noificion Depmen of elh & umn evices (D) enes fo edice & edicid evices () Tnsmil 1151 De: Novembe 16, 2012 hnge eques 8124 UBJT: Use of Q6 odifie fo Locum Tenens by oviding

More information

Information Theoretic Evaluation of Change Prediction Models for Large-Scale Software

Information Theoretic Evaluation of Change Prediction Models for Large-Scale Software Informaion Theoreic Evaluaion of Change Predicion Models for Large-Scale Sofware Mina Askari School of Compuer Science Universiy of Waerloo Waerloo, Canada maskari@uwaerloo.ca Ric Hol School of Compuer

More information

Task-Execution Scheduling Schemes for Network Measurement and Monitoring

Task-Execution Scheduling Schemes for Network Measurement and Monitoring Task-Execuion Scheduling Schemes for Nework Measuremen and Monioring Zhen Qin, Robero Rojas-Cessa, and Nirwan Ansari Deparmen of Elecrical and Compuer Engineering New Jersey Insiue of Technology Universiy

More information

DYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS

DYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS DYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS Hong Mao, Shanghai Second Polyechnic Universiy Krzyszof M. Osaszewski, Illinois Sae Universiy Youyu Zhang, Fudan Universiy ABSTRACT Liigaion, exper

More information

Signal Processing and Linear Systems I

Signal Processing and Linear Systems I Sanford Universiy Summer 214-215 Signal Processing and Linear Sysems I Lecure 5: Time Domain Analysis of Coninuous Time Sysems June 3, 215 EE12A:Signal Processing and Linear Sysems I; Summer 14-15, Gibbons

More information

Mortality Variance of the Present Value (PV) of Future Annuity Payments

Mortality Variance of the Present Value (PV) of Future Annuity Payments Morali Variance of he Presen Value (PV) of Fuure Annui Pamens Frank Y. Kang, Ph.D. Research Anals a Frank Russell Compan Absrac The variance of he presen value of fuure annui pamens plas an imporan role

More information

Age Biased Technical and Organisational Change, Training and Employment Prospects of Older Workers

Age Biased Technical and Organisational Change, Training and Employment Prospects of Older Workers DISCUSSION PAPER SERIES IZA DP No. 5544 Age Bised Technicl nd Orgnisionl Chnge, Trining nd Employmen Prospecs of Older Workers Luc Behghel Eve Croli Muriel Roger Mrch 2011 Forschungsinsiu zur Zukunf der

More information

DDoS Attacks Detection Model and its Application

DDoS Attacks Detection Model and its Application DDoS Aacks Deecion Model and is Applicaion 1, MUHAI LI, 1 MING LI, XIUYING JIANG 1 School of Informaion Science & Technology Eas China Normal Universiy No. 500, Dong-Chuan Road, Shanghai 0041, PR. China

More information

Analogue and Digital Signal Processing. First Term Third Year CS Engineering By Dr Mukhtiar Ali Unar

Analogue and Digital Signal Processing. First Term Third Year CS Engineering By Dr Mukhtiar Ali Unar Analogue and Digial Signal Processing Firs Term Third Year CS Engineering By Dr Mukhiar Ali Unar Recommended Books Haykin S. and Van Veen B.; Signals and Sysems, John Wiley& Sons Inc. ISBN: 0-7-380-7 Ifeachor

More information

2. The econometric model

2. The econometric model Age Bised Technicl nd Orgnisionl Chnge, Trining nd Employmen Prospecs of Older Workers * Luc BEHAGHEL (Pris School of Economics (INRA) nd CREST) Eve CAROLI (Universiy Pris Duphine, LED-LEGOS, Pris School

More information

INTERFEROMETRIC TECHNIQUES FOR TERRASAR-X DATA. Holger Nies, Otmar Loffeld, Baki Dönmez, Amina Ben Hammadi, Robert Wang, Ulrich Gebhardt

INTERFEROMETRIC TECHNIQUES FOR TERRASAR-X DATA. Holger Nies, Otmar Loffeld, Baki Dönmez, Amina Ben Hammadi, Robert Wang, Ulrich Gebhardt INTERFEROMETRIC TECHNIQUES FOR TERRASAR-X DATA Holger Nies, Omr Loffeld, Bki Dönmez, Amin Ben Hmmdi, Rober Wng, Ulrich Gebhrd Cener for Sensorsysems (ZESS), Universiy of Siegen Pul-Bonz-Sr. 9-, D-5768

More information

A Bayesian Approach for Personalized Booth Recommendation

A Bayesian Approach for Personalized Booth Recommendation 2011 Inernaional Conference on Social Science and Humaniy IPED vol. (2011) (2011) IACSI Press, Singapore A Bayesian Approach for Personalized Booh ecommendaion Ki Mok Ha 2bcreaor@khu.ac.kr Il Young Choi

More information

The Transport Equation

The Transport Equation The Transpor Equaion Consider a fluid, flowing wih velociy, V, in a hin sraigh ube whose cross secion will be denoed by A. Suppose he fluid conains a conaminan whose concenraion a posiion a ime will be

More information

Chapter 2 Problems. 3600s = 25m / s d = s t = 25m / s 0.5s = 12.5m. Δx = x(4) x(0) =12m 0m =12m

Chapter 2 Problems. 3600s = 25m / s d = s t = 25m / s 0.5s = 12.5m. Δx = x(4) x(0) =12m 0m =12m Chaper 2 Problems 2.1 During a hard sneeze, your eyes migh shu for 0.5s. If you are driving a car a 90km/h during such a sneeze, how far does he car move during ha ime s = 90km 1000m h 1km 1h 3600s = 25m

More information

On the degrees of irreducible factors of higher order Bernoulli polynomials

On the degrees of irreducible factors of higher order Bernoulli polynomials ACTA ARITHMETICA LXII.4 (1992 On he degrees of irreducible facors of higher order Bernoulli polynomials by Arnold Adelberg (Grinnell, Ia. 1. Inroducion. In his paper, we generalize he curren resuls on

More information

Detection of DDoS Attack in SIP Environment with Non-parametric CUSUM Sensor

Detection of DDoS Attack in SIP Environment with Non-parametric CUSUM Sensor Deecion of DDoS Aac in SIP Environmen wih Non-parameric CUSUM Sensor Luigi Alcuri Universiy of Palermo Deparmen of Elecrical, Elecronic and Telecommunicaion Engineering luigi.alcuri@i.unipa.i Piero Cassarà

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology

More information

Making a Faster Cryptanalytic Time-Memory Trade-Off

Making a Faster Cryptanalytic Time-Memory Trade-Off Making a Faser Crypanalyic Time-Memory Trade-Off Philippe Oechslin Laboraoire de Securié e de Crypographie (LASEC) Ecole Polyechnique Fédérale de Lausanne Faculé I&C, 1015 Lausanne, Swizerland philippe.oechslin@epfl.ch

More information

Distributed Echo Cancellation in Multimedia Conferencing System

Distributed Echo Cancellation in Multimedia Conferencing System Disribued Echo Cancellaion in Mulimedia Conferencing Sysem Balan Sinniah 1, Sureswaran Ramadass 2 1 KDU College Sdn.Bhd, A Paramoun Corporaion Company, 32, Jalan Anson, 10400 Penang, Malaysia. sbalan@kdupg.edu.my

More information

Factoring Polynomials

Factoring Polynomials Fctoring Polynomils Some definitions (not necessrily ll for secondry school mthemtics): A polynomil is the sum of one or more terms, in which ech term consists of product of constnt nd one or more vribles

More information

Resource allocation in multi-server dynamic PERT networks using multi-objective programming and Markov process. E-mail: bagherpour@iust.ac.

Resource allocation in multi-server dynamic PERT networks using multi-objective programming and Markov process. E-mail: bagherpour@iust.ac. IJST () A: -7 Irnin Journl of Science & Technology hp://www.shirzu.c.ir/en Resource llocion in uli-server dynic PERT neworks using uli-objecive progring nd Mrkov process S. Yghoubi, S. Noori nd M. Bgherpour

More information

An Empirical Comparison of Asset Pricing Models for the Tokyo Stock Exchange

An Empirical Comparison of Asset Pricing Models for the Tokyo Stock Exchange An Empirical Comparison of Asse Pricing Models for he Tokyo Sock Exchange Absrac In his sudy we compare he performance of he hree kinds of asse pricing models proposed by Fama and French (1993), Carhar

More information

How To Optimize Time For A Service In 4G Nework

How To Optimize Time For A Service In 4G Nework Process Opimizaion Time for a Service in 4G Nework by SNMP Monioring and IAAS Cloud Compuing Yassine El Mahoi Laboraory of Compuer Science, Operaions Research and Applied Saisics. Téouan, Morocco Souad

More information

adaptive control; stochastic systems; certainty equivalence principle; long-term

adaptive control; stochastic systems; certainty equivalence principle; long-term COMMUICATIOS I IFORMATIO AD SYSTEMS c 2006 Inernaional Press Vol. 6, o. 4, pp. 299-320, 2006 003 ADAPTIVE COTROL OF LIEAR TIME IVARIAT SYSTEMS: THE BET O THE BEST PRICIPLE S. BITTATI AD M. C. CAMPI Absrac.

More information

Predicting Stock Market Index Trading Signals Using Neural Networks

Predicting Stock Market Index Trading Signals Using Neural Networks Predicing Sock Marke Index Trading Using Neural Neworks C. D. Tilakarane, S. A. Morris, M. A. Mammadov, C. P. Hurs Cenre for Informaics and Applied Opimizaion School of Informaion Technology and Mahemaical

More information

2 DIODE CLIPPING and CLAMPING CIRCUITS

2 DIODE CLIPPING and CLAMPING CIRCUITS 2 DIODE CLIPPING nd CLAMPING CIRCUITS 2.1 Ojectives Understnding the operting principle of diode clipping circuit Understnding the operting principle of clmping circuit Understnding the wveform chnge of

More information

Dependent Interest and Transition Rates in Life Insurance

Dependent Interest and Transition Rates in Life Insurance Dependen Ineres and ransiion Raes in Life Insurance Krisian Buchard Universiy of Copenhagen and PFA Pension January 28, 2013 Absrac In order o find marke consisen bes esimaes of life insurance liabiliies

More information

LNG Pricing Differences across the Atlantic - a Comparison between the United States and Europe

LNG Pricing Differences across the Atlantic - a Comparison between the United States and Europe LNG Pricing Differences cross he Alnic - Comprison beween he Unied Ses nd Europe Virginie Krone Micel Ponce Anne Neumnn Universiä Posdm 37h IAEE Inernionl Conference, New York June, 15-18, 214 Ouline 1.

More information

Capacitors and inductors

Capacitors and inductors Capaciors and inducors We coninue wih our analysis of linear circuis by inroducing wo new passive and linear elemens: he capacior and he inducor. All he mehods developed so far for he analysis of linear

More information

The Grantor Retained Annuity Trust (GRAT)

The Grantor Retained Annuity Trust (GRAT) WEALTH ADVISORY Esae Planning Sraegies for closely-held, family businesses The Granor Reained Annuiy Trus (GRAT) An efficien wealh ransfer sraegy, paricularly in a low ineres rae environmen Family business

More information

Mathematics. Vectors. hsn.uk.net. Higher. Contents. Vectors 128 HSN23100

Mathematics. Vectors. hsn.uk.net. Higher. Contents. Vectors 128 HSN23100 hsn.uk.net Higher Mthemtics UNIT 3 OUTCOME 1 Vectors Contents Vectors 18 1 Vectors nd Sclrs 18 Components 18 3 Mgnitude 130 4 Equl Vectors 131 5 Addition nd Subtrction of Vectors 13 6 Multipliction by

More information