Non-linearity cannot help RFID resist full-disclosure attacks and terrorist fraud attacks

Size: px
Start display at page:

Download "Non-linearity cannot help RFID resist full-disclosure attacks and terrorist fraud attacks"

Transcription

1 SECURITY AND COMMUNICATION NETWORKS Seuy Comm. Newoks 203; 6: Publshed onlne 27 July 202 n Wley Onlne Lby (wleyonlnelby.om)..40 SPECIAL ISSUE PAPER Non-lney nno help RFID ess full-dslosue ks nd eos fud ks Hung-Yu Chen *, Chu-Sng Yng 2 nd Hung-Pn Hou 3 Depmen of Infomon Mngemen, Nonl Ch Nn Unvesy, Pul, Twn 2 Depmen of Elel Engneeng, Nonl Cheng Kung Unvesy, Tnn Cy, Twn 3 Pul Chsn Hospl, Pul, Twn ASTRACT As he onep of do-fequeny denfon (RFID) ely k hs been suessfully mplemened nd demonsed, he eseh of RFID dsne-boundng poools o dee RFID ely ks hs dwn muh enon fom boh he ndusy nd dem. Convenonlly, esehes doped lne omposon of sees o ess eos fud ks. Reenly, Pes-Lopez e l. suded he weknesses of pevous RFID dsne-boundng poools nd poposed h non-lne omposon of sees nd nluson of moe ndom none ould help RFID ess key dslosue k nd eos fud k. In hs ppe, we wll show h non-lne omposon of sees nno help enhne he seuy ully. Copygh 202 John Wley & Sons, Ld. KEYWORDS RFID; uhenon; mf k; eos k; dsne-boundng poool *Coespondene Hung-Yu Chen, Depmen of Infomon Mngemen, Nonl Ch Nn Unvesy, Pul, Twn. E-ml: hyhen@nnu.edu.w. INTRODUCTION In mny do-fequeny denfon (RFID)-bsed pplons suh s ess onol nd nvenoy mngemen, ede would deem h he gs uhenes e n s pomy when uhenes hese gs, beuse RFID ommunons e usully sho. The seuy of hese pplons depends on he seuy of uhenon poools (suh s hose n [ 7]) h hey use nd he ssumpon of g pomy. Fo emple, ess onol sysems of buldngs would llow ess only when he uhened g s n he pomy. Unfounely, hee e wo knds of well-known ely ks [8 0] h mgh umven he lmed nge of do hnnel nd he vefe no belevng he pomy of n uhened g (bu he g s f fom he vefe). The onvenonl RFID uhenon poools opeed n uppe newok lyes nno defe he ely ks, whee n dvesy sng beween legl g nd s vefe ( ede) elys messges beween hem o umven he ssumed ommunon nge... Rely ks The ely k nmed he mf fud k, nodued by Desmed [0], s h n ke ses up ogue pove (sy ^A) nd ogue vefe (sy ^) sng beween he el vefe (sy ) nd he el pove (sy A), nd ^A nd ^ oopevely ely he messges beween A nd so h he vefe wongly beleves h he pove A s n s pomy (bu s no). Anohe ely k lled he eos fud k [0] s h he pove onspes wh ogue ede o he he vefe, whou dslosng s pemnen sees o he onspes. Fgue () nd Fgue (b) espevely show he mf fud k nd he eos fud k, whee he dffeene s h he pove onspes wh he ouge ede nd he ouge g n he eos fud k bu he pove does no o-opee wh he ouge ede nd he ouge g n he mf fud k. Convenonl RFID uhenon poools suh s hose n [ 7] nno dee nd ess suh knds of ks..2. Dsne-boundng poool The onvenonl RFID uhenon poools h usully opee he uppe lye of he poool sk nd do modee ompuons nno obn hgh-esoluon mng of he vls of ndvdul ommunon bs nd, heefoe, nno dee whehe he messges e elyed o eend s ssumed ommunon nge. On ony, dsne-boundng poool suh s hose n [9 8] eeued 490 Copygh 202 John Wley & Sons, Ld.

2 H.-Y. Chen, C.-S. Yng nd H.-P. Hou Non-lney nno help RFID ess ks Tg Rogue Rede Rogue g Rede be fooled () mf fud k Tg Rogue Rede onspe Rogue g onspe Rede be fooled (b) eos fud k Fgue. Vous ely ks on do-fequeny denfon. by pove A nd vefe, whh s ghly neged no he physl lye, s one poenl mehnsm o defe ely ks. I onsss of wo phses slow phse nd fs phse. A pove nd vefe ehnge he hllenges nd ompue sesson sees n he slow phse, nd hen, he vefe hllenges s pove o, usng sesson sees, espond oely b-by-b n he fs phse. I depends on he posulon h no nfomon n popge hough spe me fse hn lgh. If he pove n nswe he vefe s hllenges oely, hen he pove A n onvne he vefe of A s deny nd A s physl pomy o. To effevely mplemen he RFID dsne-boundng poools, eques low-leny ommunon nd mng mehnsm. The sudes suh s [,4] hd poposed poenl mplemenons of low-leny ommunon nd mng mehnsms on low-os gs. Hnke nd Kuhn [] poposed o use ul-wde bnd (UW), whees Red e l. [4] poposed o use sde hnnel lekge s low-leny ommunon mehnsm. In hs ppe, we fous on he desgn of dsne-boundng poools, nd neesed edes e efeed o [,4] fo he dels of mng mehnsms. Whle he pevous dsne-boundng poools (suh s h n [9] h doped publ key opeons) e oo osly fo low-os RFID gs nd he muul uhenon wh dsne-boundng (MAD) poool e desgned fo d ho newoks [6], he een shemes suh s hose n [ 5] e desgned fo RFID pplons. Unfounely, vulnebles of mjo o mno elevne hve been denfed n hem. Cpkun e l. [6] hd desgned he MAD poool o enble wo nodes o deemne he muul dsne he me of he enoune, bu hey dd no ke eos fud k no oun. Km Avone s Swss-knfe RFID dsne-boundng poool [7] med o beng he bes n ems of seuy, pvy, g ompuonl ovehed nd ful olene, bu Pes-Lopez e l. [8] epoed he poool beng vulneble o full-dslosue ks f low-os gs n only suppo modee b-lengh ndom numbes (e.g., 32 bs). They epoed h, fe evesdoppng modee numbe of eeuon sessons of g, s fesble o deve ll he see keys of he g. The mn onl s h, fe evesdoppng on modee numbe of sessons, s hghly possble h some hllenge numbe wll epe nd he ke n, heefoe, dedue he see keys. Pes-Lopez e l. obseved h non-lne omposon of sees nd nluson of moe none ould enhne he seuy nd, heefoe, poposed he Hom RFID dsne-boundng poool. Howeve, we fnd h he Hom sheme s sll vulneble o ou full-dslosue k whee n ke ould dedue ll he see keys of g fe evesdoppng on esonble numbe of RFID sessons, nd he sheme s vulneble o ou eos fud k. We gue h non-lne omposon of sees nno help enhne he seuy. On ony, we popose h onvenonl ppoh of lne omposon of sees s bee. The es of hs ppe s ognzed s follows. Seon 2 evews he Hom sheme [8], nd Seon 3 shows s vulnebly o he full-dslosue k nd he eos fud k. Fnlly, he onluson s gven n Seon THE HITOMI PROTOCOL AND PERIS-LOPE AND COLLEAGUES ATTACKS The Hom poool med o seue he full-dslosue k, he mf fud k, nd he eos fud k h boheng he pevous RFID dsne-boundng shemes. In hs seon, we fs evew he Swss-knfe RFID dsne-boundng poool by Km e l., desbe he full-dslosue k of Pes-Lopez e l., nd hen evew he Hom poool. 2.. Revew of Km Avone s Swss-knfe dsne-boundng poool The noon s nodued s follows. T, pove (g); R, vefe (ede): Inlly, T nd R she see key. ID T, ID R : ID T denoes he deny of he g, nd ID R denoes he deny of he ede. ID, D: ID whou subsp denoes he deny of he g nvolved, nd D denoes he dbse n he seve s sde. f(): keyed hsh funon. N A, N : ndom numbes. C, W, W : sysem-wde onsns. Δ m : he llowed mmum hllenge esponse dely. n: he lengh of oupu sng (lso he numbe of ounds equed). Seuy Comm. Newoks 203; 6: John Wley & Sons, Ld. 49

3 Non-lney nno help RFID ess ks H.-Y. Chen, C.-S. Yng nd H.-P. Hou Km Avone s sheme onsss of hee phses pepon phse, pd b ehnge, nd he fnl phse. Tg nd ede ehnge he ndom numbes nd ompue he ommmens n he pepon phse. In he pd b ehnge phse, he vefe pobes he pove, usng ndvdul hllenge b, nd he pove should espond s nswe b n esonble me. Fnlly, he vefe, wh he pove s esponses, sehes he oespondng g n s dbse (D) nd vefes he vldy of he g. The sheme deped n Fgue 2 s desbed s follows Pepon phse The ede sends ndom numbe N A o he g, nd he g hooses ndom numbe N nd ompues = f (C, N ), 0 =, nd = Rpd b ehnge The phse s epeed n mes, nd he hllenge esponse dely fo eh eeuon s mesued. Eh nsne of pd b ehnge s denoed by subsp. The ede ss by hoosng ndom b, ss me, nd sends o he g. The b eeved by he g s denoed s (he hnnel nose o ks mgh hnge he b ). Upon eevng, he g esponds wh =. Upon eevng he esponse, he ede sops he me nd eods he eeved b s ndhedelymesδ Fnl phse The g ompues = f (,..., n, ID, N A, N ) nd sends o he ede, whh pefoms n ehusve seh ove s dbse o fnd n eny (ID, ), ssfyng. Usng hs eny, he ede ompues 0 nd nd uses hem o vefy eh eeved esponse b. e denoes he numbe of esponse bs h nno mee he mmum dely bound. e denoes he numbe of esponse bs h e no oe, nd e denoes he numbe of hllenges bs dffeen fom hose hllenges eeved by he g. If he numbe of eos (e + e + e ) s less hn he pedefned heshold, hen he ede eps hs g; ohewse, ejes hs g. If ede uhenon s equed, hen he ede sends A o he g. Km nd Avone epoed h s seuy bound gns mf fud k s (/2) n nd h s seuy bound gns eos fud k s (/2) v, ssumng h 2n v bs of 0 nd e dslosed o he dvesy befoe he pd b ehnge Full-dslosue k of Pes-Lopez e l. Pes-Lopez nd ollegues ks [8] on Km Avone s sheme e bsed on he obsevon h low-os g usully ffods modee-lengh ndom numbe (e.g., 32 bs) bu no long-lengh ndom numbes (e.g., 64 o 80 bs). Unde suh umsnes, Pes-Lopez e l. showed one effeve k s follows. () The ke denfes eh uhenon sesson by denfyng he ndom numbe N befoe he pd b ehnge. He o she eods {, } =~n of eh sesson. Rede Tg Pepon Pk ndom N A Rpd b ehnge : ~n Pk R {0,} s me sop me eod, Fnl phse hek Compue Compue e : # { : e : # { : e : # { : If e e e hen REJECT A ID v f ( N ) D 0, } m } N A N,..., n, } A Pk ndom 0 f ( C, N ), N n A, N f (,...,, ID, N vefy A ) Fgue 2. Swss-knfe dsne-boundng poool. 492 Seuy Comm. Newoks 203; 6: John Wley & Sons, Ld.

4 H.-Y. Chen, C.-S. Yng nd H.-P. Hou Non-lney nno help RFID ess ks (2) The ke evesdops eh new sesson { N, ; ¼en }nd heks whehe N of he new sesson equls n esng one n s eods. If so, hen he o she goes o he ne sep; ohewse, he o she epes hs sep fo new sessons. (3) Fo =on, he ke heks whehe 6¼.If so, he o she ompues ¼, whh s he h b of. The ke sops when ll he bs of hve been deved; ohewse, he o she jumps o Sep 2 o evesdop on moe sessons. Obvously, he suess of he foemenoned k depends on he pobbly of fndng epeed ndom numbe N. V smulons, Pes-Lopez e l. found h kes 330 nd , espevely, fo n =20ndn =30n n del hnnel (no noses), nd he numbe of equed sessons s sll ffodble f he b eo e s low nd he numbe of ehnge bs s modee [8]. Aully, he epeed numbe of sessons fo epeed ndom numbe ould be esmed by usng he bhdy pdo fomul (), whee d denoes he spe of possble dws nd p denoes he pobbly of lsenng wo sessons wh he sme ndom none. sffffffffffffffffffffffffffffffffffffffffffffffffffffffff N ff 2d log p () 3. THE HITOMI SCHEME AND ITS WEAKNESSES Afe nlyzng he seuy weknesses of pevous shemes, whh ll doped lne omposon of sees, Pes-Lopez e l. gued h non-lne omposon of sees nd nluson of moe ndom none ould enhne he seuy. Wh he obsevons, hey poposed new RFID dsne-boundng poool lled he Hom poool. I ws lmed h he sheme n effevely ess ll known ks. The Hom sheme s he fs sheme n hs egoy o eploe non-lne omposon of sees. Unfounely, we fnd h non-lney no only nno help he seuy bu even deeoes he seuy. Hee, we fs evew he sheme n Seon 3. nd hen show he seuy weknesses of non-lney n Seon The Hom poool To se he level of seuy, he Hom poool uses hee ndom numbes N T, N T2, nd N T3 on he g s sde nd hnges he ompuons of 0 nd by usng he followng non-lne elon: = f (N R, N T, W), b = f (N T2, N T3, W ), 0 = nd = b nsed of he onvenonl lne fom = f (N R, N T, W), 0 =, nd =. The Hom sheme onsss of hee phses. The poool s deped n Fgue 3, nd he seps e desbed s follows. Rede Tg Pepon Pk ndom N R Rpd b ehnge : ~n Pk R {0,} s me sop me eod, Fnl phse hek ID v D 0 Compue, Compue e : #{ : e : #{ : e : #{ : If e hen REJECT A f ( N, b) e R e } m } } N N R T, NT 2, NT 3 m, A Pk ndom N b 0 f ( N, N f ( N, R T 2 T, N T, N, W ), T 3 b T 2, W ), N T 3 m {... n... n } f( m, ID, NR, NT, NT 2, NT 3) vefy A Fgue 3. The Hom poool. Seuy Comm. Newoks 203; 6: John Wley & Sons, Ld. 493

5 Non-lney nno help RFID ess ks H.-Y. Chen, C.-S. Yng nd H.-P. Hou 3... Pepon phse The ede sends ndom numbe N R o he g. Then he g hooses hee ndom numbes (N T, N T, N T3 ) nd ompues = f (N R, N T, W), b = f (N T2, N T3, W ), 0 =, nd = b. The g sends bk (N T, N T, N T3 ) Rpd b ehnge Ths phse s he sme s h of Km Avone s sheme Fnl phse The g les m ¼ j...jj n jj jj...jj n g, ompues = f (m, ID, N R, N T, N T2, N T3 ), nd sends hem bk o he ede, whh pefoms n ehusve seh ove s dbse o fnd n eny (ID, ), ssfyng. The es of he vefon seps e he sme s hose of Km Avone s sheme. If ede uhenon s equed, hen he ede sends A o he g. The uhos gued h he nluson of moe ndom numbes wll enhne he level of seuy nd h he non-lne ngemen of 0 nd n effevely dee eos fud ks. Howeve, we le show h he Hom poool s sll vulneble o eos fud k nd full-dslosue k n Seon Aks on he Hom poool The full-dslosue k Hee, we desbe he seps of ou full-dslosue k, whh n effevely deve he see key of one g s follows. () The ke mpesones he ede nd nes eh uhenon nsne by sendng he sme N R o he g. Wh he esponse N T fom he g, he ke denfes eh uhenon nsne nd eods ll he ommunons of he uhenon nsne. Fo eh new N T eeved, sends ll s beng zeo o le he g lwys espond wh ¼ 0 ¼. He o she eods he ommunons {(N T, N T2, N T3 ){, } =~n }. If epeed N NT s eeved, hen he ke sends ; n ¼ ole he g espond wh ¼ ¼ b, eods he n ommunons N T ; NT2 ; o N T3 ; ¼en fo hs epeed N NT nsne, nd hen goes o sep 2; ohewse, he o she epes hs sep o ne new uhenon nsne. (2) Upon geng wo uhenon nsnes wh he sme N T one s {(N T, N T2, N T3 ) { n =0, } =~n } nd he ohe s? N T ; NT2 ; o N T3 ¼ ; he ke ¼en les = 2... n, ompues b¼f NT2 ;N T3 ;W, nd hen deves :¼ b j 2 jj...jjn Þ. The equon b j 2 jj...jjn Þ euns beuse ¼ ¼b. The dffeenes beween ou full-dslosue k nd Pes-Lopez nd ollegues ks nlude he followng: () The ke n Pes-Lopez nd ollegues k only evesdops on ommunons, bu ou ke mpesones he ede by sendng he sme N R ll he mes, nd les = 0 fo he sessons wh new N T nd les ¼ fo sesson wh epeed N T. Ou ks e ve, bu Pes-Lopez nd ollegues k seems o be pssve he fs glne. Howeve, we should noe h he ke n boh ks need o evesdop on mny sessons fom he sme g, nd, unde suh umsnes, he ke mus onol o even pues he g. Thus, he kes n boh ks e ully ve bu no pssve n pl sense. () The equed numbe of evesdopped sessons o deve he whole see key n ou k s muh less hn h n he sheme of Pes-Lopez e l. Ou k n olly deve he whole see key fo he fs ouene of epeed N T beuse we onol = 0 fo new N T nd ¼ fo epeed N T. u, he ke n Pes-Lopez nd ollegues k n only eove some bs of fo eh epeed N T. Theefoe, he numbe of evesdopped sessons n Pes- Lopez nd ollegues k s muh lge hn ou k Teos fud k In ode o se he seuy level gns full-dslosue k, he Hom poool poposes he non-lne ngemen of he fom = f (N R, N T, W), b = f (N T2, N T3, W ), 0 =, nd = b nsed of he onvenonl lne fom = f (N R, N T, W), 0 =, nd =. Howeve,wefnd h nus new wekness o eos fud k. A eos fud k onsdes he suon h pove (g) o-opees wh n ke (Adv) unde he onsn h he g would no dslose s long-em see key o Adv. Howeve, we n plo n effeve eos fud k on he Hom s follows. Assume n = 32 bs. Le g T dsloses ll he bs (n bs) of = b nd he fs hlf bs (sy ~ n/2 bs) of 0 = o Adv fe he pepon phse. In suh n ngemen, he long-em see key s no dslosed o Adv. Now, Adv dops hs segy s follows. Adv lwys nswes oely fo hllenges, n/2 beuse he o she hs ; n nd 0 ; n=2. Fo he es of hllenges, n/2 + n n he pd b ehnge, he o she jus ndomly hooses = 0 o. Thee e vegely n/4 hllenges wh = fo he es hllenges, n/2 + n. Fo hese n/4 = bs 2 [n/2 +, n], Adv knows he oe nswes =. So, Adv vegely only needs o guess = o 0 fo he es n/4 hllenges wh =0. On he vege, Adv guesses oely n/8 bs nd fls n/8 bs fo hese n/4 hllenges wh = 0. When n = 32, mples h he ke only guesses wongly fo 4 hllenge bs. So, f he heshold vlue of he numbe of eos (e + e + e ),, s 4, hen Adv n suessfully he he vefe. The hoe of should depend on he numbe of ehnge bs, n, nd he b eo e. In nose hnnel wh n = 32 bs, he heshold vlue s usully lge hn 4 [8]. Theefoe, ou eos fud k n suessfully defe he Hom poool. 494 Seuy Comm. Newoks 203; 6: John Wley & Sons, Ld.

6 H.-Y. Chen, C.-S. Yng nd H.-P. Hou Non-lney nno help RFID ess ks 4. CONCLUSIONS In hs ppe, we hve nodued he Hom poool nd hve nlyzed o show h he poposed onle of non-lne omposon of sees nd nluson of moe hllenge nno enhne he seuy of RFID dsneboundng poool gns he possble ks. On ony, we gue h he ppoh of lne omposon of sees would be bee. The eson fo hs s h, unde non-lne omposon of sees, he dshones g n dslose moe see bs of he esponses o he dvesy fo eos ks, whou dmgng he pvy of s long-em see key. REFERENCES. Chen HY, Hung CW. Seuy of ul-lghwegh RFID uhenon poools nd s mpovemens. ACM Openg Sysem Revews 2007; 4(4): Chen HY. SASI: new ul-lghwegh RFID uhenon poool povdng song uhenon nd song negy. IEEE Tnsons on Dependble nd Seue Compung 2007; 4(4): Lee NY, Chun-Chng Pn. Odnl uhenon poools fo RFID gs. Po. of 2008 Inenonl Confeene on usness nd Infomon (AI2008). Ademy of Twn Infomon Sysems Reseh: Seoul, Koe, 2008; Pmuhu S. Poools fo RFID g/ede uhenon. Deson Suppo Sysems 2007; 43(3): Hwng MS, Lee CC, Chong SK, Lo JW. A key mngemen fo weless ommunons. Inenonl Jounl of Innovve Compung, Infomon nd Conol 2008; 4(8): Lo NW, Yeh KH, Yeun CY. New muul geemen poool o seue moble RFID-enbled deves. Infomon Seuy Tehnl Repo, pp. 5 57, Lee JS, Chng YF, Chng CC. Seue uhenon poools fo moble ommee nsons. Inenonl Jounl of Innovve Compung, Infomon nd Conol (IJICIC) 2008; 4(9): ussd L. Tus esblshmen poools fo ommunng deves. PhD hess, Insu Euéom, Téléom, Ps, nds S, Chum D. Dsne-boundng poools. In Advnes n Cypology EUROCRYPT 93, LNCS 765. Spnge-Velg: Lofhus, Nowy, 993; Desmed Y. Mjo seuy poblems wh he unfogeble (Fege)-F Shm poofs of deny nd how o oveome hem. Po. of SeuCom 88. SEDEP Ps: Fne, 988; Hnke G, Kuhn M. An RFID dsne boundng poool. Po. of he IEEE SeueComm 2005, Sepembe Medows R, Poovendn D, Pvlov L, Chng W, Syveson P. Dsne boundng poools: uhenon log nlyss nd olluson ks. Po. Of Seue Lolzon nd Tme Synhonzon fo Weless Senso nd Ad Ho Newoks. Spnge- Velg: 2007; Munll J, Pendo A. Dsne boundng poools fo RFID enhned by usng vod-hllenges nd nlyss n nosy hnnel. Weless Communons nd Moble Compung DOI: 0.002/wm Red J, Gonzlez JM, Tng T, Sendj. Deeng ely ks wh mng-bsed poools. Po. of he 2nd ACM symposum on Infomon ompue nd ommunons seuy ASIACCS 07 (2007). 5. Tu YJ, Pmuhu S. RFID dsne boundng poools. RFID Tehnology, Sepembe S. Čpkun, uyán L, Hubu J.-P. SECTOR: seue kng of node enounes n mul-hop weless newoks. Po. of ACM Wokshop on Seuy of Ad Ho nd Senso Newoks, pp. 2 3, Km CH, Avone G. RFID dsne boundng poool wh med hllenges o peven ely ks. Po. of 8h Inenonl Confeene on Cypology nd Newok Seuy CANS 09. Spnge: Ishkw, Jpn, Pes-Lopez P, Henndez-Cso JC, Dmkks C, Mokos A, Esevez-Tpdo JM. Sheddng lgh on RFID dsne boundng poools nd eos fud ks. CSF 0, June 200. hp://v.og/ bs/ , Conell Unvesy lby. Seuy Comm. Newoks 203; 6: John Wley & Sons, Ld. 495

_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9

_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9 C C A 55NED n R 5 0 9 b c c \ { s AS EC 2 5? 9 Con 0 \ 0265 o + s ^! 4 y!! {! w Y n < R > s s = ~ C c [ + * c n j R c C / e A / = + j ) d /! Y 6 ] s v * ^ / ) v } > { ± n S = S w c s y c C { ~! > R = n

More information

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005.

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005. Techc Appedx fo Iveoy geme fo Assemy Sysem wh Poduc o Compoe eus ecox d Zp geme Scece 2005 Lemm µ µ s c Poof If J d µ > µ he ˆ 0 µ µ µ µ µ µ µ µ Sm gumes essh he esu f µ ˆ > µ > µ > µ o K ˆ If J he so

More information

Circuits 24/08/2010. Question. Question. Practice Questions QV CV. Review Formula s RC R R R V IR ... Charging P IV I R ... E Pt.

Circuits 24/08/2010. Question. Question. Practice Questions QV CV. Review Formula s RC R R R V IR ... Charging P IV I R ... E Pt. 4/08/00 eview Fomul s icuis cice s BL B A B I I I I E...... s n n hging Q Q 0 e... n... Q Q n 0 e Q I I0e Dischging Q U Q A wie mde of bss nd nohe wie mde of silve hve he sme lengh, bu he dimee of he bss

More information

Empirical equations for electrical parameters of asymmetrical coupled microstrip lines

Empirical equations for electrical parameters of asymmetrical coupled microstrip lines Epl equons fo elel petes of syel ouple osp lnes I.M. Bsee Eletons eseh Instute El-h steet, Dokk, o, Egypt Abstt: Epl equons e eve fo the self n utul nutne n ptne fo two syel ouple osp lnes. he obne ptne

More information

4.1 Schrödinger Equation in Spherical Coordinates

4.1 Schrödinger Equation in Spherical Coordinates Phs 34 Quu Mehs D 9 9 Mo./ Wed./ Thus /3 F./4 Mo., /7 Tues. / Wed., /9 F., /3 4.. -. Shodge Sphe: Sepo & gu (Q9.) 4..-.3 Shodge Sphe: gu & d(q9.) Copuo: Sphe Shodge s 4. Hdoge o (Q9.) 4.3 gu Moeu 4.4.-.

More information

X-Ray Notes, Part III

X-Ray Notes, Part III oll 6 X-y oe 3: Pe X-Ry oe, P III oe Deeo Coe oupu o x-y ye h look lke h: We efe ue of que lhly ffee efo h ue y ovk: Co: C ΔS S Sl o oe Ro: SR S Co o oe Ro: CR ΔS C SR Pevouly, we ee he SR fo ye hv pxel

More information

Rotations.

Rotations. oons j.lbb@phscs.o.c.uk To s summ Fmes of efeence Invnce une nsfomons oon of wve funcon: -funcons Eule s ngles Emple: e e - - Angul momenum s oon geneo Genec nslons n Noehe s heoem Fmes of efeence Conse

More information

STRAIGHT LINES IN LINEAR ARRAY SCANNER IMAGERY

STRAIGHT LINES IN LINEAR ARRAY SCANNER IMAGERY Devn Kelle STRIGHT LINES IN LINER RR SCNNER IMGER mn Hbb, Devn Kelle, ndne smmw Depmen of Cvl nd Envonmenl Engneeng nd Geode Sene The ho Se Unves hbb.1@osu.edu, kelle.83@osu.edu, smmw.1@osu.edu ISPRS Commsson

More information

f(x) dx with An integral having either an infinite limit of integration or an unbounded integrand is called improper. Here are two examples dx x x 2

f(x) dx with An integral having either an infinite limit of integration or an unbounded integrand is called improper. Here are two examples dx x x 2 Impope Inegls To his poin we hve only consideed inegls f() wih he is of inegion nd b finie nd he inegnd f() bounded (nd in fc coninuous ecep possibly fo finiely mny jump disconinuiies) An inegl hving eihe

More information

Primary Level and Secondary Level Coordinated Control of Power Systems

Primary Level and Secondary Level Coordinated Control of Power Systems Poeedngs of he 2006 IASM/WSAS Inenonl Confeene on neg & nvonmenl Ssems, Chlkd, Geee, M 80, 2006 (pp249253) Pm Level nd Seond Level Coodned Conol of Powe Ssems.A. ANDROULIDAIS, A.T. ALXANDRIDIS Depmen of

More information

P a g e 5 1 of R e p o r t P B 4 / 0 9

P a g e 5 1 of R e p o r t P B 4 / 0 9 P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e

More information

Reinforcement learning

Reinforcement learning CS 75 Mchine Lening Lecue b einfocemen lening Milos Huskech milos@cs.pi.edu 539 Senno Sque einfocemen lening We wn o len conol policy: : X A We see emples of bu oupus e no given Insed of we ge feedbck

More information

5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( )

5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( ) 5-1. We apply Newon s second law (specfcally, Eq. 5-). (a) We fnd he componen of he foce s ( ) ( ) F = ma = ma cos 0.0 = 1.00kg.00m/s cos 0.0 = 1.88N. (b) The y componen of he foce s ( ) ( ) F = ma = ma

More information

A L A BA M A L A W R E V IE W

A L A BA M A L A W R E V IE W A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N

More information

HERMITE SERIES SOLUTIONS OF LINEAR FREDHOLM INTEGRAL EQUATIONS

HERMITE SERIES SOLUTIONS OF LINEAR FREDHOLM INTEGRAL EQUATIONS Mhemcl nd Compuonl Applcons, Vol 6, o, pp 97-56, Assocon fo Scenfc Resech ERMITE SERIES SOLUTIOS OF LIEAR FREDOLM ITEGRAL EQUATIOS Slh Ylçınbş nd Müge Angül Depmen of Mhemcs, Fcul of Scence nd As, Cell

More information

EE 410/510: Electromechanical Systems Chapter 3

EE 410/510: Electromechanical Systems Chapter 3 EE 4/5: Eleomehnl Syem hpe 3 hpe 3. Inoon o Powe Eleon Moelng n Applon of Op. Amp. Powe Amplfe Powe onvee Powe Amp n Anlog onolle Swhng onvee Boo onvee onvee Flyb n Fow onvee eonn n Swhng onvee 5// All

More information

T h e C S E T I P r o j e c t

T h e C S E T I P r o j e c t T h e P r o j e c t T H E P R O J E C T T A B L E O F C O N T E N T S A r t i c l e P a g e C o m p r e h e n s i v e A s s es s m e n t o f t h e U F O / E T I P h e n o m e n o n M a y 1 9 9 1 1 E T

More information

African Journal of Science and Technology (AJST) Science and Engineering Series Vol. 4, No. 2, pp GENERALISED DELETION DESIGNS

African Journal of Science and Technology (AJST) Science and Engineering Series Vol. 4, No. 2, pp GENERALISED DELETION DESIGNS Af Joul of See Tehology (AJST) See Egeeg See Vol. 4, No.,. 7-79 GENERALISED DELETION DESIGNS Mhel Ku Gh Joh Wylff Ohbo Dee of Mhe, Uvey of Nob, P. O. Bo 3097, Nob, Key ABSTRACT:- I h e yel gle ele fol

More information

On Fractional Operational Calculus pertaining to the product of H- functions

On Fractional Operational Calculus pertaining to the product of H- functions nenonl eh ounl of Enneen n ehnolo RE e-ssn: 2395-56 Volume: 2 ue: 3 une-25 wwwene -SSN: 2395-72 On Fonl Oeonl Clulu enn o he ou of - funon D VBL Chu, C A 2 Demen of hem, Unve of Rhn, u-3255, n E-ml : vl@hooom

More information

Go over vector and vector algebra Displacement and position in 2-D Average and instantaneous velocity in 2-D Average and instantaneous acceleration

Go over vector and vector algebra Displacement and position in 2-D Average and instantaneous velocity in 2-D Average and instantaneous acceleration Mh Csquee Go oe eco nd eco lgeb Dsplcemen nd poson n -D Aege nd nsnneous eloc n -D Aege nd nsnneous cceleon n -D Poecle moon Unfom ccle moon Rele eloc* The componens e he legs of he gh ngle whose hpoenuse

More information

THIS PAGE DECLASSIFIED IAW EO 12958

THIS PAGE DECLASSIFIED IAW EO 12958 THIS PAGE DECLASSIFIED IAW EO 2958 THIS PAGE DECLASSIFIED IAW EO 2958 THIS PAGE DECLASSIFIED IAW E0 2958 S T T T I R F R S T Exhb e 3 9 ( 66 h Bm dn ) c f o 6 8 b o d o L) B C = 6 h oup C L) TO d 8 f f

More information

An Optimization Model for Empty Container Reposition under Uncertainty

An Optimization Model for Empty Container Reposition under Uncertainty n Omzon Mode o Emy onne Reoson nde neny eodo be n Demen o Mnemen nd enooy QM nd ene de Reee s es nsos Moné nd Mssmo D Fneso Demen o Lnd Enneen nesy o Iy o Zdds Demen o Lnd Enneen nesy o Iy Inodon. onne

More information

Appendix. In the absence of default risk, the benefit of the tax shield due to debt financing by the firm is 1 C E C

Appendix. In the absence of default risk, the benefit of the tax shield due to debt financing by the firm is 1 C E C nx. Dvon o h n wh In h sn o ul sk h n o h x shl u o nnng y h m s s h ol ouon s h num o ssus s h oo nom x s h sonl nom x n s h v x on quy whh s wgh vg o vn n l gns x s. In hs s h o sonl nom xs on h x shl

More information

Name of the Student:

Name of the Student: Engneeng Mahemacs 05 SUBJEC NAME : Pobably & Random Pocess SUBJEC CODE : MA645 MAERIAL NAME : Fomula Maeal MAERIAL CODE : JM08AM007 REGULAION : R03 UPDAED ON : Febuay 05 (Scan he above QR code fo he dec

More information

ME 141. Engineering Mechanics

ME 141. Engineering Mechanics ME 141 Engineeing Mechnics Lecue 13: Kinemics of igid bodies hmd Shhedi Shkil Lecue, ep. of Mechnicl Engg, UET E-mil: sshkil@me.bue.c.bd, shkil6791@gmil.com Websie: eche.bue.c.bd/sshkil Couesy: Veco Mechnics

More information

Caputo Equations in the frame of fractional operators with Mittag-Leffler kernels

Caputo Equations in the frame of fractional operators with Mittag-Leffler kernels nvenon Jounl o Reseh Tehnoloy n nneen & Mnemen JRTM SSN: 455-689 wwwjemom Volume ssue 0 ǁ Ooe 08 ǁ PP 9-45 Cuo uons n he me o onl oeos wh M-ele enels on Qn Chenmn Hou* Ynn Unvesy Jln Ynj 00 ASTRACT: n

More information

CHAPTER 10: LINEAR DISCRIMINATION

CHAPTER 10: LINEAR DISCRIMINATION HAPER : LINEAR DISRIMINAION Dscmnan-based lassfcaon 3 In classfcaon h K classes ( k ) We defned dsmnan funcon g () = K hen gven an es eample e chose (pedced) s class label as f g () as he mamum among g

More information

A Study of Some Integral Problems Using Maple

A Study of Some Integral Problems Using Maple Mthemtis n Sttistis (): -, 0 DOI: 0.89/ms.0.000 http://www.hpub.og A Stuy of Some Integl Poblems Ug Mple Chii-Huei Yu Deptment of Mngement n Infomtion, Nn Jeon Univesity of Siene n Tehnology, Tinn City,

More information

A Scalable Distributed QoS Multicast Routing Protocol

A Scalable Distributed QoS Multicast Routing Protocol A Slle Dsued QoS Muls Roung Poool Shgng Chen Depmen of Compue & Infomon Sene & Engneeng Unvesy of Flod, Gnesvlle, Flod 32611, USA Eml: {sghen}@se.ufl.edu Yuvl Shv Depmen of Elel Engneeng - Sysems Tel-Avv

More information

drawing issue sheet Former Royal High School - Hotel Development

drawing issue sheet Former Royal High School - Hotel Development H Forer oyal High chool - Hotel Developent drawing isse sheet general arrangeents drawing nber drawing title scale size L()1 ite Plan 1:1 / L()1 egent oad level proposed floor plan 1: 1 / L() ntrance level

More information

PHY2053 Summer C 2013 Exam 1 Solutions

PHY2053 Summer C 2013 Exam 1 Solutions PHY053 Sue C 03 E Soluon. The foce G on o G G The onl cobnon h e '/ = doubln.. The peed of lh le 8fulon c 86,8 le 60 n 60n h 4h d 4d fonh.80 fulon/ fonh 3. The dnce eled fo he ene p,, 36 (75n h 45 The

More information

MATHEMATICS II PUC VECTOR ALGEBRA QUESTIONS & ANSWER

MATHEMATICS II PUC VECTOR ALGEBRA QUESTIONS & ANSWER MATHEMATICS II PUC VECTOR ALGEBRA QUESTIONS & ANSWER I One M Queston Fnd the unt veto n the deton of Let ˆ ˆ 9 Let & If Ae the vetos & equl? But vetos e not equl sne the oespondng omponents e dstnt e detons

More information

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2 Joh Rley Novembe ANSWERS O ODD NUMBERED EXERCISES IN CHAPER Seo Eese -: asvy (a) Se y ad y z follows fom asvy ha z Ehe z o z We suppose he lae ad seek a oado he z Se y follows by asvy ha z y Bu hs oads

More information

Chapter 6 Plane Motion of Rigid Bodies

Chapter 6 Plane Motion of Rigid Bodies Chpe 6 Pne oon of Rd ode 6. Equon of oon fo Rd bod. 6., 6., 6.3 Conde d bod ced upon b ee een foce,, 3,. We cn ume h he bod mde of e numbe n of pce of m Δm (,,, n). Conden f he moon of he m cene of he

More information

Calculus 241, section 12.2 Limits/Continuity & 12.3 Derivatives/Integrals notes by Tim Pilachowski r r r =, with a domain of real ( )

Calculus 241, section 12.2 Limits/Continuity & 12.3 Derivatives/Integrals notes by Tim Pilachowski r r r =, with a domain of real ( ) Clculu 4, econ Lm/Connuy & Devve/Inel noe y Tm Plchow, wh domn o el Wh we hve o : veco-vlued uncon, ( ) ( ) ( ) j ( ) nume nd ne o veco The uncon, nd A w done wh eul uncon ( x) nd connuy e he componen

More information

Prerna Tower, Road No 2, Contractors Area, Bistupur, Jamshedpur , Tel (0657) ,

Prerna Tower, Road No 2, Contractors Area, Bistupur, Jamshedpur , Tel (0657) , R Pen Towe Rod No Conttos Ae Bistupu Jmshedpu 8 Tel (67)89 www.penlsses.om IIT JEE themtis Ppe II PART III ATHEATICS SECTION I (Totl ks : ) (Single Coet Answe Type) This setion ontins 8 multiple hoie questions.

More information

Maximum likelihood estimate of phylogeny. BIOL 495S/ CS 490B/ MATH 490B/ STAT 490B Introduction to Bioinformatics April 24, 2002

Maximum likelihood estimate of phylogeny. BIOL 495S/ CS 490B/ MATH 490B/ STAT 490B Introduction to Bioinformatics April 24, 2002 Mmm lkelhood eme of phylogey BIO 9S/ S 90B/ MH 90B/ S 90B Iodco o Bofomc pl 00 Ovevew of he pobblc ppoch o phylogey o k ee ccodg o he lkelhood d ee whee d e e of eqece d ee by ee wh leve fo he eqece. he

More information

Computer Aided Geometric Design

Computer Aided Geometric Design Copue Aided Geoei Design Geshon Ele, Tehnion sed on ook Cohen, Riesenfeld, & Ele Geshon Ele, Tehnion Definiion 3. The Cile Given poin C in plne nd nue R 0, he ile ih ene C nd dius R is defined s he se

More information

Backcalculation Analysis of Pavement-layer Moduli Using Pattern Search Algorithms

Backcalculation Analysis of Pavement-layer Moduli Using Pattern Search Algorithms Bakallaon Analyss of Pavemen-laye Modl Usng Paen Seah Algohms Poje Repo fo ENCE 74 Feqan Lo May 7 005 Bakallaon Analyss of Pavemen-laye Modl Usng Paen Seah Algohms. Inodon. Ovevew of he Poje 3. Objeve

More information

Chapter Linear Regression

Chapter Linear Regression Chpte 6.3 Le Regesso Afte edg ths chpte, ou should be ble to. defe egesso,. use sevel mmzg of esdul cte to choose the ght cteo, 3. deve the costts of le egesso model bsed o lest sques method cteo,. use

More information

Data Structures. Element Uniqueness Problem. Hash Tables. Example. Hash Tables. Dana Shapira. 19 x 1. ) h(x 4. ) h(x 2. ) h(x 3. h(x 1. x 4. x 2.

Data Structures. Element Uniqueness Problem. Hash Tables. Example. Hash Tables. Dana Shapira. 19 x 1. ) h(x 4. ) h(x 2. ) h(x 3. h(x 1. x 4. x 2. Element Uniqueness Poblem Dt Stuctues Let x,..., xn < m Detemine whethe thee exist i j such tht x i =x j Sot Algoithm Bucket Sot Dn Shpi Hsh Tbles fo (i=;i

More information

CptS 570 Machine Learning School of EECS Washington State University. CptS Machine Learning 1

CptS 570 Machine Learning School of EECS Washington State University. CptS Machine Learning 1 ps 57 Machne Leann School of EES Washnon Sae Unves ps 57 - Machne Leann Assume nsances of classes ae lneal sepaable Esmae paamees of lnea dscmnan If ( - -) > hen + Else - ps 57 - Machne Leann lassfcaon

More information

176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s

176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s A g la di ou s F. L. 462 E l ec tr on ic D ev el op me nt A i ng er A.W.S. 371 C. A. M. A l ex an de r 236 A d mi ni st ra ti on R. H. (M rs ) A n dr ew s P. V. 326 O p ti ca l Tr an sm is si on A p ps

More information

Parameter Estimation and Hypothesis Testing of Two Negative Binomial Distribution Population with Missing Data

Parameter Estimation and Hypothesis Testing of Two Negative Binomial Distribution Population with Missing Data Avlble ole wwwsceceeccom Physcs Poce 0 475 480 0 Ieol Cofeece o Mecl Physcs Bomecl ee Pmee smo Hyohess es of wo Neve Boml Dsbuo Poulo wh Mss D Zhwe Zho Collee of MhemcsJl Noml UvesyS Ch zhozhwe@6com Absc

More information

6.6 The Marquardt Algorithm

6.6 The Marquardt Algorithm 6.6 The Mqudt Algothm lmttons of the gdent nd Tylo expnson methods ecstng the Tylo expnson n tems of ch-sque devtves ecstng the gdent sech nto n tetve mtx fomlsm Mqudt's lgothm utomtclly combnes the gdent

More information

Week 8. Topic 2 Properties of Logarithms

Week 8. Topic 2 Properties of Logarithms Week 8 Topic 2 Popeties of Logithms 1 Week 8 Topic 2 Popeties of Logithms Intoduction Since the esult of ithm is n eponent, we hve mny popeties of ithms tht e elted to the popeties of eponents. They e

More information

e t dt e t dt = lim e t dt T (1 e T ) = 1

e t dt e t dt = lim e t dt T (1 e T ) = 1 Improper Inegrls There re wo ypes of improper inegrls - hose wih infinie limis of inegrion, nd hose wih inegrnds h pproch some poin wihin he limis of inegrion. Firs we will consider inegrls wih infinie

More information

Lecture 5 Single factor design and analysis

Lecture 5 Single factor design and analysis Lectue 5 Sngle fcto desgn nd nlss Completel ndomzed desgn (CRD Completel ndomzed desgn In the desgn of expements, completel ndomzed desgns e fo studng the effects of one pm fcto wthout the need to tke

More information

Invert and multiply. Fractions express a ratio of two quantities. For example, the fraction

Invert and multiply. Fractions express a ratio of two quantities. For example, the fraction Appendi E: Mnipuling Fions Te ules fo mnipuling fions involve lgei epessions e el e sme s e ules fo mnipuling fions involve numes Te fundmenl ules fo omining nd mnipuling fions e lised elow Te uses of

More information

RAKE Receiver with Adaptive Interference Cancellers for a DS-CDMA System in Multipath Fading Channels

RAKE Receiver with Adaptive Interference Cancellers for a DS-CDMA System in Multipath Fading Channels AKE v wh Apv f Cs fo DS-CDMA Ss Muph Fg Chs JooHu Y Su M EEE JHog M EEE Shoo of E Egg Sou o Uvs Sh-og Gw-gu Sou 5-74 Ko E-: ohu@su As hs pp pv AKE v wh vs og s popos fo DS-CDMA ss uph fg hs h popos pv

More information

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9 OH BOY! O h Boy!, was or igin a lly cr eat ed in F r en ch an d was a m a jor s u cc ess on t h e Fr en ch st a ge f or young au di enc es. It h a s b een s een by ap pr ox i ma t ely 175,000 sp ect at

More information

the king's singers And So It Goes the colour of song Words and Vusic by By Joel LEONARD Arranged by Bob Chilcott

the king's singers And So It Goes the colour of song Words and Vusic by By Joel LEONARD Arranged by Bob Chilcott 085850 SATB div cppell US $25 So Goes Wods nd Vusic by By Joel Anged by Bob Chilco he king's singes L he colou of song A H EXCLUSVELY DSTRBUTED BY LEONARD (Fom The King's Singes 25h Annivesy Jubilee) So

More information

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1 Lecue su Fes of efeece Ivce ude sfoos oo of H wve fuco: d-fucos Eple: e e - µ µ - Agul oeu s oo geeo Eule gles Geec slos cosevo lws d Noehe s heoe C4 Lecue - Lbb Fes of efeece Cosde fe of efeece O whch

More information

Direct Current Circuits

Direct Current Circuits Eler urren (hrges n Moon) Eler urren () The ne moun of hrge h psses hrough onduor per un me ny pon. urren s defned s: Dre urren rus = dq d Eler urren s mesured n oulom s per seond or mperes. ( = /s) n

More information

1 Constant Real Rate C 1

1 Constant Real Rate C 1 Consan Real Rae. Real Rae of Inees Suppose you ae equally happy wh uns of he consumpon good oday o 5 uns of he consumpon good n peod s me. C 5 Tha means you ll be pepaed o gve up uns oday n eun fo 5 uns

More information

P a g e 3 6 of R e p o r t P B 4 / 0 9

P a g e 3 6 of R e p o r t P B 4 / 0 9 P a g e 3 6 of R e p o r t P B 4 / 0 9 p r o t e c t h um a n h e a l t h a n d p r o p e r t y fr om t h e d a n g e rs i n h e r e n t i n m i n i n g o p e r a t i o n s s u c h a s a q u a r r y. J

More information

Integral Solutions of Non-Homogeneous Biquadratic Equation With Four Unknowns

Integral Solutions of Non-Homogeneous Biquadratic Equation With Four Unknowns Ieol Jol o Compol Eee Reech Vol Ie Iel Solo o No-Homoeeo qdc Eqo Wh Fo Uo M..Gopl G.Smh S.Vdhlhm. oeo o Mhemc SIGCTch. Lece o Mhemc SIGCTch. oeo o Mhemc SIGCTch c The o-homoeeo qdc eqo h o o epeeed he

More information

Available online Journal of Scientific and Engineering Research, 2017, 4(2): Research Article

Available online   Journal of Scientific and Engineering Research, 2017, 4(2): Research Article Avlble onlne www.jse.com Jonl of Scenfc nd Engneeng Resech, 7, 4():5- Resech Acle SSN: 394-63 CODEN(USA): JSERBR Exc Solons of Qselsc Poblems of Lne Theoy of Vscoelscy nd Nonlne Theoy Vscoelscy fo echnclly

More information

Mark Scheme (Results) January 2008

Mark Scheme (Results) January 2008 Mk Scheme (Results) Jnuy 00 GCE GCE Mthemtics (6679/0) Edecel Limited. Registeed in Englnd nd Wles No. 4496750 Registeed Office: One90 High Holbon, London WCV 7BH Jnuy 00 6679 Mechnics M Mk Scheme Question

More information

Supporting information How to concatenate the local attractors of subnetworks in the HPFP

Supporting information How to concatenate the local attractors of subnetworks in the HPFP n Effcen lgorh for Idenfyng Prry Phenoype rcors of Lrge-Scle Boolen Newor Sng-Mo Choo nd Kwng-Hyun Cho Depren of Mhecs Unversy of Ulsn Ulsn 446 Republc of Kore Depren of Bo nd Brn Engneerng Kore dvnced

More information

STD: XI MATHEMATICS Total Marks: 90. I Choose the correct answer: ( 20 x 1 = 20 ) a) x = 1 b) x =2 c) x = 3 d) x = 0

STD: XI MATHEMATICS Total Marks: 90. I Choose the correct answer: ( 20 x 1 = 20 ) a) x = 1 b) x =2 c) x = 3 d) x = 0 STD: XI MATHEMATICS Totl Mks: 90 Time: ½ Hs I Choose the coect nswe: ( 0 = 0 ). The solution of is ) = b) = c) = d) = 0. Given tht the vlue of thid ode deteminnt is then the vlue of the deteminnt fomed

More information

Released Assessment Questions, 2017 QUESTIONS

Released Assessment Questions, 2017 QUESTIONS Relese Assessmen Quesions, 17 QUESTIONS Gre 9 Assessmen of Mhemis Aemi Re he insruions elow. Along wih his ookle, mke sure ou hve he Answer Bookle n he Formul Shee. You m use n spe in his ook for rough

More information

THIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings.

THIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings. T H S PA G E D E CLA SSFED AW E O 2958 RS u blc Recod Key fo maon Ma n AR MATEREL COMM ND D cumen Type Call N u b e 03 V 7 Rcvd Rel 98 / 0 ndexe D 38 Eneed Dae RS l umbe 0 0 4 2 3 5 6 C D QC d Dac A cesson

More information

Uniform Circular Motion

Uniform Circular Motion Unfom Ccul Moton Unfom ccul Moton An object mong t constnt sped n ccle The ntude of the eloct emns constnt The decton of the eloct chnges contnuousl!!!! Snce cceleton s te of chnge of eloct:!! Δ Δt The

More information

Mathematical Reflections, Issue 5, INEQUALITIES ON RATIOS OF RADII OF TANGENT CIRCLES. Y.N. Aliyev

Mathematical Reflections, Issue 5, INEQUALITIES ON RATIOS OF RADII OF TANGENT CIRCLES. Y.N. Aliyev themtil efletions, Issue 5, 015 INEQULITIES ON TIOS OF DII OF TNGENT ILES YN liev stt Some inequlities involving tios of dii of intenll tngent iles whih inteset the given line in fied points e studied

More information

Handout on. Crystal Symmetries and Energy Bands

Handout on. Crystal Symmetries and Energy Bands dou o Csl s d g Bds I hs lu ou wll l: Th loshp bw ss d g bds h bs of sp-ob ouplg Th loshp bw ss d g bds h ps of sp-ob ouplg C 7 pg 9 Fh Coll Uvs d g Bds gll hs oh Th sl pol ss ddo o h l slo s: Fo pl h

More information

Bag for Sophia by Leonie Bateman and Deirdre Bond-Abel

Bag for Sophia by Leonie Bateman and Deirdre Bond-Abel Bag for Sopha 2012 by Leone Baeman and Derdre Bond-Abel Ths bag was desgned o go wh he beauful feled wool scarf of our book Elegan Quls, Counry Charm. Make boh and you ll have he perfec ensemble o wear

More information

SYMMETRICAL COMPONENTS

SYMMETRICAL COMPONENTS SYMMETRCA COMPONENTS Syl oponn llow ph un of volg n un o pl y h p ln yl oponn Con h ph ln oponn wh Engy Convon o 4 o o wh o, 4 o, 6 o Engy Convon SYMMETRCA COMPONENTS Dfn h opo wh o Th o of pho : pov ph

More information

4.8 Improper Integrals

4.8 Improper Integrals 4.8 Improper Inegrls Well you ve mde i hrough ll he inegrion echniques. Congrs! Unforunely for us, we sill need o cover one more inegrl. They re clled Improper Inegrls. A his poin, we ve only del wih inegrls

More information

THIS PAGE DECLASSIFIED IAW E

THIS PAGE DECLASSIFIED IAW E THS PAGE DECLASSFED AW E0 2958 BL K THS PAGE DECLASSFED AW E0 2958 THS PAGE DECLASSFED AW E0 2958 B L K THS PAGE DECLASSFED AW E0 2958 THS PAGE DECLASSFED AW EO 2958 THS PAGE DECLASSFED AW EO 2958 THS

More information

Classification of Equations Characteristics

Classification of Equations Characteristics Clssiiion o Eqions Cheisis Consie n elemen o li moing in wo imensionl spe enoe s poin P elow. The ph o P is inie he line. The posiion ile is s so h n inemenl isne long is s. Le he goening eqions e epesene

More information

Illustrating the space-time coordinates of the events associated with the apparent and the actual position of a light source

Illustrating the space-time coordinates of the events associated with the apparent and the actual position of a light source Illustting the spe-time oointes of the events ssoite with the ppent n the tul position of light soue Benh Rothenstein ), Stefn Popesu ) n Geoge J. Spi 3) ) Politehni Univesity of Timiso, Physis Deptment,

More information

calculating electromagnetic

calculating electromagnetic Theoeal mehods fo alulang eleomagne felds fom lghnng dshage ajeev Thoapplll oyal Insue of Tehnology KTH Sweden ajeev.thoapplll@ee.kh.se Oulne Despon of he poblem Thee dffeen mehods fo feld alulaons - Dpole

More information

Physics 15 Second Hour Exam

Physics 15 Second Hour Exam hc 5 Second Hou e nwe e Mulle hoce / ole / ole /6 ole / ------------------------------- ol / I ee eone ole lee how ll wo n ode o ecee l ced. I ou oluon e llegle no ced wll e gen.. onde he collon o wo 7.

More information

The Area of a Triangle

The Area of a Triangle The e of Tingle tkhlid June 1, 015 1 Intodution In this tile we will e disussing the vious methods used fo detemining the e of tingle. Let [X] denote the e of X. Using se nd Height To stt off, the simplest

More information

Math 4318 : Real Analysis II Mid-Term Exam 1 14 February 2013

Math 4318 : Real Analysis II Mid-Term Exam 1 14 February 2013 Mth 4318 : Rel Anlysis II Mid-Tem Exm 1 14 Febuy 2013 Nme: Definitions: Tue/Flse: Poofs: 1. 2. 3. 4. 5. 6. Totl: Definitions nd Sttements of Theoems 1. (2 points) Fo function f(x) defined on (, b) nd fo

More information

Answers to test yourself questions

Answers to test yourself questions Answes to test youself questions opic Descibing fields Gm Gm Gm Gm he net field t is: g ( d / ) ( 4d / ) d d Gm Gm Gm Gm Gm Gm b he net potentil t is: V d / 4d / d 4d d d V e 4 7 9 49 J kg 7 7 Gm d b E

More information

Bayesian Estimation of the parameters of the Weibull-Weibull Length-Biased mixture distributions using time censored data

Bayesian Estimation of the parameters of the Weibull-Weibull Length-Biased mixture distributions using time censored data Bys Eso of h s of h Wull-Wull gh-bs xu suos usg so S. A. Sh N Bouss I.S.S. Co Uvsy I.N.P.S. Algs Uvsy shsh@yhoo.o ou005@yhoo.o As I hs h s of h Wull-Wull lgh s xu suos s usg h Gs slg hqu u y I sog sh.

More information

Previously. Extensions to backstepping controller designs. Tracking using backstepping Suppose we consider the general system

Previously. Extensions to backstepping controller designs. Tracking using backstepping Suppose we consider the general system 436-459 Advnced contol nd utomtion Extensions to bckstepping contolle designs Tcking Obseves (nonline dmping) Peviously Lst lectue we looked t designing nonline contolles using the bckstepping technique

More information

The Shape of the Pair Distribution Function.

The Shape of the Pair Distribution Function. The Shpe of the P Dstbuton Functon. Vlentn Levshov nd.f. Thope Deptment of Phscs & stonom nd Cente fo Fundmentl tels Resech chgn Stte Unvest Sgnfcnt pogess n hgh-esoluton dffcton epements on powde smples

More information

CHAPTER 5 SPEED CONTROLLER BY SYMMETRIC OPTIMUM APPROXIMATION METHOD

CHAPTER 5 SPEED CONTROLLER BY SYMMETRIC OPTIMUM APPROXIMATION METHOD 8 CAPER 5 SPEED CONROLLER BY SYMMERIC OPIMUM APPROXIMAION MEOD 5. INRODUCION In ode o ex he be pefone fo gven elel hne, he pope degn of he peed nd uen onolle pon. oweve ll dve e pee enve o oe degee. donl

More information

Modeling and Predicting Sequences: HMM and (may be) CRF. Amr Ahmed Feb 25

Modeling and Predicting Sequences: HMM and (may be) CRF. Amr Ahmed Feb 25 Modelg d redcg Sequeces: HMM d m be CRF Amr Ahmed 070 Feb 25 Bg cure redcg Sgle Lbel Ipu : A se of feures: - Bg of words docume - Oupu : Clss lbel - Topc of he docume - redcg Sequece of Lbels Noo Noe:

More information

Physics 120 Spring 2007 Exam #1 April 20, Name

Physics 120 Spring 2007 Exam #1 April 20, Name Phc 0 Spng 007 E # pl 0, 007 Ne P Mulple Choce / 0 Poble # / 0 Poble # / 0 Poble # / 0 ol / 00 In eepng wh he Unon College polc on cdec hone, ued h ou wll nehe ccep no pode unuhozed nce n he copleon o

More information

Boyce/DiPrima 9 th ed, Ch 7.6: Complex Eigenvalues

Boyce/DiPrima 9 th ed, Ch 7.6: Complex Eigenvalues BocDPm 9 h d Ch 7.6: Compl Egvlus Elm Dffl Equos d Boud Vlu Poblms 9 h do b Wllm E. Boc d Rchd C. DPm 9 b Joh Wl & Sos Ic. W cosd g homogous ssm of fs od l quos wh cos l coffcs d hus h ssm c b w s ' A

More information

Addition & Subtraction of Polynomials

Addition & Subtraction of Polynomials Addiion & Sucion of Polynomil Addiion of Polynomil: Adding wo o moe olynomil i imly me of dding like em. The following ocedue hould e ued o dd olynomil 1. Remove enhee if hee e enhee. Add imil em. Wie

More information

I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o

I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o u l d a l w a y s b e t a k e n, i n c l u d f o l

More information

CITY OF TIMMINS BY-LAW NO

CITY OF TIMMINS BY-LAW NO CITY OF TIMMINS BEING A BY-LAW o uhoze he Copoon of he Cy of Tmmns o mend By- lw No. 2014-7561wh Rvesde Emeld ( Tmmns) Popey Holdngs Inc. nd he benefcl owne Rvesde Emeld ( Tmmns) Lmed Pneshp s epesened

More information

ME306 Dynamics, Spring HW1 Solution Key. AB, where θ is the angle between the vectors A and B, the proof

ME306 Dynamics, Spring HW1 Solution Key. AB, where θ is the angle between the vectors A and B, the proof ME6 Dnms, Spng HW Slutn Ke - Pve, gemetll.e. usng wngs sethes n nltll.e. usng equtns n nequltes, tht V then V. Nte: qunttes n l tpee e vets n n egul tpee e sls. Slutn: Let, Then V V V We wnt t pve tht:

More information

Optimization. x = 22 corresponds to local maximum by second derivative test

Optimization. x = 22 corresponds to local maximum by second derivative test Optimiztion Lectue 17 discussed the exteme vlues of functions. This lectue will pply the lesson fom Lectue 17 to wod poblems. In this section, it is impotnt to emembe we e in Clculus I nd e deling one-vible

More information

N C GM L P, u u y Du J W P: u,, uy u y j S, P k v, L C k u, u GM L O v L v y, u k y v v QV v u, v- v ju, v, u v u S L v: S u E x y v O, L O C u y y, k

N C GM L P, u u y Du J W P: u,, uy u y j S, P k v, L C k u, u GM L O v L v y, u k y v v QV v u, v- v ju, v, u v u S L v: S u E x y v O, L O C u y y, k Qu V vu P O B x 1361, Bu QLD 4575 C k N 96 N EWSLEE NOV/ DECE MBE 2015 E N u uu L O C 21 Nv, 2 QV v Py Cu Lv Su, 23 2 5 N v, 4 2015 u G M v y y : y quu u C, u k y Bu k v, u u vy v y y C k! u,, uu G M u

More information

Chapter 5: Quantization of Radiation in Cavities and Free Space

Chapter 5: Quantization of Radiation in Cavities and Free Space Quu O f Ph Ol Fh R Cll vy Ch 5: Quz f R Cv F S 5 Cll ly 5 Cll Cvy ly Mxwll u f lg J 4 h lv l C fl vy W f h g f h vy Th vy u luly ll W l u h J Cvy F Mxwll u v h wv u Th v u lv h f h fu h vy I w wh h v l

More information

Computer Propagation Analysis Tools

Computer Propagation Analysis Tools Compue Popagaion Analysis Tools. Compue Popagaion Analysis Tools Inoducion By now you ae pobably geing he idea ha pedicing eceived signal sengh is a eally impoan as in he design of a wieless communicaion

More information

Parameter Reestimation of HMM and HSMM (Draft) I. Introduction

Parameter Reestimation of HMM and HSMM (Draft) I. Introduction mee eesmon of HMM nd HSMM (Df Yng Wng Eml: yngwng@nlp..c.cn Absc: hs echncl epo summzes he pmee eesmon fomule fo Hdden Mkov Model (HMM nd Hdden Sem-Mkov Model (HSMM ncludng hes defnons fowd nd bckwd vbles

More information

Class Summary. be functions and f( D) , we define the composition of f with g, denoted g f by

Class Summary. be functions and f( D) , we define the composition of f with g, denoted g f by Clss Summy.5 Eponentil Functions.6 Invese Functions nd Logithms A function f is ule tht ssigns to ech element D ectly one element, clled f( ), in. Fo emple : function not function Given functions f, g:

More information

Global alignment in linear space

Global alignment in linear space Globl linmen in liner spe 1 2 Globl linmen in liner spe Gol: Find n opiml linmen of A[1..n] nd B[1..m] in liner spe, i.e. O(n) Exisin lorihm: Globl linmen wih bkrkin O(nm) ime nd spe, bu he opiml os n

More information

Chapter I Vector Analysis

Chapter I Vector Analysis . Chpte I Vecto nlss . Vecto lgeb j It s well-nown tht n vecto cn be wtten s Vectos obe the followng lgebc ules: scl s ) ( j v v cos ) ( e Commuttv ) ( ssoctve C C ) ( ) ( v j ) ( ) ( ) ( ) ( (v) he lw

More information

s = rθ Chapter 10: Rotation 10.1: What is physics?

s = rθ Chapter 10: Rotation 10.1: What is physics? Chape : oaon Angula poson, velocy, acceleaon Consan angula acceleaon Angula and lnea quanes oaonal knec enegy oaonal nea Toque Newon s nd law o oaon Wok and oaonal knec enegy.: Wha s physcs? In pevous

More information

Primal and Weakly Primal Sub Semi Modules

Primal and Weakly Primal Sub Semi Modules Aein Inenionl Jounl of Conepoy eeh Vol 4 No ; Jnuy 204 Pil nd Wekly Pil ub ei odule lik Bineh ub l hei Depen Jodn Univeiy of iene nd Tehnology Ibid 220 Jodn Ab Le be ouive eiing wih ideniy nd n -ei odule

More information

Chapter 3: Vectors and Two-Dimensional Motion

Chapter 3: Vectors and Two-Dimensional Motion Chape 3: Vecos and Two-Dmensonal Moon Vecos: magnude and decon Negae o a eco: eese s decon Mulplng o ddng a eco b a scala Vecos n he same decon (eaed lke numbes) Geneal Veco Addon: Tangle mehod o addon

More information

A Review of Dynamic Models Used in Simulation of Gear Transmissions

A Review of Dynamic Models Used in Simulation of Gear Transmissions ANALELE UNIVERSITĂłII ETIMIE MURGU REŞIłA ANUL XXI NR. ISSN 5-797 Zol-Ios Ko Io-ol Mulu A Rvw o ls Us Sulo o G Tsssos Th vsgo o lv s lu gg g olg l us o sov sg u o pps g svl s oug o h ps. Th pupos o h ols

More information