Institute for Advanced Computer Sciences. Abstract. are described for building these three data structures that make use of these

Size: px
Start display at page:

Download "Institute for Advanced Computer Sciences. Abstract. are described for building these three data structures that make use of these"

Transcription

1 Dt-Prlll Prmtvs or Sptl Oprtons Erk G. Holy Computr Sn Dprtmnt Unvrsty o Mryln Coll Prk, Mryln 074 ol@s.um.u Hnn Smt Computr Sn Dprtmnt Cntr or Automton Rsr Insttut or Avn Computr Sns Unvrsty o Mryln Coll Prk, Mryln 074 js@s.um.u Astrt Dt-prlll prmtvs or prormn oprtons on t PM qutr, ukt PMR qutr, n R-tr sptl t struturs r prsnt usn t sn mol. Alortms r sr or uln ts tr t struturs tt mk us o ts prmtvs. T t-prlll lortms r ssum to mn mmory rsnt. T lortms wr mplmnt on mnmlly onur Tnkn Mns CM-5 wt 3 prossors ontnn GB o mn mmory. Ts work ws support n prt y t Ntonl Sn Founton unr Grnt IRI

2 Introuton Sptl t onssts o ponts, lns, rons, rtnls, surs, volums, n vn t o r mnson w nlus tm. Sptl t rss n ppltons n mny rs nlun omputr rps, omputr vson, m prossn, pttrn ronton, roots, omputtonl omtry, sol moln, omputr- rtorpy, nry pyss, nt-lmnt nlyss, orp normton systms (GIS), n tss. T ny o solutons to prolms n ll o ts rs s nn y t o o n pproprt rprsntton (s,.., [Sm90, Sm90]). T ky ssu s tt t volum o t t s lr. Ts s l to n ntrst n prlll prossn o su t. Tr r two possl ppros trm m-sp n ojt-sp [Fol90]. In prtulr, t ojt-sp ppro ssns on prossor pr sptl ojt (.., [Bst9, Hol93, Hol94, Hol94]), wl t m-sp ppro ssns on prossor pr ron o sp (.., [Frn90]). In ts ppr our ous s on ojt-sp t-prlll rprsnttons o sptl t. T rprsnttons w w suss sort t t wt rspt to t sp tt t oups. Ts rsults n spn up oprtons nvolvn sr. T t o t sort s to ompos t sp rom w t t s rwn nto rons ll ukts. Our prsntton s or sptl t onsstn o ollton o lns su s tt oun n ro mps, utlty mps, rlwy mps, t. O ours, smlr rsults oul otn or otr typs o sptl t. On ppro known s n R-tr [Gutt84] ukts t t s on t onpt o mnmum ounn (or nlosn) rtnl. In ts s, lns r roup (opully y proxmty) nto rrs, n tn stor n notr strutur su s B-tr [Com79]. T rwk o t R- tr s tt t os not rsult n sjont omposton o sp tt s, t ounn rtnls orrsponn to rnt lns my ovrlp. Equvlntly, ln my sptlly ontn n svrl ounn rtnls, yt t s only ssot wt on ounn rtnl. Ts mns tt sptl qury my otn rqur svrl ounn rtnls to k or srtnn t prsn or sn o prtulr ln. T non-sjontnss o t R-tr s ovrom y omposton o sp nto sjont lls. In ts s, ln s ompos nto sjont sulns su tt o t sulns s ssot wt rnt ll. Tr r numrovrnts o ts ppro. Ty r n t r o rulrty mpos y tr unrlyn omposton ruls n y t wy n w t lls r rt. T pr p or t sjontnss s tt n orr to trmn t r ovr y prtulr ln, w v to rtrv ll t lls tt t oups. T rson s tt ln s ompos nto s mny ps (trm q-s) s tr r lls trou w t psss. Tr r two prnpl mtos: t R + -tr [Flo87] n vrnts o t PM qutr [Sm85, Nls86]. T prnpl rn twn tm s tt t lttr s s on rulr omposton o sp wl t ormr s not. Hr w stuy t lttr. Pror rsr n t prlll sptl omn s n lmt to qutrs, k-d-trs, n R-trs. T qutr rsr s prmrly ouss on r (or rstr) t n ron qutrs. Mu rsr s onntrt on lortms or uln (tr n top-own or ottom-up mnnr) ot pontr-s n lnr ron qutrs [Dn9, Ir93]. Otr orts v ouss on vlopn nor nn tnqus [Nn88] swll s xtrtn ron proprts n prormn st tort qurs [Bs88, Ks88, Dn9]. Som o t work s mploy proprtry prlll rtturs (.., two-mnsonl su xn ntwork [M86], or Drt [Mrt86]), or rnt prormmn lnus (.., Conurrnt Prolo [El85]) wl t mjorty s lt wt ypru rtturs. Bstul [Bst9] xtn t rsr unr t t prlll SAM (or Sn-An-Monoton-Mppn) mol o prlll omputton. In ton to ln wt lnr ron qutrs n t t prlll [Hll86] ontxt, lortms wr vlop y Bstul or uln n mnpultn (.., st tort sptl qurs) PR qutrs [Orn8, An83, Ros83] n PM qutrs. T k-d-tr [Bnt75] rsr ws lmt to smll ut mportnt srpton o t lortm or uln t t strutur or ollton o ponts usn t sn mol o omputton [Bll89]. T prlll R-tr rsr s n sprs n s onntrt on lortms or snl

3 pu{multpl prlll sk systms [Km9]. In ts ppr our ous s on t prmtvs tt r n to ntly onstrut ts rprsnttons. Our ol s on o sown t rr ow t nlos o rltvly smpl squntl oprtons n mplmnt n t-prlll nvronmnt. Our prsntton ssums tt t t-prlll lortms r mn mmory rsnt. Our lortms wr mplmnt n C on mnmlly onur Tnkn Mns CM-5 wt 3 prossors ontnn GB o mn mmory (t lortms v lso n run on 6K prossor CM-). T rst o ts ppr s ornz s ollows. Ston ry srs t sptl t struturs on w w ous. Ston 3 rvws numr o rnt prlll mols o omputton n ponts out ow ty l wt sptl t struturs. Ston 4 susss t t-prlll prmtvs tt r us to onstrut t t struturs, wl Ston 5 prsnts t lortms n trms o ts prmtvs. Ston 6 ontns som onlun rmrks. Sptl Dt Struturs In ts ston w rvw t tr t struturs tt r suss n t susqunt stons. W rst prsnt t PM qutr mly n xpln t vrnts tt w onsr, s wll s wy som o tm r not sutl or t-prlll nvronmnt. Ts s ollow y n xplnton o t R-tr. In nrl, w otn rtn t ornl nms o t t struturs ltou mor propr srpton woul us t qulr t prlll. W o not mk us o t unlss t stnton ns to mpsz n t s o potntl or msunrstnn lm.. PM Qutr T PM qutr [Sm85] svrtx{s mmr o t PM qutr mly. Wn nsrtn ln smnts nto ron, t ron s rptly suv untl rsultn ron ontns t most snl vrtx. Atonlly, ron ontns ln smnt vrtx (or npont), t my not ontn ny porton o notr ln smnt unlss tt otr ln smnt srs snl vrtx wt t ornl ln smnt n t sm ron. For xmpl, n Fur, ln smnts,, n sr ommon npont w lls n t ron ll A o t qutr. Do not tt t lr s ron ws suv s t ontns ln smnts n (w sr ommon npont tt lls outs t s rons). A Fur : PM qutr or n xmpl tst. T prmry prolm wt ts rprsntton s vnt wn two ln smnts v nponts tt r vry los totr, rsultn n lr numr o suvsons n orr to sprt t two nponts (or mor tls o ts ptolol vor, s [Nls86]). For xmpl, onsr Fur wr t nsrton o son ln smnt (ln n Fur ) rsults n v lvls o no suvson n t rton o tn nw nos n t PM qutr rprsntton (lvn o w r mpty). 3

4 () () Fur : () PM qutr onsstn o snl ln, n () t sm PM qutr tr t nsrton o son ln smnt (ln ) tt s vrtx tt s los to on o ln 's vrts.. PMR Qutr T PMR qutr (or polyonl mp rnom [Nls86, Nls87]) s n {s mmr ot PM qutr mly (s lso -Exll [Tmm8]). It mks us o prolst splttn rul wr lok s prmtt to ontn vrl numr o ln smnts. T PMR qutr s onstrut y nsrtn t ln smnts on-y-on nto n ntlly mpty strutur onsstn o on lok. E ln smnt s nsrt nto ll o t loks tt t ntrsts. Durn ts pross, t oupny o t lok sk to s t nsrton uss t to x prtrmn splttn trsol. I t splttn trsol s x, tn t lok s splt on, n only on, nto our loks o qul sz. T rtonl s to vo splttn no mny tms wn tr r w vry los lns n lok. In ts mnnr, w vo ptololly ss sr n t srpton o t PM qutr n lt n Fur. A ln smnt s lt rom PMR qutr y rmovn t rom ll t loks tt t ntrsts. Durn ts pross, t oupny o t lok n ts slns (t ons tt wr rt wn ts prssor ws splt) s k to s t lton uss t totl numr o ln smnts n tm to lss tn t prtrmn splttn trsol. I t splttn trsol xs t oupny o t lok n ts slns, ty r tn mr n t mrn pross s rursvly rppl to t rsultn lok n ts slns. Not t symmtry twn t splttn n mrn ruls. Fur 3: PMR qutr wt splttn trsol o two or t ollton o ln smnts o Fur. Fur 3 s n xmpl o PMR qutr orrsponn to st o 9 s ll trou nsrt n nrsn orr. Osrv tt t sp o t PMR qutr or vn tst s not unqu; nst, t pns on t orr n w t lns r nsrt nto t. Ts strutur ssums tt t splttn trsol vlu s two. T vnt o t PMR qutr ovr t PM qutr (n ts vrtx-s ppro) 4

5 s tt tr s no n to suv n orr to sprt ln smnts tt r vry \los" or wos vrts r vry \los" (rll Fur ). Ts s mportnt sn our loks r rt t suvson stp, n wn mny suvson stps our, mny mpty loks r rt, try ln to n nrs n t stor rqurmnts. Gnrlly, s t splttn trsol s nrs, t onstruton tms n stor rqurmnts o t PMR qutr rs wl t tm nssry to prorm oprtons on t wll nrs. It s ntrstn to pont out tt ltou ukt n ontn mor ln smnts tn t splttn trsol, ts s not prolm. In t, t n sown tt t mxmum numr o ln smnts n ukt s oun y t sum o t splttn trsol n t pt o t lok (.., t numr o tms t ornl sp s n ompos to yl ts lok), prov tt t ukt s not t t mxml pt llow y t prtulr mplmntton o t PMR qutr [Sm90]... Bukt PMR Qutr T sp o t PMR qutr s pnnt upon t nsrton orr o t nput t. In t tprlll nvronmnt, lns r nsrt smultnously urn t strutur onstruton. Tus, t orrn o t lns s unknown. Bus t sp o t PMR qutr rls upon t orrn o t t (or mor tls, s Ston 5.), t nton o t PMR qutr s sltly mo to yl t ukt PMR qutr. Fur 4: A ukt PMR qutr wt ukt pty o two n mxml tr t o tr w orrspons to t tst sown n Fur. T ukt PMR qutr [Hol94] svrnt o t PMR qutr wr nst o splttn n ovrown lok on, t lok (or ukt) s splt rptly untl su-ukt ontns not mor tn lns (wr s t mxml ukt pty). T motvton n t t strutur s t sr or t strutur wos sp s npnnt o t ln smnt nsrton orr. Not tt unlss t ukt pty s rtr tn or qul to t mxmlnumr o ntrston lns, t rursv omposton wll ontnu to t mxml pt llow y t ukt PMR qutr. For xmpl, onsr Fur 4 wr t rons orrsponn to t nponts o ln suv untl t mxml pt o t qutr (tr n ts s) s r..3 R-tr T R-tr (ornlly us to rprsnt olltons o rtnls [Gutt84]) n ts vrnts r sn to ornz ollton o rtrry omtr ojts n mnsons (most notly twomnsonl rtnls) y rprsntn tm s -mnsonl rtnls. E no n t tr orrspons to t smllst -mnsonl rtnl tt nloss ts son nos. T l nos ontn pontrs to t tul omtr ojts n t ts, nst o sons. T ojts (.., ln smnts n our s) r rprsnt y t smllst ln rtnl n w ty r ontn. 5

6 Otn t nos orrspon to sk ps n, tus, t prmtrs nn t tr r osn so tt smll numr o nos s vst urn sptl qury. Not tt t ounn rtnls orrsponn to rnt nos my ovrlp. Also, ln smnt my sptlly ontn n svrl nos, yt t s only ssot wt on no. Ts mns tt sptl qury my otn rqur svrl nos to vst or srtnn t prsn or sn o prtulr ln smnt. T s ruls or t ormton o n R-tr r vry smlr to tos or B-tr. All l nos ppr t t sm lvl. E ntry n l no s -tupl o t orm (R,O) su tt R s t smllst rtnl tt sptlly ontns ln smnt O. E ntry n non-l no s -tupl o t orm (R,P ) su tt R s t smllst rtnl tt sptlly ontns t rtnls n t l no pont t y P. An R-tr o orr (m,m) mns tt no n t tr, wt t xpton o t root, ontns twn m M= n M ntrs. T root no s t lst two ntrs unlss t s l no. R R4 R R5 R3 R6 R0 R3: R0: R R R: R3 R4 R: R5 R6 R4: R5: R6: () () Fur 5: () T sptl xtnts o t ounn rtnls n () t R-tr or t xmpl ollton o ln smnts. For xmpl, onsr t ollton o ln smnts vn n Fur. Lt M = 3 n m =. On possl R-tr or ts ollton s vn n Fur 5. Fur 5 sows t sptl xtnt o t ounn rtnls o t nos n Fur 5, wt rokn lns notn t rtnls orrsponn to t sutrs root t t non-l nos. Not tt t R-tr s not unqu. Its strutur pns vly on t orr n w t nvul ln smnts wr nsrt nto (n possly lt rom) t tr. T lortm or nsrtn ln smnt (.., ror orrsponn to ts nlosn rtnl) n n R-tr s nloous to tt us or B-trs. Nw ln smnts r to l nos. T pproprt l no s trmn y trvrsn t R-tr strtn t ts root n t stp oosn t sutr wos orrsponn ounn rtnl woul v to nlr t lst. On t l no s n trmn, k s m to s nsrton o t ln smnt wll us t no to ovrow. I ys, tn t no must splt n t M + rors must strut n t two nos. Splts r propt up t tr. Tr r mny possl wys to splt no. On possl ol s to strut t rors mon t nos so tt t lkloo tt t nos wll vst n susqunt srs wll ru. Ts s ompls y mnmzn t totl r o t ovrn rtnls or t nos (.., ovr). An ltrntv ol s to ru t lkloo tt ot nos r xmn n susqunt srs. Ts s ompls y mnmzn t r ommon to ot nos (.., ovrlp). O ours, t tms ts ols my ontrtory. For xmpl, onsr t our rtnls n Fur 6. T rst ol s sts y t splt n Fur 6, wl t son ol s sts y t splt n Fur 6. Guttmn [Gutt84] us n lortm s on t mnmzton o t totl r o t ovrn rtnls (.., t rst o t ols sr ov). Bkmnn [Bk90], owvr, mploy no splttn tnqu rsultn n wt s trm n R -tr. Ts tnqu ttmpts to mnmz t mount o ntrston r twn ovrn rtnls, w 6

7 () () () Fur 6: () Four rtnls n t splts tt woul nu, () y mnmzn t totl r o t ovrn rtnls n () y mnmzn t r o ntrston twn t ovrn rtnls o ot nos. orrspons to t son o t prvously sr ols. 3 Mols o Prlll Computton In ts ston w sr tr mols o prlll omputton: PRAM, Sn, n SAM. In t pross w lort on tr sutlty or oprtons on sptl t struturs. As w wll s, t sn mol s t most pproprt. For t sn mol w lso sr t typs o prmtv oprtons s ty wll us n t srpton o t sptl prmtv oprtons n Ston PRAMs An N prossor Prlll Rnom Ass Mn (or PRAM) onssts o prossors P ;P ;;P N n lol sr mmory [Kuk77, L9]. Fur 7 ontns smpl rprsntton o n N prossor PRAM. E o t N prossors n r or wrt rom ny loton wtn t sr mmory t stp o t omputton. lol sr mmory P P P n Fur 7: Smpl ur rprsntn N prossors onnt to ommon sr mmory n t PRAM mol. PRAMs r ommonly lss orn to onurrnt ss plts o t lol sr mmory. T most rstrtv o t mols s t xlusv-r, xlusv-wrt (EREW) PRAM. At ny st o t omputton, only on prossor s llow to tr r rom or wrt to sp mmory loton n t lol sr mmory. Iw rlx t xlusv r onstrnt n llow multpl prossors to smultnously r rom sp mmory loton, w otn t onurrnt-r, xlusv wrt (CREW) PRAM. Fnlly, t xlusv wrt onstrnts s smlrly rlx, w otn t onurrnt-r, onurrnt-wrt (CRCW) PRAM. T PRAM mol o prlll omputton rs t usr rom t tous tls o tully mplmntn prlll lortm on prlll mn. T prormmr os not n to worry out t prossor ntronnton topoloy n ommunton onts. Unortuntly, lr sr mmory prlll omputrs r ult to mplmnt, n sr-notn mns ppr to mor sll n wll sut to vlopn prlll mns wt lr numrs o prossors [DW9]. It s possl owvr to mult PRAMs on lr sr-notn mns (.., yprus [L9]) su s t CM-5, ut wt prormn pnlts [Alt87]. 7

8 3. Sn Mol T sn mol o prlll omputton [Bll88, Bll89] s n n trms o ollton o prmtv oprtons tt n oprt on rtrrly lon vtors (snl mnsonl rrys) o t. Tr typs o prmtvs (lmntws, prmutton, n sn) r us to prou rsult vtors o qul lnt. A sn oprton [Sw80] tks n ssotv oprtor L,vtor [ 0 ; ;; n, ], n rturns t vtor [ 0 ; ( 0 L ); ;( 0 L L L n, )]. Blllo [Bll90] ponts out tt t EREW PRAM mol wt t sn oprtons nlu s prmtvs s trm t sn mol. T sn mol onsrs ll prmtv oprtons (nlun sns) s tkn unt tm on ypru rttur. Ts llows sortn oprtons to prorm n O(lo n) tm. 3.. Snws Oprtons In ton to n lss s tr upwr or ownwr, sn oprtons my smnt. A smnt sn my tout o s multpl prlll sns, wr oprts npnntly on smnt o ontuous prossors. Smnt roups r ommonly lmt y smnt t, wr vlu o nots t rst prossor n t smnt. For xmpl, n Fur 8, tr r our smnt roups, orrsponn to smnts o sz 3, 4,, n 3. t s:smnt l up-sn(t,s,+,n) up-sn(t,s,+,x) own-sn(t,s,+,n) own-sn(t,s,+,x) Fur 8: Exmpl smnt sns or ot t upwr n ownwr rtons (s wll s nlusv n xlusv). Fnlly, sn oprtons my urtr lss s n tr nlusv or xlusv. For xmpl, n upwr nlusv sn oprton rturns t vtor [ 0 ; ( 0 L ); ;( 0 L L L n, )], wl n upwr xlusv sn rturns t vtor [0; 0 ;;( 0 L L L n, )]. Vrous omntons o smnt sns (wr L s oun to t ton oprtor) r sown n Fur Elmntws Oprtons An lmntws prmtv s n oprton tt tks two vtors o qul lnt n prous n nswr vtor, lso o qul lnt. T t lmnt n t nswr vtor s t rsult o t pplton o n rtmt or lol prmtv to t t lmnt o t nput vtors. In Fur 9, n xmpl lmntws ton oprton s sown. A n B orrspon to t two nput vtors, n w(+,a,b) nots t nswr vtor. A B w(+,a,b) Fur 9: Exmpl ltn n lmntws ton oprton. 8

9 3..3 Prmuttons A prmutton prmtv tks two vtors, t t vtor n n nx vtor, n rrrns (prmuts) lmnt o t t vtor to t poston sp y t nx vtor. Not tt t prmutton must on-to-on; two or mor t lmnts my not sr t sm nx vtor vlu. Fur 0 provs n xmpl prmutton oprton. A s t t vtor, nx s t nx vtor, n prmut(a,nx) nots t nswr vtor. poston A nx j poston prmut(a,nx) j Fur 0: Exmpl o prmutton. 3.3 SAM Mol A smlr ut mor rstrtv mol o prlll omputton, t SAM (Sn-An-Monotonmppn) mol o prlll omputton [Bst9] my n y on or mor lnrly orr sts o prossors w llow lmnt-ws n sn-ws oprtons to prorm. Bot wtn n twn lnrly orr st o prossors, monoton mppns my lso prorm. A monoton mppn s n s on n w t stnton prossor ns r monotonlly nrsn or monotonlly rsn unton o t sour prossor ns. For xmpl, onsr t stuton pt n Fur wr t sour prossors r ontn n prossor st A, n t stnton prossors r lot n prossor st B. Fur s vl monoton mppn, wl t mppn n Fur s not monoton mppn (s oms or n t lnr orrn). A 3 4 A 3 4 B j B j () () Fur : () An xmpl monoton mppn twn two sts o prossors, n () smlr mppn w s not monoton. Bn mor rstrtv tn t sn-mol y rqurn monoton mppns, t SAM mol lso onsrs sn oprtons s tkn unt tm, tus llown sortn oprtons to prorm n O(lo n). T SAM mol ws m npproprt or our rsr s t s unl to ntly ltt t mnpulton o R-trs. Ts s u to t ults nvolv n mntnn monoton mppns twn two rnt R-trs wn prormn sptl qurs su s mp ntrston (s [Hol94, Hol94] or mor tls). Not owvr tt our lortm or uln t-prlll R-trs s sr n Ston 5.3 os not volt t mor rstrtv SAM mol. Bukt PMR qutrs, wt tr rulr sjont ompostons, r strutur or w t SAM mol s wll-sut. 9

10 Bus o t ukt PMR qutr's rulr omposton, unqu lnr orrn my rly otn (vn prtulr lnr orrn mtooloy su s Pno urv [Pn90]). As wll sown ltr, t R-tr, wt ts rrulr omposton, os not v unqu lnr orrn. Wn prormn oprtons on two mps wt non-unqu lnr orrns, t mntnn o t monoton mppns oms xpnsv u to t nssry prossor rorrns n t t-prlll nvronmnt. For xmpl, onsr t stuton pt n Fur wr two sts o prossors (st (A,B) n st (C,D) orrspon to t ovrlppn rons n Fur. Suppos prossor n on roup must ommunt wt ntrstn prossor n t otr roup (.., A wt C n D, n B wt C n D). For t rst roun o ommunton sown n Fur, monoton mppn my mntn. T son roun (pt n Fur ) owvr volts t monoton mppn. I prossors A n B n t rst st r rorr (n xpnsv oprton or lr ollton o prossors), t monoton mppn my on n mntn s sown n Fur. C A A B A B B A B D C D C D C D () () () () Fur : () An xmpl ollton o ntrstn ounn oxs, () vl monoton mppn, () n nvl monoton mppn, n () vl monoton mppn ollown prossor rorrn. 4 Dt-Prlll Sptl Prmtv Oprtons In ts ston w sr t prmtv oprtons tt r n to onstrut PM qutr, ukt PMR qutr, n n R-tr. Svrl o t lowr-lvl prmtvs v n sr lswr (.., [Nss8, Hun89]). 4. Clonn Clonn (lso trm nrlz [Nss8]) s t pross o rpltn n rtrry ollton o lmnts wtn lnr prossor orrn. Fur 3 sows n xmpl lonn oprton. Clonn my ompls usn n xlusv upwr ton sn oprton, n lmntws ton, n prmutton oprtor. X lon l X' Fur 3: Exmpl o lonn oprton. Fur 4 tls t vrous oprtons nssry to omplt t lonn oprton. In t ur, lon l nts w lmnts o x must lon; n ts xmpl, lmnts,, n r to lon. T s tnqu s to lult t ost nssry tt xstn lmnt must mov towr t rt n t lnr orrn n orr to mk room or t nw 0

11 lon lmnts. Ts my ompls y mployn n upwr xlusv sn w sums t lon s, s not y up-sn(cf,+,x) n t ur. Atr t ost s n trmn, n lmntws ton on t ost vlu (F) n t poston nx (P) trmns t nw poston or lmnt n t orrn (w(+,p,f)). A smpl prmutton oprton s tn us to rposton t lmnts (prmut(x,f)). Fnlly, t lonn oprton s omplt wn wn o t lonn lmnts ops tsl nto t nxt lmnt n t lnr orrn (not y t smll urv rrows n t ur). P X lon l CF up-sn(cf,+,x) F w(+,p,f) F P prmut(x,f) Fur 4: Exmpl ltn t mns o t lonn oprton. 4. Unsun Unsun s t pross o pyslly sprtn two rtrry, mutully xlusv n olltvly xustv susts o n ornl roup. Ts oprton, wn ppl wtout monoton mppns, s lso n trm pkn [Krus85] or splttn [Bll89]. Unsun n ompls usn two nlusv sns (on upwr n on ownwr), two lmntws oprtons (n ton n sutrton), n prmutton oprtor. An xmpl unsun oprton s sown n Fur 5. Fur 5: Exmpl o n unsun oprton. P X up-sn(x=,+,n) F own-sn(x=,+,n) F {X=} w(-,p,f) F3 {X=} w(+,p,f) P prmut(x,f3) Fur 6: Exmpl ltn t mns o t unsu oprton. T tul mns o t unsu oprton or t t o Fur 5 r llustrt n Fur 6. T two rnt typs w must unsu v typ ntrs n. Assum

12 tt t 's r to rposton towr t lt, n t 's towr t rt n our lnr orrn. T s tnqu s, or lmnt o t two roups, to lult t numr o lmnts rom t otr roup tt r poston twn tsl n ts sr poston t tr t lt n or t rt n. An upwr nlusv sn (up-sn(x=,+,n)) s us to ount t numr o 's twn n t lt n o t orrn. Smlrly, ownwr nlusv sn (own-sn(x=,+,n)) s lso us to ount t numr o 's twn nvul n t rt n o t lnr orrn. On ts two vlus r lult, two lmntws oprtons r us to lult t nw poston nx or lmnt o t lnr orrn. For lmnt, n lmntws sutrton o t lult numr o ntrpos 's (F) rom t ornl poston nx P trmns t nw poston nx (w(-,p,f)). Smlrly, or lmnt, n lmntws ton o t lult numr o ntrpos 's (F) n t ornl poston nx P trmns tr nw poston ns (w(+,p,f)). Fnlly, vn t nw poston ns n F3, smpl prmutton oprton (prmut(x,f3)) wll rposton lmnt nto t propr poston n t lnr orrn. 4.3 Duplt Dlton Duplt lton (lso trm onntrt [Nss8]) s t pross o rmovn uplt ntrs rom sort lnr prossor orrn. An xmpl uplt lton (wt t uplt lmnts s) s sown n Fur 7. Duplt lton s ompls usn n upwr xlusv sn oprton, ollow y lmntws sutrton n nlly prmutton oprton. X X' Fur 7: Exmpl o uplt lton oprton. Assumn tt t lmnts n t lnr orrn v n sort y ntr, t s tnqu mploy wn ltn uplt ntrs s to ount t numr o uplts twn lmnt n t lt s o t orrn. E lmnt s tn mov towr t lt y ts numr o postons. Consr Fur 8 wr t lmnts r sort n t uplt tms r mrk (uplt l), n upwr xlusv sn oprton (up-sn(df,+,x)) s us to sum t numr o lmnts n t lnr orrn tt r to lt. An lmntws oprton (w(-,p,f)) s tn mploy to sutrt t numr ontrpos tms to lt (F) rom t lmnt's poston nx P. Ts vlu s tn us s t nw poston nx n smpl prmutton oprton (prmut(x,f)) n ompltn t uplt lton oprton. P X uplt l DF up-sn(df,+,x) F {DF=0} w(-,p,f) F P {DF=0} prmut(x,f) Fur 8: Exmpl ltn t mns o t uplt lton oprton.

13 4.4 No Cpty Ck For sptl ompostons su s t ukt PMR qutr n t R-tr wos no splttn rul ouss solly on t numr o tms n no, no pty k n us n trmnn wtr or not no n t tr s ovrown n ns to splt. Ts n ompls usn ownwr nlusv ton sn oprton, ollow y n lmntws wrt (or r) oprton. In Fur 9, t ownwr sn s sown or n xmpl tst. Follown t trmnton o t no ounts, nos wos ukt pty s x my mrk or suvson. 3 4 nos lns 3 4 ount Fur 9: Exmpl sown ow ownwr nlusv smnt sn oprton my mploy n no pty k. 4.5 Dtrmnn PM Qutr No Soul Splt For t PM qutr, t pross o trmnn wtr or not no soul splt rqurs mor normton tn smply t numr o lns tt ntrst t no. Gvn t mxmum n mnmum numr o nponts ssot wt ll lns wtn no, t s possl to trmn wtr or not som o t nos must suv. T no must suv tr t mxml numr o nponts s qul to two, or t mxml numr s on n t mnml numr s zro. I, owvr, t mxmum n mnmum numrs r qul to otr (.., 0 or ), tn tonl normton s nssry or t suvson trmnton n m. T tonl normton tt s nssry n t s o no wr t mxmum n mnmum r ot on, s wtr or not snl npont xsts wtn t no. I tr r two or mor nponts wtn t no, tn t no must suv. Ts npont ount my trmn y ormn t mnml ounn ox o t nponts tt l wtn t no [Bst9]. I t npont ounn ox s trvlly pont, tn ts nts tt ll lns wtn t no sr ommon vrtx, tus tr s no n to urtr suv t no. Otrws, t no must suv s tr s mor tn on npont n t no. In t s wr ot t mnm n mxm r qul to zro, t s nssry to trmn t numr o lns wtn t no. I t numr o lns wtn t no s rtr tn on, tn t no must suv. In prlll, ln rst trmns t numr o ts nponts tt xst wtn t no; tr 0,, or. In Fur 0, ts numr s rprsnt y t EPs (or nponts) l. Usn squn o ownwr nlusv smnt sn oprtons, t mxmum n mnml numr o nponts ssot wt ll lns wtn t no s trmn. Fur 0 rprsnts ts vlus n t mn EPs n mx EPs ls. Ts two numrs r tn ommunt y t rst ln n smnt roup to t orrsponn no n t tr. Bs upon t lult mxmum n mnmum npont vlus, t n trmn tt no n Fur 0 must suv. For t rmnn nos n t xmpl, tonl normton s nssry n orr to trmn wtr or not t no must suv. For nos wr t mnmum n mxmum numr o nponts s qul to on, t rqur normton s wtr t no ontns snl npont tt s sr mon ll lns n t no. Ts n trmn y ormn t mnmum 3

14 X Y nos 3 4 W 3 4 Z lns EPs 0 0 mn EPs mx EPs 0 0 Fur 0: Intl onurton o nos n lns. Usn squn o ownwr smnt sns, t mxmum n mnmum numr o nponts ssot wt ll lns n no s trmn. T ry no s trmn to rqur splt. X Y nos 3 4 W 3 4 Z lns MBBs W X X - Z Z Z Z Z Z Fur : Clulton o t npont mnmum ounn oxs (MBBs) or nos wr t mxmum n mnmum numr o nponts r qul. T rk ry no ws prvously trmn n Fur 0 to rqur splt, t lt ry no s urrntly trmn to rqur splt, wl t ross no 4 os not rqur suvson. ounn ox o t nponts tt l wtn t no. I t vrtx ounn ox s trvlly pont, tn ts nts tt ll lns wtn t no sr ommon vrtx. Tus tr s no n to urtr suv t no. T mnmum ounn oxs n trmn usn smll squn o ownwr nlusv smnt sn oprtons. In Fur, t mnmum ounn oxs r rprsnt y t ollton o npont lls (.., W, X, Y, n Z) nt ln. For xmpl, t npont mnmum ounn ox or no ontns nponts X n W, wl t mnmum ounn ox or no 4 ontns only npont Z. Bs upon t lult ounn oxs, no must suv, wl no 4 os not n to suv. In t s wr ot t mnm n mxm r qul to zro, t s nssry to trmn t numr o lns wtn t no. I t numr o lns wtn t no s rtr tn on, tn t s nssry to suv t no. In Fur, t ln ount s lult wt smpl ownwr nlusv smnt sn usn t ton oprtor. For t rmnn no n quston (no 3), ln ount o mpls tt t no os not n to suv. Ts nl oprton omplts t trmnton o wtr or not PM qutr no must suv. 4.6 Splttn Qutr No T tnqu mploy to splt qutr no s two st pross. Atr trmnn tt no soul splt, t no s rst splt vrtlly, n tn orzontlly. Ts rsults n t suvson o t no nto qul sz qurnts. A no pty k rst s mploy to ount t numr o lns ssot wt t no n trmn wtr or not t no soul splt. Fur 3 pts ts pross or snl 4

15 X Y W nos Z lns ount Fur : Clulton o t ln ount or t rmnn no (3). Bs upon t ount o, t no s not rqur to suv. Not tt prvously, nos n wr trmn to rqur suvson, wl no 4 not rqur suvson. nos lns ount Fur 3: Exmpl ntl ln to no ssoton urn no splttn pross. T no pty k ps o t pross s lt. no n v ssot ln smnts. I t numr o lns ssot wt t no prossor xs t prn no pty (4 n ts xmpl), tn t no must splt nto our sunos n o t lns must rroup, orn to t nos t ntrsts. nos lns lon Fur 4: Dtrmnn w lns ntrst t orzontl splt xs n must lon. No splttn ours n two sts, wt t rst st orrsponn to vrtl splt o t no nto two ps. In prlll, ln n t splttn no trmns wtr or not t ntrsts t splt xs. I t ln ntrsts t splt xs, t must lon. For t xmpl tst, ntrstn ln (lns n ) ssown wt t lon vlu o. A lonn oprton, s sr n Ston 4., s tn prorm on t lns n t no tt ntrst t splt xs. Ts s sown n Fur 4. On t ntrstn lns v n lon, t s nssry to rroup t lns orn to wtr ty l n t top or t ottom l o t splttn no. In prlll, ln my mk 5

16 nos lns s T B T B B T B Fur 5: Follown ln lonn, ln n prlll trmns wtr t ls n t top (T) or ottom (B) l o t two rsultn nos. An unsu oprton s tn ppl s upon w l t ln rss n. ts trmnton us ln stors t sz n poston o t no tt t rss n. In Fur 6, t s vlu rprsnts wtr t ssot ln s n t top (T) or ottom (B) l o t splttn no. T rroupn o t lns s v wt n un-su oprton s tl n Ston 4.. T un-su s us to onntrt t lns totr nto two nw smnts, o w orrspons to ll o t ln prossors lyn tr n wol or n prt ov orlow t y oornt vlu o t ntr o t splttn no. T un-su oprton omplts t rst l o t qutr no splttn oprton. T rsult o ts un-su oprton s pt n Fur 6. nos lns lon Fur 6: Rsult o t vrtl no splt. T son ps o t no splt ns wt ln trmnn wtr ty ntrst t orzontl splt xs. Intrstn lns must lon. T son l o t no splttn oprton uss nloous tnqus n splttn t two rsultn nos n n l orzontlly. Ts orzontl splt wll rsult n t ornl no pt n Fur 3 n suv nto our qul sz rons. T son st ns wt ln trmnn wtr or not t ntrsts t orzontl splt n soul lon. In Fur 6, t ntrstn lns (ln n no ) s sown wt ts lon vlu st to. Follown t ln lonn, ln n prlll trmns wtr t ls on t lt (L) or rt (R) s o t splt xs. Bs upon t ln's poston rltv to t splt xs, n un-su oprton s us on o t two nos n prlll to rt two smnt roups or o t two splttn nos. E smnt roup wll orrspons to ll o t ln prossors w l tr n wol or n prt to t lt or t rt o t splt xs. T un-su oprton s sown or t xmpl tst n Fur 7. T rsult o t un-su oprton s pt n Fur 8. At ts pont, t qutr no splttn oprton s omplt. 6

17 nos lns s R L L R L R R R Fur 7: Follown ln lonn, ln n prlll trmns wtr t ls n t lt (L) or rt (R) l o t two rsultn nos. An unsu oprton s tn ppl s upon w l t ln rss n. nos lns Fur 8: Fnl rsult o t xmpl no splt oprton. 4.7 Sltn n R-tr No Splt T top o ow to splt n ovrown no s n t sujt o mu rsr on squntl R-trs. For xmpl, t R -tr [Bk90], s n R-tr vrnt tt uss mor sopstt no nsrton n splttn lortm tn tos prov wt t onvntonl nton o t R-tr [Gutt84]. For t t-prlll R-tr, w v vlop two no splttn lortms, o vryn omputtonl omplxty. In t rst n smplst lortm, t splttn xs (.., x or y-xs n t two-mnsonl s) n t oornt vlu r trmn y nn t mn vlus lon xs o t mponts o ll ounn oxs n t ln prossor st n prlll v squn o sn oprtons. For xs n smnt roup, t mponts o t ounn oxs r rst summ usn ownwr nlusv smnt sn oprton (wt t ton oprtor). T rst no n t smnt roup tn vs t sum y t numr o ounn oxs n t smnt roup. Ts vlu s tn rost [Hun89] to ll otr nos n t smnt roup wt n upwr smnt sn (usn t opy oprtor). E no tn trmns wtr t ls n t lt or rt rsultn ounn oxs. Fnlly, smll squn o upwr n ownwr nlusv sn oprtons (usn tr mn or mx oprtor, pnn upon t ntur o t sn) s us to trmn t pysl xtnts o t two ounn oxs. T splt xs n oornt vlu r osn rom t two possl splts (.., t mn lon t x-xs n t y-xs) so s to mnmz t mount o r ommon to t two rsultn nos. Ts oprton s o omplxty O() t st o t uln oprton s onstnt numr o sns omnts t omputton. T son no splttn lortm rst sorts ll lns n t smnt orn to t lt o tr ounn oxs. A squn o upwr sn oprtons r us to trmn t xtnts o t ounn ox orm y ll lns prn ln n t sort smnt. A smlr squn o ownwr sns wll trmn t ounn ox or ll ollown lns n t smnt. For ll ll splts (.., wr o t two rsultn nos rvs t lst m=m o t lns n 7

18 rstrut), t mount o ounn ox ovrlp s lult, wt t splt orrsponn to t mnml mount o ovrlp n slt s t x-xs nt. An nloous prour s mploy or t y-xs n otnn t y-xs nt splt oornt vlu. On t two nt splt oornt vlus r trmn, t on orrsponn to t mnml ounn ox ovrlp s slt. In t vnt o t, som otr mtr su soosn t splt wt t mnml ounn ox prmtr lnts my mploy. Ts splttn lortm s o omplxty O(lo n) t st o t uln oprton s w mploy twoo(lo n) sorts n onstnt numr o sn oprtons. L Box A B C D R Box ls: lt s rs: rt s L Box lt s L Box rt s R Box lt s R Box rt s A B C D sn typ up-sn(ls,-,mn,n) up-sn(rs,-,mx,n) own-sn(ls,-,mn,x) own-sn(rs,-,mx,x) Fur 9: Exmpl ltn t vrous sn typs n tr pplton to trmnn t x-oornt vlus or t lt n rt ounn oxs. Consr t xmpl sown n Fur 9 onsstn o our ounn oxs ll A{D wr t nos v n sort orn to tr lt x-oornt vlus. In ts xmpl, w r only onsrn t x-oornt vlus o t ounn oxs tou norporton o y-oornt vlus s strtorwr. In t ur, t lt n rt oornt vlus o t our nos r nt on t lns ll ls:lt s n rs:rt s rsptvly. For xmpl, no B s lt n rt x-oornt vlus 0 n 50 rsptvly, wl no C s lt n rt x-oornt vlus 40 n 70. Assumn tt no s roup wt ll nos on ts lt wn ormn t ounn oxs (.., no C s roup wt nos A n B wn ormn no C's lt n rt ounn oxs), t ollown squn o sn oprtons n us to trmn t ounn oxs on t lt n t rt or no. As sown n Fur 9, n upwr mnmum nlusv sn on t lt oornt vlu, s us to trmn t lt x-oornt vlu or t ounn ox on nos lt s (L Box lt s). Smlrly, n upwr mxmum nlusv sn on t rt x-oornt vlus wll stls t rt x-oornt vlu or t ounn ox on nos lt s (L Box rt s). Tus, or no B, w s tt t lt n rt oornt vlus or t ounn ox to ts lt (.., t ounn ox ontnn nos A n B, ll L Box n Fur 9), v x-oornt vlus 0 n 50. Ts vlus r oun n t rows o Fur 9 ll L Box lt s n L Box rt s. Anloous ownwr mn/mx xlusv sns r us to trmn t lt n rt x-oornt vlus o t ounn ox to t rt o no. W my osrv tt t lt n rt x-oornt vlus or t ounn ox to t rt o no B(.., ounn ox ontnn nos C n D, ll R Box 8

19 n Fur 9) v vlus 40 n 80, rsptvly. Atr t two ounn oxs v n trmn or ll splt (.., no splt wr o t two rsultn nos rvs t lst m=m o t lns n rstrut), t mount o ounn ox ovrlp s lult, wt t splt orrsponn to t mnml mountoovrlp n slt s t x-xs nt splt oornt vlu. An nloous prour s mploy or t y-xs n otnn t y-xs nt splt oornt vlu. On t two nt splt oornt vlus r trmn, t on orrsponn to t mnml ounn ox ovrlp s slt. In t vnt o t, som otr mtr su soosn t splt wt t mnml ounn ox prmtr lnts my mploy. Ts splttn lortm tks O(lo n) tm t st o t uln oprton s w mploy twoo(lo n) ln sorts n onstnt numr o sn oprtons. 5 Dt-Prlll Bul Alortms In ts ston w sow ow to ul PM qutr, ukt PMR qutr, n n R-tr. T lortms r r n mk us o t prmtvs sr n Ston PM Qutr Construton T t-prlll PM -qutr uln pross ns wt ln ssn to snl qutr no s pt n Fur 30. T s PM qutr onstruton s n trtv pross wr nos r suv untl tr splttn rtron (rr to Stons. n 4.5 or tl srpton) s no lonr sts. Usn t sm tnqu s sr n Ston 4.5, t root no s mrk or suvson s upon t mxmum numr o nponts n qul to two. T no s suv n t lns r splt n rstrut usn t qutr no splttn mto sr n Ston 4.6. nos lns Fur 30: Intl onurton. Follown t suvson o t root no o t PM qutr, w r lt wt t stuton sown n Fur 3. Not tt lns,, n wr lon urn ts no splt s ty ntrst on o t splt xs. Ts omplts t rst trton o no suvsons. E susqunt trton s smlr to t rst: no s rst k to s t must suv, n tn nssry, t no s suv usn t stnr qutr no splttn prmtv rom Ston 4.6. In Fur 3, t nw, n, n s nos must suv. T rsult o t son trton o no splttn s sown n Fur 3. At ts pont, on rmnn suvson must prorm on t nw l o t s qurnt (no 0). T nl trton rsults n t omposton sown n Fur 33. Bus no mor nos must splt, t PM qutr onstruton pross s omplt. For n ln smnts, t t-prlll PM qutr onstruton oprton tks O(lo n) tm, wr o t O(lo n) suvson sts rqurs O() omputtons ( onstnt numr o sns, lonns, n un-sus). 9

20 3 4 nos lns 3 4 Fur 3: Rsult o t rst roun o no splttn nos lns Fur 3: Atr son roun o no splttn. 5. Bukt PMR Qutr Construton In t t-prlll nvronmnt, ll lns r nsrt smultnously wn onstrutn sptl t strutur. Tus tr s no prtulr orrn o t t upon nsrton. T onvntonl PMR qutr's no splttn rul s on tt splts no on n only on wn ln s n nsrt. Ts s t s vn t numr o lns tt rsult xs t no's pty. Su splttn rul s nontrmnst n t sns tt t omposton pns on t orr n w t lns r nsrt. For xmpl, onsr t stuton pt n Fur 34 wr nn t nsrton orr o lns 3 n 4 rsults n rnt ompostons. Ts nontrmnsm s unptl wn mny lns r nsrt n no smultnously s w o not know ow mny tms t no soul splt. In orr to vo ts stuton, w os t ukt PMR qutr or t t-prlll nvronmnt s ts sp s npnnt o t orr n w t lns r nsrt n ts wll-v ukt splttn rul (.., tr s no muty wt rspt to ow mny suvsons tk pl wn svrl lns r nsrt smultnously) nos lns Fur 33: Fnl rsult o t PM qutr onstruton pross or t xmpl tst. 0

21 () () Fur 34: () An xmpl PMR qutr wt splttn trsol o two, wt t lns nsrt n numrl orr, n () t rsultn PMR qutr wn t nsrton orr s sltly mo so tt ln 4 s nsrt or ln 3. nos lns Fur 35: Intl ukt PMR qutr prossor ssnmnts. A ukt PMR qutr s ult n n trtv son, smlr to tt mploy wt t PM qutr onstruton lortm. Intlly, snl prossor s ssn to ln n t t st, n on prossor to t rsultnt ukt PMR qutr s pt or t smpl t st n Fur 35 (wt t xmpl tst, ssum w v n 8 8 qutr o mxml t 3). T rst trton ns wt t qutr no splttn prmtv s sr n tl n Ston 4.6. Bslly, no trmns t numr o lns ontn n ts ssot smnt roup, n ts numr xs t ukt pty, t no s splt usn squn o lonn n unsun oprtons. In Fur 35, t snl qutr no s suv s t t numr o lns (9) xs t ukt pty o n ts xmpl. T rsult o t rst suvson s sown n Fur 36. Contnun wt ts trtv pross, n Fur 36, t nw n s nos wll suv, rsultn n t stuton pt n Fur nos lns 3 4 Fur 36: Rsult o t rst no suvson, ln lonn, n un-sun.

22 nos lns Fur 37: Rsult o t son roun o no suvsons. Ts trtv suvson pross ontnus untl ll nos n t ukt PMR qutr v ln ount lss tn or qul to t ukt pty, or t mxml rsoluton o t qutr s n r (.., no o sz ). Ts s not prolm s or prtl ukt pts (.., 8 n ov), ts stuton s xnly rr n wll not us ny lortm ults prov tt t ukt PMR qutr lortms o not ssum n uppr oun on t numr o lns ssot wt vn no nos lns Fur 38: Rsult o t ukt PMR qutr ul pross. Bus no 7's ukt pty s x (sown n Fur 37), n t mxml rsoluton s not yt n r, notr roun o suvson s nssry. T rsult o t tr n nl suvson or our xmpl t st s sown n Fur 38. Not tt on o t qutr nos (no 9) stll s ts ukt pty x. In t xmpl, t mxml rsoluton s n r (.., 8 8). Tror, no 9 wll not urtr suv. T t-prlll ukt PMR qutr uln oprton tks O(lo n) tm, wr o t O(lo n) suvson sts rqurs O() omputtons ( onstnt numr o sns n un-sus). N 0 lns ount Fur 39: Intl prossor ssnmnt or t R-tr onstruton lortm.

23 5.3 R-tr Construton T t-prlll R-tr onstruton lortm rs rom t squntl R-tr lortm s nst o nsrtn ln smnts squntlly nto t t strutur, ll ln smnts r nsrt smultnously. T t-prlll R-tr onstruton lortm pros s ollows. Intlly, on prossor s ssn to ln o t t st, n on prossor to t rsultnt t-prlll R-tr s pt or smpl tst n Fur 39. Our xmpl ssums n orr (; 3) R-tr. In t ur, t ll N 0 nots t R-tr no prossor st, wt t ssot squr ron ontnn t ntr o t R-tr no ssot wt t R-tr no prossor. W us t trm smnt to rr to t ollton o ln prossors ssot wt prtulr R-tr no prossor. Wtn t ln prossor st, t nn squr rons ontn t ln ntrs. A ownwr sn oprton s prorm on t ln prossor st to trmn t numr o lns ssot wt t snl R-tr no prossor. Ts s sown n Fur 39 s t ount l nt t ln prossor st. T numr o lns n t smnt s tn pss y t rst ln n t lnr orrn to t snl R-tr no prossor (pt n Fur 39 y t rrow rom ln to no ). I t numr o lns n t smnt xs t no pty M, tn t t-prlll R-tr root no must splt nto two l nos n root no (s s smlrly on wt t squntl R-tr). T two nw l nos r nsrt nto t R-tr no prossor st, wt t ormr root no/prossor upt to rt t two nw lrn. N 0 lns Fur 40: Un-su oprton. T son o t two R-tr no splttn lortms s tl n Ston 4.7 s us to slt t splttn xs n oornt vlu. On t splttn xs n t oornt vlu r osn, n un-su oprton s us to onntrt tos ln prossors totr nto two nw smnts, o w wll orrspon to on o t two R-tr l no prossors s pt n Fur 40. For xmpl, ll lns w v mpont tt s lss tn t splt oornt vlu r monotonlly st towr t lt, wl tos wos mpont s rtr tn t splt oornt vlu r monotonlly st towr t rt mon t ln prossors. T rsult o t un-su oprton on t lns n Fur 40 s sown n Fur 4. Not tt t root no o t t-prlll R-tr s ssot wt two smnts n t ln prossor st A (.., (,,,) n (,,,,)), n must tsl suv n n nloous mnnr. Tus, t ts st tr t rst root no splt n ln rstruton, w wll wn up wt two smnts n t ln prossor st, n two rnt R-tr prossor sts N 0 n N ( st orrsponn to no t rnt t n t t-prlll R-tr), s sown n Fur 4. T uln lortm wll now pro trtvly, wt smnt n t ollton o ln prossors trmnn t numr o lns t ontns, n trnsmttn t ount to t ssot R-tr no prossor. I t numr o lns n t smnt xs t no pty M, tn t smnt (n orrsponn R-tr no prossor) wll or to suv. Not tt ts suvson pross my rsult n prossors tt orrspon to ntrnl nos n t t-prlll R-tr splttn tmslvs (wt ts splts possly proptn upwr trou t t-prlll R-tr). T uln pross trmnts wn ll nos n t R-tr no prossor st v t most 3

24 lns N 0 Fur 4: Rsult o t un-su oprton. 3 N N 0 3 lns Fur 4: Complton o root no splt oprton. M l prossors (tr ntrnl R-tr nos or ln prossors) s sown n Fur 43 or our xmpl tst. T t-prlll R-tr root no orrspons to t snl prossor n st N, t l nos r ontn n prossor st N 0, n ll lns r roup n smnts o lnt lss tn or qul to 3 n t ln prossor st (rll tt w r ln wt n orr (; 3) R-tr n our xmpl). Gvn n lns, t t-prlll R-tr uln oprton tks O(lo n) tm, wr o t O(lo n) sts rqurs O(lo n) omputtons ( onstnt numr o sns, lonns, n two sorts). 6 Conluson Anumr o t-prlll prmtv oprtons us n uln sptl t struturs su s t PM qutr, ukt PMR qutr, n t R-tr wr sr s wll s t lortms. Ts prmtvs v n us n t mplmntton o otr t-prlll sptl oprtons su s polyonzton n sptl jon [Hol93, Hol94, Hol94]. It woul ntrstn to s 3 N N 0 lns 3 ount: Fur 43: Brostn t ln ounts to t ssot nos. 4

25 N N N lns Fur 44: Complton o t t-prlll R-tr uln oprton. wtr ts prmtvs r sunt or otr sptl oprtons n wtr mnml sust o oprtons n n. Ts s sujt or utur rsr. Rrns [Alt87] [An83] [Bk90] H. Alt, T. Hrup, K. Mlorn, n F. Prprt. Dtrmnst smulton o lz omputrs on mor rlst ons. SIAM Journl on Computn, 6:808{835, 987. D. P. Anrson. Tnqus or run pn plottn tm. ACM Trnstons on Grps, (3):97{, July 983. N. Bkmnn, H.-P. Krl, R. Snr, n B. Sr. T R*-tr: An nt n roust ss mto or ponts n rtnls. In H. Gr-Moln n H. V. Js, tors, Prons o t 990 ACM SIGMOD Intrntonl Conrn on Mnmnt o Dt, ps 3{33, Atlnt Cty, NJ, My 990. [Bnt75] J. L. Bntly. Multmnsonl nry sr trs us or ssotv srn. Communtons o t ACM, 8(9):509{57, Sptmr 975. [Bst9] [Bs88] [Bll88] [Bll89] [Bll89] [Bll90] T. Bstul. Prlll Prms n Prts or Sptl Dt. PD tss, Unvrsty o Mryln, Coll Prk, MD, Aprl 99. (lso Unvrsty o Mryln Computr Sn Tnl Rport CS-TR-897). S. K. Bskr, A. Rosnl, n A. Y. Wu. Prlll prossn o rons rprsnt y lnr qutrs. Computr Vson, Grps n Im Prossn, 4(3):37{380, Jun 988. G. E. Blllo n J. J. Lttl. Prlll solutons to omtr prolms on t sn mol o omputton. In D. H. Bly, tor, Prons o t 988 Intrntonl Conrn on Prlll Prossn (ICPP), volum 3, ps 8{, St. Crls, IL, Auust 988. G. E. Blllo. Sns s prmtv prlll oprtons. IEEE Trnstons on Computrs, 38():56{538, Novmr 989. (lso Prons o t 987 Intrntonl Conrn on Prlll Prossn, St. Crls, IL, Auust 987). G. E. Blllo. Sn Prmtvs n Prlll Vtor Mols. PD tss, Mssustts Insttut o Tnoloy, Cmr, MA, Otor 989. (lso Lortory or Computr Sn Tnl Rport MIT/LCS/TR-463). G. E. Blllo. Vtor Mols or Dt-Prlll Computn. MIT Prss, Cmr, MA,

26 [Com79] D. Comr. T uqutous B-tr. ACM Computn Survys, ():{37, Jun 979. [Dn9] F. Dn, A. G. Frrr, n A. Ru-Cpln. Ent prlll onstruton n mnpulton o qutrs. In K. So, tor, Prons o t 99 Intrntonl Conrn on Prlll Prossn (ICPP), volum 3, ps 55{6, St. Crls, IL, Auust 99. [DW9] [El85] [Flo87] [Fol90] D. J. DWtt n J. Gry. T utur o prormn ts systms. Communtons o t ACM, 35(6):85{98, Jun 99. S. Elmn n E. Spro. Qutrs n onurrnt Prolo. In D. Droot, tor, Prons o t 985 Intrntonl Conrn on Prlll Prossn (ICPP), ps 544{55, St. Crls, IL, Auust 985. C. Floutsos, T. Slls, n N. Roussopoulos. Anlyss o ojt ornt sptl ss mtos. In U. Dyl n I. Trr, tors, Prons o t 987 ACM SIGMOD Intrntonl Conrn on Mnmnt o Dt, ps 46{439, Sn Frnso, My 987. J. D. Foly, A. vn Dm, S. K. Fnr, n J. F. Hus. Computr Grps Prnpls n Prt. Ason{Wsly, Rn, MA, son ton, 990. [Frn90] W. R. Frnkln n M. Knknll. Prlll ojt-sp n sur rmovl. Computr Grps, 4(4):87{94, Auust 990. (lso Prons o t SIGGRAPH'90 Conrn, Atlnt, Auust 990). [Gutt84] [Hll86] A. Guttmn. R-trs: A ynm nx strutur or sptl srn. In Prons o t 984 ACM SIGMOD Intrntonl Conrn on Mnmnt o Dt, ps 47{57, Boston, Jun 984. W. D. Hlls n G. L. Stl Jr. Dt prlll lortms. Communtons o t ACM, 9():70{83, Dmr 986. [Hol93] E. G. Hol n H. Smt. Dt-prlll R-tr lortms. In Prons o t 993 Intrntonl Conrn on Prlll Prossn (ICPP), ps III{49{53, St. Crls, IL, Auust 993. [Hol94] [Hol94] [Hun89] [Ir93] [Km9] [Ks88] E. G. Hol n H. Smt. Dt-prlll sptl jon lortms. In Prons o t 994 Intrntonl Conrn on Prlll Prossn (ICPP), ps III{7{34, St. Crls, IL, Auust 994. E. G. Hol n H. Smt. Prormn o t-prlll sptl oprtons. In Prons o t Twntt Intrntonl Conrn on Vry Lr Dt Bss (VLDB), ps 56{67, Snto, Cl, Sptmr 994. Y. Hun n A. Rosnl. Prlll prossn o lnr qutrs on ms-onnt omputr. Journl o Prlll n Dstrut Computn, 7:{7, 989. O. H. Irr n M. H. Km. Qutr uln lortms on n SIMD ypru. Journl o Prlll n Dstrut Computn, 8():7{76, My 993. I. Kml n C. Floutsos. Prlll R-trs. In Prons o t 99 ACM SIGMOD Intrntonl Conrn on Mnmnt o Dt, ps 95{04, Sn Do, Jun 99. S. Ks. Optml prlll lortms or qutr prolms. Computr Vson, Grps n Im Prossn, 59(3):8{85, My 994. (lso Prons o t Ft Isrl Symposum on Artl Intlln, Vson, n Pttrn Ronton). 6

27 [Krus85] [Kuk77] [L9] [Mrt86] [M86] [Nn88] [Nss8] C. P. Kruskl, L. Rnolp, n M. Snr. T powr o prlll prx. IEEE Trnstons on Computrs, 34(0):965{968, Novmr 985. D. Kuk. A survy o prlll mn ornzton n prormmn. ACM Computn Survys, 9():9{59, Mr 977. F. T. Lton. Introuton to Prlll Alortms n Artturs. Morn Kumnn, Sn Mto, CA, 99. M. Mrtn, D. M. Crull, n S. S. Iynr. Prlll prossn o qutrs on orzontlly ronurl rttur omputn systm. In Prons o t 986 Intrntonl Conrn on Prlll Prossn (ICPP), ps 895{90, St. Crls, IL, Auust 986. G.-G. M n W. Lu. Prlll prossn or qutr prolms. In Prons o t 986 Intrntonl Conrn on Prlll Prossn (ICPP), ps 45{454, St. Crls, IL, Auust 986. S. K. Nny, R. Moon, n S. Rjopln. Lnr qutr lortms on t ypru. In Prons o t 988 Intrntonl Conrn on Prlll Prossn (ICPP), ps 7{9, St. Crls, IL, Auust 988. D. Nssm n S. Sn. Dt rostn n SIMD omputrs. IEEE Trnstons on Computrs, C-30():0{07, 98. [Nls86] R. C. Nlson n H. Smt. A onsstnt rrl rprsntton or vtor t. Computr Grps, 0(4):97{06, Auust 986. (lso Prons o t SIG- GRAPH'86 Conrn, Dlls, Auust 986). [Nls87] R. C. Nlson n H. Smt. A populton nlyss or rrl t struturs. In U. Dyl n I. Trr, tors, Prons o t 987 ACM SIGMOD Intrntonl Conrn on Mnmnt o Dt, ps 70{77, Sn Frnso, My 987. [Orn8] J. A. Ornstn. Multmnsonl trs us or ssotv srn. Inormton Prossn Lttrs, 4(4):50{57, Jun 98. [Pn90] [Ros83] [Sm85] [Sm90] [Sm90] [Sw80] G. Pno. Sur un our qu rmplt tout un r pln. Mtmts Annln, 36:57{60, 890. A. Rosnl, H. Smt, C. Sr, n R. E. Wr. Applton o rrl t struturs to orpl normton systms: Ps II. Computr Sn TR{37, Unvrsty o Mryln, Coll Prk, MD, Sptmr 983. H. Smt n R. E. Wr. Storn ollton o polyons usn qutrs. ACM Trnstons on Grps, 4(3):8{, July 985. (lso Prons o Computr Vson n Pttrn Ronton 83, Wsnton DC, Jun 983, 7{3; n Unvrsty o Mryln Computr Sn Tnl Rport CS-TR-37). H. Smt. T Dsn n Anlyss o Sptl Dt Struturs. Ason{Wsly, Rn, MA, 990. H. Smt. Appltons o Sptl Dt Struturs: Computr Grps, Im Prossn, n GIS. Ason{Wsly, Rn, MA, 990. J. T. Swrtz. Ultromputrs. ACM Trnstons on Prormmn Lnus n Systms, (4):484{5, Otor 980. [Tmm8] M. Tmmnn. T EXCELL mto or nt omtr ss to t. At Polytn Snnv, 98. (Mtmts n Computr Sn Srs No. 34). 7

Data-Parallel Primitives for Spatial Operations Using PM. Quadtrees* primitives that are used to construct the data. concluding remarks.

Data-Parallel Primitives for Spatial Operations Using PM. Quadtrees* primitives that are used to construct the data. concluding remarks. Dt-rlll rmtvs or Sptl Oprtons Usn M Qutrs* Erk G. Hol Hnn Smt Computr Sn Dprtmnt Computr Sn Dprtmnt Cntr or Automton Rsr Cntr or Automton Rsr Insttut or Avn Computr Sns Insttut or Avn Computr Sns Unvrsty

More information

5/1/2018. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees

5/1/2018. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees /1/018 W usully no strns y ssnn -lnt os to ll rtrs n t lpt (or mpl, 8-t on n ASCII). Howvr, rnt rtrs our wt rnt rquns, w n sv mmory n ru trnsmttl tm y usn vrl-lnt non. T s to ssn sortr os to rtrs tt our

More information

Lecture 20: Minimum Spanning Trees (CLRS 23)

Lecture 20: Minimum Spanning Trees (CLRS 23) Ltur 0: Mnmum Spnnn Trs (CLRS 3) Jun, 00 Grps Lst tm w n (wt) rps (unrt/rt) n ntrou s rp voulry (vrtx,, r, pt, onnt omponnts,... ) W lso suss jny lst n jny mtrx rprsntton W wll us jny lst rprsntton unlss

More information

Weighted Graphs. Weighted graphs may be either directed or undirected.

Weighted Graphs. Weighted graphs may be either directed or undirected. 1 In mny ppltons, o rp s n ssot numrl vlu, ll wt. Usully, t wts r nonntv ntrs. Wt rps my tr rt or unrt. T wt o n s otn rrr to s t "ost" o t. In ppltons, t wt my msur o t lnt o rout, t pty o ln, t nry rqur

More information

The R-Tree. Yufei Tao. ITEE University of Queensland. INFS4205/7205, Uni of Queensland

The R-Tree. Yufei Tao. ITEE University of Queensland. INFS4205/7205, Uni of Queensland Yu To ITEE Unvrsty o Qunsln W wll stuy nw strutur ll t R-tr, w n tout o s mult-mnsonl xtnson o t B-tr. T R-tr supports ntly vrty o qurs (s w wll n out ltr n t ours), n s mplmnt n numrous ts systms. Our

More information

Spanning Trees. BFS, DFS spanning tree Minimum spanning tree. March 28, 2018 Cinda Heeren / Geoffrey Tien 1

Spanning Trees. BFS, DFS spanning tree Minimum spanning tree. March 28, 2018 Cinda Heeren / Geoffrey Tien 1 Spnnn Trs BFS, DFS spnnn tr Mnmum spnnn tr Mr 28, 2018 Cn Hrn / Gory Tn 1 Dpt-rst sr Vsts vrts lon snl pt s r s t n o, n tn ktrks to t rst junton n rsums own notr pt Mr 28, 2018 Cn Hrn / Gory Tn 2 Dpt-rst

More information

Depth First Search. Yufei Tao. Department of Computer Science and Engineering Chinese University of Hong Kong

Depth First Search. Yufei Tao. Department of Computer Science and Engineering Chinese University of Hong Kong Dprtmnt o Computr Sn n Ennrn Cns Unvrsty o Hon Kon W v lry lrn rt rst sr (BFS). Toy, w wll suss ts sstr vrson : t pt rst sr (DFS) lortm. Our susson wll on n ous on rt rps, us t xtnson to unrt rps s strtorwr.

More information

Minimum Spanning Trees (CLRS 23)

Minimum Spanning Trees (CLRS 23) Mnmum Spnnn Trs (CLRS 3) T prolm Rll t nton o spnnn tr: Gvn onnt, unrt rp G = (V, E), sust o s o G su tt ty onnt ll vrts n G n orm no yls s ll spnnn tr (ST) o G. Any unrt, onnt rp s spnnn tr. Atully, rp

More information

(Minimum) Spanning Trees

(Minimum) Spanning Trees (Mnmum) Spnnn Trs Spnnn trs Kruskl's lortm Novmr 23, 2017 Cn Hrn / Gory Tn 1 Spnnn trs Gvn G = V, E, spnnn tr o G s onnt surp o G wt xtly V 1 s mnml sust o s tt onnts ll t vrts o G G = Spnnn trs Novmr

More information

4.1 Interval Scheduling. Chapter 4. Greedy Algorithms. Interval Scheduling: Greedy Algorithms. Interval Scheduling. Interval scheduling.

4.1 Interval Scheduling. Chapter 4. Greedy Algorithms. Interval Scheduling: Greedy Algorithms. Interval Scheduling. Interval scheduling. Cptr 4 4 Intrvl Suln Gry Alortms Sls y Kvn Wyn Copyrt 005 Prson-Ason Wsly All rts rsrv Intrvl Suln Intrvl Suln: Gry Alortms Intrvl suln! Jo strts t s n nss t! Two os omptl ty on't ovrlp! Gol: n mxmum sust

More information

Divided. diamonds. Mimic the look of facets in a bracelet that s deceptively deep RIGHT-ANGLE WEAVE. designed by Peggy Brinkman Matteliano

Divided. diamonds. Mimic the look of facets in a bracelet that s deceptively deep RIGHT-ANGLE WEAVE. designed by Peggy Brinkman Matteliano RIGHT-ANGLE WEAVE Dv mons Mm t look o ts n rlt tt s ptvly p sn y Py Brnkmn Mttlno Dv your mons nto trnls o two or our olors. FCT-SCON0216_BNB66 2012 Klm Pulsn Co. Ts mtrl my not rprou n ny orm wtout prmsson

More information

Lecture II: Minimium Spanning Tree Algorithms

Lecture II: Minimium Spanning Tree Algorithms Ltur II: Mnmum Spnnn Tr Alortms Dr Krn T. Hrly Dprtmnt o Computr Sn Unvrsty Coll Cork Aprl 0 KH (/0/) Ltur II: Mnmum Spnnn Tr Alortms Aprl 0 / 5 Mnmum Spnnn Trs Mnmum Spnnn Trs Spnnn Tr tr orm rom rp s

More information

The University of Sydney MATH 2009

The University of Sydney MATH 2009 T Unvrsty o Syny MATH 2009 APH THEOY Tutorl 7 Solutons 2004 1. Lt t sonnt plnr rp sown. Drw ts ul, n t ul o t ul ( ). Sow tt s sonnt plnr rp, tn s onnt. Du tt ( ) s not somorp to. ( ) A onnt rp s on n

More information

Having a glimpse of some of the possibilities for solutions of linear systems, we move to methods of finding these solutions. The basic idea we shall

Having a glimpse of some of the possibilities for solutions of linear systems, we move to methods of finding these solutions. The basic idea we shall Hvn lps o so o t posslts or solutons o lnr systs, w ov to tos o nn ts solutons. T s w sll us s to try to sply t syst y lntn so o t vrls n so ts qutons. Tus, w rr to t to s lnton. T prry oprton nvolv s

More information

In which direction do compass needles always align? Why?

In which direction do compass needles always align? Why? AQA Trloy Unt 6.7 Mntsm n Eltromntsm - Hr 1 Complt t p ll: Mnt or s typ o or n t s stronst t t o t mnt. Tr r two typs o mnt pol: n. Wrt wt woul ppn twn t pols n o t mnt ntrtons low: Drw t mnt l lns on

More information

Minimum Spanning Trees (CLRS 23)

Minimum Spanning Trees (CLRS 23) Mnmum Spnnn Trs (CLRS 3) T prolm Gvn onnt, unrt rp G = (V, E), sust o s o G su tt ty onnt ll vrts n G n orm no yls s ll spnnn tr (ST) o G. Clm: Any unrt, onnt rp s spnnn tr (n nrl rp my v mny spnnn trs).

More information

Improving Union. Implementation. Union-by-size Code. Union-by-Size Find Analysis. Path Compression! Improving Find find(e)

Improving Union. Implementation. Union-by-size Code. Union-by-Size Find Analysis. Path Compression! Improving Find find(e) POW CSE 36: Dt Struturs Top #10 T Dynm (Equvln) Duo: Unon-y-Sz & Pt Comprsson Wk!! Luk MDowll Summr Qurtr 003 M! ZING Wt s Goo Mz? Mz Construton lortm Gvn: ollton o rooms V Conntons twn t rooms (ntlly

More information

CMSC 451: Lecture 4 Bridges and 2-Edge Connectivity Thursday, Sep 7, 2017

CMSC 451: Lecture 4 Bridges and 2-Edge Connectivity Thursday, Sep 7, 2017 Rn: Not ovr n or rns. CMSC 451: Ltr 4 Brs n 2-E Conntvty Trsy, Sp 7, 2017 Hr-Orr Grp Conntvty: (T ollown mtrl ppls only to nrt rps!) Lt G = (V, E) n onnt nrt rp. W otn ssm tt or rps r onnt, t somtms t

More information

CMPS 2200 Fall Graphs. Carola Wenk. Slides courtesy of Charles Leiserson with changes and additions by Carola Wenk

CMPS 2200 Fall Graphs. Carola Wenk. Slides courtesy of Charles Leiserson with changes and additions by Carola Wenk CMPS 2200 Fll 2017 Grps Crol Wnk Sls ourtsy o Crls Lsrson wt ns n tons y Crol Wnk 10/23/17 CMPS 2200 Intro. to Alortms 1 Grps Dnton. A rt rp (rp) G = (V, E) s n orr pr onsstn o st V o vrts (snulr: vrtx),

More information

2 Trees and Their Applications

2 Trees and Their Applications Trs n Tr Appltons. Proprts o trs.. Crtrzton o trs Dnton. A rp s ll yl (or orst) t ontns no yls. A onnt yl rp s ll tr. Quston. Cn n yl rp v loops or prlll s? Notton. I G = (V, E) s rp n E, tn G wll not

More information

Theorem 1. An undirected graph is a tree if and only if there is a unique simple path between any two of its vertices.

Theorem 1. An undirected graph is a tree if and only if there is a unique simple path between any two of its vertices. Cptr 11: Trs 11.1 - Introuton to Trs Dnton 1 (Tr). A tr s onnt unrt rp wt no sp ruts. Tor 1. An unrt rp s tr n ony tr s unqu sp pt twn ny two o ts vrts. Dnton 2. A root tr s tr n w on vrtx s n snt s t

More information

Closed Monochromatic Bishops Tours

Closed Monochromatic Bishops Tours Cos Monoromt Bsops Tours Jo DMo Dprtmnt o Mtmts n Sttsts Knnsw Stt Unvrsty, Knnsw, Gor, 0, USA mo@nnsw.u My, 00 Astrt In ss, t sop s unqu s t s o to sn oor on t n wt or. Ts ms os tour n w t sop vsts vry

More information

Graph Search (6A) Young Won Lim 5/18/18

Graph Search (6A) Young Won Lim 5/18/18 Grp Sr (6A) Youn Won Lm Copyrt () 2015 2018 Youn W. Lm. Prmon rnt to opy, trut n/or moy t oumnt unr t trm o t GNU Fr Doumntton Ln, Vron 1.2 or ny ltr vron pul y t Fr Sotwr Founton; wt no Invrnt Ston, no

More information

The Constrained Longest Common Subsequence Problem. Rotem.R and Rotem.H

The Constrained Longest Common Subsequence Problem. Rotem.R and Rotem.H T Constrn Lonst Common Susqun Prolm Rotm.R n Rotm.H Prsntton Outln. LCS Alortm Rmnr Uss o LCS Alortm T CLCS Prolm Introuton Motvton For CLCS Alortm T CLCS Prolm Nïv Alortm T CLCS Alortm A Dynm Prormmn

More information

Platform Controls. 1-1 Joystick Controllers. Boom Up/Down Controller Adjustments

Platform Controls. 1-1 Joystick Controllers. Boom Up/Down Controller Adjustments Ston 7 - Rpr Prours Srv Mnul - Son Eton Pltorm Controls 1-1 Joystk Controllrs Mntnn oystk ontrollrs t t propr sttns s ssntl to s mn oprton. Evry oystk ontrollr soul oprt smootly n prov proportonl sp ontrol

More information

CSE 332. Data Structures and Parallelism

CSE 332. Data Structures and Parallelism Am Blnk Ltur 20 Wntr 2017 CSE 332 Dt Struturs n Prlllsm CSE 332: Dt Struturs n Prlllsm Grps 1: Wt s Grp? DFS n BFS LnkLsts r to Trs s Trs r to... 1 Wr W v Bn Essntl ADTs: Lsts, Stks, Quus, Prorty Quus,

More information

CSE 332. Graphs 1: What is a Graph? DFS and BFS. Data Abstractions. CSE 332: Data Abstractions. A Graph is a Thingy... 2

CSE 332. Graphs 1: What is a Graph? DFS and BFS. Data Abstractions. CSE 332: Data Abstractions. A Graph is a Thingy... 2 Am Blnk Ltur 19 Summr 2015 CSE 332: Dt Astrtons CSE 332 Grps 1: Wt s Grp? DFS n BFS Dt Astrtons LnkLsts r to Trs s Trs r to... 1 A Grp s Tny... 2 Wr W v Bn Essntl ADTs: Lsts, Stks, Quus, Prorty Quus, Hps,

More information

Exam 2 Solutions. Jonathan Turner 4/2/2012. CS 542 Advanced Data Structures and Algorithms

Exam 2 Solutions. Jonathan Turner 4/2/2012. CS 542 Advanced Data Structures and Algorithms CS 542 Avn Dt Stutu n Alotm Exm 2 Soluton Jontn Tun 4/2/202. (5 ont) Con n oton on t tton t tutu n w t n t 2 no. Wt t mllt num o no tt t tton t tutu oul ontn. Exln you nw. Sn n mut n you o u t n t, t n

More information

23 Minimum Spanning Trees

23 Minimum Spanning Trees 3 Mnmum Spnnn Trs Eltron rut sns otn n to mk t pns o svrl omponnts ltrlly quvlnt y wrn tm totr. To ntronnt st o n pns, w n us n rrnmnt o n wrs, onntn two pns. O ll su rrnmnts, t on tt uss t lst mount o

More information

COMP 250. Lecture 29. graph traversal. Nov. 15/16, 2017

COMP 250. Lecture 29. graph traversal. Nov. 15/16, 2017 COMP 250 Ltur 29 rp trvrsl Nov. 15/16, 2017 1 Toy Rursv rp trvrsl pt rst Non-rursv rp trvrsl pt rst rt rst 2 Hs up! Tr wr w mstks n t sls or S. 001 or toy s ltur. So you r ollown t ltur rorns n usn ts

More information

Single Source Shortest Paths (with Positive Weights)

Single Source Shortest Paths (with Positive Weights) Snl Sour Sortst Pts (wt Postv Wts) Yuf To ITEE Unvrsty of Qunslnd In ts ltur, w wll rvst t snl sour sortst pt (SSSP) problm. Rll tt w v lrdy lrnd tt t BFS lortm solvs t problm ffntly wn ll t ds v t sm

More information

Strongly connected components. Finding strongly-connected components

Strongly connected components. Finding strongly-connected components Stronly onnt omponnts Fnn stronly-onnt omponnts Tylr Moor stronly onnt omponnt s t mxml sust o rp wt rt pt twn ny two vrts SE 3353, SMU, Dlls, TX Ltur 9 Som sls rt y or pt rom Dr. Kvn Wyn. For mor normton

More information

SAMPLE CSc 340 EXAM QUESTIONS WITH SOLUTIONS: part 2

SAMPLE CSc 340 EXAM QUESTIONS WITH SOLUTIONS: part 2 AMPLE C EXAM UETION WITH OLUTION: prt. It n sown tt l / wr.7888l. I Φ nots orul or pprotng t vlu o tn t n sown tt t trunton rror o ts pproton s o t or or so onstnts ; tt s Not tt / L Φ L.. Φ.. /. /.. Φ..787.

More information

PRECAST APPROACH SLAB NOTES

PRECAST APPROACH SLAB NOTES ULNS TS ULN RWNS RPRSNT TYPL TLS OR T SN N TLN O PRST PPRO SLS. TS STS R NLU TO PROV N XMPL O T RTN LYOUT O TYPL PRST PPRO SL. TWO RNT PPRO SL SYSTMS R SOWN: SUR PPRO SLS: SLS TT R PL WT T TOP SUR T OR

More information

Dental PBRN Study: Reasons for replacement or repair of dental restorations

Dental PBRN Study: Reasons for replacement or repair of dental restorations Dntl PBRN Stuy: Rsons or rplmnt or rpr o ntl rstortons Us ts Dt Collton Form wnvr stuy rstorton s rpl or rpr. For nrollmnt n t ollton you my rpl or rpr up to 4 rstortons, on t sm ptnt, urn snl vst. You

More information

Applications of trees

Applications of trees Trs Apptons o trs Orgnzton rts Attk trs to syst Anyss o tr ntworks Prsng xprssons Trs (rtrv o norton) Don-n strutur Mutstng Dstnton-s orwrng Trnsprnt swts Forwrng ts o prxs t routrs Struturs or nt pntton

More information

MINI POST SERIES BALUSTRADE SYSTEM INSTALLATION GUIDE PRODUCT CODE: MPS-RP

MINI POST SERIES BALUSTRADE SYSTEM INSTALLATION GUIDE PRODUCT CODE: MPS-RP MN POST SRS LUSTR SYSTM NSTLLTON U PROUT O: MPS-RP 0 R0 WLL LN 0 RONT LVTON VW R0 N P 0 T RUR LOK LOT ON LSS. SLON SL TYP. OT SS 000 LSS T 0 00 SRS LSS WT 00/00 (0mm NRMNTS VLL) MX. 000 00-0 (ROMMN) 00

More information

Isomorphism In Kinematic Chains

Isomorphism In Kinematic Chains Intrntonl Journl o Rsr n Ennrn n Sn (IJRES) ISSN (Onln): 0-, ISSN (Prnt): 0- www.rs.or Volum Issu ǁ My. 0 ǁ PP.0- Isomorpsm In Knmt Cns Dr.Al Hsn Asstt.Prossor, Dprtmnt o Mnl Ennrn, F/O- Ennrn & Tnoloy,

More information

learning objectives learn what graphs are in mathematical terms learn how to represent graphs in computers learn about typical graph algorithms

learning objectives learn what graphs are in mathematical terms learn how to represent graphs in computers learn about typical graph algorithms rp loritms lrnin ojtivs loritms your sotwr systm sotwr rwr lrn wt rps r in mtmtil trms lrn ow to rprsnt rps in omputrs lrn out typil rp loritms wy rps? intuitivly, rp is orm y vrtis n s twn vrtis rps r

More information

(4, 2)-choosability of planar graphs with forbidden structures

(4, 2)-choosability of planar graphs with forbidden structures (4, )-ooslty o plnr rps wt orn struturs Znr Brkkyzy 1 Crstopr Cox Ml Dryko 1 Krstn Honson 1 Mot Kumt 1 Brnr Lký 1, Ky Mssrsmt 1 Kvn Moss 1 Ktln Nowk 1 Kvn F. Plmowsk 1 Drrk Stol 1,4 Dmr 11, 015 Astrt All

More information

CSE 332. Graphs 1: What is a Graph? DFS and BFS. Data Abstractions. CSE 332: Data Abstractions. A Graph is a Thingy... 2

CSE 332. Graphs 1: What is a Graph? DFS and BFS. Data Abstractions. CSE 332: Data Abstractions. A Graph is a Thingy... 2 Am Blnk Ltur 0 Autumn 0 CSE 33: Dt Astrtons CSE 33 Grps : Wt s Grp? DFS n BFS Dt Astrtons LnkLsts r to Trs s Trs r to... A Grp s Tny... Wr W v Bn Essntl ADTs: Lsts, Stks, Quus, Prorty Quus, Hps, Vnll Trs,

More information

An Application to Search for High-Priority War Opponent in Spatial Games Using Dynamic Skyline Query

An Application to Search for High-Priority War Opponent in Spatial Games Using Dynamic Skyline Query Intrntonl Journl o Appl Ennrn Rsr ISSN 973-4562 Volum 13, Numr 2 (218) pp. 1496-15 An Applton to Sr or H-Prorty Wr Opponnt n Sptl Gms Usn Qury Jonwn Km Smt Lrl Arts Coll, Smyook Unvrsty, 815 Hwrn-ro, Nowon-u,

More information

MATERIAL SEE BOM ANGLES = 2 FINISH N/A

MATERIAL SEE BOM ANGLES = 2 FINISH N/A 9 NOTS:. SSML N NSPT PR SOP 0-9... NSTLL K STKR N X L STKR TO NS O SROU WT TP. 3. PR-PK LNR RNS WT P (XTRM PRSSUR NL R ) RS OR NNRN PPROV QUVLNT. 4. OLOR TT Y T SLS ORR. RRN T MNS OM OR OMPONNTS ONTNN

More information

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management nrl tr T is init st o on or mor nos suh tht thr is on sint no r, ll th root o T, n th rminin nos r prtition into n isjoint susts T, T,, T n, h o whih is tr, n whos roots r, r,, r n, rsptivly, r hilrn o

More information

Priority Search Trees - Part I

Priority Search Trees - Part I .S. 252 Pro. Rorto Taassa oputatoal otry S., 1992 1993 Ltur 9 at: ar 8, 1993 Sr: a Q ol aro Prorty Sar Trs - Part 1 trouto t last ltur, w loo at trval trs. or trval pot losur prols, ty us lar spa a optal

More information

Tangram Fractions Overview: Students will analyze standard and nonstandard

Tangram Fractions Overview: Students will analyze standard and nonstandard ACTIVITY 1 Mtrils: Stunt opis o tnrm mstrs trnsprnis o tnrm mstrs sissors PROCEDURE Skills: Dsriin n nmin polyons Stuyin onrun Comprin rtions Tnrm Frtions Ovrviw: Stunts will nlyz stnr n nonstnr tnrms

More information

17 Basic Graph Properties

17 Basic Graph Properties Ltur 17: Bs Grp Proprts [Sp 10] O look t t sn y o. Tn t t twnty-svn 8 y 10 olor lossy pturs wt t rls n rrows n prrp on t k o on... n tn look t t sn y o. An tn t t twnty-svn 8 y 10 olor lossy pturs wt t

More information

d e c b a d c b a d e c b a a c a d c c e b

d e c b a d c b a d e c b a a c a d c c e b FLAT PEYOTE STITCH Bin y mkin stoppr -- sw trou n pull it lon t tr until it is out 6 rom t n. Sw trou t in witout splittin t tr. You soul l to sli it up n own t tr ut it will sty in pl wn lt lon. Evn-Count

More information

Distributed Caching of Multi-dimensional Data in Mobile Environments

Distributed Caching of Multi-dimensional Data in Mobile Environments Dstrut Cn o Mut-mnson Dt n Mo Envronmnts Bn Lu Wn-Cn L D Lun L Dprtmnt o Computr Sn Hon Kon Unvrst o Sn n Tnoo Crwtr B, Hon Kon {un, }@s.ust. Dprtmnt o Computr Sn n Ennrn Pnnsvn Stt Unvrst Unvrst Pr, PA

More information

Introduction to Fourier optics. Textbook: Goodman (chapters 2-4) Overview:

Introduction to Fourier optics. Textbook: Goodman (chapters 2-4) Overview: Introuton to ourr opts Ttbook: Goon (ptrs -) Ovrv: nr n nvrnt ssts T ourr trnsor Slr rton rsnl n runor pprotons. . nr ssts n ourr trnsor tutorl (rnr) sst onnts n nput to n output su tt: It s s to b lnr

More information

DOCUMENT STATUS: MINTP0 E-ST5080, BASE, NO DISPLAY VENDOR: 15.5 INCH MATERIAL SEE BOM FINISH REVISION HISTORY ITEM NO. PART NUMBER DESCRIPTION

DOCUMENT STATUS: MINTP0 E-ST5080, BASE, NO DISPLAY VENDOR: 15.5 INCH MATERIAL SEE BOM FINISH REVISION HISTORY ITEM NO. PART NUMBER DESCRIPTION RV T RVSON STORY SRPTON O Y 0-0-0 PROUTON RLS K. N NOTS:. SRL LL NORMTON: a) VOLTS: V b) MPS:.0 c) YLS: N/ d) WTTS: W e) PS: N/ f) PX #: PX. RTTON LOOS: S / / LN R WT SOPROPYL LOLOL PROR TO PLN.. PK M:

More information

Math 166 Week in Review 2 Sections 1.1b, 1.2, 1.3, & 1.4

Math 166 Week in Review 2 Sections 1.1b, 1.2, 1.3, & 1.4 Mt 166 WIR, Sprin 2012, Bnjmin urisp Mt 166 Wk in Rviw 2 Stions 1.1, 1.2, 1.3, & 1.4 1. S t pproprit rions in Vnn irm tt orrspon to o t ollowin sts. () (B ) B () ( ) B B () (B ) B 1 Mt 166 WIR, Sprin 2012,

More information

Fun sheet matching: towards automatic block decomposition for hexahedral meshes

Fun sheet matching: towards automatic block decomposition for hexahedral meshes DOI 10.1007/s00366-010-0207-5 ORIGINAL ARTICLE Fun st mtn: towrs utomt lok omposton or xrl mss Nols Kowlsk Frnk Loux Mttw L. Sttn Stv J. Own Rv: 19 Frury 2010 / Apt: 22 Dmr 2010 Ó Sprnr-Vrl Lonon Lmt 2011

More information

18 Basic Graph Properties

18 Basic Graph Properties O look t t sn y o. Tn t t twnty-svn 8 y 10 olor lossy pturs wt t rls n rrows n prrp on t k o on... n tn look t t sn y o. An tn t t twnty-svn 8 y 10 olor lossy pturs wt t rls n rrows n prrp on t k o on

More information

MAT3707. Tutorial letter 201/1/2017 DISCRETE MATHEMATICS: COMBINATORICS. Semester 1. Department of Mathematical Sciences MAT3707/201/1/2017

MAT3707. Tutorial letter 201/1/2017 DISCRETE MATHEMATICS: COMBINATORICS. Semester 1. Department of Mathematical Sciences MAT3707/201/1/2017 MAT3707/201/1/2017 Tutoril lttr 201/1/2017 DISCRETE MATHEMATICS: COMBINATORICS MAT3707 Smstr 1 Dprtmnt o Mtmtil Sins SOLUTIONS TO ASSIGNMENT 01 BARCODE Din tomorrow. univrsity o sout ri SOLUTIONS TO ASSIGNMENT

More information

One-Dimensional Computational Topology

One-Dimensional Computational Topology Wr rltn so n Stz: Dnn un nur nn, wnn s Sm s Grpn I) ur nn Umsltunsoprton U n BZ-R lrt, II) ur Umrunsoprton wr us r BZ-R ntstt, stllt s Sm nn u r Kullä rlsrrn Grpn r. Dmt st n Gusss Prolm ür n llmnstn Grpn

More information

DOCUMENT STATUS: RELEASE

DOCUMENT STATUS: RELEASE RVSON STORY RV T SRPTON O Y 0-4-0 RLS OR PROUTON 5 MM -04-0 NS TRU PLOT PROUTON -- S O O OR TLS 30 MM 03-3-0 3-044 N 3-45, TS S T TON O PROTTV RM OVR. 3 05--0 LT 3-004, NOT, 3-050 3 0//00 UPT ST ROM SN,

More information

An Introduction to Clique Minimal Separator Decomposition

An Introduction to Clique Minimal Separator Decomposition Alortms 2010, 3, 197-215; o:10.3390/3020197 Rvw OPEN ACCESS lortms ISSN 1999-4893 www.mp.om/ournl/lortms An Introuton to Clqu Mnml Sprtor Domposton Ann Brry 1,, Romn Poorln 1 n Gnvèv Smont 2 1 LIMOS UMR

More information

kd-trees Idea: Each level of the tree compares against 1 dimension. Let s us have only two children at each node (instead of 2 d )

kd-trees Idea: Each level of the tree compares against 1 dimension. Let s us have only two children at each node (instead of 2 d ) k-trs CMSC 420 k-trs Invnt n 1970s Jon Bntl Nm ornll mnt 3-trs, 4-trs, t wr k ws t # o mnsons Now, popl s k-tr o mnson I: E lvl o t tr omprs nst 1 mnson. Lt s us v onl two lrn t no (nst o 2 ) k-trs E lvl

More information

A New Interface to Render Graphs Using Rgraphviz

A New Interface to Render Graphs Using Rgraphviz A Nw Intr to Rnr Grps Usn Rrpvz Florn Hn Otor 30, 2017 Contnts 1 Ovrvw 1 2 Introuton 1 3 Dult rnrn prmtrs 3 3.1 Dult no prmtrs....................... 4 3.2 Dult prmtrs....................... 6 3.3 Dult

More information

23 Minimum Spanning Trees

23 Minimum Spanning Trees 3 Mnmum Spnnn Trs Eltron rut sns otn n to mk t pns o svrl omponnts ltrlly quvlnt y wrn tm totr. To ntronnt st o n pns, w n us n rrnmnt o n wrs, onntn two pns. O ll su rrnmnts, t on tt uss t lst mount o

More information

a ( b ) ( a ) a ( c ) ( d )

a ( b ) ( a ) a ( c ) ( d ) Lzy Complton o Prtl Orr to t Smllst Ltt Krll Brtt 1, Ml Morvn 1, Lour Nourn 2 1 LITP/IBP - Unvrst Dns Drot Prs 7 Cs 7014 2, pl Jussu 75256 Prs Cx 05 Frn. ml: (rtt,morvn)@ltp.p.r. 2 Dprtmnt 'Inormtqu Fonmntl

More information

Distributed Memory Allocation Technique for Synchronous Dataflow Graphs

Distributed Memory Allocation Technique for Synchronous Dataflow Graphs Dstrut Mmory Alloton Tnqu or Synronous Dtlow Grps Krol Dsnos, Mxm Plt, Jn-Frnços Nzn, Sln Ar To t ts vrson: Krol Dsnos, Mxm Plt, Jn-Frnços Nzn, Sln Ar. Dstrut Mmory Alloton Tnqu or Synronous Dtlow Grps.

More information

A Simple Method for Identifying Compelled Edges in DAGs

A Simple Method for Identifying Compelled Edges in DAGs A Smpl Mto or Intyn Compll Es n DAGs S.K.M. Won n D. Wu Dprtmnt o Computr Sn Unvrsty o Rn Rn Ssktwn Cn S4S 0A2 Eml: {won, nwu}@s.urn. Astrt Intyn ompll s s mportnt n lrnn t strutur (.., t DAG) o Bysn ntwork.

More information

Designing A Concrete Arch Bridge

Designing A Concrete Arch Bridge This is th mous Shwnh ri in Switzrln, sin y Rort Millrt in 1933. It spns 37.4 mtrs (122 t) n ws sin usin th sm rphil mths tht will monstrt in this lsson. To pro with this lsson, lik on th Nxt utton hr

More information

Phylogenetic Tree Inferences Using Quartet Splits. Kevin Michael Hathcock. Bachelor of Science Lenoir-Rhyne University 2010

Phylogenetic Tree Inferences Using Quartet Splits. Kevin Michael Hathcock. Bachelor of Science Lenoir-Rhyne University 2010 Pylont Tr Inrns Usn Qurtt Splts By Kvn Ml Htok Blor o Sn Lnor-Ryn Unvrsty 2010 Sumtt n Prtl Fulllmnt o t Rqurmnts or t Dr o Mstr o Sn n Mtmts Coll o Arts n Sns Unvrsty o Sout Croln 2012 Apt y: Év Czrk,

More information

On Hamiltonian Tetrahedralizations Of Convex Polyhedra

On Hamiltonian Tetrahedralizations Of Convex Polyhedra O Ht Ttrrzts O Cvx Pyr Frs C 1 Q-Hu D 2 C A W 3 1 Dprtt Cputr S T Uvrsty H K, H K, C. E: @s.u. 2 R & TV Trsss Ctr, Hu, C. E: q@163.t 3 Dprtt Cputr S, Mr Uvrsty Nwu St. J s, Nwu, C A1B 35. E: w@r.s.u. Astrt

More information

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology!

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology! Outlin Computr Sin 331, Spnnin, n Surphs Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #30 1 Introution 2 3 Dinition 4 Spnnin 5 6 Mik Joson (Univrsity o Clry) Computr Sin 331 Ltur #30 1 / 20 Mik

More information

16.unified Introduction to Computers and Programming. SOLUTIONS to Examination 4/30/04 9:05am - 10:00am

16.unified Introduction to Computers and Programming. SOLUTIONS to Examination 4/30/04 9:05am - 10:00am 16.unii Introution to Computrs n Prormmin SOLUTIONS to Exmintion /30/0 9:05m - 10:00m Pro. I. Kristin Lunqvist Sprin 00 Grin Stion: Qustion 1 (5) Qustion (15) Qustion 3 (10) Qustion (35) Qustion 5 (10)

More information

Power-Aware Scheduling under Timing Constraints for Mission-Critical Embedded Systems

Power-Aware Scheduling under Timing Constraints for Mission-Critical Embedded Systems owr-wr Suln unr Tmn onstrnts or Msson-rtl Em Systms Jnn Lu, H. ou, Nr rz, F Kur Dpt. o Eltrl & omputr Ennrn Unvrsty o lorn Irvn, 92697-262 US jnnl, ou, nr, kur@.u.u Dpt. o Eltrl & omputr Ennrn Unvrsty

More information

L.3922 M.C. L.3922 M.C. L.2996 M.C. L.3909 M.C. L.5632 M.C. L M.C. L.5632 M.C. L M.C. DRIVE STAR NORTH STAR NORTH NORTH DRIVE

L.3922 M.C. L.3922 M.C. L.2996 M.C. L.3909 M.C. L.5632 M.C. L M.C. L.5632 M.C. L M.C. DRIVE STAR NORTH STAR NORTH NORTH DRIVE N URY T NORTON PROV N RRONOUS NORTON NVRTNTY PROV. SPY S NY TY OR UT T TY RY OS NOT URNT T S TT T NORTON PROV S ORRT, NSR S POSS, VRY ORT S N ON N T S T TY RY. TS NORTON S N OP RO RORS RT SU "" YW No.

More information

CHELOURANYAN CALENDAR FOR YEAR 3335 YEAR OF SAI RHAVË

CHELOURANYAN CALENDAR FOR YEAR 3335 YEAR OF SAI RHAVË CHELOURANYAN CALENDAR FOR YEAR YEAR OF SAI RHAVË I tou woust n unon wt our Motr, now tt tou st nvr t Hr. I tou woust sp t v o mttr, now tt tr s no mttr n no v. ~Cry Mry KEY TO CALENDAR T Dys o t W In t

More information

CS September 2018

CS September 2018 Loil los Distriut Systms 06. Loil los Assin squn numrs to msss All ooprtin prosss n r on orr o vnts vs. physil los: rport tim o y Assum no ntrl tim sour Eh systm mintins its own lol lo No totl orrin o

More information

Graphs Depth First Search

Graphs Depth First Search Grp Dpt Frt Sr SFO 337 LAX 1843 1743 1233 802 DFW ORD - 1 - Grp Sr Aort - 2 - Outo Ø By unrtnn t tur, you ou to: q L rp orn to t orr n w vrt r ovr, xpor ro n n n pt-rt r. q Cy o t pt-rt r tr,, orwr n ro

More information

Planar convex hulls (I)

Planar convex hulls (I) Covx Hu Covxty Gv st P o ots 2D, tr ovx u s t sst ovx oyo tt ots ots o P A oyo P s ovx or y, P, t st s try P. Pr ovx us (I) Coutto Gotry [s 3250] Lur To Bowo Co ovx o-ovx 1 2 3 Covx Hu Covx Hu Covx Hu

More information

Grade 7/8 Math Circles March 4/5, Graph Theory I- Solutions

Grade 7/8 Math Circles March 4/5, Graph Theory I- Solutions ulty o Mtmtis Wtrloo, Ontrio N ntr or ution in Mtmtis n omputin r / Mt irls Mr /, 0 rp Tory - Solutions * inits lln qustion. Tr t ollowin wlks on t rp low. or on, stt wtr it is pt? ow o you know? () n

More information

ELECTRONIC SUPPLEMENTARY INFORMATION

ELECTRONIC SUPPLEMENTARY INFORMATION Elctronc Supplmntry Mtrl (ESI) or Polymr Cmstry. Ts ournl s T Royl Socty o Cmstry 2015 ELECTRONIC SUPPLEMENTARY INFORMATION Poly(lyln tcont)s An ntrstn clss o polystrs wt proclly loct xo-cn oul ons suscptl

More information

Face Detection and Recognition. Linear Algebra and Face Recognition. Face Recognition. Face Recognition. Dimension reduction

Face Detection and Recognition. Linear Algebra and Face Recognition. Face Recognition. Face Recognition. Dimension reduction F Dtto Roto Lr Alr F Roto C Y I Ursty O solto: tto o l trs s s ys os ot. Dlt to t to ltpl ws. F Roto Aotr ppro: ort y rry s tor o so E.. 56 56 > pot 6556- stol sp A st o s t ps to ollto o pots ts sp. F

More information

MATERIAL SEE BOM ANGLES = 2 > 2000 DATE MEDIUM FINISH

MATERIAL SEE BOM ANGLES = 2 > 2000 DATE MEDIUM FINISH NOTS:. LN MTN SUR WT NTUR/SOPROPYL LOOL PROR TO RN L OR LOO. PPLY LOTT 4 ON TRS. TORQU TO. Nm / 00 lb-in 4. TORQU TO 45-50 Nm / - lb-ft 5. TORQU TO Nm / 4.5 lb-ft. TORQU TO 0 Nm / lb-in. TORQU TO 5.5 Nm

More information

A Gentle Introduction to Matroid Algorithmics

A Gentle Introduction to Matroid Algorithmics A Gntl Introuton to Mtro Alortms Mtts F. Stllmnn Aprl, 06 Mtro xoms T trm mtro ws rst us n 9 y Hsslr Wtny []. ovrvw oms rom t txtooks o Lwlr [] n Wls []. Most o t mtrl n ts A mtro s n y st o xoms wt rspt

More information

OpenMx Matrices and Operators

OpenMx Matrices and Operators OpnMx Mtris n Oprtors Sr Mln Mtris: t uilin loks Mny typs? Dnots r lmnt mxmtrix( typ= Zro", nrow=, nol=, nm="" ) mxmtrix( typ= Unit", nrow=, nol=, nm="" ) mxmtrix( typ= Int", nrow=, nol=, nm="" ) mxmtrix(

More information

Outline. 1 Introduction. 2 Min-Cost Spanning Trees. 4 Example

Outline. 1 Introduction. 2 Min-Cost Spanning Trees. 4 Example Outlin Computr Sin 33 Computtion o Minimum-Cost Spnnin Trs Prim's Alorithm Introution Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #33 3 Alorithm Gnrl Constrution Mik Joson (Univrsity o Clry)

More information

CS 103 BFS Alorithm. Mark Redekopp

CS 103 BFS Alorithm. Mark Redekopp CS 3 BFS Aloritm Mrk Rkopp Brt-First Sr (BFS) HIGHLIGHTED ALGORITHM 3 Pt Plnnin W'v sn BFS in t ontxt o inin t sortst pt trou mz? S?? 4 Pt Plnnin W xplor t 4 niors s on irtion 3 3 3 S 3 3 3 3 3 F I you

More information

Physics 222 Midterm, Form: A

Physics 222 Midterm, Form: A Pysis 222 Mitrm, Form: A Nm: Dt: Hr r som usul onstnts. 1 4πɛ 0 = 9 10 9 Nm 2 /C 2 µ0 4π = 1 10 7 tsl s/c = 1.6 10 19 C Qustions 1 5: A ipol onsistin o two r point-lik prtils wit q = 1 µc, sprt y istn

More information

Stronger Virtual Connections in Hex

Stronger Virtual Connections in Hex IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, VOL 7, NO 2, JUNE 2015, PAGES 156-166 156 Stronr Vrtul Conntons n Hx Ju Pwlwz n Ryn Hywr n Plp Hnrson n Bror Arnson Astrt For onnton ms

More information

1 Introduction to Modulo 7 Arithmetic

1 Introduction to Modulo 7 Arithmetic 1 Introution to Moulo 7 Arithmti Bor w try our hn t solvin som hr Moulr KnKns, lt s tk los look t on moulr rithmti, mo 7 rithmti. You ll s in this sminr tht rithmti moulo prim is quit irnt rom th ons w

More information

Graph Search Algorithms

Graph Search Algorithms Grp Sr Aortms 1 Grp 2 No ~ ty or omputr E ~ ro or t Unrt or Drt A surprsny r numr o omputton proms n xprss s rp proms. 3 Drt n Unrt Grps () A rt rp G = (V, E), wr V = {1,2,3,4,5,6} n E = {(1,2), (2,2),

More information

DOCUMENT STATUS: LA-S5302-XXXXS LA, SSS, TRICEPS EXTENSION VERY

DOCUMENT STATUS: LA-S5302-XXXXS LA, SSS, TRICEPS EXTENSION VERY RVSON STORY RV T SRPTON O Y //0 RLS OR PROUTON T LN MR ----- L /0/0 UPT SN N OMPONNTS US: S 3-03 (*N TWO PLS ONLY) WS 3-5, PRT 3-00 TO SSMLY. T OLLOWN UPT: 3-30, 3-403, 3-403, 3-40, 3-45, 3-4, 3-5. 30

More information

Catalytic S N Ar of Unactivated Aryl Chlorides ESI

Catalytic S N Ar of Unactivated Aryl Chlorides ESI Eltron Supplmntry Mtrl (ESI) or CmComm. Ts journl s T Royl Soty o Cmstry 2014 Ctlyt S Ar o Untvt Aryl Clors ESI Tl o Contnts 1. Prour n Full Tl o Contons - Prour S1 - Intl solvnt srn (no tlyst) - Solvnt

More information

Constructive Geometric Constraint Solving

Constructive Geometric Constraint Solving Construtiv Gomtri Constrint Solving Antoni Soto i Rir Dprtmnt Llngutgs i Sistms Inormàtis Univrsitt Politèni Ctluny Brlon, Sptmr 2002 CGCS p.1/37 Prliminris CGCS p.2/37 Gomtri onstrint prolm C 2 D L BC

More information

New Biomaterials from Renewable Resources - Amphiphilic Block Copolymers from δ-decalactone. Figure S4 DSC plot of Propargyl PDL...

New Biomaterials from Renewable Resources - Amphiphilic Block Copolymers from δ-decalactone. Figure S4 DSC plot of Propargyl PDL... Eltron Supplmntry Mtrl (ESI) or Polymr Cmstry. Ts ournl s T Royl Soty o Cmstry 2015 Polymr Cmstry RSCPulsng Supportng Inormton Nw Bomtrls rom Rnwl Rsours - Amppl Blo Copolymrs rom δ-dlton Kulp K. Bnsl,

More information

EFFICIENT EXTRACTION OF CLOSED MOTIVIC PATTERNS IN MULTI-DIMENSIONAL SYMBOLIC REPRESENTATIONS OF MUSIC

EFFICIENT EXTRACTION OF CLOSED MOTIVIC PATTERNS IN MULTI-DIMENSIONAL SYMBOLIC REPRESENTATIONS OF MUSIC EFFICIENT EXTRACTION OF CLOSED MOTIVIC PATTERNS IN MULTI-DIMENSIONAL SYMBOLIC REPRESENTATIONS OF MUSIC Olvr Lrtllot Unvrsty o Jyväskylä Dprtmnt o Mus ABSTRACT In ts ppr, w prsnt n nt mol or sovrn rpt pttrns

More information

Outline. Computer Science 331. Computation of Min-Cost Spanning Trees. Costs of Spanning Trees in Weighted Graphs

Outline. Computer Science 331. Computation of Min-Cost Spanning Trees. Costs of Spanning Trees in Weighted Graphs Outlin Computr Sin 33 Computtion o Minimum-Cost Spnnin Trs Prim s Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #34 Introution Min-Cost Spnnin Trs 3 Gnrl Constrution 4 5 Trmintion n Eiiny 6 Aitionl

More information

Designing A Uniformly Loaded Arch Or Cable

Designing A Uniformly Loaded Arch Or Cable Dsinin A Unirmy Ar Or C T pr wit tis ssn, i n t Nxt uttn r r t t tp ny p. Wn yu r n wit tis ssn, i n t Cntnts uttn r r t t tp ny p t rturn t t ist ssns. Tis is t Mx Eyt Bri in Stuttrt, Grmny, sin y Si

More information

A Scalable Double In-memory Checkpoint and Restart Scheme towards Exascale

A Scalable Double In-memory Checkpoint and Restart Scheme towards Exascale A Sll Doul In-mmory Ckpont n Rstrt Sm towrs Exsl Gnn Zn, Xn N, Lxmknt V. Klé Dprtmnt o Computr Sn Unvrsty o Illnos t Urn-Cmpn Urn, IL 6181, USA E-ml: {zn, xnn2, kl}@llnos.u Astrt As t sz o supromputrs

More information

Instruction Scheduling, Register Allocation, Partial Redundancy Removal

Instruction Scheduling, Register Allocation, Partial Redundancy Removal CSC 255/455 Softwr Anlyss n Improvmnt Instruton Suln, Rstr Alloton, Prtl Runny Rmovl Lol Instruton Suln A Prmr for L 3 Comp 412 COMP 412 FALL 2008 Instrutor: Cn Dn Copyrt 2008, Kt D. Coopr & Ln Torzon,

More information

B ADDED BADGE PN , CHANGED TO C SIZE FOR ASSY, ADDED NOTES DN J DETAIL A SCALE 1 : INCH MATERIAL

B ADDED BADGE PN , CHANGED TO C SIZE FOR ASSY, ADDED NOTES DN J DETAIL A SCALE 1 : INCH MATERIAL 0 RVSONS RV. T SRPTON O Y 0--0 PROUTON RLS N 0--0 PN 00-0, N TO SZ OR SSY, NOTS N TL SL :. N TM NO. PRT NUMR SRPTON QTY. NOT 00-0, PROUT, P-ST 0 NOTS:. SRL LL NORMTON: a) VOLTS: V b) MPS:.0 c) YLS: N/

More information

EE1000 Project 4 Digital Volt Meter

EE1000 Project 4 Digital Volt Meter Ovrviw EE1000 Projt 4 Diitl Volt Mtr In this projt, w mk vi tht n msur volts in th rn o 0 to 4 Volts with on iit o ury. Th input is n nlo volt n th output is sinl 7-smnt iit tht tlls us wht tht input s

More information

RMMP Vianu 2013 Problema 1

RMMP Vianu 2013 Problema 1 RMMP Vnu Probl Dl DAVIDSCU Arn DAFINI sk. Knt nrgy o t r. Soluton Fgur Clulul ontulu nrţ nsty o wl trl ( t lngt o wl s ) s ( ) Consrng t lntry prs ng t ss y t lntry wt rspt o wl s s y r J ( ) wt y r (

More information

CSE 373: More on graphs; DFS and BFS. Michael Lee Wednesday, Feb 14, 2018

CSE 373: More on graphs; DFS and BFS. Michael Lee Wednesday, Feb 14, 2018 CSE 373: Mor on grphs; DFS n BFS Mihl L Wnsy, F 14, 2018 1 Wrmup Wrmup: Disuss with your nighor: Rmin your nighor: wht is simpl grph? Suppos w hv simpl, irt grph with x nos. Wht is th mximum numr of gs

More information