Recall from Last Time: Disjoint Set ADT

Size: px
Start display at page:

Download "Recall from Last Time: Disjoint Set ADT"

Transcription

1 Ltur 21: Unon n Fn twn Up-Trs Toy s An: Plntn n rown orst o Up-Trs Unon-n n Fn-n Extn xmpl Implmntn Unon/Fn Smrt Unon n Fn Unon-y-sz/t n Pt Comprsson Run Tm Anlyss s tou s t ts! Covr n Cptr 8 o t txtook Rll rom Lst Tm: Dsjont St ADT Stors N unqu lmnts. Two oprtons: Fn: Gvn n lmnt, rturn t nm o ts quvln lss (ts st) Unon: Gvn t nms o two quvln lsss, mr tm nto on lss Exmpl: Fn(4) Intl Clsss = {1,4,8, {2,3, 8 {6, {7, {10,9,5 Nm o quv. lss unrln Unon(3,6) {1,4,8 {10,5,9 {6 {7 {2,3,6 {2,3 Som o t mtrl on ts sls r ourtsy o: S. Wolmn, CSE 326, Up-Tr Dt Strutur or Dsjont Sts Nt mplmntton trk or Up-Trs E quvln lss (or st) s n up-tr wt ts root s ts rprsnttv mmr (= lss nm) All mmrs o vn st r nos n tt st s uptr Hs tl mps nput t to no.. nput strn! ntr nx NULL NULL NULL {,,,, {, { Up-trs r usully not nry! 3 Forst o up-trs n sly stor n n rry (ll t up ) I no nms r ntrs or rtrs, n us vry smpl, prt s unton: Hs(X) = X up[x]= prnt o X; = 0 root Arry up: 0 1 () 2 () 3 () 4 () 5 () 6 () 7 () 8 () - NULL NULL NULL

2 Exmpl o Fn Fn: Just trvrs to t root! Exmpl o Unon Unon: Just n on root rom t otr! Runtm =? Fn() = Fn() = Runtm =? Now: Fn() = Fn() = Unon(,) 0 1 () 2 () 3 () 4 () 5 () 6 () 7 () () 2 () 3 () 4 () 5 () 6 () 7 () 8 Arry up: Arry up: Cn (rom 0) to pont to (= 3) 6 A mor tl xmpl A mor tl xmpl Intl Sts: Unon(,) Unon(,) 7 8

3 A mor tl xmpl A mor tl xmpl Unon(,) But (you sy) n r not roots! My llow n som mplmnttons o Fn rst to t roots Sn Fn() = Fn(), unon lry on! Unon(,) But: wl w r nn, oul w o somtn to sp up Fn() nxt tm? (ol tt tout!) 9 10 A mor tl xmpl (ontnu) A mor tl xmpl Unon(,) Unon(,) 11 12

4 A mor tl xmpl Implmntton o Fn n Unon Unon(,) nt Fn(nt X, DsjSt up) { // Assums X = Hs(X_Elmnt) // X_Elmnt oul str/r t. (up[x] <= 0) // Root rturn X; //Rturn root = st nm ls //Fn prnt rturn Fn(up[X], up); vo Unon(DsjSt up, nt X, nt Y) { //Mk sur X, Y r //roots ssrt(up[x] == 0); ssrt(up[y] == 0); up[y] = X; Runtm o Fn: O(mx t) Runtm o Unon: O(1) Ht pns on prvous Unons!Bst s: 1-2, 1-3, 1-4, O(1)!Worst s: 2-1, 3-2, 4-3, O(N) Cn w o ttr? Lt s look k t our xmpl Spn Up Unon/Fn: Unon-y-Sz Unon(,) For M Fns n N-1 Unons, worst s tm s O(MN+N) Cn w sp tns up y n lvr out rown our up-trs? I: In Unon, lwys mk root o lrr tr t nw root Wy? Mnmzs t o t nw up-tr Coulwottrjoon ts Unon? Wt ppn to? Unon(,) Unon-y-Sz! 15 16

5 Trk or Storn Sz Inormton Inst o storn 0 n root, stor up-tr sz s ntv vlu n root no Wy not postv vlu? Woul not know rry ntry s sz or prnt pontr Arry up: NULL NULL NULL 0 1 () 2 () 3 () 4 () 5 () 6 () 7 () 8 () Unon-y-Sz Co vo Unon(DsjSt up, nt X, nt Y) { //X, Y r roots //ontnn (-sz) o up-trs ssrt(up[x] < 0); ssrt(up[y] < 0); (-up[x] > -up[y]) { //upt sz o X n root o Y up[x] += up[y]; up[y] = X; ls { //sz o X < sz o Y up[y] += up[x]; up[x] = Y; Nw run tm o Unon =? Nw run tm o Fn =? 18 Unon-y-Sz: Anlyss Unon-y-Ht Fns r O(mx up-tr t) or orst o up-trs ontnn N nos Numr o nos n n up-tr o t usn unon-y-sz s 2 Bs s: =0,trs2 0 = 1 no Inuton ypotss: Assumtruor< Pk up-tr wt mx t Tn, 2 mx t N mx t lo N Fn tks O(lo N) Inuton Stp: Nw tr o t ws orm v unon o two trs o t -1 E tr tn s 2-1 nos y t nuton ypotss So, totl nos =2! Tru or ll Txtook srs ltrntv strty o Unon-y-t Kp trk o t o up-tr n t root nos Unon mks root o up-tr wt rtr t t nw root Sm rsults n smlr mplmntton s Unon-y-Sz Fn s O(lo N) n Unon s O(1) 19 20

6 Spn Up Fn: Pt Comprsson I w o M Fns on sm lmnt! O(M lo N) tm Cn w moy Fn to v s-ts so tt nxt Fn wll str? A P.C. xmpl wt mor mt Fn() Pt Comprsson: Pont vrytn lon pt o Fn to root Rus t o ntr ss pt to 1: Fns t str! Déjà vu? I smlr to t on n your ol rn sply tr Fn() Pt omprsson! How to P.C. Pt Comprsson Co How to P.C. Pt Comprsson Co nt Fn(nt X, DsjSt up) { // Assums X = Hs(X_Elmnt) // X_Elmnt oul str/r t. nt Fn(nt X, DsjSt up) { // Assums X = Hs(X_Elmnt) // X_Elmnt oul str/r t. (up[x] <= 0) // Root rturn X; //Rturn root = st nm ls //Fn prnt rturn up[x] = Fn(up[X], up); Mk ll nos lon ss pt pont to root (up[x] <= 0) // Root rturn X; //Rturn root = st nm ls //Fn prnt rturn up[x] = Fn(up[X], up); Collpsnttry pontn to root Trvl moton o ornl Fn Nw runnn tm o Fn =? Fn stll tks O(mx up-tr t) worst s But wt ppns to t tr ts ovr tm? Wt s t mortz runtmofnwomfns? 23 24

7 Anlyss o P.C. wt Unon-y-Sz R. E. Trjn (o t up-trs m) sow tt: Wn ot P.C. n Unon-y-Sz r us, t worst s run tm or squn o M oprtons (Unons or Fns) s Θ(M α(m,n)) Wt s α(m,n)? α(m,n) s t nvrs o Akrmnn s unton Wt s Akrmnn s unton? Drsson: Tm slow-rown untons How st os lo N row? lo N = 4 or N = 16 = 2 4 Grows qut slowly Lt lo (k) N = lo (lo (lo (lo N))) (k los) Lt lo* N = mnmum k su tt lo (k) N 1 How st os lo * Nrow? lo * N = 4 or N = = Grows vry slowly Akrmnn rt rlly xplosv unton A(, j) wos nvrs α(m, N) rows vry, vry slowly (slowr tn lo * N) Howslowosα(M, N) row? α(m, N) = 4 or M ( N) r lrr tn t numr o toms n t unvrs (2 300 )!! Anlyss o P.C. wt Unon-y-Sz Summry o Dsjont St n Unon/Fn R. E. Trjn (o t up-trs m) sow tt: Wn ot P.C. n Unon-y-Sz r us, t worst s run tm or squn o M oprtons (Unons or Fns) s Θ(M α(m,n)) α(m, N) 4 or ll prtl os o M n N Txtook provs wkr rsult o O(M lo* N) tm 7 ps n 8 Lmms! (Ck t out ut no n to know t proo) Amortz run tm pr oprton = totl tm/(# oprtons) = Θ(M α(m,n))/m = Θ(α(M,N)) Θ(1) or ll prtl purposs (onstnt tm!) 27 Dsjont St t strutur rss n mny ppltons wr ojts o ntrst ll nto rnt quvln lsss or sts Cts on mp, ltrl omponnts on p, omputrs n ntwork, popl rlt to otr y loo, t. Two mn oprtons: Unon o two lsss n Fn lss nm or vn lmnt Up-Tr t strutur llows nt rry mplmntton Unons tk O(1) worst s tm, Fns n tk O(N) Unon-y-Sz rus worst s tm or Fn to O(lo N) Unon-y-Sz plus Pt Comprsson llows urtr spup Any squn o M Unon/Fn oprtons rsults n O(1) mortz tm pr oprton (or ll prtl purposs) 28

8 Nxt Clss: CSE 373 ts rp (Alo-rytms on Grps) To Do: Fns Homwork #4 (u nxt lss) Fns rn ptr 8 Strt rn ptr 9 29

Reading. Minimum Spanning Trees. Outline. A File Sharing Problem. A Kevin Bacon Problem. Spanning Trees. Section 9.6

Reading. Minimum Spanning Trees. Outline. A File Sharing Problem. A Kevin Bacon Problem. Spanning Trees. Section 9.6 Rin Stion 9.6 Minimum Spnnin Trs Outlin Minimum Spnnin Trs Prim s Alorithm Kruskl s Alorithm Extr:Distriut Shortst-Pth Alorithms A Fil Shrin Prolm Sy unh o usrs wnt to istriut il monst thmslvs. Btwn h

More information

Uses for Binary Trees -- Binary Search Trees

Uses for Binary Trees -- Binary Search Trees CS122 Algorithms n Dt Struturs MW 11:00 m 12:15 pm, MSEC 101 Instrutor: Xio Qin Ltur 10: Binry Srh Trs n Binry Exprssion Trs Uss or Binry Trs Binry Srh Trs n Us or storing n rtriving inormtion n Insrt,

More information

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

4.1 Interval Scheduling. Chapter 4. Greedy Algorithms. Interval Scheduling. Interval Scheduling: Greedy Algorithms 1 ptr 4 41 Intrvl Suln ry lortms Sls y Kvn Wyn opyrt 5 Prson-son Wsly ll rts rsrv Intrvl Suln Intrvl Suln: ry lortms Intrvl suln Jo strts t s n nss t Two os omptl ty on't ovrlp ol: n mxmum sust o mutully

More information

PRESENTED TO. Data Leakage Worldwide: The Effectiveness of Corporate Security Policies

PRESENTED TO. Data Leakage Worldwide: The Effectiveness of Corporate Security Policies PRSNTD TO Dt Lk Worlw: T tvnss o Corport Surty Pols UUST 2008 Ovrvw Rsr Otvs Cso ontrt nst xprss to xut n ntrntonl survy wt ous on t ollown otvs: xplor mploy us o ompny vs, nlun ommunton srvs n vs us,

More information

MPLS FOR MISSION-CRITICAL MICROWAVE NETWORKS BUILDING A HIGHLY RESILIENT MICROWAVE NETWORK WITH MULTI-RING TOPOLOGY

MPLS FOR MISSION-CRITICAL MICROWAVE NETWORKS BUILDING A HIGHLY RESILIENT MICROWAVE NETWORK WITH MULTI-RING TOPOLOGY MPLS FOR MISSION-CRITICAL MICROWAVE NETWORKS BUILDING A HIGHLY RESILIENT MICROWAVE NETWORK WITH MULTI-RING TOPOLOGY TECHNICAL WHITE PAPER H rslny n srv vllty r ky sn onsrtons wn uln msson-rtl mrowv ntworks.

More information

Victims Compensation Claim Status of All Pending Claims and Claims Decided Within the Last Three Years

Victims Compensation Claim Status of All Pending Claims and Claims Decided Within the Last Three Years Claim#:021914-174 Initials: J.T. Last4SSN: 6996 DOB: 5/3/1970 Crime Date: 4/30/2013 Status: Claim is currently under review. Decision expected within 7 days Claim#:041715-334 Initials: M.S. Last4SSN: 2957

More information

A simple algorithm to generate the minimal separators and the maximal cliques of a chordal graph

A simple algorithm to generate the minimal separators and the maximal cliques of a chordal graph A smpl lgortm to gnrt t mnml sprtors nd t mxml lqus o ordl grp Ann Brry 1 Romn Pogorlnk 1 Rsr Rport LMOS/RR-10-04 Fbrury 11, 20 1 LMOS UMR CNRS 6158, Ensmbl Sntqu ds Cézux, F-63 173 Aubèr, Frn, brry@sm.r

More information

Roof Terraces. Structural assemblies 04-2012

Roof Terraces. Structural assemblies 04-2012 C Roo Trrs Strutur ssms 04-2012 Prt soutons rom n xprt sour Sütr-Systms s n rn nm or ntnt strutur ssms on ons n trrs sn 1983. Tt yr, Wrnr Sütr nvnt t Sütr -TROBA mt, t rst rn mt or t r rn o ons n trrs.

More information

A New Efficient Distributed Load Balancing Algorithm for OTIS-Star Networks

A New Efficient Distributed Load Balancing Algorithm for OTIS-Star Networks Int'l Con. Pr. n Dst. Pro. T. n Appl. PDPTA' A Nw Ent Dstrut Lo Blnn Alortm or OTIS-Str Ntwors A. Aww 1, J. Al-S 1 Dprtmnt o CS, Unvrsty o Ptr, Ammn, Jorn Dprtmnt o ITC, Ar Opn Unvrsty, Ammn, Jorn Astrt

More information

DATA MANAGEMENT POLICY. SUMMARY OF PRINCIPAL CHANGES General changes None for amendments in this revision, refer to Appendix II, UPR IM16.

DATA MANAGEMENT POLICY. SUMMARY OF PRINCIPAL CHANGES General changes None for amendments in this revision, refer to Appendix II, UPR IM16. Dt Mnmnt Poly Vrson 03.0, UPR IM16 (prvously UPR IM12) Etv: 2 Mr 2011. R-ssu: 1 Sptmr 2015 DATA MANAGEMENT POLICY SUMMARY OF PRINCIPAL CHANGES Gnrl ns Non or mnmnts n ts rvson, rr to Appnx II, UPR IM16.

More information

DATA MANAGEMENT POLICY

DATA MANAGEMENT POLICY Dt Mnmnt Poly Vrson 04.0, UPR IM12 Etv: 2 Mr 2011. R-ssu: 1 Sptmr 2012 DATA MANAGEMENT POLICY SUMMARY OF PRINCIPAL CHANGES Gnrl ns Doumnt upt wt t rom 1 Sptmr 2012 to norport t Unvrsty s rvs ntrnl mnmnt

More information

tis, cis cunc - cunc - tis, cis tis, cis cunc - tis, func - def - def - tis, U func - def - func - tis, pa - tri pa - tri pa - tri tu - per - tu -

tis, cis cunc - cunc - tis, cis tis, cis cunc - tis, func - def - def - tis, U func - def - func - tis, pa - tri pa - tri pa - tri tu - per - tu - 1 B Ihsu dulcs cuncts [Supr 1] [Supr 2] Tnr B B B B - B - B - Ih - Ih - Ih - su su su cs cs cs cunc - cunc - cunc - Amns, Bblthèqu Cntl L Agn, ms 162 D, ff 2v-10 ts, ts, ts, E-tr - E-tr - E-tr - n p n

More information

Schedule C. Notice in terms of Rule 5(10) of the Capital Gains Rules, 1993

Schedule C. Notice in terms of Rule 5(10) of the Capital Gains Rules, 1993 (Rul 5(10)) Shul C Noti in trms o Rul 5(10) o th Cpitl Gins Ruls, 1993 Sttmnt to sumitt y trnsror o shrs whr thr is trnsr o ontrolling intrst Prt 1 - Dtils o Trnsror Nm Arss ROC No (ompnis only) Inom Tx

More information

Outline. Binary Tree

Outline. Binary Tree Outlin Similrity Srh Th Nikolus Augstn Fr Univrsity of Bozn-Bolzno Fulty of Computr Sin DIS 1 Binry Rprsnttion of Tr Binry Brnhs Lowr Boun for th Eit Distn Unit 10 My 17, 2012 Nikolus Augstn (DIS) Similrity

More information

- ASSEMBLY AND INSTALLATION -

- ASSEMBLY AND INSTALLATION - - SSEMLY ND INSTLLTION - Sliin Door Stm Mot Importnt! Ti rmwork n ml to uit 100 mm ini wll tikn (75 mm tuwork) or 125 mm ini wll tikn (100 mm tuwork) HOWEVER t uppli jm kit i pii to itr 100 mm or 125 mm

More information

Change Your History How Can Soccer Knowledge Improve Your Business Processes?

Change Your History How Can Soccer Knowledge Improve Your Business Processes? Symposium Inuurl Lctur o Hjo Rijrs, VU, 26-6-2015 Chn Your History How Cn Soccr Knowl Improv Your Businss Procsss? Wil vn r Alst TU/ n DSC/ 1970 born Oostrbk 1988-1992 CS TU/ 1992-1994 TS TU/ 1994-1996

More information

Distributed Systems Principles and Paradigms. Chapter 11: Distributed File Systems. Distributed File Systems. Example: NFS Architecture

Distributed Systems Principles and Paradigms. Chapter 11: Distributed File Systems. Distributed File Systems. Example: NFS Architecture Distriut Systms Prinipls n Prigms Mrtn vn Stn VU mstrm, Dpt. Computr Sin stn@s.vu.nl Chptr 11: Vrsion: Dmr 10, 2012 1 / 14 Gnrl gol Try to mk fil systm trnsprntly vill to rmot lints. 1. Fil mov to lint

More information

Applications: Lifting eyes are screwed or welded on a load or a machine to be used as lifting points.

Applications: Lifting eyes are screwed or welded on a load or a machine to be used as lifting points. Liin ys Applicions: Liin ys r scrw or wl on or mchin o us s liin poins. Rn: Vn Bs ors wi rn o liin poins in lloy sl: ix, ricul, pivoin n/or roin. Fix liin poin: Ey nu, yp EL - mric vrsion Ey ol, yp AL

More information

Operation Transform Formulae for the Generalized. Half Canonical Sine Transform

Operation Transform Formulae for the Generalized. Half Canonical Sine Transform Appl Mhmcl Scnc Vol 7 3 no 33-4 HIKARI L wwwm-hrcom Opron rnorm ormul or h nrl Hl Cnoncl Sn rnorm A S uh # n A V Joh * # ov Vrh Inu o Scnc n Humn Amrv M S In * Shnrll Khnlwl Coll Aol - 444 M S In luh@mlcom

More information

Chapter 3 Chemical Equations and Stoichiometry

Chapter 3 Chemical Equations and Stoichiometry Chptr Chmicl Equtions nd Stoichiomtry Homwork (This is VERY importnt chptr) Chptr 27, 29, 1, 9, 5, 7, 9, 55, 57, 65, 71, 75, 77, 81, 87, 91, 95, 99, 101, 111, 117, 121 1 2 Introduction Up until now w hv

More information

1.- L a m e j o r o p c ió n e s c l o na r e l d i s co ( s e e x p li c a r á d es p u é s ).

1.- L a m e j o r o p c ió n e s c l o na r e l d i s co ( s e e x p li c a r á d es p u é s ). PROCEDIMIENTO DE RECUPERACION Y COPIAS DE SEGURIDAD DEL CORTAFUEGOS LINUX P ar a p od e r re c u p e ra r nu e s t r o c o rt a f u e go s an t e un d es a s t r e ( r ot u r a d e l di s c o o d e l a

More information

December Homework- Week 1

December Homework- Week 1 Dcmbr Hmwrk- Wk 1 Mth Cmmn Cr Stndrds: K.CC.A.1 - Cunt t 100 by ns nd by tns. K.CC.A.2 - Cunt frwrd bginning frm givn numbr within th knwn squnc (instd f hving t bgin t 1). K.CC.B.4.A - Whn cunting bjcts,

More information

Othello: A Minute to Learn... A Lifetime to Master. Brian Rose

Othello: A Minute to Learn... A Lifetime to Master. Brian Rose Otllo: A Minut to Lrn... A Litim to Mstr Brin Ros Otllo n A Minut to Lrn...A litim to Mstr r Ristr Trmrks o Anjr Co., 9, 00 Anjr Co., All Rits Rsrv Copyrit 00 y Brin Ros Aknowlmnts Mu o tis ook is s on

More information

Binary Search Trees. Definition Of Binary Search Tree. Complexity Of Dictionary Operations get(), put() and remove()

Binary Search Trees. Definition Of Binary Search Tree. Complexity Of Dictionary Operations get(), put() and remove() Binary Sar Trs Compxity O Ditionary Oprations t(), put() and rmov() Ditionary Oprations: ƒ t(ky) ƒ put(ky, vau) ƒ rmov(ky) Additiona oprations: ƒ asnd() ƒ t(indx) (indxd inary sar tr) ƒ rmov(indx) (indxd

More information

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

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

More information

CompactPCI Connectors acc. to PIGMG 2.0 Rev. 3.0

CompactPCI Connectors acc. to PIGMG 2.0 Rev. 3.0 Ctlog E 074486 08/00 Eition ComptPCI Conntors. to PIGMG.0 Rv. 3.0 Gnrl Lt in 999 PCI Inustril Computr Mnufturrs Group (PICMG) introu th nw rvision 3.0 of th ComptPCI Cor Spifition. Vrsion 3.0 of this spifition

More information

WHAT HAPPENS WHEN YOU MIX COMPLEX NUMBERS WITH PRIME NUMBERS?

WHAT HAPPENS WHEN YOU MIX COMPLEX NUMBERS WITH PRIME NUMBERS? WHAT HAPPES WHE YOU MIX COMPLEX UMBERS WITH PRIME UMBERS? There s n ol syng, you n t pples n ornges. Mthemtns hte n t; they love to throw pples n ornges nto foo proessor n see wht hppens. Sometmes they

More information

11 + Non-verbal Reasoning

11 + Non-verbal Reasoning Prti Tst + Non-vrl Rsoning R th instrutions rfully. Do not gin th tst or opn th ooklt until tol to o so. Work s quikly n s rfully s you n. Cirl th orrt lttr from th options givn to nswr h qustion. You

More information

Two-stage Framework for Visualization of Clustered High Dimensional Data

Two-stage Framework for Visualization of Clustered High Dimensional Data T- F Vulzn Clu H Dnnl D Jul C Cll Cun G Inu Tnl 266 F Dv, Aln, GA 3332, USA Sn Bn Nnl Vulzn n Anl Cn P N Nnl L 92 Bll Blv, Rln, WA 99354, USA Hun P Cll Cun G Inu Tnl 266 F Dv, Aln, GA 3332, USA ABSTRACT

More information

Paper Technics Orientation Course in Papermaking 2009:

Paper Technics Orientation Course in Papermaking 2009: P P Otto Cou Pmkg 2009: g to mk u tt you ol o tgt P Wo ould ttd? Otto Cou Pmkg wll b of vlu to t followg gou of ol:- 1. P mll mloy, wo dl dtly wt t o of mkg d w to mov t udtdg of t o d t mll oto t bod

More information

Hermes: Dynamic Partitioning for Distributed Social Network Graph Databases

Hermes: Dynamic Partitioning for Distributed Social Network Graph Databases Hrms: Dynm Prttonn or Dstrut Sol Ntwork Grph Dtss Dnl Nor Unvrsty o Wtrloo nl.nor@ml.om Shhn Kml Unvrsty o Wtrloo s3kml@uwtrloo. Khuzm Duj Unvrsty o Wtrloo kuj@uwtrloo. L Chn HKUST lhn@s.ust.hk ABSTRACT

More information

Level 3. Monday FRACTIONS ⅔ ⅗ 2) ⅔ =?/18. 1) What is a) ⅕ of 30? b) ⅖ of 30?

Level 3. Monday FRACTIONS ⅔ ⅗ 2) ⅔ =?/18. 1) What is a) ⅕ of 30? b) ⅖ of 30? 2014 Th Wkly Pln. All rights rsrv. Mony 2) ⅔ =?/18 1) Wht is ) ⅕ o 30? ) ⅖ o 30? 4) Us or = to show th rltionship twn th ollowing rtions: 3) Writ n quivlnt rtion or ½ ⅔ ⅗ 5) Brook pik ouqut o 24 lowrs.

More information

Polynomial Functions. Polynomial functions in one variable can be written in expanded form as ( )

Polynomial Functions. Polynomial functions in one variable can be written in expanded form as ( ) Polynomil Functions Polynomil functions in one vrible cn be written in expnded form s n n 1 n 2 2 f x = x + x + x + + x + x+ n n 1 n 2 2 1 0 Exmples of polynomils in expnded form re nd 3 8 7 4 = 5 4 +

More information

Oracle PL/SQL Programming Advanced

Oracle PL/SQL Programming Advanced Orl PL/SQL Progrmming Avn In orr to lrn whih qustions hv n nswr orrtly: 1. Print ths pgs. 2. Answr th qustions. 3. Sn this ssssmnt with th nswrs vi:. FAX to (212) 967-3498. Or. Mil th nswrs to th following

More information

WAVEGUIDES (& CAVITY RESONATORS)

WAVEGUIDES (& CAVITY RESONATORS) CAPTR 3 WAVGUIDS & CAVIT RSONATORS AND DILCTRIC WAVGUIDS OPTICAL FIBRS 導 波 管 & 共 振 腔 與 介 質 導 波 管 光 纖 W t rqu is t irowv rg >4 G? t losss o wv i two-odutor trsissio li du to iprt odutor d loss diltri o

More information

d e f i n i c j i p o s t a w y, z w i z a n e j e s t t o m. i n. z t y m, i p o jі c i e t o

d e f i n i c j i p o s t a w y, z w i z a n e j e s t t o m. i n. z t y m, i p o jі c i e t o P o s t a w y s p o і e c z e t s t w a w o b e c o s у b n i e p e і n o s p r a w n y c h z e s z c z e g у l n y m u w z g lb d n i e n i e m o s у b z z e s p o і e m D o w n a T h e a t t i t uodf

More information

Constrained Renewable Resource Allocation in Fuzzy Metagraphs via Min- Slack

Constrained Renewable Resource Allocation in Fuzzy Metagraphs via Min- Slack Intrntonl Journl of ppld Oprtonl Rsrch Vol 1, No 1, pp 7-17, Summr 011 Journl hompg: wwworlur Constrnd Rnwl Rsourc llocton n Fuzzy Mtgrphs v Mn- Slck S S Hshmn* Rcvd: Jnury 31, 011 ; ccptd: My 1, 011 strct

More information

A122 MARION COUNTY HEALTH BUILDING HVAC, GLAZING AND LIGHTING RENOVATION 75% DOCUMENTS 08/31/2015

A122 MARION COUNTY HEALTH BUILDING HVAC, GLAZING AND LIGHTING RENOVATION 75% DOCUMENTS 08/31/2015 7 ' 7 /" ' " ' /" ' 9 /" ' 0" ' 0" ' 0" ' 0" ' " ' /" 0 NRL SHT NOTS IL VRIY XISTIN PRIOR TO WORK N NOTIY RHITT/NINR O ISRPNIS TWN RWINS N XISTIN ONITIONS. 0 0 0 PTH LOTIONS N IR PROOIN WHR XISTIN WLLS

More information

Inductive Proximity Sensors For Reliable Precision Feedback

Inductive Proximity Sensors For Reliable Precision Feedback Inutv Proxmty Snsors For R Prson F Sut to n 21 Inutv Proxmty Snsors Contnts Tn Dt... 24-27 Apptons... 28 Orrn Inormton... 29 Inutv Proxmty Snsors Ovrvw... 30-31 DC Inutv Proxmty Snsors Cynr/Tr Brr Dsn

More information

C o a t i a n P u b l i c D e b tm a n a g e m e n t a n d C h a l l e n g e s o f M a k e t D e v e l o p m e n t Z a g e bo 8 t h A p i l 2 0 1 1 h t t pdd w w wp i j fp h D p u b l i c2 d e b td S t

More information

Menu Structure. Section 5. Introduction. General Functions Menu

Menu Structure. Section 5. Introduction. General Functions Menu Menu Structure Section 5 Introduction General Functions Menu Most workstation functions are accessed by menu selections. This section explains the menu structure and provides a tree structured view of

More information

CC01[PE] 4mm² BLK. 16mm² [CC01] ASSEMBLY PLATE CB10PE. 16mm². 16mm²

CC01[PE] 4mm² BLK. 16mm² [CC01] ASSEMBLY PLATE CB10PE. 16mm². 16mm² ST WR R WR W R WR R WR R WR W R WR R WR R WR W R WR R 0 0 0 [0] 00V, 0z S R [0] SV.000 g V= 0 0 UT 0[] mm². mm² T T T T T T T T T T T T T T T T T T T T T SSY T [0] UT, VV TR 0 UT, TR VV X V V V V T, 0V

More information

Authenticated Encryption. Jeremy, Paul, Ken, and Mike

Authenticated Encryption. Jeremy, Paul, Ken, and Mike uthntcatd Encrypton Jrmy Paul Kn and M Objctvs Examn thr mthods of authntcatd ncrypton and dtrmn th bst soluton consdrng prformanc and scurty Basc Componnts Mssag uthntcaton Cod + Symmtrc Encrypton Both

More information

The Mathematics of Sudoku

The Mathematics of Sudoku T Mtmts o Suoku Tom Dvs tomrvs@rtlnk.nt ttp://www.omtr.or/mtrls (Prlmnry) Sptmr, 0 Introuton Suoku s puzzl prsnt on squr r tt s usully, ut s somtms or otr szs. In ts oumnt, w wll onsr only t s, ltou lmost

More information

MATH 150 HOMEWORK 4 SOLUTIONS

MATH 150 HOMEWORK 4 SOLUTIONS MATH 150 HOMEWORK 4 SOLUTIONS Section 1.8 Show tht the product of two of the numbers 65 1000 8 2001 + 3 177, 79 1212 9 2399 + 2 2001, nd 24 4493 5 8192 + 7 1777 is nonnegtive. Is your proof constructive

More information

SEE PAGE 2 FOR BRUSH MOTOR WIRING SEE PAGE 3 FOR MANUFACTURER SPECIFIC BLDC MOTOR WIRING EXAMPLES A

SEE PAGE 2 FOR BRUSH MOTOR WIRING SEE PAGE 3 FOR MANUFACTURER SPECIFIC BLDC MOTOR WIRING EXAMPLES A 0V TO 0V SUPPLY +0V TO +0V RS85 ONVRTR 9 TO OM PORT ON P TO P OM PORT US 9600 U 8IT, NO PRITY, STOP, NO FLOW TRL. OPTO SNSOR # +0V TO +0V RS85 RS85 OPTO SNSOR # PHOTO TRNSISTOR OPTO SNSOR # L TO OTHR Z

More information

TRIUMPH TR2 - TR4A WIRING DIAGRAMS

TRIUMPH TR2 - TR4A WIRING DIAGRAMS TOI www.autowire.com TIMH T2 T4 II IMS dmp LICTIO 2005 www.autowire.com dmp LICTIO 200 5 TOI TO IITIO I OTIOL OVIV 1 TO COTOL OX O O SH L ISTIT IITIO TO 2 O S OX HT HOSTT HT MOTO (OTIOL) OM S OX 3 (O STT

More information

Form: Parental Consent for Blood Donation

Form: Parental Consent for Blood Donation A R C Wt, C 20006 Ptl Ct f B i Ifi T f t y t ll f i y tl t q y t l A R C ly. Pl ll 1-800-RE-CROSS (1-800-733-2767) v. if y v q r t t i I iv t f yr,, t, y v t t: 1. Y y t t l i ly, 2. Y y t t t l i ( k

More information

G S e r v i c i o C i s c o S m a r t C a r e u ي a d e l L a b o r a t o r i o d e D e m o s t r a c i n R ل p i d a V e r s i n d e l S e r v i c i o C i s c o S m a r t C a r e : 1 4 ع l t i m a A c

More information

Positive Integral Operators With Analytic Kernels

Positive Integral Operators With Analytic Kernels Çnky Ünverte Fen-Edeyt Fkülte, Journl of Art nd Scence Sy : 6 / Arl k 006 Potve ntegrl Opertor Wth Anlytc Kernel Cn Murt D KMEN Atrct n th pper we contruct exmple of potve defnte ntegrl kernel whch re

More information

Classeur de Documents (à 72 Cases ) Casillero para Publicationes (72 Compartimientos)

Classeur de Documents (à 72 Cases ) Casillero para Publicationes (72 Compartimientos) an L ompany New ope, MN 55428 www.safcoproducts.com -Z Stor Literature Organizer (72 ompartments) lasseur de ocuments (à 72 ases ) asillero para Publicationes (72 ompartimientos) SSML SMLY NSTRUTONS NSTRUTONS

More information

Integration by Substitution

Integration by Substitution Integrtion by Substitution Dr. Philippe B. Lvl Kennesw Stte University August, 8 Abstrct This hndout contins mteril on very importnt integrtion method clled integrtion by substitution. Substitution is

More information

Solutions to old Exam 1 problems

Solutions to old Exam 1 problems Solutions to old Exam 1 problems Hi students! I am putting this old version of my review for the first midterm review, place and time to be announced. Check for updates on the web site as to which sections

More information

Approximate Subtree Identification in Heterogeneous XML Document Collections

Approximate Subtree Identification in Heterogeneous XML Document Collections Approximat Sutr Intiiation in Htrognous XML Doumnt Colltions Ismal Sanz 1, Maro Msiti 2, Giovanna Gurrini 3 an Raal Brlanga 1 1 Univrsitat Jaum I, Spain 2 Univrsità gli Stui i Milano, Italy 3 Univrsità

More information

Attorney Directory. Prepared for on 12/8/2008. Helping you balance work and life. To use your plan:

Attorney Directory. Prepared for on 12/8/2008. Helping you balance work and life. To use your plan: Prepared for on 12/8/2008 ttorney irectory R PRT elping you balance work and life elow is a list of etwork ttorneys with offices located near you. You can save money on legal services by using a etwork

More information

PC Problems HelpDesk Service Agreement

PC Problems HelpDesk Service Agreement Enn SS 7 b aw f Un Sa & anaa an b nnana a I IS ILLEGL ND SRILY ROHIIED O DISRIUE, ULISH, OFFER FOR SLE, LIENSE OR SULIENSE, GIVE OR DISLOSE O NY OHER RY, HIS RODU IN HRD OY OR DIGIL FORM LL OFFENDERS WILL

More information

H ig h L e v e l O v e r v iew. S te p h a n M a rt in. S e n io r S y s te m A rc h i te ct

H ig h L e v e l O v e r v iew. S te p h a n M a rt in. S e n io r S y s te m A rc h i te ct H ig h L e v e l O v e r v iew S te p h a n M a rt in S e n io r S y s te m A rc h i te ct OPEN XCHANGE Architecture Overview A ge nda D es ig n G o als A rc h i te ct u re O ve rv i ew S c a l a b ili

More information

Campus Sustainability Assessment and Related Literature

Campus Sustainability Assessment and Related Literature Campus Sustainability Assessment and Related Literature An Annotated Bibliography and Resource Guide Andrew Nixon February 2002 Campus Sustainability Assessment Review Project Telephone: (616) 387-5626

More information

Opis przedmiotu zamówienia - zakres czynności Usługi sprzątania obiektów Gdyńskiego Centrum Sportu

Opis przedmiotu zamówienia - zakres czynności Usługi sprzątania obiektów Gdyńskiego Centrum Sportu O p i s p r z e d m i o t u z a m ó w i e n i a - z a k r e s c z y n n o c i f U s ł u i s p r z» t a n i a o b i e k t ó w G d y s k i e C eo n t r u m S p o r t us I S t a d i o n p i ł k a r s k i

More information

Matching Execution Histories of Program Versions

Matching Execution Histories of Program Versions Mt Exuto Hstors o Prorm Vrsos Xyu Z Rv Gupt Dprtmt o Computr S T Uvrsty o Arzo Tuso, Arzo 85721 {xyz,upt}@s.rzo.u ABSTRACT W vlop mto or mt ym stors o prorm xutos o two prorm vrsos. T mts prou usul my

More information

LTCG. Runways: Runway 11 Takeoff length: 2640, Landing length: 2640 Runway 29 Takeoff length: 2640, Landing length: 2640

LTCG. Runways: Runway 11 Takeoff length: 2640, Landing length: 2640 Runway 29 Takeoff length: 2640, Landing length: 2640 LTG irport information: ountry: Turkey ity: INTL oordinates: N 0 59.8', E039 7. Elevation: ustoms: ustoms Fuel: Jet RFF: T 8 hours: H2 Runways: Runway Takeoff length: 260, Landing length: 260 Runway 29

More information

Example A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding

Example A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding 1 Exmple A rectngulr box without lid is to be mde from squre crdbord of sides 18 cm by cutting equl squres from ech corner nd then folding up the sides. 1 Exmple A rectngulr box without lid is to be mde

More information

Reasoning to Solve Equations and Inequalities

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

More information

EuroFGI Workshop on IP QoS and Traffic Control TITOLO. A Receiver Side Approach for Real-Time Monitoring of IP Performance Metrics

EuroFGI Workshop on IP QoS and Traffic Control TITOLO. A Receiver Side Approach for Real-Time Monitoring of IP Performance Metrics EuroFGI Workhop on IP QoS n Trff Conrol TITOLO A Rvr S Approh for Rl-T Monorng of IP Prforn Mr TESI R. G. Grroppo, S. Gorno, F. Oppno, G. Pro Dp. of Inforon Engnrng Unvry of P 1 Lbon, Porugl, Dbr 6-7,

More information

MODULE 3. 0, y = 0 for all y

MODULE 3. 0, y = 0 for all y Topics: Inner products MOULE 3 The inner product of two vectors: The inner product of two vectors x, y V, denoted by x, y is (in generl) complex vlued function which hs the following four properties: i)

More information

DATA MANAGEMENT POLICY

DATA MANAGEMENT POLICY Dt Mngmnt Poly Etv: 2 Mrh 2011. R-ssu: 1 Sptmr 2011 DATA MANAGEMENT POLICY IMPORTANT NOTICE Durng th Am Yr 2011-2012, th Unvrsty wll rvsng ts ntrnl struturs whh, mongst othr thngs, my rsult n th rplmnt

More information

Ne l'aria in questi di fatt'ho un si forte Castel,

Ne l'aria in questi di fatt'ho un si forte Castel, 10 19 29 37 46 54 62 70 N l' in qu ftt'ho un si Csl, oginl ky C l sl N l' su in qu ch, Cn poiv' l ftt' houn si Cipno d Ror v nr, nr l vn, poiv' fossin V n v prcuo ft.. mr, L'r, ch tr'l trui fol lr pugnr

More information

With content marketing, you can move beyond measuring success in terms of impressions, awareness, or perception.

With content marketing, you can move beyond measuring success in terms of impressions, awareness, or perception. L k m k?j SHSMD y! A m k b mm y SHSMD b y k w y y m. Byj 4 000 mm y SHSMDm mb y w x b y y j bm y : F w b m y x A w m m w b b T w m Am H A R b w S b B b m k A m m m! V www. m. /b. Sy H Sy Mk Dm P Mk P V

More information

body.allow-sidebar OR.no-sidebar.home-page (if this is the home page).has-custom-banner OR.nocustom-banner .IR OR.no-IR

body.allow-sidebar OR.no-sidebar.home-page (if this is the home page).has-custom-banner OR.nocustom-banner .IR OR.no-IR body.llow-sidebr OR.no-sidebr.home-pge (if this is the home pge).hs-custom-bnner OR.nocustom-bnner.IR OR.no-IR #IDENTIFIER_FOR_THIS_SITE div#pge-continer.depends_on_page_ty PE llow-sidebr mens tht there

More information

Back left Back right Front left Front right. Blue Shield of California. Subscriber JOHN DOE. a b c d

Back left Back right Front left Front right. Blue Shield of California. Subscriber JOHN DOE. a b c d Smpl ID r n sription o trms Bk lt Bk right Front lt Front right Provirs: Pls il ll lims with your lol BluCross BluShil lins in whos srvi r th mmr riv srvis or, whn Mir is primry, il ll Mir lims with Mir.

More information

ELECTRICAL CAPACITY SYMBOL EQUIPMENT TYPE LOCATION / SERVING MFR MODEL (GALLONS) VOLTS PH AMPS WATTS

ELECTRICAL CAPACITY SYMBOL EQUIPMENT TYPE LOCATION / SERVING MFR MODEL (GALLONS) VOLTS PH AMPS WATTS OT: This is a stadard symbol list ad ot all items listed may be used. bbreviatios () XT OV OOR OW OOR P OW PRVTR OT R OT. OTTO V VV W O WTR R OT TR OW T TR O OOR OT OOR R T T O P O PR OR P O PR T W R WT,

More information

SEM-SCAN ALPHA SEM-SCAN NUMERIC. AVAILABLE COLORS Red. SEM-SCAN ALPHA21-1-2" Sem-Clip in position 1 Packed

SEM-SCAN ALPHA SEM-SCAN NUMERIC. AVAILABLE COLORS Red. SEM-SCAN ALPHA21-1-2 Sem-Clip in position 1 Packed ST TMS R F R S SM-SN omparable to ardex This system makes straight alphabetic filing obsolete. t dramatically cuts filing and retrieval time and practically eliminates misfiles. t works extremely well

More information

Last time Interprocedural analysis Dimensions of precision (flow- and context-sensitivity) Flow-Sensitive Pointer Analysis

Last time Interprocedural analysis Dimensions of precision (flow- and context-sensitivity) Flow-Sensitive Pointer Analysis Flow-Insnsitiv Pointr Anlysis Lst tim Intrprocurl nlysis Dimnsions of prcision (flow- n contxt-snsitivity) Flow-Snsitiv Pointr Anlysis Toy Flow-Insnsitiv Pointr Anlysis CIS 570 Lctur 12 Flow-Insnsitiv

More information

B I N G O B I N G O. Hf Cd Na Nb Lr. I Fl Fr Mo Si. Ho Bi Ce Eu Ac. Md Co P Pa Tc. Uut Rh K N. Sb At Md H. Bh Cm H Bi Es. Mo Uus Lu P F.

B I N G O B I N G O. Hf Cd Na Nb Lr. I Fl Fr Mo Si. Ho Bi Ce Eu Ac. Md Co P Pa Tc. Uut Rh K N. Sb At Md H. Bh Cm H Bi Es. Mo Uus Lu P F. Hf Cd Na Nb Lr Ho Bi Ce u Ac I Fl Fr Mo i Md Co P Pa Tc Uut Rh K N Dy Cl N Am b At Md H Y Bh Cm H Bi s Mo Uus Lu P F Cu Ar Ag Mg K Thomas Jefferson National Accelerator Facility - Office of cience ducation

More information

Endomines - Ilomantsi Gold Project

Endomines - Ilomantsi Gold Project Endomines - Ilomantsi Gold Project Page 1 of 6 1 ILOMAN. AR E A 1 Lo c a t i o n 2 T e n u r e 3 G e o l o g y 4 E x p l o r a t i o n 5 R e s o u r c e s 6 Or e T e s t s 7 E n v i r o n 8 P l a n s OT

More information

Binary Search Trees. Definition Of Binary Search Tree. The Operation ascend() Example Binary Search Tree

Binary Search Trees. Definition Of Binary Search Tree. The Operation ascend() Example Binary Search Tree Binary Sar Trs Compxity O Ditionary Oprations t(), put() and rmov() Ditionary Oprations: ƒ t(ky) ƒ put(ky, vau) ƒ rmov(ky) Additiona oprations: ƒ asnd() ƒ t(indx) (indxd inary sar tr) ƒ rmov(indx) (indxd

More information

SAN JOSE UNIFIED RETURNING VOLUNTEER DRIVER PACKET

SAN JOSE UNIFIED RETURNING VOLUNTEER DRIVER PACKET SAN JOSE UNIFIED ETUNING VOLUNTEE DIVE PACKET VOLUNTEE DIVE S NAME: STUDENT NAME /ID# SCHOOL: SPOT/ACTIVITY: STUDENT NAME /ID# SCHOOL: SPOT/ACTIVITY: STUDENT NAME /ID# SCHOOL: SPOT/ACTIVITY: STUDENT NAME

More information

Paper Cold & Hot Drink Cups & Lids

Paper Cold & Hot Drink Cups & Lids Paper old & Hot rink ups & Lids. UL LIS W/STRW SLOTS SOLO Lids for cold drink cups. Translucent 18200297 L9N Fits 7, 7 & L7 2000/cs. 18702500 L10LN Fits 9, 9, VP95X, L91, R10NN, 2500/cs. PV12, V122, VP12

More information

Upward Planar Drawings of Series-Parallel Digraphs with Maximum Degree Three

Upward Planar Drawings of Series-Parallel Digraphs with Maximum Degree Three Upwr Plnr Drwins of ris-prlll Dirps wit Mximum Dr Tr (Extn Astrt) M. Aul Hssn m n M. iur Rmn Dprtmnt of Computr in n Eninrin, Bnls Univrsity of Eninrin n Tnoloy (BUET). {sm,siurrmn}@s.ut.. Astrt. An upwr

More information

UNIVERSITY OF ILUNOхS LIBRARY AT URBANA-CHAMPA1GN AGR1CULT-"'J?'-

UNIVERSITY OF ILUNOхS LIBRARY AT URBANA-CHAMPA1GN AGR1CULT-'J?'- ' UNVRSTY F NхS LBRARY AT URBANA-HAMPA1GN AGR1ULT-"'J?'- igitied by the nternet Arhive 2012 ith fndg frm University f llis Urbn-hmpign http://.rhive.rg/detils/illismmeri1982med s 8 h U p m UU t g 5. -

More information

55 th EOQ Congress as World Quality Congress

55 th EOQ Congress as World Quality Congress 55 h EOQ grss s Wr Qu grss HOTEL RESERVTION ND DESRITION OF HOTELS LOTION OF 55 h EOQ OFFIIL HOTELS 1 Kpsk H rvus***** (ONGRESS VENUE ND HOTEL) H-1051 Bups, Erzséb ér 7-8. 2 Dubus H Gér**** H-1111 Bups,

More information

3 Signals and Systems: Part II

3 Signals and Systems: Part II 3 Signals and Systems: Part II Recommended Problems P3.1 Sketch each of the following signals. (a) x[n] = b[n] + 3[n - 3] (b) x[n] = u[n] - u[n - 5] (c) x[n] = 6[n] + 1n + (i)2 [n - 2] + (i)ag[n - 3] (d)

More information

Cloud and Big Data Summer School, Stockholm, Aug., 2015 Jeffrey D. Ullman

Cloud and Big Data Summer School, Stockholm, Aug., 2015 Jeffrey D. Ullman Cloud and Big Data Summr Scool, Stockolm, Aug., 2015 Jffry D. Ullman Givn a st of points, wit a notion of distanc btwn points, group t points into som numbr of clustrs, so tat mmbrs of a clustr ar clos

More information

Vectors 2. 1. Recap of vectors

Vectors 2. 1. Recap of vectors Vectors 2. Recp of vectors Vectors re directed line segments - they cn be represented in component form or by direction nd mgnitude. We cn use trigonometry nd Pythgors theorem to switch between the forms

More information

G d y n i a U s ł u g a r e j e s t r a c j i i p o m i a r u c z a s u u c z e s t n i k ó w i m p r e z s p o r t o w y c h G d y s k i e g o O r o d k a S p o r t u i R e k r e a c j i w r o k u 2 0

More information

m Future of learning Zehn J a hr e N et A c a d ei n E r f o l g s p r o g r a m Cisco E x p o 2 0 0 7 2 6. J u n i 2 0 0 7, M e sse W ie n C. D or n in g e r, b m u k k 1/ 12 P r e n t t z d e r p u t

More information

Econ 4721 Money and Banking Problem Set 2 Answer Key

Econ 4721 Money and Banking Problem Set 2 Answer Key Econ 472 Money nd Bnking Problem Set 2 Answer Key Problem (35 points) Consider n overlpping genertions model in which consumers live for two periods. The number of people born in ech genertion grows in

More information

Masters Mens Physique 45+

Masters Mens Physique 45+ C G x By, F, hysq, Bk Chpshps Ap, Cv Cy, Cf Mss Ms hysq + Fs Ls Css Ov Css s G MC Chpk M+ W M+/MC y Bs 9 8 9 9 8 B O'H 8 9 8 S Rs 8 8 9 h K 9 D Szwsk 8 9 8 9 9 G M+ h D Ly Iz M+ 8 M R : : C G x By, F,

More information

Broadband Technology Opportunities Program: Sustainable Broadband Adoption and Public Computer Centers

Broadband Technology Opportunities Program: Sustainable Broadband Adoption and Public Computer Centers Broadband Technology Opportunities Program: Sustainable Broadband Adoption and Public Computer Centers National Telecommunications and Information Agency (NTIA) U. S. Department of Commerce Funded by the

More information

Process Mining Making Sense of Processes Hidden in Big Event Data

Process Mining Making Sense of Processes Hidden in Big Event Data Pross Minin Mkin Sns o Prosss Hin in Bi Evnt Dt EIS Colloquium, 7-12-2012, TU/, Einovn Wil vn r Alst www.prossminin.or omplin-orint qustions, prolms n solutions prormn-orint qustions, prolms n solutions

More information

motori asincroni monofase asynchronous single phase motors moteurs asynchrones monophasés einphasige Asynchronmotoren

motori asincroni monofase asynchronous single phase motors moteurs asynchrones monophasés einphasige Asynchronmotoren moori sinroni monos synronous sinl ps moors mours synrons monopsés inpsi synronmoorn sri oori sinroni monos synronous sinl ps moors ours synrons monopss inpsi synronmoorn onnsor prmnn iusi vnili srnmn

More information

ESNV. Runways: Runway 10 Takeoff length: 1502, Landing length: 1502 Runway 28 Takeoff length: 1502, Landing length: 1260

ESNV. Runways: Runway 10 Takeoff length: 1502, Landing length: 1502 Runway 28 Takeoff length: 1502, Landing length: 1260 ESNV irport information: ountry: Sweden ity: oordinates: N 64 34.7', E016 50.4 Elevation: 1140 ustoms: Fuel: 100LL, Jet 1 RFF: T 4 during SKE TF, other times O/R hours: See NOTM Runways: Runway 10 Takeoff

More information

SMBJ Transient Voltage Suppressor Diode Series

SMBJ Transient Voltage Suppressor Diode Series *RoHS OMPLINT eatures n RoHS compliant* n Surface Mount SM package n Standoff Voltage: 5 to 495 volts n Power issipation: 600 watts pplications n I 600-4-2 S (Min. Level 4) n I 600-4-4 T n I 600-4-5 Surge

More information

Licensed to TAP - AIR PORTUGAL,. Printed from JeppView disc 16-03.

Licensed to TAP - AIR PORTUGAL,. Printed from JeppView disc 16-03. Licensed to TP - IR PORTUGL,. Printed from JeppView disc 16-03. TRNS LEVEL: Y T TRNS LT: 31 MR 00.SI. 10-3, RZIL OT, LOL, SELO EPRTURES This SI requires take-off minimums of: eiling 500', Visibility 1600m

More information

Math 314, Homework Assignment 1. 1. Prove that two nonvertical lines are perpendicular if and only if the product of their slopes is 1.

Math 314, Homework Assignment 1. 1. Prove that two nonvertical lines are perpendicular if and only if the product of their slopes is 1. Mth 4, Homework Assignment. Prove tht two nonverticl lines re perpendiculr if nd only if the product of their slopes is. Proof. Let l nd l e nonverticl lines in R of slopes m nd m, respectively. Suppose

More information

SE3BB4: Software Design III Concurrent System Design. Sample Solutions to Assignment 1

SE3BB4: Software Design III Concurrent System Design. Sample Solutions to Assignment 1 SE3BB4: Softwre Design III Conurrent System Design Winter 2011 Smple Solutions to Assignment 1 Eh question is worth 10pts. Totl of this ssignment is 70pts. Eh ssignment is worth 9%. If you think your solution

More information

EQUATIONS OF LINES AND PLANES

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

More information

R e t r o f i t o f t C i r u n i s g e C o n t r o l

R e t r o f i t o f t C i r u n i s g e C o n t r o l R e t r o f i t o f t C i r u n i s g e C o n t r o l VB Sprinter D e s c r i p t i o n T h i s r e t r o f i t c o n s i s t s o f i n s t a l l i n g a c r u i s e c o n t r o l s wi t c h k i t i n

More information

ALL DIMENSIONS IN MILLIMETRES BUT DO NOT SCALE DRAWING

ALL DIMENSIONS IN MILLIMETRES BUT DO NOT SCALE DRAWING 3 4 5 6 7 8 9 0 PP TST UPN : MTRL: RN STL PP PS 4.3 X 8.0 WLL X 5 LN NT: T NUMR TS S T LMT WT MXMUM 4 TS. TST PLT UPN : MTRL: RN STL PLT TNSS: 0 mm. X TST PLT UPN : MTRL: RN STL PLT TNSS: 6 mm. L PNT R

More information

LISTA DOCUMENTI DOCUMENT LIST REVISIONI REVISIONS DESCRIZIONE FOGLI DESCRIPTION SHEET FOGLIO SHEET FOGLIO SHEET SCHEMA FLUIDICO FLUIDIC DIAGRAM

LISTA DOCUMENTI DOCUMENT LIST REVISIONI REVISIONS DESCRIZIONE FOGLI DESCRIPTION SHEET FOGLIO SHEET FOGLIO SHEET SCHEMA FLUIDICO FLUIDIC DIAGRAM 0 LIST OUMNTI OUMNT LIST SRIZION OGLI SRIPTION SHT OGLIO SHT SHM LTTRIO IRUITL IRUIT IGRM OGLIO SHT SHM LUIIO LUII IGRM ISPOSIZION OMPONNTI PRTS LOTION OGLIO SHT OGLIO SHT RVISIONI RVISIONS N. N. RVISION

More information