Process Mining Making Sense of Processes Hidden in Big Event Data

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Process Mining Making Sense of Processes Hidden in Big Event Data"

Transcription

1 Pross Minin Mkin Sns o Prosss Hin in Bi Evnt Dt EIS Colloquium, , TU/, Einovn Wil vn r Alst

2 omplin-orint qustions, prolms n solutions prormn-orint qustions, prolms n solutions Positionin Pross Minin pross mol nlysis (simultion, vriition, t.) pross minin t-orint nlysis (t minin, min lrnin, usinss intllin) 1

3 Avns in Pross Minin Mny pross isovry n onormn kin loritms n tools r vill (. t vrious ProM pks). Also ommril sotwr s on ts is: Diso (Fluxion), Rlt (Futur/Prntiv), BPMOn (Plls Atn/Prptiv), ARIS Pross Prormn Mnr (Sotwr AG), Futur Rlt (Futur Tnoloy), Intrst Automt Pross Disovry (Fujitsu), QPR ProssAnlyzr/Anlysis (QPR Sotwr), low (oursprk), Disovry Anlyst (StroLOGIC), t. W ppli pross minin in ovr 100 orniztions. Mor tn 75 popl involvin mor tn 50 orniztions rt t Pross Minin Mnisto in t ontxt o t IEEE Tsk For on Pross Minin. Avill in 13 lnus PAGE 2

4 PAGE 3

5 Bi Dt: Evn Dilrt n t "pointyir oss" know out it ttp://ilrt.om/strips/omi/ / PAGE 4

6 Moor's Lw D=2.03 D=1.56 D=1.92 5

7 A simpl lultion Strtin point 2010: Hrisk 1 Tryt = yts Diitl Univrs 1.2 Zttyt = 1.2*10 21 yts (stimt in IDC s nnul rport, T Diitl Univrs D Ar You Ry? My 2010) Disk ns to row = 1.2* 10 9 = 1.2*10 21 / tims its urrnt siz. Assumin D=1.56 tis tks 30.16*1.56 = yrs. Hn, in 2060 your lptop n ontin ll o toy's iitl univrs (intrnt, omputr ils, trnstion los, movis, potos, musi, ooks, tss, t.)! 6

8 Bi Dt: Opportunitis n Cllns PAGE 7

9 Wt i? tr r mor tn vnts? tr r mor tn 1000 irnt tivitis? ijkl kjil jkil kijl ijkl jikl... pross isovry skip xtr insurn onormn kin n ookin 4 5 xtr insurn skip xtr insurn i 8 9 slt r in ook r 1 xtr insurn 2 onirm 3 initit k-in 6 j k rivr s lins 10 l supply r out tr r mor tn ss? 7 k r rit r 11 PAGE 8

10 Domposin/Distriutin Pross Minin Prolms PAGE 9

11 Tis tlk is not out nw loritm! PAGE 10

12 How to ompos/istriut pross isovry?? PAGE 11

13 How to ompos/istriut pross isovry? in out PAGE 12

14 How to ompos/istriut onormn kin? in out? PAGE 13

15 How to ompos/istriut onormn kin? in out ours too otn 2 4 in 1 6 out is otn skipp 3 5 PAGE 14

16 Rplition: Sm vnt lo on ll omputin nos Only mks sns i rnom lmnts,.., nti pross minin. PAGE 15

17 Clssiition s on prtitionin o vnt lo: vrtil n orizontl sts o ss sts o tivitis PAGE 16

18 Vrtil istriution I: Split ss ritrrily sts o ss PAGE 17

19 Vrtil istriution II: Split ss s on spii tur sort mium lon PAGE 18

20 Horizontl istriution sts o tivitis = + PAGE 19

21 Horizontl istriution: T ky i projt on,,,, projt on,,, in out 3 5 PAGE 20

22 Gnrl Cs PAGE 21

23 Systm Nt t7 7 t8 8 t11 strt t1 Ll Ptri nt (P,T,F,l) 1 2 t2 t3 t4 = ristr rqust = xmin il = k tikt = i = rinitit rqust = sn ptn lttr = py ompnstion = sn rjtion lttr Silnt trnsitions n visil trnsitions (uniqu or not), On initil mrkin M init, on inl mrkin M inl 3 4 t6 t5 5 6 t9 t10 9 n PAGE 22

24 Trs n Los A systm nt SN s st o possil visil trs ϕ(sn) strtin in M init n nin M inl only sowin t visil stps. An vnt lo L is multist o trs. Two min pross minin prolms: 1. Conormn kin: Givn L n SN, vlut t "onormn" (.., itnss, prision, nrliztion, t.) o L n ϕ(sn) 2. Pross isovry: Givn L, rt SN su tt t onormn o L n ϕ(sn) is "s oo s possil" PAGE 23

25 Vli Domposition strt t1 1 2 t2 t3 t4 3 4 t7 t5 t t8 t9 t t11 n strt t1 t t2 t3 t4 t t5 t6 t11 6 t9 9 Union o sunts is oriinl nt No sr pls t5 5 t10 t6 Sr trnsitions r visil n v uniqu ll n PAGE 24

26 Anotr Domposition t7 7 t8 8 t11 strt t1 1 2 t2 t3 t4 3 4 t5 t6 5 6 t9 t10 9 n strt t1 t2 t1 2 t4 4 t5 t1 1 t3 3 t5 t6 t7 7 t8 8 t11 t6 6 t9 9 Rquirmnt t5 5 n Union o sunts is oriinl nt t10 No sr pls t6 Sr trnsitions r visil n uniqu PAGE 25

27 Mximl Vli Domposition strt t1 1 2 t2 t3 t4 3 4 t7 t5 t t8 t9 t t11 n SN 1 strt t1 SN 2 t1 1 t2 t3 3 t5 t6 SN 5 t7 t t8 t9 t10 t8 t9 t t11 n SN 6 t6 t1 2 SN 4 t5 SN 3 t4 t6 t4 4 PAGE 26

28 Mximl Domposition strt t1 1 2 t2 t3 t4 3 4 t7 t5 t t8 t9 t t11 n SN 1 strt t1 SN 3 t1 2 SN 2 t1 t4 1 t6 t2 t3 3 SN 4 t4 t5 t6 4 SN 5 t7 t5 t6 t t8 t9 t10 t8 t9 t t11 n SN 6 Constrution: roup rs itrtivly Mximl omposition is uniqu n lwys vli omposition x y y PAGE 27

29 Non-uniqu visil lls t7 7 t8 8 t11 strt t1 1 2 t2 t3 t4 3 4 t5 t6 5 6 t9 t10 9 t1 n 1 t2 t3 3 t5 SN 7 t2 t1 2 t4 t6 t4 t6 4 t5 t1 1 2 t3 t4 3 4 t5 t6 Union o sunts is oriinl nt No sr pls Sr trnsitions r visil n uniqu PAGE 28

30 Conormn kin n ompos!!! strt Lt L n vnt lo, SN systm nt, n D={SN 1,SN 2, SN n } vli omposition L i is t sulo o SN i (L projt onto visil trnsitions o SN i ) t1 1 2 t2 t3 t4 3 4 t6 t7 t t8 t9 t t11 n L is prtly ittin SN i n only i projt lo is L i is prtly ittin SN i SN 1 strt t1 SN 3 t1 2 SN 2 t4 t1 1 t6 t2 t3 SN 4 t4 3 t6 4 t5 t5 SN 5 t6 t7 t t8 t9 t10 t8 t9 t t11 n SN 6 PAGE 29

31 Exmpl o linmnt or osrv tr,,,,,,,,,,,,,,,, t2 1 t3 strt t1 2 t4 3 4 t7 t5 t t8 t9 t t11 n SN 1 strt t1 SN 3 t1 2 SN 2 t1 t4 1 t6 t2 t3 3 SN 4 t4 t5 t6 4 SN 5 t7 t5 t6 t t8 t9 t10 t8 t9 t t11 n SN 6 Et. PAGE 30

32 Quntiyin Conormn Frtion o ss prtly ittin SN quls t rtion o ss or wi projt lo is L i is prtly ittin SN i For itnss t t vnt lvl (osts s linmnt) it is possil to omput n optimisti vlu. strt 1 2 n,,,, strt 1 2 n,,, Dvitions my unrstimt ut r lwys tt! PAGE 31

33 How out isovry? PAGE 32

34 Disovry n lso istriut! Assum t st o tivitis is split in ovrlppin sts. Split lo L in sulos L i s on ts sts. Disovr mol SN i pr sulo. Mr t mols SN i into SN n rturn rsult. All t rlir urnts ol,.., L is prtly ittin SN i n only i projt lo is L i is prtly ittin SN i PAGE 33

35 Exmpl Lt's us t Alp loritm Alp loritm is not vry suitl or isovrin trnsition orr sunts. By in strt n n tivitis w t (in tis s) prtly ittin sunts. PAGE 34

36 Disovr mol pr sulo (Alp loritm) SN 1 i strt n SN 2 SN 3 strt j strt n SN 4 strt j k n n PAGE 35

37 Mr mols SN 1 i strt n SN 2 strt n L is prtly ittin SN us projt lo is L i is prtly ittin SN i SN 3 j strt n SN 4 j k strt n p1 p2 p3 {1,2,3,4} t1 p5 p6 {1,2} t2 p7 p8 p9 t4 i t3 t5 {1} {1} {2} p10 p11 j t6 {3,4} {1,2,3} t7 p13 p14 p15 t9 {4} k t10 p19 t12 {3,4} p18 {4} {4} t11 p20 p21 {1,2,3,4} t13 p22 p23 p24 p4 p12 {1,2,3} t8 p16 p17 p25 PAGE 36

38 Simpliy y rmovin runnt pls n initiliztion p1 p2 p3 p4 {1,2,3,4} t1 p5 p6 {1,2} t2 p7 p8 p9 t4 i t3 t5 {1} {1} {2} p10 p11 p12 j t6 {1,2,3} t7 {1,2,3} {3,4} t8 p13 p14 p15 p16 p17 {4} t9 p18 {4} {4} t10 p19 k t12 {3,4} t11 p20 p21 {1,2,3,4} t13 p22 p23 p24 p25 i j k strt n Lo is prtly ittin tis mol! PAGE 37

39 PAGE 38

40 Psss Wil vn r Alst. Domposin Pross Minin Prolms Usin Psss. In Ptri Nts 2012, LNCS 7347, ps Sprinr, PAGE 39

41 Mosow GUM PAGE 40

42 Pss P=(X,Y) usl pnny: my trir or nl X Y i PAGE 41

43 Miniml psss X X Y i Y pss is miniml i it os not ontin smllr psss PAGE 42

44 Psss in n quivln rltion on t s in t rp i PAGE 43

45 Miniml pss 1: (X,Y) = ({},{,}) X={} i Y={,} PAGE 44

46 Miniml pss 2: (X,Y) = ({,,},{,,}) X={,,} Y={,,} i PAGE 45

47 Miniml pss 3: (X,Y) = ({},{}) X={} Y={} i PAGE 46

48 Miniml pss 4: (X,Y) = ({},{}) i X={} Y={} PAGE 47

49 Miniml pss 5: (X,Y) = ({,},{i}) X={,} i Y={i} PAGE 48

50 Union o two psss i i i PAGE 49

51 Dirn o two psss i i i PAGE 50

52 Proprtis o psss I X 1 X 3 Y 3 Y 1 X 5 Y 5 tn: X 2 X 4 Y 4 Y 2 PAGE 51

53 Pss prtitionin P 1, P 2,,P n is pss prtitionin i n only i P 1, P 2,,P n r psss, t psss r isjoint, n t psss ovr ll s. 5 psss i PAGE 52

54 Mor xmpls o pss prtitionins 4 psss ({,,},{,,}) ({,,},{,i}) ({},{,}) ({},{}) i ({,,,},{,,,,}) 2 psss ({,,,},{,,i}) i ({,,},{,,}) 2 psss i ({,,,,},{,,,,i}) PAGE 53

55 Miniml psss A pss is miniml i it os not ontin smllr psss. E is involv in prisly on miniml pss. Psss r ompos o miniml psss. T miniml psss orm pss prtitionin. i PAGE 54

56 Psss r spil s o omposition Conormn kin: 1. Comput usl strutur rom Ptri nt 2. Comput (miniml) psss n onstrut orrsponin sunts 3. Sunts provi vli omposition 4. Hn, onormn kin* n ompos/istriut! Pross isovry: 1. Comput usl strutur rom vnt lo* 2. Comput (miniml) psss n onstrut orrsponin sulos 3. Disovr sunts or sulos* 4. Mr sunts into ovrll mol PAGE 55

57 Conormn kin l l l l l l... skip xtr insurn? n ookin 4 5 xtr insurn skip xtr insurn i 8 9 in ook r 1 xtr insurn 2 onirm 3 initit k-in 6 slt r j k rivr s lins 10 l supply r out 7 k r rit r 11 PAGE 56

58 Crt Sklton l l l l l l... skip xtr insurn onormn kin n ookin 4 5 xtr insurn skip xtr insurn i 8 9 slt r in ook r 1 xtr insurn 2 onirm 3 initit k-in 6 j k rivr s lins 10 l supply r out 7 k r rit r 11 skip xtr insurn n ookin l ook r xtr insurn onirm initit k-in supply r PAGE 57

59 Nt rmnts pr pss l l l l l l skip xtr insurn skip xtr insurn xtr insurn 2 skip xtr insurn n ookin onirm onirm... n ookin 3 initit k-in l l l l l l... initit k-in 4 5 xtr insurn skip xtr insurn 6 i slt r j k rivr s lins l supply r ook r 1 xtr insurn ook r xtr insurn onirm initit k-in l supply r 7 k r rit r 11 PAGE 58

60 Suppos is xut too lt l l l l l skip xtr insurn skip xtr insurn xtr insurn 2 skip xtr insurn n ookin onirm onirm... n ookin 3 initit k-in l l l l l l... initit k-in 4 5 xtr insurn skip xtr insurn 6 i slt r j k rivr s lins l supply r ook r 1 xtr insurn ook r xtr insurn onirm initit k-in l supply r 7 k r rit r 11 PAGE 59

61 usl strutur otin usin uristis & omin knowl Disovry xmpl PAGE in out 1 in out ({,},{}) ({},{,}) ({,},{}) ({},{,}) in out 1 in out 6

62 Tool Support in ProM PAGE 61

63 Tool Support in ProM (implmnt y Eri Vrk) isovry onormn PAGE 62

64 Pss-Bs Conormn Ckin PAGE 63

65 Rsult 11 psss pss rp PAGE 64

66 Exmpl Pss (X, Y) PAGE 65

67 Pross Mol s 11 Psss (X,Y) PAGE 66

68 Dinostis pr Pss no prolms PAGE 67

69 Prolmti Pss PAGE 68

70 Disovry (no initil mol, just vnts) loritm us to riv usl rp (to trmin psss) isovry loritm (ppli pr pss) PAGE 69

71 Rsult (lp + ILP wit propr ompltion) soun WF-nt prtly ittin t vnt lo PAGE 70

72 Conlusion Pross isovry n onormn kin n ompos! Gnri ppro wit vrious orml urnts inpnnt o t tniqus us. Opn issus: Exprimntl vlution (in prorss, s Eri's prsnttion) Bttr loritms or omputin usl strutur r n (inpnnt o omposition) W r still missin sp wit iv ls PAGE 71

73 nry iint politilly orrt 1 orml (not just pitur) st (soul not tk yrs) 2 ility to ln ll onormn imnsions (itnss, prision, nrliztion, n simpliity) inl. nois provi urnts (not just st ort) soun (rsult soul t lst r o loks, t.) PAGE 72

74 Toy's sp v only ls orml st ln soun urn. lp uristi + + +/- - - nti AK + - +/- - +/- nti JB /- uzzy minr - + +/- - - Diso - + +/- - - rions SB rions LB lp lp # SMT MFM PAGE 73

Distributed Process Discovery and Conformance Checking

Distributed Process Discovery and Conformance Checking Distriut Pross Disovry n Conormn Chkin Wil M.P. vn r Alst 1,2 1 Einhovn Univrsity o Thnoloy, Einhovn, Th Nthrlns 2 Qunsln Univrsity o Thnoloy, Brisn, Austrli www.vlst.om Astrt. Pross minin thniqus hv mtur

More information

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

On the Representational Bias in Process Mining

On the Representational Bias in Process Mining On t Rprsnttionl Bis in Pross Minin W.M.P. vn r Alst Dprtmnt of Mtmtis n Computr Sin Einovn Univrsity of Tnoloy, Einovn, T Ntrlns Emil: w.m.p.v..lst@tu.nl, WWW: vlst.om Astrt Pross minin srvs ri twn t

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

Discovering Petri Nets From Event Logs

Discovering Petri Nets From Event Logs Disovring Ptri Nts From Evnt Logs W.M.P. vn r Alst n B.F. vn Dongn Dprtmnt of Mthmtis n Computr Sin, Thnish Univrsitit Einhovn, Th Nthrlns. {W.M.P.v..Alst,B.F.v.Dongn}@tu.nl Astrt. As informtion systms

More information

Lecture 7: Minimum Spanning Trees and Prim s Algorithm

Lecture 7: Minimum Spanning Trees and Prim s Algorithm Ltur : Minimum Spnning Trs n Prim s Algorithm CLRS Chptr 3 Outlin o this Ltur Spnning trs n minimum spnning trs. Th minimum spnning tr (MST) prolm. Th gnri lgorithm or MST prolm. Prim s lgorithm or th

More information

Batch Printing. Creating New Batch Print Jobs

Batch Printing. Creating New Batch Print Jobs Bth Printing Bth printing llows you to print svrl rports t on. You n print rports to printr or to PDF or PRN fil. First, though, you must st up th th print jo, n thn you must xut it. Follow th instrutions

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

AdvancedTCA Connectors acc. to PICMG 3.0

AdvancedTCA Connectors acc. to PICMG 3.0 AvnTCA Conntors. to PICMG 3.0 ERNI is nxious to support ustomrs xtnsivly n is rully ompltin t prout rn or intronnt pltorms. Tis lso inlus t ATCA (Avn Tlom Computin Arittur) stnr. Tis stnr (lso known s

More information

Functions. A is called domain of f, and B is called codomain of f. If f maps element a A to element b B, we write f (a) = b

Functions. A is called domain of f, and B is called codomain of f. If f maps element a A to element b B, we write f (a) = b Funtions CS311H: Disrt Mthmtis Funtions Instrutor: Işıl Dilli untion rom st to st ssins h lmnt o to xtly on lmnt o. is ll omin o, n is ll oomin o. I mps lmnt to lmnt, w writ () = I () =, is ll im o ; is

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

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

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

Hospitals. Internal Revenue Service Information about Schedule H (Form 990) and its instructions is at www.irs.gov/form990.

Hospitals. Internal Revenue Service Information about Schedule H (Form 990) and its instructions is at www.irs.gov/form990. SCHEDULE H Hospitls OMB No. 1545-0047 (Form 990) Complt if th orgniztion nswr "Ys" to Form 990, Prt IV, qustion 20. Atth to Form 990. Opn to Puli Dprtmnt of th Trsury Intrnl Rvnu Srvi Informtion out Shul

More information

Graph Theory Definitions

Graph Theory Definitions Grph Thory Dfinitions A grph is pir of sts (V, E) whr V is finit st ll th st of vrtis n E is st of 2-lmnt susts of V, ll th st of gs. W viw th gs s st of onntions twn th nos. Hr is n xmpl of grph G: G

More information

Preorder Traversal. Binary Tree Traversal Methods. Binary Tree Traversal Methods. Binary Tree Traversal Methods

Preorder Traversal. Binary Tree Traversal Methods. Binary Tree Traversal Methods. Binary Tree Traversal Methods Binry Tr Trvrsl Mthos Mny inry tr oprtions r on y prorming trvrsl o th inry tr. Possil Binry Tr Oprtions: Dtrmin th hight. Dtrmin th numr o nos. Mk lon. Evlut th rithmti xprssion rprsnt y inry tr. Binry

More information

SESSION 4 PLANNING THE PROJECT PROJECT PLANNING DEFINITIONS

SESSION 4 PLANNING THE PROJECT PROJECT PLANNING DEFINITIONS SSSION 4 PLNNIN TH PROJT PROJT PLNNIN Scope planning Time planning ost planning Human resource planning Procurement planning Quality planning ommunication planning INITIONS The project plan is a list of

More information

Where preparation meets opportunity. My Academic Planner. Early Academic Outreach Program (EAOP)

Where preparation meets opportunity. My Academic Planner. Early Academic Outreach Program (EAOP) Whr prprtion mts opportunity. My Ami Plnnr Erly Ami Outrh Prorm (EAOP) Follow this 4-stp pln to prpr or mission to th Univrsity o Cliorni (UC), Cliorni Stt Univrsity (CSU) n mny inpnnt olls with similr

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

One Ring to Rule them All: Service Discovery and Binding in Structured Peer-to-Peer Overlay Networks

One Ring to Rule them All: Service Discovery and Binding in Structured Peer-to-Peer Overlay Networks On Ring to Rul thm All: Srvi Disovry n Bining in Strutur Pr-to-Pr Ovrly Ntworks Migul Cstro Mirosot Rsrh, J J Thomson Clos, Cmrig, CB 0FB, UK. mstro@mirosot.om Ptr Drushl Ri Univrsity, 100 Min Strt, MS-1,

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

Shackles Ton Green Pin bow shackle with screw collar pin

Shackles Ton Green Pin bow shackle with screw collar pin .33-55 Ton Grn P skl wt srw ollr p Mtrl: n p tnsl stl, Gr 6, qun n tmpr Sty Ftor: MBL quls 6 x WLL Stnr: En 13889 n mts prormn rqurmnts o US F. Sp. RR-C-271 Typ IVA Clss 2, Gr A Fs: ot pp lvnz Tmprtur

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

B y R us se ll E ri c Wr ig ht, DV M. M as te r of S ci en ce I n V et er in ar y Me di ca l Sc ie nc es. A pp ro ve d:

B y R us se ll E ri c Wr ig ht, DV M. M as te r of S ci en ce I n V et er in ar y Me di ca l Sc ie nc es. A pp ro ve d: E ff ec ts o f El ec tr ic al ly -S ti mu la te d Si lv er -C oa te d Im pl an ts a nd B ac te ri al C on ta mi na ti on i n a Ca ni ne R ad iu s Fr ac tu re G ap M od el B y R us se ll E ri c Wr ig ht,

More information

Usability Test Checklist

Usability Test Checklist Crtifi Profssionl for Usility n Usr Exprin Usility Tsting (CPUX-UT) Vrsion.0, Jun 0 Pulishr: UXQB. V. Contt: info@uxq.org www.uxq.org Autorn: R. Molih, T. Gis, B. Rumml, O. Klug, K. Polkhn Contnt Lgn...

More information

Graph Theoretical Analysis and Design of Multistage Interconnection Networks

Graph Theoretical Analysis and Design of Multistage Interconnection Networks 637 I TRNSTIONS ON OMPUTRS, VOL. -32, NO. 7, JULY 1983 [39].. svnt,.. jski, n. J. Kuck, "utomtic sign wit pnnc grps," in Proc. 17t s. utomt. on, I omput. Soc. TMSI, 1980, pp. 506-515. [40] M.. Mcrln, "

More information

Talk Outline. Taxon coverage pattern. Part I: Partial taxon coverage. Lassoing a tree: Phylogenetic theory for sparse patterns of taxon coverage

Talk Outline. Taxon coverage pattern. Part I: Partial taxon coverage. Lassoing a tree: Phylogenetic theory for sparse patterns of taxon coverage Lssoing tr: Phylognti thory for sprs pttrns of ton ovrg Joint work with Tlk Outlin Prt 1: Disivnss Prt 2: Lssoing tr Mik Stl Anrs Drss Kthrin Hur Prt 3: Quntifying LGT [if tim?] Phylomni Novmr 10, 2011

More information

Enhancing Downlink Performance in Wireless Networks by Simultaneous Multiple Packet Transmission

Enhancing Downlink Performance in Wireless Networks by Simultaneous Multiple Packet Transmission Enhning Downlink Prormn in Wirlss Ntworks y Simultnous Multipl Pkt Trnsmission Zhngho Zhng n Yunyun Yng Dprtmnt o Eltril n Computr Enginring, Stt Univrsity o Nw York, Stony Brook, NY 11794, USA Astrt In

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

SKILL TEST IR(H) HELICOPTER SE ME Application and report form A. Udfyldes af ansøgeren/to be filled out by the applicant:

SKILL TEST IR(H) HELICOPTER SE ME Application and report form A. Udfyldes af ansøgeren/to be filled out by the applicant: SKILL TEST IR(H) HELICOPTER SE ME Applition n rport orm A. Uyls nsørn/to ill out y th pplint: CPR-nr./Dt o Birth: Crtiikt nr./lin no.: (I ny) Ustn Stt/Stt o Lin Issu: Fornvn/First nm(s): Etrnvn/Lst nm:

More information

8 Dynamic Binary Search Trees (February 8)

8 Dynamic Binary Search Trees (February 8) Evrt s or t oputrs t o. Tr ust sot, ou u sot s. Tr ust tt, ou u to or or ou o t s pp, t sp s out o otro. B, B s 7, Bro (Mr 6, 1978) A oo spot s r s o s souto to t pro. Aoous Lt s p. E Mr [Atoo Brs], Dspro

More information

Discovering Block-Structured Process Models From Event Logs Containing Infrequent Behaviour

Discovering Block-Structured Process Models From Event Logs Containing Infrequent Behaviour Disovring Blok-Strutur Pross Mols From Evnt Logs Contining Infrqunt Bhviour Snr J.J. Lmns, Dirk Fhln, n Wil M.P. vn r Alst Einhovn Univrsity of Thnology, th Nthrlns {s.j.j.lmns,.fhln, w.m.p.v..lst}@tu.nl

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

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

P U B L I C A T I O N I N T E R N E 1800 PARTIAL ORDER TECHNIQUES FOR DISTRIBUTED DISCRETE EVENT SYSTEMS: WHY YOU CAN T AVOID USING THEM

P U B L I C A T I O N I N T E R N E 1800 PARTIAL ORDER TECHNIQUES FOR DISTRIBUTED DISCRETE EVENT SYSTEMS: WHY YOU CAN T AVOID USING THEM I R I P U B L I C A T I O N I N T E R N E 1800 N o S INSTITUT DE RECHERCHE EN INFORMATIQUE ET SYSTÈMES ALÉATOIRES A PARTIAL ORDER TECHNIQUES FOR DISTRIBUTED DISCRETE EVENT SYSTEMS: WHY YOU CAN T AVOID

More information

Operational Terms: Annex G- Process diagrams for part G (Trade Effluent)

Operational Terms: Annex G- Process diagrams for part G (Trade Effluent) Oprtionl Trms: Annx G- Pross igrms for prt G (Tr Efflunt) Sptmr 2015 Pross G1 Tr Efflunt nquiris A. Tr Efflunt nquiry riv y th Rtilr Sumits Tr Efflunt nquiry rlt to issus list t (*) using Form G/ 01 Form

More information

Sample Pages from. Leveled Texts for Mathematics: Geometry

Sample Pages from. Leveled Texts for Mathematics: Geometry Smpl Pgs rom Lvl Txts or Mthmtis: Gomtry Th ollowing smpl pgs r inlu in this ownlo: Tl o Contnts Rility Chrt Smpl Pssg For orrltions to Common Cor n Stt Stnrs, pls visit http://www.thrrtmtrils.om/orrltions.

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

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

Recall from Last Time: Disjoint Set ADT

Recall from Last Time: Disjoint Set ADT 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

More information

Ethical and Professional Standards

Ethical and Professional Standards STUDY SESSION 1 Etil n Prossionl Stnrs T rins in tis stuy sssion prsnt rmwork or til onut in t invstmnt prossion y ousin on t CFA Institut Co o Etis n Stnrs o Prossionl Conut (t Co n Stnrs) s wll s t CFA

More information

ELECTRO CRIMP CONTACTS ( I ) PVT. LTD. JAS-ANZ. Certificate No. R91 / 918

ELECTRO CRIMP CONTACTS ( I ) PVT. LTD. JAS-ANZ. Certificate No. R91 / 918 PROUT TLOU LTRO RIMP ONTTS LTRO RIMP ONTTS ( I ) PVT. LT. I S SNZ ertificate R1 / LTRO RIMP ONTTS ear user,. ll of us at LTRO RIMP ONTTS have immense pleasure and pride in bringing you this catalogue,

More information

Predicting Current User Intent with Contextual Markov Models

Predicting Current User Intent with Contextual Markov Models Priting Currnt Usr Intnt with Contxtul Mrkov Mols Juli Kislv, Hong Thnh Lm, Mykol Phnizkiy Dprtmnt of Computr Sin Einhovn Univrsity of Thnology P.O. Box 513, NL-5600MB, th Nthrlns {t.l.hong, j.kislv, m.phnizkiy}@tu.nl

More information

String Fingering Diagrams

String Fingering Diagrams STRIN FINRIN IRMS F..J. sil Strin Finrin irms F..J. sil 2n Jnury 200 strt This oumnt ontins st of strin instrumnt finrin irms tht my us for hkin multipl stops n omintions with nturl hrmonis. irms (fittin

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

/* ------------------------------------------------------------------------------------

/* ------------------------------------------------------------------------------------ Pr o g r a m v a r e fo r tr a fik k b e r e g n in g e r b a s e r t p å b a s is k u r v e m e to d e n n M a tr ix * x M a tr ix E s ta lp h a B e ta ; n M a tr ix * z M a tr ix ; g e n M a tr ix X

More information

Revised Conditions (January 2009) LLOYDS BANKING GROUP SHARE ISA CONDITIONS

Revised Conditions (January 2009) LLOYDS BANKING GROUP SHARE ISA CONDITIONS Rvis Conitions (Jnury 2009) LLOYDS BANKING GROUP SHARE ISA CONDITIONS Contnts 1 Who r th prtis?... 2 Wht o wors n phrss in ol typ mn?... 3 Whn i my pln strt?... 4 How o I invst in my pln?... 5 Who owns

More information

Cayley s Formula. Graphs - II The number of labeled trees on n nodes is n n-2. Planar Graphs. Is K 5 planar? Outline. K 5 can be embedded on the torus

Cayley s Formula. Graphs - II The number of labeled trees on n nodes is n n-2. Planar Graphs. Is K 5 planar? Outline. K 5 can be embedded on the torus Grt Thortil Is In Computr Sin Vitor Amhik CS 15-251 Crngi Mllon Univrsity Cyly s Formul Grphs - II Th numr of ll trs on n nos is n n-2 Put nothr wy, it ounts th numr of spnning trs of omplt grph K n. 4

More information

Diagram Editing with Hypergraph Parser Support

Diagram Editing with Hypergraph Parser Support Copyright 1997 IEEE. Pulish in th Proings o VL 97, Sptmr 23-26, 1997 in Cpri, Itly. Prsonl us o this mtril is prmitt. Howvr, prmission to rprint/rpulish this mtril or vrtising or promotionl purposs or

More information

Data Center end users for 40G/100G and market dy nami c s for 40G/100G on S M F Adam Carter Ci s c o 1 W Now that 40GbE is part of the IEEE 802.3ba there will be a wid er array of applic ation s that will

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

Math 316 Solutions To Sample Final Exam Problems

Math 316 Solutions To Sample Final Exam Problems Solutions to Smpl Finl Exm Prolms Mth 16 1 Mth 16 Solutions To Smpl Finl Exm Prolms 1. Fin th hromti polynomils o th thr grphs low. Clrly show your stps. G 1 G G () p = p p = k(k 1) k(k 1)(k ) () Atr simpliying,

More information

Right Angle Trigonometry

Right Angle Trigonometry Righ gl Trigoomry I. si Fs d Dfiiios. Righ gl gl msurig 90. Srigh gl gl msurig 80. u gl gl msurig w 0 d 90 4. omplmry gls wo gls whos sum is 90 5. Supplmry gls wo gls whos sum is 80 6. Righ rigl rigl wih

More information

Algorithmic Aspects of Access Networks Design in B3G/4G Cellular Networks

Algorithmic Aspects of Access Networks Design in B3G/4G Cellular Networks Algorithmi Aspts o Ass Ntworks Dsign in BG/G Cllulr Ntworks Dvi Amzllg, Josph (Si) Nor,DnnyRz Computr Sin Dprtmnt Thnion, Hi 000, Isrl {mzllg,nny}@s.thnion..il Mirosot Rsrh On Mirosot Wy, Rmon, WA 980

More information

Link-Disjoint Paths for Reliable QoS Routing

Link-Disjoint Paths for Reliable QoS Routing Link-Disjoint Pths or Rlil QoS Routing Yuhun Guo, Frnno Kuiprs n Pit Vn Mighm # Shool o Eltril n Inormtion Enginring, Northrn Jiotong Univrsity, Bijing, 000, P.R. Chin Fulty o Inormtion Thnology n Systms,

More information

C e r t ifie d Se c u r e W e b

C e r t ifie d Se c u r e W e b C r t ifi d S c u r W b Z r t ifizi r t Sic h r h it im W b 1 D l gat s N ic o las M ay n c o u r t, C EO, D r am lab T c h n o lo gi s A G M ar c -A n d r é B c k, C o n su lt an t, D r am lab T c h n

More information

SCO TT G LEA SO N D EM O Z G EB R E-

SCO TT G LEA SO N D EM O Z G EB R E- SCO TT G LEA SO N D EM O Z G EB R E- EG Z IA B H ER e d it o r s N ) LICA TIO N S A N D M ETH O D S t DVD N CLUDED C o n t e n Ls Pr e fa c e x v G l o b a l N a v i g a t i o n Sa t e llit e S y s t e

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

Approximation Algorithms

Approximation Algorithms Prsnttion or us with th txtook, Alorithm Dsin n Applitions, y M. T. Goorih n R. Tmssi, Wily, 2015 Approximtion Alorithms 1 Bik Tour Suppos you i to ri iyl roun Irln you will strt in Dulin th ol is to visit

More information

Operational Procedure: ACNC Data Breach Response Plan

Operational Procedure: ACNC Data Breach Response Plan OP 2015/03 Oprtionl Prour: ACNC Dt Brh Rspons Pln This Oprtionl Prour is issu unr th uthority of th Assistnt Commissionr Gnrl Counsl n shoul r togthr with th ACNC Poliy Frmwork, whih sts out th sop, ontxt

More information

ta tio n a l s c ie n c e b y s u p p o rtin g th e e m e rg in g G rid p ro to c o ls o n W in d o w s a n d

ta tio n a l s c ie n c e b y s u p p o rtin g th e e m e rg in g G rid p ro to c o ls o n W in d o w s a n d A p p e a rs in th e P ro c e e d in g s o f th e 2 0 0 5 In te rn a tio n a l C o n fe re n c e o n C o m p u ta tio n a l S c ie n c e (IC C S 2 0 0 5 ), E m o ry U n iv e rs ity, A tla n ta, G A, M

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

Metapuzzle. Clue: A generation grew up saying this phrase.

Metapuzzle. Clue: A generation grew up saying this phrase. Mtpuzzl Solv h o th puzzls in this ook. or h solution, not th numrs in lotions,, n. Thn look up thos thrnumr os in th oook t th k o this ook. h puzzl orrspons to numr or hrtr. S i you n in th hin mss!

More information

STEEL PIPE NIPPLE BLACK AND GALVANIZED

STEEL PIPE NIPPLE BLACK AND GALVANIZED Price Sheet CWN-616 Effective June 06, 2016 Supersedes CWN-414 A Member of The Phoenix Forge Group CapProducts LTD. Phone: 519-482-5000 Fax: 519-482-7728 Toll Free: 800-265-5586 www.capproducts.com www.capitolcamco.com

More information

1. Number of questions to be answered: ALL Multiple Choice (Section A) and 3 from 5 of the short answer questions (Section B)

1. Number of questions to be answered: ALL Multiple Choice (Section A) and 3 from 5 of the short answer questions (Section B) LEEDS METROPOLITAN UNIVERSITY UK Cntr for Evnts Mngmnt (RESIT) Moul Titl: Evnts Mrkting Ativitis Ami Yr: 2011/12 Lvl: 4 Smstr: 2 Cours: BA(Hons)/ HND Evnt Mngmnt Intrnl Exminrs: Exmintion Dt: 2 n July

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

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

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

25/8/94 (previous title) 08/06/12 [15/05/13 Formal Delegations amended] 15/12/95 13/10/00 2/11/01, 9/9/05, 14/12/11 5 yearly Immediately

25/8/94 (previous title) 08/06/12 [15/05/13 Formal Delegations amended] 15/12/95 13/10/00 2/11/01, 9/9/05, 14/12/11 5 yearly Immediately Corport Poliis & Prours Finn Doumnt CPP301 Corport Trvl First Prou: Currnt Vrsion: Pst Rvisions: Rviw Cyl: Applis From: 25/8/94 (prvious titl) 08/06/12 [15/05/13 Forml Dlgtions mn] 15/12/95 13/10/00 2/11/01,

More information

Frederikshavn kommunale skolevæsen

Frederikshavn kommunale skolevæsen Frederikshavn kommunale skolevæsen Skoleåret 1969-70 V e d K: Hillers-Andersen k. s k o l e d i r e k t ø r o g Aage Christensen f u l d m æ g t i g ( Fr e d e rik sh av n E k sp r e s- T ry k k e rie

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

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

Industry regulations Jurisdictional regulations Legal defensibility Legal frameworks Legal research

Industry regulations Jurisdictional regulations Legal defensibility Legal frameworks Legal research A Dutis, Tsks, n Stps Mnging Informtion Risk n Complin 1 Monitor lgl n rgultory lnsp Engg with lgl prtmnt n othr stkholrs Intify n intrprt xisting pplil lws of ll jurisitions n rgultions Intify rsours

More information

Network Decoupling for Secure Communications in Wireless Sensor Networks

Network Decoupling for Secure Communications in Wireless Sensor Networks Ntwork Doupling for Sur Communitions in Wirlss Snsor Ntworks Wnjun Gu, Xiol Bi, Srirm Chllppn n Dong Xun Dprtmnt of Computr Sin n Enginring Th Ohio-Stt Univrsity, Columus, Ohio 43210 1277 Emil: gu, ixi,

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

Alphabet Stitch Info Color Chart

Alphabet Stitch Info Color Chart Page 1 Alphabet Stitch Info Color Chart 0 1 2 Stitch Count: 3988 Height: 2.2 Width: 1.61 Stitch Count: 2958 Width: 1.26 Stitch Count: 3628 Width: 2.01 3 4 Stitch Count: 3671 Height: 2.2 Width: 1.54 Stitch

More information

THE LAWYER S ENGLISH LANGUAGE COURSEBOOK

THE LAWYER S ENGLISH LANGUAGE COURSEBOOK THE LAWYER S ENGLISH LANGUAGE COURSEBOOK Ctrin Mson G L O B A L L E G A L E N G L I S H L T D CONTENTS Pulis in Enln y Glol Ll Enlis Lt. T Pin Tr Cntr Durm Ro Birtly County Durm DH3 2TD Enln Emil: ino@tols.o.uk

More information

B a rn e y W a r f. U r b a n S tu d ie s, V o l. 3 2, N o. 2, 1 9 9 5 3 6 1 ±3 7 8

B a rn e y W a r f. U r b a n S tu d ie s, V o l. 3 2, N o. 2, 1 9 9 5 3 6 1 ±3 7 8 U r b a n S tu d ie s, V o l. 3 2, N o. 2, 1 9 9 5 3 6 1 ±3 7 8 T e le c o m m u n ic a t io n s a n d th e C h a n g in g G e o g r a p h ie s o f K n o w le d g e T r a n s m is s io n in th e L a te

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

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

Net Promoter Industry Report

Net Promoter Industry Report Nt Promotr Inustry Rport US CONSUMER 2014 A I R L I N E S TRAVEL & HOSPITALITY AIRLINES HOTELS S A T M E T R I X. C O M / B E N C H M A R K I N G Also Avill In th Stmtrix 2014 US Consumr Rport Sris FINANCIAL

More information

A n d r e w S P o m e r a n tz, M D

A n d r e w S P o m e r a n tz, M D T e le h e a lth in V A : B r in g in g h e a lth c a r e to th e u n d e r s e r v e d in c lin ic a n d h o m e A n d r e w S P o m e r a n tz, M D N a tio n a l M e n ta l H e a lth D ir e c to r f

More information

The Splunk Guide to Operational Intelligence

The Splunk Guide to Operational Intelligence solutions ui Th Splunk Gui to Oprtionl Intllin Turn Mhin-nrt Dt into Rl-tim Visiility, Insiht n Intllin Wht is Splunk Entrpris TM? Splunk Entrpris is th pltorm or mhin t. It ollts, inxs n hrnsss th mhin

More information

Erfa rin g fra b y g g in g a v

Erfa rin g fra b y g g in g a v Erfa rin g fra b y g g in g a v m u ltim e d ia s y s te m e r Eirik M a u s e irik.m a u s @ n r.n o N R o g Im e d ia N o rs k R e g n e s e n tra l fo rs k n in g s in s titu tt in n e n a n v e n d

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

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

SECTION 9-2 Inverse of a Square Matrix

SECTION 9-2 Inverse of a Square Matrix 7 9 Matris and Dtrminants Cral A /oz M /oz /oz N Mix X 5 oz 5 oz Cral B /oz /oz /oz Mix Y oz oz Mix Z 5 oz 5 oz Protin Caroydrat Fat Cral A Cral B (A) Find t amount of protin in mix X. (B) Find t amount

More information

Some Useful Integrals of Exponential Functions

Some Useful Integrals of Exponential Functions prvious indx nxt Som Usful Intgrls of Exponntil Functions Michl Fowlr W v shown tht diffrntiting th xponntil function just multiplis it by th constnt in th xponnt, tht is to sy, d x x Intgrting th xponntil

More information

CREDIT LINE ACCOUNT AND PERSONAL LOAN APPLICATION ACCOUNT NUMBER APPLICANT ACCOUNT NUMBER CO-APPLICANT DATE

CREDIT LINE ACCOUNT AND PERSONAL LOAN APPLICATION ACCOUNT NUMBER APPLICANT ACCOUNT NUMBER CO-APPLICANT DATE pplicant Information PRINT OR TYP LL INFORMTION 1. If You live in a community property state, are You: Married Separated Unmarried (Includes Single, Divorced and Widowed) 2. Married applicants can apply

More information

The Splunk Guide to Operational Intelligence

The Splunk Guide to Operational Intelligence Th Splunk Gui to Oprtionl Intllin Turn Mhin-Gnrt Dt Into Rl-Tim Visiility, Insiht n Intllin Wht is Splunk Entrpris? Splunk Entrpris is th lin pltorm or rltim oprtionl intllin. It s th sy, st n sur wy to

More information

B rn m e d s rlig e b e h o v... 3 k o n o m i... 6. S s k e n d e tils k u d o g k o n o m is k frip la d s... 7 F o r ld re b e ta lin g...

B rn m e d s rlig e b e h o v... 3 k o n o m i... 6. S s k e n d e tils k u d o g k o n o m is k frip la d s... 7 F o r ld re b e ta lin g... V e lf rd s s e k re ta ria te t S a g s n r. 1 4 3 4 1 5 B re v id. 9 9 3 9 7 4 R e f. S O T H D ir. tlf. 4 6 3 1 4 0 0 9 s o fie t@ ro s k ild e.d k G o d k e n d e ls e s k rite rie r fo r p riv a tin

More information

Set Notation Element v is a member of set Element v is not a member of set Cardinality (number of members) of set V Set is a subset of set

Set Notation Element v is a member of set Element v is not a member of set Cardinality (number of members) of set V Set is a subset of set CS/EE 5740/6740: Computr Ai Dsign of Digitl Ciruits Chris J. Myrs Ltur 3: Sts, Rltions, n Funtions Ring: Chptr 3.1 v v S S St Nottion Elmnt v is mmr of st Elmnt v is not mmr of st Crinlity (numr of mmrs)

More information

Magic Message Maker Amaze your customers with this Gift of Caring communication piece

Magic Message Maker Amaze your customers with this Gift of Caring communication piece Magic Mssag Makr maz your customrs with this Gift of aring communication pic Girls larn th powr and impact of crativ markting with this attntion grabbing communication pic that will hlp thm o a World of

More information

FOREST LAKES MSTU BOND PROJECT F-58 SIDEWALKS, LIGHTING & PLANTING - PHASE I & IA

FOREST LAKES MSTU BOND PROJECT F-58 SIDEWALKS, LIGHTING & PLANTING - PHASE I & IA ORST KS STU TPON: CNTURY INK P.O. OX 4 NPS,. 3414 T: [3] 63-631 ON PROJCT -58 SIWKS, IGTING & PNTING - PS I & I RVIWING GNCIS COIR COUNTY COIR COUNTY COUNITY VOPNT SRVICS 8 NORT ORSSO RIV NPS,. 3414 T:

More information

Business Process Simulation for Operational Decision Support

Business Process Simulation for Operational Decision Support Businss Procss Simultion for Oprtionl Dcision Support M. T. Wynn 1, M. Dums 1, C. J. Fidg 1, A. H. M. tr Hofstd 1, nd W. M. P. vn dr Alst 1,2 1 Fculty of Informtion Tchnology, Qunslnd Univrsity of Tchnology,

More information

JG, LG 2/6 3/6 NG, PG

JG, LG 2/6 3/6 NG, PG s Cylinr Lok Kit for Stor Enrgy Oprtor ( SEO ) Dispositivo bloquo por llv pr ionminto motorizo. ( SEO ) Dispositf vrrouillg séurité pour ommn motorisé. ( SEO ) Instlltion Instrutions / Instrutivo Instlión

More information

IncrEase: A Tool for Incremental Planning of Rural Fixed Broadband Wireless Access Networks

IncrEase: A Tool for Incremental Planning of Rural Fixed Broadband Wireless Access Networks InrEs: A Tool or Inrmntl Plnning o Rurl Fix Bron Wirlss Ass Ntworks Giomo Brnri n Mhsh K. Mrin Shool o Inormtis Th Univrsity o Einurgh, UK Frnso Tlmon n Dmitry Rykovnov EOLO L NGI SpA, Miln, Itly Astrt

More information

A MESSAGE FROM CLAIMTEK

A MESSAGE FROM CLAIMTEK A MESSAGE FROM CLAIMTEK Dr Hlthr Billing Profssionl, Thnk you for tking tim to rviw this rohur. If you'v n looking for mil prti mngmnt n illing softwr tht mks your work sy, urt, n njoyl, MOffi is your

More information

Attachment 1 Package D1-1 (Five (5) Locations) 9-26-13Revised 11-1-13

Attachment 1 Package D1-1 (Five (5) Locations) 9-26-13Revised 11-1-13 Space Identifier Near Gate ttachment Package - (Five (5) Locations) 9-26-3Revised --3 Proposed oncept Square Footage Minimum nnual Guarantee Term in Years --Z0 ustoms urrency xchange 98 $20,500 75-2-S06

More information