Expert System. Knowledge-Based Systems. Page 1. Development of KB Systems. Knowledge base. Expert system = Structured computer program
|
|
- Alisha Stanley
- 5 years ago
- Views:
Transcription
1 Knowlg-Bs Systms Exprt Systm Anrw Kusik 2139 Smns Cntr Iow City, Iow Tl: Fx: Knowlg s Infrn Engin Dt Exprt systm = Strutur omputr progrm Dvlopmnt of KB Systms Knowlg-Bs Systm Usr Tool uilr Domin xprt Usr intrf moul ES Shll KB systm uiling tool Knowlg nginr KB systm Clril Stff En-usr Knowlg s Infrn ngin Knowlgquisition moul Working mmory DM Softwr Exprts Pg 1 1
2 Knowlg Rprsnttion Mthos First-orr logi Proution ruls (inluing strutur proution ruls) Frms Smnti ntworks IF (onitions) THEN (onlusions) EXAMPLE IF Proution Ruls prt Pi is to ispth to mhin M tht is oupi y nothr prt Pj THEN hk vilility of n ltrntiv mhin M Avntgs of Proution Ruls Bsi Rsoning Strtgis Th us of rul n sily xplin to th systm usr Dvloprs n usrs n moify som ruls without rking th ntir systm Nw knowlg n inorport into th systm simply y ing nw ruls without onrn of how thy fit into th ovrll knowlg s Exmpl Ruls Bs: Forwr rsoning Bkwr rsoning R1: IF THEN Gol R2: IF THEN R3: IF THEN Pg 2 2
3 R1: IF THEN Gol Infrn (An/OR) tr IF sussmly sussmly r vill THEN initit th ssmly pross Gol R2: IF THEN IF prt prt hv n ssml THEN sussmly is vill Ruls: R1: IF THEN Gol R2: IF THEN R3: IF THEN Gol R1: IF THEN Gol R2: IF THEN R3: IF THEN R3: IF sunny, THEN hot insi R2: IF hot insi humi, THEN us AC R1: IF us AC mny popl, THEN swith on unit 2 Gol Givn th fts:,, n, riv gol Ruls: R1: IF THEN Gol R2: IF THEN R3: IF THEN Forwr Rsoning Gol R1 fir R2 fir R3 fir Infrn tr Pg 3 3
4 Givn th gol, riv fts tht prov it Bkwr Rsoning Ruls: R1: IF THEN Gol R2: IF THEN R3: IF THEN Gol R1 is stisfi, whil is not R3 R2 is stisfi, whil is not Forwr rsoning Bkwr rsoning Ruls: R1: IF THEN Gol R2: IF THEN R3: IF THEN Gol Infrn irtion Rsoning Summry Top-own infrn (Bkwr rsoning) n Infrn irtion is tru, is stisfi; thn th gol is stisfi Bottom-up infrn (Forwr rsoning) Unrtinty in Rul Bss Rul R1: IF A1 B1 THEN D1 Givn rtinty ftors: CF(A1) = CA1 CF(B1) = CB1 Th rtinty ftor of rul R1 CF(D1) = CF(R1) = CF(A1 B1) = min{cf(a1), CF(B1)} = min{ca1, CB2} Rul R2: IF A2 OR B2 Th rtinty ftor of Rul R2 THEN D2 CF(D2) = CF(R2) = CF(A2 OR B2) = mx{cf(a2), CF(B2)} = mx{ca2, CB2} Pg 4 4
5 C Rul R3: IF A1 B1 THEN D1 CF = R3.9 Crtinty ftor of R3 CF(D1) = CF(R3) = min{ca1, CB1} /OR tr with thr ruls A R B Rul R4: IF A2 OR B2 THEN D2 CF = Crtinty ftor of R4 CF(D2) = CF(R4) = mx{ca2, CB2} R1: IF F G THEN D R2: IF D E THEN A R3: IF A B THEN C D R E.8.9 F G Givn CF(F) =.8, CF(G) =.9, CF(E) =.95, n CF(B) =.75 n frtinty ftors of ruls R1, R2, n R3 CF(R1) =.85, CF(R2) =.9, n CF(R3) =.9 Dtrmin Crtinty ftors of D, A, n C CF(D) = min{cf(f), CF(G)}. CF(R1) =.6800 CF(A) = min{cf(d), CF(E)}. CF(R2) =.6120 CF(C) = min{cf(a), CF(B)}. CF(R3) =.5508 F D R A R2 G.9 C R E.75 B Givn two proution ruls n th orrsponing rtinty ftors: Rul R1: IF A1 B1 THEN D CF = 1 Rul R2: IF A2 OR B2 THEN D CF = 2 Rliility nlogy Th omin vin CF(R1, R2) = * 2 = 1 + 2(1-1) r1 r2 Pg 5 5
6 EXAMPLE: Comin Evin Rul R1: IF th infltion rt is lss thn 5% THEN stok mrkt pris go up CF = 1 = 0.7 Rul R2: IF unmploymnt rt is lss thn 7% THEN stok mrkt pris go up CF = 2 = 0.6 Th omin vin is omput s follows: KNOWLEDGE ACQUISITION METHODS KB systm intrfs Protool nlysis Nurl ntworks Dt mining CF(R1, R2) = * 2 = = 0.88 Pg 6 6
Knowledge-Based Systems. Outline 1. Outline 2. Expert System. Page 1. Development of KB Systems. CI = Computational Intelligence.
Knowldg-Bsd Systms Andrw Kusik, Profssor 9 Smns Cntr Iow City, Iow - 7 ndrw-kusik@uiow.du http://www.in.uiow.du/~nkusik Tl: 9-9 Fx: 9-9 Outlin INTRODUCTION KNOWLEDGE REPRESENTATION - First-Ordr Logi -
More informationWhy the Junction Tree Algorithm? The Junction Tree Algorithm. Clique Potential Representation. Overview. Chris Williams 1.
Why th Juntion Tr lgorithm? Th Juntion Tr lgorithm hris Willims 1 Shool of Informtis, Univrsity of Einurgh Otor 2009 Th JT is gnrl-purpos lgorithm for omputing (onitionl) mrginls on grphs. It os this y
More informationConstructive 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 informationMultipoint Alternate Marking method for passive and hybrid performance monitoring
Multipoint Altrnt Mrkin mtho or pssiv n hyri prormn monitorin rt-iool-ippm-multipoint-lt-mrk-00 Pru, Jul 2017, IETF 99 Giuspp Fiool (Tlom Itli) Muro Coilio (Tlom Itli) Amo Spio (Politnio i Torino) Riro
More informationQUESTIONS BEGIN HERE!
Points miss: Stunt's Nm: Totl sor: /100 points Est Tnnss Stt Univrsity Dprtmnt of Computr n Informtion Sins CSCI 710 (Trnoff) Disrt Struturs TEST for Fll Smstr, 00 R this for strtin! This tst is los ook
More informationCSE 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 informationUsing the Printable Sticker Function. Using the Edit Screen. Computer. Tablet. ScanNCutCanvas
SnNCutCnvs Using th Printl Stikr Funtion On-o--kin stikrs n sily rt y using your inkjt printr n th Dirt Cut untion o th SnNCut mhin. For inormtion on si oprtions o th SnNCutCnvs, rr to th Hlp. To viw th
More informationA Simple Code Generator. Code generation Algorithm. Register and Address Descriptors. Example 3/31/2008. Code Generation
A Simpl Co Gnrtor Co Gnrtion Chptr 8 II Gnrt o for singl si lok How to us rgistrs? In most mhin rhitturs, som or ll of th oprnsmust in rgistrs Rgistrs mk goo tmporris Hol vlus tht r omput in on si lok
More informationCS61B Lecture #33. Administrivia: Autograder will run this evening. Today s Readings: Graph Structures: DSIJ, Chapter 12
Aministrivi: CS61B Ltur #33 Autogrr will run this vning. Toy s Rings: Grph Struturs: DSIJ, Chptr 12 Lst moifi: W Nov 8 00:39:28 2017 CS61B: Ltur #33 1 Why Grphs? For xprssing non-hirrhilly rlt itms Exmpls:
More information12/3/12. Outline. Part 10. Graphs. Circuits. Euler paths/circuits. Euler s bridge problem (Bridges of Konigsberg Problem)
12/3/12 Outlin Prt 10. Grphs CS 200 Algorithms n Dt Struturs Introution Trminology Implmnting Grphs Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 1 Ciruits Cyl 2 Eulr
More information5/9/13. Part 10. Graphs. Outline. Circuits. Introduction Terminology Implementing Graphs
Prt 10. Grphs CS 200 Algorithms n Dt Struturs 1 Introution Trminology Implmnting Grphs Outlin Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 2 Ciruits Cyl A spil yl
More informationMULTIPLE-LEVEL LOGIC OPTIMIZATION II
MUTIPE-EVE OGIC OPTIMIZATION II Booln mthos Eploit Booln proprtis Giovnni D Mihli Don t r onitions Stnfor Univrsit Minimition of th lol funtions Slowr lgorithms, ttr qulit rsults Etrnl on t r onitions
More information# 1 ' 10 ' 100. Decimal point = 4 hundred. = 6 tens (or sixty) = 5 ones (or five) = 2 tenths. = 7 hundredths.
How os it work? Pl vlu o imls rprsnt prts o whol numr or ojt # 0 000 Tns o thousns # 000 # 00 Thousns Hunrs Tns Ons # 0 Diml point st iml pl: ' 0 # 0 on tnth n iml pl: ' 0 # 00 on hunrth r iml pl: ' 0
More informationIn order to learn which questions have been answered correctly: 1. Print these pages. 2. Answer the questions.
Crystl Rports for Visul Stuio.NET 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
More informationGarnir Polynomial and their Properties
Univrsity of Cliforni, Dvis Dprtmnt of Mthmtis Grnir Polynomil n thir Proprtis Author: Yu Wng Suprvisor: Prof. Gorsky Eugny My 8, 07 Grnir Polynomil n thir Proprtis Yu Wng mil: uywng@uvis.u. In this ppr,
More informationCSE 373. Graphs 1: Concepts, Depth/Breadth-First Search reading: Weiss Ch. 9. slides created by Marty Stepp
CSE 373 Grphs 1: Conpts, Dpth/Brth-First Srh ring: Wiss Ch. 9 slis rt y Mrty Stpp http://www.s.wshington.u/373/ Univrsity o Wshington, ll rights rsrv. 1 Wht is grph? 56 Tokyo Sttl Soul 128 16 30 181 140
More informationWeighted graphs -- reminder. Data Structures LECTURE 15. Shortest paths algorithms. Example: weighted graph. Two basic properties of shortest paths
Dt Strutur LECTURE Shortt pth lgorithm Proprti of hortt pth Bllmn-For lgorithm Dijktr lgorithm Chptr in th txtook (pp ). Wight grph -- rminr A wight grph i grph in whih g hv wight (ot) w(v i, v j ) >.
More informationModule graph.py. 1 Introduction. 2 Graph basics. 3 Module graph.py. 3.1 Objects. CS 231 Naomi Nishimura
Moul grph.py CS 231 Nomi Nishimur 1 Introution Just lik th Python list n th Python itionry provi wys of storing, ssing, n moifying t, grph n viw s wy of storing, ssing, n moifying t. Bus Python os not
More informationProblem solving by search
Prolm solving y srh Tomáš voo Dprtmnt o Cyrntis, Vision or Roots n Autonomous ystms Mrh 5, 208 / 3 Outlin rh prolm. tt sp grphs. rh trs. trtgis, whih tr rnhs to hoos? trtgy/algorithm proprtis? Progrmming
More informationDUET WITH DIAMONDS COLOR SHIFTING BRACELET By Leslie Rogalski
Dut with Dimons Brlt DUET WITH DIAMONDS COLOR SHIFTING BRACELET By Lsli Roglski Photo y Anrw Wirth Supruo DUETS TM from BSmith rt olor shifting fft tht mks your work tk on lif of its own s you mov! This
More informationGraphs. CSC 1300 Discrete Structures Villanova University. Villanova CSC Dr Papalaskari
Grphs CSC 1300 Disrt Struturs Villnov Univrsity Grphs Grphs r isrt struturs onsis?ng of vr?s n gs tht onnt ths vr?s. Grphs n us to mol: omputr systms/ntworks mthm?l rl?ons logi iruit lyout jos/prosss f
More informationCS 461, Lecture 17. Today s Outline. Example Run
Prim s Algorithm CS 461, Ltur 17 Jr Si Univrsity o Nw Mxio In Prim s lgorithm, th st A mintin y th lgorithm orms singl tr. Th tr strts rom n ritrry root vrtx n grows until it spns ll th vrtis in V At h
More informationCS 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 informationRegister Allocation. How to assign variables to finitely many registers? What to do when it can t be done? How to do so efficiently?
Rgistr Allotion Rgistr Allotion How to ssign vrils to initly mny rgistrs? Wht to o whn it n t on? How to o so iintly? Mony, Jun 3, 13 Mmory Wll Disprity twn CPU sp n mmory ss sp improvmnt Mony, Jun 3,
More informationGraphs. Graphs. Graphs: Basic Terminology. Directed Graphs. Dr Papalaskari 1
CSC 00 Disrt Struturs : Introuon to Grph Thory Grphs Grphs CSC 00 Disrt Struturs Villnov Univrsity Grphs r isrt struturs onsisng o vrs n gs tht onnt ths vrs. Grphs n us to mol: omputr systms/ntworks mthml
More informationSolutions for HW11. Exercise 34. (a) Use the recurrence relation t(g) = t(g e) + t(g/e) to count the number of spanning trees of v 1
Solutions for HW Exris. () Us th rurrn rltion t(g) = t(g ) + t(g/) to ount th numr of spnning trs of v v v u u u Rmmr to kp multipl gs!! First rrw G so tht non of th gs ross: v u v Rursing on = (v, u ):
More informationSection 10.4 Connectivity (up to paths and isomorphism, not including)
Toy w will isuss two stions: Stion 10.3 Rprsnting Grphs n Grph Isomorphism Stion 10.4 Conntivity (up to pths n isomorphism, not inluing) 1 10.3 Rprsnting Grphs n Grph Isomorphism Whn w r working on n lgorithm
More informationWalk Like a Mathematician Learning Task:
Gori Dprtmnt of Euction Wlk Lik Mthmticin Lrnin Tsk: Mtrics llow us to prform mny usful mthmticl tsks which orinrily rquir lr numbr of computtions. Som typs of problms which cn b on fficintly with mtrics
More informationFormal Concept Analysis
Forml Conpt Anlysis Conpt intnts s losd sts Closur Systms nd Implitions 4 Closur Systms 0.06.005 Nxt-Closur ws dvlopd y B. Gntr (984). Lt M = {,..., n}. A M is ltilly smllr thn B M, if B A if th smllst
More information, 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 informationS i m p l i f y i n g A l g e b r a SIMPLIFYING ALGEBRA.
S i m p l i y i n g A l g r SIMPLIFYING ALGEBRA www.mthltis.o.nz Simpliying SIMPLIFYING Algr ALGEBRA Algr is mthmtis with mor thn just numrs. Numrs hv ix vlu, ut lgr introus vrils whos vlus n hng. Ths
More informationAnalysis for Balloon Modeling Structure based on Graph Theory
Anlysis for lloon Moling Strutur bs on Grph Thory Abstrt Mshiro Ur* Msshi Ym** Mmoru no** Shiny Miyzki** Tkmi Ysu* *Grut Shool of Informtion Sin, Ngoy Univrsity **Shool of Informtion Sin n Thnology, hukyo
More informationDYNAMIC PROTOTYPE DEVELOPMENT RPA GENERAL MAINTENANCE HANGAR DRAWING LIST
IR OR IVIL NGINR NTR YNMI PROTOTYP VLOPMNT RP GNRL MINTNN HNGR INL RWING LIST NM -1 OVR -1 MOULS -2 MOULS -3 MOULS -4 MOULS -5 MOULS -6 MOULS -7 PROO O ONPT 1 ( PO 1) -8 PROO O ONPT 2 ( PO 2) PHS: INL
More informationMinimum Spanning Trees
Minimum Spnning Trs Minimum Spnning Trs Problm A town hs st of houss nd st of rods A rod conncts nd only houss A rod conncting houss u nd v hs rpir cost w(u, v) Gol: Rpir nough (nd no mor) rods such tht:
More informationFundamental Algorithms for System Modeling, Analysis, and Optimization
Fundmntl Algorithms for Sstm Modling, Anlsis, nd Optimiztion Edwrd A. L, Jijt Rohowdhur, Snjit A. Sshi UC Brkl EECS 144/244 Fll 2011 Copright 2010-11, E. A. L, J. Rohowdhur, S. A. Sshi, All rights rsrvd
More informationOutline. 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 informationFeatures and Application
I--26482 ommril rsion turs n pplitions ris I turs n pplition ro-ltri onntor hs rls ommril vrsion o th I--26482 sris 1 solr onntors mployin rvolutionry insrt molin thnoloy n will ollow this rls with Q vrsion
More informationCSC2542 State-Space Planning
CSC2542 Stte-Spe Plnning Sheil MIlrith Deprtment of Computer Siene University of Toronto Fll 2010 1 Aknowlegements Some the slies use in this ourse re moifitions of Dn Nu s leture slies for the textook
More informationNumbering Boundary Nodes
Numring Bounry Nos Lh MBri Empori Stt Univrsity August 10, 2001 1 Introution Th purpos of this ppr is to xplor how numring ltril rsistor ntworks ffts thir rspons mtrix, Λ. Morovr, wht n lrn from Λ out
More informationOutline. Circuits. Euler paths/circuits 4/25/12. Part 10. Graphs. Euler s bridge problem (Bridges of Konigsberg Problem)
4/25/12 Outlin Prt 10. Grphs CS 200 Algorithms n Dt Struturs Introution Trminology Implmnting Grphs Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 1 2 Eulr s rig prolm
More informationPaths. Connectivity. Euler and Hamilton Paths. Planar graphs.
Pths.. Eulr n Hmilton Pths.. Pth D. A pth rom s to t is squn o gs {x 0, x 1 }, {x 1, x 2 },... {x n 1, x n }, whr x 0 = s, n x n = t. D. Th lngth o pth is th numr o gs in it. {, } {, } {, } {, } {, } {,
More informationAn undirected graph G = (V, E) V a set of vertices E a set of unordered edges (v,w) where v, w in V
Unirt Grphs An unirt grph G = (V, E) V st o vrtis E st o unorr gs (v,w) whr v, w in V USE: to mol symmtri rltionships twn ntitis vrtis v n w r jnt i thr is n g (v,w) [or (w,v)] th g (v,w) is inint upon
More informationFull Review Condominium
Full Rviw Conominium I. Bsi Projt Inormtion 1 Projt Lgl Nm 2 Projt Physil Arss 3 HOA Mngmnt Arss 4 HOA Nm (i irnt rom Projt Lgl Nm) 5 HOA Tx ID # 6 HOA Mngmnt Compny Tx ID # 7 Nm o Mstr or Umrll Assoition
More informationA Low Noise and Reliable CMOS I/O Buffer for Mixed Low Voltage Applications
Proings of th 6th WSEAS Intrntionl Confrn on Miroltronis, Nnoltronis, Optoltronis, Istnul, Turky, My 27-29, 27 32 A Low Nois n Rlil CMOS I/O Buffr for Mix Low Voltg Applitions HWANG-CHERNG CHOW n YOU-GANG
More information(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely
. DETERMINANT.. Dtrminnt. Introution:I you think row vtor o mtrix s oorint o vtors in sp, thn th gomtri mning o th rnk o th mtrix is th imnsion o th prlllppi spnn y thm. But w r not only r out th imnsion,
More informationCh 1.2: Solutions of Some Differential Equations
Ch 1.2: Solutions of Som Diffrntil Equtions Rcll th fr fll nd owl/mic diffrntil qutions: v 9.8.2v, p.5 p 45 Ths qutions hv th gnrl form y' = y - b W cn us mthods of clculus to solv diffrntil qutions of
More informationCSC Design and Analysis of Algorithms. Example: Change-Making Problem
CSC 801- Dsign n Anlysis of Algorithms Ltur 11 Gry Thniqu Exmpl: Chng-Mking Prolm Givn unlimit mounts of oins of nomintions 1 > > m, giv hng for mount n with th lst numr of oins Exmpl: 1 = 25, 2 =10, =
More informationMath 61 : Discrete Structures Final Exam Instructor: Ciprian Manolescu. You have 180 minutes.
Nm: UCA ID Numr: Stion lttr: th 61 : Disrt Struturs Finl Exm Instrutor: Ciprin nolsu You hv 180 minuts. No ooks, nots or lultors r llow. Do not us your own srth ppr. 1. (2 points h) Tru/Fls: Cirl th right
More informationV={A,B,C,D,E} E={ (A,D),(A,E),(B,D), (B,E),(C,D),(C,E)}
Introution Computr Sin & Enginring 423/823 Dsign n Anlysis of Algorithms Ltur 03 Elmntry Grph Algorithms (Chptr 22) Stphn Sott (Apt from Vinohnrn N. Vriym) I Grphs r strt t typs tht r pplil to numrous
More informationGraph Isomorphism. Graphs - II. Cayley s Formula. Planar Graphs. Outline. Is K 5 planar? The number of labeled trees on n nodes is n n-2
Grt Thortil Is In Computr Sin Vitor Amhik CS 15-251 Ltur 9 Grphs - II Crngi Mllon Univrsity Grph Isomorphism finition. Two simpl grphs G n H r isomorphi G H if thr is vrtx ijtion V H ->V G tht prsrvs jny
More informationCONTINUITY AND DIFFERENTIABILITY
MCD CONTINUITY AND DIFFERENTIABILITY NCERT Solvd mpls upto th sction 5 (Introduction) nd 5 (Continuity) : Empl : Chck th continuity of th function f givn by f() = + t = Empl : Emin whthr th function f
More informationOutline. 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 informationPush trolley capacities from 1 2 through 10 Ton Geared trolley capacities from 1 2 through 100 Ton
H o i s t n T r o l l y C o m i n t i o n s Push trolly cpcitis from 2 through 0 Ton Gr trolly cpcitis from 2 through 00 Ton CB n CF hn chin hoists cn suspn from ithr PT push trollys or GT gr trollys.
More informationProperties of Hexagonal Tile local and XYZ-local Series
1 Proprtis o Hxgonl Til lol n XYZ-lol Sris Jy Arhm 1, Anith P. 2, Drsnmik K. S. 3 1 Dprtmnt o Bsi Sin n Humnitis, Rjgiri Shool o Enginring n, Thnology, Kkkn, Ernkulm, Krl, Ini. jyjos1977@gmil.om 2 Dprtmnt
More informationV={A,B,C,D,E} E={ (A,D),(A,E),(B,D), (B,E),(C,D),(C,E)}
s s of s Computr Sin & Enginring 423/823 Dsign n Anlysis of Ltur 03 (Chptr 22) Stphn Sott (Apt from Vinohnrn N. Vriym) s of s s r strt t typs tht r pplil to numrous prolms Cn ptur ntitis, rltionships twn
More informationUNCORRECTED SAMPLE PAGES 4-1. Naming fractions KEY IDEAS. 1 Each shape represents ONE whole. a i ii. b i ii
- Nming frtions Chptr Frtions Eh shp rprsnts ONE whol. i ii Wht frtion is shdd? Writ s frtion nd in words. Wht frtion is not shdd? Writ s frtion nd in words. i ii i ii Writ s mny diffrnt frtions s you
More informationCOMPLEXITY OF COUNTING PLANAR TILINGS BY TWO BARS
OMPLXITY O OUNTING PLNR TILINGS Y TWO RS KYL MYR strt. W show tht th prolm o trmining th numr o wys o tiling plnr igur with horizontl n vrtil r is #P-omplt. W uil o o th rsults o uquir, Nivt, Rmil, n Roson
More informationThis chapter covers special properties of planar graphs.
Chptr 21 Plnr Grphs This hptr ovrs spil proprtis of plnr grphs. 21.1 Plnr grphs A plnr grph is grph whih n b rwn in th pln without ny gs rossing. Som piturs of plnr grph might hv rossing gs, but it s possibl
More informationExam 1 Solution. CS 542 Advanced Data Structures and Algorithms 2/14/2013
CS Avn Dt Struturs n Algorithms Exm Solution Jon Turnr //. ( points) Suppos you r givn grph G=(V,E) with g wights w() n minimum spnning tr T o G. Now, suppos nw g {u,v} is to G. Dsri (in wors) mtho or
More informationCycles 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 informationECE 407 Computer Aided Design for Electronic Systems. Circuit Modeling and Basic Graph Concepts/Algorithms. Instructor: Maria K. Michael.
0 Computr i Dsign or Eltroni Systms Ciruit Moling n si Grph Conptslgorithms Instrutor: Mri K. Mihl MKM - Ovrviw hviorl vs. Struturl mols Extrnl vs. Intrnl rprsnttions Funtionl moling t Logi lvl Struturl
More informationECE COMBINATIONAL BUILDING BLOCKS - INVEST 13 DECODERS AND ENCODERS
C 24 - COMBINATIONAL BUILDING BLOCKS - INVST 3 DCODS AND NCODS FALL 23 AP FLZ To o "wll" on this invstition you must not only t th riht nswrs ut must lso o nt, omplt n onis writups tht mk ovious wht h
More informationDigital Signal Processing, Fall 2006
Digital Signal Prossing, Fall 006 Ltur 7: Filtr Dsign Zhng-ua an Dpartmnt of Eltroni Systms Aalborg Univrsity, Dnmar t@om.aau. Cours at a glan MM Disrt-tim signals an systms Systm MM Fourir-omain rprsntation
More informationFSA. CmSc 365 Theory of Computation. Finite State Automata and Regular Expressions (Chapter 2, Section 2.3) ALPHABET operations: U, concatenation, *
CmSc 365 Thory of Computtion Finit Stt Automt nd Rgulr Exprssions (Chptr 2, Sction 2.3) ALPHABET oprtions: U, conctntion, * otin otin Strings Form Rgulr xprssions dscri Closd undr U, conctntion nd * (if
More informationTABLE OF CONTENTS ASSEMBLY INSTRUCTIONS SHEET 1 OF 8 TABLE OF CONTENTS PAGE NUMBER DESCRIPTION B 2 PARTS LIST AND LAYOUT 3-5 PARTS A-D DETAIL DRAWINGS
TL O ONTNTS SHT O TL O ONTNTS PG NUMR SRIPTION PRTS LIST N LYOUT - PRTS - TIL RWINGS - STP Y STP SSMLY INSTRUTIONS TH INORMTION ONTIN IN THIS RWING IS TH SOL PROPRTY O STGING IMNSIONS IN. NY RPROUTION
More informationEXAMPLE 87.5" APPROVAL SHEET APPROVED BY /150HP DUAL VFD CONTROL ASSEMBLY CUSTOMER NAME: CAL POLY SLO FINISH: F 20
XMPL XMPL RVISIONS ZON RV. SRIPTION T PPROV 0.00 THIS IS N PPROVL RWING OR YOUR ORR. OR MNUTURING N GIN, THIS RWING MUST SIGN N RTURN TO MOTION INUSTRIS. NY HNGS M TO THIS RWING, TR MNUTURING HS GUN WILL
More informationCS200: Graphs. Graphs. Directed Graphs. Graphs/Networks Around Us. What can this represent? Sometimes we want to represent directionality:
CS2: Grphs Prihr Ch. 4 Rosn Ch. Grphs A olltion of nos n gs Wht n this rprsnt? n A omputr ntwork n Astrtion of mp n Soil ntwork CS2 - Hsh Tls 2 Dirt Grphs Grphs/Ntworks Aroun Us A olltion of nos n irt
More informationQUESTIONS BEGIN HERE!
Points miss: Stunt's Nm: Totl sor: /100 points Est Tnnss Stt Univrsity Dprtmnt o Computr n Inormtion Sins CSCI 2710 (Trno) Disrt Struturs TEST or Sprin Smstr, 2005 R this or strtin! This tst is los ook
More informationSimilarity Search. The Binary Branch Distance. Nikolaus Augsten.
Similrity Srh Th Binry Brnh Distn Nikolus Augstn nikolus.ugstn@sg..t Dpt. of Computr Sins Univrsity of Slzurg http://rsrh.uni-slzurg.t Vrsion Jnury 11, 2017 Wintrsmstr 2016/2017 Augstn (Univ. Slzurg) Similrity
More information5/7/13. Part 10. Graphs. Theorem Theorem Graphs Describing Precedence. Outline. Theorem 10-1: The Handshaking Theorem
Thorm 10-1: Th Hnshkin Thorm Lt G=(V,E) n unirt rph. Thn Prt 10. Grphs CS 200 Alorithms n Dt Struturs v V (v) = 2 E How mny s r thr in rph with 10 vrtis h of r six? 10 * 6 /2= 30 1 Thorm 10-2 An unirt
More informationME 522 PRINCIPLES OF ROBOTICS. FIRST MIDTERM EXAMINATION April 19, M. Kemal Özgören
ME 522 PINCIPLES OF OBOTICS FIST MIDTEM EXAMINATION April 9, 202 Nm Lst Nm M. Kml Özgörn 2 4 60 40 40 0 80 250 USEFUL FOMULAS cos( ) cos cos sin sin sin( ) sin cos cos sin sin y/ r, cos x/ r, r 0 tn 2(
More information1 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 informationXML and Databases. Outline. Recall: Top-Down Evaluation of Simple Paths. Recall: Top-Down Evaluation of Simple Paths. Sebastian Maneth NICTA and UNSW
Smll Pth Quiz ML n Dtss Cn you giv n xprssion tht rturns th lst / irst ourrn o h istint pri lmnt? Ltur 8 Strming Evlution: how muh mmory o you n? Sstin Mnth NICTA n UNSW
More informationPage 1. Question 19.1b Electric Charge II Question 19.2a Conductors I. ConcepTest Clicker Questions Chapter 19. Physics, 4 th Edition James S.
ConTst Clikr ustions Chtr 19 Physis, 4 th Eition Jms S. Wlkr ustion 19.1 Two hrg blls r rlling h othr s thy hng from th iling. Wht n you sy bout thir hrgs? Eltri Chrg I on is ositiv, th othr is ngtiv both
More informationNP-Completeness. CS3230 (Algorithm) Traveling Salesperson Problem. What s the Big Deal? Given a Problem. What s the Big Deal? What s the Big Deal?
NP-Compltnss 1. Polynomil tim lgorithm 2. Polynomil tim rution 3.P vs NP 4.NP-ompltnss (som slis y P.T. Um Univrsity o Txs t Dlls r us) Trvling Slsprson Prolm Fin minimum lngth tour tht visits h ity on
More informationJournal of Solid Mechanics and Materials Engineering
n Mtrils Enginring Strss ntnsit tor of n ntrf Crk in Bon Plt unr Uni-Axil Tnsion No-Aki NODA, Yu ZHANG, Xin LAN, Ysushi TAKASE n Kzuhiro ODA Dprtmnt of Mhnil n Control Enginring, Kushu nstitut of Thnolog,
More informationWIR OLOR O: K - LK R - ROWN - RK LU G - RK GRN GY - GRY L - LIGHT LU LG - LIGHT GRN OR - ORNG PK - PINK R - R YL - YLLOW VT - VIO WT - WHIT NOTS: ) LL ONNTORS R SHOWN IN TH LO POSITION. ) SPIL USTOMR OPTIONS
More informationb. How many ternary words of length 23 with eight 0 s, nine 1 s and six 2 s?
MATH 3012 Finl Exm, My 4, 2006, WTT Stunt Nm n ID Numr 1. All our prts o this prolm r onrn with trnry strings o lngth n, i.., wors o lngth n with lttrs rom th lpht {0, 1, 2}.. How mny trnry wors o lngth
More informationExtracting Propositional Rules from Feed-forward Neural Networks by Means of Binary Decision Diagrams
Extrating Propositional Ruls from F-forwar Nural Ntworks by Mans of Binary Dision Diagrams Sbastian Bar Dpartmnt of Computr Sin, Univrsity of Rostok, Grmany sbastian.bar@uni-rostok. Abstrat W isuss how
More informationBasic Polyhedral theory
Basic Polyhdral thory Th st P = { A b} is calld a polyhdron. Lmma 1. Eithr th systm A = b, b 0, 0 has a solution or thr is a vctorπ such that π A 0, πb < 0 Thr cass, if solution in top row dos not ist
More informationCONNECTOR SYMBOL A SPLICE WIRE GAUGE CHART:
RWING INX ONNTOR LOING IGRMS...--5--- ONNTOR LOTING IGRM...9 POWR ISTRIUTION...0- GROUN ISTRIUTION... SWITHS...-5 WIPR SYSTM... ORWR LMP WIRING... RR LIGHT WIRING-STNR...-9 LRN LIGHT SYSTM...0 RONT LRN
More informationCS 241 Analysis of Algorithms
CS 241 Anlysis o Algorithms Prossor Eri Aron Ltur T Th 9:00m Ltur Mting Lotion: OLB 205 Businss HW6 u lry HW7 out tr Thnksgiving Ring: Ch. 22.1-22.3 1 Grphs (S S. B.4) Grphs ommonly rprsnt onntions mong
More informationAerE 344: Undergraduate Aerodynamics and Propulsion Laboratory. Lab Instructions
ArE 344: Undrgraduat Arodynamics and ropulsion Laboratory Lab Instructions Lab #08: Visualization of th Shock Wavs in a Suprsonic Jt by using Schlirn tchniqu Instructor: Dr. Hui Hu Dpartmnt of Arospac
More informationMotivation. Problems. Puzzle 1
Introution to Roust Algorithms Séstin Tixuil UPMC & IUF Motition Approh Fults n ttks our in th ntwork Th ntwork s usr must not noti somthing wrong hppn A smll numr of fulty omponnts Msking pproh to fult/ttk
More information0.1. Exercise 1: the distances between four points in a graph
Mth 707 Spring 2017 (Drij Grinrg): mitrm 3 pg 1 Mth 707 Spring 2017 (Drij Grinrg): mitrm 3 u: W, 3 My 2017, in lss or y mil (grinr@umn.u) or lss S th wsit or rlvnt mtril. Rsults provn in th nots, or in
More informationCSE 373: AVL trees. Warmup: Warmup. Interlude: Exploring the balance invariant. AVL Trees: Invariants. AVL tree invariants review
rmup CSE 7: AVL trs rmup: ht is n invrint? Mihl L Friy, Jn 9, 0 ht r th AVL tr invrints, xtly? Disuss with your nighor. AVL Trs: Invrints Intrlu: Exploring th ln invrint Cor i: xtr invrint to BSTs tht
More informationBasis of test: VDE 0660, part 500/IEC Rated peak withstand current I pk. Ip peak short-circuit current [ka] Busbar support spacing [mm]
Powr istriution Short-iruit withstn strngth to EC Short-iruit withstn strngth to EC 439-1 Typ tsting to EC 439-1 During th ours of systm typ-tsting, th following tsts wr onut on th Rittl usr systms n on
More informationInstructions for Section 1
Instructions for Sction 1 Choos th rspons tht is corrct for th qustion. A corrct nswr scors 1, n incorrct nswr scors 0. Mrks will not b dductd for incorrct nswrs. You should ttmpt vry qustion. No mrks
More informationThe Plan. Honey, I Shrunk the Data. Why Compress. Data Compression Concepts. Braille Example. Braille. x y xˆ
h ln ony, hrunk th t ihr nr omputr in n nginring nivrsity of shington t omprssion onpts ossy t omprssion osslss t omprssion rfix os uffmn os th y 24 2 t omprssion onpts originl omprss o x y xˆ nor or omprss
More informationELEG 413 Lecture #6. Mark Mirotznik, Ph.D. Professor The University of Delaware
LG 43 Lctur #6 Mrk Mirtnik, Ph.D. Prfssr Th Univrsity f Dlwr mil: mirtni@c.udl.du Wv Prpgtin nd Plritin TM: Trnsvrs lctrmgntic Wvs A md is prticulr fild cnfigurtin. Fr givn lctrmgntic bundry vlu prblm,
More informationCompression. Compression. Compression. This part of the course... Ifi, UiO Norsk Regnesentral Vårsemester 2005 Wolfgang Leister
Kurs INF5080 Ifi, UiO Norsk Rgnsntrl Vårsmstr 2005 Wolfgng Listr This prt of th ours...... is hl t Ifi, UiO... (Wolfgng Listr) n t ontins mtril from Univrsity Collg Krlsruh (Ptr Ol, Clmns Knorzr) Informtion
More informationOrganization. Dominators. Control-flow graphs 8/30/2010. Dominators, control-dependence. Dominator relation of CFGs
Orniztion Domintors, ontrol-pnn n SSA orm Domintor rltion o CFGs postomintor rltion Domintor tr Computin omintor rltion n tr Dtlow lorithm Lnur n Trjn lorithm Control-pnn rltion SSA orm Control-low rphs
More informationMATH 1080 Test 2-SOLUTIONS Spring
MATH Tst -SOLUTIONS Spring 5. Considr th curv dfind by x = ln( 3y + 7) on th intrval y. a. (5 points) St up but do not simplify or valuat an intgral rprsnting th lngth of th curv on th givn intrval. =
More informationAnnouncements. Programming Project 4 due Saturday, August 18 at 11:30AM
Rgistr Allotion Announmnts Progrmming Projt 4 u Stury, August 18 t 11:30AM OH ll this wk. Ask qustions vi mil! Ask qustions vi Pizz! No lt sumissions. Pls vlut this ours on Axss. Your k rlly mks irn. Whr
More informationInner-product spaces
Inner-product spces Definition: Let V be rel or complex liner spce over F (here R or C). An inner product is n opertion between two elements of V which results in sclr. It is denoted by u, v nd stisfies:
More informationTOPIC 5: INTEGRATION
TOPIC 5: INTEGRATION. Th indfinit intgrl In mny rspcts, th oprtion of intgrtion tht w r studying hr is th invrs oprtion of drivtion. Dfinition.. Th function F is n ntidrivtiv (or primitiv) of th function
More informationGreedy Algorithms, Activity Selection, Minimum Spanning Trees Scribes: Logan Short (2015), Virginia Date: May 18, 2016
Ltur 4 Gry Algorithms, Ativity Sltion, Minimum Spnning Trs Sris: Logn Short (5), Virgini Dt: My, Gry Algorithms Suppos w wnt to solv prolm, n w r l to om up with som rursiv ormultion o th prolm tht woul
More informationA 4-state solution to the Firing Squad Synchronization Problem based on hybrid rule 60 and 102 cellular automata
A 4-stt solution to th Firing Squ Synhroniztion Prolm s on hyri rul 60 n 102 llulr utomt LI Ning 1, LIANG Shi-li 1*, CUI Shung 1, XU Mi-ling 1, ZHANG Ling 2 (1. Dprtmnt o Physis, Northst Norml Univrsity,
More information7.2 Riemann Integrable Functions
7.2 Riemnn Integrble Functions Theorem 1. If f : [, b] R is step function, then f R[, b]. Theorem 2. If f : [, b] R is continuous on [, b], then f R[, b]. Theorem 3. If f : [, b] R is bounded nd continuous
More informationa b v a v b v c v = a d + bd +c d +ae r = p + a 0 s = r + b 0 4 ac + ad + bc + bd + e 5 = a + b = q 0 c + qc 0 + qc (a) s v (b)
Outlin MULTIPLE-LEVEL LOGIC OPTIMIZATION Gionni D Mihli Stnfor Unirsit Rprsnttions. Tonom of optimition mthos: { Gols: r/l. { Algorithms: lgri/booln. { Rul-s mthos. Empls of trnsformtions. Booln n lgri
More information