i_~f e 1 then e 2 else e 3


 Derek O’Connor’
 2 years ago
 Views:
Transcription
1 A PROCEDURE MECHANISM FOR BACKTRACK PROGRAMMING* David R. HANSON + Department o Computer Siene, The University of Arizona Tuson, Arizona One of the diffiulties in using nondeterministi algorithms for the solution of ombinatorial problems is that most programming languages do not inlude features apable of easily representing baktraking proesses. This paper desribes a proedure mehanism that uses oroutines as a means for the desription and realization of nondeterministi algorithms. A solution to the eight queens problem is given to illustrate the appliation of the proedure mehanism to baktraking problems. I. INTRODUCTION Although baktrak programming has been known for several years [14], the method has yet to beome a ommon programming tehnique for the realization of nondeterministi algorithms. Floyd [1] alluded to the reason for this situation: most programming languages do not inlude features that failitate baktrak programming. He suggested that programming languages ought to possess mehanisms apable of representing nondeterministi algorithms. Sine the appearane of Floyd's paper, onsiderable researh has been undertaken to add failities of this kind to new or existing languages. This work has overed a large part of the spetrum of programming languages, from general desriptions with a slant toward Algollike languages [5,6], to languages for artifiial intelligene researh [7], and even to Fortran [8]. In all the work ited, features that were added or proposed for baktraking were ast in a framework of reursive funtions with additional builtin mehanisms or primitives with whih to implement baktraking. That is, the basi proedure mehanism of the proposed languages or language extensions was the traditional reursive funtion. This paper presents a general proedure mehanism that inludes oroutines as a means for the desription and realization of nondeterministi algorithms. The SL5 programming language [912] in whih this proedure mehanism is implemented is the vehile used to desribe this method and its appliation to baktrak programming. *This work was supported by the National Siene Foundation under Grant DCR Author's present address: Department of Computer Siene, Yale University, New Haven, Connetiut To failitate omparison with previous work, the eight queens problem [1315] is used as the example o baktraking throughout this paper. This is a nontrivial problem whose solution is ideally suited to the baktraking strategy, and has frequently been used as an example that an be solved by nondeterministi programming. 2. THE SL5 PROGRAMMING LANGUAGE SL5 is an expressionoriented language that is struturally similar to BLISS or Algol 68. SL5 is a "typeless" language in the same sense that SNOBOL4 is  a variable an have a value of any datatype at any time during program exeution. 2.1 Control Strutures and Signaling An expression returns a signal, "suess" or "failure", as well as a value. The ombination o a value and a signal is alled the result of the expression. SL5 possesses most o the "modern" ontrol strutures, eah of whih is an expression and returns a result. Control strutures are driven by signals rather than by boolean values. For an example, in the expression i_~f e 1 then e 2 else e 3 e I is evaluated first. If the resulting signal is suess, e 2 is evaluated. Otherwise, e 5 is evaluated. The result of the ifthenelse expression is the result (value and signal) o e 2 or e 3, whihever is evaluated. Other typial ontrol strutures while e I do e 2 until e I do e 2 repeat e for v from e I to e 2 do e 5 I are: 401
2 The while and for expressions behave in the onventlo~6n~manner. The until expression repeatedly evaluates e 2 until e I sueeds. The repeat expression evaluates e repeatedly until a failure signal is returned. Expressions may be grouped together as a single expression using begin... end or {... }. 2.2 Proedures In SL5, proedures and their environments (ativation reords) are separate sourelanguage data objets. A proedure is "reated" by an expression suh as gd := proedure (x, y) while x ~= y do if x > y then x := xy else y := yx; sueed x whih assigns to gd a proedure that omputes the greatest ommon divisor of its arguments. The invoation of a proedure in the standard reursive fashion is aomplished using the usual funtional notation f(el,e 2... en), whih invokes the proedure that is the urrent value of the variable f. Proedure ativation may be deomposed into several distint sourelanguage operations that permit SL5 proedures to be used as oroutines. These operations are the reation of an environment for the exeution of the given proedure, the bindin~ of the atual arguments to that environment, and the resumption of the exeution of the proedure. The reate expression takes a single argument of datatype proedure, reates an environment for its exeution, and returns this environment as its value. For example, the expression e := reate f assigns to e an environment for the exeution of f. The with. expression is used to bind the atual arguments to an environment. The expression e with (el,e 2,... e n) binds the atual arguments, e I through en, to the environment e. The exeution of a proedure is aomplished by "resuming" it via the resume expression. The expression resume e suspends exeution of the urrent proedure and ativates the proedure for whih e is an environment. A proedure usually "returns" a result to its "resumer". This is aomplished by the expressions sueed v whihreturn V as the value of the proedure and signal either suess or failure as indiated. If the proedure is ativated by a resume, the result given in sueed or fail is transmitted and beomes the result of teh6"~esume expression. The exeution of sueed or fail auses the suspension of that environment. If the environment is again resumed, exeution proeeds from where it left off. The argument v may be omitted, in whih ase the null string is assumed. A label generator illustrates oroutine usage: genlab :={proedure (n) repeat sueed "U' l] lp~cn, 3, "0"); n := n+1 } a simple example of An environment for genlab generates the next label of the form Lnnn eah time it is resumed. The sequene begins at the integer given by the argument. (lpad is a builtin proedure that pads n on the left with zeros to form a Sharater string, and [] denotes string onatenation.) For example, an expression suh as gen := reate genzab with 10 assigns to gen an environment for genlab that generates a sequene of labels beginning at L010. To obtain the next label, the exeution of the environment is resumed; x := resume gen Notie that the sequene may be restarted by retransmitting the argument, e.g., gen := gen with Delarations SL5 has delarations for identifiers that are used to determine only the interpretation and sope of identifiers that appear in a proedure, not their type. The delaration private x delares x to be a private identifier whose value is available only to the proedure in whih it is delared; it annot be examined or modified by any other proedure. Private identifiers are used, for example, when a oroutine must "remember" information from one resumption to the next. Other delarations and the sope of identifiers are desribed in refs. 9 and BACKTRACKING AND THE EIGHT QUEENS PROBLEM There are many problems for whih an analyti solution is not known, but for whih a solution an be onstruted by trial and error. A lassi example is the eight queens problem, sometimes referred to as the nbyn nonattaking queens problem. The objet is to plae eight queens on a hess board so that no queen an apture any of the others. One suh solution is shown in fig. I. 402
3 There are 92 solutions to this problem, although only 12 are unique. tow I olumn Fig. 1  A Solution to the Eight Queens Problem A brute fore approah to this problem is to test all the possible onfigurations of the queens to find the 92 "safe" ones. Although the number of possible onfigurations an be substantially redued by observing that only one queen may oupy a given olumn, the brute fore approah requires an impratial amount of omputation. 3.1 Baktraking A better approah for solving this type of problem is to onstrut a solution one queen at a time rather than testing the validity of every possible onfiguration. This is alled the "baktraking" approah. For example, if the first queen (the leftmost one in fig. I) is plaed on row 1, the seond queen an only be plaed on rows 5 through 8. Configurations with the first queen on row 1 and the seond queen on row 1 or 2 annot lead to a solution regardless of the positions of queens 5 through 8. Thus only the partial solutions (1,3), (1,4)..., {1,8) need to be onsidered when searhing for a solution. The idea in baktraking is to form the k th partial solution (Xl,X2,...,Xk) and extend it to a k+ist partial solution (Xl,X2,...,Xk,Xk+l) by seleting a suitable Xk+ 1. When k+l is equal to 8, a omplete solution has been found. The term baktrakin~ is derived from the ation taken when the k th partial solution annot be extended to a k+ist partial solution. In this ase, it is neessary to "baktrak" to the ki partial solution and try to ompute a different x k for a k th partial solution. This baktraking step requires that whatever omputation was required to form the k th partial solution be undone in order to get bak to the ki partial solution. This is often alled "reversing effets" or "bakwards exeution". For the eight queens problem, this amounts to freeing the squares on the board overed by the k th queen. For example, it is easy to plae the first five queens to form the partial solution (1,3,5,2,4). But the sixth queen annot be plaed. It is neessary to baktrak to the partial solution (1,3,5,2) and try again. This partial solution an be extended to (1,3,5,2,8) but no further. It is neessary to baktrak all the way to the partial solution (1,3,5), whih an then be extended to (1,3,5,7,2,4,6). This baktraking proess ontinues until the solution (1,5,8,6,3,7,2,4) is found, whih is shown in fig. 1. A more formal desription of the baktraking strategy is given in ref. 2. A partiularly luid explanation an be found in ref. 16, whih desribes a method for estimating the effiieny of baktraking programs. 5.2 Realization of the Nondeterministi Algorithm The usual method for programming the solution to the eight queens problem is to use a proedure that generates all solutions with the first queen on rows 1 to 8 by alling itself reursively to generate all solutions for the seond queen in rows 1 to 8, et. The foliowing proedure, similar to the Pasal solution given in ref. 15, operates in this fashion. generate := proedure (ol) private row; for row from 1 to 8 do i_~f teet(row, ol) then { oupy (row, ol) ; x[ol] := row; if ol = 8 then print(x) else generate (ol+l) ; release (row, ol) }; sueed The details of the board representation are ontained in proedures test, oupy, and release. test(row, ol) sueeds if the queen in olumn ol an be plaed on the indiated row. The proedure oupy(row, ol) marks as oupied all positions overed by the queen at the position row, ol. relea8e(row, ol) reverses the effet of oupy; it marks those positions overed by the given queen as free. Possible representations for the atual board are given in refs. 1 and print(x) prints the ontents of the solution vetor x. The program is started by generate(1). A portion of the baktraking in this solution is somewhat obsured by the reursion; it is aomplished impliitly by repeated reursive invoations of generate. It is not neessary to use reursion to aomplish the baktraking but it is sometimes used beause the only form of proedure available is the reursive funtion. The oroutine method, on the other hand, does not require the use of reursion to aomplish the baktraking. The basi approah is to reate eight environments for a single proedure; one for eah olumn. Eah environment represents one queen. The proedure, alled queen, attempts o plae a queen on the given olumn beginning with 403
4 row 1. I a queen is suessfully plaed, the proedure suspends its exeution and signals suess to its resumer. If it is subsequently resumed, it reverses its previous effets, i.e. removes the queen from the row, and tries the next row. If the queen annot be plaed, the proedure fails indiating that baktraking must our. Subsequent resumption after failure indiates that the proess should begin again at row1. The eight environments for proedure queen are stored in a vetor q. The first step is to reate the eight environments for proedure queen, eah with the proper olumn number: q := vetor(i, 8); for i from 1 to 8 do q~i] := reate queen with i; To begin the searh for a solution, the exeution of the first queen, q[1], is resumed. The seond queen is then resumed, and so on. If the resumption of a queen fails, baktraking is indiated. If the i th queen fails, queen "i1 must be resumed in order to be repositioned. This is equivalent to queen i1 attempting to find a new i1 partial solution. I the ith queen sueeds, ~een i+1 is resumed in hopes of extending the i partial solution. A omplete solution has been found when the eighth queen is suessfully plaed. This entire proess an be written as i := ~; until i > & do ~resume q~i] then i :ffi i+1 e~i := ii; p~nt ('(~; The index i is inremented as long as the ith queen is suess~ully nlaed, i.e., as long as the extension to the i ~h partial solution is possible. It is deremented when the~ th queen signals failure indiating that the ivn partial solution ould not be formed. The proedure queen is as follows. queen := proedure (ol) private row; repeat ( for rob) from I to 8 do i_ff test~, ~l) t~en { oupy(row, ol); x[ol] := row; sueed; ~(row, ol) fail ) }; The expression repeat {... } is a nonterminating loop. All 92 solutions an be found by modifying the until loop given above so that after a solution has been found the exeution of the eighth queen is again resumed. If the subsequent plaement is suessful, a seond solution is generated. If it fails, the seventh queen must be repositioned. This is equivalent to making a solution fail, after reording it, in order to searh for all possible solutions using the baktraking strategy. Theproess is stopped when the first queen signals failure. This loop an be written as follows. i := I; until i = 0 do i~ resume q~i] th~~(_ i = 8 then p~ntcx) else i := i+l) else i := i1; Notie that i is not inremented after suessful plaement of the eighth queen, thus foring its repositioning at the next resumption. This program an be generalized for n queens by substituting n wherever 8 appears. The general form is the same for many similar baktraking problems. For example, if the proedures test, oupy, and release are modified to assume rooks instead of queens, the program omputes all possible permutations of the integers 1 to n. 4. COMPARISON OF THE METHODS The major differene between the reursive approah and the oroutine approah is in the ontrol regime used to ahieve baktraking. This is illustrated in fig. 2. The left part of fig. 2 shows the ontrol relationship among the eight instantiations o generate when a reursive solution has been omputed. The relationship is stritly hierarhial: generate is written to use reursion in order to "resume" the next queen. The proedure generate must inlude not only the semantis of plaing a queen, but is must also ontain the baktraking mehanism. The right part of fig. 2 shows the ontrol relationship among the eight environments for the oroutine solution. In this ase, the proedure only needs to know how to plae a queen, not about the order in whih eah environment is resumed. The main program ontrols the resumption of the oroutines. main f progr~n ~,, generate ( I )( 2( '( 6( 7( generate (8)( in program quee~l queen I Fig. 2  Control Regimes among the Eight Queens 404
5 5. CONCLUSIONS The proedure faility of a highlevel language is one of the most powerful tools for abstration available to the programmer. The SL5 mehanism is designed to provide, at the linguisti level, failities that permit the programmer to implement solutions to baktraking problems in a way that losely parallels the abstrat formulation of the problem. The oroutine approah to baktraking is not limited to SLS. The same idea an be used in other languages that support oroutines, suh as Simula 67 LITJ. Alternatively, SL5 an be used as a speifiation language in whih to formulate the solutions to baktraking problems. The resulting program an then be used as a guide to an atual implementation in a lowerlevel language. This is done in the Appendix for the eight queens problem; the SL5 program given in se. 5.2 is used as a guide for onstruting a solution in Fortran. There are other problems, suh as parsing and string pattern mathing, that an be solved using baktraking tehniques. Unlike the eight queens problem, however, the domain of the searh is not known beforehand, but is determined as the searh proeeds. Non'etheless, the oroutine approah appears to be appliable to these types of problems. For example, SL5 ontains a patternmathing faility that is based on a oroutine model of pattern mathing in SNOBOL4 [18]. The SL5 faility is signifiantly more general and flexible tsan the faility in SNOBOL4, and has proven to be easier to implement and to understand than the resursive approah used in SNOBOL4 [19,20]. ACKNOWLEDGEMENT Signifiant ontributions to SLS have been made by Dianne E. Britton, Frederik C. Druseikis, and Ralph E. Griswold. APPENDIX The following Fortran program omputes all 92 solutions to the eight queens problem, and is derived from the SL5 program given in se The board representation, embodied in test, oupy, and release, an be derived from that given in refs main program logial queen integer row, i ommon /env/ row(8) C I=I 30 if (i.le. O) stop if (queen(i)) go to 40 I=i1 40 if (i.eq. 8) go to 50 I=i+1 50 write(6, I00) row 100 format(b(lx, il)) end logial funtion queen(ol) integer ro~ij, ol, j. p(8) logial test ommon /env/ row(8) data p/b*i/ j = p(ol) go to (10, 20, 50),j 10 if (row(ol).gt. 8) go to 40 if (.not. test(row(ol), ol)) 1 all oupy(row(ol), ol) P(COI) = 2 queen =.true return 20 all relea~(row(o]), ol) 30 row(ol) = row(ol) + I go to p(ol) = 3 queen =.false. return 50 row(ol) = l go to 10 end REFERENCES [I] Robert W. Floyd, Nondeterministi algorithms, J. ACM, vol. 14, Otober 1967, [2] Solomon W. Golomb and Leonard D. Baumert, Baktrak programming, J. ACM, vol. 12, Otober 1965, [3] Derrik H. Lehmer, Combinatorial problems with digital omputers, Pre. of the Fourth Canadian Math. Congress, 1957, [4] Robert J. Walker, An enumerative tehnique for a lass of ombinatorial problems, Pre. of the Symposium o n_napplied Mathematis, vol. 10, Otober 1960, [5] Charles J. Prenner, Jay M. Spitzen and Ben Wegbreit, An implementation of baktraking for programming languages, Pro. of the ACM Annual Conferene, August 1972, [6] John A. Self, Embedding nondeterminism, Software  Pratie and Experiene, vol. 5, September 1975, [7] Daniel G. Bobrow and Bertram Raphael, New programming languages for artifiial intelligene, Computing Surveys, vol. 6, September 1974, [8] Jaques Cohen and Eileen Carton, Nondeterministi fortran, Computer ~., vol. 17, February 1974, [9] Dianne E. Britton, et al., Proedure referening environments in SLS, Third ACM Symposium on Priniples of Programming Languages, January 1976, [10] Ralph E. Griswold and David R. Hanson, An overview of the SL5 programming language, SL5 projet doument SSLDIa, Dept. of Computer Siene, The University of Arizona, [II] Tuson, February David R. Hanson, The syntax and semantis of SL5, SL5 projet doument SSLD2a, Dept. of Computer Siene, The University of Arizona, Tuson, April [12] David R. Hanson and Ralph E. Griswold, The SL5 proedure mehanism, SL5 projet doument SSLD4, Dept. of Computer Siene, The University of Arizona, Tuson, February [13] OleJahn Dahl, Edsger W. Dijkstra and C. A. R. Hoare, Strutured Programming, Aademi Press, London, 1972, se [14] Niklaus Wirth, Program development by stepwise refinement, Comm. ACM, vol. 14, April 1971, [15] Niklaus Wirth, Algorithms + Data = Prosrams, PrentieHall, Englewood Cliffs, New Jersey, 1976, se [16] Donald E. Knuth, Estimating the effiieny of baktrak programs, Mathematis of Computation, vol. 29, January 1975, [17] 01eJahn Dahl, Bjorn Myhrhaug and Kristen Nygaard, The Simula 67 ommon base language, Norwegian Computing Centre, Oslo, Norway, [18] Frederik C. Druseikis and John N. Doyle, A proedural approah to pattern mathing in SNOBOL4, Pr0. of the ACM Annual Conferene, November 1974, [19] Ralph E. Griswold, String sanning in SL5, SL5 projet doument SSLDSa, Dept. of Computer Siene, The University of Arizona, Tuson, June [20] Ralph E. Griswold, String analysis and synthesis in SL5, Pro. of the ACM Annual Conferene, Otober
Sebastián Bravo López
Transfinite Turing mahines Sebastián Bravo López 1 Introdution With the rise of omputers with high omputational power the idea of developing more powerful models of omputation has appeared. Suppose that
More informationAn Iterated Beam Search Algorithm for Scheduling Television Commercials. Mesut Yavuz. Shenandoah University
0080569 An Iterated Beam Searh Algorithm for Sheduling Television Commerials Mesut Yavuz Shenandoah University The Harry F. Byrd, Jr. Shool of Business Winhester, Virginia, U.S.A. myavuz@su.edu POMS 19
More informationChannel Assignment Strategies for Cellular Phone Systems
Channel Assignment Strategies for Cellular Phone Systems Wei Liu Yiping Han Hang Yu Zhejiang University Hangzhou, P. R. China Contat: wliu5@ie.uhk.edu.hk 000 Mathematial Contest in Modeling (MCM) Meritorious
More informationGranular Problem Solving and Software Engineering
Granular Problem Solving and Software Engineering Haibin Zhu, Senior Member, IEEE Department of Computer Siene and Mathematis, Nipissing University, 100 College Drive, North Bay, Ontario, P1B 8L7, Canada
More informationA Holistic Method for Selecting Web Services in Design of Composite Applications
A Holisti Method for Seleting Web Servies in Design of Composite Appliations Mārtiņš Bonders, Jānis Grabis Institute of Information Tehnology, Riga Tehnial University, 1 Kalu Street, Riga, LV 1658, Latvia,
More information' R ATIONAL. :::~i:. :'.:::::: RETENTION ':: Compliance with the way you work PRODUCT BRIEF
' R :::i:. ATIONAL :'.:::::: RETENTION ':: Compliane with the way you work, PRODUCT BRIEF Inplae Management of Unstrutured Data The explosion of unstrutured data ombined with new laws and regulations
More informationChapter 6 A N ovel Solution Of Linear Congruenes Proeedings NCUR IX. (1995), Vol. II, pp. 708{712 Jerey F. Gold Department of Mathematis, Department of Physis University of Utah Salt Lake City, Utah 84112
More informationAn Enhanced Critical Path Method for Multiple Resource Constraints
An Enhaned Critial Path Method for Multiple Resoure Constraints ChangPin Lin, HungLin Tai, and ShihYan Hu Abstrat Traditional Critial Path Method onsiders only logial dependenies between related ativities
More informationHenley Business School at Univ of Reading. Chartered Institute of Personnel and Development (CIPD)
MS in International Human Resoure Management (fulltime) For students entering in 2015/6 Awarding Institution: Teahing Institution: Relevant QAA subjet Benhmarking group(s): Faulty: Programme length: Date
More informationHenley Business School at Univ of Reading. PreExperience Postgraduate Programmes Chartered Institute of Personnel and Development (CIPD)
MS in International Human Resoure Management For students entering in 2012/3 Awarding Institution: Teahing Institution: Relevant QAA subjet Benhmarking group(s): Faulty: Programme length: Date of speifiation:
More informationA ContextAware Preference Database System
J. PERVASIVE COMPUT. & COMM. (), MARCH 005. TROUBADOR PUBLISHING LTD) A ContextAware Preferene Database System Kostas Stefanidis Department of Computer Siene, University of Ioannina,, kstef@s.uoi.gr Evaggelia
More informationProgramming Basics  FORTRAN 77 http://www.physics.nau.edu/~bowman/phy520/f77tutor/tutorial_77.html
CWCS Workshop May 2005 Programming Basis  FORTRAN 77 http://www.physis.nau.edu/~bowman/phy520/f77tutor/tutorial_77.html Program Organization A FORTRAN program is just a sequene of lines of plain text.
More informationComputer Networks Framing
Computer Networks Framing Saad Mneimneh Computer Siene Hunter College of CUNY New York Introdution Who framed Roger rabbit? A detetive, a woman, and a rabbit in a network of trouble We will skip the physial
More informationRestricted Least Squares, Hypothesis Testing, and Prediction in the Classical Linear Regression Model
Restrited Least Squares, Hypothesis Testing, and Predition in the Classial Linear Regression Model A. Introdution and assumptions The lassial linear regression model an be written as (1) or (2) where xt
More information_ «..J. a.. en en. Information Systems Planning Guide U') GE ::J ' . 0
z z «..J a.. en :E w  en en U') w z en ::J '. 0      _. nformation Systems Planning Guide GE2005272 CJ z z Z
More informationExploiting Relative Addressing and Virtual Overlays in Ad Hoc Networks with Bandwidth and Processing Constraints
Exploiting Relative Addressing and Virtual Overlays in Ad Ho Networks with Bandwidth and Proessing Constraints Maro Aurélio Spohn Computer Siene Department University of California at Santa Cruz Santa
More informationUNIVERSITY AND WORKSTUDY EMPLOYERS WEB SITE USER S GUIDE
UNIVERSITY AND WORKSTUDY EMPLOYERS WEB SITE USER S GUIDE September 8, 2009 Table of Contents 1 Home 2 University 3 Your 4 Add 5 Managing 6 How 7 Viewing 8 Closing 9 Reposting Page 1 and WorkStudy Employers
More informationWORKFLOW CONTROLFLOW PATTERNS A Revised View
WORKFLOW CONTROLFLOW PATTERNS A Revised View Nik Russell 1, Arthur H.M. ter Hofstede 1, 1 BPM Group, Queensland University of Tehnology GPO Box 2434, Brisbane QLD 4001, Australia {n.russell,a.terhofstede}@qut.edu.au
More informationHierarchical Clustering and Sampling Techniques for Network Monitoring
S. Sindhuja Hierarhial Clustering and Sampling Tehniques for etwork Monitoring S. Sindhuja ME ABSTRACT: etwork monitoring appliations are used to monitor network traffi flows. Clustering tehniques are
More informationFOOD FOR THOUGHT Topical Insights from our Subject Matter Experts
FOOD FOR THOUGHT Topial Insights from our Sujet Matter Experts DEGREE OF DIFFERENCE TESTING: AN ALTERNATIVE TO TRADITIONAL APPROACHES The NFL White Paper Series Volume 14, June 2014 Overview Differene
More informationPolynomials INTRODUCTION CHAPTER 3 OUTLINE. Chapter 3 :: Prerequisite Test 182. Exponents and Polynomials 183
bar92103_h03_a_181219.qxd 9/19/09 12:03 PM Page 181 C H A P T E R hapter The MGrawHill Companies. All Rights Reserved. The Streeter/Huthison Series in Mathematis Beginning Algebra 3 > Make the Connetion
More informationA Design Environment for Migrating Relational to Object Oriented Database Systems
To appear in: 1996 International Conferene on Software Maintenane (ICSM 96); IEEE Computer Soiety, 1996 A Design Environment for Migrating Relational to Objet Oriented Database Systems Jens Jahnke, Wilhelm
More informationParametric model of IPnetworks in the form of colored Petri net
Parametri model of IPnetworks in the form of olored Petri net Shmeleva T.R. Abstrat A parametri model of IPnetworks in the form of olored Petri net was developed; it onsists of a fixed number of Petri
More informationA Keyword Filters Method for Spam via Maximum Independent Sets
Vol. 7, No. 3, May, 213 A Keyword Filters Method for Spam via Maximum Independent Sets HaiLong Wang 1, FanJun Meng 1, HaiPeng Jia 2, JinHong Cheng 3 and Jiong Xie 3 1 Inner Mongolia Normal University 2
More informationNeural networkbased Load Balancing and Reactive Power Control by Static VAR Compensator
nternational Journal of Computer and Eletrial Engineering, Vol. 1, No. 1, April 2009 Neural networkbased Load Balaning and Reative Power Control by Stati VAR Compensator smail K. Said and Marouf Pirouti
More informationprotection p1ann1ng report
f1re~~ protetion p1ann1ng report BUILDING CONSTRUCTION INFORMATION FROM THE CONCRETE AND MASONRY INDUSTRIES Signifiane of Fire Ratings for Building Constrution NO. 3 OF A SERIES The use of fireresistive
More informationDiscovering Trends in Large Datasets Using Neural Networks
Disovering Trends in Large Datasets Using Neural Networks Khosrow Kaikhah, Ph.D. and Sandesh Doddameti Department of Computer Siene Texas State University San Maros, Texas 78666 Abstrat. A novel knowledge
More informationUnit 12: Installing, Configuring and Administering Microsoft Server
Unit 12: Installing, Configuring and Administering Mirosoft Server Learning Outomes A andidate following a programme of learning leading to this unit will be able to: Selet a suitable NOS to install for
More informationClassical Electromagnetic Doppler Effect Redefined. Copyright 2014 Joseph A. Rybczyk
Classial Eletromagneti Doppler Effet Redefined Copyright 04 Joseph A. Rybzyk Abstrat The lassial Doppler Effet formula for eletromagneti waves is redefined to agree with the fundamental sientifi priniples
More informationSet Theory and Logic: Fundamental Concepts (Notes by Dr. J. Santos)
A.1 Set Theory and Logi: Fundamental Conepts (Notes by Dr. J. Santos) A.1. Primitive Conepts. In mathematis, the notion of a set is a primitive notion. That is, we admit, as a starting point, the existene
More informationOutline. Planning. Search vs. Planning. Search vs. Planning Cont d. Search vs. planning. STRIPS operators Partialorder planning.
Outline Searh vs. planning Planning STRIPS operators Partialorder planning Chapter 11 Artifiial Intelligene, lp4 2005/06, Reiner Hähnle, partly based on AIMA Slides Stuart Russell and Peter Norvig, 1998
More informationIn this chapter, we ll see state diagrams, an example of a different way to use directed graphs.
Chapter 19 State Diagrams In this hapter, we ll see state diagrams, an example of a different way to use direted graphs. 19.1 Introdution State diagrams are a type of direted graph, in whih the graph nodes
More informationchapter > Make the Connection Factoring CHAPTER 4 OUTLINE Chapter 4 :: Pretest 374
CHAPTER hapter 4 > Make the Connetion 4 INTRODUCTION Developing seret odes is big business beause of the widespread use of omputers and the Internet. Corporations all over the world sell enryption systems
More informationBENEFICIARY CHANGE REQUEST
Poliy/Certifiate Number(s) BENEFICIARY CHANGE REQUEST *L2402* *L2402* Setion 1: Insured First Name Middle Name Last Name Permanent Address: City, State, Zip Code Please hek if you would like the address
More informationAn integrated optimization model of a Closed Loop Supply Chain under uncertainty
ISSN 18166075 (Print), 18180523 (Online) Journal of System and Management Sienes Vol. 2 (2012) No. 3, pp. 917 An integrated optimization model of a Closed Loop Supply Chain under unertainty Xiaoxia
More informationCapacity at Unsignalized TwoStage Priority Intersections
Capaity at Unsignalized TwoStage Priority Intersetions by Werner Brilon and Ning Wu Abstrat The subjet of this paper is the apaity of minorstreet traffi movements aross major divided fourlane roadways
More informationSQA Advanced Higher Computing Unit 3a: Artificial Intelligence
SCHOLAR Study Guide SQA Advaned Higher Computing Unit 3a: Artifiial Intelligene David Bethune HeriotWatt University Andy Cohrane HeriotWatt University Ian King HeriotWatt University Interative University
More information5.2 The Master Theorem
170 CHAPTER 5. RECURSION AND RECURRENCES 5.2 The Master Theorem Master Theorem In the last setion, we saw three different kinds of behavior for reurrenes of the form at (n/2) + n These behaviors depended
More informationIII47 MOMENT FRAME MODEL
III47 OENT FRAE ODEL Grids and 8 were modeled in onventional strutural analysis software as twodimensional models. The seondorder option in the strutural analysis program was not used. Rather, for illustration
More informationProfessional Certificate Training in Business Writing
Professional Certifiate Training in Business Writing About Training in Business Writing ZeebraCross Centre for Management Exellene (ZCME) is an initiative of ZeebraCross (Unit of InfousRx Marketing and
More informationRecovering Articulated Motion with a Hierarchical Factorization Method
Reovering Artiulated Motion with a Hierarhial Fatorization Method Hanning Zhou and Thomas S Huang University of Illinois at UrbanaChampaign, 405 North Mathews Avenue, Urbana, IL 680, USA {hzhou, huang}@ifpuiuedu
More informationLecture 5. Gaussian and GaussJordan elimination
International College of Eonomis and Finane (State University Higher Shool of Eonomis) Letures on Linear Algebra by Vladimir Chernyak, Leture. Gaussian and GaussJordan elimination To be read to the musi
More informationBehavior AnalysisBased Learning Framework for Host Level Intrusion Detection
Behavior AnalysisBased Learning Framework for Host Level Intrusion Detetion Haiyan Qiao, Jianfeng Peng, Chuan Feng, Jerzy W. Rozenblit Eletrial and Computer Engineering Department University of Arizona
More informationWeighting Methods in Survey Sampling
Setion on Survey Researh Methods JSM 01 Weighting Methods in Survey Sampling Chiaohih Chang Ferry Butar Butar Abstrat It is said that a welldesigned survey an best prevent nonresponse. However, no matter
More informationChapter 5 Single Phase Systems
Chapter 5 Single Phase Systems Chemial engineering alulations rely heavily on the availability of physial properties of materials. There are three ommon methods used to find these properties. These inlude
More informationPattern Recognition Techniques in Microarray Data Analysis
Pattern Reognition Tehniques in Miroarray Data Analysis Miao Li, Biao Wang, Zohreh Momeni, and Faramarz Valafar Department of Computer Siene San Diego State University San Diego, California, USA faramarz@sienes.sdsu.edu
More informationOpenScape 4000 CSTA V7 Connectivity Adapter  CSTA III, Part 2, Version 4.1. Developer s Guide A31003G9310I200176D1
OpenSape 4000 CSTA V7 Connetivity Adapter  CSTA III, Part 2, Version 4.1 Developer s Guide A31003G9310I200176 Our Quality and Environmental Management Systems are implemented aording to the requirements
More informationarxiv:astroph/0304006v2 10 Jun 2003 Theory Group, MS 50A5101 Lawrence Berkeley National Laboratory One Cyclotron Road Berkeley, CA 94720 USA
LBNL52402 Marh 2003 On the Speed of Gravity and the v/ Corretions to the Shapiro Time Delay Stuart Samuel 1 arxiv:astroph/0304006v2 10 Jun 2003 Theory Group, MS 50A5101 Lawrene Berkeley National Laboratory
More informationCustomer Reporting for SaaS Applications. Domain Basics. Managing my Domain
Produtivity Marketpla e Software as a Servie Invoiing Ordering Domains Customer Reporting for SaaS Appliations Domain Basis Managing my Domain Managing Domains Helpful Resoures Managing my Domain If you
More informationOpen and Extensible Business Process Simulator
UNIVERSITY OF TARTU FACULTY OF MATHEMATICS AND COMPUTER SCIENCE Institute of Computer Siene Karl Blum Open and Extensible Business Proess Simulator Master Thesis (30 EAP) Supervisors: Luiano GaríaBañuelos,
More informationDeadlinebased Escalation in ProcessAware Information Systems
Deadlinebased Esalation in ProessAware Information Systems Wil M.P. van der Aalst 1,2, Mihael Rosemann 2, Marlon Dumas 2 1 Department of Tehnology Management Eindhoven University of Tehnology, The Netherlands
More informationA Survey of Usability Evaluation in Virtual Environments: Classi cation and Comparison of Methods
Doug A. Bowman bowman@vt.edu Department of Computer Siene Virginia Teh Joseph L. Gabbard Deborah Hix [ jgabbard, hix]@vt.edu Systems Researh Center Virginia Teh A Survey of Usability Evaluation in Virtual
More informationAgile ALM White Paper: Redefining ALM with Five Key Practices
Agile ALM White Paper: Redefining ALM with Five Key Praties by Ethan Teng, Cyndi Mithell and Chad Wathington 2011 ThoughtWorks ln. All rights reserved www.studios.thoughtworks.om Introdution The pervasiveness
More informationTHE UNIVERSITY OF TEXAS AT ARLINGTON COLLEGE OF NURSING. NURS 6390004 Introduction to Genetics and Genomics SYLLABUS
THE UNIVERSITY OF TEXAS AT ARLINGTON COLLEGE OF NURSING NURS 6390004 Introdution to Genetis and Genomis SYLLABUS Summer Interession 2011 Classroom #: TBA and 119 (lab) The University of Texas at Arlington
More informationFIRE DETECTION USING AUTONOMOUS AERIAL VEHICLES WITH INFRARED AND VISUAL CAMERAS. J. Ramiro Martínezde Dios, Luis Merino and Aníbal Ollero
FE DETECTION USING AUTONOMOUS AERIAL VEHICLES WITH INFRARED AND VISUAL CAMERAS. J. Ramiro Martínezde Dios, Luis Merino and Aníbal Ollero Robotis, Computer Vision and Intelligent Control Group. University
More informationImproved SOMBased HighDimensional Data Visualization Algorithm
Computer and Information Siene; Vol. 5, No. 4; 2012 ISSN 19138989 EISSN 19138997 Published by Canadian Center of Siene and Eduation Improved SOMBased HighDimensional Data Visualization Algorithm Wang
More informationSrinivas Bollapragada GE Global Research Center. Abstract
Sheduling Commerial Videotapes in Broadast Television Srinivas Bollapragada GE Global Researh Center Mihael Bussiek GAMS Development Corporation Suman Mallik University of Illinois at Urbana Champaign
More informationSupply chain coordination; A Game Theory approach
aepted for publiation in the journal "Engineering Appliations of Artifiial Intelligene" 2008 upply hain oordination; A Game Theory approah JeanClaude Hennet x and Yasemin Arda xx x LI CNRUMR 668 Université
More informationContext in Artificial Intelligent and Information Modeling
Context in Artifiial Intelligent and Information Modeling Manos Theodorakis ½ and Niolas Spyratos ¾ ¾ ½ FITFraunhofer Institute for Applied Information Tehnology, D53754, Sankt Augustin, Germany manos.theodorakis@fit.fraunhofer.de
More informationMEMBER. Application for election MEMBER, NEW GRADUATE. psychology.org.au. April 2015
MEMBER Appliation for eletion MEMBER, NEW GRADUATE April 2015 psyhology.org.au MEMBER Belonging to the Australian Psyhologial Soiety (APS) means you are part of an ative, progressive organisation whih
More informationSolving the Game of Awari using Parallel Retrograde Analysis
Solving the Game of Awari using Parallel Retrograde Analysis John W. Romein and Henri E. Bal Vrije Universiteit, Faulty of Sienes, Department of Mathematis and Computer Siene, Amsterdam, The Netherlands
More informationIntelligent Measurement Processes in 3D Optical Metrology: Producing More Accurate Point Clouds
Intelligent Measurement Proesses in 3D Optial Metrology: Produing More Aurate Point Clouds Charles Mony, Ph.D. 1 President Creaform in. mony@reaform3d.om Daniel Brown, Eng. 1 Produt Manager Creaform in.
More informationCA PPM 14.x Business Analyst Certification Exam (CAT242) Study Guide Version 1.2
CA PPM 14.x Business Analyst Certifiation Exam (CAT242) Study Guide Version 1.2 Certifiation Exam (CAT242) PROPRIETARY AND CONFIDENTIAL INFORMATION 2016 CA. All rights reserved. CA onfidential & proprietary
More informationBig Data Analysis and Reporting with Decision Tree Induction
Big Data Analysis and Reporting with Deision Tree Indution PETRA PERNER Institute of Computer Vision and Applied Computer Sienes, IBaI Postbox 30 11 14, 04251 Leipzig GERMANY pperner@ibaiinstitut.de,
More informationGrey Critical Chain Project Scheduling Technique and Its Application
Canadian Soial Siene Vol.3 No.3 June 2007 Grey Critial Chain Projet Sheduling Tehnique and Its ppliation TECHNIQUE DE PROGRMMTION DE L CHINE CRITIQUE GRISE DU PROJET ET SON PPLICTION Gao Peng 1 Feng Junwen
More informationDataflow Features in Computer Networks
Magyar Kutatók 1. Nemzetközi Szimpóziuma 1 th International Symposium of Hungarian Researhers on Computational Intelligene and Informatis Gyula Max Budapest University of Tehnology and Eonomis, Department
More informationTECHNOLOGYENHANCED LEARNING FOR MUSIC WITH IMAESTRO FRAMEWORK AND TOOLS
TECHNOLOGYENHANCED LEARNING FOR MUSIC WITH IMAESTRO FRAMEWORK AND TOOLS ICSRiM  University of Leeds Shool of Computing & Shool of Musi Leeds LS2 9JT, UK +441133432583 kia@imaestro.org www.imaestro.org,
More informationInteractionDriven Virtual Reality Application Design
Nar s Parés npares@iua.upf.es Ro Parés rpares@iua.upf.es Audiovisual Institute, Universitat Pompeu Fabra, Pg. Cirumval. laió, 8 08003 Barelona, Spain www.iua.upf.es/, gvirtual InterationDriven Virtual
More informationChapter 1 Microeconomics of Consumer Theory
Chapter 1 Miroeonomis of Consumer Theory The two broad ategories of deisionmakers in an eonomy are onsumers and firms. Eah individual in eah of these groups makes its deisions in order to ahieve some
More informationGABOR AND WEBER LOCAL DESCRIPTORS PERFORMANCE IN MULTISPECTRAL EARTH OBSERVATION IMAGE DATA ANALYSIS
HENRI COANDA AIR FORCE ACADEMY ROMANIA INTERNATIONAL CONFERENCE of SCIENTIFIC PAPER AFASES 015 Brasov, 830 May 015 GENERAL M.R. STEFANIK ARMED FORCES ACADEMY SLOVAK REPUBLIC GABOR AND WEBER LOCAL DESCRIPTORS
More informationCA IdentityMinder r12.x Implementation Proven Professional Exam (CAT340) Study Guide Version 1.1
Exam (CAT340) Study Guide Version 1.1 PROPRIETARY AND CONFIDENTIAL INFORMATION 2016 CA. All rights reserved. CA onfidential & proprietary information. For CA, CA Partner and CA Customer use only. No unauthorized
More informationINCOME TAX WITHHOLDING GUIDE FOR EMPLOYERS
Virginia Department of Taxation INCOME TAX WITHHOLDING GUIDE FOR EMPLOYERS www.tax.virginia.gov 2614086 Rev. 07/14 * Table of Contents Introdution... 1 Important... 1 Where to Get Assistane... 1 Online
More informationExponential Maps and Symmetric Transformations in ClusterSpin. YouGang Feng
Exponential Maps and Symmetri Transformations in ClusterSpin System for Lattie Ising Models YouGang Feng Department of Basi Sienes, College of Siene, Guizhou University, Caijia Guan, Guiyang, 550003
More informationCHAPTER 14 Chemical Equilibrium: Equal but Opposite Reaction Rates
CHATER 14 Chemial Equilibrium: Equal but Opposite Reation Rates 14.1. Collet and Organize For two reversible reations, we are given the reation profiles (Figure 14.1). The profile for the onversion of
More informationSoftware Ecosystems: From Software Product Management to Software Platform Management
Software Eosystems: From Software Produt Management to Software Platform Management Slinger Jansen, Stef Peeters, and Sjaak Brinkkemper Department of Information and Computing Sienes Utreht University,
More informationImpact Simulation of Extreme Wind Generated Missiles on Radioactive Waste Storage Facilities
Impat Simulation of Extreme Wind Generated issiles on Radioative Waste Storage Failities G. Barbella Sogin S.p.A. Via Torino 6 00184 Rome (Italy), barbella@sogin.it Abstrat: The strutural design of temporary
More informationStrategic Plan. Achieving our 2020 vision. Faculty of Health Sciences
Strategi Plan Ahieving our 00 vision Faulty of Health Sienes Our Values guide our ations Health and Understanding, promoting, and influening the holisti welleing of self and others Our Vision To e a national
More informationUse of Track Geometry Measurements for Maintenance Planning
84 TRANSPORTATION RESEARCH RECORD 147 Use of Trak Geometry Measurements for Maintenane Planning WILLEM EBERSOHN AND ERNEST T. SELIG Trak geometry measurements are disussed as a means of evaluating the
More informationStatic Fairness Criteria in Telecommunications
Teknillinen Korkeakoulu ERIKOISTYÖ Teknillisen fysiikan koulutusohjelma 92002 Mat208 Sovelletun matematiikan erikoistyöt Stati Fairness Criteria in Teleommuniations Vesa Timonen, email: vesatimonen@hutfi
More informationTRENDS IN EXECUTIVE EDUCATION: TOWARDS A SYSTEMS APPROACH TO EXECUTIVE DEVELOPMENT PLANNING
INTERMAN 7 TRENDS IN EXECUTIVE EDUCATION: TOWARDS A SYSTEMS APPROACH TO EXECUTIVE DEVELOPMENT PLANNING by Douglas A. Ready, Albert A. Viere and Alan F. White RECEIVED 2 7 MAY 1393 International Labour
More informationComputer Structure. Topic 2. Contents
31 Topi 2 Computer Struture Contents 2.1 Introdution...................................... 33 2.2 Computer Organisation............................... 33 2.2.1 Calulating mahines  from Babbage to integrated
More informationSLAbased Resource Allocation for Software as a Service Provider (SaaS) in Cloud Computing Environments
2 th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing SLAbased Resoure Alloation for Software as a Servie Provider (SaaS) in Cloud Computing Environments Linlin Wu, Saurabh Kumar
More informationInterpretable Fuzzy Modeling using MultiObjective Immune Inspired Optimization Algorithms
Interpretable Fuzzy Modeling using MultiObjetive Immune Inspired Optimization Algorithms Jun Chen, Mahdi Mahfouf Abstrat In this paper, an immune inspired multiobjetive fuzzy modeling (IMOFM) mehanism
More informationRATING SCALES FOR NEUROLOGISTS
RATING SCALES FOR NEUROLOGISTS J Hobart iv22 WHY Correspondene to: Dr Jeremy Hobart, Department of Clinial Neurosienes, Peninsula Medial Shool, Derriford Hospital, Plymouth PL6 8DH, UK; Jeremy.Hobart@
More informationChemical Equilibrium. Chemical Equilibrium. Chemical Equilibrium. Chemical Equilibriu m. Chapter 14
Chapter 14 Chemial Equilibrium Chemial Equilibriu m Muh like water in a Ushaped tube, there is onstant mixing bak and forth through the lower portion of the tube. reatants produts It s as if the forward
More informationTable of Contents. Appendix II Application Checklist. Export Finance Program Working Capital Financing...7
Export Finane Program Guidelines Table of Contents Setion I General...........................................................1 A. Introdution............................................................1
More informationIEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL. 9, NO. 3, MAY/JUNE 2012 401
IEEE TRASACTIOS O DEPEDABLE AD SECURE COMPUTIG, VOL. 9, O. 3, MAY/JUE 2012 401 Mitigating Distributed Denial of Servie Attaks in Multiparty Appliations in the Presene of Clok Drifts Zhang Fu, Marina Papatriantafilou,
More information10.1 The Lorentz force law
Sott Hughes 10 Marh 2005 Massahusetts Institute of Tehnology Department of Physis 8.022 Spring 2004 Leture 10: Magneti fore; Magneti fields; Ampere s law 10.1 The Lorentz fore law Until now, we have been
More informationUsing Live Chat in your Call Centre
Using Live Chat in your Call Centre Otober Key Highlights Yesterday's all entres have beome today's ontat entres where agents deal with multiple queries from multiple hannels. Live Chat hat is one now
More informationCUBES IN PRODUCTS OF TERMS IN ARITHMETIC PROGRESSION
CUBES IN PRODUCTS OF TERMS IN ARITHMETIC PROGRESSION L. HAJDU 1, SZ. TENGELY, R. TIJDEMAN Abstrat. Euler proved that the produt of four positive integers in arithmeti progression is not a square. Győry,
More informationINCOME TAX WITHHOLDING GUIDE FOR EMPLOYERS
Virginia Department of Taxation INCOME TAX WITHHOLDING GUIDE FOR EMPLOYERS www.tax.virginia.gov 2614086 Rev. 01/16 Table of Contents Introdution... 1 Important... 1 Where to Get Assistane... 1 Online File
More informationTHE PERFORMANCE OF TRANSIT TIME FLOWMETERS IN HEATED GAS MIXTURES
Proeedings of FEDSM 98 998 ASME Fluids Engineering Division Summer Meeting June 225, 998 Washington DC FEDSM98529 THE PERFORMANCE OF TRANSIT TIME FLOWMETERS IN HEATED GAS MIXTURES John D. Wright Proess
More informationRobust Classification and Tracking of Vehicles in Traffic Video Streams
Proeedings of the IEEE ITSC 2006 2006 IEEE Intelligent Transportation Systems Conferene Toronto, Canada, September 1720, 2006 TC1.4 Robust Classifiation and Traking of Vehiles in Traffi Video Streams
More informationA novel active mass damper for vibration control of bridges
IABMAS 08, International Conferene on Bridge Maintenane, Safety and Management, 37 July 008, Seoul, Korea A novel ative mass damper for vibration ontrol of bridges U. Starossek & J. Sheller Strutural
More informationTaylor s Formula G. B. Folland
Taylor s Formula G. B. Folland There s a lot more to be said about Taylor s formula than the brief disussion on pp.113 4 of Apostol. Let me begin with a few definitions. Definitions. A funtion f defined
More informationThe Design of Vector Programs
Algorithmi Languages, de Bakker/van Vliet (eds.) FP, NorthHolland Publishing ompany, 1981,99114 The Design of Vetor Programs Alain Bossavit and Bertrand Meyer Diretion des Etudes et Reherhes, Eletriite
More informationBUILDING CODE SUMMARY GENERAL NOTES DESIGN BUILD ELECTRICAL DESIGN BUILD MECHANICAL & PLUMBING GENERAL NOTES GENERAL NOTES G101
D D BUILDING CODE SUMMARY GENERAL NOTES PROJECT DESCRIPTION: THIS PROJECT IS THE MINOR RENOVATION OF AN EXISTING OUTPATIENT CLINIC. SCOPE CONSISTS OF PAINT, CARPET, TILE, AND UPGRADE TO DIGITAL XRAY BUILDING
More informationOn Some Mathematics for Visualizing High Dimensional Data
On Some Mathematis for Visualizing High Dimensional Data Edward J. Wegman Jeffrey L. Solka Center for Computational Statistis George Mason University Fairfax, VA 22030 This paper is dediated to Professor
More informationCA Service Virtualization 8.x Implementation Proven Professional Exam (CAT580) Study Guide Version 1.0
Exam (CAT580) Study Guide Version 1.0 PROPRIETARY AND CONFIDENTIAL INFORMATION 2016 CA. All rights reserved. CA onfidential & proprietary information. For CA, CA Partner and CA Customer use only. No unauthorized
More informationSymmetric Subgame Perfect Equilibria in Resource Allocation
Proeedings of the TwentySixth AAAI Conferene on Artifiial Intelligene Symmetri Subgame Perfet Equilibria in Resoure Alloation Ludek Cigler Eole Polytehnique Fédérale de Lausanne Artifiial Intelligene
More information