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Plotting Direction Fields in Matlab and Maxima – a Short Tutorial
Plotting direction fields in Matlab and Maxima – a short tutorial Luis Carvalho Introduction A first order differential equation can be expressed as dx x0(t) = = f(t; x) (1) dt where t is the independent variable and x is the dependent variable (on t). Note that the equation above is in normal form. The difficulty in solving equation (1) depends clearly on f(t; x). One way to gain geometric insight on how the solution might look like is to observe that any solution to (1) should be such that the slope at any point P (t0; x0) is f(t0; x0), since this is the value of the derivative at P . With this motivation in mind, if you select enough points and plot the slopes in each of these points, you will obtain a direction field for ODE (1). However, it is not easy to plot such a direction field for any function f(t; x), and so we must resort to some computational help. There are many computational packages to help us in this task. This is a short tutorial on how to plot direction fields for first order ODE’s in Matlab and Maxima. Matlab Matlab is a powerful “computing environment that combines numeric computation, advanced graphics and visualization” 1. A nice package for plotting direction field in Matlab (although resourceful, Matlab does not provide such facility natively) can be found at http://math.rice.edu/»dfield, contributed by John C. Polking from the Dept. of Mathematics at Rice University. To install this add-on, simply browse to the files for your version of Matlab and download them. -
A Note on Integral Points on Elliptic Curves 3
Journal de Th´eorie des Nombres de Bordeaux 00 (XXXX), 000–000 A note on integral points on elliptic curves par Mark WATKINS Abstract. We investigate a problem considered by Zagier and Elkies, of finding large integral points on elliptic curves. By writ- ing down a generic polynomial solution and equating coefficients, we are led to suspect four extremal cases that still might have non- degenerate solutions. Each of these cases gives rise to a polynomial system of equations, the first being solved by Elkies in 1988 using the resultant methods of Macsyma, with there being a unique rational nondegenerate solution. For the second case we found that resultants and/or Gr¨obner bases were not very efficacious. Instead, at the suggestion of Elkies, we used multidimensional p-adic Newton iteration, and were able to find a nondegenerate solution, albeit over a quartic number field. Due to our methodol- ogy, we do not have much hope of proving that there are no other solutions. For the third case we found a solution in a nonic number field, but we were unable to make much progress with the fourth case. We make a few concluding comments and include an ap- pendix from Elkies regarding his calculations and correspondence with Zagier. Resum´ e.´ A` la suite de Zagier et Elkies, nous recherchons de grands points entiers sur des courbes elliptiques. En ´ecrivant une solution polynomiale g´en´erique et en ´egalisant des coefficients, nous obtenons quatre cas extr´emaux susceptibles d’avoir des so- lutions non d´eg´en´er´ees. Chacun de ces cas conduit `aun syst`eme d’´equations polynomiales, le premier ´etant r´esolu par Elkies en 1988 en utilisant les r´esultants de Macsyma; il admet une unique solution rationnelle non d´eg´en´er´ee. -
J JNIVERSITY of MINNESOTA J 1 I
, ; THE j JNIVERSITY OF MINNESOTA j 1 i eap OJtd (/OWJt :Da11 eoJtVOCatiOJt 1962 NORTHROP MEMORIAL AUDITORIUM THURSDAY MORNING, MAY 24 AT ELEVEN-THIRTY O'CLOCK THE BOARD OF REGENTS Dr. 0. Meredith \Vilson, President Mr. Laurence R. Lunden, Secretary Mr. Clinton T. Johnson, Treasurer Mr. Sterling B. Garrison, Assistant Secretary The Honorable Charles W. Mayo, M.D., Rochester First Vice President and Chairman The Honorable Marjorie J. Howard (Mrs. C. Edward), Excelsior Second Vice President The Honorable Daniel C. Gainey, Owatonna The Honorable Richard L. Griggs, Duluth The Honorable Bjarne E. Grottum, Jackson The Honorable Robert E. Hess, \Vhitc Bear Lake The Honorable Freel J. Hughes, St. Cloud The Honorable A. I. Johnson, Beman The Honorable Lester A. Malkcrson, Minneapolis The Honorable A. J. Olson, Renville The Honorable Otto A. Silha, Minneapolis The Honorable Herman F. Skyberg, Fisher SMOKING AND USE OF CAMERAS--It is requested, by action of the Board of Regents, that in Northrop Memorial Auditorium smoking be confined to the outer lobby on the main floor, to the gallery lobbies, and to the lounge rooms. The use of cameras in the auditorium by members of the audience is prohibited. rltis ls Vuur Uuivcrsitv CHARTERED in February, 1851, by the Legislative Assembly of the Territory of Minnesota, the University of Minnesota this year celebrated its one hundred and eleventh birthday. In the coming year, it will join with Land-Grant colleges and state universities throughout the nation in observing the centennial of the Land-Grant Act which created educational opportunities for all citizens and which embodied the concept that the welfare of the nation is dependent on the advancement of learning. -
Nonlinear Evolution Equations and Solving Algebraic Systems: the Importance of Computer Algebra
- Y'M?S </#i/ ИНСТИТУТ ядерных исследований дубна Е5-89-62Ц V.P.Gerdt, N.A.Kostov, A.Yu.Zharkov* NONLINEAR EVOLUTION EQUATIONS AND SOLVING ALGEBRAIC SYSTEMS: THE IMPORTANCE OF COMPUTER ALGEBRA Submitted to International Conference "Solitons and its Applications", Dubna, August 25-27, 1989 * Saratov State University, USSR 1989 1.INTRODUCTION A wide-spread problem in the theory of nonlinear evolution equations (NEE) is to find the exact solutions of complicated algebraic systems. For example, let us consider the following evolution systems U - AU + F(U,U , ..U ), U=U(x,t)-(U1, . ,UH) , U=D1(U), D=d/dx IN 1 N-1 I /ii F«(F\ . -FH) , A==diag(A , . .A) , A *0, A *A , (i*j). The general symmetry approach to checking up the integrability and classification of integrable NEE (see the reviews [1,2] and references therein) allows to obtain the integrability conditions which are related to existence of higher order symmetries and conservation laws in a fully algorithmic way. The implementation of these algorithms in a form of FORMAC program FORMINT have been given for scalar equations (M=l in (1)) in [3 j and for the general case (M>1) in [4]. Using this program one can automatically obtain the equations in right hand side of (l) which follow from the necessary integrability conditions. The integrabiiity conditions for the right hand side with arbitrary functions have the form of systems of differential equations, the procedure of solving these equations is not generally algorithmic. But in the important particular cases when the right hand side F are polynomials and the integrability conditions are reduced to a system of nonlinear algebraic equations in coefficients of the polynomials. -
Practical Semantic Web and Linked Data Applications
Practical Semantic Web and Linked Data Applications Common Lisp Edition Uses the Free Editions of Franz Common Lisp and AllegroGraph Mark Watson Copyright 2010 Mark Watson. All rights reserved. This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works Version 3.0 United States License. November 3, 2010 Contents Preface xi 1. Getting started . xi 2. Portable Common Lisp Code Book Examples . xii 3. Using the Common Lisp ASDF Package Manager . xii 4. Information on the Companion Edition to this Book that Covers Java and JVM Languages . xiii 5. AllegroGraph . xiii 6. Software License for Example Code in this Book . xiv 1. Introduction 1 1.1. Who is this Book Written For? . 1 1.2. Why a PDF Copy of this Book is Available Free on the Web . 3 1.3. Book Software . 3 1.4. Why Graph Data Representations are Better than the Relational Database Model for Dealing with Rapidly Changing Data Requirements . 4 1.5. What if You Use Other Programming Languages Other Than Lisp? . 4 2. AllegroGraph Embedded Lisp Quick Start 7 2.1. Starting AllegroGraph . 7 2.2. Working with RDF Data Stores . 8 2.2.1. Creating Repositories . 9 2.2.2. AllegroGraph Lisp Reader Support for RDF . 10 2.2.3. Adding Triples . 10 2.2.4. Fetching Triples by ID . 11 2.2.5. Printing Triples . 11 2.2.6. Using Cursors to Iterate Through Query Results . 13 2.2.7. Saving Triple Stores to Disk as XML, N-Triples, and N3 . 14 2.3. AllegroGraph’s Extensions to RDF . -
Oliver Knill: March 2000 Literature: Peter Norvig, Paradigns of Artificial Intelligence Programming Daniel Juravsky and James Martin, Speech and Language Processing
ENTRY ARTIFICIAL INTELLIGENCE [ENTRY ARTIFICIAL INTELLIGENCE] Authors: Oliver Knill: March 2000 Literature: Peter Norvig, Paradigns of Artificial Intelligence Programming Daniel Juravsky and James Martin, Speech and Language Processing Adaptive Simulated Annealing [Adaptive Simulated Annealing] A language interface to a neural net simulator. artificial intelligence [artificial intelligence] (AI) is a field of computer science concerned with the concepts and methods of symbolic knowledge representation. AI attempts to model aspects of human thought on computers. Aspectrs of AI: computer vision • language processing • pattern recognition • expert systems • problem solving • roboting • optical character recognition • artificial life • grammars • game theory • Babelfish [Babelfish] Online translation system from Systran. Chomsky [Chomsky] Noam Chomsky is a pioneer in formal language theory. He is MIT Professor of Linguistics, Linguistic Theory, Syntax, Semantics and Philosophy of Language. Eliza [Eliza] One of the first programs to feature English output as well as input. It was developed by Joseph Weizenbaum at MIT. The paper appears in the January 1966 issue of the "Communications of the Association of Computing Machinery". Google [Google] A search engine emerging at the end of the 20'th century. It has AI features, allows not only to answer questions by pointing to relevant webpages but can also do simple tasks like doing arithmetic computations, convert units, read the news or find pictures with some content. GPS [GPS] General Problem Solver. A program developed in 1957 by Alan Newell and Herbert Simon. The aim was to write a single computer program which could solve any problem. One reason why GPS was destined to fail is now at the core of computer science. -
The Evolution of Lisp
1 The Evolution of Lisp Guy L. Steele Jr. Richard P. Gabriel Thinking Machines Corporation Lucid, Inc. 245 First Street 707 Laurel Street Cambridge, Massachusetts 02142 Menlo Park, California 94025 Phone: (617) 234-2860 Phone: (415) 329-8400 FAX: (617) 243-4444 FAX: (415) 329-8480 E-mail: [email protected] E-mail: [email protected] Abstract Lisp is the world’s greatest programming language—or so its proponents think. The structure of Lisp makes it easy to extend the language or even to implement entirely new dialects without starting from scratch. Overall, the evolution of Lisp has been guided more by institutional rivalry, one-upsmanship, and the glee born of technical cleverness that is characteristic of the “hacker culture” than by sober assessments of technical requirements. Nevertheless this process has eventually produced both an industrial- strength programming language, messy but powerful, and a technically pure dialect, small but powerful, that is suitable for use by programming-language theoreticians. We pick up where McCarthy’s paper in the first HOPL conference left off. We trace the development chronologically from the era of the PDP-6, through the heyday of Interlisp and MacLisp, past the ascension and decline of special purpose Lisp machines, to the present era of standardization activities. We then examine the technical evolution of a few representative language features, including both some notable successes and some notable failures, that illuminate design issues that distinguish Lisp from other programming languages. We also discuss the use of Lisp as a laboratory for designing other programming languages. We conclude with some reflections on the forces that have driven the evolution of Lisp. -
WORKSHOP on COMPUTATIONAL ASPECTS in the CONTROL of FLEXIBLE SYSTEMS
NASA Technical Memorandum 10 1578, Part One WORKSHOP on COMPUTATIONAL ASPECTS in the CONTROL of FLEXIBLE SYSTEMS Held at the Royce Hotel in WiIIiamsburg, Virginia (\!~?~-~*-lolj?d-pt-l) P&~C~L~IN~Y-F THE <UL (; 8.; t\jo~-l?~Su ~~KY,~+~JDfl~CnHPUTATIONAL ASPFCTI IY TcF --T )~uI)-- ~f'4T1.1L dC Ei'XfrLt. >Y>TtU,, f'AQT i (.\A>A- r\eu-lP>CL L an-1-y Rps~arihCentnr) 492 p C5CL 2LR UnLl ~s 55 3 G;/i3 J,'i74qA Sponsored by the NASA Langley Research Center Proceedings Compiled by Larry Taylor Table of Contents Page Introduction Computational Aspects Workshop Call for Papers 1 Workshop Organizing Committee 5 Attendance List 7 --------___-----__-------------------------------------- Needs for Advanced CSI Software NASA's Control/Structures Interaction (CSI) Program Brantley R. Hanks, NASA Langley Research Center 21-, Computational Controls for Aerospace Systems Guy Man, Robert A. Laskin and A. Fernando Tolivar Jet Propulsion Laboratory 33. Additional Software Developments Wanted for Modeling and Control of Flexible Systems Jiguan G. Lin, Control Research Corporation 4 9 Survey of Available Software Flexible Structure Control Experiments Using a Real-Time Workstation for Computer-Aided Control Engineering Michael E. Steiber, Communications Research Centre 6 7 CONSOLE: A CAD Tandem for Optimizationl-Based Design Interacting with User-Supplied Simulators Michael K.H. Fan, Li-Shen Wang, Jan Koninckx and Andre L. Tits,University of Maryland, College Park 8 9 mLPAGE IS QUALfTY ORIGINAL PAGE IS OF POOR QUALITY The Application of TSIM Software to ACT Design and Analysis of Flexible Aircraft Ian W. Kaynes, Royal Aerospace Establishment, Farnborouth 109 - Control/Structure Interaction Methods for Space Statian Power Systems Paul Blelloch, Structural Dynamics Research Corporation 121L, Flexible Missile Autopilot Design Studies with PC-MATLAB386 Michael J. -
Programming Languages As Operating Systems (Or Revenge of the Son of the Lisp Machine)
Programming Languages as Operating Systems (or Revenge of the Son of the Lisp Machine) Matthew Flatt Robert Bruce Findler Shriram Krishnamurthi Matthias Felleisen Department of Computer Science∗ Rice University Houston, Texas 77005-1892 Abstract reclaim the program’s resources—even though the program and DrScheme share a single virtual machine. The MrEd virtual machine serves both as the implementa- To address this problem, MrEd provides a small set of tion platform for the DrScheme programming environment, new language constructs. These constructs allow a program- and as the underlying Scheme engine for executing expres- running program, such as DrScheme, to run nested programs sions and programs entered into DrScheme’s read-eval-print directly on the MrEd virtual machine without sacrificing loop. We describe the key elements of the MrEd virtual control over the nested programs. As a result, DrScheme machine for building a programming environment, and we can execute a copy of DrScheme that is executing its own step through the implementation of a miniature version of copy of DrScheme (see Figure 1). The inner and middle DrScheme in MrEd. More generally, we show how MrEd de- DrSchemes cannot interfere with the operation of the outer fines a high-level operating system for graphical programs. DrScheme, and the middle DrScheme cannot interfere with the outer DrScheme’s control over the inner DrScheme. 1 MrEd: A Scheme Machine In this paper, we describe the key elements of the MrEd virtual machine, and we step through the implementation The DrScheme programming environment [10] provides stu- of a miniature version of DrScheme in MrEd. -
A Framework for Representing Knowledge Marvin Minsky MIT-AI Laboratory Memo 306, June, 1974. Reprinted in the Psychology of Comp
A Framework for Representing Knowledge Marvin Minsky MIT-AI Laboratory Memo 306, June, 1974. Reprinted in The Psychology of Computer Vision, P. Winston (Ed.), McGraw-Hill, 1975. Shorter versions in J. Haugeland, Ed., Mind Design, MIT Press, 1981, and in Cognitive Science, Collins, Allan and Edward E. Smith (eds.) Morgan-Kaufmann, 1992 ISBN 55860-013-2] FRAMES It seems to me that the ingredients of most theories both in Artificial Intelligence and in Psychology have been on the whole too minute, local, and unstructured to account–either practically or phenomenologically–for the effectiveness of common-sense thought. The "chunks" of reasoning, language, memory, and "perception" ought to be larger and more structured; their factual and procedural contents must be more intimately connected in order to explain the apparent power and speed of mental activities. Similar feelings seem to be emerging in several centers working on theories of intelligence. They take one form in the proposal of Papert and myself (1972) to sub-structure knowledge into "micro-worlds"; another form in the "Problem-spaces" of Newell and Simon (1972); and yet another in new, large structures that theorists like Schank (1974), Abelson (1974), and Norman (1972) assign to linguistic objects. I see all these as moving away from the traditional attempts both by behavioristic psychologists and by logic-oriented students of Artificial Intelligence in trying to represent knowledge as collections of separate, simple fragments. I try here to bring together several of these issues by pretending to have a unified, coherent theory. The paper raises more questions than it answers, and I have tried to note the theory's deficiencies. -
(12) United States Patent (10) Patent No.: US 6,203,987 B1 Friend Et Al
USOO6203987B1 (12) United States Patent (10) Patent No.: US 6,203,987 B1 Friend et al. (45) Date of Patent: Mar. 20, 2001 (54) METHODS FOR USING CO-REGULATED Garrels, JI et al “Quant exploration of the REF52 protein GENESETS TO ENHANCE DETECTION AND database: cluster analysis reveals major protein expression CLASSIFICATION OF GENE EXPRESSION profiles in resonses to growth regulation, Serum Stimulation, PATTERNS and viral transformation’, Electrophoresis, 12/90, 11(12): 1114–30.* (75) Inventors: Stephen H. Friend, Seattle, WA (US); Anderson et al., 1994, “Involvement of the protein tyrosine Roland Stoughton, San Diego, CA kinase p56' in T cell signaling and thymocyte develop (US) ment.” Adv. Immunol. 56:151-178. (73) Assignee: Rosetta Inpharmatics, Inc., Kirkland, Anderson, 1995, “Mutagenesis", Methods Cell. Biol. 48:31. WA (US) Baudin et al., 1993, “A simple and efficient method for direct gene deletion in Saccharomyces cerevisiae, ' Nucl. Acids (*) Notice: Subject to any disclaimer, the term of this ReS. 21:3329-3330. patent is extended or adjusted under 35 Belshaw et al., 1996, “Controlling protein association and U.S.C. 154(b) by 0 days. Subcellular localization with a Synthetic ligand that induces heterodimerization of proteins,” Proc. Natl. Acad. Sci. USA (21) Appl. No.: 09/179,569 93:46O4-46O7. (22) Filed: Oct. 27, 1998 Bernoist and Chambon, 1981, “In vivo sequence require ments of the SV40 early promoter region”, Nature 290: (51) Int. Cl. ............................ C12O 1/68; C12P 21/04; 304-310. GO1N 33/543 Biocca, 1995, “Intracellular immunization: antibody target ing to subcellular compartments,” Trends in Cell Biology (52) U.S. -
Lisp: Program Is Data
LISP: PROGRAM IS DATA A HISTORICAL PERSPECTIVE ON MACLISP Jon L White Laboratory for Computer Science, M.I.T.* ABSTRACT For over 10 years, MACLISP has supported a variety of projects at M.I.T.'s Artificial Intelligence Laboratory, and the Laboratory for Computer Science (formerly Project MAC). During this time, there has been a continuing development of the MACLISP system, spurred in great measure by the needs of MACSYMAdevelopment. Herein are reported, in amosiac, historical style, the major features of the system. For each feature discussed, an attempt will be made to mention the year of initial development, andthe names of persons or projectsprimarily responsible for requiring, needing, or suggestingsuch features. INTRODUCTION In 1964,Greenblatt and others participated in thecheck-out phase of DigitalEquipment Corporation's new computer, the PDP-6. This machine had a number of innovative features that were thought to be ideal for the development of a list processing system, and thus it was very appropriate that thefirst working program actually run on thePDP-6 was anancestor of thecurrent MACLISP. This earlyLISP was patterned after the existing PDP-1 LISP (see reference l), and was produced by using the text editor and a mini-assembler on the PDP-1. That first PDP-6 finally found its way into M.I.T.'s ProjectMAC for use by theArtificial lntelligence group (the A.1. grouplater became the M.I.T. Artificial Intelligence Laboratory, and Project MAC became the Laboratory for Computer Science). By 1968, the PDP-6 wasrunning the Incompatible Time-sharing system, and was soon supplanted by the PDP-IO.Today, the KL-I 0, anadvanced version of thePDP-10, supports a variety of time sharing systems, most of which are capable of running a MACLISP.