Using Computer Algebra Systems in Secondary School Mathematics: Issues of Curriculum, Assessment and Teaching
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Analysis and Verification of Arithmetic Circuits Using Computer Algebra Approach
University of Massachusetts Amherst ScholarWorks@UMass Amherst Doctoral Dissertations Dissertations and Theses March 2020 ANALYSIS AND VERIFICATION OF ARITHMETIC CIRCUITS USING COMPUTER ALGEBRA APPROACH TIANKAI SU University of Massachusetts Amherst Follow this and additional works at: https://scholarworks.umass.edu/dissertations_2 Part of the VLSI and Circuits, Embedded and Hardware Systems Commons Recommended Citation SU, TIANKAI, "ANALYSIS AND VERIFICATION OF ARITHMETIC CIRCUITS USING COMPUTER ALGEBRA APPROACH" (2020). Doctoral Dissertations. 1868. https://doi.org/10.7275/15875490 https://scholarworks.umass.edu/dissertations_2/1868 This Open Access Dissertation is brought to you for free and open access by the Dissertations and Theses at ScholarWorks@UMass Amherst. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of ScholarWorks@UMass Amherst. For more information, please contact [email protected]. ANALYSIS AND VERIFICATION OF ARITHMETIC CIRCUITS USING COMPUTER ALGEBRA APPROACH A Dissertation Presented by TIANKAI SU Submitted to the Graduate School of the University of Massachusetts Amherst in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY February 2020 Electrical and Computer Engineering c Copyright by Tiankai Su 2020 All Rights Reserved ANALYSIS AND VERIFICATION OF ARITHMETIC CIRCUITS USING COMPUTER ALGEBRA APPROACH A Dissertation Presented by TIANKAI SU Approved as to style and content by: Maciej Ciesielski, Chair George S. Avrunin, Member Daniel Holcomb, Member Weibo Gong, Member Christopher V. Hollot, Department Head Electrical and Computer Engineering ABSTRACT ANALYSIS AND VERIFICATION OF ARITHMETIC CIRCUITS USING COMPUTER ALGEBRA APPROACH FEBRUARY 2020 TIANKAI SU B.Sc., NORTHEAST DIANLI UNIVERSITY Ph.D., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Maciej Ciesielski Despite a considerable progress in verification of random and control logic, ad- vances in formal verification of arithmetic designs have been lagging. -
Solving Equations; Patterns, Functions, and Algebra; 8.15A
Mathematics Enhanced Scope and Sequence – Grade 8 Solving Equations Reporting Category Patterns, Functions, and Algebra Topic Solving equations in one variable Primary SOL 8.15a The student will solve multistep linear equations in one variable with the variable on one and two sides of the equation. Materials • Sets of algebra tiles • Equation-Solving Balance Mat (attached) • Equation-Solving Ordering Cards (attached) • Be the Teacher: Solving Equations activity sheet (attached) • Student whiteboards and markers Vocabulary equation, variable, coefficient, constant (earlier grades) Student/Teacher Actions (what students and teachers should be doing to facilitate learning) 1. Give each student a set of algebra tiles and a copy of the Equation-Solving Balance Mat. Lead students through the steps for using the tiles to model the solutions to the following equations. As you are working through the solution of each equation with the students, point out that you are undoing each operation and keeping the equation balanced by doing the same thing to both sides. Explain why you do this. When students are comfortable with modeling equation solutions with algebra tiles, transition to writing out the solution steps algebraically while still using the tiles. Eventually, progress to only writing out the steps algebraically without using the tiles. • x + 3 = 6 • x − 2 = 5 • 3x = 9 • 2x + 1 = 9 • −x + 4 = 7 • −2x − 1 = 7 • 3(x + 1) = 9 • 2x = x − 5 Continue to allow students to use the tiles whenever they wish as they work to solve equations. 2. Give each student a whiteboard and marker. Provide students with a problem to solve, and as they write each step, have them hold up their whiteboards so you can ensure that they are completing each step correctly and understanding the process. -
The Misfortunes of a Trio of Mathematicians Using Computer Algebra Systems
The Misfortunes of a Trio of Mathematicians Using Computer Algebra Systems. Can We Trust in Them? Antonio J. Durán, Mario Pérez, and Juan L. Varona Introduction by a typical research mathematician, but let us Nowadays, mathematicians often use a computer explain it briefly. It is not necessary to completely algebra system as an aid in their mathematical understand the mathematics, just to realize that it research; they do the thinking and leave the tedious is typical mathematical research using computer calculations to the computer. Everybody “knows” algebra as a tool. that computers perform this work better than Our starting point is a discrete positive measure people. But, of course, we must trust in the results on the real line, µ n 0 Mnδan (where δa denotes = ≥ derived via these powerful computer algebra the Dirac delta at a, and an < an 1) having P + systems. First of all, let us clarify that this paper is a sequence of orthogonal polynomials Pn n 0 f g ≥ not, in any way, a comparison between different (where Pn has degree n and positive leading computer algebra systems, but a sample of the coefficient). Karlin and Szeg˝oconsidered in 1961 (see [4]) the l l Casorati determinants current state of the art of what mathematicians × can expect when they use this kind of software. Pn(ak)Pn(ak 1):::Pn(ak l 1) Although our example deals with a concrete system, + + − Pn 1(ak)Pn 1(ak 1):::Pn 1(ak l 1) 0 + + + + + − 1 we are sure that similar situations may occur with (1) det . -
Addition and Subtraction
A Addition and Subtraction SUMMARY (475– 221 BCE), when arithmetic operations were per- formed by manipulating rods on a flat surface that was Addition and subtraction can be thought of as a pro- partitioned by vertical and horizontal lines. The num- cess of accumulation. For example, if a flock of 3 sheep bers were represented by a positional base- 10 system. is joined with a flock of 4 sheep, the combined flock Some scholars believe that this system— after moving will have 7 sheep. Thus, 7 is the sum that results from westward through India and the Islamic Empire— the addition of the numbers 3 and 4. This can be writ- became the modern system of representing numbers. ten as 3 + 4 = 7 where the sign “+” is read “plus” and The Greeks in the fifth century BCE, in addition the sign “=” is read “equals.” Both 3 and 4 are called to using a complex ciphered system for representing addends. Addition is commutative; that is, the order numbers, used a system that is very similar to Roman of the addends is irrelevant to how the sum is formed. numerals. It is possible that the Greeks performed Subtraction finds the remainder after a quantity is arithmetic operations by manipulating small stones diminished by a certain amount. If from a flock con- on a large, flat surface partitioned by lines. A simi- taining 5 sheep, 3 sheep are removed, then 2 sheep lar stone tablet was found on the island of Salamis remain. In this example, 5 is the minuend, 3 is the in the 1800s and is believed to date from the fourth subtrahend, and 2 is the remainder or difference. -
Diffman: an Object-Oriented MATLAB Toolbox for Solving Differential Equations on Manifolds
Applied Numerical Mathematics 39 (2001) 323–347 www.elsevier.com/locate/apnum DiffMan: An object-oriented MATLAB toolbox for solving differential equations on manifolds Kenth Engø a,∗,1, Arne Marthinsen b,2, Hans Z. Munthe-Kaas a,3 a Department of Informatics, University of Bergen, N-5020 Bergen, Norway b Department of Mathematical Sciences, NTNU, N-7491 Trondheim, Norway Abstract We describe an object-oriented MATLAB toolbox for solving differential equations on manifolds. The software reflects recent development within the area of geometric integration. Through the use of elements from differential geometry, in particular Lie groups and homogeneous spaces, coordinate free formulations of numerical integrators are developed. The strict mathematical definitions and results are well suited for implementation in an object- oriented language, and, due to its simplicity, the authors have chosen MATLAB as the working environment. The basic ideas of DiffMan are presented, along with particular examples that illustrate the working of and the theory behind the software package. 2001 IMACS. Published by Elsevier Science B.V. All rights reserved. Keywords: Geometric integration; Numerical integration of ordinary differential equations on manifolds; Numerical analysis; Lie groups; Lie algebras; Homogeneous spaces; Object-oriented programming; MATLAB; Free Lie algebras 1. Introduction DiffMan is an object-oriented MATLAB [24] toolbox designed to solve differential equations evolving on manifolds. The current version of the toolbox addresses primarily the solution of ordinary differential equations. The solution techniques implemented fall into the category of geometric integrators— a very active area of research during the last few years. The essence of geometric integration is to construct numerical methods that respect underlying constraints, for instance, the configuration space * Corresponding author. -
Teaching Strategies for Improving Algebra Knowledge in Middle and High School Students
EDUCATOR’S PRACTICE GUIDE A set of recommendations to address challenges in classrooms and schools WHAT WORKS CLEARINGHOUSE™ Teaching Strategies for Improving Algebra Knowledge in Middle and High School Students NCEE 2015-4010 U.S. DEPARTMENT OF EDUCATION About this practice guide The Institute of Education Sciences (IES) publishes practice guides in education to provide edu- cators with the best available evidence and expertise on current challenges in education. The What Works Clearinghouse (WWC) develops practice guides in conjunction with an expert panel, combining the panel’s expertise with the findings of existing rigorous research to produce spe- cific recommendations for addressing these challenges. The WWC and the panel rate the strength of the research evidence supporting each of their recommendations. See Appendix A for a full description of practice guides. The goal of this practice guide is to offer educators specific, evidence-based recommendations that address the challenges of teaching algebra to students in grades 6 through 12. This guide synthesizes the best available research and shares practices that are supported by evidence. It is intended to be practical and easy for teachers to use. The guide includes many examples in each recommendation to demonstrate the concepts discussed. Practice guides published by IES are available on the What Works Clearinghouse website at http://whatworks.ed.gov. How to use this guide This guide provides educators with instructional recommendations that can be implemented in conjunction with existing standards or curricula and does not recommend a particular curriculum. Teachers can use the guide when planning instruction to prepare students for future mathemat- ics and post-secondary success. -
Step-By-Step Solution Possibilities in Different Computer Algebra Systems
Step-by-Step Solution Possibilities in Different Computer Algebra Systems Eno Tõnisson University of Tartu Estonia E-mail: [email protected] Introduction The aim of my research is to compare different computer algebra systems, and specifically to find out how the students could solve problems step-by-step using different computer algebra systems. The present paper provides the preliminary comparison of some aspects related to step-by-step solution in DERIVE, Maple, Mathematica, and MuPAD. The paper begins with examples of one-step solutions of equations. This is followed by a cursory survey of useful commands, entering commands, programming etc. I hope that a more detailed and complete review will be composed quite soon. Suggestions for complementing the comparison are welcome. It is necessary to know which concrete versions are under consideration. In alphabetical order: DERIVE for Windows. Version 4.11 (1996) Maple V Release 5. Student Version 5.00 (1998) Mathematica for Students. Version 3.0 (1996) MuPAD Light. Version 1.4.1 (1998) Only pure systems (without additional packages, etc.) are under consideration. I believe that there may be more (especially interface-sensitive) possibilities in MuPAD Pro than in MuPAD Light. My paper is not the first comparison, of course. I found several previous ones in the Internet. For example, 1. Michael Wester. A review of CAS mathematical capabilities. 1995 There are 131 short problems covering a broad range of symbolic mathematics. http://math.unm.edu/~wester/cas/Paper.ps (One of the profoundest comparisons is probably M. Wester's book Practical Guide to Computer Algebra Systems.) 1 2. -
The Evolution of Equation-Solving: Linear, Quadratic, and Cubic
California State University, San Bernardino CSUSB ScholarWorks Theses Digitization Project John M. Pfau Library 2006 The evolution of equation-solving: Linear, quadratic, and cubic Annabelle Louise Porter Follow this and additional works at: https://scholarworks.lib.csusb.edu/etd-project Part of the Mathematics Commons Recommended Citation Porter, Annabelle Louise, "The evolution of equation-solving: Linear, quadratic, and cubic" (2006). Theses Digitization Project. 3069. https://scholarworks.lib.csusb.edu/etd-project/3069 This Thesis is brought to you for free and open access by the John M. Pfau Library at CSUSB ScholarWorks. It has been accepted for inclusion in Theses Digitization Project by an authorized administrator of CSUSB ScholarWorks. For more information, please contact [email protected]. THE EVOLUTION OF EQUATION-SOLVING LINEAR, QUADRATIC, AND CUBIC A Project Presented to the Faculty of California State University, San Bernardino In Partial Fulfillment of the Requirements for the Degre Master of Arts in Teaching: Mathematics by Annabelle Louise Porter June 2006 THE EVOLUTION OF EQUATION-SOLVING: LINEAR, QUADRATIC, AND CUBIC A Project Presented to the Faculty of California State University, San Bernardino by Annabelle Louise Porter June 2006 Approved by: Shawnee McMurran, Committee Chair Date Laura Wallace, Committee Member , (Committee Member Peter Williams, Chair Davida Fischman Department of Mathematics MAT Coordinator Department of Mathematics ABSTRACT Algebra and algebraic thinking have been cornerstones of problem solving in many different cultures over time. Since ancient times, algebra has been used and developed in cultures around the world, and has undergone quite a bit of transformation. This paper is intended as a professional developmental tool to help secondary algebra teachers understand the concepts underlying the algorithms we use, how these algorithms developed, and why they work. -
Derivation of Numerical Methods Using Computer Algebra∗
SIAM REVIEW c 1999 Society for Industrial and Applied Mathematics Vol. 41, No. 3, pp. 577–593 Derivation of Numerical Methods Using Computer Algebra∗ Walter Gandery Dominik Gruntzz Abstract. The use of computer algebra systems in a course on scientific computation is demonstrated. Various examples, such as the derivation of Newton's iteration formula, the secant method, Newton{Cotes and Gaussian integration formulas, as well as Runge{Kutta formulas, are presented. For the derivations, the computer algebra system Maple is used. Key words. numerical methods, computer algebra, Maple, quadrature formulas, nonlinear equations, finite elements, Rayleigh{Ritz, Galerkin method, Runge{Kutta method AMS subject classifications. 65-01, 68Q40, 65D32, 65H05, 65L60, 65L06 PII. S003614459935093X 1. Introduction. At ETH Z¨urich we have redesigned our courses on numerical analysis. We not only teach numerical algorithms but also introduce the students to computer algebra and make heavy use of computer algebra systems in both lectures and assignments. Computer algebra is used to generate numerical algorithms, to compute discretization errors, to derive convergence rates, to simplify proofs, to run examples, and to generate plots. We claim that it is easier for students to follow a derivation carried out with the help of a computer algebra system than one done by hand. Computer algebra systems take over the hard manual work, such as solving systems of equations. Students need not be concerned with all the details (and all the small glitches) of a manual derivation and can understand and keep an overview of the general steps of the derivation. A computer-supported derivation is also more convincing than a presentation of the bare results without any reasoning. -
Symbolicdata: Sdeval-Benchmarking for Everyone
SymbolicData:SDEval - Benchmarking for Everyone Albert Heinle1, Viktor Levandovskyy2, Andreas Nareike3 1 Cheriton School of Computer Science, University of Waterloo, Waterloo, Canada 2 Lehrstuhl D f¨urMathematik, RWTH Aachen University, Aachen, Germany 3 HTWK Leipzig, Leipzig, Germany Abstract. In this paper we will present SDeval, a software project that contains tools for creating and running benchmarks with a focus on problems in computer algebra. It is built on top of the Symbolic Data project, able to translate problems in the database into executable code for various computer algebra systems. The included tools are designed to be very flexible to use and to extend, such that they can be utilized even in contexts of other communities. With the presentation of SDEval, we will also address particularities of benchmarking in the field of computer algebra. Furthermore, with SDEval, we provide a feasible and automatizable way of reproducing benchmarks published in current research works, which appears to be a difficult task in general due to the customizability of the available programs. We will simultaneously present the current developments in the Sym- bolic Data project. 1 Introduction Benchmarking of software { i.e. measuring the quality of results and the time resp. memory consumption for a given, standardized set of examples as input { is a common way of evaluating implementations of algorithms in many areas of industry and academia. For example, common benchmarks for satisfiability modulo theorems (SMT) solvers are collected in the standard library SMT-LIB ([BST10]), and the advantages of various solvers like Z3 ([DMB08]) or CVC4 ([BCD+11]) are revealed with the help of those benchmarks. -
Constructing a Computer Algebra System Capable of Generating Pedagogical Step-By-Step Solutions
DEGREE PROJECT IN COMPUTER SCIENCE AND ENGINEERING, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2016 Constructing a Computer Algebra System Capable of Generating Pedagogical Step-by-Step Solutions DMITRIJ LIOUBARTSEV KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF COMPUTER SCIENCE AND COMMUNICATION Constructing a Computer Algebra System Capable of Generating Pedagogical Step-by-Step Solutions DMITRIJ LIOUBARTSEV Examenrapport vid NADA Handledare: Mårten Björkman Examinator: Olof Bälter Abstract For the problem of producing pedagogical step-by-step so- lutions to mathematical problems in education, standard methods and algorithms used in construction of computer algebra systems are often not suitable. A method of us- ing rules to manipulate mathematical expressions in small steps is suggested and implemented. The problem of creat- ing a step-by-step solution by choosing which rule to apply and when to do it is redefined as a graph search problem and variations of the A* algorithm are used to solve it. It is all put together into one prototype solver that was evalu- ated in a study. The study was a questionnaire distributed among high school students. The results showed that while the solutions were not as good as human-made ones, they were competent. Further improvements of the method are suggested that would probably lead to better solutions. Referat Konstruktion av ett datoralgebrasystem kapabelt att generera pedagogiska steg-för-steg-lösningar För problemet att producera pedagogiska steg-för-steg lös- ningar till matematiska problem inom utbildning, är vanli- ga metoder och algoritmer som används i konstruktion av datoralgebrasystem ofta inte lämpliga. En metod som an- vänder regler för att manipulera matematiska uttryck i små steg föreslås och implementeras. -
Analytic Geometry
CHAPTER 2 Analytic Geometry Euclid talks about geometry in Elements as if there is only one geometry. Today, some people think of there being several, and others think of there being infinitely many. Hopefully, after you get through this course, you will be in the second group. The people in the first group generally think of geometry as running from Euclid to Hilbert and then branching into Euclidean geometry, hyperbolic geometry and elliptic geometry. People in the second group understand that perfectly well, but include another, earlier brach starting with Rene Descartes (usually pronounced like “day KART”). This branch continues through people like Gauss and Riemann, and even people like Albert Einstein. In my mind, two of the major advances in the understanding of geometry were known to Descartes. One of these, was only known to Descartes, but Gauss, it seems, figured it out on his own, and we all followed him. The other you know very well, but you probably don’t know much about where it came from. This was the development of analytic geometry, geometry using coordinates. The other is not known very well at all, but Descartes noticed something that tells us that geometry should be built upon a general concept of curvature. What is generally called Modern geometry begins with Euclid and ends with Hilbert. The alternate path, the truly contemporary geometry, begins with Descartes and blossoms with Riemann. Note that, as is typical, modern usually means a long time ago. We’ll look at analytic geometry first, and Descartes’ other piece of insight will come later.