On the Connectivity of Spaces of Three-Dimensional Domino Tilings
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Tiling a Rectangle with Polyominoes Olivier Bodini
Tiling a Rectangle with Polyominoes Olivier Bodini To cite this version: Olivier Bodini. Tiling a Rectangle with Polyominoes. Discrete Models for Complex Systems, DMCS’03, 2003, Lyon, France. pp.81-88. hal-01183321 HAL Id: hal-01183321 https://hal.inria.fr/hal-01183321 Submitted on 12 Aug 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Discrete Mathematics and Theoretical Computer Science AB(DMCS), 2003, 81–88 Tiling a Rectangle with Polyominoes Olivier Bodini1 1LIRMM, 161, rue ADA, 34392 Montpellier Cedex 5, France A polycube in dimension d is a finite union of unit d-cubes whose vertices are on knots of the lattice Zd. We show that, for each family of polycubes E, there exists a finite set F of bricks (parallelepiped rectangles) such that the bricks which can be tiled by E are exactly the bricks which can be tiled by F. Consequently, if we know the set F, then we have an algorithm to decide in polynomial time if a brick is tilable or not by the tiles of E. please also repeat in the submission form Keywords: Tiling, Polyomino 1 Introduction A polycube in dimension d (or more simply a polycube) is a finite -not necessarily connected- union of unit cubes whose vertices are on nodes of the lattice Zd . -
Lesson 3: Rectangles Inscribed in Circles
NYS COMMON CORE MATHEMATICS CURRICULUM Lesson 3 M5 GEOMETRY Lesson 3: Rectangles Inscribed in Circles Student Outcomes . Inscribe a rectangle in a circle. Understand the symmetries of inscribed rectangles across a diameter. Lesson Notes Have students use a compass and straightedge to locate the center of the circle provided. If necessary, remind students of their work in Module 1 on constructing a perpendicular to a segment and of their work in Lesson 1 in this module on Thales’ theorem. Standards addressed with this lesson are G-C.A.2 and G-C.A.3. Students should be made aware that figures are not drawn to scale. Classwork Scaffolding: Opening Exercise (9 minutes) Display steps to construct a perpendicular line at a point. Students follow the steps provided and use a compass and straightedge to find the center of a circle. This exercise reminds students about constructions previously . Draw a segment through the studied that are needed in this lesson and later in this module. point, and, using a compass, mark a point equidistant on Opening Exercise each side of the point. Using only a compass and straightedge, find the location of the center of the circle below. Label the endpoints of the Follow the steps provided. segment 퐴 and 퐵. Draw chord 푨푩̅̅̅̅. Draw circle 퐴 with center 퐴 . Construct a chord perpendicular to 푨푩̅̅̅̅ at and radius ̅퐴퐵̅̅̅. endpoint 푩. Draw circle 퐵 with center 퐵 . Mark the point of intersection of the perpendicular chord and the circle as point and radius ̅퐵퐴̅̅̅. 푪. Label the points of intersection . -
The Geometry of Diagonal Groups
The geometry of diagonal groups R. A. Baileya, Peter J. Camerona, Cheryl E. Praegerb, Csaba Schneiderc aUniversity of St Andrews, St Andrews, UK bUniversity of Western Australia, Perth, Australia cUniversidade Federal de Minas Gerais, Belo Horizonte, Brazil Abstract Diagonal groups are one of the classes of finite primitive permutation groups occurring in the conclusion of the O'Nan{Scott theorem. Several of the other classes have been described as the automorphism groups of geometric or combi- natorial structures such as affine spaces or Cartesian decompositions, but such structures for diagonal groups have not been studied in general. The main purpose of this paper is to describe and characterise such struct- ures, which we call diagonal semilattices. Unlike the diagonal groups in the O'Nan{Scott theorem, which are defined over finite characteristically simple groups, our construction works over arbitrary groups, finite or infinite. A diagonal semilattice depends on a dimension m and a group T . For m = 2, it is a Latin square, the Cayley table of T , though in fact any Latin square satisfies our combinatorial axioms. However, for m > 3, the group T emerges naturally and uniquely from the axioms. (The situation somewhat resembles projective geometry, where projective planes exist in great profusion but higher- dimensional structures are coordinatised by an algebraic object, a division ring.) A diagonal semilattice is contained in the partition lattice on a set Ω, and we provide an introduction to the calculus of partitions. Many of the concepts and constructions come from experimental design in statistics. We also determine when a diagonal group can be primitive, or quasiprimitive (these conditions turn out to be equivalent for diagonal groups). -
Simple Polygons Scribe: Michael Goldwasser
CS268: Geometric Algorithms Handout #5 Design and Analysis Original Handout #15 Stanford University Tuesday, 25 February 1992 Original Lecture #6: 28 January 1991 Topics: Triangulating Simple Polygons Scribe: Michael Goldwasser Algorithms for triangulating polygons are important tools throughout computa- tional geometry. Many problems involving polygons are simplified by partitioning the complex polygon into triangles, and then working with the individual triangles. The applications of such algorithms are well documented in papers involving visibility, motion planning, and computer graphics. The following notes give an introduction to triangulations and many related definitions and basic lemmas. Most of the definitions are based on a simple polygon, P, containing n edges, and hence n vertices. However, many of the definitions and results can be extended to a general arrangement of n line segments. 1 Diagonals Definition 1. Given a simple polygon, P, a diagonal is a line segment between two non-adjacent vertices that lies entirely within the interior of the polygon. Lemma 2. Every simple polygon with jPj > 3 contains a diagonal. Proof: Consider some vertex v. If v has a diagonal, it’s party time. If not then the only vertices visible from v are its neighbors. Therefore v must see some single edge beyond its neighbors that entirely spans the sector of visibility, and therefore v must be a convex vertex. Now consider the two neighbors of v. Since jPj > 3, these cannot be neighbors of each other, however they must be visible from each other because of the above situation, and thus the segment connecting them is indeed a diagonal. -
Stony Brook University
SSStttooonnnyyy BBBrrrooooookkk UUUnnniiivvveeerrrsssiiitttyyy The official electronic file of this thesis or dissertation is maintained by the University Libraries on behalf of The Graduate School at Stony Brook University. ©©© AAAllllll RRRiiiggghhhtttsss RRReeessseeerrrvvveeeddd bbbyyy AAAuuuttthhhooorrr... Combinatorics and Complexity in Geometric Visibility Problems A Dissertation Presented by Justin G. Iwerks to The Graduate School in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Applied Mathematics and Statistics (Operations Research) Stony Brook University August 2012 Stony Brook University The Graduate School Justin G. Iwerks We, the dissertation committee for the above candidate for the Doctor of Philosophy degree, hereby recommend acceptance of this dissertation. Joseph S. B. Mitchell - Dissertation Advisor Professor, Department of Applied Mathematics and Statistics Esther M. Arkin - Chairperson of Defense Professor, Department of Applied Mathematics and Statistics Steven Skiena Distinguished Teaching Professor, Department of Computer Science Jie Gao - Outside Member Associate Professor, Department of Computer Science Charles Taber Interim Dean of the Graduate School ii Abstract of the Dissertation Combinatorics and Complexity in Geometric Visibility Problems by Justin G. Iwerks Doctor of Philosophy in Applied Mathematics and Statistics (Operations Research) Stony Brook University 2012 Geometric visibility is fundamental to computational geometry and its ap- plications in areas such as robotics, sensor networks, CAD, and motion plan- ning. We explore combinatorial and computational complexity problems aris- ing in a collection of settings that depend on various notions of visibility. We first consider a generalized version of the classical art gallery problem in which the input specifies the number of reflex vertices r and convex vertices c of the simple polygon (n = r + c). -
Unit 6 Visualising Solid Shapes(Final)
• 3D shapes/objects are those which do not lie completely in a plane. • 3D objects have different views from different positions. • A solid is a polyhedron if it is made up of only polygonal faces, the faces meet at edges which are line segments and the edges meet at a point called vertex. • Euler’s formula for any polyhedron is, F + V – E = 2 Where F stands for number of faces, V for number of vertices and E for number of edges. • Types of polyhedrons: (a) Convex polyhedron A convex polyhedron is one in which all faces make it convex. e.g. (1) (2) (3) (4) 12/04/18 (1) and (2) are convex polyhedrons whereas (3) and (4) are non convex polyhedron. (b) Regular polyhedra or platonic solids: A polyhedron is regular if its faces are congruent regular polygons and the same number of faces meet at each vertex. For example, a cube is a platonic solid because all six of its faces are congruent squares. There are five such solids– tetrahedron, cube, octahedron, dodecahedron and icosahedron. e.g. • A prism is a polyhedron whose bottom and top faces (known as bases) are congruent polygons and faces known as lateral faces are parallelograms (when the side faces are rectangles, the shape is known as right prism). • A pyramid is a polyhedron whose base is a polygon and lateral faces are triangles. • A map depicts the location of a particular object/place in relation to other objects/places. The front, top and side of a figure are shown. Use centimetre cubes to build the figure. -
Curriculum Burst 31: Coloring a Pentagon by Dr
Curriculum Burst 31: Coloring a Pentagon By Dr. James Tanton, MAA Mathematician in Residence Each vertex of a convex pentagon ABCDE is to be assigned a color. There are 6 colors to choose from, and the ends of each diagonal must have different colors. How many different colorings are possible? SOURCE: This is question # 22 from the 2010 MAA AMC 10a Competition. QUICK STATS: MAA AMC GRADE LEVEL This question is appropriate for the 10th grade level. MATHEMATICAL TOPICS Counting: Permutations and Combinations COMMON CORE STATE STANDARDS S-CP.9: Use permutations and combinations to compute probabilities of compound events and solve problems. MATHEMATICAL PRACTICE STANDARDS MP1 Make sense of problems and persevere in solving them. MP2 Reason abstractly and quantitatively. MP3 Construct viable arguments and critique the reasoning of others. MP7 Look for and make use of structure. PROBLEM SOLVING STRATEGY ESSAY 7: PERSEVERANCE IS KEY 1 THE PROBLEM-SOLVING PROCESS: Three consecutive vertices the same color is not allowed. As always … (It gives a bad diagonal!) How about two pairs of neighboring vertices, one pair one color, the other pair a STEP 1: Read the question, have an second color? The single remaining vertex would have to emotional reaction to it, take a deep be a third color. Call this SCHEME III. breath, and then reread the question. This question seems complicated! We have five points A , B , C , D and E making a (convex) pentagon. A little thought shows these are all the options. (But note, with rotations, there are 5 versions of scheme II and 5 versions of scheme III.) Now we need to count the number Each vertex is to be colored one of six colors, but in a way of possible colorings for each scheme. -
A New Mathematical Model for Tiling Finite Regions of the Plane with Polyominoes
Volume 15, Number 2, Pages 95{131 ISSN 1715-0868 A NEW MATHEMATICAL MODEL FOR TILING FINITE REGIONS OF THE PLANE WITH POLYOMINOES MARCUS R. GARVIE AND JOHN BURKARDT Abstract. We present a new mathematical model for tiling finite sub- 2 sets of Z using an arbitrary, but finite, collection of polyominoes. Unlike previous approaches that employ backtracking and other refinements of `brute-force' techniques, our method is based on a systematic algebraic approach, leading in most cases to an underdetermined system of linear equations to solve. The resulting linear system is a binary linear pro- gramming problem, which can be solved via direct solution techniques, or using well-known optimization routines. We illustrate our model with some numerical examples computed in MATLAB. Users can download, edit, and run the codes from http://people.sc.fsu.edu/~jburkardt/ m_src/polyominoes/polyominoes.html. For larger problems we solve the resulting binary linear programming problem with an optimization package such as CPLEX, GUROBI, or SCIP, before plotting solutions in MATLAB. 1. Introduction and motivation 2 Consider a planar square lattice Z . We refer to each unit square in the lattice, namely [~j − 1; ~j] × [~i − 1;~i], as a cell.A polyomino is a union of 2 a finite number of edge-connected cells in the lattice Z . We assume that the polyominoes are simply-connected. The order (or area) of a polyomino is the number of cells forming it. The polyominoes of order n are called n-ominoes and the cases for n = 1; 2; 3; 4; 5; 6; 7; 8 are named monominoes, dominoes, triominoes, tetrominoes, pentominoes, hexominoes, heptominoes, and octominoes, respectively. -
Combinatorial Analysis of Diagonal, Box, and Greater-Than Polynomials As Packing Functions
Appl. Math. Inf. Sci. 9, No. 6, 2757-2766 (2015) 2757 Applied Mathematics & Information Sciences An International Journal http://dx.doi.org/10.12785/amis/090601 Combinatorial Analysis of Diagonal, Box, and Greater-Than Polynomials as Packing Functions 1,2, 3 2 4 Jose Torres-Jimenez ∗, Nelson Rangel-Valdez , Raghu N. Kacker and James F. Lawrence 1 CINVESTAV-Tamaulipas, Information Technology Laboratory, Km. 5.5 Carretera Victoria-Soto La Marina, 87130 Victoria Tamps., Mexico 2 National Institute of Standards and Technology, Gaithersburg, MD 20899, USA 3 Universidad Polit´ecnica de Victoria, Av. Nuevas Tecnolog´ıas 5902, Km. 5.5 Carretera Cd. Victoria-Soto la Marina, 87130, Cd. Victoria Tamps., M´exico 4 George Mason University, Fairfax, VA 22030, USA Received: 2 Feb. 2015, Revised: 2 Apr. 2015, Accepted: 3 Apr. 2015 Published online: 1 Nov. 2015 Abstract: A packing function is a bijection between a subset V Nm and N, where N denotes the set of non negative integers N. Packing functions have several applications, e.g. in partitioning schemes⊆ and in text compression. Two categories of packing functions are Diagonal Polynomials and Box Polynomials. The bijections for diagonal ad box polynomials have mostly been studied for small values of m. In addition to presenting bijections for box and diagonal polynomials for any value of m, we present a bijection using what we call Greater-Than Polynomial between restricted m dimensional vectors over Nm and N. We give details of two interesting applications of packing functions: (a) the application of greater-than− polynomials for the manipulation of Covering Arrays that are used in combinatorial interaction testing; and (b) the relationship between grater-than and diagonal polynomials with a special case of Diophantine equations. -
Diagonal Tuple Space Search in Two Dimensions
Diagonal Tuple Space Search in Two Dimensions Mikko Alutoin and Pertti Raatikainen VTT Information Technology P.O. Box 1202, FIN-02044 Finland {mikkocalutoin, pertti.raatikainen}@vtt.fi Abstract. Due to the evolution of the Internet and its services, the process of forwarding packets in routers is becoming more complex. In order to execute the sophisticated routing logic of modern firewalls, multidimensional packet classification is required. Unfortunately, the multidimensional packet classifi cation algorithms are known to be either time or storage hungry in the general case. It has been anticipated that more feasible algorithms could be obtained for conflict-free classifiers. This paper proposes a novel two-dimensional packet classification algorithrn applicable to the conflict-free classifiers. lt derives from the well-known tuple space paradigm and it has the search cost of O(log w) and storage complexity of O{n2w log w), where w is the width of the proto col fields given in bits and n is the number of rules in the classifier. This is re markable because without the conflict-free constraint the search cost in the two dimensional tup!e space is E>(w). 1 Introduction Traditional packet forwarding in the Internet is based on one-dimensional route Iook ups: destination IP address is used as the key when the Forwarding Information Base (FIB) is searched for matehing routes. The routes are stored in the FIB by using a network prefix as the key. A route matches a packet if its network prefix is a prefix of the packet's destination IP address. In the event that several routes match the packet, the one with the Iongest prefix prevails. -
Length and Circumference Assessment of Body Parts – the Creation of Easy-To-Use Predictions Formulas
49th International Conference on Environmental Systems ICES-2019-170 7-11 July 2019, Boston, Massachusetts Length and Circumference Assessment of Body Parts – The Creation of Easy-To-Use Predictions Formulas Jan P. Weber1 Technische Universität München, 85748 Garching b. München, Germany The Virtual Habitat project (V-HAB) at the Technical University of Munich (TUM) aims to develop a dynamic simulation environment for life support systems (LSS). Within V-HAB a dynamic human model interacts with the LSS by providing relevant metabolic inputs and outputs based on internal, environmental and operational factors. The human model is separated into five sub-models (called layers) representing metabolism, respiration, thermoregulation, water balance and digestion. The Wissler Thermal Model was converted in 2015/16 from Fortran to C#, introducing a more modularized structure and standalone graphical user interface (GUI). While previous effort was conducted in order to make the model in its current accepted version available in V-HAB, present work is focusing on the rework of the passive system. As part of this rework an extensive assessment of human body measurements and their dependency on a low number of influencing parameters was performed using the body measurements of 3982 humans (1774 men and 2208 women) in order to create a set of easy- to-use predictive formulas for the calculation of length and circumference measurements of various body parts. Nomenclature AAC = Axillary Arm Circumference KHM = Knee Height, Midpatella Age = Age of the -
A CONCISE MINI HISTORY of GEOMETRY 1. Origin And
Kragujevac Journal of Mathematics Volume 38(1) (2014), Pages 5{21. A CONCISE MINI HISTORY OF GEOMETRY LEOPOLD VERSTRAELEN 1. Origin and development in Old Greece Mathematics was the crowning and lasting achievement of the ancient Greek cul- ture. To more or less extent, arithmetical and geometrical problems had been ex- plored already before, in several previous civilisations at various parts of the world, within a kind of practical mathematical scientific context. The knowledge which in particular as such first had been acquired in Mesopotamia and later on in Egypt, and the philosophical reflections on its meaning and its nature by \the Old Greeks", resulted in the sublime creation of mathematics as a characteristically abstract and deductive science. The name for this science, \mathematics", stems from the Greek language, and basically means \knowledge and understanding", and became of use in most other languages as well; realising however that, as a matter of fact, it is really an art to reach new knowledge and better understanding, the Dutch term for mathematics, \wiskunde", in translation: \the art to achieve wisdom", might be even more appropriate. For specimens of the human kind, \nature" essentially stands for their organised thoughts about sensations and perceptions of \their worlds outside and inside" and \doing mathematics" basically stands for their thoughtful living in \the universe" of their idealisations and abstractions of these sensations and perceptions. Or, as Stewart stated in the revised book \What is Mathematics?" of Courant and Robbins: \Mathematics links the abstract world of mental concepts to the real world of physical things without being located completely in either".