Fermat Point
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Arxiv:1605.06950V4 [Stat.ML] 12 Apr 2017 Racy of RAND Depends on the Diameter of the Network, 1 X Which Motivated Cohen Et Al
A Sub-Quadratic Exact Medoid Algorithm James Newling Fran¸coisFleuret Idiap Research Institute & EPFL Idiap Research Institute & EPFL Abstract network analysis. In clustering, the Voronoi iteration K-medoids algorithm (Hastie et al., 2001; Park and Jun, 2009) requires determining the medoid of each of We present a new algorithm trimed for ob- K clusters at each iteration. In operations research, taining the medoid of a set, that is the el- the facility location problem requires placing one or ement of the set which minimises the mean several facilities so as to minimise the cost of connect- distance to all other elements. The algorithm ing to clients. In network analysis, the medoid may is shown to have, under certain assumptions, 3 d represent an influential person in a social network, or expected run time O(N 2 ) in where N is R the most central station in a rail network. the set size, making it the first sub-quadratic exact medoid algorithm for d > 1. Experi- ments show that it performs very well on spa- 1.1 Medoid algorithms and our contribution tial network data, frequently requiring two A simple algorithm for obtaining the medoid of a set orders of magnitude fewer distance calcula- of N elements computes the energy of all elements and tions than state-of-the-art approximate al- selects the one with minimum energy, requiring Θ(N 2) gorithms. As an application, we show how time. In certain settings Θ(N) algorithms exist, such trimed can be used as a component in an as in 1-D where the problem is solved by Quickse- accelerated K-medoids algorithm, and then lect (Hoare, 1961), and more generally on trees. -
Investigating Centers of Triangles: the Fermat Point
Investigating Centers of Triangles: The Fermat Point A thesis submitted to the Miami University Honors Program in partial fulfillment of the requirements for University Honors with Distinction by Katherine Elizabeth Strauss May 2011 Oxford, Ohio ABSTRACT INVESTIGATING CENTERS OF TRIANGLES: THE FERMAT POINT By Katherine Elizabeth Strauss Somewhere along their journey through their math classes, many students develop a fear of mathematics. They begin to view their math courses as the study of tricks and often seemingly unsolvable puzzles. There is a demand for teachers to make mathematics more useful and believable by providing their students with problems applicable to life outside of the classroom with the intention of building upon the mathematics content taught in the classroom. This paper discusses how to integrate one specific problem, involving the Fermat Point, into a high school geometry curriculum. It also calls educators to integrate interesting and challenging problems into the mathematics classes they teach. In doing so, a teacher may show their students how to apply the mathematics skills taught in the classroom to solve problems that, at first, may not seem directly applicable to mathematics. The purpose of this paper is to inspire other educators to pursue similar problems and investigations in the classroom in order to help students view mathematics through a more useful lens. After a discussion of the Fermat Point, this paper takes the reader on a brief tour of other useful centers of a triangle to provide future researchers and educators a starting point in order to create relevant problems for their students. iii iv Acknowledgements First of all, thank you to my advisor, Dr. -
On the Fermat Point of a Triangle Jakob Krarup, Kees Roos
280 NAW 5/18 nr. 4 december 2017 On the Fermat point of a triangle Jakob Krarup, Kees Roos Jakob Krarup Kees Roos Department of Computer Science Faculty of EEMCS University of Copenhagen, Denmark Technical University Delft [email protected] [email protected] Research On the Fermat point of a triangle For a given triangle 9ABC, Pierre de Fermat posed around 1640 the problem of finding a lem has been solved but it is not known by 2 point P minimizing the sum sP of the Euclidean distances from P to the vertices A, B, C. whom. As will be made clear in the sec- Based on geometrical arguments this problem was first solved by Torricelli shortly after, tion ‘Duality of (F) and (D)’, Torricelli’s ap- by Simpson in 1750, and by several others. Steeped in modern optimization techniques, proach already reveals that the problems notably duality, however, Jakob Krarup and Kees Roos show that the problem admits a (F) and (D) are dual to each other. straightforward solution. Using Simpson’s construction they furthermore derive a formula Our first aim is to show that application expressing sP in terms of the given triangle. This formula appears to reveal a simple re- of duality in conic optimization yields the lationship between the area of 9ABC and the areas of the two equilateral triangles that solution of (F), straightforwardly. Devel- occur in the so-called Napoleon’s Theorem. oped in the 1990s, the field of conic optimi- zation (CO) is a generalization of the more We deal with two problems in planar geo- Problem (D) was posed in 1755 by well-known field of linear optimization (LO). -
Robust Geometry Estimation Using the Generalized Voronoi Covariance Measure Louis Cuel, Jacques-Olivier Lachaud, Quentin Mérigot, Boris Thibert
Robust Geometry Estimation using the Generalized Voronoi Covariance Measure Louis Cuel, Jacques-Olivier Lachaud, Quentin Mérigot, Boris Thibert To cite this version: Louis Cuel, Jacques-Olivier Lachaud, Quentin Mérigot, Boris Thibert. Robust Geometry Estimation using the Generalized Voronoi Covariance Measure. SIAM Journal on Imaging Sciences, Society for In- dustrial and Applied Mathematics, 2015, 8 (2), pp.1293-1314. 10.1137/140977552. hal-01058145v2 HAL Id: hal-01058145 https://hal.archives-ouvertes.fr/hal-01058145v2 Submitted on 4 Nov 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. Robust Geometry Estimation using the Generalized Voronoi Covariance Measure∗y Louis Cuel1,2, Jacques-Olivier Lachaud 2, Quentin M´erigot1,3, and Boris Thibert2 1Laboratoire Jean Kuntzman, Universit´eGrenoble-Alpes, France 2Laboratoire de Math´ematiques(LAMA), Universit´ede Savoie, France 3CNRS November 4, 2015 Abstract d The Voronoi Covariance Measure of a compact set K of R is a tensor-valued measure that encodes geometrical information on K and which is known to be resilient to Hausdorff noise but sensitive to outliers. In this article, we generalize this notion to any distance-like function δ and define the δ-VCM. -
Mathematical Gems
AMS / MAA DOLCIANI MATHEMATICAL EXPOSITIONS VOL 1 Mathematical Gems ROSS HONSBERGER MATHEMATICAL GEMS FROM ELEMENTARY COMBINATORICS, NUMBER THEORY, AND GEOMETRY By ROSS HONSBERGER THE DOLCIANI MATHEMATICAL EXPOSITIONS Published by THE MArrHEMATICAL ASSOCIATION OF AMERICA Committee on Publications EDWIN F. BECKENBACH, Chairman 10.1090/dol/001 The Dolciani Mathematical Expositions NUMBER ONE MATHEMATICAL GEMS FROM ELEMENTARY COMBINATORICS, NUMBER THEORY, AND GEOMETRY By ROSS HONSBERGER University of Waterloo Published and Distributed by THE MATHEMATICAL ASSOCIATION OF AMERICA © 1978 by The Mathematical Association of America (Incorporated) Library of Congress Catalog Card Number 73-89661 Complete Set ISBN 0-88385-300-0 Vol. 1 ISBN 0-88385-301-9 Printed in the United States of Arnerica Current printing (last digit): 10 9 8 7 6 5 4 3 2 1 FOREWORD The DOLCIANI MATHEMATICAL EXPOSITIONS serIes of the Mathematical Association of America came into being through a fortuitous conjunction of circumstances. Professor-Mary P. Dolciani, of Hunter College of the City Uni versity of New York, herself an exceptionally talented and en thusiastic teacher and writer, had been contemplating ways of furthering the ideal of excellence in mathematical exposition. At the same time, the Association had come into possession of the manuscript for the present volume, a collection of essays which seemed not to fit precisely into any of the existing Associa tion series, and yet which obviously merited publication because of its interesting content and lucid expository style. It was only natural, then, that Professor Dolciani should elect to implement her objective by establishing a revolving fund to initiate this series of MATHEMATICAL EXPOSITIONS. -
Infield Biomass Bales Aggregation Logistics and Equipment Track
INFIELD BIOMASS BALES AGGREGATION LOGISTICS AND EQUIPMENT TRACK IMPACTED AREA EVALUATION A Thesis Submitted to the Graduate Faculty of the North Dakota State University of Agriculture and Applied Science By Subhashree Navaneetha Srinivasagan In Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE Major Department: Agricultural and Biosystems Engineering November 2017 Fargo, North Dakota NORTH DAKOTA STATE UNIVERSITY Graduate School Title INFIELD BIOMASS BALES AGGREGATION LOGISTICS AND EQUIPMENT TRACK IMPACTED AREA EVALUATION By Subhashree Navaneetha Srinivasagan The supervisory committee certifies that this thesis complies with North Dakota State University’s regulations and meets the accepted standards for the degree of MASTER OF SCIENCE SUPERVISORY COMMITTEE: Dr. Igathinathane Cannayen Chair Dr. Halis Simsek Dr. David Ripplinger Approved: 11/22/2017 Dr. Sreekala Bajwa Date Department Chair ABSTRACT Efficient bale stack location, infield bale logistics, and equipment track impacted area were conducted in three different studies using simulation in R. Even though the geometric median produced the best logistics, among the five mathematical grouping methods, the field middle was recommended as it was comparable and easily accessible in the field. Curvilinear method developed (8–259 ha), incorporating equipment turning (tractor: 1 and 2 bales/trip, automatic bale picker (ABP): 8–23 bales/trip, harvester, and baler), evaluated the aggregation distance, impacted area, and operation time. The harvester generated the most, followed by the baler, and the ABP the least impacted area and operation time. The ABP was considered as the most effective bale aggregation equipment compared to the tractor. Simple specific and generalized prediction models, developed for aggregation logistics, impacted area, and operation time, have performed 2 well (0.88 R 0.99). -
Robustness Meets Algorithms
Robustness Meets Algorithms Ankur Moitra (MIT) Robust Statistics Summer School CLASSIC PARAMETER ESTIMATION Given samples from an unknown distribution in some class e.g. a 1-D Gaussian can we accurately estimate its parameters? CLASSIC PARAMETER ESTIMATION Given samples from an unknown distribution in some class e.g. a 1-D Gaussian can we accurately estimate its parameters? Yes! CLASSIC PARAMETER ESTIMATION Given samples from an unknown distribution in some class e.g. a 1-D Gaussian can we accurately estimate its parameters? Yes! empirical mean: empirical variance: R. A. Fisher The maximum likelihood estimator is asymptotically efficient (1910-1920) R. A. Fisher J. W. Tukey The maximum likelihood What about errors in the estimator is asymptotically model itself? (1960) efficient (1910-1920) ROBUST PARAMETER ESTIMATION Given corrupted samples from a 1-D Gaussian: + = ideal model noise observed model can we accurately estimate its parameters? How do we constrain the noise? How do we constrain the noise? Equivalently: L1-norm of noise at most O(ε) How do we constrain the noise? Equivalently: Arbitrarily corrupt O(ε)-fraction L1-norm of noise at most O(ε) of samples (in expectation) How do we constrain the noise? Equivalently: Arbitrarily corrupt O(ε)-fraction L1-norm of noise at most O(ε) of samples (in expectation) This generalizes Huber’s Contamination Model: An adversary can add an ε-fraction of samples How do we constrain the noise? Equivalently: Arbitrarily corrupt O(ε)-fraction L1-norm of noise at most O(ε) of samples (in expectation) -
Geometric Median Shapes
GEOMETRIC MEDIAN SHAPES Alexandre Cunha Center for Advanced Methods in Biological Image Analysis Center for Data Driven Discovery California Institute of Technology, Pasadena, CA, USA ABSTRACT an efficient linear program in practice. They observed that smooth We present an algorithm to compute the geometric median of shapes do not necessarily lead to smooth medians, an aspect we also shapes which is based on the extension of median to high dimen- verified in some of our experiments. sions. The median finding problem is formulated as an optimization We propose a method to quickly build median shapes from over distances and it is solved directly using the watershed method closed planar contours representing silhouettes of shapes discretized as an optimizer. We show that the geometric median shape faithfully in images. Our median shape is computed using the notion of represents the true central tendency of the data, contaminated or not. geometric median [12], also known as the spatial median, Fermat- It is superior to the mean shape which can be negatively affected by Weber point, and L1 median (see [13] for the history and survey the presence of outliers. Our approach can be applied to manifold of multidimensional medians), which is an extension of the median and non manifold shapes, with single or multiple connected com- of numbers to points in higher dimensional spaces. The geometric ponents. The application of distance transform and watershed algo- median has the property, in any dimension, that it minimizes the n rithm, two well established constructs of image processing, lead to sum of its Euclidean distances to given anchor points xj 2 R , an algorithm that can be quickly implemented to generate fast solu- ∗ X x = arg min kx − xj k : (1) tions with linear storage requirement. -
Rotation Averaging
Noname manuscript No. (will be inserted by the editor) Rotation Averaging Richard Hartley, Jochen Trumpf, Yuchao Dai, Hongdong Li Received: date / Accepted: date Abstract This paper is conceived as a tutorial on rota- Single rotation averaging. In the single rotation averaging tion averaging, summarizing the research that has been car- problem, several estimates are obtained of a single rotation, ried out in this area; it discusses methods for single-view which are then averaged to give the best estimate. This may and multiple-view rotation averaging, as well as providing be thought of as finding a mean of several points Ri in the proofs of convergence and convexity in many cases. How- rotation space SO(3) (the group of all 3-dimensional rota- ever, at the same time it contains many new results, which tions) and is an instance of finding a mean in a manifold. were developed to fill gaps in knowledge, answering funda- Given an exponent p ≥ 1 and a set of n ≥ 1 rotations p mental questions such as radius of convergence of the al- fR1;:::; Rng ⊂ SO(3) we wish to find the L -mean rota- gorithms, and existence of local minima. These matters, or tion with respect to d which is defined as even proofs of correctness have in many cases not been con- n p X p sidered in the Computer Vision literature. d -mean(fR1;:::; Rng) = argmin d(Ri; R) : We consider three main problems: single rotation av- R2SO(3) i=1 eraging, in which a single rotation is computed starting Since SO(3) is compact, a minimum will exist as long as the from several measurements; multiple-rotation averaging, in distance function is continuous (which any sensible distance which absolute orientations are computed from several rel- function is). -
IX Geometrical Olympiad in Honour of I.F.Sharygin Final Round. Ratmino, 2013, August 1 Solutions First Day. 8 Grade 8.1. (N
IX Geometrical Olympiad in honour of I.F.Sharygin Final round. Ratmino, 2013, August 1 Solutions First day. 8 grade 8.1. (N. Moskvitin) Let ABCDE be a pentagon with right angles at vertices B and E and such that AB = AE and BC = CD = DE. The diagonals BD and CE meet at point F. Prove that FA = AB. First solution. The problem condition implies that the right-angled triangles ABC and AED are equal, thus the triangle ACD is isosceles (see fig. 8.1a). Then ∠BCD = ∠BCA + ∠ACD = = ∠EDA + ∠ADC = ∠CDE. Therefore, the isosceles triangles BCD and CDE are equal. Hence ∠CBD = ∠CDB = ∠ECD = ∠DEC. Since the triangle CFD is isosceles and BD = CE, we obtain that BF = FE. Therefore BFE 180◦ − 2 FCD 4ABF = 4AEF. Then AFB = ∠ = ∠ = 90◦ − ECD = 90◦ − DBC = ABF, ∠ 2 2 ∠ ∠ ∠ hence AB = AF, QED. BB BB CC CC PP FF FF AA AA AA DD AA DD EE EE Fig. 8.1а Fig. 8.1b Second solution. Let BC meet DE at point P (see fig. 8.1b). Notice that ∠CBD = ∠CDB = = ∠DBE, i.e., BD is the bisector of ∠CBE. Thus F is the incenter of 4PBE. Since the quadrilateral PBAE is cyclic and symmetrical, we obtain that A is the midpoint of arc BE of the circle (PBE). Therefore, by the trefoil theorem we get AF = AB, QED. Remark. The problem statement holds under the weakened condition of equality of side lengths. It is sufficient to say that AB = AE and BC = CD = DE. 8.2. (D. Shvetsov) Two circles with centers O1 and O2 meet at points A and B. -
From Euler to Ffiam: Discovery and Dissection of a Geometric Gem
From Euler to ffiam: Discovery and Dissection of a Geometric Gem Douglas R. Hofstadter Center for Research on Concepts & Cognition Indiana University • 510 North Fess Street Bloomington, Indiana 47408 December, 1992 ChapterO Bewitched ... by Circles, Triangles, and a Most Obscure Analogy Although many, perhaps even most, mathematics students and other lovers of mathematics sooner or later come across the famous Euler line, somehow I never did do so during my student days, either as a math major at Stanford in the early sixties or as a math graduate student at Berkeley for two years in the late sixties (after which I dropped out and switched to physics). Geometry was not by any means a high priority in the math curriculum at either institution. It passed me by almost entirely. Many, many years later, however, and quite on my own, I finally did become infatuated - nay, bewitched- by geometry. Just plane old Euclidean geometry, I mean. It all came from an attempt to prove a simple fact about circles that I vaguely remembered from a course on complex variables that I took some 30 years ago. From there on, the fascination just snowballed. I was caught completely off guard. Never would I have predicted that Doug Hofstadter, lover of number theory and logic, would one day go off on a wild Euclidean-geometry jag! But things are unpredictable, and that's what makes life interesting. I especially came to love triangles, circles, and their unexpectedly profound interrelations. I had never appreciated how intimately connected these two concepts are. Associated with any triangle are a plentitude of natural circles, and conversely, so many beautiful properties of circles cannot be defined except in terms of triangles. -
Concurrency of Four Euler Lines
Forum Geometricorum b Volume 1 (2001) 59–68. bbb FORUM GEOM ISSN 1534-1178 Concurrency of Four Euler Lines Antreas P. Hatzipolakis, Floor van Lamoen, Barry Wolk, and Paul Yiu Abstract. Using tripolar coordinates, we prove that if P is a point in the plane of triangle ABC such that the Euler lines of triangles PBC, AP C and ABP are concurrent, then their intersection lies on the Euler line of triangle ABC. The same is true for the Brocard axes and the lines joining the circumcenters to the respective incenters. We also prove that the locus of P for which the four Euler lines concur is the same as that for which the four Brocard axes concur. These results are extended to a family Ln of lines through the circumcenter. The locus of P for which the four Ln lines of ABC, PBC, AP C and ABP concur is always a curve through 15 finite real points, which we identify. 1. Four line concurrency Consider a triangle ABC with incenter I. It is well known [13] that the Euler lines of the triangles IBC, AIC and ABI concur at a point on the Euler line of ABC, the Schiffler point with homogeneous barycentric coordinates 1 a(s − a) b(s − b) c(s − c) : : . b + c c + a a + b There are other notable points which we can substitute for the incenter, so that a similar statement can be proven relatively easily. Specifically, we have the follow- ing interesting theorem. Theorem 1. Let P be a point in the plane of triangle ABC such that the Euler lines of the component triangles PBC, AP C and ABP are concurrent.