Fast Visualisation and Interactive Design of Deterministic Fractals
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On the Mandelbrot Set for I2 = ±1 and Imaginary Higgs Fields
Journal of Advances in Applied Mathematics, Vol. 6, No. 2, April 2021 https://dx.doi.org/10.22606/jaam.2021.62001 27 On the Mandelbrot Set for i2 = ±1 and Imaginary Higgs Fields Jonathan Blackledge Stokes Professor, Science Foundation Ireland. Distinguished Professor, Centre for Advanced Studies, Warsaw University of Technology, Poland. Visiting Professor, Faculty of Arts, Science and Technology, Wrexham Glyndwr University of Wales, UK. Professor Extraordinaire, Faculty of Natural Sciences, University of Western Cape, South Africa. Honorary Professor, School of Electrical and Electronic Engineering, Technological University Dublin, Ireland. Honorary Professor, School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, South Africa. Email: [email protected] Abstract We consider the consequence√ of breaking with a fundamental result in complex analysis by letting i2 = ±1 where i = −1 is the basic unit of all imaginary numbers. An analysis of the Mandelbrot set for this case shows that a demarcation between a Fractal and a Euclidean object is possible based on i2 = −1 and i2 = +1, respectively. Further, we consider the transient behaviour associated with the two cases to produce a range of non-standard sets in which a Fractal geometric structure is transformed into a Euclidean object. In the case of the Mandelbrot set, the Euclidean object is a square whose properties are investigate. Coupled with the associated Julia sets and other complex plane mappings, this approach provides the potential to generate a wide range of new semi-fractal structures which are visually interesting and may be of artistic merit. In this context, we present a mathematical paradox which explores the idea that i2 = ±1. -
Object Oriented Programming
No. 52 March-A pril'1990 $3.95 T H E M TEe H CAL J 0 URN A L COPIA Object Oriented Programming First it was BASIC, then it was structures, now it's objects. C++ afi<;ionados feel, of course, that objects are so powerful, so encompassing that anything could be so defined. I hope they're not placing bets, because if they are, money's no object. C++ 2.0 page 8 An objective view of the newest C++. Training A Neural Network Now that you have a neural network what do you do with it? Part two of a fascinating series. Debugging C page 21 Pointers Using MEM Keep C fro111 (C)rashing your system. An AT Keyboard Interface Use an AT keyboard with your latest project. And More ... Understanding Logic Families EPROM Programming Speeding Up Your AT Keyboard ((CHAOS MADE TO ORDER~ Explore the Magnificent and Infinite World of Fractals with FRAC LS™ AN ELECTRONIC KALEIDOSCOPE OF NATURES GEOMETRYTM With FracTools, you can modify and play with any of the included images, or easily create new ones by marking a region in an existing image or entering the coordinates directly. Filter out areas of the display, change colors in any area, and animate the fractal to create gorgeous and mesmerizing images. Special effects include Strobe, Kaleidoscope, Stained Glass, Horizontal, Vertical and Diagonal Panning, and Mouse Movies. The most spectacular application is the creation of self-running Slide Shows. Include any PCX file from any of the popular "paint" programs. FracTools also includes a Slide Show Programming Language, to bring a higher degree of control to your shows. -
Computer Graphics and Visualization
European Research Consortium for Informatics and Mathematics Number 44 January 2001 www.ercim.org Special Theme: Computer Graphics and Visualization Next Issue: April 2001 Next Special Theme: Metacomputing and Grid Technologies CONTENTS KEYNOTE 36 Physical Deforming Agents for Virtual Neurosurgery by Michele Marini, Ovidio Salvetti, Sergio Di Bona 3 by Elly Plooij-van Gorsel and Ludovico Lutzemberger 37 Visualization of Complex Dynamical Systems JOINT ERCIM ACTIONS in Theoretical Physics 4 Philippe Baptiste Winner of the 2000 Cor Baayen Award by Anatoly Fomenko, Stanislav Klimenko and Igor Nikitin 38 Simulation and Visualization of Processes 5 Strategic Workshops – Shaping future EU-NSF collaborations in in Moving Granular Bed Gas Cleanup Filter Information Technologies by Pavel Slavík, František Hrdliãka and Ondfiej Kubelka THE EUROPEAN SCENE 39 Watching Chromosomes during Cell Division by Robert van Liere 5 INRIA is growing at an Unprecedented Pace and is starting a Recruiting Drive on a European Scale 41 The blue-c Project by Markus Gross and Oliver Staadt SPECIAL THEME 42 Augmenting the Common Working Environment by Virtual Objects by Wolfgang Broll 6 Graphics and Visualization: Breaking new Frontiers by Carol O’Sullivan and Roberto Scopigno 43 Levels of Detail in Physically-based Real-time Animation by John Dingliana and Carol O’Sullivan 8 3D Scanning for Computer Graphics by Holly Rushmeier 44 Static Solution for Real Time Deformable Objects With Fluid Inside by Ivan F. Costa and Remis Balaniuk 9 Subdivision Surfaces in Geometric -
Fractal 3D Magic Free
FREE FRACTAL 3D MAGIC PDF Clifford A. Pickover | 160 pages | 07 Sep 2014 | Sterling Publishing Co Inc | 9781454912637 | English | New York, United States Fractal 3D Magic | Banyen Books & Sound Option 1 Usually ships in business days. Option 2 - Most Popular! This groundbreaking 3D showcase offers a rare glimpse into the dazzling world of computer-generated fractal art. Prolific polymath Clifford Pickover introduces the collection, which provides background on everything from Fractal 3D Magic classic Mandelbrot set, to the infinitely porous Menger Sponge, to ethereal fractal flames. The following eye-popping gallery displays mathematical formulas transformed into stunning computer-generated 3D anaglyphs. More than intricate designs, visible in three dimensions thanks to Fractal 3D Magic enclosed 3D glasses, will engross math and optical illusions enthusiasts alike. If an item you have purchased from us is not working as expected, please visit one of our in-store Knowledge Experts for free help, where they can solve your problem or even exchange the item for a product that better suits your needs. If you need to return an item, simply bring it back to any Micro Center store for Fractal 3D Magic full refund or exchange. All other products may be returned within 30 days of purchase. Using the software may require the use of a computer or other device that must meet minimum system requirements. It is recommended that you familiarize Fractal 3D Magic with the system requirements before making your purchase. Software system requirements are typically found on the Product information specification page. Aerial Drones Micro Center is happy to honor its customary day return policy for Aerial Drone returns due to product defect or customer dissatisfaction. -
Math 253: Mathematical Methods for Data Visualization – Course Introduction and Overview (Spring 2020)
Math 253: Mathematical Methods for Data Visualization – Course introduction and overview (Spring 2020) Dr. Guangliang Chen Department of Math & Statistics San José State University Math 253 course introduction and overview What is this course about? Context: Modern data sets often have hundreds, thousands, or even millions of features (or attributes). ←− large dimension Dr. Guangliang Chen | Mathematics & Statistics, San José State University2/30 Math 253 course introduction and overview This course focuses on the statistical/machine learning task of dimension reduction, also called dimensionality reduction, which is the process of reducing the number of input variables of a data set under consideration, for the following benefits: • It reduces the running time and storage space. • Removal of multi-collinearity improves the interpretation of the parameters of the machine learning model. • It can also clean up the data by reducing the noise. • It becomes easier to visualize the data when reduced to very low dimensions such as 2D or 3D. Dr. Guangliang Chen | Mathematics & Statistics, San José State University3/30 Math 253 course introduction and overview There are two different kinds of dimension reduction approaches: • Feature selection approaches try to find a subset of the original features variables. Examples: subset selection, stepwise selection, Ridge and Lasso regression. ←− Already covered in Math 261A • Feature extraction transforms the data in the high-dimensional space to a space of fewer dimensions. ←− Focus of this course Examples: principal component analysis (PCA), ISOmap, and linear discriminant analysis (LDA). Dr. Guangliang Chen | Mathematics & Statistics, San José State University4/30 Math 253 course introduction and overview Dimension reduction methods to be covered in this course: • Linear projection methods: – PCA (for unlabled data), – LDA (for labled data) • Nonlinear embedding methods: – Multidimensional scaling (MDS), ISOmap – Locally linear embedding (LLE) – Laplacian eigenmaps Dr. -
Volume Rendering
Volume Rendering 1.1. Introduction Rapid advances in hardware have been transforming revolutionary approaches in computer graphics into reality. One typical example is the raster graphics that took place in the seventies, when hardware innovations enabled the transition from vector graphics to raster graphics. Another example which has a similar potential is currently shaping up in the field of volume graphics. This trend is rooted in the extensive research and development effort in scientific visualization in general and in volume visualization in particular. Visualization is the usage of computer-supported, interactive, visual representations of data to amplify cognition. Scientific visualization is the visualization of physically based data. Volume visualization is a method of extracting meaningful information from volumetric datasets through the use of interactive graphics and imaging, and is concerned with the representation, manipulation, and rendering of volumetric datasets. Its objective is to provide mechanisms for peering inside volumetric datasets and to enhance the visual understanding. Traditional 3D graphics is based on surface representation. Most common form is polygon-based surfaces for which affordable special-purpose rendering hardware have been developed in the recent years. Volume graphics has the potential to greatly advance the field of 3D graphics by offering a comprehensive alternative to conventional surface representation methods. The object of this thesis is to examine the existing methods for volume visualization and to find a way of efficiently rendering scientific data with commercially available hardware, like PC’s, without requiring dedicated systems. 1.2. Volume Rendering Our display screens are composed of a two-dimensional array of pixels each representing a unit area. -
Graph Visualization and Navigation in Information Visualization 1
HERMAN ET AL.: GRAPH VISUALIZATION AND NAVIGATION IN INFORMATION VISUALIZATION 1 Graph Visualization and Navigation in Information Visualization: a Survey Ivan Herman, Member, IEEE CS Society, Guy Melançon, and M. Scott Marshall Abstract—This is a survey on graph visualization and navigation techniques, as used in information visualization. Graphs appear in numerous applications such as web browsing, state–transition diagrams, and data structures. The ability to visualize and to navigate in these potentially large, abstract graphs is often a crucial part of an application. Information visualization has specific requirements, which means that this survey approaches the results of traditional graph drawing from a different perspective. Index Terms—Information visualization, graph visualization, graph drawing, navigation, focus+context, fish–eye, clustering. involved in graph visualization: “Where am I?” “Where is the 1 Introduction file that I'm looking for?” Other familiar types of graphs lthough the visualization of graphs is the subject of this include the hierarchy illustrated in an organisational chart and Asurvey, it is not about graph drawing in general. taxonomies that portray the relations between species. Web Excellent bibliographic surveys[4],[34], books[5], or even site maps are another application of graphs as well as on–line tutorials[26] exist for graph drawing. Instead, the browsing history. In biology and chemistry, graphs are handling of graphs is considered with respect to information applied to evolutionary trees, phylogenetic trees, molecular visualization. maps, genetic maps, biochemical pathways, and protein Information visualization has become a large field and functions. Other areas of application include object–oriented “sub–fields” are beginning to emerge (see for example Card systems (class browsers), data structures (compiler data et al.[16] for a recent collection of papers from the last structures in particular), real–time systems (state–transition decade). -
From Surface Rendering to Volume
What is Computer Graphics? • Computational process of generating images from models and/or datasets using computers • This is called rendering (computer graphics was traditionally considered as a rendering method) • A rendering algorithm converts a geometric model and/or dataset into a picture Department of Computer Science CSE564 Lectures STNY BRK Center for Visual Computing STATE UNIVERSITY OF NEW YORK What is Computer Graphics? This process is also called scan conversion or rasterization How does Visualization fit in here? Department of Computer Science CSE564 Lectures STNY BRK Center for Visual Computing STATE UNIVERSITY OF NEW YORK Computer Graphics • Computer graphics consists of : 1. Modeling (representations) 2. Rendering (display) 3. Interaction (user interfaces) 4. Animation (combination of 1-3) • Usually “computer graphics” refers to rendering Department of Computer Science CSE564 Lectures STNY BRK Center for Visual Computing STATE UNIVERSITY OF NEW YORK Computer Graphics Components Department of Computer Science CSE364 Lectures STNY BRK Center for Visual Computing STATE UNIVERSITY OF NEW YORK Surface Rendering • Surface representations are good and sufficient for objects that have homogeneous material distributions and/or are not translucent or transparent • Such representations are good only when object boundaries are important (in fact, only boundary geometric information is available) • Examples: furniture, mechanical objects, plant life • Applications: video games, virtual reality, computer- aided design Department of -
Bachelorarbeit Im Studiengang Audiovisuelle Medien Die
Bachelorarbeit im Studiengang Audiovisuelle Medien Die Nutzbarkeit von Fraktalen in VFX Produktionen vorgelegt von Denise Hauck an der Hochschule der Medien Stuttgart am 29.03.2019 zur Erlangung des akademischen Grades eines Bachelor of Engineering Erst-Prüferin: Prof. Katja Schmid Zweit-Prüfer: Prof. Jan Adamczyk Eidesstattliche Erklärung Name: Vorname: Hauck Denise Matrikel-Nr.: 30394 Studiengang: Audiovisuelle Medien Hiermit versichere ich, Denise Hauck, ehrenwörtlich, dass ich die vorliegende Bachelorarbeit mit dem Titel: „Die Nutzbarkeit von Fraktalen in VFX Produktionen“ selbstständig und ohne fremde Hilfe verfasst und keine anderen als die angegebenen Hilfsmittel benutzt habe. Die Stellen der Arbeit, die dem Wortlaut oder dem Sinn nach anderen Werken entnommen wurden, sind in jedem Fall unter Angabe der Quelle kenntlich gemacht. Die Arbeit ist noch nicht veröffentlicht oder in anderer Form als Prüfungsleistung vorgelegt worden. Ich habe die Bedeutung der ehrenwörtlichen Versicherung und die prüfungsrechtlichen Folgen (§26 Abs. 2 Bachelor-SPO (6 Semester), § 24 Abs. 2 Bachelor-SPO (7 Semester), § 23 Abs. 2 Master-SPO (3 Semester) bzw. § 19 Abs. 2 Master-SPO (4 Semester und berufsbegleitend) der HdM) einer unrichtigen oder unvollständigen ehrenwörtlichen Versicherung zur Kenntnis genommen. Stuttgart, den 29.03.2019 2 Kurzfassung Das Ziel dieser Bachelorarbeit ist es, ein Verständnis für die Generierung und Verwendung von Fraktalen in VFX Produktionen, zu vermitteln. Dabei bildet der Einblick in die Arten und Entstehung der Fraktale -
On Bounding Boxes of Iterated Function System Attractors Hsueh-Ting Chu, Chaur-Chin Chen*
Computers & Graphics 27 (2003) 407–414 Technical section On bounding boxes of iterated function system attractors Hsueh-Ting Chu, Chaur-Chin Chen* Department of Computer Science, National Tsing Hua University, Hsinchu 300, Taiwan, ROC Abstract Before rendering 2D or 3D fractals with iterated function systems, it is necessary to calculate the bounding extent of fractals. We develop a new algorithm to compute the bounding boxwhich closely contains the entire attractor of an iterated function system. r 2003 Elsevier Science Ltd. All rights reserved. Keywords: Fractals; Iterated function system; IFS; Bounding box 1. Introduction 1.1. Iterated function systems Barnsley [1] uses iterated function systems (IFS) to Definition 1. A transform f : X-X on a metric space provide a framework for the generation of fractals. ðX; dÞ is called a contractive mapping if there is a Fractals are seen as the attractors of iterated function constant 0pso1 such that systems. Based on the framework, there are many A algorithms to generate fractal pictures [1–4]. However, dðf ðxÞ; f ðyÞÞps Á dðx; yÞ8x; y X; ð1Þ in order to generate fractals, all of these algorithms have where s is called a contractivity factor for f : to estimate the bounding boxes of fractals in advance. For instance, in the program Fractint (http://spanky. Definition 2. In a complete metric space ðX; dÞ; an triumf.ca/www/fractint/fractint.html), we have to guess iterated function system (IFS) [1] consists of a finite set the parameters of ‘‘image corners’’ before the beginning of contractive mappings w ; for i ¼ 1; 2; y; n; which is of drawing, which may not be practical. -
On the Numerical Construction Of
ON THE NUMERICAL CONSTRUCTION OF HYPERBOLIC STRUCTURES FOR COMPLEX DYNAMICAL SYSTEMS A Dissertation Presented to the Faculty of the Graduate School of Cornell University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by Jennifer Suzanne Lynch Hruska August 2002 c 2002 Jennifer Suzanne Lynch Hruska ALL RIGHTS RESERVED ON THE NUMERICAL CONSTRUCTION OF HYPERBOLIC STRUCTURES FOR COMPLEX DYNAMICAL SYSTEMS Jennifer Suzanne Lynch Hruska, Ph.D. Cornell University 2002 Our main interest is using a computer to rigorously study -pseudo orbits for polynomial diffeomorphisms of C2. Periodic -pseudo orbits form the -chain re- current set, R. The intersection ∩>0R is the chain recurrent set, R. This set is of fundamental importance in dynamical systems. Due to the theoretical and practical difficulties involved in the study of C2, computers will presumably play a role in such efforts. Our aim is to use computers not only for inspiration, but to perform rigorous mathematical proofs. In this dissertation, we develop a computer program, called Hypatia, which locates R, sorts points into components according to their -dynamics, and inves- tigates the property of hyperbolicity on R. The output is either “yes”, in which case the computation proves hyperbolicity, or “not for this ”, in which case infor- mation is provided on numerical or dynamical obstructions. A diffeomorphism f is hyperbolic on a set X if for each x there is a splitting of the tangent bundle of x into an unstable and a stable direction, with the unstable (stable) direction expanded by f (f −1). A diffeomorphism is hyperbolic if it is hyperbolic on its chain recurrent set. -
Current Practices in Quantitative Literacy © 2006 by the Mathematical Association of America (Incorporated)
Current Practices in Quantitative Literacy © 2006 by The Mathematical Association of America (Incorporated) Library of Congress Catalog Card Number 2005937262 Print edition ISBN: 978-0-88385-180-7 Electronic edition ISBN: 978-0-88385-978-0 Printed in the United States of America Current Printing (last digit): 10 9 8 7 6 5 4 3 2 1 Current Practices in Quantitative Literacy edited by Rick Gillman Valparaiso University Published and Distributed by The Mathematical Association of America The MAA Notes Series, started in 1982, addresses a broad range of topics and themes of interest to all who are in- volved with undergraduate mathematics. The volumes in this series are readable, informative, and useful, and help the mathematical community keep up with developments of importance to mathematics. Council on Publications Roger Nelsen, Chair Notes Editorial Board Sr. Barbara E. Reynolds, Editor Stephen B Maurer, Editor-Elect Paul E. Fishback, Associate Editor Jack Bookman Annalisa Crannell Rosalie Dance William E. Fenton Michael K. May Mark Parker Susan F. Pustejovsky Sharon C. Ross David J. Sprows Andrius Tamulis MAA Notes 14. Mathematical Writing, by Donald E. Knuth, Tracy Larrabee, and Paul M. Roberts. 16. Using Writing to Teach Mathematics, Andrew Sterrett, Editor. 17. Priming the Calculus Pump: Innovations and Resources, Committee on Calculus Reform and the First Two Years, a subcomit- tee of the Committee on the Undergraduate Program in Mathematics, Thomas W. Tucker, Editor. 18. Models for Undergraduate Research in Mathematics, Lester Senechal, Editor. 19. Visualization in Teaching and Learning Mathematics, Committee on Computers in Mathematics Education, Steve Cunningham and Walter S.