James F. Peters
University of Manitoba

Sheela Ramanna
University of Winnipeg

Title: Gentle Art of Zdzisław Pawlak's Paintings

Abstract

Zdzisław Pawlak began painting as a pasttime between meetings during the early 1950s. His paintings are landscapes and waterscapes that capture the colour, symmetries and the majesty of the places he visited in Poland and North America. These paintings are reminiscent of the work by Claude Monet (1840-1926), who expressed his perceptions about nature with skillful dabs of paint to suggest the contours of familiar objects such as trees, tree shadows, rolling farmland and gradually sloping clumps of marshland, waterways and buildings in such a way that each painting is pleasing to the eye without being photographic.

Pawlak repeatedly expresses his perceptions of woodlands, marshes, rivers and forests he delighted in visiting, the same places that gave him (and us) places to dwell in comfortably. He was an artist’s artist and a great giver of life. There is a calmness, an amazing deftness and gentleness in these paintings. His paintings typically reveal his skills as a scientist with his portrayal of what he saw. This gentleness and skill becomes evident by considering the geometry of Pawlak’s paintings. It is the geometry of Pawlak’s paintings, which is the focus of our part of this discusssion.

Briefly, one selects an appropriate set of generating points in a painting and the painting is tessellated to form a mesh on the painting. After that, we consider a variant of Harer-Edelsbrunner nerves in a tessellated painting. For example, each polygon in Voronoi tessellation of a painting is the nucleus of a cluster of polygons in a mesh (such cluster is a collection of mesh polygons that are adjacent to the nucleus of the cluster). It has been found that maximal nucleus clusters occur in the parts of a tessellation having the most change and which provide the greatest source of information. In the case of the tessellation of Pawlak’s paintings, maximal nucleus clusters tend to occur in the places that Pawlak selected for the golden section of his paintings.

Short Bios

James F. Peters, B.Sc. (Math), M.Sc. (Math), Ph.D., Constructive Specification of Communicating Systems, Postdoctoral Fellow, Syracuse University and researcher in the Rome AI Laboratory, Griffiss Air Force Base, New York (1991), Asst. Prof., University of Arkansas, 1991-1994, and Researcher in the Mission Sequencing and Deep Space Telecommunications Divisions at the Jet Propulsion Laboratory / Caltech, Pasadena, California (1991-1994), Full Professor, ECE Department, University of Manitoba, 1995-present, Guest Lecturer, School of Mathematics & Computer Information Sciences, Hyderabad, India, 2011-present. In 1992, he verified the correctness of the command sequencing rules for the NASA TOPEX Poseidon ocean-monitoring satellite (it ceased operation in 2007 after 62,000 orbits but still remains 1336 km above the Earth) and, in 1993-1994, he worked on a proof of correctness of an antenna controller for the NASA deep space network. His early work at the U of M included Petri net models of satellite subsystems and the design of robotic inspection systems for Manitoba Hydro transmission lines. He is now a Full Professor in the Department of Electrical and Computer Engineering (ECE) at the University of Manitoba.

He started working on descriptively near sets in2002 and formally introduced near sets in 2007, tolerance near sets in 2009, proximity space-based near sets in 2011, and visual pattern discovery via proximity spaces in 2012. He is the author of two books entitled Computational Proximity. Excursions in the Topology of Digital Images by Springer in 2016 and Topology of Digital Images: Visual Pattern Discovery via Proximity Spaces published by Springer in 2014. He is co-author (with Prof. Som Naimpally), of Topology with Applications: Topological Spaces via Near and Far, published by World Scientific, Singapore in 2013. He is co-Editor with S. Pal, Indian Statistical Institute, Kolkata, India, Rough Fuzzy Image Analysis: Foundations and Methodologies, published in 2010 by Chapman & Hall/CRC Press, co-Editor with E. Orłowska, G. Rozenberg, A. Skowron, New Frontiers in Scientific Discovery Commemorating the Life and Work of Zdzisław Pawlak, published in 2007 by IOS Press, author of over 480 publications, including a best journal article award in2008 and 2011, best Springer Verlag conference paper award in 2007. He is co-Editor-in-Chief of the Trans. on Rough Sets journal and Editorial Board member of several journals. He serves as the Vice-President of Allahabad Mathematical Society, India and is an IRSS Fellow. He is the recipient of a TUBITAK Fellowship (Turkey) for 2014 and 2015 and IndAM Fellowship (Italy) for 2016. His main research interests are near sets, algebraic structures via descriptive proximity spaces, topology of digital images, computational proximity, computational geometry and pattern recognition.

Sheela Ramanna is a Full Professor and past Chair of the Applied Computer Science Department at the University of Winnipeg. She received a Ph.D. in Computer Science from Kansas State University, U.S.A and a B.E in Electrical Engineering and M.Tech in Computer Science and Engineering from Osmania University, India. She serves on the Editorial Board of Transactions on Rough Sets (TRS) journal and International Journal of Rough Sets and Data Analysis. She is the Managing Editor of the TRS and is a Senior Member of the IRSS. She has co-edited a book on Emerging Paradigms in Machine Learning with L.C. Jain and Robert Hewitt, published in 2013 by Springer. She was an invited speaker at MIWAI 2011 and has served as Program Co-Chair for MIWAI 2013, RSKT 2011, RSCTC 2010 and JRS2007. She has published over 34 articles in the past 6 years. She is the recipient of a TUBITAK Fellowship (Turkey) for 2015. The focus of her research is in fundamental and applied research in machine learning and intelligent systems. Her current interests are in foundations of granular computing techniques (rough sets and near sets) with applications in social networks, text categorization and mining and analysis of perception-based image and audio information.

Important dates

  • Call for event proposals: October 30, 2015
  • Call for dissemination event proposals: December 15, 2015
  • Paper submission (strict deadline): May 09 2016 23:59:59 pm HST
  • Position paper submission: May 30, 2016
  • Acceptance decision: June 13, 2016
  • Final version of paper submission: July 04, 2016
  • Final deadline for discounted fee: July 31, 2016
  • Conference dates: September 11-14, 2016

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