Daryl Hepting

Permanent URI for this collectionhttps://hdl.handle.net/10294/6891

Associate Professor
Department of Computer Science

URL: http://www2.cs.uregina.ca/~hepting/
Email: hepting@cs.uregina.ca
Phone: (306) 585-5210
Fax: (306) 585-4745
Office: College West 308.22

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Now showing 1 - 4 of 4

Open Access
Discernibility in the Analysis of Binary Card Sort Data
(Springer, 2013-10-11) Hepting, Daryl
In an open card sorting study of 356 facial photographs, each of 25 participants created an unconstrained number of piles. We consider all 63,190 possible pairs of photos: if both photos are in the same pile for a participant, we consider them as rated similar; otherwise we consider them as rated dissimilar. Each pair of photos is an attribute in an information system where the participants are the objects. We consider whether the attribute values permit accurate classification of the objects according to binary decision classes, without loss of generality. We propose a discernibility coefficient to measure the support of an attribute for classification according to a given decision class pair. We hypothesize that decision class pairs with the support of many attributes are more representative of the data than those with the support of few attributes. We present some computational experiments and discuss opportunities for future work.
Open Access
The Escape Buffer: Efficient Computation of Escape Time for Linear Fractals
(Canadian Human Computer Communications Society, 1995-05-17) Hepting, Daryl; Hart, John
The study of linear fractals has gained a great deal from the study of quadratic fractals, despite important differences. Methods for classifying points in the complement of a fractal shape were originally developed for quadratic fractals, to provide insight into their underlying dynamics. These methods were later modified for use with linear fractals. This paper reconsiders one such classification, called escape time, and presents a new algorithm for its computation that is significantly faster and conceptually simpler. Previous methods worked backwards, by mapping pixels into classified regions, whereas the new forward algorithm uses an "escape buffer" to map classified regions onto pixels. The efficiency of the escape buffer is justified by a careful analysis of its performance on linear fractals with various properties.
Open Access
Operationalizing Ethics in Food Choice Decisions
(Springer, 2014-06) Hepting, Daryl; Jaffe, JoAnn; Maciag, Timothy
There is a large gap between attitude and action when it comes to consumer purchases of ethical food. Amongst the various aspects of this gap, this paper focuses on the difficulty in knowing enough about the various dimensions of food production, distribution and consumption to make an ethical food purchasing decision. There is neither one universal definition of ethical food. We suggest that it is possible to support consumers in operationalizing their own ethics of food with the use of appropriate information and communication technology. We consider eggs as an example because locally produced options are available to many people on every continent. We consider the dimensions upon which food ethics may be constructed, then discuss the information required to assess it and the tools that can support it. We then present an overview of opportunities for design of a new software tool. Finally, we offer some points for discussion and future work.
Open Access
Rendering Methods for Iterated Function Systems
(North-Holland, 1991-12) Hepting, Daryl; Prusinkiewicz, Przemyslaw; Saupe, Dietmar
This paper describes rendering methods for iterated function systems (IFS’s). The rendering process consists of the generation of a field of data using an IFS and its visualization by means of computer graphics. Two groups of methods are presented: 1. Rendering of the attractor A of an IFS. These attracting methods may visualize the geometry and additionally the invariant measure supported by the attractor. 2. Rendering the complement of the attractor. There are three approaches, namely methods representing Euclidean distance from A; repelling methods, computing the escape time of a point from A, and methods using (electrostatic) potential functions of the attractor. The last of these methods calculates integrals with respect to the invariant measure of the attractor. An algorithm which generates an approximation of such integrals with prescribed tolerance is presented. This provides an alternative to the usual approach based on Elton's ergodic theorem and time average of trajectories generated by the “chaos game", where no error bound is available. Algorithms specifying the details of all methods are presented, some of them in the form of pseudocode. Examples of images obtained using these algorithms are given. The relationship to previously developed methods for visualizing Mandelbrot and Julia sets is also discussed.

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