Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2009. / Full text also available online. Scroll down for electronic link.

Thesis (M.S)--Ohio University, March, 2005. / Includes bibliographical references (p. 102-105)

Thesis (M.S.)--Ohio University, June, 2005. / Title from PDF t.p. Includes bibliographical references (p. 55-57)

Thesis (M.S)--Ohio University, March, 2005. / Title from PDF t.p. Includes bibliographical references (p. 102-105)

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2005. / Includes bibliographical references (leaves 138-150). Also available in electronic version.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 147-148).

Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains xii, 136 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 75-76).

Thesis (M.S.) -- University of Texas at Dallas, 2007. / Includes vita. Includes bibliographical references (p. 43)

Thesis (MTech (Business Information Systems))--Cape Peninsula University of Technology, 2016. / The emergence of big data (BD) has rendered existing conventional business intelligence (BI) tools inefficient and ineffective for real-time decision support systems (DSS). The inefficiency and ineffectiveness is perceived when business users need to make decisions based on stale and sometimes, incomplete data sets, which potentially leads to slow and poor decision making. In recent years, industry and academia have invented new technologies to process BD such as Hadoop, Spark, in-memory databases and NOSQL databases. The appearance of these new technologies have escalated to an extent, that organisations are faced with the challenge of determining most suitable technologies that are appropriate for real-time DSS requirements. Due to BD still being a new concept, there are no standard guidelines or frameworks available to assist in the evaluation and comparing of BD technologies. This research aims to explore factors that influence the selection of technologies appropriate for real-time DSSs in a BD environment. In addition, it further proposes evaluation criteria that can be used to compare and select these technologies. To achieve this aim, a literature analysis to understand the concept of BD, real-time DSSs and related technologies is conducted. Qualitative as well as quantitative research techniques are used after interviews are conducted with BI experts who have BD knowledge and experience. Experimental research in a computer laboratory is also conducted. The purpose of the interviews is to ascertain which technologies are being used for BD analytics and in addition, which evaluation criteria organisations use when choosing such a technology. Furthermore, a comparative computer laboratory experiment is conducted to compare three tools which run on Hadoop namely; Hive, Impala and Spark. The purpose of the experiment is to test if system performance is different for the three tools when analysing the same data set and the same computer resources. The impirical results reveals nine main factors which impact the selection of technologies appropriate for real-time DSS in a BD environment, and ten application independent evaluation criteria. Furthermore, the experiment results indicate that system performance in terms of latency, is significantly different among the three tools compared.

We describe quality and performance enhancements, which work in real-time, to all well-known Non-photorealistic (NPR) rendering styles for use in an interactive context. These include Comic rendering, Sketch rendering, Hatching and Painterly rendering, but we also attempt and justify a widening of the established definition of what is considered NPR. In the individual Chapters, we identify typical stylistic elements of the different NPR styles. We list problems that need to be solved in order to implement the various renderers. Standard solutions available in the literature are introduced and in all cases extended and optimised. In particular, we extend the lighting model of the comic renderer to include a specular component and introduce multiple inter-related but independent geometric approximations which greatly improve rendering performance. We implement two completely different solutions to random perturbation sketching, solve temporal coherence issues for coal sketching and find an unexpected use for 3D textures to implement hatch-shading. Textured brushes of painterly rendering are extended by properties such as stroke-direction and texture, motion, paint capacity, opacity and emission, making them more flexible and versatile. Brushes are also provided with a minimal amount of intelligence, so that they can help in maximising screen coverage of brushes. We furthermore devise a completely new NPR style, which we call super-realistic and show how sample images can be tweened in real-time to produce an image-based six degree-of-freedom renderer performing at roughly 450 frames per second. Performance values for our other renderers all lie between 10 and over 400 frames per second on homePC hardware, justifying our real-time claim. A large number of sample screen-shots, illustrations and animations demonstrate the visual fidelity of our rendered images. In essence, we successfully achieve our attempted goals of increasing the creative, expressive and communicative potential of individual NPR styles, increasing performance of most of them, adding original and interesting visual qualities, and exploring new techniques or existing ones in novel ways. / KMBT_363 / Adobe Acrobat 9.54 Paper Capture Plug-in