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Multi-dimensional functions are characterized by a large number of parameters on which the functional value depends. They are commonly used in engineering problems such as image analysis and system modeling. Multi-dimensional function spaces are very difficult to understand due to their multi-dimensional nature and the presence of a large number of data points in the functional space. A point called the focal point is selected by the user in the vast multi-dimensional parameter space. Rays called "focal rays" emanate from the focal point in all directions to the boundaries of the functional space. The focal rays contain functional data points. The focal point is mapped onto the center of the visualization with the focal rays arranged radially around it. The degree of detail decreases as we move away from the focal point toward the edges of the visualization in accordance with the focus+context technique. The functional values are mapped onto a color scheme with shades of green representing positive function values, and shades of red representing negative function values. Interactive features such as the ability to change the focal point, highlighting of functional values aid the user in exploring and analyzing the functional space. The algorithm, practical applications of the visualization approach and results of formative evaluation studies are also elaborated in this thesis. The contributions of this thesis are fourfold, namely, providing an overview of the functional space, equal treatment of all dimensions, improved scalability and a smooth blending of details with the overview. / Master of Science

Turbulent flows and turbulent flames are inherently multi-dimensional in space and transient in time. Therefore, multidimensional diagnostics that are capable of resolving such spatial and temporal dynamics have long been desired; and the purpose of this dissertation is to investigate three such diagnostics both for the fundamental study of flow and combustion processes and also for the applied research of practical devices. These multidimensional optical diagnostics are a 2D (two dimensional) two-photon laser-induced fluorescence (TPLIF) technique, a 3D hyperspectral tomography (HT) technique, and a 4D tomographic chemiluminescence (TC) technique. The first TPLIF technique is targeted at measuring temporally-resolved 2D distribution of fluorescent radicals, the second HT technique is targeted at measuring temperature and chemical species concentration at high speed, and the third TC technique is targeted at measuring turbulent flame properties. This dissertation describes the numerical and experimental evaluation of these techniques to demonstrate their capabilities and understand their limitations. The specific aspects investigated include spatial resolution, temporal resolution, and tomographic inversion algorithms. It is expected that the results obtained in this dissertation to lay the groundwork for their further development and expanded application in the study of turbulent flow and combustion processes. / Ph. D.

In the health-informatics and bio-medical domains, clinicians produce an enormous amount of data which can be complex and high in dimensionality. This scenario includes visual field data, which are used for managing the second leading cause of blindness in the world: glaucoma. Visual field data are the most common type of data collected to diagnose glaucoma in patients, and usually the data consist of 54 or 76 variables (which are referred to as visual field locations). Due to the large number of variables, the six nerve fiber bundles (6NFB), which is a collection of visual field locations in groups, are the standard clusters used in visual field data to represent the physiological traits of the retina. However, with regard to classification accuracy of the data, this research proposes a technique to find other significant spatial clusters of visual field with higher classification accuracy than the 6NFB. This thesis presents a novel clustering technique, namely, Simultaneous Modelling and Clustering (SMC). SMC performs clustering on data based on classification accuracy using heuristic search techniques. The method searches a collection of significant clusters of visual field locations that indicate visual field loss progression. The aim of this research is two-fold. Firstly, SMC algorithms are developed and tested on data to investigate the effectiveness and efficiency of the method using optimisation and classification methods. Secondly, a significant clustering arrangement of visual field, which highly interrelated visual field locations to represent progression of visual field loss with high classification accuracy, is searched to complement the 6NFB in diagnosis of glaucoma. A new clustering arrangement of visual field locations can be used by medical practitioners together with the 6NFB to complement each other in diagnosis of glaucoma in patients. This research conducts extensive experiment work on both visual field and simulated data to evaluate the proposed method. The results obtained suggest the proposed method appears to be an effective and efficient method in clustering visual field data and 3 improving classification accuracy. The key contributions of this work are the novel model-based clustering of visual field data, effective and efficient algorithms for SMC, practical knowledge of visual field data in the diagnosis of glaucoma and the presentation a generic framework for modelling and clustering which is highly applicable to many other dataset/model combinations.

Industrial furnace is very important production equipment for industrial enterprises. Its performance will directly affect the efficiency and effectiveness of enterprises in manufacturing industry, even change the competitive advantage of the organization. To achieve more high quality and synergy, there is a need to have an integrated industrial furnace system that may compose of industrial furnaces, network, computer automatic control, intelligent software, and decision support technical. The integrated industrial furnace system takes the place of the traditionally single and dummy industrial furnace gradually. The importance of the integrated industrial furnace system to the enterprise is increased dramatically. With the change of market focus from production-orientation to customer-orientation, more and more companies realize the importance of the strategy of market segment and position. ¡§The small market segment¡¨ and ¡§unease of standardization¡¨ (high customization) are major characteristics in the industrial furnace industry. Therefore, the market and position strategy is the critical successful factor for the furnace industry in addition to technical excellence. Taiwanese industrial furnace companies are becoming global business recently. This research will focus on exploring the market and position strategy of furnace industry from a global perspective. This research will combine qualitative and quantitative methods. First, we will adopt literature review, in-depth interview, and focus-group interview with suppliers, customers, scholars, market analysts, and economic officials to develop two measure instruments: the supplier strategy measure and customer preference and selection criterion measure. Second, we will survey via questionnaires, and test reliabilities and validities of the both measures conscientiously. Finally, we formally mail validated questionnaires to suppliers and customers in the industrial furnaces industry. Based on multivariate analysis, factor analysis, cluster analysis, and multi-dimensional scaling, we will provide insights and suggestion about integrated industrial furnace system industry: 1.The strategy patterns of industrial furnace suppliers 2.The selection criterion of industrial furnace in a broad customer perspective 3.The grouping of customers and supplier in the integrated industrial furnace system industry. 4.The perceptual map of major suppliers in the integrated industrial furnace system industry 5.The strategy, market segment, and position current analysis and future suggestions

With advances in imaging and communication systems, there is increased use of multi-dimensional images. Examples include multi-view image/video, hyperspectral image/video and dynamic volume imaging in CT/MRI/Ultrasound. These datasets consume even larger amounts of resources for transmission or storage compared to 2-D images. Hence, it is vital to have efficient compression methods for multi-dimensional images. In this dissertation, first, a JPEG2000 Part-2 compliant scheme is proposed for compressing multi-dimensional datasets for any dimension N>=3. Secondly, a novel view-compensated compression method is investigated for remote visualization of volumetric data. Experimental results indicate superior compression performance compared to state-of-the-art compression standards. Thirdly, a new scalable low complexity coder is designed that sacrifices some compression efficiency to get substantial gain in throughput. Potential use of the scalable low complexity coder is illustrated for two applications: Airborne video transmission and remote volume visualization.

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<p> Software Evolution is unavoidable because software systems are subject to continuous change, continuing growth and increasing complexity. As software systems become mission-critical and large in size, the complexity in software development is now focused on software evolution rather than construction. In this work, we view a software system as an entity that is evolving throughout its lifetime, during development and maintenance. Based on a broad survey of software evolution approaches, we propose an architecture-based solution for software evolution, which is defined in terms of evolution specific operations on architectural elements, that is, adding, removing, replacing components and (or) connectors, transforming configurations according to the required changes. In our view of software architectures, connectors are more likely to change since they are the architectural elements which reflect business rules. This work is focused on the evolution of connectors in architectures describing detailed design. Coordination contracts are introduced by Fiadeiro et al. as a realization of connectors at this detailed architecture level, which enables a three-layer architecture to separate concerns of components, connectors and configuration during evolution. Furthermore, to constrain the evolution in a predictable direction, we have established a matching scheme for justifying behavioral relationships between coordination contracts by specification matching based on pre- and postconditions of contracts and methods. A number of specification matches, with various degrees of similarity between the evolved and evolving contracts, have been developed for system behaviors after evolution operations. Case studies are exhibited give a better understanding of these matches.</p> / Thesis / Master of Science (MSc)

While some of the developed and emerging economies are registering phenomenal growth in their renewable energy industries, it would appear that there are still a number of factors that are limiting the renewable energy to its potential worldwide. This paper applies a theoretical framework using the systems thinking to examine three possible multi-dimensional factors that are barriers to be development of renewable energy in South Africa. The objective was to use a qualitative research to investigate further the barrier interconnection and multi-dimensional barriers limiting renewable energy development using the South Africa market for sampling and interviews.The methodology employed involved a literature review. In addition, a questionnaire was designed and interviews were conducted to ascertain the prevalence of such barrier multi-dimensional and interconnection. The results obtained were analysed using qualitative method. These analyses revealed that the possible multi-dimensional barriers that were identified namely technology; pricing and costing; policy and regulations; and market performance are valid for South Africa. In addition, even though the results highlighted, as identified initially that technology have a significant impact as a linkage, the results suggest that the regulatory framework have a more significant linkage and effect on the relationship and interconnection. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / Unrestricted

Neste trabalho apresentamos uma nova abordagem para a exploração de fibras neurais a partir de imagens de tensores de difusão. A estratégia combina técnicas de visualização de informação e visualização científica para obter uma rápida e precisa interpretação das fibras. Para isto fazemos uma transformação das fibras para vetores, e utilizamos uma nova técnica de projeção multi-dimensional (P-LSP), para trabalhar com conjuntos grandes de dados. A exploração do espaço das fibras é feita através desta projeção. Além disso, é apresentada a extensão das técnicas LSP e P-LSP para criar projeções em 3D, assim como estratégias que permitem interagir com pontos em 3D. Outra contribuição deste trabalho é a modificação de um método apresentado para criar superfícies de densidade fechadas sobre pontos esparsos. Esta modificação torna possível criar superfícies sobre conjuntos de pontos maiores com uma qualidade aceitável, o que é utilizado para representar conjunto de fibras como uma superfície. Esta nova abordagem é comparada com trabalhos similares mostrando nossas vantagens em termos de tempo de processamento, qualidade e funcionalidades para analisar esta categoria de dados / This work presents a novel approach for the exploration of neural fibers extracted from Diffusion Tensor Images. The developed strategy combines techniques from information and scientific visualization in order to attain a fast and precise interpretation of fiber sets. The approach transforms fibers into vectors from which a new multidimensional projection technique (PLSP) capable of handling large data sets. The fiber space is explored through the projection. Additionally this work extends P-LSP and LSP projections to 3D, and defines strategies to interact with 3D sparse points. Another contribution of this work is the extension of a method to create close density surfaces over the sparse space generated by the projections. The visualization approach is compared with other similar work showing advantages in processing time, quality and exploration capability to analyze this type of data sets