Thesis (M.S.)--University of North Carolina at Wilmington, 2005. / Includes bibliographical references (leaves: leaf: 28)

Thesis (M.Sc.)--Acadia University, 2006. / Includes bibliographical references (leaves 142-143). Also available on the Internet via the World Wide Web.

Thesis (Ph. D.)--University of Oregon, 1999. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 206-211). Also available for download via the World Wide Web; free to University of Oregon users. Address: http://wwwlib.umi.com/cr/uoregon/fullcit?p9948016.

Thesis (doctoral)--Technische Universiteit Eindhoven, 2000. / Includes summary in Dutch. Vita. Includes bibliographical references (p. [105]-110) and index.

Thesis (Ph. D.)--University of Stellenbosch, 2004. / Includes bibliographical references. Also available via the Internet.

Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2008. / Nemhauser,George, Committee Member ; Gu, Zonghao, Committee Member ; Ergun, Ozlem, Committee Member ; Sokol, Joel, Committee Co-Chair ; Ahmed, Shabbir, Committee Chair.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Este trabalho trata de uma aplicação de programação estocástica para administração de passivos e ativos. Inicialmente, um modelo de administração de ativos e passivos utilizando valores de retorno de ativos determinísticos é formalizado, constatando-se as suas limitações, justificando-se a necessidade de abranger formalmente a incerteza inerente aos mercados financeiros. Para isso, um modelo para administração de ativos e passivos que utiliza otimização e programação estocástica baseado em uma árvore de cenários multiestágio balanceada é apresentado, descrito, e implementado. Os seus resultados determinam uma política de investimento de ativos para o instante inicial do período considerado, definindo-se também uma regra que possibilita, a partir do equilíbrio entre o patrimônio inicial e total de passivo a ser pago ao final do período considerado, estimar a probabilidade de insolvência do fundo de pensão. Além disso, realiza-se o estudo do impacto da redução de uma proxy da taxa de juros básico na composição do portfólio administrado por essas empresas. / This work discusses an application of stochastic programming for asset-liability management. Initially, a deterministic asset-liability model is formalized. Its limitations become clear which justify the need to include uncertainty in the model. Then, a stochastic programming model based on a balanced multistage scenario tree is presented, described and implemented for an asset-liability environment. The main results are: (i) an investment policy for the fund, and, (ii) the pension’s fund insolvency probability considering an initial relation between the current assets and the present value of the future liabilities. The impact of a possible reduction in interested rate on the pension’s fund optimal portfolio is also presented.

Cardiovascular disease is one of the leading causes of the mortality in the western world. Many imaging modalities have been used to diagnose cardiovascular diseases. However, each has different forms of noise and artifacts that make the medical image analysis field important and challenging. This thesis is concerned with developing fully automatic segmentation methods for cross-sectional coronary arterial imaging in particular, intra-vascular ultrasound and optical coherence tomography, by incorporating prior and tracking information without any user intervention, to effectively overcome various image artifacts and occlusions. Combinatorial optimisation methods are proposed to solve the segmentation problem in polynomial time. A node-weighted directed graph is constructed so that the vessel border delineation is considered as computing a minimum closed set. A set of complementary edge and texture features is extracted. Single and double interface segmentation methods are introduced. Novel optimisation of the boundary energy function is proposed based on a supervised classification method. Shape prior model is incorporated into the segmentation framework based on global and local information through the energy function design and graph construction. A combination of cross-sectional segmentation and longitudinal tracking is proposed using the Kalman filter and the hidden Markov model. The border is parameterised using the radial basis functions. The Kalman filter is used to adapt the inter-frame constraints between every two consecutive frames to obtain coherent temporal segmentation. An HMM-based border tracking method is also proposed in which the emission probability is derived from both the classification-based cost function and the shape prior model. The optimal sequence of the hidden states is computed using the Viterbi algorithm. Both qualitative and quantitative results on thousands of images show superior performance of the proposed methods compared to a number of state-of-the-art segmentation methods.

abstract: Exhaustive testing is generally infeasible except in the smallest of systems. Research has shown that testing the interactions among fewer (up to 6) components is generally sufficient while retaining the capability to detect up to 99% of defects. This leads to a substantial decrease in the number of tests. Covering arrays are combinatorial objects that guarantee that every interaction is tested at least once. In the absence of direct constructions, forming small covering arrays is generally an expensive computational task. Algorithms to generate covering arrays have been extensively studied yet no single algorithm provides the smallest solution. More recently research has been directed towards a new technique called post-optimization. These algorithms take an existing covering array and attempt to reduce its size. This thesis presents a new idea for post-optimization by representing covering arrays as graphs. Some properties of these graphs are established and the results are contrasted with existing post-optimization algorithms. The idea is then generalized to close variants of covering arrays with surprising results which in some cases reduce the size by 30%. Applications of the method to generation and test prioritization are studied and some interesting results are reported. / Dissertation/Thesis / Masters Thesis Computer Science 2015