In view of the recent implementation of a publicly funded rotavirus vaccination program in Ontario, we undertook studies to help guide the design of a safety evaluation of the vaccine with respect to intussusception. We used administrative data to develop and validate an algorithm for intussusception, and quantified its incidence in Ontario. We also conducted a systematic review of study designs used to evaluate post-licensure vaccine safety, and discussed each design’s strengths and weaknesses. The validated algorithm for intussusception was sensitive (89.3%) and highly specific (>99.9%). We observed the highest mean incidence (34 / 100,000) in males <1 year of age. While other designs are more robust, the inability to ascertain individual vaccination status from Ontario’s administrative data dictated our selection of an ecological design for safety evaluation of rotavirus vaccine. Data assimilated from this thesis represent a critical step toward the timely evaluation of rotavirus vaccine safety in Ontario.

In this thesis a methodology is presented to optimise non–linear mathematical models in numerical engineering applications. The method is based on biological evolution and uses known concepts of genetic algorithms and evolutionary compu- tation. The working principle is explained in detail, the implementation is outlined and alternative approaches are mentioned. The optimisation is then tested on a series of benchmark cases to prove its validity. It is then applied to two different types of problems in computational engineering. The first application is the mathematical modeling of turbulence. An overview of existing turbulence models is followed by a series of tests of different models applied to various types of flows. In this thesis the optimisation method is used to find improved coefficient values for the k–ε, the k–ω-SST and the Spalart–Allmaras models. In a second application optimisation is used to improve the quality of a computational mesh automatically generated by a third party software tool. This generation can be controlled by a set of parameters, which are subject to the optimisation. The results obtained in this work show an improvement when compared to non–optimised results. While computationally expensive, the genetic optimisation method can still be used in engineering applications to tune predefined settings with the aim to produce results of higher quality. The implementation is modular and allows for further extensions and modifications for future applications.

Light-matter interactions lead to a variety of interesting phenomena, for example photosynthesis which is a process fundamental to life on earth. There exists many different spectroscopic methods to measure light-matter interactions, for example UV/Vis spectroscopy, that can provide information about electronically excited states. However, numerical methods and theory are important to model and gain understanding of these experiments. Quantum chemistry provides that understanding, giving the possibility to numerically calculate molecular properties like excitation energies. The aim of this thesis was to implement a reduced-space algorithm in Dalton, to solve an eigenvalue equation obtained by response theory, for the calculation of excitation energies of molecular systems. There already was a similar algorithm in Dalton, that was able to perform these calculations. However, in a different module of Dalton used mainly for complex response theory, an algorithm to obtain eigenvalues was missing. The new implementation was similar to the existing one, except for the division of the reduced space into even and odd parts used in the complex response module. The thesis starts with a quick introduction of light-matter interactions and proceeds with a description of many-body theory, including numerical methods used in that field. In the end of the theoretical part, the eigenvalue equation, used to calculate excitation energies, is derived. In the following section, the reduced-space algorithm is described. In the end of the thesis, numerical results obtained with the algorithm are presented, including a small basis set and method study. The comparison with the existing implementation of the similar algorithm verified the successful implementation of the algorithm presented in this thesis.

The problem of computing the minimum distance between two convex hulls has applications to many areas including robotics, computer graphics and path planning. Moreover, determining the minimum distance between two convex hulls plays a significant role in support vector machines (SVM). In this study, a new algorithm for finding the minimum distance between two convex hulls is proposed and investigated. A convergence of the algorithm is proved and applicability of the algorithm to support vector machines is demostrated. The performance of the new algorithm is compared with the performance of one of the most popular algorithms, the sequential minimal optimization (SMO) method. The new algorithm is simple to understand, easy to implement, and can be more efficient than the SMO method for many SVM problems.

The negative selection algorithm developed by Forrest et al. was inspired by the manner in which T-cell lymphocytes mature within the thymus before being released into the blood system. The resultant T-cell lymphocytes, which are then released into the blood, exhibit an interesting characteristic: they are only activated by non-self cells that invade the human body. The work presented in this thesis examines the current body of research on the negative selection theory and introduces a new affinity threshold function, called the feature-detection rule. The feature-detection rule utilises the inter-relationship between both adjacent and non-adjacent features within a particular problem domain to determine if an artificial lymphocyte is activated by a particular antigen. The performance of the feature-detection rule is contrasted with traditional affinity-matching functions currently employed within negative selection theory, most notably the r-chunks rule (which subsumes the r-contiguous bits rule) and the hamming-distance rule. The performance will be characterised by considering the detection rate, false-alarm rate, degree of generalisation and degree of overfitting. The thesis will show that the feature-detection rule is superior to the r-chunks rule and the hamming-distance rule, in that the feature-detection rule requires a much smaller number of detectors to achieve greater detection rates and less false-alarm rates. The thesis additionally refutes that the way in which permutation masks are currently applied within negative selection theory is incorrect and counterproductive, while placing the feature-detection rule within the spectrum of affinity-matching functions currently employed by artificial immune-system (AIS) researchers. / Dissertation (MSc)--University of Pretoria, 2009. / Computer Science / Unrestricted

The performance of optimization algorithms is sensitive to both the optimization problem's numerical characteristics and the termination criteria of the algorithm. Given these considerations two tuning algorithms named tMOPSO and MOTA are proposed to assist optimization practitioners to nd algorithm settings which are approximate for the problem at hand. For a speci ed problem tMOPSO aims to determine multiple groups of control parameter values, each of which results in optimal performance at a di erent objective function evaluation budget. To achieve this, the control parameter tuning problem is formulated as a multi-objective optimization problem. Furthermore, tMOPSO uses a noise-handling strategy and control parameter value assessment procedure, which are specialized for tuning stochastic optimization algorithms. The principles upon which tMOPSO were designed are expanded into the context of many objective optimization, to create the MOTA tuning algorithm. MOTA tunes an optimization algorithm to multiple problems over a range of objective function evaluation budgets. To optimize the resulting many objective tuning problem, MOTA makes use of bi-objective decomposition. The last section of work entails an application of the tMOPSO and MOTA algorithms to benchmark optimization algorithms according to their tunability. Benchmarking via tunability is shown to be an effective approach for comparing optimization algorithms, where the various control parameter choices available to an optimization practitioner are included into the benchmarking process. / Thesis (PhD)--University of Pretoria, 2014 / gm2015 / Mechanical and Aeronautical Engineering / PhD / Unrestricted

The purpose of this thesis was to identify the optimal design parameters for a jet nozzle which obtains a local maximum shear stress while maximizing the average shear stress on the floor of a fluid filled system. This research examined how geometric parameters of a jet nozzle, such as the nozzle's angle, height, and orifice, influence the shear stress created on the bottom surface of a tank. Simulations were run using a Computational Fluid Dynamics (CFD) software package to determine shear stress values for a parameterized geometric domain including the jet nozzle. A response surface was created based on the shear stress values obtained from 112 simulated designs. A multi-objective optimization software utilized the response surface to generate designs with the best combination of parameters to achieve maximum shear stress and maximum average shear stress. The optimal configuration of parameters achieved larger shear stress values over a commercially available design.

Segundo uma pesquisa recente realizada junto ao setor de fundições, uma importante preocupação do setor é melhorar seu planejamento de produção. Um plano de produção em uma fundição envolve duas etapas interdependentes: a determinação das ligas a serem fundidas e dos lotes que serão produzidos. Neste trabalho, estudamos o problema de dimensionamento de lotes para fundições de pequeno porte, cujo objetivo é determinar um plano de produção de mínimo custo. Como sugerido na literatura, a heurística proposta trata as etapas do problema de forma hierárquica: inicialmente são definidas as ligas e, posteriormente, os lotes que são produzidos a partir delas. Para a solução do problema, propomos um algoritmo genético que explora um conjunto de possibilidades para a determinação das ligas e utiliza uma heurística baseada em relaxação lagrangiana para determinação dos itens a serem produzidos. Além disso, uma abordagem para o mesmo problema é proposta utilizando o problema da mochila para determinar os itens a serem produzidos. Bons resultados foram obtidos pelos métodos propostos / According to a recent research made by the foundry sector, one of the most concern of the industry is to improve its production planning. A foundry production plan involves two independent stages: the determination of alloys to be merged and the lots that will be produced. In this work, we studied the lot-sizing problem for small foundries, whose purpose is to determine a plan of minimum production cost. As suggested in the literature, the heuristic proposed addresses the problem stages in a hierarchical way: rst we dene the alloys and, subsequently, the lots that are produced from them. We propose a genetic algorithm that explores some possible sets of alloys produced and uses a Lagrangian heuristic to determine the items to be produced. Also, we propose one approach to the same problem that uses the knapsack problem to determine the items to be produced. Good results were obtained by the methods proposed

O Homem tem desde o passado, tentado controlar a natureza. Um dos meios utilizados para isto, é sua observação do mundo. Através desta observação, tenta entender os fenômenos da natureza para fazer teorias e modelos. Charles Darwin, em seu trabalho Teoria da Evolução das Espécies, nos dá informações para o conhecimento de uma das mais importantes leis da natureza : sobrevive para a próxima geração o individuo mais forte. O Algoritmo Genético, pesquisado neste trabalho, é o exemplo disso. John Holland fez um Algoritmo Genético baseado na teoria de Darwin, que procura pelas melhores soluções para resolver um problema específico. Nada mais do que a simulação da teoria de Darwin. Nós pretendemos neste trabalho, estudar o Algoritmo Genético de Holland e através dele, analisar uma estrutura para encontrar seus parâmetros elásticos. / The men has since the past, tryed to control the nature. One of the way utilized for this, is his observation of the world. Through his observation, tries to understand the nature\'s fenomena, to making theories and models. Charles Darwin, in his work Theories of Species Evolution, gives us informations for the knowledges of one of the most important nature\'s laws: survives to the next generation the strongest individual . The Genetic Algorithm, the search in this work, is the example of this. John Holland, did a Genetic Algorithm. based in Darwin\'s Theories, that looks for the best solutions to solve a specific problem. Nothing else, of the simulation of the Darwin\'s theories . We intend in this work, to study the Holland\'s Genetic Algorithms and through it, to analyses a structure for find its elastic parameters.

Le sujet de cette thèse est la théorie des graphes. Formellement, un graphe est un ensemble de sommets et un ensemble d’arêtes, c’est à dire de paires de sommets, qui relient les sommets. Cette thèse traite de différents problèmes de décisions binaires ou de minimisations liés à la notion de graphe, et cherche, pour chacun de ces problèmes, à déterminer sa classe de complexité, ou à fournir un algorithme. Le premier chapitre concerne le problème de trouver le plus petit sous-graphe connexe tropical dans un graphe sommet-colorié, c’est à dire le plus petit sous-graphe connexe contenant toutes les couleurs. Le deuxième chapitre concerne les problèmes d’homomorphisme tropical, une généralisation des problèmes de coloriage de graphe. On y trouve un lien entre ces problèmes et plusieurs classes de problèmes d’homomorphismes, dont la classe des Problèmes de Satisfaction de Contraintes. Le troisième chapitre concerne deux variantes lointaines du problème de domination, nommément les problèmes d’alliances globales dans un graphe pondéré et le problème de l’ensemble sûr. Le quatrième chapitre concerne la recherche d’une décomposition arborescente étoilée, c’est à dire une décomposition arborescente dont le rayon des sacs est 1. Enfin, le cinquième chapitre concerne une variante du problème de décider du comportement asymptotique de l’itéré du graphe des bicliques. / This thesis is about graph theory. Formally, a graph is a set of vertices and a set of edges, which are pair of vertices, linking vertices. This thesis deals with various decision problem linked to the notion of graph, and, for each of these problem, try to find its complexity class, or to give an algorithm. The first chapter is about the problem of finding the smallest connected tropical subgraph of a vertex-colored graph, which is the smallest connecter subgraph containing every colors. The second chapter is about problems of tropical homomorphism, a generalization of coloring problem. A link between these problems and several other class of homomorphism problems can be found in this chapter, especially with the class of Constraint Satisfaction Problem. The third chapter is about two variant of the domination problem, namely the global alliance problems in a weighted graph and the safe set problem. The fourth chapter is about the problem of finding a star tree-decomposition, which is a tree-decomposition where the radius of bags is 1. Finally, the fifth chapter is about a variant of the problem of deciding the asymptotic behavior of the iterated biclique graph