Wireless Sensor Networks (WSNs) comprise a large number of sensor nodes, which are spread out within a region and communicate using wireless links. In some WSN applications, recognizing boundary nodes is important for topology discovery, geographic routing and tracking. In this thesis, we study the problem of identifying the boundary nodes of a WSN. In a WSN, close-by nodes can communicate with their neighbors and have the ability to estimate distances to nearby nodes, but not necessarily the true distances. Our objective is to find the boundary nodes by using the connectivity relation and neighbor distance information without any knowledge of node locations. Moreover, our main aim is to design a distributed algorithm that works even when the average degree is low. We propose a heuristic algorithm to find the boundary nodes which are connected in a boundary cycle of a location-free, low density, randomly deployed WSN. We develop the key ideas of our boundary detection algorithm in the centralized scenario and extend these ideas to the distributed scenario. Then, we show by simulation experiments that the distributed implementation outperforms the centralized one. The centralized implementation relies on the connectivity of the network to the base station. Therefore, for low density disconnected networks, the algorithm cannot find boundaries in partitions of the network that cannot establish connection to the base station. This condition leads to a low quality of boundary discovery. In contrast, the distributed implementation is more realistic for real WSNs, especially for relatively sparse networks when all local information cannot be collected very well due to sparse connectivity. In low-degree disconnected networks, the simulation results show that the distributed implementation has a higher quality of boundaries compared to the centralized implementation.

The study of nano-electronic devices is fundamental to the advancement of the semiconductor industry. As electronic devices become increasingly smaller, they will eventually move into a regime where the classical nature of the electrons no longer applies. As the quantum nature of the electrons becomes increasingly important, classical or semiclassical theories and methods will no longer serve their purpose. For example, the simplest non-classical effect that will occur is the tunnelling of electrons through the potential barriers that form wires and transistors. This results in an increase in noise and a reduction in the device?s ability to function correctly. Other quantum effects include coulomb blockade, resonant tunnelling, interference and diffraction, coulomb drag, resonant blockade and the list goes on. This thesis develops both a theoretical model and computational method to allow nanoelectronic devices to be studied in detail. Through the use of computer code and an appropriate model description, potential problems and new novel devices may be identified and studied. The model is as accurate to the physical realisation of the devices as possible to allow direct comparison with experimental outcomes. Using simple geometric shapes of varying potential heights, simple devices are readily accessible: quantum wires; quantum transistors; resonant cavities; and coupled quantum wires. Such devices will form the building blocks of future complex devices and thus need to be fully understood. Results obtained studying the connection of a quantum wire with its surroundings demonstrate non-intuitive behaviour and the importance of device geometry to electrical characteristics. The application of magnetic fields to various nano-devices produced a range of interesting phenomenon with promising novel applications. The magnetic field can be used to alter the phase of the electron, modifying the interaction between the electronic potential and the transport electrons. This thesis studies in detail the Aharonov-Bohm oscillation and impurity characterisation in quantum wires. By studying various devices considerable information can be added to the knowledge base of nano-electronic devices and provide a basis to further research. The computational algorithms developed in this thesis are highly accurate, numerically efficient and unconditionally stable, which can also be used to study many other physical phenomena in the quantum world. As an example, the computational algorithms were applied to positron-hydrogen scattering with the results indicating positronium formation.

Thesis (Ph. D.)--University of Texas at El Paso, 2007. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

Thesis (M.Eng. (Computer Enginnering)) -- University of Pretoria, 2007. / Includes bibliographical references (leaves 105-109)

Thesis (M.Eng. (Electrical, Electromic and Computer Engineering)) -- University of Pretoria, 2007. / Includes bibliographical references (leaves 82-87)

Thesis (M. App. Sc.)--Carleton University, 2005. / Includes bibliographical references (p. 71-76). Also available in electronic format on the Internet.

Thesis (Ph.D.) - Carleton University, 2005. / Includes bibliographical references (p. 164-175). Also available in electronic format on the Internet.

Thesis (Ph.D.) - Carleton University, 2006. / Includes bibliographical references (p. 248-260). Also available in electronic format on the Internet.

Thesis (M.C.S.) - Carleton University, 2007. / Includes bibliographical references (p. 77-84). Also available in electronic format on the Internet.

Neste trabalho é apresentada uma nova abordagem de algoritmo evolutivo multiobjetivo, denominado MOEA/NSM (do inglês, Multiobjective Evolutionary Algorithm integrating NSGA-II, SPEA2 and MOEA/D features). O algoritmo preserva em geral, características de um algoritmo evolutivo, concentrando qualidades de outras abordagens de sucesso na literatura em uma única abordagem, para que elas trabalhem em conjunto, por meio de subpopulações. O objetivo do estudo foi combinar as principais características dos algoritmos NSGA-II, SPEA2 e MOEA/D, e incluir ainda uma técnica de busca local para melhorar a busca no espaço de objetivos. O algoritmo MOEA/NSM foi comparado às demais abordagens clássicas utilizando 9 datasets para o problema do caixeiro viajante biobjetivo. Além disso, foram realizados experimentos aplicando também a busca local nas abordagens clássicas, resultando em considerável melhora nos resultados para esses algoritmos. A partir das fronteiras de Pareto resultantes dos experimentos, foram aplicadas as métricas de avaliação por Hipervolume, Epsilon (ε), R2, EAF, além do teste de hipótese estatístico Shapiro-Wilk. Os resultados apontaram um melhor desempenho do MOEA/NSM em relação aos demais, mesmo aplicando a busca local nas outras abordagens. Nesse sentido, o MOEA/NSM pode ser considerado um algoritmo que consegue encontrar soluções não denominadas de qualidade, tanto quanto os algoritmos clássicos da literatura. / This work presents a new approach to the multiobjective evolutionary algorithm, called MOEA/NSM (Multiobjective Evolutionary Algorithm integrating NSGA-II, SPEA2 and MOEA/D features). The algorithm preserves, in general, the characteristics of an evolutionary algorithm, concentrating qualities of other approaches of success in the literature in a single approach, so that they work together, through subpopulations. The objective of the study was to combine the main characteristics of the NSGA-II, SPEA2 and MOEA/D algorithms, and also to include a local search technique to improve the objective space search. The MOEA/NSM algorithm was compared to the other classical approaches using 9 datasets for the biobjective traveling salesman problem. In addition, experiments were carried out also applying the local search in the classical approaches, resulting in a considerable improvement in the results for these algorithms. From the Pareto frontiers resulting from experiments, we applied the evaluation metrics by Hypervolume, Epsilon (ε), R2, EAF, in addition to the Shapiro-Wilk statistical hypothesis test. The results showed a better performance of the MOEA/NSM in relation to the others, even applying the local search in the others approaches. In this sense, the MOEA/NSM can be considered an algorithm that is able to find solutions not dominated of quality, as much as the classic algorithms of the literature.