Thesis (Ph.D.)--University of Melbourne, Dept. of Computer Science and Software Engineering, Faculty of Engineering, 2007. / Typescript. Includes bibliographical references (leaves 171-179).

Made available in DSpace on 2015-03-03T11:52:50Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-11-25Bitstream added on 2015-03-03T12:06:59Z : No. of bitstreams: 1 000806273.pdf: 2878729 bytes, checksum: 780266454638376c226351f3401f09f2 (MD5) / O objetivo deste trabalho foi a criação de uma modelagem estatística, capaz de substituir o processo utilizado para a preparação de fornos de têmpera e revenimento, que tradicionalmente é realizada por meio de ajustes feitos a partir de resultados de propriedades mecânicas, ensaiadas em laboratório e exigidas em especificações de clientes. Buscou-se compreender a influência das variáveis de entrada (fatores) nas propriedades mecânicas limite de resistência à tração, dureza e estricção, em arames de aço SAE 9254, para os diâmetros 2,00mm e 6,50mm, utilizados na fabricação de molas de válvula e de embreagem para o seguimento automobilístico. Foram investigadas as principais variáveis de entrada do processo diâmetro, velocidade, temperatura de revenimento e a concentração do meio de têmpera polímero, para isso, utilizou-se as metodologias de Planejamento de Experimentos com Análise em Blocos, Regressão Múltipla e Quadrática, Análise de Variância (ANOVA), Análise de Componentes Principais (Estatística Multivariada), Metodologia de Superfícies de Resposta (RSM) e Controle Estatístico de Processo para a análise residual dos modelos estatísticos. Para otimização dos modelos estatísticos foram utilizados os métodos Desirability, Gradiente Reduzido Generalizado (GRG), Algoritmo Genético (AG) e a Meta-heurística Recozimento Simulado. Os resultados revelaram que todas as variáveis consideradas têm influência significativa e os modelos obtidos foram validados utilizando-se métodos estatísticos adequados. Essa modelagem e sua otimização, se implementada e aplicada corretamente, poderá ocasionar avanços científicos que proporcionariam a automatização deste processo, e consequentemente provocaria impacto significativo no aumento de produtividade e qualidade do produto / The purpose of this work was the creation of a statistical modeling able to replace the process used to setup of the ovens of the quench hardening and tempering, that is traditionally accomplished through adjustments made based on the results of mechanical properties as tested in laboratory and required in customer specifications. We sought to understand the influence of the input variables (factors) on the mechanical properties tensile strength, yield point and hardness, in SAE 9254 draw steel wires, with diameters 2.00 mm and 6.50 mm, used in the manufacture of valve springs and clutch for automobile tracking. Were investigated the input variables of the process wire diameter, processing speed, tempering temperature and concentration of polymer. We used the methodologies Design of experiments with analysis in blocks, Multiple regression and quadratic regression, Analysis of variance (ANOVA), Principal Components Analysis (multivariate statistical), Response surface methodology and Statistical Process Control for residual analysis of statistical models. For optimization were used Desirability method, Generalized Reduced Gradient (GRG), Genetic Algorithm (AG) and Simulated Annealing. The results revealed that all variables considered have significant influence and models obtained were validated using appropriate statistical methods. This new modeling and its optimization, if properly implemented and enforced, could lead scientific advances which would provide the automation of this process, and consequently cause great impact on increasing productivity and product quality

Orientador: Messias Borges Silva / Coorientador: Valério Antônio Pamplona Salomon / Banca: Aneirson Francisco da Silva / Banca: Fernando Augusto Silva Marins / Banca: Rosinei Batista Ribeiro / Banca: Jorge LUiz Rosa / Resumo : O objetivo deste trabalho foi a criação de uma modelagem estatística, capaz de substituir o processo utilizado para a preparação de fornos de têmpera e revenimento, que tradicionalmente é realizada por meio de ajustes feitos a partir de resultados de propriedades mecânicas, ensaiadas em laboratório e exigidas em especificações de clientes. Buscou-se compreender a influência das variáveis de entrada (fatores) nas propriedades mecânicas limite de resistência à tração, dureza e estricção, em arames de aço SAE 9254, para os diâmetros 2,00mm e 6,50mm, utilizados na fabricação de molas de válvula e de embreagem para o seguimento automobilístico. Foram investigadas as principais variáveis de entrada do processo diâmetro, velocidade, temperatura de revenimento e a concentração do meio de têmpera polímero, para isso, utilizou-se as metodologias de Planejamento de Experimentos com Análise em Blocos, Regressão Múltipla e Quadrática, Análise de Variância (ANOVA), Análise de Componentes Principais (Estatística Multivariada), Metodologia de Superfícies de Resposta (RSM) e Controle Estatístico de Processo para a análise residual dos modelos estatísticos. Para otimização dos modelos estatísticos foram utilizados os métodos Desirability, Gradiente Reduzido Generalizado (GRG), Algoritmo Genético (AG) e a Meta-heurística Recozimento Simulado. Os resultados revelaram que todas as variáveis consideradas têm influência significativa e os modelos obtidos foram validados utilizando-se métodos estatísticos adequados. Essa modelagem e sua otimização, se implementada e aplicada corretamente, poderá ocasionar avanços científicos que proporcionariam a automatização deste processo, e consequentemente provocaria impacto significativo no aumento de produtividade e qualidade do produto / Abstract: The purpose of this work was the creation of a statistical modeling able to replace the process used to setup of the ovens of the quench hardening and tempering, that is traditionally accomplished through adjustments made based on the results of mechanical properties as tested in laboratory and required in customer specifications. We sought to understand the influence of the input variables (factors) on the mechanical properties tensile strength, yield point and hardness, in SAE 9254 draw steel wires, with diameters 2.00 mm and 6.50 mm, used in the manufacture of valve springs and clutch for automobile tracking. Were investigated the input variables of the process wire diameter, processing speed, tempering temperature and concentration of polymer. We used the methodologies Design of experiments with analysis in blocks, Multiple regression and quadratic regression, Analysis of variance (ANOVA), Principal Components Analysis (multivariate statistical), Response surface methodology and Statistical Process Control for residual analysis of statistical models. For optimization were used Desirability method, Generalized Reduced Gradient (GRG), Genetic Algorithm (AG) and Simulated Annealing. The results revealed that all variables considered have significant influence and models obtained were validated using appropriate statistical methods. This new modeling and its optimization, if properly implemented and enforced, could lead scientific advances which would provide the automation of this process, and consequently cause great impact on increasing productivity and product quality / Doutor

This study is focused on grafical modeling of embedded systems using dialects of UML. It provides a brief description of existing profiles. Furthemore it deals with modeling frameworks for the Eclipse platform and describes an implementation of such modeling tool as a part of project Lissom.

Thesis: Ph. D., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2016. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 209-225). / Identifying and tracking an unknown linear system from observations of its inputs and outputs is a problem at the heart of many different applications. Due to the complexity and rapid variability of modern systems, there is extensive interest in solving the problem with as little data and computation as possible. This thesis introduces the novel approach of reducing problem dimension by exploiting statistical structure on the input. By modeling the input to the system of interest as a graph-structured random process, it is shown that a large parameter identification problem can be reduced into several smaller pieces, making the overall problem considerably simpler. Algorithms that can leverage this property in order to either improve the performance or reduce the computational complexity of the estimation problem are developed. The first of these, termed the graphical expectation-maximization least squares (GEM-LS) algorithm, can utilize the reduced dimensional problems induced by the structure to improve the accuracy of the system identification problem in the low sample regime over conventional methods for linear learning with limited data, including regularized least squares methods. Next, a relaxation of the GEM-LS algorithm termed the relaxed approximate graph structured least squares (RAGS-LS) algorithm is obtained that exploits structure to perform highly efficient estimation. The RAGS-LS algorithm is then recast into a recursive framework termed the relaxed approximate graph structured recursive least squares (RAGS-RLS) algorithm, which can be used to track time-varying linear systems with low complexity while achieving tracking performance comparable to much more computationally intensive methods. The performance of the algorithms developed in the thesis in applications such as channel identification, echo cancellation and adaptive equalization demonstrate that the gains admitted by the graph framework are realizable in practice. The methods have wide applicability, and in particular show promise as the estimation and adaptation algorithms for a new breed of fast, accurate underwater acoustic modems. The contributions of the thesis illustrate the power of graphical model structure in simplifying difficult learning problems, even when the target system is not directly structured. / by Atulya Yellepeddi. / Ph. D.

Graphical models use Markov properties to establish associations among dependent variables. To estimate spatial correlation and other parameters in graphical models, the conditional independences and joint probability distribution of the graph need to be specified. We can rely on Gaussian multivariate models to derive the joint distribution when all the nodes of the graph are assumed to be normally distributed. However, when some of the nodes are discrete, the Gaussian model no longer affords an appropriate joint distribution function. We develop methods specifying the joint distribution of a chain graph with both discrete and continuous components, with spatial dependencies assumed among all variables on the graph. We propose a new group of chain graphs known as the generalized tree networks. Constructing the chain graph as a generalized tree network, we partition its joint distributions according to the maximal cliques. Copula models help us to model correlation among discrete variables in the cliques. We examine the method by analyzing datasets with simulated Gaussian and Bernoulli Markov random fields, as well as with a real dataset involving household income and election results. Estimates from the graphical models are compared with those from spatial random effects models and multivariate regression models. / Graduation date: 2013

In emergency management and in military operations, command and control comprises the collection of functions, systems and staff personnel that one or several executives draw on to arrive at decisions and seeing that these decisions are carried out. The large amount of available information coupled with modern computers and computer networks brings along the potential for making well-informed and quick decisions. Hence, decision-making is a central aspect in command and control, emphasizing an obvious need for development of adequate decision-supporting tools to be used in command and control centers. However, command and control takes place in a versatile environment, including both humans and artifacts, making the design of useful computer tools both challenging and multi-faceted. This thesis deals with preparatory action in command and control settings with a focus on the strategic properties of a situation, i.e., to aid commanders in their operational planning activities with the utmost goal of ensuring that strategic interaction occurs under the most favorable circumstances possible. The thesis highlights and investigates the common features of interaction by approaching them broadly using a gaming perspective, taking into account various forms of strategic interaction in command and control. This governing idea, the command and control gaming perspective, is considered an overall contribution of the thesis. Taking the gaming perspective, it turns out that the area ought to be approached from several research directions. In particular, the persistent gap between theory and applications can be bridged by approaching the command and control gaming perspective using both an applied and a theoretical research direction. On the one hand, the area of game theory in conjunction with research findings stemming from artificial intelligence need to be modified to be of use in applied command and control settings. On the other hand, existing games and simulations need to be adapted further to take theoretical game models into account. Results include the following points: (1) classification of information with proposed measurements for a piece of information's precision, fitness for purpose and expected benefit, (2) identification of decision help and decision analysis as the two main directions for development of computerized tools in support of command and control, (3) development and implementation of a rule based algorithm for map-based decision analysis, (4) construction of an open source generic simulation environment to support command and control microworld research, (5) development of a generic tool for prediction of forthcoming troop movements using an algorithm stemming from particle filtering, (6) a non-linear multi-attribute utility function intended to take prevailing cognitive decision-making models into account, and (7) a framework based on game theory and influence diagrams to be used for command and control situation awareness enhancements. Field evaluations in cooperation with military commanders as well as game-theoretic computer experiments are presented in support of the results. / QC 20100825

Networks of distributed, remote sensors are providing ecological scientists with a view of our environment that is unprecedented in detail. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures in network communications. This behavior manifests as corrupt or missing measurements in the data. Consequently, before the data can be used in ecological models, future experiments, or even policy decisions, it must be quality controlled (QC'd) to flag affected measurements and impute corrected values. This dissertation describes a probabilistic modeling approach for real-time automated QC that exploits the spatial and temporal correlations in the data to distinguish sensor failures from valid observations. The model adapts to a site by learning a Bayesian network structure that captures spatial relationships among sensors, and then extends this structure to a dynamic Bayesian network to incorporate temporal correlations. The final QC model contains both discrete and continuous variables, which makes inference intractable for large sensor networks. Consequently, we examine the performance of three approximate methods for inference in this probabilistic framework. Two of these algorithms represent contemporary approaches to inference in hybrid models, while the third is a greedy search-based method of our own design. We demonstrate the results of these algorithms on synthetic datasets and real environmental sensor data gathered from an ecological sensor network located in western Oregon. Our results suggest that we can improve performance over networks with less sensors that use exhaustive asynchronic inference by including additional sensors and applying approximate algorithms. / Graduation date: 2013

Avec le développement de l’éolien, les prescriptions techniques de raccordement de cette technologie obligeront le maintient de sa connexion lors d’incidents sur la tension du réseau électrique. L’enjeu pour le gestionnaire du réseau est de pouvoir utiliser tous les générateurs pour garantir la stabilité du système électrique.A partir d’un modèle dynamique d’une éolienne à base de Machine Asynchrone à Double Alimentation (MADA), une commande vectorielle améliorée a été proposée en prenant en compte la dynamique du flux statorique engendrée par la chute de tension. Les performances supérieures en terme de maintient de la production ont été établies par comparaison avec la méthode de commande classique. Son domaine d’utilisation a été également déterminé.Pendant les creux de tension importants, une protection matérielle (crowbar) est implémentée avec un contrôle de la démagnétisation de la MADA. En outre, de la puissance réactive peut être produite à la fois par la MADA et par le convertisseur connecté au réseau électrique au cours de la défaillance du réseau.Un contrôle vectoriel à hystérésis des courants pour les deux convertisseurs électroniques multiniveaux est proposé et évalué pour améliorer la réponse dynamique de ces convertisseurs et pour réduire les effets des variations des paramètres sur les performances de la commande. Selon la durée du défaut, des objectifs différents de contrôle doivent être réalisés en priorité pour empêcher des surintensités rotoriques et pour fournir de la puissance réactive. Une reconfiguration complète du dispositif de commande de cette éolienne est détaillée pour renforcer le maintient de la production éolienne lors de défaillances / With the massive development of wind energy, the technical requirements for connecting this technology will require the improvement of the fault ride-through capability of grid-connected wind turbines. The task for the grid system operator is to use all generators to ensure the stability of the electrical system.From a dynamic model of a Doubly Fed Induction Generator (DFIG) based wind generator, an improved vector control has been proposed by taking into account the dynamics of the magnetic flux, which are generated by the voltage dip. The higher performances have been established by comparison with the conventional control method. The operation domain was also determined.During serious voltage dips, a hysteresis control scheme of the active Crowbar is proposed to protect the system within a demagnetization method of the DFIG. Moreover, additional reactive power can be produced both by the MADA and the grid-side converter in order to support the electric network during the grid fault.A space vector hysteresis current control strategy of both three-level converters is proposed to improve the dynamic response of the system and to reduce the parameter variation effects on the control performanceDepending on the grid fault duration, different control objectives have to be achieved with priority to restrain the rotor over-current or to supply reactive power. Then the reconfiguration scheme of the control strategies of high power DFIG wind turbine system is proposed to enhance the fault ride-through capability of the DFIG system. With this specific methodology, the DFIG can stay connected and can supply maximal reactive current during voltage dips to help voltage recovery

Ein wesentliches Ziel während der Produktentwicklung ist die frühzeitige Absicherung der Produkteigenschaften auf Basis der definierten Produktmerkmale unter Beachtung der äußeren Randbedingungen. Digitale Modelle und Methoden unterstützen den Produktentwickler bei der frühzeitigen virtuellen Evaluation des Produktes. [...] In diesem Beitrag wird eine Methodik präsentiert, die mit Hilfe der SysML-Modelle eine Simulation in VR ermöglicht. Die SysML-Beschreibung wird als Kern der Simulation dienen und das gesamte Simulationsmodell steuern. Weiterhin wird erläutert, wie die SysML-Beschreibung mit einem VR-Tool und einem Physikberechnungstool verbunden werden kann. Die in CAVE und HMD durchgeführten Simulationen wurden im Rahmen von Usability Tests evaluiert. Aus diesen Tests werden Ergebnisse präsentiert, die sich mit Verwendungsschwerpunkten in VR und der Zufriedenheit bei der Beurteilung von Produkten in VR beschäftigt haben. Schlussendlich wird ein Beispiel-Simulationsszenario in der CAVE-VR und einem Head Mounted Display (HMD) diskutiert. [... aus der Einleitung]