Thesis. 1977. Ocean E.--Massachusetts Institute of Technology. Dept. of Ocean Engineering. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by William Augustus Tyler Cassedy IV. / Ocean E.

Resumo: O objetivo deste trabalho foi avaliar o posto de trabalho do operador de trator, utilizando dados antropométricos do perfil do trabalhador brasileiro para a análise dos controles e mostradores que os compõem. Como objeto da pesquisa, foram utilizados os tratores com potência média de 73.550 W. Foi realizado um levantamento do estado da arte em publicações pertinentes ao assunto, englobando o fator histórico do trator, a ergonomia, energia humana, posto de trabalho, antropometria, biomecânica, controles e manejos, dispositivos de informação, cores e contrastes, sistema CAD e as normas utilizadas pelas empresas. Utilizando a metodologia da Análise Ergonômica do Trabalho (AET), foi executada uma avaliação dos controles e mostradores do posto de trabalho dos tratores, considerando-se seus diferenciais ergonômicos; com esta triagem foi possível detectar os pontos positivos e negativos. Em seguida, efetivou-se um estudo estatístico com perguntas aos operadores de tratores, para verificar sua real necessidade confrontando-se as análises estatísticas dos questionários com a avaliação ergonômica. Os resultados desta avaliação demonstram que alguns controles e mostradores dos tratores avaliados possuem erros em relação à ergonomia e aos dados antropométricos da população brasileira, podendo este trabalho ser de grande valia para oferecer conforto ao operador de trator. / Abstract: The objective of this work is evaluating the workstation of the tractor operator, using given anthropometrics of the Brazilian worker's profile for the analysis of the controls and displays cases that compose them. As object of the research, the tractors were used with medium potency of 73.550 W. The rising of the state of the art was accomplished in pertinent publications to the subject, including the historical factor of the tractor, the ergonomics, human energy, workstation, anthropometric, biomechanics, controls and handlings, devices of information, colors and contrasts, CAD system and the norms used by the companies. Using the methodology of the Analysis Ergonomic of the Work (AET), it was executed an evaluation of the controls and displays cases of the workstation of the tractors, being considered their differential ergonomic ones; with this selection it was possible to detect the positive and negative points. Soon afterwards, a statistical study was executed with questions to the operators of tractors, to verify his/her real need being confronted the statistical analysis of the questionnaires with the ergonomic evaluation. The results of this evaluation demonstrate that some controls and displays cases of the appraised tractors possess mistakes in relation to the ergonomics and to the data antropométricos of the Brazilian population, being able to this work to be valuable to offer comfort to the tractor operator. Keywords: Ergonomics, work, agricultural tractors and agricultural machines. / Orientador: João Eduardo Guarnetti dos Santos / Coorientador: Mário Morio Isa / Banca: João Candido Fernandes / Banca: Jair Rosas da Silva / Mestre

A pesquisa pretende estudar as interfaces gráficas, o desenho dos caixas eletrônicos e a arquitetura das salas de auto-atendimento das instituições bancárias mais representativas no cenário nacional, de acordo com seus índices de faturamento anual, desde a criação do Banco Central do Brasil na década de 1960 e os primeiros indícios de uma automação bancária, até o momento atual, sob a luz da funcionalidade, usabilidade e acessibilidade, dando início a uma abordagem crítica sobre o tema, investigando a partir de uma análise criteriosa, importantes aspectos do processo criativo, projetual e de implantação das interfaces gráficas, dos caixas eletrônicos e da arquitetura das salas de auto-atendimento. / This research intends to study the graphic interfaces, the design of the ATM machines and the remote banking rooms of the most representative bank institutions in the Brazilian scenario, according to their annual profits data, since the creation of the Central Bank of Brazil in the 1960\'s and the first appearances of the bank automation, until nowadays, focusing on the aspects of usability, function ability and accessibility, investigating important aspects of the creation, project and implantation processes of the graphic interfaces, the ATM machines and the remote banking rooms architecture.

Este trabalho aborda o estudo e aplicação das ferramentas da metodologia TRIZ (Teoria da Resolução de Problemas Inventivos) aplicada na fase do projeto conceitual, no qual é desenvolvido um estudo de caso para escolha dos mancais, para cabeçotes de máquinas de corte do tipo \"Dicing Saw\". A metodologia TRIZ é direcionada para busca de idéias, através de uma abordagem sistemática da criatividade para a solução de problemas inventivos, consiste no reconhecimento da similaridade de um problema de projeto específico com um problema análogo, o qual tem uma solução conhecida no universo das patentes. É demonstrada a importância da capacidade de inovação como vantagem competitiva dentro do cenário atual, e como a TRIZ se apresenta como ferramenta sistêmica de suporte à criatividade inserida na fase de projeto conceitual, dentro do processo de desenvolvimento de produto. É desenvolvido um estudo de caso, no qual a TRIZ conduz à escolha sistemática de tipos de mancais apropriados, para eixos-árvore de alta velocidade para uma máquina denominada \"Dicing Saw\". O resultado da aplicação da TRIZ, dada as restrições operacionais foi a escolha de mancais aerostáticos porosos não-metálicos, os quais em conjunto com trabalhos na área de dinâmica de rotores foram manufaturados. A decisão pelo cabeçote com mancais aerostáticos porosos cerâmicos pode minimizar a influência de elevadas amplitudes de vibração durante usinagens sob alta rotação. Dessa forma, é possível concluir que, a metodologia TRIZ é uma ferramenta que permite a identificação de forma rápida e sistêmica os conceitos utilizados para solucionar problemas semelhantes direcionam a busca de soluções criativas para os problemas inventivos, intensifica a capacidade produtiva do engenheiro projetista, ampliando as alternativas, para encontrar melhores soluções, que podem resultar em um menor tempo, para lançamento de novos produtos, bem como melhorar desempenhos funcionais. / This work treats of study and application of the tools of methodology TRIZ (Theory of Inventive Problem Solving) applied to conceptual design where it is developed a case study to choice of pair of bearings more adequate for Dicing Saw machines. The TRIZ methodology leads the idea searches through systematic approach of creativity to solution of inventive problems where is recognized the common behavior of a specific problem with similar problem using patents database. It is demonstrated the importance of the innovation capacity as competitive advantage considering the current scenario and as the TRIZ technique acts as systematic tool to support for creativity and decision making during the conceptual design into product development process. So, it is developed a case study where the TRIZ lead the systematic selection of bearings for spindles of Dicing Saw machines or ultraprecision machines. The results of this study considering the operational constraints it was choice of aerostatic no-metallic porous bearings which were manufacturing to posterior study of dynamic behavior. The decision on spindle using ceramic aerostatic porous bearings can minimize the influence of high amplitudes of vibrations during the manufacturing on different operational ranges. Therefore it is possible to conclude that TRIZ is a technique or procedure that allows the fast and efficient identification of the physical and technical concepts to solution of the similar problems that directed creative alternatives when it is necessary new conceptual approaches, moreover to stimulate the productive capacity of the design engineer lead the search of the better solutions relating better functional solutions, less costs and small time to market.

Doctor de Sistemas de Ingeniería / Recientemente los datos se han incrementado en todas las áreas del conocimiento, tanto en el número de instancias como en el de atributos. Bases de datos actuales pueden contar con decenas e incluso cientos de miles de variables con un alto grado de información tanto irrelevante como redundante. Esta gran cantidad de datos causa serios problemas a muchos algoritmos de minería de datos en términos de escalabilidad y rendimiento. Dentro de las áreas de investigación en selección de atributos se incluyen el análisis de chips de ADN, procesamiento de documentos provenientes de internet y modelos de administración de riesgo en el sector financiero. El objetivo de esta tarea es triple: mejorar el desempeño predictivo de los modelos, implementar soluciones más rápidas y menos costosas, y proveer de un mejor entendimiento del proceso subyacente que generó los datos. Dentro de las técnicas de minería de datos, el método llamado Support Vector Machines (SVMs) ha ganado popularidad gracias a su capacidad de generalización frente a nuevos objetos y de construir complejas funciones no lineales. Estas características permiten obtener mejores resultados que otros métodos predictivos. Sin embargo, una limitación de este método es que no está diseñado para identificar los atributos importantes para construir la regla discriminante. El presente trabajo tiene como objetivo desarrollar técnicas que permitan incorporar la selección de atributos en la formulación de SVMs no lineal, aportando eficiencia y comprensibilidad al método. Se desarrollaron dos metodologías: un algoritmo wrapper (HO-SVM) que utiliza el número de errores en un conjunto de validación como medida para decidir qué atributo eliminar en cada iteración, y un método embedded (KP-SVM) que optimiza la forma de un kernel Gaussiano no isotrópico, penalizando la utilización de atributos en la función de clasificación. Los algoritmos propuestos fueron probados en bases de datos de de diversa dimensionalidad, que van desde decenas a miles de atributos, y en problemas reales de asignación de créditos para entidades financieras nacionales. De los resultados se obtiene que SVMs no lineal con kernel Gaussiano muestra un mejor desempeño que con las funciones de kernel lineal y polinomial. Asimismo, los métodos de selección de atributos propuestos permiten mantener o incluso mejorar el desempeño predictivo de SVMs no lineal, logrando además una reducción significativa en la utilización de atributos. Para las bases de mayor dimensionalidad se reduce de miles a decenas de atributos seleccionados, logrando un desempeño predictivo significativamente mejor que los enfoques alternativos de selección de atributos para SVMs. Se concluye que los enfoques presentados representan la alternativa más efectiva dentro de las estudiadas para resolver el problema de selección de atributos en modelos de aprendizaje computacional. Como trabajo futuro se propone adaptar las metodologías propuestas para problemas con desbalance de clases, donde se requiere una evaluación distinta del desempeño del modelo considerando costos por error de clasificación asimétricos, una problemática común en aplicaciones como detección de fuga y riesgo crediticio.

Made available in DSpace on 2014-06-11T19:22:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2001-02-17Bitstream added on 2014-06-13T19:07:26Z : No. of bitstreams: 1 fiorotto_dj_me_sjrp.pdf: 485977 bytes, checksum: 8cd2b3ba49a25a9c6a863795f27811c3 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / O problema de dimensionamento de lotes é um problema de otimização da produção, em que o objetivo é planejar a quantidade de itens a ser produzida em várias, ou única, máquinas em cada período ao longo do horizonte de tempo, de modo a tender uma demanda e otimizar uma função objetivo. Este trabalho aborda o problema de dimensionamento de lotes em um único estágio em um ambiente com máquinas paralelas distintas. Cada item pode ser produzido em qualquer máquina, acarretando um tempo de preparação que é gasto antes de começar a produção. O objetivo do trabalho consiste em obter limitantes inferiores de boa qualidade para este problema. Para tanto, é desenvolvido um método de solução baseado numa reformulação do problema a e na relaxação lagrangiana de um conjunto de restrições. Alguns resultados computacionais são apresentados algumas propostas futuras para a continuidade do trabalho. / The lot-sizing problem is a production optimization problem, where the objective is to plan the quantity of items to be produced in multiple, or single, machines in each period over a time horizon, in order to satisfy a demand and optimize an objective function. This work addresses the single stage parallel machine lot-sizing problem. Each item can be produced on any machine, and incur a setup time before to start the production. The objective of this work is to lower bounds of good quality for this problem. A solution method is developed based on a reformulation of the problem and the Lagrangian relaxation of a set of constrainsts. Some computational results are presented comparing the proposed method with a method from the literature, and, some future researches are proposed.

Falls and fall-induced fractures are very common among the elderly. Hip fractures account for most of the deaths and costs of all the fall-induced fractures. This dissertation presents a novel MEMS based human airbag system used as a hip protector. A Micro Inertial Measurement Unit (muIMU) which is based on MEMS accelerometers and gyro sensors is developed as the motion sensing part of the system. The result using this muIMU based on Support Vector Machine (SVM) training to recognize falling-motions are presented, where we showed that selected eigenvector sets generated from 200 experimental data can be separated into falling and other motions completely. For real-time recognition, the SVM filter should be embedded to a high speed DSP system for fast computation and complex filter analyses. After the simulations for SVM filter and FFT were performed on a computer simulator (TI DSP320 C6713), we used DSK6713 (DSP Starter Kit) as our target board and integrated FFT and SVM filter on the chip. The whole algorithm works well with exist sensor data. Demo shows that our DSP system can successfully classify fall and non-fall states. At the same time, the system can trigger our airbag inflation mechanism when a fall occurs. The system was shown to open the airbag in real-time and protected the experimenter's hip area. / by Shi, Guangyi. / "March 2008." / Adviser: Wen Jung Li. / Source: Dissertation Abstracts International, Volume: 70-03, Section: B, page: 1855. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (p. 108-111). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Regularization is a dominant theme in machine learning and statistics due to its prominent ability in providing an intuitive and principled tool for learning from high-dimensional data. As large-scale learning applications become popular, developing efficient algorithms and parsimonious models become promising and necessary for these applications. Aiming at solving large-scale learning problems, this thesis tackles the key research problems ranging from feature selection to learning with unlabeled data and learning data similarity representation. More specifically, we focus on the problems in three areas: online learning, semi-supervised learning, and multiple kernel learning. / The first part of this thesis develops a novel online learning framework to solve group lasso and multi-task feature selection. To the best our knowledge, the proposed online learning framework is the first framework for the corresponding models. The main advantages of the online learning algorithms are that (1) they can work on the applications where training data appear sequentially; consequently, the training procedure can be started at any time; (2) they can handle data up to any size with any number of features. The efficiency of the algorithms is attained because we derive closed-form solutions to update the weights of the corresponding models. At each iteration, the online learning algorithms just need O (d) time complexity and memory cost for group lasso, while they need O (d x Q) for multi-task feature selection, where d is the number of dimensions and Q is the number of tasks. Moreover, we provide theoretical analysis for the average regret of the online learning algorithms, which also guarantees the convergence rate of the algorithms. In addition, we extend the online learning framework to solve several related models which yield more sparse solutions. / The second part of this thesis addresses a general scenario of semi-supervised learning for the binary classification problern, where the unlabeled data may be a mixture of relevant and irrelevant data to the target binary classification task. Without specifying the relatedness in the unlabeled data, we develop a novel maximum margin classifier, named the tri-class support vector machine (3C-SVM), to seek an inductive rule that can separate these data into three categories: --1, +1, or 0. This is achieved by adopting a novel min loss function and following the maximum entropy principle. For the implementation, we approximate the problem and solve it by a standard concaveconvex procedure (CCCP). The approach is very efficient and it is possible to solve large-scale datasets. / The third part of this thesis focuses on multiple kernel learning (MKL) to solve the insufficiency of the L1-MKL and the Lp-MKL models. Hence, we propose a generalized MKL (GMKL) model by introducing an elastic net-type constraint on the kernel weights. More specifically, it is an MKL model with a constraint on a linear combination of the L1-norm and the square of the L2-norm on the kernel weights to seek the optimal kernel combination weights. Therefore, previous MKL problems based on the L1-norm or the L2-norm constraints can be regarded as its special cases. Moreover, our GMKL enjoys the favorable sparsity property on the solution and also facilitates the grouping effect. In addition, the optimization of our GMKL is a convex optimization problem, where a local solution is the globally optimal solution. We further derive the level method to efficiently solve the optimization problem. / Yang, Haiqin. / Advisers: Kuo Chin Irwin King; Michael Rung Tsong Iyu. / Source: Dissertation Abstracts International, Volume: 73-04, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 152-173). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Bibliography: leaves 160-163. / by Mostafa Hamed Ammar. / M.S.

Thesis. 1976. Ph.D.--Massachusetts Institute of Technology. Dept. of Mechanical Engineering. / Microfiche copy available in Archives and Engineering. / Vita. / Includes bibliographical references. / Ph.D.