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Abstract The objective of this study was to explore the feasibility of using the One-Variable Linear Equation Situational Test to investigate the development of the concept of one-variable linear equation for middle school students. The conduct of the first stage of this study was as follows: first, a thorough literature review was made; which was followed by interviews with middle and high school math teachers; finally a survey of the eighth-grade students was made using the ¡§One-Variable Linear Equation Concept Unstructured Questionnaire¡¨. The second stage of this study was to devise the One-Variable Linear Equation Situational Test. First, a detailed concept map of the one-variable linear equation was made based on the results obtained in the first stage of this study. Then, a situational test of one-variable linear equation was constructed according to the map. This test was to be used later in the one-to-one interviews with twelve seventh-grade students from a middle school in Kaohsiung, who did not learn the one-variable linear equation before. These twelve subjects were randomly devided into two groups: with guidance and without guidance. The data of the math achievement tests were also collected for these subjects. The results of the test interviews were analyzed and the feasibility of using the One-Variable Linear Equation Situational Test to investigate the development of the concept of one-variable linear equation was discussed. The analysis results of individual questions of the situational test of one-variable linear equation indicated that the concepts of one-variable linear equation for middle school students were detectable. This suggested that it was feasible to use the One-Variable Linear Equation Situational Test to investigate the development of the concept of one-variable linear equation for middle school students. All subjects who participated in this study already had some preliminary ideas of the one-variable linear equation. The factor of providing guidance would enhance the development of the concept of one-variable linear equation and it would reduce the differences in numbers of various concepts of one-variable linear equation developed among the high, medium and low achievement students. Therefore, the variable of with- or without-guidance would have some effects on the detectable concepts of one-variable linear equation by the One-Variable Linear Equation Situational Test.

<p>The development of fuel efficient internal combustion engines (ICE)have resulted in a variety of different solutions. One of those are the variable valve timing and an implemenation of such is the Continuous Variable Cam Phasing (CVCP). This thesis have used a simulation package, psPack, for the simulation of the gas exchange process for an ICE with CVCP. The purpose of the simulations was to investigate what kind of design parameters, e.g. the length of an intake pipe or the duration of combustion, that were significant for the gas exchange process with the alternation of intake pressure, engine speed and valve setting. The parameters that showed a vast impact were those who affected the amount of residual gas and the temperature of the air charge. Furthermore a validation was made between simulation data acquired from psPack and measured data provided in Heywood (1988). The validation showed that for the general behaviour the simulation results from psPack corresponded well to the measured data.</p>

This thesis is based on three essays. The first chapter analyses the impact of 27 years of civil war in Angola on human capital, expenditures per adult equivalent and fertility. The prediction of the effects of civil war is done through a neoclassical unitary household model in the tradition of Rosenzweig. Using instrumental variable method, this thesis shows that civil war has a negative and disastrous impact in short-term on health of children, this effect is persistent. Civil war has no impact on expenditures per adult equivalent. It increases enrollment and decreases fertility in the short term. The second chapter ofthis thesis analyzes the effectiveness of a social program in a conflict country such as Angola and explores whether this effectiveness depends on the intensity of the conflict. Our identification strategy is based on the political geography of the deployment of the program based on a model of spatial competition of Hotelling. This thesis shows that the Angola Social Fund had a positive impact on expenditures per adult equivalent and on one of the main anthropometric measurements namely the height for age z-score. The program's effectiveness in function to the intensity of the conflict is analyzed using the local instrumental variable estimator. The thesis shows that the program's effectiveness increases with the intensity of the conflict. The last chapter of this thesis analyzes in the case of Cameroon, the impact of teacher training on HIV/AIDS. The two criteria for selecting participating schools, leads us to choose as identification strategy the regression discontinuity design. This thesis shows that 15 to 17 year old girls in teacher training schools are between 7 and 10 percentage points less likely to have started childbearing. For 12 to 13 year old girls, the likelihood of self-reported abstinence and condom use is also significantly higher in treated schools.

Dans le domaine aéronautique, la détection des défauts sur structures composites sefait lors des phases de maintenance. Celles-ci sont prévues de manière à détecter lesdéfauts avant que ceux-ci ne deviennent critiques pour la tenue des structures en service.L’optimisation des intervalles de maintenance représente donc un fort intérêt que ce soitau niveau financier ou opérationnel. Les dommages des structures composites sont aujourd’hui traités par la non-propagationdes défauts : lorsque ceux-ci apparaissent et qu’ils sont détectés, les pièces sont immédiatementréparées ou remplacées. Afin d’améliorer ces intervalles de maintenance, lecomportement des défauts soumis aux spectres de charges aéronautique nécessite d’êtrecaractérisé. Cela permettrait une transition vers une philosophie de tolérance aux dommages,en définissant des phases de propagation non-critique pour la tenue mécanique desstructures. Dans ce contexte, la propagation de délaminage est étudiée sous chargement de fatigue.En mode I de propagation, les effets de la fréquence de sollicitation et du rapport de chargesur la propagation de délaminage en fatigue sont déterminés. Ceux-ci amorcent l’étudede la propagation de délaminage sous spectre de charges à niveau variable. Les effets del’historique de chargement sont mis en évidence. En mode II de propagation, les effets de la fréquence de sollicitation sur la propagationde délaminage sont abordés pour quatre matériaux à l’aide d’un montage d’essaisvibratoires dédié. Une analyse thermique des essais est également conduite. De plus, leseffets du rapport de charge sont déterminés pour ce mode de propagation. / The detection of damage in composite aeronautical structures is carried out duringmaintenance phases. These operations are planned so that damage is detected beforereaching any critical size for the in-service structures. The optimization of maintenanceintervals is therefore of great interest both financially and operationally. Damage in composites structures is currently dealt through the no-growth approach :when damage appears and is detected, the affected parts are immediately repaired orreplaced. In order to improve the maintenance schedule, the behaviour of defects subjectedto aeronautical load spectra needs to be characterized. This would enable a transitiontowards a damage tolerance philosophy with a slow-growth approach by defining noncriticalpropagation phases for the mechanical strength of structures. In this context, delamination propagation under fatigue loading is studied. The effectsof loading frequency and load ratio on fatigue delamination propagation are determinedin mode I. Then a study of delamination propagation under complex load spectra isconducted for blocks at different loading amplitudes. Effects of the loading history arehighlighted. For the propagation in mode II, loading frequency effects on delamination propagationare investigated for four different composite materials using a dedicated vibration testingdevice. A thermal analysis is also conducted during high frequency tests. In addition, loadratio effects are determined for this propagation mode.

A presente dissertação propõe métodos para seleção de variáveis preditivas com base em índices de importância das variáveis e regressão PLS (Partial Least Squares). Partindo-se de uma revisão da bibliografia sobre PLS e índices de importância das variáveis, sugere-se um método, denominado Eliminação Backward (EB), para seleção de variáveis a partir da eliminação sistemática de variáveis de acordo com a ordem definida por índices de importância das variáveis. Um novo índice de importância de variáveis, proposto com base nos parâmetros da regressão PLS, tem seu desempenho avaliado frente a outros índices reportados pela literatura. Duas variações do método EB são propostas e testadas através de simulação: (i) o método EBM (Eliminação backward por mínimos), que identifica o conjunto que maximiza o indicador de acurácia preditiva sem considerar o percentual de variáveis retidas, e (ii) o método EBDE (Eliminação backward por distância euclidiana), que seleciona o conjunto de variáveis responsável pela mínima distância euclidiana entre os pontos do perfil gerado pela eliminação das variáveis e um ponto ideal hipotético definido pelo usuário. A aplicação dos três métodos em quatro bancos de dados reais aponta o EBDE como recomendável, visto que retém, em média, apenas 13% das variáveis originais e eleva a acurácia de predição em 32% em relação à utilização de todas as variáveis. / This dissertation presents new methods for predictive variable selection based on variable importance indices and PLS regression. The novel method, namely Backward Elimination (BE), selects the most important variables by eliminating process variables according to their importance described by the variable importance indices. A new variable importance index is proposed, and compared to previous indices for that purpose. We then offer two modifications on the BE method: (i) the EBM method, which selects the subset of variables yielding the maximum predictive accuracy (i.e., the minimum residual index), and (ii) the EBDE, which selects the subset leading to the minimum Euclidian distance between the points generated by variable removal and a hypothetical ideal point defined by the user. When applied to four manufacturing data sets, the recommended method, EBDE, retains average 13% of the original variables and increases the prediction accuracy in average 32% compared to using all the variables.

Les Stations de Transfert d’Energie par Pompage (STEP) sont des structures importantes pour stabiliser le réseau électrique.Les technologies à vitesse variable peuvent améliorer l'efficacité et la souplesse d’utilisation des STEPs. Les technologies actuelles telles que les machines alimentées en fréquence variable, ou les Machines Asynchrone à Double Alimentations (MADA) présentent des inconvénients. Dans ce travail, nous nous concentrons sur une structure non conventionnelle de machine à vitesse variable : la Machine à Induction à Double Alimentation sans Balais (BDFM). Les objectifs sont de mieux comprendre le fonctionnement de cette machine pour la dimensionner, l’optimiser et finalement la comparer aux structures existantes.Après un examen des techniques de dimensionnement et d'optimisation des machines classiques, des approches similaires sont étudiées pour les BDFM. Deux méthodes différentes pour des simulations éléments finis plus rapides de la BDFM sont présentées : une première, la plus rapide mais qui ne considère pas le phénomène de saturation et une seconde basée sur le principe des simulations magnétoharmoniques. Une analyse harmonique minutieuse combinée à une comparaison de cas en charges (couplage-croisés) entre des simulations FE et les résultats obtenus avec des schémas équivalents obtenus dans la littérature conduit à une modification du circuit équivalent de la BDFM. Une nouvelle méthode pour déterminer les paramètres de ce circuit grâce à des essais électriques est ensuite présentée. La détermination des paramètres à partir de la géométrie est également abordée pour aboutir à un modèle semi-analytique dérivable. Un tel modèle, couplé à un algorithme d'optimisation du 1er ordre pourrait être extrêmement puissant lors du dimensionnement d'une BDFM. Le potentiel d'une telle approche est montré dans ce travail grâce à l'optimisation d'une machine à induction. / Pumped-hydro storage plants (PSP) are important assets to stabilize electric grids.Variable speed technologies can improve the cycle efficiency and the power adjustability of PSPs. Current technologies such as fully-fed machines or Doubly-Fed Induction Machines (DFIM) have drawbacks. In this work, the focus will be on an unconventional design of variable speed machine: the Brushless Doubly-Fed Induction Machine (BDFM). The objectives are to better understand the working principles of this machine so as to size it, optimize it, and compare it to other types of variable speed machines.Following a review of sizing and optimization techniques for conventional machines, similar approaches are investigated for BDFMs. Two different methods for faster Finite-Element (FE) simulations of the BDFM are presented: a fast one without saturation considerations and another one based on the principle of magneto-harmonic simulations. A careful harmonic analysis combined with a comparison of cross-coupling tests between FE simulations and results of equivalent circuit found in the literature will lead to a modification of the BDFM equivalent circuit. A new method to determine the parameters of thisequivalent circuit from electrical tests is presented. The parameters determination from the geometry will also be considered for the elaboration of a derivable semi-analytical model. Such a model, paired with a 1st order optimization algorithm could be extremely powerful during the sizing of a BDFM. The potential of such an approach is shown in this work with the optimization of an Induction Machine.

L'utilisation de correcteur discret à période d'échantillonnage variable peut être intéressante dans plusieurs cas, par exemple lorsque la mesure, bien qu'envoyée de façon périodique, est reçue à intervalle variable. C'est le cas en milieu marin lorsque la mesure d'altitude est effectuée avec un capteur à ultrason (la durée du trajet du signal dans l'eau dépend de la distance par rapport au fond). Le délai variable entre deux réceptions de mesures, peut être vu comme une variation de période d'échantillonnage pour le contrôleur. La synthèse de lois de commande discrète à période d'échantillonnage variable a déjà été étudiée pour des systèmes stationnaires. On se propose ici d'étendre cette méthode pour des systèmes Linéaires à Paramètres Variants (LPV), qui permettent de conserver des paramètres importants d'un système non-linéaire en temps que paramètres d'un système linéaires. La synthèse de contrôleur repose sur le méthodologie H∞, appliquée aux systèmes LPV. En particulier, on s'intéressera à deux approches existantes dans la littérature : l'approche polytopique (où le paramètre variant évolue dans un volume convexe) et la Représentation Linéaire Fractionnelle (LFR). La méthode proposée est appliquée au contrôle d'un AUV (Autonomous Underwater Vehicle), qui est système difficile à contrôler du fait d'importantes non-linéarités. Des résultats de simulations permettront de montrer l'intérêt de la méthode pour le contrôle d'altitude d'un AUV, et notamment les améliorations apportées par l'ajout de paramètres issus du système non-linéaire au modèle utilisé pour la synthèse des régulateurs. / Discrete time controller using variable sampling can ba interesting in several cases, for axample when the measure, even if send periodically, is received with a variable interval. This is the case in submarine environement, when the altitude measurement is done using an ultrasonic sensor. Discrete control laws synthesis with variable sampling period have already been studied for LTI systems. The results are here extended to Linear Parameter Varying systems, that allow to keep some non-linearities as parameters of a linear system. In particular, two approaches are investigated : the polytopic and the LFR. The proposed method is applied for the altitude control of an autonomous underwater vehicle (AUV). Simulations results will show the interest of the method, in particular how results are improved by adding some parameters coming from the non linear model.

A presente dissertação propõe métodos para seleção de variáveis preditivas com base em índices de importância das variáveis e regressão PLS (Partial Least Squares). Partindo-se de uma revisão da bibliografia sobre PLS e índices de importância das variáveis, sugere-se um método, denominado Eliminação Backward (EB), para seleção de variáveis a partir da eliminação sistemática de variáveis de acordo com a ordem definida por índices de importância das variáveis. Um novo índice de importância de variáveis, proposto com base nos parâmetros da regressão PLS, tem seu desempenho avaliado frente a outros índices reportados pela literatura. Duas variações do método EB são propostas e testadas através de simulação: (i) o método EBM (Eliminação backward por mínimos), que identifica o conjunto que maximiza o indicador de acurácia preditiva sem considerar o percentual de variáveis retidas, e (ii) o método EBDE (Eliminação backward por distância euclidiana), que seleciona o conjunto de variáveis responsável pela mínima distância euclidiana entre os pontos do perfil gerado pela eliminação das variáveis e um ponto ideal hipotético definido pelo usuário. A aplicação dos três métodos em quatro bancos de dados reais aponta o EBDE como recomendável, visto que retém, em média, apenas 13% das variáveis originais e eleva a acurácia de predição em 32% em relação à utilização de todas as variáveis. / This dissertation presents new methods for predictive variable selection based on variable importance indices and PLS regression. The novel method, namely Backward Elimination (BE), selects the most important variables by eliminating process variables according to their importance described by the variable importance indices. A new variable importance index is proposed, and compared to previous indices for that purpose. We then offer two modifications on the BE method: (i) the EBM method, which selects the subset of variables yielding the maximum predictive accuracy (i.e., the minimum residual index), and (ii) the EBDE, which selects the subset leading to the minimum Euclidian distance between the points generated by variable removal and a hypothetical ideal point defined by the user. When applied to four manufacturing data sets, the recommended method, EBDE, retains average 13% of the original variables and increases the prediction accuracy in average 32% compared to using all the variables.

Bancos de dados oriundos de processos industriais são caracterizados por elevado número de variáveis correlacionadas, dados ruidosos e maior número de variáveis do que observações, tornando a seleção de variáveis um importante problema a ser analisado no monitoramento de tais processos. A presente dissertação propõe sistemáticas para seleção de variáveis com vistas à classificação de bateladas produtivas. Para tanto, sugerem-se novos métodos que utilizam Índices de Importância de Variáveis para eliminação sistemática de variáveis combinadas a ferramentas de classificação; objetiva-se selecionar as variáveis de processo com maior habilidade discriminante para categorizar as bateladas em classes. Os métodos possuem uma sistematização básica que consiste em: i) separar os dados históricos em porções de treino e teste; ii) na porção de treino, gerar um Índice de Importância de Variáveis (IIV) que ordenará as variáveis de acordo com sua capacidade discriminante; iii) a cada iteração, classificam-se as amostras da porção de treino e removem-se sistematicamente as variáveis; iv) avaliam-se então os subconjuntos através da distância Euclidiana dos resultados dos subconjuntos a um ponto hipotético ótimo, definindo assim o subconjunto de variáveis a serem selecionadas. Para o cumprimento das etapas acima, são testadas diferentes ferramentas de classificação e IIV. A aplicação dos métodos em bancos reais e simulados verifica a robustez das proposições em dados com distintos níveis de correlação e ruído. / Databases derived from industrial processes are characterized by a large number of correlated, noisy variables and more variables than observations, making of variable selection an important issue regarding process monitoring. This thesis proposes methods for variable selection aimed at classifying production batches. For that matter, we propose new methods that use Variable Importance Indices for variable elimination combined with classification tools; the objective is to select the process variables with the highest discriminating ability to categorize batch classes. The methods rely on a basic framework: i) split historical data into training and testing sets; ii) in the training set, generate a Variable Importance Index (VII) that will rank the variables according to their discriminating ability; iii) at each iteration, classify samples from the training set and remove the variable with the smallest VII; iv) candidate subsets are then evaluated through the Euclidean distance to a hypothetical optimum, selecting the recommended subset of variables. The aforementioned steps are tested using different classification tools and VII’s. The application of the proposed methods to real and simulated data corroborates the robustness of the propositions on data with different levels of correlation and noise.