The retrieval of similar images in databases is a wide and complex research field that shows a great demand for good performance applications. The increasing volume of information available in the Internet and the success of textual search engines motivate the development of tools that make possible image searches by content similarity. Many features can be applied in determining the similarity between images, such as size, color, shape, color variation, texture, objects and their spatial distribution, among others. Texture and color are the most important features which allow a preliminary analysis of image similarity. This dissertation presents many techniques introduced in the literature, which analyze texture and color. Some of them were implemented, their performances were compared and the results were presented. This comparison allows the determination of the best techniques, making possible the analysis of their applicability and can be used as a reference in future works. The quantitative performance analyses were done using the ANMRR metric, defined in the MPEG-7 standard, and the confusion matrices were presented for each of the tested techniques. Two groups of quantitative tests were realized: the first one was applied upon a gray scale texture database and the second one, upon a color image database. For the experiment with the gray scale texture images, the techniques PBLIRU16, MCNC and their combination presented the best performances. For the experiment with the color images, SCD, HDCIG and CSD techniques performed best. / A recuperação de imagens semelhantes em bancos de dados é um campo de pesquisa amplo, complexo e que apresenta grande demanda por aplicativos que apresentem bons resultados. O volume crescente de informações disponibilizadas ao público e o sucesso das ferramentas de busca textuais na Internet motivam a criação de utilitários que possibilitem a busca de imagens por semelhança de conteúdo. Podem-se utilizar várias características para a determinação da semelhança entre imagens digitais, tais como tamanho, cor, forma, variação de cores, textura, objetos e sua disposição espacial, entre outras. A textura e a cor são as duas características mais importantes que permitem uma análise preliminar da semelhança. Este trabalho apresenta várias técnicas constantes da literatura, que analisam textura e cor. Algumas dessas técnicas foram implementadas, seus desempenhos foram analisados e comparados e os resultados foram apresentados detalhadamente. Esse comparativo amplo permite determinar as melhores técnicas, possibilita a análise da aplicabilidade de cada uma delas e pode ser utilizada como referência em estudos futuros. As análises quantitativas de desempenho foram realizadas utilizando a métrica ANMRR, definida no padrão MPEG-7, e as matrizes de confusão, apresentadas para cada técnica testada. Dois grupos de testes quantitativos foram realizados: o primeiro utilizando um banco de imagens de texturas em tons de cinza e o segundo utilizando um banco de imagens coloridas. Os resultados dos testes com o banco de texturas em tons de cinza mostraram que as técnicas PBLIRU16, MCNC e sua combinação apresentaram os melhores desempenhos. Para o banco de imagens coloridas, os melhores desempenhos foram observados com a utilização das técnicas SCD, HDCIG e CSD. / Mestre em Ciências

In the novel Alice’s Adventures in Wonderland by Lewis Carroll, Alice, the protagonist, is supposed to be seven years of age. However, the reader can perceive her as older than that and get the impression that she has entered adolescence. Alice vacillates between being a child and striving to act like an adult in her various encounters in Wonderland. In this essay, I will examine Alice’s emotional and intellectual phases in her search for identity, and show the different levels according to developmental theory. Erik Erikson’s, Jean Piaget’s and John Dewey’s research together with other studies form the theoretical framework of this paper. I will demonstrate that while the book does not trace her development as such (i.e. it is not a typical Bildungsroman), it nevertheless highlights a child’s development by juxtaposing different developmental stages. The scientific and realistic functions of developmental theory may at first seem haphazard in the analysis of a literary character in a fantasy world. But, this essay illustrates Carroll’s professional familiarity with his child protagonist through the logic and consistency of his depiction of Alice.  Alice’s adventures in Wonderland reflect the child-adult conflict of Alice on her inner quest for identity. To her the first steps into adulthood, ie. adolescence, include not only psychological growth as in maturity but also physical growth; to grow is to grow up. Her dramatic alterations in size in Wonderland cause great turmoil and confusion as she senses an obligation to adapt her behavior.  Lewis Carroll knew his child protagonist well.

La responsabilité des associés est une notion peu évoquée dans les enseignements du droit des sociétés. Dans les sociétés in bonis, et s’agissant de rapports externes, la responsabilité personnelle des associés pourrait être engagée pour faute détachable. Mais le principe d’un engagement de la responsabilité personnelle des associés, dans les rapports avec des tiers, est contesté, compte tenu du caractère essentiellement interne de leur activité. Dans une procédure collective, la non-responsabilité de la mère des actes de sa filiale, est contestée. Le développement de cette contestation est favorisé grâce à des armes de poursuite efficaces de l’arsenal répressif, des armes à utiliser dans un environnement hautement dérogatoire des procédures collectives. On constate une certaine tendance aggravante de la responsabilité de la mère, notamment dans le domaine social et dans l’environnement. La recherche d’une meilleure protection des victimes, pousse le législateur à légiférer dans des ilots en difficulté, distillant le caractère irréversible des solutions partielles et spécifiques, et forçant de ce fait, le passage vers l’instauration d’une présomption de responsabilité de la mère des actes de sa filiale. Pourtant, un arsenal répressif important et efficace existe, et des pistes permettent d’adoucir la responsabilité de la mère tout en la faisant participer aux difficultés de sa filiale. / The liability of shareholders is a notion not often referred to in coursebook. In in bonis companies, and in the case of external relationships, the shareholder personal liability could be engaged for ‘ fault detachable’. However, the principle of a commitment to personal liability on the part of shareholders in relations with third parties is contested, due to the essentially internal nature of their activity In a collective procedure, the non-liability of the parent company for the acts of their subsidiary is challenged. The development of this challenge is facilitated by powerful weapons of the repressive arsenal, weapons to be used in a highly derogatory environment of collective procedures. There is an aggravating trend in the parent company responsibility, particularly in regard to social and environmental domains. The search for a better protection of the victims pushes the legislator to legislate on isolated problematic issues, distilling the irreversible character of partial and specific solutions, and thus forcing the passage towards the establishment of a presumption of liability of the parent company for the acts of their subsidiary. However, there is a large and effective repressive arsenal, and there are avenues to limit the parent company’s liability while involving them in their subsidiary problems.

The aim of this thesis is comparison of selected classification methods which are logistic regression (binary and multinominal), multilayer perceptron and classification trees, CHAID and CRT. The first part is reminiscent of the theoretical basis of these methods and explains the nature of parameters of the models. The next section applies the above classification methods to the six data sets and then compares the outputs of these methods. Particular emphasis is placed on the discriminatory power rating models, which a separate chapter is devoted to. Rating discriminatory power of the model is based on the overall accuracy, F-measure and size of the area under the ROC curve. The benefit of this work is not only a comparison of selected classification methods based on statistical models evaluating discriminatory power, but also an overview of the strengths and weaknesses of each method.

The diploma thesis deals with machine learning, expert systems, fuzzy logic, genetic algorithms, neural networks and chaos theory, which fall into the category of artificial intelligence. The aim of this work is to describe and implement three different classification methods, according to which the data set will be processed. The GNU Octave software environment was chosen for the data application for licensing reasons. Further evaluate the success of data classification, including visualization. Three different classification methods are used for comparison, so that we can compare the processed data with each other.

Depth of field is a naturally occurring effect in lenses describing the distance between theclosest and furthest object that appears in focus. The effect is commonly used in film andphotography to direct a viewers focus, give a scene more complexity, or to improve aes-thetics. In computer graphics, the same effect is possible, but since there are no naturaloccurrences of lenses in the virtual world, other ways are needed to achieve it. There aremany different approaches to simulate depth of field, but not all are suited for real-time usein computer games. In this thesis, multiple methods are explored and compared to achievedepth of field in real-time with a focus on computer games. The aspect of bokeh is alsocrucial when considering depth of field, so during the thesis, a method to simulate a bokeheffect similar to reality is explored. Three different methods based on the same approachwas implemented to research this subject, and their time and memory complexity weremeasured. A questionnaire was performed to measure the quality of the different meth-ods. The result is three similar methods, but with noticeable differences in both quality andperformance. The results give the reader an overview of different methods and directionsfor implementing it on their own, based on which requirements suits them.

La randomisation mendélienne est une méthode d’instrumentation utilisant des instruments de nature génétique afin d’estimer, via par exemple la régression des moindres carrés en deux étapes, une relation de causalité entre un facteur d’exposition et une réponse lorsque celle-ci est confondue par une ou plusieurs variables de confusion non mesurées. La randomisation mendélienne est en mesure de gérer le biais de confusion à condition que les instruments utilisés soient valides, c’est-à-dire qu’ils respectent trois hypothèses clés. On peut généralement se convaincre que deux des trois hypothèses sont satisfaites alors qu’un phénomène génétique, la pléiotropie, peut parfois rendre la troisième hypothèse invalide. En présence d’invalidité, l’estimation de l’effet causal de l’exposition sur la réponse peut être sévèrement biaisée. Afin d’évaluer la potentielle présence d’invalidité lorsqu’un seul instrument est utilisé, Glymour et al. (2012) ont proposé une méthode qu’on dénomme ici l’approche de la différence simple qui utilise le signe de la différence entre l’estimateur des moindres carrés ordinaires de la réponse sur l’exposition et l’estimateur des moindres carrés en deux étapes calculé à partir de l’instrument pour juger de l’invalidité de l’instrument. Ce mémoire introduit trois méthodes qui s’inspirent de cette approche, mais qui sont applicables à la randomisation mendélienne à instruments multiples. D’abord, on introduit l’approche de la différence globale, une simple généralisation de l’approche de la différence simple au cas des instruments multiples qui a comme objectif de détecter si un ou plusieurs instruments utilisés sont invalides. Ensuite, on introduit les approches des différences individuelles et des différences groupées, deux méthodes qui généralisent les outils de détection de l’invalidité de l’approche de la différence simple afin d’identifier des instruments potentiellement problématiques et proposent une nouvelle estimation de l’effet causal de l’exposition sur la réponse. L’évaluation des méthodes passe par une étude théorique de l’impact de l’invalidité sur la convergence des estimateurs des moindres carrés ordinaires et des moindres carrés en deux étapes et une simulation qui compare la précision des estimateurs résultant des différentes méthodes et leur capacité à détecter l’invalidité des instruments. / Mendelian randomization is an instrumentation method that uses genetic instruments to estimate, via two-stage least squares regression for example, a causal relationship between an exposure and an outcome when the relationship is confounded by one or more unmeasured confounders. Mendelian randomization can handle confounding bias provided that the instruments are valid, i.e., that they meet three key assumptions. While two of the three assumptions can usually be satisfied, the third assumption is often invalidated by a genetic phenomenon called pleiotropy. In the presence of invalid instruments, the estimate of the causal effect of exposure on the outcome may be severely biased. To assess the potential presence of an invalid instrument in single-instrument studies, Glymour et al. (2012) proposed a method, hereinafter referred to as the simple difference approach, which uses the sign of the difference between the ordinary least squares estimator of the outcome on the exposure and the two-stage least squares estimator calculated using the instrument. Based on this approach, we introduce three methods applicable to Mendelian randomization with multiple instruments. The first method is the global difference approach and corresponds to a simple generalization of the simple difference approach to the case of multiple instruments that aims to detect whether one or more instruments are invalid. Next, we introduce the individual differences and the grouped differences approaches, two methods that generalize the simple difference approach to identify potentially invalid instruments and provide new estimates of the causal effect of the exposure on the outcome. The methods are evaluated using a theoretical investigation of the impact that invalid instruments have on the convergence of the ordinary least squares and two-stage least squares estimators as well as with a simulation study that compares the accuracy of the respective estimators and the ability of the corresponding methods to detect invalid instruments.

Organizations gather enormous amounts of data and analyze these data to extract insights that can be useful for them and help them to make better decisions. Predictive data analytics is a crucial subfield within data analytics that make accurate predictions. Predictive data analytics extracts insights from data by using machine learning algorithms. This thesis presents the supervised learning algorithm to perform predicative data analytics in Embedded Test System at the Nordic Engineering Partner company. Predictive Maintenance is a concept that is often used in manufacturing industries which refers to predicting asset failures before they occur. The machine learning algorithms used in this thesis are support vector machines, multi-layer perceptrons, random forests, and gradient boosting. Both binary and multi-class classifier have been provided to fit the models, and cross-validation, sampling techniques, and a confusion matrix have been provided to accurately measure their performance. In addition to accuracy, recall, precision, f1, kappa, mcc, and roc auc measurements are used as well. The prediction models that are fitted achieve high accuracy.

L'association entre l'exposition prolongée aux particules fines (PM2.5) et la mortalité pourrait varier selon les méthodes de contrôle de la confusion. L'objectif était de comparer les estimations de cette association issues d’approches avec différentes méthodes pour le contrôle de la confusion. En utilisant la cohorte du Système de surveillance des maladies chroniques du Québec (SISMACQ), les estimations d'association provenant d’une régression de Cox avec contraste interindividuel et d’une régression conditionnelle logistique stratifiée sur les cas avec contraste intra-individuel ont été comparées. De plus, les estimations d’association de modèles de Cox ajustés pour des variables individuelles et locales, et ajustés seulement pour des variables locales, en utilisant la cohorte Santé et environnement du recensement canadien (CSERcan) pour la province de Québec ont été comparées afin d’évaluer comment les estimations d’association varient avec les variables incluses dans les modèles. Quatre-vingt-dix-huit millions de personées-années du SISMACQ ont été enregistrées. Des augmentations de la mortalité de 3,0% (Intervalles de confiance [IC à 95%] 1,8-4,3) et de 9,3% (IC à 95%] 4,1-14,8) par augmentation de 3,4 µg/m3 ont été observées pour la régression de Cox et la régression logistique, respectivement. Vingt et un millions de personnes-années de la cohorte CSERcan ont été enregistrées. Des augmentations de la mortalité de 2,2% (IC à 95% : 1,9-2,5) et de 0,8% (IC à 95% :0,6-1,0) par 1 µg/m3 ont été observées pour le modèle ajusté pour des variables individuelles et locales, et pour celui ajusté pour des variables locales seulement. Ces résultats confirment l'association entre l'exposition prolongée aux PM2.5 et la mortalité, et suggèrent que les méthodes de contrôle de la confusion peuvent influencer l’importance et la variabilité de ces estimations. / The association between long-term exposure to ambient fine particles (PM2.5) and mortality may vary depending on the methods of confounding control. The objective was to compare estimates of association using approaches varying by their confounding control methods. Using the cohort from the Quebec Integrated Chronic Disease Surveillance System (SISMACQ), association estimates from a Cox proportional hazard model with inter-individual contrast and from a conditional logistic regression with intra-individual contrast were compared. Additionally, results from Cox models adjusted for individual and local confounders, and adjusted only for local confounders using the Canadian Census Health and Environment Cohorts (CSERcan) for the province of Quebec were compared to evaluate how estimates vary when adjusting for individual and contextual confounders compared to adjusting for contextual factors only. For the SISMACQ cohort, 98 million person-years were recorded. Increase in mortality of 3.0% (95% CI: 1.8, 4.3) and of 9.3% (95% CI: 4.1, 14.8) were observed per 3.4 µg/m3 increment in exposure for the Cox model and conditional logistic regression. For the CSERcan cohort, 21 million person-years were recorded. Increase in mortality of 2.2% (95% CI: 1.9, 2.5) and of 0.8% (95% CI: 0.6, 1.0) were observed per 1 µg/m3 increment in exposure for the model adjusted for both local and individual confounders, and for the model adjusted only for local confounders. These results confirm the association between long-term exposure tom PM2.5 and mortality, and suggest that confounding control methods can influence the magnitude and variability of estimates of association.

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