Made available in DSpace on 2014-12-17T15:42:05Z (GMT). No. of bitstreams: 1 CiroJFR_DISSERT.pdf: 5688343 bytes, checksum: f082f764a617b016bd522ef00e0f6125 (MD5) Previous issue date: 2012-08-30 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / Nowadays, the use of chemicals that satisfactorily meet the needs of different sectors of the chemical industry is linked to the consumption of biodegradable materials. In this context, this work contemplated biotechnological aspects with the objective of developing a more environmentally-friendly corrosion inhibitor. In order to achieve this goal, nanoemulsion-type systems (NE) were obtained by varying the amount of Tween 80 (9 to 85 ppm) a sortitan surfactant named polyoxyethylene (20) monooleate. This NE-system was analyzed using phase diagrams in which the percentage of the oil phase (commercial soybean oil, codenamed as OS) was kept constant. By changing the amount of Tween 80, several polar NE-OS derived systems (O/W-type nanoemulsion) were obtained and characterized through light scattering, conductivity and pH, and further subjected to electrochemical studies. The interfacial behavior of these NE-OS derived systems (codenamed NE-OS1, S2, S3, S4 and S5) as corrosion inhibitors on carbon steel AISI 1020 in saline media (NaCl 3.5%) were evaluated by measurement of Open Circuit Potential (OCP), Polarization Curves (Tafel extrapolation method) and Electrochemical Impedance Spectroscopy (EIS). The analyzed NE-OS1 and NE-OS2 systems were found to be mixed inhibitors with quantitative efficacy (98.6% - 99.7%) for concentrations of Tween 80 ranging between 9 and 85 ppm. According to the EIS technique, maximum corrosion efficiency was observed for some tested NE-OS samples. Additionaly to the electrochemical studies, Analysis of Variance (ANOVA) and Principal Component Analysis (PCA) were used, characterization of the nanoemulsion tested systems and adsorption studies, respectively, which confirmed the results observed in the experimental analyses using diluted NE-OS samples in lower concentrations of Tween 80 (0.5 1.75 ppm) / Atualmente, a utiliza??o de produtos qu?micos que atendam satisfatoriamente as necessidades de diferentes setores da ind?stria qu?mica encontra-se vinculada ao consumo de materiais biodegrad?veis. Neste contexto, o presente trabalho foi desenvolvido contemplando aspectos biotecnol?gicos com o objetivo de se desenvolver um inibidor de corros?o menos agressivo ao meio ambiente. Para tanto, uma nanoemuls?o (denominada de NE-OS) foi obtida com Tween 80 (polioxietileno (20) monooleato), ?leo de soja (OS) e ?gua bidestilada. A modifica??o dos percentuais deste tensoativo sorbitano (entre 9 e 85 ppm) foi avaliada em diagramas de fases em que se manteve constante o percentual da fase ?leo, possibilitando a forma??o do sistema NE-OS em diferentes concentra??es. Desta forma, nanoemuls?es (NE-OS1, S2, S3, S4 e S5) polares (do tipo O/A) foram caracterizadas (an?lise de dispers?o de luz, condutividade e pH) e submetidas a estudos eletroqu?micos. O comportamento interfacial destes sistemas nanoemulsionados como inibidores de corros?o na presen?a de a?o-carbono AISI 1020, em meio salino (NaCl 3,5%) foi avaliado pela determina??o do Potencial de Circuito Aberto (OCP), Curvas de Polariza??o (obtidas pela extrapola??o das curvas de Tafel) e Espectroscopia de Imped?ncia Eletroqu?mica (EIE). De acordo com os resultados obtidos pelas an?lises das Curvas de Polariza??o, foi poss?vel caracterizar o sistema NE-OS (e suas varia??es) como inibidores mistos com efici?ncias m?ximas de inibi??es quantitativas (98,6% - 99,7%) para NE-OS1 e NE-OS2 (9 - 85 ppm do tensoativo). No entanto, de acordo com a t?cnica EIE, as efici?ncias m?ximas de inibi??es quantitativas foram observadas para v?rias amostras deste sistema NE-OS. Como ferramentas adicionais aos estudos eletroqu?micos foram realizados quimiom?tricos de An?lise de Vari?ncia (ANOVA) e An?lise de Componentes Principais (PCA), utilizadas, respectivamente, para caracteriza??o das nanoemuls?es e estudo de isotermas de adsor??o, que confirmaram os resultados observados nas investiga??es experimentais em que se utilizaram as nanoemuls?es dilu?das com o tensoativo em concentra??es reduzidas (0,5 1,75 ppm)

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Ce travail concerne les analyses visant à étudier les données où les individus sont structurés en différents groupes (données multi-groupes). La thèse aborde la question des données multi-groupes ayant une structure en un seul tableau, plusieurs tableaux, trois voies et deux blocs (régression). Cette thèse présente plusieurs méthodes d'analyse de données multi-groupes dans le cadre de l'analyse factorielle. Notre travail comporte trois parties. La première partie traite de l'analyse de données multi-groupes (un bloc de variables divisé en sous-groupes d'individus). Le but est soit descriptif (analyse intra-groupes) ou prédictif (analyse discriminante ou analyse inter-groupe). Nous commençons par une description exhaustive des méthodes multi-groupes. En outre, nous proposons deux méthodes : l'Analyse Procrustéenne duale et l'Analyse en Composantes Communes et Poids Spécifiques duale. Nous exposons également de nouvelles propriétés et algorithmes pour l'Analyse en Composantes Principales multi-groupes. La deuxième partie concerne l'analyse multi-blocs et multi-groupes et l'analyse trois voies et multi-groupes. Nous présentons les méthodes existantes. Par ailleurs, nous proposons deux méthodes, l'ACP multi-blocs et multi-groupes et l'ACP multi-blocs et multi-groupes pondérée, vues comme des extensions d'Analyse en Composantes Principales multi-groupes. L'analyse en deux blocs et multi-groupes est prise en compte dans la troisième partie. Tout d'abord, nous présentons des méthodes appropriées pour trouver la relation entre un ensemble de données explicatives et un ensemble de données à expliquer, les deux tableaux présentant une structure de groupe entre les individus. Par la suite, nous proposons quatre méthodes pouvant être vues comme des extensions de la régression PLS au cas multi-groupes, et parmi eux, nous en sélectionnons une et la développons dans une stratégie de régression. Les méthodes proposées sont illustrées sur la base de plusieurs jeux de données réels dans le domaine de la biologie. Toutes les stratégies d'analyse sont programmées sur le logiciel libre R. / This work deals with multi-group analysis, to study multi-group data where individuals are a priori structured into different groups. The thesis tackles the issue of multi-group data in a multivariate, multi-block, three-way and two-block (regression) setting. It presents several methods of multi-group data analysis in the framework of factorial analysis. It includes three sections. The first section concerns the case of multivariate multi-group data. The aim is either descriptive (within-group analysis) or predictive (discriminant analysis, between-group analysis). We start with a comprehensive review of multi-group methods. Furthermore, we propose two methods namely Dual Generalized Procrustes Analysis and Dual Common Component and Specific Weights Analysis. We also exhibit new properties and algorithms for multi-group Principal Component Analysis. The second section deals with multiblock multi-group and three-way multi-group data analysis. We give a general review of multiblock multi-group methods. In addition, we propose two methods, namely multiblock and multi-group PCA and Weighted-multiblock and multi-group PCA, as extensions of multi-group Principal Component Analysis. The two-block multi-group analysis is taken into account in the third section. Firstly, we give a presentation of appropriate methods to investigate the relationship between an explanatory dataset and a dependent dataset where there is a group structure among individuals. Thereafter, we propose four methods, namely multi-group PLS, in the PLS approach, and among them we select one and develop it into a regression strategy. The proposed methods are illustrated on the basis of several real datasets in the field of biology. All the strategies of analysis are implemented within the framework of R.

A análise de dados composicionais está sendo amplamente utilizada nas diversas áreas do conhecimento como por exemplo na análise de sedimentos rochosos, na comparação de diferentes células e até na análise criminalística na comparação de evidências de crimes. Durante a história da análise deste tipo de dados existiram muitos tipos de ajustes utilizados para contornar o problema da soma constante das variáveis e ainda hoje não temos um consenso de qual a melhor solução a ser utilizada. Neste trabalho, temos como objetivo a enunciação das 7 transformações que mais foram utilizadas ao longo do tempo e suas vantagens e desvantagens. A análise de componentes principais foi escolhida para o comparativo destas transformações. Fizemos a aplicação destas transformações em três bancos de dados reais com características diferentes entre si, comparamos os resultados e analisamos qual das transformações apresentou o melhor desempenho em cada base de dados. Os critérios de comparação foram o percentual da variância explicada, as variáveis que foram mais importantes para a primeira componente principal, cargas das variáveis nas componentes principais mais importantes assim como suas correlações com as variáveis. Também, simulamos quatro estruturas de bases de dados composicionais para avaliar o desempenho das transformações. Para essas comparações e simulações, foram desenvolvidas algumas funções, utilizando o \\textit estatístico R, que visam facilitar a comparação entre as sete transformações, assim auxiliando na escolha de qual das transformações melhor se adapta aos dados. Pelos resultados obtidos notamos que: nas bases de dados reais, os resultados das explicações da variância das transformações são similares e as transformações Ref e Alr mostram melhores desempenhos que as demais; nas quatro estruturas simuladas as transformações Ref e Alr também possuem os melhores resultados na explicação da variância e a interpretação de suas componentes principais são parecidas, assim como as transformações Trad, Log e Clr. Com isso notamos que independentemente da aplicação do logaritmo nas transformações Alr e Log elas apresentaram resultados muitos similares às transformações Ref e Trad, respectivamente, tanto na explicação da variância como na interpretação das componentes principais. / The compositional data analysis is being widely used in several areas of knowledge such as the analysis of rocky sediments, to compare different biological cells and even in forensic analysis to compare crimes evidences. During the history of the analysis of such data, to circumvent the problem of variable\'s constant sum were used many types of adjustments. Until now, we do not have a consensus in which is the best solution to be used in this cases. In this paper, we aim to enunciate seven transformations that most were used over time and their advantages and disadvantages. The principal component analysis was chosen for the comparison of these transformations. We applied this transformations in three real databases with different characteristics, we hope to compare the results and analyze which transformation have the best performance in each database. The comparison criteria were the percentage of explained variance, the variables that were most important to the first principal component,variable\'s loads in the most important principal components as well their correlation with the variables. We also simulated four compositional data bases structures to evaluate the performance of the transformations. For these comparisons and simulations were developed some functions, using the statistical software R, to facilitate comparison between the seven transformations, thus assisting in choosing which of the best transformation fits to the data. From the results we note that: for the real databases, the results of the variance explanation of all transformations are similar, thus Ref and Alr transformations show better performances than the others; in the four simulated structures the Ref and Alr transformations also have the best results in the variance explanation and interpretation of its main components are similar, as well as the transformations Trad, Log and Clr. Thus we note that independently of applying logarithm in and Log and Alr transformations they present very similar results as Ref and Trad transformations, respectively, both in variance explanation and in the interpretation of the principal components.

CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior / Neste trabalho, à discutido o problema de reconhecimento de objetos utilizando imagens extraÃdas de um sensor industrial 3D. NÃs nos concentramos em 9 extratores de caracterÃsticas, dos quais 7 sÃo baseados nos momentos invariantes (Hu, Zernike, Legendre, Fourier-Mellin, Tchebichef, Bessel-Fourier e Gaussian-Hermite), um outro à baseado na Transformada de Hough e o Ãltimo na anÃlise de componentes independentes, e, 4 classificadores, Naive Bayes, k-Vizinhos mais PrÃximos, MÃquina de Vetor de Suporte e Rede Neural Artificial-Perceptron Multi-Camadas. Para a escolha do melhor extrator de caracterÃsticas, foram comparados os seus desempenhos de classificaÃÃo em termos de taxa de acerto e de tempo de extraÃÃo, atravÃs do classificador k-Vizinhos mais PrÃximos utilizando distÃncia euclidiana. O extrator de caracterÃsticas baseado nos momentos de Zernike obteve as melhores taxas de acerto, 98.00%, e tempo relativamente baixo de extraÃÃo de caracterÃsticas, 0.3910 segundos. Os dados gerados a partir deste, foram apresentados a diferentes heurÃsticas de classificaÃÃo. Dentre os classificadores testados, o classificador k-Vizinhos mais PrÃximos, obteve a melhor taxa mÃdia de acerto, 98.00% e, tempo mÃdio de classificaÃÃo relativamente baixo, 0.0040 segundos, tornando-se o classificador mais adequado para a aplicaÃÃo deste estudo. / In this work, the problem of recognition of objects using images extracted from a 3D industrial sensor is discussed. We focus in 9 feature extractors (where seven are based on invariant moments -Hu, Zernike, Legendre, Fourier-Mellin, Tchebichef, BesselâFourier and Gaussian-Hermite-, another is based on the Hough transform and the last one on independent component analysis), and 4 classifiers (Naive Bayes, k-Nearest Neighbor, Support Vector machines and Artificial Neural Network-Multi-Layer Perceptron). To choose the best feature extractor, their performance was compared in terms of classification accuracy rate and extraction time by the k-nearest neighbors classifier using euclidean distance. The feature extractor based on Zernike moments, got the best hit rates, 98.00 %, and relatively low time feature extraction, 0.3910 seconds. The data generated from this, were presented to different heuristic classification. Among the tested classifiers, the k-nearest neighbors classifier achieved the highest average hit rate, 98.00%, and average time of relatively low rank, 0.0040 seconds, thus making it the most suitable classifier for the implementation of this study.

Um Sistema Elétrico de Potência (SEP) está susceptível à presença de diversas fontes de distúrbios que prejudicam a Qualidade da Energia Elétrica (QEE). Desta forma, as suas tensões e/ou correntes podem conter m´múltiplos distúrbios com ocorrência simultânea. Este trabalho apresenta uma metodologia para decomposição do sinal medido em componentes que estimem as formas de onda dos distúrbios individuais quando da ocorrência de m´múltiplos distúrbios, com o posterior reconhecimento de cada um deles. A Análise de Componentes Independentes (ICA) é utilizada como principal ferramenta na etapa de decomposição dos distúrbios. A ICA é originalmente uma t´técnica aplicada em análise multivariada de dados, o que significa que ela necessita de medições realizadas por múltiplos sensores dispostos em diferentes posições de um sistema. No entanto, este trabalho propõe a sua aplicação tendo disponível apenas um sinal medido. Para tanto, são propostos dois métodos para produzir a diversidade necessária para a t´técnica funcionar adequadamente. É demonstrado que ambos os métodos equivalem a um banco de filtros lineares adaptativos capaz de realizar a separação não-supervisionada de múltiplos distúrbios independentes e que sejam espectralmente disjuntos. Por fim, é proposto um sistema de classificação que utiliza Redes Neurais Artificiais (RNAs) para identificar os distúrbios decompostos pela etapa anterior. A metodologia completa é avaliada por meio de testes utilizando dados sintéticos e reais, alcançando resultados altamente satisfatórios para decomposição de sinais contendo múltiplos distúrbios e taxas de acerto globais dos classificadores superiores a 97% / The power system is susceptible to the presence of several sources of disturbances that harm the power quality. In this sense, its voltages and/or currents may contain multiple disturbances with simultaneous occurrence. This work presents a methodology that decomposes the measured signal in components which estimate the waveforms of the individual disturbances followed by their recognition when a multiple disturbance situation occurs. The Independent Component Analysis (ICA) is the main tool in the disturbance decomposition stage. The ICA is originally a technique applied in multivariate data analysis, which means that it requires measurements from multiple sensors allocated in different positions of the system. However, this work proposes its application for a single measured signal available. For this, two methods were developed in order to provide the required diversity to the ICA technique. It is demonstrated that both methods are equivalent to an adaptive linear filter bank capable to perform an unsupervised separation of multiple independent disturbances, if they are spectrally disjoint. A classification system based on artificial neural networks is proposed to identify the disturbances decomposed by the previous stage. The complete system is tested using synthetic and actual data, presenting highly satisfactory results for the decomposition of signals containing multiple disturbances, and precision for the classification task above 97%

A Política Nacional do Meio Ambiente visa compatibilizar o desenvolvimento socioeconômico com a qualidade ambiental. A Avaliação de Impacto Ambiental, um de seus instrumentos, utiliza-se do Estudo de Impacto Ambiental (EIA) na sua aplicação em projetos ou empreendimentos. A elaboração do EIA envolve a etapa de diagnóstico para análise da qualidade ambiental da área. A qualidade do EIA e do diagnóstico tem sido objeto de críticas e descrédito junto à sociedade, principalmente à comunidade científica e às associações ambientalistas. Sabe-se que a qualidade do diagnóstico influencia diretamente a efetividade processual do EIA e seu papel como influenciador da tomada de decisão; assim, uma avaliação da qualidade dessa etapa do EIA contribui com a aplicação mais efetiva desse instrumento. A pesquisa visou avaliar a qualidade do diagnóstico biótico dos EIAs do Estado de São Paulo elaborados entre 2005 e 2014. Para isso, proposições ao diagnóstico biótico foram reunidas em uma lista de verificação, utilizada para a avaliação de 55 diagnósticos bióticos e 35 termos de referência de EIAs. Os resultados foram analisados qualitativamente e em comparação com as recomendações dos termos de referência (TRs) analisados. Posteriormente, a qualidade dos diagnósticos foi analisada sob três perspectivas: aprovação dos estudos, tipo de empreendimento e ano de elaboração do EIA. Por fim, foi realizada análise de componentes principais não-linear (NLPCA) para os dados de diagnóstico, no intuito de testar a sugestão de aplicação dessa ferramenta para a identificação dos critérios determinantes para a qualidade dos diagnósticos e possíveis relações entre esses critérios e entre os estudos. A qualidade dos diagnósticos bióticos analisados foi mais satisfatória para aspectos descritivos do que analíticos. Foram determinantes para a qualidade dos estudos critérios relativos à coleta de dados quantitativos e levantamentos para espécies raras, segundo a NLPCA. Tempo de levantamento e sazonalidade foram considerados insatisfatórios, e apresentaram relação estatística com a identificação do grau de vulnerabilidade da área. Os resultados realçaram a importância da sistematização de dados de biodiversidade em fontes confiáveis e atualizadas para elaboração e análise de diagnósticos, e para TRs mais específicos, uma vez que, apesar de estarem sendo cumpridos pelos estudos, os TRs são genéricos e apresentam mais recomendações descritivas do que analíticas. Não houve diferença representativa entre a qualidade dos diagnósticos referentes a estudos aprovados e não aprovados, o setor de Obras Hidráulicas apresentou avaliações mais satisfatórias, o que foi salientado pela NLPCA e pode estar relacionado ao porte do projeto, e a análise temporal evidenciou uma tendência de melhora dos estudos e TRs. Tanto a lista de verificação quanto a NLPCA se mostraram ferramentas adequadas para a investigação da qualidade de diagnósticos biológicos de EIA / The Brazilian National Environmental Policy established Environmental Impact Assessment (EIA) as one of the 13 tools to reconcile socio-economic development with environmental quality. EIA involves the Environmental Impact Statements (EIS) in its application to development projects. EIS drafting involves a baseline step for analysis of environmental quality of the area. The quality of the EIS and the baseline process has been criticized by society, especially by scientific community and environmental groups, and this quality directly influences the effectiveness of the EIA procedure and its role as a decision making tool. Thus, an evaluation of the quality of this EIS step contributes to a more effective application of this instrument. The research aimed to evaluate the quality of biotic baseline studies of EIS drawn up between 2005 and 2014 in the state of São Paulo. We assessed 55 biotic baseline studies and 35 terms of reference (TRs) of EISs by a checklist which consists of a set of recommendations from literature and regulations to biotic baseline studies. The results of baseline and TRs were analyzed qualitatively and compared to one another. Then, we looked at the baseline quality under three approaches: license emission, sector and project type of activity, and year of EIS preparation. Finally, multivariate analysis was performed by Nonlinear Principal Component Analysis (NLPCA) for the baseline quality data in order to test the application of this analysis for the identification of critical and determinant criteria for the quality of baseline and the investigation of how these criteria and the EISs are related to one another. Results point to more satisfactory descriptive than analytical issues. Criteria of quantitative data collecting and surveys of rare species were determinants for baseline quality. Time of survey and seasonality was an unsatisfactory criterion, and statistically related to the vulnerability degree of the area. Results highlighted the importance of systematization of biodiversity data in reliable and updated sources useful for EISs preparation and analysis and for the draft of TRs in a more specific way. TRs were satisfactorily complied by the baseline content, but they are generic and present more descriptive than analytical recommendations. There was no representative difference between the quality of baseline of approved and not approved EISs. Hydraulic project showed more satisfactory evaluations, emphasized by NLPCA, and it may be related to the size of the project. Temporal analysis highlighted an improvement trend of studies and TRs. Thus, both the checklist as NLPCA proved to be suitable tools to the assessment of biological baseline studies of EIS

La recherche développée dans le cadre de cette thèse aborde différents aspects relevant de l’analyse statistique de données. Dans un premier temps, une analyse de trois indices d’associations entre deux tableaux de données est développée. Par la suite, des stratégies d’analyse liées à la standardisation de tableaux de données avec des applications en analyse en composantes principales (ACP) et en régression, notamment la régression PLS sont présentées. La première stratégie consiste à proposer une standardisation continuum des variables. Une standardisation plus générale est aussi abordée consistant à réduire de manière graduelle non seulement les variances des variables mais également les corrélations entre ces variables. De là, une approche continuum de régression a été élaborée regroupant l’analyse des redondances et la régression PLS. Par ailleurs, cette dernière standardisation a inspiré une démarche de régression biaisée dans le cadre de régression linéaire multiple. Les propriétés d’une telle démarche sont étudiées et les résultats sont comparés à ceux de la régression Ridge. Dans le cadre de l’analyse de plusieurs tableaux de données, une extension de la méthode ComDim pour la situation de K+1 tableaux est développée. Les propriétés de cette méthode, appelée P-ComDim, sont étudiées et comparées à celles de Multiblock PLS. Enfin, la situation où il s’agit d’évaluer l’effet de plusieurs facteurs sur des données multivariées est considérée et une nouvelle stratégie d’analyse est proposée. / The research developed in this thesis deals with several statistical aspects for analyzing datasets. Firstly, investigations of the properties of several association indices commonly used by practitioners are undergone. Secondly, different strategies related to the standardization of the datasets with application to principal component analysis (PCA) and regression, especially PLS-regression were developed. The first strategy consists of a continuum standardization of the variables. The interest of such standardization in PCA and PLS-regression is emphasized.A more general standardization is also discussed which consists in reducing gradually not only the variances of the variables but also their correlations. Thereafter, a continuum approach was developed combining Redundancy Analysis and PLS-regression. Moreover, this new standardization inspired a biased regression model in multiple linear regression. Properties related to this approach are studied and the results are compared on the basis of case studies with those of Ridge regression. In the context of the analysis of several datasets in an exploratory perspective, the method called ComDim, has certainly raised interest among practitioners. An extension of this method for the analysis of K+1 datasets was developed. Properties related to this method, called P-ComDim, are studied and compared to Multiblock PLS. Finally, for the analysis of datasets depending on several factors, a new approach based on PLS regression is proposed.

La thématique générale des travaux de la thèse porte sur l’utilisation des Technologies de l’information et de la communication afin de promouvoir l’activité physique et limiter les troubles dus à la sédentarité. Ils s’inscrivent dans le cadre d’un projet qui vise à développer une solution d’évaluation de la motricité des sujets humains à faible coût, en utilisant des capteurs inertiels embarqués. L’objectif du présent travail de thèse est d’évaluer les capacités posturales au travers deux exercices de Yoga. En premier lieu, nous avons validé l’utilisation des dispositifs BodyTrack, par rapport à un système de référence (Plateforme de force), dans le cadre de l’évaluation des oscillations posturales. Ensuite, une méthodologie est proposée afin d’évaluer la performance motrice selon 3 facteurs. Le premier considère le maintien de l’équilibre postural lors des phases statique des deux exercices. Le deuxième facteur évalue la durée de ces phases statiques et le troisième permet de vérifier la bonne exécution de la posture. L’ensemble des facteurs mesurés permet de construire une vue d’ensemble de l’exercice effectué et rend compte de la performance motrice. / Balance is a key element for daily activities, that’s making balance training, is important for ev eryone. In the aim of promoting physical activity and changing exercise behaviour, BodyScoring’s balance application, using an inexpensive mobile device provided with accelerometers, gyroscope and magnetometer, proposes tow Yoga exercises (‘Tadasana and Vrksasana’), for balance improvement, an d calculates a score to determine the level skills and share it with friends. First, this thesis examines th e validity, reliability and the sensitivity of accelerometer data by comparing them to force platform data. Second, a postural scoring system is developed. Based on three key factors, it allows evaluating the postural performance, the duration and the appropriate execution of the exercise. The graphical re presentation of the score has allowed a straightforward and simple interpretation of results.

Cette thèse développe des méthodes de diagonalisation conjointe de matrices et de tenseurs d’ordre trois, et son application à la séparation MIMO de sources de télécommunications numériques. Après un état, les motivations et objectifs de la thèse sont présentés. Les problèmes de la diagonalisation conjointe et de la séparation de sources sont définis et un lien entre ces deux domaines est établi. Par la suite, plusieurs algorithmes itératifs de type Jacobi reposant sur une paramétrisation LU sont développés. Pour chacun des algorithmes, on propose de déterminer les matrices permettant de diagonaliser l’ensemble considéré par l’optimisation d’un critère inverse. On envisage la minimisation du critère selon deux approches : la première, de manière directe, et la seconde, en supposant que les éléments de l’ensemble considéré sont quasiment diagonaux. En ce qui concerne l’estimation des différents paramètres du problème, deux stratégies sont mises en œuvre : l’une consistant à estimer tous les paramètres indépendamment et l’autre reposant sur l’estimation indépendante de couples de paramètres spécifiquement choisis. Ainsi, nous proposons trois algorithmes pour la diagonalisation conjointe de matrices complexes symétriques ou hermitiennes et deux algorithmes pour la diagonalisation conjointe d’ensembles de tenseurs symétriques ou non-symétriques ou admettant une décomposition INDSCAL. Nous montrons aussi le lien existant entre la diagonalisation conjointe de tenseurs d’ordre trois et la décomposition canonique polyadique d’un tenseur d’ordre quatre, puis nous comparons les algorithmes développés à différentes méthodes de la littérature. Le bon comportement des algorithmes proposés est illustré au moyen de simulations numériques. Puis, ils sont validés dans le cadre de la séparation de sources de télécommunications numériques. / This thesis develops joint diagonalization of matrices and third-order tensors methods for MIMO source separation in the field of digital telecommunications. After a state of the art, the motivations and the objectives are presented. Then the joint diagonalisation and the blind source separation issues are defined and a link between both fields is established. Thereafter, five Jacobi-like iterative algorithms based on an LU parameterization are developed. For each of them, we propose to derive the diagonalization matrix by optimizing an inverse criterion. Two ways are investigated : minimizing the criterion in a direct way or assuming that the elements from the considered set are almost diagonal. Regarding the parameters derivation, two strategies are implemented : one consists in estimating each parameter independently, the other consists in the independent derivation of couple of well-chosen parameters. Hence, we propose three algorithms for the joint diagonalization of symmetric complex matrices or hermitian ones. The first one relies on searching for the roots of the criterion derivative, the second one relies on a minor eigenvector research and the last one relies on a gradient descent method enhanced by computation of the optimal adaptation step. In the framework of joint diagonalization of symmetric, INDSCAL or non symmetric third-order tensors, we have developed two algorithms. For each of them, the parameters derivation is done by computing the roots of the considered criterion derivative. We also show the link between the joint diagonalization of a third-order tensor set and the canonical polyadic decomposition of a fourth-order tensor. We confront both methods through numerical simulations. The good behavior of the proposed algorithms is illustrated by means of computing simulations. Finally, they are applied to the source separation of digital telecommunication signals.