Orientador: Suely Cunha Amaro Mantovani / Resumo: No estudo dos manipuladores são utilizados os conceitos da cinemática direta e a inversa. No cálculo da cinemática direta tem-se a facilidade da notação de Denavit-Hartenberg, mas o desafio maior é a resolução da cinemática inversa, que se torna mais complexa conforme aumentam os graus de liberdade do manipulador, além de apresentar múltiplas soluções. As variáveis angulares obtidas pelas equações da cinemática inversa são utilizadas pelo controlador, para posicionar o órgão terminal do manipulador em um ponto específico de seu volume de trabalho. Na busca de alternativas para contornar estes problemas, neste trabalho utilizam-se os Modelos Adaptativos de Inferência Neuro-Fuzzy - ANFIS para a resolução da cinemática inversa, por meio de simulações, para obter o posicionamento de um manipulador robótico de 5 graus de liberdade, composto por sete servomotores controlados pela plataforma de desenvolvimento Intel® Galileo Gen 2, usado como caso de estudo. Nas simulações usamse ANFIS com uma arquitetura com três e quatro funções de pertinência de entrada, do tipo gaussiana. O desempenho da arquitetura da ANFIS implementada foi comparado com uma Rede Perceptron Multicamadas, demonstrando com os resultados favoráveis a ANFIS, a sua capacidade de aprender e resolver com baixo erro quadrático médio e com precisão, a cinemática inversa para o manipulador em estudo. Verifica-se também, que a performance das ANFIS melhora, quanto à precisão dos resultados, demonstrado pelo desvio médio d... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In the study of manipulator’s, the concepts of direct and inverse kinematics are used. In the computation of forward kinematics, it has of the ease of Denavit-Hartenberg notation, but the biggest challenge is the resolution of the inverse kinematics, which becomes more complex as the manipulator's degrees of freedom increase, besides presenting multiple solutions. The angular variables obtained by the inverse kinematics equations are used by the controller to position the terminal organ of the manipulator at a specific point in its work volume. In the search for alternatives to overcome these problems, in this work, the Adaptive Neuro-Fuzzy Inference Models (ANFIS) are used to solve the inverse kinematics, by means of simulations, to obtain the positioning of a robot manipulator of 5 degrees of freedom, consisting of seven servomotors controlled by the Intel® Galileo Gen 2 development platform, used as a case's study . In the simulations ANFIS's architecture are used three and four Gaussian membership functions of input. The performance of the implemented ANFIS architecture was compared to a Multi-layered Perceptron Network, demonstrating with the favorable results the ANFIS, its ability to learn and solve with low mean square error and with precision, the inverse kinematics for the manipulator under study. It is also verified that the performance of the ANFIS improves, as regards the accuracy of the results in the training process, , demonstrated by the mean deviation of the... (Complete abstract click electronic access below) / Mestre

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Des troubles moteurs ont été décrits dans les Troubles du Spectre Autistiques (TSA), toutefois tous les enfants atteints de TSA ne montrent pas de diminution des performances motrices. La nature et l'origine des perturbations motrices dans les TSA ne sont pas claires. Les processus neuro-développementaux, en lien avec la maturation du système nerveux central, sont peu explorés dans les TSA, or ces processus sous-tendent les performances motrices. Peu d'études portent sur l'analyse fine de la sémiologie des fonctions neuro-psychomotrices dans les TSA et l'existence d'une trajectoire neuro-développementale de ces fonctions n'est pas connue chez les enfants avec TSA. L'objectif de cette étude est de mettre en évidence la sémiologie des troubles psychomoteurs auprès d'enfants avec TSA, à l'aide d'une batterie standardisée Française d'évaluation développementale des fonctions neuro-psychomotrices de l'enfant (NP-MOT) (Vaivre-Douret, 2006). L'évaluation neuro-psychomotrice complète les évaluations de premières instances (psychiatrique; psychologique; compréhension; psychomotrice). L'identification d'un profil clinique neuro-psychomoteur, l'identification de troubles ou décalages par rapport à une norme de référence, la mise en évidence de fonctions cérébrales éventuellement touchées dans les TSA devraient permettre de mieux comprendre l'origine et la nature des troubles observés dans les TSA. Les résultats de plus en plus nombreux concernant la motricité chez ces enfants doivent pouvoir également être analysés au regard des évaluations cognitives et neuro-cognitives, afin d'affiner le profil de développement et permettre ainsi de mieux comprendre la nature des troubles autistiques parmi une comorbidité d'éventuels autres dysfonctionnements. / Motor disorders have been described in the Autistic Spectrum Disorders (ASD), however all children with ASD show no decrease in motor performances. The nature and origin of motor disturbances in ASD are unclear. Neurodevelopmental processes linked to the maturation of the central nervous system, are not really explored in ASD, but these processes underlie motor performances. Few studies trat of an acute semiology of motor abnormalities in ASD and the existence of a neuro-developmental trajectory of neuro-psychomotor functions is not known in children with ASD. The aim of this study is to highlight the semiology of psychomotor disorders among children with ASD, using a French standardized neurodevelopmental assessment tool (NP-MOT) (Vaivre-Douret, 2006). Evaluations of the first instances (psychiatric; psychological; understanding; psychomotor) were supplemented by a standardized assessment battery of neuro-developmental psychomotor functions (NP-MOT). The identification of a neuro-psychomotor clinical profile, identification of problems or discrepancies compared to a standard reference, the identification of potentially affected brain functions in ASD should provide a better understanding of the origin and nature the observed disorders in ASD. The results, more and more numerous concerning motor skills in these children, should be able to be analyzed in light of cognitive or neuro-cognitive assessments and should allow to refine the profile of development and thereby enable a better understanding of the nature of autism among a comorbidity other possible malfunctions.

[pt] Neste trabalho foram desenvolvidos e avaliados métodos com o objetivo de melhorar e acelerar o processo de aprendizado do modelo de Reinforcement Learning Neuro-Fuzzy Hierárquico Politree (RL-NFHP). Este modelo pode ser utilizado para dotar um agente de inteligência através de processo de Aprendizado por Reforço (Reinforcement Learning). O modelo RL-NFHP apresenta as seguintes características: aprendizado automático da estrutura do modelo; auto-ajuste dos parâmetros associados à estrutura; capacidade de aprendizado da ação a ser adotada quando o agente está em um determinado estado do ambiente; possibilidade de lidar com um número maior de entradas do que os sistemas neuro-fuzzy tradicionais; e geração de regras linguísticas com hierarquia. Com intenção de melhorar e acelerar o processo de aprendizado do modelo foram implementadas seis políticas de seleção, sendo uma delas uma inovação deste trabalho (Q-DC-roulette); implementado o método early stopping para determinação automática do fim do treinamento; desenvolvido o eligibility trace cumulativo; criado um método de poda da estrutura, para eliminação de células desnecessárias; além da reescrita do código computacional original. O modelo RL-NFHP modificado foi avaliado em três aplicações: o benchmark Carro na Montanha simulado, conhecido na área de agentes autônomos; uma simulação robótica baseada no robô Khepera; e uma num robô real NXT. Os testes efetuados demonstram que este modelo modificado se ajustou bem a problemas de sistemas de controle e robótica, apresentando boa generalização. Comparado o modelo RL-NFHP modificado com o original, houve aceleração do aprendizado e obtenção de menores modelos treinados. / [en] In this work, methods were developed and evaluated in order to improve and accelerate the learning process of Reinforcement Learning Neuro-Fuzzy Hierarchical Politree Model (RL-NFHP). This model is employed to provide an agent with intelligence, making it autonomous, due to the capacity of ratiocinate (infer actions) and learning, acquired knowledge through interaction with the environment by Reinforcement Learning process. The RL-NFHP model has the following features: automatic learning of structure of the model; self-adjustment of parameters associated with its structure, ability to learn the action to be taken when the agent is in a particular state of the environment; ability to handle a larger number of inputs than the traditional neuro-fuzzy systems; and generation of rules with linguistic interpretable hierarchy. With the aim to improve and accelerate the learning process of the model, six selection action policies were developed, one of them an innovation of this work (Q-DC-roulette); implemented the early stopping method for automatically determining the end of the training; developed a cumulative eligibility trace; created a method of pruning the structure, for removing unnecessary cells; in addition to rewriting the original computer code. The modified RL-NFHP model was evaluated in three applications: the simulated benchmark Car-Mountain problem, well known in the area of autonomous agents; a simulated application in robotics based on the Khepera robot; and an application in a real robot. The experiments show that this modified model fits well the problems of control systems and robotics, with a good generalization. Compared the modified RL-NFHP model with the original one, there was acceleration of learning process and smaller structures of the model trained.

This work describes a procedure for a soft sensor design to predict the top composition of a methanol-water distillation column. Soft sensor is a mathematical model that is used to estimate variables of interest from secondary variables easy to measure. This technique comes from an operational difficulty or high cost obtaining the desired variable. The approach to build a soft sensor was an artificial intelligence modeling, a black-box type, using a hybrid neuro-fuzzy technique. The data acquisition to train and validate the soft sensor comes from a mathematical model validated from pilot plat data. One of the limitations of neuro-fuzzy system is that it works with a limited number of inputs, depending on the combinatorial explosion of fuzzy rules. To minimize these effects and to reduce the number of rules in the training data sets of virtual analyzer, a data clustering technique called substractive clustering was used. To obtain a better performance of soft sensor for the dynamic process, distillation column, a regression of lone sampling time in selected variables was used, changing the number of entries from 9 to 18 variables, nine variables at actual sampling time and nine variables at previous sampling time. The distillation column is a good process for the present study because composition measurements are the main objective of this process and are difficult to obtain. The computational strategy for a soft sensor design produced good results in estimating the top composition of the methanol-water distillation column. / Este trabalho descreve um procedimento para o desenvolvimento de um analisador virtual, para predição da composição de topo de uma coluna destilação metanol-água em uma planta piloto. Analisador virtual é um modelo matemático que é usado para estimar variáveis de interesse a partir de variáveis secundárias de fácil medição. Esta tecnologia surge de uma real dificuldade operacional ou do alto custo de obtenção da variável desejada. O modelo utilizado nesta abordagem de construção do analisador virtual utiliza técnicas de sistemas inteligentes, tipo caixa preta, através da técnica híbrida neuro-fuzzy. A aquisição dos dados para treinar e validar o analisador virtual foi feita através de um modelo matemático validado a partir de dados experimentais da planta piloto. Uma das limitações do sistema neuro-fuzzy é que ele trabalha com um número limitado de entradas, dependendo da explosão combinatória das regras fuzzy. Para minimizar estes efeitos e conseguir reduzir o número de regras nos conjuntos de treinamento da rede neuro-fuzzy, foi utilizada a técnica de agrupamento de dados, denominada agrupamento substrativo. Com a intenção de se obter um melhor desempenho do analisador virtual no processo dinâmico, que é a coluna de destilação, foi empregada uma regressão de um tempo de amostragem nas variáveis de entrada selecionadas, alterando o número de entradas de 9 para 18, sendo 9 variáveis no tempo de amostragem atual e 9 variáveis em um tempo de amostragem anterior. O processo de destilação mostrou-se adequado para o presente estudo, pois as medições de composições são de difíceis obtenções. A estratégia computacional para um projeto de analisador virtual produziu bons resultados, de forma a estimar a composição do topo da coluna de destilação binária metanol-água.

[pt] A presente pesquisa busca evidenciar uma atitude diante do conhecimento desenvolvido na rede pública, em seu Ensino Médio, na cidade do Rio de Janeiro / RJ. Instala-se como atividade complementar pedagógica, através de dinâmicas arte-terapêuticas, com o enfoque do Neuro-Design, integrando o Design Social. Esse novo segmento, o Neuro-Design, visa demonstrar de modo lúdico, a plasticidade cerebral como a capacidade do sistema nervoso para alterar o funcionamento do sistema motor e perceptivo baseado em mudanças do ambiente, através da conexão e (re)aconexão das sinapses nervosas, organizando e (re) organizando as informações dos estímulos motores e sensitivos. (Relvas, 2005:69-70) 1. Entre outros, são utilizados como canais, elementos biológicos como o bambu e as flores, além de nosso próprio corpo, pela linguagem da música e da dança. / [en] This investigation aims at evidencing na attitude facing the knowledge developed in the Public School System, within the Middle School, in the city of Rio de Janeiro, a Pedagogical complementary activity via the use of dynamic arttherapies, such as the emphasis on Neuro-Design integrating Social Design. Such new segment - The Neuro Design, aims at demonstrating, in a playful manner, the cerebral plasticity as a capacity of the Nervous System to alter functioning of both motor and perception systems, based on changes to the environment trough connection and (re)connection of the nervous synapses, thereby organizing and (re)organizing the information of motor and sensitive stimuli. (Relvas, 2005: 69-70) 1. Among other, used as channels, the biological elements, such as bamboo and flowers, by the language of music and dance.

Le syndrome du défilé thoracique se définit par la compression du plexus brachial et/ou des vaisseaux subclaviers, à leur traversée dans l'étroit passage constitué par le défilé inter-scalénique - entre les muscles scalènes, l’espace costo-claviculaire et l'espace rétro-pectoral - pour atteindre le creux axillaire. Les symptômes peuvent être à prédominance artérielle, veineuse et/ou neurologique selon la structure impliquée. Malheureusement, le syndrome du défilé thoracique demeure controversé par son manque de critères diagnostiques acceptables. De ce fait, les tests orthopédiques utilisés pour diagnostiquer ce syndrome sont régulièrement remis en question. Ce mémoire de recherche vise à répondre à la problématique majeure entourant le syndrome du défilé thoracique : « Est-ce que les tests orthopédiques utilisés en clinique pour diagnostiquer ce syndrome sont valides ? » Au préalable, nous chercherons à identifier la qualité des articles pertinents sur le sujet à travers une revue de la littérature diagnostique. Ensuite, la validité des tests orthopédiques sera vérifiée à l’aide d’un appareil à échographie doppler lors d’une étude clinique. Les retombées de ce projet de recherche sont multiples pour les cliniciens. Tout d’abord, il pourra aider à clarifier ce syndrome controversé tout en offrant une meilleure connaissance de la qualité des articles publiés jusqu’à présent sur le sujet. Enfin, les résultats de l’étude clinique sur la validité des tests orthopédiques permettront d’améliorer l’utilisation des tests par le clinicien et ainsi, l’aider à poser un meilleur diagnostic. / Thoracic outlet syndrome (TOS) is defined as a neurovascular syndrome associated with compression of the brachial bundle (brachial plexus and/or subclavian vessels). Patients may have a compression of one structure or a combination of neurovascular symptoms, which can complicate the diagnosis. Based on the clinical presentation, the clinician often performs selected provocative tests to identify a site of compression of the brachial bundle specific to a type of TOS to confirm the syndrome and propose a management plan. However, due to the lack of accepted criteria for the diagnosis of TOS, test results may be unable to confirm or rule out the presence of the syndrome. This has important implications for the generalization of results relating to test performance. The purpose of this thesis was to establish the validity of orthopedic tests commonly used to diagnose a thoracic outlet syndrome. A systematic literature review was first conducted on the subject. Afterward, a clinical research on the accuracy of commonly used orthopedic tests used in practice was done using an echography Doppler machine. A better understanding of the validity of these tests should improve the clinical diagnosis and help define a clear plan of management. The advantages offered by this research project are multiple for clinicians, the study provides a better understanding of this controversial syndrome, knowledge on the quality of the research done up until now and lastly, clinicians have a better understanding of the validity of TOS orthopedic tests in an objective to help improve its diagnosis.

[pt] Este trabalho apresenta procedimentos de modelagem e controle neuro-fuzzy de sistemas dinâmicos. Neste contexto, é proposta e avaliada a utilização simultânea da abordagem neuro-fuzzy em todo o sistema de malha fechada controlador-planta.Na modelagem da planta, o espaço de entrada do sistema dinâmico é inicialmente dividido em um número de regiões de operação fuzzy onde modelos de ordem reduzida (ARMAX) representam o comportamento do sistema dinâmico. A saída completa do sistema - modelo global - é obtida através da conjunção das saídas dos modelos locais usando uma rede neuro-fuzzy.No controle da planta, é proposto um novo controlador neuro-fuzzy chamado Controlador Neuro-fuzzy de Coeficientes Variáveis (CNFCV), que tem como objetivos melhorar a robustez do sistema de controle a perturbações e a geração automática da variável manipulada, que é uma dificuldade normalmente encontrada em controladores neurais ou neuro-fuzzy. Esse controlador é originado dos modelos de redes neurais de Mellem (1997) e Velloso (1999), e utiliza redes neuro-fuzzy para a geração dos coeficientes variáveis de um modelo ARMA da variável manipulada. Apesar de juntar modelos de séries temporais com a abordagem neuro-fuzzy, o CNFCV tem como função não a previsão, mas sim o controle de uma planta ou processo.Para avaliar o desempenho do CNFCV são utilizados, como meios de comparação,controladores neuro- fuzzy conhecidos - FALCON-H Fuzzy Adaptive Learning Control Network with Hybrid Learning e NEFCON Neuro-Fuzzy Controller - e o tradicional controlador PID Proporcional- Integral-Derivativo.As plantas utilizadas são uma planta linear Bobinador, uma planta linearizada Pêndulo Invertido e uma planta não linear %CO2. A escolha de tais plantas deve-se ao fato de serem utilizadas e modeladas em aplicações práticas e em trabalhos acadêmicos. Os resultados obtidos com o CNFCV são analisados e comparados aos proporcionados pelas outras estruturas.Ao final são apresentadas conclusões e sugestões para trabalhos futuros. / [en] In this work procedures for neuro-fuzzy modelling and control of dynamic systems are reviewed and a new structure is proposed. In this, modelling and closed-loop control are performed simultaneously by using a neuro-fuzzy approach. In the modelling stage the input space of a dynamic system (plant) is initially divided into a number of fuzzy operating regions within which reduced order models are able to represent the system. The complete system model output - the global model - is obtained through the conjunction of the outputs of the local models. A new structure, called Neuro-Fuzzy Controller with Variable Coefficients (NFCVC) is proposed and evaluated. Its main objectives are to improve the system s robustness and to provide automatic generation of the manipulated variable in order to overcome a difficulty of neural and neuro-fuzzy controllers in general. The NFCVC is originated from models proposed by Mellem (1997) and Velloso (1999) and makes use of neuro-fuzzy networks to generate variable coefficients of an ARMA model. Despite combining times series models with a neuro-fuzzy approach, the main function of NFCVC is to perform the control of the plant.In order to evaluate the performance of NFCVC two well-known neuro-fuzzy controllers - FALCON-H (Fuzzy Adaptive Learning Control Network with Hybrid Learning) and the NEFCON (Neuro-Fuzzy Controller) - as well as the traditional PID controller are used as means of comparison.A linear plant (Rotor Winder), a linearized plant (Inverted Pendulum) and a nonlinear plant (%CO2) are used in the experiments. These plants are well-known and generally used in practical applications and/or academic works. The results for the NFCVC are analyzed and compared to those obtained with the others structures. Finally, conclusions and suggestions for future work are presented.

This research was aimed at the development, implementation and evaluation of an empowerment programme for parents with children in their middle childhood, focused on temperament analysis. The motivation for this study stemmed from the absence of relevant programmes in the field of social work concerning different temperaments and needs of children that parents does not understand or meet. Intervention research was applied. A two-phase research approach was undertaken. In phase 1, a qualitative research was used to do a need assessment. The need assessment was done by means of two focus group discussions with ten parents in each group. The following research question was formulated for this phase: What is the needs of parents related to a programme that focus on temperament analysis for children in there middle childhood. This data complemented the literature study which was undertaken and provided information that established the contents of the empowerment programme. The research question could therefore be answered. The qualitative approach was used in phase 2 as the single-system design. The following research hypothesis was formulated for this phase: If an empowerment programme that includes a temperament analysis is attempted with parents, a significant change in their knowledge in handling and understanding of their children should realise. The empowerment programme for parents with children in their middle childhood consisted of six sessions and was implemented over a period of two weeks. Four parents and one single parent undertook the empowerment programme. A group assessment was undertaken with the five children of the parents who attended the empowerment programme. The focus of the group assessment was to determine a tendency to respond. The self-designed questionnaire was completed prior to the empowerment programme and thereafter. This instrument of measurement confirmed the hypothesis. Conclusions and recommendations for the utilization of the programme in future research were formulated as a result of the research study. / Thesis (PhD (Human Movement Science))--University of Pretoria, 2007. / Social Work and Criminology / unrestricted

L'apprentissage automatique et la vision par ordinateur sont deux sujets de recherche d'actualité. Des contributions clés à ces domaines ont été les fruits de longues années d'études du cortex visuel et de la fonction des réseaux cérébraux. Dans cette thèse, nous nous intéressons à la conception des architectures neuro-inspirées pour le traitement de l'information sur trois niveaux différents du cortex visuel. Au niveau le plus bas, nous proposons un réseau de neurones pour l'acquisition des signaux visuels. Ce modèle est étroitement inspiré par le fonctionnement et l'architecture de la retine et les premières couches du cortex visuel chez l'humain. Il est également adapté à l'émulation des mouvements oculaires qui jouent un rôle important dans notre vision. Au niveau le plus haut, nous nous intéressons à la mémoire. Nous traitons un modèle de mémoire associative basée sur une architecture neuro-inspirée dite `Sparse Clustered Network (SCN)'. Notre contribution principale à ce niveau est de proposer une amélioration d'un algorithme utilisé pour la récupération des messages partiellement effacés du SCN. Nous suggérons également une formulation générique pour faciliter l'évaluation des algorithmes de récupération, et pour aider au développement des nouveaux algorithmes. Au niveau intermédiaire, nous étendons l'architecture du SCN pour l'adapter au problème de la mise en correspondance des caractéristiques d'images, un problème fondamental en vision par ordinateur. Nous démontrons que la performance de notre réseau atteint l'état de l'art, et offre de nombreuses perspectives sur la façon dont les architectures neuro-inspirées peuvent servir de substrat pour la mise en oeuvre de diverses tâches de vision. / Computer vision and machine learning are two hot research topics that have witnessed major breakthroughs in recent years. Much of the advances in these domains have been the fruits of many years of research on the visual cortex and brain function. In this thesis, we focus on designing neuro-inspired architectures for processing information along three different stages of the visual cortex. At the lowest stage, we propose a neural model for the acquisition of visual signals. This model is adapted to emulating eye movements and is closely inspired by the function and the architecture of the retina and early layers of the ventral stream. On the highest stage, we address the memory problem. We focus on an existing neuro-inspired associative memory model called the Sparse Clustered Network. We propose a new information retrieval algorithm that offers more flexibility and a better performance over existing ones. Furthermore, we suggest a generic formulation within which all existing retrieval algorithms can fit. It can also be used to guide the design of new retrieval approaches in a modular fashion. On the intermediate stage, we propose a new way for dealing with the image feature correspondence problem using a neural network model. This model deploys the structure of Sparse Clustered Networks, and offers a gain in matching performance over state-of-the-art, and provides a useful insight on how neuro-inspired architectures can serve as a substrate for implementing various vision tasks.