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Traditionally robots are controlled using devices like joysticks, keyboards, mice and other similar human computer interface (HCI) devices. Although this approach is effective and practical for some cases, it is restrictive only to healthy individuals without disabilities, and it also requires the user to master the device before its usage. It becomes complicated and non-intuitive when multiple robots need to be controlled simultaneously with these traditional devices, as in the case of Human Swarm Interfaces (HSI). This work presents a novel concept of using human bio-signals to control swarms of robots. With this concept there are two major advantages: Firstly, it gives amputees and people with certain disabilities the ability to control robotic swarms, which has previously not been possible. Secondly, it also gives the user a more intuitive interface to control swarms of robots by using gestures, thoughts, and eye movement. We measure different bio-signals from the human body including Electroencephalography (EEG), Electromyography (EMG), Electrooculography (EOG), using off the shelf products. After minimal signal processing, we then decode the intended control action using machine learning techniques like Hidden Markov Models (HMM) and K-Nearest Neighbors (K-NN). We employ formation controllers based on distance and displacement to control the shape and motion of the robotic swarm. Comparison for ground truth for thoughts and gesture classifications are done, and the resulting pipelines are evaluated with both simulations and hardware experiments with swarms of ground robots and aerial vehicles.

Um estudo das relações existentes entre a estrutura de couraça e a prática escolar. Procura-se investigar o conceito de couraça e o fenômeno do encouraçamento como definido por Wilhelm Reich para aplicá-lo à realidade dos dias atuais, especialmente no ambiente escolar. Em um primeiro momento, realiza-se uma revisão da teoria reichiana do encouraçamento desde sua formulação no campo da psicanálise até sua aplicação ao funcionamento corporal e energético. Com base na visão estrutural do funcionamento encouraçado examina-se, então, o funcionamento virtual fronteiriço mais comum aos dias de hoje, relacionando-o às mudanças estruturais e superestruturais da atualidade. Acompanham-se, em seguida, as relações entre o aspecto biopsíquico dos indivíduos que compõem uma população e a forma cultural que a sociedade por eles formada assume. Na sequência, o estudo da rotina escolar enquanto currículo-oculto é empreendido em busca da compreensão do papel que esta tem na formação da couraça. Finalmente, uma confrontação é feita entre o funcionamento encouraçado e a forma com que a escola se organiza. Evidenciam-se aí as mútuas influências entre prática escolar e o encouraçamento. / A scrutiny on the relationship between school practice and the structure of the armor. The aim is to investigate the concept of the armor and the armoring phenomenon as defined by Wilhelm Reich to apply it to nowadays reality, especially in the school environment. At first, a review of Reich\'s theory of armoring was carried out, since its formulation in the field of psychoanalysis up to its application to body function and energy. Then, based on the structural view of the operation of the armor, the virtual borderline functioning, more common in the last decades, is examined and related to structural and super structural changes of present time. Following, the relationship between the bio-psychological aspect of individuals in a population and the cultural form that their society assumes is examined. Further, the study of school routine as hidden-curriculum is undertaken in search for the understanding of the role it plays in shaping the armor. Finally, a confrontation is made between the functioning of the armor and the way the school is structured. There becomes manifest the mutual influences between school practice and armoring.

A demanda por abordagens eficientes para o problema de reconhecer a estrutura de cada gene numa sequência genômica motivou a implementação de um grande número de programas preditores de genes. Fizemos uma análise dos programas de sucesso com abordagem probabilística e reconhecemos semelhanças na implementação dos mesmos. A maior parte desses programas utiliza a cadeia oculta generalizada de Markov (GHMM - generalized hiddenMarkov model) como um modelo de gene. Percebemos que muitos preditores têm a arquitetura da GHMM fixada no código-fonte, dificultando a investigação de novas abordagens. Devido a essa dificuldade e pelas semelhanças entre os programas atuais, implementamos o sistema MYOP (Make Your Own Predictor) que tem como objetivo fornecer um ambiente flexível o qual permite avaliar rapidamente cada modelo de gene. Mostramos a utilidade da ferramenta através da implementação e avaliação de 96 modelos de genes em que cada modelo é formado por um conjunto de estados e cada estado tem uma distribuição de duração e um outro modelo probabilístico. Verificamos que nem sempre um modelo probabilísticomais sofisticado fornece um preditor melhor, mostrando a relevância das experimentações e a importância de um sistema como o MYOP. / The demand for efficient approaches for the gene structure prediction has motivated the implementation of different programs. In this work, we have analyzed successful programs that apply the probabilistic approach. We have observed similarities between different implementations, the same mathematical framework called generalized hidden Markov chain (GHMM) is applied. One problem with these implementations is that they maintain fixed GHMM architectures that are hard-coded. Due to this problem and similarities between the programs, we have implemented the MYOP framework (Make Your Own Predictor) with the objective of providing a flexible environment that allows the rapid evaluation of each gene model. We have demonstrated the utility of this tool through the implementation and evaluation of 96 gene models in which each model has a set of states and each state has a duration distribution and a probabilistic model. We have shown that a sophisticated probabilisticmodel is not sufficient to obtain better predictor, showing the experimentation relevance and the importance of a system as MYOP.

Les modèles de Markov cachés (MMC) par exemple ceux de la librairie Pfam sont des outils très populaires pour l'annotation des domaines protéiques. Cependant, ils ne sont pas toujours adaptés aux protéines les plus divergentes. C'est notamment le cas avec Plasmodium falciparum (principal agent du paludisme chez l'Homme), où les MMC de Pfam identifient peu de familles distinctes de domaines, et couvrent moins de 50% des protéines de l'organisme. L'objectif de cette thèse est d'apporter des méthodes nouvelles pour affiner la détection de domaines dans les protéines divergentes.Le premier axe développé est une approche d'identification de domaines utilisant leurs propriétés de co-occurrence. Différentes études ont montré que la majorité des domaines apparaissent dans les protéines avec un ensemble très réduits d'autres domaines favoris. Notre méthode exploite cette propriété pour détecter des domaines trop divergents pour être identifiés par l'approche classique. Cette détection s'accompagne d'une estimation du taux d'erreur par une procédure de ré-échantillonnage. Chez P. falciparum, elle permet d'identifier, avec un taux d'erreur estimé inférieur à 20%, 585 nouveaux domaines dont 159 familles étaient inédites dans cet organisme ce qui représente 16% du nombre de domaines connus.Le second axe de mes recherches présente plusieurs méthodes de corrections statistiques et évolutives des MMC pour l'annotation d'organismes divergents. Deux types d'approches ont été proposées. D'un côté, nous intégrons aux alignements d'apprentissage des MMC, les séquences précédemment identifiés dans l'organisme cible ou ses proches relatifs. La limitation de cette solution est que seules des familles de domaines déjà connues dans le taxon peuvent ainsi être identifiées. Le deuxième type d'approche contourne cette limitation en corrigeant tous les modèles par une prise en compte de l'évolution des séquences d'apprentissage. Pour cela, nous faisons appel à des techniques classiques de la bioinformatique et de l'apprentissage statistique. Les résultats obtenus offrent un ensemble de prédictions complémentaires totalisant 663 nouveaux domaines supplémentaires dont 504 familles inédites soit une augmentation de 18% à ajouter aux précédents résultats. / Hidden Markov Models (HMMs) from Pfam database for example are popular tools for protein domain annotation. However, they are not well suited for studying highly divergent proteins. This is notably the case with Plasmodium falciparum (main causal agent of human malaria), where Pfam HMMs identify few distinct domain families and cover less than 50% of its proteins. This thesis aims at providing new methods to enhance domain detection in divergent proteins.The first axis of this work is an approach of domain identification based on domain co-occurrence. Several studies shown that a majority of domains appear in proteins with a small set of other favourite domains. Our method exploits this tendency to detect domains escaping to the classical procedure because of their divergence. Detected domains come along with an false discovery rate (FDR) estimation computed with a shuffling procedure. In P. falciparum proteins, this approach allows us identify, with an FDR below 20%, 585 new domains with 159 families that were previously unseen in this organism which account for 16% of the known domains.The second axis of my researches involves the development of statistical and evolutionary methods of HMM correction to improve the annotation of divergent organisms. Two kind of approaches are proposed. On the one hand, the sequences previously identified in the target organism and its close relatives are integrated in the learning alignments. An obvious limitation of this solution is that only new occurrences of previously known families in the taxon can be discovered. On the other hand, we evade this limitation by adjusting HMM parameters by simulating the evolution of the learning sequences. To this end, classical techniques from bioinformatics and statistical learning were used. Alternative libraries offer a complementary set of predictions summing 663 new domains with 504 previously unseen families corresponding to an improvement of 18% to add to the previous results.

Modelos de Markov ocultos (MMOs) são uma ferramenta importante em matemática aplicada e estatística. Eles se baseiam em dois processos estocásticos. O primeiro é uma cadeia de Markov, que não é observada diretamente. O segundo é observável e sua distribuição depende do estado na cadeia de Markov. Supomos que os processos são discretos no tempo e assumem um número finito de estados. Para extrair informações dos MMOs, é necessário estimar seus parâmetros. Diversos algoritmos locais têm sido utilizados nas últimas décadas para essa tarefa. Nosso trabalho estuda a estimação de parâmetros em modelos de Markov ocultos, do ponto de vista da otimização global. Desenvolvemos algoritmos capazes de encontrar, em uma execução bem sucedida, todos os estimadores de máxima verossimilhança globais de um modelo de Markov oculto. Para tanto, usamos aritmética intervalar. Essa aritmética permite explorar sistematicamente o espaço paramétrico, excluindo regiões que não contém soluções. O cálculo da função objetivo é feito através da recursão \\textit, descrita na literatura estatística. Modificamos a extensão intervalar natural dessa recursão usando programação linear. Nossa abordagem é mais eficiente e produz intervalos mais estreitos do que a implementação padrão. Experimentos mostram ganhos de 16 a 250 vezes, de acordo com a complexidade do modelo. Revisamos os algoritmos locais, tendo em vista sua aplicação em métodos globais. Comparamos os algoritmos de Baum-Welch, pontos interiores e gradientes projetados espectrais. Concluímos que o método de Baum-Welch é o mais indicado como auxiliar em otimização global. Modificamos o \\textit{interval branch and bound} para resolver a estimação de modelos com eficiência. Usamos as condições KKT e as simetrias do problema na construção de testes para reduzir ou excluir caixas. Implementamos procedimentos de aceleração da convergência, como o método de Newton intervalar e propagação de restrições e da função objetivo. Nosso algoritmo foi escrito em \\textit{C++}, usando programação genérica. Mostramos que nossa implementação dá resultados tão bons quanto o resolvedor global BARON, porém com mais eficiência. Em média, nosso algoritmo é capaz de resolver $50\\%$ mais problemas no mesmo período de tempo. Concluímos estudando aspectos qualitativos dos MMOs com mistura Bernoulli. Plotamos todos os máximos globais detectados em instâncias com poucas observações e apresentamos novos limitantes superiores da verossimilhança baseados na divisão de uma amostra grande em grupos menores. / Hidden Markov models(HMMs) are an important tool in statistics and applied mathematics. Our work deals with processes formed by two discrete time and finite state space stochastic processes. The first process is a Markov chain and is not directly observed. On the other hand, the second process is observable and its distribution depends on the current state of the hidden component. In order to extract conclusions from a Hidden Markov Model we must estimate the parameters that defines it. Several local algorithms has been used to handle with this task. We present a global optimization approach based on interval arithmetic to maximize the likelihood function. Interval arithmetic allow us to explore parametric space systematically, discarding regions which cannot contain global maxima. We evaluate the objective function and its derivatives by the so called backward recursion and show that is possible to obtain sharper interval extensions for such functions using linear programming. Numerical experiments shows that our approach is $16$ to $250$ times more efficient than standard implementations. We also study local optimization algorithms hidden Markov model estimation. We compare Baum-Welch procedure with interior points and spectral projected gradients. We conclude that Baum-Welch is the best option as a sub-algorithm in a global optimization framework. We improve the well known interval branch and bound algorithm to take advantages on the problem structure. We derive new exclusion tests, based on its KKT conditions and symmetries. We implement our approach in C++, under generic programming paradigm. We show that our implementation is compatible with global optimization solver BARON in terms of precision. We also show that our algorithm is faster than BARON. In average, we can handle with $50\\%$ more problems within the same amount of time. We conclude studying qualitative aspects of Bernoulli hidden Markov models. We plot all global maxima found in small observations instances and show a new upper bound of the likelihood based on splitting observations in small groups.

Trata-se de uma pesquisa qualitativa de abordagem interpretativista (cf. Bortoni, 2009; Flick, 2002; Denzin e Lincoln, 2010), cujo objetivo principal é investigar, nas práticas discursivas, o que há da língua e cultura do imigrado italiano no contexto cascavelense, mediante dados levantados por meio de observação simples da citada comunidade e entrevistas semiestruturadas, com pessoas de três gerações: jovens, adultos e idosos. Buscamos responder às seguintes perguntas de pesquisa: a língua e cultura do imigrado italiano existem em Cascavel? De que modo? Por esse âmbito, nosso objetivo maior foi descobrir formas de cultura e língua invisibilizadas e as razões que levaram e levam a tal situação. O aporte teórico se sustentou principalmente nas perspectivas teóricas de autores como Schlieben-Lange (1993), Rajagopalan (2002, 2003 e 2007), Bourdieu (1998), Burke (2003 e 2006), Bosi (1994 e 2003) e Halbawchs (1990) que nos direcionaram para a compreensão da linguagem a partir do contexto social. Assim pudemos compreender que: a) de fato, nem sempre a negação e ou indiferença sobre o conhecimento do talian é verdadeira; b) alguns estudiosos da linguagem, com suas linhas de pesquisas, infelizmente, enfatizam o desprestígio de uma língua minoritária e decretam sua morte; c) a ativação da memória tem o poder de desencadear discursos sobre o passado e trazer à tona língua e cultura étnica, evidenciando a possibilidade de manter viva a língua taliana em Cascavel. Nesse contexto, algumas vertentes teóricas, bem como poder político e história oficial têm trabalhado contra a memória oral, importante na formação ideológica do indivíduo. Tendo em conta esse aspecto, desejamos que a nossa pesquisa possa corroborar outros estudos de desvelamento linguístico cultural, e, ainda, que a memória e a história oficial possam trabalhar juntas na divulgação, valorização e resguardo dessa língua. / This qualitative research is based on an interpretative approach (cf. Bortoni, 2009; Flick, 2002; Denzin and Lincoln, 2010), whose main objective is to investigate, in the discursive practices, what exists in the language and culture of the immigrated Italian in the Cascavelense context, upon data researched through the simple observation of the cited community and semi-structured interviews, with people form three generations: youth, adults and elderly people. We seek to answer the following research questions: Do the language and the culture of the Italian immigrated exist in Cascavel? How? Through this framework, our major objective was to find out ways of invisible language and culture, and the reasons that took and take to this situation. The theoretical support is composed mainly by the theoretical perspectives of authors such as Schlieben-Lange (1993), Rajagopalan (2002, 2003 and 2007), Bourdieu (1998), Burke (2003 and 2006), Bosi (1994 and 2003) and Halbawchs (1990) who directed us to a better language comprehension from the social context. This way, we could understand that: a) Indeed, not always the negation and/or the indifference about the Talians knowledge is true; b) Some language scholars, with their line of research, unfortunately, emphasize the discredit of a minority language and declare its death; c) The activation of the memory has the power to trigger speeches about the past and elicits language and ethnic culture, highliting the possibility of keeping alive the Taliana language in Cascavel. In this scenario, some theoretical aspects, just like the political power and the official history have worked against the oral memory, important in the ideological formation of the individual. Considering this fact, we hope that our research can corroborate to other cultural linguistic unveiling studies and, still, that the memory and the official history can work together in the dissemination, appreciation and protection of this language.

For young animals, surviving the first year of nutritional independence requires rapid development of effective foraging behaviour before the onset of terminal starvation. Grey seal (Halichoerus grypus) pups are abandoned on the natal colony after a brief (15-21 days) suckling period and must learn to dive and forage without parental instruction. Regional and sex-specific differences in diet and foraging behaviour have been described for adults and juveniles, but the early-life behaviour of pups during the critical first months at sea remains poorly understood. This thesis investigates sources of intrinsic and extrinsic variation in the development of foraging behaviour and resource selection in grey seal pups. The studies presented here feature tracking and dive data collected from 52 recently-weaned pups, tagged at six different breeding colonies in two geographically-distinct regions of the United Kingdom (UK). Original aspects of this thesis include: (Chapter I) a comprehensive review of analytical methods for inferring foraging behaviour from tracking and dive data in pinnipeds; (Chapter II) description and comparison of regional and sex differences in movements and diving characteristics of recently-weaned pups during their first trips at sea; (Chapter III) implementation of a novel generalized hidden Markov modelling (HMM) technique to investigate the development of foraging movement patterns whilst accounting for sources of intrinsic (age, sex) and extrinsic (regional) variation; and (Chapter IV) the first analysis of grey seal pup foraging habitat preference, incorporating behavioural inferences from HMMs and investigating changes in preference through time.

O Processamento de Linguagem Natural (PLN) é uma área da Ciência da Computação, que vem tentando, ao longo dos anos, aperfeiçoar a comunicação entre o homem e o computador. Varias técnicas tem sido utilizadas para aperfeiçoar esta comunicação, entre elas a aplicação de métodos estatísticos. Estes métodos tem sido usados por pesquisadores de PLN, com um crescente sucesso e uma de suas maiores vantagens é a possibilidade do tratamento de textos irrestritos. Em particular, a aplicação dos métodos estatísticos, na marcação automática de "corpus" com categorias morfo-sintáticas, tem se mostrado bastante promissora, obtendo resultados surpreendentes. Assim sendo, este trabalho descreve o processo de marcação automática de categorias morfo-sintáticas. Inicialmente, são apresentados e comparados os principais métodos aplicados a marcação automática: os métodos baseados em regras e os métodos estatísticos. São descritos os principais formalismos e técnicas usadas para esta finalidade pelos métodos estatísticos. E introduzida a marcação automática para a Língua Portuguesa, algo até então inédito. O objetivo deste trabalho é fazer um estudo detalhado e uma avaliação do sistema rotulador de categorias morfo-sintáticas, a fim de que se possa definir um padrão no qual o sistema apresente a mais alta precisão possível. Para efetuar esta avaliação, são especificados alguns critérios: a qualidade do "corpus" de treinamento, o seu tamanho e a influencia das palavras desconhecidas. A partir dos resultados obtidos, espera-se poder aperfeiçoar o sistema rotulador, de forma a aproveitar, da melhor maneira possível, os recursos disponíveis para a Língua Portuguesa. / Natural Language Processing (NLP) is an area of Computer Sciences, that have been trying to improve communication between human beings and computers. A number of different techniques have been used to improve this communication and among them, the use of stochastic methods. These methods have successfully being used by NLP researchers and one of their most remarkable advantages is that they are able to deal with unrestricted texts. Namely, the use of stochastic methods for part-of-speech tagging has achieving some extremely good results. Thus, this work describes the process of part-of-speech tagging. At first, we present and compare the main tagging methods: the rule-based methods and the stochastic ones. We describe the main stochastic tagging formalisms and techniques for part-of-speech tagging. We also introduce part-of-speech tagging for the Portuguese Language. The main purpose of this work is to study and evaluate a part-of-speech tagger system in order to establish a pattern in which it is possible to achieve the greatest accuracy. To perform this evaluation, several parameters were set: the corpus quality, its size and the relation between unknown words and accuracy. The results obtained will be used to improve the tagger, in order to use better the available Portuguese Language resources.

Distance sampling and spatial capture-recapture are statistical methods to estimate the number of animals in a wild population based on encounters between these animals and scientific detectors. Both methods estimate the probability an animal is detected during a survey, but do not explicitly model animal movement. The primary challenge is that animal movement in these surveys is unobserved; one must average over all possible paths each animal could have travelled during the survey. In this thesis, a general statistical model, with distance sampling and spatial capture-recapture as special cases, is presented that explicitly incorporates animal movement. An efficient algorithm to integrate over all possible movement paths, based on quadrature and hidden Markov modelling, is given to overcome the computational obstacles. For distance sampling, simulation studies and case studies show that incorporating animal movement can reduce the bias in estimated abundance found in conventional models and expand application of distance sampling to surveys that violate the assumption of no animal movement. For spatial capture-recapture, continuous-time encounter records are used to make detailed inference on where animals spend their time during the survey. In surveys conducted in discrete occasions, maximum likelihood models that allow for mobile activity centres are presented to account for transience, dispersal, and heterogeneous space use. These methods provide an alternative when animal movement causes bias in standard methods and the opportunity to gain richer inference on how animals move, where they spend their time, and how they interact.