Ao abordar o tema mercado sexual, destacamos a prática da prostituição como uma das principais maneiras de se inserir e atuar nesse universo. No presente trabalho voltamos o olhar para a prostituição de rua praticada por garotos de programa, com o intuito de entender e revelar subjetividades presentes nesse contexto, uma vez que, no campo da Saúde Pública, esse tema geralmente culmina em um viés epidemiológico, voltado para os riscos que correm de contraírem doenças sexualmente transmissíveis. Com base nas referidas pesquisas, programas de Saúde Pública, na maioria das vezes, planejam e executam ações que entendemos como engessamento social e de saúde. Nesse sentido, contribuímos trazendo novas informações sobre o tema, oriundas da pesquisa realizada no período de 2010-2011, junto a garotos de programa da região de Osasco, Grande São Paulo/SP. Metodologicamente, contamos com contribuições de pesquisas etnográficas, destacando-se a observação-participante, o diário de campo, as entrevistas itinerantes e em profundidade. Ao longo da pesquisa emergiram categorias de análise como sexualidades, hierarquias sexuais e masculinidades. Referências de autores como Gayle Rubin, Michael Foucault e Nestor Perlongher foram fundamentais para a aproximação teórico-metodológica. Consideramos que, comparativamente ao cenário no qual estavam inseridos os garotos de programa que atuavam em São Paulo entre as décadas de 70 e 80, surgiram novos códigos e novas categorias de atuação, cujas práticas não necessariamente são interpretadas como prostituição. Nesse sentido, esses garotos não se identificam inseridos em um mercado sexual e elegem o prazer remunerado como uma nova categoria para justificar suas vivências que se dão entre a clandestinidade, as práticas homossexuais e a afirmação da masculinidade. Por último, apresentamos também suas diversidades, especificidades e enfatizamos as inúmeras violências às quais estão expostos em suas práticas sexuais e comerciais / To discuss about sex market, we focus on the prostitution practice as the primary way of enter and work in this universe. In this present study we look at the street prostitution practiced by lover boys with the intention of understand and reveal subjectivities present in this context, since, in the field of public health, this subject usually leads to an epidemiological bias, facing the risks of contracting sexually transmitted diseases. Based on these cited researches, public health programs often plan and develop actions that we understand as a social and health immobilization. In order to contribute about the subject we bring new information in this research performed with lover boys from Osasco São Paulo/SP, between 2010-2011. Methodologically we have ethnographic research contributions, especially dynamic observation, field notes, itinerant and deep interviews. Some categories of analysis arose during the study as sexuality, sexual hierarchies and masculinities. Contributions of authors: Gayle Rubin, Michael Foucault and Nestor Perlongher were fundamental to the theoretical and methodological approach. We believe that compared to the lover boys who worked in São Paulo between 70s and 80s came up new codes and new categories of performance that are not necessarily interpreted as prostitution. In this sense, they do not identify themselves inserted into a sex market and choose the paid-pleasure as a new category to justify their experiences that takes place between the clandestinity, homosexual practices and the masculinity assertion. Finally, there are their diversities, specificities and countless violence which are involved during their sexual and commercial practices

Com a grande variedade de produtos e serviços disponíveis na Web, os usuários possuem, em geral, muita liberdade de escolha, o que poderia ser considerado uma vantagem se não fosse pela dificuldade encontrada em escolher o produto ou serviço que mais atenda a suas necessidades dentro do vasto conjunto de opções disponíveis. Sistemas de recomendação são sistemas que têm como objetivo auxiliar esses usuários a identificarem itens de interesse em um conjunto de opções. A maioria das abordagens de sistemas de recomendação foca em recomendar itens mais relevantes para usuários individuais, não levando em consideração o contexto dos usuários. Porém, em muitas aplicações é importante também considerar informações contextuais para fazer as recomendações. Por exemplo, um usuário pode desejar assistir um filme com a sua namorada no sábado à noite ou com os seus amigos durante um dia de semana, e uma locadora de filmes na Web pode recomendar diferentes tipos de filmes para este usuário dependendo do contexto no qual este se encontra. Um grande desafio para o uso de sistemas de recomendação sensíveis ao contexto é a falta de métodos para aquisição automática de informação contextual para estes sistemas. Diante desse cenário, neste trabalho é proposto um método para extrair informações contextuais do conteúdo de páginas Web que consiste em construir hierarquias de tópicos do conteúdo textual das páginas considerando, além da bag-of-words tradicional (informação técnica), também informações mais valiosas dos textos como entidades nomeadas e termos do domínio (informação privilegiada). Os tópicos extraídos das hierarquias das páginas Web são utilizados como informações de contexto em sistemas de recomendação sensíveis ao contexto. Neste trabalho foram realizados experimentos para avaliação do contexto extraído pelo método proposto em que foram considerados dois baselines: um sistema de recomendação que não considera informação de contexto e um método da literatura de extração de contexto implementado e adaptado para este mestrado. Além disso, foram utilizadas duas bases de dados. Os resultados obtidos foram, de forma geral, muito bons apresentando ganhos significativos sobre o baseline sem contexto. Com relação ao baseline que extrai informação contextual, o método proposto se mostrou equivalente ou melhor que o mesmo. / With the wide variety of products and services available on the web, it is difficult for users to choose the option that most meets their needs. In order to reduce or even eliminate this difficulty, recommender systems have emerged. A recommender system is used in various fields to recommend items of interest to users. Most recommender approaches focus only on users and items to make the recommendations. However, in many applications it is also important to incorporate contextual information into the recommendation process. For example, a user may want to watch a movie with his girlfriend on Saturday night or with his friends during a weekday, and a video store on the Web can recommend different types of movies for this user depending on his context. Although the use of contextual information by recommendation systems has received great focus in recent years, there is a lack of automatic methods to obtain such information for context-aware recommender systems. For this reason, the acquisition of contextual information is a research area that needs to be better explored. In this scenario, this work proposes a method to extract contextual information of Web page content. This method builds topic hierarchies of the pages textual content considering, besides the traditional bag-of-words, valuable information of texts as named entities and domain terms (privileged information). The topics extracted from the hierarchies are used as contextual information in context-aware recommender systems. By using two databases, experiments were conducted to evaluate the contextual information extracted by the proposed method. Two baselines were considered: a recommendation system that does not use contextual information (IBCF) and a method proposed in literature to extract contextual information (\\methodological\" baseline), adapted for this research. The results are, in general, very good and show significant gains over the baseline without context. Regarding the \"methodological\" baseline, the proposed method is equivalent to or better than this baseline.

Algoritmos de aprendizado semi-supervisionado ativo podem se configurar como ferramentas úteis em cenários práticos em que os dados são numerosamente obtidos, mas atribuir seus respectivos rótulos de classe se configura como uma tarefa custosa/difícil. A literatura em aprendizado ativo destaca diversos algoritmos, este trabalho partiu do tradicional Hierarchical Sampling estabelecido para operar sobre hierarquias de grupos. As características de tal algoritmo o coloca à frente de outros métodos ativos, entretanto o mesmo ainda apresenta algumas dificuldades. A fim de aprimorá-lo e contornar suas principais dificuldades, incluindo sua sensibilidade na escolha particular de uma hierarquia de grupos como entrada, este trabalho propôs estratégias que possibilitaram melhorar o algoritmo na sua forma original e diante de variantes propostas na literatura. Os experimentos em diferentes bases de dados reais mostraram que o algoritmo proposto neste trabalho é capaz de superar e competir em qualidade dentro do cenário de classificação ativa com outros algoritmos ativos da literatura. / Active semi-supervised learning can play an important role in classification scenarios in which labeled data are laborious and/or expensive to obtain, while unlabeled data are numerous and can be easily acquired. There are many active algorithms in the literature and this work focuses on an active semi-supervised algorithm that can be driven by clustering hierarchy, the well-known Hierarchical Sampling (HS) algorithm. This work takes as a starting point the original Hierarchical Sampling algorithm and perform changes in different aspects of the original algorithm in order to tackle its main drawbacks, including its sensitivity to the choice of a single particular hierarchy. Experimental results over many real datasets show that the proposed algorithm performs superior or competitive when compared to a number of state-of-the-art algorithms for active semi-supervised classification.

De nos jours, on a de plus en plus de capteurs qui ont tendance à apporter confort et facilité dans notre vie quotidienne. Ces capteurs sont faciles à déployer et à intégrer dans une variété d’applications (monitoring de bâtiments intelligents, aide à la personne,...). Ces milliers (voire millions)de capteurs sont de plus en plus envahissants et génèrent sans arrêt des masses énormes de données qu’on doit stocker et gérer pour le bon fonctionnement des applications qui en dépendent. A chaque fois qu'un capteur génère une donnée, deux dimensions sont d'un intérêt particulier : la dimension temporelle et la dimension spatiale. Ces deux dimensions permettent d'identifier l'instant de réception et la source émettrice de chaque donnée. Chaque dimension peut se voir associée à une hiérarchie de granularités qui peut varier selon le contexte d'application. Dans cette thèse, nous nous concentrons sur les applications nécessitant une conservation à long terme des données issues des flux de données capteurs. Notre approche vise à contrôler le stockage des données capteurs en ne gardant que les données jugées pertinentes selon la spécification des granularités spatio-temporelles représentatives des besoins applicatifs, afin d’améliorer l'efficacité de certaines requêtes. Notre idée clé consiste à emprunter l'approche déclarative développée pour la conception de bases de données à partir de contraintes et d'étendre les dépendances fonctionnelles avec des composantes spatiales et temporelles afin de revoir le processus classique de normalisation de schéma de base de données. Étant donné des flux de données capteurs, nous considérons à la fois les hiérarchies de granularités spatio-temporelles et les Dépendances Fonctionnelles SpatioTemporelles (DFSTs) comme objets de premier ordre pour concevoir des bases de données de capteurs compatibles avec n'importe quel SGBDR. Nous avons implémenté un prototype de cette architecture qui traite à la fois la conception de la base de données ainsi que le chargement des données. Nous avons mené des expériences avec des flux de donnés synthétiques et réels provenant de bâtiments intelligents. Nous avons comparé notre solution avec la solution de base et nous avons obtenu des résultats prometteurs en termes de performance de requêtes et d'utilisation de la mémoire. Nous avons également étudié le compromis entre la réduction des données et l'approximation des données. / Nowadays, sensors are cheap, easy to deploy and immediate to integrate into applications. These thousands of sensors are increasingly invasive and are constantly generating enormous amounts of data that must be stored and managed for the proper functioning of the applications depending on them. Sensor data, in addition of being of major interest in real-time applications, e.g. building control, health supervision..., are also important for long-term reporting applications, e.g. reporting, statistics, research data... Whenever a sensor produces data, two dimensions are of particular interest: the temporal dimension to stamp the produced value at a particular time and the spatial dimension to identify the location of the sensor. Both dimensions have different granularities that can be organized into hierarchies specific to the concerned context application. In this PhD thesis, we focus on applications that require long-term storage of sensor data issued from sensor data streams. Since huge amount of sensor data can be generated, our main goal is to select only relevant data to be saved for further usage, in particular long-term query facilities. More precisely, our aim is to develop an approach that controls the storage of sensor data by keeping only the data considered as relevant according to the spatial and temporal granularities representative of the application requirements. In such cases, approximating data in order to reduce the quantity of stored values enhances the efficiency of those queries. Our key idea is to borrow the declarative approach developed in the seventies for database design from constraints and to extend functional dependencies with spatial and temporal components in order to revisit the classical database schema normalization process. Given sensor data streams, we consider both spatio-temporal granularity hierarchies and Spatio-Temporal Functional Dependencies (STFDs) as first class-citizens for designing sensor databases on top of any RDBMS. We propose a specific axiomatisation of STFDs and the associated attribute closure algorithm, leading to a new normalization algorithm. We have implemented a prototype of this architecture to deal with both database design and data loading. We conducted experiments with synthetic and real-life data streams from intelligent buildings.

This dissertation focuses on social interaction patterns between young people in an online chat room, analyzing how social order is displayed and constituted. An overall issue concerns when and how the participants manage to co-create social communities within this setting. The data draw on an ethnographic study, where chat room observations and online recordings were carried out during three years. Methodological guidelines from discursive psychology and conversation analysis have been used in making detailed sequential analyses of chat room interactions. The thesis builds on social practice theories, including sociocultural theorizing and studies of language socialization, and work on positionings. The findings show that familiarity with chat language, including the use of emoticons and leet speak, as well as familiarity with netiquette and conversational routines such as greeting- and parting routines, are vital for the participants in order to become parts of local groups and alignments. Playful improvisation is an important feature in the chat room intercourse. Moreover, full participation requires involvement in the lives of co-participants and extended dialogues over time. In the process of moving from peripheral to more central participation, the participants formed alignments with other participants and positioned themselves and their co-participants in the chat room. Such alignments were often founded on a shared taste in, for example musical genres and everyday consumption patterns. Shared views on school, sex and relationships, as well as age or gender alignments also played a role in the creation of local communities. Conversely, issues of exclusion were recurrent features of chat room interplay. All considered this created participation patterns that formed local hierarchies which were not fixed or static, but rather fleeting and dynamic. And yet, the participants generally did not transcend or challenge contemporary age and gender boundaries.

We apply the semidefinite programming method to obtain a new upper bound on the cardinality of codes made of subspaces of a linear vector space over a finite field. Such codes are of interest in network coding.Next, with the same method, we prove an upper bound on the cardinality of sets avoiding one distance in the Johnson space, which is essentially Schrijver semidefinite program. This bound is used to improve existing results on the measurable chromatic number of the Euclidean space.We build a new hierarchy of semidefinite programs whose optimal values give upper bounds on the independence number of a graph. This hierarchy is based on matrices arising from simplicial complexes. We show some properties that our hierarchy shares with other classical ones. As an example, we show its application to the problem of determining the independence number of Paley graphs.

The need for efficient interference detection frequently arises in computer graphics, robotics, virtual prototyping, surgery simulation, computer games, and visualization. To prevent bodies passing directly through each other, the simulation system must be able to track touching or intersecting geometric primitives. In interactive simulations, in which millions of geometric primitives may be involved, highly efficient collision detection algorithms are necessary. For these reasons, new adaptive collision detection algorithms for rigid and different types of deformable polygon meshes are proposed in this thesis. The solutions are based on adaptive bounding volume hierarchies. For deformable body simulation, different refit and reconstruction schemes to efficiently update the hierarchies as the models deform are presented. These methods permit the models to change their entire shape at every time step of the simulation. The types of deformable models considered are (i) polygon meshes that are deformed by arbitrary vertex repositioning, but with the mesh topology preserved, (ii) models deformed by linear morphing of a fixed number of reference meshes, and (iii) models undergoing completely unstructured relative motion among the geometric primitives. For rigid body simulation, a novel type of bounding volume, the slab cut ball, is introduced, which improves the culling efficiency of the data structure significantly at a low storage cost. Furthermore, a solution for even tighter fitting heterogeneous hierarchies is outlined, including novel intersection tests between spheres and boxes as well as ellipsoids and boxes. The results from the practical experiments indicate that significant speedups can be achieved by using these new methods for collision queries as well as for ray shooting in complex deforming scenes.

The ways that categories of immigration are drawn and standards of successful citizenship are measured in Canadian society influence the ways that people script themselves to appear as worthy immigrant applicants and potential Canadian citizens. For immigrant hopefuls, scripting oneself using the language of immigration and positioning oneself as a deserving and desirable immigrant is crucial for gaining mobility and passage into Canadian society. In my thesis, I explore the literature surrounding processes and concepts like borders, mobility, good citizenship, the ???white standard???, and racialization that serve as foundations and outcomes of scripting ???good??? immigrants and ???successful??? citizenship. I embed the experiences of my informants within an analysis of this literature as well as the processes of immigration outlined by Citizenship and Immigration Canada (CIC). I find that scripting immigrant categories and citizenship can result in immigrants enacting only a limited Canadianness. Immigrant categories involve restrictive policies that can result in exploitation. I also offer that immigrants may live a double-consciousness through their transnationalism and constituting of ???back home???. The larger hope for this project is to provide an understanding of the processes of scripting that work to make exclusive the right to be Canadian so that the vulnerability and suffering caused by the existence of hierarchies of citizenship can be tackled as a public issue and make for a more inclusive and equitable Canada.

In a large number of applications, the processing relies on objects or area of interests, and the pixel-based image representation is notwell adapted. These applications would benefit from a region-based processing. Early examples of region-based processing can be found in the area of image segmentation, such as the quad tree. Recently, in mathematical morphology, the connected operators have received much attention. They are region-based filtering tools that act by merging flat zones. They have good contour preservation properties in the sense that they do not create any new boundaries, neither do they shift the existing ones. One popular implementation for connected operators relies on tree-based image representations, notably threshold decomposition representations and hierarchical representations. Those tree-based image representations are widely used in many image processing and computer vision applications. Tree-based connected operators consist in constructing a set of nested or disjoint connected components, followed by a filtering of these connected components based on an attribute function characterizing each connected component. Finally, the filtered image is reconstructed from the simplified tree composed of the remaining connected components. In the work presented in this thesis, we propose to expand the ideas of tree-based connected operators. We introduce the notion of tree-based shape spaces, built from tree-based image representations. Many state-of-the-art methods relying on tree-based image representations consist of analyzing this shape space. A first consequence of this change of point of view is our proposition of a local feature detector, called the tree-based Morse regions (TBMR). It can be seen as a variant of the MSER method. The selection of TBMRs is based on topological information, and hence it extracts the regions independently of the contrast, which makes it truly contrast invariant and quasi parameters free. The accuracy and robustness of the TBMR approach are demonstrated by the repeatability test and by applications to image registration and 3D reconstruction, as compared to some state-of-the-art methods. The basic idea of the main proposition in this thesis is to apply connected filters on the shape space. Such a processing is called the framework of shape-based morphology. It is a versatile framework that deals with region-based image representations. It has three main consequences. 1) For filtering purpose, it is a generalization of the existing tree-based connected operators. Indeed, the framework encompasses classical existing connected operators by attributes. Besides, It also allows us to propose two classes of novel connected operators: shape-based lower/upper levelings and shapings. 2) This framework can be used to object detection/segmentation by selecting relevant points in the shape space. 3) We can also use this framework to transform the hierarchies using the extinction values, so that a hierarchical simplification or segmentation is obtained. Some applications are developed using the framework of shape-based morphology to demonstrate its usefulness. The applications of the shape-based filtering to retinal image analysis show that a mere filtering step that we compare to more evolved processings, achieves state-of-the-art results. An efficient shaping used for image simplification is proposed by minimizing Mumford-Shah functional subordinated to the topographic map. For object detection/segmentation, we proposed a context-based energy estimator that is suitable to characterize object meaningfulness. Last, we extend the hierarchy of constrained connectivity using the aspect of hierarchy transformation of constrained connectivity using the aspect ofhierarchy transformation.

This essay deals with the difficulties of cooperation between leisure-time teachers and the class teachers, and what that may mean in the joint work during the school day. In my story, I describe a situation that becomes a dilemma for me as a leisure-time teacher when I am expected to be in two places at the same time and my decisions causes me to fail an agreement with the class teacher. In the essay, I discuss the occupational role, hierarchies and power structures as well as practical knowledge. My purpose is to investigate where and in what way the difficulties arises and if it´s possible to identify and find solutions to them. The method I use is scientific essay where I reflect on my dilemma and have a dialogue with other research and the school's governing documents. One of my conclusions is that we must reach a common vision and decide how we communicate that within the work team.