Nas últimas décadas, o cenário empresarial mundial tem presenciado profundas modificações que afetam diretamente as empresas e definem novas formas de atuação no mercado. Por um lado, pode-se identificar a posição de destaque ocupada pelos consumidores, ávidos por produtos e serviços de alta qualidade e que de fato atendam às suas necessidades. Por outro, destaca-se o fenômeno da globalização dos mercados e seu reflexo na concorrência entre as empresas, que agora passa a ser mundial. Além disto, esta troca de paradigmas traz em seu bojo mudanças nos fatores definidores de competitividade para as empresas. Esta situação desfavorece, sobretudo, as micro e pequenas empresas (MPE\'s), que muitas vezes não contam com capacidade competitiva necessária para se adaptarem a esta nova era. Para sobreviver às condições impostas pela economia vigente, observa-se o surgimento de novas formas de organização industrial, com destaque às que estimulam a cooperação entre empresas de um mesmo setor ou de setores complementares, dentre os quais destacam-se os chamados aglomerados ou clusters. Pelas suas características, a presença em um cluster possibilita às MPE\'s incrementos em seus processos produtivos, tanto em termos de volume de produção quanto em termos de aumento de possibilidades tecnológicas, através do compartilhamento de meios produtivos e de investimentos na busca por melhores tecnologias, sejam elas de produto, de processo ou de gestão. De acordo com este cenário, o objetivo desta tese consiste em desenvolver uma análise da competitividade das MPE\'s do cluster alimentício do município de Marília/SP, possibilitando identificar ações a serem tomadas para aumento da competitividade deste conjunto de empresas. Para a realização desta análise foi elaborado um modelo geral adotado na pesquisa, considerando as particularidades do cluster em questão: a predominância de MPE\'s e as características da indústria alimentícia. / In the last decades, the managerial scenery in the world has been witnessing deep modifications that affect the companies directly and define its new forms of performance in the market. On one side, it can be verified the prominent position occupied by the consumers, avid for products and services of high quality and that in fact assist to their needs. On other side, it can be stand out the phenomenon of the globalization of the markets, enlarging the horizons of the companies for besides the national limits, increasing, with that, the competition among them. Besides this, this change of paradigms in its core some changes in the factors that define the competitiveness for a company. This situation disfavors, above all the small firms, that don\'t have necessary competitive capacity for adapt itself to this new era. Thus, to survive to the conditions imposed by the effective economy, these firms create new ways of industrial organization that stimulate cooperation among companies that belongs to the same sector or to the complementary sectors, which can be stand out as agglomerates or clusters. For its characteristics, the presence in a cluster facilitates to the MPE\'s increments in its productive processes, so much in terms of production volume as in terms of increase of technological possibilities, through the share alike of productive means and of investments in the search for better technologies, be them of product, of process or of administration. In agreement with this scenery, the objective of this consists of developing an analysis of the competitiveness of MPE\'s agroindustrial cluster in the municipal district of Marília/SP, facilitating to identify actions to be taken for the competitiveness increasing of this group of companies. For the accomplishment of this analysis a general model adopted in the research was elaborated, considering the particularities of the cluster in subject: the predominance of ) MPE\'s and the characteristics of the nutritious industry.

A SOA está se tornando uma abordagem difundida no desenvolvimento de sistemas. Em sistemas maiores onde se utiliza SOA pode ocorrer problemas de alta demanda, que podem ser resolvidos com arquiteturas distribuídas como clusters. Esta dissertação apresenta a proposta de uma nova arquitetura para distribuição de requisições em clusters de web services. A arquitetura proposta tem foco na distribuição flexível de requisições, possibilitando o emprego de políticas diversificadas, estas voltadas a diferentes objetivos, aplicações e plataformas. A arquitetura também propõe trabalhar de forma dinâmica, possibilitando decisões baseadas na coleta de estado dos elementos que compõem a estrutura de atendimento. A transparência, do ponto de vista do cliente, também é tratada na arquitetura. Os testes da arquitetura foram realizados através de um protótipo que a implementa. O protótipo instancia os objetivos propostos na arquitetura, apresentando ganhos de desempenho em relação à solução existente atualmente. A flexibilidade das políticas de distribuição é destacada através da construção de uma política, cujo objetivo é melhorar a eficiência no consumo de energia de clusters. Dentre as contribuições do trabalho está a criação de uma nova arquitetura de software que atua como facilitadora para a criação de políticas de distribuição de requisições mais eficiente para web services / SOA is becoming a widespread approach to develop systems. High demand problems may appear in huge systems where SOA and web services are used. This problems can be solved by means of distributed architectures like clusters. This work presents the proposal of a new architecture for request distribution in web service clusters. The proposed architecture provides flexible request distribution. It allows the use of several policies, these related to different objectives, applications and platforms. The architecture\'s dynamic feature enables decisions based on states of the cluster\'s elements, in a transparent way, under clients\' point of view. The architecture was tested using a prototype that implements the proposed ideas in this work. The objectives of the proposal were reached by the prototype and still shown performance improving in many cases, when comparing to an existing solution. The use of a novel policy, related to energetic efficiency for clusters, is also shown on the experiments related to flexibility. Among architecture\'s contributions is a novel software architecture that acts as a facility to create and to test more efficient web services policies

Covariate adjustment is common in the analysis of randomised trials, and can increase statistical power without increasing sample size. Published research on covariate adjustment, and guidance for choosing covariates, focusses on trials where individuals are randomised to treatments. In cluster randomised trials (CRTs) clusters of individuals are randomised. Valid analyses of CRTs account for the structure imposed by cluster randomisation. There is limited published research on the e ects of covariate adjustment, or guidance for choosing covariates, in analyses of CRTs. I summarise existing guidance for choosing covariates in individually randomised trials and CRTs, and review the methods used to investigate the e ects of covariate adjustment. I review the use of adjusted analyses in published CRTs. I use simulation, analytic methods, and analyses of trial data to investigate the e ects of covariate adjustment in mixed models. I use these results to form guidance for choosing covariates in analyses of CRTs. Guidance to choose covariates a priori and adjust for covariates used to stratify randomisation is also applicable to CRTs. I provide guidance speci c to CRTs using linear and logistic mixed models. Cluster size, the intra-cluster correlations (ICCs) of the outcome and covariate, and the strength of the relationship between the outcome and covariate in uence the power of adjusted analyses and the precision of treatment e ect estimates. An a priori estimate of the product of cluster size and the ICC of the outcome can be used to assist choosing covariates. When this product is close to one, adjusting for a cluster level covariate or a covariate with a negligible ICC provide similar increases in power. For smaller values of this product, adjusting for a cluster level covariate gives minimal increases in power. The use of separate withincluster and contextual covariate e ect parameters may increase power further in some circumstances.

Este trabalho descreve um projeto simples de gerenciamento de clusters que apresenta uma interface de usuário para as tarefas mais comuns de uso e gerenciamento de um cluster utilizado como máquina paralela. A partir do estudo de vários softwares existentes hoje, o sistema projetado foi adequado às necessidades do cluster do Laboratório de Processamento Paralelo Aplicado do Instituto de Física de São Carlos. O sistema é baseado em páginas HTML e scripts CGI. O uso de HTML e CGI se demonstrou apropriado para o desenvolvimento desse tipo de sistemas. / This work describes a simple cluster management system that operates as a user interface for some common user and manager tasks performed on a cluster used as parallel machine. We studied some cluster management systems from the literature and then designed a system with the needs of our research laboratory in mind. The system was implemented using HTML pages and CGI scripts. The use of HTML and CGI was found adequate for this type of systems.

A demanda por alto desempenho é um desafio enfrentado por diversas aplicações científicas. Nesse sentido, ambientes para processamento distribuído, tais como, clusters e grades computacionais, têm sido desenvolvidos para prover suporte ao uso de diversos recursos simultaneamente para uma mesma aplicação. Aplicações computacionalmente intensivas são organizadas em workflows e executadas com suporte de middlewares para abstrair a complexidade de uso de tais ambientes. Em ambientes de grade computacional, a execução de workflows contendo tarefas sequenciais e tarefas com paralelismo interno, obtendo bom desempenho, é um desafio, devido à heterogeneidade e comportamento dinâmico do ambiente. Nesse sentido, o escalonamento de workflows em ambientes de grade computacional é essencial. O problema de escalonamento de tarefas, em sua forma geral, é NPCompleto, dessa forma, o estudo do escalonamento de workflows em ambientes de grade computacional é fundamental para aprimorar a execução de aplicações computacionalmente intensivas. O objetivo dessa tese é propor estratégias de escalonamento de workflows, que exploram os seguintes aspectos: Avaliação da possibilidade de executar cada tarefa com paralelismo interno usando recursos de múltiplos clusters; Adaptação de planos de escalonamento no momento da submissão de novos workflows. Foram desenvolvidas duas estratégias: a primeira é uma estratégia para escalonamento estático de workflows, que considera o ambiente dedicado a execução de um workflow. A segunda foi desenvolvida para ser utilizada em conjunto com a primeira, para melhorar o tempo de resposta de múltiplos workflows que podem ser submetidos em diferentes momentos. As estratégias propostas foram avaliadas em um ambiente de simulação. / The demand for high performance is a common problem in many scientific applications. In this sense, distributed processing environments such as cluster, grid computing and multi-cluster environments have been developed to provide support for the use of several resources simultaneously for the same application. Computationally intensive applications are structured as workflows and executed with the support of middleware to abstract the complexity of using such environments. In grid computing environments the execution of workflows containing sequential and parallel tasks, with good performance is a challenge due to the heterogeneity and dynamic behavior of the environment. In this sense, the scheduling of workflows on grid computing environments is essential. The task scheduling problem in its general form is NP-Complete, in this sense, the study concerning workflow scheduling in grid computing environments is fundamental to improve the performance of computationally intensive applications. The aim of this thesis is to propose strategies for scheduling workflows that exploit the following aspects: Explore the possibility of performing single parallel tasks using multiple clusters; Adaptation plans escalation in accordance with the submission of new workflows. Two strategies were developed: the first one is a strategy for static scheduling of workflows, which considers a dedicated environment to the execution of a workflow. The second one was developed to use in conjunction with the first one, in order to improve the response time of multiple workflows that can be submitted at different times. The proposed strategies were evaluated in a simulation environment.

Sistemas de Recomendação ajudam na personalização de sites na Internet oferecendo conteúdo ou produtos específicos aos usuários. Com dispositivos móveis, aumentou o interesse do usuário em ter recomendações personalizadas de locais para ir de acordo com o seu histórico de navegação e avaliações como restaurantes e pontos turísticos. Para que as recomendações personalizadas por locais sejam mais precisas é necessário contextualizá-las de acordo com o interesse do usuário que caracterizado por locais que ele visitou e por regiões de interesse como moradia, onde trabalha ou mesmo onde passará férias. Várias técnicas de contextualização utilizaram todos os locais que o usuário visitou para geração da recomendação contextual do local, outras técnicas trabalham na arquitetura híbrida. Muitas assumem que é necessário a posição exata do usuário para que as recomendações sejam online, o que muitas vezes não é possível por limitações técnicas ou mesmo indisponibilização do usuário por questões de privacidade. O objetivo principal deste trabalho é geração de recomendações usando multicontextos de forma offline, gerando vários contextos de cada usuário. Os locais são recomendados utilizando apenas dados históricos, sem a localização exata no usuário do momento da recomendação. Para atingir este objetivo foram utilizadas técnicas de clustering para mapeamento e divisão dos contextos em regiões indicando o interesse do usuário gerando a recomendação final dos locais a partir de um método híbrido de recomendação que usa filtragem colaborativa e a recomendação contextual proposta. Os resultados mostraram que a técnica proposta apresenta recomendações melhores do que apenas a recomendação colaborativa pura e, para usuários assíduos, as recomendações são melhores do que as técnicas base usadas para comparação. / Recommender Systems help in web sites personalization, offering specific content or products to users. With mobile devices, user interest in Point-of-Interest (POI) recommendation has increased to receive recommendations about places to go according to your navigation and evaluation history in the web site. POI recommendation are improved by contextualizing according to users interest, based on places to where user has been and on regions of interest such as the region where the user lives, works or the region intends go on vacation. Many contextualization techniques use all places that user visited for generation of POI contextual recommendation. Other techniques use hybrid architectures and many of them assume that is necessary the exact point where the user is for online recommendation and this in not possible always due technical limitations or user privacy. The main objective of this work is the offline generation of recommendations using multicontexts. Places to be recommended use only user historical data, without the user current localization at the moment of recommendation. Several techniques have been used for clustering for mapping and division of contexts in regions, indicating the user interests and, finally, generating the final recommendation using a hybrid method with collaborative filtering and contextual recommendation proposed. The results indicate that the proposed technique builds better recommendations than the pure collaborative filtering technique and for heavy users the proposed technique has better results the baseline technique used for comparison.

Notre recherche pose la problématique des effets de la politique industrielle sur la localisation d’entreprises, dans le cadre de la France et des firmes des pays investisseurs en France. Notre thèse a pour but d’étudier d’abord les éléments essentiels de la localisation d’entreprises et pour cela, d’en mesurer et analyser les variables. Nous évaluons ensuite les effets de la politique industrielle d’un côté, sur la localisation à travers une analyse statistique, en comparant le degré d’attractivité de la France et sa politique industrielle avec les pays investisseurs en France ; de l’autre, à travers une étude économétrique qui identifie les déterminants existants de la localisation parmi lesquels surtout, la politique industrielle mise en place par le gouvernement pour favoriser l’attractivité de la localisation d’entreprises. Les résultats statistiques et économétriques montrent que les politiques industrielles – comme la taxe professionnelle et la prime d’aménagement du territoire – ont peu d’impact sur la localisation d’entreprises. / This research raises the question of the effects of industrial policies on the localization of companies, more specifically in the case of France and of foreign companies investing in France. The dissertation studies the elements essential to company localization, first through statistical analysis, by comparing both France’s and French industrial policies’ attraction with countries investing in France; then through an econometric study which identifies the existing determinants of localization, among which we find the industrial policy set up by the administration in order to influence company localization. The statistical and econometric results show that industrial policies such as the company taxation system [Taxe Professionnelle] and the land settlement incentives [Prime d’Aménagement du Territoire] have little impact on company localization.

In this paper, a similarity-driven cluster merging method is proposed for unsupervised fuzzy clustering. The cluster merging method is used to resolve the problem of cluster validation. Starting with an overspecified number of clusters in the data, pairs of similar clusters are merged based on the proposed similarity-driven cluster merging criterion. The similarity between clusters is calculated by a fuzzy cluster similarity matrix, while an adaptive threshold is used for merging. In addition, a modified generalized objective function is used for prototype-based fuzzy clustering. The function includes the p-norm distance measure as well as principal components of the clusters. The number of the principal components is determined automatically from the data being clustered. The performance of this unsupervised fuzzy clustering algorithm is evaluated by several experiments of an artificial data set and a gene expression data set. / Singapore-MIT Alliance (SMA)

Impacts of high kinetic energy massive gold clusters (~ 500 keV Au400+4) exhibit significantly enhanced secondary ion yields relative to traditional atomic or polyatomic primary ions (e.g. Au3 and C60). The one-of-a-kind instrument used to generate these hypervelocity nanoparticles (~2 nm diameter, ~30 km/s) and monitor emissions from their impacts (SIMS) is described in detail for the first time. The projectile range of 520 keV Au400+4 is measured to be ~20 nm in amorphous carbon and projectile disintegration is observed at the exit of carbon foils as thin as 5 nm. These experiments were performed by monitoring carbon cluster ions emitted from both sides of a foil impacted by the projectile. Surprisingly, clusters emitted in the forward direction are larger than those emitted backward. The composition of the mass spectra is shown to depend on both the thickness of the foil and the size of the projectile. Secondary ion yields for a variety of materials including peptides, lipids, drugs, polymers, inorganic salts, and various small molecules have been measured and molecular ion yields for many of these species exceed unity. Multiplicity measurements show that up to seven molecular ions of leucine-enkephalin (YGGFL) can be detected from the impact of a single projectile. SI yields measured with ~500 keV Au400+4 are generally one to two orders of magnitude greater than those obtained with 130 keV Au3+ and 50 keV C60+ projectiles. The high molecular ion yields observed suggest the internal energies of ions emitted from massive cluster impacts are relatively low. In order to address this hypothesis, a novel method for measuring secondary ion internal energies was developed using a series of benzylpyridinium salts. Using this method, the internal energies were measured to be ~0.19 eV/atom, which is a factor of five less than that seen in atomic-SIMS. Sample metallization is shown to be ineffective for further increasing secondary ion yields with Au400, despite observations from previous molecular dynamic simulations. Coincidence mass spectrometry is applied to nanometric chemical segregations found on samples coated with thin layers of gold and silver. It is possible to measure the surface coverages of the metallic and underlying organic layers using mass spectrometry in a non-imaging mode.

In this thesis I examine clustering evaluation, with a subfocus on text clusterings specifically. The principal work of this thesis is the development, analysis, and testing of a new internal clustering quality measure called informativeness. I begin by reviewing clustering in general. I then review current clustering quality measures, accompanying this with an in-depth discussion of many of the important properties one needs to understand about such measures. This is followed by extensive document clustering experiments that show problems with standard clustering evaluation practices. I then develop informativeness, my new internal clustering quality measure for estimating the clarity of clusterings. I show that informativeness, which uses classification accuracy as a proxy for human assessment of clusterings, is both theoretically sensible and works empirically. I present a generalization of informativeness that leverages external clustering quality measures. I also show its use in a realistic application: email spam filtering. I show that informativeness can be used to select clusterings which lead to superior spam filters when few true labels are available. I conclude this thesis with a discussion of clustering evaluation in general, informativeness, and the directions I believe clustering evaluation research should take in the future.