A governança corporativa nos clubes de futebol : um estudo multi-caso baseado nas práticas de governança corporativa dos clubes cariocas

Esta dissertação objetiva mapear as estruturas e as práticas de governança adotadas pelos clubes de futebol profissional no Brasil, aprofundando em estudo de caso o Flamengo, o Vasco da Gama, o Fluminense e o Botafogo. A partir de levantamento da situação econômico-financeira dos clubes brasileiros e da literatura dedicada à governança de associações e de clubes de futebol, foi realizado levantamento de aspectos da governança dispostos no Estatuto dos clubes, e dirigentes anteriores dos clubes foram entrevistados sobre esses aspectos. Para a análise desse material, buscou-se identificar o tratamento vinculado a aspectos fundamentais da boa governança tratados em códigos nacionais e internacionais. Os resultados evidenciaram uma grande diferença entre as estruturas e as práticas de governança dos clubes e aquelas recomendadas pelos códigos, apontando a necessidade de melhorias, mas também de melhores identificação e definição de boas práticas de governança específica para os clubes.

A Informatização da saúde no Brasil: uma análise multi-paper inspirada na teoria ator-rede

As tecnologias da informação e comunicação (TIC) estão presentes nas mais diversas áreas e atividades cotidianas, mas, em que pesem as ações de governos e instituições privadas, a informatização da saúde ainda é um desafio em aberto no Brasil. A situação atual leva a um questionamento sobre as dificuldades associadas à informatização das práticas em saúde, assim como, quais efeitos tais dificuldades têm causado à sociedade Brasileira. Com objetivo de discutir as questões acima citadas, esta tese apresenta quatro artigos sobre processo de informação da saúde no Brasil. O primeiro artigo revisa a literatura sobre TIC em saúde e baseado em duas perspectivas teóricas – estudos Europeus acerca dos Sistemas de Informação em Saúde (SIS) nos Países em Desenvolvimento e estudos sobre Informação e Informática em Saúde, no âmbito do Movimento da Reforma Sanitária –, formula um modelo integrado que combina dimensões de análise e fatores contextuais para a compreensão dos SIS no Brasil. Já o segundo artigo apresenta os conceitos e teóricos e metodológicos da Teoria Ator-Rede (ANT), uma abordagem para o estudo de controvérsias associadas às descobertas científicas e inovações tecnológicas, por meio das redes de atores envolvidos em tais ações. Tal abordagem tem embasado estudos de SI desde 1990 e inspirou as análises dois artigos empíricos desta tese. Os dois últimos artigos foram redigidos a partir da análise da implantação de um SIS em um hospital público no Brasil ocorrida entre os anos de 2010 e 2012. Para a análise do caso, seguiram-se os atores envolvidos nas controvérsias que surgiram durante a implantação do SIS. O terceiro artigo se debruçou sobre as atividades dos analistas de sistema e usuários envolvidos na implantação do SIS. As mudanças observadas durante a implantação do sistema revelam que o sucesso do SIS não foi alcançado pela estrita e técnica execução das atividades incialmente planejadas. Pelo contrário, o sucesso foi construído coletivamente, por meio da negociação entre os atores e de dispositivos de interessamento introduzidos durante o projeto. O quarto artigo, baseado no conceito das Infraestruturas de Informação, discutiu como o sistema CATMAT foi incorporado ao E-Hosp. A análise revelou como a base instalada do CATMAT foi uma condição relevante para a sua escolha durante a implantação do E-Hosp. Além disso, descrevem-se negociações e operações heterogêneas que aconteceram durante a incorporação do CATMAT no sistema E-Hosp. Assim, esta tese argumenta que a implantação de um SIS é um empreendimento de construção coletiva, envolvendo analistas de sistema, profissionais de saúde, políticos e artefatos técnicos. Ademais, evidenciou-se como os SIS inscrevem definições e acordos, influenciando as preferências dos atores na área de saúde.

Supply chain turbulence: the impact of a mid-range event in multi-tier, multi-dimension supply chains

Nota: A autora agradece à Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) pela concessão de bolsa de estudos para o desenvolvimento deste projeto de pesquisa.

Opening ILT blackbox: Exploring recognition-based leadership perceptions with conjoint analysis

Although research on Implicit Leadership Theories (ILT) has put great effort on determining what attributes define a leader prototype, little attention has been given to understanding the relative importance of each of these attributes in the categorization process by followers. Knowing that recognition-based leadership perceptions are the result of the match between followers’ ILTs and the perceived attributes in their actual leaders, understanding how specific prototypical leader attributes impact this impression formation process is particularly relevant. In this study, we draw upon socio-cognitive theories to explore how followers cognitively process the information about a leader’s attributes. By using Conjoint Analysis (CA), a technique that allows us to measure an individual’s trade-offs when making choices about multi-attributed options, we conducted a series of 4 studies with a total of 879 participants. Our results demonstrate that attributes’ importance for individuals’ leadership perceptions formation is rather heterogeneous, and that some attributes can enhance or spoil the importance of other prototypical attributes. Finally, by manipulating the leadership domain, we show that the weighting pattern of attributes is context dependent, as suggested by the connectionist approach to leadership categorization. Our findings also demonstrate that Conjoint Analysis can be a valuable tool for ILT research.

Análise e desenvolvimento de controladores preditivos multivariáveis baseados em multi-modelos bilineares

This work addresses issues related to analysis and development of multivariable predictive controllers based on bilinear multi-models. Linear Generalized Predictive Control (GPC) monovariable and multivariable is shown, and highlighted its properties, key features and applications in industry. Bilinear GPC, the basis for the development of this thesis, is presented by the time-step quasilinearization approach. Some results are presented using this controller in order to show its best performance when compared to linear GPC, since the bilinear models represent better the dynamics of certain processes. Time-step quasilinearization, due to the fact that it is an approximation, causes a prediction error, which limits the performance of this controller when prediction horizon increases. Due to its prediction error, Bilinear GPC with iterative compensation is shown in order to minimize this error, seeking a better performance than the classic Bilinear GPC. Results of iterative compensation algorithm are shown. The use of multi-model is discussed in this thesis, in order to correct the deficiency of controllers based on single model, when they are applied in cases with large operation ranges. Methods of measuring the distance between models, also called metrics, are the main contribution of this thesis. Several application results in simulated distillation columns, which are close enough to actual behaviour of them, are made, and the results have shown satisfactory

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aplicação de sistemas multi-classificadores no diagnóstico de falhas em motores de indução trifásicos

Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

Multi-resolução com fóvea móvel para redução e abstração de dados em tempo real

We propose a new approach to reduction and abstraction of visual information for robotics vision applications. Basically, we propose to use a multi-resolution representation in combination with a moving fovea for reducing the amount of information from an image. We introduce the mathematical formalization of the moving fovea approach and mapping functions that help to use this model. Two indexes (resolution and cost) are proposed that can be useful to choose the proposed model variables. With this new theoretical approach, it is possible to apply several filters, to calculate disparity and to obtain motion analysis in real time (less than 33ms to process an image pair at a notebook AMD Turion Dual Core 2GHz). As the main result, most of time, the moving fovea allows the robot not to perform physical motion of its robotics devices to keep a possible region of interest visible in both images. We validate the proposed model with experimental results

An Intelligent System for Petroleum Well Drilling Cutting Analysis

Cutting analysis is a important and crucial task task to detect and prevent problems during the petroleum well drilling process. Several studies have been developed for drilling inspection, but none of them takes care about analysing the generated cutting at the vibrating shale shakers. Here we proposed a system to analyse the cutting's concentration at the vibrating shale shakers, which can indicate problems during the petroleum well drilling process, such that the collapse of the well borehole walls. Cutting's images are acquired and sent to the data analysis module, which has as the main goal to extract features and to classify frames according to one of three previously classes of cutting's volume. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and efficiency. We used the Optimum-Path Forest (OPF), Artificial Neural Network using Multi layer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC) for this task. The first one outperformed all the remaining classifiers. Recall that we are also the first to introduce the OPF classifier in this field of knowledge. Very good results show the robustness of the proposed system, which can be also integrated with other commonly system (Mud-Logging) in order to improve the last one's efficiency.

Optimization analysis of dual-purpose systems

This paper aims to analyze dual-purpose systems focusing the total cost optimization; a superstructure is proposed to present cogeneration systems and desalination technologies alternatives for the synthesis process. The superstructure consists of excluding components, gas turbines or conventional steam generators with excluding alternatives of supplying fuel for each combustion system. Also, backpressure or condensing/extraction steam turbine for supplying process steam could be selected. Finally one desalination unit chosen between electrically-driven or steam-driven reverse osmosis. multi-effect and multistage flash should be included. The analysis herein performed is based on energy and mass conservation equations, as well as the technological limiting equation of equipment. The results for ten different commercial gas turbines revealed that electrically-driven reverse osmosis was always chosen together with both natural gas and gasified biomass gas turbines. (C) 2009 Elsevier B.V. All rights reserved.

Quantitative characterization of multi-phase materials by digital image processing

An automatic image processing and analysis technique has been developed for quantitative characterization of multi-phase materials. For the development of this technique is used the Khoros system that offers the basic morphological tools and a flexible, visual programming language. These techniques are implemented in a highly user oriented image processing environment that allows the user to adapt each step of the processing to his special requirements.To illustrate the implementation and performance of this technique, images of two different materials are processed for microstructure characterization. The result is presented through the determination of volume fraction of the different phases or precipitates.

Carbon fiber non-crimp multi-axial reinforcement and epoxy mono-component system composite: fatigue behavior

Fiber reinforced polymer composites have been widely applied in the aeronautical field. However, composite processing, which uses unlocked molds, should be avoided in view of the tight requirements and also due to possible environmental contamination. To produce high performance structural frames meeting aeronautical reproducibility and low cost criteria, the Brazilian industry has shown interest to investigate the resin transfer molding process (RTM) considering being a closed-mold pressure injection system which allows faster gel and cure times. Due to the fibrous composite anisotropic and non homogeneity characteristics, the fatigue behavior is a complex phenomenon quite different from to metals materials crucial to be investigated considering the aeronautical application. Fatigue sub-scale specimens of intermediate modulus carbon fiber non-crimp multi-axial reinforcement and epoxy mono-component system composite were produced according to the ASTM 3039 D. Axial fatigue tests were carried out according to ASTM D 3479. A sinusoidal load of 10 Hz frequency and load ratio R = 0.1. It was observed a high fatigue interval obtained for NCF/RTM6 composites. Weibull statistical analysis was applied to describe the failure probability of materials under cyclic loads and fractures pattern was observed by scanning electron microscopy. (C) 2010 Published by Elsevier Ltd.

Utilizando Pesos estáticos e dinâmicos em sistemas multi-classificadores com diferentes níveis de diversidade

Although some individual techniques of supervised Machine Learning (ML), also known as classifiers, or algorithms of classification, to supply solutions that, most of the time, are considered efficient, have experimental results gotten with the use of large sets of pattern and/or that they have a expressive amount of irrelevant data or incomplete characteristic, that show a decrease in the efficiency of the precision of these techniques. In other words, such techniques can t do an recognition of patterns of an efficient form in complex problems. With the intention to get better performance and efficiency of these ML techniques, were thought about the idea to using some types of LM algorithms work jointly, thus origin to the term Multi-Classifier System (MCS). The MCS s presents, as component, different of LM algorithms, called of base classifiers, and realized a combination of results gotten for these algorithms to reach the final result. So that the MCS has a better performance that the base classifiers, the results gotten for each base classifier must present an certain diversity, in other words, a difference between the results gotten for each classifier that compose the system. It can be said that it does not make signification to have MCS s whose base classifiers have identical answers to the sames patterns. Although the MCS s present better results that the individually systems, has always the search to improve the results gotten for this type of system. Aim at this improvement and a better consistency in the results, as well as a larger diversity of the classifiers of a MCS, comes being recently searched methodologies that present as characteristic the use of weights, or confidence values. These weights can describe the importance that certain classifier supplied when associating with each pattern to a determined class. These weights still are used, in associate with the exits of the classifiers, during the process of recognition (use) of the MCS s. Exist different ways of calculating these weights and can be divided in two categories: the static weights and the dynamic weights. The first category of weights is characterizes for not having the modification of its values during the classification process, different it occurs with the second category, where the values suffers modifications during the classification process. In this work an analysis will be made to verify if the use of the weights, statics as much as dynamics, they can increase the perfomance of the MCS s in comparison with the individually systems. Moreover, will be made an analysis in the diversity gotten for the MCS s, for this mode verify if it has some relation between the use of the weights in the MCS s with different levels of diversity

Um ambiente multi-middleware para desenvolvimento de aplicações distribuídas

This work presents a proposal of a multi-middleware environment to develop distributed applications, which abstracts different underlying middleware platforms. This work describes: (i) the reference architecture designed for the environment, (ii) an implementation which aims to validate the specified architecture integrating CORBA and EJB, (iii) a case study illustrating the use of the environment, (iv) a performance analysis. The proposed environment allows interoperability on middleware platforms, allowing the reuse of components of different kinds of middleware platforms in a transparency away to the developer and without major losses in performance. Also in the implementation we developed an Eclipse plugin which allows developers gain greater productivity at developing distributed applications using the proposed environment