977 resultados para Telecomunicações


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This Master s Thesis proposes the application of Data Envelopment Analysis DEA to evaluate economies of scale and economies of scope in the performance of service teams involved with installation of data communication circuits, based on the study of a major telecommunication company in Brazil. Data was collected from the company s Operational Performance Division. Initial analysis of a data set, including nineteen installation teams, was performed considering input oriented methods. Subsequently, the need for restrictions on weights is analyzed using the Assurance Region method, checking for the existence of zero-valued weights. The resulting returns to scale are then verified. Further analyses using the Assurance Region Constant (AR-I-C) and Variable (AR-I-V) models verify the existence of variable, rather than constant, returns to scale. Therefore, all of the final comparisons use scores obtained through the AR-I-V model. In sequence, we verify if the system has economies of scope by analyzing the behavior of the scores in terms of individual or multiple outputs. Finally, conventional results, used by the company in study to evaluate team performance, are compared to those generated using the DEA methodology. The results presented here show that DEA is a useful methodology for assessing team performance and that it may contribute to improvements on the quality of the goal setting procedure.

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This Master s Thesis proposes the application of Data Envelopment Analysis DEA to evaluate the performance of sales teams, based on a study of their coverage areas. Data was collected from the company contracted to distribute the products in the state of Ceará. Analyses of thirteen sales coverage areas were performed considering first the output-oriented constant return to scale method (CCR-O), then this method with assurance region (AR-O-C) and finally the method of variable returns to scale with assurance region (AR-O-V). The method used in the first approach is shown to be inappropriate for this study, since it inconveniently generates zero-valued weights, allowing that an area under evaluation obtain the maximal score by not producing. Using weight restrictions, through the assurance region methods AR-O-C and AR-O-V, decreasing returns to scale are identified, meaning that the improvement in performance is not proportional to the size of the areas being analyzed. Observing data generated by the analysis, a study is carried out, aiming to design improvement goals for the inefficient areas. Complementing this study, GDP data for each area was compared with scores obtained using AR-O-V analysis. The results presented in this work show that DEA is a useful methodology for assessing sales team performance and that it may contribute to improvements on the quality of the management process.

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This dissertation describes the use of new Technologies of the Areas of Telecommunications, Networks and Industrial Automation for increase of the Operational Safety and obtaining of Operational Improvements in the Platforms Petroliferous Offshore. The presented solution represents the junction of several modules of these areas, making possible the Supervision and Contrai of the Platforms Petroliferous Offshore starting from an Station Onshore, in way similar to a remote contral, by virtue of the visualization possibility and audition of the operational area through cameras and microphones, looking the operator of the system to be "present" in the platform. This way, it diminishes the embarked people's need, increasing the Operational Safety. As consequence, we have the obtaining of Operational Improvements, by virtue of the use of a digital link of large band it releases multi-service. In this link traffic simultaneously digital signs of data (Ethernet Network), telephony (Phone VoIP), image and sound

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This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

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Incluye Bibliografía

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A inovação tecnológica trazida pela digitalização das transmissões de rádio e TV acentua a necessidade de novos formatos de regulação e não dispensa a atuação do Estado. Diante deste contexto, deve-se considerar que a reformulação do quadro legal das comunicações no Brasil traz a possibilidade de se instituir um órgão regulador não apenas de fomento, mas de regulação e fiscalização dos serviços públicos de radiodifusão. No mundo, existem pelo menos 84 órgãos dessa natureza, em 54 países. No Reino Unido, o caso do Ofcom (Offi ce of Communications) pode trazer referências relevantes para o Brasil, que apresenta obstáculos culturais e institucionais a serem devidamente enfrentados na luta pela constituição de um serviço público de televisão nos moldes das bem-sucedidas experiências européias. Este artigo sintetiza lições trazidas pela construção do atual quadro regulatório do Reino Unido e da União Européia e analisa as barreiras à implementação deste modelo no Brasil.

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

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A reestruturação do setor de telecomunicações brasileiro é o tema desse trabalho. Essa mudança veio acompanhada da privatização do SISTEMA TELEBRÁS, monopólio estatal organizado em diversas subsidiárias, que forneciam os serviços através de uma rede de telecomunicações interligada em todo o território nacional (PIRES, 1999). Segundo REED (1997), privatização pode ser entendida como um processo através do qual os governos vendem suas empresas estatais na totalidade ou em blocos de ações a investidores privados locais ou internacionais. Apesar de ter sido iniciada ainda nos anos 80, a privatização brasileira só ganhou destaque quando chegou aos serviços públicos na segunda metade da década de 90, trazendo implicações micro e macroeconômicas, tornando-se necessário melhorar as instituições e o sistema de regulação dos setores. O objetivo do estudo é analisar a mudança ocorrida no setor de telecomunicações no Brasil, desde a criação da Telebrás nos anos 70 até a sua privatização; o que promoveu a transformação de um sistema estatal sem regulamentação e freqüentemente ineficiente para um novo setor, que necessitaria de grandes investimentos e esforços para atingir as metas de desenvolvimento

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

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