904 resultados para Full-Time Work
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Com o aumento de plataformas móveis disponíveis no mercado e com o constante incremento na sua capacidade computacional, a possibilidade de executar aplicações e em especial jogos com elevados requisitos de desempenho aumentou consideravelmente. O mercado dos videojogos tem assim um cada vez maior número de potenciais clientes. Em especial, o mercado de jogos massive multiplayer online (MMO) tem-se tornado muito atractivo para as empresas de desenvolvimento de jogos. Estes jogos suportam uma elevada quantidade de jogadores em simultâneo que podem estar a executar o jogo em diferentes plataformas e distribuídos por um "mundo" de jogo extenso. Para incentivar a exploração desse "mundo", distribuem-se de forma inteligente pontos de interesse que podem ser explorados pelo jogador. Esta abordagem leva a um esforço substancial no planeamento e construção desses mundos, gastando tempo e recursos durante a fase de desenvolvimento. Isto representa um problema para as empresas de desenvolvimento de jogos, e em alguns casos, e impraticável suportar tais custos para equipas indie. Nesta tese e apresentada uma abordagem para a criação de mundos para jogos MMO. Estudam-se vários jogos MMO que são casos de sucesso de modo a identificar propriedades comuns nos seus mundos. O objectivo e criar uma framework flexível capaz de gerar mundos com estruturas que respeitam conjuntos de regras definidas por game designers. Para que seja possível usar a abordagem aqui apresentada em v arias aplicações diferentes, foram desenvolvidos dois módulos principais. O primeiro, chamado rule-based-map-generator, contem a lógica e operações necessárias para a criação de mundos. O segundo, chamado blocker, e um wrapper à volta do módulo rule-based-map-generator que gere as comunicações entre servidor e clientes. De uma forma resumida, o objectivo geral e disponibilizar uma framework para facilitar a geração de mundos para jogos MMO, o que normalmente e um processo bastante demorado e aumenta significativamente o custo de produção, através de uma abordagem semi-automática combinando os benefícios de procedural content generation (PCG) com conteúdo gráfico gerado manualmente.
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Project work presented as a partial requirement to obtain a Master Degree in Information Management
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Dissertação para obtenção do Grau de Doutor em Biologia
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering
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Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Human Activity Recognition systems require objective and reliable methods that can be used in the daily routine and must offer consistent results according with the performed activities. These systems are under development and offer objective and personalized support for several applications such as the healthcare area. This thesis aims to create a framework for human activities recognition based on accelerometry signals. Some new features and techniques inspired in the audio recognition methodology are introduced in this work, namely Log Scale Power Bandwidth and the Markov Models application. The Forward Feature Selection was adopted as the feature selection algorithm in order to improve the clustering performances and limit the computational demands. This method selects the most suitable set of features for activities recognition in accelerometry from a 423th dimensional feature vector. Several Machine Learning algorithms were applied to the used accelerometry databases – FCHA and PAMAP databases - and these showed promising results in activities recognition. The developed algorithm set constitutes a mighty contribution for the development of reliable evaluation methods of movement disorders for diagnosis and treatment applications.
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Enhanced biological phosphorus removal (EBPR) is the most economic and sustainable option used in wastewater treatment plants (WWTPs) for phosphorus removal. In this process it is important to control the competition between polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs), since EBPR deterioration or failure can be related with the proliferation of GAOs over PAOs. This thesis is focused on the effect of operational conditions (volatile fatty acid (VFA) composition, dissolved oxygen (DO) concentration and organic carbon loading) on PAO and GAO metabolism. The knowledge about the effect of these operational conditions on EBPR metabolism is very important, since they represent key factors that impact WWTPs performance and sustainability. Substrate competition between the anaerobic uptake of acetate and propionate (the main VFAs present in WWTPs) was shown in this work to be a relevant factor affecting PAO metabolism, and a metabolic model was developed that successfully describes this effect. Interestingly, the aerobic metabolism of PAOs was not affected by different VFA compositions, since the aerobic kinetic parameters for phosphorus uptake, polyhydroxyalkanoates (PHAs) degradation and glycogen production were relatively independent of acetate or propionate concentration. This is very relevant for WWTPs, since it will simplify the calibration procedure for metabolic models, facilitating their use for full-scale systems. The DO concentration and aerobic hydraulic retention time (HRT) affected the PAO-GAO competition, where low DO levels or lower aerobic HRT was more favourable for PAOs than GAOs. Indeed, the oxygen affinity coefficient was significantly higher for GAOs than PAOs, showing that PAOs were far superior at scavenging for the often limited oxygen levels in WWTPs. The operation of WWTPs with low aeration is of high importance for full-scale systems, since it decreases the energetic costs and can potentially improve WWTP sustainability. Extended periods of low organic carbon load, which are the most common conditions that exist in full-scale WWTPs, also had an impact on PAO and GAO activity. GAOs exhibited a substantially higher biomass decay rate as compared to PAOs under these conditions, which revealed a higher survival capacity for PAOs, representing an advantage for PAOs in EBPR processes. This superior survival capacity of PAOs under conditions more closely resembling a full-scale environment was linked with their ability to maintain a residual level of PHA reserves for longer than GAOs, providing them with an effective energy source for aerobic maintenance processes. Overall, this work shows that each of these key operational conditions play an important role in the PAO-GAO competition and should be considered in WWTP models in order to improve EBPR processes.
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Double Degree.