12 resultados para Android Market application


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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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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 Finance from the NOVA – School of Business and Economics

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MSC Dissertation in Computer Engineering

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão de Sistemas Ambientais

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Critical Issues in Environmental Taxation: International and Comparative Perspectives: Volume VI, 699-715

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Biotecnologia

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

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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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We present a calibrated model of the UK mobile telephony market with four mobile networks; calls to and from the fixed network; network-based price discrimination; and call externalities. Our results show that reducing mobile termination rates broadly in line with the recent European Commission Recommendation to either pure long-run incremental cost ; reciprocal termination charges with fixed networks; or Bill & Keep (i.e. zero termination rates), increases social welfare, consumer surplus and networks profits. Depending on the strength of call externalities, social welfare may increase by as much as £ 990 million to £ 4.5 billion per year, with Bill & Keep leading to the highest increase in welfare. We also apply the model to estimate the welfare effects of the 2010 merger between Orange and T-Mobile under different scenarios concerning MTRs, and predict that consumer surplus decreases strongly.

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This paper presents an application of an Artificial Neural Network (ANN) to the prediction of stock market direction in the US. Using a multilayer perceptron neural network and a backpropagation algorithm for the training process, the model aims at learning the hidden patterns in the daily movement of the S&P500 to correctly identify if the market will be in a Trend Following or Mean Reversion behavior. The ANN is able to produce a successful investment strategy which outperforms the buy and hold strategy, but presents instability in its overall results which compromises its practical application in real life investment decisions.

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In the past few years, prompted by the globalization and the quality and ease of travel, the world has witnessed a boom in the tourism sector. The forecast is that this tendency will continue in the upcoming years, representing a set of opportunities for companies operating in this business area. Boost Tourism operates in the tourism entertainment industry. Its revenues growth has been exponential so the founders decided that it was time to take it to new heights. This Work Project aims to study three alternative growth strategies and, based on a comprehensive analysis of the industry and the market, provide recommendations to outline the optimal expansion path.