989 resultados para PORTAL WEB - CONGRESOS, CONFERENCIAS, ETC.
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Trabalho de projeto apresentado para o cumprimento dos requisitos necessários à obtenção do grau de Mestre em em Novos Media e Práticas Web
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Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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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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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ciência da Informação e Documentação – Área de especialização em Arquivística
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in Varia, Revista do IHA, N.3 (2007), pp.328-331
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in Varia, Revista do IHA, N.4 (2007), pp.379-382
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Relatório de Estágio apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Novos Media e Práticas Web
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O Kosovo declarou-‐se independente a 17 de Fevereiro de 2008, sendo, neste momento, o segundo país mais recente do mundo, só ultrapassado pelo Sudão do Sul em 2011. Após a desintegração da ex-‐Jugoslávia e todos os conflitos militares que se sucederam, a história do Kosovo, as suas origens, é talvez a que apresenta ainda mais questões por responder. O web-‐documentário “Quem és tu, Kosovo?” trata-‐se de um projecto documental de recolha de histórias de vida, onde o ponto central de cada entrevista é a procura de uma paralelismo entre a identidade dos seus cidadãos e o seu país. Este projecto, e o trabalho desenvolvido pelo jornalista no país, propõem-‐se a ser uma experiência piloto para ser apresentado à população do Kosovo, e não só, com o objectivo de criar um arquivo de histórias do país e aumentar a diversidade de perspectivas identitárias.
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O crescente poder computacional dos dispositivos móveis e a maior eficiência dos navegadores fomentam a construção de aplicações Web mais rápidas e fluídas, através da troca assíncrona de dados em vez de páginas HTML completas. A OutSystems Platform é um ambiente de desenvolvimento usado para a construção rápida e validada de aplicaçõesWeb, que integra numa só linguagem a construção de interfaces de utilizador, lógica da aplicação e modelo de dados. O modelo normal de interação cliente-servidor da plataforma é coerente com o ciclo completo de pedido-resposta, embora seja possível implementar, de forma explícita, aplicações assíncronas. Neste trabalho apresentamos um modelo de separação, baseado em análise estática sobre a definição de uma aplicação, entre os dados apresentados nas páginas geradas pela plataforma e o código correspondente à sua estrutura e apresentação. Esta abordagem permite a geração automática e transparente de interfaces de utilizador mais rápidas e fluídas, a partir do modelo de uma aplicação OutSystems. O modelo apresentado, em conjunto com a análise estática, permite identificar o subconjunto mínimo dos dados a serem transmitidos na rede para a execução de uma funcionalidade no servidor, e isolar a execução de código no cliente. Como resultado da utilização desta abordagem obtém-se uma diminuição muito significativa na transmissão de dados, e possivelmente uma redução na carga de processamento no servidor, dado que a geração das páginasWeb é delegada no cliente, e este se torna apto para executar código. Este modelo é definido sobre uma linguagem, inspirada na da plataforma OutSystems, a partir da qual é implementado um gerador de código. Neste contexto, uma linguagem de domínio específico cria uma camada de abstração entre a definição do modelo de uma aplicação e o respetivo código gerado, tornando transparente a criação de templates clientside e o código executado no cliente e no servidor.
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Ontologies formalized by means of Description Logics (DLs) and rules in the form of Logic Programs (LPs) are two prominent formalisms in the field of Knowledge Representation and Reasoning. While DLs adhere to the OpenWorld Assumption and are suited for taxonomic reasoning, LPs implement reasoning under the Closed World Assumption, so that default knowledge can be expressed. However, for many applications it is useful to have a means that allows reasoning over an open domain and expressing rules with exceptions at the same time. Hybrid MKNF knowledge bases make such a means available by formalizing DLs and LPs in a common logic, the Logic of Minimal Knowledge and Negation as Failure (MKNF). Since rules and ontologies are used in open environments such as the Semantic Web, inconsistencies cannot always be avoided. This poses a problem due to the Principle of Explosion, which holds in classical logics. Paraconsistent Logics offer a solution to this issue by assigning meaningful models even to contradictory sets of formulas. Consequently, paraconsistent semantics for DLs and LPs have been investigated intensively. Our goal is to apply the paraconsistent approach to the combination of DLs and LPs in hybrid MKNF knowledge bases. In this thesis, a new six-valued semantics for hybrid MKNF knowledge bases is introduced, extending the three-valued approach by Knorr et al., which is based on the wellfounded semantics for logic programs. Additionally, a procedural way of computing paraconsistent well-founded models for hybrid MKNF knowledge bases by means of an alternating fixpoint construction is presented and it is proven that the algorithm is sound and complete w.r.t. the model-theoretic characterization of the semantics. Moreover, it is shown that the new semantics is faithful w.r.t. well-studied paraconsistent semantics for DLs and LPs, respectively, and maintains the efficiency of the approach it extends.
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The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.
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In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.