978 resultados para text message analysis and question-answering system


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Most of distributed generation and smart grid research works are dedicated to network operation parameters studies, reliability, etc. However, many of these works normally uses traditional test systems, for instance, IEEE test systems. This paper proposes voltage magnitude and reliability studies in presence of fault conditions, considering realistic conditions found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12-bus sub-transmission network.

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This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

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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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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 Economics from the NOVA – School of Business and Economics

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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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This thesis focused on the study and treatment of a 19th century female portrait in oil from ECOMUSEU Municipal do Seixal, Portugal. The portrait, which depicts Isabel Maria Lourenço Affonso was in poor condition and a large strip of paint and canvas was missing (approximately 9cm by 66cm, almost 11% of the total surface area). The portrait is a companion piece to a male portrait (the relationship was established as part of this study), therefore a technical study of both paintings was considered essential to support the choices made during the treatment. The project involved three main areas: - The study of the history, condition, materials and techniques of both paintings. This allowed their comparison and understanding of their relationship; - The treatment of Isabel Maria Lourenço Affonso. The choices made and problems encountered are described. - The production of a replacement for the missing strip of paint and canvas. The practical solution developed to overcome such an unusual challenge is described along with the creative and flexible thinking required. Because not all traditional infill materials cope well on a mechanical level with thin layers over a very large surface (many are too brittle), strict criteria had to be employed to choose the appropriate material. The primary goal was to find a fill which would remain flexible and be capable of accepting surface texture, such that there would be a good visual match with the painting. Analysis and testing was carried out to evaluate the physical properties of the fill material chosen, BEVA® Gesso-P. The successful creation of the replacement strip has resulted in two publications and one presentation: Publication pending in The Picture Restorer, Leslie Carlyle, Raquel Marques, Isabel Pombo Cardoso and Sara Babo, “Creating a Textured Replacement Strip for the Missing Lower Portion of an Oil Portrait: Problem Solving and Practical Solutions”. Abstract accepted for presentation and publication, International Meeting on Retouching of Cultural Heritage (2RECH), Raquel Marques, Leslie Carlyle and Isabel Pombo Cardoso, “Textured Replacement Strip for a Missing Portion of a Portrait: Problem Solving and Practical Solutions”.

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The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

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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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Although literature is lacking in the topic of internationalization of services, we manage to apply both the Uppsala model and the Eclectic Theory to the healthcare service. A cross-case study analysis with three international hospitals is done in order to define an internationalization pattern and conditions for a successful process. This is then applied to Associação Protectora dos Diabéticos de Portugal with the purpose of defining an internationalization strategy to the Association.