994 resultados para Data Organization
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Trabalho de Projeto apresentado ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do grau de Mestre em Auditoria Orientado por: Doutora Alcina Augusta de Sena Portugal Dias
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Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientada por Prof. Doutor José Freitas Santos
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Um dos grandes desafios da atualidade reside em construir uma escola inclusiva para todos, respeitando as diferenças entre os alunos e procurando dar resposta a todas as suas necessidades educativas, através do acesso igualitário a uma educação de qualidade, no sentido de uma preparação para a vida social e profissional ao longo da vida. Desta forma, é necessária uma mudança não só na maneira de pensar como também nas práticas dos agentes educativos, no sentido de adequarem o currículo às necessidades educativas especiais dos alunos. O presente estudo constitui, pois, uma tentativa de conhecer não apenas as conceções dos professores do 1º Ciclo do Ensino Básico sobre a inclusão e as adaptações curriculares para alunos com NEE, mas também as práticas curriculares que desenvolvem quando têm estes alunos nas suas turmas. O trabalho desenvolveu-se através de um estudo de caso, incidindo sobre 6 professores do 1º CEB e respetivas turmas com alunos com NEE incluídos. Como metodologia de recolha de dados utilizámos as técnicas da entrevista, da análise documental e da observação naturalista em contexto de sala de aula. Articulando os resultados das entrevistas com os das observações em sala de aula, podemos concluir que, para que a escola seja efetivamente inclusiva, não basta que os professores adotem este conceito. Algumas das maiores dificuldades que se colocaram aos professores foram a gestão do tempo e a adequação de estratégias no atendimento a todos os alunos, o que decorre da forma de organização do ensino, uma vez que os professores continuam a percecionar o seu papel como transmissores de conteúdos e executores de programas, apostando num ensino unilateral e homogéneo. No entanto, foi possível também verificar algumas formas de diferenciação pedagógica, sobretudo através da adequação da estrutura dos trabalhos individuais, do apoio individualizado do professor aos alunos com mais dificuldades ou da tutoria interpares e da realização de diferentes atividades consoante as necessidades específicas de cada aluno.- ABSTRACT One of today´s main challenges lies on building an inclusive school for everyone, respecting students’ differences, giving an answer to their educational needs through equal access to qualified education, preparing them to their professional future and social life. Consequently, a change is necessary, not only in the way of thinking but also in the practices of the educational agents, to adequate the curriculum to the special educational students’ needs. The present study is an attempt to understand not only the conceptions of the elementary school teachers about the inclusion and the curricular adjustments for students with special educational needs, but also the curricular practices they develop when those students are included in their classes. This work was developed through a study case focused on six elementary school teachers and their respective classes with students with special educational needs included. The data collection methods used were interview techniques, documental analysis and context observation in classroom. Articulating the interview results with the classroom observations we can conclude that for a school to be effectively inclusive, the adoption of those conceptions are not enough. Some of the major difficulties that appear to the teachers were time management and adequate strategies on attending all students, which follows from their teaching organization, since teachers are still carrying their role as pure contents transmitters and programs implementers, investing in a unilateral and homogeneous education. However, it was also possible to ascertain some pedagogical differentiation strategies, mainly through individual work adaptation, direct and individualized teacher’s support to students with more difficulties or by peer tutoring as well as carrying out different activities depending on the specific needs of each student.
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Dissertação para a obtenção do Grau de Mestre em Contabilidade e Finanças Orientadora: Doutora Cláudia Lopes
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This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.
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The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.
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This work addresses the present-day (<100 ka) mantle heterogeneity in the Azores region through the study of two active volcanic systems from Terceira Island. Our study shows that mantle heterogeneities are detectable even when "coeval" volcanic systems (Santa Barbara and Fissural) erupted less than 10 km away. These volcanic systems, respectively, reflect the influence of the Terceira and D. Joao de Castro Bank end-members defined by Beier et at (2008) for the Terceira Rift Santa Barbara magmas are interpreted to be the result of mixing between a HIMU-type component, carried to the upper mantle by the Azores plume, and the regional depleted MORB magmas/source. Fissural lavas are characterized by higher Ba/Nb and Nb/U ratios and less radiogenic Pb-206/Pb-204, Nd-143/Nd-144 and Hf-176/Hf-177, requiring the small contribution of delaminated sub-continental lithospheric mantle residing in the upper mantle. Published noble gas data on lavas from both volcanic systems also indicate the presence of a relatively undegassed component, which is interpreted as inherited from a lower mantle reservoir sampled by the ascending Azores plume. As inferred from trace and major elements, melting began in the garnet stability field, while magma extraction occurred within the spinel zone. The intra-volcanic system's chemical heterogeneity is mainly explained by variable proportions of the above-mentioned local end-members and by crystal fractionation processes. (C) 2011 Elsevier By. All rights reserved.
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Solubility measurements of quinizarin. (1,4-dihydroxyanthraquinone), disperse red 9 (1-(methylamino) anthraquinone), and disperse blue 14 (1,4-bis(methylamino)anthraquinone) in supercritical carbon dioxide (SC CO2) were carried out in a flow type apparatus, at a temperature range from (333.2 to 393.2) K and at pressures from (12.0 to 40.0) MPa. Mole fraction solubility of the three dyes decreases in the order quinizarin (2.9 x 10(-6) to 2.9.10(-4)), red 9 (1.4 x 10(-6) to 3.2 x 10(-4)), and blue 14 (7.8 x 10(-8) to 2.2 x 10(-5)). Four semiempirical density based models were used to correlatethe solubility of the dyes in the SC CO2. From the correlation results, the total heat of reaction, heat of vaporization plus the heat of solvation of the solute, were calculated and compared with the results presented in the literature. The solubilities of the three dyes were correlated also applying the Soave-Redlich-Kwong cubic equation of state (SRK CEoS) with classical mixing rules, and the physical properties required for the modeling were estimated and reported.
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The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.
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This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.
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In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.
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Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Artística - Especialização em Teatro na Educação
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In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.
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In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.
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Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação, especialidade em Educação Especial, ramo de Problemas de Cognição e Multideficiência