950 resultados para Symbolic Execution


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A transmissão de microrganismos patogénicos pode ocorrer através da sua presença em resíduos de alimentos ou água depositados sobre os utensílios que se encontram em deficientes condições de higienização. Para que seja assegurada a higiene alimentar torna-se essencial a conservação e higienização dos utensílios, desempenhando os manipuladores de alimentos um papel determinante no que diz respeito à execução de um eficaz protocolo de higienização, uma correcta manipulação e a adopção de normas higiénicas que evitem a contaminação dos utensílios. Da totalidade das amostras realizadas aos utensílios alimentares provenientes das duas instituições de ensino pré-escolar analisados neste estudo, 27% encontravam-se contaminadas e num insuficiente estado de higienização devido à presença de microrganismos mesófilos aeróbios a 30ºC em número superior a 100 UFC/peça. Foi verificado a presença de fungos e a pesquisa positiva de enterobactérias e bactérias presumíveis de E. coli. Em ambos os estabelecimentos de ensino, os utensílios constituídos por material plástico apresentaram níveis de contaminação na generalidade superiores em relação aos constituídos por aço inoxidável. O tipo de material e o estado dos utensílios são também aspectos relevantes que podem influenciar o processo de adesão microbiana e consequente formação de biofilme, pelo que na aquisição dos utensílios devem ser consideradas as características inerentes aos diferentes materiais, devendo os mesmos ser substituídos periodicamente devido ao desgaste causado pelo seu frequente uso. Para além disso, os utensílios devem passar constantemente por uma avaliação microbiológica para controlo da eficiência do processo de higienização, contribuindo para a garantia da higiene alimentar e segurança do alimento. A garantia da higiene alimentar constitui uma base importante em idades de maior vulnerabilidade.

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Introdução – Numa era em que os tratamentos de Radioterapia Externa (RTE) exigem cada vez mais precisão, a utilização de imagem médica permitirá medir, quantificar e avaliar o impacto do erro provocado pela execução do tratamento ou pelos movimentos dos órgãos. Objetivo – Analisar os dados existentes na literatura acerca de desvios de posicionamento (DP) em patologias de cabeça e pescoço (CP) e próstata, medidos com Cone Beam Computed Tomography (CBCT) ou Electronic Portal Image Device (EPID). Metodologia – Para esta revisão da literatura foram pesquisados artigos recorrendo às bases de dados MEDLINE/PubMed e b-on. Foram incluídos artigos que reportassem DP em patologias CP e próstata medidos através de CBCT e EPID. Seguidamente foram aplicados critérios de validação, que permitiram a seleção dos estudos. Resultados – Após a análise de 35 artigos foram incluídos 13 estudos e validados 9 estudos. Para tumores CP, a média (μ) dos DP encontra-se entre 0,0 e 1,2mm, com um desvio padrão (σ) máximo de 1,3mm. Para patologias de próstata observa-se μDP compreendido entre 0,0 e 7,1mm, com σ máximo de 7,5mm. Discussão/Conclusão – Os DP em patologias CP são atribuídos, maioritariamente, aos efeitos secundários da RTE, como mucosite e dor, que afetam a deglutição e conduzem ao emagrecimento, contribuindo para a instabilidade da posição do doente durante o tratamento, aumentando as incertezas de posicionamento. Os movimentos da próstata devem-se principalmente às variações de preenchimento vesical, retal e gás intestinal. O desconhecimento dos DP afeta negativamente a precisão da RTE. É importante detetá-los e quantificá-los para calcular margens adequadas e a magnitude dos erros, aumentando a precisão da administração de RTE, incluindo o aumento da segurança do doente. - ABSTRACT - Background and Purpose – In an era where precision is an increasing necessity in external radiotherapy (RT), modern medical imaging techniques provide means for measuring, quantifying and evaluating the impact of treatment execution and movement error. The aim of this paper is to review the current literature on the quantification of setup deviations (SD) in patients with head and neck (H&N) or prostate tumors, using Cone Beam Computed Tomography (CBCT) or Electronic Portal Image Device (EPID). Methods – According to the study protocol, MEDLINE/PubMed and b-on databases were searched for trials, which were analyzed using selection criteria based on the quality of the articles. Results – After assessment of 35 papers, 13 studies were included in this analysis and nine were authenticated (6 for prostate and 3 for H&N tumors). The SD in the treatment of H&N cancer patients is in the interval of 0.1 to 1.2mm, whereas in prostate cancer this interval is 0.0 to 7.1mm. Discussion – The reproducibility of patient positioning is the biggest barrier for higher precision in RT, which is affected by geometrical uncertainty, positioning errors and inter or intra-fraction organ movement. There are random and systematic errors associated to patient positioning, introduced since the treatment planning phase or through physiological organ movement. Conclusion – The H&N SD are mostly assigned to the Radiotherapy adverse effects, like mucositis and pain, which affect swallowing and decrease secretions, contributing for the instability of patient positioning during RT treatment and increasing positioning uncertainties. Prostate motion is mainly related to the variation in bladder and rectal filling. Ignoring SD affects negatively the accuracy of RT. Therefore, detection and quantification of SD is crucial in order to calculate appropriate margins, the magnitude of error and to improve accuracy in RTE and patient safety.

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Indian Journal of Gender Studies October 2012 vol. 19 no. 3 437-467

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International Congress Marketing Trends Annual Conference in Paris, 17 – 19 January 2013

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Dissertação apresentada ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Logística Orientada por: Prof. Dr. Pedro Godinho

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This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

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This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

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The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

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To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

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Mestrado em Radiações Aplicadas às Tecnologias da Saúde.

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Projeto de Intervenção apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação - Especialidade Educação Especial

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Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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This paper proposes two meta-heuristics (Genetic Algorithm and Evolutionary Particle Swarm Optimization) for solving a 15 bid-based case of Ancillary Services Dispatch in an Electricity Market. A Linear Programming approach is also included for comparison purposes. A test case based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is used to demonstrate that the use of meta-heuristics is suitable for solving this kind of optimization problem. Faster execution times and lower computational resources requirements are the most relevant advantages of the used meta-heuristics when compared with the Linear Programming approach.