98 resultados para Graphics processing unit programming


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One of the most difficult problems that face researchers experimenting with complex systems in real world applications is the Facility Layout Design Problem. It relies with the design and location of production lines, machinery and equipment, inventory storage and shipping facilities. In this work it is intended to address this problem through the use of Constraint Logic Programming (CLP) technology. The use of Genetic Algorithms (GA) as optimisation technique in CLP environment is also an issue addressed. The approach aims the implementation of genetic algorithm operators following the CLP paradigm.

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This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

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This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

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Clinical education is recognized as being crucial for the training of health professionals. This subject is debated amongst teachers, students and professionals. Besides the clinical and research skills, we look for other competencies such as oratory, creative thinking or leadership. We present the results of a study with 4th graders. It’s a exploratory study; the main purpose was to evaluate the outcomes of a unit of clinical education prepared according a new set of competencies and methodologies. The competencies were seen as valuable. Organization, leading or supporting a colleague, rethinking a program to serve client and family are equally important.

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Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

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A operação dos Mercados de Energia Eléctrica passa, actualmente, por uma profunda reestruturação, com o principal foco nas transacções do sistema de transmissão entre os diferentes agentes. Tendo isso em conta, o serviço de transmissão neste novo esquema de funcionamento do Mercado de Energia Eléctrica deve ser provido de máxima eficiência económica, atendendo sempre às restrições de segurança do sistema. Com esta reorganização do sector eléctrico da última década surgiu também a necessidade de rever os modelos tradicionais de optimização económica do Sistema Eléctrico de Energia, como por exemplo o despacho e prédespacho (unit commitment). A reestruturação e liberalização dos mercados de energia eléctrica trouxeram novas restrições a alguns dos problemas tradicionais associados aos Sistemas Eléctricos de Energia. Um desses problemas é o Escalonamento da Produção de Energia Eléctrica, que no contexto actual, implica quase sempre negociação entre os diferentes agentes do mercado e consequentemente reescalonamento. A maioria dos métodos usados para a resolução do problema não permitem reformular o prédespacho, algo para que a Programação Lógica por Restrições é extremamente adequada. O trabalho desenvolvido nesta dissertação visa criar uma aplicação computacional com base na Programação Lógica por Restrições, através da plataforma ECLiPSe, para resolver o problema do Escalonamento da Produção de Energia Eléctrica dos grupos térmicos, demonstrando assim a versatilidade e flexibilidade deste tipo de programação aplicada a problema combinatoriais deste género.

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An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.

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Actualmente verifica-se que a complexidade dos sistemas informáticos tem vindo a aumentar, fazendo parte das nossas ferramentas diárias de trabalho a utilização de sistemas informáticos e a utilização de serviços online. Neste âmbito, a internet obtém um papel de destaque junto das universidades, ao permitir que alunos e professores possam interagir mais facilmente. A internet e a educação baseada na Web vêm oferecer acesso remoto a qualquer informação independentemente da localização ou da hora. Como consequência, qualquer pessoa com uma ligação à internet, ao poder adquirir informações sobre um determinado tema junto dos maiores peritos, obtém vantagens significativas. Os laboratórios remotos são uma solução muito valorizada no que toca a interligar tecnologia e recursos humanos em ambientes que podem estar afastados no tempo ou no espaço. A criação deste tipo de laboratórios e a sua utilidade real só é possível porque as tecnologias de comunicação emergentes têm contribuído de uma forma muito relevante para melhorar a sua disponibilização à distância. A necessidade de criação de laboratórios remotos torna-se imprescindível para pesquisas relacionadas com engenharia que envolvam a utilização de recursos escassos ou de grandes dimensões. Apoiado neste conceito, desenvolveu-se um laboratório remoto para os alunos de engenharia que precisam de testar circuitos digitais numa carta de desenvolvimento de hardware configurável, permitindo a utilização deste recurso de uma forma mais eficiente. O trabalho consistiu na criação de um laboratório remoto de baixo custo, com base em linguagens de programação open source, sendo utilizado como unidade de processamento um router da ASUS com o firmware OpenWrt. Este firmware é uma distribuição Linux para sistemas embutidos. Este laboratório remoto permite o teste dos circuitos digitais numa carta de desenvolvimento de hardware configurável em tempo real, utilizando a interface JTAG. O laboratório desenvolvido tem a particularidade de ter como unidade de processamento um router. A utilização do router como servidor é uma solução muito pouco usual na implementação de laboratórios remotos. Este router, quando comparado com um computador normal, apresenta uma capacidade de processamento e memória muito inferior, embora os testes efectuados provassem que apresenta um desempenho muito adequado às expectativas.

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In recent years several countries have set up policies that allow exchange of kidneys between two or more incompatible patient–donor pairs. These policies lead to what is commonly known as kidney exchange programs. The underlying optimization problems can be formulated as integer programming models. Previously proposed models for kidney exchange programs have exponential numbers of constraints or variables, which makes them fairly difficult to solve when the problem size is large. In this work we propose two compact formulations for the problem, explain how these formulations can be adapted to address some problem variants, and provide results on the dominance of some models over others. Finally we present a systematic comparison between our models and two previously proposed ones via thorough computational analysis. Results show that compact formulations have advantages over non-compact ones when the problem size is large.

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Background: Temporal lobe epilepsy (TLE) is a neurological disorder that directly affects cortical areas responsible for auditory processing. The resulting abnormalities can be assessed using event-related potentials (ERP), which have high temporal resolution. However, little is known about TLE in terms of dysfunction of early sensory memory encoding or possible correlations between EEGs, linguistic deficits, and seizures. Mismatch negativity (MMN) is an ERP component – elicited by introducing a deviant stimulus while the subject is attending to a repetitive behavioural task – which reflects pre-attentive sensory memory function and reflects neuronal auditory discrimination and perceptional accuracy. Hypothesis: We propose an MMN protocol for future clinical application and research based on the hypothesis that children with TLE may have abnormal MMN for speech and non-speech stimuli. The MMN can be elicited with a passive auditory oddball paradigm, and the abnormalities might be associated with the location and frequency of epileptic seizures. Significance: The suggested protocol might contribute to a better understanding of the neuropsychophysiological basis of MMN. We suggest that in TLE central sound representation may be decreased for speech and non-speech stimuli. Discussion: MMN arises from a difference to speech and non-speech stimuli across electrode sites. TLE in childhood might be a good model for studying topographic and functional auditory processing and its neurodevelopment, pointing to MMN as a possible clinical tool for prognosis, evaluation, follow-up, and rehabilitation for TLE.

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TLE in infancy has been the subject of varied research. Topographical and structural evidence is coincident with the neuronal systems responsible for auditory processing of the highest specialization and complexity. Recent studies have been showing the need of a hemispheric asymmetry for an optimization in central auditory processing (CAP) and acquisition and learning of a language system. A new functional research paradigm is required to study mental processes that require methods of cognitive-sensory information analysis processed in very short periods of time (msec), such as the ERPs. Thus, in this article, we hypothesize that the TLE in infancy could be a good model for topographic and functional study of CAP and its development process, contributing to a better understanding of the learning difficulties that children with this neurological disorder have.

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Alheiras are a traditional, smoked, fermented meat sausage, produced in Portugal, with an undeniable cultural and gastronomic legacy. In this study, we assessed the nutritional value of this product, as well as the influence of different types of thermal processing. Alheiras from Mirandela were submitted to six different procedures: microwave, skillet, oven, charcoal grill, electric fryer and electric grill. Protein, fat, carbohydrate, minerals, NaCl, and cholesterol contents, as well as fatty acid profile were evaluated. The results show that alheiras are not hypercaloric but an unbalanced foodstuff (high levels of proteins and lipids) and the type of processing has a major impact on their nutritional value. Charcoal grill is the healthiest option: less fat (12.5 g/100 g) and cholesterol (29.3 mg/100 g), corresponding to a lower caloric intake (231.8 kcal, less 13% than the raw ones). Inversely, fried alheiras presented the worst nutritional profile, with the highest levels of fat (18.1 g/100 g) and cholesterol (76.0 g/100 g).

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In the last two decades, there was a proliferation of programming exercise formats that hinders interoperability in automatic assessment. In the lack of a widely accepted standard, a pragmatic solution is to convert content among the existing formats. BabeLO is a programming exercise converter providing services to a network of heterogeneous e-learning systems such as contest management systems, programming exercise authoring tools, evaluation engines and repositories of learning objects. Its main feature is the use of a pivotal format to achieve greater extensibility. This approach simplifies the extension to other formats, just requiring the conversion to and from the pivotal format. This paper starts with an analysis of programming exercise formats representative of the existing diversity. This analysis sets the context for the proposed approach to exercise conversion and to the description of the pivotal data format. The abstract service definition is the basis for the design of BabeLO, its components and web service interface. This paper includes a report on the use of BabeLO in two concrete scenarios: to relocate exercises to a different repository, and to use an evaluation engine in a network of heterogeneous systems.

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Several Web-based on-line judges or on-line programming trainers have been developed in order to allow students to train their programming skills. However, their pedagogical functionalities in the learning of programming have not been clearly defined. EduJudge is a project which aims to integrate the “UVA On-line Judge”, an existing on-line programming trainer with an important number of problems and users, into an effective educational environment consisting of the e-learning platform Moodle and the competitive learning tool QUESTOURnament. The result is the EduJudge system which allows teachers to apply different pedagogical approaches using a proven e-learning platform, makes problems easy to search through an effective search engine, and provides an automated evaluation of the solutions submitted to these problems. The final objective is to provide new learning strategies to motivate students and present programming as an easy and attractive challenge. EduJudge has been tried and tested in three algorithms and programming courses in three different Engineering degrees. The students’ motivation and satisfaction levels were analysed alongside the effects of the EduJudge system on students’ academic outcomes. Results indicate that both students and teachers found that among other multiple benefits the EduJudge system facilitates the learning process. Furthermore, the experi- ment also showed an improvement in students’ academic outcomes. It must be noted that the students’ level of satisfaction did not depend on their computer skills or their gender.

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A repository of learning objects is a system that stores electronic resources in a technology-mediated learning process. The need for this kind of repository is growing as more educators become eager to use digital educa- tional contents and more of it becomes available. The sharing and use of these resources relies on the use of content and communication standards as a means to describe and exchange educational resources, commonly known as learning objects. This paper presents the design and implementation of a service-oriented reposi- tory of learning objects called crimsonHex. This repository supports new definitions of learning objects for specialized domains and we illustrate this feature with the definition of programming exercises as learning objects and its validation by the repository. The repository is also fully compliant with existing commu- nication standards and we propose extensions by adding new functions, formalizing message interchange and providing a REST interface. To validate the interoperability features of the repository, we developed a repository plug-in for Moodle that is expected to be included in the next release of this popular learning management system.