Effects of dual-task training on balance and executive functions in Parkinson's disease: A pilot study

The aim of this study was to analyze the efficacy of cognitive-motor dual-task training compared with single-task training on balance and executive functions in individuals with Parkinson's disease. Fifteen subjects, aged between 39 and 75 years old, were randomly assigned to the dual-task training group (n = 8) and single-task training group (n = 7). The training was run twice a week for 6 weeks. The single-task group received balance training and the dual-task group performed cognitive tasks simultaneously with the balance training. There were no significant differences between the two groups at baseline. After the intervention, the results for mediolateral sway with eyes closed were significantly better for the dual-task group and anteroposterior sway with eyes closed was significantly better for the single-task group. The results suggest superior outcomes for the dual-task training compared to the single-task training for static postural control, except in anteroposterior sway with eyes closed.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

ANN based support for distributed energy resources scheduling in smart grids

The future scenarios for operation of smart grids are likely to include a large diversity of players, of different types and sizes. With control and decision making being decentralized over the network, intelligence should also be decentralized so that every player is able to play in the market environment. In the new context, aggregator players, enabling medium, small, and even micro size players to act in a competitive environment, will be very relevant. Virtual Power Players (VPP) and single players must optimize their energy resource management in order to accomplish their goals. This is relatively easy to larger players, with financial means to have access to adequate decision support tools, to support decision making concerning their optimal resource schedule. However, the smaller players have difficulties in accessing this kind of tools. So, it is required that these smaller players can be offered alternative methods to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), intended to support smaller players’ resource scheduling. The used methodology uses a training set that is built using the energy resource scheduling solutions obtained with a reference optimization methodology, a mixed-integer non-linear programming (MINLP) in this case. The trained network is able to achieve good schedule results requiring modest computational means.

Condicionamento acústico e certificação energética de edifícios

O presente relatório desenvolvido no âmbito do estágio curricular realizado na empresa – ASL & Associados, com duração de seis meses, tem como objetivo a elaboração e desenvolvimento de estudos acústicos de edifícios e elaboração de certificados energéticos de edifícios existentes. Inicialmente, será feita uma descrição da empresa acolhedora expondo a sua missão, valores e o portfólio abarcando projetos e revisão de projetos, certificação energética, ensaios acústicos, gestão e fiscalização de empreendimentos. As atividades desenvolvidas no estágio englobam a certificação energética de edifícios existentes aplicando a nova regulamentação térmica (REH), apresentando as simplificações de cálculo aplicadas a edifícios existentes e dois exemplos específicos de uma fração autónoma e um edifício unifamiliar. No campo da acústica foram estudados três edifícios, um habitacional, um misto e um de serviços. Para o condicionamento acústico dos casos de estudo serão aplicados métodos de cálculo utilizados na empresa e um método de cálculo para avaliação e classificação da qualidade acústica, o qual foi desenvolvido pelo Laboratório Nacional de Engenharia Civil – LNEC. Por fim, foram elaborados as ponderações sobre a experiência vivida, como considerações sobre os resultados obtidos tendo em conta os objetivos propostos para o desenvolvimento do estágio.