Society’s concerns with electricity consumption have motivated researchers to improve on the way that energy consumption management is done. The reduction of energy consumption and the optimization of energy management are, therefore, two major aspects to be considered. Additionally, load forecast provides relevant information with the support of historical data allowing an enhanced energy management, allowing energy costs reduction. In this paper, the proposed consumption forecast methodology uses an Artificial Neural Network (ANN) and incremental learning to increase the forecast accuracy. The ANN is retrained daily, providing an updated forecasting model. The case study uses 16 months of data, split in 5-min periods, from a real industrial facility. The advantages of using the proposed method are illustrated with the numerical results.
Abstract. Schematic Maps are mainly used for depicting transportation networks. They are generated through a schematization process where irrelevant details are eliminated and important details are emphasized. This process, being manually performed by teams of expert designers, is expensive and time consuming. Such manual execution is unsuitable for the production of schematic maps for location-based services or ondemand schematic maps, as near real-time and user-centered properties are needed. This work proposes GeneX, a framework that can support the automated generation of schematic maps. The framework and the new algorithms developed were able to completely eliminate erroneous map point placement, and to decrease by 33% the contention for map point placement, producing schematic maps without human intervention in soft real time.
Objetivos: Mapear a evidência científica acerca da influência do isolamento social por Covid-19 no Manejo da Dor Crónica. Sugerir ações que minimizem as interferências da Pandemia por Covid-19 no manejo da dor crónica. Método: Foi seguida a metodologia JBI (Joanna Briggs Institute), a pesquisa foi realizada entre outubro e novembro de 2020 nas bases de dados Biblioteca do Conhecimento, Ebscohost, PubMed Central (PMC) e PubMed, foi considerado o espaço temporal de janeiro de 2019 a dezembro de 2020 e conjugados os boleanos “and” e “not”. A Scoping Review (SR) pretende mapear os procedimentos metodológicos e partiu da seguinte questão central: “O manejo da dor crónica foi afetado pelo Isolamento Social causado pela Pandemia por Covid-19?”, sendo esta definida pela questão PCC. Resultados: Do universo de 862 artigos encontrados foram selecionados 16 após aplicação dos critérios de exclusão. Conclusão: Corroboramos que se revela fulcral adotar medidas individualizadas no acompanhamento do doente com dor crónica em fase de Pandemia por Covid-19, de modo a diminuir as comorbilidades nestes doentes e aumentar a qualidade de vida.
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