Abstract

Abstract
The major challenge in coordinating between fast-acting energy storage systems (FA-ESSs) and renewable energy sources (RESs) in the existing transmission grid is to determine the location and capacity of the FA-ESS in the power systems. The optimal allocation of FA-ESS with conventional hourly discrete time method (DTM) can result in the increased operation cost, non-optimal placements and larger storage capacity and therefore, having an opposite effect on the operation. Accordingly, in this paper, a continuous-time method (CTM) is proposed to coordinate FA-ESS and RESs to cover fast fluctuations of renewable generations (RGs). Besides, based on the CTM, an adaptive interval-based robust optimization framework, to deal with uncertainty of the RGs, has been proposed. The proposed optimal allocation of FA-ESS with CTM provides the best sitting and sizing for the installation of the FA-ESSs and the best possible continuous-time scheduling plan for FA-ESSs. Also, in other to have better implementations of their ramping capability to track the continuous-time changes and deviations of the RGs rather than hourly DTM. The proposed model has been implemented and evaluated on the IEEE Reliability Test System (IEEE-RTS).

Abstract
As transformações digitais têm provocado alterações na Educação, mas ainda não disseminadas. A compreensão da natureza, limites e potencialidades dessas transformações, exige um repensar das epistemologias e das teorias de aprendizagem.  Propomos um quadro de interpretação dessas alterações, que encara o ensinar e o aprender enquanto percursos que se coengendram num habitar e co-habitar cada vez mais atópico, em contextos híbridos e multimodais. Por meio desse quadro, é possível compreender a transformação digital na Educação enquanto deslocamento disruptivo num espaço-tempo de interações ecossistêmicas de inovação. Este quadro de interpretação nasce do cruzamento das contribuições de Di Felice sobre os movimentos epistemológico do processo de digitalização que nos leva a uma nova condição habitativa, pós-urbana e atópica, originando  epistemologias reticulares; e da perspectiva dos ecossistemas educacionais como sistemas vivos e cognitivos de Capra, Latour e Di Felice, onde se conectam diferentes ecologias, para além das humanas.

Abstract
This article describes tsmp, an R package that implements the MP concept for TS. The tsmp package is a toolkit that allows all-pairs similarity joins, motif, discords and chains discovery, semantic segmentation, etc. Here we describe how the tsmp package may be used by showing some of the use-cases from the original articles and evaluate the algorithm speed in the R environment. This package can be downloaded at https://CRAN.R-project.org/package=tsmp.

Abstract
The fields of artificial intelligence, knowledge inference, data science, etc. have been deeply studied over time and many theoretical approaches have been developed, including its application to health and diseases inference. The creation of prototype and consumer systems has been restrained by the technology limitations on data acquisition and processing, which has been greatly overcome with the new sensors and mobile devices technologies. So, in this work we go through a literature review of the current state of the art on record to the usage of mobile technologies for diseases inference. The review methodology is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The criteria were based on journal articles, prior to 2008, and using the defined keywords. A total of 14 selected articles were analyzed. A general conclusion was attained regarding the current state of maturity of the field, leading to fully functional consumer and professional market products.

Abstract