Abstract
Em cada pessoa existe um potencial empreendedor sendo a educação para o empreendedorismo o meio mais eficaz para o dinamizar e promover (Dolabela, 2008). Contudo, como abordar um tema tão complexo com crianças? Objetivo: Identificar a existência ou não de características empreendedoras em contexto de narração de história em crianças. Participantes: Uma turma do 1º ano com 18 alunos e uma de 3º ano com 19 alunos entre os 6 e os 9 anos (7,2±1,1) de uma escola de Braga. Instrumentos/Procedimentos: Construíram-se categorias e subcategorias suportadas pela revisão da literatura que determinaram as características empreendedoras a avaliar. Elaborou-se uma história construída de raiz, tendo por base o tema piratas e a procura de tesouros. Trata-se de uma história dinâmica, em que, cada uma das suas etapas termina com um desafio ou questão para os alunos. Assim, estes podem assumir-se como personagens, dar sugestões argumentadas sobre o caminho a seguir na história e ainda fazer opções entre várias possíveis. A história foi aplicada, em cada um dos anos de escolaridade, em grupos focais, de seis crianças. Discussão dos resultados: A observação das diferentes subcategorias permitiram-nos verificar comportamentos positivos (CP), inversos (CI) e não observados (CNO). Constatamos que em cinco das oito categorias a maioria dos alunos as revelou de forma positiva com destaque para a “Autoconfiança” e “Relações interpessoais” e ainda que aquelas em que se verificou maior percentagem de alunos que manifestaram CI foram a “Autoconfiança”, “Relações interpessoais” destacando-se a “Persistência/Resistência ao Fracasso. As categorias em que mais se verificaram CNO foram a “Liderança / Tomada de decisão” e “Organização e Planeamento”. São necessárias mais investigações de forma a reunir um número considerável de contribuições para a validação de um instrumento que se adapte à linguagem da criança e que, de uma forma lúdica e motivadora, permita identificar características empreendedoras.

Abstract

Abstract
Heart rate variability (HRV) analysis has been used as a quantitative marker of the autonomous nervous system activity to measure mental stress. Wearable sensors have been emerging as a solution to collect HRV data for stress assessment in a real context, however such studies raise additional requirements. The wearable system must be minimally obtrusive to allow the subjects to perform their tasks without interference, and inconspicuous to avoid the anxiety associated with wearing medical devices in public. The purpose of this study was to quantify the accuracy trade-off in the use of a chest band heart rate sensor that is less intrusive and less costly than a wearable electrocardiogram (ECG). The HRV metrics extracted from a chest band heart rate monitor, Zephyr HxM (TM) (Zph (TM)), were compared with those extracted from an ECG certified medical device, Vital Jacket (TM) (VJ (TM)). The two systems were worn simultaneously. under laboratory conditions by a population of 14 young and healthy subjects, aged 20 to 26 years, under the stress induced by the Trier Social Stress Test (TSST) procedure. The results showed a mean difference between RR intervals of 9 ms; a. root-mean square error. (RMSE) of less than 8% and. a Pearson's correlation higher than 0.946, considering all TSST phases. In the HRV analysis, the average of all normal intervals (AVNN) showed errors less than 2% between the two systems with a correlation higher than 0.99 for all TSST phases. We thus conclude that the used chest band sensor represents an alternative to the current wearable medical devices to monitor RR intervals, and could be used for mental stress monitoring similar to the TSST protocol.

Abstract
The increasing demand for human activity analysis in surveillance scenarios has been triggered by the emergence of new features and concepts to help in identifying activities of interest. However, the characterisation of individual and group behaviours is a topic not so well studied in the video surveillance community due to not only its intrinsic difficulty and large variety of topics involved, but also because of the lack of valid semantic concepts that relate human activity to social context. In this paper, we address the topic of social semantic meaning in a well-defined surveillance scenario, namely shopping mall, and propose new definitions of individual and group behaviour that consider environment context, a relational descriptor that emphasises position and attention-based characteristics, and a new classification approach based on mini-batches. We also present a wide evaluation process that analyses the sociological meaning of the individual features and outlines the performance impact of automatic features extraction processes into our classification framework. We verify the discriminative value of the selected features, state the descriptor performance and robustness over different stress conditions, confirm the advantage of the proposed mini-batch classification approach which obtains promising results, and outline future research lines to improve our novel social behavioural analysis framework.

Abstract
The general energy demand of the residential sector and the ensuing option for fossil fuels produce adverse results by both CO2, greenhouse gases (GHG) and extra air pollutant emissions. As domestic energy demand consists mostly of energy necessities for space and water heating alongside the energy dedicated for appliances, distinct strategies that target to foment a practical consumption of energy have to be reinforced at all levels of human activity. In this paper the aim is to make a comparison between proportional-integral-derivative (PID), thermostat (ON/OFF) control and Model Predictive Control (MPC) models of a domestic heating, ventilation and air conditioning (HVAC) system controlling the temperature of a room. The model of the household with local solar microgeneration is implicit to be located in a Portuguese city. The house of the case study is at the mercy to the local solar temperature, irradiance and 5 Time-of-Use (ToU) electricity rates applied on a complete week of August, 2016. The second purpose of this study is to assess which is the best electricity ToU rate option provided by the local electricity retailer for the residential sector.

Abstract
We address sampled–data nonlinear Model Predictive Control (MPC) schemes, in particular we address methods to efficiently and accurately solve the underlying continuous-time optimal control problems (OCP). In nonlinear OCPs, the number of discretization points is a major factor affecting the computational time. Also, the location of these points is a major factor affecting the accuracy of the solutions. We propose the use of an algorithm that iteratively finds the adequate time–mesh to satisfy some pre–defined error estimate on the obtained trajectories. The proposed adaptive time–mesh refinement algorithm provides local mesh resolution considering a time–dependent stopping criterion, enabling an higher accuracy in the initial parts of the receding horizon, which are more relevant to MPC. The results show the advantage of the proposed adaptive mesh strategy, which leads to results obtained approximately as fast as the ones given by a coarse equidistant–spaced mesh and as accurate as the ones given by a fine equidistant–spaced mesh. © Springer International Publishing Switzerland 2017.