Abstract

Abstract
Procurement plays an essential role in the supply of materials for the production of goods or products. The success of procurement management to fulfill demand with high service levels and on-time delivery relies on the suppliers' performance. Suppliers should be appropriately selected to source materials with the right quality, in the right quantity, at the right time, and for the right price. The scope of this problem, as well as other aspects such as the sourcing strategy, will depend on the type of items. Critical items, which represent high-profit impacts and high supply risks, should be approached comprehensively by considering all the main activities of the procurement process. This study focuses on a supplier selection problem integrated with inventory management under a multi-sourcing strategy, by taking into account stochastic demand and supply disruptions. This problem is approached by a simulation-optimization method, composed of discrete-event simulation and a genetic algorithm (GA). Finally, a numerical example is provided to illustrate the solution procedure.

Abstract
The purpose of this work was to collect information about how technology influences children nowadays, in Portugal, an intermediate technology country in the European Union. The methods used were interviews and questionnaires presented to children (a total of 38 children), parents (15 parents) and teachers (three teachers) in order to find out how they feel about today’s technological devices and how they think they can influence the society of the future, and whether they have a negative or positive impact or both. The methods selected were seen to be the best to obtain the desired answers, because public opinion is assuredly a good way to receive feedback about various contemporary products and phenomena. The conclusion was that every child in the sample owns digital devices and this influences them mostly in a positive way, in the opinion of their parents and teachers. Technology can also influence them in a negative way, but only if used so much that it becomes an addiction, affecting the child’s attention in school, as well as their daily activities. The motivation to do this research study was mainly that one of the authors has four children and can see the profound changes inflicted in them by technology versus older generations and thus an exploratory study into technological change brought on by devices, gadgets and social media was decided upon. © Springer Nature Switzerland AG 2019.

Abstract
The aim of the present study is to analyse the effect of the alcohol on driving considering distinct blood alcohol concentration up to 0.49 g/l, which is the legal limit in some countries such as Portugal. Additionally, a comparison between the ascending with the descending phases is considered. A driving simulator is used to ensure the safety of the participants. Two questionnaires were applied to analyse the perception of the 20 participants about the alcohol sensation and confidence to drive as well as the driving performance facing two critical events. Also, the number of correct answers to simple questions was analysed to evaluate the cognitive ability. The study results indicate that the cognitive ability and perception of the participants are affected while the driving performance is less affected.

Abstract
This paper presents a generic framework to evaluate and compare the quality of the uncertainties provided by probabilistic forecasts of power system state when used to perform security assessment for branch overloads. Besides exploiting advanced univariate and multivariate metrics that are traditionally used in weather prediction, the evaluation is complemented by assessing the benefits from exploiting probabilistic forecasts over the current practices of using deterministic forecasts of the system operating conditions. Another important feature of this framework is the provision of parameters tuning when applying flow probabilistic forecasts to perform security assessment for branch overloads. The quality and scalability of this framework is demonstrated and validated on recent historical data of the French transmission system. Although being developed to address branch overload problems, with proper adaptations, this work can be extended to other power system security problems.

Abstract
Visual exploration of the larynx represents a relevant technique for the early diagnosis of laryngeal disorders. However, visualizing an endoscopy for finding abnormalities is a time-consuming process, and for this reason much research has been dedicated to the automatic analysis of endoscopic video data. In this work we address the particular task of discriminating among informative laryngoscopic frames and those that carry insufficient diagnostic information. In the latter case, the goal is also to determine the reason for this lack of information. To this end, we analyze the possibility of training three different state-of-the-art Convolutional Neural Networks, but initializing their weights from configurations that have been previously optimized for solving natural image classification problems. Our findings show that the simplest of these three architectures not only is the most accurate (outperforming previously proposed techniques), but also the fastest and most efficient, with the lowest inference time and minimal memory requirements, enabling real-time application and deployment in portable devices.