Abstract
The Portuguese Micromouse Contest®* is an innovated robotic contest in Portugal that address the need to enhance student interest and performance in science, technology, engineering, and mathematics (STEM) courses, while fostering skills that are important prerequisites for IT careers. To facilitate the access to younger students a robot kit and an Arduino library was developed and made available on GitHub. Some of the library examples include the common algorithms used to solve mazes, like the Flood Fill, Right or Left Wall Following to name a few. Recursive Backtracking algorithm is often used to solve mazes especially if there is a lot of computer power. This is not the case of the Arduino platform that only has 2.5 KB of SRAM and a clock speed of 16 MHz, so implementing Recursive Backtracking becomes quite difficult. In this work we show how to implement Recursive Backtracking to find if there are better solutions for solving the maze. We also show the memory measurements for three Arduino common platforms the Leonardo, the UNO and the DUE. © 2018 by World Scientific Publishing Co. Pte. Ltd.

Abstract
Overtime, in the electricity sector, there has been a technological transfer to renewable electricity generation. With this change, processes, in the economic and availability terms, are expected to improve. In this new paradigm, society demands electricity without an impact on the environment and with the lowest possible cost. The wind power (WP) integration appears in this evolution process by achieving important technological advances, supporting in 2017 a growth of 44% of new projects in Europe, higher than any other renewable technology. However, the renewable energy sources (RES) integration in the electricity networks still presents technical difficulties and challenges, leading to challenges in the electricity markets (EMs). Therefore, this work evaluates the importance of WP and its influence on the Iberian Electricity Market (MIBEL), at the level of the intraday electricity spot market (IESM). This is an innovative study because literature usually focuses on day-ahead WP impact and this study focuses on intraday markets, which are closer to the consumption periods. The goal was to make an analysis on the impacts when betting on WP sources, in order to improve the market interaction with WP integration, considering as criteria the consumer satisfaction, in terms of lower electricity prices and WP availability. For this study, the market bids registered by the Iberian Electricity Market Operator (OMIE), from 2015 to 2017, ran over a new market simulator, specially developed for this proposal, considering a virtual market condition, but not considering the bids made by WP producers. The comparison of the results allowed the evaluation of the WP influence on the EM quantitative, which is noteworthy.

Abstract
How to handle big amounts of data with several structures in an efficient way has been the key point of Big Data. The appearance of Hadoop has been a breakthrough in this field, by allowing to perform an analysis of important volumes of data, without the need of large supercomputers, but through commodity hardware complemented with a set of powerful software tools. The computing advantages provided by this new technology have made it very popular in a massive amount of areas and one of them is health data management. The purpose of this paper is to analyze the state of the art on Hadoop and its ecosystem, as well as to determine how it is possible to use the strength of these technologies, not only to analyze health data but also to reveal hidden information that can explain medical records in a better way. In particular, our work will be focused on determine how, behind veterinary data, there is an influence of the environmental changes.

Abstract

Abstract
This chapter introduces biased random-key genetic programming, a new metaheuristic for evolving programs. Each solution program is encoded as a vector of random keys, where a random key is a real number randomly generated in the continuous interval [0,1]. A decoder maps each vector of random keys to a solution program and assigns it a measure of quality. A Program-Expression is encoded in the chromosome using a head-tail representation which is later transformed into a syntax tree using a prefix notation rule. The artificial simulated evolution of the programs is accomplished with a biased random-key genetic algorithm. Examples of the application of this approach to symbolic regression are presented.

Abstract
The Internet of Things (IoT) represents a technical innovation that is already starting to play an important role in smarter water management, when a wide variety of sensors are incorporated into intelligent metering equipment and connected through wireless networks throughout the domiciliary water distribution network, being able to measure volume, flow, temperature, pressure, levels of chlorine, salinity and more. Water scarcity, aging or inadequate water distribution infrastructure, population variation, pollution, more intense and frequent droughts and floods, generate pressures that converge on the need to increase global investment in water infrastructures and to develop solutions for the conservation and management of water. The main stakeholders in the water distribution sector are the ones that can benefit most from the use of telemanagement. However, the results of adopting this innovation are contrary to expectations, with a slow change in traditional business models. The objective of this research is the construction of a value model that allows the identification of actors and value markets and the exchange of value related to the adoption of telemanagement in Portugal, having a solid theoretical basis and a real practical validation. Copyright