Abstract
Modern storage infrastructures feature long and complicated I/O paths composed of several layers, each employing their own optimizations to serve varied applications with fluctuating requirements. However, as these layers do not have global infrastructure visibility, they are unable to optimally tune their behavior to achieve maximum performance. Background storage tasks, in particular, can rapidly overload shared resources, but are executed either periodically or whenever a certain threshold is hit regardless of the overall load on the system. In this paper, we argue that to achieve optimal holistic performance, these tasks should be dynamically programmable and handled by a controller with global visibility. To support this argument, we evaluate the impact on performance of compaction and checkpointing in the context of HBase and PostgreSQL. We find that these tasks can respectively increase 99th percentile latencies by 955.2% and 61.9%. We also identify future research directions to achieve programmable background tasks.

Abstract
Over the last decades Information and Communication Technologies (ICTs) are increasingly being used in sports, especially in football, aiming to improve the athletes training and results. However, training systems for young athletes do not have, for the most part, learning abilities in order to adapt, evolve and find new training recommendations, designed specifically for each young athlete. In this paper introduce the Smart Coach user adaptation model, and whose main goal is to present our hybrid recommendation system to help young athletes evolve. This facilitate the interaction between members of a club technical staff and their young athletes, reinforcing the young person counselling, and their potential as an athlete. © Springer Nature Switzerland AG 2020.

Abstract
The digital transformation that is on-going worldwide, and triggered by the Industry 4.0 initiative, has brought to the surface new concepts and emergent technologies. One of these new concepts is the Digital Twin, which recently started gaining momentum, and is related to creating a virtual copy of the physical system, providing a connection between the real and virtual systems to collect and analyze and simulate data in the virtual model to improve the performance of the real system. The benefits of using the digital twin approach is attracting significant attention and interest from research and industry communities in the last few years, and its importance will increase in the upcoming years. Having this in mind, this paper surveys and discusses the digital twin concept in the context of the 4th industrial revolution, particularly focusing the concept and functionalities, the associated technologies, the industrial applications and the research challenges. The applicability of the digital concept is illustrated by the virtualisation of an UR3 collaborative robot which used the V-REP simulation environment and the Modbus communication protocol.

Abstract

Abstract
The use of metaheuristics to solve real-life problems has increased in recent years since they are easy to implement, and the problems become easy to model when applying metaheuristic approaches. However, arguably the most important aspect is the simulation time since results can be obtained from metaheuristic methods in a much smaller time, and with a good approximation to the results obtained with exact methods. In this work, the Genetic Algorithm (GA) metaheuristic is adapted and apphed to solve the optimization of electricity markets participation portfolios. This work considers a multiobjective model that incorporates the calculation of the profit and the risk incurred in the electricity negotiations. Results of the proposed approach are compared to those achieved with an exact method, and it can be concluded that the proposed GA model can achieve very close results to those of the deterministic approach, in much quicker simulation time. © 2018 IEEE.

Abstract
Energy harvesting devices can increase autonomy of submersible marine sensors. However, only the water movements can be used as energy source, since neither solar or temperature gradients are available bellow surface waters. A Linear Electromagnetic Generator (LEG), in a milliwatt energy harvester, is presented. Any moving parts are in contact with water, thus avoiding biofouling problems in the harvester. In this work, a 100mm length, 60mm diameter, cylindrical LEG was designed to maximize output power, and analyzed the effects of magnets size and geometry as well as coils position, at several working conditions. Two coils were used, with an internal resistance of 130 ? in 1500 turns, together with N38-N42 magnets. A mean electrical power of 25 mW (100 mW peak) was experimental measured in the optimized configuration, in realistic conditions, which is enough to power almost any electronic low-power sensor.