A Fuzzy Rule-Based System to predict energy consumption of Genetic Programming Algorithms

In recent years, the energy-awareness has become one of the most interesting areas in our environmentally conscious society. Algorithm designers have been part of this, particularly when dealing with networked devices and, mainly, when handheld ones are involved. Although studies in this area has increased, not many of them have focused on Evolutionary Algorithms. To the best of our knowledge, few attempts have been performed before for modeling their energy consumption considering different execution devices. In this work, we propose a fuzzy rulebased system to predict energy comsumption of a kind of Evolutionary Algorithm, Genetic Prohramming, given the device in wich it will be executed, its main parameters, and a measurement of the difficulty of the problem addressed. Experimental results performed show that the proposed model can predict energy consumption with very low error values.

Analyzing quality clarinet sound using deep learning. A preliminary study.

When a music student begins training, one of the main problems encountered is the proper understanding of specific terms that teachers introduce as a way of analyzing the type of sound produced by the student. The goal of a music teacher is that their students improve the quality of the sound they are emitting, but not in all cases students understand and know how to apply the concepts that the teacher wants the instrument to be able to emit the expected sound. Any tool that allows students to distinguish between sound quality would be helpful. The work presented here is a preliminary study of the quality of the sound emitted by a clarinet using deep learning techniques. It presents a first approximation of what will become a software tool that will allow music students to see that the sound quality they are emitting is correct and in real time. With this type of tools music students will be able to understand and associate the concepts explained by the teacher in a simpler way, and will even serve as a guide to improve their learning when the teacher is not present.

DOI: 10.1109/SSCI.2017.8285322

Involving local administrations in STEM promotion: how to extend STEM initiatives to a whole region.

This paper describes a novel initiative whose main goal is not only to encourage young students to pursue careers in science, technology, engineering, and mathematics (STEM); Although this is typically seen as the core of any STEM project, we aim at involving local administrations in the project, thus allowing to more easily disseminate and promote STEM areas among students' families and teachers. The central idea of our approach relies on involving local administrations, and making them allies for the project: they will not only help to disseminate information about the project in their local areas; they will also attract teachers to promote the activities within schools, and more importantly, when convinced of the need of the project, will provide fundings to hire specialized teachers in charge of developing a series of after school learning activities along the academic year. This way, every local administration becomes partner of the project, allowing to hire specific professionals from STEM areas instead of making the project to rely on volunteers. The methodology developed has allowed to reach 20 small towns in Extremadura, their local governments, teachers and families, with more than 400 students, some of them attending sessions for several years.

DOI: 10.1109/FIE.2017.8190726