Abstract
This paper explores the content of various Sustainable Energy Action Plans (SEAPs) necessary to the Covenant of Mayors. This study has the aim of providing an overview of existing methodologies for the development and implementation of SEAPs by municipalities. As the number and complexity of issues related with energy are very broad, it is very important to know and identify good practices and guidelines to increasing participant municipalities. Based on the methodologies collected in several studies, it is possible to identify key aspects and issues municipalities might consider for the development of their own plan. The SEAP can't be only a collection of measures; it must have a coherent strategy with the European and National policies. This study also shows that a good coordinator with project management skills is necessary to overcome obstacles due to the lack of communication or collaboration among the different municipality's departments. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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This paper discusses the teaching of Fourier Series concepts in undergraduate Electrical Engineering education with the help of an Android application, especially developed to that end. In order to better understand the links and implications, some of the basic Fourier series theory is briefly reviewed. The Android application has an easy-to-use, friendly interface, conceived to help undergraduate students test and assess the Fourier series expansions on a typical set of signals. The application also allows the students to control the total approximation error and the number of terms/harmonics used in the expansions. It has been found a very useful learning resource in the Fourier series context.

Abstract
Nowadays, there are many technologies that support location systems involving intrusive and nonintrusive equipment and also varying in terms of precision, range, and cost. However, the developers some time neglect the noise introduced by these systems, which prevents these systems from reaching their full potential. Focused on this problem, in this research work a comparison study between three different filters was performed in order to reduce the noise introduced by a location system based on RFID UWB technology with an associated error of approximately 18 cm. To achieve this goal, a set of experiments was devised and executed using a miniature train moving at constant velocity in a scenario with two distinct shapes-linear and oval. Also, this train was equipped with a varying number of active tags. The obtained results proved that the Kalman Filter achieved better results when compared to the other two filters. Also, this filter increases the performance of the location system by 15% and 12% for the linear and oval paths respectively, when using one tag. For a multiple tags and oval shape similar results were obtained (11-13% of improvement).

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The prediction of overall survival in patients has an important role, especially in diseases with a high mortality rate. Encompassed in this reality, patients with oncological diseases, particularly the more frequent ones like woman breast cancer, can take advantage of a very good customization, which in some cases may even lead to a disease-free life. In order to achieve this customization, in this work a comparison between three algorithms (evolutionary, hierarchical and k-medoids) is proposed. After constructing a database with more than 800 breast cancer patients from a single oncology center with 15 clinical variables (heterogeneous data) and having 25% of the data missing, which illustrates a real clinical scenario, the algorithms were used to group similar patients into clusters. Using Tukey's HSD (Honestly Significant Difference) test, from both comparison between k-medoids and the other two approaches (evolutionary and hierarchical clustering) a statistical difference were detected (p- value < 0.0000001) as well as for the other comparison (evolutionary versus hierarchical clustering) - p-value = 0.0061354 - for a significance level of 95%. The future work will consist primarily in dealing with the missing data, in order to achieve better results in future prediction. © 2014, Springer International Publishing Switzerland.

Abstract