Abstract
The aim of this work is to demonstrate a novel fuzzy-based expert system for selecting renewable energy technologies (RET). Fuzzy multi-rules and fuzzy multi-sets are used to evaluate the main operational characteristics of six types of RET fuelled by biogas from municipal solid waste (MSW) landfills. The construction of the fuzzy multi-rules and fuzzy multi-sets is based on the following method: Mamdani controller using the Max-Min (inference process) and Center of Gravity (defuzzification process). Several criteria are used for the investigation: costs, efficiency, cogeneration, life-cycle and environmental impacts. The fuzzy-based expert system considers three different settings with two different constraints: costs and environmental impacts. One of the most relevant aspects presented by this work is about the previous criteria rank. It was created according to the different relevance observed among the attributes. The purpose of the proposed arrangement is to facilitate the understanding of the methodology and to increase the possibility of incorporating the decision makers' preferences on the decision-aid process. These aspects are essential to strengthen the final decision.

Abstract

Abstract
This chapter describes the design-flow approach developed in the REFLECT project as presented originally in [1]. Over the course of the project, this design-flow has evolved and has been extended into a fully operational toolchain. We begin by presenting an overview of the underlying aspect-oriented compilation flow followed by an extended description of the design-flow and its toolchain. © Springer Science+Business Media New York 2013. All rights are reserved.

Abstract
Between first responder professionals, firefighters registered the highest number of deaths on duty. An abnormal high proportion is associated with cardiovascular events. Our main goal is to identify fatigue/stress during daily routine activities, focusing on the cardiovascular analysis. To accomplish this purpose, ECG wave morphological alterations are analyzed. It was observed that the RR, PP and ST segment significantly differentiate the most stressful tasks from the others.

Abstract
This paper describes an approach to model and to solve the Generation Expansion Planning Problem, GEP, using Genetic Algorithms. This approach was developed in order to help investors in new generation capacity to take decisions regarding new investments. This approach was developed in the scope of the implementation of electricity markets given that they eliminated the traditional centralized planning activities leading to the creation of several generation companies competing to supply the demand. As a result, the generation activity is more risky than in the past and so it becomes important to develop new tools to help decision makers to analyze the investment alternatives, having in mind the possible behavior of the competitors. The developed model aims at maximizing the expected profits that will be obtained by an investor, while it evaluates the reliability and the security of supply and it incorporates uncertainties related with the volatility of electricity prices, with the reliability of generation groups, with the evolution of the demand, and with the operation and investment costs The developed model and the implemented solution algorithm will be applied to a Case Study to illustrate the use of the developed approach to build the expansion plans. © 2013, Springer Science+Business Media Dordrecht.

Abstract
Optical Music Recognition (OMR) systems are an indispensable tool to transform the paper-based music scores and manuscripts into a machine-readable symbolic format. A system like this potentiates search, retrieval and analysis. One of the problematic stages is the musical symbols detection where operations to localize and to isolate musical objects are developed. The complexity is caused by printing and digitalization, as well as the paper degradation over time. Distortions inherent in staff lines, broken, connected and overlapping symbols, differences in sizes and shapes, noise, and zones of high density of symbols is even worst when we are dealing with handwritten music scores. In this paper the exploration of an optimization approach to support semantic and syntactic consistency after the music symbols extraction phase is proposed. The inclusion of this ongoing technique can lead to better results and encourage further experiences in the field of handwritten music scores recognition.