Abstract
This paper provides an approach to short-term scheduling of thermal units, designed to simultaneously address the economic issue of the fuel cost incurred on the commitment of the units and the environmental consideration due to emission allowance trading. The simultaneous address of the fuel cost with the emission is modeled by a multi-objective optimization problem, which is solved by a combination of the weighted sum method with the epsilon-constraining method. A numerical example for different values of a scaling factor is considered in order to obtain the non-dominated solutions of the trade-off curve between fuel cost and emission. Our approach presents a new parameter, ratio of change, and the corresponding gradient angle, to enable the proper selection of a compromise commitment for the units. Copyright (C) 2007 John Wiley & Sons, Ltd.

Abstract
Nowadays the education on electrical engineering, in European countries, is facing on one side a high demand for engineers coming from industry and on the other hand a reduced interest from younger generation, whose interest is highly polarised by information and communication technologies. A permanent-magnet synchronous motor (PMSM) controller for an electric wheelchair demo track has been set up, in order to reinforce the demonstrative aspects of modern technology as a contribution to the motivation of students for the industrial electronics world. The motors are controlled at different operating conditions by means of a current control law using a low cost microcontroller board. The prototype has been designed specifically to meet the requirement of low cost and it contains all of the active functions required to implement the control of the electric wheelchair. The resulting prototype has a very low cost compared to commercial "black-box" modules. This prototype allows a first approach between a real technical system and power electronics, increasing the student's motivation for the power electronics area and to significantly enhance their skills to measure and interpret measurements and comparing those to theoretical predictions.

Abstract
A robust all-fibre interferometric interrogation technique based on the wavelength modulation of a pi-shifted fibre Bragg grating is proposed. The concept is demonstrated for strain measurement using a Bragg-grating-based Fabry-Perot interferometer. The strain-phase relationship is shown to be linear with a sensitivity slope of (2.19 +/- 0.02)degrees/mu epsilon. A strain resolution of approximate to 2.4 mu e is demonstrated.

Abstract
This paper proposes a non-parametric method for the classification of thin-layer chromatographic (TLC) images from patterns represented in a dissimilarity space. Each pattern corresponds to a mixture of Gaussian approximation of the intensity profile. The methodology comprises various phases, including image processing and analysis steps to extract the chromatographic profiles and a classification phase to discriminate among two groups, one corresponding to normal cases and the other to three pathological classes. We present an extensive study of several dissimilarity-based approaches analysing the influence of the dissimilarity measure and the prototype selection method on the classification performance. The main conclusions of this paper are that, Match and Profile-difference dissimilarity measures present better results, and a new prototype selection methodology achieves a performance similar or even better than conventional methods. Furthermore, we also concluded that simplest classifiers, such as k-NN and linear discriminant classifiers (LDCs), present good performance being the overall classification error less than 10% for the four-class problem.

Abstract

Abstract
Within ballroom dance music, tempo and rhythmic style are strongly related. In this paper we explore this relationship, by using knowledge of rhythmic style to improve tempo estimation in musical audio signals. We demonstrate how the use of a simple 1-NN classification method, able to determine rhythmic style with 75% accuracy, can lead to an 8% point improvement over existing tempo estimation algorithms with further gains possible through the use of more sophisticated classification techniques.