Abstract
In this paper we apply a two state switching model to the problem of audio based beat tracking. Our analysis is based around the generation and application of adaptively weighted comb filter-bank structures to extract beat timing information from the midlevel representation of an input audio signal known as the onset detection function [1]. We evaluate our system using a previously published dataset [2] and in performing a direct comparison with the current state of the art, present comparable results. © 2005 IEEE.

Abstract
This paper describes a model to perform transmission expansion planning studies together with the computation of Long Term Marginal Prices along the planning horizon. The model includes four criteria and adopts a Simulated Annealing based algorithm to solve the problem. The algorithm also provides Long Term Marginal Prices reflecting both investment and operation costs, thus being able to conveniently address the Revenue Reconciliation Problem that would arise if short-term approaches were used. The paper includes a case study based on the 400/220/150 kV Portuguese transmission system to illustrate the application of the proposed algorithm and highlight its potential.

Abstract
This paper is about environmental protection of our habitat in what regards limiting the pollutant emission due to thermal power plants, burning fossil fuels, burning coal, oil or gas to convert into electric energy. On the one hand, within the liberalized energy power markets, schedule of thermal power plants has evolved from a point of view optimisation problem of electric companies to a market level problem. On the other hand, as a consequence of growing environmental concern, the impact of conventional power plants on the environment is being considered and efforts are being made to limit this impact. Consequently, the short-term schedule for thermal power plants needs to be not only considered within the energy market, but also within preserving healthy conditions and self recovery cycles in the environment. We present a case study for thermal power plants considering pollutant emissions and compare the results with the usual approach, ignoring pollutant emissions.

Abstract
One major practical problem when applying traditional metaheuristics seems to be their strong dependency on parameter tuning. This issue is frequently pointed out as a major shortcoming of metaheuristics and is often a reason for Decision-Makers to reject using this type of approach in practical situations. In this paper we present a new search strategy - Constraint Oriented Neighbourhoods - that tries to overcome the referred drawback. The aim is to control the grade of randomness of metaheuristics, by defining "special" neighbourhood movements, that lead to a more robust heuristic, less dependent on parameter tuning. This is achieved by selecting and applying particular movements that take into account the potential violation of problem constraints. The strategy is illustrated in a real problem arising in the area of Power Systems Management - the Unit Commitment Problem, the computational experiments on a set of problem instances systematically outperforming those presented in the literature, both in terms of efficiency, quality of the solution and robustness of the algorithm.

Abstract
Restructuring of power markets has helped in the penetration of Distributed Generation (DG) in the electricity networks. Microgrids are Low Voltage distribution networks comprising various distributed generators (DG), storage devices and controllable loads that can operate interconnected or isolated from the main distribution grid, as a controlled entity. This paper describes the main functions of the Microgrid Central Controller required for the optimization of Microgrid operation its interconnected operation. This is achieved by maximizing its value, i.e. optimizing production of the local DGs and power exchanges with the main distribution grid.

Abstract
In this paper, we consider the single machine earliness/tardiness scheduling problem with no idle time. Two of the lower bounds previously developed for this problem are based on Lagrangean relaxation and the multiplier adjustment method, and require an initial sequence. We investigate the sensitivity of the lower bounds to the initial sequence, and experiment with different dispatch rules and some dominance conditions. The computational results show that it is possible to obtain improved lower bounds by using a better initial sequence. The lower bounds are also incorporated in a branch-and-bound algorithm, and the computational tests show that one of the new lower bounds has the best performance for larger instances.