Abstract
A new algorithm for an effective and automatic segmentation of the carotid wall in ultrasonic images is proposed. It combines the speed of thresholding algorithms with the accuracy, flexibility and robustness of a successful geometric active contour model which incorporates an optimal image segmentation model in a level set framework. Due to the multiphase nature of these images, a sequential minimum cross entropy thresholding is used to get a first approximation of the segments, reducing the problem to a two phase segmentation. This thresholding solution is then used as a starting point for a two phase piecewise constant version of a geometric active contour model to reduce noise, smooth contours, improve their position accuracy and close eventual gaps in the carotid wall.

Abstract
In this paper, we present filtered and recovering beam search algorithms for the single machine earliness/tardiness scheduling problem with no idle time, and compare them with existing neighbourhood search and dispatch rule heuristics. Filtering procedures using both priority evaluation functions and problem-specific properties have been considered. The computational results show that the recovering beam search algorithms outperform their filtered counterparts, while the priority-based filtering procedure proves superior to the rules-based alternative. The best solutions are given by the neighbourhood search algorithm, but this procedure is computationally intensive and can only be applied to small or medium size instances. The recovering beam search heuristic provides results that are close in solution quality and is significantly faster, so it can be used to solve even large problems.

Abstract
This paper presents a multicriteria formulation for multiyear dynamic transmission expansion planning problems. This formulation considers three criteria: investment costs, operation costs, and. the expected energy not supplied. The solution algorithm adopts an interactive decision-making approach that starts at a nondominated solution of the problem. This solution is identified transforming two of the three criteria in constraints specifying aspiration levels and using afterwards simulated annealing to deal with the integer nature of investment decisions. After obtaining this first solution, the decision maker can alter the aspiration levels and run the application again to obtain a new solution. Once an expansion plan is accepted, the algorithm computes long-term marginal costs, reflecting both investment and operation costs. These costs are more stable than short-term ones and inherently address the revenue reconciliation problem well known in short-term approaches. The developed algorithm is tested using a case study based on the Portuguese 400/220/150-kV transmission network.

Abstract
In this paper we address the issue of causal rhythmic analysis, primarily towards predicting the locations of musical beats such that they are consistent with a musical audio input. This will be a key component required for a system capable of automatic accompaniment with a live musician. We are implementing our approach as part of the aubio real-time audio library. While performance for this causal system is reduced in comparison to our previous non-causal system, it is still suitable for our intended purpose.

Abstract

Abstract