This paper describes a Minimum Message Length (MML) approach to nding the most appropriate Hidden Markov Model (HMM) to describe a given sequence of observations. A MML estimate for the expected length of a two-part message stating a speci c HMM and the observations given this model is presented along with an e ective search strategy for nding the best number of states for the model. The inform...

We give a tight analysis of the MST heuristic recently introduced by G.-H. Lin and G. Xue for approximating the Steiner tree with minimum number of Steiner points and bounded edge-lengths. The approximation factor of the heuristic is shown to be one less than the MST number of the underlying space, de ned as the maximum possible degree of a minimum-degree MST spanning points from the space. In ...

This paper presents a work in progress for indoor and outdoor target detection and feature extraction in video sequences. The framework can be applied to AmI systems related to surveillance activities. The system is based on a Local Search Particle Filter (LSPF) algorithm, which tracks a moving target and calculates its bounding box. Possible applications of this prototype include assisted moni...

Historically, discrete minimization problems in constrained logical programming were modeled with the help of an isolated bounding constraint on the objective that is to be decreased. To overcome this frequently inefficient way of searching for improving solutions, the notion of optimization constraints was introduced. Optimization constraints can be viewed as global constraints that link the o...

In this paper, we develop, study and test new neighborhood structures for the Hopconstrained Minimum Spanning Tree Problem (HMSTP). These neighborhoods are defined by restricted versions of a new dynamic programming formulation for the problem and provide a systematic way of searching neighborhood structures based on the node-level exchanges. We have also developed several local search methods ...

The artificial potential field based path planning has been most wisely used for local path planning because it provides simple and efficient motion planners for practical purposes. However, this approach has a local minimum problem which can trap a robot before reaching its goal. The local minimum problem is sometimes inevitable when a mobile robot moves in unknown environments, because the ro...

Current tools for VLSI placement are based either on quadratic placement, or on min-cut heuristics, or on simulated annealing. For the most complex chips with millions of movable objects, algorithms based on quadratic placement seem to yield the best results within reasonable time. In this paper we prove several new theoretical results on quadratic placement. We point out connections to random ...