In the field of qualitative spatial and temporal reasoning combinations of constraint calculi have attracted considerable research interest in recent years. Beside combinations of spatial and temporal calculi, it is an important research topic to develop generic methods for combining calculi dealing with different spatial aspects. The prototypical example is the combination of the region connec...

In this paper, we incorporate a nonmonotone technique with the new proposed adaptive trust region radius (Shi and Guo, 2008) [4] in order to propose a new nonmonotone trust region method with an adaptive radius for unconstrained optimization. Both the nonmonotone techniques and adaptive trust region radius strategies can improve the trust region methods in the sense of global convergence. The g...

We introduce a new technique for counting models of Boolean satisfiability problems. Our approach incorporates information obtained from sampling the solution space. Unlike previous approaches, our method does not require uniform or near-uniform samples. It instead converts local search sampling without any guarantees into very good bounds on the model count with guarantees. We give a formal an...

For a large class of bounded-error estimation problems, the posterior feasible set S for the parameters can be de…ned by nonlinear inequalities. The set-inversion approach combines classical interval analysis with branch-and-bound algorithms to characterize S. Unfortunately, as bisections have to be done in all directions of the parameter space, this approach is limited to problems involving a ...

In the analysis of brain Magnetic Resonance Images (MRI), tissue classification is an important issue. Many works have been done to classify the brain tissues from the brain MRI. This paper presents a new technique to classify the brain MRI images and to perform tissue classification by using Dual Mode Classifier (DMC). Initially, the brain MRI images are obtained from the brain databases and f...

This paper presents and examines the behaviour of a system whereby the rules governing local search within a Memetic Algorithm are co-evolved alongside the problem representation. We describe the rationale for such a system, and the implementation of a simple version in which the evolving rules are encoded as (condition:action) patterns applied to the problem representation, and are e ectively ...

Extracting an optimal set of parameter values for a MOS device is great importance in contemporary technology is a complex problem. Traditional methods of parameter extraction can produce far from optimal solutions because of the presence of local optimum in the solution space. Genetic algorithms are well suited for finding near optimal solutions in irregular parameter spaces. In this study*, W...

A general class of algorithms for unconstrained optimization is introduced, which subsumes the classical trust-region algorithm and two of its newer variants, as well as the cubic and quadratic regularization methods. A unified theory of global convergence to first-order critical points is then described for this class. An extension to projection-based trust-region algorithms for nonlinear opti...

HISTORY OF THE TAP BLOCK Abdominal field blocks and costo-iliac block have been used in anaesthesia for surgery involving the anterior abdominal wall for several decades. A technique involving multiple injections of local anaesthetic in the abdominal wall was used in the 1980s.1 This technique was improved with a blind landmark technique, via the ‘lumbar triangle of Petit’.2 The clinical effica...

In this paper we propose a new approach for false positive reduction in the field of mammographic mass detection. The goal is to distinguish between the true recognized masses and the ones which actually are normal parenchyma. Our proposal is based on Local Binary Patterns (LBP) for representing salient micro-patterns and preserving at the same time the spatial structure of the masses. Once the...