Remarks on methods for the computation of boundary-element integrals by co-ordinate transformation

It is well known that the evaluation of the influence matrices in the boundary-element method requires the computation of singular integrals. Quadrature formulae exist which are especially tailored to the specific nature of the singularity, i.e. log(*- x0)9 Ijx- JC0), etc. Clearly the nodes and weights of these formulae vary with the location Xo of the singular point. A drawback of this approach is that a given problem usually includes different types of singularities, and therefore a general-purpose code would have to include many alternative formulae to cater for all possible cases. Recently, several authors1"3 have suggested a type independent alternative technique based on the combination of standard Gaussian rules with non-linear co-ordinate transformations. The transformation approach is particularly appealing in connection with the p.adaptive version, where the location of the collocation points varies at each step of the refinement process. The purpose of this paper is to analyse the technique in eference 3. We show that this technique is asymptotically correct as the number of Gauss points increases. However, the method possesses a 'hidden' source of error that is analysed and can easily be removed.

Zonificación del espacio por agrupación de unidades superficiales. Aplicación a la gestión de sistemas extensivos del tipo cereal-ovino

RESUMEN Los procesos de diseño de zonas o diseño del territorio implican la partición de un espacio geográfico, organizado en un conjunto de unidades de área, en diferentes regiones o zonas según un conjunto especifico de criterios que varían en función del campo de aplicación. En la mayoría de los casos, el objetivo fundamental consiste en crear zonas de tamaño aproximadamente igual respecto a uno o varios atributos de medida -de carácter cuantitativo- (zonas con igual número de habitantes, igual promedio de ventas...). Sin embargo, están apareciendo nuevas aplicaciones, algunas en el contexto de las políticas de desarrollo sostenible, cuya finalidad es la definición de regiones con un tamaño predeterminado, no necesariamente similar. Además, en estos casos las zonas han de formarse en torno a un conjunto específico de posiciones, semillas o generadores. Este tipo de particiones no han sido lo suficientemente investigadas, de manera que no se conocen modelos de solución para la delimitación automática de las zonas. En esta tesis se ha diseñado un nuevo método basado en una versión discreta del diagrama de Voronoi con peso aditivo adaptativo (DVPAA), que permite la partición de un espacio bidimensional en zonas de un tamaño específico, considerando tanto la posición como el peso de cada uno de los generadores. El método consiste en resolver repetidamente un tradicional diagrama de Voronoi con peso aditivo, de forma que los pesos de cada generador se actualizan en cada iteración. En el proceso de cálculo de distancias se usa una métrica basada en el camino más corto, lo que garantiza que la partición obtenida esté formada por un conjunto de zonas conexas. La heurística diseñada se integra en una aplicación prototipo, desarrollada en un entorno SIG (Sistemas de Información Geográfica), que permite el trazado automático de zonas según los criterios anteriormente expuestos. Para analizar la viabilidad del método se ha utilizado como caso de estudio la gestión de los recursos pastorales para la ganadería extensiva en tres municipios de Castilla-La Mancha. Las pruebas realizadas ponen de manifiesto que la heurística diseñada, adaptada a los criterios que se plantean en el contexto de la gestión de sistemas extensivos agropecuarios, es válida para resolver este tipo de problemas de partición. El método propuesto se caracteriza por su eficacia en el tratamiento de un gran número de unidades superficiales en formato vectorial, generando soluciones que convergen con relativa rapidez y verifican los criterios establecidos. En el caso estudiado, aunque la posición prefijada de los generadores reduce considerablemente la complejidad del problema, existen algunas configuraciones espaciales de estos elementos para las que el algoritmo no encuentra una solución satisfactoria, poniéndose de manifiesto una de las limitaciones de este modelo. Tal y como se ha podido comprobar, la localización de los generadores puede tener un considerable impacto en la zonificación resultante, por lo que, de acuerdo con Kalcsics et al. (2005), una selección "inadecuada" difícilmente puede generar regiones válidas que verifiquen los criterios establecidos. ABSTRACT Tenitory or zone design processes entail partitioning a geographic space, organized as a set of basic areal units, into different regions or zones according to a specific set of entena that are dependent on the application context. In most cases the aim is to create zones that have approximately equal sizes with respect to one or several measure attributes (zones with equal numbers of inhabitants, same average sales, etc). However, some of the new applications that have emerged, particularly in the context of sustainable development policies, are aimed at defining zones of a predetermined, though not necessarily similar, size. In addition, the zones should be built around a given set of positions, seeds or generators. This type of partitioning has not been sufñciently researched; therefore there are no known approaches for automated zone delimitation. This thesis proposes a new method based on a discrete versión of the Adaptive Additively Weighted Voronoi Diagram (AAWVD) that makes it possible to partition a 2D space into zones of specific sizes, taking both the position and the weight of each (seed) generator into account. The method consists of repeatedly solving a traditional additively weighted Voronoi diagram, so that the weights of each generator are updated at every iteration. The partition s zones are geographically connected nsing a metric based 011 the shortest path. The proposed heuristic lias been included in an application, developed in a GIS environment that allows the automated zone delimitation according to the mentioned criteria. The management of the extensive farming system of three municipalities of Castilla-La Mancha (Spain) has been used as study case to analyze the viability of the method. The tests carried out have established that the proposed method, adapted to the criteria of this application field, is valid for solving this type of partition problem. The applied algorithm is capable of handling a high number of vector areal units, generating solutions that converge in a reasonable CPU time and comply with the imposed constraints. Although the complexity of this problem is greatly reduced when the generator's positions are fixed, in many cases, these positions impose a spatial confignration that the algorithm proposed is unable to solve, thus revealing one of the limitations of this method. It has been shown that the location of the generators has a considerable impact on the final solution, so that, as Kalcsics et al. (2005) observed, an "inadequate" selection can hardly generate valid zones that comply with the established criteria.

Data Mining with Enhanced Neural Networks-CMMSE

Abstract This paper presents a new method to extract knowledge from existing data sets, that is, to extract symbolic rules using the weights of an Artificial Neural Network. The method has been applied to a neural network with special architecture named Enhanced Neural Network (ENN). This architecture improves the results that have been obtained with multilayer perceptron (MLP). The relationship among the knowledge stored in the weights, the performance of the network and the new implemented algorithm to acquire rules from the weights is explained. The method itself gives a model to follow in the knowledge acquisition with ENN.

Power-Aware Multi-Objective Evolvable Hardware System on an FPGA

Dynamic and Partial Reconfiguration (DPR) allows a system to be able to modify certain parts of itself during run-time. This feature gives rise to the capability of evolution: changing parts of the configuration according to the online evaluation of performance or other parameters. The evolution is achieved through a bio-inspired model in which the features of the system are identified as genes. The objective of the evolution may not be a single one; in this work, power consumption is taken into consideration, together with the quality of filtering, as the measure of performance, of a noisy image. Pareto optimality is applied to the evolutionary process, in order to find a representative set of optimal solutions as for performance and power consumption. The main contributions of this paper are: implementing an evolvable system on a low-power Spartan-6 FPGA included in a Wireless Sensor Network node and, by enabling the availability of a real measure of power consumption at run-time, achieving the capability of multi-objective evolution, that yields different optimal configurations, among which the selected one will depend on the relative “weights” of performance and power consumption.