Topology-preserving ordering of the RGB space with an evolutionary algorithm

Mathematical morphology (MM) is broadly used in image processing. MM operators require to establish an order between the values of a set of pixels. This is why MM is basically used with binary and grayscale images. Many works have been focused on extending MM to colour images by mapping a multi-dimensional colour space onto a linear ordered space. However, most of them are not validated in terms of topology preservation but in terms of the results once MM operations are applied. This work presents an evolutionary method to obtain total- and P-orderings of a colour space, i.e. RGB, maximising topology preservation. This approach can be used to order a whole colour space as well as to get a specific ordering for the subset of colours appearing in a particular image. These alternatives improve the results obtained with the orderings usually employed, in both topology preservation and noise reduction

A memetic algorithm for the delineation of local labour markets

Given a territory composed of basic geographical units, the delineation of local labour market areas (LLMAs) can be seen as a problem in which those units are grouped subject to multiple constraints. In previous research, standard genetic algorithms were not able to find valid solutions, and a specific evolutionary algorithm was developed. The inclusion of multiple ad hoc operators allowed the algorithm to find better solutions than those of a widely-used greedy method. However, the percentage of invalid solutions was still very high. In this paper we improve that evolutionary algorithm through the inclusion of (i) a reparation process, that allows every invalid individual to fulfil the constraints and contribute to the evolution, and (ii) a hillclimbing optimisation procedure for each generated individual by means of an appropriate reassignment of some of its constituent units. We compare the results of both techniques against the previous results and a greedy method.José M. Casado-Díaz has received financial support from the Spanish Ministry of Transports (Ministerio de Fomento) for the project ”New methods for the analysis of the determinants and effects of commuting flows (MOVICO)” under Grant T 75/2006 (Spanish National Plan of A+D+i). Lucas Martíınez-Bernabeu acknowledges financial support from the Spanish Ministry of Education and Science, the European Social Fund (ESF) and the University of Alicante. Raúl Gómez-Hernández acknowledges financial support from the University of Alicante

An evolutionary approach to the delineation of functional areas based on travel-to-work flows

This paper presents a new approach to the delineation of local labor markets based on evolutionary computation. The aim of the exercise is the division of a given territory into functional regions based on travel-to-work flows. Such regions are defined so that a high degree of inter-regional separation and of intra-regional integration in both cases in terms of commuting flows is guaranteed. Additional requirements include the absence of overlap between delineated regions and the exhaustive coverage of the whole territory. The procedure is based on the maximization of a fitness function that measures aggregate intra-region interaction under constraints of inter-region separation and minimum size. In the experimentation stage, two variations of the fitness function are used, and the process is also applied as a final stage for the optimization of the results from one of the most successful existing methods, which are used by the British authorities for the delineation of travel-to-work areas (TTWAs). The empirical exercise is conducted using real data for a sufficiently large territory that is considered to be representative given the density and variety of travel-to-work patterns that it embraces. The paper includes the quantitative comparison with alternative traditional methods, the assessment of the performance of the set of operators which has been specifically designed to handle the regionalization problem and the evaluation of the convergence process. The robustness of the solutions, something crucial in a research and policy-making context, is also discussed in the paper.This work was supported by Spanish National Plan of R+D+i from Spanish Ministry of Education and Science (Ministerio de Educación y Ciencia) for the project Local Labour Markets: New Methods of Delineation and Analysis (No. SEJ2007-67767-C04-02), and the European Social Fund (ESF) and the University of Alicante

Predictors of outcome after decompressive lumbar surgery and instrumented posterolateral fusion

There has been no agreement among different authors on guidelines to specify the situations in which arthrodesis is justified in terms of results, risks and complications. The aim of this study was to identify preoperative predictors of outcome after decompressive lumbar surgery and instrumented posterolateral fusion. A prospective observational study design was performed on 203 consecutive patients. Potential preoperative predictors of outcome included sociodemographic factors as well as variables pertaining to the preoperative clinical situation, diagnosis, expectations and surgery. Separate multiple linear regression models were used to assess the association between selected predictors and outcome variables, defined as the improvement after 1 year on the visual analog scale (VAS) for back pain, VAS for leg pain, physical component scores (PCS) of SF-36 and Oswestry disability index (ODI). Follow-up was available for 184 patients (90.6%). Patients with higher educational level and optimistic preoperative expectations had a more favourable postoperative leg pain (VAS) and ODI. Smokers had less leg pain relief. Patients with better mental component score (emotional health) had greater ODI improvement. Less preoperative walking capacity predicted more leg pain relief. Patients with disc herniation had greater relief from back pain and more PCS and ODI improvement. More severe lumbar pain was predictive of less improvement on ODI and PCS. Age, sex, body mass index, analgesic use, surgeon, self-rated health, the number of decompressed levels and the length of fusion had no association with outcome. This study concludes that a higher educational level, optimistic expectations for improvement, the diagnosis of “disc herniation”, less walking capacity and good emotional health may significantly improve clinical outcome. Smoking and more severe lumbar pain are predictors of worse results