Extending Distance-based Ranking Models In Estimation of Distribution Algorithms

Recently, probability models on rankings have been proposed in the field of estimation of distribution algorithms in order to solve permutation-based combinatorial optimisation problems. Particularly, distance-based ranking models, such as Mallows and Generalized Mallows under the Kendall’s-t distance, have demonstrated their validity when solving this type of problems. Nevertheless, there are still many trends that deserve further study. In this paper, we extend the use of distance-based ranking models in the framework of EDAs by introducing new distance metrics such as Cayley and Ulam. In order to analyse the performance of the Mallows and Generalized Mallows EDAs under the Kendall, Cayley and Ulam distances, we run them on a benchmark of 120 instances from four well known permutation problems. The conducted experiments showed that there is not just one metric that performs the best in all the problems. However, the statistical test pointed out that Mallows-Ulam EDA is the most stable algorithm among the studied proposals.

Contributions on distance-based algorithms, multi-classifier construction and pairwise classification

179 p.

EUSMT: incorporating linguistic information to SMT for a morphologically rich language. Its use in SMT-RBMT-EBMT hybridation

148 p.: graf.

Handover en LTE basado en distancia en plataforma de simulación

[ES]Mejorar el proceso de handover en el despliegue de comunicaciones inalámbricas de banda ancha tradicionalmente ha motivado muchas iniciativas de investigación. En el dominio de los ferrocarriles de alta velocidad, el reto es incluso mayor. Debido a las largas distancias que se cubren, el nodo móvil se ve envuelto en una secuencia obligatoria de procesos de handover. Consecuentemente, un rendimiento pobre en la ejecución de esos procesos de handover degrada significativamente el rendimiento global extremo a extremo. Este documento propone una nueva estrategia de handover para el dominio de los ferrocarriles: un algoritmo de decisión para LTE basado en distancia en lugar de en potencia. La decisión de realizar el handover se realiza cuando un eNB candidato se encuentra más cerca del UE que el eNB fuente. Adicionalmente, cabe la posibilidad de retrasar esa decisión mediante un umbral. Asimismo, se añade una nueva función al modelo de LTE de la plataforma de simulación empleada en la verificación de este modelo. Este mecanismo de decisión introduce un retardo menor en los procesos de handover y, en consecuencia, la calidad extremo-a-extremo aumenta.

Can environmental constraints determine random patterns of plant species co-occurrence?

Plant community ecologists use the null model approach to infer assembly processes from observed patterns of species co-occurrence. In about a third of published studies, the null hypothesis of random assembly cannot be rejected. When this occurs, plant ecologists interpret that the observed random pattern is not environmentally constrained - but probably generated by stochastic processes. The null model approach (using the C-score and the discrepancy index) was used to test for random assembly under two simulation algorithms. Logistic regression, distance-based redundancy analysis, and constrained ordination were used to test for environmental determinism (species segregation along environmental gradients or turnover and species aggregation). This article introduces an environmentally determined community of alpine hydrophytes that presents itself as randomly assembled. The pathway through which the random pattern arises in this community is suggested to be as follows: Two simultaneous environmental processes, one leading to species aggregation and the other leading to species segregation, concurrently generate the observed pattern, which results to be neither aggregated nor segregated - but random. A simulation study supports this suggestion. Although apparently simple, the null model approach seems to assume that a single ecological factor prevails or that if several factors decisively influence the community, then they all exert their influence in the same direction, generating either aggregation or segregation. As these assumptions are unlikely to hold in most cases and assembly processes cannot be inferred from random patterns, we would like to propose plant ecologists to investigate specifically the ecological processes responsible for observed random patterns, instead of trying to infer processes from patterns