Chemical composition of manganese nodules and crusts from the Pacific and Indian Ocean and Loch Fyne, Scotland

The first part of this thesis includes some topics of a non-geochemical nature but which are of importance in interpreting the geochemistry of nodules. The points covered include their distribution, petrography, structure, mineralogy and internal compositional variations. Part Two includes the geochemistry of both nodules and that of their surrounding sediments, This geochemical study has been divided into firstly, a general geochemical study of both nodules and sediments using a statistical approach to the interpretation of the data, secondly, the regional geochemistry of Pacific and Indian Ocean nodules and sediments, the latter entirely uninvestigated in the past, and thirdly, local variations in the composition of nodules. Throughout, emphasis has been placed on the geochemistry of nodules in terms of their environment of formation.

Players Redux: A Cyclical History of World Trade Center

Articulo publicado con ocasión de los 10 años del 9/11, el día 11.09.2011 en portada de edición on-line. ... The towers seemed provisional to Pammy. They remained mere concepts, not because their excessive volume less temporary than any regular distortion of light.

Co-evolutionary and Reinforcement Learning Techniques Applied to Computer Go players

The objective of this thesis is model some processes from the nature as evolution and co-evolution, and proposing some techniques that can ensure that these learning process really happens and useful to solve some complex problems as Go game. The Go game is ancient and very complex game with simple rules which still is a challenge for the Artificial Intelligence. This dissertation cover some approaches that were applied to solve this problem, proposing solve this problem using competitive and cooperative co-evolutionary learning methods and other techniques proposed by the author. To study, implement and prove these methods were used some neural networks structures, a framework free available and coded many programs. The techniques proposed were coded by the author, performed many experiments to find the best configuration to ensure that co-evolution is progressing and discussed the results. Using co-evolutionary learning processes can be observed some pathologies which could impact co-evolution progress. In this dissertation is introduced some techniques to solve pathologies as loss of gradients, cycling dynamics and forgetting. According to some authors, one solution to solve these co-evolution pathologies is introduce more diversity in populations that are evolving. In this thesis is proposed some techniques to introduce more diversity and some diversity measurements for neural networks structures to monitor diversity during co-evolution. The genotype diversity evolved were analyzed in terms of its impact to global fitness of the strategies evolved and their generalization. Additionally, it was introduced a memory mechanism in the network neural structures to reinforce some strategies in the genes of the neurons evolved with the intention that some good strategies learned are not forgotten. In this dissertation is presented some works from other authors in which cooperative and competitive co-evolution has been applied. The Go board size used in this thesis was 9x9, but can be easily escalated to more bigger boards.The author believe that programs coded and techniques introduced in this dissertation can be used for other domains.

Training-induced changes in drag-flick technique in female field hockey players

The penalty corner is one of the most important goal plays in field hockey. The drag-flick is used less by women than men in a penalty corner. The aim of this study was to describe training-induced changes in the drag-flick technique in female field hockey players. Four female players participated in the study. The VICON optoelectronic system (Oxford Metrics, Oxford, UK) measured the kinematic parameters of the drag-flick with six cameras sampling at 250 Hz, prior to and after training. Fifteen shots were captured for each subject. A Wilcoxon test assessed the differences between pre-training and post-training parameters. Two players received specific training twice a week for 8 weeks; the other two players did not train. The proposed drills improved the position of the stick at the beginning of the shot (p<0.05), the total distance of the shot (p<0.05)and the rotation radius at ball release (p<0.01). It was noted that all players had lost speed of the previous run. Further studies should include a larger sample, in order to provide more information on field hockey performance.

Evolving and coevolving computer go players using neuroevolution.

The Go game is ancient very complex game with simple rules which still is a challenge for the AI.This work cover some neuroevolution techniques used in reinforcement learning applied to the GO game as SANE (Symbiotic Adaptive Neuro-Evolution) and presents a variation to this method with the intention of evolving better strategies in the game. The computer Go player based in SANE is evolved againts a knowed player which creates some problem as determinism for which is proposed the co-evolution. Finally, it is introduced an algorithm to co-evolve two populations of neurons to evolve better computer Go players.