Failure detectors and communication efficiency in the crash and general omisión failure models

122 p.

Una longeva técnica forestal: los trasmochos o desmochos guiados en Guipúzcoa durante la Edad Moderna

[ES] A fin de garantizar el aprovechamiento deun recurso renovable como la madera, en un momento de retroceso forestal y escasez de materiales, los habitantes de la provincia de Guipúzcoa, ante lo exiguo de su territorio, arbitraron un sistema que permitió combinar las necesidades y demandas de actividades tan dispares como la ganadería, el consumo doméstico, la siderurgia o la construcción naval. El presente artículo pretende analizar el origen, desarrollo y desaparición de los trasmochos guiados y describir su técnica en el territorio guipuzcoano. A falta de mayores evidencias, parece que la técnica del trasmochado o desmochado guiado inició su andadura en la Baja Edad Media, aunque hasta las primeras décadas del siglo XVI no existen datos documentales de su utilización en territorio guipuzcoano. Su generalización en todo el territorio guipuzcoano no parece producirse definitivamente hasta finales del siglo XVII, aunque para entonces se venía aplicando en la costa y el sector oriental de la reclamaciones de las autoridades reales y territoriales, la obligación de dejar horca y pendón se encontró con la oposición de carboneros y ferrones, quienes trasmochaban los árboles pero sin guiarlos, perjudicando de ese modo a las autoridades e intereses de la Marina Real. Precisamente el incumplimiento de las ordenanzas fue lo que provocó la aparición de dos modelos, con usos diferenciados: trasmochos sin guiar y trasmochos guiados. A lo largo del siglo XIX dicha técnica se fue perdiendo, coincidiendo con la paulatina desaparición de la construcción naval en madera.

An Open and Social Spaced Repetition System for Language Learning

In the last decades big improvements have been done in the field of computer aided learning, based on improvements done in computer science and computer systems. Although the field has been always a bit lagged, without using the latest solutions, it has constantly gone forward taking profit of the innovations as they show up. As long as the train of the computer science does not stop (and it won’t at least in the near future) the systems that take profit of those improvements will not either, because we humans will always need to study; Sometimes for pleasure and some other many times out of need. Not all the attempts in the field of computer aided learning have been in the same direction. Most of them address one or some few of the problems that show while studying and don’t take into account solutions proposed for some other problems. The reasons for this can be varied. Sometimes the solutions simply are not compatible. Some other times, because the project is an investigation it’s interesting to isolate the problem. And, in commercial products, licenses and patents often prevent the new projects to use previous work. The world moved forward and this is an attempt to use some of the options offered by technology, mixing some old ideas with new ones.

Towards complex system design and management in the engineering domain – the smart grid challenge

This is an Author's Accepted Manuscript of an article published in “Emergence: Complexity and Organization”, 15 (2), pp. 14-22 (2013), copyright Taylor & Francis.

Using the system dynamics paradigm in teaching and learning technological university subjets

2nd International Conference on Education and New Learning Technologies

Analysis, optimization and development of an answer scoring system

The main contribution of this work is to analyze and describe the state of the art performance as regards answer scoring systems from the SemEval- 2013 task, as well as to continue with the development of an answer scoring system (EHU-ALM) developed in the University of the Basque Country. On the overall this master thesis focuses on finding any possible configuration that lets improve the results in the SemEval dataset by using attribute engineering techniques in order to find optimal feature subsets, along with trying different hierarchical configurations in order to analyze its performance against the traditional one versus all approach. Altogether, throughout the work we propose two alternative strategies: on the one hand, to improve the EHU-ALM system without changing the architecture, and, on the other hand, to improve the system adapting it to an hierarchical con- figuration. To build such new models we describe and use distinct attribute engineering, data preprocessing, and machine learning techniques.