Analysis and evaluation of public health policy in Cuba : progress on millennium development goals

[EN] The main objective of this project is to analyze Cuban public health policy and the Millennium Development Goals, especially those linked to the issue of health, presenting their potential and strengths with a well-defined time horizon (2000-2015). The Millennium Development Goals are the international consensus on development and was signed as an international minimum agreement, with which began the century. The MDGs promote various goals and targets, with the corresponding monitoring indicators, which should be achieved by all countries for the present year. Health is an area that is at the center of the Millennium Development Goals, which reinforce each other to get a true human development itself. The research was done through theoretical frameworks of social production of health and disease, social justice and the power structure. A retrospective analysis of Cuban economic and social context is performed in order to study whether health-related MDGs are likely to be completed by the deadline on the island and likewise, the main parameters related to health compared with those of the neighboring countries in the Americas.

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.

Water quality assessment and characterisation of chlorophyll-a variability related to river discharges, within the southeastern Bay of Biscay : evaluation and development of chlorophyll-a algorithms for MODIS and MERIS imagery

222 p. : il.

Design, analysis and implementation of a versatile low level radio frequency system for accelerating cavities

179 p.