Abstract
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that continuously evolve over time, run in resource-aware environments, and detect and react to changes in the environment generating data. One important issue, not yet conveniently addressed, is the design of experimental work to evaluate and compare decision models that evolve over time. In this paper we propose a general framework for assessing the quality of streaming learning algorithms. We defend the use of Predictive Sequential error estimates over a sliding window to assess performance of learning algorithms that learn from open-ended data streams in non-stationary environments. This paper studies properties of convergence and methods to comparatively assess algorithms performance. Copyright 2009 ACM.

Abstract
The first Portuguese corporate governance code was issued by the Portuguese Securities Commission (CMVM) in 1999. This code has been revised every two years. More recently, in 2006 the civil society issued a code of good governance as well. In this paper we argue that the issuance of codes of good governance in Portugal has been very important for two reasons. First, it has been leading the discussion on corporate governance matters. Second, it has induced the evolution of the governance system both by inspiring the enacting of rules and regulations, and by influencing the existing practices. We show that the level of the companies' compliance with the good governance code has been increasing, which means that companies have been changing their practices. Furthermore, large and more liquid companies are more likely to comply with the recommendations. We conclude that the "one size fits all" model is not appropriate for the Portuguese case, and that the good governance code should account for size and liquidity. On the other hand, assuming that the best practice code is specially designed for large companies, it is expectable that smallest companies rely more intensively on the "explain" prerogative of the "comply or explain" principle than the biggest companies.

Abstract
IdSay is an open domain Question Answering (QA) system for Portuguese. Its current version can be considered a baseline version, using mainly techniques from the area of Information Retrieval (IR). The only external information it uses besides the text. collections is lexical information for Portuguese. It was submitted to the monolingual Portuguese task of the QA track of the Cross-Language Evaluation Forum 2008 (QA@CLEF) for the first time, and it answered correctly to 65 of the 200 questions in the first answer, and to 85 answers considering the three answers that could be returned per question. Generally, the types of questions that are answered better by IdSay system are measure factoids, Count factoids and definitions, but there is still work to be done in these areas, as well as in the treatment of time. List questions, location and people/organization factoids are the types of question with more room for improvement.

Abstract
In this work we consider the problem of forecasting integer-valued time series, modelled by the INAR(1) process introduced by McKenzie (1985) and Al-Osh and Alzaid (1987). The theoretical properties and practical applications of INAR and related processes have been discussed extensively in the literature but there is still some discussion on the problem of producing coherent, i.e. integer-valued, predictions. Here Bayesian methodology is used to obtain point predictions as well as confidence intervals for future values of the process. The predictions thus obtained are compared with their classic counterparts. The proposed approaches are illustrated with a simulation study and a real example.

Abstract

Abstract
Taking into account that the non renewable recourses are less and less available worldwide we need to use renewable energies to produce electricity. The wind energy is nowadays the most attractive renewable energy, after hydropower, to produce electricity. Wind energy is the renewable energy source that had a higher growing in the last decades and can be considered a hope in future based on clean and sustainable energy. All over the world, energy companies are investing in technologies to make better use of renewable energy to generate electric power. Wind energy is the renewable energy source that had a higher growing in the last decades and can be considered a hope in future based on clean and sustainable energy. Unlike conventional fuels, wind energy is a massive indigenous power source permanently available in virtually every nation in the world. Wind power delivers the energy security benefits of fuel costs, no long term fuel price risk, and avoids the economic and supply risks that can arise with reliance on imported fuels and political dependence on other countries. The problems resulting by the production of electricity using wind power and by the interconnection of wind parks to the grid are discussed in this paper.