Abstract
The rising challenges in the field of iris recognition, concerning the development of accurate recognition algorithms using images acquired under an unconstrained set of conditions, is leading to the a renewed interest in the area. Although several works already report excellent recognition rates, these values are obtained by acquiring images in very controlled environments. The use of such systems in daily security activities, such as airport security and bank account management, is therefore hindered by the inherent unconstrained nature under which images are to be acquired. The proposed work focused on mutual context information from iris centre and iris limbic contour to perform robust and accurate iris segmentation in noisy images. A random subset of the UBIRIS.v2 database was tested with a promising E1 classification rate of 0.0109.

Abstract
Os sistemas vestíveis são uma tendência crescente na aquisição de sinais fisiológicos e de parâmetros biomecânicos de forma não obstrutiva. A utilização de elétrodos têxteis tornou-se muito popular devido à simplicidade e homogeneidade providenciada pela sua introdução em têxteis e peças de vestuário. Neste trabalho foi realizada a validação de elétrodos têxteis para medições electromiográficas através da comparação com elétrodos convencionais de cloreto de prata. Os resultados evidenciam que os elétrodos têxteis são capazes de medir potenciais mioeléctricos de forma semelhante aos elétrodos convencionais.

Abstract
Electricity markets are complex environments with very particular characteristics. A critical issue concerns the constant changes they are subject to. This is a result of the electricity markets' restructuring, performed so that the competitiveness could be increased, but with exponential implications in the increase of the complexity and unpredictability in those markets' scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behavior. The need for understanding the market mechanisms and how the involved players' interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This paper presents the Multi-Agent System for Competitive Electricity Markets (MASCEM) - a simulator based on multi-agent technology that provides a realistic platform to simulate electricity markets, the numerous negotiation opportunities and the participating entities. © 2013 Springer-Verlag Berlin Heidelberg.

Abstract
The success of the textile industry largely depends on the products offered and on the speed of response to variations in demand that are induced by changes in consumer lifestyles. The study of behavioral habits and buying trends can provide models to be integrated into the decision support systems of companies. Data mining techniques can be used to develop models based on data. This approach has been used in the past to develop models to improve sales in the textile industry. However, the discovery of scientific models based on subgroup discovery algorithms, that characterize subgroups of observations with rare distributions, has not been made in this area. The goal of this work is to investigate whether these algorithms can extract knowledge that is useful for a particular kind of textile industry, which produces highly customized garments. We apply the CN2-SD subgroup discovery method to find rare and interesting subgroups products on a database provided by a manufacturer of custom-made shirts. The results show that it is possible to obtain knowledge that is useful to understand customer preferences in highly customized textile industries using subgroup discovery techniques. © Springer International Publishing Switzerland 2013.

Abstract
In the last two decades, there was a proliferation of programming exercise formats that hinders interoperability in automatic assessment. In the lack of a widely accepted standard, a pragmatic solution is to convert content among the existing formats. BabeLO is a programming exercise converter providing services to a network of heterogeneous e-learning systems such as contest management systems, programming exercise authoring tools, evaluation engines and repositories of learning objects. Its main feature is the use of a pivotal format to achieve greater extensibility. This approach simplifies the extension to other formats, just requiring the conversion to and from the pivotal format. This paper starts with an analysis of programming exercise formats representative of the existing diversity. This analysis sets the context for the proposed approach to exercise conversion and to the description of the pivotal data format. The abstract service definition is the basis for the design of BabeLO, its components and web service interface. This paper includes a report on the use of BabeLO in two concrete scenarios: to relocate exercises to a different repository, and to use an evaluation engine in a network of heterogeneous systems.

Abstract
Lightweight formal methods ought to provide to the end user the rigorousness of mathematics, without compromising simplicity and intuitiveness. Alloy is a powerful tool, particularly successful on this mission. Limitations on the verification side, however, are known to prevent its wider use in the development of safety or mission critical applications. A number of researchers proposed ways to connect Alloy to other tools in order to meet such challenges. This paper's proposal, however, is not establishing a link from Alloy to another single tool, but rather to 'plunge' it into the Hets network of logics, logic translators and provers. This makes possible for Alloy specifications to 'borrow' the power of several, non dedicated proof systems. Semantical foundations for this integration are discussed in detail. © 2013 IEEE.