Abstract
The non-stationary and stochastic nature of wind power reveals itself a difficult task to forecast and manage. In this context, with the continuous increment of wind farms and their capacity production in Portugal, there is an increasing need to develop new forecasting tools with enhanced capabilities. On the one hand, it is crucial to achieve higher accuracy and less uncertainty in the predictions. On the other hand, the computational burden should be kept low to enable fast operational decisions. Hence, this paper proposes a new hybrid evolutionary-adaptive methodology for wind power forecasting in the short-term, successfully combining mutual information, wavelet transform, evolutionary particle swarm optimization, and the adaptive neuro-fuzzy inference system. The strength of this paper is the integration of already existing models and algorithms, which jointly show an advancement over present state of the art. The results obtained show a significant improvement over previously reported methodologies.

Abstract
Breast cancer is one of the most mediated malignant diseases, because of its high incidence and prevalence, but principally due to its physical and psychological invasiveness. The study of this disease using computer science tools resorts often to the image segmentation operation. Image segmentation, although having been extensively studied, is still an open problem. Shortest path algorithms are extensively used to tackle this problem. There are, however, applications where the starting and ending positions of the shortest path need to be constrained, defining a closed contour enclosing a previously detected seed. Mass and calcification segmentation in mammograms and areola segmentation in digital images are two particular examples of interest within the field of breast cancer research. Usually the closed contour computation is addressed by transforming the image into polar coordinates, where the closed contour is transformed into an open contour between two opposite margins. In this work, after illustrating some of the limitations of this approach, we show how to compute the closed contour in the original coordinate space. After defining a directed acyclic graph appropriate for this task, we address the main difficulty in operating in the original coordinate space. Since small paths collapsing in the seed point are naturally favored, we modulate the cost of the edges to counterbalance this bias. A thorough evaluation is conducted with datasets from the breast cancer field. The algorithm is shown to be fast and reliable and suffers no loss in resolution.

Abstract
This paper reviews the main characteristics of cloud computing, where they are exposed their main components and ways of use. In addition to the technological review that is done, is also carried out a critical analysis of their potential and challenges in the context of SMEs. To understand how cloud computing can lead to a powerful ally of SMEs in the context of organizational competitiveness in a world where the role of information systems for a long time proved decisive, it is a reflection that the SMEs, whose core business is not technology, need to carry out.

Abstract
This paper addresses the cutting stock/leftover problem (CSLP), which differs from the ordinary cutting stock problem (CSP) by retaining stock leftovers that can be cut in the future to meet new demands. Therefore, leftovers are not considered waste in the current period. A new mathematical model for the CSLP is presented to capture a well-used strategy in the practice of cutting, which consists of partially cutting the objects in stock, and keeping the leftovers to be cut in the next periods. Computational experiments were made for the one-dimensional case, although other dimensions can be considered straightforward.

Abstract
Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European electricity market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. However, physical constraints, such as the grid limited capacity, are major setbacks, which make the full European market unification a more distant goal. This paper presents a study that aims at analyzing the capability of the existing European transmission network in accommodating a full unification of the European electricity markets. This study considers the real European transmission network capacities, supporting a unified Pan-European electricity market scenario, which is simulated using the Multi-Agent System for Competitive Electricity Markets.

Abstract