Abstract
The increased integration of wind power into the electric grid, as it occurs today in Portugal, poses new challenges due to its intermittency and volatility. Wind power forecasting plays a key role in tackling these challenges. A novel hybrid approach, combining wavelet transform, particle swarm optimization, and an adaptive-network-based fuzzy inference system, is proposed in this paper for short-term wind power forecasting in Portugal. A thorough comparison is carried out, taking into account the results obtained with seven other approaches. Finally, conclusions are duly drawn.

Abstract
Construction of LEGO models is a popular hobby, not only among children and young teenagers, but also for adults of all ages. Following the technological evolution and the integration of computers into the everyday life, several applications for virtual LEGO modelling have been created. However, these applications generally have interfaces based on windows, icons, menus and pointing devices, the so-called WIMP interfaces, thus being unnatural and hard-to-use for many users. Taking advantage of new trends in of interaction paradigms we developed an innovative solution for virtual LEGO modelling using a horizontal multi-touch surface. To achieve better results, we selected the most common virtual LEGO applications and performed a comparative study, identifying advantages and disadvantages of each one. In this paper we briefly present that study and describe the application developed upon it.

Abstract
Time series motif discovery is the task of extracting previously unknown recurrent patterns from time series data. It is an important problem within applications that range from finance to health. Many algorithms have been proposed for the task of efficiently finding motifs. Surprisingly, most of these proposals do not focus on how to evaluate the discovered motifs. They are typically evaluated by human experts. This is unfeasible even for moderately sized datasets, since the number of discovered motifs tends to be prohibitively large. Statistical significance tests are widely used in bioinformatics and association rules mining communities to evaluate the extracted patterns. In this work we present an approach to calculate time series motifs statistical significance. Our proposal leverages work from the bioin-formatics community by using a symbolic definition of time series motifs to derive each motif's p-value. We estimate the expected frequency of a motif by using Markov Chain models. The p-value is then assessed by comparing the actual frequency to the estimated one using statistical hypothesis tests. Our contribution gives means to the application of a powerful technique - statistical tests - to a time series setting. This provides researchers and practitioners with an important tool to evaluate automatically the degree of relevance of each extracted motif. Copyright © SIAM.

Abstract

Abstract
A highly birefringent photonic bandgap Bragg fiber loop mirror configuration for simultaneous measurement of strain and temperature is proposed. The group birefringence and the sharp loss peaks are observable in the spectral response. Because the sensing head presents different sensitivities for strain and temperature measurands, these physical parameters can be discriminated by using the matrix method. It should be noted that this Bragg fiber presents high sensitivity to temperature, of similar to 5.75 nm/degrees C, due to the group birefringence variation. The rms deviations obtained are +/- 19.32 mu e and +/- 0.5 degrees C, for strain and temperature measurements, respectively. (C) 2011 Optical Society of America

Abstract
This paper is on the short-term thermal scheduling (STTS) problem, particularly concerning the new competitive and environmentally constrained electricity supply industry. On the one hand, within the electricity market, STTS has evolved from a minimum-cost policy in state-owned monopolistic companies to a profit-based policy under market conditions. On the other hand, as a consequence of growing environmental concerns, an unprecedented change points to a scenario where it is necessary to take into account the constraints related to the environment. We propose a multiobjective optimization (MO) approach to solve the profit-based STTS problem with environmental concerns. Two case studies are considered: the IEEE 30-bus system and a 75-bus system. Finally, conclusions are duly drawn.