Abstract
Job shop scheduling problem (JSP) with sequence-dependent setup time and re-entrant work flows is considered in this paper. This is an NP-hard problem which needs to be solved using (meta)heuristic methods (e.g. genetic algorithm (GA)), especially for relatively large instances. However, the GA may face premature convergence (i.e. converging to a local optima), especially for rough solution spaces. In this paper, a fuzzy genetic algorithm (FGA) is proposed to overcome this issue. The objective is to minimize makespan of such problem. Research results show that the FGA outperforms the standard GA and offers better solutions in the same number of runs. © 2013 IEEE.

Abstract
The promotion of quality of life is becoming ever more important in a scenario of regional, national and even international competition among cities, triggered by globalization. Public sites, and green spaces in particular, which are available in varying extent in all urban areas, can bring important benefits to urban vitality and, as a consequence, to quality of life. However, cities are intricate entities and measuring their success in converting the potential for public green space usage into increased quality of life is a difficult task. In order to contribute to the objective of assessing the potential for public green space use, and its consequences on urban vitality, we applied the Data Envelopment Analysis technique to assess a total of 174 European cities. The results detect the best performing cities, and for the cities considered inefficient, a set of benchmarks is identified, whose best practices can be copied to support efforts of performance improvement.

Abstract
Phase-sensitive optical time-domain reflectometry (phi OTDR) is a simple and effective tool allowing the distributed monitoring of vibrations along single-mode fibers. We show in this Letter that modulation instability (MI) can induce a position-dependent signal fading in long-range phi OTDR over conventional optical fibers. This fading leads to a complete masking of the interference signal recorded at certain positions and therefore to a sensitivity loss at these positions. We illustrate this effect both theoretically and experimentally. While this effect is detrimental in the context of distributed vibration analysis using phi OTDR, we also believe that the technique provides a clear and insightful way to evidence the Fermi-Pasta-Ulam recurrence associated with the MI process. (C) 2013 Optical Society of America

Abstract
Several real world prediction problems involve forecasting rare values of a target variable. When this variable is nominal we have a problem of class imbalance that was already studied thoroughly within machine learning. For regression tasks, where the target variable is continuous, few works exist addressing this type of problem. Still, important application areas involve forecasting rare extreme values of a continuous target variable. This paper describes a contribution to this type of tasks. Namely, we propose to address such tasks by sampling approaches. These approaches change the distribution of the given training data set to decrease the problem of imbalance between the rare target cases and the most frequent ones. We present a modification of the well-known Smote algorithm that allows its use on these regression tasks. In an extensive set of experiments we provide empirical evidence for the superiority of our proposals for these particular regression tasks. The proposed SmoteR method can be used with any existing regression algorithm turning it into a general tool for addressing problems of forecasting rare extreme values of a continuous target variable. © 2013 Springer-Verlag.

Abstract
This paper puts forth projections designs for compressive classification of Gaussian mixture models. In particular, we capitalize on the asymptotic characterization of the behavior of an (upper bound to the) misclassification probability associated with the optimal Maximum-A-Posteriori (MAP) classifier, which depends on quantities that are dual to the concepts of the diversity gain and coding gain in multi-antenna communications, to construct measurement designs that maximize the diversity-order of the measurement model. Numerical results demonstrate that the new measurement designs substantially outperform random measurements. Overall, the analysis and the designs cast geometrical insight about the mechanics of compressive classification problems.

Abstract
The adoption of NAO humanoid robots in the RoboCup Standard Platform League (SPL) broguht a new set of challenges on this league on the computer vision area. This paper presents a new color indexing mode and a study of the impact of the reduction of the color spectrum, to be processed on the classification, segmentation and object detection, in a NAO robot, playing on the SPL league. The experiments were performed in the context of the Portuguese Team concluding that a 21 bit look-up table may replace the current 24 bit table used.