Abstract
Simulated Annealing (SA) is a powerful tool for optimization problems that have several local optima. This tool has the ability to escape from a local optima accepting relatively bad solutions for a period and searching for good solutions in your neighborhood. This paper describes the use of SA based on Gaussian Probability Density Function as a decision support criteria in resolution of Transmission Expansion Planning (TEP) problem. This method consists in starting from an initial solution with all possible circuits added and over the iterations removing, replacing or adding new circuits. The method proved to be a reasonable computational effort and proved able to find optimal values known in the literature.

Abstract
This manuscript presents the performance evaluation of our algorithm that precisely finds human eyes in still gray-scale images and describes the state of the founded eye. This algorithm has been evaluated considering two descriptors - Pyramid transform domain (PLBP) and Multi-Block Histogram LBP (BHLBP), which are extended versions of the Local Binary Pattern descriptor (LBP). For the classification stage, two types of supervised learning techniques have also been evaluated, Support Vector Machine (SVM) and Multilayer Perceptron (MLP). The proposed method is assessed on the Face Recognition Grand Challenge (BioID) and (CAS-PEAL-R1) databases, and experimental results demonstrate improved performance than some state-of-the-art eye detection approaches.

Abstract
In this paper we discuss collaborative learning strategies based on the use of digital stories in corporate training and lifelong learning. The text starts with a concise review on theoretical and technical foundations about the use of digital technologies in collaborative strategies in lifelong learning. We will also discuss if the corporate training may be improved by the use of individual audio-visual experience in learning process. Careful planning, scripting and production of audio-visual digital stories can help in the construction of collaborative learning spaces in which adults are in the context of vocational training throughout life. Our analysis concludes emphasizing on the need to experience the routing performance of digital stories in the context of corporate training, following the reference levels mentioned here, so we can have in a future more theoretical and empirical elements for the validation and conceptualization in the use of digital stories in the context of corporate training. Ultimately we believe that lifelong learning can be improved with the use of strategies that promote the production of personal audio-visual for those involved in teaching and learning process in organizational context.

Abstract
This paper presents the design and implementation of a GaN-HEMT, class-J power amplifier suitable for cognitive radio transceivers, i.e., which presents high-efficiency and wideband characteristics, being these maintained for large load variations. Simulation results are presented which show large-signal measurement results of 30 dB gain with 60%-76% power-added efficiency (PAE) over a band of 1.3-2.3 GHz. Adaptivity to load changes is being developed to ensure PAE above 70% for large load variations.

Abstract
The term Dynamic Manufacturing Network (DMN) refers to a new collaborative business model that relies on real-time information sharing, synchronized planning and common business processes. DMNs are operational networks formed among autonomous and globally dispersed partners, and can be seen as the manufacturing industry application of the Virtual Enterprise (VE) concept. Despite their numerous practical benefits such as optimized processes and access to new and global markets, they are particularly vulnerable to disruptions. Any disruption in manufacturing or transportation of products may obviously result in failed orders, thus impacting the whole DMN reliability. Instead of developing stochastic models to deal with uncertainty, as it is usually done, we have rather integrated the concept of flexibility into the tactical and operational planning of such networks. We therefore propose in this work, a multi-objective optimization model that simultaneously maximizes reactive flexibility measures while minimizing total operating costs.

Abstract
Path relinking has been used for solving deterministic problems by exploring the neighborhood of elite solutions in an intelligent way. We present an algorithm that combines a mixed-integer linear solver with a truncated path-relinking method in order to solve two-stage stochastic integer problems with complete recourse and first-stage integer variables. This method takes advantage of a possible scenario-based decomposition in an innovative way. Therefore, path relinking is used to combine optimized solutions from different scenarios in order to pursue good stochastic solutions. To assess the computational performance of this method, we use the stochastic lot sizing and scheduling problem dealing with perishable products. In this problem, first-stage decision variables are linked to production sequences and production quantities. After the uncertain demand is unveiled, the second-stage variables decide on the inventory usage. Computational results show a clear advantage of the proposed method when compared to a state-of-the-art mixed-integer linear solver.