Abstract
In this paper, it is presented a study concerning about the use of the three-dimensional virtual world Second Life (SL) to visualize and contextualize the learning of computer programming. SL allows students to use avatars to create 3D objects and program their behaviours, process data, and interact with external servers, using Linden Scripting Language (LSL), a language with C-like syntax and a state machine. Scripts can execute concurrently, and several students can simultaneously work over the same object and/or script. Through action research, we explore and analyse the potential of SL for teaching-learning introductory computer programming in computer science undergraduate courses. We believe this virtual environment has potential to help students, since it presents an immediately visual feedback of the program execution.

Abstract
The goals of the present work are to automatically extract the contour of an object and to simulate its deformation using a physical approach. Thus, to segment an object represented in an image, an initial contour is manually defined for it that will then automatically evolve until it equals the border of the desired object. The contour is modelled by a physical formulation, and its evolution to the desired final contour is driven by internal and external forces. To build the physical model of the contour used in the segmentation process, we adopted the isoparametric finite element proposed by Sclaroff, and to obtain its evolution towards the object border we used the methodology presented by Nastar that consists in solving the dynamic equilibrium equation between two consecutive instants. As for the simulation of the deformation between two different instances of an object, or between two objects, after their contours have been properly modelled, modal analysis, complemented with global optimization techniques, is employed to establish the correspondence between their nodes (data points). After the matching phase, the displacements field between the two contours is simulated using the dynamic equilibrium equation. The proposed approach will be here considered in dynamic pedobarography images.

Abstract
In recent years optimization of fuzzy controllers has been widely considered by researchers, especially using genetic algorithms. Genetic supervisory fuzzy (GSF) control architecture for multi-part-Type production line is proposed in this paper. GSF control architecture composed of two layer controller. In first layer heuristic distributed fuzzy (HDF) controllers has been used to control each machine separately, while GSF controllers has been used in second layer. GSF controllers tune the decisions made by HDF controllers, based on overall conditions of production system. Genetic algorithm (GA) is used to adapt the membership functions of fuzzy supervisory controllers, to improve the performance of such controllers. The overall objective is to control the production rate in a way that satisfies the demand for final products while keeping minimum work-in-process (WIP) and backlog within the production system. GA is used to minimize costs of WIP and backlog. The results show that in most of the cases GSF outperform the conventional supervisory controllers. Copyright© (2008) by Computers & Industrial Engineering.

Abstract
OTDM-to-WDM conversion from 128.1 Gbit/s to 3x42.7Gbit/s is achieved by wavelength conversion using side filtering of SPM broadened spectrum in HNLF, followed by a single electro-absorption modulator based optical gate. A maximum 2dB penalty was achieved. (C) 2008 Optical Society of America.

Abstract
The main goals of the present work are to automatically extract the Contour of an object and to simulate its deformation using a physical approach. In this work, to segment an object represented in an image, an initial contour is manually defined for it that will then automatically evolve until it reaches the border of the desired object. In this approach, the contour is modelled by a physical formulation using the finite element method. and its temporal evolution to the desired final Contour is driven by Internal and external forces. The internal forces are defined by the intrinsic characteristics of the material adopted for the physical model and the interrelation between its nodes. The external forces are determined in function of the image features most suitable for the object to be segmented. To build the physical model of the contour used In the Segmentation process, the isoparametric finite element proposed by Sclaroff is adopted, and to obtain its evolution towards the object border the methodology presented by Nastar is used, that consists in solving the dynamic equilibrium equation between two Consecutive instants. To simulate the deformation between two different instances of an object, after they each have their contours properly modelled, modal analysis, complemented with global optimization techniques, is employed to establish the correspondence between their nodes (data points). After this matching phase, the displacements field between the two contours is simulated using the dynamic equilibrium equation that balances the internal forces defined by the physical model. and the external forces determined by the distance between the two contours.

Abstract