Abstract
This paper presents the Usense2learn platform, a platform designed and implemented to enable children and teachers to use georeferenced multisensory information together with information acquired by sensors. Usense2learn places the creation of content in the hands of children. While using Usense2learn, mobile sensors can be held across the exploration area and provide georeferenced environmental information such as air temperature and humidity. Using multimedia (video, image, sound and text) teachers and children can bring the outside world into their classroom and share it with other classrooms across the globe. Having the limited schools' budgets in mind, content creation can be made anywhere without communication costs. Internet connection is only required, together with Google Earth, for visualization. The Usense2learn platform was successfully used in a curricular context, engaging children and teachers in meaningful environmental education activities. © 2010 ACM.

Abstract
The benefits of robot simulation technology have been recognized by scientists and engineers, with applications ranging from simple robot path simulation to complete robotic cell layout simulation. Robot simulation is one of the essential elements of modern and agile manufacturing plants, as it allows to visualize and test a robotic system, even if it does not exist physically. High-growth industries and emerging manufacturing processes will increasingly depend on advanced robot technology such as robotic simulation. Robot path simulation is a very useful process to predict and pre-evaluate performance of robot programs generated off-line. This paper presents a simulation system where a relatively low cost and commercially available 3D CAD package is used as an interface to visualize/simulate pre-programmed robot paths. The developed system is intuitive and friendly, so that in a few minutes any user without knowledge of CAD and robot programming will be able to simulate robot paths and visualize it in a CAD environment. This way, this simulator can be useful for small and medium sized enterprises and for educational purposes. Three different experiments (simulation of robot motion/paths) are presented and discussed: a material handling task; a robot performing work in the footwear industry (shoes soles); and finally, the simulation of robot paths for a robot operating in a bending cell. The experimental results showed that the proposed system is flexible, easy to use and efficient. This paper also covers topics like how simulation makes robot programming easier, advantages and disadvantages of simulation in robotics, and the future trends in this field. Finally, the results of the experiments will be analyzed and discussed. The pros and cons of the system in relation to off-the-shelf robot simulation packages are analyzed. ©2010 IEEE.

Abstract
Trajectory sensitivity analysis can provide valuable insights into the security of an electric power system. There is a strong correlation relating the system stability and the corresponding trajectory sensitivity. In this paper it is analyzed the influence of load shedding in the voltage stability of an electric power system using trajectory sensitivity analysis. It is recognized that voltage instability and collapse have led to major system failures. The emergency load shedding is one of the most important methods to preserve the system stability. In this study different values of load shedding were used to avoid voltage collapse. The automatic voltage regulators of the generating units and the turbine speed governors were modelled. Different load models were used and the under load tap changers were also taken into account. The simulation results were obtained using EUROSTAG program and post-processing module developed using the Matlab software package.

Abstract
In this paper we address two major challenges presented by stochastic discrete optimisation problems: the multiobjective nature of the problems, once risk aversion is incorporated, and the frequent difficulties in computing exactly, or even approximately, the objective function. The latter has often been handled with methods involving sample average approximation, where a random sample is generated so that population parameters may be estimated from sample statistics-usually the expected value is estimated from the sample average. We propose the use of multiobjective metaheuristics to deal with these difficulties, and apply a multiobjective local search metaheuristic to both exact and sample approximation versions of a mean-risk static stochastic knapsack problem. Variance and conditional value-at-risk are considered as risk measures. Results of a computational study are presented, that indicate the approach is capable of producing high-quality approximations to the efficient sets, with a modest computational effort.

Abstract
Multi-agent systems (MAS) are a research topic with ever-increasing importance. This is due to their inherently distributed organization that copes more naturally with real-life problems whose solution requires people to coordinate efforts. One of its most prominent challenges consists on the creation of efficient coordination methodologies to enable the harmonious operation of teams of agents in adversarial environments. This challenge has been promoted by the Robot World Cup (RoboCup) international initiative every year since 1995. RoboCup provides a pragmatic testbed based on standardized platforms for the systematic evaluation of developed MAS coordination techniques. This initiative encompasses a simulated robotic soccer league in which 11 against 11 simulated robots play a realistic soccer game that is particularly suited for researching coordination methodologies. This paper presents a comprehensive overview of the most relevant coordination techniques proposed up till now in the simulated robotic soccer domain.

Abstract
Traditional industrial robot programming, using the robot teach pendant, is a tedious and time-consuming task that requires technical expertise. Hence, new and more intuitive ways for people to interact with robots are required to make robot programming easier. The goal is to develop methodologies that help users to program a robot in an intuitive way, with a high-level of abstraction from the robot language. In this paper we present a CAD-based system to program a robot from a 3D CAD environment, allowing users with basic CAD skills to generate robot programs off-line, without stop robot production. This system works as a human-robot interface (HRI) where, through a relatively low cost and commercially available CAD package, the user is able to generate robot programs. The methods used to extract information from the CAD and techniques to treat/convert it into robot commands are presented. The effectiveness of the proposed method is proved through various experiments. The results showed that the system is easy to use and within minutes an untrained user can set up the system and generate a robot program for a specific task. Finally, the time spent in the robot programming task is compared with the time taken to perform the same task but using the robot teach pendant as interface. ©2010 IEEE.