Educating for sustainability in virtual worlds : does the virtual have value?

Two key elements of education for sustainability (EfS) are action-competence, and the importance of place and experiencing the natural world. These elements emphasise and depend on the relationship between learners and their real world contexts, and have been incorporated to some extent into the sustainability cross-curricular perspective of the new Australian curriculum. Given the importance of real-world experiential learning in EfS, what is to be made of the use of multi-user virtual worlds in EfS? We went with our preservice secondary science teachers to the very appealing virtual world Quest Atlantis, which we are using in this paper as an example to explore the value of virtual worlds in EfS. In assessing the virtual world of Quest Atlantis against Australia’s Sustainability Curriculum Framework, many areas of coherence are evident relating to world viewing, systems thinking and futures thinking, knowledge of ecological and human systems, and implementing and reflecting on the consequences of actions. The power and appeal of these virtual experiences in developing these knowledges is undeniable. However there is some incoherence between the elements of EfS as expressed in the Sustainability Curriculum Framework and the experience of QA where learners are not acting in their real world, or developing connection with real place. This analysis highlights both the value and some limitations of virtual worlds as a venue for EfS.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.

Engaging in videogame play: An activity-centric analysis of the player experience

This paper focuses on examining play activities in people's favourite videogame experience. Through interviews with 30 videogame players we discovered which types of play activities are most appealing. Our research identifies the level of appeal of a wide range of game play activities. We have established that high levels of engagement for many participants is grounded in play as power and play as strategy, with play as fantasy adding to the experience. Through our study we established that conflict-based activities hold strong appeal. We subsequently investigated the context in which players talked about their experience of conflict within game. By using activities as a categorisation of gameplay we have been able to capture the play experience across a range of games and a range of gaming contexts. By examining players' individual experience we begin to understand why conflict in videogames appears to be a popular choice of activities.

Design and developement of a pulsed power system for a Vircator based HPM source

Pulse Forming Line (PFL) based high voltage pulsed power systems are well suited for low impedance High Power Microwave (HPM) sources such as a virtual cathode oscillator (VIRCATOR) operating in nanosecond regimes. The system under development consists of a primary voltage source that charges the capacitor bank of a Marx pulser over a long time duration. The Marx pulser output is then conditioned by a PFL to match the requirement of the HPM diode load. This article describes the design and construction of an oil insulated pulse forming line for a REB (Relativistic Electron Beam) diode used in a VIRCATOR for the generation of high power microwaves. Design of a 250 kV/10 kA/60 ns PFL, including the PSPICE simulation for various load conditions are described.

Network congestion management by fuzzy inference using virtual flows

Effective network overload alleviation is very much essential in order to maintain security and integrity from the operational viewpoint of deregulated power systems. This paper aims at developing a methodology to reschedule the active power generation from the sources in order to manage the network congestion under normal/contingency conditions. An effective method has been proposed using fuzzy rule based inference system. Using virtual flows concept, which provides partial contributions/counter flows in the network elements is used as a basis in the proposed method to manage network congestions to the possible extent. The proposed method is illustrated on a sample 6 bus test system and on modified IEEE 39 bus system.

Thermal fatigue on pistons induced by shaped high power laser. Part II: Design of spatial intensity distribution via numerical simulation

In the laser induced thermal fatigue simulation test on pistons, the high power laser was transformed from the incident Gaussian beam into a concentric multi-circular pattern with specific intensity ratio. The spatial intensity distribution of the shaped beam, which determines the temperature field in the piston, must be designed before a diffractive optical element (DOE) can be manufactured. In this paper, a reverse method based on finite element model (FEM) was proposed to design the intensity distribution in order to simulate the thermal loadings on pistons. Temperature fields were obtained by solving a transient three-dimensional heat conduction equation with convective boundary conditions at the surfaces of the piston workpiece. The numerical model then was validated by approaching the computational results to the experimental data. During the process, some important parameters including laser absorptivity, convective heat transfer coefficient, thermal conductivity and Biot number were also validated. Then, optimization procedure was processed to find favorable spatial intensity distribution for the shaped beam, with the aid of the validated FEM. The analysis shows that the reverse method incorporated with numerical simulation can reduce design cycle and design expense efficiently. This method can serve as a kind of virtual experimental vehicle as well, which makes the thermal fatigue simulation test more controllable and predictable. (C) 2007 Elsevier Ltd. All rights reserved.

Utilización de la plataforma virtual eKasi en la docencia de la tecnología farmacéutica

[ES] Una de las aplicaciones más interesantes de las nuevas tecnologías en la docencia, es la utilización de plataformas virtuales accesibles por el alumno a través de Internet. eKASI es una plataforma informática para el apoyo a la docencia presencial desarrollada en la Universidad del Pais Vasco, que permite la gestión de los documentos y la gestión de los estudiantes de un curso, a la vez que facilita el aprendizaje del alumno. Es una herramienta de distribución gratuita y de fácil manejo. Durante el curso 2005/2006, se ha utilizado esta plataforma como apoyo a la docencia de la asignatura Tecnología Farmacéutica I de 4º curso de la Licenciatura en Farmacia de la Universidad del País Vasco. La plataforma está accesible en la dirección de Internet http://ekasi.ehu.es mediante la introducción de una clave facilitada por el administrador del sistema. En la sección correspondiente al aula virtual de la plataforma, el alumno tiene a su disposición la información y documentos relacionados con la asignatura (plan docente, presentaciones utilizadas en las clases, cuestionarios de autoevaluación, enlaces de interés a paginas web, materiales multimedia, etc.). Por otra parte, esta plataforma permite la colaboración y discusión on line de los materiales estudiados, a través del foro y del correo electrónico y posibilita al profesor tutorizar y realizar un seguimiento del progreso de los estudiantes, mediante la realización de tests y de las diferentes tareas propuestas al grupo de alumnos. La plataforma eKASI ha supuesto un instrumento de gran utilidad como apoyo a la docencia presencial tal como se deduce de los resultados de la encuesta realizada a los alumnos al finalizar el curso académico.

Virtual Sensors for On-line Wheel Wear and Part Roughness Measurement in the Grinding Process

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 mu m). In the case of surface finish, the absolute error is well below R-a 1 mu m (average value 0.32 mu m). The present approach can be easily generalized to other grinding operations.

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

Detecting Deceptive Movement in 1 vs. 1 Based on Global Body Displacement of a Rugby Player

A key to success in many sports stems from the ability to anticipate what a player is going to do next. In sporting duels such as a 1 vs. 1 in rugby, the attacker can try and beat the defender by using deceptive movement. Those strategies involve an evolution of the centre of mass (COM) in the medio-lateral plane, from a minimal state to maximal displacement just before the final reorientation. The aim of this work is to consider this displacement as a motion-gap, as outlined in Tau theory, as a potential variable that may specify deceptive movement and as a means of comparing anticipatory performance between mid-level players and novices in rugby. Using a virtual reality set-up, 8 mid-level rugby players (ML) and 8 novices (NOV) observed deceptive (DM) and non-deceptive movements (NDM). The global framework used an occlusion time paradigm with four occlusion times. Participants had to judge the final direction of the attacker after the different cuts-off. For each movement and at each occlusion time, we coupled the ability to predict the good final direction with the value of the COM displacement in the medio-lateral (COM M/L) plane or with the Tau of this parameter (Tau COM). Firstly, results show that the Tau COM is a more predictive optical variable than the simple COM M/L. Secondly, this optical variable Tau COM is used by both groups, and finally, with a specific methodology we showed that mid-level players have significantly better anticipatory ability than the novice group.

The Development of an Immersive Virtual Reality Environment for Manufacturing and Improving Organizational Learning

This paper examines the applicability of an immersive virtual reality (VR) system to the process of organizational learning in a manufacturing context. The work focuses on the extent to which realism has to be represented in a simulated product build scenario in order to give the user an effective learning experience for an assembly task. Current technologies allow the visualization and manipulation of objects in VR systems but physical behaviors such as contact between objects and the effects of gravity are not commonly represented in off the shelf simulation solutions and the computational power required to facilitate these functions remains a challenge. This work demonstrates how physical behaviors can be coded and represented through the development of more effective mechanisms for the computer aided design (CAD) and VR interface.

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array. 

Virtual Thrower Versus Real Goalkeeper: The Influence of Different Visual Conditions on Performance

In order to use virtual reality as a sport analysis tool, we need to be sure that an immersed athlete reacts realistically in a virtual environment. This has been validated for a real handball goalkeeper facing a virtual thrower. However, we currently ignore which visual variables induce a realistic motor behavior of the immersed handball goalkeeper. In this study, we used virtual reality to dissociate the visual information related to the movements of the player from the visual information related to the trajectory of the ball. Thus, the aim is to evaluate the relative influence of these different visual information sources on the goalkeeper's motor behavior. We tested 10 handball goalkeepers who had to predict the final position of the virtual ball in the goal when facing the following: only the throwing action of the attacking player (TA condition), only the resulting ball trajectory (BA condition), and both the throwing action of the attacking player and the resulting ball trajectory (TB condition). Here we show that performance was better in the BA and TB conditions, but contrary to expectations, performance was substantially worse in the TA condition. A significant effect of ball landing zone does, however, suggest that the relative importance between visual information from the player and the ball depends on the targeted zone in the goal. In some cases, body-based cues embedded in the throwing actions may have a minor influence on the ball trajectory and vice versa. Kinematics analysis was then combined with these results to determine why such differences occur depending on the ball landing zone and consequently how it can clarify the role of different sources of visual information on the motor behavior of an athlete immersed in a virtual environment.