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.

A heuristic model for the simulation of the deformation of elastic and spongy material for virtual reality applications

This paper presents a practical algorithm for the simulation of interactive deformation in a 3D polygonal mesh model. The algorithm combines the conventional simulation of deformation using a spring-mass-damping model, solved by explicit numerical integration, with a set of heuristics to describe certain features of the transient behaviour, to increase the speed and stability of solution. In particular, this algorithm was designed to be used in the simulation of synthetic environments where it is necessary to model realistically, in real time, the effect on non-rigid surfaces being touched, pushed, pulled or squashed. Such objects can be solid or hollow, and have plastic, elastic or fabric-like properties. The algorithm is presented in an integrated form including collision detection and adaptive refinement so that it may be used in a self-contained way as part of a simulation loop to include human interface devices that capture data and render a realistic stereoscopic image in real time. The algorithm is designed to be used with polygonal mesh models representing complex topology, such as the human anatomy in a virtual-surgery training simulator. The paper evaluates the model behaviour qualitatively and then concludes with some examples of the use of the algorithm.

Judging the ‘passability’ of dynamic gaps in a virtual rugby environment

Affordances have recently been proposed as a guiding principle in perception–action research in sport (Fajen, Riley, & Turvey, 2009). In the present study, perception of the ’passability’ affordance of a gap between two approaching defenders in rugby is explored. A simplified rugby gap closure scenario was created using immersive, interactive virtual reality technology where 14 novice participants (attacker) judged the passability of the gap between two virtual defenders via a perceptual judgment (button press) task. The scenario was modeled according to tau theory (Lee, 1976) and a psychophysical function was fitted to the response data. Results revealed that a tau-based informational quantity could account for 82% of the variance in the data. Findings suggest that the passability affordance in this case, is defined by this variable and participants were able to use it in order to inform prospective judgments as to passability. These findings contribute to our understanding of affordances and how they may be defined in this particular sporting scenario; however, some limitations regarding methodology, such as decoupling perception and action are also acknowledged.

Science for sale in a free market economy: But at what price? ABA and the treatment of autism in Europe.

Educating the public accurately about Applied Behavior Analysis (ABA) is an important undertaking, not least because misconceptions and myths about ABA abound. In this paper we argue that, unfortunately, the efforts of many dedicated professionals and parents to disseminate accurate information about the benefits of ABA for children diagnosed with autism spectrum disorder (ASD) are damaged by a few behavior analysts whose focus seems to be more on monetary gains than social responsibility. We cite examples of the resulting harm to the public image of behavior analysis from a number of European countries. We conclude by calling upon fellow scientists to unite in their opposition to unscrupulous abuses of free market forces for short-term monetary gains that damage the dissemination of the science of behavior analysis and thereby ultimately disadvantage those who should benefit primarily from our science, i.e., some of the most vulnerable citizens of society.

Social Inclusion or Market Competitiveness? A Comparison of Rural Development Policies in the European Union and the United States

The language of EU rural development policy appears more interested in social inclusion and that of US policy more interested in market competitiveness. We seek to determine why policies directed at rural development in the EU and the USA differ. In both contexts new rural development policies emphasize partnership and participation but we find local participation is used to promote social inclusion in the EU and market competitiveness in the USA. An examination of these dimensions illustrates important transcontinental differences and similarities in rural development policies. We explore the socio-historical reasons for differences in the commitment to social inclusion, while also noting similarities in the priority of market competitiveness.