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Since the first description of childhood autism by Kanner in 1943, this syndrome has progressively been differentiated along a continuum of autistic spectrum disorders (ASD), on the basis of various levels of sensorimotor, verbal, cognitive and social disabilities. Several neuropsychological hypotheses have already been proposed to clarify the underlying(More)
The effectiveness of a multiple components therapy regarding claustrophobia and involving virtual reality (VR) will be demonstrated through a trial which immersed six claustrophobic patients in multiple context-graded enclosed virtual environments (VE) using affordable VR apparatus and software. The results of the questionnaires and behavior tests exhibited(More)
We propose a graphics processor unit (GPU)-accelerated method for real-time computing and rendering cellular automata (CA) that is applied to hexagonal grids. Based on our previous work [9] –which introduced first and second dimensional cases– this paper presents a model for hexagonal grid algorithms. Proposed method is novel and it encodes and transmits(More)
We propose a method for generating all possible rules of multi-dimension Boolean cellular automata (CA). Based on an original encoding method and the programming of graphical processor units (GPU), this method allows us to visualize the CA information flow in real-time so that emerging behaviors can be easily identified. Algorithms of first and von Neumann(More)
The present study aimed at testing the general assumption that virtual reality can enhance the experience of exercising. More specifically, we tested the effects of sensory input (music and video feedback) during physical training on performance, enjoyment , and attentional focus by means of a computerized ergometer coupled with VR software. Twelve(More)
—Despite growing interest over the decades, the question of estimating cognitive workload of operators involved in complex multitask operations, such as helicopter pilots, remains a key issue. One of the main difficulties facing workload inference models is that no single specific indicator of workload exists, so that multiple sources of information have to(More)
—This paper uses Bayesian networks to investigate the impact of three different kind of inputs, namely, physiological, cognitive and affect features, on workload estimation, from a computational point of view. The ability of the proposed models to infer the workload variation of subjects involved in successive tasks demanding different levels of cognitive(More)
— This paper presents an approach based on Bayesian Networks to estimate the workload of operators. The models take as inputs the entropy of different number of physiological features, as well as a cognitive feature (reaction time to a secondary task). They output the workload variation of subjects involved in successive tasks demanding different levels of(More)