No abstract

The fire safety can be one of the biggest problems in metropolitan area. To reduce injuries in a fire, the virtual reality based behavioural skills training (BST) has been used to train people to survive in emergency circumstance. VR-based BST training has been demonstrated to effectively help people of different ages to acquire safe escape skills in a virtual environment. However, most of people have encountered difficulty to train in a right gesture or poor body performance, such as running at unsuitable body position. Gesture-based technology can effectively help people to learn the correct gestures in order to enhance training efficiency. Thus, this paper proposes a theoretical framework of “VR-Gesture BST”, which is expected to improve behavioural skills training more effectively for fire safety training. It adopts motion capture device obtaining user’s body data to evaluate the body performance during the BST training. The outcomes of the study provide guideline and suggestions for VR based design in practice of the behavioural skills training adopted gesture-based technology.

Previous studies have shown that task-irrelevant auditory information can provide temporal clues for the detection of visual targets and improve visual perception; such sounds are called informative sounds. The neural mechanism of the integration of informative sound and visual stimulus has been investigated extensively, using behavioral measurement or neuroimaging methods such as functional magnetic resonance imaging (fMRI) and event-related potential (ERP), but the dynamic processes of audiovisual integration cannot be characterized formally in terms of directed neuronal coupling. The present study adopts dynamic causal modeling (DCM) of fMRI data to identify changes in effective connectivity in the hierarchical brain networks that underwrite audiovisual integration and memory. This allows us to characterize context-sensitive changes in neuronal coupling and show how visual processing is contextualized by the processing of informative and uninformative sounds. Our results show that audiovisual integration with informative and uninformative sounds conforms to different optimal models in the two conditions, indicating distinct neural mechanisms of audiovisual integration. The findings also reveal that a sound is uninformative owing to low-level automatic audiovisual integration and informative owing to integration in high-level cognitive processes.

Non-contact laser scanning is widely used in aircraft parts inspection and components assembly, especially for the dimensional error of complex structural parts. Careful scan path planning can greatly improve the measurement accuracy and efficiency of scanning. This paper presents a methodology to solve the design and optimization problems of scanning posture. The scanning quality is improved by reducing measurement uncertainty to obtain the optimum posture angle and spatial position for scanning. A posture coordinate system is established to obtain the posture angle deviation between the current scanning posture and the principal direction of all points in the corresponding measuring area, which quantifies the measurement uncertainty of the scanning area. The posture adjustment interval is defined according to the limit scanning envelope to search for the feasible direction and position of the scanner, and the measurement uncertainty of the scanning area is reduced by optimizing the posture angles iteratively. We demonstrate the effectiveness of the proposed method by comparing it with other posture planning algorithms.