A model of extended, semisystematic visual search.

OBJECTIVE: A model of semisystematic search was sought that could account for both memory retrieval and other performance-shaping factors. BACKGROUND: Visual search is an important aspect of many examination and monitoring tasks. As a result, visual search performance has been the topic of many empirical investigations. These investigations have reported that individual search performance depends on participant factors such as search behavior, which has motivated the development of models of visual search that incorporate this behavior. Search behavior ranges from random to strictly systematic; variation in behavior is commonly assumed to be caused by differences in memory retrieval and search strategy. METHODS: This model ultimately took the form of a discrete-time nonstationary Markov process. RESULTS: It yields both performance and process measures that include accuracy, time to perception, task time, and coverage while avoiding the statistical difficulties inherent to simulations. In particular, it was seen that as the search behavior becomes more systematic, expected coverage and accuracy increase while expected task time decreases. CONCLUSION: In addition to explaining these outcomes and their interrelationships from a theoretical standpoint, the model can predict these outcomes in practice to a certain extent as it can create an envelope defined by best- and worst-case search performance. APPLICATION: The model also has the capability of supporting assessment. That is, it can be used to assess the effectiveness of an individual's search performance, and to provide possible explanations for this performance, through the use of one or more of the output measures.

Using virtual reality technology for aircraft visual inspection training: presence and comparison studies.

The aircraft maintenance industry is a complex system consisting of several interrelated human and machine components. Recognizing this, the Federal Aviation Administration (FAA) has pursued human factors related research. In the maintenance arena the research has focused on the aircraft inspection process and the aircraft inspector. Training has been identified as the primary intervention strategy to improve the quality and reliability of aircraft inspection. If training is to be successful, it is critical that we provide aircraft inspectors with appropriate training tools and environment. In response to this need, the paper outlines the development of a virtual reality (VR) system for aircraft inspection training. VR has generated much excitement but little formal proof that it is useful. However, since VR interfaces are difficult and expensive to build, the computer graphics community needs to be able to predict which applications will benefit from VR. To address this important issue, this research measured the degree of immersion and presence felt by subjects in a virtual environment simulator. Specifically, it conducted two controlled studies using the VR system developed for visual inspection task of an aft-cargo bay at the VR Lab of Clemson University. Beyond assembling the visual inspection virtual environment, a significant goal of this project was to explore subjective presence as it affects task performance. The results of this study indicated that the system scored high on the issues related to the degree of presence felt by the subjects. As a next logical step, this study, then, compared VR to an existing PC-based aircraft inspection simulator. The results showed that the VR system was better and preferred over the PC-based training tool.