Development of a new model of feeding strategy analysis of fish incorporating resource availability and use data

A feeding strategy model is proposed using stomach content and resource availability data as a modification to Costello (1990) and Amundsen et al. (1996). Incorporation of feeding electivity index (E) instead of the prey-specific abundance signifies the importance of resource availability in prey selection as well as the predator's ability to specialize, generalize or avoid particular prey items at the individual and population level.

Competitive training in hidden Markov models

The use of hidden Markov models is placed in a connectionist framework, and an alternative approach to improving their ability to discriminate between classes is described. Using a network style of training, a measure of discrimination based on the a posteriori probability of state occupation is proposed, and the theory for its optimization using error back-propagation and gradient ascent is presented. The method is shown to be numerically well behaved, and results are presented which demonstrate that when using a simple threshold test on the probability of state occupation, the proposed optimization scheme leads to improved recognition performance.

Manufacturing vision and competitiveness

Discusses a refinement to the process by which manufacturing strategy is created. Builds on an existing strategy process (Platts, 1990) and adapts it to fit more closely within the dynamic manufacturing vision. The method for creating a manufacturing vision allows a business to do this in a two- to three-week period as part of a 10-12 week manufacturing strategy project. A conceptual model of manufacturing vision has been developed that enables practitioners to explore the factors that influenced the potential competitive contribution of manufacturing and to agree an explicit direction for change. Describes the successful application of the process in six manufacturing organizations and highlights the practical limitations of the approach.

Step synchronization and third person speed perception in virtual environment locomotion simulators

Human locomotion is known to be influenced by observation of another person's gait. For example, athletes often synchronize their step in long distance races. However, how interaction with a virtual runner affects the gait of a real runner has not been studied. We investigated this by creating an illusion of running behind a virtual model (VM) using a treadmill and large screen virtual environment showing a video of a VM. We looked at step synchronization between the real and virtual runner and at the role of the step frequency (SF) in the real runner's perception of VM speed. We found that subjects match VM SF when asked to match VM speed with their own (Figure 1). This indicates step synchronization may be a strategy of speed matching or speed perception. Subjects chose higher speeds when VMSF was higher (though VM was 12km/h in all videos). This effect was more pronounced when the speed estimate was rated verbally while standing still. (Figure 2). This may due to correlated physical activity affecting the perception of VM speed [Jacobs et al. 2005]; or step synchronization altering the subjects' perception of self speed [Durgin et al. 2007]. Our findings indicate that third person activity in a collaborative virtual locomotive environment can have a pronounced effect on an observer's gait activity and their perceptual judgments of the activity of others: the SF of others (virtual or real) can potentially influence one's perception of self speed and lead to changes in speed and SF. A better understanding of the underlying mechanisms would support the design of more compelling virtual trainers and may be instructive for competitive athletics in the real world. © 2009 ACM.