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Olsen and Moon [23] have proposed that the interest function might be related to user interactions.
We validated the interest function model and our results provide evidence that our approach improves the simulation fidelity regarding occupancy forecasting.
Consequently, the reliability of the occupancy predictions of pedestrian simulations can be enhanced by integrating the interest function model into choices models.
Most notably, Peng et al. [24] have developed a system that connects the interest function to actual user attention, as measured through eye tracking and face recognition.
The interest function model is based on the psychological concept of goal-related memory accessibility and on fundamental coherences found in pedestrian-related data that is measurable at locations.
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Therefore, the period of the interests' functions is one year, a fact that can be reflected in realistic situations as the ones explained in "Background".
This fact has an impact on the design of possible forms for the interests' functions (R_i^m(t),~forall m,i), which should be continuous in time.
Contractions in beating areas were measured as change in cell edge position using confocal microscopy, and analyzed with the region of interest function in the software [9].
Computer-obtained tumor volume was obtained with the Living Image software through the use of the free-style region of interest function.
The appropriate interest functions for this case are formulated, (forall i), as follows: begin{aligned} R_i^1 t)=Bfrac{At}{At+C},~ R_i^2 t)=Bfrac{C}{At+C}, end{aligned} (7 where A, B, C are constants.
The app's points of interest function as analogies to scenic vistas on a nature trail.
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