Occupational therapists' interests and attitudes toward animal assisted therapy as a treatment modality

One hundred seventy-nine occupational therapists (OTs) responded to a survey regarding their interests and attitudes toward animal assisted therapy as a treatment modality. It was found that most of the practitioners would be interested in learning more about animal assisted therapy and most felt it is a valid treatment modality to be used by occupational therapists. Furthermore, the most common answer to the question "why would you not be interested in participating in an AAT program," was "I feel I don't know enough about it". It was also found that therapists' most commonly selected patient goals for AAT were in the realm of mental health, whereas the least mentioned goals were more physically based goals. Further, a recommendation was made to educate OTs regarding the uses and benefits of AAT through more research, continuing education programs on AAT, publications in professional journals, and media awareness.

Classroom Simulation is Computer Based

The authors review and evaluate the use of a business simulation, specifically he Hotel Operational Training Simulation (HOTS), in the fourth year of a hospitality undergraduate program. Four dimensions were explored: learning experience, alternative method of instruction, critical and analytical thinking ability and delivery time frame, in addition to the student overall satisfaction with the learning experience.

A simulation-based decision support system for evaluating operating policies in an emergency room facility

Increased pressure to control costs and increased competition has prompted health care managers to look for tools to effectively operate their institutions. This research sought a framework for the development of a Simulation-Based Decision Support System (SB-DSS) to evaluate operating policies. A prototype of this SB-DSS was developed. It incorporates a simulation model that uses real or simulated data. ER decisions have been categorized and, for each one, an implementation plan has been devised. Several issues of integrating heterogeneous tools have been addressed. The prototype revealed that simulation can truly be used in this environment in a timely fashion because the simulation model has been complemented with a series of decision-making routines. These routines use a hierarchical approach to organize the various scenarios under which the model may run and to partially reconfigure the ARENA model at run time. Hence, the SB-DSS tailors its responses to each node in the hierarchy.

Evaluating the effectiveness of signal timing optimization based on microscopic simulation evaluation

The optimization of the timing parameters of traffic signals provides for efficient operation of traffic along a signalized transportation system. Optimization tools with macroscopic simulation models have been used to determine optimal timing plans. These plans have been, in some cases, evaluated and fine tuned using microscopic simulation tools. A number of studies show inconsistencies between optimization tool results based on macroscopic simulation and the results obtained from microscopic simulation. No attempts have been made to determine the reason behind these inconsistencies. This research investigates whether adjusting the parameters of macroscopic simulation models to correspond to the calibrated microscopic simulation model parameters can reduce said inconsistencies. The adjusted parameters include platoon dispersion model parameters, saturation flow rates, and cruise speeds. The results from this work show that adjusting cruise speeds and saturation flow rates can have significant impacts on improving the optimization/macroscopic simulation results as assessed by microscopic simulation models.

A simulation-based heuristic for fleet assignment

Integer programming, simulation, and rules of thumb have been integrated to develop a simulation-based heuristic for short-term assignment of fleet in the car rental industry. It generates a plan for car movements, and a set of booking limits to produce high revenue for a given planning horizon. Three different scenarios were used to validate the heuristic. The heuristic's mean revenue was significant higher than the historical ones, in all three scenarios. Time to run the heuristic for each experiment was within the time limits of three hours set for the decision making process even though it is not fully automated. These findings demonstrated that the heuristic provides better plans (plans that yield higher profit) for the dynamic allocation of fleet than the historical decision processes. Another contribution of this effort is the integration of IP and rules of thumb to search for better performance under stochastic conditions.