Phase 4 training was divided in 4 modules each with its goals and rational, didactic training, and skills training.Materials from both survey formats (written and online) were identical.

 The exercise consisted of four linked scenarios played over a period of 2 weeks.Each scenario was followed by short periods of evaluation and debriefingR&E was applied to capture the course of events and reconstruct it in F-REX for further analysis and evaluation.

Two months after the earthquake, Miyagi prefecture conducted a self-administered health survey of prefectural public servants

qualitative simulation technology-QSIM algorithm

A simulation tool is developed that is able to support the negotiation of both people and automated agents. Pg 8.A realistic scenario about a conflict between Canada and spain ( a fishing dispute) was used to evaluate the tool. pg 11

Literature searches were conducted to identify evidence to answer the key questions in these areas. Given a lack of data on which to develop evidence based recommendations, expert-opinion suggestions were developed, and consensus was achieved using a modified Delphi process.

Engagement of participants through participatory design:1-hour interviews focused on area managers, who play a key role in decision-making during routine and emergency operations (over a 4-month period)Guide for semi-structured interviews was:Based on prior field work at the study settingAnalysis of continuity of operations planning (COOP)Documents from the local health jurisdictionSystematic review of literature covering public health, information technology, and COOP.

The study used a quantitative experimental method with a withingroup design, in which participants' self-efficacy was measured using questionnaires before and after partaking in three simulated surge capacity scenarios. An a priori power analysis indicated a minimum participant sample of 12 to detect a large effect

Planning of the simulation:During the simulation, the dynamic attribute values are updated at each process stage as described belowThe Perception Module updates four attributes such as:• Emergency cues, such as smoke and alarm, that are visible or audible to the agent.• Visible floor objects, such as doors and signs, that are visible to the agent.• Visible group members that are visible to the agent.• Neighboring agents that are visible to and are located within a certain radius from the agentThe Interpretation Module maps the current knowledge of the agent into a set of internal thresholds that describe the urge and well-being of the agent.The decision-making module invokes the decision tree modeling the behavior assigned to the agent. Given the agent’s characteristics and the invoked decision tree, it looks up the agent’s behavior and determines the long- term navigation goal, such as the familiar exit of the agent or the location of the group leader, and the intermediate navigation point given the agent’s knowledge and location.The Locomotion Module calculates the agent’s movement toward the navigation target and returns the updated spatial position of the agents, which areCartesian coordinates (x, y, and z) in the continuous space.The Memory Module registers the decision made during the simulation cycle and updates the spatial knowledge. The spatial knowledge is an array storing the navigation points that the agents have visited. The agents remembered the traveled navigation points and can later refer to the spatial knowledge to avoid backtracking.

Simulation development safegress