Simulated setup: Non-cooperative games:50 iterations of same player-resource pair. A total of around 9,000 tests was performed.

Multiresource dynamic allocation model for emergency rescues is a multigoal optimization model with two goals, maximizing rescue effectiveness and minimizing allocating cost.Maximum of rescue effectiveness. The purpose of rescue resource allocation is to deal with emergencies, so the maximum of rescue effectiveness is the first goal and the maximum of the importance of all the resources could reflect this goal. On the other hand, according to the dynamic change of the threat of the disasters, the rescue period could be divided into several time intervals, and the model seeks the maximum of rescue resource effectiveness during the whole projection period. The so-called “maximum of rescue resource effectiveness” here concerns not only the effectiveness of the resource allocation, but also the maximum of the whole rescue project with the consideration of the whole rescue demands.

Through simulation + surveys

In order to verify the validity of the model and algorithm, this paper established the simulation network as shown in figure 3, the network node number is 28, road number is 45, we specifie node 1 as a starting point and node 28 as the end.

spatially correlated elevation data released by the U.S. Geological Survey. We select a 100 × 100 spatial subset of the original data as our data sets. This subset size can be easily scaled to cover the square where all nodes are.

The team distributed 1,187 questionnaires to a cohort of soldiers.The respondents were encouraged to answer as many questions as they liked.

In progress

Modeling

Three sets of data from documentary reviews, open ended questionnaires and semistructured interviews were drawn from the cases. Samples of organisational literature and documentation were analysed to understand the organisational views of their own learning and knowledge development practises. Written definitions of professional development, learning, knowledge and the differentforms of processes and their implementation were also examined.

Sixteen participants were recruited to participate (eight novices and eight experts).careful instruction and observation of the operating room,10 under the supervision of the senior author.These included background images, an iPad to display a heart tracing and monitoring “beeps,” a real fluid stand and equipment trolley (Figure 2), and provision of a realistic clinical scenario via a set of real case notesParticipants evaluated the realism of TBS using Likert- style questionnaires, specifically developed for this simulation