|Defining Team Performance for Simulation-based Training: Methodology, Metrics, and Opportunities for Emergency Medicine||
1) proposes a scientifically based methodology for SBT design and evaluation, 2) reviews existing team performance metrics in health care along with recommendations, and 3) focuses on leadership as a target for SBT because it has a high likelihood to improve many team processes and ultimately performance
|A decision support system for debris-flow hazard mitigation in towns based on numerical simulation: a case study at Dongchuan, Yunnan Province.||
This method involves complicated arithmetic, and needs to obtain all kinds ofphysical parameters of debris flow, such as bulk density, coefficient of viscosity, yield stress etc
|Multi-objective evacuation routing optimization for toxic cloud releases.||
We carry out our computational tests on an emergency evacuation network G=(V,E) with 20 nodes.Suppose an accident of ammonia spill happens in a chemical plant at node 2, the safety area is at node 20, and the starting point of the evacuees is at node 1.
|Do or die--Strategic decision-making following a shock event.||
Nine semi-structured interviews were held with the chief executive officer, the chairman of the board of directors and all key senior managers of one regional Australian airport.
|Geotagging Twitter Messages in Crisis Management.||
Software developmentFirst, we evaluated the system by comparing its output against human judgement as ground truth for a selection of 500 tweetsSecondly, we tested our geotagger performance with the testing dataset against other geocoding platforms including: The Alchemy API NER and the Yahoo! GeoPlanet service.The IBM research (Australia) plans the OzCrsisTracker 2.0 deployment in the Australian Bushfire and Flood season 2014.
|Simulating effects of signage, groups, and crowds on emergent evacuation patterns.||
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.
|Situation awareness and virtual globes: Applications for disaster management||
Software Development:Implicit information processing functions of the CDA are based on the use of geocoding algorithms, automated reasoning procedures, and disaster ontologies to extract geographic and thematic references from web documents referenced from real simple syndication (RSS) feeds. RSS feeds are used as a primary information source as they are an increasingly used format for web content publication and are easy to access computationally due to their XML structur.Upon retrieving an RSS feed, results found by the CDA’s geographic text extraction and geocoding process are rendered in KML and presented in Google Earth using a network link object connected to the CDA information processing server.If an origin point is established, connection line thickness indicates the frequency of place references in a document. The geographic scales of entities found (country, city, county, town etc.) are represented using point symbol shapes. Line and point transparencies indicate how old a document is relative to when the KML was created by the CDA.These visual encoding strategies are used to help disaster managers to remove potentially irrelevant or unneeded information by providing a quick information overview through visual cues.
|Project training evaluation: Reshaping boundary objects and assumptions||
Four organisations were selected as two matched pairs: one pair from the manufacturing sector and one from the services sector. All the cases are companies which are publicly listed and are of a similar capitalisation, workforce size and using projects as a means of achieving their contracts and in-house initiatives. Companies 1 and 4 are manufacturing organisations using projects for non-process activities and inhouse improvement initiatives. Companies 2 and 3 are projectbased service organisations. Company 2 and Company 4 are nationally acclaimed learning organisations (LO). Learning is strongly encouraged and employee learning is fed back into the organisation as increased innovative capabilities.
|Decision support system for emergency management: Road tunnels||
The stochastic analysis performs multiple simulations and provides reliable results for evacuation times in less than 5s
|Modeling and simulation method of the emergency response systems based on OODA||
the coupled OODA framework is built to analyze the interaction between the emergency response units. In order to demonstrate the emergency response mechanism in theoretic way, the simulation theory of DEVS (Discrete Event System Specification) is adopted to build up the simulator model of the basic OODA process framework.With this scenario: “In the year 20XX, in the city Y in province X of southwest China, suddenly suffering to a Richter 8.0 degree earthquake disaster. This earthquake disaster has caused severe damage to the local city, with a large number of houses collapsed, casualties serious, road and transformation, electricity and other basic infrastructure paralyzed. State and government at all levels immediately launched the emergency response plans, organize and command the emergency response departments and their team units to carry out emergency rescue operations. Considering the disaster zone in the dangerous mountain area with less information, it is very difficult to make emergency response to rescue refugees in the disaster area.” (p. 535)Simulation, in STAGE (‘a scenario developing system’): (1) Edit the scenario database of the emergency environment(2) Edit the mission scripts(3) Edition of the emergency response plans(4) (4) Run the simulation (pp. 538-9)