We presented a robust, modular algorithm for context-based urban terrain modeling from sensor data. Except for the choice of parameter values and integration of additional sources of information, the algorithm is automatic and requires only a 2.5D elevation map as input.The elevation map may stem from an airborne laser scan or may be computed by a dense matching algorithm

We propose measures to assess this aggregated scale’s internal consistency, reliability, and validity, and we discuss how to use the scale effectively.

Advantages of simulation (based on review) for training: -  Allows trainees to gain experience when mitigating the risk of harm to patients-  Allows for an interchangeable curriculum depending on trainees’ level- Affords the trainees’ multiple opportunities to practice and learn in a less stressful environment-  Acquire skills, which can be translated to improve in both technical/ procedural and diagnostic/interpretive skills.

The capabilities of formal leaders all contributed to the overall management of a crisis. Informal leaders are a very cohesive group of motivated people who can make a substantial contribution and improve overall team performance in a crisis.

Business students, to a greater extent, chose more passive strategies and also strategies that are less risky compared to students of public relations. On the other hand, students of public relations in general mostly opted for strategies that carry proactive features and additional risk, not waiting for certain negative information to become publicly available

With the CDIRS method proposed in this paper, the heterogeneity and disorder can be avoided, and the targets and constraints of the offsite nuclear emergency response problems in the original space can be transformed into the target space, being processed unified by formal modeling and ordered reasoning.(1) The ‘‘feature mapping and space modeling – interoperable mediating and interoperability verifying – ordered integrating and reasoning” based CDIRS framework is proposed for offsite nuclear emergency response. (2) Under the CDIRS framework, the concrete space mapping and modeling principles are presented, and then the integrated decision-making problems can be mapped from the original space into the CDIRS spaces; (3) To solve the possible interoperability problems of the cross-domain integration processes, relevant interoperable mediator models and interoperability verifying methods of the CDIRS spaces are proposed; (4) The CDIRS spaces ordering principles and relevant basic reasoning rules are defined for obtaining the integrated cross-domain nuclear emergency response solutions; (5) the formally expression and achievement method based on the protégé tools is presented.

It appears that in situations of perceived leader culpability during a crisis, followers tightly couple their leaders with the organization as a whole. In contrast, their judgments that external stakeholders were culpable were associated with increased trust toward their leaders, increased organizational identification, and they had no relationship with their levels of emotional exhaustion.

 Compared with the existing methods, D-DEMATEL has ability to obtain the total relations of influential factors and identify the CSFs in emergency management.The optimization of these CSFs can promote the overall welfare of emergency management.

Using fire incidents as an example, we have developed a systematic data model to capture and standardize response-critical information for fire incident management. The paper provides a detailed data model along with a data dictionary and an object-oriented structureThis project represents one of the first attempts in the response community to propose solutions that would contribute to the creation of a widely accepted set of emergency data standards. The fire incident data model improves collaboration and information sharing among response organizations and agencies.

In this paper, we have modelled the RCR domain in terms of a CFST constraints. We then provided a DCOP formulation of the problem and showed how to solve it using the Max- Sum algorithm. On the basis of this, we then developed the novel F-Max-Sum algorithm that improves upon Max-Sum to deal with disruptions in its underlying factor graph more effectively. In so doing, we have provided the first full solution to the problem of decentralized coalition formation that pervades disaster management. Our solution is also one that is able to efficiently adapt to a dynamic environment.