Reza Nourjou

Building Seismic Loss Model for Tehran

In order to model the building seismic loss for Tehran, urban databases have been compiled and processed considering different census zones, city blocks, and parcel records. Aerial photos, together with stereo image processing and ground survey data, have provided parcel level geospatial information. These data sets include urban features, land uses, and building inventory with height information. This research also focuses on the selection and the development of structural vulnerability functions and risk algorithms. The damage curves are selected or modified according to some regional data, the ATC-13 report, and the functions obtained for Costa Rica. Also, analytical fragility curves are derived and adopted for the area of study after the HAZUS-FEMA methodology. Finally, an upgradeable seismic risk model is developed in GIS using all compiled input data and structural vulnerability functions.

Using GIS to Develop an Efficient Spatio-temporal Task Allocation Algorithm to Human Groups in an Entirely Dynamic Environment Case Study: Earthquake Rescue Teams

Using GIS, the present paper aims at modeling task allocation to human groups in a dynamic and spatio-temporal form. To do this, a novel method inspired by Market Based Procedure is proposed. Governing factors such as space, time, tiredness of the persons, importance, priority and the difficulty of the work and environmental dynamism, the functions referred to cost, reward and profit are considered in developing the model. By holding auctions and profits proposed by each of the bidders, the tasks are dedicated to those who yield the most profit to the group. On this basis, in a group consisting of several different tasks, it can be determined who, when and where should do what activity in order to increase the efficiency and effectiveness of the group. The proposed model was evaluated in ArcGIS software by simulation of the tasks of two groups of life-detectors and rubble-removers of earthquake rescue teams. In this way, in addition to confirming the efficiency of the suggested model, a new and spatio-temporal method is presented for the management of earthquake rescue teams in a fully dynamic environment.

Introduction to spatially distributed intelligent assistant agents for coordination of human-agent teams' actions

Earthquake emergency response requires different number of teams to cooperate with each other and coordinate their activities to achieve global objectives. Coordination is the key challenging problem that field teams face in urban search and rescue (USAR) emergency response because of the geographic and uncertain environment. Therefore, it is necessary to optimize coordination of teams by allocating tasks to teams in time and space efficiently and sufficiently. The present paper aims to propose an efficient approach that allows humans to collaborate with coordinator assistant agents to assign tasks to teams. To achieve this purpose, we did the following stages: (1) the structure of the USAR task force and environment characteristics were analyzed, (2) we analyzed the spatial coordination problem and then modeled it, (3) features and properties of required approach were assessed, (4) we designed a contract net based model for distributed spatial task allocation and proposed the architecture of spatially distributed intelligent assistant agents (SpDI2A), and (5) finally, our approach was implemented and validated in a geospatial simulation which was developed using AnyLogic software and Java programming. The final result composes of 10 features satisfying the features of the required system.

Simulation of an Organization of Spatial Intelligent Agents in the Visual C#.NET Framework

 Abstract—Problem: This paper investigates the simulation of a community of spatial intelligent agents, an important issue for the implementation and evaluation of distributed algorithms. The research question is how to simulate this organization using Visual C#.NET. Objective: This paper intends to use the C# programming language to develop a simulator. In a simulated environment, a social agent needs to communicate with other agents and respond to received messages. Method: Our approach is to integrate the thread and delegate methods provided by the .NET framework. We enhance the architecture of a spatial intelligent agent in order to embed several in a simulated society. A basic C# program is presented to demonstrate how to implement a contract net protocol (CNP) among three simple agents. Results: Two results were achieved: 1) the responses and actions of three agents during a simulated CNP and 2) a simulated environment that contains distributed spatial intelligent agents that can interact with each other and a human user. Conclusion: The proposed methodology and presented code provide a flexible and efficient framework for C# developers to develop, simulate, and evaluate a society of advanced software agents using the .NET platform.

Search algorithm for optimal execution of incident commander guidance in macro action planning

This paper presents a state space search algorithm that solves the optimal execution problem of incident commanders guidance during disaster emergency management. To achieve a joint goal, the IC should select the best choice, as an optimal strategic decision, from available alternatives in a definite time. A strategic decision coordinates/controls macro actions of a team of field units by constraining a subteam to a subgoal in sublocation in a time window; moreover a sequence of strategic decisions generates a macro action plan that defines howto reach the goal. Three results are achieved by running this algorithm for a scenario: 1 calculate an optimal macro action plan; 2 estimate a minimum total time to achieve a joint goal and 3 reason about the best choice. We applied our approach to develop an intelligent software system autonomous agent for assisting the human in crisis response to earthquake disaster.