Shifei Shen

Numerical investigation of the impact of different configurations and aspect ratios on dense gas dispersion in urban street canyons

The dispersion of chlorine gas in urban street canyons was numerically simulated using the fire dynamics simulator, a code developed by the National Institute of Standards and Technology of USA, which uses large eddy simulation coupled with the Smagorinsky sub-grid scale model. The unsteady flow fields were computed by solving the filtered incompressible Navier-Stokes equations under low Mach number approximation by the finite difference method. The studies analyzed the influence of different street canyon configurations and aspect ratios on the flow and chlorine gas dispersion. The geometric configuration and aspect ratio both affect the vortices and the local concentration distributions in street canyons.

The impacts of adaptive attacking and defending strategies on mitigation of intentional threats

– The purpose of this paper is to focus on resource allocation and information disclosure policy for defending multiple targets against intentional attacks. The intentional attacks, like terrorism events, probably cause great losses and fatalities. Attackers and defenders usually make decisions based on incomplete information. Adaptive attacking and defending strategies are considered, to study how both sides make more effective decisions according to previous fights., – A stochastic game‐theoretic approach is proposed for modeling attacker‐defender conflicts. Attackers and defenders are supposed both to be strategic decision makers and partially aware of adversarys information. Adaptive strategies are compared with different inflexible strategies in a fortification‐patrol problem, where the fortification affects the security vulnerability of targets and the patrol indicates the defensive signal., – The result shows that the intentional risk would be elevated by adaptive attack strategies. An inflexible defending strategy probably fails when facing uncertainties of adversary. It is shown that the optimal response of defenders is to adjust defending strategies by learning from previous games and assessing behaviors of adversaries to minimize the expected loss., – This paper explores how adaptive strategies affect attacker‐defender conflicts. The key issue is defense allocation and information disclosure policy for mitigation of intentional threats. Attackers and defenders can adjust their strategies by learning from previous fights, and the strategic adjustment of both sides may be asynchronous.

Dynamic forecasting conditional probability of bombing attacks based on time-series and intervention analysis

In recent years, various types of terrorist attacks occurred, causing worldwide catastrophes. According to the Global Terrorism Database (GTD), among all attack tactics, bombing attacks happened most frequently, followed by armed assaults. In this article, a model for analyzing and forecasting the conditional probability of bombing attacks (CPBAs) based on time-series methods is developed. In addition, intervention analysis is used to analyze the sudden increase in the time-series process. The results show that the CPBA increased dramatically at the end of 2011. During that time, the CPBA increased by 16.0% in a two-month period to reach the peak value, but still stays 9.0% greater than the predicted level after the temporary effect gradually decays. By contrast, no significant fluctuation can be found in the conditional probability process of armed assault. It can be inferred that some social unrest, such as Americas troop withdrawal from Afghanistan and Iraq, could have led to the increase of the CPBA in Afghanistan, Iraq, and Pakistan. The integrated time-series and intervention model is used to forecast the monthly CPBA in 2014 and through 2064. The average relative error compared with the real data in 2014 is 3.5%. The model is also applied to the total number of attacks recorded by the GTD between 2004 and 2014.

A Preliminary Study of Mobility Patterns in Urban Subway

Understanding human mobility patterns is of great importance to traffic forecasting, urban planning, epidemic spread and many other socioeconomic dynamics covering spatiality and human travel. Based on the records of Beijing subway, we presented a preliminary study of human mobility patterns at urban scale, including return ratio and trip distance. Especially, both linear distance and actual route distance are considered. We found that for a single mode of transportation, the displacement distribution not only decays exponentially, but also has a peak, which represents the characteristics of travel radius (CTR). The CTR of actual route distance is significantly greater than that of linear distance, which indicates that quite of the passengers make detours relative to the linear path when traveling by subway.

Study on RSS/AOA hybrid localization in life detection in huge disaster situation

Rescue is a tough and time-consuming task in huge disaster. After stricken by a catastrophic natural disaster, the rescue force is typically deployed under the circumstance of traffic paralysis and lack of supplies. To cope with this situation, plenty of human resource and professional equipment are required. However, both the human resource and equipment are insufficient in most situations. The rescue force needs an efficient technology for searching the survivals, such as the life detection, which can be a key factor in disaster relief. Fast and accurate locating of the survivals will guide the limited rescue resource to save more survivors. However, current life detection technology cannot meet the demand of rescue in huge disaster. A novel life detection system based on fake base station is proposed. The detection system can scan the whole disaster area and find the cell phones, which leads to the surviving owners. As the system works in different way with other traditional human localization technology, a novel RSS/AOA hybrid positioning algorithm was proposed in this paper to increase the accuracy of localization. To verify the accuracy, two simulation tests were designed. The result of the two tests illustrates that the novel algorithm is more suitable to work with the novel life detection system.

Asymmetric Information in Combating Terrorism: Is the Threat Just a Bluff?*

Abstract This paper explores the mitigation of terrorism risks based on dynamic interactions between terrorist organizations and governments with asymmetric information. Uncertainties in the objectives and capabilities of terrorists complicate defensive resource allocations for the public safety. Simultaneous and sequential game models are developed to investigate the asymmetric information effects on defensive strategies and terrorism risk analysis. The government can detect explicit or implicit signals to support decisions and update its beliefs according to a Bayesian law after it receives a terrorist threat. Analyses of the equilibrium for the signaling game indicate that the optimal government defensive strategy will significantly impact the actions of the terrorists. Asymmetric information is shown to play a crucial role in security decision making and terrorism risk mitigation, with the optimal defensive strategy changing according to terrorists and government capabilities.