Modeling and Risk Analysis of Chemical Terrorist Attacks: A Bayesian Network Method

Zhu, Rongchen; Hu, Xiaofeng; Li, Xin; Ye, Han; Jia, Nan

doi:10.3390/ijerph17062051

Cited by 16 publications

(9 citation statements)

References 52 publications

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“…The dataset of cross-tabulation within the prevalence of dental caries was used for network plot and correspondence analysis [ 40 , 41 ]. The network plot was performed using SPSS Modeler Ver.18.0 (IBM, Tokyo, Japan), and correspondence analysis was performed using SPSS Statistics Ver 24.0 (IBM, Tokyo, Japan).…”

Section: Methodsmentioning

confidence: 99%

Tooth-Level Analysis of Dental Caries in Primary Dentition in Myanmar Children

Nomura

Otsuka

Wint

et al. 2020

IJERPH

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In developing countries, the prevalence of dental caries in children remains high, which means that implementing a simple and convenient classification is critical. The classification needs to be evidence-based and needs to reflect tooth-level information. In this study, the prevalence of dental caries in the primary dentition of 352 Myanmar school children at the ages of 5, 6, and 7 was analyzed at the tooth level to clarify the underlying data structure of the patterns of dental caries in the population. Ninety-three percent of subjects had caries in primary dentition and the mean number of decayed teeth in primary dentition was 7.54 ± 4.82. Based on the item response theory analysis, mixed-effect modeling, and Bayesian network analysis, we proposed the following classification: Group 1: No dental caries; Group 2: Dental caries in molar teeth or dental caries in maxillary anterior teeth; Group 3: Dental caries in both molar and maxillary anterior teeth; Group 4: Dental carries in mandibular anterior teeth. Dental caries (dmft) in the groups was different between groups. The results of characteristics of tooth-level information and classification presented in this study may be a useful instrument for the analysis of the data of dental caries prevalence in primary dentition.

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Section: Methodsmentioning

confidence: 99%

Tooth-Level Analysis of Dental Caries in Primary Dentition in Myanmar Children

Nomura

Otsuka

Wint

et al. 2020

IJERPH

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“…Faced with different risk factors input by users, it is necessary to make a proper classification and determine the scope before accurate risk analysis. Other risk factors related to terrorist attacks are obtained from books and terrorist attack risk analysis articles [3], [40]- [43], [45]. For example, Khakzad et al [46] listed some information which needs to be considered from the perspective of terrorist organization: (1) the general history of threats and attacks against similar targets, (2) location-specific attack records, (3) attacker's capabilities and potential behaviours, (4) the attractiveness of chemical facilities in the eyes of attackers.…”

Section: A Risk Factors Identificationmentioning

confidence: 99%

“…Firstly, three targets (Suning shopping center, Municipal government, and Phoenix mountain park) with different characteristics in HZ District are selected as the research object of the chemical terrorist attack. Secondly, we select risk factors, most of which have appeared in [43]. The network parameters are partly derived from data learning (the GTD database that comes with the system) and partly from the expert experience conditional probability table (Figure 8).…”

Section: A Case Studymentioning

confidence: 99%

“…However, the risk factors considered in these studies are not comprehensive. In particular, Zhu et al established a Bayesian network for chemical terrorist attacks for risk analysis [43], conducting attacking risk analysis from multiple dimensions including terrorist organizations, target attractiveness, defensive forces, emergency response forces, and danger level of the weapon. Nevertheless, this model is not able to obtain specific attack risk indicators or values, which further limits the practicality of the risk analysis.…”

Section: Introductionmentioning

confidence: 99%

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A Personalized and Practical Method for Analyzing the Risk of Chemical Terrorist Attacks

Zhu

et al. 2020

IEEE Access

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The chemical terrorist attack is a type of unconventional terrorism that threatens the safety of cities. This kind of terrorist attack is highly concealed and difficult to be detected. Once the attack is successful, the consequences will be severe and the scope of impact will be enormous. Therefore, public security and emergency departments need to perform risk analysis and dynamic knowledge update to reduce risk or mitigate the effects of accidents. In order to quickly and effectively analyze the risk of chemical terrorist attacks, this article proposed a hybrid approach (B-R model) to analyze the risk of chemical terrorist attacks. First, a modular and customizable Bayesian network (BN) model library was built, which can satisfy users to select multi-dimensional risk factors. Based on the personalized BN, a risk knowledge graph (RKG) is constructed with multi-source data to realize the combination of risk analysis and knowledge acquisition. Then the threat degree of terrorist organizations, the strength of defensive forces, and the risk value of targets is calculated and displayed. The BN-RKG method provides data and theoretical support for defenders' resource allocation and emergency decision-making. Finally, a case study was conducted for a hypothetical scenario analysis. The result shows that the hybrid method can help with risk control and have the potential to support practical policymaking. INDEX TERMS Chemical terrorist attack, Bayesian network, knowledge graph, risk analysis.

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“…This method is widely used in risk analysis [ 18 , 19 , 20 , 21 ], risk assessment [ 22 , 23 , 24 , 25 ] and decision-making [ 26 , 27 ]. Zhu et al constructed a BN model of chemical terrorist attacks to conduct risk analysis, which provided theoretical support for the security prevention work of the risk management department [ 28 ]. Liu et al applied BN to analyze the role of emergency organization elements in the evolution of flood Na-Tech events [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

Bayesian Network-Based Risk Analysis of Chemical Plant Explosion Accidents

Wang

Liu

2020

IJERPH

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The chemical industry has made great contributions to the national economy, but frequent chemical plant explosion accidents (CPEAs) have also caused heavy property losses and casualties, as the CPEA is the result of interaction of many related risk factors, leading to uncertainty in the evolution of the accident. To systematically excavate and analyze the underlying causes of accidents, this paper first integrates emergency elements in the frame of orbit intersection theory and proposes 14 nodes to represent the evolution path of the accident. Then, combined with historical data and expert experience, a Bayesian network (BN) model of CPEAs was established. Through scenario analysis and sensitivity analysis, the interaction between factors and the impact of the factors on accident consequences was evaluated. It is found that the direct factors have the most obvious influence on the accident consequences, and the unsafe conditions contribute more than the unsafe behaviors. Furthermore, considering the factor chain, the management factors, especially safety education and training, are the key link of the accident that affects unsafe behaviors and unsafe conditions. Moreover, effective government emergency response has played a more prominent role in controlling environmental pollution. In addition, the complex network relationship between elements is presented in a sensitivity index matrix, and we extracted three important risk transmission paths from it. The research provides support for enterprises to formulate comprehensive safety production management strategies and control key factors in the risk transmission path to reduce CPEA risks.

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Modeling and Risk Analysis of Chemical Terrorist Attacks: A Bayesian Network Method

Cited by 16 publications

References 52 publications

Tooth-Level Analysis of Dental Caries in Primary Dentition in Myanmar Children

Tooth-Level Analysis of Dental Caries in Primary Dentition in Myanmar Children

A Personalized and Practical Method for Analyzing the Risk of Chemical Terrorist Attacks

Bayesian Network-Based Risk Analysis of Chemical Plant Explosion Accidents

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