Optimization of sensor deployment sequences for hazardous gas leakage monitoring and source term estimation

Nowadays, chemical safety has attracted considerable attention, and chemical gas leakage monitoring and source term estimation(STE) have become hot spots. However, few studies have focused on sensor layouts in scenarios with multiple potential leakage sources and wind conditions, and studies on the risk information(RI) detection and prioritization order of sensors have not been performed. In this work, the monitoring area of a chemical factory is divided into multiple rectangles with a uniform mesh. The RI value of each grid node is calculated on the basis of the occurrence probability and normalized concentrations of each leakage scenario. A high RI value indicates that a sensor at a grid node has a high chance of detecting gas concentrations in different leakage scenarios. This situation is beneficial for leakage monitoring and STE. The methods of similarity redundancy detection and the maximization of sensor RI detection are applied to determine the sequence of sensor locations. This study reveals that the RI detection of the optimal sensor layout with eight sensors exceeds that of the typical layout with 12 sensors. In addition, STE with the optimized placement sequence of the sensor layout is numerically simulated. The statistical results of each scenario with various numbers of sensors reveal that STE is affected by sensor number and scenarios(leakage locations and winds). In most scenarios, appropriate STE results can be retained under the optimal sensor layout even with four sensors. Eight or more sensors are advised to improve the performance of STE in all scenarios. Moreover, the reliability of the STE results in each scenario can be known in advance with a specific number of sensors. Such information thus provides a reference for emergency rescue.

Fuzzy Risk Assessment Method for Airborne Network Security Based on AHP-TOPSIS

With the exponential increase in information security risks,ensuring the safety of aircraft heavily relies on the accurate performance of risk assessment.However,experts possess a limited understanding of fundamental security elements,such as assets,threats,and vulnerabilities,due to the confidentiality of airborne networks,resulting in cognitive uncertainty.Therefore,the Pythagorean fuzzy Analytic Hierarchy Process(AHP)Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne networks.First,Pythagorean fuzzy AHP is employed to construct an index system and quantify the pairwise comparison matrix for determining the index weights,which is used to solve the expert cognitive uncertainty in the process of evaluating the index system weight of airborne networks.Second,Pythagorean fuzzy the TOPSIS to an Ideal Solution is utilized to assess the risk prioritization of airborne networks using the Pythagorean fuzzy weighted distance measure,which is used to address the cognitive uncertainty in the evaluation process of various indicators in airborne network threat scenarios.Finally,a comparative analysis was conducted.The proposed method demonstrated the highest Kendall coordination coefficient of 0.952.This finding indicates superior consistency and confirms the efficacy of the method in addressing expert cognition during information security risk assessment for airborne networks.

Farmers’Demand for Informal Risk Management Strategy and Weather Index Insurance:Evidence from China

In the absence of formal risk management strategies,agricultural production in China is highly vulnerable to climate change.In this study,field experiments were conducted with 344 households in Heilongjiang(Northeast China)and Jiangsu(East China)Provinces.Probit and logistic models and independent sample T-test were used to explore farmers’demand for weather index insurance,in contrast to informal risk management strategies,and the main factors that affect demand.The results show that the farmers prefer weather index insurance to informal risk management strategies,and farmers’characteristics have significant impacts on their adoption of risk management strategies.The variables non-agricultural labor ratio,farmers’risk perception,education,and agricultural insurance purchase experience significantly affect farmers’weather index insurance demand.The regression results show that the farmers’weather index insurance demand and the influencing factors in the two provinces are different.Farmers in Heilongjiang Province have a higher participation rate than those in Jiangsu Province.The government should conduct more weather index insurance pilot programs to help farmers understand the mechanism,and insurance companies should provide more types of weather index insurance to meet farmers’diversified needs.

Risk Analysis of Information System Security Based on Distance of Information-State Transition

The configuration of information system security policy is directly related to the information asset risk, and the configuration required by the classified security protection is able to ensure the optimal and minimum policy in the corresponding security level. Through the random survey on the information assets of multiple departments, this paper proposes the relative deviation distance of security policy configuration as risk measure parameter based on the distance of information-state transition（DIT） theory. By quantitatively analyzing the information asset weight, deviation degree and DIT, we establish the evaluation model for information system. With example analysis, the results prove that this method conducts effective risk evaluation on the information system intuitively and reliably, avoids the threat caused by subjective measurement, and shows performance benefits compared with existing solutions. It is not only theoretically but also practically feasible to realize the scientific analysis of security risk for the information system.

Risk Information Sources for Snow Disaster Risk Preparedness in Scotland

Heavy snow disruptions are common and costly occurrences in the UK,including Scotland.Yet,heavy snow remains an underresearched aspect of disaster risks in Scotland.This study critically examined the 2018 heavy snow event in Scotland referred to as the“Beast from the East”(BfE)in order to explore the different sources of information used by the public in preparation for and response to heavy snow emergencies.Our study also examined the effectiveness of BfE risk communication between authorities and the public and sought to determine if there is a relationship between risk information received and the intention to mitigate risk.Data were collected through a semistructured survey from(n=180)residents of the Annandale and Eskdale region of Dumfries and Galloway,Scotland.Our analysis shows that public authority information sources were the most sought-after information sources,followed by online and web sources.We found statistically significant differences between groups(such as age,gender,and mobility/disability)in terms of using risk information sources.Further analysis shows that the relationship between information received and the intention to mitigate risks is not linear but influenced by intervening variables such as work pressures,financial commitment,and stakeholders’expectations.We argue that where full adherence to official risk advice is required,policymakers should carefully consider issues around these three factors.

Appetite for Natech Risk Information in Japan:Understanding Citizens'Communicative Behavior Towards Risk Information Disclosure Around Osaka Bay

Effective risk communication is essential for disaster risk management.Apart from empowering communities to make informed risk choices,risk information disclosure can also drastically enhance their disaster preparedness,especially concerning conjoint scenarios of technological and natural hazards(Natech).A fundamental precondition is the actual demand for such information.This study ventures to assess whether residents around Osaka Bay have this demand,or"appetite,"for risk information disclosure,as well as to understand their communicative behavior and perceived challenges in the Japanese context through the prism of the Situational Theory of Problem Solving.To test this framework under realistic conditions,data were collected through a household questionnaire survey from two urban areas near industrial complexes in Osaka Bay.The results show that identifying Natech risk information deficiency as a problem was not a statistically significant predictor for individuals'motivation to communicate.However,their motivation increased as their perceived personal involvement with the situation rose,while the perceived obstacles in doing something about it exerted a negative influence on their motivation.Individuals'motivation intensified their communicative actions to solve this problem.Public segmentation underscored the elevated public perceptions concerning the issue of risk information deficiency in nearly nine out of ten respondents.These findings indicate a strong community appetite for chemical and Natech risk information,which subsequently led to high situational motivation to engage in communicative action,particularly information acquisition.Risk management policy is suggested to focus on introducing chemical risk information disclosure regulatory initiatives to encourage citizen engagement.

How Does the Internet Impact the Public's Perception of Information Security Risk?

Clarifying the relationship between internet use and public information security risk perception helps us gain a better understanding of the factors influencing public risk perception.However,the relationship is still under-explored.This paper empirically examines the relationship between internet use and information security risk perception based on data from the 2021 Chinese Social Survey.It was found that whether to use the internet and the frequency of use are both significantly positively correlated with the perception of information security risk.On this basis,the mechanism by which internet use affects public information security risk perceptions is verified from the perspective of interpersonal trust.The mechanism analysis found that interpersonal trust exerts an indirect effect between internet use and perceived information security risk.The findings of this study provide new insights for our further understanding of how internet use affects residents'perceptions of securityrisk.

Remembering,Forgetting,and Absencing Disasters in the Post-disaster Recovery Process

Sustainable post-disaster recovery implies learning from past experience in order to prevent recreating forms of vulnerability.Memory construction supports both the healing process and redevelopment plans.Hence,memory of disaster results from the balance between remembering,forgetting,and absencing elements of the disaster,and can be both a tool and an obstacle to sustainable recovery.We explore here how collective memory is built in a post-disaster context to respond to the needs of this critical period,and how it shapes recovery.This ethnographic study,conducted between 2015 and 2017,explores the recovery processes in Montserrat,a small Caribbean island affected by an extended volcanic crisis from 1995 to 2010.Although this study does not give tangible solutions for disaster risk reduction in a post-disaster context,it highlights potential obstacles for learning from a disaster and how they may be surmounted.We argue that it is crucial to acknowledge evolving collective memory in order to implement effective measures for preserving and sharing a shared understanding of disaster across generations and social groups in a way that supports disaster risk awareness.We also maintain that acknowledging the dilemma faced by authorities and disaster management agencies during a period of conflicting needs may encourage the reconsideration of risk framing,and hence reveal how to improve implementation of disaster risk reduction measures.

Use of Internet Technology for the Improvement of Execution Management in Geotechnical Engineering Projects

An internet-based information and monitoring platform for the specific requirements of geotechnical engineering projects is presented. The platform is based on a hybrid-model approach consisting of a model-based information management system and a resource management system, the latter also referred to as DCMS. Project key information can be accessed via the main user interface, the 'graphical navigator'. The graphical navigator provides also a direct access to additional information in the DCMS. Prompt reac-tion in exceptional situations as well as in daily work gets an extensive support. In practical applications it has been proven that this platform seems to be an adequate tool especially for risk assessment and management in geotechnical engineering projects. Components and advantages of the platform as well as ex periences from the applications are presented and discussed in the paper.