安全科学与韧性(英文)最新文献_第2页

Intelligent emergency assisted decision-making method based on standard digitalization: Hazardous chemical accidents in industrial parks

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-08-16 DOI: 10.1016/j.jnlssr.2024.06.009

Zhenxiang Tao , Xiaohan Liu , Ying Li , Peifeng Hu , Weitong Tang , Ning Luo , Jiansong Wu , Rui Yang

Contemporary society is confronted with multifaceted challenges, and the intricate interplay of interconnected factors significantly complicates emergency response efforts. Current practices rely on quick decisions by domain experts; however, the limitations of individual expertise and the urgency of crises hinder both precision and standardization. To address these issues, we propose a novel approach: an intelligent method for emergency decision-making grounded in a standardized digital knowledge graph. First, our study examined the underlying theory of standardized digital transformation and event-chain evolution. This led to the construction of a knowledge graph encompassing standard emergency knowledge, as well as supplementary derivative data pertinent to event response. Second, through the application of semantic analysis and intention recognition of the decision target, coherent and interpretable query sentences for the decision system were crafted. These query sentences then served as a conduit for retrieving standard emergency knowledge relevant to the current emergency situation, as well as potential secondary disasters. The overarching goal is to provide emergency decision makers with effective support mechanisms that are both well informed and tailored to the specific demands of each situation.

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引用次数: 0

Novel explicit models for assessing the frictional resistance of pipe piles subjected to seismic effects

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-08-15 DOI: 10.1016/j.jnlssr.2024.06.010

Duaa Al-Jeznawi , Laith Sadik , Saif Alzabeebee , Musab Aied Qissab Al-Janabi , Suraparb Keawsawasvong

This paper introduces novel explicit models to predict the frictional resistance of open and closed-ended pipe piles subjected to seismic loading. This research employs genetic programming (GP) and multiobjective genetic algorithm-based evolutionary polynomial regression (EPR-MOGA) to develop closed-form expressions for estimating pile frictional resistance, utilizing widely used input parameters for enhanced practicality and applicability in engineering practice. The proposed models are developed using only three input variables: the corrected standard penetration test (SPT) blow count (N₁)₆₀, the pile slenderness ratio (L/D), and the peak ground acceleration (PGA). This deliberate reduction in input complexity significantly enhances the models' applicability across a wide range of geotechnical scenarios and industries. The accuracy of the developed models was assessed via the coefficient of determination (R²), root mean squared error (RMSE), and mean absolute error (MAE). In the case of the GP model, the evaluation metrics for the testing set for open-ended piles (R², RMSE, and MAE values) are 0.89, 0.43, and 0.35, respectively, whereas the corresponding values for closed-ended piles are 0.93, 0.38, and 0.3, respectively. On the other hand, the EPR-MOGA approach achieves similarly encouraging results, with performance metrics of 0.92, 0.37, and 0.29 for open-ended piles and 0.91, 0.39, and 0.30 for closed-ended piles.

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引用次数: 0

Vehicle-augmented evacuation integer programming model for improving safety and efficiency in underground mines

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-08-09 DOI: 10.1016/j.jnlssr.2024.06.007

Frimpong Kwaku Asare, Amin Moniri-Morad, Peter Chidi Augustine, Javad Sattarvand

Ensuring the safe evacuation of miners during fire emergencies in the shortest possible time is one of the most critical aspects of underground mining operations. Despite advances in mining evacuation methods, little research has been conducted on mine vehicles in this context. This study proposed a vehicle-augmented evacuation integer programming (VEIP) model to minimize the total evacuation cost as a function of the required evacuation time during fire emergencies. This approach aims to minimize the risk of miners being exposed to dangerous fire conditions by strategically integrating mine vehicles into the evacuation procedure. The approach determines the optimal evacuation path for each miner, considering factors such as available mine vehicles, miners’ locations, refuge chambers, and fresh-air bases. To validate the effectiveness of the developed VEIP model, a case study was conducted using the mine layout of the Turquoise Ridge Underground Mine in the United States. Furthermore, a statistical comparison was conducted between the VEIP model and the evacuation integer programming (EIP) model, tailored to evacuation on foot, to emphasize vehicles' influence on the evacuation process. The results showed that integrating mine vehicles into evacuation procedures significantly reduces the total evacuation time. A cost savings analysis in the VEIP model revealed that the evacuation time savings increase exponentially as the number of miners present during evacuation increases. The potential benefits of using mine vehicles to improve the efficiency of evacuation from underground mine fires were highlighted in this study.

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引用次数: 0

Risk assessment of fire casualty in underground commercial building based on FFTA-BN model 基于 FFTA-BN 模型的地下商业建筑火灾伤亡风险评估

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-08-08 DOI: 10.1016/j.jnlssr.2024.06.008

Wenjun Fu, Jintao Li, Jinghong Wang, Jialin Wu

With the development of urbanization, underground commercial buildings (UCB) are facing severe challenges in fire safety management due to their unique structure and environmental characteristics. This study constructed a fire casualty risk assessment model that combines fuzzy fault tree analysis (FFTA) and Bayesian network (BN), aiming to quantitatively analyze the dynamic risk of casualties caused by fires in UCB. Fault tree analysis (FTA) is used to comprehensively identify the key risk factors leading to fire casualties in UCB, involving 55 basic events, and the occurrence probability of basic events was calculated via a fuzzy set. The FTA model was transformed into a BN structure via conversion rules and was optimized. The optimized BN model can dynamically analyze the specific fire evolution process and quantify the impacts of different emergency response measures on fire control, evacuation, and casualties. Innovatively, from the post-incident (a historical case study) and pre-incident (two potentially different fire scenarios) perspectives, various emergency plans were scientifically evaluated, providing reasonable suggestions and decision support for emergency management. The results indicate that the model can effectively guide the formulation of fire prevention and control strategies and emergency response work of UCB and provide an innovative tool for improving the safety of UCB and reducing fire accidents and casualties.

随着城市化的发展，地下商业建筑（UCB）因其独特的结构和环境特点，在消防安全管理方面面临着严峻的挑战。本研究结合模糊故障树分析法（FFTA）和贝叶斯网络（BN）构建了火灾伤亡风险评估模型，旨在定量分析地下商业建筑火灾造成伤亡的动态风险。采用故障树分析法（FTA）全面识别了导致城市综合体火灾伤亡的关键风险因素，涉及 55 个基本事件，并通过模糊集计算了基本事件的发生概率。通过转换规则将 FTA 模型转换为 BN 结构并进行优化。优化后的 BN 模型可以动态分析具体的火灾演变过程，量化不同应急措施对火灾控制、人员疏散和人员伤亡的影响。创新性地从事故后（历史案例研究）和事故前（两种可能不同的火灾场景）两个角度，对各种应急方案进行了科学评估，为应急管理提供了合理建议和决策支持。研究结果表明，该模型能有效指导UTB火灾防控策略的制定和应急响应工作，为提高UTB的安全性、减少火灾事故和人员伤亡提供了创新工具。

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引用次数: 0

Determination of individual disaster resilience levels of hospital staff: A case study of Kartal Dr. Lütfi Kirdar City Hospital 确定医院员工的个人抗灾能力水平：卡尔塔尔-吕特菲-克尔达尔博士市医院案例研究

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-08-03 DOI: 10.1016/j.jnlssr.2024.06.006

Emine Üstünoldu

Istanbul is one of Turkey's most important financial and industrial centers, and it is located in a region with a high potential for seismicity. Due to its historical architecture and high level of urbanization, the city has a large population and is particularly vulnerable due to the building stock that will be affected by earthquakes. In the event of a possible earthquake in Istanbul, it is crucial that the hospital staff have high levels of disaster resilience/resilience. This is particularly important given the seismically isolated and earthquake-resistant structure of Istanbul Kartal Dr. Lütfi Kırdar City Hospital and its capacity to serve those injured by the earthquake. This study examines the resilience levels of hospital staff at Kartal Dr. Lütfi Kırdar City Hospital in the face of earthquake disasters and the various factors that affect these resilience levels. The data for this study were collected using a 13-question personal information form and the ‘Individual Disaster Resilience Assessment (IDRA)’ scale developed by DiTirro (2018). Descriptive statistics, Pearson Chi-square tests, Independent Samples T-tests, and One-Way ANOVA were used to analyze the data. The research found that the hospital staff's IDRA scores averaged 3.27. It was concluded that the mean resilience score of the participants was above the medium level. The research findings show that receiving disaster training or being prepared for disasters in advance significantly influences individual resistance/resilience. In this context, it is essential to determine the earthquake resistance levels of all healthcare workers in Istanbul, especially those at the city hospital where the study was conducted. Necessary training should be provided, and simulation-based disaster drills should be planned and integrated into in-service training programs. Additionally, projects should be developed to ensure that healthcare workers can reach their hospitals safely during disaster situations.

伊斯坦布尔是土耳其最重要的金融和工业中心之一，位于地震高发区。由于其历史悠久的建筑和高度城市化，该市人口众多，受地震影响的建筑群尤其脆弱。在伊斯坦布尔可能发生地震的情况下，医院员工必须具备较高的抗灾/复原能力。鉴于伊斯坦布尔 Kartal Dr. Lütfi Kırdar 市立医院的地震隔离和抗震结构及其为地震伤员提供服务的能力，这一点尤为重要。本研究探讨了 Kartal Dr. Lütfi Kırdar 市医院员工面对地震灾害时的应变能力水平，以及影响这些应变能力水平的各种因素。本研究的数据是通过 13 个问题的个人信息表和 DiTirro（2018 年）开发的 "个人抗灾能力评估（IDRA）"量表收集的。数据分析采用了描述性统计、皮尔逊卡方检验、独立样本 T 检验和单向方差分析。研究发现，医院员工的 IDRA 分数平均为 3.27。结论是参与者的平均抗灾能力得分高于中等水平。研究结果表明，接受灾害培训或提前做好防灾准备对个人的抵抗力/复原力有显著影响。在这种情况下，有必要确定伊斯坦布尔所有医护人员的抗震水平，尤其是本研究所在城市医院的医护人员。应提供必要的培训，规划模拟灾难演习，并将其纳入在职培训计划。此外，还应制定项目，确保医护人员在灾难发生时能安全到达医院。

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引用次数: 0

Improving the industrial safety management system at enterprises with chemically hazardous sites 完善化学危险场所企业的工业安全管理体系

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-07-30 DOI: 10.1016/j.jnlssr.2024.06.005

Pavel V. Yemelin , Sergey S. Kudryavtsev , Natalya K. Yemelina

This study focuses on developing an industrial and occupational safety management system for enterprises that contain chemically hazardous sites. The methodology, based on an expert approach, enabled the authors to design the structure of the risk management system at such enterprises. It also facilitated the identification of clusters and their descriptors, along with their roles in evaluating the state of the safety management system. The proposed methodology features a flexible and universal structure, making it applicable for assessing industrial and occupational safety across different enterprises, taking into account the specific technological aspects of production processes. In this case study, the authors examined the accident rates, injury hazards, and health risks associated with chemically hazardous sites in enterprises located in the Republic of Kazakhstan. The findings of this study provide a methodological approach that industrial enterprises can use to evaluate the effectiveness of their safety management systems. This allows for the development of measures aimed at preventing chemical accidents and reducing their impacts.

本研究的重点是为包含化学危险场所的企业开发工业和职业安全管理系统。该方法以专家方法为基础，使作者能够设计此类企业风险管理系统的结构。该方法还有助于确定群组及其描述符，以及它们在评估安全管理系统状况中的作用。所提出的方法具有灵活、通用的结构，可用于评估不同企业的工业和职业安全，同时考虑到生产流程的具体技术方面。在本案例研究中，作者考察了哈萨克斯坦共和国企业中与化学危险场所相关的事故率、伤害危害和健康风险。这项研究的结果提供了一种方法论，工业企业可用来评估其安全管理系统的有效性。这有助于制定旨在预防化学事故和减少其影响的措施。

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引用次数: 0

DyHDGE: Dynamic heterogeneous transaction graph embedding for safety-centric fraud detection in financial scenarios DyHDGE：动态异构交易图嵌入，用于金融场景中以安全为中心的欺诈检测

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-07-22 DOI: 10.1016/j.jnlssr.2024.05.005

Xinzhi Wang, Jiayu Guo, Xiangfeng Luo, Hang Yu

Dynamic graph fraud detection aims to distinguish fraudulent entities that deviate significantly from most benign entities within an ever-changing graph network. However, when dealing with different financial fraud scenarios, existing methods face challenges, resulting in difficulty in effectively ensuring financial security. In fraud scenarios, transaction data are generated in real time, in which a strong temporal relationship between multiple fraudulent transactions is observed. Traditional dynamic graph models struggle to effectively balance the temporal features of nodes and spatial structural features, failing to handle different types of nodes in the graph network. In this study, to extract the temporal and structural information, we proposed a dynamic heterogeneous transaction graph embedding (DyHDGE) network based on a dynamic heterogeneous transaction graph, considering both temporal and structural information while incorporating heterogeneous data. To separately extract temporal relationships between transactions and spatial structural relationships between nodes, we used a heterogeneous temporal graph representation learning module and a temporal graph structure information extraction module. Additionally, we designed two loss functions to optimize node feature representations. Extensive experiments demonstrated that the proposed DyHDGE significantly outperformed previous state-of-the-art methods on two simulated datasets of financial fraud scenarios. This capability contributes to enhancing security in financial consumption scenarios.

动态图欺诈检测旨在区分在不断变化的图网络中明显偏离大多数良性实体的欺诈实体。然而，在处理不同的金融欺诈场景时，现有方法面临挑战，难以有效确保金融安全。在欺诈场景中，交易数据是实时生成的，其中可以观察到多个欺诈交易之间存在很强的时间关系。传统的动态图模型难以有效平衡节点的时间特征和空间结构特征，无法处理图网络中不同类型的节点。在本研究中，为了提取时间和结构信息，我们提出了一种基于动态异构交易图的动态异构交易图嵌入（DyHDGE）网络，在结合异构数据的同时考虑了时间和结构信息。为了分别提取交易之间的时间关系和节点之间的空间结构关系，我们使用了异构时间图表示学习模块和时间图结构信息提取模块。此外，我们还设计了两个损失函数来优化节点特征表示。广泛的实验表明，在两个金融欺诈场景的模拟数据集上，所提出的 DyHDGE 明显优于之前的先进方法。这种能力有助于提高金融消费场景的安全性。

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引用次数: 0

Exploring the risks of automation bias in healthcare artificial intelligence applications: A Bowtie analysis 探索医疗人工智能应用中的自动化偏差风险：Bowtie 分析

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-07-19 DOI: 10.1016/j.jnlssr.2024.06.001

Moustafa Abdelwanis, Hamdan Khalaf Alarafati, Maram Muhanad Saleh Tammam, Mecit Can Emre Simsekler

This study conducts an in-depth review and Bowtie analysis of automation bias in AI-driven Clinical Decision Support Systems (CDSSs) within healthcare settings. Automation bias, the tendency of human operators to over-rely on automated systems, poses a critical challenge in implementing AI-driven technologies. To address this challenge, Bowtie analysis is employed to examine the causes and consequences of automation bias affected by over-reliance on AI-driven systems in healthcare. Furthermore, this study proposes preventive measures to address automation bias during the design phase of AI model development for CDSSs, along with effective mitigation strategies post-deployment. The findings highlight the imperative role of a systems approach, integrating technological advancements, regulatory frameworks, and collaborative endeavors between AI developers and healthcare practitioners to diminish automation bias in AI-driven CDSSs. We further identify future research directions, proposing quantitative evaluations of the mitigation and preventative measures.

本研究对医疗机构中人工智能驱动的临床决策支持系统（CDSS）中的自动化偏差进行了深入评述和 Bowtie 分析。自动化偏差是指人类操作员过度依赖自动化系统的倾向，这对人工智能驱动技术的实施提出了严峻的挑战。为了应对这一挑战，本研究采用了 Bowtie 分析法来研究医疗保健领域过度依赖人工智能驱动系统所导致的自动化偏差的原因和后果。此外，本研究还提出了在 CDSS 的人工智能模型开发设计阶段解决自动化偏差的预防措施，以及部署后的有效缓解策略。研究结果强调了系统方法的重要作用，即整合技术进步、监管框架以及人工智能开发人员和医疗从业人员之间的合作努力，以减少人工智能驱动的 CDSS 中的自动化偏差。我们进一步确定了未来的研究方向，提出了对缓解和预防措施的定量评估。

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引用次数: 0

A spatial scene reconstruction framework in emergency response scenario 应急场景中的空间场景重建框架

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-07-15 DOI: 10.1016/j.jnlssr.2024.05.004

Nan Zheng, Danhuai Guo

Rapid and accurate acquisition and analysis of information is crucial for emergency management, but traditional methods have limitations such as incomplete information acquisition and slow processing speed. The natural language oriented spatial scene reconstruction method provides a new solution for emergency management, but existing generative models have limited understanding of spatial relationships and lack high-quality training samples. To address these issues, this paper proposes a novel spatial scene reconstruction framework. Specifically, the BERT based spatial information knowledge graph extraction method is used to encode the input text, label and classify the encoded text, identify spatial objects and relationships in the text, and accurately extract spatial information. Additionally, a large number of manual experiments were conducted to explore quantitative biases in human spatial cognition, and based on the obtained biases, a greedy resolution method based on cost functions was used to fine tune the layout of conflicting spatial objects and solve the conflicting spatial information in the spatial information knowledge graph. Finally, use graph convolutional neural networks to obtain scene knowledge graph embeddings that consider spatial constraints. In addition, a high-quality training sample set of “text-scene-knowledge graph” was constructed.

快速准确地获取和分析信息对应急管理至关重要，但传统方法存在信息获取不完整、处理速度慢等局限性。面向自然语言的空间场景重建方法为应急管理提供了新的解决方案，但现有的生成模型对空间关系的理解有限，且缺乏高质量的训练样本。为解决这些问题，本文提出了一种新型空间场景重建框架。具体来说，本文采用基于 BERT 的空间信息知识图提取方法，对输入文本进行编码，对编码后的文本进行标注和分类，识别文本中的空间对象和空间关系，准确提取空间信息。此外，还进行了大量人工实验，探索人类空间认知中的定量偏差，并根据得到的偏差，采用基于代价函数的贪婪解析法对空间冲突对象的布局进行微调，解决空间信息知识图谱中的空间信息冲突问题。最后，利用图卷积神经网络获得考虑空间约束的场景知识图嵌入。此外，还构建了高质量的 "文本-场景-知识图谱 "训练样本集。

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引用次数: 0

Comfort assessment of wind induced vibrations for slender structures by field monitoring and numerical analysis 通过现场监测和数值分析评估风引起的细长结构振动的舒适性

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-07-14 DOI: 10.1016/j.jnlssr.2024.06.004

D. Kesavan Periyasamy, Vinay Shimpi, Madappa VR Sivasubramanian

Slender structures often lead to vibration discomfort for occupants when exposed to wind forces. This study proposes an innovative method for assessing comfort against wind-induced vibrations for slender structures that combines field monitoring, numerical simulations, codal provisions, and Chang's comfort chart. The method utilizes ambient vibration tests (AVT) and operational modal analysis (OMA) to create a reliable finite element (FE) model for the structure. It involves analyzing the time history and calculating the peak acceleration values at various points within the structure using synthetic ambient wind forces derived from superposing waves. The comfort assessment compares peak acceleration values estimated from time history analysis against those provided in Chang's chart for different comfort levels. The effectiveness of the proposed method is demonstrated through a case study on a tall, slender reinforced concrete (RC) staircase structure, confirming its suitability for practical applications.

细长结构在风力作用下往往会导致居住者产生振动不适感。本研究提出了一种创新方法，用于评估细长结构在风引起的振动下的舒适度，该方法结合了现场监测、数值模拟、法规规定和张氏舒适度图表。该方法利用环境振动测试 (AVT) 和运行模态分析 (OMA) 为结构创建可靠的有限元 (FE) 模型。它包括分析时间历史，并利用叠加波产生的合成环境风力计算结构内各点的峰值加速度值。舒适度评估将时间历程分析估算出的峰值加速度值与 Chang 图表中提供的不同舒适度等级的峰值加速度值进行比较。通过对一个高大、细长的钢筋混凝土（RC）楼梯结构进行案例研究，证明了所提方法的有效性，从而证实了其在实际应用中的适用性。

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引用次数: 0