安全科学与韧性(英文)最新文献_第9页

Combining Bayesian Networks and MCDA methods to maximise information gain during reconnaissance in emergency situations 结合贝叶斯网络和MCDA方法，在紧急情况下侦察时最大限度地获取信息

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-08-22 DOI: 10.1016/j.jnlssr.2024.07.001

Daniel Lichte

In the immediacy of an event that disrupts the operation of an infrastructure, the time between its occurrence and the arrival of qualified personnel for emergency response can be valuable. For example, it can be used for gathering information about the status of the infrastructure by using automated reconnaissance devices. In an operation that precedes the intervention of human first responders, such devices can gather information about the situation, providing knowledge about the locations of stressors (e.g. fire), the inaccessibility of parts of the infrastructure or the presence of hazardous materials. In this study, we show how a Bayesian Networks can be used for knowledge representation and how it can be combined with methods from the realm of Multi-Criteria Decision Analysis (MCDA) for situation reconnaissance and route-optimisation in emergency situations, where different criteria (current belief about the location of zones of special interest, such as emergency exits, distance to the next point of interest, etc.) can be considered. As an example, we consider the case of an outbreak of a fire in a building. A pedantic check of all rooms by an automated reconnaissance device would take too long and thus delay intervention. Due to the limited time in which the building can be explored, the route is optimised to gather the greatest possible amount of information in the available time window. Results show how it is possible to maximise the information collected in a limited time window. This is done by discovering the location of fire and any hazardous materials through causal inferences automatically calculated by the Bayesian network. Route optimisation is facilitated by sequential MCDA using a parameter selection that meets the priorities of the specific application example.

在立即发生破坏基础设施运行的事件时，从事件发生到合格的应急人员到达之间的时间可能是宝贵的。例如，它可以通过使用自动侦察设备来收集有关基础设施状态的信息。在人类第一响应者介入之前的行动中，这种装置可以收集有关情况的信息，提供有关压力源位置（例如火灾）、部分基础设施难以接近或存在有害物质的知识。在本研究中，我们展示了如何将贝叶斯网络用于知识表示，以及如何将其与多标准决策分析（MCDA）领域的方法相结合，用于紧急情况下的态势侦察和路线优化，其中可以考虑不同的标准（关于特殊利益区域位置的当前信念，例如紧急出口，到下一个利益点的距离等）。作为一个例子，我们考虑在建筑物中发生火灾的情况。通过自动侦察装置对所有房间进行迂腐的检查将花费太长时间，从而延误干预。由于探索建筑物的时间有限，因此优化了路线，以便在可用的时间窗口内收集尽可能多的信息。结果表明，如何在有限的时间窗口内最大限度地收集信息。这是通过贝叶斯网络自动计算的因果推理来发现火灾和任何危险物质的位置来完成的。通过使用符合特定应用示例优先级的参数选择，顺序MCDA促进了路由优化。

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引用次数: 0

Scenario construction and vulnerability assessment of natural hazards-triggered power grid accidents 自然灾害引发电网事故的情景构建和脆弱性评估

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2024-08-20 DOI: 10.1016/j.jnlssr.2024.06.011

Yuxin Sun , Jiansong Wu , Jun Zhang , Yuwei Xiong , Xiaohan Liu , Yiping Bai

In light of escalating urbanization trends and climate change impacts worldwide, the susceptibility of urban power grids to natural disasters has become an overarching global concern. Prior research has predominantly concentrated on singular calamities while often disregarding cumulative repercussions from multiple concurrent events affecting power grid resilience. This investigation presents an exhaustive framework for assessing grid vulnerabilities by quantifying diverse impacts from potential natural disaster scenarios and delineating adaptive pathways for evaluating inadvertent occurrences. The framework amalgamates an extensive array of metrics— including probability assessments, system state evaluations, trigger threshold analyses, responsiveness measurements, and adaptability adjustments— within a dynamic scenario-oriented model. The inquiry progresses through distinct stages: formulating an all-encompassing methodology for assessing vulnerabilities; assessing varied impacts stemming from different environmental perils; mapping out post-disaster evolutions; and executing a case analysis focusing on an urban power grid.

Concentrating specifically on rainfall, snowfall, and freezing incidents, the case analysis uses locale-specific data to appraise grid susceptibilities while employing multi-criteria decision analysis (MCDA) to facilitate decision-making. During this deliberative process, optimal strategies are derived, and mitigative actions are recommended with the aim of diminishing power-grid vulnerabilities. This investigation underscores intricate risk dynamics within urban power grids while presenting a feasible framework for sustainable planning and effective emergency responses in confronting natural hazards.

鉴于全球城市化趋势和气候变化的影响不断升级，城市电网易受自然灾害影响已成为全球关注的首要问题。之前的研究主要集中在单一灾害上，而往往忽视了影响电网恢复能力的多种并发事件的累积影响。本研究提出了一个详尽的电网脆弱性评估框架，通过量化潜在自然灾害情景的各种影响，并划定评估意外事件的适应途径。该框架在一个以情景为导向的动态模型中整合了大量指标，包括概率评估、系统状态评估、触发阈值分析、响应性测量和适应性调整。该研究经历了不同的阶段：制定评估脆弱性的全面方法；评估不同环境危害造成的各种影响；绘制灾后演变图；以及执行以城市电网为重点的案例分析。案例分析特别关注降雨、降雪和冰冻事件，使用当地特定数据评估电网的易受影响程度，同时采用多标准决策分析（MCDA）促进决策制定。在这一审议过程中，得出了最佳策略，并建议采取缓解行动，以降低电网的脆弱性。这项调查强调了城市电网中错综复杂的风险动态，同时为应对自然灾害的可持续规划和有效应急响应提供了一个可行的框架。

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引用次数: 0

Intelligent emergency assisted decision-making method based on standard digitalization: Hazardous chemical accidents in industrial parks 基于标准数字化的工业园区危险化学品事故智能应急辅助决策方法

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.

当代社会面临着多方面的挑战，相互关联的因素错综复杂的相互作用使应急响应工作大大复杂化。当前的实践依赖于领域专家的快速决策；然而，个人专业知识的局限性和危机的紧迫性阻碍了准确性和标准化。为了解决这些问题，我们提出了一种新颖的方法：一种基于标准化数字知识图的应急决策智能方法。首先，我们的研究考察了标准化数字化转型和事件链演化的基础理论。这导致构建了一个包含标准应急知识的知识图，以及与事件响应相关的补充衍生数据。其次，通过对决策目标的语义分析和意图识别，为决策系统构建连贯、可解释的查询语句。然后，这些查询语句作为检索与当前紧急情况以及潜在的次生灾害相关的标准应急知识的渠道。首要目标是向紧急情况决策者提供有效的支助机制，这些机制既了解情况，又适合每种情况的具体需求。

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引用次数: 0

Novel explicit models for assessing the frictional resistance of pipe piles subjected to seismic effects 评估地震作用下管桩摩阻力的新显式模型

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.

本文引入了新的显式模型来预测地震荷载作用下开端和闭端管桩的摩阻力。本研究采用遗传规划（GP）和基于多目标遗传算法的进化多项式回归（EPR-MOGA），利用广泛使用的输入参数，建立了估算桩侧摩阻力的封闭表达式，以增强工程实践中的实用性和应用性。所提出的模型仅使用三个输入变量：修正的标准贯入试验（SPT）吹风计数（N1）60，桩长细比（L/D）和峰值地面加速度（PGA）。这种刻意降低输入复杂性的做法显著提高了模型在岩土工程场景和行业中的适用性。通过决定系数（R2）、均方根误差（RMSE）和平均绝对误差（MAE）来评估所建立模型的准确性。在GP模型中，开放式桩测试集的评价指标（R2、RMSE和MAE值）分别为0.89、0.43和0.35，封闭式桩测试集的评价指标分别为0.93、0.38和0.3。另一方面，EPR-MOGA方法取得了同样令人鼓舞的结果，开放式桩的性能指标为0.92、0.37和0.29，封闭式桩的性能指标为0.91、0.39和0.30。

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引用次数: 0

Vehicle-augmented evacuation integer programming model for improving safety and efficiency in underground mines 提高地下矿山安全效率的车辆增强型疏散整数规划模型

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.

在发生火灾时，如何在最短的时间内确保矿工安全撤离是井下采矿作业的关键问题之一。尽管采矿疏散方法取得了进步，但在这方面对矿用车辆的研究很少。本文提出了一种车辆增强疏散整数规划（VEIP）模型，以最小化火灾紧急情况下疏散总成本作为疏散时间的函数。这种方法旨在通过战略性地将矿用车辆纳入疏散程序，将矿工暴露在危险火灾条件下的风险降至最低。该方法确定了每个矿工的最佳疏散路径，考虑了诸如可用的矿车、矿工的位置、避难室和新鲜空气基地等因素。为了验证所建立的VEIP模型的有效性，以美国Turquoise Ridge地下矿的矿山布局为例进行了研究。进一步，将VEIP模型与针对步行疏散的疏散整数规划（EIP）模型进行统计比较，强调车辆对疏散过程的影响。结果表明，将矿用车辆纳入疏散流程可显著缩短总疏散时间。VEIP模型中的成本节约分析表明，随着疏散期间矿工人数的增加，疏散时间的节省呈指数增长。本研究强调了使用矿用车辆提高井下火灾疏散效率的潜在效益。

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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