Burnout in seafarers: its antecedents and effects on incidents at sea

Seafarer health and well-being has long been a concern in the shipping industry because of the unique characteristics of working at sea. This paper aims to identify the role of burnout in seafarer health and well-being and its effect on safety. In particular, we differentiated seafarer burnout into personal and work-related burnout to reflect the ambiguous distinction between rest and work in seafarers’ job environment. We also investigate the effectiveness of emotion regulation for seafarers to reduce burnout. This study proposes a conceptual framework to identify the causal relationship between occupational stress, sleepiness, emotion regulation, burnout, and incidents at sea. To verify the proposed framework, scales were adapted from established scales in the literature; a cross-sectional survey was also conducted to collect empirical data for analysis with path and simultaneous equation models. The analysis results revealed that personal and work-related burnout in seafarers are mutually affected; however, only work-related burnout exerts a direct effect on incidents. Reappraisal is an effective emotion regulation strategy in seafarers to reduce personal burnout, but not work-related burnout. Occupational stress and sleepiness exert positive effects on both personal and work-related burnout; yet, their effect on incidents is mediated by work-related burnout.     

上海轨道交通共线运营非正常事件处置对策初探

结合上海轨道交通3、4号线共线运营模式的特性,利用现有轨道交通线路运营经验,针对几种影响面较大的运营非正常事件进行探讨,使故障对乘客的出行影响降至最低限度。     

Estimating freeway route travel time distributions with consideration to time‐of‐day,inclement weather,and traffic incidents

This paper develops an efficient probabilistic model for estimating route travel time variability, incorporating factors of time‐of‐day, inclement weather, and traffic incidents. Estimating the route travel time distribution from historical link travel time data is challenging owing to the interactions among upstream and downstream links. Upon creating conditional probability function for each link travel time, we applied Monte Carlo simulation to estimate the total travel time from origin to destination. A numerical example of three alternative routes in the City of Buffalo shows several implications. The study found that weather conditions, except for snow, incur minor impact on off‐peak and weekend travel time, whereas peak travel times suffer great variations under different weather conditions. On top of that, inclement weather exacerbates route travel time reliability, even when mean travel time increases moderately. The computation time of the proposed model is linearly correlated to the number of links in a route. Therefore, this model can be used to obtain all the origin to destination travel time distributions in an urban region. Further, this study also validates the well‐known near‐linear relation between the standard deviation of travel time per unit distance and the corresponding mean value under different weather conditions. Copyright © 2016 John Wiley & Sons, Ltd.     

交通事件和干预作用影响下的高速公路车流波分析

运用流体力学车流波理论,分析了交通事件和干预措施综合作用下对车流状态的影响,建立了基于车速———交通密度一般模型下的车流波波速模型、干预作用产生的干预波和交通事件影响产生的集结波、启动波、消散波相互作用产生的车流波位置和对应时刻模型以及分流干预措施解除时刻模型.这些模型或关键参数的确定,为有效确定事件处理方案,尽快消除拥挤或阻塞提供了理论依据.     

辅导员应对高校突发性事件的对策分析

随着我国高等教育的发展,学校各类突发性事件逐渐增多,给学校的稳定与发展带了诸多负面影响。辅导员作为高校教师队伍和管理队伍的重要组成部分,是维护学校稳定与发展的一支重要力量,在高校突发事件的应对中起着重要的作用。     

基于完全信息静态博弈论的工程安全监管分析

利用博弈论为工程安全监管提供一个示范,提出了“边际政绩收益”概念,为政府安全监管提供一个参考指标,并且通过安全监管博弈分析,建立博弈模型,对模型进行求解,对工程监管决策中可控因素进行计算,得到一些有利于我国工程安全监管决策的结论．     

基于时间序列挖掘的隧道交通事件分析

为了及时发现隧道内交通安全隐患,尽量减少交通事故的发生,针对现有隧道交通事件预测方法在实际应用中的不足,引入时间序列法,建立了隧道交通事件时间序列预测模型,该模型可以快捷地得出事故影响因素的预测值,预测出道路交通事件总体发展趋势。实验证明,模型能很好地适应于道路交通事故预测,同时具备了资料较少,建模简单,计算快捷等优点。     

高速公路交通事件线性模型及车流波分析

高速公路由于交通事件的发生导致正常交通流发生改变,为了消散车流拥挤或阻塞,减少排队延误,应采取一定干预措施。运用流体力学车流波理论,分析了交通事件和干预措施综作用下对车流状态的影响,建立了关于车速与交通密度线性模型下的车流波波速模型,这些模型为有效确定事件处理方案,尽快消除拥挤或阻塞提供了理论依据。     

高速公路交通事件清除时间模糊逻辑预测模型

清除时间是高速公路交通事件持续时间中的一部分,与事件影响范围密切相关.通过对某高速公路事件数据及交警执勤记录进行分析,提出了救援车辆的清除时间新定义,该定义与事件持续时间有更强的相关性.随后采用含自适应算法的TSK模糊逻辑推理方法,通过对基于事件数据的人工神经网络训练,建立了交通事件清除时间的预测模型,并讨论了模型的适...     

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提出一种新颖的基于boosting模糊分类的交通事件检测方法。该方法利用Boosting方法和遗传算法以迭代形式获取一组模糊规则及规则对应的权值，分类器以加权投票方式进行分类决策。运用Matlab 进行了仿真分析，结果表明提出的交通事件检测算法利用较少样本数据即可快速实现交通事件检测。