水体富营养化及蓝藻水华预警模型研究进展

目前,水体富营养化及蓝藻水华污染已成为最为突出的世界性水环境问题之一,做好水华的预测预警工作显得尤为重要.预警模型是水体富营养化及蓝藻水华预警工作的前提与基础.文章讨论了主要预警参数因子的选择,包括物理因子、化学因子和生物因子;介绍了常用的水体寓营养化及蓝藻水华预警模型的研究进展,总结了各个常用模型的概念、优缺点、建模...     

BP神经网络预警在旅游安全预警信息系统中的应用

将BP神经网络预警技术应用于旅游安全预警信息系统的开发实践，研究建立了一个基于BP神经网络的旅游安全预警模型。该模型有4个子系统构成，即预警知识提取子系统、预警信息库、报警系统和人机互动设备，分析总结了包含旅游地灾害频度、出游设施安全度和旅游地区域安全度三大类10个子因子为内容的旅游安全预警影响因素。在旅游安全预警的影响因素和安全预警的报警判别模式的基础上，进行了旅游安全预警应用的实验设计。实验结果显示，该模型应用效果良好。     

基于RFID及WSN技术的矿山实时三维定位及灾害预警平台

通过对比分析国内外矿山灾害死亡事故数据,突显我国矿山安全生产形势十分严峻,提出了构建矿山实时三维定位及灾害预警平台的重要性。平台基于无线射频识别技术和无线传感网络技术,实现井下工作人员、井下移动设备的三维定位,实现井下巷道工作环境的各种参数（如温度、湿度、井巷通风风速、有害气体含量等）的实时监测,分析实时监测数据,预警井下数据异常区域,防止灾害发生,分析灾害发生位置、原因及发生时井下人员、移动设备等信息,为灾后救援工作提供有价值的决策参考。     

重金属在线监测技术在常州市饮用水水源地预警监测中的应用

简述了重金属在线分析仪的系统架构、方法验证、系统流程的优化、运维周期及应急预警功能。通过重金属在线技术在常州市饮用水水源地预警监测中的应用,表明仪器在测试地表水中镍、铅、砷、镉、铜等金属时相对稳定,基本能满足预警应急的要求;通过系统流程的优化,及对远程控制能力的开发,较好地满足了无人值守的自动监测要求;仪器初步应用于饮用水水源地预警监测中,形成了行之有效的预警应急流程,增加了一道饮用水水质的安全屏障。     

太湖流域水生态环境功能分区管理指标达成效率评估和预警研究

太湖流域严峻的水生态环境形势备受关注,而水生态环境功能分区管理体系实施现状和效果无法被准确把握。以太湖流域水生态环境功能分区为研究对象,基于四象限法则和二维向量结构指标体系等方法论,综合障碍因子分析与目标可达性分析,对太湖流域水生态环境功能分区管理绩效评估目标达成效率进行评估和预警,为水生态环境功能分区管控提供技术指导。结果表明,江苏省太湖流域目标达成效率情况较好,"高效"、"一般"、"低效"的比例依次下降,高预警级别的区域较少;环境效率指标中单位面积污染物减排管控效率较高,环境质量指标整体表现良好,须谨防向"低效"转变。     

基于图论的生产安全事故风险预警指标筛选及分析

为提高事故风险预警准确性,降低事故发生频率,通过对现有生产安全事故案例进行因果连锁理论分析,构建事故成因结构图,采用图论中节点属性分析法,筛选事故风险预警指标,并利用最短路径介数和紧密度改进复杂网络概念,从局部与整体角度探讨事故风险预警指标敏感性.结果表明:人与物类风险预警指标敏感性较高且相近,环境类风险预警指标敏感性...     

Characteristics of rear-end crashes involving passenger vehicles with automatic emergency braking

Abstract

Objectives: Automatic emergency braking (AEB) is a proven effective countermeasure for preventing front-to-rear crashes, but it has not yet fully lived up to its estimated potential. This study identified the types of rear-end crashes in which striking vehicles with AEB are overrepresented to determine whether the system is more effective in some situations than in others, so that additional opportunities for increasing AEB effectiveness might be explored.

Methods: Rear-end crash involvements were extracted from 23?U.S. states during 2009–2016 for striking passenger vehicles with and without AEB among models where the system was optional. Logistic regression was used to examine the odds that rear-end crashes with various characteristics involved a striking vehicle with AEB, controlling for driver and vehicle features.

Results: Striking vehicles were significantly more likely to have AEB in crashes where the striking vehicle was turning relative to when it was moving straight (odds ratio [OR]?=?2.35; 95% confidence interval [CI], 1.76, 3.13); when the struck vehicle was turning (OR = 1.66; 95% CI, 1.25, 2.21) or changing lanes (OR = 2.05; 95% CI, 1.13, 3.72) relative to when it was slowing or stopped; when the struck vehicle was not a passenger vehicle or was a special use vehicle relative to a car (OR = 1.61; 95% CI, 1.01, 2.55); on snowy or icy roads relative to dry roads (OR = 1.83; 95% CI, 1.16, 2.86); or on roads with speed limits of 70+ mph relative to those with 40 to 45?mph speed limits (OR = 1.49; 95% CI, 1.10, 2.03). Overall, 25.3% of crashes where the striking vehicle had AEB had at least one of these overrepresented characteristics, compared with 15.9% of strikes by vehicles without AEB.

Conclusions: The typical rear-end crash occurs when 2 passenger vehicles are proceeding in line, on a dry road, and at lower speeds. Because atypical crash circumstances are overrepresented among rear-end crashes by striking vehicles with AEB, it appears that the system is doing a better job of preventing the more typical crash scenario. Consumer information testing programs of AEB use a test configuration that models the typical rear-end crash type. Testing programs promoting good AEB performance in crash circumstances where vehicles with AEB are overrepresented could guide future development of AEB systems that perform well in these additional rear-end collision scenarios.     

Forward collision warning based on a driver model to increase drivers’ acceptance

Abstract

Objective: Systems that can warn the driver of a possible collision with a vulnerable road user (VRU) have significant safety benefits. However, incorrect warning times can have adverse effects on the driver. If the warning is too late, drivers might not be able to react; if the warning is too early, drivers can become annoyed and might turn off the system. Currently, there are no methods to determine the right timing for a warning to achieve high effectiveness and acceptance by the driver. This study aims to validate a driver model as the basis for selecting appropriate warning times. The timing of the forward collision warnings (FCWs) selected for the current study was based on the comfort boundary (CB) model developed during a previous project, which describes the moment a driver would brake. Drivers’ acceptance toward these warnings was analyzed. The present study was conducted as part of the European research project PROSPECT (“Proactive Safety for Pedestrians and Cyclists”).

Methods: Two warnings were selected: One inside the CB and one outside the CB. The scenario tested was a cyclist crossing scenario with time to arrival (TTA) of 4?s (it takes the cyclist 4?s to reach the intersection). The timing of the warning inside the CB was at a time to collision (TTC) of 2.6?s (asymptotic value of the model at TTA = 4?s) and the warning outside the CB was at TTC = 1.7?s (below the lower 95% value at TTA = 4?s). Thirty-one participants took part in the test track study (between-subjects design where warning time was the independent variable). Participants were informed that they could brake any moment after the warning was issued. After the experiment, participants completed an acceptance survey.

Results: Participants reacted faster to the warning outside the CB compared to the warning inside the CB. This confirms that the CB model represents the criticality felt by the driver. Participants also rated the warning inside the CB as more disturbing, and they had a higher acceptance of the system with the warning outside the CB. The above results confirm the possibility of developing wellsaccepted warnings based on driver models.

Conclusions: Similar to other studies’ results, drivers prefer warning times that compare with their driving behavior. It is important to consider that the study tested only one scenario. In addition, in this study, participants were aware of the appearance of the cyclist and the warning. A further investigation should be conducted to determine the acceptance of distracted drivers.     

上海崇明岛蔬菜地土壤重金属含量与生态风险预警评估

崇明3城镇蔬菜地土壤重金属的总体含量为Cu 29.2 mg·kg^-1、Pb 26.5 mg·kg^-1、Cr 79.4 mg·kg^-1、Zn 91.2 mg·kg^-1和Cd 0.222 mg·kg^-1.除Cd在城桥镇和陈家镇超过国家土壤一级标准(GB 15618-1995)外,其余均低于国家土壤一级标准,并且满足国家对绿色食品产地土壤重金属含量的要求(NY/T391-2000).与上海土壤背景值相比,Cu、Pb、Cr、Zn和Cd分别高出上海土壤背景值 24.3％、24.4％、22.9％、18.8％和65.7％.崇明3城镇蔬菜地土壤重金属生态风险预警评估得出,23个采样点中有3个样点属于中警,10个样点属于轻警,8个样点属于预警,1个样点属于无警,综合评估I_{ER＝1.562,为轻警.3城镇生态风险排序为堡镇（IER=1.799）>城桥镇（IER=1.636）>陈家镇（IER=1.368）,均属于轻警.}     

高危作业监测预警系统的总体设计

为探索高危作业监测预警系统的建立,对风险监测预警系统进行了系统研究,在研究总结其基本原理的基础上,从理论上提出筛选高危作业监测预警指标的原则、要求和方法,进而提出高危作业监测预警的核心技术指标体系的建立及其基本结构和运行模式的总体设计思路,首次提出职业危害控制的先行指标、同步指标和滞后指标,在高危作业监测预警系统中建立信息咨询系统、信息监测系统、风险评估与诊断系统、预防控制与应急救援决策系统等子系统和高危作业监测预警系统基本结构与运行模式。该系统可以科学判断出当前政策、法规、标准、规划,经济贸易的影响及相应需采取的政策调整,在控制、检测、评价、诊断、防护等领域应重点开展的关键技术研究,当前机构、人员、设施、财力等方面的能力建设要求,分析政府、企业、劳动者应采取的主要行为干预。本文逻辑清晰、系统性强、内容全面,可为进一步开展职业病防治工作提供前沿考虑。