Modeling the contribution of speeding and impaired driving to insurance claim counts and costs when contributing factors are unknown

PROBLEM: There are no specific indicators for distinguishing insurance claims related to speeding and impaired driving in the information warehouse at the Insurance Corporation of British Columbia. Contributing factors are only recorded for that part of the claim data that is also reported by the police. Most published statistics on crashes that are related to alcohol or speeding are based on police-reported data, but this represents only a fraction of all incidents. METHOD: This paper proposes surrogate models to estimate the counts and the average costs associated with speeding and impaired driving to insurance claims when contributing factors are unknown. Using police-reported data, classification rules and logistic regression models are developed to form such estimates. One approach applies classification rules to categorize insurance claims into those related to speeding, impaired driving, and other factors. The counts and the costs of insurance claims for each of these strata and overall are then estimated. A second method models the probability that an insurance claim is related to speeding or impaired driving using logistic regression and uses this to estimate the overall counts and the average costs of the claims. The two methods are compared and evaluated using simulation studies. RESULTS: The logistic regression model was found to be superior to the classification model for predicting insurance claim counts by category, but less efficient at predicting average claim costs. IMPACT: Having estimates of counts and costs of insurance claims related to impaired driving or speeding for all reported crash events provides a more accurate basis for policy-makers to plan changes and benefits of road safety programs.     

污染源自动监测异常数据识别规则及处理方法探索

基于大量污染源自动监测数据的特征分析与异常原因解析,探索建立针对自动监测异常数据的识别规则与标志处理方法,并通过模型训练实现了异常数据的自动标志.经实例验证,该方法可识别异常偏高、异常偏低、异常为0、迟滞不变、逻辑错误等5种类型的异常数据,按照数据有效性及异常原因进行标志处理,可以为后续数据分析及各类模型训练提供数据基...     

建设项目竣工环保验收监测中影响数据质量因素分析

分析了建设项目竣工环境保护验收监测中常见的一些数据质量问题,通过实例对产生监测数据质量问题的原因进行了分析,并探讨了如何使监测数据反映验收监测期间的排污实态。     

以空气和废气中颗粒物和SO2监测为例分析便携式监测设备进行环境执法的认证体系及方法支撑

在中国,快速有效的环境监测执法需求越来越急迫,特别是在出现疫情与地质灾害等特殊时期,便携式快速监测仪器能更好地保证执法的时效性,但应用上却在执法环节一直受到监测数据合法性及标准方法等问题的困扰。笔者首先采用关键词频统计法研究了便携式环境监测设备相关领域的研究热点,在此基础上基于执法机构实践,调研了解了中国现行常规环境监测仪器设备质控和认证流程,指出便携监测与常规流程不匹配之处,以空气和废气中颗粒物和SO₂监测为例系统梳理了方法标准、质控、论证等内容,分析论证便携式设备在环境执法中数据有效性的问题,并针对便携监测设备的型式批准、强检、监测方法和数据合法性认定等问题提出具体建议。     

基于DEA理论的中国区域环境效率分析

利用数据包络分析(DEA)模型对中国大陆31个省市区的环境效率进行总体分析与评价,并利用Tobit回归模型分析环境效率的影响因素.结果表明,我国区域环境效率总体水平比较低,但环境效率正逐年好转.根据经济与环境的协调程度可以将全国划分为生态平衡区、优化发展区和集约发展区3类环境-经济功能区.人均GDP、产业结构、城市化率、生产技术水平等都是影响环境效率的重要因素,其中人均GDP、第三产业比重与环境效率呈显著正相关,城市化率和单位GDP能耗与环境效率呈弱负相关.     

Renewable energy,non-renewable energy and sustainable development

The purpose of the present study is to analyse the effects of renewable energy and non-renewable energy on sustainable development. This study is pioneering in this respect because it analyses the effect of renewable energy on adjusted net savings, which is a good sustainable development variable. For this purpose, the data of 40 developed and 73 developing countries were included. According to the estimation results obtained in the study, renewable energy has a positive and statistically significant effect on sustainable development both in developed countries and in developing countries. The impact of renewable energy on sustainable development is greater than the impact of non-renewable energy. In this respect, as the renewable energy amount increases, the level of sustainable development increases. According to these results, the fact that countries use renewable energy more than non-renewable energy sources is extremely important in terms of making progress towards sustainability of development and the 2030 Sustainable Development Goals.     

Using medico-legal data to investigate fatal older road user crash circumstances and risk factors

Objective: This study used medico-legal data to investigate fatal older road user (ORU, aged 65 years and older) crash circumstances and risk factors relating to 4 key components of the Safe System approach (e.g., roads and roadsides, vehicles, road users, and speeds) to identify areas of priority for targeted prevention activity.

Method: The Coroners' Court of Victoria's (CCOV) Surveillance Database was searched to identify and describe the frequency and rate per 100,000 population of fatal ORU crashes in the Australian state of Victoria for 2013–2014. Information relating to the deceased ORU, crash characteristics and circumstances, and risk factors was extracted and analyzed.

Results: One hundred and thirty-eight unintentional fatal ORU crashes were identified in the CCOV Surveillance Database. Of these fatal ORU crashes, most involved older drivers (44%), followed by older pedestrians (32%), older passengers (17%), older pedal cyclists (4%), older motorcyclists (1%), and older mobility scooter users (1%). The average annual rate of fatal ORU crashes per 100,000 population was 8.1 (95% confidence interval [CI], 6.0–10.2). In terms of the crash characteristics and circumstances, most fatal ORU crashes involved a counterpart (98%), of which the majority were passenger cars (50%) or fixed/stationary objects (25%), including trees (46%) or embankments (23%). In addition, most fatal ORU crashes occurred close to home (73%), on-road (87%), on roads that were paved (94%), on roads with light traffic volume (37%), and during low-risk conditions: between 12 p.m. and 6 p.m. (44%), on weekdays (80%), during daylight (75%), and under dry/clear conditions (81%). Road user (RU) error was identified by the police and/or the coroner for the majority of fatal crashes (55%), with a significant proportion of deceased ORUs deemed to have failed to yield (54%) or misjudged (41%).

Conclusions: RU error was the most significant factor identified in fatal ORU crashes, which suggests that there is a limited capacity of the road system to fully accommodate RU errors. Initiatives related to safer roads and roadsides, vehicles, speed zones, as well as behavioral approaches are key areas of priority for targeted activity to prevent fatal ORU crashes in the future.     

灾害多发地域社会关系网络建构路径的实证研究——以云南省大关县翠华镇为例

为了更好地构建典型灾害多发地域的社会关系网络,进而为相关应急管理工作提供支撑,采用灾害多发地域档案数据与问卷数据验证相结合的方法,提出灾害多发地域社会关系网络的建构路径;选取位于古滑坡带上的云南省大关县翠华镇为例进行说明,通过地理信息系统（Arcgis）分析当地档案数据与问卷获取数据的空间对象分布特征,并以问卷调查的局部数据验证相关档案数据的可靠性,最后,在翠华镇社会关系网络基础上,分析该灾害多发地域的应急预警信息传播特点,提出“分区域预警,以户为单位传播预警信息“的措施建议。研究结果表明:通过档案数据与问卷数据相结合方法构建灾害多发地域社会关系网络的方法可行,能够为相关应急管理措施提供参考和支撑。     

基于电网防台抗台系统的应急主题数据仓库分析与设计

为解决电网防台抗台过程中缺少应急辅助支持的问题,提出基于现有电网防台抗台系统中的业务数据,采用星型结构分析与设计“台风气象灾情”、“电网因灾（台风）损失”、“电网因灾（台风）应急资源投入”等应急主题数据仓库,充分利用、开发相关的数据探查与ETL工具实现相关的数据集成,构建相关应急主题下的多维数据模型,并开展联机分析处理（OLAP）研究工作,为相关企业和部门开展电网应急管理工作提供应急辅助支持。     

基于大数据的特种设备宏观安全风险预警方法研究

特种设备监管机构在监督检验过程中积累了大量数据资料,为充分挖掘其中的潜在价值,增强监管针对性,提高检验效率,应用并优化关联规则挖掘、社区发现、可视化等数据挖掘技术,构建1种宏观安全风险预警方法。该方法以特种设备安全监督检验大数据为基础,通过挖掘单台设备微观因素间的关联关系,实现整类特种设备宏观安全风险的识别与预警;以2008—2016年全国长管拖车检验数据为例,进行应用实践分析。研究结果表明:该方法可以对区域范围、缺陷类别等多种宏观指标进行预警,指导针对性监管与检验。