A machine-learning method for improving crash injury severity analysis: a case study of work zone crashes in Cairo,Egypt

Abstract

The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequently lead to biased conclusions and poorly designed countermeasures. This is particularly true for imbalanced data where the number of samples in one class far outnumber the other. To improve the classification performance of the injury severity, the paper presents a robust noise filtering technique to deal with the mislabels in the imbalanced crash dataset using the advanced machine learning algorithms. We examine the state-of-the-art filtering algorithms, including Iterative Noise Filtering based on the Fusion of Classifiers (INFFC), Iterative Partitioning Filter (IPF), and Saturation Filter (SatF). In the case study of Cairo (Egypt), the empirical results show that: (1) the mislabels in crash data significantly influence the injury severity predictions, and (2) the proposed M-IPF filter outperforms its counterparts in terms of the effectiveness and efficiency in eliminating the mislabels in crash data. The test results demonstrate the efficacy of the M-IPF in handling the data noise and mitigating the impacts thereof.     

The COVID-19 crisis: A public choice view

Many observers have been puzzled by the sight of otherwise freedom-loving citizens consenting to the stripping of their civil rights and the massive budgetary expansion of their governments in response to the COVID-19 pandemic. Conversely, governments who ‘kept their cool’ such as those of Brazil and Sweden were heavily criticised by the Western media. Adopting James Buchanan's contractarian approach, this article seeks to model how the interplay between citizens and their government is affected by a health crisis. Citizens' increased willingness to pay for improved control of risks is found to play a major role.     

基于CEL法的故障齿轮热流固耦合有限元分析

为探究风电机组传动系统中齿轮不同故障热流固耦合下应力演化规律,利用ABAQUS软件,采用CEL有限元法对啮合齿轮进行数值模拟。研究了温度场对齿轮啮合最大接触应力的影响以及热流固耦合下不同损坏程度齿轮在齿宽、齿厚方向最大接触应力值的演化规律。结果表明：引入温度场后不同阶段啮合齿轮的最大接触应力分别增长了20.63%,41.28%,6.13%,说明热力场的介入对应力结果有重要影响;点蚀孔边缘接触应力明显大于正常部位且会扩展,损坏程度越大接触应力值越大;断齿故障在断裂位置接触应力会激增,并且越靠近断裂端接触应力越大且断裂深度越大,最大接触应力也越大;在不同断齿工况下,沿齿厚方向的应力变化趋势一致,断裂程度与齿厚方向上整体应力值呈正相关。CEL有限元法适用于齿轮热流固耦合分析,可以较好地模拟故障齿轮运行状态,为齿轮模拟仿真提供借鉴与指导。     

发动机汽缸压力测试方法探析

发动机的汽缸压力是评价发动机动力性能的一项重要指标,在对发动机进行检查、评价和维修时需要经常测试。文章从汽车实践技术的角度阐述了发动机汽缸压力的测试仪器、测试方法与技巧,并在理论上对测试的数据和测试误差加以科学系统地分析,提出解决办法,为汽车发动机的技术维修提供科学合理的依据。     

财务重述、管理层权力与股价崩盘风险：来自中国证券市场的经验证据

股市震荡引发投资者和监管层对股价崩盘风险的关注。从财务重述背后所反映的财务信息质量低下和公司治理失效出发,探讨其对股价崩盘风险的影响,结合管理层权力这一影响组织行为和产出能力的代理人特征,探讨其对财务重述与股价崩盘风险之间关系的影响。研究结果表明：相比未发生财务重述的公司,发生了财务重述的公司的股价崩盘风险明显更高;进一步纳入代理人特征———管理层权力后,发现代理人的这一特征对上述关系有明显的促进作用。     

Auditor Quality,IFRS Adoption,and Stock Price Crash Risk: Korean Evidence

This paper investigates the relationship among auditor quality, International Financial Reporting Standard (IFRS) adoption and stock price crash risk. Using 657 unique listed companies spanning 2002–2014 in Korea, this study finds that stock price crash risk decreases, especially for firms using Big 4 auditors, after IFRS adoption in Korea. Stock price crash risk decreases for a firm included in Big 4 auditors, while it does not increase for a firm excluded from Big 4 auditors after IFRS adoption. Finally, this study finds that Big 4 auditor decreases stock price crash risk only when the firm size is above-median.     

股价暴跌、投资者认知与信息透明度

本文基于Merton(1987)不完全信息市场下的认知风险假说,研究了我国股票市场个股股价暴跌与投资者认知风险的关系。我们发现投资者认知风险越大,股价暴跌的风险越大,股价暴跌造成的损失也越大。进一步我们研究了影响认知风险的因素,发现在控制住经营风险和异质信念后,信息披露不透明是影响投资者认知风险的重要因素。稳健性检验的结果表明我们的发现并不受所使用的数据频率的影响。     

论暖气罩对室内温度及计量供热的影响

本文通过对暖气罩这种散热设备的认识,了解它的工作原理、性能和特点,并深入论述了其对室内温度及计量供热的影响。使更多的人对室内暖气罩散热设备的散热过程有了系统而详细的了解,也避免了许多人胡乱改装和加装暖气罩的错误想法,为暖气罩散热设备的维修和维护打开了方便之门。     

客户集中度与股价崩盘风险：火上浇油还是扬汤止沸*

客户是企业重要的利益相关者,重要客户是否对供应商的经营决策、财务决策以及风险产生影响是一个重要的理论和实务问题。本文从股价崩盘风险的角度研究客户集中度的影响。研究结果表明,客户集中度越高,公司股价崩盘风险越低。这表明,整体上客户集中度有助于股价崩盘风险的缓解。进一步研究发现,客户集中度对股价崩盘风险的治理作用主要源于供应链整合而非客户议价能力。这表明,客户集中有利于公司与客户之间供应链整合,进而降低公司的经营风险和信息披露风险,最终缓解股价崩盘风险。