Injury severity in delivery-motorcycle to vehicle crashes in the Seoul metropolitan area

More than 56% of motorcycles in Korea are used for the purpose of delivering parcels and food. Since such delivery requires quick service, most motorcyclists commit traffic violations while delivering, such as crossing the centerline, speeding, running a red light, and driving in the opposite direction down one-way streets. In addition, the fatality rate for motorcycle crashes is about 12% of the fatality rate for road traffic crashes, which is considered to be high, although motorcycle crashes account for only 5% of road traffic crashes in South Korea. Therefore, the objective of this study is to analyze the injury severity of vehicle-to-motorcycle crashes that have occurred during delivery. To examine the risk of different injury levels sustained under all crash types of vehicle-to-motorcycle, this study applied an ordered probit model. Based on the results, this study proposes policy implications to reduce the injury severity of vehicle-to-motorcycle crashes during delivery.     

Investigating the influence of curbs on single-vehicle crash injury severity utilizing zero-inflated ordered probit models

The severity of traffic-related injuries has been studied by many researchers in recent decades. However, previous research has seldom accounted for the effects of curbed outside shoulders on traffic-related injury severity. This study applies the zero-inflated ordered probit (ZIOP) model to evaluate the influences of curbed outside shoulders, speed limit change, as well as other traditional factors on the injury severity of single-vehicle crashes. Crash data from 2003 to 2007 in the Illinois Highway Safety Database were employed in this study.     

Usefulness of Plasma YKL-40 in Management of Community-Acquired Pneumonia Severity in Patients

Plasma YKL-40 level has been reported as playing a significant role in community-acquired pneumonia (CAP). However, the correlation between plasma level of YKL-40 and the severity of CAP has not been reported. This study identifies the relationship between plasma level changes of the YKL-40 gene in adult patients hospitalized with CAP. The ELISA was used to measure the plasma YKL-40 level from 61 adult CAP patients before and after antibiotic treatment and from 60 healthy controls. The plasma YKL-40 levels were significantly increased in patients with CAP compared to normal controls. Moreover, the plasma concentration of YKL-40 correlated with the severity of CAP based on the pneumonia severity index (PSI) score (r = 0.630, p < 0.001), the CURB-65 (confusion, uremia, respiratory rate, BP, age 65 years) score (r = 0.640, p < 0.001), the Acute Physiology And Chronic Health Evaluation II (APACHE II) score (r = 0.539, p < 0.001) and length of hospital stay (r = 0.321, p = 0.011), respectively. In conclusion, plasma YKL-40 may play a role in the diagnosis and clinical assessment of CAP severity, which could potentially guide the development of treatment strategies.     

A two-stage mining framework to explore key risk conditions on one-vehicle crash severity

This paper proposes a two-stage mining framework to explore the key risk conditions that may have contributed to the one-vehicle crash severity in Taiwan's freeways. In the first stage, a genetic mining rule (GMR) model is developed, using a novel stepwise rule-mining algorithm, to identify the potential risk conditions that best elucidate the one-vehicle crash severity. In the second stage, a mixed logit model is estimated, using the antecedent part of the mined-rules as explanatory variables, to test the significance of the risk conditions. A total of 5563 one-vehicle crash cases (226 fatalities, 1593 injuries and 3744 property losses) occurred in Taiwan's freeways over 2003–2007 are analyzed. The GMR model has mined 29 rules for use. By incorporating these 29 mined-rules into a mixed logit model, we further identify one key safe condition and four key risk conditions leading to serious crashes (i.e., fatalities and injuries). Each key risk condition is discussed and compared with its adjacent rules. Based on the findings, some countermeasures to rectify the freeway's serious one-vehicle crashes are proposed.     

The safety of urban cycle tracks: A review of the literature

Cycling has to be a safe activity, and perceived as such, if bicycle trips by all populations are to increase and the public health benefits are to be realized. A key characteristic of developed countries with a high cycling mode share is their provision of cycle tracks – separated bikeways along city streets – on major routes. This literature review therefore sought to examine studies of cycle tracks from different countries in order elucidate the safety of these facilities relative to cycling in the street and to point to areas where further research is needed. The review indicates that one-way cycle tracks are generally safer at intersections than two-way and that, when effective intersection treatments are employed, constructing cycle tracks on busy streets reduces collisions and injuries. The evidence also suggests that, when controlling for exposure and including all collision types, building one-way cycle tracks reduces injury severity even when such intersection treatments are not employed. However, the extent of this effect has not been well examined, as very few studies both look at severity and control for exposure. Future studies of the safety of cycle tracks and associated intersection treatments should focus foremost on examining injury severity, while controlling for exposure. In the U.S., where the obesity epidemic and its health consequences and costs are well documented, the benefits of increased cycling should be a focus of research and policy development in order to provide the infrastructure needed to attract people to cycling while minimizing injuries.     

Evaluating alternate discrete choice frameworks for modeling ordinal discrete variables

There is considerable debate on the appropriate discrete choice framework for examining injury severity. Researchers in the safety field have employed ordered and unordered frameworks for examining the various factors influencing injury severity. The objective of the current study is to investigate the performance of the ordered and unordered response frameworks at a fundamental level. Towards this end, we undertake a comparison of the alternative frameworks by estimating ordered and unordered response models using data generated through ordered, unordered data and a combination of ordered and unordered data generation processes. We also examine the influence of aggregate sample shares on the appropriateness of the modeling framework. Rather than be limited by the aggregate sample shares in an empirical dataset, simulation allows us to explore the influence of a broad spectrum of sample shares on the performance of ordered and unordered frameworks. We also extend the data generation process based analysis to under reported data and compare the performance of the ordered and unordered response frameworks. Finally, based on these simulation exercises, we provide a discussion of the merits of the different approaches. The results clearly highlight the emergence of the generalized ordered logit model as a true equivalent ordered response model to the multinomial logit model for ordinal discrete variables.     

Fault Diagnosis of an Induction Generator in a Wind Energy Conversion System Using Signal Processing Techniques

In this article, a contribution to fault diagnosis of an induction machine in a wind energy conversion system in closed-loop operation using a combination between short-time Fourier transform and discrete wavelet transform algorithms is proposed. An on-line fault diagnostic technique based on stator currents analysis of the squirrel-cage induction generator is proposed to detect and localize abnormal electrical conditions that indicate, or may lead to, a stator or rotor failure in a squirrel-cage induction generator. This technique also permits identification of a fault severity factor and consequently helps to determine the best choice of corrective maintenance. Furthermore, a generalized model of the squirrel-cage induction generator is used to simulate both the rotor and stator faults, taking iron losses, main flux, and cross-flux saturation into account. The efficiency of diagnostic procedure in closed-loop operation of the wind energy conversion system under non-stationary operating conditions is illustrated with simulation results.     

HTR-PM反应堆保护系统软件可靠性增长模型的研究

研究数字化反应堆保护系统软件的可靠性对提高保护系统的整体可靠性具有重要的意义。本文在分析、整理HTR-PM保护系统软件开发过程中记录的测试数据基础上,研究并提出了基于错误严重程度的软件可靠性模型。软件测试过程中不同严重程度的错误其检测难度不同,导致检测率随时间的变化趋势不同,本文提出了严重程度比函数的概念以表述这一现象,并对不同严重程度错误的检测数据分别建模,使软件可靠性模型的预测结果更具有工程应用价值。     

Identifying significant predictors of injury severity in traffic accidents using a series of artificial neural networks

Understanding the circumstances under which drivers and passengers are more likely to be killed or more severely injured in an automobile accident can help improve the overall driving safety situation. Factors that affect the risk of increased injury of occupants in the event of an automotive accident include demographic or behavioral characteristics of the person, environmental factors and roadway conditions at the time of the accident occurrence, technical characteristics of the vehicle itself, among others. This study uses a series of artificial neural networks to model the potentially non-linear relationships between the injury severity levels and crash-related factors. It then conducts sensitivity analysis on the trained neural network models to identify the prioritized importance of crash-related factors as they apply to different injury severity levels. In the process, the problem of five-class prediction is decomposed into a set of binary prediction models (using a nationally representative sample of 30358 police-recorded crash reports) in order to obtain the granularity of information needed to identify the "true" cause and effect relationships between the crash-related factors and different levels of injury severity. The results, mostly validated by the findings of previous studies, provide insight into the changing importance of crash factors with the changing injury severity levels.     

The roles of exposure and speed in road safety analysis

Speed is a determining factor in road safety analysis. It is generally believed that an increase in speed harms road safety. However, it can also be argued that driving at high speed reduces the length of time exposure and thus the likelihood of a crash. It is therefore critical to clarify the roles that exposure and speed play in road safety analysis. This study evaluates the relationship between speed and crash risk with respect to distance and time exposure, using disaggregated crash and speed data collected from 112 road segments in Hong Kong. A joint probability model based on a full Bayesian method is applied simultaneously to model crash occurrence and crash severity. In addition, we consider the explanatory variables, including road design, weather conditions, and temporal distribution, in the proposed crash prediction model. The results indicate that average speed plays a significant role in crash risk, despite opposing correlations with respect to distance and time exposure; the correlation between speed and crash risk is positive when distance exposure is considered, but negative when time exposure is used. However, in both cases, speed is positively associated with the injury severity.