Parametric and Non-Parametric Analyses for Pedestrian Crash Severity Prediction in Great Britain

The study aims to investigate the factors that are associated with fatal and severe vehicle– pedestrian crashes in Great Britain by developing four parametric models and five non-parametric tools to predict the crash severity. Even though the models have already been applied to model the pedestrian injury severity, a comparative analysis to assess the predictive power of such modeling techniques is limited. Hence, this study contributes to the road safety literature by comparing the models by their capabilities of identifying the significant explanatory variables, and by their performances in terms of the F-measure, the G-mean, and the area under curve. The analyses were carried out using data that refer to the vehicle–pedestrian crashes that occurred in the period of 2016–2018. The parametric models confirm their advantages in offering easy-to-interpret outputs and understandable relations between the dependent and independent variables, whereas the non-parametric tools exhibited higher classification accuracies, identified more explanatory variables, and provided insights into the interdependencies among the factors. The study results suggest that the combined use of parametric and non-parametric methods may effectively overcome the limits of each group of methods, with satisfactory prediction accuracies and the interpretation of the factors contributing to fatal and serious crashes. In the conclusion, several engineering, social, and management pedestrian safety countermeasures are recommended

Catalytic activity of DBTDL in polyurethane formation

330-333Polyurethane has been prepared from neopentyl glycol (NPG) and toluene diisocyanate (TDI) using dibutyltin dilaurate (DBTDL) catalyst. The rates of both the uncatalyzed and catalyzed polyurethane formation reactions were investigated. In case of catalyzed reaction the sequence of addition of catalyst was also investigated and it was observed that the activity of the catalyst is dependent on the sequence of addition of DBTDL catalyst. Titrimetric method was used for the determination of residual isocyanate content. Highest reaction rate was observed when the catalyst was added after the addition of TDI to diol and lowest rate was observed when no catalyst was used. It was observed that when the catalyst was added to NPG followed by TDI addition the rate of reaction was slower compared to that when catalyst was added to the mixture of diol and TDI. 1H NMR and IR study of the complex formation between the tin catalyst and diol was evaluated to account for the lower reaction rate

G-AUC: An improved metric for classification model selection

The performance of classification models is often measured using the metric, area under the curve (AUC). The non-parametric estimate of this metric only considers the ranks of the test instances and fails to consider the predicted scores of the model. Consequently, not all the valuable information about the model’s output is utilized. To address this issue, the present paper introduces a new metric, called Gamma AUC (G-AUC) that can take into account both ranks as well as scores. The parameter G tackles the problem of overfitting scores into the metric. To validate the proposed metric, we tested it on 20 UCI datasets with 10 state-of-the-art models. Out of all the values of the parameter G that we tested, four of them got p-value less than 0.05 for the alternative hypothesis that, on the training sets, G-AUC has a greater correlation than AUC itself, with AUC on test sets. Furthermore, for all values of G considered, G-AUC always won majority of the times than AUC for selecting better models

Parametric and Non-Parametric Analyses for Pedestrian Crash Severity Prediction in Great Britain

The study aims to investigate the factors that are associated with fatal and severe vehicle–pedestrian crashes in Great Britain by developing four parametric models and five non-parametric tools to predict the crash severity. Even though the models have already been applied to model the pedestrian injury severity, a comparative analysis to assess the predictive power of such modeling techniques is limited. Hence, this study contributes to the road safety literature by comparing the models by their capabilities of identifying the significant explanatory variables, and by their performances in terms of the F-measure, the G-mean, and the area under curve. The analyses were carried out using data that refer to the vehicle–pedestrian crashes that occurred in the period of 2016–2018. The parametric models confirm their advantages in offering easy-to-interpret outputs and understandable relations between the dependent and independent variables, whereas the non-parametric tools exhibited higher classification accuracies, identified more explanatory variables, and provided insights into the interdependencies among the factors. The study results suggest that the combined use of parametric and non-parametric methods may effectively overcome the limits of each group of methods, with satisfactory prediction accuracies and the interpretation of the factors contributing to fatal and serious crashes. In the conclusion, several engineering, social, and management pedestrian safety countermeasures are recommended

Parametric and Non-Parametric Analyses for Pedestrian Crash Severity Prediction in Great Britain

The study aims to investigate the factors that are associated with fatal and severe vehicle–pedestrian crashes in Great Britain by developing four parametric models and five non-parametric tools to predict the crash severity. Even though the models have already been applied to model the pedestrian injury severity, a comparative analysis to assess the predictive power of such modeling techniques is limited. Hence, this study contributes to the road safety literature by comparing the models by their capabilities of identifying the significant explanatory variables, and by their performances in terms of the F-measure, the G-mean, and the area under curve. The analyses were carried out using data that refer to the vehicle–pedestrian crashes that occurred in the period of 2016–2018. The parametric models confirm their advantages in offering easy-to-interpret outputs and understandable relations between the dependent and independent variables, whereas the non-parametric tools exhibited higher classification accuracies, identified more explanatory variables, and provided insights into the interdependencies among the factors. The study results suggest that the combined use of parametric and non-parametric methods may effectively overcome the limits of each group of methods, with satisfactory prediction accuracies and the interpretation of the factors contributing to fatal and serious crashes. In the conclusion, several engineering, social, and management pedestrian safety countermeasures are recommended

Measurement and Modeling of Job Stress of Electric Overhead Traveling Crane Operators

Background: In this study, the measurement of job stress of electric overhead traveling crane operators and quantification of the effects of operator and workplace characteristics on job stress were assessed. Methods: Job stress was measured on five subscales: employee empowerment, role overload, role ambiguity, rule violation, and job hazard. The characteristics of the operators that were studied were age, experience, body weight, and body height. The workplace characteristics considered were hours of exposure, cabin type, cabin feature, and crane height. The proposed methodology included administration of a questionnaire survey to 76 electric overhead traveling crane operators followed by analysis using analysis of variance and a classification and regression tree. Results: The key findings were: (1) the five subscales can be used to measure job stress; (2) employee empowerment was the most significant factor followed by the role overload; (3) workplace characteristics contributed more towards job stress than operator's characteristics; and (4) of the workplace characteristics, crane height was the major contributor. Conclusion: The issues related to crane height and cabin feature can be fixed by providing engineering or foolproof solutions than relying on interventions related to the demographic factors