Development of driving fatigue strain index to analyze risk levels of driving activity

2017 ◽  
Author(s):  
Mohammad Firdaus Ani ◽  
Mohamad Minhat ◽  
Wan Hasrulnizzam Wan Mahmood ◽  
Seri Rahayu Kamat ◽  
Minoru Fukumi
Keyword(s):  
Strain Index ◽  
Risk Levels ◽  
Driving Fatigue

Development of driving fatigue strain index using fuzzy logic to analyze risk levels of driving activity

2019 ◽  
Vol 14 (12) ◽  
pp. 1764-1771
Author(s):  
Mohammad Firdaus Ani ◽  
Minoru Fukumi ◽  
Seri RahayuKamat ◽  
Mohamad Minhat ◽  
Kalthom Husain
Keyword(s):  
Fuzzy Logic ◽  
Strain Index ◽  
Risk Levels ◽  
Driving Fatigue

Prolonged Standing Strain Index (PSSI): A Proposed Method to Quantify Risk Levels of Standing Jobs in Industrial Workplaces

2012 ◽  
Vol 433-440 ◽  
pp. 497-506 ◽  
Author(s):  
Halim Isa ◽  
A.R. Omar
Keyword(s):  
Risk Factors ◽  
Indoor Air ◽  
Automotive Industry ◽  
Standing Position ◽  
Whole Body ◽  
Strain Index ◽  
Prolonged Standing ◽  
Risk Levels ◽  
Working Posture ◽  
Metal Stamping

Industrial occupations such as metal stamping workers, electronics parts assembly operators, automotive industry welders, and lathe operators perform their jobs in standing position for a long period of time. Prolonged standing can contribute to discomfort, and muscle fatigue particularly in the back and legs. This study developed prolonged standing strain index (PSSI) to quantify risk levels due to standing jobs and propose recommendations to minimize the risk levels. Risk factors associated with standing jobs such as working posture, muscles activity, standing duration, holding time, whole-body vibration, and indoor air quality were considered as basis to develop the PSSI. All risk factors are assigned with multipliers, and the PSSI is the product of these multipliers. Based on PSSI, recommendations were proposed, however, extensive studies are required to validate their effectiveness.

Denosumab Curbed Fractures Equally at All Risk Levels

2011 ◽  
Vol 41 (7) ◽  
pp. 50
Author(s):  
MIRIAM E. TUCKER
Keyword(s):  
Risk Levels

The prospects of occupational risk management during reforms of regulatory legislation basis

2019 ◽  
pp. 39-44 ◽  
Author(s):  
Vadim B. Alekseev ◽  
Nina V. Zaitseva ◽  
Pavel Z. Shur
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Social Insurance ◽  
Well Being ◽  
Occupational Risk ◽  
Risk Level ◽  
Federal Law ◽  
Work Safety ◽  
Risk Levels ◽  
Legal Principles

Despite wide legislation basis of regulating relations in work safety and workers’ health, one third of workplaces demonstrate exceeded allowable normal levels of workers’ exposure to occupational hazards and present occupational risk for health disorders.In accordance to national legislation acts, evaluation should cover factors of occupational environment and working process, and occupational risk is understood in context of mandatory social insurance. This approach has been formed due to mostly compensatory trend in legal principles of work safety in Russia by now. Implementation of new preventive concept of work safety, based on idea of risk management for workers, necessitates development of legal acts that regulate requirements to evaluation of occupational risk and its reports with consideration of changes in Federal Law on 30 March 1999 №52 FZ “On sanitary epidemiologic well-being of population”.Those acts can include Sanitary Rules and Regulations “Evaluation of occupational risk for workers’ health”, that will contain main principles of risk assessment, requirements to risk assessment, including its characteristics which can serve as a basis of categorizing the risk levels with acceptability.To standardize requirements for informing a worker on the occupational risk, the expediency is specification of sanitary rules “Notifying a worker on occupational risk”. These rules should contain requirements: to a source of data on occupational risk level at workplace, to informational content and to ways of notifying the worker. Specification and implementation of the stated documents enable to fulfil legal requirements completely on work safety — that will provide preservation and increase of efficiency in using work resources.

The impact of the ON-S1 standard on railway risk levels in Australia

2008 ◽  
Author(s):  
A.L. Aas ◽  
M. Baysari ◽  
C. Caponecchia ◽  
T. Skramstad
Keyword(s):  
Risk Levels ◽  
The Impact

scholarly journals Evaluating the Safety Risk of Rural Roadsides Using a Bayesian Network Method

2019 ◽  
Vol 16 (7) ◽  
pp. 1166 ◽  
Author(s):  
Tianpei Tang ◽  
Senlai Zhu ◽  
Yuntao Guo ◽  
Xizhao Zhou ◽  
Yang Cao
Keyword(s):  
Bayesian Network ◽  
Low Cost ◽  
Road Networks ◽  
Access Point ◽  
Safety Risk ◽  
Crash Data ◽  
Risk Levels ◽  
The Road ◽  
Run Off ◽  
Point Density

Evaluating the safety risk of rural roadsides is critical for achieving reasonable allocation of a limited budget and avoiding excessive installation of safety facilities. To assess the safety risk of rural roadsides when the crash data are unavailable or missing, this study proposed a Bayesian Network (BN) method that uses the experts’ judgments on the conditional probability of different safety risk factors to evaluate the safety risk of rural roadsides. Eight factors were considered, including seven factors identified in the literature and a new factor named access point density. To validate the effectiveness of the proposed method, a case study was conducted using 19.42 km long road networks in the rural area of Nantong, China. By comparing the results of the proposed method and run-off-road (ROR) crash data from 2015–2016 in the study area, the road segments with higher safety risk levels identified by the proposed method were found to be statistically significantly correlated with higher crash severity based on the crash data. In addition, by comparing the respective results evaluated by eight factors and seven factors (a new factor removed), we also found that access point density significantly contributed to the safety risk of rural roadsides. These results show that the proposed method can be considered as a low-cost solution to evaluating the safety risk of rural roadsides with relatively high accuracy, especially for areas with large rural road networks and incomplete ROR crash data due to budget limitation, human errors, negligence, or inconsistent crash recordings.

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