scholarly journals A Bayesian network based study on determining the relationship between job stress and safety climate factors in occurrence of accidents

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Amir Hossein Khoshakhlagh ◽  
Saeid Yazdanirad ◽  
Masoud Motalebi Kashani ◽  
Elham Khatooni ◽  
Yaser Hatamnegad ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Job Stress ◽  
Network Model ◽  
Work Experience ◽  
Safety Climate ◽  
Occupational Accidents ◽  
Climate Factors ◽  
Occurrence Probability ◽  
Bayesian Network Model ◽  
The Relationship

Abstract Background Job stress and safety climate have been recognized as two crucial factors that can increase the risk of occupational accidents. This study was performed to determine the relationship between job stress and safety climate factors in the occurrence of accidents using the Bayesian network model. Methods This cross-sectional study was performed on 1530 male workers of Asaluyeh petrochemical company in Iran. The participants were asked to complete the questionnaires, including demographical information and accident history questionnaire, NIOSH generic job stress questionnaire, and Nordic safety climate questionnaire. Also, work experience and the accident history data were inquired from the petrochemical health unit. Finally, the relationships between the variables were investigated using the Bayesian network model. Results A high job stress condition could decrease the high safety climate from 53 to 37% and increase the accident occurrence from 72 to 94%. Moreover, a low safety climate condition could increase the accident occurrence from 72 to 93%. Also, the concurrent high job stress and low safety climate could raise the accident occurrence from 72 to 93%. Among the associations between the job stress factor and safety climate dimensions, the job stress and worker’s safety priority and risk non-acceptance (0.19) had the highest mean influence value. Conclusion The adverse effect of high job stress conditions on accident occurrence is twofold. It can directly increase the accident occurrence probability and in another way, it can indirectly increase the accident occurrence probability by causing the safety climate to go to a lower level.

scholarly journals Predicting the risk of GenX contamination in private well water using a machine-learned Bayesian network model

2021 ◽  
pp. 125075
Author(s):  
Javad Roostaei ◽  
Sarah Colley ◽  
Riley Mulhern ◽  
Andrew A. May ◽  
Jacqueline MacDonald Gibson
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Well Water ◽  
Bayesian Network Model

scholarly journals Impact Mechanism of the Ecological Vulnerability of Highly Developed Islands Based on the Bayesian Network Model—Applied to the Changshan Islands

2021 ◽  
Vol 18 (8) ◽  
pp. 4150
Author(s):  
Keyu Qin ◽  
Haijun Huang ◽  
Jingya Liu ◽  
Liwen Yan ◽  
Yanxia Liu ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Geographical Information ◽  
Global Changes ◽  
Bayesian Network Model ◽  
Island Ecosystems ◽  
Impact Mechanism ◽  
The North ◽  
Ecological Vulnerability ◽  
The Impact

Islands are one of the most sensitive interfaces between global changes and land and sea dynamic effects, with high sensitivity and low stability. Therefore, under the dynamic coupling effect of human activities and frequent natural disasters, the vulnerability of the ecological environment of islands shows the characteristics of complexity and diversity. For the protection of island ecosystems, a system for the assessment of island ecosystems and studies on the mechanism of island ecological vulnerability are highly crucial. In this study, the North and South Changshan Islands of China were selected as the study area. Considering various impact factors of island ecological vulnerability, the geographical information systems (GIS) spatial analysis, field surveys, data sampling were used to evaluate island ecological vulnerability. The Bayesian network model was used to explore the impact mechanism of ecological vulnerability. The results showed that the ecological vulnerability of the North Changshan Island is higher than that of the South Changshan Island. Among all the indicators, the proportion of net primary productivity (NPP) and the steep slope has the strongest correlation with ecological vulnerability. This study can be used as references in the relevant departments to formulate management policies and promote the sustainable development of islands and their surrounding waters

scholarly journals Misper-Bayes: A Bayesian Network Model for Missing Person Investigations

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Denis Reilly ◽  
Mark Taylor ◽  
Paul Fergus ◽  
Carl Chalmers ◽  
Steven Thompson
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Bayesian Network Model

scholarly journals Exploring the Relationship between Safety Climate and Worker Safety Behavior on Building Construction Sites in Taiwan

2021 ◽  
Vol 13 (6) ◽  
pp. 3326
Author(s):  
Wei Tong Chen ◽  
Hew Cameron Merrett ◽  
Ying-Hua Huang ◽  
Theresia Avila Bria ◽  
Ying-Hsiu Lin
Keyword(s):  
Safety Climate ◽  
Organizational Factors ◽  
Safety Training ◽  
Building Construction ◽  
Construction Workers ◽  
Occupational Accidents ◽  
Successful Implementation ◽  
Construction Sites ◽  
Safety Behavior ◽  
The Relationship

Construction occupational accidents are often attributed to workers’ having an insufficient perception of how their actions influence safety in the construction site. This research explores the relationship between safety climate (SC) and personnel safety behavior (SB) of construction workers operating on building construction sites in Taiwan. The study discovered a significant positive relationship between SC and SB of Taiwan’s building construction sites, and in turn SC level had a positive impact on SB participation and overall safety perceptions. The higher the SC cognition of Taiwan’s building construction workers, the better the performance of SB was found to be. The dimension of "safety commitment and safety training" had the greatest relationship with SB. Safety training also had a deep impact on the cognition of SB. Therefore, the organizational culture and attitudes to safety coupled with the successful implementation of safety education and training can effectively enhance SC and worker SB on building construction sites in Taiwan, thereby potentially reducing the impacts of the underlying organizational factors behind safety related incidents.

Probabilistic Model-Based Fault Diagnosis of the Rotor System

2007 ◽  
Author(s):  
Jiye Shao ◽  
Rixin Wang ◽  
Jingbo Gao ◽  
Minqiang Xu
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Network Model ◽  
Rotating Machinery ◽  
Rotor System ◽  
Bayesian Network Model ◽  
Diagnosis System ◽  
Model Based ◽  
Core Components ◽  
Fault Diagnosis System

The rotor is one of the most core components of the rotating machinery and its working states directly influence the working states of the whole rotating machinery. There exists much uncertainty in the field of fault diagnosis in the rotor system. This paper analyses the familiar faults of the rotor system and the corresponding faulty symptoms, then establishes the rotor’s Bayesian network model based on above information. A fault diagnosis system based on the Bayesian network model is developed. Using this model, the conditional probability of the fault happening is computed when the observation of the rotor is presented. Thus, the fault reason can be determined by these probabilities. The diagnosis system developed is used to diagnose the actual three faults of the rotor of the rotating machinery and the results prove the efficiency of the method proposed.

Corrosion threat assessment of crude oil flow lines using Bayesian network model

2015 ◽  
Vol 50 (3) ◽  
pp. 236-247 ◽  
Author(s):  
G. Koch ◽  
F. Ayello ◽  
V. Khare ◽  
N. Sridhar ◽  
A. Moosavi
Keyword(s):  
Bayesian Network ◽  
Crude Oil ◽  
Network Model ◽  
Threat Assessment ◽  
Bayesian Network Model ◽  
Flow Lines ◽  
Oil Flow
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