Development of a Conceptual Framework for Occupational Safety and Health in Palestinian Manufacturing Industries

Tuhul, Hanan S; El‐Hamouz, Amer; Hasan, A. Rasem; Jafar, Hanan A.

doi:10.3390/ijerph18031338

Cited by 6 publications

(6 citation statements)

References 38 publications

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“…Finally, the results are presented to customers in a way that is easy to understand (Keramati et al. , 2020; Tuhul et al. , 2021).…”

Section: Methodsmentioning

confidence: 99%

“…If they are not met, the previous operations will be carried out again. Finally, the results are presented to customers in a way that is easy to understand (Keramati et al, 2020;Tuhul et al, 2021). The quality of data mining is related to the reliability of the data technology and the quality of the data used.…”

Section: Data Mining Based On Rbf Neural Network Algorithmmentioning

confidence: 99%

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Analyzing the Internet financial market risk management using data mining and deep learning methods

Feng

Xiao-e

2021

JEIM

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PurposeTo identify and analyze the occurrence of Internet financial market risk, data mining technology is combined with deep learning to process and analyze. The market risk management of the Internet is to improve the management level of Internet financial risk, improve the policy of Internet financial supervision and promote the healthy development of Internet finance.Design/methodology/approachIn this exploration, data mining technology is combined with deep learning to mine the Internet financial data, warn the potential risks in the market and provide targeted risk management measures. Therefore, in this article, to improve the application ability of data mining in dealing with Internet financial risk management, the radial basis function (RBF) neural network algorithm optimized by ant colony optimization (ACO) is proposed.FindingsThe results show that the actual error of the ACO optimized RBF neural network is 0.249, which is 0.149 different from the target error, indicating that the optimized algorithm can make the calculation results more accurate. The fitting results of the RBF neural network and ACO optimized RBF neural network for nonlinear function are compared. Compared with the performance of other algorithms, the error of ACO optimized RBF neural network is 0.249, the running time is 2.212 s, and the number of iterations is 36, which is far less than the actual results of the other two algorithms.Originality/valueThe optimized algorithm has a better spatial mapping and generalization ability and can get higher accuracy in short-term training. Therefore, the ACO optimized RBF neural network algorithm designed in this exploration has a high accuracy for the prediction of Internet financial market risk.

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“…Finally, the results are presented to customers in a way that is easy to understand (Keramati et al. , 2020; Tuhul et al. , 2021).…”

Section: Methodsmentioning

confidence: 99%

Section: Data Mining Based On Rbf Neural Network Algorithmmentioning

confidence: 99%

Analyzing the Internet financial market risk management using data mining and deep learning methods

Feng

Xiao-e

2021

JEIM

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“…As a result, it will reduce critical safety and health risks [7]. OSHA recommends that by performing proper occupational safety analysis, many accidents and diseases can be prevented, and finally, the necessary measures of engineering control, training, personal protection, and executive instructions can be determined [8].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Critical Safety and Health Risks by Job Safety Analysis and Analytic Hierarchy Process in Industrial Printing

Badoozadeh¹,

Pouya²

2023

HDQ

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Background: Critical risks are one of the most important problems in industries, which have high costs for the industry. This study aimed to assess critical safety and health risks through job safety analysis and analytic hierarchy process in industrial printing. Materials and Methods: The present study was conducted as a descriptive and analytical in one of the printing industries in Iran, in 2020. Critical risks were collected by visiting and observing the job safety analysis checklist. Then, critical risk prioritization was performed by an analytic hierarchy process using Expert Choice software, version 11. Results: A total of 23 hazards were identified. Mechanical hazards (61%) and chemical hazards (9%) had the highest and lowest frequencies, respectively. The identified safety and health hazards included musculoskeletal disorders (MSDs) in the upper and lower back, respiratory and skin exposure to chemicals, the risk of electric shock, and mechanical hazards (hand entrapment, hand amputation, and falling objects). Conclusion: The highest priority of critical risk was related to MSDs of the upper and lower back. The next priority of critical risk was related to chemical agents, respiratory exposure to organic solvents, and dermal exposure to organic solvents.

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“…OSH is generally defined as the science of the anticipation, recognition, evaluation, and control of hazards arising in or from the workplace that could impair the health and well-being of workers, taking into account the possible impact on the surrounding communities and the general environment [17,18]. A multidisciplinary activity focuses on fostering a safe and healthy working environment [19]. Given this fact, the requirement of the Rio Declaration on healthy and productive life is particularly relevant to the work environment, and calls for occupational health action [20].…”

Section: Introductionmentioning

confidence: 99%

Occupational Health and Safety Scope Significance in Achieving Sustainability

et al. 2022

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A safe and healthy working environment is vital for overall sustainability, due to the fact that it affects opportunities of economic and social development. However, according to the International Labour Organization (ILO), despite the international commitment to Occupational Health and Safety (OSH) via the 2030’s Agenda Sustainable Development Goals (SDGs), work-related accidents are still far too common. Work-related mortality accounts for 5% of all deaths worldwide; a toll which has increased dramatically due to the COVID-19 pandemic. Yet, in the context of COVID-19, new demands on the labour market, such as teleworking, adequate protective measures, and proper use of personal protective equipment when physical presence cannot be avoided, are necessitating new approaches to ensure health and safety. Arguably, education can be viewed as a cross-cutting strategy in advance of a culture of safety for future generations, through strengthening skills and broadening knowledge. Indeed, even though education cannot be considered a panacea, related to SDG 4, which seeks to ensure inclusive and equitable quality education and promote lifelong learning opportunities for all, it can be considered a critical component to deal with OSH issues using a preventive, rather than a reactive, approach. Given this fact, European Agency for Safety and Health at Work (EU-OSHA) has stressed the prevention approach through mainstreaming OSH in education at all levels, and in all fields of vocational and academic training. Aware of the potential of universities to provide graduates the broad-based knowledge to produce labour-market skills including OSH, the aim of this study is to contribute to the discussion on mainstreaming OSH into Greek university education, using Harokopio University (HUA) as a case study. For this purpose, a web-based survey was conducted to address HUA’s students, faculty members, and staff OSH knowledge, risks awareness, and attitudes, as well as their perceptions, opinions, and beliefs about the role of OSH for academia. A statistical analysis depicted respondents’ high level of willingness to contribute to the promotion of OSH, while additional evidence suggests a considerable commitment of the respondents to participate in HUA’s OSH-related training and education.

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Development of a Conceptual Framework for Occupational Safety and Health in Palestinian Manufacturing Industries

Cited by 6 publications

References 38 publications

Analyzing the Internet financial market risk management using data mining and deep learning methods

Analyzing the Internet financial market risk management using data mining and deep learning methods

Evaluating Critical Safety and Health Risks by Job Safety Analysis and Analytic Hierarchy Process in Industrial Printing

Occupational Health and Safety Scope Significance in Achieving Sustainability

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