Safety Improvement Measures Research Articles

Automated Audible Truck-Mounted Attenuator Alerts: Vision System Development and Evaluation

Background: The rise in work zone crashes due to distracted and aggressive driving calls for improved safety measures. While Truck-Mounted Attenuators (TMAs) have helped reduce crash severity, the increasing number of crashes involving TMAs shows the need for improved warning systems. Methods: This study proposes an AI-enabled vision system to automatically alert drivers on collision courses with TMAs, addressing the limitations of manual alert systems. The system uses multi-task learning (MTL) to detect and classify vehicles, estimate distance zones (danger, warning, and safe), and perform lane and road segmentation. MTL improves efficiency and accuracy, making it ideal for devices with limited resources. Using a Generalized Efficient Layer Aggregation Network (GELAN) backbone, the system enhances stability and performance. Additionally, an alert module triggers alarms based on speed, acceleration, and time to collision. Results: The model achieves a recall of 90.5%, an mAP of 0.792 for vehicle detection, an mIOU of 0.948 for road segmentation, an accuracy of 81.5% for lane segmentation, and 83.8% accuracy for distance classification. Conclusions: The results show the system accurately detects vehicles, classifies distances, and provides real-time alerts, reducing TMA collision risks and enhancing work zone safety.

Evaluation of SSF, Roof Crush Test as an Alternative to Dynamic Rollover Test using Numerical Approach

Rollover accidents are classified into various scenarios, and with the increasing prevalence of high-centre-of-gravity (CG) vehicles in Southeast Asia (SEA) particularly in Malaysia, such as SUVs, MPVs and pickup trucks; assessing vehicle rollover risk has become critical. Even though rollover incident recorded low number of cases compared to other crash types in Malaysia, it had the highest casualty index for killed or seriously injured (KSI) and the situation induces worries because majority of the fatalities in rollover crashes among passenger vehicle occupants goes to high CG vehicle type. There are several limitations from the SEA nations to enforce costly dynamic rollover test as safety specification for SEA market requirement. Therefore, this study aims to evaluate Static Stability Factor (SSF), and roof resistance test (FMVSS 216), as an alternative to the dolly rollover test (FMVSS 208) using Finite Element Analysis (FEA). A correlated Chevrolet Silverado MY 2014 model is employed, with different SSF values representing varying levels of vehicle stability. The study evaluates peak force, peak energy absorption, and maximum intrusion during rollover simulations according to FMVSS 208 for vehicle models with different SSF values. Results indicated that vehicles with lower SSF values lead to higher energy absorption and intrusion, signifying increased rollover impact. Additionally, the article suggests that FMVSS 216 Roof Resistance Test is more severe than FMVSS 208 and vehicle rating system based on SSF value is vital for market awareness. Understanding the vehicle structural integration in rollover scenarios is essential for improving safety measures and vehicle design, especially for high-centre-of-gravity vehicles prevalent in the market.

THE TRANSFORMATIVE IMPACT OF JUDO ON ATHLETES WITH DISABILITIES: INCLUSION, ADAPTATION, AND PERFORMANCE INSIGHTS

Judo is celebrated for its inclusivity and adaptability, offering significant benefits for athletes with disabilities (PwD). It fosters physical, emotional, social, and cognitive growth, enhancing motor skills, coordination, and balance. For athletes with physical disabilities, mastering techniques such as falling safely promotes strength and agility. Moreover, engaging in judo boosts self-esteem and confidence as athletes achieve milestones like advancing through belt ranks and earning medals. The supportive environment encourages personal accomplishment and helps develop social skills through interaction with peers. Research highlights the diverse range of disabilities in judo, including visual, auditory, and intellectual impairments. Studies by Oblak et al. (2020) reveal the therapeutic benefits of judo for individuals with intellectual disabilities, emphasizing the need for more research in this area. Bocioacă and Marin (2023) explore the role of adapted judo for individuals with Autism Spectrum Disorder (ASD) and Down syndrome, demonstrating improvements in integration skills through tailored practices. Additional research by Kons et al. (2021) and Krabben et al. (2017) addresses the dynamics of Paralympic judo, revealing challenges related to classification systems for visually impaired athletes. Kons et al. (2022) identify a concerning rise in injury rates among judo athletes with disabilities, indicating the need for improved safety measures. Lastly, the comparative study of neuromuscular control by Kons et al. (2019) shows that visually impaired judokas can excel in balance and certain strength metrics. Overall, these studies underscore judo’s role in promoting physical development and social integration for PwD, while also highlighting the need for further research to ensure equitable and inclusive practices in the sport.

Boron neutron capture therapy and environmental health

Boron Neutron Capture Therapy (BNCT) is an innovative cancer treatment modality that exploits neutron beams to specifically destroy malignant cells. Despite its assuring clinical benefits, BNCT familiarizes itself with unique environmental health considerations, including radiation safety, waste supervision, and potential ecological ramifications. This review investigates these aspects by appraising radiation safety protocols, waste disposal procedures, and environmental monitoring implementations associated with BNCT facilities. Effective radiation shielding and demanding safety protocols are necessary to protect occupational and public health from potential neutron radiation exposure. Waste management implementations must inscribe the treatment, handling, and disposal of radioactive and biological waste to anticipate environmental contamination. Long-term ecological monitoring is decisive for detecting and mitigating any adverse influences on surrounding ecosystems. The review also emphasizes the significance of public awareness and education in addressing environmental health concerns. By integrating case studies from various international perspectives and recognizing research gaps, this review aims to contribute comprehensive insights into the ecological health suggestions of BNCT and propose strategies for enhancing its sustainability. The findings accentuate the need for continuous improvement in safety measures, waste management, and public engagement to corroborate that BNCT can be safely and effectively implemented in a technique that protects both human health and the environment.

Assessing Supply-Side Determinants of Passenger Satisfaction in Long-Distance Expressway Bus Services in Sri Lanka: A Case Study of Southern Expressway

The transportation sector plays a vital role in fostering economic growth, societal connectivity, and individual mobility. Long-distance bus services have emerged as a prominent mode of transportation, offering an efficient and cost-effective means of travel for both urban and intercity commuters. This study aims to comprehensively assess and elucidate the supply-side determinants that significantly impact passenger satisfaction with long-distance expressway bus service in Sri Lanka. To ensure the collection of detailed and relevant insights from frequent users of the Southern Expressway's long-distance bus services, a purposive sampling technique was employed. Data collection was guided by variables identified in the literature review, and exploratory factor analysis was used to analyse the sample data. The study identified six salient supply-side factors affecting passenger satisfaction: service quality, comfort, accessibility and convenience, safety and security, cost, and customer service. These factors explained 74% of the total variance, with service quality being the most influential, accounting for 18% of the total variance. The findings recommend upgrading the bus fleet, maintaining cleanliness, optimizing scheduling, enhancing reservation systems, implementing staff training, improving safety measures, ensuring fair pricing, enhancing customer service, raising passenger awareness, and encouraging innovation to improve expressway bus services, attract more passengers, and build a reliable public transport system.

Human behavior and decision-making in earthquake emergencies: insights from virtual reality and serious games

Earthquakes can severely impact public spaces with complex layouts and high crowd densities, resulting in devastating consequences and deaths. Gaining insights into the actions of individuals during an earthquake can provide valuable information about areas where their decision-making may be flawed. Addressing these areas can improve safety measures and better protect people during emergencies. Moreover, acquiring this knowledge can enhance evacuation strategies for future earthquakes. Immersive Virtual Reality and Serious Games (IVR SGs) present an effective method for examining and understanding how people behave in emergency scenarios, such as earthquakes. Using IVR SGs, we created several potential scenarios during an earthquake in a shopping mall to explore how people act in an emergency when the evacuees feel pressure, urgency, and stress. A total of 146 participants were involved in the study. We investigated the human tendency to follow authority figures’ instructions (rational and irrational), help injured people of different genders and ages, and social influence during an emergency. Moreover, we investigated how familiarity with the environment impacts human wayfinding performance when evacuating the building.

Detection of anticoagulant medication errors by triggers

Medication errors can cause preventable adverse events. For example, inappropriate use of anticoagulants (AC) can result in bleeding and thromboembolic complications. Detection and analysis of AC medication errors allow to reveal deficiencies in the safety systems in healthcare organizations. The study was aimed to develop a method of systematic detection of anticoagulant medication errors for consequent audit, analysis and development of medication safety improvement measures. The study was conducted in the multidisciplinary hospital and included 4924 patients admitted from January 2019 to December 2021 who received AC. Three laboratory triggers (international normalized ratio ≥4, serum creatinine ≥133 μmol/l, and glomerulofiltration rate <30 ml/min/1.73 m2) helped to reveal 4304 cases. Their matching with patient's data helped to develop combined triggers. Two clinical pharmacologists reviewed all cases identified by combined triggers for checking medication errors. The trigger was considered positive when anticoagulant medication error was detected in the history selected by combined trigger. Of the 4924 patients 253 (5.3%) were selected by combined triggers. Combined trigger allowed to reduce the amount of medical health records audit by 97.3%. Medication errors were detected in 137 patients. Positive predictive value of selected combined triggers varied from 0 to 63.9%. Aggregated positive predictive value of all combined triggers amounted to 54.2%. AC medication errors were detected in 2.8% patients. Method of systematic detection of AC medication errors using combined triggers in all hospitalized patients receiving AC allowed to reveal typical medication errors for consequent analysis and elaboration of measures to reduce preventable patient harm in healthcare settings.

A Systematic Review of Occupational Health and Safety in Mining Sector in Pakistan

The mining sector in Pakistan is regarded as a hazardous occupation due to its dangerous nature and workingenvironment, which frequently results in deadly accidents. This study is aimed to conduct a systematic review of theexisting studies on occupational safety and health in the mining sector of Pakistan. For this systematic review, Web ofScience, PubMed, Science Direct, Science Hub, and Google Scholar were consulted to search data. Followingkeywords were used related to occupational health and safety in mining: occupational health and safety (OH&amp;S),mining safety measures, mining health issues, and mining safety culture in Pakistan's mining industry. The result of themeta-analysis shows that OH&amp;S is a major concern in the mining sector. Natural factors, including roof falls, gases anddust, and explosions, as well as human factors such as lack of training, ignorance of safety measures, lack ofknowledge, outdated mining methods, and neglect of safety equipment (helmets, goggles, safety gloves, and masks),have led to accidents and casualties. Demographic factors such as age and personal factors like work experience andduration of job are also major causes of mining accidents that lead to fatalities and injuries. The government,stakeholders, and miners themselves have not been able to take serious initiatives to ensure safety. This studyconcluded that mining conditions are hazardous throughout the country. Workers lives are in danger. Improvements insafety measures not only protect workers lives but also decrease mining accidents, and lead to increased production

A Hierarchical Analysis Method for Evaluating the Risk Factors of Pile Foundation Construction for Offshore Wind Power

To improve the safety level of pile foundation construction for offshore wind power, in this study, the risk indicators of pile foundation construction were evaluated using the analytic hierarchy process (AHP) and comprehensive evaluation methods. The pile foundation construction operation process for offshore wind power mainly includes four phases: preparation for construction, pile sinking, end of construction, and foundation scour protection construction. Pile foundation construction risk indicators are systematically identified as human factors, material factors, management factors, and environmental factors. The most important indicators for pile foundation construction for offshore wind power were evaluated using AHP and comprehensive evaluation methods, which included five indicators: piling equipment, protective equipment, special skills, safety awareness, and emergency management. The four more important indicators are workplace environment, lifting equipment, fire protection systems, and operations. According to the results of our evaluation of the pile foundation construction safety indicators presented herein, corresponding recommendations are made that consider four aspects—human factors, material factors, management factors, and environmental factors. The construction industry should focus on improving the safety measures related to aspects with greater risk indicators. Pile foundation construction for offshore wind power can be evaluated using the method discussed in this paper, allowing industry stakeholders to prioritize and focus on improving safety measures related to aspects with greater risk indicators.

Technological disasters in Asia: Epidemiological profile from the year 2000 to 2021.

Technological disasters in Asia have significant public health and environmental implications, but there is limited epidemiological analysis of these events. This study aims to characterize the epidemiological profile of technological disasters in Asia from 2000 to 2021, focusing on morbidity and mortality trends. A retrospective descriptive observational analysis was conducted using data from emergency events database (EM-DAT), DesInventar, NatCAt, and Sigma. The study categorized disasters into transport, industrial, and miscellaneous accidents. Statistical analyses were used to examine frequencies, trends, and correlations among the different disaster types. From 2000 to 2021, Asia experienced 2333 technological disasters, with transport accidents being the most frequent (55.77%), followed by industrial (26.10%) and miscellaneous accidents (18.13%). The overall trend showed a statistically significant decrease in the frequency of these disasters and in average mortality and injury rates. The study highlighted the varying impact of different disaster types, with industrial accidents causing the highest fatality and affected rates despite being less frequent than transport accidents. The study indicates a declining trend in the frequency and severity of technological disasters in Asia, reflecting improved safety measures and disaster management. However, the high impact of industrial accidents underscores the need for targeted prevention strategies.

Rationales behind international students’ not selecting India as an education destination – An empirical investigation

India’s higher education sector faces significant challenges in attracting international students, evidenced by hosting less than 1 % of globally mobile students despite substantial efforts to increase this number. This study explores critical barriers preventing international students from choosing India as their destination, including financial constraints, safety concerns, and cultural integration issues. It also assesses the impact of the COVID-19 pandemic on these decisions and examines the potential of online education as an alternative. Findings reveal that inadequate financial support and safety concerns are primary deterrents, with varying impacts across educational levels and regions. Recommendations include enhancing financial aid, improving safety measures, fostering cultural integration, and leveraging online education. Addressing these issues is crucial for India to align with global education trends and improve its international appeal.

Unintentionally retained lap sponge mimicking an ovarian cyst two years after Caesarean section in a 37-year old patient: case report of a rare “never event” in Sudan

IntroductionThis case report reports an unusual occurrence of gossypiboma, which refers to the accidental retention of surgical materials like sponges in the peritoneal cavity. The term is derived from “gossypium” (cotton) and “boma” (place of concealment). Its incidence varies with surgical type, posing diagnostic challenges due to nonspecific symptoms and equivocal imaging. Despite its rarity, gossypiboma poses significant risks, including intestinal obstruction and abscess formation.Case presentationA 37-year-old woman with ten previous pregnancies and an emergent caesarean section presented with abdominal pain. Examination and ultrasound suggested an ovarian cyst. During surgery, a 10 × 10 cm gauze-filled mass adherent to the ovary and jejunum was found. Postoperatively, she recovered well with no complications. The patient was treated with intravenous fluids and antibiotics for five days post-surgery and recovered without any complications. She was discharged from the hospital five days after the procedure.ConclusionTo the best of our knowledge, this is the first reported case of gossypiboma in Sudan in 2024, highlighting diagnostic challenges and the need for preventive protocols. Root cause analysis of accidents, enhanced training, application of advanced technologies and a collaborative culture in the operating room can prevent the occurrence of such incidents. This case underscores the importance of meticulous surgical protocols and continuous improvement in safety measures to prevent retained surgical items, ensuring patient safety and optimal outcomes.

Multi-Task Intelligent Monitoring of Construction Safety Based on Computer Vision

Effective safety management is vital for ensuring construction safety. Traditional safety inspections in construction heavily rely on manual labor, which is both time-consuming and labor-intensive. Extensive research has been conducted integrating computer-vision technologies to facilitate intelligent surveillance and improve safety measures. However, existing research predominantly focuses on singular tasks, while construction environments necessitate comprehensive analysis. This study introduces a multi-task computer vision technology approach for the enhanced monitoring of construction safety. The process begins with the collection and processing of multi-source video surveillance data. Subsequently, YOLOv8, a deep learning-based computer vision model, is adapted to meet specific task requirements by modifying the head component of the framework. This adaptation enables efficient detection and segmentation of construction elements, as well as the estimation of person and machine poses. Moreover, a tracking algorithm integrates these capabilities to continuously monitor detected elements, thereby facilitating the proactive identification of unsafe practices on construction sites. This paper also presents a novel Integrated Excavator Pose (IEP) dataset designed to address the common challenges associated with different single datasets, thereby ensuring accurate detection and robust application in practical scenarios.

Orthopedic injuries due to hoverboard use, reported in the NEISS database, 2015–2022

IntroductionHoverboards are a popular means of recreation in the United States and are associated with significant injury risk, leading to recent efforts to improve their safety. Prior studies on hoverboard-related injuries were either conducted prior to implementation of safety regulations, consisted of short study intervals, or did not place a focus on injuries as they pertain to the orthopedic specialist. The purpose of this study is to provide an updated assessment of the epidemiology of orthopedic hoverboard-related injuries presenting to US emergency departments. Materials and MethodsA retrospective analysis from 2015 to 2022 of the National Electronic Injury Surveillance System (NEISS) database was conducted, limited to product codes detailing hoverboard-related injuries leading to emergency department visits. Diagnoses of interest included fractures, dislocations, contusions/abrasions, and strains/sprains. Diagnoses were further broken down to analyze anatomic region affected. National estimates (NE) were calculated using survey methods. One-way ANOVA and chi square tests were used to test for changes over time in injuries, age, and gender. Results4,718 total hoverboard-related injuries were captured, with a national estimate of 154,121. The majority of patients were under 18 years old (79.6 %; P < 0.001) and female (52.5 %; P = 0.038). Orthopedic injuries accounted for 68.6 % of the total, with no significant year-by-year change in this proportion (P = 0.069). Fractures were the most common orthopedic injury (64.2 %), followed by contusions/abrasions (20.2 %), strains/sprains (14.6 %), and dislocations (1.0 %). Most fractures affected the forearm (33.8 %) followed by the wrist (29.2 %). Injuries peaked in 2018 (NE = 25,192) and 2020 (NE = 24,958), followed by a decline in incidence more recently. ConclusionHoverboard-related injuries continue to be a common presentation to US emergency departments, though injury rates appear to be decreasing. Orthopedic injuries consistently account for the majority of hoverboard-related injuries reporting to emergency departments, with fractures of the forearm and wrist being most common. Continued efforts toward improving safety measures regarding hoverboard use are warranted.

Bidirectional Long Short-Term Memory Development for Aircraft Trajectory Prediction Applications to the UAS-S4 Ehécatl

The rapid advancement of unmanned aerial systems in various civilian roles necessitates improved safety measures during their operation. A key aspect of enhancing safety is effective collision avoidance, which is based on conflict detection and is greatly aided by accurate trajectory prediction. This paper represents a novel data-driven trajectory prediction methodology based on applying the Long Short-Term Memory (LSTM) prediction algorithm to the UAS-S4 Ehécatl. An LSTM model was designed as the baseline and then developed into a Staked LSTM to better capture complex and hierarchical temporal trajectory patterns. Next, the Bidirectional LSTM was developed for a better understanding of the contextual trajectories from both its past and future data points, and to provide a more comprehensive temporal perspective that could enhance its accuracy. LSTM-based models were evaluated in terms of mean absolute percentage errors. The results reveal the superiority of the Bidirectional LSTM, as it could predict UAS-S4 trajectories more accurately than the Stacked LSTM. Moreover, the developed Bidirectional LSTM was compared with other state-of-the-art deep neural networks aimed at aircraft trajectory prediction. Promising results confirmed that Bidirectional LSTM exhibits the most stable MAPE across all prediction horizons.

High-Precision Drilling by Anchor-Drilling Robot Based on Hybrid Visual Servo Control in Coal Mine

Rock bolting is a commonly used method for stabilizing the surrounding rock in coal-mine roadways. It involves installing rock bolts after drilling, which penetrate unstable rock layers, binding loose rocks together, enhancing the stability of the surrounding rock, and controlling its deformation. Although recent progress in drilling and anchoring equipment has significantly enhanced the efficiency of roof support in coal mines and improved safety measures, how to deal with drilling rigs’ misalignment with the through-hole center remains a big issue, which may potentially compromise the quality of drilling and consequently affect the effectiveness of bolt support or even result in failure. To address this challenge, this article presents a robotic teleoperation system alongside a hybrid visual servo control strategy. Addressing the demand for high precision and efficiency in aligning the drilling rigs with the center of the drilling hole, a hybrid control strategy is introduced combining position-based and image-based visual servo control. The former facilitates an effective approach to the target area, while the latter ensures high-precision alignment with the center of the drilling hole. The robot teleoperation system employs the binocular vision measurement system to accurately determine the position and orientation of the drilling-hole center, which serves as the designated target position for the drilling rig. Leveraging the displacement and angle sensor information installed on each joint of the manipulator, the system utilizes the kinematic model of the manipulator to compute the spatial position of the end-effector. It dynamically adjusts the spatial pose of the end-effector in real time, aligning it with the target position relative to its current location. Additionally, it utilizes monocular vision information to fine-tune the movement speed and direction of the end-effector, ensuring rapid and precise alignment with the target drilling-hole center. Experimental results demonstrate that this method can control the maximum alignment error within 7 mm, significantly enhancing the alignment accuracy compared to manual control. Compared with the manual control method, the average error of this method is reduced by 41.2%, and the average duration is reduced by 4.3 s. This study paves a new path for high-precision drilling and anchoring of tunnel roofs, thereby improving the quality and efficiency of roof support while mitigating the challenges associated with significant errors and compromised safety during manual control processes.

Optimizing phased-evacuation strategy for high-rise buildings in fire

Evacuation in high-rise buildings is a critical safety issue due to multiple floors and high occupant density. Phased evacuation strategies can mitigate this challenge. This research focuses on developing optimal phased evacuation strategies to enhance occupant safety during high-rise building fires. The study demonstrates these strategies in a 25-story building, housing 2400 individuals, across various scenarios. To simulate fire and smoke development, a two-zone model is employed to analyze behavior within the building. Pedestrian evacuation scenarios are simulated using Pathfinder and a mathematical model, providing insights into individual movements and congestion during evacuation to analyze different phased evacuation strategies. Findings underscore the importance of smoke flow and pedestrian motion in optimizing phased evacuation strategies. The modeling results show that implementing the optimal strategy can lead to a 65 % reduction in staircase congestion time. This study provides a quantitative analysis of high-rise building fires, considering dynamic fire and evacuation evolution. It emphasizes the importance of phased evacuation strategies and advocates for their real-life application. This research enhances the understanding of high-rise building evacuations to improve safety measures and provides a robust framework for optimizing evacuation strategies by integrating fire modeling. This study demonstrates the effectiveness of phased evacuation and paves the way for future applications to ensure occupant safety in fire emergencies.

Detection and Localization of Firearm Carriers in Complex Scenes for Improved Safety Measures

Detection and Localization of Firearm Carriers in Complex Scenes for Improved Safety Measures

Occupational Safety and Health Implementation Model in Construction Safety Management System Based on PUPR Minister Regulation Number 10 Of 2021 to Support Infrastructure Development in East Java Province

Purpose: This study aimed to assess the application of occupational safety and health in the construction safety management system and develop a framework for implementing it based on PUPR ministerial regulation Number 10 of 2021, to support infrastructure development in East Java Province. Method: This study used a qualitative method with a phenomenological approach to gather detailed descriptions of participants' impressions, opinions, and views. It applied Alfred Schutz's approach to establish statements and causal relationships between themes. The research involved six participants and took place at the Department of Public Housing in East Java Province. Results and conclusion: The results and conclusions of the research unveil (1) 8 groups of themes and meanings shaping the implementation of occupational safety and health within the construction safety management system, rooted in PUPR Ministerial Regulation Number 10 of 2021 to bolster infrastructure development in East Java Province. (2) These findings are consolidated into 8 major propositions, leading to the construction of a comprehensive model for implementing occupational safety and health aligned with PUPR Ministerial Regulation Number 10 of 2021. Research implications: The findings of this study can help construction companies and policymakers in East Java Province and beyond improve safety measures. Understanding the framework developed here can lead to safer work environments for construction workers. The qualitative methods used in this research also add to the toolbox of qualitative research methods, providing effective ways to capture subjective experiences. Originality/value: This study offers a unique framework for implementing safety measures in construction projects, specifically designed for the East Java Province and based on relevant regulations. By bringing together various themes from qualitative data, it presents new perspectives on applying regulatory frameworks. Additionally, the use of Alfred Schutz's approach enhances our understanding of how regulations, organizational practices, and individual experiences interact to ensure safety.

Fuzzy Bayesian network analysis for quantifying risk reduction rate of hierarchy of controls

In industries dealing with chemical substances, accidents can pose threats not only the workplace but also to neighboring communities. Therefore, it is crucial to assess and manage these risks. In South Korea, conducting risk assessments is mandatory as a preventive measure to avert accidents. However, determining the acceptability of risk levels and estimating the effectiveness of risk-reducing measures can be challenging during these assessments, despite prioritizing existing measures. This study focuses on evaluating the risk reduction rate of the Hierarchy of Controls. To address the challenges associated with estimating the risk reduction rate, especially in the face of unpredictability and uncertainties, we utilized the Fuzzy Bayesian Network (FBN). FBN combines Fuzzy set theory with the Bayesian Network, providing a more reliable approach to risk assessment. Specifically, our study examines quantifying the risk reduction rate of Controls concerning fire and explosion risks, considering the severity of potential accidents. The findings from this research have the potential to enhance the efficiency of decision-making processes in risk assessments, contributing to improved safety measures.