Hasil untuk "Industrial medicine. Industrial hygiene"

Salim Fares

A growing number of publications address the best practices to use Large Language Models (LLMs) for software engineering in recent years. However, most of this work focuses on widely-used general purpose programming languages like Python due to their widespread usage training data. The utility of LLMs for software within the industrial process automation domain, with highly-specialized languages that are typically only used in proprietary contexts, remains underexplored. This research aims to utilize and integrate LLMs in the industrial development process, solving real-life programming tasks (e.g., generating a movement routine for a robotic arm) and accelerating the development cycles of manufacturing systems.

Wahyu Rahmaniar, Kenji Suzuki

Traditional deep learning models often lack annotated data, especially in cross-domain applications such as anomaly detection, which is critical for early disease diagnosis in medicine and defect detection in industry. To address this challenge, we propose Multi-AD, a convolutional neural network (CNN) model for robust unsupervised anomaly detection across medical and industrial images. Our approach employs the squeeze-and-excitation (SE) block to enhance feature extraction via channel-wise attention, enabling the model to focus on the most relevant features and detect subtle anomalies. Knowledge distillation (KD) transfers informative features from the teacher to the student model, enabling effective learning of the differences between normal and anomalous data. Then, the discriminator network further enhances the model's capacity to distinguish between normal and anomalous data. At the inference stage, by integrating multi-scale features, the student model can detect anomalies of varying sizes. The teacher-student (T-S) architecture ensures consistent representation of high-dimensional features while adapting them to enhance anomaly detection. Multi-AD was evaluated on several medical datasets, including brain MRI, liver CT, and retina OCT, as well as industrial datasets, such as MVTec AD, demonstrating strong generalization across multiple domains. Experimental results demonstrated that our approach consistently outperformed state-of-the-art models, achieving the best average AUROC for both image-level (81.4% for medical and 99.6% for industrial) and pixel-level (97.0% for medical and 98.4% for industrial) tasks, making it effective for real-world applications.

Tasmiya Rangila, Andiswa Zondo, Andiswa Mtshali et al.

<b>Background/Objectives</b>: Although children’s playgrounds foster physical, cognitive and emotional health, sandpits can harbour antibiotic-resistant bacteria, representing a health concern for kids. Therefore, this point prevalence study investigated the presence and antimicrobial resistance of <i>Escherichia coli</i> in sandpits at four schools in Durban to ascertain the potential risk to schoolchildren and inform school authorities of the need to prevent such occurrences. <b>Methods</b>: Twenty samples were collected from schools on a single day. <i>E. coli</i> was isolated using colilert-18^® and confirmed using PCR. Antibiotic susceptibility testing was performed against 19 antibiotics using the disc diffusion method and Clinical and Laboratory Standards Institute (CLSI) guidelines. <b>Results</b>: <i>E. coli</i> was detected in 2/4 schools (50%), yielding 100 pure isolates. Of these, 71% (31 Site B and 40 Site C isolates) were resistant to at least one of the antibiotics tested, displaying 36 antibiograms. The highest resistance was to CFX (<i>n</i> = 40), and the lowest was to AMK and MEM (<i>n</i> = 1). All isolates were susceptible to CIP, CHL, GEN and TZP. At Site B, the highest resistance was against CFX (<i>n</i> = 16) and the lowest against AMK, CTX and NAL (<i>n</i> = 1). The highest resistance at Site C was against TET (n = 26), and the lowest against ATH and AUG (<i>n</i> = 1). Twenty isolates (20%) were multidrug-resistant, displaying resistance to at least one antibiotic from 3 classes. <b>Conclusions</b>: These results show that children with poor hygiene practices could get sick from playing in sandpits. Schools must change their sand regularly and ensure that sandpits are constantly exposed to the sun.

Imran Riaz Hasrat, Eun-Young Kang, Christian Uldal Graulund

Safety and reliability are crucial in industrial drive systems, where hazardous failures can have severe consequences. Detecting and mitigating dangerous faults on time is challenging due to the stochastic and unpredictable nature of fault occurrences, which can lead to limited diagnostic efficiency and compromise safety. This paper optimizes the safety and diagnostic performance of a real-world industrial Basic Drive Module(BDM) using Uppaal Stratego. We model the functional safety architecture of the BDM with timed automata and formally verify its key functional and safety requirements through model checking to eliminate unwanted behaviors. Considering the formally verified correct model as a baseline, we leverage the reinforcement learning facility in Uppaal Stratego to optimize the safe failure fraction to the 90 % threshold, improving fault detection ability. The promising results highlight strong potential for broader safety applications in industrial automation.

Ali Bakhshi Movahed, Hamed Nozari, Aminmasoud Bakhshi Movahed

Technology plays an undeniable role in today's industrial world, especially in manufacturing and smart factories. Unlike previous industrial revolutions, humans are at the core of the fifth generation of the Industrial Revolution. One of the critical aspects of Industry 5.0 (I 5.0) is its emphasis on human-centricity. The integration of modern technologies can be clearly observed in smart factories, which offer enhanced comfort and professionalism. This study highlights the significance of I 5.0 and smart factory production (SFP). A total of 36 articles are reviewed and systematically categorized using the meta-synthesis methodology. The research emphasizes the influence of I 5.0 on SFP through the use of modern technologies and comprehensive policy frameworks. This new paradigm has the potential to streamline people's lives and bring a transformative shift to smart factory production lines. Enhancing the structure of factories appears feasible under this optimistic perspective.

Changheon Han, Yuseop Sim, Hoin Jung et al.

Acoustic signals from industrial machines offer valuable insights for anomaly detection, predictive maintenance, and operational efficiency enhancement. However, existing task-specific, supervised learning methods often scale poorly and fail to generalize across diverse industrial scenarios, whose acoustic characteristics are distinct from general audio. Furthermore, the scarcity of accessible, large-scale datasets and pretrained models tailored for industrial audio impedes community-driven research and benchmarking. To address these challenges, we introduce DINOS (Diverse INdustrial Operation Sounds), a large-scale open-access dataset. DINOS comprises over 74,149 audio samples (exceeding 1,093 hours) collected from various industrial acoustic scenarios. We also present IMPACT (Industrial Machine Perception via Acoustic Cognitive Transformer), a novel foundation model for industrial machine sound analysis. IMPACT is pretrained on DINOS in a self-supervised manner. By jointly optimizing utterance and frame-level losses, it captures both global semantics and fine-grained temporal structures. This makes its representations suitable for efficient fine-tuning on various industrial downstream tasks with minimal labeled data. Comprehensive benchmarking across 30 distinct downstream tasks (spanning four machine types) demonstrates that IMPACT outperforms existing models on 24 tasks, establishing its superior effectiveness and robustness, while providing a new performance benchmark for future research.

Antoine Houssard

In the field of artificial intelligence (AI) research, there seems to be a rapprochement between academics and industrial forces. The aim of this study is to assess whether and to what extent industrial domination in the field as well as the ever more frequent switch between academia and industry resulted in the adoption of industrial norms and practices by academics. Using bibliometric information and data on scientific code, we aimed to understand academic and industrial researchers' practices, the way of choosing, investing, and succeeding across multiple and concurrent artifacts. Our results show that, although both actors write papers and code, their practices and the norms guiding them differ greatly. Nevertheless, it appears that the presence of industrials in academic studies leads to practices leaning toward the industrial side, but also to greater success in both artifacts, suggesting that if convergence is, then it is passing through those mixed teams rather than through pure academic or industrial studies.

S. Nobrega, Yuan Zhang

Background: Occupational safety and health (OSH) professionals increasingly need interdisciplinary collaborative practice competencies to respond to complex worker safety, health, and well-being risks. Effective collaboration with non-OSH-trained professionals (e.g., health promotion, human resources) is critical for planning integrated interventions that address work and non-work risks, consistent with a “Total Worker Health” (TWH) approach. Interprofessional education (IPE) pedagogy offers skill-building for interdisciplinary collaboration, but little attention has been given to IPE in OSH education and training literature. The goal of this study was to assess OSH professionals’ perceptions about IPE to guide application in postgraduate TWH education. Methods: The mixed-methods study involved 210 U.S. professionals in safety (31%), industrial hygiene (16%), occupational nursing (12%) and medicine (11%), and related disciplines (30%). Participants completed a 12-item Readiness for Interprofessional Education Scale (RIPLS) adapted for TWH. Nineteen survey-takers also participated in virtual focus groups to share opinions about IPE benefits, barriers, and desirable course features. Findings: Occupational safety and health professionals reported high overall readiness for IPE (RIPLS, 4.45 ± 0.47), endorsing IPE for interdisciplinary skill-building. Salient IPE motivators were learning new perspectives from diverse disciplines and industries; gaining new subject expertise; developing common ground across disciplines; and learning TWH best practices. Participants recommended case studies to practice interdisciplinary problem-solving through group work. Conclusions/Application to Practice: Interprofessional education is a promising pedagogy for OSH continuing education to promote interdisciplinary collaboration skills needed for TWH practice in the workplace. Occupational safety and health educators need to build competency in IPE pedagogical theory and practice to ensure effective training design and evaluation.

Vivek Chavan, Oliver Heimann, Jörg Krüger

Egocentric vision aims to capture and analyse the world from the first-person perspective. We explore the possibilities for egocentric wearable devices to improve and enhance industrial use cases w.r.t. data collection, annotation, labelling and downstream applications. This would contribute to easier data collection and allow users to provide additional context. We envision that this approach could serve as a supplement to the traditional industrial Machine Vision workflow. Code, Dataset and related resources will be available at: https://github.com/Vivek9Chavan/EgoVis24

Sarah AlMuammar, Rahaf Alkhaldi, Roaa Alsharif et al.

Abstract Background Depression poses a significant challenge globally, including in safety-critical industries such as aviation. In Saudi Arabia, where the aviation sector is rapidly expanding, pilots encounter unique stressors inherent to their profession. However, research on pilot mental health, particularly within the Saudi context, remains limited despite its critical role in flight safety. Methods This cross-sectional survey was designed to estimate the self-reported prevalence of depression in a convenience sample of airline pilots in Saudi Arabia. Participants were recruited from various commercial airlines in Saudi Arabia. Recruitment efforts utilized targeted outreach on social media platforms, focusing on pilot forums and groups. The survey was administered online for accessibility and convenience. The structured questionnaire, developed through a literature review and expert consultation, comprises sections on demographic and professional characteristics, occupational information, health habits, and depression assessment via the Patient Health Questionnaire-9 (PHQ-9). Results This study enrolled 310 participants, with the largest cohort (34.8%, n = 108) falling within the 30–39 years age group, closely followed by individuals under 30 years (30.0%, n = 93). Males dominated the sex distribution (99.0%, n = 307). The mean PHQ-9 score was 8.2 ± 5.4. Notably, 40.6% (n = 126) of the participants had a score of 10 or higher, indicating the potential for moderate, moderate-severe, or severe depression. Multivariable binary logistic regression analysis revealed that pilots with 11–15 years of experience had greater odds of experiencing depression than did those with 0–10 years of experience did (odds ratio [OR]: 3.0, 95% confidence interval [CI]: [1.1–8.4], p = 0.04). Pilots with rest times exceeding 24 h had lower odds of depression than did those with rest times less than 1 h (OR: 0.3, 95% CI: [0.1–0.8], p = 0.02). Engaging in regular exercise was associated with reduced odds of depression (OR: 0.3, 95% CI: [0.2–0.5], p < 0.01), as was longer sleep duration (> 8 h) (OR: 0.2, 95% CI: [0.1–1.0], p = 0.04). Conclusion Our study estimates the prevalence and severity of self-reported depressive symptoms among airline pilots in Saudi Arabia, surpassing global estimates. The identified factors, including lack of regular exercise, short sleep duration, and insufficient rest between flights, underscore the complex mental health challenges faced by pilots in this region. Addressing these issues is crucial not only for pilot well-being but also for flight safety.

Nathan B. Morris, Nicholas Ravanelli, Georgia K. Chaseling

Abstract Background Ethyl alcohol (ethanol) consumption is ostensibly known to increase the risk of morbidity and mortality during hot weather and heatwaves. However, how alcohol independently alters physiological, perceptual, and behavioral responses to heat stress remains poorly understood. Therefore, we conducted a systematic scoping review to understand how alcohol consumption affects thermoregulatory responses to the heat. Methods We searched five databases employing the following eligibility criteria, studies must have: 1) involved the oral consumption of ethanol, 2) employed a randomized or crossover-control study design with a control trial consisting of a volume-matched, non-alcoholic beverage, 3) been conducted in healthy adult humans, 4) reported thermophysiological, perceptual, hydration status markers, and/or behavioral outcomes, 5) been published in English, 6) been conducted in air or water at temperatures of > 28°C, 7) involved passive rest or exercise, and 8) been published before October 4th, 2023. Results After removing duplicates, 7256 titles were screened, 29 papers were assessed for eligibility and 8 papers were included in the final review. Across the 8 studies, there were a total of 93 participants (93 male/0 female), the average time of heat exposure was 70 min and average alcohol dose was 0.68 g·kg1. There were 23 unique outcome variables analyzed from the studies. The physiological marker most influenced by alcohol was core temperature (lowered with alcohol consumption in 3/4 studies). Additionally, skin blood flow was increased with alcohol consumption in the one study that measured it. Typical markers of dehydration, such as increased urine volume (1/3 studies), mass loss (1/3 studies) and decreased plasma volume (0/2 studies) were not consistently observed in these studies, except for in the study with the highest alcohol dose. Conclusion The effect of alcohol consumption on thermoregulatory responses is understudied, and is limited by moderate doses of alcohol consumption, short durations of heat exposure, and only conducted in young-healthy males. Contrary to current heat-health advice, the available literature suggests that alcohol consumption does not seem to impair physiological responses to heat in young healthy males.

S. Nobrega, Yuan Zhang

Occupational safety and health (OSH) professionals increasingly need interdisciplinary collaborative practice competencies to respond to complex worker safety, health, and social concerns. Effective communication with non-OSH-trained professionals (e.g., health promotion, human resources) is critical for delivering interventions that address interrelated work and non-work sources of risks, per the US “Total Worker Health” (TWH) and WHO Healthy Workplace frameworks. Interprofessional education (IPE) pedagogy offers skill-building specific to interdisciplinary collaboration, but little evidence is available for IPE implementation in OSH post-graduate education settings. We prospectively assessed OSH professionals’ attitudes for participating in post-graduate IPE to learn TWH practices and applications in the workplace. This mixed methods study involved 210 US professionals in safety (31%), industrial hygiene (16%), occupational nursing (12%) and medicine (11%), and related disciplines (30%). Participants completed a 12-item Readiness for Interprofessional Education Scale (RIPLS) adapted for TWH. Nineteen survey-takers also participated in virtual focus groups to share opinions about IPE benefits, barriers, and desirable course features. OSH professionals reported high overall readiness for IPE (RIPLS, 4.45±0.47), endorsing IPE for interdisciplinary skill-building. Salient IPE motivators were learning new perspectives from diverse disciplines and industries; gaining new subject expertise; and learning TWH best practices. Participants recommended case studies to practice interdisciplinary problem-solving and time for interdisciplinary group work. Participants strongly endorsed IPE pedagogy for interdisciplinary collaborative skill-building and developing “common ground” across disciplines. Interprofessional education is a promising pedagogy for OSH continuing education settings. OSH educators need to build competency in IPE pedagogical theory and practice.

E. K. Danyo, M. Ivantsova, I. Selezneva

There are two main types of radiation: ionizing and non-ionizing. Radiations are widely distributed in the earth’s crust with small amounts found in water, soil, and rocks. Humans can also produce them through military, scientific, and industrial activities. Ionizing and nonionizing radiations have a wide application in the food industry and medicine. γ-rays, X-rays, and electron beams are the main sources of radiation used in the food industry for food processing. This review discusses advantages and disadvantages of ionizing radiation on microorganisms and its potential applications in the food industry. We also looked at its advantages and disadvantages. Studies have revealed that ionizing radiation is used in the food industry to inactivate microorganisms in food products to improve hygiene, safety, and extend shelf life. Microorganisms such as bacteria and fungi are susceptible to high doses of irradiation. However, some bacterial and fungal species have developed an exceptional ability to withstand the deleterious effect of radiation. These organisms have developed effective mechanisms to repair DNA damage resulting from radiation exposure. Currently, radiation has become a promising technology for the food industry, since fruits, tubers, and bulbs can be irradiated to delay ripening or prevent sprouting to extend their shelf life.

Razin Farhan Hussain, Mohsen Amini Salehi

Industry 4.0 operates based on IoT devices, sensors, and actuators, transforming the use of computing resources and software solutions in diverse sectors. Various Industry 4.0 latency-sensitive applications function based on machine learning to process sensor data for automation and other industrial activities. Sending sensor data to cloud systems is time consuming and detrimental to the latency constraints of the applications, thus, fog computing is often deployed. Executing these applications across heterogeneous fog systems demonstrates stochastic execution time behavior that affects the task completion time. We investigate and model various Industry 4.0 ML-based applications' stochastic executions and analyze them. Industries like oil and gas are prone to disasters requiring coordination of various latency-sensitive activities. Hence, fog computing resources can get oversubscribed due to the surge in the computing demands during a disaster. We propose federating nearby fog computing systems and forming a fog federation to make remote Industry 4.0 sites resilient against the surge in computing demands. We propose a statistical resource allocation method across fog federation for latency-sensitive tasks. Many of the modern Industry 4.0 applications operate based on a workflow of micro-services that are used alone within an industrial site. As such, industry 4.0 solutions need to be aware of applications' architecture, particularly monolithic vs. micro-service. Therefore, we propose a probability-based resource allocation method that can partition micro-service workflows across fog federation to meet their latency constraints. Another concern in Industry 4.0 is the data privacy of the federated fog. As such, we propose a solution based on federated learning to train industrial ML applications across federated fog systems without compromising the data confidentiality.

Jobish John, Md. Noor-A-Rahim, Aswathi Vijayan et al.

This paper explores the role that 5G, WiFi-7, and Time-Sensitive Networking (TSN) can play in driving smart manufacturing as a fundamental part of the Industry 4.0 vision. The paper provides an in-depth analysis of each technology's application in industrial communications, with a focus on TSN and its key elements that enable reliable and secure communication in industrial networks. In addition, the paper includes a comparative study of these technologies, analyzing them based on a number of industrial use-cases, supported secondary applications, industry adoption, and current market trends. The paper concludes by highlighting the challenges and future directions for the adoption of these technologies in industrial networks and emphasizes their importance in realizing the Industry 4.0 vision within the context of smart manufacturing.

Hossein Ebrahimi

Background and Objective: Musculoskeletal disorders are among the cumulative injuries that result from working in dangerous conditions and poor postures over several years. One of the major problems for computer users is musculoskeletal disorders. The present study investigated the effect of teaching ergonomics to computer users on the prevalence of musculoskeletal disorders. Materials and Methods: This descriptive and cross-sectional study was performed on the administrative staff of Imam Reza (AS) hospital in Mashhad, Iran. In this study, 77 administrative and support staff were selected using the simple random sampling method. After the initial assessment of their physical condition during work, an ergonomic educational intervention program was given to the users to reduce their musculoskeletal injury factors during a three-month period. Their physical condition was assessed before and after the training using the rapid office strain assessment method. The collected data were analyzed using SPSS software (version 20). Results: The mean age of participants was 36.4±6.62 years old and their mean work experience was 13/8%±6.12 years. The prevalence of discomfort and pain was mainly reported in the lumbar region (57.2%) and neck (43.8%). Moreover, the highest frequency of rapid office strain assessment method score was 5 before training (42.3%), which reached 9.6% after the intervention and training of staff. The scores of 6, 3, 4, and 2 were 18.3%, 15.7%, 14.6%, and 7.1%, respectively. Conclusion: The results showed the importance of teaching the principles of ergonomics for using computer systems in reducing musculoskeletal disorders. Moreover, it was found that the level of musculoskeletal disorders in this group of occupations can be minimized with proper training.

Abubakar Sadiq Mohammed, Philipp Reinecke, Pete Burnap et al.

The offshore oil and gas industry has recently been going through a digitalisation drive, with use of `smart' equipment using technologies like the Industrial Internet of Things (IIoT) and Industrial Cyber-Physical Systems (ICPS). There has also been a corresponding increase in cyber attacks targeted at oil and gas companies. Oil production offshore is usually in remote locations, requiring remote access and control. This is achieved by integrating ICPS, Supervisory, Control and Data Acquisition (SCADA) systems, and IIoT technologies. A successful cyber attack against an oil and gas offshore asset could have a devastating impact on the environment, marine ecosystem and safety of personnel. Any disruption to the world's supply of oil and gas (O\&G) can also have an effect on oil prices and in turn, the global economy. This makes it important to secure the industry against cyber threats. We describe the potential cyberattack surface within the oil and gas industry, discussing emerging trends in the offshore sub-sector, and provide a timeline of known cyberattacks. We also present a case study of a subsea control system architecture typically used in offshore oil and gas operations and highlight potential vulnerabilities affecting the components of the system. This study is the first to provide a detailed analysis on the attack vectors in a subsea control system and is crucial to understanding key vulnerabilities, primarily to implement efficient mitigation methods that safeguard the safety of personnel and the environment when using such systems.

Kazhan Othman Mohammed Salih, Tarik A. Rashid, Dalibor Radovanovic et al.

There is no doubt that new technology has become one of the crucial parts of most people's lives around the world. By and large, in this era, the Internet and the Internet of Things (IoT) have become the most indispensable parts of our lives. Recently, IoT technologies have been regarded as the most broadly used tools among other technologies. The tools and the facilities of IoT tech-nologies within the marketplace are part of Industry 4.0. The marketplace is too regarded as a new area that can be used with IoT technologies. One of the main purposes of this paper is to highlight using IoT technologies in Industry 4.0, and the Industrial Internet of Things (IIoT) is another feature revised. This paper focuses on the value of the IoT in the industrial domain in general; it reviews the IoT and focuses on its benefits and drawbacks, and presents some of the IoT applications, such as in transportation and healthcare. In addition, the trends and facts that are related to the IoT technologies on the marketplace are reviewed. Finally, the role of IoT in telemedicine and healthcare and the benefits of IoT technologies for COVID-19 are presented as well.

Martin Törngren, Haydn Thompson, Erik Herzog et al.

Industry is moving towards advanced Cyber-Physical Systems (CPS), with trends in smartness, automation, connectivity and collaboration. We examine the drivers and requirements for the use of edge computing in critical industrial applications. Our purpose is to provide a better understanding of industrial needs and to initiate a discussion on what role edge computing could take, complementing current industrial and embedded systems, and the cloud. Four domains are chosen for analysis with representative use-cases; manufacturing, transportation, the energy sector and networked applications in the defense domain. We further discuss challenges, open issues and suggested directions that are needed to pave the way for the use of edge computing in industrial CPS.

Johannes Gerding, Lea Anhäuser, Udo Eickmann et al.

Abstract Background Several drugs for human use possess genotoxic properties as a necessary consequence of their intended therapeutic effect (e.g. antineoplastics). Health workers may be exposed to these chemicals in various occupational settings such as dose preparation and administration. To date, there are no quantitative risk assessment models to estimate the cancer risk of health workers due to the handling of genotoxic drugs. We therefore developed a quantitative risk assessment model to assess the cancer risk of occupational exposure to genotoxic drugs in healthcare settings based on the threshold of toxicological concern (TTC) concept. This model was used to evaluate the cancer risk of health workers due to the handling of genotoxic drugs in modern health care facilities. Methods We modified the threshold of toxicological concern (TTC) concept to fit the purpose of occupational cancer risk assessment. The risk model underlying ICH guideline M7 (R1): “assessment and control of DNA reactive (mutagenic) impurities in pharmaceuticals to limit potential carcinogenic risk” was used as a starting point for our model. We conducted a short review of studies on the occupational exposure of health workers to genotoxic drugs. These occupational exposure data were compared to the acceptable exposure levels resulting from our TTC based risk model. Results Based on the threshold of toxicological concern (TTC) concept, we defined an acceptable daily intake (ADI) of 4 μg/day as threshold of no concern for the exposure of health workers to genotoxic drugs. Regarding the dermal exposure of health workers to genotoxic drugs, we derived a corresponding acceptable surface contamination level (ASCL) of 20 ng/cm2. Both ADI and ASCL are usually not exceeded in modern healthcare settings. Current safety precautions provide sufficient protection to health workers. Conclusions The application of our model indicates that workers in modern healthcare facilities are not at risk of developing work related cancer above widely accepted cancer risk levels due to the occupational exposure to genotoxic drugs. Hence, the present study may assist employers and public authorities to make informed decisions concerning the need for (further) protective measures and during risk communication to health workers.