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                <text>Management Architecture With Multi-modal Ensemble AI Models for&#13;
Worker Safety</text>
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                <text>Autonomous platform&#13;
Ensemble AI&#13;
Power industry&#13;
Risk index&#13;
Safety management</text>
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                <text>Introduction: Following the Republic of Korea electric power industry site-specific safety management&#13;
system, this paper proposes a novel safety autonomous platform (SAP) architecture that can automatically and precisely manage on-site safety through ensemble artificial intelligence (AI) models. The&#13;
ensemble AI model was generated from video information and worker’s biometric information as&#13;
learning data and the estimation results of this model are based on standard operating procedures of the&#13;
workplace and safety rules.&#13;
Methods: The ensemble AI model is designed and implemented by the Hadoop ecosystem with Kafka/&#13;
NiFi, Spark/Hive, HUE, and ELK (Elasticsearch, Logstash, Kibana).&#13;
Results: The functional evaluation shows that the main function of this SAP architecture was operated&#13;
successfully.&#13;
Discussion: The proposed model is confirmed to work well with safety mobility gateways to provide&#13;
some safety applications</text>
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                <text>Dongyeop Lee *, Daesik Lim , Jongseok Park , Soojeong Woo , Youngho Moon , Aesol Jung</text>
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                <text>Team of Occupational Safety, Convergence Technology Lab, KEPCO Research Institute, Daejeon, Republic of Korea</text>
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                <text>FAJAR BAGUS W</text>
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                <text>Respiratory and Other Hazard Characteristics of Substances in&#13;
Cleaning Products Used in Healthcare Centres in England and Wales</text>
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                <text>Cleaning product&#13;
Healthcare worker&#13;
Respiratory hazard&#13;
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                <text>Occupational use of cleaning products can cause asthma in healthcare workers but the cleaning agents&#13;
responsible are not yet known. This study aimed to identify respiratory and other hazards in cleaning&#13;
products on the National Health Service (NHS) supply chain online catalogue and used in the NHS. Information on cleaning products, their composition, and H-statements that identified hazard characteristics of chemical substances in them was obtained from chemical safety data sheets (SDSs). Furthermore,&#13;
a quantitative structure-activity relationship model and a published asthmagen list were used to identify&#13;
potential additional respiratory hazards. 473 cleaning products and 229 substances were identified. SDSs&#13;
reported only 4 respiratory sensitizers but an additional 51 were suggested by the other 2 methods. In&#13;
contrast, 25 respiratory irritants were identified using SDSs and only one from the asthmagen list. This&#13;
comprehensive overview of cleaning agents’ hazards has potential use in future risk assessment and&#13;
epidemiological studies</text>
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                <text>Centre for Occupational and Environmental Health, School of Health Sciences, University of Manchester, Manchester, UK</text>
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                <text>FAJAR BAGUS W</text>
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                  <text>Safety and Health at Work Vol. 15 Issue 3 2024</text>
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                <text>Assessment of Occupational Exposure to Inhalable Aerosols&#13;
in an Instant Powdered Food Manufacturing Plant in Norway</text>
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                <text>Food industry&#13;
Inhalable aerosols&#13;
Occupational exposure&#13;
Personal sampling&#13;
Powders</text>
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                <text> In the food manufacturing industry, exposure to inhalable aerosols contributes to&#13;
respiratory illnesses such as occupational asthma and rhinitis. However, there is a lack of comprehensive&#13;
exposure assessment studies. This study evaluated occupational exposure to inhalable aerosols in an&#13;
instant powdered food manufacturing plant during work operations involving dried food and powders.&#13;
Methods: In total, 50 workers from an instant powdered food manufacturing plant were recruited.&#13;
Personal inhalable aerosol exposure measurements were taken for both full-shift and task-based&#13;
activities. The concentrations of inhalable aerosols were analyzed to identify any variation within and&#13;
across departments, as well as between seasons, handedness, and sex.&#13;
Results: In total, 134 personal air samples were collected, and the particulate mass was determined&#13;
gravimetrically. The concentrations of inhalable aerosols ranged from 0.1 to 27 mg/m3 for full-shift&#13;
exposure measurements and 3.1 to 73 mg/m3 for task-based measurements. Statistically significant&#13;
differences in mean aerosol concentrations were found across departments (A:B p &lt; 0.001, A:C p &lt; 0.05,&#13;
B:C p &lt; 0.001) and between seasons (p &lt; 0.001).&#13;
Conclusion: This study revealed high exposure to inhalable aerosols among workers, particularly those&#13;
involved in manual weighing, mixing, and adding powders. The significant differences between&#13;
departments highlight the specific activities contributing to increased inhalable aerosol concentrations.&#13;
Seasonal variations were also evident, with autumn showing higher concentrations of inhalable aerosols&#13;
in all departments compared with summer. These findings emphasize the importance of understanding&#13;
the distribution of aerosol concentrations across different work tasks and departments, particularly&#13;
during different seasons.</text>
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                <text>1National Institute of Occupational Health (STAMI), Oslo, Norway&#13;
2University of Oslo, Oslo, Norway</text>
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                <text>FAJAR BAGUS W</text>
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                  <text>Safety and Health at Work Vol. 15 Issue 3 2024</text>
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                <text>Association Between Organizational Downsizing and Depressive&#13;
Symptoms Among Korean Workers: A Cross-sectional Analysis</text>
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                <text>4 July 2024</text>
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                <text>Organizational downsizing may be significantly linked to depressive symptoms, yet&#13;
research on this impact in Asian contexts is limited. This study investigates the association between&#13;
downsizing during the COVID-19 pandemic and depressive symptoms across diverse employment&#13;
statuses.&#13;
Methods: This study used the data from 6th Korean Working Conditions Survey. Depressive symptoms&#13;
were measured using WHO-5 well-being index with a cut-off of 50. Downsizing was defined as&#13;
decrease in the number of employees during last three years. Multivariable logistic regression adjusted&#13;
for socio-demographic and occupational factors was used to estimate the adjusted odds ratio (OR) and&#13;
95% confidence interval (CI) for depressive symptoms associated with downsizing, including subgroup&#13;
analyses.&#13;
Results: Among 26,247 Korean workers (mean age: 43.4, men: 47.5%), the prevalence of depressive&#13;
symptoms was 29.5% (n ¼ 7,751), and the proportion of downsizing was 15.2% (n ¼ 3,978). The prevalence of depressive symptoms was significantly higher among the downsizing group (36.7%,&#13;
n ¼ 1,460) than among the no-downsizing group (28.3%, n ¼ 6,291). The result of logistic regression&#13;
revealed a significant association between downsizing and depressive symptoms (adjusted OR [95% CI]:&#13;
1.39 [1.29e1.50]), particularly pronounced among high socioeconomic status workers.&#13;
Conclusion: This study underscores the significant association between depressive symptoms and&#13;
organizational downsizing, especially high vulnerability of socioeconomically advantaged and stable&#13;
workers. These findings highlight the necessity for targeted mental health support and further&#13;
longitudinal research to clarify the relationship between employment changes and mental health within&#13;
the Korean workforc</text>
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                <text>Youngsun Park 1&#13;
, Juyeon Oh 2&#13;
, Heejoo Park 2&#13;
, Jian Lee 2&#13;
, Byungyoon Yun 1,*, Jin-Ha Yoon 1,3,4</text>
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              <elementText elementTextId="125941">
                <text>1Department of Preventive Medicine, Yonsei University College of Medicine, Seoul 03722, Republic of Korea&#13;
2Department of Public Health, Graduate School, Yonsei University, Seoul 03722, Republic of Korea&#13;
3 The Institute for Occupational Health, Yonsei University College of Medicine, Seoul 03722, Republic of Korea&#13;
4 Institute for Innovation in Digital Healthcare, Yonsei University Health System, Seoul 03722, Republic of Korea&#13;
</text>
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                <text> 4 July 2024</text>
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            <elementTextContainer>
              <elementText elementTextId="125943">
                <text>FAJAR BAGUS W</text>
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              <elementTextContainer>
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                  <text>Safety and Health at Work Vol. 15 Issue 3 2024</text>
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                <text>Association of Physical Fitness With the Work Ability of Aging&#13;
Workers With Physically Demanding Jobs in a University Hospital in&#13;
Thailand</text>
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          <element elementId="49">
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            <description>The topic of the resource</description>
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                <text>Aging&#13;
Physical fitness&#13;
Work ability</text>
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                <text> A decrease in physical fitness with age can impact work ability. Exploring the role of&#13;
physical fitness is important for identifying interventions to enhance work ability among aging workers.&#13;
We sought to determine the association between physical fitness and physically demanding work ability&#13;
in aging workers.&#13;
Methods: We recruited workers aged 45e65 years from eight departments of a university hospital in&#13;
Bangkok, Thailand. Work ability was assessed using the work ability index (WAI), and physical fitness&#13;
components were evaluated through various tests. Associations between work ability and physical&#13;
fitness were examined using a multivariable regression analysis.&#13;
Results: The response rate was 46.4% (n ¼ 216). The mean WAI score was 41.6. Participants with an&#13;
overweight or obese body mass index (BMI) had 1.8 (95% CI e3.1, e0.4) points lower WAI scores than did&#13;
those within a healthy BMI range. A handgrip strength test revealed that participants in the good/very&#13;
good group had 2.5 (95% CI: 0.6, 4.3) higher WAI scores than did those in the very poor/poor group. For a&#13;
single-leg stance test, participants in the above-average group had 2.1 (95% CI: 0.7, 3.5) points greater&#13;
WAI scores than did those in the below-average group. No significant associations were found between&#13;
work ability and 3-min step, chair stand, or sit-and-reach test scores.&#13;
Conclusion: The overall work ability of the participants was good. Body composition, muscle strength,&#13;
and balance were associated with work ability. Promoting physical fitness is a viable strategy for&#13;
enhancing work ability among aging workers</text>
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              <elementText elementTextId="125928">
                <text>idapa Hanvoravongchai 1&#13;
, Methasit Laochindawat 1&#13;
, Soontorn Supapong 1&#13;
,&#13;
Jate Ratanachina </text>
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              <elementText elementTextId="125930">
                <text>1Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand&#13;
2National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom</text>
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                <text> 14 June 2024</text>
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                <text>FAJAR BAGUS W</text>
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                  <text>Safety and Health at Work Vol. 15 Issue 3 2024</text>
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                <text>Association Between Sickness Presenteeism and Depressive&#13;
Symptoms by Occupation and Employment Type During the COVID-19&#13;
Pandemic</text>
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          <element elementId="49">
            <name>Subject</name>
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                <text>COVID-19&#13;
Depressive symptoms&#13;
Employment type&#13;
Occupation&#13;
Sickness presenteeism</text>
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                <text>Sickness presenteeism (SP) has gained attention in occupational health. This study aimed to&#13;
analyze the relationship between SP and depressive symptoms by occupation and employment type&#13;
during the COVID-19 pandemic in Korea.&#13;
Methods: Community Health Survey data (August 16 to October 31, 2020e2021) were used to assess&#13;
depressive symptoms and SP among workers (n ¼ 221,241; mean age 46.0; 53.5% male). Depressive&#13;
symptoms were measured using the Patient Health Questionnaire-9, and SP was defined by the ability to&#13;
rest at home when exhibiting COVID-19 symptoms. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of depressive symptoms were estimated using multiple logistic regression analyses for each&#13;
sex and year stratum. The interaction between SP and occupation on depressive symptoms was assessed&#13;
using relative excess risk due to interaction (RERI).&#13;
Results: The prevalence of depressive symptoms was higher in individuals with SP than in those without&#13;
SP (4.22% [n ¼ 696] vs. 1.89% [n ¼ 3861], respectively). After adjusting for demographic and occupational&#13;
variables, the association between SP and depressive symptoms was significant in both sexes in 2020 and&#13;
2021 (OR [95% CI]: 2.18 [1.82e2.62], 2.41 [1.97e2.93], 2.05 [1.77e2.38], 2.47 [2.11e2.88] for malee2020,&#13;
malee2021, femalee2020, and femalee2021, respectively). A marginally significant interaction between&#13;
service workers and SP on depressive symptoms was observed among male workers in 2021&#13;
(RERI ¼ 2.37, 95% CI ¼ [0.04e4.78]) but not in other strata.&#13;
Conclusion: SP is significantly associated with depressive symptoms in Korean workers across employment and occupational types, with a prominent association in service workers</text>
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                <text>Minkoo Kang 1&#13;
, Won-Tae Lee 2&#13;
, Byungyoon Yun 3,4,5,*, Jin-Ha Yoon 3,4,5</text>
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                <text>https://pdf.sciencedirectassets.com/287282/1-s2.0-S2093791124X00049/1-s2.0-S2093791124000416/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEFEaCXVzLWVhc3QtMSJGMEQCIHAqIL1k2cjbRVeGm0pYyxqf3kaQFlhYMJ4X8BCIOyXZAiBE6Y1Qy15gbVtz%2FrvcwemVcQDaN1X9gUmr%2F28DDliTmSqzBQgaEAUaDDA1OTAwMzU0Njg2NSIMo7ePalv3AN4hk0YlKpAFdcr4b%2BGY4CR2b6Zh9yPCmCwgZnP%2BNbWM1xZ2WWc%2FaR4JKRpbZBvWf%2Be%2F8z%2Bb9zQntGhbxsvIPyjm52CX2oIXfAhproGzCybVsqwGD0Vg%2FwCk%2FcJXoNzSUGGPTX3PLjYB6IRyFOFq1yfNVcHUOj0KIe8U100NEt%2Bqe%2F6%2BzAZbWPaWXy%2B4LvJXPVfYBEN87i33yq2Y0WSxJSxSDSEClU96U8%2BpPF01dJx3d7KpU1OSTEJYFobIZ9EiKNzeZs%2FRfENbf1lFKBDQPqVA9Hx22mN94oRdKFCt032aGTCt5gKZ2eKZr9UEZUF%2FroiMiyNbOuZqVKil138rcCmwQuxxnRGp2UF4HHPlS4%2Bl%2Fum1iJarl9rhh%2B0kOE1g2fgqUjGM%2FbRTs4z8dk%2Fci0ZAU0UIBd9SUcDIe24Ns3wIYQe7EdM1XoOvCs8WwyCBfDclkSrVf%2FJetueSsoQaXgIpqphR%2BwIWOWBnvdjrrVoD4XZtmL%2Fnk6owt2lMIA7a7ODb9mZsTxRoYPLiJrEYsB8OfWWrJI9S%2FWFOz0Q4bmkY8AYUJVUmvuf3iGxYO%2BiXfQ4BW8tSmG2gA1AsKC0FYbXfMglck9b0f8jHC8xBQXYNtR11TdUFkOj9uEp2r77bMcfhBOlOBxvHJEVWmhtZ0HiN1p53GWB7IVT30VVLEBAgwbVDgoV0W9l427mSIwpJk9B%2BjYPRMi3uojHjdFTIe3Dv4B6zAib9FIvxSLBBxjRFTInUdAsHE8EjUMppE%2FHUTFrewc%2Ff8UDDGe3QqqK%2FFj1ZKL9AUM0bbnU9f8foEDektubw%2FECeTwG056eeohMfex4COgho%2BKH1u%2FAp1kM%2BBgxY5upmkfFpul503DHhMh3F5DH%2F4v%2FJtU8wzbH%2BzAY6sgG8%2BUgeTiXVNSAG6xQHdSe6%2F6rs7QrJH4GtXdsBcaiQQPS%2BJ2UjD8NxloOq9ZmgExepeQrkCD%2FNgX%2BrJqbYDs2NJ9oeQN4ENbnLw6qoA3Ic9CG1yaddgStACpKOCb%2FtXYA2W0x8WrUTs6PxXfz6eSNKDLue9SfpYCC7i5ym7gw5HXzNQfrfpMQRa9AjVM%2Fk0i7bzuEkNBIFRZXgaNYd0FYwrns94Xj7XlIxSXdIOBoS%2FQbk&amp;X-Amz-Algorithm=AWS4-HMAC-SHA256&amp;X-Amz-Date=20260226T022405Z&amp;X-Amz-SignedHeaders=host&amp;X-Amz-Expires=300&amp;X-Amz-Credential=ASIAQ3PHCVTY5KFVDIR4%2F20260226%2Fus-east-1%2Fs3%2Faws4_request&amp;X-Amz-Signature=5fb684481a037409819fbd6babe91b004cd41ed006540143a48127604b8c0e07&amp;hash=3207486ddf82d57a96ed05a6edcf51b1b650ec8ebcef2a23b336fdfa4e249a42&amp;host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&amp;pii=S2093791124000416&amp;tid=spdf-182e9332-ba0c-44e5-a56d-a8665f34a207&amp;sid=830681cc5d60f646526bf61913cd5206d1e8gxrqb&amp;type=client&amp;tsoh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&amp;rh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&amp;ua=0b015e065400070506&amp;rr=9d3bfbf11e904573&amp;cc=id</text>
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              <elementText elementTextId="125919">
                <text>1 Yonsei University College of Medicine, Seoul, Republic of Korea&#13;
2Division of Infectious Disease Control, Jeollanam-do Provincial Government, Jeollanam-do, Republic of Korea&#13;
3Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea&#13;
4 Institute for Occupational Health, Yonsei University College of Medicine, Seoul, Republic of Korea&#13;
5 Institute for Innovation in Digital Healthcare, Yonsei University Health System, Seoul, Republic of Korea</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="125920">
                <text> 11 June 2024</text>
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            <description>An entity responsible for making contributions to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="125921">
                <text>FAJAR BAGUS W</text>
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            <description>The file format, physical medium, or dimensions of the resource</description>
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              <elementText elementTextId="125922">
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          <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
              <elementTextContainer>
                <elementText elementTextId="125792">
                  <text>Safety and Health at Work Vol. 15 Issue 3 2024</text>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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        <name>Dublin Core</name>
        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
        <elementContainer>
          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="125903">
                <text>How Resilient are Lucid Motivators? Endeavoring Reforms for Effects&#13;
of Psycho-social Factors on Workers Health Through Concurrent&#13;
Engineering</text>
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            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="125904">
                <text>Concurrent engineering&#13;
Health and safety services&#13;
Human factors analysis&#13;
Multi-criteria decision-making&#13;
Occupational health and safety</text>
              </elementText>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="125905">
                <text> As the tremendous impact of extreme workloads, arduous working conditions, and disorganization disrupt humane job definitions in some industries, the need for workplace re-articulation was&#13;
interfered to ameliorate psycho-social factors and suggest organizational intervention strategies. Especially for colossally wounded health-care (HC) systems, today it is now even more unrealizable to retain&#13;
workforce resilience considering the immense impact of overwhelming working conditions.&#13;
Methods: This study introduces employment of concurrent engineering tools to re-design humane&#13;
workplaces annihilating abatement over devoured resources. The study handles HC-workforce resilience&#13;
in a pioneering motive to introduce transformation of well-known motivators and proposes solutions for&#13;
retention and resilience issues grounding on HC workers’ own voice.&#13;
Results: The proposed adjustable approach introduces integral use of focus group studies, SWARA, and&#13;
QFD methods, and was practiced on a real-world case regarding Turkish HC workforce. The paper also&#13;
presents widespread effects of findings by tendering generalized psycho-social rehabilitation strategies.&#13;
Results confirmed the modifications of the most potent incessant motivators.&#13;
Conclusion: “Burn out issues” and “Challenging work” were found as the most important motivator and&#13;
satisfier, respectively, to be exigently fulfilled. Corrective interventions, required resolutions, and&#13;
workplace articulation connotations were arbitrated in terms of entire outcomes on four dimensions in&#13;
three different planning periods considering the current status, repercussions of pandemic, and contingency of similar catastrophes. Descriptive illustrations were additionally presented to support&#13;
deducted interpretations</text>
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            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="125906">
                <text>Burcu Yılmaz Kaya 1,*, Elif Kılıç Delice 2</text>
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            </elementTextContainer>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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                <text>1 Industrial Engineering Department, Faculty of Engineering, Gazi University, Ankara, Turkey&#13;
2 Industrial Engineering Department, Faculty of Engineering, Atatürk University, Erzurum, Turkey</text>
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                <text>Artificial neural network&#13;
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                <text> Dust generated during various wood-related activities, such as cutting, sanding, or processing wood materials, can pose significant health and environmental risks due to its potential to cause&#13;
respiratory problems and contribute to air pollution. Understanding the factors influencing dust emission&#13;
is important for devising effective mitigation strategies, ensuring a safer working environment, and&#13;
minimizing environmental impact. This study focuses on developing an artificial neural network (ANN)&#13;
model to predict dust emission values in the machining of black poplar (Populus nigra L.), oriental beech&#13;
(Fagus orientalis L.), and medium-density fiberboards.&#13;
Methods: The multilayer feed-forward ANN model is developed using a customized application built&#13;
with MATLAB code. The inputs to the ANN model include material type, cutting width, number of blades,&#13;
and cutting depth, whereas the output is the dust emission. Model performance is assessed through&#13;
graphical and statistical comparisons.&#13;
Results: The results reveal that the developed ANN model can provide adequate predictions for dust&#13;
emission with an acceptable level of accuracy. Through the implementation of the ANN model, the study&#13;
predicts intermediate dust emission values for different cutting widths and cutting depths, which are not&#13;
considered in the experimental work. It is observed that dust emission tends to decrease with reductions&#13;
in cutting width and cutting depth.&#13;
Conclusion: This study introduces an alternative approach to optimize machining-process conditions for&#13;
minimizing dust emissions. The findings of this research will assist industries in obtaining dust emission&#13;
values without the need for additional experimental activities, thereby reducing experimental time and&#13;
cost</text>
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, Erol Burdurlu 3</text>
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                <text>1Department of Industrial Engineering, Bolu Abant Izzet Baysal University, Bolu, Turkey&#13;
2Nevzat Hüseyin Tiryaki Vocational and Technical Anatolian High School, Ankara, Turkey&#13;
3Department of Wood Products Industrial Engineering, Gazi University, Ankara, Turkey</text>
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Performance and Climate in Wood-processing Companies</text>
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                <text>Behavior-based safety&#13;
Safety behavior&#13;
Safety coaching&#13;
Safety leadership&#13;
Sawmill site</text>
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                <text>The wood-processing industry has historically exhibited high rates of occupational hazards&#13;
resulting in illness and injury. One of the major causes of high injury rates is small firm size, as resource&#13;
constraints generally preclude hiring safety officers. This study examined the effect of a safety leadership&#13;
training program that included coaching for managers on workers’ safety behaviors and safety climate in&#13;
three wood-processing companies.&#13;
Methods: One or two managers at each site participated in this study. The manager training consisted of&#13;
safety leadership education, safety observation, positive or corrective feedback on workers’ behaviors,&#13;
goal setting, and low-cost rewards for meeting goals. The dependent variable was the percentage of safe&#13;
employee behaviors recorded on a critical behavior checklist developed for this study. Safety climate was&#13;
measured before and after the intervention. An AB multiple baseline design across settings was adopted.&#13;
After the baseline (A), the training program (B) was introduced to each site at different points in time.&#13;
Results: After the introduction of safety leadership training, the mean rate of safety compliance increased&#13;
by 15.3%, from 80.38% to 95.68%, and safety climate scores increased significantly from an average of 3.2&#13;
to 3.47.&#13;
Conclusion: These results suggest that safety leadership coaching can be effective in improving safety&#13;
management in small sawmilling sites. Implications, limitations, and possible future research directions&#13;
are discussed</text>
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                <text>Department of Psychology, Chung-Ang University, Seoul, Republic of Korea&#13;
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of Anchoring Effects and Influential Factors in Workers’ Assessment&#13;
of Unsafe Behavior</text>
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                <text>Accident-injury experiences&#13;
Anchoring effects&#13;
Risk perception&#13;
Unsafe behavior&#13;
Workplace safety</text>
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                <text> Risk perception plays a crucial role in workers’ unsafe behaviors. However, little research&#13;
has explored why workers generate biased risk perceptions, namely underestimating or overestimating&#13;
the risks of unsafe actions. Cognitive biases in risk perception arise from uncertainties about the dangers&#13;
of unsafe behaviors. As a typical heuristic strategy, the anchoring effect is critical in decision-making&#13;
under uncertain conditions. Consequently, this study empirically analyzed the influence of anchoring&#13;
effects on workers’ risk perception.&#13;
Methods: In 2022, a survey was conducted with 1,418 coal mine workers from Shanxi Province, China.&#13;
The survey instruments assessed workers’ risk perception of unsafe behavior, anchoring effects, need for&#13;
cognition, and safety knowledge. Multivariable linear regression models were employed to analyze the&#13;
associations among these variables.&#13;
Results: The findings verified the proposed anchoring effects. Specifically, experimenter-provided highrisk anchors led workers to overestimate unsafe behavior risks, thus reducing their tendency to engage in&#13;
such behavior. In contrast, experimenter-provided low-risk anchors and accident-injury experiences&#13;
(self-generated anchors) decreased workers’ risk perception, increasing their propensity to engage in&#13;
unsafe behavior. Additionally, workers’ safety knowledge and need for cognition significantly affected&#13;
anchoring effects.&#13;
Conclusion: This research enhances workplace safety studies by applying the anchoring effect from&#13;
psychology to risk perception research. Suggestions for improving risk perception encompass implementing hazard warnings, fostering safety education, and providing training. Furthermore, managers&#13;
should give special attention to workers with accident-injury experience and promptly correct their&#13;
accident fluke mentality, thereby improving overall risk awareness</text>
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, Quanlong Liu 1,2,*, Xinchun Li 1,2&#13;
, Yueqian Zhang 1&#13;
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                <text>School of Economics and Management, China University of Mining and Technology, Xuzhou, China&#13;
2 Key Construction Bases of Philosophy and Social Sciences in Jiangsu Universities (Safety Management Research Center), China University of Mining and&#13;
Technology, Xuzhou, China&#13;
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