• Safety and Health at Work
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• v.11 no.4
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• pp.397-404
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• 2020

Background: Most job exposure matrices (JEMs) have been developed for chemical and physical hazards in the United States (US). In addition, the overall validity of most JEMs of work organization hazards using self-reported data in the literature remains to be further tested due to several methodological weaknesses. Methods: This paper aims to review important methodological issues with regard to a JEM of work organization hazards using self-report data and to present a research protocol for developing a four-axis (job titles, hazards, sex, and time) JEM of major work organization hazards using the US General Social Survey-Quality of Work-Life (GSS-QWL) data (2002-2018; N = 7,100 workers). Results: Five methodological weaknesses in existing JEMs of work organization hazards using self-report data were identified: having only two axes (hazard and occupation), using psychometrically weak items and scales, including scales having little interoccupational variability, unresolved optimal minimum numbers of subjects per occupation, and low accessibility. The methodological weaknesses were successfully addressed in the proposed research protocol. Conclusion: The work organization JEM to be developed will significantly facilitate and strengthen occupational epidemiological studies on work organization hazards and major health outcomes, improve national and occupational surveillance of work organization hazards, and promote interventions for a healthy work environment in the US.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.40-41
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• 2021

The construction industry has the highest occupational accidents/injuries among all industries. Korean government installed surveillance camera systems at construction sites to reduce occupational accident rates. Construction safety managers are monitoring potential hazards at the sites through surveillance system; however, the human capability of monitoring surveillance system with their own eyes has critical issues. Therefore, this study proposed to build a deep learning-based safety monitoring system that can obtain information on the recognition, location, identification of workers and heavy equipment in the construction sites by applying multiple-object tracking with instance segmentation. To evaluate the system's performance, we utilized the MS COCO and MOT challenge metrics. These results present that it is optimal for efficiently automating monitoring surveillance system task at construction sites.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.330-335
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• 2001

The occurrences of occupational illness and injury have been seriously underestimated in Korea. Surveillance systems for occupational diseases have recently emerged as important strategies for the control of occupational hazards and the implementation of intervention programs to protect workers. However, health service providers do not actively diagnose occupational diseases and are unwilling to report occupational diseases. With the rapid growth of Internet usage in Korea, the computer network has become the predominant means of communicating and sharing information. Therefore, we developed a web-based updated information and education network to assist the health services providers in reporting occupational diseases. Information systems for occupational disease surveillance were also designed to support occupational disease reporting. Commonly available database systems, such as web databases, are useful to manage occupational diseases data efficiently. Standardized case definitions and report guidelines were also established, which included cumulative trauma disorder, occupational asthma, occupational contact dermatitis, and occupational cancer. This system may provide the basis of an efficient and continuously updated source of educational information and provide specific information concerning the occurrence of occupational diseases in specific areas. Background information on occupational diseases obtained in this way will be invaluable for preventing hazards and enforcing occupational disease prevention programs. Moreover, our experiences in establishing these information systems will be of great use in other countries and settings.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.7.1-7.14
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• 2023

Background: At present, no short standard questionnaire exists for assessing and comparing major work organization hazards in the workplaces of the United States. Methods: We conducted a series of psychometric tests (content validity, factor analysis, differential-item functioning analysis, reliability, and concurrent validity) to validate and identify core items and scales for major work organization hazards using the data from the 2002-2014 General Social Surveys (GSSs), including the Quality of Worklife (QWL) questionnaire. In addition, an extensive literature review was undertaken to find other major work organization hazards which were not addressed in the GSS. Results: Although the overall validity of the GSS-QWL questionnaire was satisfactory in the psychometric tests, some GSS-QWL items of work-family conflict, psychological job demands, job insecurity, use of skills on the job, and safety climate scales appeared to be weak. In the end, 33 questions (31 GSS-QWL and 2 GSS) were chosen as the least, but best validated core questions and included in a new short standard questionnaire (called the Healthy Work Survey [HWS]). And their national norms were established for comparisons. Furthermore, based on the literature review, fifteen more questions for assessing other significant work organization hazards (e.g., lack of scheduling control, emotional demands, electronic surveillance, wage theft) were included in the new questionnaire. Thus, the HWS includes 48 questions in total for assessing traditional and emerging work organization hazards, which covers seven theoretical domains: work schedule/arrangement, control, support, reward, demands, safety, and justice. Conclusions: The HWS is a short standard questionnaire for assessing work organization hazards which can be used as a first step toward the risk management of major work organization hazards in the workplaces of the US.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.736-743
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• 2022

Construction workers experience a high rate of fatal incidents from mobile equipment in the industry. One of the major causes is the decline in the acoustic condition of workers due to the constant exposure to construction noise. Previous studies have proposed various ways in which audio sensing and machine learning techniques can be used to track equipment's movement on the construction site but not on the audibility of safety signals. This study develops a novel framework to help automate safety surveillance in the construction site. This is done by detecting the audio sound at a different signal-to-noise ratio of -10db, -5db, 0db, 5db, and 10db to notify the worker of imminent dangers of mobile equipment. The scope of this study is focused on developing a signal processing model to help improve the audible sense of mobile equipment for workers. This study includes three-phase: (a) collect audio data of construction equipment, (b) develop a novel audio-based machine learning model for automated detection of collision hazards to be integrated into intelligent hearing protection devices, and (c) conduct field experiments to investigate the system' efficiency and latency. The outcomes showed that the proposed model detects equipment correctly and can timely notify the workers of hazardous situations.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.34 no.3
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• pp.222-237
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• 2024

Objectives: This study aims to assess the current status of work environment measurement (WEM) for carcinogenic, mutagenic, reproductive toxic substances and to identify their high-risk industries for hazard surveillance and risk assessment. Methods: WEM Data from 37 specially managed CMR substances (2018-2022), the high-risk industries were identified by using estimated 95th percentile levels (X_0.95) of measurements compared with the occupational exposure limit (OEL). Results: The substances most frequently measured were nickel (insoluble), followed by sulfuric acid, lead, chromium (VI), formaldehyde, phenol, dimethylformamide and benzene. The industries with highest number of measurement samples for special management substances were plating of metals, followed by hospitals, general repair services of motor vehicles, building of ships, manufacture of synthetic resin and other plastic materials, manufacture of finished medicaments. Out of the 37 special management substances studied, 22 had a non-detection rate of over 90%. The rate of samples exceeding the OEL was less than 1% for all substances. The substance with the highest number of samples exceeding the OEL was trichloroethylene, which also had the highest average concentration compared to exposure limit. The substances with the highest percentage of industries which (X_0.95) exceeding OEL was formaldehyde followed by sulfuric acid, trichloroethylene, lead, I-bromopropane etc. Conclusions: This study identified high-risk industries of CMR sunstances, highlighting the need for prioritizing these industries in hazards surveillance and risk assessment.

• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.397-408
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• 2021

The construction industry has the highest occupational accidents/injuries and has experienced the most fatalities among entire industries. Korean government installed surveillance camera systems at construction sites to reduce occupational accident rates. Construction safety managers are monitoring potential hazards at the sites through surveillance system; however, the human capability of monitoring surveillance system with their own eyes has critical issues. A long-time monitoring surveillance system causes high physical fatigue and has limitations in grasping all accidents in real-time. Therefore, this study aims to build a deep learning-based safety monitoring system that can obtain information on the recognition, location, identification of workers and heavy equipment in the construction sites by applying multiple object tracking with instance segmentation. To evaluate the system's performance, we utilized the Microsoft common objects in context and the multiple object tracking challenge metrics. These results prove that it is optimal for efficiently automating monitoring surveillance system task at construction sites.

• Journal of Yeungnam Medical Science
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• v.40 no.1
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• pp.65-77
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• 2023

Background: This study aimed to compare clinical outcomes between surveillance and adjuvant therapy (AT) groups after R0 resection for cholangiocarcinoma (CCA). Methods: A total of 154 patients who underwent R0 resection for CCA at the Daegu Catholic University Medical Center between January 2010 and December 2019 were included. Overall survival (OS) and progression-free survival (PFS) were analyzed. Results: The median follow-up duration was 899 days. There were 109 patients in the AT group and 45 patients in the surveillance group. The patients in the AT group were younger (67 years vs. 74 years, p<0.001) and included more males (64.2% vs. 46.7%, p=0.044). The proportion of patients with stage III CCA was larger in the AT group than in the surveillance group (13.8% vs. 2.2%, p=0.005). In addition, AT did not improve OS (5-year OS rate, 69.3% in the AT group vs. 64.2% in the surveillance group, p=0.806) or PFS (5-year PFS rate, 42.6% in the AT group vs. 48.9% in the surveillance group, p=0.113). In multivariate analysis using the Cox proportional hazards model, stage III CCA (hazard ratio [HR], 10.81; 95% confidence interval [CI], 2.92-40.00; p<0.001) was a significant predictor of OS. American Society of Anesthesiologists classification II (HR, 0.50; 95% CI, 0.31-0.81; p=0.005), and American Joint Committee on Cancer stages II (HR, 3.14; 95% CI, 1.25-7.89; p=0.015) and III (HR, 8.08; 95% CI, 2.80-23.32; p<0.001) were independent predictors of PFS. Conclusion: AT after R0 resection for CCA did not improve OS or PFS.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.3
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• pp.273-279
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• 2023

Objectives: Objectives of this study were: 1) to introduce industrial situation and health hazards of synthetic fiber, 2) to review a case of chronic obstructive pulmonary disease in a worker exposed to synthetic fiber reported to the Korea Occupational Disease Surveillance Center, and 3) to suggest supplementary measures for the occupational health system for workers exposed to synthetic fibers. Methods: Respiratory exposure, health hazards, and exposure standards for synthetic fiber dust in Korea and other countries were reviewed. In addition, a case of chronic obstructive pulmonary disease due to exposure to nylon dust reported to the Korea Occupational Disease Surveillance Center was reviewed and summarized. Results: The worker was a 53-year-old non-smoking male who had been involved in the nylon weaving process for 26 years. He had shortness of breath from three years ago. He was diagnosed with chronic obstructive pulmonary disease. PM1.0, PM_2.5, and PM10 were measured at 26.6 ㎍/m³, 48.2 ㎍/m³, and 91.7 ㎍/m³, respectively. Fiber components estimated as nylon fiber were detected in the microscopic examination of a solid sample. Conclusions: For workers exposed to synthetic fiber dust, special health examinations of the respiratory system, regular work environment measurement, and work environment management through workplace health management should be performed. It is necessary to research on health effects of synthetic fibers.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.349-359
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• 2017

In this paper, we conducted survival analyses by fitting the Cox proportional hazards model to stage III proximal colon cancer data obtained from the Surveillance, Epidemiology, and End Results program of the National Cancer Institute. We investigated the effect of covariates on the hazard function for death from proximal colon cancer in stage III with surgery performed and estimated the survival probability for a patient with specific covariates. We showed that the proportional hazards assumption is satisfied for covariates that were used to analyses, using a test based on the Schoenfeld residuals and plots of the Schoenfeld residuals and $log[-log\{{\hat{S}}(t)\}]$. We evaluated the model calibration and discriminatory accuracy by calibration plot and time-dependent area under the ROC curve, which were calculated using 10-fold cross validation.