• Safety and Health at Work
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• 제11권4호
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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.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 봄 학술논문 발표대회
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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.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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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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• 제35권
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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.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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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.

• 한국산업보건학회지
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• 제34권3호
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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.

• 한국건축시공학회지
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• 제21권5호
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• pp.397-408
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• 2021

건설업은 업무상 재해 발생빈도와 사망자 수가 다른 산업군에 비해 높아 가장 위험한 산업군으로 불린다. 정부는 건설 현장에서 발생하는 산업 재해를 줄이고 예방하기 위해 CCTV 설치 의무화를 발표했다. 건설 현장의 안전 관리자는 CCTV 관제를 통해 현장의 잠재된 위험성을 찾아 제거하고 재해를 예방한다. 하지만 장시간 관제 업무는 피로도가 매우 높아 중요한 상황을 놓치는 경우가 많다. 따라서 본 연구는 딥러닝 기반 컴퓨터 비전 모형 중 개체 분할인 YOLACT와 다중 객체 추적 기법인 SORT을 적용하여 다중 클래스 다중 객체 추적 시스템을 개발하였다. 건설 현장에서 촬영한 영상으로 제안한 방법론의 성능을 MS COCO와 MOT 평가지표로 평가하였다. SORT는 YOLACT의 의존성이 높아서 작은 객체가 적은 데이터셋을 학습한 모형의 성능으로 먼 거리의 물체를 추적하는 성능이 떨어지지만, 크기가 큰 객체에서 뛰어난 성능을 나타냈다. 본 연구로 인해 딥러닝 기반 컴퓨터 비전 기법들의 안전 관제 업무에 보조 역할로 업무상 재해를 예방할 수 있을 것으로 판단된다.

• Journal of Yeungnam Medical Science
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• 제40권1호
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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.

• 한국산업보건학회지
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• 제33권3호
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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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• 제28권2호
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• pp.349-359
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• 2017

본 논문에서는 미국 국립암연구소의 SEER 프로그램에서 제공하는 우측 대장암 3기 자료에 Cox 비례위험모형을 적합하여 생존분석을 하였다. 우측 대장암 3기 환자의 사망률에 유의한 영향을 미치는 공변량들을 파악하고, 관심있는 공변량들을 가진 환자의 생존율을 추정하였다. Schoenfeld 잔차를 기반한 검정과 Schoenfeld 잔차 도표, $log[-log\{{\hat{S}}(t)\}]$ 도표를 이용하여 분석에 사용된 공변량들이 비례위험 가정을 만족함을 확인하였다. 적합된 Cox 비례위험모형의 타당성을 검증하기 위해 10-fold 교차 검증을 이용하여 calibration 도표와 시간에 의존하는 ROC 곡선 아래 면적을 계산하였다. 이를 통해 적합된 Cox 비례위험모형의 타당성을 확인하였다.