• Safety and Health at Work
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• 제6권4호
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• pp.353-356
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• 2015

Background: In 2012, the Alaska Section of Epidemiology investigated personnel potentially exposed to a Brucella suis isolate as it transited through three laboratories. Methods: We summarize the first implementation of the United States Centers for Disease Control and Prevention 2013 revised recommendations for monitoring such exposures: (1) risk classification; (2) antimicrobial postexposure prophylaxis; (3) serologic monitoring; and (4) symptom surveillance. Results: Over 30 people were assessed for exposure and subsequently monitored for development of illness. No cases of laboratory-associated brucellosis occurred. Changes were made to gaps in laboratory biosafety practices that had been identified in the investigation. Conclusion: Achieving full compliance for the precise schedule of serologic monitoring was challenging and resource intensive for the laboratory performing testing. More refined exposure assessments could inform decision making for follow-up to maximize likelihood of detecting persons at risk while not overtaxing resources.

• 자동차안전학회지
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• 제11권2호
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• pp.11-16
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• 2019

This paper suggests an algorithm for detecting fault of longitudinal controller in autonomous vehicles. Guaranteeing safety in fault situation is essential because electronic devices in vehicle are dependent each other. Several methods like alarm to driver, ceding control to driver, and emergency stop are considered to cope with fault. This research investigates the fault monitoring process in fail-safe system, for controller which is responsible for accelerating and decelerating control in vehicle. Residual is computed using desired acceleration control command and actual acceleration, and detection of its abnormal increase leads to the decision that system has fault. Before computing residual for controller, health monitoring process of acceleration signal is performed using hardware and analytic redundancy. In fault monitoring process for controller, a process model which is fitted using driving data is considered to improve the performance. This algorithm is simulated via MATLAB tool to verify performance.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.893-903
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• 2022

Recently, computer vision (CV)-based safety monitoring (i.e., object detection) system has been widely researched in the construction industry. Sufficient and high-quality data collection is required to detect objects accurately. Such data collection is significant for detecting small objects or images from different camera angles. Although several previous studies proposed novel data augmentation and synthetic data generation approaches, it is still not thoroughly addressed (i.e., limited accuracy) in the dynamic construction work environment. In this study, we proposed a game engine-driven synthetic data generation model to enhance the accuracy of the CV-based object detection model, mainly targeting small objects. In the virtual 3D environment, we generated synthetic data to complement training images by altering the virtual camera angles. The main contribution of this paper is to confirm whether synthetic data generated in the game engine can improve the accuracy of the CV-based object detection model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권5호
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• pp.1597-1610
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• 2022

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

• Structural Monitoring and Maintenance
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• 제10권2호
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• pp.107-116
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• 2023

The health condition of of deep water high pile foundation is vital to the safe operation of bridges. However, pier foundations are vulnerable to damage in deep water due to exposure to sea torrents and corrosive environments over an extended period. In this paper, combined with aninvestigation and analysis of the typical damage characteristics of main pier group pile foundations, we study the safety monitoring and real-time early warning technology of the deep water high pile foundations, we propose an early warning index item and early warning threshold of deep water high pile foundation by utilizing a numerical simulation analysis and referring to domestic and foreign standards and literature. First, we combine the characteristics of structures and draw on more mature evaluation theories and experience in civil engineering-related fields such as dam and bridge engineering. Then, we establish a scheme consisting of a Early Warning Index Systemand evaluation model based on the analytic hierarchy process and constant weight evaluation method and apply the research results to a project based on the Jiashao bridge in Zhejiang province, China. Finally, we verify the rationality and reliability of the Early Warning Index Systemof the Deep Water High Pile Foundations.

• 한국재난정보학회 논문집
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• 제16권2호
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• pp.331-342
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• 2020

연구목적: 본 연구는 건설업에서의 사고·장애 예방을 위해 시행되고 있는 안전관리비 제도의 문제점과 개선방안 도출을 목적으로 한다. 연구방법: 연구를 위하여 건설안전관리자 20명을 대상으로 세부 설문지를 개발하여 전문가집단인터뷰(FGI) 분석기법을 시행하고 분석하였다. 연구결과: 분석결과 '안전관리비 제도의 이해'를 위해 기준 매뉴얼 작성, 정기 현장교육 시행, 안전관리비 모니터링 시스템 구축 등의 대안이 도출되었고, '안전관리비 제도의 효율성과 필요성'을 개선하기 위해 이례상황 시 즉시 투입할 수 있도록 유연한 비용 집행의 자율성을 보장할 필요성이 있으며, 과도한 증빙서류 요구로 개선되어야 할 항목으로 분석되었다. 결론: 본 연구를 통해 건설현장의 안전관리비 제도 개선을 위한 문제점을 인식하고, 건설안전관리자에 의한 개선방안을 정책적·제도적인틀속에서 마련되어야 할 것이다.

• Safety and Health at Work
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• 제9권2호
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• pp.140-143
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• 2018

Background: The Occupational Safety and Health Monitoring and Assessment Tool (OSH-MAT) is a practical instrument that is currently used in the German woodworking and metalworking industries to monitor safety conditions at workplaces. The 12-item scoring system has three subscales rating technical, organizational, and personnel-related conditions in a company. Each item has a rating value ranging from 1 to 9, with higher values indicating higher standard of safety conditions. Methods: The reliability of this instrument was evaluated in a cross-sectional survey among 128 companies and its validity among 30,514 companies. The inter-rater reliability of the instrument was examined independently and simultaneously by two well-trained safety engineers. Agreement between the double ratings was quantified by the intraclass correlation coefficient and absolute agreement of the rating values. The content validity of the OSH-MAT was evaluated by quantifying the association between OSH-MAT values and 5-year average injury rates by Poisson regression analysis adjusted for the size of the companies and industrial sectors. The construct validity of OSH-MAT was examined by principle component factor analysis. Results: Our analysis indicated good to very good inter-rater reliability (intraclass correlation coefficient = 0.64-0.74) of OSH-MAT values with an absolute agreement of between 72% and 81%. Factor analysis identified three component subscales that met exactly the structure theory of this instrument. The Poisson regression analysis demonstrated a statistically significant exposure-response relationship between OSH-MAT values and the 5-year average injury rates. Conclusion: These analyses indicate that OSH-MAT is a valid and reliable instrument that can be used effectively to monitor safety conditions at workplaces.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2008년도 추계 학술발표회
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• pp.234-246
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• 2008

최근 기상이변과 빈번한 지진발생 및 기타 내외적 요인에 의한 노화/열화 등으로 인하여 댐 안전관리 문제가 국가의 재난관리 차원에서 주요 이슈가 되고 있다. 이에 본 논문에서는 기존 댐에 대한 안전관리를 효율적으로 수행할 수 있도록 하기 위해 개발된 댐 안전관리 시스템(Dam Safety Management System)의 세부구성 및 기능 등에 대하여 소개하고, 향후 선진화된 댐 안전관리를 위해 보완되어야 할 부분에 대한 제언을 하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.321-322
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• 2010

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2017년도 공동학술발표회
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• pp.249-249
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• 2017