• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.67-75
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• 2004

The landslide is one of the most significant natural disasters, which cause a lot of loss of human lives and properties. The landslides in natural slopes generally occur by complicated problems such as soil properties, topography, and geology. Artificial Neural Network (ANN) model is efficient computing technique that is widely used to solve complicated problems in many research fields. In this paper, the ANN model with application of error back propagation method was proposed for estimation of landslide hazard in natural slope. This model can evaluate the possibility of landslide hazard with two different approaches: one considering only soil properties; the other considering soil properties, topography, and geology. In order to evaluate reasonably the landslide hazard, the SlideEval (Ver, 1.0) program was developed using the ANN model. The evaluation of slope stability using the ANN model shows a high accuracy. Especially, the prediction of landslides using the ANN model gives more stable and accurate results in the case of considering such factors as soil, topographic and geological properties together. As a result of comparison with the statistical analysis(Korea Institute of Geosciences and Mineral Resources, 2003), the analysis using the ANN model is approximately equal to the statistical analysis. Therefore, the SlideEval (Ver. 1.0) program using ANN model can predict landslides hazard and estimate the slope stability.

• Journal of the Korean Society of Safety
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• v.12 no.1
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• pp.60-70
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• 1997

Since, human error is a major factor contributing to disaster during start-up of operation in Boiler plant. it is necessary to develop an automation system which prevent mode of operation that are known to be dangerous and to bring a loss of energy. The aim of this study is to suggest a model for the computer-aided synthesis of operation sequence as a part of automation system for start-up operation. Synthesis is accomplished by the formation of a hierarchical network of goals which decide sequence of operations. Hierarchical Network is formed by using method which upper goals ( i.e. upper operation al situation) are classified by the function of themselves into lower goals (i.e. lower operational situation). Knowledge for deciding operation sequence is generated by putting In order the knowledge of hazard operation and energy management.

• Journal of Biomedical Engineering Research
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• v.33 no.3
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• pp.105-113
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• 2012

Biopsy is a type of histopathological examinations, in which a physician samples cells or tissues from a patient's suspicious lesion. Such a lesion frequently resides deep inside human body, and then a percutaneous biopsy is therefore performed using a thick needle with the assistance of medical imaging such as computed tomography(CT) and magnetic resonance imaging(MRI). Recently modern robotic technology is being introduced to percutaneous biopsy in order to reduce any possible human error and hazard on physicians caused by medical imaging. After medical imaging locates the exact location of lesion, an optimization algorithm plans the path for a biopsy needle. Subsequently, a robot system moves the biopsy needle to the lesion in accurate and safe way with the control of a practitioner or automatically. In this article, we try to look into the state-of-art of percutaneous biopsy using such robotic technology. We classified percutaneous biopsy robots by mechanical characteristics and by imaging technology. Then, advantage and disadvantage of each class type are described as well as the basic description, and a few representative designs for each type are introduced. Current research issues of robotized percutaneous biopsy are subjectively selected for the readers' convenience. We emphasize the basic technology of actuator and sensors compatible with imaging technology to conclude this review.

• Korean Chemical Engineering Research
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• v.52 no.6
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• pp.736-742
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• 2014

If an accident occurs at work places that handle 'the accident preparedness substances', it causes more property damage and casualties than accidents of normal chemical substances. Even though various systems and regulations have been operated in order to prevent accidents, techniques for reducing and removing human error, which is one of the main reasons of accidents, are still inadequate. In this paper, hazardous work digitization, potential hazard verification, and work evaluation based on domestic technical guidelines have been performed through a case study of the accident of hydrofluoric acid leakage in Gumi in September 2012, and development of a new risk mapping method has been studied to supplement existing systems.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.313-322
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• 2020

The recognition of the risk hazards is a vital step to effectively prevent accidents on a construction site. The advanced development in computer vision systems and the availability of the large visual database related to construction site made it possible to take quick action in the event of human error and disaster situations that may occur during management supervision. Therefore, it is necessary to analyze the risk factors that need to be managed at the construction site and review appropriate and effective technical methods for each risk factor. This research focuses on analyzing Occupational Safety and Health Agency (OSHA) related to risk zone identification rules that can be adopted by the image recognition technology and classify their risk factors depending on the effective technical method. Therefore, this research developed a pattern-oriented classification of OSHA rules that can employ a large scale of safety hazard recognition. This research uses joint reasoning of risk zone Identification and numeric input by utilizing a stereo camera integrated with an image detection algorithm such as (YOLOv3) and Pyramid Stereo Matching Network (PSMNet). The research result identifies risk zones and raises alarm if a target object enters this zone. It also determines numerical information of a target, which recognizes the length, spacing, and angle of the target. Applying image detection joint logic algorithms might leverage the speed and accuracy of hazard detection due to merging more than one factor to prevent accidents in the job site.

• Journal of Biomedical Engineering Research
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• v.18 no.3
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• pp.233-241
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• 1997

The research on chromosomes is very significant in cytogenetics since genes of the chromosomes control revelation of the inheritance plasma. The human chromosome analysis is widely used to study leukemia, malignancy, radiation hazard, and mutagen dosimetry as well as various congenital anomalies such as Down's, Klinefelter's, Edward's, and Patau's syndrome. The framing and analysis of the chromosome karyogram, which requires specific cytogenetic knowledge is most important in this field. Many researches on automated chromosome karyotype analysis methods have been carried out, some of which produced commercial systems. However, there still remains much room to improve the accuracy of chromosome classification and to reduce the processing time in real clinic environments. In this paper, we proposed a hierarchical artificial neural network(HANN) to classify the chromosome karyotype. We extracted three or four chromosome morphological feature parameters such as centromeric index, relative length ratio, relative area ratio, and chromosome length by preprocessing from ten human chromosome images. The feature parameters of five human chromosome images were used to learn HANN and the rest of them were used to classify the chromosome images. The experiment results show that the chromosome classification error is reduced much more than that of the other researchers using less feature parameters.

• Transactions of the Korean hydrogen and new energy society
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• v.31 no.1
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• pp.73-81
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• 2020

For the fault tree analysis (FTA) analysis of the packaged hydrogen filling station, the composition of the charging station was analyzed and the fault tree (FT) diagram was prepared. FT diagrams were created by dividing the causes of events into external factors and internal factors with the hydrogen event as the top event. The external factors include the effects of major disasters caused by natural disasters and external factors as OR gates. Internal factors are divided into tube tailer, compressor & storage tank, and dispenser, which are composed of mistakes in operation process and causes of accidents caused by parts leakage. In this study, the purpose was to improve the hydrogen station. The subjects of this study were domestic packaged hydrogen stations and FTA study was conducted based on the previous studies, failure mode & effect analysis (FMEA) and hazard & operability study (HAZOP). Top event as a hydrogen leaking event and constructed the flow of events based on the previous study. Refer to "Off shore and onshore reliability data 6th edition", "European Industry Reliability Data Bank", technique for human error rate prediction (THERP) for reliability data. We hope that this study will help to improve the safety and activation of the hydrogen station.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.2
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• pp.147-154
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• 2020

The questionnaire survey was carried out to collect basic data to identify the cause of the risk that did not appear in the current data provided by the fishermen's occupational accidents of the National Federation of Fisheries Cooperative (NFFC) to the onsite specialist, such as a fishing master, chief engineer and fisher in stow net fishing vessel from June to July 2018. The results are as follows. A total of 134 cases were surveyed, including 53 cases in Yeosu, 44 cases in Mokpo, 30 cases in Boryeong and 7 cases in Gunsan. Approximately 60% of the respondents on board the stow net fishing vessel were more than 20 years old, and the boarding experience was seasoned and suitable for the respondents. In the 4M analysis by safety accident factor during fishing work, the mechanical factors included 51 cases (25.0%) of decrepit equipment or poor maintenance and 49 cases (24.0%) of systemic error of fishing equipment. The environmental factors exhibited 71 cases (33.5%) of poor communication by mixed manning of foreign fishermen and 63 cases (29.7%) of poor environment such as heavy weather etc. The human factors showed 78 cases (37.3%) of personnel's carelessness and 45 cases (21.5%) of unskillfulness of operating net and haulers. The management factors exhibited 59 cases (32.1%) of work practice of poor safety precautions and 56 cases (30.4%) of inadequacy of education on hazard factor. The results are expected to contribute to the creation of a safe operating environment for stow net fishery, such as a fisher boarding a stow net fishing vessel, enabling the analysis of major causes of working safety accidents by cause.

• Journal of the Korean Institute of Gas
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• v.28 no.1
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• pp.27-34
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• 2024

In accordance with the clean hydrogen-centered hydrogen industry development plan, technology development and demonstration operation of water electrolysis devices are being actively carried out. Risk assessments are performed on newly developed hydrogen-using facilities and supplies to identify potential hazard factors. However, in general, most industrial accidents are caused by operator's human error or incorrect work practices. Additionally, the possibility of accidents occurring during operation control, maintenance, and inspection increases. For this reason, for equipment developed for demonstration operation, the correct work methods for the main jobs of operator must be reviewed and work procedures must be prepared. Accordingly, in this study, we conducted a job safety analysis (JSA) on major jobs in the operation of water electrolysis facilities to study safe work methods and necessary measures.