• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.82-90
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• 1995

This paper pressents a condition-based maintenance (CBM) method through bibration analysis. The well known frequency analysis is employed for performing machine fault diagnosis. The statistical control chart is also applied for analyzing the trend of the bearing wear. Vibration sensors are attached to prototype machine and signals are continuously monitored. The sampled data are utilized to evaluate how well the fast fourier transform(FFT) and the statistical control chart techniques could be used to identify defects of machine and to analyze the machine degradation. Experimental results show that the propowed approach could classify every mal-function and could be utilized for real machine diagnosis system.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.35 no.1
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• pp.15-21
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• 2024

Autism spectrum disorder (ASD) is diagnosed by the clinical decision of a trained professional based on the Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition or International Classification of Diseases 11th Revision diagnostic criteria. To obtain information for diagnostic formulation, professionals should explore detailed developmental history, and can use structured or semi-structured assessment tools to observe interaction between the child and parents or strangers. Diagnostic assessment should include a profile of the strength and weaknesses of the individual and should be conducted using an optimal approach by a multidisciplinary team with appropriate techniques and experience. Assessment of language, cognitive, neuropsychological, and adaptive functioning should be conducted in ASD individuals prior to establishing an individualized treatment plan. Genetic testing, brain magnetic resonance imaging or electroencephalogram testing can be considered for identification of underlying causes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2007.10a
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• pp.329-330
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• 2007

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.426-430
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• 1987

The reliability is the critical issue in many computer applications, particularly in process control system. In this paper we describe how to achieve the reliability improvement in controller system based multiprocessor. The proposed method is accomplished by using the techniques of fault detection, fault isolation, safe action, and fault diagnosis.

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.18 no.1
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• pp.49-52
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• 2014

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.245-253
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• 2004

There has been recent demand for extending the life of age-degraded structures and equipment by such techniques as diagnosis, maintenance, safety assessment, and estimating residual life on iron-making plants and hydraulic, thermal, and nuclear power plants. These techniques take into account comprehensive scenarios that may cause malfunction and structural damage and allow an assessment of risk based on the likely scenarios. In particular the safety assessment and residual life estimation of age-degraded ships and equipment facilities require consideration of various factors such as mechanical and thermal stresses, corrosion, hardness, load variation due to changes of operating condition, crack generation and strength reduction of material by fatigue. In this study, a detail thermal stress analysis, one of useful techniques of safety assessment and maintenance, is performed on a blast furnace by using general FEM code (MSC/NASTRAN).

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.44 no.2
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• pp.52-58
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• 2018

Dry socket, also termed fibrinolytic osteitis or alveolar osteitis, is a complication of tooth exodontia. A dry socket lesion is a post-extraction socket that exhibits exposed bone that is not covered by a blood clot or healing epithelium and exists inside or around the perimeter of the socket or alveolus for days after the extraction procedure. This article describes dry socket lesions; reviews the basic clinical techniques of treating different manifestations of dry socket lesions; and shows how microscope level loupe magnification of $6{\times}$ to $8{\times}$ or greater, combined with co-axial illumination or a dental operating microscope, facilitate more precise treatment of dry socket lesions. The author examines the scientific validity of the proposed causes of dry socket lesions (such as bacteria, inflammation, fibrinolysis, or traumatic extractions) and the scientific validity of different terminologies used to describe dry socket lesions. This article also presents an alternative model of what causes dry socket lesions, based on evidence from dental literature. Although the clinical techniques for treating dry socket lesions seem empirically correct, more evidence is required to determine the causes of dry socket lesions.

• Tribology and Lubricants
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• v.20 no.1
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• pp.21-26
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• 2004

The average frictional coefficient was used generally to analyze the working process of the lubricated machine parts. But it is difficult of taking the correct frictional coefficient because the average frictional coefficient of it is progressed always unstably with a large amplitude on working condition. If the correct analysis of frictional coefficient on working condition for the lubricated machine parts can be possible, it can be effect on condition diagnosis of lubricated machine system. This study was carried out to get the optimum working condition of the hydraulic actuator parts using statistical techniques. From this result, it has the lowest friction coefficient in case of applied load of 3 kg and sliding speed of 120 mm/sec.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2003.11a
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• pp.307-312
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• 2003

The average frictional coefficient was used generally to analyze the moving state of lubricated machine. But It is difficult of getting the correct friction coefficient because the average frictional coefficient of it is progressed always unstably with a large amplitute on driving condition. If correct analysis of frictional coefficient on working condition for lubricated machine can be possible, it can be effect on diagnosis of lubricated machine. The purpose of this study is carried out to get the working condition with a minimum frictional coefficient of transmission gear materials using statistical techniques.