• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11b
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• pp.270-273
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• 2001

Electrical tree is studied widely by manufacture state of insulating material fare and blazing fire diagnosis system of use in phenomenon of part discharge that happen for main cause of dielectric breakdown of equipment for electric power. Use process that draw tree pattern here measuring above zero to study special quality of this electricity tree, real-time processing by image processing is proposed because reproduction of tree blazing fire process drops and pattern of tree is difficult correct quantification of tree growth by existent visual observation by involution. This research presents general process that need in image processing of tree blazing fire, and that remove various noises that happen in above zero by measuring electrical tree dividing background and complete view in measured above zero taking advantage of specially proposed complete view object abstraction techniques effectively and quantification of tree becomes easy naturally, can apply to dielectric breakdown estimate because can chase growth process of tree.

• 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.

• The Korean Journal of Cytopathology
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• v.11 no.1
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• pp.11-18
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• 2000

Pancreaticobiliary tract strictures are frequent Indications for endoscopic retrograde cholangiopancreatography(ERCP). We have investigated the brushing cytology in order to determine its efficacy for diagnosis of pancreaticobiliary malisnancies. Brushing cytology during ERCP was evaluated in 56 patients with biliary tract stricture presenting to the Catholic Hospital of Taegu-Hyosung from April 1997 to August 1999. A comparison was made between the cytologic and histologic diagnoses on 32 cases from 30 patients. A diagnosis of malignancy was establishied in 78.1%, benign in 15.6%, and inadequate in 6.3% of the cases. Statistical data on cytologic diagnoses in strictures of the bile duct were as follows; specificity and sensitivity of blushing procedure was 100% & 83.3%, respectively: sensitivity of interpretation was 89.3%: with no false positive cases and 3 false negative cases: predictive value for malignancy was 100% & 100%, respectively: predictive value for benign was 28.6% & 40%,, respectively: overall diagnostic efficiency was 84.4%. It is concluded that brush cytology is a diagnostically reliable, highly specific technique for malignant lesions encounted at ERCP, although a negative result does not rule out the diagnosis of malignancy.

• Tuberculosis and Respiratory Diseases
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• v.78 no.3
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• pp.203-209
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• 2015

Background: Induced sputum (IS) has been used to collect airway secretions in subjects who have inadequate sputum production. The aim of this study was to investigate the efficacy of IS for the diagnosis of pulmonary tuberculosis (PTB) in adults unable to expectorate sputum. Methods: Medical records of 39 PTB patients who underwent IS due to absence of spontaneous sputum production between January 2011 and March 2014 at a tertiary hospital in South Korea were reviewed. Results of acid fast bacilli smear, Mycobacterium tuberculosis culture and polymerase chain reaction assay for M. tuberculosis (TB-PCR) of IS specimens from these patients were analyzed. Clinical and high-resolution computed tomography (HRCT) characteristics were also analyzed to find characteristics associated with IS culture positivity. Results: Of the 39 IS specimens from PTB patients, 7 (17.9%) were smear positive and 31 (79.5%) were culture positive. Twenty-four IS specimens were tested for TB-PCR and 13 (54.2%) were positive on TB-PCR. Multivariate analysis showed that younger age (p=0.04) and presence of tree-in-bud appearance on HRCT (p=0.03) were independent predictors of IS culture positivity. Conclusion: IS is useful for the diagnosis of PTB in adults unable to expectorate sputum. Younger age and tree-in-bud appearance on HRCT were associated with IS culture positivity in these patients.

• The Journal of Korean Medicine
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• v.33 no.4
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• pp.1-8
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• 2012

Objectives: The purpose of this study was to specify major tongue diagnostic indicators and evaluate their significance in discriminating pattern identification subtypes in stroke patients. Methods: This study used a community based multi-center observational design. Participants (n=1,502) were stroke patients admitted to 11 oriental medical university hospitals between December 2006 and February 2010. To determine which tongue indicator affected each pattern identification, a decision tree analysis of the chi-square automatic interaction detector (CHAID) algorithm was performed. The chi-squared test was used as the criterion in splitting data with a p-value less than 0.05 for division, which is the main procedure for developing a decision tree. The minimum sample size for each node was specified as n =10, and branching was limited to two levels. Results: From the 9 tongue diagnostic indicators, 6 major tongue indicators (red tongue, pale tongue, yellow fur, white fur, thick fur, and teeth-marked tongue) were identified through the decision tree analysis. Furthermore, each pattern identification was composed of specific combinations of the 6 major tongue indicators. Conclusions: This study suggests that the 6 tongue indicators identified through the decision tree analysis can be used to discriminate pattern identification subtypes in stroke patients. However, it is still necessary to re-evaluate other pattern identification indicators to further the objectivity and reliability of traditional Korean medicine.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1603-1603
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• 2011

As time goes by these cables make a insulation problems, and ask for a preventive diagnosis method. Cable has very high electrostatic capacity and insulation defects mainly caused by water-tree(WT). Dissipation factor test is very useful for detecting WT but it needs huge power supply. In this paper we presented a cable insulation diagnosis by dissipation factor using low frequency power supply.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1705-1711
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• 1991

On-line fault detection and diagnosis has an increasing interest in a chemical process industry, especially for a process control and automation. The chemical process needs an intelligent operation-aided workstation which can do such tasks as process monitoring, fault detection, fault diagnosis and action guidance in semiautomatic mode. These tasks can increase the performance of a process operation and give merits in economics, safety and reliability. Aiming these tasks, series of researches have been done in our lab. Main results from these researches are building appropriate knowledge representation models and a diagnosis mechanism for fault detection and diagnosis in a chemical process. The knowledge representation schemes developed in our previous research, the symptom tree model and the fault-consequence digraph, showed the effectiveness and the usefulness in a real-time application, of the process diagnosis, especially in large and complex plants. However in our previous approach, the diagnosis speed is its demerit in spite of its merits of high resolution, mainly due to using two knowledge models complementarily. In our current study, new knowledge representation scheme is developed which integrates the previous two knowledge models, the symptom tree and the fault-consequence digraph, into one. This new model is constructed using a material balance, energy balance, momentum balance and equipment constraints. Controller related constraints are included in this new model, which possesses merits of the two previous models. This new integrated model will be tested and verified by the real-time application in a BTX process or a crude unit process. The reliability and flexibility will be greatly enhanced compared to the previous model in spite of the low diagnosis speed. Nexpert Object for the expert system shell and SUN4 workstation for the hardware platform are used. TCP/IP for a communication protocol and interfacing to a dynamic simulator, SPEEDUP, for a dynamic data generation are being studied.

• Proceedings of the KIEE Conference
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• 1994.07b
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• pp.1655-1657
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• 1994

To measure treeing, visual measurement with an optical microscope has been used to explain breakdown mechanism by treeing in materials. The conventional direct visual method of tree deterioration observation is difficult to measure in short time processing, and impossible to analyze the deteriorated area by treeing, direction of tree growth, tree patterns etc. In this paper, we have developed a tree-measuring system using image processing for the tree growth, the area of deterioration, and other progresses of treeing. As experimental result, image processing is an effective alternative to direct visual observation method.

• Korean Journal of Heritage: History & Science
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• v.56 no.1
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• pp.118-130
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• 2023

Decay or large cavities inside trees are the main causes of trees overturning and broken branches, and structurally weakened trees are more vulnerable to strong winds and heavy snowfall. Recently, as strong winds and typhoons increase due to climate change, the damage to human life and property due to trees overturning continues to increase, and cultural assets are in a similar situation. In particular, old big trees are structurally vulnerable to external shocks such as strong winds and heavy snowfall. This study was aimed at providing a scientific basis for preventive protection measures by conducting a structural stability diagnosis of seven retusa fringe trees designated as natural monuments. For the structural stability diagnosis, tree risk assessment and internal tree defect measurements were performed. As a result of the tree risk assessment, the Retusa Fringe Trees in Sinjeon-ri, Yangsan and Gwangyangeupsu had the highest risk of broken branches due to weak branch attachment strength. As a result of the diagnosis of internal defects of cross sections of measured trees, there were suspected cavities or severe decay in all except two trees of the population of Retusa Fringe Trees in Pyeongji-ri. Natural disasters due to climate change are increasing, and the scale is getting larger, so it is very important to preemptively manage large old trees through scientific structural safety diagnosis to manage trees that are vulnerable to environmental changes.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.41
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• pp.6.1-6.10
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• 2019

Background: Osteomyelitis is an intraosseous inflammatory disease characterized by progressive inflammatory osteoclasia and ossification. The use of quantitative analysis to assist interpretation of osteomyelitis is increasingly being considered. The objective of this study was to perform early diagnosis of osteomyelitis on digital panoramic radiographs using basic functions provided by picture archiving and communication system (PACS), a program used to show radiographic images. Methods: This study targeted a total of 95 patients whose symptoms were confirmed as osteomyelitis under clinical, radiologic, pathological diagnosis over 11 years from 2008 to 2017. Five categorized patients were osteoradionecrosis, bisphosphonate-related osteonecrosis of jaw (BRONJ, suppurative and sclerosing type), and bacterial osteomyelitis (suppurative and sclerosing type), and the control group was 117 randomly sampled. The photographic density in a certain area of the digital panoramic radiograph was determined and compared using the "measure area rectangle," one of the basic PACS functions in INFINITT PACS^® (INFINITT Healthcare, Seoul, South Korea). A conditional inference tree, one type of decision making tree, was generated with the program R for statistical analysis with SPSS^®. Results: In the conditional inference tree generated from the obtained data, cases where the difference in average value exceeded 54.49 and the difference in minimum value was less than 54.49 and greater than 12.81 and the difference in minimum value exceeded 39 were considered suspicious of osteomyelitis. From these results, the disease could be correctly classified with a probability of 88.1%. There was no difference in photographic density value of BRONJ and bacterial osteomyelitis; therefore, it was not possible to classify BRONJ and bacterial osteomyelitis by quantitative analysis of panoramic radiographs based on existing research. Conclusions: This study demonstrates that it is feasible to measure photographic density using a basic function in PACS and apply the data to assist in the diagnosis of osteomyelitis.