• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.4
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• pp.194-199
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• 2017

Power transformers are an important factor for power transmission and cause fatal losses if faults occur. Various diagnostic methods have been applied to predict the failure and to identify the cause of the failure. Typical diagnostic methods include the IEC diagnostic method, the Duval diagnostic method, the Rogers diagnostic method, and the Doernenburg diagnostic method using the ratio of the main gas. However, each diagnostic method has a disadvantage in that it can't diagnose the state of the power transformer unless the gas ratio is within the defined range. In order to solve these problems, we propose a diagnosis method using ELM based intelligent algorithm and fuzzy membership function. The final diagnosis is performed by multiplying the result of diagnosis in the four diagnostic methods (IEC, Duval, Rogers, and Doernenburg) by the fuzzy membership values. To show its effectiveness, the proposed fault diagnostic system has been intensively tested with the dissolved gases acquired from various power transformers.

• Journal of the Korea Safety Management & Science
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• v.2 no.4
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• pp.1-8
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• 2000

Equipment and machine of industrial plant are give effect to mechanical-stress of many working-stop or long time operating. Therefore, to be old and decrepit of every king of equipment. As long time operating equipment period into increase conservation and of repair equipment time is efficacious necessity of utility factor gradually that of productivity of diminution and complete equipment expense of increase. Conservation at special skill working and necessity is that will effectually and complete a period prevention management diagnosis can conservation point at issues at in advance.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2004.11a
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• pp.316-322
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• 2004

Wear volume was used generally to analyze the moving state of lubricated machine. But It is difficult of getting the correct wear volume because wear volume of it is progressed always unstably with a large amplitude on working condition. If correct analysis of wear volume on working condition for lubricated machine can be possible, it can be effect on diagnosis of failure condition. The purpose of this study is carried out to analysis friction factors affecting on wear volume for prediction of failure condition of alloy steel for machine structural use by design of experiment. The results show that the most important friction factors affecting on wear volume was applied load, neat sliding distance, sliding speed and materials.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.2
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• pp.185-190
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• 2010

Condition monitoring(CM) is a method based on non-destructive test(NDT). So, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days because of high sensitivity than common accelerometers and detectable low energy vibration signals. And crack is considered one of severe fault in the rotating machine. Therefore, in this paper, study on early detection using AE has been accomplished for the crack of the low-speed shaft. There is a seeded initial crack on the shaft then the AE signal had been measured with low-speed rotation as the applied load condition. The signal detected from crack in rotating machine was detected by the AE transducer then the trend of crack growth had found out by using some of feature values such as peak value, skewness, kurtosis, crest factor, frequency center value(FC), variance frequency value(VF) and so on.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.81-84
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• 1994

A clinically oriented EEG and EP mapping system was developed with user-friendly interface and easy interactive operations. The system was based on the graphical user interface developed with C/C++ and Software Development Kit (SDK) operated under Microsoft Windows 3.1. Continuous acquisition for the EEG signal and burst mode acquisition for EEG signal syncronized to the external stimuli arc implemented with real time display. A neural network based automatic artifact discrimation is developed and implemented with which examination time can be reduced by a factor of 3 or more. Several bands of spectral maps and spectrums arc displayed for EEG diagnosis. Amplitude maps of EP signal at specified times by operator are displayed together with cine mode of EP maps for dynamic study. Source localization and other statistical signal processing are also included.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.254-265
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• 2021

Purpose: Inspection and diagnosis on the performance and safety through domestic port facilities have been conducted for over 20 years. However, the long-term development strategies and directions for facility renewal and performance improvement using the diagnosis history and results are not working in realistically. In particular, in the case of port structures with a long service life, there are many problems in terms of safety and functionality due to increasing of the large-sized ships, of port use frequency, and the effects of natural disasters due to climate change. Method: In this study, the maintenance history data of the gravity type quay in element level were collected, defined as big data, and a predictive approximation model was derived to estimate the pattern of deterioration and aging of the facility of project level based on the data. In particular, we compared and proposed models suitable for the use of big data by examining the validity of the state-based deterioration pattern and deterioration approximation model generated through machine learning algorithms of GP and SGP techniques. Result: As a result of reviewing the suitability of the proposed technique, it was considered that the RMSE and R² in GP technique were 0.9854 and 0.0721, and the SGP technique was 0.7246 and 0.2518. Conclusion: This research through machine learning techniques is expected to play an important role in decision-making on investment in port facilities in the future if port facility data collection is continuously performed in the future.

• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.62-67
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• 2019

The purpose of this study was to evaluate the performance of deep neural network model in order to determine whether there is a risk factor for coronary artery disease based on the cardiac variation parameter. The study used unidentifiable 297 data to evaluate the performance of the model. Input data consists of heart rate parameters, which are SDNN (standard deviation of the N-N intervals), PSI (physical stress index), TP (total power), VLF (very low frequency), LF (low frequency), HF (high frequency), RMSSD (root mean square of successive difference) APEN (approximate entropy) and SRD (successive R-R interval difference), the age group and sex. Output data are divided into normal and patient groups, and the patient group consists of those diagnosed with diabetes, high blood pressure, and hyperlipidemia among the various risk factors that can cause coronary artery disease. Based on this, a binary classification model was applied using Deep Neural Network of deep learning techniques to classify normal and patient groups efficiently. To evaluate the effectiveness of the model used in this study, Kernel SVM (support vector machine), one of the classification models in machine learning, was compared and evaluated using same data. The results showed that the accuracy of the proposed deep neural network was train set 91.79% and test set 85.56% and the specificity was 87.04% and the sensitivity was 83.33% from the point of diagnosis. These results suggest that deep learning is more efficient when classifying these medical data because the train set accuracy in the deep neural network was 7.73% higher than the comparative model Kernel SVM.

• Journal of Chest Surgery
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• v.13 no.3
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• pp.174-185
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• 1980

It was my great nohour that I can be exposed to such plenty materials of the coronary bypass surgery. Here, I am summarizing the xoronary bypass surgery, clinically. The material is serial 101 patients who underwent coronary bypass surgery between July 17, 1979 to November 30, 1979 in Shadyside Hospital, University of Pittsburgh. 1. Incidence of the Atherosclerosis is frequent in white, male, fiftieth who are living in industrialized country. It has been told the etiologic factor of the atherosclerosis is hereditary, hyperlipidemia, hypertension, smoking, drinking, diabetes, obesity, stress, etc. 2. The main and most frequent complication of the coronary atherosclerosis is angina pectoris. Angina pectoris is the chief cause of coronary bypass surgery and the other causes of coronary bypass surgery are obstruction of the left main coronary artery, unstable angina, papillary muscle disruption or malfunction and ventricular aneurysm complicated by coronary artery disease. 3. The preoperative clinical laboratory examination shows abnormal elevation of plasma lipid in 82 patint, plasma glucose in 40 patient, total CPK-MB in 24 patient stotal LDH in 22 patient out of 101 patient. 4. Abnormal ECG findings in preoperative examine were 29.1% myocardial infarction, 25.8% ischemia and injury, 14.6T conduction defect. 5. Also we had done Echocardiography, Tread Mill Test, Myocardial Scanning, Vectorcardiography and Lung function test to get adjunctive benefit in prediction of prognosis and accurate diagnosis. 6. The frequency of coronary atherosclerosis in main coronary arteries were LAD, RCA and Circumflex in that order. 7. The patients' main complaints which were became as etiologic factor undergoing coronary bypass surgery were angina, dyspnea, diaphoresis, dizziness, nausea and etc. 8. For the coronary bypass surgery, we used cardiopulmonary bypass machine, non-blood, diluting prime, cold cardioplegic solution and moderate cooling for the myocardial protection. 9. We got the grafted veins from Saphenous and Cephalic vein. Reversed and anastomosed between aorta and distal coronary A. using 5-0 and 7-0 prolene continuous suture. Occasionally we used internal mammary A. as an arterial blood source and anastomosed to the distal coronary A. and to side fashion. 10. The average cardiopulmonary bypass time for every graft was 43.9 min. and aortic clamp time was 23 minute. We could Rt. coronary A. bypass surgery only by stand by the cardiopulmonary machine and in the state of pumping heart. 11. Rates by the noumbers of graft were as follow : 21.8% single, 33.7% double, 26.7% triple, 13.9% quadruple, 3% quintuple and 1% was sixtuple graft. 12. combined procedures with coronary bypass surgery were 6% aneurysmectomy, 3% AVR, 1% MVR, 13% pacer implantation and 1% intraaortic ballon setting. 13. We could see the complete abolition of anginal pain after operation in 68% of patient, improvement 25.8%, no change in 3.1%, and there was unknown in 3%. 14. There were 4% immediate postoperative deaths, 13.5% some kinds of heart complication, 51.3% lung complications 33.3% pleural complications as prognosis.

• The Journal of the Korean Society for Microbiology
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• v.3 no.1
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• pp.15-23
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• 1968

For the effective control of Syphilis, many investigators have developed a more rapid, simple and economical screening serological test which is adequately sensitive and specific. To fulfill the requirements of a more rapid serologic test for syphlis, a substitute for the conventional serum specimen was needed since considerable time and labor are involved in the processing of blood to serum. Burdon suggested the use of plasma in the serologic tests for syphilis as a substitute for serum. He noticed that plasma was more sensitive than serum in the Kline and Kahn tests, and attributed this to the presence of more antibody-like substance, "reagin" in plasma than in serum. However, to make plasma sufficiently sensitive, it was necessary to inactivate plasma by heating at a temperature of $56^{\circ}C$ for about 30 minutes. Heating of plasma resulted in the precipitation of fibrinogen which made centrifugation necessary to obtain dear plasma. Since the chief disadvantage to the use of unheated plasma(or serum) was a reduction in sensitivity of results-which probably was due to a labile factor such as complement-Portnoy et al began to consider rapid chemical methods of inactivation of plasma(or serum). They experienced that choline chloirde was shown to be anticomplementary which suggested its use as an inactivating agent for unheated plasma(or serum). In 1959 Portnoy et al reported the Rapid Plasma Reagin(RPR) Test for syphilis which is a more rapid, economical and simple. But still this test has many disadvantages as a rapid performing, field and office procedure, because it requires the usual laboratory equipments such as centrifuge, rotating machine, microscope etc. To substitute these disadvantages of the RPR test, in 1962, Portnoy et al developed the Rapid Plasma Reagin(RPR) card test for syphilis, which has the following advantages: a) Simplicity and rapidity of performance, b) Requires no laboratory equipments, c) Stable antigen suspension, d) Adequate sensitivity and specificity. This RPR card test can be used as a rapidly performing and screening test in field investigation, outpatient clinics, small laboratories and hospitals doing limited syphilis serology, and predonor in blood bank. Private clinic which has limited laboratory equipment and technic for syphilis serology can also use this RPR card test as a tool in the rapid diagnosis of syphilis. It was thought that this RPR card test is a useful tool in Korea for private physician and mass survey for syphilis diagnosis. But Portnoy patented the reagents needed for the performing the RPR card test. Therefore authors developed newly the reagents and according to Portnoy's method evaluated the newly developed. RPR card test compared with the VDRL, Kolmer CF, and RPCF tests. The RPR card and VDRL tests were performed plasma and serum from the total 1,132 cases. Among these 1,131 cases, 521 were syphilis suspected laboratory specimens, and 611 were syphilis unsuspected healthy young men. After screening with these two tests, the RPR card and VDRL tests, reactive specimens to the above one or both tests were retested by the Kolmer CF and RPCF tests.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.1-9
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• 2023

Research using AI and big data is also being actively conducted in the health and medical fields such as disease diagnosis and treatment. Most of the existing research data used cohort data from research institutes or some patient data. In this paper, the difference in the prediction rate of survival and the factors affecting survival between breast cancer patients in their 40~50s and other age groups was revealed using health insurance review claim data held by the HIRA. As a result, the accuracy of predicting patients' survival was 0.93 on average in their 40~50s, higher than 0.86 in their 60~80s. In terms of that factor, the number of treatments was high for those in their 40~50s, and age was high for those in their 60~80s. Performance comparison with previous studies, the average precision was 0.90, which was higher than 0.81 of the existing paper. As a result of performance comparison by applied algorithm, the overall average precision of Decision Tree, Random Forest, and Gradient Boosting was 0.90, and the recall was 1.0, and the precision of multi-layer perceptrons was 0.89, and the recall was 1.0. I hope that more research will be conducted using machine learning automation(Auto ML) tools for non-professionals to enhance the use of the value for health insurance review claim data held by the HIRA.