• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.754-759
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• 2001

In this paper, we propose a TSK(Takagi-Sugeno-Kang)-type fuzzy classifier using PCA(Principal Component Analysis), FCM(Fuzzy c-Means) clustering, ANFIS(Adaptive Neuro-Fuzzy Inference System) and hybrid GA(Genetic Algorithm). First, input data is transformed to reduce correlation among the data components by PCA. FCM clustering is applied to obtain a initial TSK-type fuzzy classifier. Parameter identification is performed by AGA(Adaptive GA) and RLSE(Recursive Least Square Estimate). Finally, we applied the proposed method to Iris data classificationl problems and obtained a better performance than previous works.

• Korea Journal of Hospital Management
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• v.10 no.2
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• pp.26-44
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• 2005

The purpose of this study was to investigate these major factors on patient satisfaction, and to examine the affecting level of major factors in. The subjects in this study was 70 hospitals that were surveyed the hospital evaluation program containing the survey of patient satisfaction by KHIDI(Korea Health Industry Development Institute) from 1997 to 1999. The collected data was analysed SPSS for Windows(Ver 10.0). On basically, frequency analysis, t-test, and ANOVA was performed and, for more analysis, correlation analysis, factor analysis, multiple regression analysis, logistic regression analysis was utilized. According to this study, the major factors of inpatient satisfaction are divided 3 types facility factor, manpower factor, and service factor. And the major factors of outpatient satisfaction are analyzed 5 types; facility factor related direct medical service, facility factor related indirect medical services, manpower factor, pharmacy factor, and facility factor related utilization convenience. The importance of this study lies in the identification of major factors on hospital patient satisfaction.

• Bulletin of the Korean Chemical Society
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• v.28 no.2
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• pp.200-206
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• 2007

Pharmacophore models for lymphocyte-specific protein tyrosine kinase (P56 LCK) were developed using CATALYST HypoGen with a training set comprising of 25 different P56 LCK inhibitors. The best quantitative pharmacophore hypothesis comprises of one hydrogen bond acceptor, one hydrogen bond donor, one hydrophobic aliphatic and one ring aromatic features with correlation coefficient of 0.941, root mean square deviation (RMSD) of 0.933 and cost difference (null cost-total cost) of 66.23. The pharmacophore model was validated by two methods and the validated model was further used to search databases for new compounds with good estimated LCK inhibitory activity. These compounds were evaluated for their binding properties at the active site by molecular docking studies using GOLD software. The compounds with good estimated activity and docking scores were evaluated for physiological properties based on Lipinski's rules. Finally 68 compounds satisfied all the properties required to be a successful inhibitor candidate.

• Proceedings of the Ginseng society Conference
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• 1980.09a
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• pp.59-69
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• 1980

A new HPLC-method for separation and quantitative determination of ginsenosides in Panax ginseng, Panax quinquefolium and in pharmaceutical drug preparations is elaborated. A reversed-phase-system with ${\mu}Bondapak\;C_{18}$ column (3.9 mm $I.D.{\times}30\;cm$) using acetonitrile-water (30:70) 2 ml/min and acetonitrile-water (18:82) 4 ml/min is suitable for the base-line separation of $Rb_1,\;Rb_2,\;Rc,\;Rd,\;Rf,\;Rg_2,\;respectively\;Re,\;Rg_1$ in 30 minutes. The ginsenosides are directly detected at 203 nm (without derivatization) with the LC-55 or LC-75 spectrophotometer (Perkin-Elmer) at $100\%$ transmission. Detection limit is 300 ng at a signal-to-noise ratio of 10:1. The ginsenosides-peak identification is carried out with HPTLC (high performance thin layer chromatography), with MIR-IR (multiple internal reflection-IR-spectros-copy) and with FD-MS (field desorption mass spectrometry). The calibration curve of each ginsenoside has a correlation coefficient very near to 1. Relative standard deviation for quantitative determinations depends upon the amount of ginsenosides and is approximately 1\%$ for ginsenoside contents of 1\%$. This method is adaptable for routine analysis in quality control laboratories.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.33-38
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• 2020

Anomaly detection of Machine Learning such as PCA anomaly detection and CNN image classification has been focused on cross-sectional data. In this paper, two approaches has been suggested to apply ML techniques for identifying the failure time of big time series data. PCA anomaly detection to identify time rows as normal or abnormal was suggested by converting subjects identification problem to time domain. CNN image classification was suggested to identify the failure time by re-structuring of time series data, which computed the correlation matrix of one minute data and converted to tiff image format. Also, LASSO, one of feature selection methods, was applied to select the most affecting variables which could identify the failure status. For the empirical study, time series data was collected in seconds from a power generator of 214 components for 25 minutes including 20 minutes before the failure time. The failure time was predicted and detected 9 minutes 17 seconds before the failure time by PCA anomaly detection, but was not detected by the combination of LASSO and PCA because the target variable was binary variable which was assigned on the base of the failure time. CNN image classification with the train data of 10 normal status image and 5 failure status images detected just one minute before.

• Earthquakes and Structures
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• v.8 no.4
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• pp.821-841
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• 2015

This paper proposes a two-stage imaging approach for quantitative inspection of damages in metallic plates using the fundamental anti-symmetric mode of ($A_0$) Lamb wave. The proposed approach employs a number of transducers to transmit and receive $A_0$ Lamb wave pulses, and hence, to sequentially scan the plate structures before and after the presence of damage. The approach is applied to image the corrosion damages, which are simplified as a reduction of plate thickness in this study. In stage-one of the proposed approach a damage location image is reconstructed by analyzing the cross-correlation of the wavelet coefficient calculated from the excitation pulse and scattered wave signals for each transducer pairs to determine the damage location. In stage-two the Lamb wave diffraction tomography is then used to reconstruct a thickness reduction image for evaluating the size and depth of the damage. Finite element simulations are carried out to provide a comprehensive verification of the proposed imaging approach. A number of numerical case studies considering a circular transducer network with eight transducers are used to identify the damages with different locations, sizes and thicknesses. The results show that the proposed methodology is able to accurately identify the damage locations with inaccuracy of the order of few millimeters of a circular inspection area of $100mm^2$ and provide a reasonable estimation of the size and depth of the damages.

• 한국지구물리탐사학회:학술대회논문집
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• 1999.08a
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• pp.156-175
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• 1999

Recently the application of geophysical well logging to geotechnical site investigation is increasing, because the merit that geophysical logs provide the high resolution and in-situ physical properties in volumes of rock surrounding the borehole. Geophysical well logs are used to identify lithologic boundaries and fracture, to determine the physical properties of rock(i.e., density, velocity etc.), and to detect permeable fracture zones that could be conduits for ground water movement through the rocks. The principle of heat-pulse meter, the calibration of gamma-gamma logging, and principles and data processing of full waveform sonic logging are briefly reviewed, and the case studies of geophysical logs are discussed. Correlation between velocity by sonic logging and rock mass classification such as RMR(Rock Mass Rating) value is considered.

• Journal of Korean Biological Nursing Science
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• v.21 no.4
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• pp.283-291
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• 2019

Purpose: The aim of this study was to identify awareness and competency for Multi-Drug Resistant Organisms (MDRO) infection control in nursing students with experience of clinical practice. Methods: This cross-sectional descriptive study was conducted from March 2019 to May 2019 by including 231 nursing students in four nursing schools located in Seoul, Gyeonggi-do and Chungcheongnam-do. The data were collected using self-report questionnaires. Results: The awareness and the competency for Carbapenem-Resistant Enterobacteriaceae (CRE) infection control were lower than that of Methicillin-Resistant Staphylococcus aureus (MRSA). The agreement between the awareness and the competency of MDRO infection control in participants was low with regard to isolation, contact precautions, and disinfection for MRSA. Also, it was low with respect to disinfection, isolation, contact precautions, and carrier identification for CRE. The awareness and the competency of MDRO infection control exhibited significant positive correlation. Conclusion: The infection control competency is required to prevent MDRO infection. In order to enhance the infection control competency, it is important to raise awareness about MDRO infection control by providing education based on the guidelines and the principles of infection control.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.267-272
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• 2010

This paper suggests an evaluation method through corporate culture's evaluation model considering the relationship and affection between types and elements of corporate culture. 314 data obtained from the members of small and medium enterprises analyzed the relationship by the correlation analysis, and the degree affecting rate the corporate culture types by the regression analysis. Finally, fuzzy system was used to analyze the evaluation model of the corporate culture type. The evaluation model of the corporate culture types in this paper is mixed possibility and necessity sides and showed the usefulness through reviewing the model which has an identification problem of the fuzzy system estimated fuzzy relation matrix for corporate culture types using the model.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.5
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• pp.373-378
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• 1999

In order to analyse the degradation mechanism of polymer materials for outdoor condition, FRP laminate was exposed to high temperature and ultraviolet rays. Then, thedegradation process was evaluated by comparing contact angle, surface potential decay, and polarity effect respectively. Especially, the analysis of surface degradation phenomena by corona charging method showed the exact correlation with the result of chemical properties. Therefore we can confirm that the application of corona charging method on the identification of degradation process is very useful. If this method is usedin degradation studies on the polymer surface, it will be more effective on the surface analysis of polymer insulators. With corona charging method and chemical spectrum analysis, it was possible concretely to define degradation process on the polymer surface exposed at the situation of different environmental conditions.