• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1913-1920
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• 2009

An intelligent accurate sun tracking controller for solar lighting system was developed. This controller can detect the faulty sensor and correct the error signal based on Principle Component Analysis theory. A fuzzy controller was developed to control the tracker by using the collected sensor signal for precise position control. Also a multiple range searching sensor module for sun tracking was designed. To show the validity of the developed system, some experiments in the field were illustrated.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.79-84
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• 2021

A feature extraction method capable of reflecting features well while mainaining the properties of data is required in order to process high-dimensional data. The principal component analysis method that converts high-level data into low-dimensional data and express high-dimensional data with fewer variables than the original data is a representative method for feature extraction of data. In this study, we propose a principal component analysis method based on adaptive correlation when selecting principal component variables in principal component analysis for data feature extraction when the data is high-dimensional. The proposed method analyzes the principal components of the data by adaptively reflecting the correlation based on the correlation between the input data. I want to exclude them from the candidate list. It is intended to analyze the principal component hierarchy by the eigen-vector coefficient value, to prevent the selection of the principal component with a low hierarchy, and to minimize the occurrence of data duplication inducing data bias through correlation analysis. Through this, we propose a method of selecting a well-presented principal component variable that represents the characteristics of actual data by reducing the influence of data bias when selecting the principal component variable.

• Journal of Pharmacopuncture
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• v.15 no.4
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• pp.42-51
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• 2012

Objectives: This study used the basic principle of Oriental medicine, the sovereign, minister, assistant and courier principle (君臣佐使論) to investigate the effects of the component of ONGABO, which is composed of Ginseng Radix (Red Ginseng), Angelica Gigantis Radix, Schisandrae Fructus, Cuscuta Semen and Curcumae tuber on the viability of HepG2 cells. Methods: Single and mixed extracts of the component of ONGABO were prepared by lypohilizing powder of Red Ginseng (6-year root from Kanghwa), Angelica Gigantis Radix, Schisandrae Fructus, Cuscuta Semen, Curcumae Tuber (from Omniherb Co., Ltd., Korea) at the laboratory of herbal medicine in Woosuk University and were eluted after being macerated with 100% ethanol for three days. The cell viability of HepG2 was determined by using an absorptiometric analysis with PrestoBlue (Invitrogen) reagent after the plate had been incubated for 48 hours. All of the experiments were repeated three times to obtain the average value and standard deviation. The statistical analysis was done and the correlation factor was obtained by using Microsoft Office Excel 2007 and Origin 6.0 software. Results: Although Ginseng Radix (Red Ginseng) and Schisandrae Fructus did not enhance the viability of HepG2 cells, they were shown to provide protection of those cells. On the other hand, Angelica Gigantis Radix decreased the viability of HepG2 cells significantly, Cuscuta Semen and Curcumae Tuber had a small or no effect on the viability of HepG2 cells. Conclusions: In the sovereign, minister, assistant and courier principle (君臣佐使論), Ginseng Radix (Red Ginseng) corresponds to the sovereign component because it provides cell protection effects, Angelica Gigantis Radix corresponds to minister medicinal because it kills cells, Schisandrae Fructus corresponds to the assistant medicinal to help red ginseng having cell protect effects. Cuscuta Semen and Curcumae Tuber correspond to the courier medicinal having no effect in cell viability in HepG2. We hope this study provides motivation for advanced research on the sovereign, minister, assistant and courier principle.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.153-161
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• 1999

For composing the structure model of national maritime power system by system structural modelling, in this study, the 50 basic factors are selected by survey of the extensive and thorough literatures on maritime, sea, maritime power and sea power. And the basic factors are classified into 36 component factors by cluster method. The 9 attributes are extracted by the application of the principle component analysis method, one of the factor analysis method in system engineering, to component factors. We defined the attributes composing the national maritime power system by integration the result of this study and existed our studies relate to this topic. Which are showed in table 8. and we showed the structure model of national maritime power system in figure 3. In table 8, the 9 attributes are as follows: the fundamental power of maritime, shipping and port power, naval power, fishing power, shipbuilding power, the power of ocean research and development, dependency on seaborne trade, the protection power of ocean environment and the will and inclination of government.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.600-605
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• 2003

PCA(Principle Component Analysis) has emerged as a useful tool for process monitoring and fault diagnosis. The general approach requires the user to identify the root cause by interpreting the residual or principle components. This could be tedious and often impossible for a large process. In this paper, PCA scheme is combined with the FCM-based fault diagnostic algorithm to enhance the diagnostic results. The implementation of the FCM-based fault diagnostic system by using PCA is done and its application is illustrated on the two-tank system.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.159-166
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• 2009

In this paper, we analyse the noise robustness of MLPs(Multilayer perceptrons) through deriving the probability density function(p.d.f.) of output nodes with additive input noises and the misclassification ratio with the integral form of the p.d.f. functions. Also, we propose linear preprocessing methods to improve the noise robustness. As a preprocessing stage of MLPs, we consider ICA(independent component analysis) and PCA(principle component analysis). After analyzing the noise reduction effect using PCA or ICA in the viewpoints of SNR(Singal-to-Noise Ratio), we verify the preprocessing effects through the simulations of handwritten-digit recognition problems.

• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.814-821
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• 2007

This study was estimated water quality to raw water quality management of the Maeri intake station in the Nakdong River using Multivariate Analysis. The results of Principle Component Analysis was explained up to 76.9% of total water quality by three principle components. The 1st, 2nd was explained 44.7%, 17.9% and third was explained 14.3%. Also, the three factors was derived from Factor Analysis. The 1st factor was estimated as the matabolism and organic matter pattern related to algal growth. The 2nd factor was judged as the pollution of pattern related to the discharge from stream of the Nakdong River and 3rd factor was viewed as the hydrological variation pattern related to particle matter. The results of Cluster Analysis were classified into three groups.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.75-80
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• 2002

Putnam develops SLIM (Software LIfecycle Management) model based upon the assumption that the manpower utilization during software project development is followed by a Rayleigh distribution. To obtain the manpower distribution, we have to be estimate the total development effort and difficulty ratio parameter. We need a way to accurately estimate these parameters early in the requirements and specification phase before investment decisions have to be made. Statistical tests show that system attributes are highly correlation (redundant) so that Putnam discards one and get a parameter estimator from the other attributes. But, different statistical method has different system attributes and presents different performance. To select the principle system attributes, this paper uses the principle component analysis (PCA) instead of Putnam's method. The PCA's results improve a 9.85 percent performance more than the Putnam's result. Also, this model seems to be simple and easily realize.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.63-70
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• 2016

A housing market in an urban area is not just a single market but a combination of regionally different submarkets. This study begins with a critical mind that previous researches did not consider the spatial autocorrelation of each area where the housings are located. The clustering analysis of housing submarket which considers spatial autocorrelation is performed as it follows. First, 4 housing market attribute variables are reducted to 1 variable by principle component analysis. Then, after calculating $Gi^*max$ by AMOEBA, 7 housing submarkets which have similar characteristics based on $Gi^*max$ are classified. The characteristics of each submarket are investigated, then political implication is deduced as the following. Different level of housing policy should be made to each cluster because each cluster has different level of spatial autocorrelation.

• Journal of the Korean Solar Energy Society
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• v.39 no.3
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• pp.67-79
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• 2019

The reliable Typical Meteorological Year (TMY) data, sometimes called Test Reference Year (TRY) data, are necessary in the feasibility study of renewable energy installation as well as zero energy building. In Korea, there are available TMY data; TMY from Korea Institute of Energy Research (KIER), TRY from the Korean Solar Energy Society (KSES) and TRY from Passive House Institute Korea (PHIKO). This study aims at examining their characteristics by using Principle Component Analysis (PCA) at six ground observing stations. First step is to investigate the annual averages of meteorological elements from TMY data and their standard deviations. Then, PCA is done to find which principle components are derived from different TMY data. Temperature and solar irradiance are determined as the main principle component of TMY data produced by KIER and KSES at all stations whereas TRY data from PHIKO does not show similar result from those by KIER and KSES.