• Korean Journal of Food Science and Technology
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• v.48 no.5
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• pp.418-423
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• 2016

This study was conducted to identify the geographical origin of soybeans in Cheonggukjang by analyzing its organic components and inorganic elements with Fourier transform near-infrared spectroscopy (FT-NIRS) and with energy dispersive X-ray fluorescence (ED-XRF) coupled with multivariate statistical analysis. For method development, 280 samples from various regions were collected and analyzed. The discriminant accuracy for the developed methods was 97.5% for FT-NIRS and 98.0% for ED-XRF with multivariate statistical analysis. A validation test confirmed the discriminant accuracy to be 96.3% for FT-NIRS and 95.0% for ED-XRF. Overall, the results showed that methods using FT-NIRS and ED-XRF could be used to identify the geographical origin of Cheonggukjang.

• Health Policy and Management
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• v.20 no.3
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• pp.123-137
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• 2010

The main purpose of this article is for deriving functions related to the prediction of the closure of the hospitals, and finding out how the discriminant functions affect the closure of the hospitals. Empirical data were collected from 3 years financial statements of 41 private hospitals closed down from 2000 till 2006 and 62 private hospitals in business till now. As a result, the functions related to the prediction of the closure of the private hospital are 4 indices: Return on Assets, Operating Margin, Normal Profit Total Assets, Interest expenses to Total borrowings and bonds payable. From these discriminant functions predicting the closure, I found that the profitability indices - Return on Assets, Operating Margin, Normal Profit Total Assets - are the significant affecting factors. The discriminant functions predicting the closure of the group of the hospitals, 3 years before the closure were Normal Profit to Gross Revenues, Total borrowings and bonds payable to total assets, Total Assets Turnover, Total borrowings and bonds payable to Revenues, Interest expenses to Total borrowings and bonds payable and among them Normal Profit to Gross Revenues, Total borrowings and bonds payable to total assets, Total Assets Turnover, Total borrowings and bonds payable to Revenues are the significant affecting factors. However 2 years before the closure, the discriminant functions predicting the closure of the hospital were Interest expenses to Total borrowings and bonds payable and it was the significant affecting factor. And, one year before the closure, the discriminant functions predicting the closure were Total Assets Turnover, Fixed Assets Turnover, Growth Rate of Total Assets, Growth Rate of Revenues, Interest expenses to Revenues, Interest expenses to Total borrowings and bonds payable. Among them, Total Assets Turnover, Growth Rate of Revenues, Interest expenses to Revenues were the significant affecting factors.

• Health Policy and Management
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• v.10 no.2
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• pp.1-21
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• 2000

This study reviewde various parametic and nonparametic method for forexasting hospital closures in Korea. We compared multivariate discriminant analysis, multivartiate logistic regression, classfication and regression tree, and neural network method based on hit ratio of each model for forecasting hospital closure. Like other studies in the literture, neural metwork analysis showed highest average hit ratio. For policy and business purposes, we combined the four analytical method and constructed a foreasting model that can be easily used to predict the probabolity of hospital closure given financial information of a hospital.

• Economic and Environmental Geology
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• v.27 no.3
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• pp.237-246
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• 1994

Tin mineralizations in South Korea have been found only in the Ulchin and Sangdong areas. They appear to be in close spatial association with the Wangpiri granitoid in the UlChin area, and the Nonggeori and Naedeogri granites in the Sangdong area. However, previous works have revealed that there are considerable differences in geological setting, mineralogical and geochemical compositions among these granitoids concerned. The roles of discriminant and multiple regression analysis have been examed to establish geochemical differences among the tin-granitoids and to identify elements relating to tin mineralizations. The data set used in this study consists of 60 observations with 29 elements which are cited from pre-existing publications. A stepwise discriminant analysis determined the group of variables that differentiate between samples from four training sets; Buncheon, Wangpiri, Nonggeori and Naedeogri granitoids. These granitoids were most effectively discriminated on the basis of major elements FeO, CaO and $P_2O_5$ and also by the trace elements Rb and Zr. Results of the multiple regression analysis shows that the level of Sn in granitoids depends positively on ones of MnO, Rb and FeO and negatively $P_2O_5$. Graphical representation of discriminant scores on sampling locations greatly aid recognition of differences in the geochemical characteristics in terms of spatial distribution of granitoids examed. The application of the discriminant analysis provides a potential means of identifying and comparing geochemical characteristics.

• Journal of the Korean Statistical Society
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• v.33 no.1
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• pp.1-24
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• 2004

This paper is concerned with statistical methods for multivariate data when the number p of variables is large compared to the sample size n. Such data appear typically in analysis of DNA microarrays, curve data, financial data, etc. However, there is little statistical theory for high dimensional data. On the other hand, there are some asymptotic results under the assumption that both and p tend to $\infty$, in some ratio p/n ${\rightarrow}$c. The results suggest that the new asymptotic results are more useful and insightful than the classical large sample asymptotics. The main purpose of this paper is to review some asymptotic results for high dimensional statistics as well as classical statistics under a high dimensional asymptotic framework.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.3
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• pp.237-245
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• 2004

In designing a tunnel, RMR has been widely used to classify rock mass and to decide the support pattern according to the class of rock mass. However, this RMS system can't help relying on the empirical judgment of engineers who use variables which can be obtained only through consideration of the site conditions. In actuality, it is impossible to consider all the rating factors of RMS when using RMR system at the stage of designing. Therefore, in order to confirm possibility of RMR by use of only the quantitative factors for designing, this paper has done discriminant analysis. Rock strength or RQD has high coefficient of correlation with RMR value, and in consideration of the existing standards for rock mass classification, rock intensity and RQD are important factors for classification of rock mass. Through rock mass classification by the existing RMR system and rock mass classification by the discriminant analysis which has considered two variables only, the discriminant analysis using the rock intensity as an independent variable has shown 74.8% accuracy while the discriminant analysis using RQD as an independent variable has shown 74.3% accuracy. In case of the discriminant analysis which has considered both rock intensity and RQD, it has shown 82.5% accuracy. The existing cases have shown 40.3% accuracy at the stage of designing in which all the RMR factors are considered. It means that at the stage of designing, RMR system can work only with the rock intensity and RQD.

• Korean Journal of Food Science and Technology
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• v.23 no.6
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• pp.711-716
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• 1991

Various multivariate statistics were applied to determine the relationships between sensory properties of 9 pre-cooked foods. Twelve sensory terms were selected to differentiate the food samples in stepwise discriminant analysis. Three factors accounted for 61.9% of total variation of 12 sensory attributes detected. Factor I was highly related to the qualitative sensory terms, while factor II to the quantitative ones. The principal component plot made it possible to define the relationships between sensory properties and food samples. In cluster analysis using average linkage and Ward's method, nine pre-cooked foods were classified into three clusters in terms of their sensorial similarities.

• Plant Biotechnology Reports
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• v.3 no.1
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• pp.87-93
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• 2009

To determine whether pattern recognition based on metabolite fingerprinting for whole cell extracts can be used to discriminate cultivars metabolically, leaves and fruits of five commercial strawberry cultivars were subjected to Fourier transform infrared (FT-IR) spectroscopy. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA) and Fisher's linear discriminant function analysis. The dendrogram based on hierarchical clustering analysis of these spectral data separated the five commercial cultivars into two major groups with originality. The first group consisted of Korean cultivars including 'Maehyang', 'Seolhyang', and 'Gumhyang', whereas in the second group, 'Ryukbo' clustered with 'Janghee', both Japanese cultivars. The results from analysis of fruits were the same as of leaves. We therefore conclude that the hierarchical dendrogram based on PCA of FT-IR data from leaves represents the most probable chemotaxonomical relationship between cultivars, enabling discrimination of cultivars in a rapid and simple manner.

• Journal of the Korean Home Economics Association
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• v.38 no.10
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• pp.45-51
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• 2000

This study illucidated the importance of drop Value in the resets of surveying the current values of sizing and grading. Therefore, it is meaningful to get the classification of body form with the appropriate distribution of drop values of the body. The distribution of drop value and the frequency of each form is very helpful to name the combined sizing or coverage of ready-made clothes. This study aimed at classifying body forms with various drop values using multivariate analysis for sizing and grading. Factor analysis and cluster analysis were done using measured values from unmarried women. The resets are as follows; The factor which explains body forms was obtained by factor analysis, and the representative major 18 items which have important roles in classifying body forms were selected among the measured values with high factor loading and communality. 1) The body forms were classified into 3 groups based on the characteristics, frequencies and distributions of them obtained from cluster analysis. 2) Each classified body form showed conspicuous difference in drop value and the difference of body form mainly resulted from the difference between bust and hip(drop value) in Korean unmarried women. 3) Discriminant analysis showed that the most significant discriminant factor of the trunk classification were bust circumference, upper bust circumference, hip circumference and stature. 4) The cover ratio of size studied in this study for the Korean Sizing system for women's garment were founded high.

• Horticultural Science & Technology
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• v.34 no.2
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• pp.324-330
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• 2016

To determine whether FT-IR spectral analysis based on multivariate analysis for whole cell extracts can be used to discriminate between artichoke (Cynara cardunculus var. scolymus L.) plants at the metabolic level, leaves of ten artichoke plants were subjected to Fourier transform infrared(FT-IR) spectroscopy. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and $1,100-950cm^{-1}$, respectively. These spectral regions reflect the quantitative and qualitative variations of amide I, II from amino acids and proteins ($1,700-1,500cm^{-1}$), phosphodiester groups from nucleic acid and phospholipid ($1,500-1,300cm^{-1}$) and carbohydrate compounds ($1,100-950cm^{-1}$). PCA revealed separate clusters that corresponded to their species relationship. Thus, PCA could be used to distinguish between artichoke species with different metabolite contents. PLS-DA showed similar species classification of artichoke. Furthermore these metabolic discrimination systems could be used for the rapid selection and classification of useful artichoke cultivars.