• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.19-31
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• 2005

Brain injured patients who had the driver's license before the injury of the brain were tested with the newly developed tool CPAD by Hangyang Medical School and the National Rehabilitation Center. The CPAD contains many variables to measure the ability of driving. Also for each patient the American standard CBDI score was measured and the result was compared with the CPAD results. Of interest is to classify the patients as pass, border, fail group after the CPAD test. To derive the discriminant functions with the group information based on CBDI, parametric/nonparametric and multivariate/univariate discriminant analysis was performed and discussed.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.831-842
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• 1999

We propose a wavelet decomposition feature extraction method for the hand-written character recognition. Comparing the recognition rates of which methods with original image features and with selected features by the wavelet decomposition we study the characteristics of the proposed method. LDA(Linear Discriminant Analysis) QDA(Quadratic Discriminant Analysis) RDA(Regularized Discriminant Analysis) and NN(Neural network) are used for the calculation of recognition rates. 6000 hand-written numerals from CENPARMI at Concordia University are used for the experiment. We found that the set of significantly selected wavelet decomposed features generates higher recognition rate than the original image features.

• Bulletin of the Korean Mathematical Society
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• v.49 no.1
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• pp.75-88
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• 2012

A new algorithm is proposed for the construction of Brezing-Weng-like elliptic curves such that polynomials defining the CM discriminant are linear. Using this construction, new families of curves with variable discriminants and embedding degrees of $k{\in}\{8,16,20,24\}$, which were not covered by Freeman, Scott, and Teske [9], are presented. Our result is useful for constructing elliptic curves with larger and more flexible discriminants.

• Korean Journal of Remote Sensing
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• v.6 no.1
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• pp.11-24
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• 1990

This is the study about the meteorological satellite cloud image classification by objective methods. For objective cloud classification, linear discriminant analysis was tried. In the linear discriminant analysis 27 cloud characteristic parameters were retrieved from GMS infrared image data. And, linear cloud classification model was developed from major parameters and cloud type coefficients. The model was applied to GMS IR image for weather forecasting operation and cloud image was classified into 5 types such as Sc, Cu, CiT, CiM and Cb. The classification results were reasonably compared with real image.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.2
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• pp.399-413
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• 2015

This study was to validate the WSSECT (Workplace Spirituality Scale for Early Childhood Teacher) using discriminant analysis on early childhood teachers' happiness and job satisfaction. The data from 504 teachers working at kindergartens and daycare centers were analyzed statistically through t-test and discriminant analysis. The results indicated that 1) the higher group in workplace spirituality significantly gets more scores of happiness and job satisfaction than the lower group, 2) 4 factors of the WSSECT have discriminant power on early childhood teachers' happiness, and 3) 2 factors ('meaning for life' and 'calling for ECE teacher job') of the WSSECT are effective to discriminate early childhood teachers' job satisfaction. Further statistical works are supplementary needed to validate the WSSECT and to increase its'feasibility.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.511-518
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• 2008

Medical diagnosis systems have been developed to make the knowledge and expertise of human experts more widely available, therefore achieving high-quality diagnosis. In this study, in order to support the diagnosis by the medical diagnosis system, we have preformed medical diagnosis inference three times: first by a neural network with the backpropagation algorithm, secondly by a discriminant analysis with all of the variables, and thirdly by a discriminant analysis with the selected variables. A discussion on comparison of these three methods has been provided.

• Korean journal of applied entomology
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• v.32 no.1
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• pp.30-41
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• 1993

In the present investigation, some multivariate discriminant analyses were done for each population of the native honeybee workers (Apis cerana), which were selected for 15 different localities in spring and 16 in summer form Korea. when the comparison of both seasons for different populations and regardless of seasons were conducted, all the classification results revealed that the differences were significantly prominent. And the length of fore tibia(FTL) was the best contributed character among the 47 morphometric characters used in the analysis.

• Culinary science and hospitality research
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• v.9 no.1
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• pp.65-80
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• 2003

The purpose of this study was to identify the college students'frequent usage groups of Western style restaurant in Ansan city. 200 samples among subjects were utilized for the analysis, and 150 samples were reserved far validating the discriminant function. Crosstabs, reliability analysis, stepwise discriminant analysis, and anova analysis were used for this study. The findings from this study were as follows. First, the result suggested that the four variables were important in discriminating the frequent usage group. Second, the result suggested that each discriminating variable between frequent usage groups was different significantly. Third, the result suggested that each usage situation between frequent usage groups was different significantly. Finally the study indicated the implications that could be provided some insight into the types of marketing strategies that can be successfully used by operators who manage Western style restaurants.

• MALSORI
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• no.64
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• pp.77-88
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• 2007

Nowadays, mel-frequency cesptral coefficients (MFCCs) and Gaussian mixture models (GMMs) are used for the pathological voice detection. This paper suggests a method to improve the performance of the pathological/normal voice classification based on the MFCC-based GMM. We analyze the characteristics of the mel frequency-based filterbank energies using the fisher discriminant ratio (FDR). And the feature vectors through the linear discriminant analysis (LDA) transformation of the filterbank energies (FBE) and the MFCCs are implemented. An accuracy is measured by the GMM classifier. This paper shows that the FBE LDA-based GMM is a sufficiently distinct method for the pathological/normal voice classification, with a 96.6% classification performance rate. The proposed method shows better performance than the MFCC-based GMM with noticeable improvement of 54.05% in terms of error reduction.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.193-217
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• 2001

Despite of the rich literature in discriminant analysis, this complicated subject remains much to be explored. In this article, we study the theoretical foundation that supports Fisher's linear discriminant analysis (LDA) by setting up the classification problem under the dimension reduction framework as in Li(1991) for introducing sliced inverse regression(SIR). Through the connection between SIR and LDA, our theory helps identify sources of strength and weakness in using CRIMCOORDS(Gnanadesikan 1977) as a graphical tool for displaying group separation patterns. This connection also leads to several ways of generalizing LDA for better exploration and exploitation of nonlinear data patterns.