• 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.

• Journal of Korea Technology Innovation Society
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• v.10 no.2
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• pp.183-205
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• 2007

An investigation was undertaken of the optimal discriminant model for predicting the likelihood of insolvency in advance for medium-sized firms based on the technology evaluation. The explanatory variables included in the discriminant model were selected by both factor analysis and discriminant analysis using stepwise selection method. Five explanatory variables were selected in factor analysis in terms of explanatory ratio and communality. Six explanatory variables were selected in stepwise discriminant analysis. The effectiveness of linear discriminant model and logistic discriminant model were assessed by the criteria of the critical probability and correct classification rate. Result showed that both model had similar correct classification rate and the linear discriminant model was preferred to the logistic discriminant model in terms of criteria of the critical probability In case of the linear discriminant model with critical probability of 0.5, the total-group correct classification rate was 70.4% and correct classification rates of insolvent and solvent groups were 73.4% and 69.5% respectively. Correct classification rate is an estimate of the probability that the estimated discriminant function will correctly classify the present sample. However, the actual correct classification rate is an estimate of the probability that the estimated discriminant function will correctly classify a future observation. Unfortunately, the correct classification rate underestimates the actual correct classification rate because the data set used to estimate the discriminant function is also used to evaluate them. The cross-validation method were used to estimate the bias of the correct classification rate. According to the results the estimated bias were 2.9% and the predicted actual correct classification rate was 67.5%. And a threshold value is set to establish an in-doubt category. Results of linear discriminant model can be applied for the technology financing banks to evaluate the possibility of insolvency and give the ranking of the firms applied.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.04a
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• pp.237-241
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• 2005

The physical and chemical characteristics of soils in a small watershed were investigated and the effect of geology and land use on soil quality were examined by using multivariate statistical methods, principal components analysis and discriminant analysis. It was considered that the accumulation of salts in the farmland soils indicated by electrical conductivity, contents of cations and anions and pH was caused by fertilizer input during cultivation. The contents of inorganic components are increased as following order: upland > orchard > paddy field > forest. The results of two discriminant analyses using water extractable inorganic components and their ratios by land use were also clearly classified by discriminant function 1 and 2. In discriminant analysis by components, discriminant function 1 indicated the effect of fertilizer application and increased as following order: upland > orchard > paddy field > forest soil.

• Journal of Biosystems Engineering
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• v.24 no.4
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• pp.325-334
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• 1999

The aim of this study was to present a groundwork for development of a sorting system of peeled garlics using machine vision. Images of various garlic samples such as sound, partially defective, discolored, rotten and un-peeled were obtained with a B/W machine vision system. Sorting factors which were based on normalized histogram and statistical analysis(STEPDISC Method) had good separability for various garlic samples. Bayes discriminant function and neural network sorting algorithms were developed with the sample images and were experimented on various garlic samples. It was showed that garlic samples could be classified by sorting algorithm with average sorting accuracies of 88.4% by Bayes discriminant function and 93.2% by neural network.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.5
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• pp.573-581
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• 2002

This study was done to classify children's somatotypes and to provide the fundamental data or their clothing sizing system for the purpose of designing patterns fur children's wear and standardizing sizes of ready-made clothes. The sampling was done for 7-8 years-old-girl living in Pusan and Kyungsangnam-do. Data from each girl comprises 33 anthropometic measurments and 7 photogrphic measurments, based on the somatometric characteristics of girls which I had obtained. Factor analysis, cluster analysis, discriminant analysis were performed for statistical analysis of the data. Seven factors which explain 76.49% of the whole variances were extracted. The thirst and second factors which explain more than 70% of the whole variances represent 'horizontal size 'and 'vortical size', which characterize most aspects of the body shape of the subjects. On the basis of the cluster analysis, three different upper body types were categorized. Type 1 has quite long surface length of the upper body and rising shoulders and are close to the averages of this age group. Type 2 has highest stature, biggest frame, dropped shoulders and surface length of the upper body similar to the type 1. Type 3 has shortest stature, smallest frame and sloping shoulders. According to the analysis to discriminate somatotypes of the upper body by this age group, the discriminative items in discriminant function are follows. As this group, waist circumference of discriminant function 1 and front length and length between both shoulder points of discriminant function 2 have large coefficient values.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1179-1189
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• 2017

In this study, we propose an alternative method for discriminant analysis using a multivariate empirical distribution function to express multivariate data as a simple one-dimensional statistic. This method turns to be the estimation process of the optimal threshold based on classification accuracy measures and an empirical distribution function of data composed of classes. This can also be visually represented on a two-dimensional plane and discussed with some measures in ROC curves, surfaces, and manifolds. In order to explore the usefulness of this method for discriminant analysis in the study, we conducted comparisons between the proposed method and the existing methods through simulations and illustrative examples. It is found that the proposed method may have better performances for some cases.

• International Commerce and Information Review
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• v.8 no.3
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• pp.71-95
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• 2006

In recent, T-commerce is widely dispersed as alternative type of commerce. It is forecasted that t-commerce system is used more than e-commerce system. Therefore more and more t-commerce-related industries are also recognizing that t-commerce is a critical business model. It is needed to understand the concept of t-commerce and develop the t-commerce marketing strategy. CEO analyses consumer's behaviors according to the data about buyers and applies the advantage of t-commerce to the communication with customers. This t-commerce system plays an important role in maximizing customer satisfaction and affecting their intention to reuse it. Therefore this paper attempts to identify T-commerce critical success factors and divide between use-intention group and unuse-intention group by taking out a discriminant function by the discriminant analysis. This lays a foundation in developing T-commerce strategy. According to the discriminant function extracted, convenience factor, amusement factor, system quality factor, product perception factor are significant in the sequence of influential degree. However, usefulness factor and speedy connection factor are not significant. In result, the target hitting rate is 77.9% in the first unuse-intention group and it is 95.2% in the second use-intention group. The total discriminant target hitting rate is computed to higher value, 86.55%. The statistic package, SPSS 12.0, is used to survey and analyse data and test the hypothesis. The validity and reliability of variables are verified by both reliability analysis and factor analysis. The discriminant analysis is used to tell the difference between use-intention group and unuse-intention group.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.49-63
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• 1997

We consider the problem of classifying a p x 1 observation into one of two multivariate normal populations when the training smaples contain a block of missing observation. A new classification procedure is proposed which is a linear combination of two discriminant functions, one based on the complete samples and the other on the incomplete samples. The new discriminant function is easy to use.

• Korean journal of food and cookery science
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• v.18 no.1
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• pp.109-118
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• 2002

The purpose of this study was to identify the behavioral, attitudinal, and demographic correlates of light, medium, and heavy users of eating out at family restaurants. Among 358 reponses from the subjects, 224 responses were utilized for the analysis, and 134 responses were reserved for validating the discriminant function. Descriptive statistics, reliability analysis, stepwise discriminant analysis, canonical discriminant analysis, and anova analysis were used for this study. The findings from this study were as follows: First, He behavioral characteristics were found to discriminate among the three usage groups. Second, it was found that heavy users expressed greater difference between perception and expectation on the quantity of food that are appropriately served and the consistent quality of food at every visit. Third, the usage rate of eating out was not dependent on the sex, but dependent on the companion, average expenditure, and the time of eating out in chi-square test. Finally, the results of the study provide some insight into the pattern of marketing strategies that can be successfully used by the managers of family restaurants.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.41-48
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• 2005

This paper presents a face recognition method based on the combination of well-known statistical representations of Principal Component Analysis(PCA), and Linear Discriminant Analysis(LDA) with Radial Basis Function Networks. The original face image is first processed by PCA to reduce the dimension, and thereby avoid the singularity of the within-class scatter matrix in LDA calculation. The result of PCA process is applied to LDA classifier. In the second approach, the LDA process Produce a discriminational features of the face image, which is taken as the input of the Radial Basis Function Network(RBFN). The proposed approaches has been tested on the ORL face database. The experimental results have been demonstrated, and the recognition rate of more than 93.5% has been achieved.