• Journal of Physiology & Pathology in Korean Medicine
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• v.18 no.6
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• pp.1892-1895
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• 2004

The purpose of this study was to investigate the personality traits in constitutional types. The Questionnaire for the Sasang Constitution Classification Ⅱ and Eysenck Personality Questionnaire were completed by 155 university students. Statistical analyses of the Questionnaire for the Sasang Constitution Classification Ⅱ and Eysenck Personality Questionnaire scale scores and results are as follows : First, Personality differences in constitutional types are revealed significantly with respect to Eysenck Personality Questionnaire scales such as neuroticism, addiction, and criminality. Second, there is a significant difference between Eum(음) type and Yang(양) type along psychoticism and neuroticism. Third, sex difference is significant along the dimension of extraverion-intraversion.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.713-716
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• 2005

In this paper, in order to identify and recognize attack patterns, we propose a Bayesian classification using frequent patterns. In theory, Bayesian classifiers guarantee the minimum error rate compared to all other classifiers. However, in practice this is not always the case owing to inaccuracies in the unrealistic assumption{ class conditional independence) made for its use. Our method addresses the problem of attribute dependence by discovering frequent patterns. It generates frequent patterns using an efficient FP-growth approach. Since the volume of patterns produced can be large, we propose a pruning technique for selection only interesting patterns. Also, this method estimates the probability of a new case using different product approximations, where each product approximation assumes different independence of the attributes. Our experiments show that the proposed classifier achieves higher accuracy and is more efficient than other classifiers.

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.98-113
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• 2003

Kano model distinguishes three types of customer requirements, namely, one-dimensional quality, must-be quality, and attractive quality. There are a few methods for classifying a given customer requirement into one of the Kano's quality elements. However, the existing methods have a common limitation in that they are based on Kano evaluation table. Kano evaluation table is not always effective for the classification task, and suffers from a significant information loss. This paper proposes an alternative to Kano's evaluation table and a new classification scheme based on fuzzy set concept. The proposed method is illustrated using a case study on the ADSL service.

• Journal of the Korean Statistical Society
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• v.16 no.2
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• pp.92-101
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• 1987

Our interest is to access in some way teh relative odds or probability that a multivariate observation Z belongs to one of k multivariate normal populations with unequal covariance matrices. We derived the empirical Bayes posterior odds ratio for the classification rule when population parameters are unknown. It is a generalization of the posterior odds ratio suggested by Gelsser (1964). The classification rule does not have complicated distribution theory which a large variety of techniques from the sampling viewpoint have. The proposed posterior odds ratio is compared to the Gelsser's posterior odds ratio through a Monte Carlo study. The results show that the empiricla Bayes posterior odds ratio, in general, performs better than the Gelsser's. Especially, for large dimension of Z and small training sample, the performance is prominent.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.1
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• pp.18-20
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• 2017

In this paper, we propose a new classification method to complement a $na{\ddot{i}}ve$ Bayesian classifier. This classifier assumes data distribution to be Gaussian, finds the discriminant function, and derives the decision curve. However, this method does not investigate finding the decision curve in much detail, and there are some minor problems that arise in finding an accurate discriminant function. Our findings also show that this method could produce errors when finding the decision curve. The aim of this study has therefore been to investigate existing problems and suggest a more reliable classification method. To do this, we utilize the gradient to find the decision curve. We then compare/analyze our algorithm with the $na{\ddot{i}}ve$ Bayesian method. Performance evaluation indicates that the average accuracy of our classification method is about 10% higher than $na{\ddot{i}}ve$ Bayes.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2525-2527
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• 2004

This paper classify using Adaptive Resonance Theory 1(ART1) as a vigilance parameter of pattern clustering algorithm. Inherent characteristics of the model are analyzed. In particular the vigilance parameter $\rho$ and its role in classification of patterns is examined. Our estimates show that the vigilance parameter as designed originally does not necessarily increase the number of categories with its value but can decrease also. This is against the claim of solving the stability-plasticity dilemma. However, we have proposed a modified vigilance parameter setting criterion which takes into account the problem of subset and superset patterns and stably categorizes arbitrarily many input patterns in one list presentation when the vigilance parameter is closer to one. And this paper goal is the input pattern cognition and classification using neural network.

• Journal of Korean Library and Information Science Society
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• v.43 no.2
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• pp.273-292
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• 2012

This study unpackes semiotic character of knowledge classification and wants to know how sign structure of classification effects on canon and banned book etc, and by this impact stems from the semoitic structure structurally, discusses coidentity between banned book and internet in social and cultural structure aspect. and proposes way for understanding and interpretation text like mass media using structuralism theory.

• Communications for Statistical Applications and Methods
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• v.29 no.3
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• pp.319-331
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• 2022

In this paper, we develop a new statistical model to forecast the PM_2.5 level in Seoul, South Korea. The proposed model is based on the extreme quantile regression model with lasso penalty. Various meteorological variables and air pollution variables are considered as predictors in the regression model, and the lasso quantile regression performs variable selection and solves the multicollinearity problem. The final prediction model is obtained by combining various extreme lasso quantile regression estimators and we construct a binary classifier based on the model. Prediction performance is evaluated through the statistical measures of the performance of a binary classification test. We observe that the proposed method works better compared to the other classification methods, and predicts 'very bad' cases of the PM_2.5 level well.

• Communications of the Korean Mathematical Society
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• v.39 no.4
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• pp.997-1025
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• 2024

A periodic weave is the lift of a particular link embedded in a thickened surface of genus g ≥ 1 to the universal cover. Its components are infinite unknotted simple open curves that can be partitioned in at least two distinct sets of threads. The classification of periodic weaves can be reduced to the one of their generating cells, namely their weaving motifs. However, this classification cannot be achieved through the classical theory of links in thickened surfaces since periodicity in the universal cover is not encoded. In this paper, we first introduce the notion of hyperbolic periodic weaves, which generalizes our doubly periodic weaves embedded in the Euclidean thickened plane. Then, Tait's first and second conjectures are extended to minimal reduced alternating weaving motifs and proved using a generalized Kauffman bracket polynomial defined for periodic weaving diagrams of 𝔼² and generalized to ℍ². The first conjecture states that any minimal alternating reduced weaving motif has the minimum possible number of crossings, while the second one formulates that two such oriented weaving motifs have the same writhe.

• The Journal of Korean Medical History
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• v.30 no.1
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• pp.11-22
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• 2017

This paper is a study on the life and clinical reasoning of Kim Goo Young (1958-2014). Offering a new perspective through his interpretation of Donguibogam (東醫寶鑑), Kim introduced his unique theory of Korean medicine, 'The Theory of Byeongin (病因論)'. Kim recognized the confusing situation of communication between people studying Korean medicine and tried to make a new standard based on the principle that many people can share. 'The Theory of Byeongin' offers a newly constituted "Donguibogam" focusing on 'Byeongin' (病因, pathologic origin) which can be translated as the cause of a disease. In so doing Kim recognized 'Byeongin' as the most important factor in 'Byeonjeung' (辨證, classifying the origin), or the classification method of symptoms. In addition, Kim recognized how 'Byeongin' was considered to be a diseased lifestyle, and tried interpreting. The patient's lifestyle to treat diseases. As a result, 'The Theory of Byeongin' is a theory consisting of an intuitive structure, reducing notable elements like Yin Yang Five Movement theory. The theory's significant characteristic is its easy application in clinical settings due the established core principles which are based on Kim's insight and clinical experience. This study contributes to the understanding of the theoretical and clinical development of Korean medicine through deeper studies on 'The Theory of Byeongin' and Kim's medical theory.