• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1111-1113
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• 2003

In this paper, we investigated a method for feature - based classification to develop software which is suitable to the classification of high resolution satellite imagery . So, we developed related algorithm and designed user interfaces of convenience, considering various elements require for the feature - based classification. The software was tested with eCognition software which is unique commercial software for feature - based classification.

• Journal of Korean Neurosurgical Society
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• v.62 no.3
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• pp.288-295
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• 2019

In 2011, the International League against Epilepsy (ILAE) proposed a first international consensus of the classification of focal cortical dysplasia (FCD). This FCD classification had been widely used in worldwide. In this review paper, the authors would like to give helpful comments for better understanding of the current FCD classification. Especially, the basic concepts of FCD type I, such as "radial", "tangential" and "microcolumn" will be discussed with figures. In addition, the limitations, genetic progress and prospect of FCD will be suggested.

• Communications for Statistical Applications and Methods
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• v.28 no.1
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• pp.89-97
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• 2021

Due to boundedness and sum constraint, compositional data are often transformed by logratio transformation and their transformed data are put into traditional binary classification or discriminant analysis. However, it may be problematic to directly apply traditional multivariate approaches to the transformed data because class distributions are not Gaussian and Bayes decision boundary are not polynomial on the transformed space. In this study, we propose to use flexible classification approaches to transformed data for compositional data classification. Empirical studies using synthetic and real examples demonstrate that flexible approaches outperform traditional multivariate classification or discriminant analysis.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.245-250
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• 2004

The classification of the satellite images is basic part in Remote sensing. In classification of the satellite images, class separability feature is very effective accuracy of the images classified. For improving classification accuracy, It is necessary to study classification methode than analysis of class separability feature deciding classification probability. In this study, IKONOS, SPOT 5, Landsat TM, were resampled to sizes 1m grid. Above images were calculated the class separability prior to the step for classification of pixels. The results of the study were valued necessary process in geometric information building. This study help to improve accuracy of classification as feature of class separability in the class through optimizing previous classification steps.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.4
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• pp.276-284
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• 2012

Classification algorithms generally assume that the data is complete. However, missing values are common in real data sets due to various reasons. In this paper, we propose to use locally linear reconstruction (LLR) for missing value imputation to improve the classification performance when missing values exist. We first investigate how much missing values degenerate the classification performance with regard to various missing ratios. Then, we compare the proposed missing value imputation (LLR) with three well-known single imputation methods over three different classifiers using eight data sets. The experimental results showed that (1) any imputation methods, although some of them are very simple, helped to improve the classification accuracy; (2) among the imputation methods, the proposed LLR imputation was the most effective over all missing ratios, and (3) when the missing ratio is relatively high, LLR was outstanding and its classification accuracy was as high as the classification accuracy derived from the compete data set.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.190-195
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• 2004

We propose a pattern classification algorithm using self-nonself discrimination principle of immune cells and apply it to DNA pattern classification problem. Pattern classification problem in bioinformatics is very important and frequent one. In this paper, we propose a classification algorithm based on the negative selection of the immune system to classify DNA patterns. The negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes ${\eta}$ groups of antigenic receptor for ${\eta}$ different patterns, these receptor groups can classify into ${\eta}$ patterns. We propose a pattern classification algorithm based on the negative selection in nucleotide base level and amino acid level. Also to show the validity of our algorithm, experimental results of RNA group classification are presented.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.107-109
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• 2003

Optical sensor-based land cover categories produce spectral signature confusion along with degraded classification accuracy. In the classification tasks, the goal of fusing data from different sensors is to reduce the classification error rate obtained by single source classification. This paper describes the result of land cover/land use classification derived from solely of Landsat TM (TM) and multisensor image fusion between JERS 1 SAR (JERS) and TM data. The best radar data manipulation is fused with TM through various techniques. Classification results are relatively good. The highest Kappa Coefficient is derived from classification using principal component analysis-high pass filtering (PCA+HPF) technique with the Overall Accuracy significantly high.

• The Journal of Korean Medicine
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• v.21 no.3
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• pp.9-19
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• 2000

Objective : We proposed fundamental rules of prospective Korean Standard Classification of Diseases(Oriental Medicine). Methods : We analysed Korean Standard Classification of Diseases(Oriental Medicine)(established in 1994) in comparison with ICD-10 and Chinese Standard Classification of Disease(Traditional Chinese Medicine). Secondly, we analysed the diagnostic structure of Modem oriental medicine. Results : Korean Standard Classification of Diseases has an inappropriate writing structure, logical errors of classification, confusion of symptoms, 'bing', and 'zheng', inappropriate comparison of disease designations in oriental medicine and western medicine, and the ommission of important items. Secondly, we demonstrate the relations of 'bing' and 'zheng' in modem oriental medicine and disease designations in oriental medicine and western medicine. Conclusions : We propose the separate classification of 'bing' and 'zheng', the qualification of designated names, the structure of 'bing' and 'zheng' system, and a different writing method.

• International Journal of Contents
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• v.10 no.1
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• pp.43-46
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• 2014

Subject classification of journals is important because it can be utilized for the improvement of scholarly information services and analysis by research area. The classification by experts in a subject area wastes a lot of time and expense. On the other hand, the simple classification with basic information, such as the journal title has limitations. To solve this problem, this paper suggests the automatic classification of Korean journals using the SCI journals information cited by Korean journals, and an analysis of the classification result. In particular, this study adopted the WoS subject categories for classification to support the base for comparison between the Korean citation database and the global citation database (KSCI vs. SCI).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.12
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• pp.21-26
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• 2011

This is a study to establish regulations against light pollution for lighting on roads. Many kinds of light pollution by luminaire on roads was calculated and analyzed by applying the classification method of luminaires(Cut-off classification of IDA-IESNA, BUG Rating Classification) and the calculation method of Upward Lighting Ratio of CIE among measures to prevent light pollution that international lighting organizations suggest. As a result of the analysis, it was found that the regulation by Cutoff of IESNA and ULR classification of CIE could be one for scattered light of light pollution compared to BUG classification but is not sufficient for the regulation of light tresspass or glare. BUG classification by each lighting zone was suggested as threshold value of the light pollution regulation considering domestic conditions.