• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.285-290
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• 2009

In this paper, we propose a new algorithm that improves the lossless data compression rate. The proposed algorithm lessens the redundancy and improves the compression rate evolutionarily around 40 up to 80 percentile depending on the characteristics of binary images used for compression. In order to demonstrate the superiority of the proposed method, the comparison between the proposed method and the LZ78 (LZ77) is demonstrated through experimental results theoretical analysis.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1135-1143
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• 2007

The singular value decomposition and the spectral decomposition are the useful methods in the area of matrix computation for multivariate techniques such as principal component analysis and multidimensional scaling. These techniques aim to find a simpler geometric structure for the data points. The singular value decomposition and the spectral decomposition are the methods being used in these techniques for this purpose. In this paper, the singular value decomposition and the spectral decomposition are compared.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.117.1-117
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• 2001

A motion handling technique that transforms existing animation motion data to a mathematically well-defined form. The transformed data can be utilized in any kind of autonomous motion creation process that handles such cases as changed environment, structure (kinematic / dynamic) modification, or changed constraints. To overcome the computational burden of traditional spacetime optimization, we divide full motion data frame into several parts, and we applied the transformation technique to each part using an optimizing tool(CFSQP). To show Ire feasibility of the proposed method, a comparison study results with traditional technique is included.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.513-516
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• 1999

I here are many kinds of method to compress data. To very simple methods from very complex methods, a kind is various. In this study, the simplest form of the Tolerance-Comparison method, zero-order method is used. Using this method, despite using low speed CPUs, it is possible to compress real time data. So this method is suitable for ECG holler system. In this study, to complement zero-order method, it is needed to develop prediction technique and to research ways to apply the technique.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.04a
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• pp.571-576
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• 2000

This paper summarized deformation properties of hydroelectric power concrete dam through the comparison between measured and analysed data. This is a part of the process to evaluate concrete dam safety, which has become a critical concern in the country. We analysed strain and angle deformation data by considering only the effect of atmosphere temperature to evaluate deformation properties of Gaisan hydroelectric power concrete dam. Analysis results are almost identical with measured data, and behavior of Gusian dam can be cleared up more reliably in case of acting the external loads (seismic, wind water pressure, etc.) except the influence of temperature.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1079-1086
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• 2005

Most discussions of single imputation methods and the EM algorithm concern point estimation of population quantities with missing values. A second concern is how to get standard errors of the point estimates obtained from the filled-in data by single imputation methods and EM algorithm. Now we focus on how to estimate standard errors with incorporating the additional uncertainty due to nonresponse. There are some approaches to account for the additional uncertainty. The general two possible approaches are considered. One is the jackknife method of resampling methods. The other is multiple imputation(MI). These two approaches are reviewed and compared through simulation studies.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.717-724
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• 2005

We often extract a new feature from the original features for the purpose of reducing the dimensions of feature space and better classification. In this paper, we show feature extraction method based on independent component analysis can be used for classification. Entropy and mutual information are used for the selection of ordered features. Performance of classification based on independent component analysis is compared with principal component analysis for three real data sets.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.945-955
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• 2004

'Complete-case analysis' is easy to carry out and it may be fine with small amount of missing data. However, this method is not recommended in general because the estimates are usually biased and not efficient. There are numerous alternatives to complete-case analysis. One alternative is the single imputation. Some of the most common single imputation methods are reviewed and the performances are compared by simulation studies.

• Journal of Family Resource Management and Policy Review
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• v.1 no.1
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• pp.117-129
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• 1997

This study explored a terminal values of home economics students at Chonnam national university in Korea. And the terminal values of them were compared with those of USA and Japan. Through this, it make to explain the similarities and differences in terminal values among 3 nations. 175 students were adapted as data in Korea. Data of USA and Japan were obtained from Holyoak, Sawai, and Rauniyar(1993). The data were analyzed by frequency, percentage, means, one-way ANOVA, Duncan-test. The results showed significant similarities and differences in terminal values among 3 groups.

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.645-654
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• 2004

In this paper, we develop the Bayesian test procedure for the intraclass correlation coefficient in the unbalanced one-way random effect model based on the reference priors. That is, the objective is to compare two nested model such as the independent and intraclass models using the factional Bayes factor. Thus the model comparison problem in this case amounts to testing the hypotheses $H_1:\rho=0$ versus $H_2:{\rho}{\neq}0$. Some real data examples are provided.