• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1996.06a
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• pp.403-407
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• 1996

• Proceedings of the Korean Nuclear Society Conference
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• 1999.10a
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• pp.343-343
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• 1999

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.4
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• pp.11-20
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• 2004

This paper suggests the site-dependent ductility factor which is a key component of response modification factor(R). To compute the ductility factor, a group of 1,860 ground motions recorded from 47 earthquake was considered. Based on the local site conditions at the recording station, ground motions were classified into four groups according to average shear wave velocity. This site classification was consistent with site categories of the UBC(1997), NEHRP(1997) and IBC 2000(1997). Based on the results of regression analysis, a simplified equations were proposed to compute site-dependent ductility factors. The proposed equations were relatively simple and provide a good estimation of mean ductility factors. Based on the proposed equation, ductility factors considering the site conditions can be evaluated in accordance with the present building codes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2521-2526
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• 2011

This paper proposes a speaker recognition algorithm using a perceptron neural network and LPC (Linear Predictive Coding) cepstrum coefficients. The proposed algorithm first detects the voiced sections at each frame. Then, the LPC cepstrum coefficients which have speaker characteristics are obtained by the linear predictive analysis for the detected voiced sections. To classify the obtained LPC cepstrum coefficients, a neural network is trained using the LPC cepstrum coefficients. In this experiment, the performance of the proposed algorithm was evaluated using the speech recognition rates based on the LPC cepstrum coefficients and the neural network.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.21 no.2
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• pp.94-111
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• 1995

In this study, the relationship between partition coefficients(Kw) of oils and antimicrobial effects Ivas investigated. The antimicrobial activity of paraben has been known to be controlled by the concentration of the paraben in the aqueous phase. The concentration of paraben in the aqueous phase was measured by the UV/VIS spectrophotometer at the wavelength of 256nm. It was found that the hydrocarbon oils and silicone oils had the lowest Kw value(<1.0) among the tested oils. Also, the emulsions which were made of oils having low Kw values had a good antimicrobial effects. Thus, the cosmetic safety against microorganisms could be improved by using the oils which have low Kw values.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.43-56
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• 2004

The KHCM procedure is a micro level analysis at signalized intersections requiring a lot of input variables and complex computations. The research was to investigate the possibility of simplifying the analysis procedures by using the generalized or the combined variables that less influence on the adjusted traffic volume and through-car equivalents of left or right turns. It was also tried to make lane grouping into directional flow ratio(v/s) based on a field surveys. The maximum and minimum values of each variables were compared with each other through the KHCM analysis procedures in terms of control delay. The lane grouping and the synthetical influence of a simplified method was evaluated with the scenario built in prevailing maximum and minimum conditions. The study showed that the control delay was not significantly sensitive to the selected variables and the lane grouping and their synthetical influence as well.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.127-135
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• 2010

In motion adaptive temporal noise reduction filtering used for reducing video noises, the strength of motion adaptive temporal filtering should be carefully controlled according to temporal movement. This paper presents a motion adaptive temporal filtering scheme based on least-square training. Each pixel is classified to a specific class code according to temporal movement, and then, an iterative least-square training method is applied for each class code to find optimal filtering coefficients. The iterative least-square training is an off-line procedure, and the trained filter coefficients are stored in a lookup table (LUT). In actual noise reduction filtering operation, after each pixel is classified by temporal movement, simple filtering operation is applied with the filter coefficients stored in the LUT according to the class code. Experiment results show that the proposed method efficiently reduces video noises without introducing blurring.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1901-1906
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• 2010

This classification of walking patterns is important and many kinds of applications. Therefore, we attempted to classify walking on level ground from slow walking to fast walking using a waist acceleration signal. A tri-axial accelerometer was fixed to the subject's waist and the three acceleration signals were recorded by bluetooth module at a sampling rate of 100 Hz eleven healthy. The data were analyzed using discrete wavelet transform. Walking patterns were classified using two parameters; One was the ratio between the power of wavelet coefficients which were corresponded to locomotion and total power in the anteroposterior direction (RPA). The other was the ratio between root mean square of wavelet coefficients at the anteroposterior direction and that at the vertical direction(RAV). Slow walking could be distinguished by the smallest value in RPA from other walking pattern. Fast walking could be discriminated from level walking using RAV. It was possible to classify the walking pattern using acceleration signal in healthy people.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2259-2264
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• 2008

Significant genes are defined as genes in which the expression level characterizes a specific experimental condition. Such genes in which the expression levels differ significantly between different groups are highly informative relevant to the studied phenomenon. In this paper, first the system can detect informative genes by similarity scale combination method being proposed in this paper after normalizing data with methods that are the most widely used among several normalization methods proposed the while. And it compare and analyze a performance of each of normalization methods with multi-perceptron neural network layer. The Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) after Lowess normalization represented the improved classification performance of 98.84%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1159-1174
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• 2004

In this paper, we present an efficient algorithm for region analysis of business card images acquired in a PDA by using DCT and information pixel density. The proposed method consists of three parts: region segmentation, information region classification, and text region classification. In the region segmentation, an input business card image is partitioned into 8 f8 blocks and the blocks are classified into information and background blocks using the normalized DCT energy in their low frequency bands. The input image is then segmented into information and background regions by region labeling on the classified blocks. In the information region classification, each information region is classified into picture region or text region by using a ratio of the DCT energy of horizontal and vertical edge components to that in low frequency band and a density of information pixels, that are black pixels in its binarized region. In the text region classification, each text region is classified into large character region or small character region by using the density of information pixels and an averaged horizontal and vertical run-lengths of information pixels. Experimental results show that the proposed method yields good performance of region segmentation, information region classification, and text region classification for test images of several types of business cards acquired by a PDA under various surrounding conditions. In addition, the error rates of the proposed region segmentation are about 2.2-10.1% lower than those of the conventional region segmentation methods. It is also shown that the error rates of the proposed information region classification is about 1.7% lower than that of the conventional information region classification method.