• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.1
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• pp.11-23
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• 2003

This study Investigates the short and long-run dynamic relationships between the domestic and U.S. stock markets for the period of declining stock prices. It Is well known that the domestic stock market variations are largely caused by the U.S. stock market movements. Multivariate causal tty test Is utilized to examine the lead-lag relationships among four stock prices of KOSPI and KOSDAQ In the domestic part and DOWJONES and NASDAQ In the U.S. part. When the stock prices tend to decrease In the long run, It Is found that both KOSPI and KOSDAQ have closer relations with NASDAQ than DOWJONES. When both of domestic stock markets are severely fluctuate, bidirectional causal relationships appear to exist between NASDAQ and each of KOSPI and KOSDAQ. On the other hand. when the domestic stock markets are relatively stable, unidirectional causality Is found to exist between NASDAQ and each of KOSPI and KOSDAQ. which is explicitly validated by the analysis of variance decomposition.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.10
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• pp.483-491
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• 2005

To solve the 3D eddy current problems by using FE(finite element) method with MVP(magnetic vector potential) and electric scalar potential, Coulomb gauge condition and current continuity condition have to be considered. Coulomb gauge condition enforced on existing FE formulations to insure the uniqueness of MVP looks unnatural and current continuity condition which can be driven from Ampere's law looks unnecessary. So in this paper the effect of two conditions on FE formulations are investigated in order to help to obtain accurate numerical simulation results.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.509-511
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• 2004

This paper outlines the development of image processing system, which will allow the general users in Government and Public organizations easily to use and apply KOMPSAT EOC images in their own business. The system includes an import/export module of EOC image distributed in Hierarchical Data Format (HDF) file and various image processing analysis modules. Especially, the image mosaic and subset functions are designed to use EOC image as an image map, generating the Ortho-image module. To update the various spatial data with EOC image, some essential modules such as change detection by pattern recognition, overlay between images and vector data, and modification of vector data are implemented in the system. The system is developed based on the user request analysis of government agency, and suited for more efficient use of satellite image in public applications. Such system is expected to contribute to practical application of KOMPSAT-2 that will be launched in 2005. Further efforts will be made to accommodate the KOMPSAT -2 MSC data.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.2
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• pp.43-51
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• 2017

In this study, the effect of the steering vector model mismatch due to array uncertainties on the performance of array processing was analyzed through simulation, along with the alleviation of the model mismatch effect depending on array calibration. To increase the reliability of the simulation results, the actual steering vector of the array antenna obtained by electromagnetic simulation was used along with the Jahn's channel model, which is an experimental channel model. Based on the analysis of the power spectrum for each direction, beam pattern, and the signal-to-interference-plus-noise ratio of the beamformer output, the performance deterioration of array processing due to array uncertainties was examined, and the performance improvement of array processing through array calibration was also examined.

• Speech Sciences
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• v.12 no.2
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• pp.171-182
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• 2005

An efficient GMM (Gaussian mixture modeling) method based on LPCA (local principal component analysis) with VQ (vector quantization) for speaker identification is proposed. To reduce the dimension and correlation of the feature vector, this paper proposes a speaker identification method based on principal component analysis. The proposed method firstly partitions the data space into several disjoint regions by VQ, and then performs PCA in each region. Finally, the GMM for the speaker is obtained from the transformed feature vectors in each region. Compared to the conventional GMM method with diagonal covariance matrix, the proposed method requires less storage and complexity while maintaining the same performance requires less storage and shows faster results.

• Phonetics and Speech Sciences
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• v.5 no.4
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• pp.211-216
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• 2013

The IVA(Independent Vector Analysis) is a well-known FD-ICA method used to solve the frequency permutation problem. It generally works quite well for blind source separation problems, but still needs some improvements in the frequency bin permutation problem. This paper proposes a post-processing method which can improve the source separation performance with the IVA by fixing the remaining frequency permutation problem. The proposed method makes use of the correlation coefficient of power ratio between frequency bins for separated signals with the IVA-based 2-channel source separation. Experimental results verified that the proposed method could fix the remaining frequency permutation problem in the IVA and improve the speech quality of the separated signals.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3152-3159
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• 1996

Previous works about the cylindrical shape elastic body which is under longitudinal temperature distribution mostly show the results of free expansion, therefore exact thermo-elastic analysis is needed. The object of this work is to analyze the thermo-elastic problem of the hollow cylinder when the cylinder is under longitudinal temperature distribution. In this paper, the analytical solution is found by using Galerkin vector, and it is compared by the results of FEM. For displacements of cylinder, analytical values are almost same as the results of FEM, but free expansion is not fit for analytical solution and the results of FEM. stresses from analytical solution and the results of FEM show good agreement also. but the results are different near the end boundary, since St. Venant principle is applied.

• Journal of Advanced Marine Engineering and Technology
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• v.14 no.4
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• pp.46-56
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• 1990

Stress analysis of axi-symetric body with non-symetric loading and non-symetric given displacements is investigated in this paper using the finite element method. As the non-symetric load and non-symetric given displacements of axi-symetric body are generally periodic functions of angle .theta., the nodal forces and nodal displacements can be expanded in cosine and sine series, that is, Fourier series. Furthermore, using Euler's formula, the cosine and sine series can be converted into exponential series and it is prooved that the related calculus become more clear. Substituting the nodal displacements expanded in Fourier series into the strain components of cylindrical coordinates system, the element strains are expressed in series form and by the principal of virtual work, the element stiffness martix and element load vector are obtained for each order. It is also showed that if the non-symetric loads are even or odd functions of angle ${\theta}$ the stiffness matrix and load vector of the system are composed with only real numbers and relatively small capacity fo computer memory is enough for calculation.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.24
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• pp.10573-10576
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• 2015

Background: Accuracy in feature extraction is an important factor in image classification and retrieval. In this paper, a breast tissue density classification and image retrieval model is introduced for breast cancer detection based on thermographic images. The new method of thermographic image analysis for automated detection of high tumor risk areas, based on two-directional two-dimensional principal component analysis technique for feature extraction, and a support vector machine for thermographic image retrieval was tested on 400 images. The sensitivity and specificity of the model are 100% and 98%, respectively.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.233-243
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• 2015

A hotspot is a spatial pattern that properties or events of spaces are densely revealed in a particular area. Whereas location information is easily captured with increasing use of mobile devices, so is not our emotion unless asking directly through a survey. Tweet provides a good way of analyzing such spatial sentiment, but relevant research is hard to find. Therefore, we analyzed hotspots of emotion in the twitter using spatial autocorrelation. 10,142 tweets and related GPS data were extracted. Sentiment of tweets was classified into good or bad with a support vector machine algorithm. We used Moran's I and Getis-Ord $G_i^*$ for global and local spatial autocorrelation. Some hotspots were found significant and drawn on Seoul metropolitan area map. These results were found very similar to an earlier conducted official survey of happiness index.