• Journal of Advanced Marine Engineering and Technology
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• v.39 no.9
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• pp.903-910
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• 2015

The purpose of this research is to develop a full-spectral fatigue analysis program, based on rigid-body ship motion analysis, in order to perform a full-spectral fatigue analysis that considers hydroelasticity effects. To gain credibility, fatigue analysis results of two ship types, performed by the developed program, were compared with those of a classification society, and it was found that both are identical. Full-spectral fatigue analysis considering hydroelasticity effects would be developed in further studies by including flexible-body ship motion analysis results and by supplementing the developed program with a wide-band fatigue damage model.

• Journal of Astronomy and Space Sciences
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• v.29 no.4
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• pp.407-411
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• 2012

Space-borne remote sensing is an effective and inexpensive way to identify crop fields and detect the crop condition. We examined the multi-temporal spectral characteristics of rice fields in South Korea to detect their phenological development and condition. These rice fields are compact, small-scale parcels of land. For the analysis, moderate resolution imaging spectroradiometer (MODIS) and RapidEye images acquired in 2011 were used. The annual spectral tendencies of different crop types could be detected using MODIS data because of its high temporal resolution, despite its relatively low spatial resolution. A comparison between MODIS and RapidEye showed that the spectral characteristics changed with the spatial resolution. The vegetation index (VI) derived from MODIS revealed more moderate values among different land-cover types than the index derived from RapidEye. Additionally, an analysis of various VIs using RapidEye satellite data showed that the VI adopting the red edge band reflected crop conditions better than the traditionally used normalized difference VI.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.111-116
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• 2021

The hyper-spectral image is data obtained by dividing the electromagnetic wave band in the infrared region into hundreds of wavelengths. It is used to find or classify objects in various fields. Recently, deep learning classification method has been attracting attention. In order to use hyper-spectral image data as deep learning training data, a processing technique is required compared to conventional visible light image data. To solve this problem, we developed a software that selects specific wavelength images from the hyper-spectral data cube and performs the ground truth task. We also developed software to manage data including environmental information. This paper describes the configuration and function of the software.

• Current Optics and Photonics
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• v.5 no.3
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• pp.322-328
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• 2021

In this paper, a pretreatment method for a matrix in convex optimization is proposed to optimize the spectral reconstruction process of a disordered dispersion spectrometer. Unlike the reconstruction process of traditional spectrometers using Fourier transforms, the reconstruction process of disordered dispersion spectrometers involves solving a large-scale matrix equation. However, since the matrices in the matrix equation are obtained through measurement, they contain uncertainties due to out of band signals, background noise, rounding errors, temperature variations and so on. It is difficult to solve such a matrix equation by using ordinary nonstationary iterative methods, owing to instability problems. Although the smoothing Tikhonov regularization approach has the ability to approximatively solve the matrix equation and reconstruct most simple spectral shapes, it still suffers the limitations of reconstructing complex and irregular spectral shapes that are commonly used to distinguish different elements of detected targets with mixed substances by characteristic spectral peaks. Therefore, we propose a special pretreatment method for a matrix in convex optimization, which has been proved to be useful for reducing the condition number of matrices in the equation. In comparison with the reconstructed spectra gotten by the previous ordinary iterative method, the spectra obtained by the pretreatment method show obvious accuracy.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1064-1069
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• 2014

In this paper, we propose a novel approach to improve the performance of a voice activity detection(VAD) which is based on the adaptive band-partitioning with the likelihood ratio(LR). The previous method based on the adaptive band-partitioning use the weights that are derived from the variance of the spectral. In our VAD algorithm, the weights are derived from LR, and then the weights are incorporated with the entropy. The proposed algorithm discriminates the voice activity by comparing the weighted entropy with the adaptive threshold. Experimental results show that the proposed algorithm yields better results compared to the conventional VAD algorithms. Especially, the proposed algorithm shows superior improvement in non-stationary noise environments.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.89-94
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• 1999

The paper first proposes an empirical algorithm for detecting dust-loaded airmass observed by Sea Wide Field-of-view Scanner (SeaWiFS). The proposed dust index formula is based on the curvature of the spectral reflectance estimated from the SeaWiFS band 4 (510 nm band) through band 8 (865 nm band) data, assuming "clear ocean water" reflectance. Evaluation of the algorithm is made over several typical Asian dust images including the ones over the Pacific in April, 1998, when a major dust event was reported. The study analyzes the performance and the characteristics of the algorithm by comparing the satellite-derived dust index images with contemporaneous columnar concentration of dust particles predicted by a numerical dust transport model. The comparison reveals several small-scale differences although their dust distribution patterns show good agreement generally.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.622-626
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• 2005

This paper presents an active vision system for ITS(intelligent transportation system : ITS). We have described a novel method to provide high quality imaging signals to a system that will perform passenger detection and counting in the roadway. The method calls for two co-registered near-infrared cameras with spectral sensitivity above (upper-band) and below (lower-band) the quality of the signal remains. We propose a novel system based on fusion of near-infrared imaging signals and we demonstrate its adequacy with theoretical and experimental arguments.

• Journal of the Korean Chemical Society
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• v.17 no.4
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• pp.240-246
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• 1973

An analytic expression for the intensity of collision-induced light scattering obstained by introducing both short-range and long-range effects on the induced anisotropy. By taking argon as a specific example, it is shown that a narrow band at small frequency shifts is caused by long-range effects, while a broad band in the far wing of the spectrum is due to short-range effects. The overall intensity is a synthesis of these two bands and does not follow a simple exponential form. As temperature increases, the intensity at large frequency shifts increases makedly, while at small frequency shifts it changes little.

• Journal of the Korean Society of Safety
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• v.25 no.3
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• pp.123-130
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• 2010

Electroencephalogram(EEG) would be the most objective psychophysiological research technique on human errors though few research has been taken yet. This study aimed to get characteristics of human error while committing simple Odd-Ball tasks by utilizing the power spectrum technique of EEG data. Each experiment was composed of 3 tasks with different rules, and 8 young undergraduate students participated in this study as paid subjects. The result showed in the affirmative that subject and the interaction of subject and task factors were statistically significant on variation of $\alpha$ band power $P_{\alpha/(\alpha+\beta+\theta)}$ and $\beta$ band power $P_{\beta/(\alpha+\beta+\theta)}$, and that the former increasing in backward direction to Pz reflects compatibility whereas the latter increasing in forward direction to Fz reflects familiarity. Therefore it was coucluded that, since task 2 carried out in the present research requiring decoding process would be more difficult to human beings than the task merely requiring psychological recall process, task 1 and task 3 were classified into a homogenious group excluding task 2, and the ratio $\alpha$ band power to $\beta$ band power indicated enormous increase of $\alpha$ band power relative to $\beta$ band power in the cases of contra-lateral errors, especially in task 2.

• Speech Sciences
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• v.10 no.2
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• pp.249-258
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• 2003

This study attempted to examine a speaker identification method using difference sum and correlation coefficient determined from a pair of intensity level matrices of band-pass-filtered numeric sounds produced by ten female speakers of similar age and height. Subjects recorded three digit numbers at a quiet room at a sampling rate of 22 kHz on a personal computer. Collected data were band-pass-filtered at five different band ranges. Then, matrices of five intensity levels at 100 proportional time points were obtained. Pearson correlation coefficients and the sum of absolute intensity differences between a pair of given matrices were determined within and across the speakers. Results showed that very high correlation coefficient and small difference sum generally occurred within each speaker but some individual variation was also observed. Thus, the matrix pair with a higher coefficient and a smaller difference sum was averaged to form each individual's model. Comparison among the speakers yielded generally low coefficients and large differences, which suggests successful speaker identification, but among them there were a few cases with very high coefficients and small differences. Future studies will focus on finer band ranges and additional spectral parameters at some peak points of the intensity contour at a low frequency band.