• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5B
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• pp.321-329
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• 2012

Two regular progressive wave trains, the directions of which are slightly different from each other, develop a honeycomb pattern of wave crests due to their nonlinear interaction. In the honeycomb pattern of wave crest, the nodal line area, which has very low wave energy, is formed. When the honeycomb pattern is developed near the beach area, rip current evolves through the nodal line area formed in the cross shore direction. In this study, to confirm that the formation of honeycomb pattern of waves near the beach area is a dominant mechanism of rip current occurred at Haeundae beach, we performed a numerical simulation of nearshore circulation at Haeundae beach under an unidirectional and monochromatic wave condition by using a nonlinear Boussinesq equation model. As a result, wave refraction due to topographical characteristics (i.e., submerged shoal) of Haeundae gave rise to several wave trains propagating with slightly different directions toward the beach, and consequently rip currents well developed through the nodal line area of honeycomb patterns of wave crest. In addition, we found that a narrow-banded spectral wave condition (i.e., a swell spectrum) increases more likelihood of rip current than a broad-banded spectral wave condtion based on the simulations employing various wave spectra with an equivalent wave height and period.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.640-643
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• 2003

A Walsh function based associative memory is capable of storing m patterns in a single pattern storage space with Walsh encoding of each pattern. Furthermore, each stored pattern can be matched against the stored patterns extremely fast using algorithmic parallel processing. As such, this special type of memory is ideal for real-time processing of large scale information. However this incredible efficiency generates large amount of crosstalk between stored patterns that incurs mis-recognition. This crosstalk is a function of the set of different sequencies [number of zero crossings] of the Walsh function associated with each pattern to be stored. This sequency set is thus optimized in this paper to minimize mis-recognition, as well as to maximize memory saying. In this paper, this Walsh memory has been applied to the problem of face recognition, where PCA is applied to dimensionality reduction. The maximum Walsh spectral component and genetic algorithm (GA) are applied to determine the optimal Walsh function set to be associated with the data to be stored. The experimental results indicate that the proposed methods provide a novel and robust technology to achieve an error-free, real-time, and memory-saving recognition of large scale patterns.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.5
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• pp.187-196
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• 2003

Effects of Airgap and anisotropy substrate on input impedance and radiation pattern of rectangular microstrip patch antenna are studied in terms of an integral equation formulation. The input impedance and radiation pattern of microstrip patch antenna is investigated by using Galerkin's moment method in solving the integral equation. Sinusoidal functions are selected as basis functions, which resemble in the actual standing wave on the Patch. From the numerical results, the variation of input impedance and radiation patterns in the variation of air gap thickness, anisotropy ratio of substrate, and relative permittivity of anisotropy substrate are presented.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.537-543
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• 2003

Transient vibration generated by developing localized fault in gear can be used as indicators in gear fault detection. This vibration signal suffers from the background noise such as gear meshing frequency and its harmonics and broadband noise. Thus in order to extract the information about the only gear fault from the raw vibration signal measured on the gearbox this signal is processed to reduce the background noise with many kinds of signal-processing tools. However, these signal-processing tools are often very complex and time waste. Thus. in this paper. we propose a novel approach detecting the damage of gearbox and analyzing its pattern using the raw vibration signal. In order to do this, the residual signal. which consists of the sideband components of the gear meshing frequent) and its harmonics frequencies, is extracted from the raw signal by the power spectral density (PSD) to obtain the information about the fault and is used as the input data of the artificial neural network (ANN) for analysis of the pattern of gear fault. This novel approach has been very successfully applied to the damage analysis of a laboratory gearbox.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.314-319
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• 2021

The measurement of the Underwater Radiated Noise (URN) for the underwater vehicle should consider both the acoustic interference due to the surface reflection and the calculation of the Closet Point of Approach (CPA). In this paper, I tried to analyze the underwater vehicle's URN using the Lloyd's mirror effect. First, the theoretical Lloyd's mirror pattern was compared with the sea trial result, and the sea trial results corresponded well with the theoretical predicted pattern. And then the CPA distance could be estimated by the Lloyd's mirror pattern. As a results, acoustic source level shows the spectral fluctuation due to the acoustic interference of the Lloyd's mirror effect.

• Journal of Radiation Protection and Research
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• v.42 no.2
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• pp.91-97
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• 2017

Background: A gamma energy identifying algorithm using spectral decomposition combined with smoothing method was suggested to confirm the existence of the artificial radio isotopes. The algorithm is composed by original pattern recognition method and smoothing method to enhance the performance to identify gamma energy of radiation sensors that have low energy resolution. Materials and Methods: The gamma energy identifying algorithm for the compact radiation sensor is a three-step of refinement process. Firstly, the magnitude set is calculated by the original spectral decomposition. Secondly, the magnitude of modeling error in the magnitude set is reduced by the smoothing method. Thirdly, the expected gamma energy is finally decided based on the enhanced magnitude set as a result of the spectral decomposition with the smoothing method. The algorithm was optimized for the designed radiation sensor composed of a CsI (Tl) scintillator and a silicon pin diode. Results and Discussion: The two performance parameters used to estimate the algorithm are the accuracy of expected gamma energy and the number of repeated calculations. The original gamma energy was accurately identified with the single energy of gamma radiation by adapting this modeling error reduction method. Also the average error decreased by half with the multi energies of gamma radiation in comparison to the original spectral decomposition. In addition, the number of repeated calculations also decreased by half even in low fluence conditions under $10^4$ ($/0.09cm^2$ of the scintillator surface). Conclusion: Through the development of this algorithm, we have confirmed the possibility of developing a product that can identify artificial radionuclides nearby using inexpensive radiation sensors that are easy to use by the public. Therefore, it can contribute to reduce the anxiety of the public exposure by determining the presence of artificial radionuclides in the vicinity.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.51-56
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• 2007

Feature functions were used for the classification of music. The spectral roll-off, variance, average peak level, and class were chosen to make up a feature function vector. Among these, it is the spectral roll-off function that has a low-frequency to high-frequency ratio. To find the optimal roll-off point, the roll-off points from 0.05 to 0.95 were swept. The classification success rate was monitored as the roll-off point was being changed. The data that were used for the experiments were taken from the sounds made by a modern violin and a baroque one. Their shapes and sounds are similar, but they differ slightly in sound texture. As such, the data obtained from the sounds of these two kinds of violin can be useful in finding an adequate roll-off point. The optimal roll-off point, as determined through the experiment, was 0.85. At this point, the classification success rate was 85%, which was the highest.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.369-376
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• 2002

This paper presents a method to enhance the performance of supervised classification by separating the spectral signature of the training data sets for each class. Using clustering technique, a training data set is divided into several subsets which show a pattern of the normal distribution with small value of spectral variances. Then a supervised classification is applied with the divided training data set as training data for the temporary subclasses of the original class. The proposed method is applied to a Landsat TM image of Busan area for the applicability test. The result shows that the proposed method produces better classified results than the conventional statistical classification methods. It is expected that the proposed method will reduce the effort and expense for selecting the training data set for each class in an area which has spectrally homogeneous signature.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1
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• pp.29-37
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• 2005

This paper proposes an automatic genre classification system for Korean traditional music. The Proposed system accepts and classifies queried input music as one of the six musical genres such as Royal Shrine Music, Classcal Chamber Music, Folk Song, Folk Music, Buddhist Music, Shamanist Music based on music contents. In general, content-based music genre classification consists of two stages - music feature vector extraction and Pattern classification. For feature extraction. the system extracts 58 dimensional feature vectors including spectral centroid, spectral rolloff and spectral flux based on STFT and also the coefficient domain features such as LPC, MFCC, and then these features are further optimized using SFS method. For Pattern or genre classification, k-NN, Gaussian, GMM and SVM algorithms are considered. In addition, the proposed system adopts MFC method to settle down the uncertainty problem of the system performance due to the different query Patterns (or portions). From the experimental results. we verify the successful genre classification performance over $97{\%}$ for both the k-NN and SVM classifier, however SVM classifier provides almost three times faster classification performance than the k-NN.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.241-251
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• 2007

The observed spectra from Odaesan earthquake were fitted to a point-source spectral model to evaluate the source spectrum and spatial features of the modelling error. The source spectrum was calculated by removing from the observed spectra the path and site dependent responses (Yun, 2007) that were previously revealed through an inversion process applied to a large accumulated spectral dataset. The stress drop parameter of one-corner Brune's ${\omega}^2$ source model fitted to the estimated source spectrum was well predicted by the scaling relation between magnitude and stress drop developed by Yun et al. (2006). In particular, the estimated spectrum was quite comparable to the two-corner source model that was empirically developed for recent moderate earthquakes occurring around the Korean Peninsula, which indicates that Odaesan earthquake is one of typical moderate earthquakes representative of Korean Peninsula. Other features of the observed spectra from Odaesan earthquake were also evaluated based on the commonly treated random error between the observed data and the estimated point-source spectral model. Radiation pattern of the error according to azimuth angle was found to be similar to the theoretical estimate. It was also observed that the spatial distribution of the errors was correlated with the geological map and the $Q_0$ map which are indicatives of seismic boundaries.