• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.7
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• pp.1030-1040
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• 1998

One of the main unresolved issues in large-eddy simulation(LES) of wall-bounded turbulent flows is the requirement of high spatial resolution in the near-wall region, especially in the spanwise direction. Such high resolution required in the near-wall region is generally used throughout the computational domain, making simulations of high Reynolds number, complex-geometry flows prohibitive. A grid-embedding strategy using a nonconforming spectral domain-decomposition method is proposed to address this limitation. This method provides an efficient way of clustering grid points in the near-wall region with spectral accuracy. LES of transitional and turbulent channel flow has been performed to evaluate the proposed grid-embedding technique. The computational domain is divided into three subdomains to resolve the near-wall regions in the spanwise direction. Spectral patching collocation methods are used for the grid-embedding and appropriate conditions are suggested for the interface matching. Results of LES using the grid-embedding strategy are promising compared to LES of global spectral method and direct numerical simulation. Overall, the results show that the spectral domain-decomposition grid-embedding technique provides an efficient method for resolving the near-wall region in LES of complex flows of engineering interest, allowing significant savings in the computational CPU and memory.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.507-516
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• 2014

We present a hybrid method for spectral reflectivity recovery, using 3D extrapolation as a supplemental method for 3D interpolation. The proposed 3D extrapolation is an extended version of 3D interpolation based on the barycentric algorithm. It is faster and more accurate than the conventional spectral-recovery techniques of principal-component analysis and nonnegative matrix transformation. Four different extrapolation techniques (based on nearest neighbors, circumcenters, in-centers, and centroids) are formulated and applied to recover spectral reflectivity. Under the standard conditions of a D65 illuminant and 1964 $10^{\circ}$ observer, all reflectivity data from 1269 Munsell color chips are successfully reconstructed. The superiority of the proposed method is demonstrated using statistical data to compare coefficients of correlation and determination. The proposed hybrid method can be applied for fast and accurate spectral reflectivity recovery in image processing.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.131-133
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• 2003

The streamfunction-vorticity equations for two-dimentional cavity flow are solved by a new finite element method which uses finite spectral basis functions as interpolation functions for rectangular elements. Results for several cases with different Renold's number are compared with benchmark solutions and found to be in well agreement.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.6
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• pp.789-795
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• 2003

It is studied that the measuring method of the spectral emissivity by using hemispherical mirror with an inclined observation hole. The in-service calibration method of mirror reflectivity is also dealed with. It is possible to apply this method on measuring emissivity of conductor or non-conductor.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.411-416
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• 2004

This paper introduces a fast Fourier transform (FFT)-based spectral analysis method for the transient responses as well as the steady-state responses of linear dynamic systems with non-proportional damping. The force vibration of a non-proportionally damped three-DOF system is considered as the illustrative numerical example. The proposed spectral analysis method is evaluated by comparing with the numerical solution obtained by the Runge-Kutta method

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.253-258
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• 1993

In this paper, we propose a new method to extract the line spectrum pair (LSP) frequencies. When speech signal is analyzed by the autocorrelation method, the spectral difference in the logarithmic spectra of the model at steps p and p-1 oscillates. There are p-1 frequency points where the values of the spectral dfference take on either maximum or minimum between 0 and half sampling frequency. We show that these frequencies are excatly the LSP frequencies of order p-1, which can be found by searching the frequencies where the spectral difference reaches either maxima or minima. also, the LSP frequencies of order p can be obtained from this spectral difference. In this case, we derive the expression governing the pth order LSP frequencies. The efficient search for finding the LSP frequencies of order p can be done by proving the property that the LSP frequencies of order p and p-1 are interlaced with each other.

• The Journal of the Acoustical Society of Korea
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• v.31 no.3
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• pp.179-187
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• 2012

This paper presents a novel method for estimating reliable noise spectral magnitude for acoustic background noise suppression where only a single microphone recording is available. The proposed method finds noise estimates from spectral magnitudes measured at line spectral frequencies (LSFs), under the observation that adjacent LSFs are near the peak frequencies and isolated LSFs are close to the relatively flattened valleys of LPC spectra. The parameters used in the proposed method are LPC coefficients, their corresponding LSFs, and the gain of LPC residual signals, so it suits well to LPC-based speech coders.

• Economic and Environmental Geology
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• v.17 no.4
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• pp.237-243
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• 1984

Burg's algorithm for maximum entropy spectral analysis is studied with respect to its computational efficiency and stableness. The Burg's method is not only less efficient than the Yule-Walker's method but also sometimes unstable due to its mathematical irrationality. This irrationality is demonstrated by analyzing an artificial time series, and more stable and effective method is proposed. An efficient procedure using Goertzel's algorithm to compute power spectral densities is also proposed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7C
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• pp.672-679
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• 2006

Cognitive radio, which is designed to dynamically adapt its transmission to the environments, is believed to be one of the fundamental techniques for future spectrum utilization. As the first step of cognitive radio, spectrum sensing is treated as the most important technique, through which cognition is well explained. In this paper, we propose a spectral correlation based detection method for spectrum sensing. An unlicensed secondary user system operating in TV broadcast bands is taken as an example. Based on the cyclostationarity of communication signals, spectral correlation function is used to minimize the effect of random noise and interference. Energy measurement and peak detection based criteria are proposed. Simulation results show that the proposed detection method outperforms the energy detection and is more suitable for spectrum sensing in cognitive radios.