• Journal of Ocean Engineering and Technology
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• v.25 no.2
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• pp.1-6
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• 2011

Vibration-based Structural Health Monitoring (SHM) systems use field measurements of operational signals, which are distorted by noise from many sources. Reducing this noise allows a more accurate assessment of the original "clean" signal and improves analysis results. The implementation of a noise reduction methodology for the Modal Distribution Method (MDM) is reported here. The spectral subtraction method is a popular broadband noise reduction technique used in speech signal processing. Its basic principle is to subtract the magnitude of the noise from the total noisy signal in the frequency domain. The underlying assumption of the method is that noise is additive and uncorrelated with the signal. In speech signal processing, noise can be measured when there is no signal. In the MDM, however, the magnitude of the noise profile can be estimated only from the magnitude of the Power Spectral Density (PSD) at higher frequencies than the frequency range of the true signal associated with structural vibrations under the additional assumption of white noise. The implementation of the spectral subtraction method to MDM may decrease the energy of the individual mode. In this work, a modification of the spectral subtraction method is introduced that enables the conservation of the energies of individual modes. The main difference is that any (negative) bars with a height below zero after subtraction are set to the absolute value of their height. Both noise reduction methods are implemented in the MDM, and an application example is presented that demonstrates its effectiveness when used with a signal corrupted by noise.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.11
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• pp.1192-1201
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• 2009

Analysis of the vibration characteristic for cylindrical shell is more complex than plates since the coupling effects are considered on three dimensions. Based on Love's equation, spectral finite element method(SFEM) is introduced to predict frequency response function of finite circular cylindrical shell in the air with simply supported - free boundary condition without simplifying the equation of motion. And for the radiated noise analysis of cylindrical shell, indirect boundary element method(BEM) is applied using out-of-plane displacements as an input from structural vibration analysis. Comparisons of the structural vibration results by the spectral finite element method and commercial code, NASTRAN(FEM based) are carried out. Likewise, for verification of radiated noise analysis results, commercial code, SYSNOISE(BEM based) are used.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1994.10a
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• pp.103-112
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• 1994

Various kinds of fatigue failures of ocean structures were reported and the importance of fatigue life estimation at the design state is significantly recognized and various kinds of analysis approaches have been discussed. In this paper characteristics of the simplified method proposed here and the spectral method are studied and the elements of the approach are discussed. The merits and demerits of the forementioned analysis schemes are studied and the relating parameters such as SCF and S-N curves are also investigated. The simplified fatigue analysis approach and tile spectral fatigue analysis technique is applied for the analysis of bracing members of typical semi-submersible drilling rig structure for the verification of the usage of two methods and the sensitivity study has been performed using the simplified method. The result from the spectral analysis give a more realistic picture of the fatigue life of the offshore structure considered here.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.211-216
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• 2006

The Constrained Linear Spectral Unmixing(CLSU) is investigated for sub-pixel image processing, Its result is the abundance map which mean fractions of endmember existing in a mixed pixel. Compared to the Linear Spectral Unmixing using least square method, CLSU uses the NNLS (Non-Negative Least Square) algorithm to guarantee that the estimated fractions are constrained. But, CLSU gets Into difficulty in image processing due to select endmember at a user's disposition. In this study, endmember selection optimization method using entropy in the error-image analysis is proposed. In experiments which is used hyperion image, it is shown that our method can select endmember number than CLSU based on unsupervised endemeber selection.

• Bulletin of the Korean Mathematical Society
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• v.51 no.2
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• pp.595-612
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• 2014

The spectral collocation method for a second order elliptic boundary value problem on a domain ${\Omega}$ with curved boundaries is studied using the Gordon and Hall transformation which enables us to have a transformed elliptic problem and a square domain S = [0, h] ${\times}$ [0, h], h > 0. The preconditioned system of the spectral collocation approximation based on Legendre-Gauss-Lobatto points by the matrix based on piecewise bilinear finite element discretizations is shown to have the high order accuracy of convergence and the efficiency of the finite element preconditioner.

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.238-241
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• 1993

We present a new method to normalize spectral variations of different speakers based on physiological studies of hearing. The proposed method uses the cochlear frequency map to warp the input speech spectra by interpolation or decimation. Using this normalization method, we can obtain much improved recognition results for speaker independent speech recognition.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.587-599
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• 1995

This paper proposes a method for pattern recognition using spectral analysis and a hybrid genetic-neural-fuzzy networks. The feature vectors using spectral analysis on contour sequences of 2-D images are extracted, and the vectors are not effected by translation, rotation and scale variance. A combined model using the advantages of conventional method is proposed, those are supervised learning BP, global searching genetic algorithm, and unsupervised learning fuzzy c-method. The proposed method is applied to 10 aircraft recognition to confirm the performance of the method. The experimental results show that the proposed method is better accuracy than conventional method using BP or fuzzy c-method, and learning speed is enhanced.

• Honam Mathematical Journal
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• v.37 no.3
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• pp.299-315
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• 2015

In this paper, we study the first-order system least-squares (FOSLS) spectral method for parabolic partial differential equations. There were lots of least-squares approaches to solve elliptic partial differential equations using finite element approximation. Also, some approaches using spectral methods have been studied in recent. In order to solve the parabolic partial differential equations in parallel, we consider a parallel numerical method based on a hybrid method of the frequency-domain method and first-order system least-squares method. First, we transform the parabolic problem in the space-time domain to the elliptic problems in the space-frequency domain. Second, we solve each elliptic problem in parallel for some frequencies using the first-order system least-squares method. And then we take the discrete inverse Fourier transforms in order to obtain the approximate solution in the space-time domain. We will introduce such a hybrid method and then present a numerical experiment.

• Analytical Science and Technology
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• v.8 no.4
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• pp.477-480
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• 1995

Isotopic-spectral method [I] was applicated for determination of carbon in silicate materials (pure silica, guartz glasses, geological probs etc.). Isotopic heterogeneous balancing of carbon in gaseous phase and solid samples was carried out at the temperature of $1500-1900^{\circ}K$. Spectroscopic measuring of isotope concentration in a balanced gas was made using the electron-vibrational band heads of CO molecules excited in HF discharge. Limits of detection of carbon concentrations appear to be $n^*10^{-6}$.

• Journal of Korea Multimedia Society
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• v.4 no.4
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• pp.306-315
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• 2001

In noise reduction method from noisy speech for speech recognition in noisy environments, conventional spectral subtraction method has a disadvantage which distinction of noise and speech is difficult, and characteristic of noise can't be estimated accurately. Also, noise reduction method in the wavelet transform domain has a disadvantage which loss of signal is generated in the high frequency domain. In order to compensate theme disadvantage, this paper propose spectral subtraction method in continuous wavelet transform domain which speech and non- speech intervals is distinguished by standard deviation of wavelet coefficient, and signal is divided three scales at different scale. The proposed method extract accurately characteristic of noise in order to apply spectral subtraction method by end detection and band division. The proposed method shows better performance than noise reduction method using conventional spectral subtraction and wavelet transform from viewpoint signal to noise ratio and Itakura-Saito distance by experimental.