• YAKHAK HOEJI
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• v.38 no.4
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• pp.366-371
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• 1994

To improve the identification power of TLC/HPTLC the in situ reflectance spectra obtained directly from plates with commercial scanner are used. The spectrum normalization should be carried out prior to comparing and searching the spectra from library for the identification of compounds. Because the reflectance does not obey the Lambert-Beer's law, there arise some problems in normalization. These problems could be solved to some extent by normalizing the spectra with regression methods. The spectra are manipulated with the regression function of a curve obtained from the correlation plot. When the parabola was used as the manipulating function, the spectra were identified with the accuracy of 97% and this result was better than that of conventionally used the point and area normalization method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.3
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• pp.941-953
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• 2012

A novel and universal method of video image text detection is proposed. A coarse-to-fine text detection method is implemented. Firstly, the spectral clustering (SC) method is adopted to coarsely detect text regions based on the stationary wavelet transform (SWT). In order to make full use of the information, multi-parameters kernel function which combining the features similarity information and spatial adjacency information is employed in the SC method. Secondly, 28 dimension classifying features are proposed and support vector machine (SVM) is implemented to classify text regions with non-text regions. Experimental results on video images show the encouraging performance of the proposed algorithm and classifying features.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1140-1152
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• 2012

A novel and universal method of video image text detection is proposed. A coarse-to-fine text detection method is implemented. Firstly, the spectral clustering (SC) method is adopted to coarsely detect text regions based on the stationary wavelet transform (SWT). In order to make full use of the information, multi-parameters kernel function which combining the features similarity information and spatial adjacency information is employed in the SC method. Secondly, 28 dimension classifying features are proposed and support vector machine (SVM) is implemented to classify text regions with non-text regions. Experimental results on video images show the encouraging performance of the proposed algorithm and classifying features.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.2
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• pp.82-87
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• 1985

The performance comparison method against ground clutter, when the trasnfer function of MTI filter or integrator is given, is considered for the MTI signal processors using a constant PRF. The MTI signal processors are modelled as the transversal filters, and the ground clutter power density spectrum as Gaussian type and the performance of the MTI signal processors are compared by calculating the MTI improvent factors. The MTI imrpovement factors versus normalized spectral width is depicted as examples for the MTI filters, the integrator using Hanning weighting function and the cascading of the two.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.4
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• pp.197-202
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• 2013

Large gains in speech intelligibility can be obtained using the SNR-based binary mask approach. This approach retains the time-frequency (T-F) units of the mixture signal, where the target signal is stronger than the interference noise (masker) (e.g., SNR > 0 dB), and removes the T-F units, where the interfering noise is dominant. This paper introduces two alternative binary masks based on the distortion constraints to improve the speech intelligibility. The distortion constraints are induced by a gain function for estimating the short-time spectral amplitude. One binary mask is designed to retain the speech underestimated (T-F) units while removing the speech overestimated (T-F)units. The other binary mask is designed to retain the noise overestimated (T-F) units while removing noise underestimated (T-F) units. Listening tests with oracle binary masks were conducted to assess the potential of the two binary masks in improving the intelligibility. The results suggested that the two binary masks based on distortion constraints can provide large gains in intelligibility when applied to noise-corrupted speech.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1999.04a
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• pp.61-68
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• 1999

In the nonlinear dynamic structural analysis the given ground excitation as an input should be well defined. Because of the lack of recorded accelerograms in Korea it is required to generate an artificial earthquake by a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms. It is well known that earthquake motions are generally non-stationary with time-varying intensity and frequency content. Many researchers have proposed non-stationary random process models. Yeh and Wen (1990) proposed a non-stationary modulation function and a power spectral density function to describe such non-stationary characteristics. Satio and Wen(1994) proposed a non-stationary stochastic process model to generate earthquake ground motions which are compatible with design reponse spectrum at sites in Japan. this paper shows the process to modify power spectrum compatible with target design response spectrum for generating of nonstationary artificial earthquake ground motions. Target reponse spectrum is chosen by ATC14 to calibrate the response spectrum according to a give recurrence period.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.401-403
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• 2015

We present the results of the analysis of FLS 1718+59, a galaxy-galaxy gravitational lens system in the Spitzer First Look Survey (FLS) field. A background galaxy ($z_s=0.245$) is severely distorted by a nearby elliptical galaxy ($z_l=0.08$), via gravitational lensing. The system is analysed by several methods, including surface brightness fitting, gravitational lens modeling, and spectral energy distribution fitting. From Galfit and Ellipse we measure basic parameters of the galaxy, such as the effective radius and the average surface brightness within it. gravlens yields the total mass inside the Einstein radius ($R_{Ein}$), and MAGPHYS gives us an estimate of the stellar mass inside $R_{Ein}$. By comparing these parameters, we confirm that the lens galaxy is an elliptical galaxy on the Fundamental Plane and calculate the stellar mass fraction inside $R_{Ein}$, and discuss the results with regards to the initial mass function.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.240-242
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• 1994

Spectroscopic ellipsometry(SE) was employed to characterize the Si/$Si_{1-x}Ge_x$ heterostructure. The dielectric function spectrum of $Si_{1-x}Ge_x$ at an arbitrary x value in the spectral range of $1.5{\sim}4.5\;eV$ was computed by EMA (effective medium approximation) model using the available optical constants measured at a number of fixed x values of Ge composition. The thickness and the Ge composition of $Si_{1-x}Ge_x$ measured by SE was compared with those measured by RBS. DC bias effect on the $E_2$ peak of dielectric function spectra was studied.

• MALSORI
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• no.60
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• pp.181-190
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• 2006

This paper describes a speech enhancement scheme that leads to significant improvements in recognition performance when used in the ASR front-end. The proposed approach is based on adaptive comb filtering and an MMSE-related parameter estimator. While adaptive comb filtering reduces noise components remarkably, it is rarely effective in reducing non-stationary noises. Furthermore, due to the uniformly distributed frequency response of the comb-filter, it can cause serious distortion to clean speech signals. This paper proposes an improved comb-filter that adjusts its spectral magnitude to the original speech, based on the speech absence probability and the gain modification function. In addition, we introduce the modified comb filtering-based speech enhancement scheme for ASR in mobile environments. Evaluation experiments carried out using the Aurora 2 database demonstrate that the proposed method outperforms conventional adaptive comb filtering techniques in both clean and noisy environments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.945-950
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• 2001

Floor impact noise has been evaluated by investigating the temporal and spectral characteristics of the noise. The noises generated by different impactors were analyzed to find out whether there is any correlation with the factors of ACF /IACF (Autocorrelation Function/Inter-aural Cross-correlation Function) [1] and Zwicker parameters [2]. Experiments were undertaken to compare the objective and subjective parameters of the floor impact noises generated by a bang/tapping machine, a rubber ball [3], and a walker. As a result, it was found that $\phi$ (0) and IACC extracted from ACF/IACF, and Loudness, Unbiased Annoyance from Zwicker parameters showed high correlation with subjective evaluations of loudness concerning floor impact noises. In addition, it was revealed that jumping is similar to the ball.