• Journal of Information Processing Systems
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• v.19 no.3
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• pp.275-288
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• 2023

Many image edge details are easily lost in the image denoising process, and the smooth image regions are prone to produce jagged. In this paper, we propose a wavelet-based image global k- singular value decomposition variational method to remove image noise. A layer of wavelet decomposition is applied to the noisy image first. Then, the image global k-singular value decomposition (IGK-SVD) method is used to remove the random noise of low-frequency components. Furthermore, a constructed variational denoising method (VDM) removes the random noise in the high-frequency component. Finally, the denoised image is obtained by wavelet reconstruction. The experimental results show that the proposed method's peak signal-to-noise ratio (PSNR) value is higher than other methods, and its structural similarity (SSIM) value is closer to one, indicating that the proposed method can effectively suppress image noise while retaining more image edge details. The denoised image has better denoising effects.

• KSBB Journal
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• v.13 no.5
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• pp.577-584
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• 1998

A sensitive membrane strip assay for plasma lipoprotein cholesterol that can be performed without handling reagents has been investigated. We previously developed an assay system with immobilized enzymes (cholesterol esterase and cholesterol oxidase) on the surfaces of nitrocellulose membrane(1). In such a case, the amount of enzymes present on the membrane was limited by its surface area and, thus, the detection capability was relatively poor (> 50 mg/dL cholesterol). To overcome this problem, we devised a new system with non-immobilized enzymes by placing them within interstitial spaces of a celullose membrane pad in a dry state. Upon contact with sample medium, the enzymes were immediately dissolved and participated in the reactions with cholesterol in a liquid phase. We constructed a user-friendly system consisting of four membrane pads fro sample application, cholesterol decomposition, color development as signal, and medium absorption to invoke a continuous flow (sequential location from the bottom). A sample containing lipoproteins was added into the application pad by capillary action and transferred to the next pad for decomposition. The decomposition pad (namely, enzyme pad) contained a detergent (sodium cholate) for the destruction of lipoprotein particles, the two enzymes for cholesterol decomposition, and a chromogen (3,3'-diaminobenzidine). As a consequence of the enzyme reactions, hydrogen peroxide was produced, and then reacted in the presence of the chromogen with horseradish peroxidase immobilized on the signal generation pad. Finally, a colorimetric signal directly proportional to the cholesterol concentration was produced. The detection limit determined from this system under optimal conditions was at least 2 times lower than of the enzyme-immobilized system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.81-88
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• 2018

Spectrum sensing, the key technology of the cognitive radio networks, is used by a secondary user to determine the frequency state of a primary user. The energy detection in the spectrum sensing determines the presence or absence of a primary user according to the intensity of the allocated channel signal. Since this technique simply uses the strength of the signal for spectrum sensing, it is difficult to detect the signal of a primary user in the low SNR band. In this paper, we propose a way to combine spectrum sensing and support vector machine using wavelet packet decomposition to overcome performance degradation in low SNR band. In our proposed scheme, the sensing signals were extracted by wavelet packet decomposition and then used as training data and test data for support vector machine. The simulation results of the proposed scheme are compared with the energy detection using the AUC of the ROC curve and the accuracy according to the SNR band. With simulation results, we demonstrate that the proposed scheme show better determining performance than one of energy detection in the low SNR band.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.6
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• pp.482-493
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• 2016

The identification of modal damping of a segmented hull model with torsional response is difficult task due to the coupling of modal response. This is because the 1st and 2nd torsional vibration modes are closely spaced in frequency domain leading to the situation that the modal decomposition is difficult to achieve by simple band-pass filter. Present study applied several different modal decomposition methods to derive the damping ratio of different modes. The modal decomposition methods considered in this study are simple band-pass filter, Hilbert vibration decomposition, Wavelet transform and proper orthogonal decomposition. Coupled free decay signal obtained from the torsional hammering test on a segmented hull model was processed with four different methods and the derived damping ratios were compared with each other. Discussions also have been made on the pros and cons of the different methodologies.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.128-137
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• 2016

In mobile communication, air conduction(AC) speech signal had been commonly used, but it was easily affected by ambient noise environment such as emergency, military action and rescue. To overcome the weakness of the AC speech signal, bone conduction(BC) speech signal have been used. The BC speech signal is transmitted through bone vibration, so it is affected less by the background noise. In this paper, we proposed noise cancellation algorithm of the BC speech signal using noise feature of decomposed bands. The proposed algorithm consist of three steps. First, the BC speech signal is divided into 17 bands using perceptual wavelet packet decomposition. Second, threshold is calculated by noise feature during short time of separated-band and compared to absolute average of the signal frame. Therefore, the speech and noise parts are detected. Last, the detected noise parts are removed and then, noise eliminated bands are re-synthesised. In order to confirm the efficiency of the proposed algorithm, we compared the proposed algorithm with conventional algorithm. And the proposed algorithm has better performance than the conventional algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.50-56
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• 2001

As the fuzzy control is applied to servo system, the hardware implementation of the fuzzy information systems requires the high speed operations, short real time control and the small size systems. The aims of this study is to develop hardware of the fuzzy information systems to be apply to servo system. In this paper, we propose a calculation method of approximate reasoning for fuzzy control based on $\alpha$ -level set decomposition of fuzzy sets by quantize $\alpha$ -cuts. This method can be easily implemented with analog hardware. The influence of quantization Bevels of $\alpha$-cuts on output from fuzzy inference engine is investigated. It is concluded that 4 quantization levels give sufficient result for fuzzy control performance of dc servo system. The hardware implementation of proposed operation method and of the defuzzification by gravity center method which is directly converted to PWM actuating signal is also presented. It is verified useful with experiment for dc servo system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.8
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• pp.816-827
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• 2009

This paper deals with a bearing faults localization technique based on holographic approach by visualizing sound radiated from the faults. The main idea stems from the phenomenon that bearing faults in a moving vehicle generate impulsive sound. To visualize fault signal from the moving vehicle, we can use the moving frame acoustic holography [Kwon, H.-S. and Kim, Y.-H., 1998, "Moving Frame Technique for Planar Acoustic Holography," J. Acoust. Soc. Am. Vol. 103, No. 4, pp. 1734${\sim}$1741]. However, it is not easy to localize faults only by applying the method. This is because the microphone array measures noise(for example, noise from other parts of the vehicle and the wind noise) as well as the fault signal while the vehicle passes by the array. To reduce the effect of noise, we propose two ideas which utilize the characteristics of fault signal. The first one is to average holograms for several frequencies to reduce the random noise. The second one is to apply the partial field decomposition algorithm [Nam, K.-U., Kim, Y.-H., 2004, "A Partial Field Decomposition Algorithm and Its Examples for Near-field Acoustic Holography," J. of Acoust. Soc. Am. Vol. 116, No. 1, pp. 172${\sim}$185] to the moving source, which can separate the fault signal and noise. Basic theory of those methods is introduced and how they can be applied to localize bearing faults is demonstrated. Experimental results via a miniature vehicle showed how well the proposed method finds out the location of source in practice.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.6
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• pp.302-308
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• 2001

SVD(Singular Value Decomposition) filter for the suppression of EMG in multi-lead stress ECG is studied. SVD filter consists of two parts. In the first part, the basis vectors were chosen from the averaged singular vectors obtained from the decomposed noise-free ECG. The singular vector is computed from the stress ECG and is compared itself with basis vectors to know whether the noise exist in stress ECG. In the second part, the existing elimination method is used, when one(or two) channels is(or are) contaminated by noise. But the proposed enhanced SVD filter is used in case of having the noise in the many channels. During signal decomposition and reconstruction, the noise-free channel or the least noisy channel have the weight of 1, the next less noisy channel has the weight of 0.8. In this way, every channel was weighted by decreased of 0.2 in proportion to the amount of the added noise. For the evaluation of the proposed enhanced SVD filter, we compared the SNR computed by the enhanced SVD filter with the standard average filter for the noise-free signal added with artificial noise and the patient data. The proposed SVD filter showed better in the SNR than the standard average filter. In conclusion, we could find that the enhanced SVD filter is more proper in processing multi-lead stress ECG.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.6
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• pp.700-708
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• 2014

Jet engine modulation(JEM) is a frequency modulation phenomenon of the radar signal induced by electromagnetic scattering from a rotating jet engine turbine. Although JEM can be used as a representative radar target recognition method by providing unique information on the target, its recognition performance may be degraded in the observation range of weakly present JEM. Hence, this paper presents a method for extracting the JEM component by decomposing the radar signal into intrisic mode functions(IMFs) via complex empirical mode decomposition(CEMD) and by combining them based on signal eccentricity. Its application to various signals demonstrated that the proposed method improved the clarity of JEM analysis and could extend the effective observation range of JEM.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.811-823
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• 2018

Multivariate control chart based on Hotelling's $T^2$ statistic is a powerful tool in statistical process control for identifying an out-of-control process. It is used to monitor multiple process characteristics simultaneously. Detection of the out-of-control signal with the $T^2$ chart indicates mean vector shifts. However, these multivariate signals make it difficult to interpret the cause of the out-of-control signal. In this paper, we review methods of signal interpretation based on the Mason, Young, and Tracy (MYT) decomposition of the $T^2$ statistic. We also provide an example on how to implement it using R software and demonstrate simulation studies for comparing the performance of these methods.