• Proceedings of the KSPS conference
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• 2007.05a
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• pp.123-126
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• 2007

This paper suggests a method to improve the performance of the pathological/normal voice classification. The effectiveness of the mel frequency-based filter bank energies using the fisher discriminant ratio (FDR) is analyzed. And mel frequency cepstrum coefficients (MFCCs) and the feature vectors through the linear discriminant analysis (LDA) transformation of the filter bank energies (FBE) are implemented. This paper shows that the FBE LDA-based GMM is more distinct method for the pathological/normal voice classification than the MFCC-based GMM.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.5
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• pp.446-454
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• 2022

This study proposes a carrier-based pulse width modulation (PWM) method for leakage current reduction and neutral point (NP) current control in a three-phase three-level converter, which is a carrier-based PWM version of the previously proposed low-frequency common mode voltage PWM. Three groups of space vectors with the same common mode voltage are used. When the averaged NP current needs to be positive or negative, the specific groups are employed to produce low-frequency common mode voltages. The validity of the proposed PWM method is verified through experiments.

• Journal of Korea Water Resources Association
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• v.41 no.1
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• pp.35-47
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• 2008

The low flow analysis is an important part in water resources engineering. Also, the results of low flow frequency analysis can be used for design of reservoir storage, water supply planning and design, waste-load allocation, and maintenance of quantity and quality of water for irrigation and wild life conservation. Especially, for identification of the uncertainty in frequency analysis, the Bayesian approach is applied and compared with conventional methodologies in at-site low flow frequency analysis. In the first manuscript, the theoretical background for the Bayesian MCMC (Bayesian Markov Chain Monte Carlo) method and Metropolis-Hasting algorithm are studied. Two types of the prior distribution, a non-data- based and a data-based prior distributions are developed and compared to perform the Bayesian MCMC method. It can be suggested that the results of a data-based prior distribution is more effective than those of a non-data-based prior distribution. The acceptance rate of the algorithm is computed to assess the effectiveness of the developed algorithm. In the second manuscript, the Bayesian MCMC method using a data-based prior distribution and MLE(Maximum Likelihood Estimation) using a quadratic approximation are performed for the at-site low flow frequency analysis.

• Structural Engineering and Mechanics
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• v.68 no.1
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• pp.39-51
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• 2018

In this study, a frequency domain model updating method is presented using power spectral density (PSD) data. It uses the sensitivity of PSD function with respect to the unknown structural parameters through a decomposed form of transfer function. The stiffness parameters are captured with high accuracy through solving the sensitivity equations utilizing the least square approach. Using numerically noise polluted data, the model updating results of a truss model prove robustness of the method against measurement and mass modelling errors. Results prove the capabilities of the method for parameter estimation using highly noise polluted data of low ranges of excitation frequency.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.11
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• pp.100-105
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• 2014

In this paper, Uninterruptible Power Supply(UPS) Inverter system using Carrier Frequency Modulated PWM (CFM-PWM) is proposed to reduced harmonics and electromagnetic noise. Power conversion of UPS system is executed by the ON-OFF operation of semiconductor switching devices. However, this switching operation causes the surge and EMI which deteriorate the reliability of the UPS system. This Problems improved by Random PWM switching method. The simulation results of the proposed system was compared with the system using conventional method using Matlab/Simulink. The results show that the output voltage and current harmonics of the proposed UPS system significantly decreased and spread into wide band area by the proposed Carrier Frequency Modulated PWM(CFM-PWM) method based on the Space Vector Modulation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.5
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• pp.65-76
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• 2001

In this paper, performance of frequency-based watermarking methods is compared, which are used to protect copyright of image data. For performance comparison of each transform method, a test image is transformed into frequency domain by a full- and block-discrete cosine transforms and wavelet transform, and after general image processing, robustness of each transform is evaluated with using the same watermark signals. Simulation results show that the watermarking method based on DCTs are more robust than WT. Especially, $8{\times}8$ BDCT is most robust for JPEG lossy compression and sharpening, while $8{\times}8$ FDCT is best. for smoothing and scaling. In addition, watermarking based on BDCT shows decreasing robustness for a larger block size, compared with general image processing.

• Smart Media Journal
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• v.8 no.2
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• pp.16-20
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• 2019

Fast Fourier Transform in the vibration acceleration analysis system has recently been utilized in the field of sensor measurement. In this paper, we propose a Fast Fourier Transform based method of detecting the normal frequency among the many frequency types of diffuse field. This normal frequency is expressed by the formula of frequency damping recognition which is calculated in a similar way to the octave center frequency. Based on this theory, this paper can more accurately inform noise producers of the degree of damping, which is different from the vibration type of diffuse field.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.713-725
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• 2022

Mostly, artificial intelligence does not show any definite change in emotions. For this reason, it is hard to demonstrate empathy in communication with humans. If frequency modification is applied to neutral emotions, or if a different emotional frequency is added to them, it is possible to develop artificial intelligence with emotions. This study proposes the emotion conversion using the Generative Adversarial Network (GAN) based voice frequency synthesis. The proposed method extracts a frequency from speech data of twenty-four actors and actresses. In other words, it extracts voice features of their different emotions, preserves linguistic features, and converts emotions only. After that, it generates a frequency in variational auto-encoding Wasserstein generative adversarial network (VAW-GAN) in order to make prosody and preserve linguistic information. That makes it possible to learn speech features in parallel. Finally, it corrects a frequency by employing Amplitude Scaling. With the use of the spectral conversion of logarithmic scale, it is converted into a frequency in consideration of human hearing features. Accordingly, the proposed technique provides the emotion conversion of speeches in order to express emotions in line with artificially generated voices or speeches.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1335-1341
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• 2015

The utilization of electric vehicles has been suggested to support the frequency regulation of power system. Assuming that an intermediate aggregator exists, this study suggests a decentralized vehicle-to-grid operation scheme in which each vehicle-to-grid aggregator can behave independently of the power system operator. To implement this type of decentralized operation, this study adopts a price-based operation that has been proposed by many researches as an alternative operation scheme for the power system. In this environment, each vehicle-to-grid aggregator can determine its participation in vehicle-to-grid service in consideration of its residual energy of aggregated system and real-time market price. Consequently, the main purpose of this study is to verify whether or not the vehicle-to-grid power can effectively support the current frequency regulation function within the price-based operation scheme. Specifically, a frequency regulation method is proposed based on the real-time price signal, and a feedback controller for battery management is designed for decentralized vehicle-to-grid operation.

• Structural Monitoring and Maintenance
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• v.4 no.4
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• pp.301-329
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• 2017

Impedance-based damage detection method has been known as an innovative tool with various successful implementations for structural health monitoring of civil structures. To monitor the local critical area of a structure, the impedance-based method utilizes the high-frequency impedance responses sensed by piezoelectric sensors as the local dynamic features. In this paper, current advances and future challenges of the impedance-based structural health monitoring are presented. Firstly, theoretical background of the impedance-based method is outlined. Next, an overview is given to recent advances in the wireless impedance sensor nodes, the interfacial impedance sensing devices, and the temperature-effect compensation algorithms. Various research works on these topics are reviewed to share up-to-date information on research activities and implementations of the impedance-based technique. Finally, future research challenges of the technique are discussed including the applicability of wireless sensing technology, the predetermination of effective frequency bands, the sensing region of impedance responses, the robust compensation of noise and temperature effects, the quantification of damage severity, and long-term durability of sensors.