• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.1-7
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• 2011

This paper proposes an enhanced noise robust algorithm for fault location on double-circuit transmission line for the case of single line-to-ground (SLG) fault, which uses distributed parameter line model that also considers the mutual coupling effect. The proposed algorithm requires the voltages and currents from single-terminal data only and does not require adjacent circuit current data. The fault distance can be simply determined by solving a second-order polynomial equation, which is achieved directly through the analysis of the circuit. The algorithm, which employs the faulted phase network and zero-sequence network with source impedance involved, effectively eliminates the effect of load flow and fault resistance on the accuracy of fault location. The proposed algorithm is tested using MATLAB/Simulink under different fault locations and shows high accuracy. The uncertainty of source impedance and the measurement errors are also included in the simulation and shows that the algorithm has high robustness.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.58-60
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• 2019

Double JPEG compression detection is one of the most important ways of exposing the integrity of the JPEG image in image forensics. Several methods have been proposed for discriminating against the double JPEG image. In this paper, we propose a new method for restoring the JPEG compressed image and making the detector confused by introducing a Generative Adversarial Network (GAN). First, a generator network is designed for restoring the JPEG compressed image and analyzed the quality. Then, the restored image is tested with the double compression detector for evaluating the robustness of the proposed GAN model. The detection accuracy reduces from 98% to 58%.

• Journal of Electrical Engineering and Technology
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• v.3 no.3
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• pp.308-313
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• 2008

This article proposes the study and simulation of an RST regulator based on a double fed induction machine. The RST polynomial controller can improve the double fed induction machine performance in terms of overshoot, rapidity, cancellation of disturbance, and capacity to maintain a high level of performance. A control law is synthesized using an RST controller. Simulation results indicate that the proposed regulator has better performance response to speed variation, sensitivity to perturbation, and robustness. The designed control algorithm is tested on a simulation matlab code.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.142-145
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• 2001

In the double-talk situation where both the near-end and far-end signal present, the performance of echo cancellation using the NLMS algorithm is degraded easily since it freezes the adaptation in this situation. To solve this problem, which utilize the correlation function values of input signal instead of the input signal itself, have been proposed. Because this algorithm could be used to adapt the filter's parameters continuously even in the double-talk situation, give good convergence property compared with the NLMS. In this paper, we compare and analyze its performance. The computer simulation was performed and the results showed as that ECLMS algorithms were robust and kept the desirable performance even in the double-talk situation.

• Journal of Korean Association for Spatial Structures
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• v.17 no.4
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• pp.51-58
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• 2017

The characteristics and effectiveness of double tuned mass dampers (DTMD) have been studied by many researchers. DTMD usually consists of one larger mass block and one smaller mass block. In this study, DTMD was proposed to reduce the vibration of vertical pumps in industrial plants. In order to assess the efficiency of the proposed method, numerical analysis for the simplified vertical pump model with single and double TMDs was carried out. It was also investigated that the effects of optimal TMD parameters such as frequency ratio and damping ratio on dynamic responses of the main structure. According to analysis results, DTMD are more effective to control the vibration of the vertical pump and show good robustness to the change in the stiffness of TMD.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.309-327
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• 2021

Dynamic treatment regimes (DTRs) are decision-making rules designed to provide personalized treatment to individuals in multi-stage randomized trials. Unlike classical methods, in which all individuals are prescribed the same type of treatment, DTRs prescribe patient-tailored treatments which take into account individual characteristics that may change over time. The Q-learning method, one of regression-based algorithms to figure out optimal treatment rules, becomes more popular as it can be easily implemented. However, the performance of the Q-learning algorithm heavily relies on the correct specification of the Q-function for response, especially in observational studies. In this article, we examine a number of double-robust weighted least-squares estimating methods for Q-learning in high-dimensional settings, where treatment models for propensity score and penalization for sparse estimation are also investigated. We further consider flexible ensemble machine learning methods for the treatment model to achieve double-robustness, so that optimal decision rule can be correctly estimated as long as at least one of the outcome model or treatment model is correct. Extensive simulation studies show that the proposed methods work well with practical sample sizes. The practical utility of the proposed methods is proven with real data example.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.1
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• pp.116-121
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• 2018

In this paper, we propose the SIIM fuzzy Quasi-sliding mode controller for the system of a double inverted pendulum on a cart. Since it is difficult to handle this 6th-order system, we decoupled the entire system into three $2^{nd}$ order subsystem, and we designed the SIIM fuzzy Quasi-sliding mode controller for each subsystem, which was easy and did not require the derivation of the equivalent control. The stability of the entire system is guaranteed using Lyapunov function. The validity and robustness of the proposed controller are demonstrated through the computer simulation, and the results are compared with the results of former studies.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1315-1323
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• 2014

Although the power density in Double Stator Switched Reluctance Motor (DSSRM) has been improved, the torque ripple is still very high. So, it is important to reduce the torque ripple for specific applications such as Electric Vehicles (EVs). In This paper, an effective rotor shaping optimization technique for torque ripple reduction of DSSRM is presented. This method leads to the lower torque pulsation without significant reduction in the average torque. The method is based on shape optimization of the rotor using Finite Element Method and Taguchi's optimization method for rotor reshaping for redistribution of the flux so that the phase inductance profile has smoother variation as the rotor poles move into alignment with excited stator poles. To check on new design robustness, mechanical analysis was used to evaluate structural conformity against local electromagnetic forces which cause vibration and deformation. The results show that this shape optimization technique has profound effect on the torque ripple reduction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.478-486
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• 2007

Double-talk detection errors can result in either large residual echo or distorting the near-end talker's input speech. Thus accurate double-talk detection is an important problem in the acoustic echo canceller to improve the speech quality. In the double-talk detection algorithm using a cross-correlation coefficient, double-talk detection errors can occur in the initial convergence period of an adaptive filter or in noisy environment since the cross-correlation coefficient becomes large in such situations. In this paper, we propose a new double-talk detection algorithm based on the cross-correlation method using a normalized error signal power to reduce the double-talk detection errors. The experimental results have shown the performance improvement of an acoustic echo canceller as well as the noise-robustness of the proposed double-talk detector.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.401-407
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• 2009

In this paper, we propose a novel method for the cross-correlation based double-talk detection (DTD), which employing the Gaussian Mixture Model (GMM) in the frequency domain. The proposed algorithm transforms the cross correlation coefficient used in the time domain into 16 channels in the frequency domain using the discrete fourier transform (DFT). The channels are then selected into seven feature vectors for GMM and we identify three different regions such as far-end, double-talk and near-end speech using the likelihood comparison based on those feature vectors. The presented DTD algorithm detects efficiently the double-talk regions without Voice Activity Detector which has been used in conventional cross correlation based double-talk detection. The performance of the proposed algorithm is evaluated under various conditions and yields better results compared with the conventional schemes. especially, show the robustness against detection errors resulting from the background noises or echo path change which one of the key issues in practical DTD.