• 품질경영학회지
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• 제19권2호
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• pp.172-180
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• 1991

The null hypothesis being tested by $the{\bar{X}}$ control chart is that the process is in control at a quality level ${\mu}o$. An ${\bar{X}}control$ chart is a tool for detecting process average changes due to assingnable causes. The major weakness of $the{\bar{X}}$ control chart is that it is relatively insensitive to small changes in the population mean. This paper presents one way to remedy this weakness is to allow each plotted value to depend not only on the most recent subgroup average but on some of the other subgroup averages as well. Two approaches for doing this are based on (1) moving averages and (2) exponentially weighted moving averages of forecasting method.

• Journal of Electrochemical Science and Technology
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• 제8권2호
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• pp.115-123
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• 2017

Electrochemical noise signals in many cases exhibit a DC drift that should be removed prior to further data analysis. Polynomial fitting and moving average removal method have been used to remove trends of electrochemical noise (EN) in time domain. The corrosion inhibition of synthesized schiff base N,N'-bis(3,5-dihydroxyacetophenone)-2,2-dimethylpropandiimine on API-5L-X70 steel in hydrochloric acid solutions were used to study the effects of drifts removal methods on noise resistance calculation. Also, electrochemical impedance spectroscopy (EIS) was used to study the corrosion inhibition property of the inhibitor. The results showed that for the calculation of $R_n$, both methods were effective in trend removal and the polynomial with m=4 and MAR with p=40 were in agreement.

• 대한전기학회논문지
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• 제45권3호
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• pp.432-437
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• 1996

This paper describes a diagnostic technique of power transformers by on-line detection of ultrasonic signals. A trend of partial discharge variation in a real transformer was estimated by counting the number of ultrasonic signals until insulation paper in the point-to-plane electrode is punctured. The number of electrical signals is closely related to the ultrasonic signals generated by partial discharge. The trend of the ultrasonic signal number could easily be distinguished by taking moving average. The insulation failure due to partial discharge in transformers can be predicted based on the trend analysis of ultrasonic signal number caused by partial discharge. (author). 14 refs., 10 figs.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.982-985
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• 2000

This paper presents channel estimation of an asynchronous W-CDMA reverse link using the interpolation and moving average algorithm in frequency-selective Rayleigh fading channel. The proposed algorithm is an interpolated decision-directed (IDD) block-wise moving average (BWMA) algorithm. The IDD-BWMA algorithm performs two- stage processes. The first stage performs data decision to make a virtual pilot channel by using linear interpolation channel estimation scheme. Then, the second stage performs the channel estimation of the “block-wise moving average” type by using a virtual pilot channel obtained in the first stage. By using Monte-Carlo computer simulations, we show that the proposed channel estimator is superior to other estimation schemes such as the WMSA(K=1) and DD-RAKE at higher Doppler frequencies, especially.

• International journal of advanced smart convergence
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• 제4권2호
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• pp.46-53
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• 2015

This paper suggests a method of real time confidence interval estimation to detect abnormal states of sensor data. For real time confidence interval estimation, the mean square errors of the exponential smoothing method and moving average method, two of the time series analysis method, were compared, and the moving average method with less errors was applied. When the sensor data passes the bounds of the confidence interval estimation, the administrator is notified through alarms. As the suggested method is for real time anomaly detection in a ship, an Android terminal was adopted for better communication between the wireless sensor network and users. For safe navigation, an administrator can make decisions promptly and accurately upon emergency situation in a ship by referring to the anomaly detection information through real time confidence interval estimation.

• 말소리와 음성과학
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• 제2권4호
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• pp.145-151
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• 2010

In this paper, a robust feature compensation method is proposed for improving the performance of speech recognition. The proposed method is incorporated into the auto-regressive moving average (ARMA) based feature compensation. We employ variable weights for the ARMA filter according to the degree of speech activity, and pass the normalized cepstral sequence through the weighted ARMA filter. Additionally when normalizing the cepstral sequences in training, the cepstral means and variances are estimated from total training utterances. Experimental results show the proposed method significantly improves the speech recognition performance in the noisy and reverberant environments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 B
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• pp.1202-1204
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• 2004

This paper propose the control algorithm for improving the power quality through the voltage compensation when source voltage is dropped. The algorithm signified occurrence of voltage drop in source voltage of each phase storing source voltage for two cycles using the concept of moving average and using the source voltage of last half cycle. If there are voltage drops in the source voltages, series active power filter compensates the differences between reference waveform and source voltage waveform. Therefore, voltage drop is compensated. It proposed series active power filter of three phases three lines to apply to the proposed algorithm and the presented experiment results verified logicality and effectiveness of the proposed algorithm.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.271-287
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• 2019

The synchronization scheme based on moving average is robust and suitable for the same rule to be adopted in embedding watermark and synchronization code, but the imperceptibility and search efficiency is seldom reported. The study aims to improve the original scheme for robust audio watermarking. Firstly, the survival of the algorithm from desynchronization attacks is improved. Secondly, the scheme is improved in inaudibility. Objective difference grade (ODG) of the marked audio is significantly changed. Thirdly, the imperceptibility of the scheme is analyzed and the derived result is close to experimental result. Fourthly, the selection of parameters is optimized based on experimental data. Fifthly, the search efficiency of the scheme is compared with those of other synchronization code schemes. The experimental results show that the proposed watermarking scheme allows the high audio quality and is robust to common attacks such as additive white Gaussian noise, requantization, resampling, low-pass filtering, random cropping, MP3 compression, jitter attack, and time scale modification. Moreover, the algorithm has the high search efficiency and low false alarm rate.

• 전력전자학회논문지
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• 제27권4호
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• pp.316-324
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• 2022

This paper uses seasonal auto-regressive integrated moving average (S-ARIMA), which is efficient in seasonality between time-series models, to predict the degradation tendency for lithium-ion batteries and study a method for improving the predictive performance. The proposed method analyzes the degradation tendency and extracted factors through an electrical characteristic experiment of lithium-ion batteries, and verifies whether time-series data are suitable for the S-ARIMA model through several statistical analysis techniques. Finally, prediction of battery aging is performed through S-ARIMA, and performance of the model is verified through error comparison of predictions through mean absolute error.

• 풍력에너지저널
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• 제10권3호
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• pp.5-11
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• 2019

This paper suggests and compares two algorithms, a moving average filter method and a method developed by the National Renewable Energy Laboratory (NREL), to verify the yaw control algorithm characteristic to reduce yaw error for a wind turbine. A characteristic change for yaw movement in accordance with control parameter change that consists of each control method has been verified. Also, yaw simulations were performed using nacelle wind data measured from two areas with different turbulence intensities and the yaw movement data in each area was compared. These two algorithms and real data were compared by calculating mean absolute error (MSE) and the number of yawing (NY). As a result of the analysis, the MSE values were not significantly different between the two algorithms, but the algorithm proposed by the NREL was found to reduce yaw movement by up to 50 percent more than the moving average filter method.