• Journal of Digital Convergence
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• v.11 no.8
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• pp.183-190
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• 2013

The Photoplethysmogram is a similar periodic signal that synchrinized to a heartbeat. In this paper, we propose a exponential weight moving average filter that use similarity of Photoplethysmogram. This filtering method has the average value of each samples through separating the cycle of PPG signal. If there are some motion artifacts in continuous PPG signal, disjoin the signal based on cycle. And then, we made these signals to have same cycle by coordinating the number of sample. After arrange these cycles in 2 dimension, we put the average value of each samples from starting till now. So, we can eliminate the motion artifacts without damaged PPG signal.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.75-82
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• 2012

The Photoplethysmogram is a similar periodic signal that synchronized to a heartbeat. In this paper, we propose a periodic moving average filter that use similarity of Photoplethysmogram. This filtering method has the average value of each samples through separating the cycle of PPG signal. If there are some motion artifacts in continuous PPG signal, disjoin the signal based on cycle. And then, we made these signals to have same cycle by coordinating the number of sample. After arrange these cycles in 2 dimension, we put the average value of each samples from starting till now. So, we can eliminate the motion artifacts without damaged PPG signal.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.139-146
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• 2023

Maritime object detection systems, which detects small maritime obstacles such as fish farm buoys and visualizes distance and direction, is equipped with a 3-axis gimbal to compensate for errors caused by hull motion, but there is a limit to distance error corrections necessitated by the vertical movement of the camera and the maritime object due to wave motions. Therefore, in this study, the distance error of maritime object detection systems caused by the movement of the water surface according to the external environment is analyzed and corrected using average filter and moving average filter. Random numbers following a Gaussian standard normal distribution were added to or subtracted from the image coordinates to reproduce the rise or fall of the buoy under irregular waves. The distance calculated according to the change of image coordinates, the predicted distance through the average filter and the moving average filter, and the actual distance measured by laser distance meter were compared. In phases 1 and 2, the error rate increased to a maximum of 98.5% due to the changes of image coordinates due to irregular waves, but the error rate decreased to 16.3% with the moving average filter. This error correction capability was better than with the average filter, but there was a limit due to failure to respond to the distance change. Therefore, it is considered that use of the moving average filter to correct the distance error of the maritime object detection system will enhance responses to the real-time distance change and greatly improve the error rate.

• The Journal of Engineering Geology
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• v.18 no.1
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• pp.1-6
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• 2008

Precipitation and groundwater level data sets from Kum river watershed were analyzed and compared. The correlation between groundwater level and the moving average of precipitation was analyzed. Moving averaging technique is stochastic method and that was used to consider the effect of precipitation events on groundwater level fluctuation. Groundwater level generally follows seasonal precipitation pattern and low level occurs from early December to late April. Relatively high groundwater level is appeared in wet spell (July and August). The correlation between groundwater level and the moving average of precipitation to consider precedent precipitation events was analyzed with minimum two-year data sets. When the precipitation and groundwater level data set pair was selected the precipitation gauge station is closely located to groundwater level gauge station in the upstream direction to minimize the non-homogeneous precipitation distribution effect. The maximum correlation was occurred when the averaging periods were from 10 days to 150 days with Kum river watershed data. The correlation coefficients are influenced by data quality, missing data periods, or snow melt effect, etc. The maximum coefficient was 0.8886 for Kum river watershed data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.97-104
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• 2007

Adaptive echo canceller(AEC) has become an important component in speech communication systems, including mobile phones and speech recognition. In these applications, the acoustic echo path has a long impulse response. We propose a moving-averge least mean square(MVLMS) algorithm with a detection method for acoustic echo cancellation. Using, the result of the tests that used colored input models clearly shows that the MVLMS detection algorithm has convergence performance superior to the least mean square(LMS) detection algorithm alone. Although the computational complexity of the new MVLMS algorithm is only slightly greater than that of the standard LMS detection algorithm, the new algorithm confers a significant improvement in stability.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.327-340
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• 2009

To achieve the noise reduction effect in boundary image matching, we use the moving average transform of time-series matching. Our motivation is based on an intuition that using the moving average transform we may exploit the noise reduction effect in boundary image matching as in time-series matching. To confirm this simple intuition, we first propose $\kappa$-order image matching, which applies the moving average transform to boundary image matching. A boundary image can be represented as a sequence in the time-series domain, and our $\kappa$-order image matching identifies similar images in this time-series domain by comparing the $\kappa$-moving average transformed sequences. Next, we propose an index-based matching method that efficiently performs $\kappa$-order image matching on a large volume of image databases, and formally prove the correctness of the index-based method. Moreover, we formally analyze the relationship between an order $\kappa$ and its matching result, and present a systematic way of controlling the noise reduction effect by changing the order $\kappa$. Experimental results show that our $\kappa$-order image matching exploits the noise reduction effect, and our index-based matching method outperforms the sequential scan by one or two orders of magnitude.

• Journal of the Korean Wood Science and Technology
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• v.43 no.3
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• pp.311-319
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• 2015

Near infrared (NIR) reflectance spectroscopy was employed to develop moisture content prediction model of pitch pine (Pinus rigida), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), yellow poplar (Liriodendron tulipifera) wood below fiber saturation point. NIR reflectance spectra of specimens ranging from 1000 nm to 2400 nm were acquired after humidifying specimens to reach several equilibrium moisture contents. To determine the optimal moisture contents prediction model, 5 mathematical preprocessing methods (moving average (smoothing point: 3), baseline, standard normal variate (SNV), mean normalization, Savitzky-Golay $2^{nd}$ derivatives (polynomial order: 3, smoothing point: 11)) were applied to reflectance spectra of each specimen as 8 combinations. After finishing mathematical preprocessings, partial least squares (PLS) regression analysis was performed to each modified spectra. Consequently, the mathematical preprocessing methods deriving optimal moisture content prediction were 1) moving average/SNV for pitch pine and red pine, 2) moving average/SNV/Savitzky-golay $2^{nd}$ derivatives for Korean pine and yellow poplar. Every model contained three principal components.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.115-125
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• 2016

The Bollinger Band indicating the current price position in the recent price action range is obtained by adding/substracting the simple standard deviation (SSD) to/from the simple moving average (SMA). In this paper, we first compare the characteristics of the SMA and the exponential moving average (EMA) in the operator's point of view. A basic equation is obtained between the interval length N of the SMA operator and the weighting factor ${\rho}$ of the EMA operator, that makes the centers of the 1st order momentums of each operator impulse respoinse identical. For equivalent N and ${\rho}$, frequency response examples are obtained and compared by using the discrete time Fourier transform. Based on observation that the SMA operator reacts more excessively than the EMA operator, we propose a novel exponential standard deviation (ESD) band centered at the EMA and derive an auto recursive formula for the proposed ESD band. Practical examples for the ESD band show that it has a smoother bound on the price action range than the Bollinger Band. Comparisons are also made for the gap corrected chart to show the advantageous feature of the ESD band even in the case of gap occurrence. Trading techniques developed for the Bollinger Band can be straight forwardly applied to those for the ESD band.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10A
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• pp.1034-1041
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• 2007

In this paper, we propose a FD USE (frequency domain minimum mean square error) equalizer algorithm for MBOK DS-UWB (M-ary bi-orthogonal keying direct sequence UWB) systems considered as a PHY proposal for high-speed wireless communication in IEEE 802.15.TG3a. The conventional FD MMSE equalization scheme has a structural limit due to insertion of the cyclic prefix (CP) in all transmit packets, but the proposed scheme is able to equalize the channel effect without CP. In order to overcome channel estimation error by multipath delay, we introduce a moving FFT and a moving average scheme. Compared with conventional FD MMSE equalizer and the traditional TD (time domain) MMSE-RAKE receiver, the proposed FD MMSE equalizer has better BER performance and we demonstrate this result by computer simulation.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.457-468
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• 2007

This paper proposes an adaptive moving average (A-MA) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI A-MA chart is to adjust sampling intervals as well as to accumulate previous samples selectively in order to increase the sensitivity. The VSI A-MA chart employs a threshold limit to determine whether or not to increase sampling rate as well as to accumulate previous samples. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI A-MA chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The control length L is introduced to prevent small mean shifts from being undetected for a long period. A Markov chain model is employed to investigate the VSI A-MA sampling process. Formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI A-MA chart is proposed. Comparative studies show that the proposed VSI A-MA chart is uniformly superior to the adaptive Cumulative sum (CUSUM) chart and to the Exponentially Weighted Moving Average (EWMA) chart, and is comparable to the variable sampling size (VSS) VSI EWMA chart with respect to the ATS performance.