• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2213-2220
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• 2017

This paper proposes an efficient approach for hardware implementation of moving object detection (MOD) processor using effective Gaussian mixture learning (EGML)-based background subtraction method. Arithmetic units used in background generation were implemented using LUT-based approximation to reduce hardware complexity. Hardware resources used for both background subtraction and Gaussian probability density calculation were shared. The MOD processor was verified by FPGA-in-the-loop simulation using MATLAB/Simulink. The MOD performance was evaluated by using six types of video defined in IEEE CDW-2014 dataset, which resulted the average of recall value of 0.7700, the average of precision value of 0.7170, and the average of F-measure value of 0.7293. The MOD processor was implemented with 882 slices and block RAM of $146{\times}36kbits$ on Virtex5 FPGA, resulting in 60% hardware reduction compared to conventional design based on EGML. It was estimated that the MOD processor could operate with 75 MHz clock, resulting in real-time processing of $800{\times}600$ video with a frame rate of 39 fps.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.250-257
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• 2011

In this paper, we proposed the method detecting multiple pedestrians using motion information and SVM(Support Vector Machine) from a moving camera image. First, we detect moving pedestrians from both the difference image and the projection histogram which is compensated for the camera ego-motion using corresponding feature sets. The difference image is simple method but it is not detected motionless pedestrians. Thus, to fix up this problem, we detect motionless pedestrians using SVM The SVM works well particularly in binary classification problem such as pedestrian detection. However, it is not detected in case that the pedestrians are adjacent or they move arms and legs excessively in the image. Therefore, in this paper, we proposed the method detecting motionless and adjacent pedestrians as well as people who take excessive action in the image using motion information and SVM The experimental results on our various test video sequences demonstrated the high efficiency of our approach as it had shown an average detection ratio of 94% and False Positive of 2.8%.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.4
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• pp.200-205
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• 2017

In this paper, we propose a technique to determine the normal and arc of an alternating current using a mixed filter composed of an average filter and a band-pass filter and a frequency analysis. The proposed method uses the moving average filter of the FIR filter structure for noise removal and the band-pass filter of the IIR filter structure for detecting only specific frequency components after normalizing the measured current signal based on the maximum value. After performing Fast Fourier Transform (FFT) using the band-pass filtered signal, the total energy is calculated using the magnitude component of the frequency, and the arc is detected using the magnitude of the calculated energy. In order to show the validity of the proposed method, we experimented with various data and found that arc and steady state can be easily discriminated by calculating spectral energy. Therefore, it is considered that the proposed method can be applied to arc diagnosis of low voltage electric wire.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.112-115
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• 2010

The heart rate is the most important vital sign in diagnosing heart status. The simple method to measure the heart rate in the mobile healthcare device is using the PPG signal. In developing the mobile healthcare device using the PPG signal, the most important issue is the inaccuracy of the measured heart rate because the PPG signal is distorted from the user's motions. To improve the problem, this study proposed the new method that is to estimate the heart rate without an additional sensor in real life. The proposed method in this study is using the histogram filter. In order to evaluate the performance of the proposed method, the study compares its results with the moving average method in motion environment. According to the experimental results, the performance of the proposed method was more than 40% better than the performances of the MAF.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.135-141
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• 2003

For the analysis of machined surface topography and machine-tool chatter, the cutting system is considered to be a single degree of freedom system. This paper presents a modeling method of equivalent vibratory system for precision cutting in end-milling using an impact test, an Autoregressive Moving Average (ARMA) mode] and a bisection method It has been shown that the proposed modeling method provides a good identification of the cutting system. The advantages of the proposed method in comparison to the existing method are that it is very easy and accurate.

• Journal of the Korea Safety Management & Science
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• v.18 no.4
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• pp.161-169
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• 2016

In this research, we propose efficient demand forecasting scheme for intermittent demand. For this purpose, we first extensively analyze the drawbacks of the existing forecasting methods such as Croston method and Syntetos-Boylan approximation, then using these findings we propose the new demand forecasting method. Our goal is to develop forecasting method robust across many situations, not necessarily optimal for a limited number of specific situations. For this end, we adopt combining forecasting method that utilizes unbiased forecasting methods such as simple exponential smoothing and simple moving average. Various simulation results show that the proposed forecasting method performed better than the existing forecasting methods.

• Journal of Korean Society of Forest Science
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• v.101 no.2
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• pp.213-219
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• 2012

The $5^{th}$ national forest inventory (NFI5) has been reorganized to annual inventory system for providing multi-resources forest statistics at a point in time. The objective of this study is to evaluate statistical estimators for estimating forest growing stock in Chungcheongbuk-Do from annual inventory data. When comparing two estimators; simple random sampling (SRS) and double sampling for post-stratification (DSS), for estimating mean forest growing stock ($m^3/ha$) at each surveyed year, the estimate for DSS in which a population of interest is stratified into three sub-population (forest cover types) was more precise than that for SRS. To combine annual inventory field data, three estimators (Temporally Indifferent Method; TIM, Moving Average; MA, and Weighted Moving Average; WMA) were compared. Even though the estimated mean for TIM and WMA is identical, WMA-DSS is preferred to provide more smaller variance of estimated mean and to adjust for catastrophic events at a surveyed year (so-called "lag bias") by annual inventory data.

• Journal of Korea Water Resources Association
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• v.37 no.5
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• pp.437-448
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• 2004

The traditional fixed areal DAD(rainfall Depth-Area-Duration) method, generally quoted in most hydrology texts, is a simple and useful procedure when watersheds are small and storm movement is not an important factor of consideration. However, it is difficult to obtain satisfactory results for the more apparent forms of storm movement such as typhoons, or for large watershed. In the latter case, especially the margin of error for the areal average rainfall increases proportionally to the area of study, causing biased result. To overcome these limitations, this study focuses on the storm-centered DAD analysis(moving area DAD method) developed and programmed by the isohyetal concept to obtain accurate and objective results. By comparing and analyzing the observed rainfall rates through both method, it was proved that the currently Proposed method more accurately reflected the average rainfall rate. In short, through this new method, approximately 130 storm events nationwide from 1969 to 1999 was analyzed and compared with the fixed areal method results.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.4
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• pp.431-435
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• 2008

Since previous work CDP(Congestion Driven Placement) [1] considers all possible directions to move every cell in nets which contribute highly to routing congestion, it consumes CPU time a lot. In this paper, we propose a faster global placement technique, so called ICDGP(Improved Congestion Driven Global Placement) to relieve the routing congestion. ICDGP uses the force-directed method to determine the target locations of the cells in the nets in the congested spots, and considers only to move the target location for each cell. If moving multiple cells simultaneously is considered better than moving each cell one by one it moves multiple cells simultaneously. By experimental results, ICDGP produces less congested placement than CDP does. Particularly, the CPU time is reduced by 36% on average.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.867-872
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• 2005

This study introduces a method to evaluate the probability of a specific area to be affected by a drought of a given severity and shows its potential for investigating agricultural drought characteristics. The method is applied to Gyeonggi as a case study. The proposed procedure includes Standard Precipitation Index(SPI) time series, which are linearly transformed by the Empirical Orthogonal Functions(EOF) method, These EOFs are extended temporally with AutoRegressive Moving Average(ARMA) method and spatially with Kriging method. By performing these simulations, long time series of SPI can be simulated for each designed grid cell in whole Gyeonggi area. The probability distribution functions of the area covered by a drought and the drought severity are then derived and combined to produce drought severity-area-frequency(SAF) curves.