• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.505-510
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• 2014

Normalized Difference Vegetation Index (NDVI) is a major indicator for monitoring climate change and detecting vegetation coverage. In order to retrieve NDVI, it is preprocessed using cloud masking and atmospheric correction. However, the preprocessed NDVI still has abnormally low values known as noise which appears in the long-term time series due to rainfall, snow and incomplete cloud masking. An existing method of using polynomial regression has some problems such as overestimation and noise detectability. Thereby, this study suggests a simple method using amoving average approach for correcting NDVI noises using SPOT/VEGETATION S10 Product. The results of the moving average method were compared with those of the polynomial regression. The results showed that the moving average method is better than the former approach in correcting NDVI noise.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.19-27
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• 1998

To achieve the required services in the next-generation cellular telephone systems, the size of the cell become smaller and/or is of mixed macrocells and microcells. For more efficient system control, We make use of the mobile position and velocity information, provided that the mobility information is relatively accurate. In this paper, we propose an improved version of path-loss measurement algorithm introduced in literature[11]. The microcellular structure with severe multipath fading, reflection and refraction make mobile position and velocity estimation very difficult. In the proposed method, the pre-recorded path-loss informations, called the discrete position data base, are searched to estimate the position. Velocity estimation is obtained as a difference of the position values with respect to the time difference. Moving average filter is applied to smooth the estimated velocity and to reduce the error in the estimates. We also propose a method to simplify system implementation by reducing search area for discrete area database.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.5
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• pp.307-313
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• 2015

Leak detection in a pipeline usually involves acoustic emission sensors such as contact type sensors. These contact type sensors pose difficulties for installation and cannot operate in areas having high temperature and radiation. Therefore, recently, many researchers have studied the leak detection phenomenon by using a camera. Leak detection by using a camera has the advantages of long distance monitoring and wide area surveillance. However, the conventional leak detection method by using difference images often mistakes the vibration of a structure for a leak. In this paper, we propose a method for steam leakage detection by using the moving average of difference images and histogram analysis. The proposed method can separate the leakage and the vibration of a structure. The working performance of the proposed method is verified by comparing with experimental results.

• Journal of Information Display
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• v.6 no.4
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• pp.16-25
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• 2005

In this paper, a new 3D object tracking system using the disparity motion vector (DMV) is presented. In the proposed method, the time-sequential disparity maps are extracted from the sequence of the stereo input image pairs and these disparity maps are used to sequentially estimate the DMV defined as a disparity difference between two consecutive disparity maps Similarly to motion vectors in the conventional video signals, the DMV provides us with motion information of a moving target by showing a relatively large change in the disparity values in the target areas. Accordingly, this DMV helps detect the target area and its location coordinates. Based on these location data of a moving target, the pan/tilt embedded in the stereo camera system can be controlled and consequently achieve real-time stereo tracking of a moving target. From the results of experiments with 9 frames of the stereo image pairs having 256x256 pixels, it is shown that the proposed DMV-based stereo object tracking system can track the moving target with a relatively low error ratio of about 3.05 % on average.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.230-236
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• 2011

This paper proposes the possibility which the fuzzy theory can be used to improve the performance of the parabolic SAR(Stop-And-Reverse) indicator in the trading systems for stock market. The simulation results with data of the KOSPI 200 future show that the occurred number of trading signals and the false signals in the proposed fuzzy SAR indicator is less than that in the conventional SAR indicator. In the conventional SAR system, the incremental value of the acceleration factor is usually setted as 0.02 and the maximum value of the acceleration factor is usually limited as 0.2. But in the proposed fuzzy SAR system, the incremental value and the maximum value of the acceleration factor are automatically adjusted by using the fuzzy rules, which are designed based-on the difference between short-term moving average and medium-term moving average and also based-on the slope of short-term moving average.

• 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%.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.2
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• pp.89-98
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• 2020

Prediction of clock behaviors is necessary to generate very high stable system time which is essential for a satellite navigation system. For the purpose, we applied the Auto-Regressive Integrated Moving Average (ARIMA) model to the prediction of two hydrogen masers' behaviors with respect to the rapid Coordinated Universal Time (UTCr). Using the packaged programming language R, we made an analysis and prediction of time series data of [UTCr - clocks]. The maximum variation width of the residuals which were obtained by the difference between the predicted and measured values, was 6.2 ns for 106 days. This variation width was just one-sixth of [UTCr-UTC (KRIS)] published by the BIPM for the same period. Since the two hydrogen masers were found to be strongly correlated, we applied the Vector Auto-Regressive Moving Average (VARMA) model for more accurate prediction. The result showed that the prediction accuarcy was improved by two times for one hydrogen maser.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.50 no.9
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• pp.471-475
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• 2001

ln this paper, a micromachined micromechanical switch is presented. The presented switch is operated in the vertical direction to the substrate by an electrostatic force between two parallel plates. The moving plate is pulled down to connect the bumps of the bias node$(V_{DD}/ or GND)$ to the bumps of the output node when a oltage difference exists between the moving plate and the input plate. The switch was designed to operate at a low switching voltage$(\risingdotseq5V)$ by including a large-area, narrow-gap, parallel plate capacitor A theoretical analysis of the designed switch was performed in order to determine its geometry fitting the desired pull-in voltage and release voltage. The designed switch was fabricated by surface micromachining combined with Ni electroplating. From the experimental results of the fabricated switch, its pull-in voltage came Out to be less than 5V and the measured maximum allowable current was 150mA. The measured average ON-state resistance was about 8$\Omega$, and the OFF-state resistance was too high to be measured with digital multimeter.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.45-51
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• 1996

This paper presents a neural network approach for on-line estimation of partial discharge(PD) location using advanced correlation technique in power transformer. Ultrasonic sensors detect ultrasonic signals generated by a PD and the proposed method calculates time difference between the ultrasonic signals at each sensor pair using the cross-correlation technique applied by moving average and the Hamming window. The neural network takes distance difference as inputs converted from time difference, and estimates the PD location. Case studies showed that the proposed method using advanced correlation technique and a neural network estimated the PD location better than conventional methods.

• Korean Journal of Agricultural Science
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• v.41 no.3
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• pp.169-175
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• 2014

Objective of this study was to investigate effects of pre-processing method and number of sampling leaves on stability of the reflectance measurement for Chinese cabbage and kale leaves. Chinese cabbage and kale were transplanted and cultivated in a plant factory. Leaf samples of the kale and cabbage were collected at 4 weeks after transplanting of the seedlings. Spectra data were collected with an UV/VIS/NIR spectrometer in the wavelength region from 190 to 1130 nm. All leaves (mature and young leaves) were measured on 9 and 12 points in the blade part in the upper area for kale and cabbage leaves, respectively. To reduce the spectral noise, the raw spectral data were preprocessed by different methods: i) moving average, ii) Savitzky-Golay filter, iii) local regression using weighted linear least squares and a $1^{st}$ degree polynomial model (lowess), iv) local regression using weighted linear least squares and a $2^{nd}$ degree polynomial model (loess), v) a robust version of 'lowess', vi) a robust version of 'loess', with 7, 11, 15 smoothing points. Effects of number of sampling leaves were investigated by reflectance difference (RD) and cross-correlation (CC) methods. Results indicated that the contribution of the spectral data collected at 4 sampling leaves were good for both of the crops for reflectance measurement that does not change stability of measurement much. Furthermore, moving average method with 11 smoothing points was believed to provide reliable pre-processed data for further analysis.