• Journal of Korea Water Resources Association
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• v.42 no.4
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• pp.355-363
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• 2009

The purpose of this paper is to investigate the influence of noise on chaotic time series. We used two time series of Lorenz system and of Great Salt Lake's volume data which are well known as chaotic systems. This study investigated the attractors, correlation dimensions, and Close Returns Plots and Close Returns Histograms of two time series to investigate the influence of noise as increasing noise level. We performed Chi-square test to the relative frequency of Close Returns Histogram from Close Returns Plot for the investigation of stochastic process of chaotic time series as increasing noise level of time series. As the results, two time series were changed from chaotic to stochastic series as noise level is increased. Finally, we analyzed the effect of noise cancellation by using Simple Moving Average method. The results of applications of Simple Moving Average method to Lorenz and GSL time series showed that we could effectively cancel the noise. Then we could confirm the applicability of Simple Moving Average method to cancel the noise for the hydrologic time series having chaotic characteristics.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.75-81
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• 2005

Borror et al. discussed the EWMA(Exponentially Weighted Moving Average) chart to monitor the count of defects which follows the Poisson distribution, referred to the $EWMA_c$ chart, as an alternative Shewhart c chart. In the $EWMA_c$ chart, the Markov chain approach is used to calculate the ARL (Average Run Length). On the other hand, in order to monitor the process fraction defectives P in high-yield processes, Xie et al. presented the CCC(Cumulative Count of Conforming)-r chart of which quality characteristic is the cumulative count of conforming item inspected until observing $r({\geq}2)$ nonconforming items. Furthermore, Ohta and Kusukawa presented the $CS(Confirmation Sample)_{CCC-r}$ chart as an alternative of the CCC-r chart. As a more superior chart in high-yield processes, in this paper we present an $EWMA_{CCC-r}$ chart to detect more sensitively small or moderate shifts in P than the $CS_{CCC-r}$ chart. The proposed $EWMA_{CCC-r}$ chart can be constructed by applying the designing method of the $EWMA_C$ chart to the CCC-r chart. ANOS(Average Number of Observations to Signal) of the proposed chart is compared with that of the $CS_{CCC-r}$ chart through computer simulation. It is demonstrated from numerical examples that the performance of proposed chart is more superior to the $CS_{CCC-r}$ chart.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.4
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• pp.43-48
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• 2015

In this study, a method to enhance the dynamic range of seismic sensor is proposed. The low frequency noise included in the measurement of seismic sensor is modelled as an ARMA(Auto Regressive Moving Average) model and the order and parameters of the model are identified through system identification method. The identified noise model is augmented into Kalmman filter which estimate seismic signal from sensor measurement. The proposed method is applied to a newly developed seismic sensor which is MEMS based 3-axis accelerometer type. The experiment show that the proposed method can enhance the dynamic range compared to the simple low pass filtering.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.331-341
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• 2002

In order to extract 3-dimensional information from 2-D image, stereo images are prerequisite. Moreover, for the measurement of moving objects, the synchronized sequential stereo images have to be captured and image matching should be implemented for determining the location of moving objects. In this research, a simple method computing 3-dimensional coordinates from sequential images of moving objects was implemented. The sequential stereo images were captured by a video camera with a beam splitter. Once video images were digitalized by frame grabber, the interest points were extracted and matched in each stereo image, and the coordinates of center of them are calculated using weighted average method. Then, 3-dimensional coordinates of moving objects were computed by DLT algorithms.

• Journal of Korea Water Resources Association
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• v.53 no.7
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• pp.533-543
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• 2020

In order to provide information for proper management of groundwater resources, it is necessary to estimate the rise time of groundwater level by calculating the delay time between the time series of precipitation and groundwater level and to understand the characteristics of groundwater level variation. In this study, total delay time (TDT) and cross correlation coefficient between the moving averaged precipitation generated by using the moving average method to take into account the preceding precipitation and the groundwater level were calculated and analyzed for the nine groundwater level monitoring wells in the Pyoseon watershed in the southeast of Jeju Island. As a result, when the moving averaged precipitation was used, the correlation with the groundwater level was higher in all monitoring wells than in the case of using the raw precipitation, so that it was possible to more clearly estimate the delay time between precipitation and groundwater level. When using the moving averaged precipitation, it had cross correlation coefficients of up to 0.57 ~ 0.58 with the time series data of the groundwater level, and had a relatively high correlation when considering the preceding precipitation of about 24 days on average. The TDT was about 32 days on average, and it was confirmed that the consideration of preceding precipitation plays an important role in estimating the TDT because the days of moving averaged precipitation greatly influences the calculation of the TDT. In addition, through the use of moving averaged precipitation, we found an error in estimating the TDT due to the use of raw precipitation. Through the method of estimating the TDT used in this study and the use of the R code for estimating the TDT presented in the appendix of this paper, it will be possible to estimate the TDT for other regions in the future relatively easily.

• Journal of Advanced Marine Engineering and Technology
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• v.41 no.1
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• pp.56-61
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• 2017

This paper presents a data prediction method and its application to haptic-based teleoperation systems. In general, time delays inevitably occur during data transmission in a network environment, which degrades the overall performance of haptic-based teleoperation systems. To address this situation, this paper proposes an autoregressive moving average (ARMA) model-based data prediction algorithm for estimating model parameters and predicting future data recursively in real time. The proposed method was applied to haptic data captured every 5 ms while bilateral haptic interaction was carried out by two users with an object in a virtual space. The results showed that the prediction performance of the proposed method had an error of less than 1 ms when predicting position-level data 100 ms ahead.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.117-124
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• 2009

If time series data with seasonal effect exist, various statistical models like winters for successful forecasts could be used. But if the data are not enough to estimate seasonal effect, not much methods are available. This paper proposes the statistical forecasting method based on cumulative data when the data are not enough to estimate seasonal effect. We apply this method to real cosmetic sales data and show its better performance over moving average method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.293-297
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• 2007

This thesis suggests a new algorithm to detects multiple moving objects using a CMODE(Correct Multiple Object DEtection) method in the color images acquired in real-time and to track the interested pedestrian using motion and hue information. The multiple objects are detected, and then shaking trees or moving cars are removed using structural characteristics and shape information of the man , the interested pedestrian can be detected, The first similarity judgment for tracking an interested pedestrian is to use the distance between the previous interested pedestrian's centroid and the present pedestrian's centroid. For the area where the first similarity is detected, three feature points are calculated using k-mean algorithm, and the second similarity is judged and tracked using the average hue value for the $3{\times}3$ area of each feature point. The zooming of camera is adjusted to track an interested pedestrian at a long distance easily and the FOV(Field of View) of camera is adjusted in case the pedestrian is not situated in the fixed range of the screen. As a experiment results, comparing the suggested CMODE method with the labeling method, an average approach rate is one fourth of labeling method, and an average detecting time is faster three times than labeling method. Even in a complex background, such as the areas where trees are shaking or cars are moving, or the area of shadows, interested pedestrian detection is showed a high detection rate of average 96.5%. The tracking of an interested pedestrian is showed high tracking rate of average 95% using the information of situation and hue, and interested pedestrian can be tracked successively through a camera FOV and zooming adjustment.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.1
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• pp.58-66
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• 2007

Genetic Algorithms (GA) have some difficulties in practical applications because of too many function evaluations. To overcome these limitations, an approximated modeling method such as Response Surface Modeling(RSM) is coupled to GAs. Original RSM method predicts linear or convex problems well but it is not good for highly nonlinear problems cause of the average effect of the least square method(LSM). So the locally approximated methods. so called as moving least squares method(MLSM) have been used to reduce the error of LSM. In this study, the efficient evolutionary GAs tightly coupled with RSM with MLSM are constructed and then a 2-dimensional inviscid airfoil shape optimization is performed to show its efficiency.

• Journal of Integrative Natural Science
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• v.7 no.3
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• pp.200-207
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• 2014

Average number of samples to signal (ANSS) and average time to signal (ATS) are the most widely used criterion for comparing the efficiencies of the quality control charts. In this study the method of evaluating ANSS and ATS values of the multivariate exponentially weighted moving average (EWMA) control charts with Markov chain approach was presented when the production process is in control state or out of control state. Through numerical results, it is found that when the number of transient state r is less than 50, the calculated ANSS and ATS values are unstable; and ATS(r) tends to be stabilized when r is greater than 100; in addition, when the properties of multivariate EWMA control chart is evaluated using Markov chain method, the number of transient state r requires bigger values when the smoothing constatnt ${\lambda}$ becomes smaller.