• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.451-459
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• 2018

We calculated the optimal exponent values based on the hourly rainfall data observed in South Korea by treating the exponent value as a variable without fixing it as a square in the inverse distance method. For this purpose, rainfall observation stations providing the data are classified into four groups which are located at the Han river upstream, downstream, the Geum river upstream, and the Nakdong river midstream area. A total of 52 cases were analyzed for seven stations in each group. The optimal exponent value of distance was calculated in a case including one base station and four surrounding stations in a group. We applied the golden section search method to calculating this optimum values using rainfall data for 10 years (2004~2013) and verified the optimum values for the last three years (2014~2016). We compared and analyzed two results of the conventional inverse distance method and the inverse distance method in this study. The optimal values of distance exponent obtained in this study were 3.280, 1.839, 2.181, and 2.005 respectively, in the four groups, and totally mean value was 2.326. It is shown the proposed inverse distance method applying the optimal exponent is superior to the conventional inverse distance method.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.318-321
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• 2003

In this paper, path loss and delay profile characteristics are measured in the subway platform. To evaluate the fading characteristics of the measured signals, the standard deviations are computed. The standard deviation is bigger for shorter distance. The shorter the distance, the bigger the phase difference between direct wave and reflected waves according the distance, which results in heavy fading. To compute the path loss according to distance, the average values of path loss exponent(n) is evaluated. The path loss exponents measured in the subway environment for Omni-VP(omni-directional vertical polarization) antenna and CP(circular polarization) antenna are 1.418 and 1.680, respectively, which are considerably less than 2.0, the free space path loss exponent.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.7 s.166
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• pp.1065-1074
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• 1999

This study proposes the analysis and evaluation method of time series ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaotic time series signal analysis quantitatively welding defects. For this purpose analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaoticity resulting from distance shills such as 0.5 and 1.0 skip distance. Such differences in chaoticity enables the evaluation of unique features of defects in the weld zone. In experiment fractal(correlation) dimension and Lyapunov exponent extracted from 6dB ultrasonic defect signals of weld zone showed chaoticity. In quantitative chaotic feature extraction, feature values(mean values) of 4.2690 and 0.0907 in the case of porosity and 4.2432 and 0.0888 in the case of incomplete penetration were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaotic feature extraction in this study enhances ultrasonic pattern recognition results from defect signals of weld zone such as vertical hole.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.55-63
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• 2013

In cognitive radio networks, acquirement of position information of primary user is very important to secondary network since localization information of primary users can be utilized for improving the spectrum efficiency of secondary network and for avoiding harmful interference to primary users by using proper power control. Among various location methods, Received Signal Strength (RSS)-based localization has been widely used for distance measurements in the location detection process despite its inherent inaccuracy because it can be easily implemented without any additional hardware cost. In the RSS-based localization, the distance is measured by the received signal strength, and distance error can be caused by many factors such as fading, shadowing and obstacle between two nodes. In the paper, therefore we propose a localization scheme based on estimation of path-loss exponent to localize the location of primary users more accurately. Through simulations, it is shown that the proposed scheme can provide less localization error and interference rate to primary users than other schemes.

• Journal of Welding and Joining
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• v.16 no.5
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• pp.108-118
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• 1998

This study proposes th analysis and evaluation method of time series ultrasonic signal using the chaos feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaos time series signal analyze quantitatively weld defects. For this purpose, analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaosity resulting from distance shifts such as 0.5 and 1.0 skip distance. Such differences in chaosity enables the evaluation of unique features of defects in the weld zone. In quantitative chaos feature extraction, feature values of 4.511 and 0.091 in the case of side hole and 4.539 and 0.115 in the case of vertical hole were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaos feature extraction in this study can enhances ultrasonic pattern recognition results from defect signals of weld zone such as side hole and vertical hole.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2338-2356
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• 2013

In cognitive radio networks, acquiring the position information of the primary user is critical to the communication of the secondary user. Localization of primary users can help improve the efficiency with which the spectrum is reused, because the information can be used to avoid harmful interference to the network while simultaneity is exploited to improve the spectrum utilization. Despite its inherent inaccuracy, received signal strength based on range has been used as the standard tool for distance measurements in the location detection process. Most previous works have employed the path-loss propagation model with a fixed value of the path loss exponent. However, in actual environments, the path loss exponent for each channel is different. Moreover, due to the complexity of the radio channel, when the number of channel increases, a larger number of RSS measurements are needed, and this results in additional energy consumption. In this paper, to overcome this problem, we propose using the Bayesian compressive sensing method with a calibrated path loss exponent to improve the performance of the PU localization method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.243-257
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• 2010

Rapid developments in wireless sensor networks have extended many applications, hence, many studies have developed wireless sensor network positioning systems for indoor environments. Among those systems, the Global Position System (GPS) is unsuitable for indoor environments due to Line-Of-Sight (LOS) limitations, while the wireless sensor network is more suitable, given its advantages of low cost, easy installation, and low energy consumption. Due to the complex settings of indoor environments and the high demands for precision, the implementation of an indoor positioning system is difficult to construct. This study adopts a low-cost positioning method that does not require additional hardware, and uses the received signal strength (RSS) values from the receiver node to estimate the distance between the test objects. Since many objects in indoor environments would attenuate the radio signals and cause errors in estimation distances, knowing the path loss exponent (PLE) in an environment is crucial. However, most studies preset a fixed PLE, and then substitute it into a radio propagation loss model to estimate the distance between the test points; such method would lead to serious errors. To address this problem, this study proposes a Path Loss Exponent Estimation Algorithm, which uses only four beacon nodes to construct a radio propagation loss model for an indoor environment, and is able to provide enhanced positioning precision, accurate positioning services, low cost, and high efficiency.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.2
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• pp.123-129
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• 2010

The purpose of study is to investigate the correlation between the Lyapunov exponent (LE) and the displacement of the center of gravity (DCG) for clarifying walking stability on the treadmill. From fifteen young healthy subjects volunteered, lower extremity joint angles were recorded using a three-dimensional motion capture system with reflective markers. The anteroposterior DCG and the LE were calculated by a commercial software. A linear correlation between LE and DCG (p<0.05) showed that LEs compensated for walking distance on the treadmill walking. However, LEs were found to be independent of self-selected walking speeds by a negligible correlation between LE and the Froude number (p>0.05).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1450-1456
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• 2015

The received signal strengths according to the propagation distance between a transmitting shore station with a 53 m antenna hight and a receiving ship station with about 6m antenna hight from 700 m upto about 20 km are measured at ship's moving velocity of $5{\pm}1m/s$ using a single carrier signal at 150.0625MHz. In this paper, the path loss exponents at the propagation distance from 700 m to 20km are estimated via minimum-mean-square-error method using the measurements of the received signal strength, and the mean of the estimated path loss exponent become 3.79. The estimated propagation path loss exponents is similar to that calculated based on the field-strength values from 2 km to 20 km in Annex 2 of ITU-R P.1546-4, which is measuring results at maritime VHF at 100 MHz carrier frequency. Therefore, the estimated propagation path loss exponent shall be used as the expected path loss exponents for summer in costal area of South Sea of Korea.

• Journal of Environmental Science International
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• v.20 no.1
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• pp.25-34
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• 2011

The new empirical static model was constructed on the basis of dimension analysis to predict the pressure drop according to the operating conditions. The empirical static model consists of the initial pressure drop term (${\Delta}P_{initial}$) and the dust mass number term($N_{dust}=\frac{{\omega}_0{\nu}_f}{P_{pulse}t}$), and two parameters (dust deposit resistance and exponent of dust mass number) have been estimated from experimental data. The optimum injection distance was identified in the 64 experimental data at the fixed filtration velocity and pulse pressure. The dust deposit resistance ($K_d$), one of the empirical static model parameters got the minimum value at d=0.11m, at which the total pressure drop was minimized. The exponent of dust mass number was interpreted as the elasticity of pressure drop to the dust mass number. The elasticity of the unimodal behavior had also a maximum value at d=0.11m, at which the pressure drop increased most rapidly with the dust mass number. Additionally, the correlation coefficient for the new empirical static model was 0.914.