• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.760-766
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• 2008

This paper proposes an efficient location technique to find an indoor location under the IEEE 802.11 wireless local area networks. The proposed method is based on the range measurements obtained from a simple radio frequency propagation model. Thus, unlike the radio frequency fingerprint correlation method, it does not suffer from the computational burden during the real-time location service period and can quickly reply the location requests of many users at the same time. To increase the location accuracy in spite of the frequent non-line-of-sight error occurrences, the proposed method calibrates the distortion of the non-line-of-sight error by a simple measurement surveying procedure that does not require the surveyor's manual interaction. Experimental results show the capability of the proposed method.

• Journal of KSNVE
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• v.9 no.2
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• pp.377-386
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• 1999

This paper is a study on model method for estimating system inputs from vibration responses, which is one of indirect input identification methods in frequency domain. The method has advantages over direct inverse method especially when points of operational inputs are inaccessible so that artificial excitation forces cannot be applied to obtain frequency response functions of the complete system. Procedures of extended modal model method are proposed and checked by numerical experiment. Mechanisms of error propagation, i.e., how errors in modal parameters such as poles nad mode shape vectors affect estimation of the input forces, are illustrated. Then, in order to counteract the error propagation, discrete modal filter approach is taken in this paper to compute the inversion of modal matrix in which the most serious errors seem to be generated. Further, a Reduced form of Modified Reciprocal Modal Vector(RMRMV) is proposed for estimating multiple inputs. It is shown to have smaller orthogonality error than MRMV.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.170-179
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• 2007

This paper introduces the optimal disposition of direction finder using EM(Electro-magnetic) wave propagation analysis which is based on LR(Longley-Rice) propagation model and the characteristics of direction finder, emitter and terrain. Initial model is simulated and modified to minimize propagation error as a result of the field trials. Proposed analysis used line-of-sight analysis and mountain-top extraction algorithm to optimize the disposition in the assigned area and the result can be displayed in the 3D map in order of the percentage coverage for direction finding possibility area.

• Journal of Astronomy and Space Sciences
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• v.9 no.1
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• pp.69-88
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• 1992

The effects of the ionosphere on the radio wave propagation are scattering of radio waves, attenuation, angle error, ranging error, and time delay. If ionospheric conditions are suitable, the charged particles can remove energy from radio waves and thus attenuate the signal. Also, a radio wave traveling a path along which the electron density is not constant undergoes changes in direction, positon and time of propagation. The present study is based on Korean ionospheric data obtained at the AnYang Radio Research Institute from Jan. 1985 through Oct. 1989. The data are used to simulate the Korean ionosphere following the Chapman law. The effects of the model ionosphere on the radio wave propagation, such as the angle, position error, time delay, and the attenuation, are studied for the various cases of the wave frequency and the altitude.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3194-3210
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• 2022

Wall obstruction is the main factor leading to the non-line of sight (NLoS) error of indoor localization based on received signal strength indicator (RSSI). Modeling and correcting the path loss of the signals through the wall will improve the accuracy of RSSI localization. Based on electromagnetic wave propagation theory, the reflection and transmission process of wireless signals propagation through the wall is analyzed. The path loss of signals through wall is deduced based on power loss and RSSI definition, and the theoretical model of path loss of signals through wall is proposed. In view of electromagnetic characteristic parameters of the theoretical model usually cannot be accurately obtained, the statistical model of NLoS error caused by the signals through the wall is presented based on the log-distance path loss model to solve the parameters. Combining the statistical model and theoretical model, a hybrid model of path loss of signals through wall is proposed. Based on the empirical values of electromagnetic characteristic parameters of the concrete wall, the effect of each electromagnetic characteristic parameters on path loss is analyzed, and the theoretical model of regional path loss of signals through the wall is established. The statistical model and hybrid model of regional path loss of signals through wall are established by RSSI observation experiments, respectively. The hybrid model can solve the problem of path loss when the material of wall is unknown. The results show that the hybrid model can better express the actual trend of the regional path loss and maintain the pass loss continuity of adjacent areas. The validity of the hybrid model is verified by inverse computation of the RSSI of the extended region, and the calculated RSSI is basically consistent with the measured RSSI. The hybrid model can be used to forecast regional path loss of signals through the wall.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12A
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• pp.1883-1890
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• 1999

Wireless communication in an urban area, the accurate prediction of wave propagation characteristics are very important to determine communication service areas, select optimal base-stations, and design cells, etc. The CCIR model is a propagation prediction model using a shadowing by the buildings in an urban area. This model represent the shadowing rate by the means of the effect of shadowing between base-station and mobile unit in a shaped linear plane. But, This one occurred a lot of prediction error because it did not consider that density area by the buildings and terrain configurations by the hill and mountain on Line-Of-Sight. In this thesis, an improved propagation prediction model is proposed to reduce prediction error. We presents a new equation, which is using the SAS. This equation is associated with the shadow height by the buildings that considers the topology and the number of blocks that can affect the building shadow in the Line-Of-Sight. We measure the received electrical field level of base-station that high density area, medium density area, and low density area, and then compare and analysis the result to prediction of CCIR model and proposed model. The result compared with the measurement, the proposed model has the improvement of 9.71dB in a high density area, 9.66dB in a medium density area, and 4.02dB in a low density area better than the CCIR model. The result compared with the measurement, the proposed model has the improvement of 9.71dB in a high density area, 9.66dB in a medium density area, and 4.02dB in a low density area better than the CCIR model.

• Journal of KIISE:Information Networking
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• v.31 no.4
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• pp.375-383
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• 2004

As wireless mobile networks have been widely adopted due to their convenience for deployment, the research for improving their performance has been actively conducted. Since their throughput is restrained by the packet corruption rate not by congestion as in wired networks, however, network simulations for performance evaluation need to select the appropriate wireless channel model representing the behavior of propagation errors for the evaluated channel. The selection of the right model should depend on various factors such as the adopted frequency band, the level of signal power, the existence of obstacles against signal propagation, the sensitivity of protocols to bit errors, and etc. This paper analyzes 10-day bit traces collected from real sensor channels exhibiting the high bit error rate to determine a suitable sensor channel model. For selection, it also evaluates the performance of two error recovery algorithms such as a link layer FEC algorithm and three TCPs (Tahoe, Reno, and Vegas) over several channel models. The comparison analysis shows that CM(Chaotic Map) model predicts 3-time less BER variance and 10-time larger PER(Packet Error Rate) than traces while these differences between the other models and traces are larger than 10-time. The simulation experiments, furthermore, prove that CM model evaluates the performance of these algorithms over sensor channels with the precision at least 10-time more accurate than any other models.

• Journal of Magnetics
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• v.22 no.1
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• pp.34-42
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• 2017

Material defects in the Steam Generator Tubes (SGT) of sodium cooled fast breeder reactor (PFBR) can lead to leakage of water into sodium. The water and sodium reaction will lead to major accidents. Therefore, the examination of steam generator tubes for the early detection of defects is an important requirement for safety and economic considerations. In this work, the Magnetic Flux Leakage (MFL) based Non Destructive Testing (NDT) technique is used to perform the defect detection process. The rectangular notch defects on the outer surface of steam generator tubes are modeled using COMSOL multiphysics 4.3a software. The obtained MFL images are de-noised to improve the integrity of flaw related information. Grey Level Co-occurrence Matrix (GLCM) features are extracted from MFL images and taken as input parameter to train the neural network. A comparative study on characterization have been carried out using feed-forward back propagation (FFBP) and cascade-forward back propagation (CFBP) algorithms. The results of both algorithms are evaluated with Mean Square Error (MSE) as a prediction performance measure. The average percentage error for length, depth and width are also computed. The result shows that the feed-forward back propagation network model performs better in characterizing the defects.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.81-86
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• 2007

Spectral features of the seismic wave propagation from Odaesan Earthquake were evaluated based on the commonly treated random error between the observed data and the prediction values by the stochastic point-source ground-motion spectral model regarding the source, path and site effects. Radiation pattern of the error according to azimuth angle was found to be similar to the theoretical estimate. It was also observed that the spatial distribution of the errors was correlated with the geological map and the Q0 map which are indicatives of seismic boundaries.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.118-124
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• 2004

In this paper, we present a indirect adaptive control method using a wavelet neural network (WNN) for the control of chaotic nonlinear systems without precise mathematical models. The proposed indirect adaptive control method includes the off-line identification and on-line control procedure for chaotic nonlinear systems. In the off-line identification procedure, the WNN based identification model identifies the chaotic nonlinear system by using the serial-parallel identification structure and is trained by the gradient-descent method. And, in the on-line control procedure, a WNN controller is designed by using the off-line identification model and is trained by the error back-propagation algorithm. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with applications to the chaotic nonlinear systems.