• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2139-2146
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• 2008

This paper presents a numerical algorithm for fault location estimation which used to data from both end of the transmission line. The proposed algorithm is also based on the synchronized voltage and current phasor measured from the PMUs(Phasor Measurement Units) in the time-domain. This paper has separated from two part of with/without shunt capacitance(short/long distance). Most fault was arc one-ground fault which is 75% over [1]. so most study focused with it. In this paper, the numerical algorithm has calculated to distance for ground fault and line-line fault. In this paper, the algorithm is given with/without shunt capacitance using II parameter line model, simple impedance model and estimated using DFT(Discrete Fourier Transform) and the LES(Least Error Squares Method). To verify the validity of the proposed algorithm, the EMTP(Electro- Magnetic Transient Program) and MATLAB did used.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.885-890
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• 2009

A fault location algorithm using estimated local source impedance after a fault is proposed in this paper. The method uses after fault data only at the local end. It uses the negative sequence current distribution factor for more accurate estimation. The proposed algorithm can keep up with the variation of the local source impedance. Therefore, the proposed algorithm especially is valid for a transmission line interconnected to a wind farm that the equivalent source impedance changes continuously. The performance of the proposed algorithm was verified under various fault conditions using the Simpowersystem of MATLAB Simulink. The proposed algorithm is largely insensitive to the variation in fault distance and fault resistance. The test results show a very high accurate performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.391-399
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• 2012

This paper proposes a particle filter approach for SLAM(Simultaneous Localization and Mapping) of a mobile robot. The SLAM denotes estimation of both the robot location and map while the robot navigates in an unknown environment without map. The proposed method estimates robot location simultaneously with the locations of the ultrasonic beacons which constitute landmarks for navigation. The particle filter method represents the locations of the robot and landmarks in probabilistic manner by the distribution of particles. The method takes care of the uncertainty of the landmarks' location as well as that of the robot motion. Therefore, the locations of the landmarks are updated including uncertainty at every sampling time. Performance of the proposed method is verified through simulation and experiments. The method yields practically useful mapping information even if the range data from the landmarks include random noise. Also, it provides more accurate and robust estimation of the robot location than the usual least squares methods or dead-reckoning method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.55-61
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• 2009

This paper proposes a position estimation of a mobile robot based on USN(Ubiquitous Sensor Network) and encoder, and development of tele-operation system using Internet. USN used in experiments is based on ZigBee protocol and has location estimation engine which uses RSSI signal to estimate distance between nodes. By distortion the estimated distance using RSSI is not correct, compensation method is needed. We obtained fuzzy model to calculate more accurate distance between nodes and use encoder which is built in robot to estimate accurate position of robot. Based on proposed position estimation method, tele-operation system was developed. We show by experiment that proposed method is more appropriate for estimation of position and remote navigation of mobile robot through Internet.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1692-1698
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• 2010

In this paper we use wireless sensor network and ultrasonic sensors to estimate local position of mobile robots, and to navigate it. Ultra sonic sensor is simple and accurate so it is good to use in local estimation and navigation of mobile robots. But to obtain accurate distance of two sensors they need to face each others as possible as they can. To solve this problem we rotate ultra sonic sensor which is attached to robot in 360 degrees and obtain accurate distance. We can estimate precise position of mobile robot by triangulation using obtained distance information. A mobile robot navigates using embedded encoder and compensates its coordinates by ultrasonic sensors. Results of Experiments show proposed method obtains accurate distance between sensors and coordinates of position of robot. And mobile robots can navigate designated path well.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.522-522
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• 2000

In this paper, two pre-filtering techniques are presented for accurately estimating the impact location of a loose part. The reason why a pre-filterng technique Is necessary in a Loose Part Monitoring System is that the effects of background noise on the signal to noise ratio (SNR) can be reduced considerably resulting in improved estimation accuracy. The first method is to take d moving average operation in the time domain. The second one is to adopt band-pass filters designed in the frequency domain such as a Butterworth filter, Chebyshev filter I & II and an Elliptic Filter. To show the effectiveness, the impact test data (signals) from the YGN3 power plant are first preprocessed and then used to estimate the loose pan impact position. Resultantly. we observed that SNR is much improved and the average estimation error is below 7.5%.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.47-54
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• 2017

Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

• Smart Media Journal
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• v.1 no.4
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• pp.27-34
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• 2012

In this paper, a novel text binarization is presented that can deal with some complex conditions, such as shadows, non-uniform illumination due to highlight or object projection, and messy backgrounds. To locate the target text region, a focus line is assumed to pass through a text region. Next, connected component analysis and stroke width estimation based on location information of the focus line is used to locate the bounding box of the text region, and each box of connected components. A series of classifications are applied to identify whether each CC(Connected component) is text or non-text. Also, a modified K-means clustering method based on an HCL color space is applied to reduce the color dimension. A text binarization procedure based on location of text component and seed color pixel is then used to generate the final result.

• Journal of IKEEE
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• v.24 no.4
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• pp.982-990
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• 2020

Groundwater is essential source of the freshwater. Groundwater is stored in the body of the rocks or sediments, called aquifer. Finding an aquifer is a very important part of the geophysical survey. The best method to find the aquifer is to make a borehole. Single borehole is not a suitable method if the aquifer is not located in the borehole drilled area. To overcome this problem, a cross borehole method is used. Using a cross borehole method, we can estimate aquifer location more precisely. Electrical impedance tomography is use to estimate the aquifer location inside the subsurface using the cross borehole method. Electrodes are placed inside each boreholes and area between these boreholes are analysed. An aquifer is a non-uniform structure with complex shape which can represented by the truncated Fourier series. Deep neural network is evaluated as an inverse problem solver for estimating the aquifer boundary coefficients.

• Journal of KIISE:Information Networking
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• v.34 no.5
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• pp.370-378
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• 2007

In wireless sensor networks (WSNs), thousands of sensors are often deployed in a hostile environment. In such an environment, WSNs can be applied to various applications by using the absolute or relative location information of the sensors. Until now, the time-of-arrival (TOA) based localization method has been considered most accurate. In the TOA method, however, inaccuracy in distance estimation is caused by clock drift and clock skew between sensor nodes. To solve this problem, several numbers of periodic time synchronization methods were suggested while these methods introduced overheads to the packet traffic. In this paper, we propose a new localization method based on multiple round-trip times (RTOA) of a signal which gives more accurate distance and location estimation even in the presence of clock skew between sensor nodes. Our experimental results show that the Proposed RTOA method gives up to 93% more accurate location estimation.