• Journal of IKEEE
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• v.14 no.1
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• pp.25-32
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• 2010

In this paper, we analyze the location accuracy of real-time locating systems (RTLS) in multipath environments, where the RTLS complies with an ISO/IEC 24730-2 international standard. RTLS readers should have an ability not only to recover the transmitted signal but also provide arrival timing information from the received signal. In the multipath environments, in general, the transmitted signal goes through both direct and indirect paths, and then it becomes some distorted form of the transmitted signal. Such multipath components have a critical effect on deciding the first arrival timing of the received signal. To analyze the location error of the RTLS in the multipath environments, we assume two multipath components without considering an additive white Gaussian noise. Through the simulation and real test results, we confirm that the location error does not occur when the time difference between two paths is more than 1.125Tc, but the location error of about 2.4m happens in case of less than 0.5Tc. In particular, we see that the resolvability of two different paths depends largely on the phase difference for the time difference of less than 1Tc.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.411-418
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• 2017

During the intramedullary nailing procedure, surgeons feel difficulty in manipulation of the X-ray device to align it to axes of nailing holes and suffer from the large radiation exposure from the X-ray device. These problems are caused by the fact the surgeon cannot see the hole's location directly and should use the X-ray device to find the hole's location and direction. In this paper, we proposed the robotic guidance of the distal screwing using an optical tracking system. To track the location of the hole for the distal screwing, the reference marker is attached to the proximal end of an intramedullary nail. To guide the drill's direction robustly, the 6-degree-of-freedom robotic arm is used. The robotic arm is controlled so as to align the drill guiding tool attached the robotic arm with the obtained the hole's location. For the safety, the robot's linear and angular velocities are restricted to the predefined values. The experimental results using the artificial bones showed that the position error and the orientation error were 0.91 mm and $1.64^{\circ}$, respectively. The proposed method is simple and easy to implement, thus it is expected to be adopted easily while reducing the radiation exposure significantly.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.1
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• pp.41-46
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• 2006

Ubiquitous location based services, offer helpful services anytime and anywhere by using real-time location information of objects based on ubiquitous network. Particularly, autonomous mobile robots can be a solution for various applications related to ubiquitous location based services, e.g. in hospitals, for cleaning, at airports or railway stations. However, a meaningful and still unsolved problem for most applications is to develop a robust and cheap positioning system. A typical example of position measurements is dead reckoning that is well known for providing a good short-term accuracy, being inexpensive and allowing very high sampling rates. However, the measurement always has some accumulated errors because the fundamental idea of dead reckoning is the integration of incremental motion information over time. The other hand, a localization system using RFID offers absolute position of robots regardless of elapsed time. We construct an absolute positioning system based on RFID and investigate how localization technique can be enhanced by RFID through experiment to measure the location of a mobile robot. Tags are placed on the floor at 5cm intervals in the shape of square in an arbitrary space and the accuracy of position measurement is investigated . To reduce the error and the variation of error, a weighting function based on Gaussian function is used. Different weighting values are applied to position data of tags since weighting values follow Gaussian function.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.381-389
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• 2012

This paper proposes a method which corrects location data of GPS for navigation of outdoor mobile robot. The method uses a Bayesian filter approach called the particle filter(PF). The method iterates two procedures: prediction and correction. The prediction procedure calculates robot location based on translational and rotational velocity data given by the robot command. It incorporates uncertainty into the predicted robot location by adding uncertainty to translational and rotational velocity command. Using the sensor characteristics of the GPS, the belief that a particle assumes true location of the robot is calculated. The resampling from the particles based on the belief constitutes the correction procedure. Since usual GPS data includes abrupt and random noise, the robot motion command based on the GPS data suffers from sudden and unexpected change, resulting in jerky robot motion. The PF reduces corruption on the GPS data and prevents unexpected location error. The proposed method is used for navigation of a mobile robot in the 2011 Robot Outdoor Navigation Competition, which was held at Gwangju on the 16-th August 2011. The method restricted the robot location error below 0.5m along the navigation of 300m length.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.603-613
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• 2005

We propose some estimators of the location parameter and derive the approximate maximum likelihood estimators (AMLEs) of the scale parameter in the exponential distribution based on multiply Type-II censored samples. We calculate the moments for the proposed estimators of the location parameter, and the AMLEs which are the linear functions of the order statistics. We compare the proposed estimators in the sense of the mean squared error (MSE) for various censored samples.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.141-146
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• 2018

Recently, location recognition technology has attracted much attention, especially for locating people or objects in an indoor environment without being influenced by the surrounding environment GPS technology is widely used as a method of recognizing the position of an object or a person. GPS is a very efficient, but it does not allow the positions of objects or people indoors to be determined. RFID is a technology that identifies the location information of a tagged object or person using radio frequency information. In this study, an RFID system is constructed and the position is measured using tags. At this time, an error occurs between the actual and measured positions. To overcome this problem, a neural network is trained using the measured and actual position data to reduce the error. In this case, since the number of read tags is not constant, they are not suitable as input values for training the neural network, so the neural network is trained by converting them into center-of-gravity inputs and median value inputs. This allows the position error to be reduce by the neural network. In addition, different numbers of trained data are used, viz. 50, 100, 200 and 300, and the correlation between the number of data input values and the error is checked. When the training is performed using the neural network, the errors of the center-of-gravity input and median value input are compared. It was found that the greater the number of trained data, the lower the error, and that the error is lower when the median value input is used than when the center-of-gravity input is used.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.648-651
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• 2001

This paper describes the 8-error-correction (204, 188) Reed-Solomon Decode. over GF(2$^{8}$ ) for a satellite communication. It is synthsized using a CMOS library. Decoding algorithm of Reed-Solomon codes consists of four steps which are to compute syndromes, to find error-location polynomial, to decide error-location, and to slove error-values. The decoder is designed using Modified Euclid algorithm in this paper. First of all, The functionalities of the circuit are verified through C++ programs, and then it is designed in Verilog HDL. It is verified through the logic simulations of each blocks. Finally, The Reed-Solomon Decoder is synthesized with Synopsys Tool.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.30 no.1
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• pp.28-37
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• 2016

Fault locating is an important element to minimize the damage of power system. The computation error of fault locator may occur by the influence of the DC offset component during phasor extraction. In order to minimize the bad effects of DC offset component, this paper presents an improved fault location algorithm based on a DC offset removal filter for short fault in a double circuit transmission line. We have modeled a 154kV double circuit transmission line by the ATP software to demonstrate the effectiveness of the proposed fault locating algorithm. The line to line short faults were simulated and then collected simulation data was used. It can be seen that the error rate of fault locating estimation by the proposed algorithm decreases than the error rate of fault locating estimation by conventional algorithm.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.889-897
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• 2016

This paper presents an improved approach for compensating rotor position signal displacement in brushless DC (BLDC) motors with misaligned hall-effect sensors. Typically, the hall-effect sensors in BLDC motors are located in each phase and positioned exactly 120 electrical degrees apart. However, limitations in mechanical tolerances make it difficult to place hall-effect sensors at the correct location. In this paper, a position error compensator to counteract the hall-effect sensor positioning error is proposed. The proposed position error compensator uses least squares error analysis to adjust the relative position error and back-EMF information to reduce the absolute offset error. The effectiveness of the proposed approach is verified through several experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.647-658
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• 2010

Many localization schemes estimate the locations of radio nodes based on the physical locations of anchors and the connectivity from the anchors. Since they only consider the knowledge of the anchors without else other nodes, they are likely to have enormous error in location estimate unless the range information from the anchors is accurate or there are sufficiently many anchors. In this paper, we propose a novel localization algorithm with the location knowledge of anchors and even one-hop neighbors to localize unknown nodes in the uniform distance from all the one-hop neighbors without the range information. The node in the uniform distance to its all neighbors reduces the location error relative to the neighbors. It further alleviates the location error between its actual and estimated locations. We evaluate our algorithm through extensive simulations under a variety of node densities and anchor placement methods.