• Radiation Oncology Journal
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• 제29권2호
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• pp.107-114
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• 2011

Purpose: To assess the degree and clinical impact of location error of the dens on the X-axis during radiotherapy to brain and head and neck tumors. Materials and Methods: Twenty-one patients with brain tumors or head and neck tumors who received three-dimensional conformal radiation therapy or intensity-modulated radiation therapy from January 2009 to June 2010 were included in this study. In comparison two-dimensional verification portal images with initial simulation images, location error of the nasal septum and the dens on the X-axis was measured. The effect of set-up errors of the dens was simulated in the planning system and analyzed with physical dose parameters. Results: A total of 402 portal images were reviewed. The mean location error at the nasal septum was 0.16 mm and at the dens was 0.33 mm (absolute value). Location errors of more than 3 mm were recorded in 43 cases (10.7%) at the nasal septum, compared to 133 cases (33.1%) at the dens. There was no case with a location error more than 5 mm at the nasal septum, compared to 11 cases (2.7%) at the dens. In a dosimetric simulation, a location error more than 5 mm at the dens could induce a reduction in the clinical target volume 1 coverage (V95: 100%${\rightarrow}$87.2%) and overdosing to a critical normal organ (Spinal cord V45: <0.1%${\rightarrow}$12.6%). Conclusion: In both brain and head and neck radiotherapy, a relatively larger set-up error was detected at the dens than the nasal septum when using an electronic portal imaging device. Consideration of the location error of the dens is necessary at the time of the precise radiation beam delivery in two-dimensional verification systems.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.479-483
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• 2006

Indoor positioning is recently highlighted and various kinds of indoor positioning systems are under developments. Since positioning systems have their own characteristics, proper positioning scheme should be chosen according to the required specifications. Positioning methods are often classified into time-based and angle-based one, and this paper presents the error analysis of these location methods. Because measurement equations of these methods are nonlinear, linearization is usually needed to get the position estimate. In this paper, Gauss-Newton method is used in the linearization. To analyze the position error, we investigate the error ellipse parameters that include eccentricity, rotation angle, and the size of ellipse. Simulation results show that the major axes of error ellipses of TOA and AOA method lie in different quadrants at most region of workspace, especially where the geometry is poor. When the TOA/AOA hybrid scheme is employed, it is found that the error ellipse is reduced to the intersection of ellipses of TOA and AOA method.

• Journal of information and communication convergence engineering
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• 제8권2호
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• pp.228-233
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• 2010

In this paper, the iteration localization algorithm that NLOS signal is iteratively removed to get the exact location in the wireless sensor network is proposed. To evaluate the performance of the proposed algorithm, TDOA location estimation method is used, and readers are located on every 150m intervals with rectangular shape in $300m{\times}300m$ searching field. In that searching field, the error distance is analyzed according to increasing the number of iteration, sub-blink and the estimated sensor node locations which are located in the iteration range. From simulation results, the error distance is diminished according to increasing the number of the sub-blink and iteration with the proposed location estimation algorithm in NLOS environment. Therefore, to get more accurate location information in wireless sensor network in NLOS environments, the proposed location estimation algorithm removing NLOS signal effects through iteration scheme is suitable.

• Journal of Institute of Control, Robotics and Systems
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• 제14권8호
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• pp.752-759
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• 2008

In this paper, we propose a high accurate geo-location system based on a single base station, where its location is obtained by Time-of-Arrival(ToA) and Direction-of-Arrival(DoA) of the radio signal. For estimating accurate ToA and DoA information, a MUltiple SIgnal Classification(MUSIC) is adopted. However, the estimation of ToA and DoA using MUSIC algorithm is a time-consuming process. The position tracking bias is occurred by the time delay caused by the estimation process. In order to mitigate the bias error, we propose the estimation method of the position tracking bias and compensate the location error produced by the time delay using the position tracking bias mitigation. For accurate self-localization of mobile robot, the Unscented Kalman Filter(UKF) with position tracking bias is applied. The simulation results show the efficiency and accuracy of the proposed geo-location system and the enhanced performance when the Unscented Kalman Filter is adopted for mobile robot application.

• Journal of Information Technology Applications and Management
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• 제13권3호
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• pp.59-74
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• 2006

According to developing Wireless Communication, not only a location based service at the outside but also a location based service at the inside was more increased socially. This paper proposes the efficient algorithm to locate a transfer object in frequent change of indoor environment using indoor location tracking system we develop ourself. Proposing algorithm in this paper can locate a transfer object using the Fingerprint, one of the Location Tracking techniques which are used in general to minimize error data between Location Tracking System and Fingerprint, using this way that corrects location data as KF apply to result data can improve accuracy of a transfer object. At last we are going to compare and analyze existing typical triangulation with proposed Indoor location tracking system to demonstrate algorithm efficiency for proposed Indoor location tracking system.

• Proceedings of the KIEE Conference
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.10-11
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• 2006

The fault location is obtained from the distance relay that detects the fault of the transmission line. In this time, transmission line crews track down the fault location and the reasons. However, because of having error at the fault location of the distance relay, there is a discordance between real and obtained fault location. As this reason, the inspection time for finding fault location can be longer. In this paper, we proposed the statistical (regression) analysis method based on each type of relay's the historical fault location data and the real fault distance data to improve the problems. With finding the regression equation based on the regression analysis, and putting the relay fault location into that equation, the real fault distance is calculated. As a result of the Prediction fault location, the inspection time of transmission line can be reduced.

• Journal of IKEEE
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• 제20권2호
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• pp.143-151
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• 2016

Smart care surveillance system can take the position information of the user and monitor by controlling neighbor CCTVs using GPS receiver built into smart device. But because the position information contains a significant error, in general smart device, it is necessary to be corrected for precise monitoring. In previous smart care system, this error is corrected by using a plurality of CCTV. But it has disadvantage that two or more CCTVs pointed toward the same point at the same time. In this paper, we propose the method to correct error of the GPS location information by using only one CCTV. With experiment result, we find that the accuracy of GPS location information corrected with only one CCTV is as improved as two CCTVs.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제41권7호
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• pp.715-722
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• 2016

In this paper, by applying the linear least squared error algorithm, we derive an estimation technique for three dimensional target location when a number of radars are used in detecting a target. The proposed technique is then enhanced by combining GPS information and by assigning variable weights to information sources. The enhanced performance of proposed techniques is confirmed via simulation. It is also observed from simulation results that the performance is robust to the uncertainty of information.

• The Transactions of the Korean Institute of Electrical Engineers A
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• 제51권8호
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• pp.371-378
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• 2002

This paper presents the rapid and accurate algorithm for fault detection and location estimation in the transmission line. This algorithm uses wavelet transform for fault detection and harmonics elimination and utilizes least square error method for fault impedance estimation. Wavelet transform decomposes fault signals into high frequence component Dl and low frequence component A3. The former is used for fault phase detection and fault types classification and the latter is used for harmonics elimination. After fault detection, an adaptive data window technique using LSE estimates fault impedance. It can find a optimal data window length and estimate fault impedance rapidly, because it changes the length according to the fault disturbance. To prove the performance of the algorithm, the authors test relaying signals obtained from EMTP simulation. Test results show that the proposed algorithm estimates fault location within a half cycle after fault irrelevant to fault types and various fault conditions.

• Journal of KIBIM
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• 제10권2호
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• pp.21-28
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• 2020

As the number of aging bridges increases, more studies are being conducted on developing effective and reliable methods for the assessment and maintenance of bridges. With the advancement in new sensing systems and data learning techniques through AI technology, there is growing interests in how to evaluate bridges using these advanced techniques. This paper presents a CNN(Convolution Neural Network) deep learning based technique for evaluating the damage existence and for estimating the damage location in PSC bridges using static strain data. Simulation studies were conducted to investigate the proposed method with error analysis. Damage was simulated as the reduction in the stiffness of a finite element. A data learning model was constructed by applying the CNN technique as a type of deep learning. The damage status and its location were estimated using data set built through simulation. It was assumed that the strain gauges were installed in a regular interval under the PSC bridge girders. In order to increase the accuracy in evaluating damage, the squared error between the intact and measured strains are computed and applied for training the data model. Considering the damage occurring near the supports, the results of error analysis were compared according to whether strain data near the supports were included.