• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.74-82
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• 2002

In Intensity Modulated Radiotherapy (IMRT), radiation is delivered in a multiple of Multileaf Collimator (MLC) subfields. A subfield with a small leaf-to-leaf opening is highly sensitive to a leaf-positional error. We introduce a method of identifying and rejecting IMRT plans that are highly sensitive to a systematic MLC gap error (sensitivity to possible random leaf-positional errors is not addressed here). There are two sources of a systematic MLC gap error: Centerline Mechanical Offset (CMO) and, in the case of a rounded end MLC, Radiation Field Offset (RFO). In IMRT planning system, using an incorrect value of RFO introduces a systematic error ΔRFO that results in all leaf-to-leaf gaps that are either too large or too small by (2ㆍΔRFO), whereas assuming that CMO is zero introduces systematic error ΔCMO that results in all gaps that are too large by ΔCMO = CMO. We introduce a concept of the Average Leaf Pair Opening (ALPO) that can be calculated from a dynamic MLC delivery file. We derive an analytic formula for a fractional average fluence error resulting from a systematic gap error of Δ$\chi$ and show that it is inversely proportional to ALPO; explicitly it is equal to, (equation omitted) in which $\varepsilon$ is generally of the order of 1 mm and Δx=2ㆍΔRFO+CMO. This analytic relationship is verified with independent numerical calculations.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.655-657
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• 1999

In this paper we will introduce an posture error reduction algorithm for Mobile Robot. We classified odometry error into two categories. and focus on systematic odometry error correction only. Because it is the primary reason for mobile robot navigation. For this procedure we used some robot specifications and modeled robot behavior. Through some experiment, we could obtain new system specs. After modeling, Robot navigation precision was improved.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.158-164
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• 1994

A volumetric error compensation method was stueide with measuring systematic error of a Coordinate Measuring Machine(CMM). The volumetric error equations were proposed for a Moving Bridge type CMM. Using the error equations, error vectors in the measuring volume were corrected by a software method. The CMM was controlled by the compensation program separately in the measuring and moving function of the CMM proving. The linear accuracy of the CMM was measured by the Laser Interferometer and compared with the data before the volumetric error compensation. This method was proved as low cost and effective to reduce the systematic error of the CMM, as no hardware modification is required.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.6
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• pp.1545-1553
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• 1995

For general geometry of Coordinate Measuring Machine (CMM), volumetric error equation including 21 systematic error components was showed using vector expression. Different types of CMM listed on an international standard (BS 6808) were classified according to their geometry, and the general volumetric error equation was used for the CMMs. Application of volumetric error equation was also introduced, such as position error compensation, error equation of CNC-machine and parametric error analysis, etc.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.233-244
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• 2014

Precise Point Positioning (PPP) is an increasingly recognized precisely the GPS/GNSS positioning technique. In order to improve the accuracy of PPP, the error sources in PPP measurements should be reduced as much as possible and the ambiguities should be correctly resolved. The correct ambiguity resolution requires a careful control of residual errors that are normally categorized into random and systematic errors. To understand effects from two categorized errors on the PPP ambiguity resolution, those two GPS datasets are simulated by generating in locations in South Korea (denoted as SUWN) and Hong Kong (PolyU). Both simulation cases are studied for each dataset; the first case is that all the satellites are affected by systematic and random errors, and the second case is that only a few satellites are affected. In the first case with random errors only, when the magnitude of random errors is increased, L1 ambiguities have a much higher chance to be incorrectly fixed. However, the size of ambiguity error is not exactly proportional to the magnitude of random error. Satellite geometry has more impacts on the L1 ambiguity resolution than the magnitude of random errors. In the first case when all the satellites have both random and systematic errors, the accuracy of fixed ambiguities is considerably affected by the systematic error. A pseudorange systematic error of 5 cm is the much more detrimental to ambiguity resolutions than carrier phase systematic error of 2 mm. In the $2^{nd}$ case when only a portion of satellites have systematic and random errors, the L1 ambiguity resolution in PPP can be still corrected. The number of allowable satellites varies from stations to stations, depending on the geometry of satellites. Through extensive simulation tests under different schemes, this paper sheds light on how the PPP ambiguity resolution (more precisely L1 ambiguity resolution) is affected by the characteristics of the residual errors in PPP observations. The numerical examples recall the PPP data analysts that how accurate the error correction models must achieve in order to get all the ambiguities resolved correctly.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.389-392
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• 1996

We propose a method to improve repeatability positioning precision of a linear pulse motor. By using this method the systematic error which may make the precision worse can be suppressed easily. And also we show that Power OP-Amp drive system enables the accidental error to be suppressed in comparison with PWM control drive system using IGBT inverter. As a result of the suppression of systematic and accidental error, improved performance of a linear pulse motor with repetitive positioning control is shown by experimental results.

• Korean Journal of Optics and Photonics
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• v.13 no.2
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• pp.98-104
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• 2002

We present a new self-calibration method to remove the systematic error of a 2-axis lateral shearing interferometer that has been specially designed for optical testing of aspheric optics. The method takes multiple measurements by rotating the test optics and extracts the systematic error by fitting the measured wavefronts into the Zernike polynomials. The method works with arbitrary azimuthal angles for test optics rotation, which offers an advantage of correcting the error induced by the non-orthogonality of the two axes of wavefront shearing as well as the error caused by the optical components of the interferometer system itself.

• Journal of Navigation and Port Research
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• v.37 no.5
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• pp.447-452
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• 2013

Vessel traffic system uses multiple sea surveillance radars as a primary sensor to obtain maritime traffic information like as ship's position, speed, course. The systematic errors such as the range bias and the azimuth bias of the two-dimensional radar system can significantly degrade the accuracy of the radar image and target tracking information. Therefore, the systematic errors of the radar system should be corrected precisely in order to provide the accurate target information in the vessel traffic system. In this paper, it is proposed that the method compensates the range bias and the azimuth bias using AtoN information installed at VTS coverage. The radar measurement residual error model is derived from the standard error model of two-dimensional radar measurements and the position information of AtoN, and then the linear Kalman filter is designed for estimation of the systematic errors of the radar system. The proposed method is validated via Monte-Carlo runs. Also, the convergence characteristics of the designed filter and the accuracy of the systematic error estimates according to the number of AtoN information are analyzed.

• Korean Journal of Clinical Laboratory Science
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• v.38 no.3
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• pp.184-188
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• 2006

The purpose of the recovery experiment in clinical chemistry is performed to estimate proportional systematic error. We must know all measurements have some error margin in measuring analytical performance. Proportional systematic error is the type of error whose magnitude increases as the concentration of analyte increases. This error is often caused by a substance in the sample matrix that reacts with the sought for analyte and therefore competes with the analytical reagent. Recovery experiments, therefore, are used rather selectively and do not have a high priority when another analytical method is available for comparison purposes. They may still be useful to help understand the nature of any bias revealed in the comparison of kit experiments. Recovery should be expressed as a percentage because the experimental objective is to estimate proportional systematic error, which is a percentage type of error. Good recovery is 100.0%. The difference between 100 and the observed recovery(in percent) is the proportional systematic error. We calculated the amount of analyte added by multiplying the concentration of the analyte added solution by the dilution factor(mL standard)/(mL standard + mL specimen) and took the difference between the sample with addition and the sample with dilution. When making judgments on method performance, the observed that the errors should be compared to the defined allowable error. The average recovery needs to be converted to proportional error(100%/Recovery) and then compared to an analytical quality requirement expressed in percent. The results of recovery experiments were total protein(101.4%), albumin(97.4%), total bilirubin(104%), alkaline phosphatase(89.1%), aspartate aminotransferase(102.8), alanine aminotransferase(103.2), gamma glutamyl transpeptidase(97.6%), creatine kinase(105.4%), lactate dehydrogenase(95.9%), creatinine(103.1%), blood urea nitrogen(102.9%), uric acid(106.4%), total cholesterol(108.5), triglycerides(89.6%), glucose(93%), amylase(109.8), calcium(102.8), inorganic phosphorus(106.3%). We then compared the observed error to the amount of error allowable for the test. There were no items beyond the CLIA criterion for acceptable performance.

• Atmosphere
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• v.26 no.3
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• pp.483-492
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• 2016

We have examined the random error of eddy covariance (EC) measurements on the basis of two-tower approach during daytime. Two EC towers were placed on the grassland with different vegetation density near Gumi-weir. We calculated the random error using three different methods. The first method (M1) is two-tower method suggested by Hollinger and Richardson (2005) where random error is based on differences between simultaneous flux measurements from two towers in very similar environmental conditions. The second one (M2) is suggested by Kessomkiat et al. (2013), which is extended procedure to estimate random error of EC data for two towers in more heterogeneous environmental conditions. They removed systematic flux difference due to the energy balance deficit and evaporative fraction difference between two sites before determining the random error of fluxes using M1 method. Here, we introduce the third method (M3) where we additionally removed systematic flux difference due to available energy difference between two sites. Compared to M1 and M2 methods, application of M3 method results in more symmetric random error distribution. The magnitude of estimated random error is smallest when using M3 method because application of M3 method results in the least systematic flux difference between two sites among three methods. An empirical formula of random error is developed as a function of flux magnitude, wind speed and measurement height for use in single tower sites near Nakdong River. This study suggests that correcting available energy difference between two sites is also required for calculating the random error of EC data from two towers at heterogeneous site where vegetation density is low.