• Journal of the Optical Society of Korea
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• v.3 no.2
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• pp.35-40
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• 1999

One of main error sources in white light scanning interferometry is the inaccuracy of scanning mechanisms in that PZT(piezoelectric transducer) micro-actuators are preferably used. We propose a new calibration method that is capable of identifying actual scanning errors directly by analyzing the spectral distribution of sampled interferograms. This calibration provides an effective means of self-compensation for the non-linearity errors caused by PZT hysteresis, enhancing the measurement uncertainty to a level of 5 nanometers over an entire measuring range of 100 ${\mu}{\textrm}{m}$.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.6
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• pp.145-152
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• 2004

Depth-sensing indentation is wifely used for evaluation of mechanical properties of thin films. It is generally accepted that the most significant source of uncertainty in nanoindentation measurement is the geometry of the indenter tip. Therefore the successful application of the technique requires accurate calibration of the indenter tip geometry. The direct measurement of geometry of a Berkovich indenter was determined using a atomic force microscope. The indentation geometrical calibration of contact area was performed by analyzing the indenter tip profile. The equations of area functions were proposed for nanoscale thin films..

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.48.3-48.3
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• 2019

In the early stages of star formation, a protostar is deeply embedded in an optically thick envelope such that it is not directly observable. Variations in the protostellar accretion rate, however, will cause luminosity changes that are reprocessed by the surrounding envelope and are observable at submillimeter wavelengths. We searched for submillimeter flux variability toward 12 Planck Galactic Cold Clumps detected by the James Clerk Maxwell Telescope (JCMT)-SCUBA-2 Continuum Observations of Pre-protostellar Evolution (SCOPE) survey. These observations were conducted at 850 ㎛ using the JCMT/SCUBA-2. Each field was observed three times over about 14 months between 2016 April and 2017 June. We applied a relative flux calibration and achieved a calibration uncertainty of ~3.6% on average. We identified 136 clumps across 12 fields and detected four sources with flux variations of ~30%. For three of these sources, the variations appear to be primarily due to large-scale contamination, leaving one plausible candidate.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.2
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• pp.122-133
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• 2021

Cultivar parameter calibration can be affected by the reliability of the input data to a crop growth model. In South Korea, two sets of weather stations, which are included in the automated synoptic observing system (ASOS) or the automatic weather system (AWS), are available for preparation of the weather input data. The objectives of this study were to estimate the cultivar parameter using those sets of weather data and to compare the uncertainty of these parameters. The cultivar parameters of CERES-Rice model for Shindongjin cultivar was calibrated using the weather data measured at the weather stations included in either ASO S or AWS. The observation data of crop growth and management at the experiment farms were retrieved from the report of new cultivar development and research published by Rural Development Administration. The weather stations were chosen to be the nearest neighbor to the experiment farms where crop data were collected. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to calibrate the cultivar parameters for 100 times, which resulted in the distribution of parameter values. O n average, the errors of the heading date decreased by one day when the weather input data were obtained from the weather stations included in AWS compared with ASO S. In particular, reduction of the estimation error was observed even when the distance between the experiment farm and the ASOS stations was about 15 km. These results suggest that the use of the AWS stations would improve the reliability and applicability of the crop growth models for decision support as well as parameter calibration.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1933-1938
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• 2003

A covariance matrix is a tool that expresses odometry uncertainty of the wheeled mobile robot. The covariance matrix is a key factor in various localization algorithms such as Kalman filter, topological matching and so on. However it is not easy to acquire an accurate covariance matrix because we do not know the real states of the robot. Up to the authors knowledge, there seems to be no established result on the covariance matrix estimation for the odometry. In this paper, we propose a new method which can estimate the covariance matrix from empirical data. It is based on the PC-method and shows a good estimation ability. The experimental results validate the performance of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.10
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• pp.1012-1017
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• 2007

Rain data and water-level data are importantly used for dam operation at flood period. Because dams are directly controlled by the water-level data, the characteristic of the water-level gauges is necessary to be managed. Thus, we developed the standard test facility and method for testing the water-level gauges which are a float type, a supersonic type and a radar type. And we calculated the uncertainty of the standard test facility to maintain the accuracy of water-level gauges. Through development of this facility, we could obtain the characteristics and the calibration factor of the water-level gauges. And, this study showed that the standard test facility can be widely used for dam operation and basin management.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.10
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• pp.95-101
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• 2000

The purpose of this study is to develop an improved measuring system, which allows for effectively measure spring clamping forces. This system consists of eight or twelve measuring points in order to acquire the clamping force distribution of the whole range of spring clamp. Each measuring point consists of load cells equipped with 4 strain gauges. Using different bearings, we calibrate the roundness of the measuring points. For quality control and database construction, a software system is established. furthermore, uncertainty is calculated to validate the confidence of this system. Various experiments confirm the effectiveness of this measuring system.

• Journal of electromagnetic engineering and science
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• v.18 no.3
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• pp.169-174
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• 2018

In this paper, we propose an estimation method using multiple in-phase and quadrature (IQ) signals of different frequencies to evaluate the sample-time errors in the sampling oscilloscope. The estimator is implemented by ODRPACK, and a novel iteration scheme is applied to achieve fast convergence without any prior information. Monte-Carlo simulation is conducted to confirm the proposed method. It clearly shows that the multiple IQ approach achieves more accurate results compared to the conventional method. Finally, the criteria for the frequency selection and the signal capture time are investigated.

• Proceedings of the KIEE Conference
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• 2002.07c
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• pp.1862-1864
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• 2002

In this study, micro-ohm shunts with rated ac current of 2, 20, 80kA intended for use as an approved system for ac current measurement were calibrated according to IEC 60060. The scale factor and linearity were determined by comparison with the reference measuring system. Measurements of temperature rise due to the rated current was also investigated to analyze a temperature effect. One of the main goals was the determination of the measurement uncertainty of the shunt. The expanded uncertainty of the scale factor for the complete measuring system was satisfied with the STL(Short-circuit Testing Liaison) guide recognized tentatively.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.457-462
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• 2005

An empirical way of a covariance matrix which expresses the odometry uncertainty of mobile robots is proposed. This method utilizes PC-method which removes systematic errors of odometry. Once the systematic errors are removed, the odometry error can be modeled using the Gaussian probability distribution, and the parameters of the distribution can be represented by the covariance matrix. Experimental results show that the method yields $5{\%}$ and $2.3{\%}$ offset for the synchro and differential drive robots.