• Bulletin of the Korean Space Science Society
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• 1995.04a
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• pp.39-39
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• 1995

No Abstract. See Full-text

• Journal of Power System Engineering
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• v.22 no.1
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• pp.18-24
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• 2018

This paper focuses on systematic design about the membership ranges of the main design factors such as control error, control error rate, and sampling time for the fuzzy logic control of the variable speed drive refrigeration cycle. The upper and the lowest limit of the membership ranges are set up from the data of static characteristics obtained by experiments. Three kinds of membership ranges on the control error and the control error rate are tested by experiments. Especially, an effect of sampling time on control performance is also investigated in the same way. Experimental data showed the control error rate and the sampling time strongly effected on the control performance of the refrigeration cycle with a variable speed drive.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1817-1827
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• 2009

Although human error is recognized as the primary cause of railway accidents and incidents, there have been limitations in finding the root causes of errors and developing effective corrective actions in the Korean railway industry, due to the absence of a systematic method and lack of professional knowledge and skills of investigators. Therefore, there has been a strong need for a systematic methodology for human error analysis. This paper introduces a methodology for analyzing human error m railway operations, called HEAR (Human Error Analysis and Reduction). HEAR is intended to help analysts identify the sequences and various levels of causes of operators' erroneous actions in railway accidents or incidents and make recommendations to eliminate or reduce the future possibility of similar errors and accidents. It was developed based on a thorough investigation of various techniques for human errors analysis and feedback from field investigators.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.258-258
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• 2018

In this study, a hydraulic flow model and an error correction model are combined to improve the flood simulation accuracy. First, the hydraulic flow model is calibrated by optimizing the Manning's roughness coefficient that considers spatial and temporal variability. Then, an error correction model were used to correct the systematic errors of the calibrated hydraulic model. The error correction model is developed using Artificial Neural Networks (ANNs) that can estimate the systematic simulation errors of the hydraulic model by considering some state variables as inputs. The input variables are selected using parital mutual information (PMI) technique. It was found that the calibrated hydraulic model can simulate flood water levels with good accuracy. Then, the accuracy of estimated flood levels is improved further by using the error correction model. The method proposed in this study can be used to the flood control and water resources management as it can provide accurate water level eatimation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.5
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• pp.335-341
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• 2013

The variation of systematic bias errors in the wind tunnel testing has been studied. A Design of Experiments(DOE) approach to an experimental study of fuselage drag and stability characteristics of a helicopter configuration was applied. When forces and moments measured in one time block differ significantly from measurements made in another time block under assumption that sample observations can be expected to yield same results within permissible measuring errors. The practical implication of this paper is that the systematic error can not be assumed not to exist. The those error reduction could be achieved through the process of randomization, blocking, and replication of the data points.

• Journal of the Korean Solar Energy Society
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• v.38 no.6
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• pp.65-72
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• 2018

Since data-driven building technologies have been widely applied to building energy systems, the accuracy of building sensors has more impacts on the building performance and system performance analysis. Various building sensors, however, can have typical errors including a random error (noise) and a systematic error (bias). The systematic error is indicated by the difference between the mean of measurements and their true value. It may occur due to the sensor's physical condition, measured phenomena, working environments inside the systems. Unfortunately, a conventional calibration method has limitations in calibrating the systematic errors because of the difference between working environments and calibration conditions. In such situations, a novel sensor calibration method is needed to handle various sensor errors, especially for systematic errors, in building energy systems having various thermodynamic environments. This study proposes a building sensor calibration method named Virtual In-situ Calibration (VIC) and shows how it is applied into a real building system and how it solves the sensor errors.

• Atmosphere
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• v.19 no.2
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• pp.213-226
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• 2009

In order to investigate the characteristics of Changma over the Korean peninsula, KEOP-2007 IOP (Intensive Observing Period) was conducted from 15 June 2007 to 15 July 2007. KEOP-2007 IOP is high spatial and temporal radiosonde observations (RAOB) which consisted of three special stations (Munsan, Haenam, and Ieodo) from National Institute of Meteorological Research, five operational stations (Sokcho, Baengnyeongdo, Pohang, Heuksando, and Gosan) from Korea Meteorological Administration (KMA), and two operational stations (Osan and Gwangju) from Korean Air Force (KAF) using four different types of radiosonde sensors. The error statistics of the sensor of radiosonde were investigated using quality control check. The minimum and maximum error frequency appears at the sensor of RS92-SGP and RS1524L respectively. The error frequency of DFM-06 tends to increase below 200 hPa but RS80-15L and RS1524L show vice versa. Especially, the error frequency of RS1524L tends to increase rapidly over 200 hPa. Systematic biases of radiosonde show warm biases in case of temperature and dry biases in case of relative humidity compared with ECMWF (European Center for Medium-Range Weather Forecast) analysis data and precipitable water vapor from GPS. The maximum and minimum values of systematic bias appear at the sensor of DFM-06 and RS92-SGP in case of temperature and RS80-15L and DFM-06 in case of relative humidity. The systematic warm and dry biases at all sensors tend to increase during daytime than nighttime because air temperature around sensor increases from the solar heating during daytime. Systematic biases of radiosonde are affected by the sensor type and the height of the sun but random errors are more correlated with the moisture conditions at each observation station.

• Korean Journal of Optics and Photonics
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• v.25 no.1
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• pp.29-37
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• 2014

We have studied and demonstrated general, systematic error-correction methods for a dual rotating quarter-wave plate ellipsometer. To estimate and correct 5 systematic error sources (three offset angles and two unexpected retarder phase delays), we used 11 of the 25 Fourier components of the ellipsometry signal obtained in the absence of an optical sample. Using these 11 Fourier components, we can determine the errors from the 5 sources with nonlinear optimization methods. We found systematic errors ${\epsilon}_3$, ${\epsilon}_4$, ${\epsilon}_5$) are more sensitive to the inverted Mueller matrix than retarder phase delay errors (${\epsilon}_1$, ${\epsilon}_2$) because of their small condition numbers. To correct these systematic errors we have found that error of any variety must be less than 0.05 rad. Finally, we can use the magnitudes of these errors to correct the Mueller matrix of optical components. From our experimental ellipsometry signals, we can measure phase delay and the rotational angular position of its fast axis for a half-wave plate.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.306-313
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• 1999

To measure the accurate position of mobile robot, dead-reckoning method using the encoder attached to each wheel is conventionally used, since it is easy to compute and inexpensive to develop. However, that method is useless when slip occurs and error is accumulated with time. This paper proposes a position estimation method using encoder trailer composed of 2 encoders only(ET-2). This method provides accurate position information even when slip occurs, and can reduce accumulated error if we select the proper link lengths of encoder trailer. Experimental results show the performance of ET-2 when slip occurs. Finally, accumulated systematic error from encoder resolution is analyzed in comparison with an existing method with encoder trailer composed of 3 encoders. (As a matter of convenience, we will call the existing encoder trailer ‘ET-3’)

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.1033-1041
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• 2013

In this paper, we investigate several variance estimators for pps systematic sampling. Unfortunately, there is no unbiased variance estimators for a systematic sample because systematic sampling can be regarded as a random selection of one cluster. This study provides guidance on which variance estimator may be more appropriate than others in several circumstances. We judge the efficiency of variance estimators for systematic sampling based on of their relative biases and relative mean square error. Also, we investigate variance estimation problems for two-stage systematic sampling applied for the Food Raw Material Consumption Survey and the Establishment Labor Force Survey simulation study, in order to consider the popular two-stage pps systematic sample design for establishment and household survey in Korea.