• The KSFM Journal of Fluid Machinery
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• v.17 no.4
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• pp.5-10
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• 2014

It is possible for the nation's largest flowmeter calibration system in K-water to calibrate flow rate up to $2,700m^3/h$ and diameter 800mm. However, the calibration and measurement capability of K-water's system is not satisfied in comparison with other developed countries. In this study, we find the dominant factors related to the uncertainty of weight and time measurement for gravimetric flowmeter calibration system. As a results of improving the system, the combined standard uncertainty has been improved $1.099{\times}10^{-3}$ to $2.332{\times}10^{-4}$. So calibration and measurement capability got 0.08 percent of the relative expanded uncertainty for maximum flow rate using the coverage factor(k=2).

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.861-874
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• 2012

To fulfill applicability of Soil and Water Assessment Tool (SWAT) model, it is important that this model passes through a careful calibration and uncertainty analysis. In recent years, many researchers have come up with various uncertainty analysis techniques for SWAT model. To determine the differences and similarities of typical techniques, we applied three uncertainty analysis procedures to Chungju Dam watershed (6,581.1 $km^2$) of South Korea included in SWAT-Calibration Uncertainty Program (SWAT-CUP): Sequential Uncertainty FItting algorithm ver.2 (SUFI2), Generalized Likelihood Uncertainty Estimation (GLUE), Parameter Solution (ParaSol). As a result, there was no significant difference in the objective function values between SUFI2 and GLUE algorithms. However, ParaSol algorithm shows the worst objective functions, and considerable divergence was also showed in 95PPU bands with each other. The p-factor and r-factor appeared from 0.02 to 0.79 and 0.03 to 0.52 differences in streamflow respectively. In general, the ParaSol algorithm showed the lowest p-factor and r-factor, SUFI2 algorithm was the highest in the p-factor and r-factor. Therefore, in the SWAT model calibration and uncertainty analysis of the automatic methods, we suggest the calibration methods considering p-factor and r-factor. The p-factor means the percentage of observations covered by 95PPU (95 Percent Prediction Uncertainty) band, and r-factor is the average thickness of the 95PPU band.

• Structural Engineering and Mechanics
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• v.49 no.2
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• pp.163-182
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• 2014

Safety factors proposed in codes CEB, B.A.E.L 91 and EUROCODE 1 cover a great number of uncertainties; making them inadequate for the assessment of existing structures. Suitable safety factors are established using a probabilistic assessment, once real dimensions, materials strength and existing structures deterioration mechanisms are taken into account. This paper presents a calibration method for safety factors using a typical set of RC bridges in France. It considers the principal stages of corrosion provoked by $CO_2$ and $Cl^-$ penetration and threshold indexes (${\beta}_0$) for existing structures. Reliability indexes are determined by the FORM method in the calibration method.

• Journal of Industrial Technology
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• v.25 no.B
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• pp.157-164
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• 2005

Two methods, the bin averaging method and least square method, are often used in calibrating wind turbine test sites. The objective of this work was to determine a better method to predict the wind speed at wind turbine installing point. The calibration was done at the test site on a complex terrain located in Daegwallyeong, Korea. It was performed for two different cases based on the IEC 61400-12 power performance measurement standard. The wind speeds averaged for 10 minutes ranged between 4 m/s and 16 m/s. The wind-direction bins of each meteorological mast were 10 degrees apart, and only the bins having data measured for more than 24 hours were employed for the test site calibration. For both cases, the two methods were found to yield almost same results which estimated real wind speed very closely.

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.483-488
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• 2003

Calibration and gauge factor readjustment process made for the health monitoring system installed in the railway bridges is reviewed and some findings are explained in this study: specifically, the calibrators made for this purpose are illustrated and the regression processes of the calibration on long-term displacement using water level sensor, longitudinal displacement using LVDT sensor, instantaneous displacement using LVDT sensors and accelerometer are described in details. Based on the regression results, new gauge factors are obtained from regression equation and another verification is made by performing another calibration again with new factors. From the second calibration, it was found that the suggested regression curves and their factors are appropriate and much better results are expected. Future work will be concentrated on the long-term analysis of the measurement data and on the database structures so that the assessment of the structure such as damage detection and remaining life estimation is possible.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.5
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• pp.827-835
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• 2022

Clothing pressure is considered the essential factor affecting the comfort of clothing, so it is crucial that it is measured precisely. The purpose of this study is to construct a prototype using the Adafruit Flora as the Arduino system, which can be used as a wearable framework for easy, low-cost, and precise clothing pressure measurement. The study also aims to determine how best to conduct the procedure of sensor calibration. To optimize the accuracy of the sensors, the calibration procedure was implemented using mathematical methods that combined polynomial and exponential regression in a hybrid approach. The prototype can easily measure clothing pressure even during active movements, as seen in the detection of stable signals. In addition, since the system was specifically proposed as a wearable patch that can be easily attached and removed as necessary, it can also be used to standardize the value of clothing pressure in each movement.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.163-172
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• 2010

In this paper, we deal with the problem for testing homogeneity of coecients of variation in several normal distributions. We propose Bayesian hypothesis testing procedures based on the Bayes factor under noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be dened up to a multiplicative constant. So we propose the objective Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Simulation study and a real data example are provided.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.643-646
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• 2006

An operational calibration is applied to improve radar rainfall intensity using rainfall obtained from rain gauge. The method is applied under the assumption of the temporal continuity of rainfall, the rainfall intensity from rain gauge is linearly related to that from radar. The method is applied to the cases of typhoon and rain band using the reflectivity of CAPPI at 1.5km obtained from Jindo radar. The CAPPI is obtained by bilinear interpolation. For the two cases, the rainfall intensities obtained by operational calibration are very consistent with the ones by the rain gauges. The present study shows that the correlation between the rainfall intensity by operational calibration and rain gauges is better than the one between the rainfall intensity by M-P relationship and rain gauges. The correlation coefficients between the total rainfall intensity obtained by operational calibration and rain gauges in typhoon and rain band cases are 0.99 and 0.97, respectively. Areal rainfalls are estimated using the field of calibration factor interpolated by Barnes objective analysis. The method applied here shows an improvement in the areal rainfall estimation. For the cases of typhoon and rain band, the correlation between the areal rainfall by operational calibration and rain gauges is better than the one between the area rainfall by M-P relationship and rain gauges. The correlation coefficients between the areal rainfall obtained by operational calibration and rain gauges in typhoon and rain band cases are 0.97 and 0.84, respectively. The present study suggests that the operational calibration is very useful for the real-time estimation of rainfall intensity and areal rainfall.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.1
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• pp.11-20
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• 2018

This study is to calibrate the SWAT (Soil and Water Assessment Tool) water quality of SS (Suspended Solid), T-P (Total Phosphorus), and T-N (Total Nitrogen) by focusing on 2014~2015 drought periods and identify the important parameters. For Gongdo watershed ($366.5km^2$), the SWAT was calibrated for 2 cases of 2002~2006 normal year focusing calibration and 2014~2015 drought focusing calibration respectively. The parameters of N_UPDIS (Nitrogen uptake distribution parameter) and CMN (Rate factor for humus mineralization of active organic nutrients) played important roles for T-N calibration during drought periods. The SWAT SS, T-N, and T-P average $R^2$ (Coefficient of determination) results by focusing on 2014~2015 drought periods calibration showed 0.71, 0.65 and 0.62 while 2002~2006 normal year focusing calibration showed 0.63, 0.58 and 0.50 respectively. Also SWAT SS, T-N, and T-P model efficiency NSE (Nash-Sutcliffe efficiency) results by focusing on drought period (2014~2015) calibrated showed 0.76, 0.77, 0.87 respectively. Even though the SS, T-P parameters were unchanged during the calibration, the SS and T-P results were improved by the hydrological parameters (SCS-CN, SOL_K, SLSOIL) during the drought periods. The SWAT water quality calibration needs to be considered for the movement of SS and nutrients transport especially focusing on the drought characteristics.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.123-137
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• 2021

In this study, we performed cross calibration of KOMPSAT-3 AEISS imaging sensor with reference to normalized pixels in the Landsat 8 OLI scenes of homogenous ROI recorded by both sensors between January 2014 and December 2019 at the Libya 4 PICS. Cross calibration is using images from a stable and well-calibrated satellite sensor as references to harmonize measurements from other sensors and/or characterize other sensors. But cross calibration has two problems; RSR and temporal difference. The RSR of KOMPSAT-3 and Landsat 8 are similar at the blue and green bands. But the red and NIR bands have a large difference. So we calculate SBAF of each sensor. We compared the SBAF estimated from the TOA Radiance simulation with KOMPSAT-3 and Landsat 8, the results displayed a difference of about 2.07~2.92% and 0.96~1.21% in the VIS and NIR bands. Before SBAF, Reflectance and Radiance difference was 0.42~23.23%. Case of difference temporal, we simulated by 6S and Landsat 8 for alignment the same acquisition time. The SBAF-corrected cross calibration coefficients using KOMPSAT-3, 6S and simulated Landsat 8 compared to the initial cross calibration without correction demonstrated a percentage difference in the spectral bands of about 0.866~1.192%. KOMPSAT-3 maximum uncertainty was estimated at 3.26~3.89%; errors due to atmospheric condition minimized to less than 1% (via 6S); Maximum deviation of KOMPSAT-3 DN was less than 1%. As the result, the results affirm that SBAF and 6s simulation enhanced cross-calibration accuracy.