• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2003.12a
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• pp.31-34
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• 2003

We developed a new systematic calibration procedure which was applied to the calibration of the diffusivity, segregation and TED model of the indium impurity. The TED of the indium impurity has been studied using 4 different groups of experimental conditions. Although the indium is susceptible to the TED, the RTA is effective to suppress the TED effect and maintain a steep retrograde profile. Like the boron, the indium shows significant oxidation-enhanced diffusion in silicon and has segregation coefficients at the $Si/SiO_2$ interface much less than 1. In contrast, however, the segregation coefficient of indium decreases as the temperature increases. The accuracy of the proposed technique is validated by SIMS data with errors less than 5% between simulation and experiment.

• International Journal of Highway Engineering
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• v.17 no.1
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• pp.51-58
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• 2015

PURPOSES : The objective of this study is to compare the densities of asphalt pavements measured both in the field and in the laboratory, and also to evaluate the applicability of field density measuring equipment, such as the pavement quality indicator (PQI), by using statistical analysis. METHODS : For the statistical analysis of the density measured from asphalt pavement, student t-tests and a coefficient of correlation are investigated. In order to compare the measured densities, two test sections are prepared, with a base layer and an intermediate layer constructed. Each test section consists of 9 smaller sections. During construction, the field densities are measured for both layers (base and intermediate) in each section. Core samples are extracted from similar regions in each section, and moved to the laboratory for density measurements. All the measured densities from both the field and laboratory observations are analyzed using the selected statistical analysis methods. RESULTS AND CONCLUSION : Based on an analysis of measured densities, analysis using a correlation coefficient is found to be more accurate than analysis using a student t-test. The correlation coefficient (R) between the field density and the core density is found to be very low with a confidence interval less than 0.5. This may be the result of inappropriate calibration of the measuring equipment. Additionally, the correlation coefficient for the base layer is higher than for the intermediate layer. Finally, we observe that prior to using the density measuring equipment in the field, a calibration process should be performed to ensure the reliability of measured field densities.

• Journal of the Korean Society of Radiology
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• v.11 no.1
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• pp.37-42
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• 2017

We measured the absorbed dose and the area dose using an ionization chamber type of area dose product (DAP) meter and measured the calibration factor in the X-ray examination. In the indirect dose measurement method, the detector was installed in the radiation part of the X-ray equipment, and the measured value was calculated as the dose at the exposure part. The instrument used to calculate the calibration factor was an X-ray equipment (DK-550R / F, DongKang Medical Co., Ltd., Seoul, Korea). The calibration method for the calibration factor was to connect the DAP meter (PD-8100, Toreck Co. Ltd., Japan) to the calibration dosimeter tube voltage of 70 kV, tube current of 500 mA, 0.158 sec. The reference dosimeter used a semiconductor (DOSIMAX plus A, Scanditronix, $Wellh{\ddot{o}}fer$, Germany). After installing the DAP meter on the front of the multi-collimator of the ionization chamber, the calibration factor of the dosimeter was obtained using the reference dosimeter for accurate dose measurement. Experimental exposure values and values from the calibration dosimeter were calculated by multiplying each calibration factor. The calibration factor was calculated as 1.045. In order to calculate the calibration coefficient according to the tube voltage in the ionization type DAP dosimeter, the absorbed dose and the area dose were calculated and the calibration factor was calculated. The corrective area dose was calculated by calculating the calibration factor of the DAP meter.

• Animal Bioscience
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• v.37 no.7
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• pp.1196-1203
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• 2024

Objective: A study was conducted to quantify the performance differences of the near-infrared spectroscopy (NIRS) calibration models developed with different degrees of hay sample preparations. Methods: A total of 227 imported alfalfa (Medicago sativa L.) and another 360 imported timothy (Phleum pratense L.) hay samples were used to develop calibration models for nutrient value parameters such as moisture, neutral detergent fiber, acid detergent fiber, crude protein, and in vitro dry matter digestibility. Spectral data of hay samples prepared by milling into 1-mm particle size or unground were separately regressed against the wet chemistry results of the abovementioned parameters. Results: The performance of the developed NIRS calibration models was evaluated based on R², standard error, and ratio percentage deviation (RPD). The models developed with ground hay were more robust and accurate than those with unground hay based on calibration model performance indexes such as R² (coefficient of determination), standard error, and RPD. Although the R² of calibration models was mainly greater than 0.90 across the feed value indexes, the R² of cross-validations was much lower. The R² of cross-validation varies depending on feed value indexes, which ranged from 0.61 to 0.81 in alfalfa, and from 0.62 to 0.95 in timothy. Estimation of feed values in imported hay can be achievable by the calibrated NIRS. However, the NIRS calibration models must be improved by including a broader range of imported hay samples in the modeling. Conclusion: Although the analysis accuracy of NIRS was substantially higher when calibration models were developed with ground samples, less sample preparation will be more advantageous for achieving rapid delivery of hay sample analysis results. Therefore, further research warrants investigating the level of sample preparations compromising analysis accuracy by NIRS.

• Water Engineering Research
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• v.4 no.3
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• pp.141-154
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• 2003

Nonpoint source pollutants from agriculture are identified as one of the main causes of water quality degradation in the United States. The Hydrological Simulation Program-Fortran (HSPF) was used to simulate runoff, nitrogen, and sediment loads from an urbanizing watershed; the Polecat Creek watershed located in Virginia. Model parameters related to hydrology and water quality were calibrated and validated using observed hydrologic and water quality data collected at the watershed outlet and at several sub-watershed outlets. A comparison of measured and simulated monthly runoff at the outlet of the watershed resulted in a correlation coefficient of 0.94 for the calibration period and 0.74 for the validation period. The annual observed and simulated sediment loads for the calibration period were 220.9 kg/ha and 201.5 kg/ha, respectively. The differences for annual nitrate nitrogen ($NO_3$) loads between the observed and simulated values at the outlet of the watershed were 5.1% and 42.1% for the calibration and validation periods, respectively. The corresponding values for total Kjeldahl nitrogen (TKN) were 60.9% and 40.7%, respectively. Based on the simulation results, the calibrated HSPF input parameters were considered to adequately represent the Polecat Creek watershed.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.1
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• pp.1-9
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• 2009

The objective of this paper was to evaluate the auto-calibration with multi-objective optimization method to calibrate the parameters of the Soil and Water Assessment Tool (SWAT) model. The model was calibrated and validated by using nine years (1996-2004) of measured data for the 384-ha Baran reservoir subwatershed located in central Korea. Multi-objective optimization was performed for sixteen parameters related to runoff. The parameters were modified by the replacement or addition of an absolute change. The root mean square error (RMSE), relative mean absolute error (RMAE), Nash-Sutcliffe efficiency index (EI), determination coefficient ($R^2$) were used to evaluate the results of calibration and validation. The statistics of RMSE, RMAE, EI, and $R^2$ were 4.66 mm/day, 0.53 mm/day 0.86, and 0.89 for the calibration period and 3.98 mm/day, 0.51 mm/day, 0.83, and 0.84 for the validation period respectively. The statistical parameters indicated that the model provided a reasonable estimation of the runoff at the study watershed. This result was illustrated with a multi-objective optimization for the flow at an observation site within the Baran reservoir watershed.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.657-664
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• 1999

This paper introduced the basic theory of LRCS(Linear Reservoir and Channel System) rainfall runoff model proposed by Korean researchers(Lee and Lee, 1995), and discussed the change of model output according to objective functions in sensitivity analysis and calibration process of model. It proposed "hat" matrix and affluence measures for affluence analysis of parameters in calibration, and investigated relationship between change of model output according to error propagation in parameter estimation, and sensitivity of model output according to variance of model output and change of parameters. Accuracy of parameter estimates was known by analysis of sensitivity coefficient, diagonal element $h_i$ and $D_i$._i$.

• Journal of the Korean Society of Tobacco Science
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• v.20 no.2
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• pp.183-190
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• 1998

This study was conducted to analyze chemical components in flue-cured tobacco using near infrared spectroscopy(NIRS). Samples were collected in '96 and '97 crop year and were scanned in the wavelengths of 400 ～ 2500 nm by near infrared analyzer(NIRSystem Co., Model 6500). Calibration equations were developed and then analyzed flue-cured samples by NIRS. The standard error of calibration(SEC) and performance (SEP) of '96 crop year samples between NIRS and standard laboratory analysis(SLA) were 0.18% and 0.24% for nicotine, 1.60% and 1.77% for total sugar, 0.13% and 0.15% for total nitrogen, 0.58% and 0.68% for crude ash, 0.23% and 0.28% for ether extracts, and 0.09% and 0.08% for chlorine, respectively. The coefficient of determination($R^2$) of calibration and prediction samples between NIRS and SLA of '96 crop year samples was 0.94～0.99 and 0.83～0.97 depending on chemical components, respectively. The SEC and SEP of '97 crop year samples were similar to those of '96 crop year samples. The SEP of '97 crop year samples which were analyzed using '96 calibration equation was 0.32 % for nicotine, 2.72% for total sugar, 0.14 % for total nitrogen, 1.00 % for crude ash, 0.48 for ether extracts and 0.17% for chlorine, respectively. The prediction result was more accurate when calibration and prediction samples were produced in the same crop year than those of the different crop year. The SEP of '96 and '97 crop year samples using calibration equation which was developed '96 plus '97 crop year samples was similar to that of '96 crop year samples using 96 calibration equation and that of '97 crop year samples using '97 calibration equation, respectively. The SEP of '97 crop year samples using calibration equation which was developed '96 plus '97 crop year samples was lower than that of '97 crop year samples analyzed by '96 calibration equation. To improve the analytical inaccuracy caused by the difference of crop year between calibration and prediction samples, we need to include the prediction sample spectra which are different from calibration sample spectra in recalibration sample spectra, and then develop recalibration equation. Although the analytical result using NIR is not as good as SLA, the chemical component analysis using NIR can apply to tobacco leaves, leaf process or tobacco manufacturing process which demand the rapid analytical result.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.468-473
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• 1999

This study was carried out to assess the use of RADARSAT data which is C-band with HH polarization for the rice growth monitoring in Korea. Nine time-series data were taken by shallow incidence angle (standard beam mode 5 or 6) during rice growing season. And then, backscatter coefficient ($\sigma$$^{\circ}$) were extracted by calibration process for comparing with rice growth parameters such as plant height leaf area index(LAI), and fresh and dry biomass. Field experimental data concerned with rice growth were collected 8 times for the ground truth at the study area, Tangjin, Chungnam, Korea. At the maximum vegetative stage of rice, backscatter coefficients were the highest at the flooded rice field ranging from -4.4dB~-3.1dB. The temporal variation of backscatter coefficient($\sigma$$^{\circ}$) in rice field was significant in this study Backscatter coefficient ($\sigma$$^{\circ}$) of rice field was a little bit lower again after heading stage. This results show RADARSTA data is promising for rice monitoring.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.1007-1016
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• 2011

This article deals with the problem of testing for the correlation coefficient in the bivariate normal distribution. We propose Bayesian hypothesis testing procedures for the bivariate normal correlation coefficient under the noninformative prior. The noninformative priors are usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. A simulation study and an example are provided.