• 한국국방경영분석학회지
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• 제36권1호
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• pp.29-38
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• 2010

In Korea weapon system acquisition processes, it's required a cost estimation report obtained from a commercial cost model. The PRICE model is generally used as a cost estimation model in Korea. However, the model uses American historical R&D data and it's output cost component is different from our cost component of defense accounting system. Also, we found that estimating results show about 10% of difference when we comparing with actual costs in 44 finished weapon acquisition projects. There are some limitations in calibration to increase an accuracy of the PRICE model because it's difficult obtain good real input data, detailed cost and technical data in low level WBS. So, only 8% of the defense R&D projects are calibrated and validation of calibration results is more difficult. Therefore, we studied the standard calibration process and performed the calibration about the MCPLXS/E parameters of the PRICE model based on actual cost data. In order to obtain a good calculation result, we collected the actual material costs from the defense industry companies. Our results can be used for an reference in similar weapon system R&D and production cost estimation cases.

• 한국수자원학회논문집
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• 제39권10호
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• pp.867-880
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• 2006

많은 수의 매개변수와 복잡한 구조를 가진 수문모형의 적용 시 세밀하고 강력한 모델 검 보정이 요구된다. 본 연구에서 금강유역에 위치한 갑천 소유역에 준 분포형 모형인 SWAT모형을 이용하여 다 목적 지점 검 보정 방법을 제시하였다. 모형의 보정 전 민감도 분석을 통한 각 소유역별로 특성 분석이 이루어 졌고, 유출에 민감한 매개변수들을 추정하였다. 그리고 최소한의 보정을 통한 모형의 유효성을 높이기 위해, 관측된 데이터로부터 매개변수 값을 선보정하는 과정을 거쳤다. 그 결과 각 소유역 별로 다른 매개변수들의 민감도가 나타났다. 관측유량에 대한 보정 단계에서 $R_{eff}$는 0.41-0.84, $R^2$은 0.5-0.86 값으로 신뢰성 있는 결과를 얻었다. Recursive digital filter로 추정된 기저 유출량을 약 2% 범위에서 산정하였다. 관측 지하수 수위와의 비교에서도 전체적으로 관측된 지하수 수위의 시간적 변동추이와 변동 폭을 잘 나타내었으며, $R^2$는 0.69로 만족스러운 결과를 보였다. 결론적으로, 다 목적 지점 방법의 사용은 모형기 구조와 추정된 매개변수들에 높은 신뢰도를 제공하였다.

• 한국물환경학회지
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• 제34권3호
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• pp.328-338
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• 2018

The objective of this study was to evaluate the applicability of a HSPF (Hydrological Simulation Program-Fortran) model for runoff estimation in the Namgang dam watershed. Spatial data, such as watershed, stream, land use, and a digital elevation map, were used as input for the HSPF model, which was calibrated and validated using observed runoff data from 2004 to 2015 for three stations (Sancheong, Shinan, Changchon) in the study watershed. Parameters for runoff calibration were selected based on the user's manual and references, and parameter calibration was done by trial and error. The $R^2$ (determination coefficient), RMSE (root-mean-square error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (relative mean absolute error) were used to evaluate the model's performance. Calibration and validation results showed that annual mean runoff was within a ${\pm}5%$ error in Sancheong and Shinan, whereas there was a14% error in Changchon. The model performance criteria for calibration and validation showed that $R^2$ ranged from 0.80 to 0.92, RMSE was 2.33 to 2.39 mm/day, NSE was 0.71 to 0.85, and RMAE was 0.37 to 0.57 mm/day for daily runoff. Visual inspection showed that the simulated daily flow, monthly flow, and flow exceedance graph agreed well with observations for the Sancheong and Shinan stations, whereas the simulated flow was higher than observed at the Changchon station.

• Nuclear Engineering and Technology
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• 제42권2호
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• pp.219-230
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• 2010

In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component-based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method.

• 한국농공학회논문집
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• 제55권1호
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• pp.17-29
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• 2013

Long-Term Hydrologic Impact Assessment (L-THIA) model which is a distributed watershed model was applied to analyze the spatial distribution of surface runoff and nonpoint source pollutant loading from Imha watershed during 2001~2010. L-THIA CN Calibration Tool linked with SCE-UA was developed to calibrate surface runoff automatically. Calibration (2001~2005) and validation (2006~2010) of monthly surface runoff were represented as 'very good' model performance showing 0.91 for calibration and 0.89 for validation as Nash-Sutcliffe (NS) values. Average annual surface runoff from Imha watershed was 218.4 mm and Banbyun subwatershed was much more than other watersheds due to poor hydrologic condition. Average annual nonpoint source pollutant loading from Imha wateshed were 2,295 ton/year for $BOD_5$, 14,752 ton/year for SS, 358 ton/year for T-N, and 79 ton/year for T-P. Amount of pollutant loading and pollutant loading rates from Banbyun watershed were much higher than other watersheds. As results of analysis of loading rate from grid size ($30m{\times}30m$), most of high 10 % of loading rate were generated from upland. Therefore, major hot spot area to manage nonpoint source pollution in Imha watershed is the combination of upland and Banbyun subwatershed. L-THIA model is easy to use and prepare input file and useful tool to manage nonpoint source pollution at screening level.

• 한국작물학회지
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• 제56권1호
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• pp.88-93
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• 2011

This experiment was carried out to find suitable sample type for the more accurate prediction and non-destructive way in the application of near infrared reflectance spectroscopy (NIRS) technique for estimation the protein, total amino acids, and total isoflavone of soybean by comparing three different sample types, single seed, whole seeds, and milled seeds powder. The coefficient of determination in calibration ($R^2$) and coefficient of determination in cross-validation (1-VR) for three components analyzed using NIRS revealed that milled powder sample type yielded the highest, followed by single seed, and the whole seeds as the lowest. The coefficient of determination in calibration for single seed was moderately low($R^2$ 0.70-0.84), while the calibration equation developed with NIRS data scanned with whole seeds showed the lowest accuracy and reliability compared with other sample groups. The scatter plot for NIRS data versus the reference data of whole seeds showed the widest data cloud, in contrary with the milled powder type which showed flatter data cloud. By comparison of NIRS results for total isoflavone, total amino acids, and protein of soybean seeds with three sample types, the powder sample could be estimated for the most accurate prediction. However, based from the results, the use of single bean samples, without grinding the seeds and in consideration with NIRS application for more nondestructive and faster prediction, is proven to be a promising strategy for soybean component estimation using NIRS.

• 한국작물학회지
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• 제61권1호
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• pp.64-69
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• 2016

This study was conducted to develop a fast and efficient screening method to determine the quantity of fatty acid in peanut oil for high oleate breeding program. A total of 329 peanut samples were used in this study, 227 of which were considered in the calibration equation development and 102 were utilized for validation, using near infrared reflectance spectroscopy (NIRS). The NIRS equations for all the seven fatty acids had low standard error of calibration (SEC) values, while high R2 values of 0.983 and 0.991 were obtained for oleic and linoleic acids, respectively in the calibration equation. Furthermore, the predicted means of the two main fatty acids in the calibration equation were very similar to the means based on gas chromatography (GC) analysis, ranging from 36.7 to 77.1% for oleic acid and 7.1 to 42.7% for linoleic acid. Based on the standard error of prediction (SEP), bias values, and $R^2$ statistics, the NIRS fatty acid equations were accurately predicted the concentrations of oleic and linoleic acids of the validation sample set. These results suggest that NIRS equations of oleic and linoleic acid can be used as a rapid mass screening method for fatty acid content analysis in peanut breeding program.

• Nuclear Engineering and Technology
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• 제51권2호
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• pp.526-532
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• 2019

In this study, an in-house $^{152}Eu$ calibration source was produced from a custom epoxy matrix with a density of ${\rho}=1.14g\;cm^{-3}$, which is chemically stable and durable form after its solidification. The homogeneity of $^{152}Eu$ in matrix was obtained better than 98%. For a Marinelli beaker geometry, an efficiency calibration procedure was applied to a n-type, coaxial, 78.5% relative efficient HPGe detector in the energy range of 121.7-1408.0 keV by using in-house $^{152}Eu$ calibration source. Then the measured efficiencies for Marinelli geometry were compared with the results calculated by MEFFTRAN and ANGLE softwares for the validation. Although MEFFTRAN and ANGLE have two different efficiency transfer algorithms to calculate the efficiencies, they usually need to use a reliable and accurate reference efficiency values as input data. Hence, reference efficiency values were obtained experimentally from a multinuclide standard source for the same detector-Marinelli geometry. In the present source characterization, the corrections required for self-absorption and true coincidence summing effects for $^{152}Eu$ gamma-rays were also obtained for a such close counting geometry condition. The experimental results confirmed the validity of efficiency calculations obtained by MEFFTRAN and ANGLE softwares that are calculation tools.

• 한국전자통신학회논문지
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• 제8권12호
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• pp.1923-1932
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• 2013

본 논문에서는 광각 카메라로 촬영한 영상에서 생기는 영상의 왜곡 문제를 해결하기 위하여, 카메라 모델의 추정과 검증을 통하여 광각 카메라 영상에서의 방사형 왜곡을 보정하는 방법을 제안한다. 먼저, 교정 패턴으로부터 렌즈의 초점 거리와 주점의 위치 등으로 구성된 내부 파라미터와 회전과 위치 정보로 구성된 외부 파라미터를 찾음으로써 카메라의 왜곡 모델을 추정한다. 다음으로, 추정된 카메라 모델로부터 역으로 코너점을 다시 추출하여 검증하고, 마지막으로, 검증된 카메라 모델을 이용하여 영상의 왜곡을 보정한다. 일반 웹 카메라와 광각 카메라로부터 격자 모양의 교정 패턴을 촬영한 영상을 이용하여 방사형 왜곡을 보정하는 실험을 수행한 결과, 제안된 방법이 80% 이상의 개선 성능을 보임을 확인하였다.

• 한국물환경학회지
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• 제28권2호
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• pp.247-254
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• 2012

Soil and Water Assessment Tool (SWAT) model has been widely used in estimation of flow and water quality at various watersheds worldwide, and it has an auto-calibration tool that could calibrate the flow and water quality data automatically from thousands of simulations. However, only continuous measured day flow/water quality data could be used in the current SWAT auto-calibration tool. Therefore, 8-day interval flow and water quality data measured nationwide by Korean Ministry of Environment (MOE) could not be used in SWAT auto-calibration even though long-term flow and water quality data in the Korean Total Maximum Daily Load (TMDL) watersheds available. In this study, current SWAT auto-calibration was modified to calibrate flow and water quality using 8-day interval flow and water quality data. As a result of this study, the Nash and Sutcliffe Efficiency (NSE) values for flow estimation using auto-calibration are 0.77 (calibration period) and 0.68 (validation period), and NSE value for water quality (T-P load) estimation (using the 8-day interval water quality data) is 0.80. The enhanced SWAT auto-calibration could be used in the estimation of continuous flow and water quality data at the outlet of TMDL watersheds and ungaged point of watersheds. In the next study, the enhanced SWAT auto-calibration will be integrated with Web based Load Duration Curve (LDC) system, and it could be suggested as methods of appraisal of TMDL in South Korea.