• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.6
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• pp.39-48
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• 2010

Sediment yields from Imha watershed were simulated during 1993-2008 using Hydrologic Simulation Program-Fortran (HSPF). Using observed daily stream flow for 2004-2008 and hourly suspended solid concentration for three events during 2006, HSPF was calibrated and validated at the sites of Imha and Youngyang for stream flow and Dongchun and Jangpachun for sediment yield. The calibration and validation results represented high model efficiency for simulating daily stream flow and hourly suspended solid. The determination coefficients of calibration and validation were 0.90 and 0.81 for daily stream flow, and 0.91 and 0.86 for monthly stream flow, respectively. Based on model tolerances for calibration and validation of stream flow, HSPF performance for simulating stream flow represented 'very good'. The determination coefficients of calibration and validation were 0.94-0.96 and 0.95 for hourly sediment yields, respectively. The average yearly sediment yield during 1993-2008 was 122,290 ton/year and most of sediment yield (77 % of total yield) were generated from June to August. The calibrated HSPF simulated well the movement of water and eroded soil within Imha watershed.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.189-199
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• 2012

PURPOSES: The purpose of this study is to propose a new methodology for developing statistical collision models and to show the validation results of the methodology. METHODS: A new modeling method of introducing variables into the model one by one in a multiplicative form is suggested. A method for choosing explanatory variables to be introduced into the model is explained. A method for determining functional forms for each explanatory variable is introduced as well as a parameter estimating procedure. A model selection method is also dealt with. Finally, the validation results is provided to demonstrate the efficacy of the final models developed using the method suggested in this study. RESULTS: According to the results of the validation for the total and injury collisions, the predictive powers of the models developed using the method suggested in this study were better than those of generalized linear models for the same data. CONCLUSIONS: Using the methodology suggested in this study, we could develop better statistical collision models having better predictive powers. This was because the methodology enabled us to find the relationships between dependant variable and each explanatory variable individually and to find the functional forms for the relationships which can be more likely non-linear.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.3966-3978
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• 2021

ISFRA (Integrated SFR Analysis Program for PSA) computer program has been developed for simulating the response of the PGSFR pool design with metal fuel during a severe accident. This paper describes validation of the ISFRA aerosol model against the Aerosol Behavior Code Validation and Evaluation (ABCOVE) experiments undertaken in 1980s for radionuclide transport within a SFR containment. ABCOVE AB5, AB6, and AB7 tests are simulated using the ISFRA aerosol model and the results are compared against the measured data as well as with the simulation results of the MELCOR severe accident code. It is revealed that the ISFRA prediction of single-component aerosols inside a vessel (AB5) is in good agreement with the experimental data as well as with the results of the aerosol model in MELCOR. Moreover, the ISFRA aerosol model can predict the "washout" phenomenon due to the interaction between two aerosol species (AB6) and two-component aerosols without strong mutual interference (AB7). Based on the theory review of the aerosol correlation technique, it is concluded that the ISFRA aerosol model can provide fast, stable calculations with reasonable accuracy for most of the cases unless the aerosol size distribution is strongly deformed from log-normal distribution.

• Journal of Food Hygiene and Safety
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• v.34 no.4
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• pp.374-379
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• 2019

This study developed predictive growth models of Salmonella enterica Serovar Typhimurium on lettuce washed with chlorine (100~300 ppm) and ultrasound (US, 37 kHz, 380 W) treatment and stored at different temperatures ($10{\sim}25^{\circ}C$) using a polynomial equation. The primary model of specific growth rate (SGR) and lag time (LT) showed a good fit ($R^2{\geq}0.92$) with a Gompertz equation. A secondary model was obtained using a quadratic polynomial equation. The appropriateness of the secondary SGR and LT model was verified by coefficient of determination ($R^2=0.98{\sim}0.99$ for internal validation, 0.97~0.98 for external validation), mean square error (MSE=-0.0071~0.0057 for internal validation, -0.0118~0.0176 for external validation), bias factor ($B_f=0.9918{\sim}1.0066$ for internal validation, 0.9865~1.0205 for external validation), and accuracy factor ($A_f=0.9935{\sim}1.0082$ for internal validation, 0.9799~1.0137 for external validation). The newly developed models for S. Typhimurium could be incorporated into a tertiary modeling program to predict the growth of S. Typhimurium as a function of combined chlorine and US during the storage. These new models may also be useful to predict potential S. Typhimurium growth on lettuce, which is important for food safety purposes during the overall supply chain of lettuce from farm to table. Finally, the models may offer reliable and useful information of growth kinetics for the quantification microbial risk assessment of S. Typhimurium on washed lettuce.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.2
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• pp.142-148
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• 2005

This paper proposes a cell age model for Penicillium chrysogenum fed-batch cultivation to supply a qualitative insight into morphology-associated dynamics. The average ages of the segregated cell populations, such as growing cells, non-growing cells and intact productive cells, were estimated by this model. A combined model was obtained by incorporating the aver-age ages of the cell sub-populations into a known but modified segregated kinetic model from literature. For simulations, no additional effort was needed for parameter identification since the cell age model has no internal parameters. Validation of the combined model was per-formed by 20 charges of industrial-scale penicillin cultivation. Meanwhile, only two charge-dependent parameters were required in the combined model among approximately 20 parameters in total. The model is thus easily transformed into an adaptive model for a further application in on-line state variables prediction and optimal scheduling.

• Journal of Korean Society on Water Environment
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• v.29 no.3
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• pp.365-376
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• 2013

The purpose of this study was to evaluate effects of spatio-temporal changes in land uses and rainfall magnitude using the Soil and Water Assessment Tool (SWAT). Prior of application of the model to real-world problem, the model should be calibrated and validated properly. In most modeling approaches, the validation process is done assuming no significant changes occurring at the study watershed between calibration and validation periods, which is not proper assumption for agricultural watersheds. If simulated results obtained with calibrated parameters match observed data with higher accuracy for validation period, this does not always mean the simulated result represents rainfall-runoff, pollutant generation and transport mechanism for validation period because temporal and spatial variables and rainfall magnitude are often not the same. In this study SWAT was applied to Mandae study watershed in Korea to evaluate effects of spatio-temporal changes in landuses using 2009 and 2010 crop data for each field at the watershed. The Nash-Sutcliffe model efficiency (NSE) values for calibration and validation with either 2009 or 2010 was evaluated and the NSE value for calibration with 2009 and calibration with 2010 were compared. It was found that if there is substantial change in land use and rainfall, model calibration period should be determined to reflect those changes. Through these approaches, inherent limitation of the SWAT, which does not consider changes in land uses over the simulation period, was investigated. Also, Effects of changes in rainfall magnitude during calibration process were analyzed.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.577-587
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• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.105-113
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• 2009

The feature models are widely used to model the commonalities and variabilities among the products in the domain engineering phase of software product line developments. The findings and corrections of the errors or consistencies in the feature models are essential to the successful software product line engineering. The aids of the automated tools are needed to perform the validation of the feature models effectively. This paper describes the approach based on JESS rule-base system to validate the feature models and proposes the feature model validation tool using this approach. The tool of this paper validates the feature models in real-time when modeling the feature models. Then it provides the information on existence of errors and the explanations on causes of those errors, which allows the feature modeler to create the error-free feature models. This attempt to validate the feature model using the rule-based system is supposed to be the first time in this research field.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.5
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• pp.69-77
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• 2019

The objective of this study was to calibrate and validate the HSPF (Hydrological Simulation Program-Fortran) model for estimating the runoff of the Hapcheon dam watershed. Spatial data, such as watershed, stream, land use, and a digital elevation map, were used as input data for the HSPF model. Observed runoff data from 2000 to 2016 in study watershed were used for calibration and validation. Hydrologic parameters for runoff calibration were selected based on the user's manual and references, and trial and error method was used for parameter calibration. The $R^2$, RMSE (root-mean-square error), RMAE (relative mean absolute error), and NSE (Nash-Sutcliffe efficiency coefficient) were used to evaluate the model's performance. Calibration and validation results showed that annual mean runoff was within ${\pm}4%$ error. The model performance criteria for calibration and validation showed that $R^2$ was in the rang of 0.78 to 0.83, RMSE was 2.55 to 2.76 mm/day, RMAE was 0.46 to 0.48 mm/day, and NSE was 0.81 to 0.82 for daily runoff. The amount of inflow to Hapcheon Dam was calculated from the calibrated HSPF model and the result was compared with observed inflow, which was -0.9% error. As a result of analyzing the relation between inflow and storage capacity, it was found that as the inflow increases, the storage increases, and when the inflow decreases, the storage also decreases. As a result of correlation between inflow and storage, $R^2$ of the measured inflow and storage was 0.67, and the simulated inflow and storage was 0.61.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.422-433
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• 2009

As an effort to secure Semantic Web, in this paper, we introduce an RDF access authorization model based on an ontology hierarchy and an RDF triple pattern. In addition, we apply the authorization model to RDF query validation for approved access authorizations. A subscribed SPARQL or RQL query, which has RDF triple patterns, can be denied or granted according to the corresponding access authorizations which have an RDF triple pattern. In order to efficiently perform the query validation process, we first analyze some primary authorization conflict conditions under RDF subsumption inference, and then we introduce an efficient query validation algorithm using the conflict conditions and Dewey graph labeling technique. Through experiments, we also show that the proposed validation algorithm provides a reasonable validation time and when data and authorizations increase it has scalability.