• Journal of Wetlands Research
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• v.14 no.4
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• pp.519-535
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• 2012

In order to establish a rainfall-runoff model, calibration of hydrological parameters for the model is very important. Especially, Curve Number(CN), estimated by NRCS method, is a main factor to apply unit hydrograph theory to calculation of peak discharge. For using NRCS method, it is needed selecting AMC because CN is strongly connected with that. In this study, we focus our concern on finding a applicable standard for selecting AMC for CN. For this, three dams which are Boryeong, Habchon, Namgang are selected as target basins to use observed data including rainfall and dam inflow. As a result of this research, it is found that CN must be included as a calibrated parameter to calculate effective rainfall for the rainfall-runoff model. Also, it is preferred to use PWRMSE of HEC-HMS program as a objective function for optimizing hydrological parameters. From the analyzing result of variation of AMC for peak discharge, it is recommended to apply AMC-III to estimation of CN for calculating effective rainfall of design hydrograph.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.657-664
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• 2003

Reliable tracking of moving humans is essential to motion estimation, video surveillance and human-computer interface. This paper presents a new approach to human motion tracking that combines appearance-based and model-based techniques. Monocular color video is processed at both pixel level and object level. At the pixel level, a Gaussian mixture model is used to train and classily individual pixel colors. At the object level, a 3D human body model projected on a 2D image plane is used to fit the image data. Our method does not use inverse kinematics due to the singularity problem. While many others use stochastic sampling for model-based motion tracking, our method is purely dependent on nonlinear programming. We convert the human motion tracking problem into a nonlinear programming problem. A cost function for parameter optimization is used to estimate the degree of the overlapping between the foreground input image silhouette and a projected 3D model body silhouette. The overlapping is computed using computational geometry by converting a set of pixels from the image domain to a polygon in the real projection plane domain. Our method is used to recognize various human motions. Motion tracking results from video sequences are very encouraging.

• Clean Technology
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• v.24 no.3
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• pp.239-248
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• 2018

In this study, pervaporation experiments of water, ethanol and IPA (Isopropyl alcohol) single components and water/ethanol, water/IPA mixtures were carried out using zeolite 4A membranes developed by Fine Tech Co. Ltd. Those membranes were fabricated by hydrothermal synthesis (growth in hydrothermal condition) after uniformly dispersing the zeolite seeds on the tubular alumina supports. They have a pore size of about $4{\AA}$ by ion exchange of $Na^+$ to the LTA structure with Si/Al ratio of 1.0, and shows strong hydrophilic property. Physical characteristics of prepared membranes were evaluated by using SEM (surface morphology), porosimetry (macro- or meso- pore analysis), BET (micropore analysis), and load tester (compressive strength). Pervaporation experiments with various temperature and concentration conditions confirmed that the zeolite 4A membrane can selectively separate water from ethanol and IPA. Water/ethanol separation factor was over 3,000 and water/IPA separation factor was over 1,500 (50 : 50 wt%, initial feed concentration). Pervaporation behaviors of single components and binary mixtures were predicted using ACM (activity coefficient model), GMS (generalized Maxwell Stefan) model and DGM (Dusty Gas Model). The adsorption and diffusion coefficients of the zeolite top layer were obtained by parameter estimation using GA (Genetic Algorithm, stochastic optimization method). All the calculations were carried out using MATLAB 2018a version.

• The Korean Journal of Food And Nutrition
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• v.29 no.3
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• pp.371-381
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• 2016

The present study investigated the effects of processing parameters such as time (10, 20, 30, 40 min), pressure (25, 50, 75, 100 MPa), and the salinity of brine (0~10%(w/v)) on jacopever (Sebastes schlegeli Hilgendorf) in order to establish optimization of the three factors using a high hydrostatic pressure (HHP) machine. To do so, it analyzed the quality characteristics of volatile basic nitrogen (VBN), trimethylamine (TMA), total bacterial counts, dynamic viscoelasticities, and differential scanning calorimetry (DSC) properties. First, when the time increased to 40 mins, by 10 min intervals, the total bacterial counts in HHP groups under $25^{\circ}C$, 100 MPa, and 4%(w/v) brine were significantly decreased except for the first 10 min in comparison to the control group. In regards to DSC properties, the onset temperature ($T_O$) of the first endothermal curve was significantly reduced. Second, when the pressure level increased up to 100 MPa by 25 MPa increments, the total bacterial counts in the HHP samples significantly decreased for 20 min at 50 MPa or higher. As the pressure increased, G', G" and the slope of tan ${\delta}$ decreased (except for 50 MPa). Third, in regards to the salinities of brine, when the HHP processing was treated at 100 MPa, $25^{\circ}C$ for 20 min, the total bacterial counts of all the HHP groups significantly decreased in comparison to those of the control group. A significant difference was found in the enthalpy of the second endothermic curve in the 6~10%(w/v) (except 7%(w/v)) HHP groups. Therefore, the salinity of the immersion water under the HHP condition was appropriate when it was lower than 6%(w/v). The present study demonstrated that the optimum parameter condition according to/under the condition of the microbial inhibition and economic effects using an HHP would be the reaction time for 20 min, reaction pressure at 100 MPa, and the salinity of 4%(w/v) brine.

• Korean Journal of Food Science and Technology
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• v.33 no.6
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• pp.686-692
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• 2001

The effects of extrusion on solubilization of brown rice, glutinuous rice, barley and job's tear were analyzed by response surface methodology (RSM). Solubilization of whole grains by extrusion was characterized in terms of water solubility index (WSI), concentration of water soluble polysaccharides (C) and intrinsic viscosity $([\eta])$. Considering both concentration and intrinsic viscosity, a dimensionless target parameter $([\eta])$ was also included for analysing the extrusion effects on cereal extrusion. Response surface methodology analysis showed that the moisture content was the most significant contributor among screw speed, temperature and moisture content affecting the solubilizing phenomena of cereals processed with extrusion. Brown rice was not showed the significant relationship on $([\eta])$ because $([\eta])$ was more affected by intrinsic viscosity. The critical point of whole grains extrusion except brown rice was corresponded to screw speed of 300 rpm, moisture content of 20% and temperature of $120^{\circ}C$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.121-131
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• 2007

Despite the close linkage in changes between the ecological and hydrological processes in forest ecosystems, an integrative approach has not been incorporated successfully. In this study, based on the vegetation and hydrologic data of the Gwangneung headwater catchment with the Geographic Information System, we attempted such an integrated approach by employing the Regional Hydro-Ecologic Simulation System (RHESSys). To accomplish this, we have (1) constructed the input data for RHESSys, (2) developed an integrated calibration system that enables to consider both ecological and hydrological processes simultaneously, and (3) performed sensitivity analysis to estimate the optimum parameters. Our sensitivity analyses on six soil parameters that affect streamflow patterns and peak flow show that the decay parameter of horizontal saturated hydraulic conductivity $(s_1)$ and porosity decay by depth (PD) had the highest sensitivity. The optimization of these two parameters to estimate the optimum streamflow variation resulted in a prediction accuracy of 0.75 in terms of Nash-Sutcliffe efficiency (NSec). These results provide an important basis for future evaluation and mapping of the watershed-scale soil moisture and evapotranspiration in forest ecosystems of Korea.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.29-38
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• 2012

The noise generated in the process of obtaining the medical image acts as the element obstructing the image interpretation and diagnosis. To restore the true image from the image polluted from the noise, the total variation optimization algorithm was proposed by the R.O. F (L.Rudin, S Osher, E. Fatemi). This method removes the noise by fitting the balance of the regularity and fidelity. However, the blurring phenomenon of the border area generated in the process of performing the iterative operation cannot be avoided. In this paper, we propose the adaptive total variation method by mapping the control parameter to the proposed transfer function for minimizing boundary error. The proposed transfer function is determined by the noise variance and the local property of the image. The proposed method was applied to 464 tooth images. To evaluate proposed method performance, PSNR which is a indicator of signal and noise's signal power ratio was used. The experimental results show that the proposed method has better performance than other methods.

• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1053-1067
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• 2013

Distributed ecohydrological model which can simulate hydrological components, vegetation and landsurface temperature using practically available input and observed data with minimum parameters is introduced. This model is designed to properly simulate in area with lack of observed data. Parameter estimation and calibration of the model can be carried out with indirectly estimated data (monthly surface runoff by NRCS-CN method and annual actual vaporization by empirical equation) and remote sensing data (NDVI, LST) instead of observed data. We applied this model in the Naeseong creek basin to evaluate the model validity. Firstly, we found the sensitive parameters which largely influence the simulation results by sensitivity analysis, and then hydrological components, vegetation, land-surface temperature, routed streamflow and water temperature were simulated over 10 years (2001 to 2010) using calibrated parameters. Parameters are estimated by optimization method. It is shown that most of grids are well simulated. In the case of streamflow and water temperature, we checked two observed points in the outlet of watershed and it is shown that streamflow and water temperature are properly simulated as well. Hence, it can be shown that this model properly simulate the hydrological components, vegetation, land-surface temperature, routed streamflow and water temperature as well, even though in despite of using limited input data and minimum parameters.

• Journal of the Korean Chemical Society
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• v.53 no.6
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• pp.653-662
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• 2009

Developing effective tools for predicting absorption, distribution, metabolism, excretion properties and toxicity (ADME/T) of new chemical entities in the early stage of drug design is one of the most important tasks in drug discovery and development today. As one of these attempts, support vector machines (SVM) has recently been exploited for the prediction of ADME/T related properties. However, two problems in SVM modeling, i.e. feature selection and parameters setting, are still far from solved. The two problems have been shown to be crucial to the efficiency and accuracy of SVM classification. In particular, the feature selection and optimal SVM parameters setting influence each other, which indicates that they should be dealt with simultaneously. In this account, we present an integrated practical solution, in which genetic-based algorithm (GA) is used for feature selection and grid search (GS) method for parameters optimization. hERG ion-channel inhibitor classification models of ADME/T related properties has been built for assessing and testing the proposed GA-GS-SVM. We generated 6 different models that are 3 different single models and 3 different ensemble models using training set - 1891 compounds and validated with external test set - 175 compounds. We compared single model with ensemble model to solve data imbalance problems. It was able to improve accuracy of prediction to use ensemble model.

• Composites Research
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• v.33 no.2
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• pp.39-43
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• 2020

Recently, fabrication process of thermoplastic polyamide-based composites with recyclability as well as impact, chemical, and abrasion resistance have been widely studied. In particular, thermoplastic reactive resin transfer molding (TRTM) in which monomer with low viscosity is injected and in-situ polymerized inside mold has received a great attention, because thermoplastic melts are hard to impregnate fiber preform due to their very high viscosity. However, it is difficult to optimize the processing conditions because of high reactivity and sensitivity to external environments of the used monomer, ε-caprolactam. In this study, viscosity as an important process parameter in TRTM was measured during in-situ anionic polymerization of ε-caprolactam and the solutions for problems caused by high polymerization rate and sensitivity to moisture and oxygen were suggested. Reliability of the improved measurement technique was verified by comparing the viscosity behavior at various environmental conditions including humidity and atmosphere, and it is expected to be helpful for optimization of TRTM process.