• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.1
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• pp.14-17
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• 2005

In this paper, an automated methodology for generating model parameters considering real manufacturing processes is presented with verified results. In addition, the outcomes of applications to the next generation of flash memory devices using the parameters calibrated from the process specification decision are analyzed. The test vehicle is replaced with a well-calibrated TCAD simulation. First, the calibration methodology is introduced and tested for a flash memory device. The calibration errors are less than 5% of a full chip operation, which is acceptable to designers. The results of the calibration are then used to predict the I-V curves and the model parameters of various transistors for the design of flash devices.

• Journal of Korean Society on Water Environment
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• v.25 no.3
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• pp.432-440
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• 2009

The effect of selecting hydrologic item for calculating objective function on calibration of stream flow was evaluated by Hydrologic Simulation Porgram-Fortran (HSPF) linked with Model Independent Parameter Optimizer (PEST). Daily and monthly stream flow and flow duration were used to calculate objective function. Automated calibration focused on monthly stream was proper to analyze seasonal or yearly water budget but not proper to predict daily stream flow or percent chance flow exceeded. Calibration result focused on flow duration is proper to predict precent chance flow exceeded but not proper to analyze water budget or predict peak flow. These results indicate that hydrologic item calculated for objective function on calibration procedure could influence calibration results and watershed modeler should select carefully hydrologic item for the purpose of model application. Current, the criteria of stream flow of Korean TMDL is generated based on percent chance flow exceeded, so flow duration should be included to calculate objective function on calibration procedure for the estimation of criteria of stream flow using hydrologic model.

• Economic and Environmental Geology
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• v.29 no.6
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• pp.699-712
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• 1996

Field scale experiments using an automated 144-channel TDR system were conducted which monitored the movement of solute through unsaturated loamy soils. The experiments were carried out on two different field plots of 0.54 ha to study the vertical movement of solute plume created by applying a square pulse of $CaCl_2$ as a tracer. The residence concentration was monitored at 24 locations on a transect and 5 depths per location by horizontally-positioning 50 cm long triple wire TDR probes to study the heterogeneity of solute travel times and the governing transport concept at field scale. This paper describes details of experimental methodology and calibration aspects of the TDR system. Three different calibration methods for estimation of solute concentration from TDR-measured bulk soil electrical conductivity were used for each field site. Data analysis of mean breakthrough curves (BTCs) and parameters estimated using the convection-dispersion model (CDE) and the convective-lognormal transfer function model (CLT) reveals that the automated TDR system is a viable technique to study the field scale solute transport providing a normal distribution of resident concentration in a high resolution of time series, and that calibration method does not significantly affect both the shape of BTC and the parameters related to the peak travel time. Among the calibration methods, the simple linear model (SLM), a modified version of Rhoades' model, appears to be promising in the calibration of horizontally-positioned TDR probes at field condition.

• Journal of Sensor Science and Technology
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• v.14 no.2
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• pp.109-115
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• 2005

Calibration is a prerequisite procedure for employing a camera as a 3D sensor in an automated machines like robots. As accurate sensing is possible only when the vision sensor is calibrated accurately, many different approaches and models have been proposed for increasing calibration accuracy. Particularly an important factor which greatly affects the calibration accuracy is the nonlinearity in the mapping between 3D world and corresponding 2D image. In this paper GMDH algorithm is used to learn the nonlinearity without physical modelling. The technique proposed can be effective in various situations where the levels of noises and characteristics of nonlinear distortion are different. In simulations and an experiment, the proposed technique showed good and reliable results.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.629-642
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• 2021

Land-use change has an important role in the hydrologic characteristics of watersheds because it alters various hydrologic components such as interception, infiltration, and evapotranspiration. For example, rapid urbanization in a watershed reduces infiltration rates and increases peak flow which lead to changes in the hydrologic responses. In this study, a physical hydrologic model the soil and water assessment tool (SWAT) was used to assess long-term continuous daily streamflow corresponding to land-use changes that occurred in the Naesungchun river watershed. For a 30-year model simulation, 3 different land-use maps of the 1990s, 2000s, and 2010s were used to identify the impacts of the land-use changes. Using SWAT-CUP (calibration and uncertainty program), an automated parameter calibration tool, 23 parameters were selected, optimized and compared with the daily streamflow data observed at the upstream, midstream and downstream locations of the watershed. The statistical indexes used for the model calibration and validation show that the model performance is improved at the downstream location of the Naesungchun river. The simulated streamflow in the mainstream considering land-use change increases up to -2 - 30 cm compared with the results simulated with the single land-use map. However, the difference was not significant in the tributaries with or without the impact of land-use change.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.111-116
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• 1998

In this study, we try to coincide virtual robot system in an OLP(off-line programming) with actual robot system even though kinematic differences between them are made. The virtual robot in the OLP may be modeled according to kinematics of the actual robot system. However, it is a complicated problem to find exactly all kinematic parameters of actual robot and environment. In this paper, an automated calibration method is proposed In order to find some kinematical parameters which are necessary for the modeling of a robot and environment in the OLP. It is applicable to SCARA robot for assembly task. In this method, a well-marked worktable of environment Is regarded as reference coordinate frame. The robot detects some marks on the worktable through sensors attached to the end-effector. The necessary parameters are calculated from the data of the robot joint variables when the robot detects the mark. The model in the OLP is modified by the parameters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.1-9
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• 2008

The impact of snow accumulation and snowmelt in rainfall-runoff modelling was analyzed for the Soyanggang dam basin by comparing the measured and simulated discharges simulated by the NWS-PC model. Sugawara's conceptual model was used to simulate the snow accumulation and snowmelt phenomena and NWS-PC model was employed to simulate rainfall-runoff. Parameters in model calibration were estimated by the Multi-step Automated Calibration Scheme and optimized using SCE-UA algorithm in each step. The results of the model calibration and verification show that the model considering snowmelt process is better than the one without consideration of snowmelt under the performance criteria such as RMSE, PBIAS, NSE, and PME. The measured discharge time series has over 60 days of persistence. Correlograms for each simulation showed that the simulated discharge with snowmelt model reproduce the persistence closely to the measured discharge's while the one without snow accumulation and snowmelt model reproduce only 20 days of persistence. The study result indicates that the inclusion of snow accumulation and snowmelt model is important for the accurate simulation of rainfall-runoff phenomena in the Soyanggang dam basin.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.65-71
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• 2018

The Long-Term Hydrologic Impact Assessment (L-THIA) model is a quick and straightforward analysis tool to estimate direct runoff and nonpoint source pollution. L-THIA was originally implemented as a spreadsheet application. GIS-based versions of L-THIA have been developed in ArcView 3 and upgraded to ArcGIS 9. However, a major upgrade was required for L-THIA to operate in the current version of ArcGIS and to provide more options in runoff and NPS estimation. An updated L-THIA interfaced with ArcGIS 10.0 and 10.1 has been developed in the study as an ArcGIS Desktop Tool. The model provides a user-friendly interface, easy access to the model parameters, and an automated watershed delineation process. The model allows use of precipitation data from multiple gauge locations for the watershed when a watershed is large enough to have more than one precipitation gauge station. The model estimated annual direct runoff well for our study area compared to separated direct runoff in the calibration and validation periods of ten and nine years. The ArcL-THIA, with a user-friendly interface and enhanced functions, is expected to be a decision support model requiring less effort for GIS processes or to be a useful educational hydrology model.

• Economic and Environmental Geology
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• v.29 no.6
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• pp.713-724
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• 1996

The time-series resident solute concentrations, monitored at two field plots using the automated 144-channel TDR system by Kim (this issue), are used to investigate the dominant transport mechanism at field scale. Two models, based on contradictory assumptions for describing the solute transport in the vadose zone, are fitted to the measured mean breakthrough curves (BTCs): the deterministic one-dimensional convection-dispersion model (CDE) and the stochastic-convective lognormal transfer function model (CLT). In addition, moment analysis has been performed using the probability density functions (pdfs) of the travel time of resident concentration. Results of moment analysis have shown that the first and second time moments of resident pdf are larger than those of flux pdf. Based on the time moments, expressed in function of model parameters, variance and dispersion of resident solute travel times are derived. The relationship between variance or dispersion of solute travel time and depth has been found to be identical for both the time-series flux and resident concentrations. Based on these relationships, the two models have been tested. However, due to the significant variations of transport properties across depth, the test has led to unreliable results. Consequently, the model performance has been evaluated based on predictability of the time-series resident BTCs at other depths after calibration at the first depth. The evaluation of model predictability has resulted in a clear conclusion that for both experimental sites the CLT model gives more accurate prediction than the CDE model. This suggests that solute transport at natural field soils is more likely governed by a stream tube model concept with correlated flow than a complete mixing model. Poor prediction of CDE model is attributed to the underestimation of solute spreading and thus resulting in an overprediction of peak concentration.