• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.4
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• pp.67-74
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• 2011

The objectives of this study were to assess the rice yields and evaluate fertilizer reduction effect of reclaimed wastewater irrigation in paddy fields using the Decision Support System for Agrotechnology Transfer (DSSAT) v4.5 model. The experimental plots were designed, which was located near the Suwon wastewater treatment plant in Gyeonggi-do, Korea. The rice yield, irrigation amount, irrigation water quality and soil data were monitored and collected between 2006 and 2009. The DSSAT model was calibrated and validated with observed data. The methods that were used to evaluate this model were the root mean square error (RMSE), normalized root mean square error (nRMSE), and index of agreement (d). The values of RMSE, nRMSE, and d ranged from 145 to $789\;kg\;ha^{-1}$, 3.0 to 13.3 %, and 0.90 to 0.95 for the calibration period, respectively and represented from 91 to $538\;kg\;ha^{-1}$, 2.0 to 10.4 %, 0.94 to 0.98 for the validation period, respectively. Overall, this model showed good agreement with observed data of rice yields irrigated with reclaimed wastewater. The fertilizer reduction effect in paddy field of reclaimed wastewater irrigation was assessed about 60 % in 2008 and 40 % in 2009.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.1
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• pp.11-19
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• 1992

This paper proposes a reduced order method which reduces passband error by changing controllability and observability gramian based on weighted functions in the linear time invariant system. In the case that the 4-order model is the reduced to 3-order model in the low-pass filter, the QEI in the proposed method is improved to 6.15724 compared to 10.16464 in the balanced realization method and the sensitivity is improved to 5.45962 compared to 7.790568. The frequency property curves show that the proposed method is superior to the balanced realization method.

• Journal of Environmental Science International
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• v.12 no.9
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• pp.957-966
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• 2003

Gunsan coastal area is one of region increasing pollution problems. To improve water quality, the reduction of these nutrients loads should be indispensible. In this study, the three-dimensional numerical hydrodynamic and ecosystem model were applied to analyze the processes affecting the eutrophication. In field survey, the average concentrations of dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus(DIP) at surface waters were found to be 0.43mg/$\ell$ and 0.03mg/$\ell$ respectively, which were exceeding second grade of water quality criteria. In hydrodynamic modelling, the comparison between the simulated and observed tidal ellipses showed fairly good agreement. The ecosystem model was calibrated with the observed data in study area. The simulated results of DIN were fairly good coincided with the observed values within relative error of 32.39%, correlation coefficient(r) of 0.99. In the case of DIP, the simulated results were fairly good coincided with the observed values within relative error of 24.26%, correlation coefficient(r) of 0.82. The simulations of DIN and DIP concentrations using ecosystem model were performed under the conditions of 20∼80% reductions for pollutant loading. At simulation results, concentration of DIN and DIP were reduced to 20∼80% and under 10% in case of the 80% reduction of pollutant loading, respectively.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.68-74
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• 1998

This paper deals with a model reduction problem for the linear systems with state delay. After defining the controllability/observability Gramians, the concept of a balanced model for the linear systems with state delay is introduced. Based on solutions of linear matrix inequalities, the model reduction method with guaranteed error bounds is developed. In order to demonstrate the efficacy of teh suggested method, a numerical example is also performed.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.170-177
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• 1998

In this paper, a unified solution of Hankel norm approximation problem is proposed by $\delta$-operator. To derive the main result, all-pass property is derived from the inner and co-inner property in the $\delta$-domain. The solution of all-pass becomes an optimal Hankel norm approximation problem in .delta.-domain through LLFT(Low Linear Fractional Transformation) inserting feedback term $\phi(\gamma)$, which is a free design parameter, to hold the error bound desired against the variance between the original model and the solution of Hankel norm approximation problem. The proposed solution does not only cover continuous and discrete ones depending on sampling interval but also plays a key role in robust control and model reduction problem. The verification of the proposed solution is exemplified via simulation for the zero-order Hankel norm approximation problem and the model reduction problem applied to a 16th order MIMO system.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.721-733
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• 2022

In this paper we compare parameter estimation by Grassmann manifold optimization and sequential candidate set algorithm in a structured principal fitted component (PFC) model. The structured PFC model extends the form of the covariance matrix of a random error to relieve the limits that occur due to too simple form of the matrix. However, unlike other PFC models, structured PFC model does not have a closed form for parameter estimation in dimension reduction which signals the need of numerical computation. The numerical computation can be done through Grassmann manifold optimization and sequential candidate set algorithm. We conducted numerical studies to compare the two methods by computing the results of sequential dimension testing and trace correlation values where we can compare the performance in determining dimension and estimating the basis. We could conclude that Grassmann manifold optimization outperforms sequential candidate set algorithm in dimension determination, while sequential candidate set algorithm is better in basis estimation when conducting dimension reduction. We also applied the methods in real data which derived the same result.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.1
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• pp.84-92
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• 2015

This paper proposes a new approach to reduce the target estimation error of the measurement angle, especially applied to the medium and long range surveillance radar. If the target has no maneuver and no change in heading direction for a certain time interval, the predicted angle of interacting multiple model(IMM) from the previous track information can be used to reduce the angle estimation error. The proposed method is simulated in 2 scenarios, a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new fusion solution(weighted IMM) with the predicted azimuth and the measured azimuth is worked properly in the two scenarios.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1902-1908
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• 2022

In many of the complex systems modeled in the field of nuclear engineering, it is often useful to use linear regression-based analyses to analyze relationships between model parameters and responses of interests. In cases where the response of interest is calculated by a simulation which uses Monte Carlo methods, there will be some uncertainty in the responses. Further, the reduction of this uncertainty increases the time necessary to run each calculation. This paper presents some discussion on how the Monte Carlo error in the response of interest influences the error in computed linear regression coefficients. A mathematical justification is given that shows that when performing linear regression in these scenarios, the error in regression coefficients can be largely independent of the Monte Carlo error in each individual calculation. This condition is only true if the total number of calculations are scaled to have a constant total time, or amount of work, for all calculations. An application with a simple pin cell model is used to demonstrate these observations in a practical problem.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.760-763
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• 2005

Optimum design of the tooth surface for the reduction of transmission error is very difficult to determine analytically due to nonlinearity of transmission error under the several load condition. The design of tooth surface that can give a low noise under the various load condition is very important. Therefore, this study proposes the method to determine the optimal lead curve and robust design of the tooth surface by using the response surface method. To do so, the design variables are selected by a screening experiment. Then the fitted regression model Is built with the check of the usefulness of the model. The model with constraints is solved to obtain the optimum values for the lead curve and the robust design fur the tooth surface.

• Wind and Structures
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• v.22 no.1
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• pp.17-41
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• 2016

To address the uncertainty of the flight trajectories caused by the turbulence and gustiness of the wind field over the roof and in the wake of a building, a 3-D probabilistic trajectory model of flat-type wind-borne debris is developed in this study. The core of this methodology is a 6 degree-of-freedom deterministic model, derived from the governing equations of motion of the debris, and a Monte Carlo simulation engine used to account for the uncertainty resulting from vertical and lateral gust wind velocity components. The influence of several parameters, including initial wind speed, time step, gust sampling frequency, number of Monte Carlo simulations, and the extreme gust factor, on the accuracy of the proposed model is examined. For the purpose of validation and calibration, the simulated results from the 3-D probabilistic trajectory model are compared against the available wind tunnel test data. Results show that the maximum relative error between the simulated and wind tunnel test results of the average longitudinal position is about 20%, implying that the probabilistic model provides a reliable and effective means to predict the 3-D flight of the plate-type wind-borne debris.