• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.1009-1019
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• 2009

In this research, various characteristics of South Korea's design flood have been examined by deriving appropriate design flood, using data obtained from careful observation of actual floods occurring in selected main watersheds of the nation. 19 watersheds were selected for research in Korea. The various characteristics of annual rainfall were analyzed by using a moving average method. The frequency analysis was decided to be performed on the annual maximum flood of succeeding one year as a reference year. For the 19 watersheds, tests of basic statistics, independent, homogeneity, and outlier were calculated per period of annual maximum flood series. By performing a test using the LH-moment ratio diagram and the Kolmogorov-Smirnov (K-S) test, among applied distributions of Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distribution was found to be adequate compared with other probability distributions. Parameters of GEV distribution were estimated by L, L1, L2, L3 and L4-moment method based on the change in the order of probability weighted moments. Design floods per watershed and the periods of annual maximum flood series were derived by GEV distribution. According to the result of the analysis performed by using variation rate used in this research, it has been concluded that the time for changing the design conditions to ensure the proper hydraulic structure that considers recent climate changes of the nation brought about by global warming should be around the year 2002.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.5
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• pp.120-127
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• 2009

An electric furnace, inside which desired temperatures are kept constant by generating heat, is known to be a difficult system to control and model exactly because system parameters and response delay time vary as the temperature and position are changed. In this study the heating system of ceramic drying furnaces with time-varying parameters is mathematically modeled as a second order system and control parameters are estimated by using a RIV (Recursive Instrumental-Variable) method. A modified bang-bang control with magnitude tuning is proposed in the time optimal temperature control of ceramic drying electric furnaces and its performance is experimentally verified. It is proven that temperature tracking of adaptive time optimal control using a second order model is more stable than the GPCEW (Generalized Predictive Control with Exponential Weight) and rapidly settles down by pre-estimation of the system parameters.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.158-160
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• 2005

This paper presents a new approach to the problem of designing a cascaded three-parameters controller for a given linear time invariant (LTD plant in unity feedback system. We consider a proportional-integral-derivative (PID) and a first-order controller with specified overshoot and settling time. This problem is difficult to solve because there may be no analytical solution due to the use of low-order controller and furthermore. the zeros of controller just appear in the zeros of feedback system. The key idea of our method is to impose a constraint on the controller parameters so that the zeros of resulting controller are distant from the dominant pole of closed-loop system to the left as far as the given interval. Two methods realizing the idea are suggested. We have employed the characteristic ratio assignment (CRA) in order to deal with the time response specifications. It is noted that the proposed methods are accomplished only in parameter space. Several illustrative examples are given.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.22-33
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• 1999

This paper presents the method for the automatic tuning of a design weighting polynomial parameters of a generalized minimum-variance stochastic ultivariable self-tuning controller which adapts to changes in the higher order nonminimum phase system parameters with time delays and noises. The self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing the design weighting polynomial parameters of the controller. The proposed multivariable self-tuning method is simple and effective compared with pole restriction method. The computer simulation results are presented to adapt the higher order multivariable system with nonminimum phase and with changeable system parameters.

• Bulletin of the Korean Chemical Society
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• v.31 no.10
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• pp.2903-2908
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• 2010

Protein S-nitrosation is common in cells under nitrosative stress. In order to model proteins with S-nitrosocysteine (CysSNO) residues, we first developed an Amber force field for S-nitrosoethanethiol (EtSNO) and then transferred it to CysSNO. Partial atomic charges for EtSNO and CysSNO were obtained by a restrained electrostatic potential approach to be compatible with the Amber-99 force field. The force field parameters for bonds and angles in EtSNO were obtained from a generalized Amber force field (GAFF) by running the Antechamber module of the Amber software package. The GAFF parameters for the CC-SN and CS-NO dihedrals were not accurate and thus determined anew. The CC-SN and CS-NO torsional energy profiles of EtSNO were calculated quantum mechanically at the level of B3LYP/cc-pVTZ//HF/6-$31G^*$. Torsional force constants were obtained by fitting the theoretical torsional energies with those obtained from molecular mechanics energy minimization. These parameters for EtSNO reproduced, to a reasonable accuracy, the corresponding torsional energy profiles of the capped tripeptide ACE-CysSNO-NME as well as their structures obtained from quantum mechanical geometry optimization. A molecular dynamics simulation of myoglobin with a CysSNO residue produced a well-behaved trajectory demonstrating that the parameters may be used in modeling other S-nitrosated proteins.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.1
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• pp.20-23
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• 2006

This paper presents a new approach to the problem of designing a cascaded three-parameters controller for a given linear time invariant (LTI) plant in unity feedback system. We consider a proportional-integral-derivative (PID) and a first-order controller with the specified overshoot and settling time. This problem is difficult to solve because there may be no analytical solution due to the use of low-order controller. Furthermore, the zeros of controller just appear in the zeros of feedback system. The key idea of our method is to impose a constraint on the controller parameters so that the zeros of resulting controller are distant from the dominant pole of closed-loop system to the left as far as the given interval. Two methods realizing the idea are suggested. We have employed the characteristic ratio assignment (CRA) in order to deal with the time response specifications. It is noted that the proposed methods are accomplished only in parameter space. Several illustrative examples are given.

• Structural Engineering and Mechanics
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• v.72 no.1
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• pp.83-97
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• 2019

In this research, the vulnerability of some reinforced concrete frames with different stories are studied based on the Park-Ang Damage Index. The damages of the frames are investigated under various earthquakes with nonlinear dynamic analysis in IDARC software. By examining the most important characteristics of earthquake parameters, the damage index and vulnerability of these frames are investigated in this software. The intensity of Erias, velocity spectral intensity (VSI) and peak ground velocity (PGV) had the highest correlation, and root mean square of displacement ($D_{rms}$) had the lowest correlation coefficient among the parameters. Then, the particle swarm optimization (PSO) algorithm was used, and the sinusoidal waves were equivalent to the used earthquakes according to the most influential parameters above. The damage index equivalent to these waves is estimated using nonlinear dynamics analysis. The comparison between the damages caused by earthquakes and equivalent sinusoidal waves is done too. The generations of sinusoidal waves equivalent to different earthquakes are generalized in some reinforced concrete frames. The equivalent sinusoidal wave method was exact enough because the greatest difference between the results of the main and artificial accelerator damage index was about 5 percent. Also sinusoidal waves were more consistent with the damage indices of the structures compared to the earthquake parameters.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.749-755
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• 2009

Support vector classification (SVC) provides more complete description of the lin-ear and nonlinear relationships between input vectors and classifiers. In this paper. we propose the sparse kernel classifier to solve the optimization problem of classification with a modified hinge loss function and absolute loss function, which provides the efficient computation and the sparsity. We also introduce the generalized cross validation function to select the hyper-parameters which affects the classification performance of the proposed method. Experimental results are then presented which illustrate the performance of the proposed procedure for classification.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.325-338
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• 1997

This paper suggests a sequence of dependence models as a statistical analysis model for vaccination data on chickenpox and discusses a method for evaluating maximum likelihood estimates of unknown parameters in the suggested model.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.219-225
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• 1998

The parameters in linear models with censored normal responses are usually estimated by the iterative maximum likelihood and least square methods. However, the iterative least square method is simple but hardly has theoretical justification, and the iterative maximum likelihood estimating equations are complicatedly derived. In this paper, we justify these methods via Wedderburn (1974)'s quasi-likelihood approach. This provides an explicit justification for the iterative least square method and also directly the iterative maximum likelihood method for estimating the regression coefficients.