• Journal of Korean Association for Spatial Structures
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• v.17 no.4
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• pp.123-132
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• 2017

A smart tuned mass damper (TMD) was developed to provide better control performance than a passive TMD for reduction of earthquake induced-responses. Because a passive TMD was developed decades ago, optimal design methods for structural parameters of a TMD, such as damping constant and stiffness, have been developed already. However, studies of optimal design method for structural parameters of a smart TMD were little performed to date. Therefore, parameter studies of structural properties of a smart TMD were conducted in this paper to develop optimal design method of a smart TMD under seismic excitation. A retractable-roof spatial structure was used as an example structure. Because dynamic characteristics of a retractable-roof spatial structure is changed based on opened or closed roof condition, control performance of smart TMD under off-tuning was investigated. Because mass ratio of TMD and smart TMD mainly affect control performance, variation of control performance due to mass ratio was investigated. Parameter studies of structural properties of a smart TMD was performed to find optimal damping constant and stiffness and it was compared with the results of optimal passive TMD design method. The design process developed in this study is expected to be used for preliminary design of a smart TMD for a retractable-roof spatial structure.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.283-292
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• 2008

Smoothing parameter or bandwidth plays a key role in nonparametric classification based on kernel density estimation. We consider choosing smoothing parameter in nonparametric classification, which optimize the Bayes risk. Hall and Kang (2005) clarified the theoretical properties of smoothing parameter in terms of minimizing Bayes risk and derived the optimal order of it. Bootstrap method was used in their exploring numerical properties. We compare cross-validation and bootstrap method numerically in terms of optimal order of bandwidth. Effects on misclassification rate are also examined. We confirm that bootstrap method is superior to cross-validation in both cases.

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.301-309
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• 2012

This paper proposes some alternative classes of shrinkage estimators and analyzes their properties. In particular, some new shrinkage estimators are identified and compared with Pandey (1983), Pandey and Srivastav (1985) and Jani (1991) estimators. Numerical illustrations are also provided.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.219-227
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• 2001

Another approach (multi-parameter measurement method) of interlaboratory studies of test methods is presented. When the unrestricted normal likelihood for the fixed latent variable model is unbounded, we propose a me쇙 of restricting the parameter space by formulating realistic alternative hypothesis under which the likelihood is bounded. A simulation study verified the claim of conservatism of level of significance based on assumptions about central chi-square distributed test statistics and on Bonferroni approximations. We showed a randomization approach that furnished empirical significance levels would be better than a Bonferroni adjustment.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.149-158
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• 2009

It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.672_673
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• 2009

In this paper seeks the parameter which relates with the efficiency from premium efficiency level single-phase induction motor. Also it compares with the parameters and it analyzes and an optimum parameter it seeks by FEM. Consquently, a optimal design is accomplished from the this paper. Also parameters compare efficiency. And it analyzes and studies about optimum parameter by FEM. The sample single-phase induction motor selection selected existing premium level motor. We analyze each parameter using 2-D finite element analysis (FEM). According to Study of losses and Design flow, losses and efficiency can be explain by many parameter. So this paper present optimal parameters. Finally, this paper presents the method which raises the efficiency of premium efficiency level single-phase induction motor.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.119-124
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• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.2
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• pp.112-120
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• 2016

The nonlinearity parameter is frequently measured as a sensitive indicator in damaged material characterization or tissue harmonic imaging. Several previous studies have employed the plane wave solution, and ignored the effects of beam diffraction when measuring the non-linearity parameter ${\beta}$. This paper presents a multi-Gaussian beam approach to explicitly derive diffraction corrections for fundamental and second harmonics under quasilinear and paraxial approximation. Their effects on the nonlinearity parameter estimation demonstrate complicated dependence of ${\beta}$ on the transmitter-receiver geometries, frequency, and propagation distance. The diffraction effects on the non-linearity parameter estimation are important even in the nearfield region. Experiments are performed to show that improved ${\beta}$ values can be obtained by considering the diffraction effects.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.671-674
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• 2005

The series parasitic resistances ($R_s$, $R_g$, $R_d$, $R_{sub}$) of BSIM3v3 RF MOSFET macro model were directly extracted from measured S-parameters in the GHz region by using simple 2-port parameter equations. Also, overlap capacitance and junction capacitance parameters were extracted by tuning $S_{11}$, $S_{12}$, and $S_{22}$ respectively while DC-parameters and all parasitic resistances are fixed at previously extracted values. These data are verified to be accurate by observing good correspondence between modeled and measured S-parameters up to 10GHz.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.5
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• pp.485-489
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• 2015

An accurate large-signal BSIM4 macro model including new empirical bias-dependent equations of the drain-source capacitance and channel resistance constructed from bias-dependent data extracted from S-parameters of RF MOSFETs is developed to reduce $S_{22}$-parameter error of a conventional BSIM4 model. Its accuracy is validated by finding the much better agreement up to 40 GHz between the measured and modeled $S_{22}$-parameter than the conventional one in the wide bias range.