• Bulletin of the Korean Chemical Society
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• v.8 no.1
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• pp.19-26
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• 1987

A statistical thermodynamical treatment for polymer adsorption from solution is presented. The canonical partition function for the polymer solution in the presence of a surface or an impermeable interface is formulated on the basis of usual quasi-crystalline lattice model, Bragg-Williams approximation of random mixing, and Pak's simple treatment of liquid. The present theory gives the surface excess ${\Gamma}_{exc}$ and the surface coverage ${\phi}^s_2$ of the polymer as a function of the chain length x, the Flory-Huggins parameter x, the adsorption energy parameter $x_s$, and polymer concentration $v_2$. Present theory is also applicable to the calculation of interfacial tension of polymer solution against water. For the idealized flexible polymer, interfacial tensions according to our theory fit good to the experimental data to the agreeable degrees.

• Bulletin of the Korean Chemical Society
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• v.22 no.12
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• pp.1375-1379
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• 2001

Monte Carlo simulations of hard-spheres confined in parallel hard walls have been carried out extensively at various densities and for various wall distances. The compressibility factors in the directions parallel and normal to the wall have been calculated from the radial free space distribution function (RFSDF) with the results showing that the compressibility factors normal to the wall are smaller than those in parallel direction and that a solid phase is formed in the direction normal to the wall while a fluid phase remains in the parallel direction. An order parameter is found to classify the phases whether a system (or a molecule) is in a fluid or a solid state. The compressibility factors of narrow wall are very small compared to those when the wall is put away. A plausible mechanism of the rise of sap in xylem vessel has been proposed.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.213-228
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• 2008

Using a linear loss function, this paper considers the one-sided testing problem for the exponential distribution via the empirical Bayes(EB) approach. Based on right censored data, we propose an EB test for the exponential parameter and obtain its convergence rate and asymptotic optimality, firstly, under the condition that the censoring distribution is known and secondly, that it is unknown.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.195-198
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• 2000

Sliding mode control method is popularly used for robustness to distrurbance and variance of systems internal parameter. However, one of the serious problem of this method is Chattering which occurs in neighborhood of sliding manifold. Another problem is that we cannot expect robustness before system starts sliding mode. A new tuning method of sliding manifold which changes the parameter of sliding manifold dynamically using Wavelet Neural Network is proposed in this paper. We can expect the better performance in sliding mode control by the wavelet neural networks excellent property of approximating arbitrary function for multi-resolution analysis and decrease chattering drastically.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.7 no.5
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• pp.395-407
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• 1996

In this paper, we describe the crossover of the parasitic capacitance at the interconnections for the system miniature, analyse ground capacitance and mutual capacitance due to actually coupled line in the ICs or MCMs. From the results of deviding interconnection line with infinite parts, using Green's function with image charge method and moments, we could obtain 70% decrease of system runtime parasitic inductance because of simplicity of transforming formular.

• Journal of applied mathematics & informatics
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• v.6 no.2
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• pp.487-502
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• 1999

The hydrodynamic flow between two eccentric cylinders is examined for small values of modified Reynolds number porosity parameter and the non-dimensional slip velocity parameter in the presence of a radial magnetic field. The stream function and the pres-sure distribution are calculated and the results are presented graph-ically.

• Bulletin of the Korean Mathematical Society
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• v.54 no.4
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• pp.1309-1321
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• 2017

In this paper, we present a practical Mittag Leffler stability for fractional-order nonlinear systems depending on a parameter. A sufficient condition on practical Mittag Leffler stability is given by using a Lyapunov function. In addition, we study the problem of stability and stabilization for some classes of fractional-order systems.

• Journal of the Korean Statistical Society
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• v.16 no.2
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• pp.102-112
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• 1987

This paper treats the problem of estimating an arbitrary parametric function in the case when the parameter and sample spaces are countable and the decision space is arbitrary. Using the notions of a stepwise Bayesian procedure and finite admissibility, a theorem is proved. It shows that under some assumptions, every finitely admissible estimator is unique stepwise Bayes with respect to a finite or countable sequence of mutually orthogonal priors with finite supports. Under an additional assumption, it is shown that the converse is true as well. The first can be also extended to the case when the parameter and sample space are arbitrary, i.e., not necessarily countable, and the underlying probability distributions are discrete.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.397-405
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• 1998

We develop parametric bootstrap model selection criteria in an example to fit a random sample to either a general normal distribution or a normal distribution with prespecified mean. We apply the bootstrap methods in two ways; one considers the direct substitution of estimated parameter for the unknown parameter, and the other focuses on the bias correction. These bootstrap model selection criteria are compared with AIC. We illustrate that all the selection rules reduce to the one sample t-test, where the cutoff points converge to some certain points as the sample size increases.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1253-1256
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• 1996

In this paper, a new nonlinear feedback linearization control scheme for induction motors is developed. The control scheme employs a fuzzy nonlinear identification scheme based on fuzzy basis function expansion to adoptively compensate the parameter variations, i.e. rotor resistance, mutual and self inductance etc. An important feature of the proposed control scheme is to incorporate the sliding mode controller into the scheme to speed up convergence rate. Simulation tests show the robust behavior of the proposed controller in the presence of the parameter uncertainties of the machine.