• Structural Engineering and Mechanics
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• v.28 no.3
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• pp.263-280
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• 2008

Information on the distribution of the basic random variable is essential for the accurate analysis of structural reliability. The usual method for determining the distributions is to fit a candidate distribution to the histogram of available statistical data of the variable and perform approximate goodness-of-fit tests. Generally, such candidate distribution would have parameters that may be evaluated from the statistical moments of the statistical data. In the present paper, a cubic normal distribution, whose parameters are determined using the first four moments of available sample data, is investigated. A parameter table based on the first four moments, which simplifies parameter estimation, is given. The simplicity, generality, flexibility and advantages of this distribution in statistical data analysis and its significance in structural reliability evaluation are discussed. Numerical examples are presented to demonstrate these advantages.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.19-24
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• 2004

A number of creep data were collected and filed for type 316LN stainless steels through literature survey and experimental data produced in KAERI. Using these data, polynomial equations for predicting creep life were obtained for Larson Miller (L-M), Qrr-Sherby-Dorn (O-S-D) and Manson-Haferd (M-H) parametric methods. In order to find out the suitability for them, the relative standard error (RSE) and standard error of estimate (SEE) values were obtained by statistical process of creep data. The O-S-D parameter showed better fitting to creep-rupture data than the L-M or the M-H parameters, and the three parametric methods did not generate the large difference in the SEE and the RSE values.

• Journal of Magnetics
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• v.8 no.4
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• pp.153-156
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• 2003

The values of crystalline-electric-field parameters $A_{nm}$ for $RFe_{11}$Ti $H_{x}$ (R=Tb,Ho) (x=0,l) are obtained by fitting calculations to the magnetization curves along the crystal axes at 4.2 K and higher temperatures. The insertion of H element in RFe$_{11}$Ti significantly affects CEF parameters $A_{nm}$ . By using exchange field 2${\mu}$$_{B}$ $H_{ex}$ derived by inelastic neutron scattering and fitted $A_{nm}$ , the calculations reproduce the experimental curves well.

• Speech Sciences
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• v.11 no.4
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• pp.43-52
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• 2004

Model parameters in HMM based speech recognition systems are normally estimated using Maximum Likelihood Estimation(MLE). The MLE method is based mainly on the principle of statistical data fitting in terms of increasing the HMM likelihood. The optimality of this training criterion is conditioned on the availability of infinite amount of training data and the correct choice of model. However, in practice, neither of these conditions is satisfied. In this paper, we propose a training algorithm, MCE(Minimum Classification Error), to improve the performance of a speech recognizer detecting mispronunciation of a foreign language. During the conventional MLE(Maximum Likelihood Estimation) training, the model parameters are adjusted to increase the likelihood of the word strings corresponding to the training utterances without taking account of the probability of other possible word strings. In contrast to MLE, the MCE training scheme takes account of possible competing word hypotheses and tries to reduce the probability of incorrect hypotheses. The discriminant training method using MCE shows better recognition results than the MLE method does.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.241-245
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• 2015

In this work we present the results of light curve analysis for two cataclysmic variables detected recently in the SDSS project: SDSS J090350.73+330036.1 and J150240.98+333423.9. Photometric observations of the first were obtained during a superoutburst in May 2010. Our observations clearly indicate the presence of superhumps in the light curves, suggesting SDSS J090350.73+330036.1 is an SU UMa dwarf nova. We determined the period of the superhumps. We also carried out fitting using a spiral-arm model in order to determine parameters of the accretion disk, hot line, and other components of this system. Photometric observations of the second, J150240.98+333423.9, were obtained during the post-maximum decline, during April-June 2012. Photometric variability of this system has been studied in an inactive state. We obtained its parameters via a combined model fitted to the observed light curves by ${\chi}^2$ minimization.

• Steel and Composite Structures
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• v.8 no.5
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• pp.361-388
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• 2008

The Eurocode 4 presents some negative aspects in the design of composite slabs by the m-k Method or the Partial Connection Method. On one hand, the component chemical adherence is not accounted for in the connection between the profiled steel sheet and the concrete. On the other hand, the application of these methods requires some fitting parameters that must be determined by full scale tests. In this paper, the Eurocode 4 methods are compared with a method developed at the Federal Polytechnic School of Lausanne, based on pullout tests, which can be a valid alternative. Hence, in order to calculate the necessary parameters for the three methods, several tests have been performed such as the full scale test described in Eurocode 4 and pull-out tests. This last type of tests is of small dimensions and implicates lower costs. Finally, a full-scale test of a steel-concrete composite slab with a generic loading is presented, with the goal of verifying the analytical formulation.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.362-363
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• 2006

Nano-structured tungsten carbide compacts with cobalt matrices (WC-Co) offer new opportunities for achieving superior hardness and toughness combinations. A unified modeling and simulation tool has been developed to produce maps of sintering pathways from nanocrystalline WC powder to sintered nano-structured WC-Co compacts. This tool includes (1) die compaction, (2) grain growth, (3) densification, (4) sensitivity analysis, and (5) optimization. All material parameters were obtained by curve fitting based on results with two WC-Co powders. Critical processing parameters are determined based on sensitivity analysis and are optimized to minimize grain size with high density.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.163-170
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• 2012

This paper presents a DFT (Discrete Fourier Transform) based estimation algorithm for the parameters of a low-frequency oscillating signal. The proposed method estimates the parameters, i.e., the frequency, the damping factor, the mode amplitude, and the phase, by fitting a discrete Fourier spectrum with an exponentially damped cosine function. Parameter estimation algorithms that consider the spectrum leakage of the discrete Fourier spectrum are introduced. The multi-domain mode test functions are tested in order to verify the accuracy and efficiency of the proposed method. The results show that the proposed algorithms are highly applicable to the practical computation of low-frequency parameter estimations based on DFTs.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.1037-1047
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• 2012

The generalized linear mixed model(GLMM) is widely used in fitting categorical responses of clustered data. In the numerical approximation of likelihood function the normality is assumed for the random effects distribution; subsequently, the commercial statistical packages also routinely fit GLMM under this normality assumption. We may also encounter departures from the distributional assumption on the response variable. It would be interesting to investigate the impact on the estimates of parameters under misspecification of distributions; however, there has been limited researche on these topics. We study the sensitivity or robustness of the maximum likelihood estimators(MLEs) of GLMM for counts data when the true underlying distribution is normal, gamma, exponential, and a mixture of two normal distributions. We also consider the effects on the MLEs when we fit Poisson-normal GLMM whereas the outcomes are generated from the negative binomial distribution with overdispersion. Through a small scale Monte Carlo study we check the empirical coverage probabilities of parameters and biases of MLEs of GLMM.

• Bulletin of the Korean Chemical Society
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• v.15 no.2
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• pp.106-112
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• 1994

Six physical properties (molecular weight, heat capacity, side chain weight, side chain volume, standard entropy and partial molar volume) of amino acids, peptides and their derivatives were examined by molecular modeling techniques. The molecular connectivity index, Wiener distance index and ad hoc descriptor are employed as structural parameters to encode information about branching, size, cyclization, unsaturation, heteroatom content and polarizability. This paper examines the correlation of the molecular modeling techique's parameters and the physicochemical properties of amino acids and their derivatives. As a result, calculated values were in agreement with experimental data in the above six physical properties of amino acids, peptides and their derivatives and the molecular connectivity index was superior to the other indices in fitting the calculated data.