• 품질경영학회지
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• 제26권3호
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• pp.130-140
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• 1998

Studies present a guide to parameter estimation of software reliability models using SAS JMP. In this paper, we consider only software reliability growth model(SRGM), where mean value function has a S-shaped growth curve, such as Yamada et al. model, and ohba inflection model. Besides these stochastic SRGM, deterministic SRGM's, by fitting Logistic and Gompertz growth curve, have been widely used to estimate the error content of software systems. Introductions or guide lines of JMP are concerned. Estimation of parameters of Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is discussed, along with the variability in the estimates or error sum of squares. This paper have shown that JMP can be an effective tool I these research.

• 대한의용생체공학회:의공학회지
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• 제2권1호
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• pp.31-38
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• 1981

The objective of the present study was to develop an equivalent circuit model of glucose kinetics including the hepatic glucose balance functions which were neglected in the previous compartmental models. Using this circuit model, the insulin resistivity parameter and hepatic glucose sensitivity parameter were estimated in optimal fitting of the model based data of glucose and insulin concentration to the reported clinical intravenous glucose tolerance test(IVGTT) data in normal and diabetic subjects. The addition of the hepatic function in the model has improved the overall performance of the simulation. Also, the computed tissue insulin resistivity and the hepatic glucose sensitivity are shown to be significant in distinguishin four clinical groups of normal and diabetic groups.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.623-625
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• 1998

This paper focuses on the fast convergence in nonlinear parameter optimization which is necessary for the fitting of nonlinear models to data. The simulated annealing(SA) and genetic algorithm(GA), which are widely used for combinatorial optimization problems, are stochastic strategy for search of the ground state and a powerful tool for optimization. However, their main disadvantage is the long convergence time by unnecessary extra works. It is also recognised that gradient-based nonlinear programing techniques would typically fail to find global minimum. Therefore, this paper develops a modified SA which is the SDS(Stochastic deterministic stochastic) algorithm can minimize cost function of optimal problem.

• Computational Structural Engineering : An International Journal
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• 제2권1호
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• pp.1-10
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• 2002

Information on the distribution of the basic random variables is essential for the accurate evaluation of structural reliability. The usual method for determining the distribution is to fit a candidate distribution to the histogram of available statistical data of the variable and perform appropriate goodness-of-fit tests. Generally, such candidate distributions would have two parameters that may be evaluated from the mean value and standard deviation of the statistical data. In the present paper, a-parameter Gamma distribution, whose parameters can be directly defined in terms of the mean value, standard deviation and skewness of available data, is suggested. The flexibility and advantages of the distribution in fitting statistical data and its significance in structural reliability evaluation are identified and discussed. Numerical examples are presented to demonstrate these advantages.

• Structural Engineering and Mechanics
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• 제28권3호
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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.

• 한국생산제조학회지
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• 제21권1호
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• pp.76-84
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• 2012

This paper presents the measurement system of arrow's point of impact using laser scan camera and describes the image calibration method. The calibration process of distorted image is primarily divided into explicit and implicit method. Explicit method focuses on direct optical property using physical camera and its parameter adjustment functionality, while implicit method relies on a calibration plate which assumed relations between image pixels and target positions. To find the relations of image and target position in implicit method, we proposed the performance criteria based polynomial theorem model that overcome some limitations of conventional image calibration model such as over-fitting problem. The proposed method can be verified with 2D position of arrow that were taken by SICK Ranger-D50 laser scan camera.

• Bulletin of the Korean Chemical Society
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• 제18권9호
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• pp.976-981
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• 1997

The magnetic susceptibilities of molybdenum ions with 4d1 electronic configuration in the octahedral crystal field were calculated on the basis of ligand field theory. The experimental magnetic susceptibilities for molybdenum ions, which are stabilized at the octahedral site in the perovskite lattice of Ba2ScMoⅤO6 and Sr2YMoⅤO6, were compared with the theoretical ones. We have tried to fit their temperature dependence of magnetic susceptibility with ligand field parameters, spin-orbit coupling constant ζSO, and orbital reduction parameter κ according to intermediate field coupling and strong field theory. Strong field coupling theory could not explain experimental curves without unrealistically large axial ligand field, since it ignores the mixing up between different state via spin-orbit interaction and ligand field. On the other hand, the intermediate field coupling theory could successfully reproduce experimental data in octahedral and trigonal ligand field. The fitting result demonstrates not only the fact that spin-orbit interaction is primarily responsible for the variation of magnetic behavior but also the fact that effective orbital overlap, enhanced by cubic crystal structure, reduces significantly orbital angular momentum as indicated by κ parameter.

• Advances in environmental research
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• 제3권2호
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• pp.131-149
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• 2014

Two different model selection indices, the Akaike information criterion (AIC) and the coefficient of determination ($R^2$), are used to discriminate competing isotherm equations for aqueous pollutant removal systems. The former takes into account model accuracy and complexity while the latter considers model accuracy only. The five types of isotherm shape in the Brunauer-Deming-Deming-Teller (BDDT) classification are considered. Sorption equilibrium data taken from the literature were correlated using isotherm equations with fitting parameters ranging from two to five. For the isotherm shapes of types I (favorable) and III (unfavorable), the AIC favors two-parameter equations which can easily track these simple isotherm shapes with high accuracy. The $R^2$ indicator by contrast recommends isotherm equations with more than two parameters which can provide marginally better fits than two-parameter equations. To correlate the more intricate shapes of types II (multilayer), IV (two-plateau) and V (S-shaped) isotherms, both indices favor isotherm equations with more than two parameters.

• Communications for Statistical Applications and Methods
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• 제29권6호
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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.

• Structural Engineering and Mechanics
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• 제91권4호
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• pp.403-416
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• 2024

The single-column pier girder bridge, due to its low engineering cost, small footprint, and aesthetic appearance, is extensively employed in urban viaducts and interchange ramps. However, its structural design makes it susceptible to eccentric loads, flexural-torsional coupling effects, and centrifugal forces, among others. To evaluate its anti-overturning performance reasonably, it is crucial to determine the reaction force of the support for the single-column pier girder bridge. However, due to the interaction between vehicle and bridge and the complexity of vibration modes, it poses a significant challenge to analyze the theory or finite element method of single-column pier girder bridges. The unit load bearing reaction coefficient method is proposed in this study to facilitate the static analysis. Numerous parameter analyses have been conducted to account for the dynamic amplification effect. The results of these analyses reveal that the dynamic amplification factor is independent of road surface roughness but is influenced by factors such as the position of the support. Based on parameter analysis, the formula of the dynamic amplification factor is derived by fitting.