• Journal of Power System Engineering
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• v.21 no.6
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• pp.86-93
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• 2017

Silicone rubber wire seals are widely used in automotive connector systems for waterproofing and so on. The purpose of this paper is to predict and evaluate the sealing performance of wire seals using finite element analysis. The material properties of the rubber seals were determined by the curve fitting of uniaxial tensile test and equibiaxial tensile test data. The response surface method was used to determine the optimum shape of the wire seal. In order to verify the accuracy and reliability of the simulations on the deformation prediction of wire seals, experiments were also carried out.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.229-232
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• 2002

This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study.

• Transactions of Materials Processing
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• v.13 no.1
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• pp.21-26
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• 2004

Instrumented indentation tests have been used for estimating material properties. In order to analyze deformation characteristics with various factors, the unloading stiffness should be properly determined from the elastic behavior. The unloading stiffness is generally obtained from the shifted power functions fitting with the experimental unloading data. However, the functions often give rise to a poor representation of actual data, and also the unloading stiffness is governed by unloading condition. In this study, both numerical and experimental conditions to obtain proper unloading stiffness were investigated. The result showed that the amount of unloading ratio and hold time played an important role in fitting the unloading curves. The current efforts can successfully provide the unloading stiffness for indentation material properties.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.30.2-30.2
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• 2010

A direct tilted-ring fitting method allows us to investigate kinematic structure of spiral galaxies. By employing the method to high-resolution HI data cubes, we can more easily trace warp characteristics of spiral galaxies than ever. In this contribution, we make use of TiRiFiC to VLA HI data cube of spiral galaxies in Virgo cluster, and present our preliminary yet interesting results. The TiRiFiC (Tilted-Ring-Fitting-Code) is publicly available code that provides 'best-fit' tilted-ring parameters (i.e. position angle and inclination) via chi-square minimization technique. We also discuss possible biases (e.g., resolution dependency) and its effect on our conclusions.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.8
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• pp.907-918
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• 2006

In this study capacitance and dielectric loss factor were measured with low-voltage signal and the simulation of equivalent circuits for the data was conducted. As the result it was shown that the equivalent circuit model considered the grain-boundary structure with semiconducting layer, dielectric layer and depletion layer was well approximated with the observed data. Various parameters were determined by a optimum curve-fitting method and could be used to analyze the characteristics of varistor. It also seems that the proposed equivalent circuit model will be adopted for other BL type varistors.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.179-187
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• 2011

The purpose of a Phase I clinical trial is to estimate the maximum tolerated dose, MTD, of a new drug. In this paper, the MTD estimation method is suggested by curve fitting the dose-toxicity data to an S-shaped curve. The suggested MTD estimation method is compared with established MTD estimation procedures using a Monte Carlo simulation study.

• Earthquakes and Structures
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• v.11 no.1
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• pp.109-127
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• 2016

This paper examines the contribution of three sources of uncertainties to probabilistic seismic behaviour of wood frame buildings, including ground motions, intensity and seismic mass. This sensitivity analysis is performed using three methods, including the traditional method based on the conditional distributions of ground motions at given intensity measures, a method using the summation of conditional distributions at given ground motion records, and the Monte Carlo simulation. FEMA P-695 ground motions and its scaling methods are used in the analysis. Two archetype buildings are used in the sensitivity analysis, including a two-storey building and a four-storey building. The results of these analyses indicate that using data-fitting techniques to obtain probability distributions may cause some errors. Linear interpolation combined with data-fitting technique may be employed to improve the accuracy of the calculated exceeding probability. The procedures can be used to quantify the risk of wood frame buildings in seismic events and to calibrate seismic design provisions towards design code improvement.

• Geomechanics and Engineering
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• v.25 no.4
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• pp.341-345
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• 2021

1D sand compression response to ko-loading experiences volume contraction from low to high effective stress regimes. Previous study suggested compressibility model with physically correct asymptotic void ratios at low and high stress levels and examined only for both remolded clays and natural clays. This study extends the validity of Enhanced Terzaghi model for different sand types complied from 1D compression data. The model involved with four parameters can adequately fit 1D sand compression data for a wide stress range. The low stress obtained from fitting parameters helps to identify the initial fabric conditions. In addition, strong correlation between compressibility and the void ratio at low stress facilitates determination of self-consistent fitting parameters. The computed tangent constrained modulus can capture monotonic stiffening effect induced by an increase in effective stress. The magnitude of tangent stiffness during large strain test should not be associated with small strain stiffness values. The use of a single continuous function to capture 1D stress-strain sand response to ko-loading can improve numerical efficiency and systematically quantify the yield stress instead of ad hoc methods.

• Elastomers and Composites
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• v.56 no.2
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• pp.79-84
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• 2021

A strain energy density function is used to characterize the hyperelasticity of rubber-like materials. Conventional models, such as the Neo-Hookean, Mooney-Rivlin, and Ogden models, are widely used in automotive industries, in which the strain potential is derived from strain invariants or principal stretch ratios. A fitting procedure for experimental data is required to determine material constants for each model. However, due to the complexities of the mathematical expression, these models can only produce an accurate curve fitting in a specified strain range of the material. In this study, a hyperelastic model for Neodymium Butadiene rubber is developed by using the Artificial Neural Network. Comparing the analytical results to those obtained by conventional models revealed that the proposed model shows better agreement for both uniaxial and equibiaxial test data of the rubber.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9731-9737
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• 2014

Large scale secular registry or surveillance systems have been accumulating vast data that allow mathematical modeling of cancer incidence and mortality rates. Most contemporary models in this regard use time series and APC (age-period-cohort) methods and focus primarily on predicting or analyzing cancer epidemiology with little attention being paid to implications for designing cancer registry, surveillance or evaluation initiatives. This research models age-specific cancer incidence rates using logistic growth equations and explores their performance under different scenarios of data completeness in the hope of deriving clues for reshaping relevant data collection. The study used China Cancer Registry Report 2012 as the data source. It employed 3-parameter logistic growth equations and modeled the age-specific incidence rates of all and the top 10 cancers presented in the registry report. The study performed 3 types of modeling, namely full age-span by fitting, multiple 5-year-segment fitting and single-segment fitting. Measurement of model performance adopted adjusted goodness of fit that combines sum of squred residuals and relative errors. Both model simulation and performance evalation utilized self-developed algorithms programed using C# languade and MS Visual Studio 2008. For models built upon full age-span data, predicted age-specific cancer incidence rates fitted very well with observed values for most (except cervical and breast) cancers with estimated goodness of fit (Rs) being over 0.96. When a given cancer is concerned, the R valuae of the logistic growth model derived using observed data from urban residents was greater than or at least equal to that of the same model built on data from rural people. For models based on multiple-5-year-segment data, the Rs remained fairly high (over 0.89) until 3-fourths of the data segments were excluded. For models using a fixed length single-segment of observed data, the older the age covered by the corresponding data segment, the higher the resulting Rs. Logistic growth models describe age-specific incidence rates perfectly for most cancers and may be used to inform data collection for purposes of monitoring and analyzing cancer epidemic. Helped by appropriate logistic growth equations, the work vomume of contemporary data collection, e.g., cancer registry and surveilance systems, may be reduced substantially.