• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.357-366
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• 2001

The present paper develops a method to check the propriety of link functions for binary data. In order to parameterize a certain type of goodness of the link, a family of link functions indexed by a shape parameter is proposed. I first investigate the maximum likelihood estimation of the shape parameter as well as regression parameters and then derive their large sample behaviors of the estimators. A score test is considered to evaluate the goodness of the current link function. For illustration, I employ two families of power transformations, the modulus transformation by John and Draper (1980) and the extended power transformation by Yeo and Johnson (2000), which are appropriate to detect symmetric and asymmetric inadequacy of the selected link function. respectively.

• Journal of the Korean Society for Advanced Composite Structures
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• v.7 no.1
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• pp.39-44
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• 2016

This study analyzes gestation stall structures with high strength concrete. The ANSYS program described in this paper is effective not only because it shows good accuracy but also it shows the goodness of parameter studies by using APDL(ANSYS Parametric Design Language). We have performed the various parameter studies by thickness change. The results is presented by using contours and tables. The analysis results showed that it was effective to increase the height thickness(tz) rather than longitudinal thickness(tx).

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1997.04a
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• pp.25-32
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• 1997

The neural network was applied to identify wear debris generated from the lubricated machine moving surface. The wear test was carried out under different experimental conditions. In order to describe characteristics of debris of various shapes and sizes. The four parameter(50% volumetric diameter, aspect, roundness and reflec- tivity) of wear debris are used as inputs to the network and learned the friction condition of five values (material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network.

• Korea-Australia Rheology Journal
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• v.21 no.4
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• pp.289-297
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• 2009

We numerically analyzed flow characteristics of the polymer melt in the screw equipment using a proper modeling and investigated design parameters which have influence on the mixing performance as the capability of the screw equipment. We considered the non-Newtonian and non-isothermal flow in a single rotor equipment to investigate the mixing performance with respect to screw dimensions as shape parameter of the single rotor equipment and screw speed as process parameter. We used Bird-Carreau-Yasuda model as a viscous model of the polymer melt and the particle tracking method to investigate the mixing performance in the screw equipment and considered four mixing performance indexes: residence time distribution, deformation rate, total strain and particle standard deviation as a new mixing performance index. We compared these indexes to determine design parameters and object function. On basis of the analysis results, we carried out the optimal design by using the response surface method and design of experiments. In conclusion, the differences of results between the optimal value and numerical analysis are about 5.0%.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.42-49
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• 1998

This wear debris can be harvested from the lubricants of operating machinery and its morphology is directly related to the damage to the interacting surface from which the particles originated. The morphological identification of wear debris can therefore provide very early detection of a fault and can also often facilitate a diagnosis. The purpose of this study is to attempt the developement of intelligent system for moving condition diagnosis of the machine driving system. The four shape parameter(50% volumetric diameter, aspect, roundness and reflectivity) of war debris are used as inputs to the neural network and learned the moving condition of five values(material3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristics and recognized the moving condition and materials very well by neural network.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.12
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• pp.2165-2171
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• 1997

The analysis model is the infinite power law creep material containing the rigid inclusion with crack shape. The present analysis is performed using the complex pseudo-stress function method. The strain rate intensity factor is developed as new fracture mechanics parameter which represents the stress and strain rate distribution near a crack tip in power law creep material. The strain rate intensity factor is developed in terms of Kolosoff stress functions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.95-99
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• 1996

The form accuracy of parts has become an important parameter. Therefore dimensional tolerance and geometric tolerance are used in design to satisfy required quility and functions of parts. But the informations for machining conditions, which can satisfy the assigned geometric tolerance in design, are insufficient. The objectives of this research are to study the effects of the grinding parameters such as traverse speed, work speed, depth of cut, and dwell time on the after-ground workpiece shape, and to find out the major parameters among these parameters. Finally, a methodology is proposed for getting the optimal grinding condition for precision workpiece The results are as follows; The effects of work speed and depth of cut on workpiece shape are ignorable compared to the effect of traverse speed. These is the optimal dwell time depending on the traverse speed. The optimal dwell time is decreasing when the traverse speed is increased.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.133-140
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• 1998

The neural network was applied to identify wear debris generated from the lubricated machine surface. The wear test was carried out under different experimental conditions. In order to describe characteristics of debris of various shapes and sizes, the four shape parameter(50％ volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction condition of five values(material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristics and recognized the friction condition and materials very well by neural network.

• Proceedings of the Korean Reliability Society Conference
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• 2004.07a
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• pp.129-137
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• 2004

This paper presents an accelerated life test for burnout of tungsten filament of incandescent lamp. From failure analyses of field samples, it is shown that their root causes are local heating or hot sports in the filament caused by tungsten evaporation and wire sag. Finite element analysis is performed to evaluate the effect of vibration and impact for burnout, but any points of stress concentration or structural weakness are not found in the sample. To estimate the burnout life of lamp, an accelerated life test is planned by using quality function deployment and fractional factorial design, where voltage, vibration, and temperature are selected as accelerating variables. We assumed that Weibull lifetime distribution and a generalized linear model of life-stress relationship hold through goodness of fit test and test for common shape parameter of the distribution. Using accelerated life testing software, we estimated the common shape parameter of Weibull distribution, life-stress relationship, and accelerating factor.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.175-180
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• 1999

Generally, When we measure of object 3D surfaces with phase shifting shadow moire method, it is use of optical system consist of light source, grating, and ccd camera. At this time, it is important parameter that vertical distance of grating and camera, grating and light source, and horizontal distance of camera and light source. When use camera consist of complex lens vertical distance of grating and camera is unknown parameter. From this cause equivalent wave length of moire fringe is uncertain. In this study, We exactly obtain a vertical distance of grating and camera so improve on measurement accuracy.