• Journal of The Korean Astronomical Society
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• v.15 no.1
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• pp.9-18
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• 1982

To derive the distributions of electron density, temperature and gas-phase metal abundances within the Orion Nebula, we have performed a non-LTE analysis to the radio observations of hydrogen recombination lines and continuum flux over the frequency range from 0.1GHz to 100GHz. We have explicitly included the thermal balance condition in our analysis, hence our derived distributions have their internal consistencies. This enables us to derive the radial distribution of Oxygen and Nitrogen. The gas-phase concentrations of these cooling agents show about the solar values at the very central part of the nebula, then, decrease slowly outward, and finally become about one quarter of the solar values in the outer extended envelope. Such an outward decrease is interpreted as an outward increase of dust concentrations in the Orion.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1836-1839
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• 1997

This paper presents machine vision technique with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.179-185
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• 1997

This paper presents machine vision technique with a camera modeling that accounts for major sources of camera distortion, namely,radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to varios degrees of decentering,that is,the optical centers of lens elements are not strictly collinear. Thin prism distortion arises form imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of and to apply the line of part manufacturing.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.725-732
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• 2003

It was achieved that Rowecell test for this undisturbed sample was picked by Block sampler($\phi$:250mm, L:500mm) and hydraulic piston sampler($\phi$:76mm, L:850mm) in the marine clay of YONGYUDO and YEONGJONGDO in this research. Ratio of coefficient of consolidation was analyzed through comparison with C$\_$h/ by CPTu and C$\_$v/ and C$\_$h/ by existent consolidation test. According to analysis, coefficient of consolidation of block sample is fairly greater than coefficient of consolidation of piston sample. And the bigger diameter of undisturbed sample, sample disturbance could know decreasing. Coefficient of consolidation by Rowecell test measured more greatly than coefficient of consolidation by existent consolidation test. Rowecell test could know decreasing consolidation rate because of smear effect by Mandrel injection. Also, C$\_$h/ by CPTu shows deviation by each analysis method, selection of suitable analysis method judged by important leading in the coefficient of consolidation.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1617-1620
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• 1997

This paper describes the camera caliberation based-neural network with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distoriton causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing. The performance of proposed camera aclibration is illustrated by simulation and experiment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.179-183
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• 2002

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. radial distortion causes an inward or outward displacement of a given Image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.225-229
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• 1997

This paper describes the camera calibration based-neural network with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes and inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing. The performance of proposed camera calibration is illustrated by simulation and experiment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.65-69
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• 1997

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.117-121
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• 2001

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.64-72
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• 1998

This paper a new approach to the design of machine vision technique with a camera modeling that accounts for major sources of geometric distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering , that is , the optical centers of lens design and manufacturing as well as camera assembly. It is our propose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing. The performance of proposed vision system is illustrated by simulation and experiment.