• Journal of the Korean Mathematical Society
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• v.35 no.2
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• pp.371-386
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• 1998

Let G be a compact Lie group and M a semialgebraic G space in some orthogonal representation space of G. We prove that if G is finite then M has an equivariant semialgebraic triangulation. Moreover this triangulation is unique. When G is not finite we show that M has a semialgebraic G CW complex structure, and this structure is unique. As a consequence compact semialgebraic G space has an equivariant simple homotopy type.

• Honam Mathematical Journal
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• v.39 no.1
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• pp.101-113
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• 2017

Let G be a semialgebraic group which is not necessarily compact. Let X be a proper semialgebraic G-set whose orbit space has a semialgebraic structure. In this paper we prove that X has a finite open straight G-CW complex structure.

• Fashion & Textile Research Journal
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• v.15 no.6
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• pp.1010-1017
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• 2013

Current global textiles and fashion industries have gradually shifted focus to high value-added, high sensibility, and multi-functional products based on new human-friendliness and sustainable growth technologies. Textile design CAD systems have been developed in conjunction with computer hardware and software sector advances. This study compares the patterns or images of actual woven fabrics and virtual fabrics prepared with a textile design CAD system. In this study, several weave structures (such as fancy yarn weave and patterns) were prepared with a shuttle loom. The woven textile images were taken using a CCD camera. The same weave structure data and yarn data were fed into a textile design CAD system in order to simulate fabric images as similarly as possible. Similarity Index analysis methods allowed for an analysis of the index between the actual fabric specimen and the simulated image of the corresponding fabric. The results showed that repeated small pattern weaves provide superior similarity index values than those of a fancy yarn weave that indicate some irregularities due to fancy yarn attributes. A Complex Wavelet Structural Similarity(CW-SSIM) index resulted in a better index than other methods such as Multi-Scale(MS) SSIM, and Feature Similarity(FS) SSIM, across fabric specimen images. A correlation analysis of the similarity index based on an image analysis and a similarity evaluation by panel members was also implemented.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.4
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• pp.437-445
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• 2019

After the permanent shutdown of K1 in 2017, decommissioning processes have attracted great attention. According to the current decommissioning roadmap, the dismantling of the activated components of K1 may start in 2026, following the removal of its spent fuel. Since the reactor vessel (RV) and reactor vessel internal (RVI) of K1 contain massive components and are relatively highly activated, their decommissioning process should be conducted carefully in terms of radiological and industrial safety. For achieving maximum efficiency of nuclear waste management processes for K1, we present activation analysis of the segmentation process and waste classification of the RV and RVI components of K1. For RVI, the active fuel regions and some parts of the upper and lower active regions are classified as intermediate-level waste (ILW), while other components are classified as low-level waste (LLW). Due to the RVI's complex structure and high activation, we suggest various underwater segmentation techniques which are expected to reduce radiation exposure and generate approximately nine ILW and nineteen very low level waste (VLLW)/LLW packages. For RV, the active fuel region and other components are classified as LLW, VLLW, and clearance waste (CW). In this case, we suggest in-situ remote segmentation in air, which is expected to generate approximately forty-two VLLW/LLW packages.