• Annual Conference of KIPS
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• 2010.04a
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• pp.251-254
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• 2010

현대사회의 전자와 물리공간의 융합인 유비쿼터스가 진행되고 있다. 이 유비쿼터스 사회가 가능하려면 모든 사물에 컴퓨터 칩인 RFID태그가 부착되어야 한다. RFID는 무선을 통하여 사물의 ID정보를 제공하며, 향후 주변의 상황정보(온도, 습도, 오염정보, 균열정보 등)까지 탐지하여 이를 실시간으로 네트워크에 연결하여 정보를 관리하는 것이다. 앞으로 이 RFID가 가정에서 모든 기기에 부착되어. 시스템화가 된다면 유비쿼터스 가정이 된다. 본 논문에서는 유비쿼터스 사회의 기술적 정의와 자동화 된 지역내 환경제어를 위한 네트웍크를 구현하기 위한 RFID/USN에 대하여 연구하였다.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2002.11a
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• pp.251-253
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• 2002

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2012.05a
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• pp.251-252
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• 2012

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.251-257
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• 2015

Rationality only based on human experience and visuals takes huge toll on nation at the time of disasters. Accordingly, it is required to convert its system into national disaster-managing system based on governmental departments effective cooperation against catastrophic emergencies. Thus, this manuscript rejects empirical model of calamity measures and provides substituting prototype based on u-Gov which utilizes UT service from the developed countries' cases. Moreover, in order to provide nation's administrative services, the paper suggests alternative for politic issues which realizes a new incorporated control towel reflecting policies.

• Bulletin of the Korean Mathematical Society
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• v.56 no.1
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• pp.245-251
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• 2019

Assume that ${\Omega}$ is a bounded domain in ${\mathbb{R}}^n$ with $n{\geq}2$. We study positive solutions to the problem, ${\Delta}u=u^p$ in ${\Omega}$, $u(x){\rightarrow}{\infty}$ as $x{\rightarrow}{\partial}{\Omega}$, where p > 1. Such solutions are called boundary blow-up solutions of ${\Delta}u=u^p$. We show that a boundary blow-up solution exists in any bounded domain if 1 < p < ${\frac{n}{n-2}}$. In particular, when n = 2, there exists a boundary blow-up solution to ${\Delta}u=u^p$ for all $p{\in}(1,{\infty})$. We also prove the uniqueness under the additional assumption that the domain satisfies the condition ${\partial}{\Omega}={\partial}{\bar{\Omega}}$.

• Toxicological Research
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• v.33 no.1
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• pp.63-69
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• 2017

Transmembrane protein 39A (TMEM39A) belongs to the TMEM39 family. TMEM39A gene is a susceptibility locus for multiple sclerosis. In addition, TMEM39A seems to be implicated in systemic lupus erythematosus. However, any possible involvement of TMEM39A in cancer remains largely unknown. In the present report, we provide evidence that TMEM39A may play a role in brain tumors. Western blotting using an anti-TMEM39A antibody indicated that TMEM39A was overexpressed in glioblastoma cell lines, including U87-MG and U251-MG. Deep-sequencing transcriptomic profiling of U87-MG and U251-MG cells revealed that TMEM39A transcripts were upregulated in such cells compared with those of the cerebral cortex. Confocal microscopic analysis of U251-MG cells stained with anti-TMEM39A antibody showed that TMEM39A was located in dot-like structures lying close to the nucleus. TMEM39A probably located to mitochondria or to endosomes. Immunohistochemical analysis of glioma tissue specimens indicated that TMEM39A was markedly upregulated in such samples. Bioinformatic analysis of the Rembrandt knowledge base also supported upregulation of TMEM39A mRNA levels in glioma patients. Together, the results afford strong evidence that TMEM39A is upregulated in glioma cell lines and glioma tissue specimens. Therefore, TMEM39A may serve as a novel diagnostic marker of, and a therapeutic target for, gliomas and other cancers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.251-260
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• 2022

Although the number of trees affected by pine wilt disease is decreasing, the affected area is expanding across the country. Recently, with the development of deep learning technology, it is being rapidly applied to the detection study of pine wilt nematodes and dead trees. The purpose of this study is to efficiently acquire deep learning training data and acquire accurate true values to further improve the detection ability of U-Net models through learning. To achieve this purpose, by using a filtering method applying a step-by-step deep learning algorithm the ambiguous analysis basis of the deep learning model is minimized, enabling efficient analysis and judgment. As a result of the analysis the U-Net model using the true values analyzed by period in the detection and performance improvement of dead pine trees of wilt nematode using the U-Net algorithm had a recall rate of -0.5%p than the U-Net model using the previously provided true values, precision was 7.6%p and F-1 score was 4.1%p. In the future, it is judged that there is a possibility to increase the precision of wilt detection by applying various filtering techniques, and it is judged that the drone surveillance method using drone orthographic images and artificial intelligence can be used in the pine wilt nematode disaster prevention project.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.251-252
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• 2007

• Proceedings of the Optical Society of Korea Conference
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• 2008.07a
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• pp.251-252
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• 2008

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2011.10a
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• pp.251-252
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• 2011