• Bulletin of the Korean Chemical Society
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• 제22권9호
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• pp.1023-1029
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• 2001

The positions of Kr atoms encapsulated in the molecular-dimensioned cavities of fully dehydrated zeolite A of unit-cell composition Cs3Na8HSi12Al12O48 (Cs3-A) have been determined. Cs3-A was exposed to 1025 atm of krypton gas at 400 $^{\circ}C$ for four days, followed by cooling at pressure to encapsulate Kr atoms. The resulting crystal structure of Cs3-A(6Kr) (a = $12.247(2)\AA$, R1 = 0.078, and R2 = 0.085) has been determined by single-crystal X-ray diffraction techniques in the cubic space group Pm3m at $21(1)^{\circ}C$ and 1 atm. In the crystal structure of Cs3-A(6Kr), six Kr atoms per unit cell are distributed over three crystallographically distinct positions: each unit cell contains one Kr atom at Kr(1) on a threefold axis in the sodalite unit, three at Kr(2) opposite four-rings in the large cavity, and two at Kr(3) on threefold axes in the large cavity. Relatively strong interactions of Kr atoms at Kr(1) and Kr(3) with Na+ ions of six-rings are observed: Na-Kr(1) = 3.6(1) $\AA$ and Na-Kr(3) = $3.08(5)\AA.$ In each sodalite unit, one Kr atom at Kr(1) was displaced $0.74\AA$ from the center of the sodalite unit toward a Na+ ion, where it can be polarized by the electrostatic field of the zeolite, avoiding the center of the sodalite unit which by symmetry has no electrostatic field. In each large cavity, five Kr atoms were found, forming a trigonal-bipyramid arrangement with three Kr(2) atoms at equatorial positions and two Kr(3) atoms at axial positions. With various reasonable distances and angles, the existence of Kr5 cluster was proposed (Kr(2)-Kr(3) = $4.78(6)\AA$ and Kr(2)-Kr(2) = $5.94(7)\AA$, Kr(2)-Kr(3)-Kr(2) = 76.9(3), Kr(3)-Kr(2)-Kr(3) = 88(1), and Kr(2)-Kr(2)-Kr(2) = $60^{\circ}).$ These arrangements of the encapsulated Kr atoms in the large cavity are stabilized by alternating dipoles induced on Kr(2) by four-ring oxygens and Kr(3) by six-ring Na+ ions, respectively.

• 대한화학회지
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• 제26권4호
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• pp.211-217
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• 1982

흑연 표면에 흡착된 Kr분자를 2D기체로 보고 2D비리알상태방정식의 넷째 비리알 계수를 cluster intergral을 이용해서 계산하였으며, 또한 Henry 상수와 둘째 및 셋째 비리알계수도 계산하였다. 그리고 이 상태방정식으로부터 흡착등온곡선을 구하여 실험결과와 비교하여 본 결과 상당히 만족스런 결과를 얻었다. Kr-고체표면 사이의 상호작용 에너지는 Lennard-Jones(12,6)퍼텐셜의 pairwise additivity를 가정하여 구하였으며, 여기에 사용한 파라미터는 ${\varepsilon}_{gs}$/k = 71.1 K, ${\varepsilon}_{gg}$/k = 170 K, ${\sigma}_{gs}$ = 354 pm 및 ${\sigma}_{gg}$ = 368 pm이다.

• 한국식품영양과학회지
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• 제30권5호
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• pp.765-769
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• 2001

향미찰벼 전분의 이화학적 특성을 알기 위하여 scanning electron microscope(SEM), 요드정색반응, differential scanning calorimetry(DSC), 그리고 산가수분해도, glucoamylase와 $\alpha$-amylase 가수분해도를 측정하였다. 향미찰벼의 전분입자는 다각형구조이며 직경 4~6$\mu\textrm{m}$였다. 호화특성으로서 호화개시온도는 59.8~62.5$^{\circ}C$였으며 향미찰벼 중 KR92021-B-B-42-3-B와 KR92021-B-B-165-1-B의 호화엔탈피값은 대체로 높았다. 향미찰벼 전분의 아밀로펙틴의 무정형 분획을 품종간 비교하기 위하여 15% H$_2$SO$_4$에 의한 산가수분해도를 측정한 결과 KR92021-B-B-5-2-B와 KR92021-B-B-42-3-B는 산가수분해도가 낮아 아밀로펙틴의 cluster 구조가 다른 품종에 비해 질서있게 나열되어 있음을 알 수 있었다. 향미찰벼 중 KR92021-B-B-5-2-B는 glucoamylase와 $\alpha$-amylase에 의한 전분가수분해도가 높은 특성을 보였다.

• Communications for Statistical Applications and Methods
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• 제22권1호
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• pp.55-67
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• 2015

An important problem in cluster analysis is the selection of variables that define cluster structure that also eliminate noisy variables that mask cluster structure; in addition, outlier detection is a fundamental task for cluster analysis. Here we provide an automated K-means clustering process combined with variable selection and outlier identification. The Automated K-means clustering procedure consists of three processes: (i) automatically calculating the cluster number and initial cluster center whenever a new variable is added, (ii) identifying outliers for each cluster depending on used variables, (iii) selecting variables defining cluster structure in a forward manner. To select variables, we applied VS-KM (variable-selection heuristic for K-means clustering) procedure (Brusco and Cradit, 2001). To identify outliers, we used a hybrid approach combining a clustering based approach and distance based approach. Simulation results indicate that the proposed automated K-means clustering procedure is effective to select variables and identify outliers. The implemented R program can be obtained at http://www.knou.ac.kr/~sskim/SVOKmeans.r.

• 응용통계연구
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• 제25권3호
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• pp.471-483
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• 2012

One of the most important problems in cluster analysis is the selection of variables that truly define cluster structure, while eliminating noisy variables that mask such structure. Brusco and Cradit (2001) present VS-KM(variable-selection heuristic for K-means clustering) procedure for selecting true variables for K-means clustering based on adjusted Rand index. This procedure starts with the fixed number of clusters in K-means and adds variables sequentially based on an adjusted Rand index. This paper presents an updated procedure combining the VS-KM with the automated K-means procedure provided by Kim (2009). This automated variable selection procedure for K-means clustering calculates the cluster number and initial cluster center whenever new variable is added and adds a variable based on adjusted Rand index. Simulation result indicates that the proposed procedure is very effective at selecting true variables and at eliminating noisy variables. Implemented program using R can be obtained on the website "http://faculty.knou.ac.kr/sskim/nvarkm.r and vnvarkm.r".

• 응용통계연구
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• 제31권4호
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• pp.517-528
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• 2018

다변량 자료에서 특이점을 검출하고, 검출된 특이점을 시각화와 연결한 R 스크립트를 제공한다. 개발된 R 스크립트는 특이점을 검출하는 방법으로서 1) Robust Mahalanobis distance, 2) High Dimensional data, 3) Density-based approach 방법을 이용하였다. 특이점을 연결하면서 데이터 구조를 파악하기 위한 시각화 방법으로는 1) multidimensional scaling (MDS)와 minimal spanning tree (MST)를 K-means 군집분석과 연결하여 표시하는 방법, 2) MDS를 fviz cluster와 연결하는 방법, 3) principal component analysis (PCA)를 fviz cluster와 연결한 방법을 이용하였다. 사례분석의 예로서는 Major League Baseball (MLB) 자료에서 류현진이 적극적으로 활동하던 2013년, 2014년 투수자료를 이용하였다. 개발된 R 스트립트는 "http://www.knou.ac.kr/~sskim/ddpoutlier.html (R 스크립트와 R 패키지도 다운로드 받을 수 있다. 실행방법도 설명되어 있다.)"에서 다운받으면 된다.

• 천문학회보
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• 제44권1호
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• pp.47.3-47.3
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• 2019

We discovered 722 open clusters within 1 kpc using Gaia DR2 data. These clusters are detected in the proper motion space and confirmed on the spatial distribution with parallax information. We divided the 3628 regions and visually searched using python program. Among 722 open clusters, 430 clusters are previously unknown clusters. Catalogue of discovered clusters is unloaded on the online catalogue at https://radio.kasi.re.kr/project/shlee/. Owing to the good membership criteria, we could see the halo structure of the clusters. In that reason, the average size of the discovered cluster is about 9 times than that of previously known clusters.

• 한국식물병리학회:학술대회논문집
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• 한국식물병리학회 2003년도 정기총회 및 추계학술발표회
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• pp.142-143
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• 2003

Ammi majus (white lace flower, Unbelliferae) is an ornamental plant used for cut-flower arrangements worldwide. A potyvirus was isolated from its leaves with mosaic and chlorotic symptoms in the cultivated field of Chiba, Japan. Compared with Japanese homuort mosaic virus (JHMV) previously isolated from Cryptotaenia japonica, it showed similar characteristics in host reactions and molecular properties. The nucleotide sequences of coat protein and 3'- nontranslated region were highly homologous and shared 87％ and 91％ identities with those of JHMV, respectively. This virus was thus supposed to be an isolate of JHMV and designated as JHMV-Am. Phylogenetic tree was constructed using CP nucleotide sequences of the two isolates and other potyviruses previously reported. JHMV-Am and JHMV fell into a cluster with Korean strain of Zantedeschia mosaic virus (ZaMV-KR). However, low identity in amino acid sequences was found in the termini of CP genes between the two isolates of JHMV and ZaMV-KR.

• 한국컴퓨터정보학회논문지
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• 제9권4호
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• pp.33-39
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• 2004

본 논문에서는 LVQ 네트워크의 분류성능을 향상시키기 위하여 F.C.P. Net.을 이용하여 LVQ 학습알고리즘을 설계하였다. F.C.P. Net.의 입력층과 부류층 사이의 연결강도는 SOM과 LVQ 알고리즘을 이용하여 초기 참조벡터의 설정 및 학습이 가능하게 하였다. 마지막으로 패턴벡터를 부류층의 뉴런에 의해 종속부류로 분류하고, F.C.P. Net.의 부류층과 출력층 사이의 연결강도는 분류된 종속부류를 부류로 지정하는 학습을 하게 된다. 또한 부류의 수가 결정되기만 하면 입력층, 부류층, 출력층의 뉴런의 수를 결정 할 수 있도록 하였다. 제안된 학습알고리즘의 성능을 검증하기 위하여 Fisher의 Iris 데이터를 학습벡터 및 시험 벡터로 사용하여 시뮬레이션 하였고, 제안된 학습방식의 분류 성능은 기존의 LVQ와 비교되어 기존의 학습방식보다 우수한 분류성공률을 확인하였다.

• Biotechnology and Bioprocess Engineering:BBE
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• 제11권6호
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• pp.510-515
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• 2006

The putative EPA synthesis gene cluster was mined from the entire genome sequence of Shewanella oneidensis MR-1. The gene cluster encodes a PKS-like pathway that consists of six open reading frames (ORFs): ORFSO1602 (multi-domain beta-ketoacyl synthase, KS-MAT-4ACPs-KR), ORFSO1600 (acyl transferase, AT), ORFSO1599 (multi-domain beta-ketoacyl synthase, KS-CLF-DH-DH), ORFSO1597 (enoyl reductase, ER), ORFSO1604 (phosphopentetheine transferase, PPT), and ORFSO1603 (transcriptional regulator). In order to prove involvement of the PKS-like machinery in EPA synthesis, a 20.195-kb DNA fragment containing the genes was amplified from S. oneidensis MR-1 by the long-PCR method. Its identity was confirmed by the methods of restriction enzyme site mapping and nested PCR of internal genes orfSO1597 and orfSO1604. The DNA fragment was cloned into Escherichia coli using cosmid vector SuperCos1 to form pCosEPA. Synthesis of EPA was observed in four E. coli clones harboring pCosEPA, of which the maximum yield was 0.689% of the total fatty acids in a clone designated 9704-23. The production yield of EPA in the E. coli clone was affected by cultivation temperature, showing maximum yield at $20^{\circ}C$ and no production at $30^{\circ}C$ or higher. In addition, production yield was inversely proportional to glucose concentration of the cultivation medium. From the above results, it was concluded that the PKS-like modules catalyze the synthesis of EPA. The synthetic process appears to be subject to regulatory mechanisms triggered by various environmental factors. This most likely occurs via the control of gene expression, protein stability, or enzyme activity.