• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권2호
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• pp.138-143
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• 2006

In this paper, we have presented a Sequential Agglomerative Hierarchical Nested (SAHN) algorithm-based data clustering method in fuzzy inference system to achieve optimal performance of fuzzy model. SAHN-based algorithm is used to give possible range of number of clusters with cluster centers for the system identification. The axes of membership functions of this fuzzy model are optimized by using cluster centers obtained from clustering method and the consequence parameters of the fuzzy model are identified by standard least square method. Finally, in this paper, we have observed our model's output performance using the Box and Jenkins's gas furnace data and Sugeno's non-linear process data.

• 천문학회보
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• 제43권1호
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• pp.59.2-59.2
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• 2018

Recent studies of galaxy clusters have shown that the galaxy clusters in dense environment tend to have lower star formation rate in local universe with z < 1. However, this correlation is not significant in galaxy clusters with z > 1. The study of galaxy clusters around z=1 can yield insight into cosmological galaxy evolution. Nevertheless, the identification of galaxy clusters beyond the scope of immediate local universe requires wide field data in optical and near-infrared bands. By incorporating data from Canada-France-Hawaii Telescope Legacy Survey(CFHTLS) and Infrared Medium-Deep Survey(IMS), the photometric redshifts of galaxies in CFHTLS W2 field were calculated. Using spatial distribution and photometric redshifts, the galaxies in the field were divided into redshift bins. The image of each redshift bin was analyzed by measuring the number density within proper distance of 1Mpc. By comparing high density regions in consecutive redshift bins, we identified the cluster candidates and mapped the large-scale structure within the CFHTLS W2 field.

• Journal of Microbiology and Biotechnology
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• 제20권11호
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• pp.1484-1490
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• 2010

In the Streptomyces hygroscopicus JCM4427 geldanamycin biosynthetic gene cluster, five putative regulatory genes were identified by protein homology searching. Among those genes, gel14, gel17, and gel19 are located downstream of polyketide synthase genes. Gel14 and Gel17 are members of the LAL family of transcriptional regulators, including an ATP/GTP-binding domain at the N-terminus and a DNA-binding helix-turn-helix domain at the C-terminus. Gel19 is a member of the TetR family of transcriptional regulators, which generally act to repress transcription. To verify the biological significance of the putative regulators in geldanamycin production, they were individually characterized by gene disruption, genetic complementation, and transcriptional analyses. All three genes were confirmed as positive regulators of geldanamycin production. Specifically, Gel17 and Gel19 are required for gel14 as well as gelA gene expression.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2020년도 추계학술대회
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• pp.109-112
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• 2020

사람 재인식을 수행하기 위해서 많은 연구들이 진행되어 좋은 결과들을 보였다 그러나 이 결과들은 라벨이 있는 도메인에서의 지도 학습으로 얻은 결과들이었다. 라벨이 없는 도메인에서의 사람 재인식의 성능은 아직 많이 부족한 상태이다. 사람 재인식을 수행하고자 하는 목표 도메인에 반해 주어진 소스 도메인에서는 라벨이 풍부하다. 지금까지의 논문에서는 소스 도메인에서의 사람 이미지를 목표 도메인의 이미지처럼 만들어서 소스 도메인에서 높은 성능을 보이는 사람 재인식기를 목표 도메인에서도 잘 동작하도록 학습하는 방법들이 주를 이루었다. 하지만 이 방법에서는 소스 도메인의 사람 이미지를 목표 도메인의 이미지와 비슷하게 만들기만하고 사람의 신원에 대한 일관성을 유지시키지는 못하였다. 본 논문에서는 비지도 도메인 적응 사람 재인식을 수행하기 위해 클러스터 일관성(cluster consistency)을 유지하는 기법을 제안한다. 제안한 방법은 사람의 신원에 대한 일관성을 유지시켜서 사람 재인식의 성능을 높인다.

• Journal of Microbiology and Biotechnology
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• 제6권4호
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• pp.260-264
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• 1996

An isolate, 90-GT-129 was found to produce antibiotics with a selective inhibitory activity against Streptococcus pyogenes and Xanthomonas sp. The isolate formed a gray spiral aerial spore mass with smooth surface. Analysis of the cell wall acid hydrolysate of the isolate revealed presence of LL-di-aminopimelic acid, which indicates that the isolate belongs to a cell wall type Ⅰ actinomycetes. Cultural and physiological characteristics of the isolate placed it in Streptomyces rochei synonym cluster. A comparison of the isolate with 26 reference strains of Streptomyces rochei synonym demonstrated differences in physiological and cultural characteristics.

• 한국미생물·생명공학회지
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• 제25권6호
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• pp.537-545
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• 1997

The aim of the present research program was to isolate a strain of actinomycetes producing antifungal substance. Soil samples were collected from various sites in Korea and a number of actinomycetes were isolated from the soil samples by applying selective agar for actinomycetes. Among isolates, a strain (NA -52) producing antifungal substance against Pyricularia oryzae was selected. Chemotaxonomic and numerical identification were carried out for the isolate. Fifty taxonomic unit characters were tested and the data were analyzed numerically using TAXON program. The isolate was identified as a synonym of streptomyces diastaticus belong to cluster No. 19 (Streptomyces diastaticus). But it showed a low similarity to S. diastaticus in simple matching coefficients, hence it was considered as one new species in Streptomyces.

• Journal of Microbiology and Biotechnology
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• 제12권3호
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• pp.497-502
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• 2002

Thirty-nine strains of Leuconostocs found to be tolerant to $10\%$ or more garlic were selected for further identification, by comparing their whole-cell protein pattern, 16S rRNA gene (first 530 bases) sequence, cellular fatty acid composition, and carbon source metabolism. Two isolates were Identified as Leuconostoc mesenteroides and 32 others as Leuconostoc citreum. Five other strains belonging to a cluster could not be allocated to the existing species. 16S rRNA gene sequence and cellular fatty acid composition of the unidentified bacteria exhibited close similarity with Leuconostoc argentinum. The unidentified isolates were not allocated to L. argentinum, because they formed polysaccharide from sucrose, while L. argentinum strains do not. Leuconostocs tolerant to high concentration of garlic were found predominantly on garlic surface, an extreme environment which is unfit for most of other microorganisms.

• 센서학회지
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• 제32권6호
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• pp.378-385
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• 2023

Human biosignals provide essential information for diagnosing diseases such as dementia and Parkinson's disease. Owing to the shortcomings of current clinical assessments, noninvasive solutions are required. Machine learning (ML) on wearable sensor data is a promising method for the real-time monitoring and early detection of abnormalities. ML facilitates disease identification, severity measurement, and remote rehabilitation by providing continuous feedback. In the context of wearable sensor technology, ML involves training on observed data for tasks such as classification and regression with applications in clinical metrics. Although supervised ML presents challenges in clinical settings, unsupervised learning, which focuses on tasks such as cluster identification and anomaly detection, has emerged as a useful alternative. This review examines and discusses a variety of ML algorithms such as Support Vector Machines (SVM), Random Forests (RF), Decision Trees (DT), Neural Networks (NN), and Deep Learning for the analysis of complex clinical data.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.39-49
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• 2001

When an appropriate model is fitted to explain a certain categorical data, outlying cell detection plays very important role to reduce the lack of fit. There exist many statistical methods to identify outlying cells in contingency table. In this paper, correspondence analysis is applied to identify one or two outlying cells. When corresponding relationships between categories of the row and columns are explored, we find that outlying cells could be identified via the correspondence analysis map.

• Bulletin of the Korean Chemical Society
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• 제34권9호
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• pp.2635-2639
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• 2013

The rapid and accurate identification of biological agents is a critical step in the case of bio-terror and biological warfare attacks. Recently, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry has been widely used for the identification of microorganisms. In this study, we describe a method for the rapid and accurate discrimination of Bacillus anthracis spores using MALDI-TOF MS. Our direct in-situ analysis of MALDI-TOF MS does not involve subsequent high-resolution mass analyses and sample preparation steps. This method allowed the detection of species-specific biomarkers from each Bacillus spores. Especially, B. anthracis spores had specific biomarker peaks at 2503, 3089, 3376, 6684, 6698, 6753, and 6840 m/z. Cluster and PCA analyses of the mass spectra of Bacillus spores revealed distinctively separated clusters and within-groups similarity. Therefore, we believe that this method is effective in the real-time identification of biological warfare agents such as B. anthracis as well as other microorganisms in the field.