• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.64-70
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• 2018

The development of weapon systems (or components) is hindered by the number of tests due to the limited development period and cost, which reduces the scale of accumulated data related to failures. Nevertheless, because a large amount of failure data and maintenance details during the operational period are managed by computerized data, the cause of failure of weapon systems (or components) can be analyzed using the data. On the other hand, analyzing the failure and maintenance details of various weapon systems is difficult because of the variation among groups and companies, and details of the cause of failure are described as unstructured text data. Fortunately, the recent developments of big data processing technology, machine learning algorithm, and improved HW computation ability have supported major research into various methods for processing the above unstructured data. In this paper, unstructured data related to the failure / maintenance of defense weapon systems (or components) is presented by applying doc2vec, a machine learning technique, to analyze the failure cases.

• Molecular & Cellular Toxicology
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• v.5 no.3
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• pp.250-256
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• 2009

Toxicogenomics using microarray technology offers the ability to conduct large-scale detections and quantifications of mRNA transcripts, particularly those associated with alterations in mRNA stability or gene regulation. In this study, we developed the HazChem Human Array V2 using the Agilent Sure-Print technology-based custom array, which is expected to facilitate the identification of environmental toxicants. The array was manufactured using 600 VOCs and PAHs-specific genes identified in previous studies. In order to evaluate the viability of the manufactured HazChem human array V2, we analyzed the gene expression profiles of 9 environmental toxicants (6 VOCs chemicals and 3 PAHs chemicals). As a result, nine toxicants were separated into two chemical types-VOCs and PAHs. After the chip validations with VOCs and PAHs, we conducted an expression profiling comparison of additional chemical groups (POPs and EDCs) using data analysis methods such as hierarchical clustering, 1-way ANOVA, SAM, and PCA. We selected 58 genes that could be classified into four chemical types via statistical methods. Additionally, we selected 63 genes that evidenced significant alterations in expression with all 13 environmental toxicants. These results suggest that the HazChem Human Array V2 will expedite the development of a screening system for environmentally hazardous materials at the level of toxicogenomics in the future.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.1
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• pp.207-228
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• 2013

Due to the advance of scholarly communication, the field of open access has been studied over the last decade. The purpose of this study is to analyze and demonstrate the field of open access via co-word analysis. The data set was collected from Web of Science citation database during the period from January 1998 to July 2012 using the Topic category. A total of 479 journal articles were retrieved and 8,643 noun keywords were extracted from the titles and abstracts. In order to achieve the purpose of this study, network analysis, clustering analysis and multidimensional scaling mapping were used to examine the domain and the sub-domains of open access field. 18 clusters in the network analysis are recognized and 4 clusters are shown in the map of multidimensional scaling. In addition, the centrality analysis in the weighted networks was used to explore the significant keywords in this field. The results of this study are expected to demonstrate and guide the intellectual structure and new approaches of open access field.

• Journal of Ginseng Research
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• v.35 no.1
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• pp.86-91
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• 2011

Ginsenoside (G)-F1 is an enzymatic metabolite generated from G-Rg1. Although this metabolite has been reported to suppress platelet aggregation and to reduce gap junction-mediated intercellular communication, the modulatory activity of G-F1 on the functional role of skin-derived cells has not yet been elucidated. In this study, we evaluated the regulatory role of G-F1 on the cellular responses of B16 melanoma cells. G-F1 strongly suppressed the proliferation of B16 cells up to 60% at 200 ${\mu}g/mL$, while only diminishing the viability of HEK293 cells up to 30%. Furthermore, G-F1 remarkably induced morphological change and clustering of B16 melanoma cells. The melanin production of B16 cells was also significantly blocked by G-F1 up to 70%. Interestingly, intracellular signaling events involved in cell proliferation, migration, and morphological change were up-regulated at 1 h incubation but down-regulated at 12 h. Therefore, our results suggest that G-F1 can be applied as a novel anti-skin cancer drug with anti-proliferative and anti-migration features.

• Microbiology and Biotechnology Letters
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• v.47 no.1
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• pp.25-33
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• 2019

Lactobacillus rhamnosus BFE5264, isolated from a Maasai fermented milk product ("kule naoto"), was previously shown to exhibit bile acid resistance, cholesterol assimilation, and adhesion to HT29-MTX cells in vitro. In this study, we re-annotated and analyzed the previously reported complete genome sequence of strain BFE5264. The genome consists of a circular chromosome of 3,086,152 bp and a putative plasmid, which is the largest one identified among L. rhamnosus strains. Among the 2,883 predicted protein-coding genes, those with carbohydrate-related functions were the most abundant. Genome analysis of strain BFE5264 revealed two consecutive CRISPR regions and no known virulence factors or antimicrobial resistance genes. In addition, previously known highly variable regions in the genomes of L. rhamnosus strains were also evident in strain BFE5264. Pairwise comparison with the most studied probiotic strain L. rhamnosus GG revealed strain BFE5264-specific deletions, probably due to insertion sequence-mediated recombination. The latter was associated with loss of the spaCBA pilin gene cluster and exopolysaccharide biosynthetic genes. Comparative genomic analysis of the sequences from all available L. rhamnosus strains revealed that they were clustered into two groups, being within the same species boundary based on the average nucleotide identities. Strain BFE5264 had a sister group relationship with the group that contained strain GG, but neither ANI-based hierarchical clustering nor core-gene-based phylogenetic tree construction showed a clear distinctive pattern associated with the isolation source, implying that the genotype alone cannot account for their ecological niches. These results provide insights into the probiotic mechanisms of strain BFE5264 at the genomic level.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.191-199
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• 2023

In this paper, we propose a method to extract the features of five sensor-only facilities built as infrastructure for autonomous cooperative driving, which are from point cloud data acquired by LiDAR. In the case of image acquisition sensors installed in autonomous vehicles, the acquisition data is inconsistent due to the climatic environment and camera characteristics, so LiDAR sensor was applied to replace them. In addition, high-intensity reflectors were designed and attached to each facility to make it easier to distinguish it from other existing facilities with LiDAR. From the five sensor-only facilities developed and the point cloud data acquired by the data acquisition system, feature points were extracted based on the average reflective intensity of the high-intensity reflective paper attached to the facility, clustered by the DBSCAN method, and changed to two-dimensional coordinates by a projection method. The features of the facility at each distance consist of three-dimensional point coordinates, two-dimensional projected coordinates, and reflection intensity, and will be used as training data for a model for facility recognition to be developed in the future.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.35-43
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• 2013

As texture images have become prevalent throughout a variety of industrial applications, copyright protection of these images has become important issues. For this reason, this paper proposes a color-texture image watermarking algorithm utilizing texture properties inherent in the image. The proposed algorithm selects suitable blocks to embed a watermark using the energy and homogeneity properties of the grey level co-occurrence matrices as inputs for the fuzzy c-means clustering algorithm. To embed the watermark, we first perform a discrete wavelet transform (DWT) on the selected blocks and choose one of DWT subbands. Then, we embed the watermark into discrete cosine transformed blocks with a gain factor. In this study, we also explore the effects of the DWT subbands and gain factors with respect to the imperceptibility and robustness against various watermarking attacks. Experimental results show that the proposed algorithm achieves higher peak signal-to-noise ratio values (47.66 dB to 48.04 dB) and lower M-SVD values (8.84 to 15.6) when we embedded a watermark into the HH band with a gain factor of 42, which means the proposed algorithm is good enough in terms of imperceptibility. In addition, the proposed algorithm guarantees robustness against various image processing attacks, such as noise addition, filtering, cropping, and JPEG compression yielding higher normalized correlation values (0.7193 to 1).

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.1
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• pp.111-134
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• 2016

The purpose of this study is to investigate and compare the intellectual structure of cardiovascular research area in Korea and the United States. For the purpose of this study, a data set was collected; one journal Korean Circulation Journal is in Korea and two journals Circulation, and Circulation Research are in the United States. Based on the frequency of citation counts, 45 authors and 53 authors were selected for author co-citation analysis. By multidimensional scaling, clustering, and factor analyses, the results demonstrate that researchers in both countries commonly tend to work on several, rather than focus on certain sub-areas. In both countries, the core areas are revealed as 'cardiovascular disease treatment', 'cardiovascular disease diagnose', 'cardiovascular disease fundamentals', and 'cardiovascular disease preventives'. One of distinctive differences between two is that research in Korea is likely to focus on clinical medicines while research in the United States tends to be on fundamental medicines. While the area of 'Disorders of Rhythm' is revealed in Korea, 'Pharmacology of the Cardiovascular System' area is found in the United States. In addition, the sub-areas of fundamental medicines such as 'Epidemiology of Cardiovascular Disease', 'Biology', 'Biochemistry', 'Physiology' are revealed distinctively in the United States.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.579-588
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• 2013

This paper proposes an effective watermarking approach for copyright protection of fire video images. The proposed watermarking approach efficiently utilizes the inherent characteristics of fire data with respect to color and texture by using a gray level co-occurrence matrix (GLCM) and fuzzy c-means (FCM) clustering. GLCM is used to generate a texture feature dataset by computing energy and homogeneity properties for each candidate fire image block. FCM is used to segment color of the fire image and to select fire texture blocks for embedding watermarks. Each selected block is then decomposed into a one-level wavelet structure with four subbands [LL, LH, HL, HH] using a discrete wavelet transform (DWT), and LH subband coefficients with a gain factor are selected for embedding watermark, where the visibility of the image does not affect. Experimental results show that the proposed watermarking approach achieves about 48 dB of high peak-signal-to-noise ratio (PSNR) and 1.6 to 2.0 of low M-singular value decomposition (M-SVD) values. In addition, the proposed approach outperforms conventional image watermarking approach in terms of normalized correlation (NC) values against several image processing attacks including noise addition, filtering, cropping, and JPEG compression.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.133-141
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• 2021

This research suggests a design process that effectively complements the human-centered design through an objective data-driven approach. The subjective human-centered design process can often lack objectivity and can be supplemented by the data-driven approaches to effectively discover hidden user needs. This research combines the data mining analysis with co-design process and verifies its applicability through the case study on the smart heating jacket. In the data mining process, the clustering can group the users which is the basis for selecting the target groups and the decision tree analysis primarily identifies the important user perception attributes and values. The broad point of view based on the data analysis is modified through the co-design process which is the deeper human-centered design process by using the developed workbook. In the co-design process, the journey maps, needs and pain points, ideas, values for the target user groups are identified and finalized. They can become the basis for starting new product development.