• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1243-1248
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• 2008

As development in technology of bioinformatics recently mates it possible to operate micro-level experiments, we can observe the expression pattern of total genome through on chip and analyze the interactions of thousands of genes at the same time. In this thesis, we used CDNA microarrays of 3840 genes obtained from neuronal differentiation experiment of cortical stem cells on white mouse with cancer. It analyzed and compared performance of each of the experiment result using existing DT, NB, SVM and multi-perceptron neural network classifier combined the similar scale combination method after constructing class classification model by extracting significant gene list with a similar scale combination method proposed in this paper through normalization. Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) represented the accuracy of 98.84%, which show that it improve classification performance than case to experiment using other classifier.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2259-2264
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• 2008

Significant genes are defined as genes in which the expression level characterizes a specific experimental condition. Such genes in which the expression levels differ significantly between different groups are highly informative relevant to the studied phenomenon. In this paper, first the system can detect informative genes by similarity scale combination method being proposed in this paper after normalizing data with methods that are the most widely used among several normalization methods proposed the while. And it compare and analyze a performance of each of normalization methods with multi-perceptron neural network layer. The Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) after Lowess normalization represented the improved classification performance of 98.84%.

• Journal of Ginseng Research
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• v.43 no.1
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• pp.154-160
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• 2019

Background: Compound K (CK) is an active metabolite of ginseng saponin, ginsenoside Rb1, that has been shown to have ameliorative properties in various diseases. However, its role in inflammation and the underlying mechanisms are poorly understood. In this report, the antiinflammatory role of CK was investigated in macrophage-like cells. Methods: The CK-mediated antiinflammatory mechanism was explored in RAW264.7 and HEK293 cells that were activated by lipopolysaccharide (LPS) or exhibited overexpression of known activation proteins. The mRNA levels of inflammatory genes and the activation levels of target proteins were identified by quantitative and semiquantitative reverse transcription polymerase chain reaction and Western blot analysis. Results: CK significantly inhibited the mRNA expression of inducible nitric oxide synthase and tumor necrosis factor-${\alpha}$ and morphological changes in LPS-activated RAW264.7 cells under noncytotoxic concentrations. CK downregulated the phosphorylation of AKT1, but not AKT2, in LPS-activated RAW264.7 cells. Similarly, CK reduced the AKT1 overexpression-induced expression of aldehyde oxidase 1, interleukin-$1{\beta}$, interferon-${\beta}$, and tumor necrosis factor-${\alpha}$ in a dose-dependent manner. Conclusion: Our results suggest that CK plays an antiinflammatory role during macrophage-mediated inflammatory actions by specifically targeting the AKT1-mediated signaling pathway.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.217-226
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• 2021

Based on the theory of use and satisfaction, this study investigated the strength of TikTok usage motives (entertainment, information-seeking, interaction, self-expression, and escape) and the effect of each motive on users' adherence (frequency of use, time of use). investigated. After conducting a survey on TikTok Chinese users and removing insincere answers, 101 survey results were analyzed. The analysis results are as follows: First, the intensity of motivation for using TikTok was in the following order: entertainment-seeking, information-seeking, interaction, self-expression, and escape. Among them, the motives of pursuit of entertainment and escape were higher in females than in males. And the motives of pursuit of entertainment and escape were higher in the case of women than in the case of men. Second, as a result of analyzing the effect on user adhesion, the influence of the users' entertainment pursuit motive, interaction motive, and escape motive was significant for the frequency of use, and the influence of interaction was high. Third, the influence of entertainment-seeking motives and escape motives was found to be significant for use time. This means that users often use TikTok for entertainment, interaction, and escapism, and longer TikTok usage time for entertainment or escapism.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.635-638
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• 2009

The latest, Digital art is attempt new field's Art, that is utilize variously digital media image, sound, simulation, 3D holography. A large number of Digital Art is contact with the audiance in pavilion(limit place and limit period). However, It will be possible, If Digital Art can use place digital form media even there are indoor, outdoor, anywhere. This paper analyze reciprocal action for utilize Digital Art in indoor space design, and this paper study expression about indoor design base of interactive.

• Journal of Ginseng Research
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• v.45 no.2
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• pp.354-360
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• 2021

Background: Protopanaxatriol (PPT) is a secondary intestinal metabolite of ginsenoside in ginseng. Although the effects of PPT have been reported in various diseases including cancer, diabetes and inflammatory diseases, the skin protective effects of PPT are poorly understood. Methods: HaCaT cells were treated with PPT in a dose-dependent manner. mRNA and protein levels which related to skin barrier and hydration were detected compared with retinol. Luciferase assay was performed to explore the relative signaling pathway. Western blot was conducted to confirm these pathways and excavated further signals. Results: PPT enhanced the expression of filaggrin (FLG), transglutaminase (TGM)-1, claudin, occludin and hyaluronic acid synthase (HAS) -1, -2 and -3. The mRNA expression levels of FLG, TGM-1, HAS-1 and HAS-2 were suppressed under NF-κB inhibition. PPT significantly augmented NF-κB-luc activity and upregulated Src/AKT/NF-κB signaling. In addition, PPT also increased phosphorylation of the mitogen-activated protein kinases (MAPKs) ERK, JNK and p38 and upstream MAPK activators (MEK and MKK). Furthermore, transcriptional activity of AP-1 and CREB, which are downstream signaling targets of MAPK, was enhanced by PPT. Conclusion: PPT improves skin barrier function and hydration through Src/AKT/NF-κB and MAPK signaling. Therefore, PPT may be a valuable component for cosmetics or treating skin disorders.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.100-112
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• 2021

With the recent growth of the big data technology market, interest in visualization technology has steadily increased over the past few years. Data visualization is currently used in a wide range of disciplines such as information science, computer science, human-computer interaction, statistics, data mining, cartography, and journalism, each with a slightly different meaning. Big data visualization in smart cities that require multidisciplinary research enables an objective and scientific approach to developing user-centered smart city services and related policies. In particular, spatial-based data visualization enables efficient collaboration of various stakeholders through visualization data in the process of establishing city policy. In this paper, a user-centered spatial big data visualization expression request method was derived by examining the spatial-based big data visualization expression process and principle from the viewpoint of effective information delivery, not just a visualization tool.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.175-181
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• 2022

In this study, we tested the anti-inflammatory effects of broccoli leaf hexane fraction to confirm the applicability as a functional material in food and cosmetics. This sample was extracted using 70% ethanol from Broccoli leaf and then fractionated with hexane. The production of pro-inflammatory cytokines (TNF-α, IL-4, IL-6, IL-1β), protein expression of iNOS and COX-2, phosphorylation of MAPKs (ERK, JNK, p38) and NF-κB with broccoli leaf hexane fraction were assayed on LPS-stimulated RAW264.7 cells. The broccoli leaf hexane fraction inhibited the secretion of pro-inflammatory cytokines and protein expression of iNOS and COX-2. Also, the broccoli leaf hexane fraction reduced the phosphorylation of MAPKs and NF-κB. Therefore, it is considered that th broccoli leaf hexane fraction has the potential to be used as a natural anti-inflammatory material in food and cosmetics. In the future, it is considered necessary to study the anti-inflammatory mechanism and identification of major bioactive substances.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1512-1518
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• 2021

Since single cell RNA sequencing provides the expression profiles of individual cells, it provides higher cellular differential resolution than traditional bulk RNA sequencing. Using these single cell RNA sequencing data, clustering analysis is generally conducted to find cell types and understand high level biological processes. In order to effectively process the high-dimensional single cell RNA sequencing data fir the clustering analysis, this paper uses a variational autoencoder to transform a high dimensional data space into a lower dimensional latent space, expecting to produce a latent space that can give more accurate clustering results. By clustering the features in the transformed latent space, we compare the performance of various classical clustering methods for single cell RNA sequencing data. Experimental results demonstrate that the proposed framework outperforms many state-of-the-art methods under various clustering performance metrics.

• Journal of Creative Information Culture
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• v.7 no.3
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• pp.157-165
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• 2021

As the use of various application services utilizing Web and IoT and the need for large amounts of data management expand accordingly, the importance of efficient data expression and exchange scheme and data query processing is increasing. JSON, characterized by its simplicity, is being used in various fields as a format for data exchange and data storage instead of XML, which is a standard data expression and exchange language on the Web. This means that it is important to develop indexing and query processing techniques to effectively access and search large amounts of data expressed in JSON. Therefore, in this paper, we modeled JSON data with a hierarchical structure in a tree form, and proposed indexing and query processing using the path concept. In particular, we designed an index structure using a suffix array widely used in text search and introduced simple and complex path-based JSON data query processing methods.