• Journal of the Korean Society of Earth Science Education
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• v.13 no.3
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• pp.226-237
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• 2020

The purpose of the research is to analyze research trends related to climate change education by network analysis based on keywords extracted from the research title. For this purpose, 62 papers were selected from Korean Citation Index(KCI) journals published from 2011 to 2020 using such keywords as "climate change" and "climate change education" in the Research Information Sharing Service. The analysis procedure consisted of selection of analysis papers, keyword extraction and purification, and keyword network analysis and visualization. Textom, Ucinet 6.0, and NetDraw were used to analyze the frequency, degree centrality, and betweenness centrality. The results of the research showed that, first, Early 'Energy and Climate Change Education' had the highest frequency of papers examining climate change education. Second, the keywords/phrases that appeared most frequently in research on climate change education were "program" "energy," "analysis," "elementary school," "elementary school," "elementary school students," "development," and "impact." Third, the analysis of the centrality of betweenness centrality showed that the index of 'program', 'primary students' and 'primary schools' were the highest, and the largest group was 'development and effect of teaching and learning programs'. Based on these results, it was concluded that future research on climate change education needs to be examined in further detail and expanded into more specific areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.937-945
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• 2016

Recently, Rural tourism in China is developing rapidly, however, the rural tourism remains unsatisfactory due to ignoring the landscape aspect which is considered as an integral part for rural tourism. Therefore, we aim to investigate the effect of the landscape elements on vitalization of rural tourism by evaluation of the landscape elements. To this end, we made a questionnaire survery concerning importance and satisfaction of landscape elements through factor analysis, and clamp IPA analysis. As the result, 1) Regional product, safety facilities and public parking lots are the primary considerations as primary factor. 2)Traffic facilities and accommodation should reflect regional characteristics; Garbage collection facility, food and beverage facilities, network and electricity facility should be rectified and maintained; Regaining the original nature characteristics of river and lake, Securing the integrity of the visual appreciation by shelter landscape for Sewage Purification. Our study results may provide a basic reference for the development and management of rural tourism attractions in China.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.1
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• pp.181-191
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• 2013

The design process of ecological and environmental detention system located in the housing district of Sinjeong 3-jigu in Seoul are as follows. At stage one, a new dispersal detention was created in the neighborhood park located near the originally planned detention. From this, the amount of storage of this dispersal detention system was enlarged from $28,337m^3/d$, the initial storage amount, to $33,606m^3/d$ as the post storage amount, responsible to the amount of rainfall which happens every 100 years. In particular, the SSB (Sustainable Structured wetland Biotop) system, which was the New Excellent Technology verified by the Ministry of Environment (No. 258) was applied to enhance ecological functioning and water quality with the detention as a constructed wetland. At stage two, the treatment plans for non-point pollutant source occurred at the initial period of rain, flowing into the detention system were built for purifying the water of the retention pond at the base of the detentions, and the water-circulation system was designed at the dispersal detentions on the period of regular rainfalls. The non-point pollutant source flowing into detention site was calculated as $11,699m^3/d$ flowing down from seven small watersheds, which occurred at the initial period of rain. In particular the SSB systems improved the average efficiency of the water processing performance to BOD 60%, SS 90%, T-N 30%, T-P 60%. At stage three, the ecological network and biological diversity were strongly considered so that it brought the residents with amenity places. In particular, the dispersal detentions were successfully designed to restore the ecological habitat of endangered plant and animal species such as narrow-mouthed.

• Journal of Plant Biotechnology
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• v.37 no.2
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• pp.196-204
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• 2010

With the completion of genome sequencing of several organisms, attention has been focused to determine the function and functional network of proteins by proteome analysis. The recent techniques of proteomics have been advanced quickly so that the high-throughput and systematic analyses of cellular proteins are enabled in combination with bioinformatics tools. Furthermore, the development of proteomic techniques helps to elucidate the functions of proteins under stress or diseased condition, resulting in the discovery of biomarkers responsible for the biological stimuli. Ultimate goal of proteomics orients toward the entire proteome of life, subcellular localization, biochemical activities, and their regulation. Comprehensive analysis strategies of proteomics can be classified as three categories: (i) protein separation by 2-dimensional gel electrophoresis (2-DE) or liquid chromatography (LC), (ii) protein identification by either Edman sequencing or mass spectrometry (MS), and (iii) quanitation of proteome. Currently MS-based proteomics turns shiftly from qualitative proteome analysis by 2-DE or 2D-LC coupled with off-line matrix assisted laser desorption ionization (MALDI) and on-line electrospray ionization (ESI) MS, respectively, to quantitative proteome analysis. Some new techniques which include top-down mass spectrometry and tandem affinity purification have emerged. The in vitro quantitative proteomic techniques include differential gel electrophoresis with fluorescence dyes, protein-labeling tagging with isotope-coded affinity tag, and peptide-labeling tagging with isobaric tags for relative and absolute quantitation. In addition, stable isotope labeled amino acid can be in vivo labeled into live culture cells through metabolic incorporation. MS-based proteomics extends to detect the phosphopeptide mapping of biologically crucial protein known as one of post-translational modification. These complementary proteomic techniques contribute to not only the understanding of basic biological function but also the application to the applied sciences for industry.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.287-294
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• 2022

The purpose of this study is to find out consumers' perceptions of "metaverse," a newly spotlighted technology, through big data analysis as a non-face-to-face society continues after the outbreak of COVID-19. This study conducted a big data analysis using text mining to analyze consumers' perceptions of metaverse before and after COVID-19. The top 30 keywords were extracted through word purification, and visualization was performed through network analysis and concor analysis between each keyword based on this. As a result of the analysis, it was confirmed that the non-face-to-face society continued and metaverse emerged as a trend. Previously, metaverse was focused on textual data such as SNS as a part of life logging, but after that, it began to pay attention to virtual reality space, creating many platforms and expanding industries. The limitation of this study is that since data was collected through the search frequency of portal sites, anonymity was guaranteed, so demographic characteristics were not reflected when data was collected.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.284-290
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• 2023

Domestic water supply and sewage facilities are rapidly aging and maintenance difficulties such as aging of operation and management personnel are overlapping, so Digital Twin technology is attracting attention as an intelligent means of process management. Digital twin projects for domestic water treatment processes include the smart sewage treatment project promoted by the Ministry of Environment, projects independently promoted by some local governments, and digital twin purification plant projects promoted by K-water. However, the content of digital twin promotion is different for each institution. Therefore, in the water treatment process, technological standardization and step-by-step implementation methods for digital twins must be preceded to reduce trial and error in future business promotion. This study aims to provide an efficient promotion plan by prescribing the digital twin element technology and composition method in the water treatment process and reviewing the contents currently being promoted by the Ministry of Environment, local governments, and K-Water individually.

• Journal of the Korean Institute of Gas
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• v.28 no.1
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• pp.44-52
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• 2024

This study presents a novel approach to hydrogen production by biogas from organic waste without CO₂ removal. A process model was developed to reduce the costs associated with biogas pretreatment and purification processes. Through optimization of heat exchange networks, the simulation aimed to minimize process costs, maximizing hydrogen production and flue gas temperature. The results reveal that the most efficient process model maximizes the flue gas temperature while following the constraint of the number of heat exchangers. These findings hold promise for contributing to the expansion of "Biogas-to-clean hydrogen" energy conversion technology.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.179-184
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• 2024

Franchise are now a red ocean in Food industry and they need to find other options to appeal for their product, the uprising content, food tech. The franchises are working on R&D to help franchisees with the operations. Through this paper, we analyze the franchise interest on food tech and to help find the necessity of development for franchisees who are in needs with hand, not of human, but of technology. Using Textom, a big data analysis tool, "franchise" and "food tech" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 01 January, 2023 to 31 December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "food tech" was removed through the refining process, and similar keywords were grouped into the same keyword to perform analysis. As a result of the word refining process, a total of 10,049 words were derived, and among them, the top 50 keywords with the highest relevance and search frequency were selected and applied to this study. The top 50 keywords derived through word purification were subjected to TF-IDF analysis, visualization analysis using Ucinet6 and NetDraw programs, network analysis between keywords, and cluster analysis between each keyword through Concor analysis. By using big data analysis, it was found out that franchise do have interest on food tech. "technology", "franchise", "robots" showed many interests and keyword "R&D" showed that franchise are keen on developing food tech to seize competitiveness in Franchise Industry.

• IMMUNE NETWORK
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• v.16 no.1
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• pp.61-74
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• 2016

Dendritic cells (DCs) are professional antigen-presenting cells that sample their environment and present antigens to naïve T lymphocytes for the subsequent antigen-specific immune responses. DCs exist in a range of distinct subpopulations including plasmacytoid DCs (pDCs) and classical DCs (cDCs), with the latter consisting of the cDC1 and cDC2 lineages. Although the roles of DC-specific transcription factors across the DC subsets have become understood, the posttranscriptional mechanisms that regulate DC development are yet to be elucidated. MicroRNAs (miRNAs) are pivotal posttranscriptional regulators of gene expression in a myriad of biological processes, but their contribution to the immune system is just beginning to surface. In this study, our in-house probe collection was screened to identify miRNAs possibly involved in DC development and function by targeting the transcripts of relevant mouse transcription factors. Examination of DC subsets from the culture of mouse bone marrow with Flt3 ligand identified high expression of miR-124 which was able to target the transcript of TCF4, a transcription factor critical for the development and homeostasis of pDCs. Further expression profiling of mouse DC subsets isolated from in vitro culture as well as via ex vivo purification demonstrated that miR-124 was outstandingly expressed in CD24⁺ cDC1 cells compared to in pDCs and CD172α⁺ cDC2 cells. These results imply that miR-124 is likely involved in the processes of DC subset development by posttranscriptional regulation of a transcription factor(s).

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.45-51
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• 2021

With the development of deep learning, semantic segmentation methods are being studied in various fields. There is a problem that segmenation accuracy drops in fields that require accuracy such as medical image analysis. In this paper, we improved PSPNet, which is a deep learning based segmentation method to minimized the loss of features during semantic segmentation. Conventional deep learning based segmentation methods result in lower resolution and loss of object features during feature extraction and compression. Due to these losses, the edge and the internal information of the object are lost, and there is a problem that the accuracy at the time of object segmentation is lowered. To solve these problems, we improved PSPNet, which is a semantic segmentation model. The multi-scale attention proposed to the conventional PSPNet was added to prevent feature loss of objects. The feature purification process was performed by applying the attention method to the conventional PPM module. By suppressing unnecessary feature information, eadg and texture information was improved. The proposed method trained on the Cityscapes dataset and use the segmentation index MIoU for quantitative evaluation. As a result of the experiment, the segmentation accuracy was improved by about 1.5% compared to the conventional PSPNet.