• Korean Journal of Ecology and Environment
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• v.57 no.1
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• pp.1-16
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• 2024

Most wetlands worldwide have suffered from extensive human exploitation. Unfortunately they have been less explored compared to river and lake ecosystems despite their ecological importance and economic values. This is the same case in Korea. This study was aimed to estimate the assemblage attributes and distribution characteristics of benthic macroinvertebrates for fifty wetlands distributed throughout subtropical Jeju Island in 2021. A total of 133 taxa were identified during survey periods belonging to 53 families, 19 orders, 5 classes and 3 phyla. Taxa richness ranged from 4 to 31 taxa per wetland with an average of 17.5 taxa. Taxa richness and abundance of predatory insect groups such as Odonata, Hemiptera and Coleoptera respectively accounted for 67.7% and 68.2% of the total. Among them Coleoptera were the most diverse and abundant. Taxa richness and abundance did not significantly differ from each wetland type classified in accordance with the National Wetland Classification System. There were three endangered species (Clithon retropictum, Lethocerus deyrolli and Cybister (Cybister) chinensis) and several restrictively distributed species only in Jeju Island. Cluster analysis based on the similarity in the benthic macroinvertebrate composition largely classified 50 wetlands into two major clusters: small wetlands located in lowland areas and medium-sized wetlands in middle mountainous regions. All cluster groups displayed significant differences in wetland area, long axis, percentage of fine particles and macrophyte composition ratio. Indicator Species Analysis selected 19 important indicators with the highest indicator value of Ceriagrion melanurum at 63%, followed by Noterus japonicus (59%) and Polypylis hemisphaerula (58%). Our results are expected to provide fundamental information on the biodiversity and habitat environments for benthic macroinvertebrates in wetland ecosystems, consequently helping to establish conservation and restoration plans for small wetlands relatively vulnerable to human disturbance.

• Journal of Applied Biological Chemistry
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• v.66
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• pp.416-423
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• 2023

Figs has known to have antioxidant, whitening, anti-inflammatory, and antibacterial effects in their leaves, roots, stems, latex, and fruits. In order to develop cosmetic materials based on natural products, we have studied on the skin activity of the ficin in latex as well as the whitening function of the fruit extract with 70% ethanol, and used it as a raw material for released cosmetic product. However, there is little research on the demand for the development of new eutectic solvent extraction methods and its ability to control skin inflammation and psoriasis regulation. Thus, in this study, we evaluated the effectiveness of fig fruit extracts and fractions using eutectic solvent extraction for skin inflammation control and psoriasis. First, fig fruits were extracted under optimal eutectic solvent conditions and fractionated with n-hexane, dichloromethane, ethyl acetate, and butanol. First, the antioxidant activity and inhibition of nitric oxide (NO) production were confirmed in mouse macrophage RAW264.7 cells. In addition, as a result of observing the mRNA expression through RT-PCR, pro-inflammatory cytokines such as TNF-α, IL1α, and IL-1β were suppressed significantly in the hexane, dichloromethane, and ethyl acetate fractions. In addition, it was confirmed in TNF-α stimulated HaCaT keratinocyte model. Finally, chemokine CC motif ligand 20 (CCL20), marker gene of human psoriasis skin disease, was significantly suppressed in the hexane, dichloromethane, and ethyl acetate fractions. These results suggested its anti-inflammatory and skin soothing effect and the possibility of development as an excellent skin soothing natural cosmetic material in the future through future clinical trials.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.155-172
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• 2024

The COVID-19 pandemic not only posed an enormous human crisis, but also had a profound impact on firms' survival. Social distancing and global lockdown measures designed to protect human lives have paradoxically impaired the business environment. As a result, firms that sought to gain competitive advantage by leveraging external resources were cut off from the external world and faced unexpected challenges. Under these circumstances, researches were conducted in the early stage of the pandemic to explore how certain firms survived while others fell, but they were limited to re-examining business performance using traditional financial factors. However, this study aims to investigate the role of entrepreneurs' competency in crisis situations from the Resource-Based View (RBV), as such competency plays an important role in improving business performance and subsequently the probability of startups' survival. Specifically, we evaluated the performance as of end of 2019 of 1,127 startups evaluated by the Korea Technology Finance Corporation (KOTEC), which provides policy financing based on technology assessment, in 2016. We then conducted an empirical study to determine the mediating role of business performance in the relationship between entrepreneurial competencies and firm survival by verifying how many of the sample firms were still in operation at the end of June 2023, when the Korean government declared COVID-19 as an endemic. For this purpose, we defined technological, financial, and marketing competencies as the sub-factors of entrepreneurial competency, and sales growth rate and employment growth rate as the sub-factors of business performance. The results of the empirical analysis showed that technological and financial competencies of the entrepreneur had a positive impact on both business performance and firm survival, and that sales growth rate and employment growth rate mediated the relationship between technological competence and firm survival. However, the positive influence of entrepreneurs' financial competence of the survival of startups was only evident through the growth of employment. This study is the first study in South Korea to define the survival factors of startups in the context of the COVID-19 pandemic, and is expected to contribute to the theoretical and practical discussions on the importance of entrepreneurs' competency as a firms' survival factor based on RVB.

• Journal of Christian Education in Korea
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• v.78
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• pp.57-85
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• 2024

Purpose of the study: In order to utilize artificial intelligence-generated AI in educational ministry, this study analyzes the concept of artificial intelligence and generative AI and the educational theological aspects of educational ministry to find ways to efficiently utilize artificial intelligence ChatGPT in educational ministry. Contents and methods of the study: The contents of this study are. First, the contents of this study were analyzed by dividing the concepts of artificial intelligence and generative AI into the concept of artificial intelligence, types of artificial intelligence, and generative language model AI ChatGPT. Second, the educational theological analysis of educational ministry was divided into the concept of educational ministry, the goals of educational ministry, the content of educational ministry, and the direction of educational ministry in the era of artificial intelligence. Third, the plan to use artificial intelligence ChatGPT in educational ministry is to provide tools for writing sermon manuscripts, preparation tools for worship and prayer, and church education, focusing on the five functions of the early church community. It was analyzed by dividing it into tools for teaching, tools for teaching materials for believers, and tools for serving and volunteering. Conclusion and Recommendation: The conclusion of this study is that, first, when writing sermon manuscripts through artificial intelligence ChatGPT, high-quality sermon manuscripts can be written through the preacher's spirituality, faith, and insight. Second, through artificial intelligence ChatGPT, you can efficiently design and plan worship services and prepare services that serve the congregation objectively through various scenarios. Third, by using artificial intelligence ChatGPT in church education, it can be used while maintaining a complementary relationship with teachers through collaboration with human and artificial intelligence teachers. Fourth, through artificial intelligence ChatGPT, we provide a program that allows members of the church community to share spiritual fellowship, a plan to meet the needs of church members and strengthen interdependence, and an attitude of actively welcoming new people and respecting diversity. It provides useful materials that can play an important role in giving, loving, serving, and growing together in the love of Christ. Lastly, through artificial intelligence ChatGPT, we are seeking ways to provide various information about volunteer activities, learning support for children and youth in the community, mentoring-related programs, and playing a leading role in forming a village community in the local community.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.