• Atmosphere
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• v.33 no.5
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• pp.477-492
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• 2023

Based on the new climate normals (1991~2020), annual mean, maximum and minimum temperature is 12.5℃, 18.2℃, and 7.7℃, respectively while annual precipitation is 1,331.7 mm, the annual mean wind speed is 2.0 m s^-1, and the relative humidity is 67.8% in the Republic of Korea. Compared to 1981~2010 normal, annual mean temperature increased by 0.2℃, maximum and minimum temperatures increased by 0.3℃, while the amount of precipitation (0.7%) and relative humidity (1.1%) decreased. There was no distinct change in annual mean wind speed. The spatial range of the annual mean temperature in the new normals is large from 7.1 to 16.9℃. Annual precipitation showed a high regional variability, ranging from 787.3 to 2,030.0 mm. The annual mean relative humidity decreased at most weather stations due to the rise in temperature, and the annual mean wind speed did not show any distinct difference between the new and old normals. With the addition of a warmer decade (2011~2020), temperatures all increased consistently and in particular, the increase in the maximum temperature, which had not significantly changed in previous decades, was evident. The increasing trend of annual and summer precipitation by the 2010s has disappeared in the new normals. Among extreme climate indices, MxT30 (Daily maximum temperature ≥ 33℃ days), MnT25 (Daily minimum temperature ≥ 25℃ days), and PH30 (1 hour maximum precipitation ≥ 30 mm days) increased while MnT-10 (Daily minimum temperature < -10℃ days) and W13.9 (Daily maximum wind speed ≥ 13.9 m/s days) decreased at a statistically significant level. It is thought that a detailed study on the different trends of climate elements and extreme climate indices by region should be conducted in the future.

• Korean Journal of Ecology and Environment
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• v.56 no.3
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• pp.268-279
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• 2023

Nowadays, artificial intelligence model approaches such as machine and deep learning have been widely used to predict variations of water quality in various freshwater bodies. In particular, many researchers have tried to predict the occurrence of cyanobacterial blooms in inland water, which pose a threat to human health and aquatic ecosystems. Therefore, the objective of this study were to: 1) review studies on the application of machine learning models for predicting the occurrence of cyanobacterial blooms and its metabolites and 2) prospect for future study on the prediction of cyanobacteria by machine learning models including deep learning. In this study, a systematic literature search and review were conducted using SCOPUS, which is Elsevier's abstract and citation database. The key results showed that deep learning models were usually used to predict cyanobacterial cells, while machine learning models focused on predicting cyanobacterial metabolites such as concentrations of microcystin, geosmin, and 2-methylisoborneol (2-MIB) in reservoirs. There was a distinct difference in the use of input variables to predict cyanobacterial cells and metabolites. The application of deep learning models through the construction of big data may be encouraged to build accurate models to predict cyanobacterial metabolites.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.169-175
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• 2023

This paper analyzes museum-related big data using museums and gamification using social media big data, identifies and compares the perceptions of visitors mentioned in social media, and presents ways to use gamification. Based on the collected data, this paper aims to provide data by comparing and analyzing the perception of visitors to the museum and visitors to the museum using gamification. This paper investigates the perception of visitors through social media analysis using TEXTOM, a social media analysis tool, to identify differences in perception. As a result of the analysis, it was found that compared to museums that were previously viewed in the form of exhibitions, they felt fun and interest in visiting museums using geikipication. In addition, based on the analysis results of keywords and related keywords, the perception, motivation, and type of viewing of the museum of the National Museum of Korea and the Independence Hall of Korea were confirmed. In addition, it can be seen that the sense of achievement of visitors who visited the museum using gamification is higher than that of the existing museum. It is believed that by developing and activating game-related content in future museum visits, many visitors will be able to increase their interest in the museum and feel fun and interested. The results of the study are believed to be meaningful as basic data to grasp the overall perception of visitors to the museum, and based on this, it is expected that visitors will be able to see and experience the museum in various ways.

• Journal of Practical Agriculture & Fisheries Research
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• v.26 no.1
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• pp.22-29
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• 2024

In this study, we summarized the definition of smart vegetable seedling production technology, analysis of smart seedling production system, a hardware and software configuration model for smart seedling production system, research and development trends in smart seedling production system, and proposed future research and development plans for smart seedling production technology. Smart vegetable seedling production is a data-based seedling production, management, and distribution system that utilizes 4th Industrial Revolution technology to improve seedling productivity and quality. The production of vegetable seedlings using smart seedling production technology can be efficiently managed by collecting, analyzing, and managing information on seedlings, environment, and tasks at each stage of production by linking with the smart seedling integrated management system. However, there is still a lack of standardization of seedling standards and quality for each vegetable crop to establish smart seeding production technology, as well as development of smart seedling production element technology, which requires national wide R&D support.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.1
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• pp.169-192
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• 2024

This study was conducted with the aim of providing a foundation for high-quality national place name authority data by developing Korean-specific guidelines for place name authority data in response to the need for systematic construction and standardization of authority databases. To this end, a survey of domestic and international trends and cases related to place name authority data was conducted, and the rules and guidelines of each country for establishing place name authority data were analyzed. Based on these surveys and rule analyses, the scope of concepts and terminology required to build a place name authority database were defined and the direction for the development of place name authority data guidelines was set. The analysis also determined the scope and framework of the guidelines, and how they should be referenced to existing rules. The structure of the guidelines proposed in this study is based on the original RDA and NCR. Based on the implications derived from the analysis process, the guidelines were organized and presented in terms of scope of construction, selection and recording of preferred place names, recording of variant place names, and attributes of place names to propose a technical guideline for place name authority data that fits the Korean situation. Future discussions were revealed accordingly.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.2
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• pp.1-16
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• 2024

To achieve carbon neutrality and restore the national environment, there is growing interest in policies to transform national land areas into green space, such as expanding nature-based solutions, increasing biodiversity, and improving ecosystem service functions. In addition to complying with international agreements such as the United Nations Framework Convention on Climate Change and the Convention on Biological Diversity, it is necessary to expand green spaces to achieve the 2050 Carbon Neutrality goal, which can be achieved by restoring the damaged land in an ecological way. However, it is challenging to implement green restoration in a systematic and active way due to conflicts of interest among landowners and lack of institutional support and advanced technology. Therefore, this study aims to develop a strategy to expand green restoration and implement it smoothly and systematically. This study examined the current status of green restoration in South Korea by investigating green restoration laws and systems and overseas trends, and by surveying the perceptions of 1,000 people selected from a pool of the public. The results of this study show that it is difficult to implement the green restoration efficiently because the laws related to restoration are scattered. According to the relevant legal plans, the perception and direction of restoration is to pursue a sustainable national land environment, allow people to benefit from nature, improve the quality of life, and nurture related industries and human resources. In the international community, it is mentioned that green restoration contributes to achieving the 2050 Carbon Neutrality goal, revitalizing green industries, developing and applying advanced technologies, maintaining consistency in restoration-related policies, expanding citizens' access to green spaces, and adopting nature-based solutions. Both experts and the public are aware of the seriousness of the damage to the natural environment and prefer restoration with human use rather than focusing on natural recovery. It is expected that this study will contribute to the future direction of green restoration and the implementation of tasks for the sustainable restoration of the national land environment and the zero-carbon era.

• Journal of Korean Library and Information Science Society
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• v.55 no.1
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• pp.123-143
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• 2024

In this study, we analyzed the trends in staffing changes in academic libraries over the past ten years and surveyed staff working there to assess their perceptions of staffing levels and the current criteria for staffing allocation in academic libraries. We utilized statistical data from academic libraries to analyze staffing changes from 2014 to 2023. The survey was conducted through an online questionnaire targeting library staff, and responses from 216 respondents from 4-year universities and junior colleges were analyzed. The analysis of staffing changes revealed a decrease in the average number of employees in large 4-year universities and junior colleges, with a decrease in regular positions and an increase in non-regular positions. Survey results suggest causes such as declining school-age population and admissions quotas, budget shortages in universities, and structural adjustments. The perception of staff from 4-year universities and junior colleges regarding the criteria for staffing allocation was mainly negative, suggesting improvements such as increasing and refining criteria numbers, specifying standards for full-time librarians, clarifying criteria for compliance, and enhancing enforcement of standards. The results of this study can enhance understanding of staffing situations in academic libraries and serve as fundamental data for improving staffing criteria in the future, based on an understanding of librarians' perceptions on the ground.

• Journal of Ginseng Culture
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• v.6
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• pp.13-34
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• 2024

The abolishment of the red ginseng monopoly act by the Korean government in 1996 resulted in a drastic change in the Korean ginseng industry, leading to a significant increase in the market size and consumption of ginseng products. Red ginseng is most popular type, with approximately 74% of harvested fresh ginseng being processed into various red ginseng products. Since 1997, there has been a substantial increase in the cultivation of ginseng for production of red ginseng, which, in turn, has contributed to the proliferation of ginseng processing companies. To investigate the products of ginseng manufacturing businesses, we select 200 companies primarily engaged in ginseng processing or specializing solely in ginseng. Our survey on the status of ginseng industry covered 8 different categories. 1) Root ginseng: There were 66 companies involved in manufacturing red ginseng root, accounting for 33.0% of all surveyed companies. This was followed by black ginseng root with 36 companies (18.0%) and red ginseng fine roots with 22 companies (11%). 2) Red ginseng products: A total of 144 companies were involved in manufacturing red ginseng pouches, making it the most common product category. This was closely followed by 142 companies producing pure(100%) red ginseng extract concentrate. 3) Fermented red ginseng products: Companies producing fermented red ginseng extract concentrate products were the most numerous, totaling 26. Following this, companies producing fermented red ginseng stick and pouch products were next in line. 4) Ginseng products: There were 15 companies involved in the production of ginseng products, with the majority focusing on ginseng tea. 5) Black ginseng products: Companies producing black ginseng extract concentrate were the most numerous, with 31 companies, followed by 26 companies producing black ginseng extract pouches. 6) Taegeuk ginseng products: Only 5 companies were involved in the production of taegeuk ginseng products. 7) Fermented black ginseng, and 8) Ginseng berry products: These categories are manufactured by less than 5 companies each. However, the variety in ginseng berry products suggests the potential for future growth. In the 2000s, a trend emerged with the development of new processed products aimed at enhancing the functional components of red ginseng, and these products have captured the attention of consumers. However, this study primarily focuses on black ginseng, fermented red ginseng/fermented black ginseng, and ginseng berry products as they have exerted a significant influence on the overall ginseng industry.

• Korean Association of Arts Management
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• no.50
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• pp.5-31
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• 2019

The main purpose of this study was to use Deep Learning based Topic Modeling and Semantic Network Analysis to examine research trend of arts management-related papers in korea. For this purpose, research subjects such as 'The Journal of Cultural Policy', 'The Journal of Cultural Economics', 'The Journal of Culture Industry', 'The Journal of Arts Management', and 'The Journal of Human Content', which are the registered journal of the National Research Foundation of Korea directly or indirectly related to arts management field. From 1988 to 2017, a total of 2,110 domestic journals' signature, abstract, and keyword were analyzed. We tried Big Data analysis such as Topic Modeling and Semantic Network Analysis to examine changes in trends in arts management. The analysis program used open software R and standard statistical software SPSS. Based on the results of the analysis, the implications and limitations of the study and suggestions for future research were discussed. And the potential for development of convergent research such as Arts & Artificial Intelligence and Arts & Big Data.

• Information Systems Review
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• v.20 no.2
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• pp.63-85
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• 2018

Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.