• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.125-130
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• 2019

This research is about alternative measure of main components for sprinkler system like automatic wet pipe sprinkler system, dry pipe sprinkler system, pre-action sprinkler system, vacuum sprinkler system, deluge sprinkler system, and so on. By replacing the alarm check valve, dry valve, pre-operated valve, and deluge open valve with a solenoid valve, it be can be simplifed the various processes of the manufacturing process into one process, it creates an environment in which one standardized product can be produced simultaneously on a single machine. Therefore, it could improve the price competitiveness of products, reduce the maintenance cost, and help the adaptability of new sprinkler systems in the future. There is a benefit when it comes to apply to sprinkler system. Only replace the valve which is used to control primary and secondary valve such as wet, dry, pre operated, vacuum, deluge system valve. Other components such as retarding chambers, automatic air compressors, accelerators or adjusters, supervisory panels, vacuum pumps, and manual starters can be used as they are, so they can be easily applied to existing sprinkler system. It is needed to legal and institutional study for solenoid valve applied sprinkler system to commercialize.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.61-70
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• 2019

The The government has recently announced its mid- to long-term plans for promoting art. With the advent of the 4th industrial revolution, contemporary art contents that are integrated with Intelligent Information Technologies such as Artificial Intelligence (AI), Virtual Reality (VR), and Big Data are being introduced, and social interest in humanities and creative convergence is rising. In addition, the industrialization of the art market is expanding amid the rising popularity of art among the general public and the growing interest of art as an investment replacement system, along with the strengthening of the creative personality education of our Education Ministry. Therefore, it is necessary to establish a strategy for transparency and revitalization of the art market by providing comprehensive information such as search functions, analysis data, and criticism by writer and price. This paper has established an information system plan for the establishment of an online supply system for art transaction information, providing auction transaction information for art market, providing report and news for art market, providing public relations platform, and providing art market analysis service and membership relationship management service. To this end, the future model was established through environmental analysis and focus analysis of the art market, and strategic tasks and implementation plans were established accordingly.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.85-99
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• 2021

Graphene, called the "dream material" is drawing attention as a groundbreaking new material that will lead the era of the 4th Industrial Revolution. Graphene has high strength, excellent electrical and thermal conductivity, excellent optical permeability, and excellent gas barrier properties. In this paper, as the South Korean government recently announced Green New Deal and Digital New Deal policy, we analyze graphene technology, which is also attracting attention for its application to Corona 19 biosensor, to understand its national R&D trend and knowledge structure, and to explore the possibility of its application. Firstly, 4,054 cases of national R&D project information for the last 10 years are collected from the National Science & Technology Information Service(NTIS) to analyze the trend of graphene-related R&D. Besides, projects classified as green technology are analyzed concerning the government's Green New Deal policy. Secondly, text mining analysis is conducted by collecting 500 recent graphene-related articles from e-newspapers. According to the analysis, the field with the largest number of projects was found to be high-efficiency secondary battery technology, and the proportion of total research funds was also the highest. It is expected that South Korea will lead the development of graphene technology in the future to become a world leader in diverse industries including electric vehicles, cellular phone batteries, next-generation semiconductors, 5G, and biosensors.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.376-387
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• 2021

This study is to analyze the research trends related to the 'glass ceiling' phenomenon using big data analysis methods and to suggest social implications. To analyze the research trends of 'glass ceiling', the historical event that broke the 'glass ceiling' was set as an important issue, and keywords were collected by dividing park's term into three. Before, throughout and after, her term. As a result of frequency analysis, research was conducted based on 'public servants' which was selected as the main keyword in the first period, while 'women's work family compatibility' was chosen as the main keyword group in the second period. In the third period, keywords for women's occupational groups were being diversified. As a result of applying CONCOR techniques to make the studied main topics grouped, we were able to confirm that the main issues were the differentiating factors, the customary gender discrimination culture, the jobs aimed for studying, the work-family balance, the glass ceiling and the organizational performance adjustment factors, the public sector, organizational performance, and the private sector. Besides work-family compatibility support system, it was suggested as a social implication that research on improving the system to resolve the glass ceiling factor and to expand the target jobs to give solutions to real-life issues were needed, and also suggested that research on the 'glass ceiling' which the general public perceives through social medias or articles in the news, was needed in the future.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.575-585
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• 2022

Negative perceptions about corporate social responsibility (CSR) crises and repeated crises are increasing. It is necessary to examine the effects of a proactive strategy of disclosing crisis information against the negative perceptions. The research is intended to analyze ability-based trust, and benevolence-based trust by crisis type, crisis history, and timing of crisis disclosure. In this regard, a 2 (crisis history: present vs. absent) x 2 (crisis type: corporate ability crisis vs CSR crisis) x 2 (timing of crisis disclosure: stealing thunder vs thunder) between-groups design experiment was conducted. Research results show crisis type and crisis history have significant interaction effects on ability-based trust. In the CSR crisis, the case with crisis history shows lower ability-based trust than the case without crisis history. Timing of crisis disclosure showed significant interactions with crisis history and crisis type. The stealing thunder strategy heigntened ability-based trust and benevolence-based trust against the CSR crises and the cases without crisis history more than the corporate ability crises and the cases with crisis history. Considering that the stealing thunder strategy is more effective with the CSR crises than the corporate ability crises, the research results suggest that future CSR crisis responses should prepare active disclosure of crisis information before news media disclosure of such information.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.199-204
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• 2022

The purpose of this study is to broaden the understanding of the Security Services Industry Act, and also to examine the meanings of various phenomena by analyzing the media report big data rather than the researchers' perspective on the Security Services Industry Act. In the research method, this study searched for a keyword 「Security Services Industry Act」 that prescribes the security work as an important subject of crime prevention and maintenance of public order in Korea. The data was searched from 1990 to 2021 the BIG KINDS could provide. Also, for the concrete analysis during the period of data search, it was divided into settlement period(1976~2001), growth period-quantitative(2002~2012), and growth period-qualitative(2013~2021). In the results of this study, the media report perception of the Security Services Industry Act is continuously emphasizing the social roles and importance of private security according to the flow of time. The consequent marketability of private security will play great roles in the protection of people's lives and properties in the combination with various other industries in the future. However, the private security industry that provides public peace service together with the police, could be rising as an element that hinders the development of private security industry because of various social issues caused by legal regulations and illegal problems, so it would be necessary to more strengthen its responsibility and roles accordingly.

• Journal of Science Education
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• v.46 no.3
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• pp.223-236
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• 2022

The purpose of this study is to investigate pre-service elementary teachers' awareness on the sources of microplastics. The participants were 75 male and 91 female undergraduates. A 15-item survey questionnaire was developed based on prior researches regarding microplastics emission sources and were modified through expert review and preliminary research. The survey results show that over 80% of the respondents had heard of microplastics before through news, internet, TV, etc. However, they tended not to be aware that things such as lab coats, wet tissue, dust protective mask, or paper cup were made of microplastics-causing substances. For the questions on the expected situation of microplastics contamination, the frequency of their choices were relatively low in 'Tires of cars running are worn out' and 'The gum stuck to the floor becomes smaller.' These results show that many of them were not aware that synthetic fiber or synthetic rubber was one of the microplastics emission sources. Gender differences were found in the attitudes toward microplastics problems. Female students are more interested in the issues and are more willing to participate in the solution, and recognize the need for more education on microplastics. The implications and future directions for science education were discussed.

• SUVANNABHUMI
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• v.10 no.2
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• pp.181-213
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• 2018

How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region's rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, "Area Studies" more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region's "Big Data", while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT's work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA's "soft power". That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.57-67
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• 2024

This research investigates training methods for large language models to accurately identify sentiments and comprehend information about increasing and decreasing fluctuations in the financial domain. The main goal is to identify suitable datasets that enable these models to effectively understand expressions related to financial increases and decreases. For this purpose, we selected sentences from Wall Street Journal that included relevant financial terms and sentences generated by GPT-3.5-turbo-1106 for post-training. We assessed the impact of these datasets on language model performance using Financial PhraseBank, a benchmark dataset for financial sentiment analysis. Our findings demonstrate that post-training FinBERT, a model specialized in finance, outperformed the similarly post-trained BERT, a general domain model. Moreover, post-training with actual financial news proved to be more effective than using generated sentences, though in scenarios requiring higher generalization, models trained on generated sentences performed better. This suggests that aligning the model's domain with the domain of the area intended for improvement and choosing the right dataset are crucial for enhancing a language model's understanding and sentiment prediction accuracy. These results offer a methodology for optimizing language model performance in financial sentiment analysis tasks and suggest future research directions for more nuanced language understanding and sentiment analysis in finance. This research provides valuable insights not only for the financial sector but also for language model training across various domains.

• Journal of Industrial Convergence
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• v.22 no.6
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• pp.51-59
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• 2024

The purpose of the paper is to suggest government policies that are practically helpful to small business owners in pandemic situations such as COVID-19. To this end, keyword frequency analysis and word cloud analysis of text mining analysis were performed by crawling news articles centered on the keywords "COVID-19 Support for Small Businesses", "The Impact of Small Businesses by Response System to COVID-19 Infectious Diseases", and "COVID-19 Small Business Economic Policy", and major issues were identified through LDA topic modeling analysis. As a result of conducting LDA topic modeling, the support policy for small business owners formed a topic label with government cash and financial support, and the impact of small business owners according to the COVID-19 infectious disease response system formed a topic label with a government-led quarantine system and an individual-led quarantine system, and the COVID-19 economic policy formed a topic label with a policy for small business owners to acquire economic crisis and self-sustainability. Focusing on the organized topic label, it was intended to provide basic data for small business owners to understand the damage reduction policy for small business owners and the policy for enhancing market competitiveness in the future pandemic situation.