• Knowledge Management Research
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• v.22 no.2
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• pp.145-165
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• 2021

As of late December 2019, the spread of COVID-19 pandemic began which put the entire world in panic. In order to overcome the crisis and minimize any subsequent damage, the government as well as its affiliated institutions must maximize effects of pre-existing policy support and introduce a holistic response plan that can reflect this changing situation- which is why it is crucial to analyze social topics and people's interests. This study investigates people's major thoughts, attitudes and topics surrounding COVID-19 pandemic through the use of social media and big data. In order to collect public opinion, this study segmented time period according to government countermeasures. All data were collected through NAVER blog from 31 December 2019 to 12 December 2020. This research applied TF-IDF keyword extraction and LDA topic modeling as text-mining techniques. As a result, eight major issues related to COVID-19 have been derived, and based on these keywords, this research presented policy strategies. The significance of this study is that it provides a baseline data for Korean government authorities in providing appropriate countermeasures that can satisfy needs of people in the midst of COVID-19 pandemic.

• Journal of Wetlands Research
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• v.23 no.1
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• pp.94-105
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• 2021

Two vertical flow biofilters in series (BFS) employing synthetic fiber (FBF) followed by woodchip (WBF) was investigated in order to assess its potential as an alternative to the typical vertical-horizontal flow configuration in removing nonpoint source pollutants specifically nutrients and organics. These lab-scale column biofilters were operated for 176 days alongside three other columns that were added for control and sampling purposes. The biofilter columns were fed with either a semi-artificial piggery stormwater or artificial stormwater with specific ammonia and nitrate contents. Results reveal that the BFS was more effective than a single biofilter in removing pollutants especially nitrogen. FBF was found to remove up to 100% of ammonia from the stormwater with corresponding increase in nitrate in the outflow which shows evidence of active nitrification. Meanwhile, the succeeding vertical WBF was able to subsequently remove 77% of the nitrate. The effective reduction of nitrate in a vertical flow biofilter was believed to be due to the use of woodchip which can provide a carbon source that is required for denitrification. However, further investigation is needed to support this claim. Nonetheless, the study shows the potential of vertical flow BFS as a nitrogen removal mechanism especially in areas where enough land space for horizontal flow biofilters is limited.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.318-331
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• 2022

With the recent development of hardware computing devices and software based frameworks, machine tasks using deep learning networks are expected to be utilized in various industrial fields and personal IoT devices. However, in order to overcome the limitations of high cost device for utilizing the deep learning network and that the user may not receive the results requested when only the machine task results are transmitted from the server, Collaborative Intelligence (CI) proposed the transmission of feature maps as a solution. In this paper, an efficient compression method for feature maps with vast data sizes to support the CI paradigm was analyzed and presented through experiments. This method increases redundancy by applying feature map reordering to improve compression efficiency in traditional video codecs, and proposes a feature map method that improves compression efficiency and maintains the performance of machine tasks by simultaneously utilizing image compression format and video compression format. As a result of the experiment, the proposed method shows 14.29% gain in BD-rate of BPP and mAP compared to the feature compression anchor of MPEG-VCM.

• Trans-
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• v.13
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• pp.1-16
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• 2022

Recently, the method of contacting and purchasing NFT art has been popularly evolving, and various prospects and predictions for NFT art have emerged. The discussion of NFT art is mainly a hot topic in terms of market size, profit, and sustainability. As the transition to digital accelerated after COVID-19, almost all genres of culture and arts faced a forced transition with the topic of combining digital and technology, but in terms of profitability, it was generally difficult to guarantee positive continuity. On the other hand, the combination of art and blockchain, and the new distribution method called NFT, attracted a lot of attention by causing fundamental changes that lead to technological transformation, continuity through profit creation, and even genre expansion of visual art. The discourse on NFT and the art market is a recent phenomenon and is being discussed focusing on statistics and numerical reports through data from newspapers and art-related research institutes rather than academic analysis or research. However, discussions related to NFT art should be considered in various aspects, such as the incorporation of technology and art, changes in distribution methods, and changes in creative methods according to media changes, not just short stories of phenomena such as high prices and winning bids. In this paper, we would like to examine the impact of changes in creators and distribution methods.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.161-183
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• 2022

Opinion polls have become a powerful means for election campaigns and one of the most important subjects in the media in that they predict the actual election results and influence people's voting behavior. However, the more active the polls, the more often they fail to properly reflect the voters' minds in measuring the effectiveness of election campaigns, such as repeatedly conducting polls on the likelihood of winning or support rather than verifying the pledges and policies of candidates. Even if the poor predictions of the election results of the polls have undermined the authority of the press, people cannot easily let go of their interest in polls because there is no clear alternative to answer the instinctive question of which candidate will ultimately win. In this regard, we attempt to retrospectively grasp public opinion on the 20th presidential election by applying the 'YouTube Analysis' function of Sometrend, which provides an environment for discovering insights through online big data. Through this study, it is confirmed that a result close to the actual public opinion (or opinion poll results) can be easily derived with simple YouTube data results, and a high-performance public opinion prediction model can be built.

• Iberoamérica
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• v.23 no.2
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• pp.93-134
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• 2021

With the inauguration of the Bolsonaro administration in 2019, Brazil experienced a noticeable transformation in its policy lines at home and abroad. Limiting this change to diplomacy, it can be pointed out that pro-U.S. and anti-China diplomacy, which is clearly distinguished from the previous regimes, has begun in earnest. Nevertheless, the existing literature on this topic is limited, and it is mainly poetic reporting through the media. This paper aims to derive the main determinant of Bolsonaru's pro-U.S. and anti-China diplomatic lines by postulating the individual level of the political leader as a key variable. This study argues that his personal experience and beliefs and world views formed by his life history, and Bolsonaro's political calculation that would strengthen his domestic political support through linking between his domestic politics and diplomatic lines, ultimately influenced the dependent variable. This study is thought to be meaningful in that it enhanced the theoretical implications of not only the theory of foreign policy determinants but also the understanding of Brazil's foreign policy by explaining the factors of Brazil's pro-U.S. and anti-China diplomacy through focusing on an individual level.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.801-806
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• 2022

In the modern era, the necessity of color capability in the digital era is the demand of the era, and research on improving color practice on the subdivided digital four areas that are not in the existing practice is needed. For digital majors who are difficult to solve in existing paint color practice, classes in digital color practice in four more specialized areas are needed, and the use of efficient artificial intelligence was studied for classes in digitized color and color sense. In this paper, we tried to show the expansion of the color practice area by suggesting digital color practice and color matching method based on Photoshop artificial intelligence and big data technology that existing color and color matching were practice that only CMYK could do. In addition, based on the color quantification data of individual users provided by the latest Adobe Sceney program artificial intelligence, the purpose of the practice was to improve learners' predictions of actual color combinations and random colors using filter effects. In conclusion, it is a study on the use of programs that eliminate ambiguity in the mixing process of existing paint practice, secure digital color details, and propose a practical method that can provide effective learning methods for beginners and intermediates to develop their senses through artificial intelligence support. The Adobe program practice method necessary for coloration and main color through theoretical consideration and improvement of teaching skills that are better than existing paint practice were presented.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.291-301
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• 2023

The purpose of this study is to examine the perception of early childhood teachers on ecological art activities oriented to education for sustainable development. The research results are as follows. First, Early childhood teachers recognized the visual art of natural media, the pursuit of community values, and the participation and communication of social members as educational significance of ecological art activities. And difficulties in practicing ecological art were recognized as lack of educational environment, lack of ecological art teaching materials and specific examples, and teachers' lack of understanding of ecological art. Also, they recognized that ecological art activities foster core competencies in art experience area, such as nature-friendly communication skills, eco-friendly sensibility, and creative convergence skills. Second, regarding ecological art activities and sustainable development education, early childhood teachers considered the difficulties in practice as lack of awareness about sustainable development, lack of play meia and materials, lack of educational policies and support, and insufficient teacher training programs. Also, regarding the SDGs that can be practiced in ecological art activities, teachers were found to be highly aware of 'grow affordable and clean energy', 'improve clean water and sanitation', 'provide quality education' in the order. In the contents of education for sustainable development that can be practiced in ecological art activities, teachers are given the order of 'climate change response', 'clean energy', 'water and sanitation', 'quality education', 'health and well-being' and 'marine ecosystem'. was highly recognized. If an ecological art activity program is developed, the rate of responding that it will be used is high, so it is considered that the development of an ESD-oriented ecological art activity program is urgent.

• Journal of agricultural medicine and community health
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• v.49 no.2
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• pp.132-145
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• 2024

Objectives: This study compares cases of Dalgubeol Health Care Project, 301 Network Project, and 3 for 1 Project based on program logic models to derive measures for promoting integrated healthcare and welfare services centered around medical institutions. Methods: From January to December 2021, information on the implementation systems and performance of each institution was collected. Data sources included prior academic research, project reports, operational guidelines, official press releases, media articles, and written surveys from project managers. A program logic model analysis framework was applied, structuring the information based on four elements: situation, input, activity, and output. Results: All three projects aimed to address the fragmentation of health and welfare services and medical blind spots. Despite similar multidisciplinary team compositions, differences existed in specific fields, recruitment scale, and employment types. Variations in funding sources led to differences in community collaboration, support methods, and future directions. There were discrepancies in the number of beneficiaries and medical treatments, with different results observed when comparing the actual number of people to input manpower and project cost per beneficiary. Conclusions: To design an integrated health and welfare service provision system centered on medical institutions, securing a stable funding mechanism and establishing an appropriate target population and service delivery system are crucial. Additionally, installing a dedicated department within the medical institution to link activities across various sectors, rather than outsourcing, is necessary. Ensuring appropriate recruitment and stable employment systems is needed. A comprehensive provision system offering services from mild to severe cases through public-private cooperation is suggested.

• Journal of Industrial Convergence
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• v.22 no.5
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• pp.1-10
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• 2024

This study proposes a developmental policy direction for the online platform industry, moving away from the regulatory-centered discussions that have predominated thus far. To offer policy directions, the PEST-SWOT-AHP analysis model was employed. The study first categorizes the issues of the domestic online platform industry into political, economic, social, and technological aspects, which are then further categorized into 16 strengths, weaknesses, opportunities, and threats. The relative importance among these factors was measured, leading to the derivation of four final strategies. The analysis indicates that policy directions should prioritize addressing weaknesses, with 'improving regulations that hinder innovation' being the most important factor across all categories, while technological factors were consistently rated highly in importance apart from this. Accordingly, the policy direction for the domestic online platform industry suggests avoiding excessive regulation and instead emphasizing policy support centered around technological development. This study is significant in that it presents a macroscopic developmental direction for online platform policies that have not been discussed in existing academic research, and it provides professional and objective indicators through consensus among scholars and researchers. In the future, it is hoped that research will continue to propose detailed policy strategies and implementation systems based on a macroscopic perspective.