• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.205-210
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• 2024

Nowadays, online messengers are the main communication tool of modern people. Currently, not only messengers that communicate based on text and images, but also services that can interact in real time through voice or screen sharing are actively used by the MZs. This study aims to figure out 1) the motivation of users of voice chat services, and 2) to explore the influence of motivation for use on satisfaction that one of the factors that determine the user's experience. As a result, five major motivations for using voice chat service(Relationship formation, Usefulness, Relationship maintenance, communication supplementation, and distance overcoming) were found. Among them 'Usefulness' and 'Relationship maintenance had a positive effect on user satisfaction. This study, highlighted the various needs of users who communicate in a non-face-to-face environments as well as factors to be satisfied for their positive experiences. These results should be actively used in the online communications market.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.107-132
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• 2024

This study attempted to analyze newspaper articles related to May 18 through frequency analysis and network analysis using news data related to May 18 for about 30 years from 1990 to 2022 at the Korea Press Foundation's Big Kinds. Specifically, quantitative change trends were examined by analyzing the amount of articles by period and region, and the connection structure between major keywords by the regime was explored through network analysis by regime using co-appearance keywords. As a result of the analysis, it was found that 2019 had the largest amount of coverage, which had many social issues in time, and the Jeolla-do region had the largest amount of coverage in the region. And as a result of network analysis, there were differences in words related to May 18 in news data according to the perception and policy of the regime toward May 18. As a result of synthesizing the analysis of May 18 news data, it was confirmed that May 18 was becoming a democratic movement over time regardless of region, but at the same time, the distortion of May 18 was not resolved.

• Journal of the Health Care and Life Science
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• v.11 no.1
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• pp.97-103
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• 2023

The purpose of this study was to find out view on the teaching profession of teachers working in early childhood education and to find ways to support teachers in the field. Data were collected through telephone interviews with 16 teachers at private kindergartens and daycare centers in Chungnam and Daejeon. As a result of the research, active support is needed to form a teaching profession based on an understanding of the profession. In addition, there is a need to create an atmosphere that can improve the perception of the teaching profession in society, as well as institutional mechanisms to ensure that the teaching authority can be adequately established. Various programmes related to the formation of the right teaching profession to develop an understanding of the profession of pre-school teachers should be provided as retraining to teachers in the field.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.9-14
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• 2024

This study developed a voice recognition chatbot system to address depression and loneliness among the elderly in an aging society. The system utilizes the Whisper model, GPT 2.5, and XTTS2 to provide high-performance voice recognition, natural language processing, and text-to-speech conversion. Users can express their emotions and states and receive appropriate responses, with voice recognition functionality using familiar voices for comfort and reassurance. The UX/UI design considers the cognitive responses, visual impairments, and physical limitations of the smart senior generation, using high contrast colors and readable fonts for enhanced usability. This research is expected to improve the quality of life for the elderly through voice-based interfaces.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.27-33
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• 2024

The environment of academic research is continuously changing due to the increase of information, which raises the need for an effective way to analyze and organize large amounts of documents. In this paper, we propose Performance Improvement of Topic Modeling using BART(Bidirectional and Auto-Regressive Transformers) based Document Summarization. The proposed method uses BART-based document summary model to extract the core content and improve topic modeling performance using LDA(Latent Dirichlet Allocation) algorithm. We suggest an approach to improve the performance and efficiency of LDA topic modeling through document summarization and validate it through experiments. The experimental results show that the BART-based model for summarizing article data captures the important information of the original articles with F1-Scores of 0.5819, 0.4384, and 0.5038 in Rouge-1, Rouge-2, and Rouge-L performance evaluations, respectively. In addition, topic modeling using summarized documents performs about 8.08% better than topic modeling using full text in the performance comparison using the Perplexity metric. This contributes to the reduction of data throughput and improvement of efficiency in the topic modeling process.

• Cartoon and Animation Studies
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• s.43
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• pp.123-150
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• 2016

There has been discussed very little about animation authorship studies, especially the themes of authors and their original animation texts since 1990s. This study is to explore the academic discourse of animation authorship studies understanding the media aesthetics of animation and the scholarly approach of animation studies about authorship. This article examines 55 articles via meta analysis about animation authorship studies drawn from the 1,516 articles on the general animation studies. The results were as follows. First, the domestic animation studies on the authorship were made about animators of Japan, US, and european countries. Second, It was dominant that scholarly interest on the screen direction and visual expression of animation texts. This shows the authorship approaches were mainly about visual aspects of animations. The domestic animation authorship studies did not trace the authorship issues on author's world view and visual style revealed in the corpus of texts. Instead, they discussed authorship issues on the characteristics of individual animation text. It has been evident that animation studies were not enthusiastic about building the independent theory on animation. Therefore, animation studies have tried theorizing the animation issues borrowing the literature and film theories. This study can contribute to increase phase of animation studies by drawing the intensive discussion of animation authors and their authorship.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.908-921
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• 2022

Purpose: As the connection between physical and non-physical structures in cities is expanding and becoming more complex, the risk of complex disaster which causes damage in a complex way is increasing. Preparing for these complex disasters, it is important to preemptively identify and manage disasters that can develop into complex disasters. Therefore, this study analyzes the disaster types studied as complex disasters by analyzing the trends of domestic and international studies related to complex disasters, and presents the direction of complex disaster management in the future. Method: We first established co-occurrence networks between disaster types based on 993 articles related to complex disasters published in disaster-related journals for the last 20 years (2002-2021). Then, through network analysis, domestic and international complex disaster research trends were compared and analyzed. Result: Research on complex disasters related to storm and flood damage, infrastructure failure and fire was high in domestic studies, and it was analyzed that research on complex disasters related to earthquakes and landslides has recently increased. However, in international studies, the proportion of studies on infrastructure failure along with storm and flood damage and earthquake was high, and various types of disasters such as tsunami and drought appeared. Conclusion: The results of this study are expected to increase the understanding of the trends in complex disaster research and provide suggestions of domestic complex disaster research in the future.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.139-155
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• 2016

The purpose of this study is to find the research identity of the Korea Intelligent Information Systems Society through the profiling methods and co-word analysis in the most recent three-year('2014~'2016) study to collect keyword. In order to understand the research identity for intelligence information system, we need that the relative position of the study will be to compare identity by collecting keyword and research methodology of The korea Society of Management Information Systems and Korea Association of Information Systems, as well as Korea Intelligent Information Systems Society for the similar. Also, Korea Intelligent Information Systems Society is focusing on the four research areas such as artificial intelligence/data mining, Intelligent Internet, knowledge management and optimization techniques. So, we analyze research trends with a representative journals for the focusing on the four research areas. A journal of the data-related will be investigated with the keyword and research methodology in Korean Society for Big Data Service and the Korean Journal of Big Data. Through this research, we will find to research trends with research keyword in recent years and compare against the study methodology and analysis tools. Finally, it is possible to know the position and orientation of the current research trends in Korea Intelligent Information Systems Society. As a result, this study revealed a study area that Korea Intelligent Information Systems Society only be pursued through a unique reveal its legitimacy and identity. So, this research can suggest future research areas to intelligent information systems specifically. Furthermore, we will predict convergence possibility of the similar research areas and Korea Intelligent Information Systems Society in overall ecosystem perspectives.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.146-172
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• 2018

In the Small and Medium Enterprises(SMEs) sector, research has shown an increasing trend due to changes in industrial society and policy. Therefore, the interrelationship between academic research and policy is relatively high. In this study, we analyzed the trends of academic research related to SMEs innovation policy. Moreover, we examined the interrelationships. By using text mining techniques, we have identified key themes and changes in domestic policy papers published since the announcement of the "Five-Year Plan for Innovation of SMEs". Also, we compared them with "Five-Year Plan for Innovation of SMEs" of each period. The result shows that the gap between academic research and policy has been closing over time. This study shows that there is an increasing number of research studies that verify policies at the relevant time from an academic point of view, and that policy issues are in turn influencing academic research due to government-driven policies. Also, it was confirmed that there was a time gap between academic research and policy. Academic research tended to increase compared to the previous year's level, when the policy had been implemented. The results of this study are expected to contribute to the establishment of the "2019~2023 five-year plan for Small and Medium Enterprises" which will be announced in the future, and this study will demonstrate the possibility of devising evidence-based policy.

• Journal of Life Science
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• v.33 no.8
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• pp.663-679
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• 2023

This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.