• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2007.06a
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• pp.203-206
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• 2007

연속 전자 모델과 결합된 종래의 분자 동역학 방법은 원자 사이의 힘과 원자의 전기용량에 의해 야기되는 탄소 나노튜브의 구부러지는 성질의 특성을 해석하였다. 탄소 원자의 전기 용량은 탄소 원자의 길이에 따라 변하였다. 본 연구는 11.567nm($L_{CNT}$)의 길이와 $0.9{\sim}1.5nm(H)$의 안쪽 깊이를 가진 (5,5) 탄소 나노튜브 브리지로 MD 시뮬레이션을 수행하였다. 탄소 나노튜브는 금 표면에 부딪힌 후 탄소 나노튜브 브리지는 약 ${\sim}1{\AA}$의 크기로 금 표면에서 진동하며, 크기는 차츰 감소하였다. $H{\leq}1.3nm$일 때, 탄소 나노튜브 브리지는 첫 번째 충돌 후에 금 표면과 계속 접촉해 있었고, $H{\leq}1.4nm$일 때, 탄소 나노튜브 브리지는 몇 번의 충돌 후에 금 표면과 안정한 접촉상태가 되었다. $H/L_{CNT}$가 0.13보다 작을 때, 탄소 나노튜브 초소형 전자기기 메모리는 반영구적인 비활성의 메모리 장치가 되는 반면에 $H/L_{CNT}$가 0.14보다 클 때 탄소 나노튜브 초소형 전자기기 메모리는 휘발성이거나 스위치 장치로 동작할 수 있다.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.232-235
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• 2006

본 논문은 금속 이온에 둘러싸인 다중벽 탄소 나노튜브를 이용한 기가급 진동자의 응용 가능성에 대한 해석을 수행하였다. 탄소 나노튜브 오실레이터 안쪽에 포함된 칼슘 이온들은 외부에서 공급된 전계에 의해 가속될 수 있고 $nK^+@CNT$ 오실레이터로 구성된 기가 헤르쯔 진동자는 본 연구의 분자동역학 시뮬레이션에서 공급된 전계에 의해 초기화될 수 있었다.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.19-36
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• 2023

As advances in information and communication technology have made it easier for anyone to produce and disseminate information, a new problem has emerged: fake news, which is false information intentionally shared to mislead people. Initially spread mainly through text, fake news has gradually evolved and is now distributed in multimedia formats. Since its founding in 2005, YouTube has become the world's leading video platform and is used by most people worldwide. However, it has also become a primary source of fake news, causing social problems. Various researchers have been working on detecting fake news on YouTube. There are content-based and background information-based approaches to fake news detection. Still, content-based approaches are dominant when looking at conventional fake news research and YouTube fake news detection research. This study proposes a fake news detection method based on background information rather than content-based fake news detection. In detail, we suggest detecting fake news by utilizing related video information from YouTube. Specifically, the method detects fake news through CNN, a deep learning network, from the vectorized information obtained from related videos and the original video using Doc2vec, an embedding technique. The empirical analysis shows that the proposed method has better prediction performance than the existing content-based approach to detecting fake news on YouTube. The proposed method in this study contributes to making our society safer and more reliable by preventing the spread of fake news on YouTube, which is highly contagious.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.4
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• pp.59-76
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• 2023

This study examines critical issues and topics related to services using YouTube videos and research publications. We analyzed 2,853 YouTube videos and 19,973 research papers related to services, released during the 2013-June, 2023 period, using text mining and network analysis. In addition, the collected data was divided into pre- and post-COVID-19 pandemic periods to explore how key issues and topics regarding services have changed. These papers were sequentially analyzed through text mining and network construction and procedures. The results indicate that the central themes of YouTube videos were IT, data, and solution, while academic research focused on service quality, quality, and customer satisfaction. Regarding ego network analysis, the key issues in YouTube video contents revolved primarily around words related to the service industry. Although it was found that they generally lacked specific industry fields, academic papers explored diverse issues in various service fields. The results of this study can be utilized to understand changes in customer concerns in the service industry from practical and academic perspectives.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.1-19
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• 2023

Despite the growing importance of video-based social media content, such as vlogs, as a marketing tool in the travel industry, there is limited research on the characteristics that enhance engagement among potential travelers. This study explores the influence of emotional valence in YouTube travel content on viewer engagement, specifically likes and comments. We analyzed 4,619 travel-related YouTube videos from eight popular tourist cities. Using negative binomial regression analysis, we found that both positive and negative emotions significantly influence the number of likes received. Videos with higher positive emotions as well as negative emotions receive more likes. However, when it comes to the number of comments, only negative emotions showed a significant positive influence, while positive emotions had no significant impact. These findings offer valuable insights for marketers seeking to optimize engagement strategies on YouTube, considering the unique nature of travel products. Further research into the effects of specific emotions on engagement is warranted to improve marketing strategies. This study highlights the powerful impact of emotions on viewer engagement in the context of social media, particularly on YouTube.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.576-583
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• 2020

This paper proposes a technique to determine the spam comments on YouTube, which have recently seen tremendous growth. On YouTube, the spammers appeared to promote their channels or videos in popular videos or leave comments unrelated to the video, as it is possible to monetize through advertising. YouTube is running and operating its own spam blocking system, but still has failed to block them properly and efficiently. Therefore, we examined related studies on YouTube spam comment screening and conducted classification experiments with six different machine learning techniques (Decision tree, Logistic regression, Bernoulli Naive Bayes, Random Forest, Support vector machine with linear kernel, Support vector machine with Gaussian kernel) and ensemble model combining these techniques in the comment data from popular music videos - Psy, Katy Perry, LMFAO, Eminem and Shakira.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.157-169
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• 2021

YouTube has rapidly grown as a news media outlet. As political content without fact-checking is actively provided and YouTube algorithms are used for content recommendations, users are selectively exposed to certain political ideologies, which could escalate conflicts among political groups. In particular, the stronger the identification of in-group, the greater the antipathy toward outgroup, and the more exposed the content to the parties that support or oppose it, the stronger the identification or the antipathy can be. This study investigated the relationship between selective exposure and political attitude polarization in the context of political video on YouTube. Based on social identity theory, this study also found that political identification mediates the relationship between selective exposure and political attitude polarization.

• Composites Research
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• v.37 no.1
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• pp.32-39
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• 2024

Solid-state hydrogen storage is gaining prominence as a crucial subject in advancing the hydrogen-based economy and innovating energy storage technology. This storage method shows superior characteristics in terms of safety, storage, and operational efficiency compared to existing methods such as compression and liquefied hydrogen storage. In this study, we aim to evaluate the solid hydrogen storage performance on the nanotube surface by various structural design factors. This is accomplished through molecular dynamics simulations (MD) with the aim of uncovering the underlying ism. The simulation incorporates diverse carbon nanotubes (CNTs) - encompassing various diameters, multi-walled structures (MWNT), single-walled structures (SWNT), and boron-nitrogen nanotubes (BNNT). Analyzing the storage and effective release of hydrogen under different conditions via the radial density function (RDF) revealed that a reduction in radius and the implementation of a double-wall configuration contribute to heightened solid hydrogen storage. While the hydrogen storage capacity of boron-nitrogen nanotubes falls short of that of carbon nanotubes, they notably surpass carbon nanotubes in terms of effective hydrogen storage capacity.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.435-444
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• 2022

There are three focuses in the paper. Firstly, the study identified what channels were most viewed by YouTube users to watch the 'Daejang-dong scandal,' which was the most powerful agenda to influence the candidate preference among voters during the 20th presidential election. Secondly, the study analyzed whether the political tone of the first videos was in line with that of the subsequent videos. Finally, we compared the sentiment of comments on the first and subsequent videos. The results showed that TBS 'News Factory' and 'TV Chosun News' represented liberal and conservative factions, respectively. Secondly, the political tone of channels that were viewed subsequently was neutral, but the conservative channel users left more negative comments and that was significant statistically. In addition, about 80% of the conservative and liberal channel users shared the same political tendency with the channel they watched first, and more than 90% of the comments left at the subsequent videos in line with that of at the first news. Based on these results, the study concluded that the voters tended to seek political news that was similar with their political ideology, and it was considered a sort of echo chamber phenomenon on the YouTube. The study suggests that the performance of high-quality journalism by traditional news outlet might contribute to decrease the negative influence of political contents on YouTube users.

• Composites Research
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• v.33 no.4
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• pp.198-204
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• 2020

In this study, we employ the full atomistic molecular dynamics simulation and finite element homogenization method to predict the thermo-mechanical properties of nanocomposites including carbon nanotube bundle. As the number of carbon nanotubes within the single bundle increases, the effective in-plane Young's modulus and in-plane shear modulus decrease, and in-plane thermal expansion coefficient increases, despite the same volume fraction of carbon nanotubes. To investigate the thickness of interphase zone, we employ the radial density distribution. It is investigated that the interphase thickness is almost independent on the number of carbon nanotubes within the single bundle. It is assumed that the matrix and interphase are isotropic materials. According to the predicted thermo-mechanical properties of interphase zone, the Young's modulus and shear modulus of interphase zone clearly decrease, and the thermal expansion coefficient increases. Based on the thermo-mechanical interphase behavior, we developed the multiscale homogenization model to predict the thermo-mechanical properties of PLA nanocomposites that include the carbon nanotube bundle.