• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.124-132
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• 2022

Recently, due to COVID-19, online remote classes and non-face-to-face exams have made it difficult to manage class attitudes and exam cheating. Therefore, there is a need for a system that automatically recognizes and detects the behavior of students online. Action recognition, which recognizes human action, is one of the most studied technologies in computer vision. In order to develop such a technology, data including human arm movement information and information about surrounding objects, which can be key information in online classes and exams, are needed. It is difficult to apply the existing dataset to this system because it is classified into various fields or consists of daily life action. In this paper, we propose a dataset that can classify attitudes in real-time online tests and classes. In addition, it shows whether the proposed dataset is correctly constructed through comparison with the existing action recognition dataset.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.115-127
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• 2023

Video stabilization is one of the camera technologies that the importance is gradually increasing as the personal media market has recently become huge. For deep learning-based video stabilization, existing methods collect pairs of video datas before and after stabilization, but it takes a lot of time and effort to create synchronized datas. Recently, to solve this problem, unsupervised learning method using only unstable video data has been proposed. In this paper, we propose a network structure that learns the stabilized trajectory only with the unstable video image without the pair of unstable and stable video pair using the Convolutional Auto Encoder structure, one of the unsupervised learning methods. Optical flow data is used as network input and output, and optical flow data was mapped into grid units to simplify the network and minimize noise. In addition, to generate a stabilized trajectory with an unsupervised learning method, we define the loss function that smoothing the input optical flow data. And through comparison of the results, we confirmed that the network is learned as intended by the loss function.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.351-356
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• 2023

The purpose of this study is to analyze how the movie <The Book of Fish> (2021) represents Joseon, which is slowly collapsing with the Neo-Confucian order of the 19th century shaking, and to discuss its meaning. Prior to the analysis, the analysis framework of the historical drama was presented considering the narration characteristics of the historical drama. Using the analysis framework of historical dramas, we confirmed that <The Book of Fish> is representing the image of Jeong Yak-jeon and Jang Chang-dae living their lives as independent individuals between the limitations and possibilities of the times based on the plot structure of the narrative of exile. Through the central memory and surplus memory created through plot and style elements such as contrast between black and white and color images, voice-over narration, chinese poetry subtitles and music, the film asks us universal questions about what it takes to live as an independent individual.

• Trans-
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• v.14
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• pp.123-155
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• 2023

This study analyzes the characteristics of the social value creation process through the collective appreciation of film. It focuses on the historical development of community cinema in Japan. In modern-day Japan, where digital video is easily accessible and the use of private, personalized media spaces widespread, a sub-culture of collective film appreciation is spreading, as more and more Japanese begin to attend movie screenings in non-commercial theaters. In addition, Japanese community cinema center has begun to integrate and support this viewing experience, which has come to be known as community cinema. A literature review revealed the following characteristics of community cinema. First, local theater screening groups or appreciation groups cooperate with residents to establish and operate movie theaters. Second, these spaces create theoretical and practical participatory learning opportunities that foster understanding of and participation in film culture, through large-scale associations with organizations or institutions that offer viewings. Third, based on collective appreciation, the film culture created through repeated joint viewings produces a social arena in which community can be realized. In these communities film can be put to socially productive uses, such as problem solving.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.655-662
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• 2023

Big data research plays a role of supplementing existing social science research methods. If the survey and experimental methods are somewhat inaccurate because they mainly rely on recall memories, big data are more accurate because they are real-time records. Social science research so far, which mainly conducts sample research for reasons such as time and cost, but big data research analyzes almost total data. However, it is not easy to repeat and reproduce social research because the social atmosphere can change and the subjects of research are not the same. While social science research has a strong triangular structure of 'theory-method-data', big data analysis shows a weak theory, which is a serious problem. Because, without the theory as a scientific explanation logic, even if the research results are obtained, they cannot be properly interpreted or fully utilized. Therefore, in order for big data research to become a methodological innovation, I proposed big thinking along with researchers' efforts to create new theories(black boxes).

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.367-375
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• 2022

Given the growing changes in media environment and cultural consumption, globally popular contents of Korean Wave(Hallyu) has also been transformed in its forms and genres. Moreover, extant research on Hallyu has focused on any single respective genre, mostly on East-Asian countries, or studied from Korea-centered perspective. This study examined the social capital effect of Korean Wave in users' own counties, especially in non-English European societies. Survey analysis results reveal that both narrative and non-narrative contents in Hallyu had negative impact on social trust and trust toward people of their own country, whereas positive effect on trust toward Koreans. In contrast, K-pop Hallyu showed positive effect on all types of social trust toward their own country and Koreans, as well as on social participation and bridging/bonding social networks.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.509-515
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• 2023

Despite the continued development of alternative energies, fuel consumption is increasing. In particular, the price of gasoline fluctuates greatly according to fluctuations in international oil prices. Gas stations adjust their gasoline inventory to respond to gasoline price fluctuations. In this study, news datasets is used to analyze the gasoline consumption patterns through fluctuations of the gasoline inventory. First, collecting news datasets with web crawling. Second, summarizing news datasets using KoBART, which summarizes the Korean text datasets. Finally, preprocessing and deriving the fluctuations factors through N-Gram Language Model and TF-IDF. Through this study, it is possible to analyze and predict gasoline consumption patterns.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.787-800
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• 2023

This paper is a study aimed at facilitating a comprehensive understanding of the music metaverse platform that will emerge in the era of Web 3.0 and exploring productive strategies for its construction. We examine the significance of the metaverse music platform from various perspectives and investigate the developmental process of digital music platforms from Web 1.0 to 3.0. Subsequently, assuming the emergence of metaverse platforms as a transition to Web 3.0, we align this transition with technological(VR technology, wearable devices, generative AI), cultural(digital avatars, fandom), and economic(NFT) discussions related to Web 3.0. These discussions are integrated with the developmental strategies of the metaverse music platform. Through this study, we hope to enhance the understanding of the metaverse music platform and provide insights into potential construction strategies.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.535-542
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• 2023

This study attempted to identify various variables that affect satisfaction and continued use intention of the subscription economy services. Through previous research studies, individual characteristics and service characteristic variables were considered together. Finally, use motivation, platform characteristic factors, and product and service characteristic factors were classified and examined. As a result of the study, the motive for using the service that affects the satisfaction of the subscription economy service was found to be functional hedonic, and economic motive, and platform recency and convenience, economic utility, and perceived personalization had a positive effect. Functional and hedonic motives and convenience showed positive influences on continued use intention, while social motives showed negative influences. In addition, it was confirmed that economic motivation, platform recency, economic utility, and perceived personalization showed a positive influence on the intention to continued use intention by mediating satisfaction with subscription economy services.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.441-449
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• 2021

With advances in autonomous vehicles, there is a growing demand for more accurate position estimation. Especially, this is a case for a moving robot for the indoor operation which necessitates the higher accuracy in position estimation when the robot is required to execute the task at a predestined location. Thus, a method for improving the position estimation which is applicable to both the fixed and the moving object is proposed. The proposed method exploits the initial position estimation from Bluetooth beacon signals as observation signals. Then, it estimates the gravitational acceleration applied to each axis in an inertial frame coordinate through computing roll and pitch angles and combining them with magnetometer measurements to compute yaw angle. Finally, it refines the control inputs for an object with motion dynamics by computing acceleration on each axis, which is used for improving the performance of Kalman filter. The experimental assessment of the proposed algorithm shows that it improves the position estimation accuracy in comparison to a conventional Kalman filter in terms of average error distance at both the fixed and moving states.