• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1483-1489
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• 2022

Recently, due to the influence of the 4th industrial revolution and the development of communication media, various digital video equipment are being used in industrial fields. Image data is easily damaged by noise in the process of acquiring and transmitting and receiving from the camera and sensor, and since the damaged image has a great effect on the processing of the system, noise removal is essential. In this paper, a weight filter algorithm using a weight graph is proposed to restoration images damaged by high-density impulse noise. The proposed algorithm obtains a weight graph using pixel values inside the filtering mask of the image, and restores the image by applying the final weight to the filtering mask. Simulation was conducted to analyze the noise removal performance of the proposed algorithm, and the magnified image and PSNR were used to compare with the existing method. The resulting image of the proposed algorithm showed excellent performance by removing high-density impulse noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1441-1446
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• 2022

Modern people can access various information about food recipes very easily on the Internet or social media. As the supply of food recipes increases, it is difficult to find a suitable recipe for each user in the overflowing information. As such, the need to provide information by reflecting users' requirements has increased, and research related to food recipes and cooking recommendations is becoming active. In addition, the Internet, video, and application markets using this are also rapidly activating. In this study, in order to classify recipes from the user's perspective of food recipe users, the user's review data was applied with the k-mean clustering technique, which is unsupervised learning, and a "food recipe classification model" was derived. As a result, it was classified into a total of 25 clusters including information needed by many users, such as specific purposes and cooking stages.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.718-727
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• 2022

The Korean domestic cartoon industry has grown explosively by 65% compared to the previous year. Then the market size is expected to exceed KRW 1 trillion. However, excessive work results in health deterioration. Moreover, this working environment makes the production of human resources insufficient, repeating a vicious cycle. Although some tasks require creation activity during cartoon production, there are still a lot of simple repetitive tasks. Therefore, this study aimed to develop a method for creating a character pose through human pose estimation (HPE). The HPE is to detect key points for each joint of a user. The primary role of the proposed method was to make each joint of the character match that of the human. The proposed method enabled us to create the pose of the two-dimensional cartoon character through the results. Furthermore, it was possible to save the static image for one character pose and the video for continuous character pose.

• Archives of Plastic Surgery
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• v.49 no.5
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• pp.614-616
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• 2022

As of November 2021, TikTok has one billion monthly active users and is recognized as the most engaging social media platform. TikTok has seen a surge in users and content creators, ranging from athletes to medical professionals. In the past year, content creators have utilized the app to advocate for social reforms, education, and other uses that were not previously considered. Breast cancer is the most commonly diagnosed cancer in women, with an expected 281,550 new cases of invasive breast cancer in 2021. As more individuals with breast cancer choose to undergo resection, the demand for autologous fat grafting in breast reconstruction has increased due to the natural look and feel of breast tissue. The purpose of this article is to analyze content related to breast reconstruction with fat grafting found on TikTok and recommend methods to improve patient education, care, and outcomes. We searched TikTok on November 1, 2021, for videos using the phrase "breast reconstruction with fat grafting." The top 200 videos retrieved from the TikTok search algorithm were analyzed, and all commentaries, duplicates, and nonrelevant videos were removed. Video characteristics were collected, and two independent reviewers generated a DISCERN score A total of 131 videos were included in the study. They were found to have a combined 1,871,980 likes, 41,113 comments, and 58,662 shares. The videos had an average DISCERN score of 2.16. Content creators had an overall low DISCERN score in items involving the use of references, disclosure of risks for not obtaining treatment, and support for shared decision-making. When stratified, the DISCERN score was higher for videos created by physicians (DISCERN average 2.48) than for videos created by nonphysicians (DISCERN average 1.99; p < 0.001).

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.441-452
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• 2021

In this paper, we propose a method for generating luma signal mapping function to improve the coding efficiency of luma signal mapping methods in LMCS. In this paper, we propose a method to reflect the cognitive and perceptual features by multiplying the attention map of convolutional neural networks on local spatial variance used to reflect local features in the existing LMCS. To evaluate the performance of the proposed method, BD-rate is compared with VTM-12.0 using classes A1, A2, B, C and D of MPEG standard test sequences under AI (All Intra) conditions. As a result of experiments, the proposed method in this paper shows improvement in performance the average of -0.07% for luma components in terms of BD-rate performance compared to VTM-12.0 and encoding/decoding time is almost the same.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.89-96
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• 2022

This study examines the strategy of delivering the drama's poet Kim Soo-young and his literary works to the public through the drama (2004). This drama shows Kim's inner self and his literary view by inserting poems into scenes where the poet suffers internal conflict, while presenting relatively less well-known poems to broaden the public's understanding of poetry. In addition, the drama maintains viewers' interest by properly placing elements of conflict, and effectively shows how the conflict affected his life and the world of time. Therefore, the drama is a meaningful text that embodies a poet named Kim Soo-young in three dimensions along with the historical transformation and social problems of the time and the literary chapter of the time through the video.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.42-54
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• 2023

It is an important issue to compress huge holographic data in a digital format. In particular, research on the compression of phase-only holograms for commercialization is noteworthy. Conventional video coding standards optimized for natural images are not suitable for compressing phase signals, and neural network-based compression model that can be optimized for phase signals can achieve high performance, but has a memory issue in learning high-resolution holographic data. In this paper, we show that by applying a block-based learned image compression model that can solve memory problems to phase-only holograms, the proposed method can demonstrate significant performance improvement over standard codecs even under the same conditions as block-based. Block-based learned compression model can provide compatibility with conventional standard codecs, solve memory problems, and can perform significantly better against phase-only hologram compression.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.17-22
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• 2023

This study analyzed the genres of popular character web dramas and studied the development of story recommendations through the language model GPT. As a result of the study, it was confirmed that similar cliches are repeated in web dramas. In this study, a common story structure (cliché) was analyzed and a typical story structure was standardized and presented so that even unskilled video producers can easily produce character web dramas. For analysis, clichés of web dramas in the school romance genre, which is the most popular genre among teenagers, were listed in order of success. In addition, this study studied the story recommendation mechanism for users by learning the clichés that were analyzed and cataloged in GPT. Through this study, it is expected to accelerate the production of various contents as well as popular popularity through the acceptance of various databases from the standpoint of database consumption theory of web contents.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.647-659
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• 2023

As digital evidence becomes more important in criminal investigations, disputes are increasing in court. As media diversifies and the scope of analysis expands, the level of expertise in digital forensics is also increasing. However, no competency model has been developed to define the capabilities of digital evidence examiners or to judge their expertise. There have been some studies that have derived the capabilities necessary for digital evidence examiner, but they are still insufficient. Therefore, in this study, 25 competency evaluation factors in a total of 9 competency groups were defined using methodologies such as expert FGI and Delphi survey. Specifically, it was defined as Digital Forensics Theory, Digital Evidence Collection&Management, Disk Forensics, Mobile Forensics, Video Forensics, infringement forensics, DB Forensics, Embedded(IoT) Forensics, and Cloud Forensics. The digital evidence examiner competency model is expected to be used in various fields such as recruitment, education and training, and performance evaluation in the future.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.319-326
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• 2022

As digital content services, especially OTT(over-the-top) video services, diffuse rapidly, so do smartTVs. Based on the indirect network effect theory and the complementarity theory, this study explores the relationship between digital content services and smartTV. Using the Media panel dataset, this study analyzes how the usage of digital content service (OTT usage, OTT usage volume, the usage of various OTT service types, and online game/music/education/news service) affects smartTV usage. This study shows that OTT usage and its usage volume is positively associated with smartTV usage, and that the usage of various OTT service types is positively associated with smartTV usage compared with non-OTT users. As for online content services, the usage of online education service is positively associated with smartTV usage while the usage of online news service is associated negatively. These results support the indirect network effect theory and the complementarity theory.