• Journal of Digital Convergence
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• v.19 no.2
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• pp.373-378
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• 2021

The study is a user experience design study on the function of action cams used for leisure activities that have been on the rise recently. Along with the video platforms that are developing in a user-friendly way, the size of the action cam market is also growing. However, there is a lack of research on the quality of a function that enhances the user experience. Thus, this study classified action cam functions according to user experience elements by using Kano Model's analysis method and in-depth interview, and analyzed how the quality of action cam functions affects the user experience by conducting a satisfaction survey by function. The results of the study have shown which functions should be improved first and which functions should be continuously researched and invested. I hope this study will contribute useful information to developing user-centered action cams.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.24 no.1
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• pp.65-74
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• 2021

Purpose: The coronavirus disease 2019 (COVID-19) pandemic has influenced the lives of people worldwide. Little is known about the effects of the COVID-19 pandemic on the behavior and fears of pediatric patients with inflammatory bowel disease (IBD) and their families. We conducted a survey to determine the COVID-19 exposure, related perceptions, and information sources; medication compliance; and patients' and parents' behaviors, fears, and physician contact. Methods: An anonymous cross-sectional survey of pediatric patients with IBD and their parents at one pediatric gastroenterology unit of a university medical center was performed. Results: A total of 46 pediatric patients with IBD and 44 parents completed the survey. Parents of pediatric patients with IBD had high fear of their children becoming infected with severe acute respiratory syndrome coronavirus 2. They perceived schools as the most hazardous environment, whereas the children did not. Half the pediatric patients with IBD feared infection. Patients and parents felt sufficiently informed about COVID-19. The primary source of guidance for pediatric patients was their parents (43%), followed by television and social media, whereas the parents mainly consulted internet news websites (52.2%), television, and public health institutes. Pediatric patients with IBD adhered to their prescribed medication. They also showed cautious behavior by enhancing hand hygiene (84%) and leaving the house less frequently than before. However, in-person medical visits remained favored over video consultations. Conclusion: Although parents expressed overprotective concerns, both parents and pediatric patients with IBD are coping well with the COVID-19 pandemic. IBD-relevant information should be actively conveyed.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.255-264
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• 2020

In the database design course, the team project is a very important process to develop students' database design competencies. In order to carry out team projects smoothly, active interaction between students and the professor as well as collaboration among team members are very important. However, a full uncontacted class was suddenly decides in the first semester of 2020, it was questionable whether it would be possible to effectively manage this course, where team projects to construct database take up a big portion. However team projects were able to proceed without major problems through interaction using real-time video media such as zoom, and discussions, quizzes, and Q&A supported by the online education support system (LMS), and online presentations, mutual evaluations, and so on. This paper shares the experience of managing engineering team projects in uncontacted classes and based on three surveys introduces desirable improving directions of this instruction and some suggestions to improve uncontacted classes overall.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1321-1329
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• 2019

With the development of social information networks, the marketing methods are also changing in various ways. Unlike successful marketing methods based on existing celebrities and financial support, Influencer-based marketing is a big trend and very famous. In this paper, we first extract influencer features from more than 54 YouTube channels using the multi-dimensional qualitative analysis based on the meta information and comment data analysis of YouTube, model representative themes to maximize a personalized video satisfaction. Plus, the purpose of this study is to provide supplementary means for the successful promotion and marketing by creating and distributing videos of new items by referring to the existing Influencer features. For that we assume all comments of various videos for each channel as each document, TF-IDF (Term Frequency and Inverse Document Frequency) and LDA (Latent Dirichlet Allocation) algorithms are applied to maximize performance of the proposed scheme. Based on the performance evaluation, we proved the proposed scheme is better than other schemes.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.355-360
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• 2021

Recently Youtube has been more popular. As many studies show the comparative deprivation of the Social Medeia, this study looks into whether the comparative deprivation is expressed on the YouTube comments. It focuses on the Luxury Haul contents, videos about huge amounts of luxurious products, of which Youtubers'economic feature are demonstrative. The comments of the videos are analyzed with LDA TF-IDF and Word2Vec. Additionally, the comments were classified into positive and negative groups by the LSTM model as well. As a result of the study, even though many comments turned out positive, the negative keywords were indicated related to comparative deprivation. Also it was found that the viewers compared themselves with Youtubers. In particular, some YouTubers are more criticized if they are younger or does not seem to afford the luxurious products themselves. This study suggests that the users express the comparative deprivation on YouTube as well like on the other Social Media.

• 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.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.207-215
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• 2022

The latest volumetric technology's high geometrical accuracy and realism ensure a high degree of correspondence between the real object and the captured 3D model. Nevertheless, since the 3D model obtained in this way constitutes a sequence as a completely independent 3D model between frames, the consistency of the model surface structure (geometry) is not guaranteed for every frame, and the density of vertices is very high. It can be seen that the interconnection node (Edge) becomes very complicated. 3D models created using this technology are inherently different from models created in movie or video game production pipelines and are not suitable for direct use in applications such as real-time rendering, animation and simulation, and compression. In contrast, our method achieves consistency in the quality of the volumetric 3D model sequence by linking re-meshing, which ensures high consistency of the 3D model surface structure between frames and the gradual deformation and texture transfer through correspondence and matching of non-rigid surfaces. And It maintains the consistency of volumetric 3D model sequence quality and provides post-processing automation.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.283-294
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• 2022

The feature map used in the network for deep learning generally has larger data than the image and a higher compression rate than the image compression rate is required to transmit the feature map. This paper proposes a method for transmitting a pyramid feature map with high compression rate, which is used in a network with an FPN structure that has robustness to object size in deep learning-based image processing. In order to efficiently compress the pyramid feature map, this paper proposes a structure that predicts a pyramid feature map of a level that is not transmitted with pyramid feature map of some levels that transmitted through the proposed prediction network to efficiently compress the pyramid feature map and restores compression damage through the proposed reconstruction network. Suggested mAP, the performance of object detection for the COCO data set 2017 Train images of the proposed method, showed a performance improvement of 31.25% in BD-rate compared to the result of compressing the feature map through VTM12.0 in the rate-precision graph, and compared to the method of performing compression through PCA and DeepCABAC, the BD-rate improved by 57.79%.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.111-118
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• 2022

In recent years, the number of single-person elderly households has increased, but when an emergency situation occurs inside the house in the case of single-person households, it is difficult to inform the outside world. Various smart home solutions have been proposed to detect emergency situations in single-person households, but it is difficult to use video media such as home CCTV, which has problems in the privacy area. Furthermore, if only a single sensor is used to analyze the abnormal situation of the elderly in the house, accurate situational analysis is limited due to the constraint of data amount. In this paper, therefore, we propose an algorithm of abnormal situation detection fusion inside the house by fusing 2DLiDAR, dust, and voice sensors, which are closely related to everyday life while protecting privacy, based on their correlations. Moreover, this paper proves the algorithm's reliability through data collected in a real-world environment. Adnormal situations that are detectable and undetectable by the proposed algorithm are presented. This study focuses on the detection of adnormal situations in the house and will be helpful in the lives of single-household users.