• ETRI Journal
• /
• v.36 no.2
• /
• pp.264-270
• /
• 2014

This paper introduces a novel repetitive delivery scheme for the left and right views in service-compatible (SC) 3D video that provides full backward compatibility to a legacy DTV system while retaining HD 3D visual quality without additional bandwidth or a codec over the legacy broadcasting channel. The proposed SC delivery scheme transmits individual view sequences of a 3D video in interlaced form, that is, a left-view sequence of a 3DTV program to be used repeatedly is transmitted first and stored locally, and the right-view sequence of the 3D program is then transmitted. This paper specifically describes the signaling, synchronization, and storage format methods used to validate the proposed SC delivery scheme. The experiment results show that the proposed SC delivery scheme can be effectively applied for an SC 3DTV service without degrading the DTV quality using only legacy DTV platforms.

• International journal of advanced smart convergence
• /
• v.13 no.1
• /
• pp.140-151
• /
• 2024

This study explores an innovative advertising technique on Bilibili, where product links are embedded as bullet comments visible only to mobile app users. The research involved 140 participants, divided equally between followers and non-followers of a popular influencer, 'Gourmet WanggangR.' These groups were further split, with half viewing a video containing the product link on the app and the other half via PC. The study revealed that influencer attachment significantly increased viewer immersion (transportation) and positively influenced attitudes towards the content, which in turn elevated purchase intentions. Importantly, the influencer's followers showed a stronger attachment and more favorable attitudes towards the content, alongside a heightened likelihood to purchase the advertised product. The presence of the product link further accentuated these effects among the influencer's followers. Conversely, in the absence of the link, the correlation between influencer attachment and content attitude was less pronounced. These findings highlight the effectiveness of embedding product links in video content as a marketing strategy, particularly when targeting an influencer's followers through mobile platforms.

• International Journal of Advanced Culture Technology
• /
• v.12 no.3
• /
• pp.148-158
• /
• 2024

We investigate Autism Spectrum Disorder (ASD), which is typified by deficits in social interaction, repetitive behaviors, limited vocabulary, and cognitive delays. Traditional diagnostic methodologies, reliant on expert evaluations, frequently result in deferred detection and intervention, particularly in South Korea, where there is a dearth of qualified professionals and limited public awareness. In this study, we employ advanced deep learning algorithms to enhance early ASD screening through automated video analysis. Utilizing architectures such as Convolutional Long Short-Term Memory (ConvLSTM), Long-term Recurrent Convolutional Network (LRCN), and Convolutional Neural Networks with Gated Recurrent Units (CNN+GRU), we analyze video data from platforms like YouTube and TikTok to identify stereotypic behaviors (arm flapping, head banging, spinning). Our results indicate that the LRCN model exhibited superior performance with 79.61% accuracy on the augmented platform video dataset and 79.37% on the original SSBD dataset. The ConvLSTM and CNN+GRU models also achieved higher accuracy than the original SSBD dataset. Through this research, we underscore AI's potential in early ASD detection by automating the identification of stereotypic behaviors, thereby enabling timely intervention. We also emphasize the significance of utilizing expanded datasets from social media platform videos in augmenting model accuracy and robustness, thus paving the way for more accessible diagnostic methods.

• Information Systems Review
• /
• v.25 no.2
• /
• pp.57-76
• /
• 2023

This study classifies the success of creators and YouTubers who have created channels on YouTube recently, which is the most influential digital platform. Based on the actual information disclosure of YouTubers who are in the field of science and technology category, video upload cycle, video length, number of selectable multilingual subtitles, and information from other social network channels that are being operated, the success of YouTubers using machine learning was classified and analyzed, which is the closest to the YouTube revenue structure. Our findings showed that neural network algorithm provided the best performance to predict the success or failure of YouTubers. In addition, our five factors contributed to improve the performance of the classification. This study has implications in suggesting various approaches to new individual entrepreneurs who want to start YouTube, influencers who are currently operating YouTube, and companies who want to utilize these digital platforms. We discuss the future direction of utilizing digital platforms.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.10 no.4
• /
• pp.241-255
• /
• 2015

Recent network environment has been rapidly evolved to cloud computing environment based on the development of the Internet technologies. Furthermore there is an increasing demand on mobile cloud computing due to explosive growth of smart devices and wide deployment of LTE-based cellular networks. Thus mobile Desktop-as-a-Service(DaaS) could be a pervasive service for nomadic users. In addition, video streaming traffic is currently more than two-thirds of mobile traffic and ever increasing. All such trends enable that video streaming in mobile DaaS could be an important concern for mobile cloud computing. It should be noted that the performance of the Transmission Control Protocol(TCP) on cloud host servers greatly affects Quality of Service(QoS) of video streams for mobile users. With widely deployed Linux server platforms for cloud computing, in this paper, we conduct an experimental analysis of the twelve Linux TCP variants in mobile DaaS environments. The results of our experiments show that the TCP Illinois outperforms the other TCP variants in terms of wide range of packet loss rate and propagation delay over LTE-based wireless links between cloud servers and mobile devices, even though TCP CUBIC is usually used in default in the current Linux systems.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.5
• /
• pp.37-45
• /
• 2022

As of 2020, about 500 hours of videos are uploaded to YouTube, a representative online video platform, per minute. As the number of users acquiring information through various uploaded videos is increasing, online video platforms are making efforts to provide better recommendation services. The currently used recommendation service recommends videos to users based on the user's viewing history, which is not a good way to recommend videos that deal with specific purposes and interests, such as educational videos. The recent recommendation system utilizes not only the user's viewing history but also the content features of the item. In this paper, we extract the content features of educational video for educational video recommendation based on YouTube, design a recommendation system using it, and implement it as a web application. By examining the satisfaction of users, recommendataion performance and convenience performance are shown as 85.36% and 87.80%.

• International Journal of Advanced Culture Technology
• /
• v.7 no.4
• /
• pp.289-294
• /
• 2019

As social network service platforms grow and one-person media market expands, people upload their own photos and/or videos through multiple open platforms. However, it can be illegal to upload the digital contents containing the faces of others on the public sites without their permission. Therefore, many people are spending much time and effort in editing such digital contents so that the faces of others should not be exposed to the public. In this paper, we propose an automatic face hiding system called 'autoblur', which detects all the unregistered faces and mosaic them automatically. The system has been implemented using the GitHub MIT open-source 'Face Recognition' which is based on deep learning technology. In this system, two dozens of face images of the user are taken from different angles to register his/her own face. Once the face of the user is learned and registered, the system detects all the other faces for the given photo or video and then blurs them out. Our experiments show that it produces quick and correct results for the sample photos.

• Journal of Digital Convergence
• /
• v.17 no.6
• /
• pp.335-340
• /
• 2019

With the development of the media, pirate platforms and technologies are critical to the design of video content. Games based on online platforms and networking can help you develop games and expand your game as games are developed. Better yet. This paper is a major feature of the growth of the sandbox game that leads the game of InGame. Phenotypical 3D Dress Graphics You can study the usefulness of graphics based on doubles, the advantages of game characters, and space game graphics.

• International journal of advanced smart convergence
• /
• v.8 no.1
• /
• pp.9-17
• /
• 2019

In this article, we present a performance enhancement scheme for mobile applications by adopting persistent memory. The proposed scheme supports the deadline guarantee of real-time applications like a video player, and also provides reasonable performances for non-real-time applications. To do so, we analyze the program execution path of mobile software platforms and find two sources of unpredictable time delays that make the deadline-guarantee of real-time applications difficult. The first is the irregular activation of garbage collection in flash storage and the second is the blocking and time-slice based scheduling used in mobile platforms. We resolve these two issues by adopting high performance persistent memory as the storage of real-time applications. By maintaining real-time applications and their data in persistent memory, I/O latency can become predictable because persistent memory does not need garbage collection. Also, we present a new scheduler that exclusively allocates a processor core to a real-time application. Although processor cycles can be wasted while a real-time application performs I/O, we depict that the processor utilization is not degraded significantly due to the acceleration of I/O by adopting persistent memory. Simulation experiments show that the proposed scheme improves the deadline misses of real-time applications by 90% in comparison with the legacy I/O scheme used in mobile systems.

• The Korean Journal of Applied Statistics
• /
• v.35 no.1
• /
• pp.147-159
• /
• 2022

Nowadays, various social media platforms are widely spread and people closely use such platforms in daily life. By doing so, social influencers with a large number of subscribers, views, and comments have huge impact in our society. Following this trend, many companies are actively using influencers for marketing purpose to promote their products and services. In this study, we extract the speeches of influencers from videos for game marketing and analyze them using various text mining techniques. In the analysis, we distinguish game videos leading to successful marketing and failed marketing, and we explore and compare the linguistic features of the influencers for successful and failed marketings.