• Journal of Communications and Networks
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• v.14 no.3
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• pp.286-295
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• 2012

To meet the increased demand of video-on-demand (VoD) services, peer-to-peer (P2P) mesh-based multiple video approaches have been recently proposed, where each peer is able to find a video segment interested without resort to the video server. However, they have not considered the constraint of the server's upload bandwidth and the fairness between upload and download amounts at each peer. In this paper, we propose a novel P2P VoD streaming system, named peer cache adaptation (PECAN) where each peer adjusts its cache capacity adaptively to meet the server's upload bandwidth constraint and achieve the fairness. For doing so, we first propose a new cache replacement algorithm that designs the number of caches for a segment to be proportional to its popularity. Second, we mathematically prove that if the cache capacity of a peer is proportional to its segment request rate, the fairness between upload and download amounts at each peer can be achieved. Third, we propose a method that determines each peer's cache capacity adaptively according to the constraint of the server's upload bandwidth. Against the proposed design objective, some selfish peers may not follow our protocol to increase their payoff. To detect such peers, we design a simple distributed reputation and monitoring system. Through simulations, we show that PECAN meets the server upload bandwidth constraint, and achieves the fairness well at each peer. We finally verify that the control overhead in PECAN caused by the search, reputation, and monitoring systems is very small, which is an important factor for real deployment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.78-85
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• 2007

With the advancement of the digital broadcasting and popularity of the Internet, recently, many studies are making on the digital watermarking for the copyright protection of digital data. This paper proposes the minimum modification method of motion vector to minimize the degradation of video quality, hiding subtitles of many language and information of OST(original sound track), character profiles, etc. as well as the copyright protection. Our proposed algorithm extracts feature vector by comparing motion vector data with watermark data, and minimize the modification of motion vectors by deciding the inversion of bit. Thus the degradation of video quality is minimized comparing to conventional algorithms. This algorithm also can check data integrity, and retrieve embedded hidden data simply and blindly. And our proposed scheme can be useful for conventional MPEG-1, -2 standards without any increment of bit rate in the compressed video domain. The experimental result shows that the proposed scheme obtains better video quality than other previous algorithms by about $0.5{\sim}1.5dB$.

• Clinics in Shoulder and Elbow
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• v.26 no.2
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• pp.162-168
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• 2023

Background: Reverse shoulder arthroplasty (RSA) has evolved continuously over recent years, with expanded indications and better outcomes. YouTube is one of the most popular sources globally for health-related information available to patients. Evaluating the reliability of YouTube videos concerning RSA is important to ensure proper patient education. Methods: YouTube was queried for the term "reverse shoulder replacement." The first 50 videos were evaluated using three different scores: Journal of the American Medical Association (JAMA) benchmark criteria, the global quality score (GQS), and the reverse shoulder arthroplasty-specific score (RSAS). Multivariate linear regression analyses were conducted to determine the presence of a relationship between video characteristics and quality scores. Results: The average number of views was 64,645.78±264,160.9 per video, and the average number of likes was 414 per video. Mean JAMA, GQS, and RSAS scores were 2.32±0.64, 2.31±0.82, and 5.53±2.43, respectively. Academic centers uploaded the highest number of videos, and surgical techniques/approach videos was the most common video content. Videos with lecture content predicted higher JAMA scores whereas videos uploaded by industry predicted lower RSAS scores. Conclusions: Despite its massive popularity, YouTube videos provide a low quality of information on RSA. Introducing a new editorial review process or developing a new platform for patients' medical education may be necessary. Level of evidence: Not applicable.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.494-506
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• 2003

Recently, explosive popularity of multimedia information has triggered the need for retrieving multimedia contents efficiently from the database including audio, video and images. In this paper, we propose an XML-based retrieval scheme and a data model that complement the weak aspects of annotation and conent based retrieval methods. The Property and hierarchy structure of image and video data are represented and manipulated based on the Multimedia Description Schema (MDS) that conforms to the MPEG-7 standard. For audio contents, pitch contours extracted from their acoustic features are converted into UDR string. Especially, to improve the retrieval performance, user's access pattern and frequency are utilized in the construction of an index. We have implemented a prototype system and evaluated its performance through various experiments.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.20-26
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• 2019

This study multi-dimensionally analyzes a sport documentary, All or Nothing: Manchester City, which is an original content on Prime Video, an American Over-The-Top (OTT) platform. Due to the success of South Korean soccer player Heung-min Son who plays Tottenham Hotspur of England, the popularity of the English Premier league is recently the greatest in South Korea along with the fact that soccer has been a popular sport for a long time. This study focuses on the success of the soccer club, Manchester City, which has become a rising star with its huge investment from United Arab Emirates; Manchester City won the league four times since 1992/1993 season. Also, during the 2017/2018 season, the background the documentary, Manchester City won the league title with new records, which shows the greatness of Manchester City. Especially, this study examines the documentary by 1) Story 2) Type of Scene 3) How to watch. Thus, this study explores not only the aspects of team-themed sport documentary that shows how and why Manchester City is excellent, but also the traits of the original content that explores the structure of the media platform.

• Journal of Digital Convergence
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• v.11 no.8
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• pp.315-320
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• 2013

The content of emerging hero is a material of many roles in the development of video content. In recent years, the hero story taking advantage of the powered suit are appearing, and the popularity is also high. The powered suit was first advocated by Robert Anson Heinlein called science fiction writer, and he contributed to creation of diverse and numerous powered suit content. In particular, the powered suit content combined with epic heroes has become popular with many crush to audiences. In this study, what is the powered suit content and analyzed characteristics within the content of the powered suit by content analysis of utilizing the powered suit materials. It is thought that the powered suit content is gaining popularity to a large audience because it focused on realistic, scientific storyline than a traditional hero narrative.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.775-782
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• 2005

In this paper, we propose multicast technique in order to reduce the required network bandwidth by n times, by merging the adjacent multicasts depending on the number of HENs (Head-End-Nodes) n that request the same video. Allowing new clients to immediately join an existing multicast through patching improves the efficiency of the multicast and offers services without any initial latency. A client might have to download data through two channels simultaneously, one for multicast and the other for patching. The more the frequency of requesting the video is, the higher the probability of caching it among HENs increases. Therefore, the requests for the cached video data can be served by HENs. Multicast from server is generated when the playback time exceeds the amount of cached video data. Since the interval of multicast can be dynamically expanded according to the popularity of videos, it can be reduced the server's workload and the network bandwidth. We perform simulations to compare its performance with that of conventional multicast. From simulation results, we confirm that the Proposed multicast technique offers substantially better performance.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1066-1077
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• 2004

Dramatic increase in the number of Internet users want highly qualified service of continuous media contents on the web. To solve these problems, we present two network caching schemes(PPC, PPCwP) which consider the characteristics of continuous media objects and user access pattern in this paper. While there are plenty of reasons to create rich media contents, delivering this high bandwidth contents over the internet presents problems such as server overload, network congestion and client-perceived latency. PPC scheme periodically calculates the popularity of objects based on the playback quantity and determines the optimal size of the initial fraction of a continuous media object to be cached in proportion to the calculated popularity. PPCwP scheme calculates the expected popularity using the series information and prefetches the expected initial fraction of newly created continuous media objects. Under the PPCwP scheme, the initial client-perceived latency and the data transferred from a remote server can be reduced and limited cache storage space can be utilized efficiently. Trace-driven simulation have been performed to evaluate the presented caching schemes using the log-files of iMBC. Through these simulations, PPC and PPCwP outperforms LRU and LFU in terms of BHR and DSR.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.423-429
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• 2016

The study evaluates user experiences of YouTube and Vimeo, typical Video-sharing websites, to suggest guidelines that are more user-cantered and useful. I did some literature research followed with evaluation of theoretical backgrounds, present conditions and future services. Also, I used the six principles of "Creating Pleasurable Interface" by Stephen Anderson to conduct an in-depth interview. The results indicate that YouTube needs to improve availability of its functions and usability by reducing advertisement. Vimeo needs to improve its popularity by increasing popular contents and add relationship service such as personal broadcasting system and community services. I expect this study will become a good resource for upgrading user experiences of Video-sharing websites. I also believe that this study can guide other studies about user experience in other fields.