• Convergence Security Journal
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• v.12 no.3
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• pp.93-97
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• 2012

In this paper, we apply the next generation Internet TV solution, FLV has been designed and implemented. Currently being broadcast in the field to compress HD video in real time, as well as live Internet VOD services are available through the online system, the Internet LIVE broadcast and VOD service easy to operate and UCC services that support the solution. VOD video cameras and in real time using H264 CORECODEC to compress MPEC4, WMV, and real-time video streaming on the Internet, and phone system that supports the first, real-time recording of camera images featured nation's first real-time encoder system (Real time encoder system) is, Web and smart environment suitable for supporting the latest CORECODEC technology and software products. Second, the video can be played in MP4 player and customize your chat, and Custer (customizing) is a possible two-way Internet Broadcasting System. Third, CMS (Contents Management System) feature video content and course management content in real time via the Android phone and iPhone streaming service is available.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.421-431
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• 2008

Recently XML is becoming a de facto standard for online data exchange between heterogeneous systems and also the research of streaming XML data filtering comes into the spotlight. Since streaming XML data filtering technique needs rapid matching of queries with XML data, it is required that the query processing should be efficiently performed. Until now, most of researches focused only on partial sharing of path expressions or efficient predicate processing and they were work for time and space efficiency. However, if containment relationship between queries is previously calculated and the lowest level query is matched with XML data, we can easily get a result that high level queries can match with the XML data without any other processing. That is, using this containment technique can be another optimal solution for streaming XML data filtering. In this paper, we suggest an efficient XML data filtering based on prime number indexing and containment relationship between queries. Through some experimental results, we present that our suggested method has a better performance than the existing method. All experiments have shown that our method has a more than two times better performance even though each experiment has its own distinct test purpose.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.137-144
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• 2015

This study tried to anticipate the near future changes of domestic online video, music service and media usage through the status quo. The research group was focused on the twenties, University students because they are the active media contents users. It surveyed the students in Busan, and used the method of descriptive statistics analysis for the understanding of the present state and near future prospect. This study shows that almost half of them use both services, and three people out of ten are the heavy users who use the services for over 3 hours a week. The streaming method is higher proportion than download method in using type. They are getting accustomed to pay contents cost, but it couldn't be said the paying content cost has been established. Preferred contents genre appears to be the RMC(Ready Made Contents) such as existing broadcaster contents and movies. Notable result on media usage was the proportion of the so-called 'Zero-TV'. It was 32%, significantly higher than the proportion of the total population(4.4%). Integrating the analysis results, we can expect that the usage pattern will be changed gradually, thus the advent of various revenue models will emerge.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.819-825
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• 2014

In this paper, monaural ambient component extraction algorithm based on nonnegative matrix factorization (NMF) is described. The ambience component extraction algorithm in this paper is developed for audio upmixing system; Recent researches have shown that they can enhance listener envelopment if the extracted ambient signal is applied into the multichannel audio upmixing system. However, the conventional method stores all of the audio signal and processes all at once, so it cannot be applied to streaming system and digital signal processor (DSP) system. In this paper, the ambient component extraction algorithm based on on-line nonnegative matrix factorization is developed and evaluated to solve the problem. As a result of analysis of the processed signal with spectral flatness measures in the experiment, it was shown that the developed system can extract the ambient signal similarly with the conventional batch process system.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.41-49
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• 2010

Digital broadcasting system has various affecting factors unlike analog broadcasting system, and has possibility of no signal reception in case of errors due to characteristics of digital system. And, digital broadcasting system has monitoring system for error occurrences handling various factors. ATSC mobile DTV system uses legacy frequency and provides mobile broadcasting services, and also requires monitoring systems for monitoring online broadcasting services and reporting to administrator about interference or influence with legacy systems, and error situations. In this paper, we propose efficient monitoring system which monitors online broadcasting status of ATSC mobile DTV, reports on poor signal reception, video streaming failures to administrator, and maintains reliable digital broad ca sting system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.99-105
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• 2021

In addition to the OTT video production service represented by Nexflix and YouTube, a personalized recommendation system for content with artificial intelligence has become common. YouTube's personalized recommendation service system consists of two neural networks, one neural network consisting of a recommendation candidate generation model and the other consisting of a ranking network. Netflix's video recommendation system consists of two data classification systems, divided into content-based filtering and collaborative filtering. As the online platform-led content production is activated by the Corona Pandemic, the field of virtual influencers using artificial intelligence is emerging. Virtual influencers are produced with GAN (Generative Adversarial Networks) artificial intelligence, and are unsupervised learning algorithms in which two opposing systems compete with each other. This study also researched the possibility of developing AI platform based on individual recommendation and virtual influencer (metabus) as a core content of OTT in the future.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.705-712
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• 2022

The pandemic over the past three years has brought drastic changes in our lives, and those changes are now becoming a natural part of our daily lives. Daily life and economic activities based on online, such as video conferencing, remote classes, telecommuting, and online streaming services, have become daily routines after Corona. And the result of rapid development of communication and graphic technology is the metaverse. Therefore, the purpose of this study is to study the possibility from the perspective of public design for the correct use of the metaverse space of local governments. To this end, in this study, big data analysis was performed on 'local government', 'public design', and 'metaverse'. As a result of this study, we should actively use metaverse with high topic and potential as a space for local governments' promotion or discussion as a means to restore the reliability of local governments and overcome negative perceptions. In addition, it is necessary to actively reflect public design in order to increase the public reliability of local governments' metaverse.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.806-817
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• 2016

Opportunistic routing (OR) has been proposed as a viable approach to improve the performance of wireless multihop networks with lossy links. However, the exponential growth of the bandwidth-sensitive mobile traffic (e.g., mobile video streaming and online gaming) poses a great challenge to the performance of OR in term of bandwidth guarantee. To solve this problem, a novel mechanism is proposed to opportunistically forwarding data packets and provide bandwidth guarantee for the bandwidth-sensitive traffic. The proposal exploits the broadcast characteristic of wireless transmission and reduces the negative effect of wireless lossy links. First, the expected available bandwidth (EAB) and the expected transmission cost (ETC) under OR are estimated based on the local available bandwidth, link delivery probability, forwarding candidates, and prioritization policy. Then, the policies for determining and prioritizing the forwarding candidates is devised by considering the bandwidth and transmission cost. Finally, bandwidth-aware routing algorithm is proposed to opportunistically delivery data packets; meanwhile, admission control is applied to admit or reject traffic flows for bandwidth guarantee. Extensive simulation results show that our proposal consistently outperforms other existing opportunistic routing schemes in providing performance guarantee.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.2977-2997
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• 2018

In big data era, fresh data grows rapidly every day. More than 30,000 gigabytes of data are created every second and the rate is accelerating. Many organizations rely heavily on real time streaming, while big data stream computing helps them spot opportunities and risks from real time big data. Storm, one of the most common online stream computing platforms, has been used for big data stream computing, with response time ranging from milliseconds to sub-seconds. The performance of Storm plays a crucial role in different application scenarios, however, few studies were conducted to evaluate the performance of Storm. In this paper, we investigate the performance of Storm under different application scenarios. Our experimental results show that throughput and latency of Storm are greatly affected by the number of instances of each vertex in task topology, and the number of available resources in data center. The fault-tolerant mechanism of Storm works well in most big data stream computing environments. As a result, it is suggested that a dynamic topology, an elastic scheduling framework, and a memory based fault-tolerant mechanism are necessary for providing high throughput and low latency services on Storm platform.

• KSCI Review
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• v.14 no.1
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• pp.185-196
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• 2006

IIn this paper, we developed e-Leaning system based on open source software. We selected the Moodle that after compared the open source learning management systems. Moodle is APM(Apache, PHP, MySQL) based learning management system(LMS) support SCORM(Sharable Content Object Reference Model), a software package designed to help educators create quality online courses. One of the main advantages of Moodle over other systems is a strong grounding in social constructionist pedagogy. Also we integrated Moodle and legacy systems such as streaming service, webhard service, and short message service. Therefore this research showed that open source based e-Learning system include learning management system is stable and possible.