• Title/Summary/Keyword: Video Content Distribution

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Video Learning Enhances Financial Literacy: A Systematic Review Analysis of the Impact on Video Content Distribution

  • Yin Yin KHOO;Mohamad Rohieszan RAMDAN;Rohaila YUSOF;Chooi Yi WEI
    • Journal of Distribution Science
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    • v.21 no.9
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    • pp.43-53
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    • 2023
  • Purpose: This study aims to examine the demographic similarities and differences in objectives, methodology, and findings of previous studies in the context of gaining financial literacy using videos. This study employs a systematic review design. Research design, data and methodology: Based on the content analysis method, 15 articles were chosen from Scopus and Science Direct during 2015-2020. After formulating the research questions, the paper identification process, screening, eligibility, and quality appraisal are discussed in the methodology. The keywords for the advanced search included "Financial literacy," "Financial Education," and "Video". Results: The results of this study indicate the effectiveness of learning financial literacy using videos. Significant results were obtained when students interacted with the video content distribution. The findings of this study provide an overview and lead to a better understanding of the use of video in financial literacy. Conclusions: This study is important as a guide for educators in future research and practice planning. A systematic review on this topic is the research gap. Video learning was active learning that involved student-centered activities that help students engage with financial literacy. By conducting a systematic review, researchers and readers may also understand how extending an individual's financial literacy may change after financial education.

Proposed Open Source Model for Video Offline Distribution using Cinema DRM for Home Users

  • Pardeshi, Sunil;Kwon, Soon Chul;Lee, Seung Hyun;Hamacher, Alaric
    • International Journal of Internet, Broadcasting and Communication
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    • v.7 no.1
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    • pp.10-14
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    • 2015
  • Video Content owners seek to squeeze the maximum amount of revenue from their assets via distribution into more territories. Digital Cinema Package(DCP), trusted solution to distribute protected content to theaters, caters to relatively small user base, which limits revenue. With the growth of the Internet & other digital media, the economics of media content has changed dramatically. Security remains main concern to deliver content to millions of consumers using intelligent digital display devices like Tablets, Smartphones, Smart TVs, Desktop & Laptop. By making the video content available to this segment securely, content owners will benefit from increased revenue. Through this paper we propose Open Source HomeDCP model to distribute the content to home users for offline viewing. We propose to include other open source CODEC than JPEG2000/MPEG2, which are specifically designed for theatrical performance. Final image size will be further reduced considering the display device resolution where video will be finally played. Key Delivery Message(KDM) system to be altered to suit new devices. This will be a big boost to Content Economy as content owners would be able to distribute the content securely to the wider audience & ensure more revenue.

Actual Feeling Service Model for Video-Media Contents (영상미디어콘텐츠에 대한 실감 서비스 모델)

  • Lee, Ji-Hye;Yoon, Yong-Ik
    • Journal of Digital Contents Society
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    • v.10 no.3
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    • pp.453-459
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    • 2009
  • In recently, as the interest of media contents increase among internet users, a variety of media contents are circulated in the web. Especially, video-media content in media contents attracts internet user's interest. In conjunction with web 2.0, internet users open and share their making contents by themselves. Their attitude about accepting media contents is not passive but aggressive. Additionally, they create new form of distribution of the flow. Video media content for distribution on the Web is created by experts to a professional content, but Web 2.0 era, the UCC (User Create Contents) in the form of self-produced content is the most. The generated media by the general internet users, but self-produced content, provides video information only and has limitations. To satisfy internet users as consumers in the web 2.0 eras, it has needed to provide actual feeling contents that add various effects not just simple media. Therefore, this paper represents the existing media content with simple information based on the concept of ontology and the meaning to the subject for the media content. We will provide an actual feeling how to offer the configuration of a service model (AF-VS : Actual Feeling Video Service).

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Research on Online Video Content Distributors in China (중국 온라인 동영상 플랫폼의 발전 현황과 사례 분석)

  • Park, Sung-Eun;Lee, Gun-Woong
    • The Journal of the Korea Contents Association
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    • v.16 no.5
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    • pp.137-147
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    • 2016
  • The Online video content service developed into one of the most popular network service of internet and mobile users. The number of online video content distributors are rapidly increasing in China. But, at present, Online video content distributors in china has the following problems: severe similar content, copyright infringement issue and profit model absence. The purpose of this study is to analyze the development of these distributors, especially YoukuTudou and iQiyiPPS. This study also reviews the stage of development and current situation of online video content market in china.

Development and Distribution of Deep Fake e-Learning Contents Videos Using Open-Source Tools

  • HO, Won;WOO, Ho-Sung;LEE, Dae-Hyun;KIM, Yong
    • Journal of Distribution Science
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    • v.20 no.11
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    • pp.121-129
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    • 2022
  • Purpose: Artificial intelligence is widely used, particularly in the popular neural network theory called Deep learning. The improvement of computing speed and capability expedited the progress of Deep learning applications. The application of Deep learning in education has various effects and possibilities in creating and managing educational content and services that can replace human cognitive activity. Among Deep learning, Deep fake technology is used to combine and synchronize human faces with voices. This paper will show how to develop e-Learning content videos using those technologies and open-source tools. Research design, data, and methodology: This paper proposes 4 step development process, which is presented step by step on the Google Collab environment with source codes. This technology can produce various video styles. The advantage of this technology is that the characters of the video can be extended to any historical figures, celebrities, or even movie heroes producing immersive videos. Results: Prototypes for each case are also designed, developed, presented, and shared on YouTube for each specific case development. Conclusions: The method and process of creating e-learning video contents from the image, video, and audio files using Deep fake open-source technology was successfully implemented.

Flexible Video Authentication based on Aggregate Signature

  • Shin, Weon;Hong, Young-Jin;Lee, Won-Young;Rhee, Kyung-Hyune
    • Journal of Korea Multimedia Society
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    • v.12 no.6
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    • pp.833-841
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    • 2009
  • In this paper we propose a flexible video authentication scheme based on aggregate signature, which provides authenticity of a digital video by means of cryptographic signature to guarantee right of users. In contrast to previous works, the proposed scheme provides flexible usages on content distribution system, and it allows addition of new contents to the signed contents and deletion of some parts of the signed contents. A modification can be done by content owner or others. Although contents are modified by one or more users, our scheme can guarantee each user's right by aggregation of the each user's signatures. Moreover, proposed scheme has half size of Digital Signature Algorithm (DSA) with comparable security.

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Content based Video Copy Detection Using Spatio-Temporal Ordinal Measure (시공간 순차 정보를 이용한 내용기반 복사 동영상 검출)

  • Jeong, Jae-Hyup;Kim, Tae-Wang;Yang, Hun-Jun;Jin, Ju-Kyong;Jeong, Dong-Seok
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.2
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    • pp.113-121
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    • 2012
  • In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.

A case study of blockchain-based public performance video platform establishment: Focusing on Gyeonggi Art On, a new media art broadcasting station in Gyeonggi-do (블록체인 기반 공연영상 공공 플랫폼 구축 사례 연구: 경기도 뉴미디어 예술방송국 경기아트온을 중심으로)

  • Lee, Seung Hyun
    • Journal of Service Research and Studies
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    • v.13 no.1
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    • pp.108-126
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    • 2023
  • This study explored the sustainability of a blockchain-based cultural art performance video platform through the construction of Gyeonggi Art On, a new media art broadcasting station in Gyeonggi-do. In addition, the technical limitations of video content transaction using block chain, legal and institutional issues, and the protection of personal information and intellectual property rights were reviewed. As for the research method, participatory observation methods such as in-depth interviews with developers and operators and participation in meetings were conducted. The researcher participated in and observed the entire development process, including designing and developing blockchain nodes, smart contracts, APIs, UI/UX, and testing interworking between blockchain and content distribution services. Research Question 1: The results of the study on 'Which technology model is suitable for a blockchain-based performance video content distribution public platform?' are as follows. 1) The blockchain type suitable for the public platform for distribution of art performance video contents based on the blockchain is the private type that can be intervened only when the blockchain manager directly invites it. 2) In public platforms such as Gyeonggi ArtOn, among the copyright management model, which is an art based on NFT issuance, and the BC token and cloud-based content distribution model, the model that provides content to external demand organizations through API and uses K-token for fee settlement is suitable. 3) For public platform initial services such as Gyeonggi ArtOn, a closed blockchain that provides services only to users who have been granted the right to use content is suitable. Research question 2: What legal and institutional problems should be reviewed when operating a blockchain-based performance video distribution public platform? The results of the study are as follows. 1) Blockchain-based smart contracts have a party eligibility problem due to the nature of blockchain technology in which the identities of transaction parties may not be revealed. 2) When a security incident occurs in the block chain, it is difficult to recover the loss because it is unclear how to compensate or remedy the user's loss. 3) The concept of default cannot be applied to smart contracts, and even if the obligations under the smart contract have already been fulfilled, the possibility of incomplete performance must be reviewed.

How to Search and Evaluate Video Content for Online Learning (온라인 학습을 위한 동영상 콘텐츠 검색 및 평가방법)

  • Yong, Sung-Jung;Moon, Il-Young
    • Journal of Advanced Navigation Technology
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    • v.24 no.3
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    • pp.238-244
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    • 2020
  • The development and distribution rate of smartphones have progressed so rapidly that it is safe for the entire nation to use them in the smart age, and the use of smartphones has become an essential medium for the use of domestic media content, and many people are using various contents regardless of gender, age, or region. Recently, various media outlets have been consuming video content for online learning, indicating that learners utilize video content online for learning. In the previous research, satisfaction studies were conducted according to the type of content, and the improvement plan was necessary because no research was conducted on how to evaluate the learning content itself and provide it to learners. In this paper, we would like to propose a system through evaluation and review of learning content itself as a way to improve the way of providing video content for learning and quality learning content.

Detecting near-duplication Video Using Motion and Image Pattern Descriptor (움직임과 영상 패턴 서술자를 이용한 중복 동영상 검출)

  • Jin, Ju-Kyong;Na, Sang-Il;Jenong, Dong-Seok
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.4
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    • pp.107-115
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    • 2011
  • In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.