• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.587-595
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• 2005

The vision for MPEG-21 is to define a multimedia framework to enable transparent and augmented use of multimedia resources across a wide range of networks and devices used by different communities MPEG-21 Event Reporting is required within the MPEG-21 Multimedia Framework in order to provide a standardized means for sharing information about Events amongst Peers and Users. There are several Time used in MPEG-21 Event Reporting. In this paper, we analyze and categorize various kinds of Time used in Event Reporting. And we define ERTimeType to be applied for every. Time used in Event Reporting and implement it by XML to support interoperability of standard. The ERTimeType structure we defined is established its objectivity as it is selected to 'ISO/IEC 21000-Part IS: Event Reporting WD 2.0'.

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.427-436
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• 2003

Many applications that are transport multimedia data through the networks should put existing network structure to practical use. Because the existing network structure and protocols are designed for static data transmission, multimedia applications with timing concept have limitations for using existence. In this paper, we present limitations of existing network structure for multimedia delivery, survey network element's characteristics in side view of multimedia application, present the streaming protocol for realtime multimedia traffic. Lastly, we consider a protocol stack for MPEG-21 Digital Item transmission using these existing protocols.

• Journal of Korea Game Society
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• v.20 no.5
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• pp.65-76
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• 2020

This paper studied cooperation and reciprocity mechanism by analyzing game mechanics of MMORPG 'World of Warcraft: Classic'. MMORPG is the genre of game where social interaction vigorously occurs. This study figured out the structure of cooperation based on evolutionary psychology, anthropology and social psychology through participatory observation. Four cooperation and reciprocity mechanism were drawn through investigating game mechanics like instance dungeon, clear role setting, item, soulbind. In addition, this paper suggests providing ideas of making cooperation mechanism in the field of game design.

• Journal of Korea Game Society
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• v.9 no.1
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• pp.33-41
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• 2009

In this paper we tried to figure out the types of real money trade of game items, and in order to study it we examined the Leveling System of MMORPG which is a perfect competitive market and how the closed structure of the game economy emits real money trade. The over production of the MMORPG's leveling system which is a perfect competitive market increases the amount of currency in circulation and then induces arbitrage due to mudfalation inside the game. In order to improve this problem, there are three methods of resolutions. The first is stabling the game economy by spontaneous order among the game users, but this is much local than the artificial order which takes a long time and evokes discrepance in MMORPG competitive characteristic. Secondly, legislational regulations from the government could improve the problem, but this method doesn't grant information or services as non-material labor in which it couldn't follow up the developing speed of the game market. Finally, delicate modulation among game items by the designer isn't possible to constrain them, and there is a limited reason that it couldn't control the increase of currency which is the main factor of arbitrage.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.1085-1088
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• 2006

MPEG-21 멀티미디어 프레임워크의 주요 기술 중 하나인 이벤트 리포팅은 MPEG-21 내에서 사용자, 피어, 디지털아이템 사이에서 발생하는 모든 보고 가능한 이벤트에 대한 정보를 공유하기 위한 표준적인 측정 방법과 인터페이스를 제공한다는 점에서 그 중요성을 가진다. 현재 MPEG을 중심으로 MPEG-21 이벤트 리포팅에 대한 연구가 진행되고 있으나 이를 구현한 예가 극히 드물다. 본 논문은 MPEG-21의 이벤트 리포팅 표준 기술을 바탕으로 이벤트 리포트 요구 생성 도구의 설계 및 구현 그리고 구현 결과에 대해 논하였다. 이벤트 리포트 요구 생성 도구는 메인 프레임, 입력 다이얼로그, 그리고 생성 프로세스로 구성되어 있다. 이벤트 리포트 요구의 표현언어는 XML이며 XML 표준 문법과 이벤트 리포트 요구 디지털 아이템 구조에 맞게 생성되도록 설계되었다.

• Broadcasting and Media Magazine
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• v.14 no.2
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• pp.113-122
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• 2009

RoSE(representation of sensory effects)기술은 A/V미디어에서 제공하는 시청각 효과 이외에 바람/향기/진동 등의 실감효과를 팬/발향기/진동의자 등의 다양한 디바이스와 연동시킴으로써 미디어의 실감효과를 극대화하는 기술이다. 2007년 10월 82차 MPEG회의에 처음 제안된 RoSE프레임워크는 SE(sensory effects), USP(user sensory preferences), SDC(sensory device capabilities), SDCom(sensory device commands)의 표준아이템이 상호 연동하는 시스템 구조를 갖는다. 지난 2월 87차 MPEG로잔(Lausanne)미팅에서는 이들을 현실과 가상을 연결하는 인터페이스 표준을 정하는 MPEG-V(ISO/IEC 23005) 프로젝트의 Part 2(control information)와 Part 3(sensory information)으로 분리 배치하고 오는 7월 89차 런던 미팅에서 CD(committee drait)를 목표로 표준화를 진행하고 있다. 본 논문에서는 XML에 기반한 이들 4개의 표준 아이템 구성을 살펴보고 현재까지 MPEG 에서 진행되어 온 RoSE표준화 과정을 소개한다.

• Journal of Korea Technology Innovation Society
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• v.8 no.2
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• pp.860-885
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• 2005

This study relates to develop a quantitative method through which promising technology-based business items can be discovered and selected. For this study, we utilized patent trend analysis, technology-industry concordance analysis, and keyword co-occurrence analysis of US patents. By analyzing patent trends and technology-industry concordance, we were able to find out the emerging industry trends : prevalence of bio industry, service industry, and B2C business. From the direct and co-occurrence analysis of newly discovered patent keywords in the year, 2000, 28 promising business item candidates were extracted. Finally, the promising item candidates were prioritized using 4 business attractiveness determinants; market size, product life cycle, degree of the technological innovation, and coincidence with the industry trends. This result implicates that reliable discovery and selection of promising technology-based business items can be performed by a quantitative, objective and low- cost process using knowledge discovery method from patent database instead of peer review.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.41-43
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• 2018

소설 데이터는 인터넷 상의 수 많은 개인과 개인의 상호 작용에 의하여 연결되어 있으며, 이러한 데이터를 분석하여, 분석 대상에 내재하고 있는 구조와 특성을 파악하는 일은 중요하다. 특히, 개인 추천을 위해서는 개별 데이터들의 관계 그래프를 활용하여 빠르고 정확하게 추천 값을 도출하는 것이 효율적이다. 하지만, 기존 추천 기법으로는 신규 사용자와 아이템이 끊임없이 등장하는 상황을 즉각적으로 반영하기가 어렵고, 또한 많은 결측값을 포함하는 sparse 한 데이터일 경우에는 추천 시스템의 연산 공간과 시간에 많은 제약이 있다. 이에 본 논문에서는 Spark GraphX 를 활용한 개인 추천 시스템을 설계 및 개발하였으며, 이를 통하여 사용자와 아이템간에 내재하는 복합 요인이 반영된 그래프 기반 추천을 실행하여, 개인 추천 결과의 우수성을 확인하였다.

• Electronics and Telecommunications Trends
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• v.25 no.2
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• pp.142-151
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• 2010

LED는 화합물 반도체 특성을 이용해, 전기신호를 적외선 또는 빛으로 주고 받는 반도체의 일종으로 가정용 가전제품, 리모콘, 전광판, 표시기, 각종 자동화기기 등에 사용된다. LED는 최근 컴퓨터, 냉장고, 가로등, 주택용 일반 조명에 이르기까지 반도체산업을 뛰어넘을 차세대 산업군으로 주목받고 있다. LED 조명산업은 저탄소 녹색성장의 핵심축이고, 무(無)수은 친환경 아이템으로 포스트 교토의 기후협약, 저탄소사회 구현을 앞당기는 미래산업이다. 본 고에서는 LED 조명의 가치사슬 및 국내외 산업 구조를 분석하고 결론에서 시사점을 도출하고자 한다.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.119-137
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• 2022

Recent recommendation system studies apply various deep learning models to represent user and item interactions better. One of the noteworthy studies is ONCF(Outer product-based Neural Collaborative Filtering) which builds a two-dimensional interaction map via outer product and employs CNN (Convolutional Neural Networks) to learn high-order correlations from the map. However, ONCF has limitations in recommendation performance due to the problems with CNN and the absence of side information. ONCF using CNN has an inductive bias problem that causes poor performances for data with a distribution that does not appear in the training data. This paper proposes to employ a Vision Transformer (ViT) instead of the vanilla CNN used in ONCF. The reason is that ViT showed better results than state-of-the-art CNN in many image classification cases. In addition, we propose a new architecture to reflect side information that ONCF did not consider. Unlike previous studies that reflect side information in a neural network using simple input combination methods, this study uses an independent auxiliary classifier to reflect side information more effectively in the recommender system. ONCF used a single latent vector for user and item, but in this study, a channel is constructed using multiple vectors to enable the model to learn more diverse expressions and to obtain an ensemble effect. The experiments showed our deep learning model improved performance in recommendation compared to ONCF.