• Title/Summary/Keyword: Comunication System

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One-Time Overlay Multicast Techniques Considering Receipt Quality for m-to-n Comunication over Large Internet (다자간의 통신환경에서 다양한 수신품질을 고려한 One-Time 오버레이 멀티캐스트 기법에 관한 연구)

  • Yoon Mi-youn;Kim Ki-Young;Kim Dae-Won;Shin Yong-Tae
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.1B
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    • pp.27-38
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    • 2005
  • IP Multicast has not been deployed because of hardware problems. So a new scheme that is called Overlay Multicast for group communication has been emerged. It supports IP Multicast functions, which is located on application level. For developing it, we have been focused on efficient overlay tree construction among group members with low stretch and stress. However, we should consider a variety of transmission or receipt condition since a real internet environment has users with various transmission/receipt rates. Thus, we make one-time source specific tree depending on required bandwidth informationof group members when a member requests data transmission. Our mechanism provides satisfied data quality limited maximum transmission rate of the source to each group members. Furthermore, we manage a large group enough as distributing control information to cores that are designated membersfor maintaining host member information. Lastly, we prove that our tree guarantees data quality to each group members, and show low tree consruction time is required. In addition, for evaluating group scalability, we analyze control information increasing rate via group size, and validate its scalability.

Design and Implementation of Interactive Search Service based on Deep Learning and Morpheme Analysis in NTIS System (NTIS 시스템에서 딥러닝과 형태소 분석 기반의 대화형 검색 서비스 설계 및 구현)

  • Lee, Jong-Won;Kim, Tae-Hyun;Choi, Kwang-Nam
    • Journal of Convergence for Information Technology
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    • v.10 no.12
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    • pp.9-14
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    • 2020
  • Currently, NTIS (National Technology Information Service) is building an interactive search service based on artificial intelligence technology. In order to understand users' search intentions and provide R&D information, an interactive search service is built based on deep learning models and morpheme analyzers. The deep learning model learns based on the log data loaded when using NTIS and interactive search services and understands the user's search intention. And it provides task information through step-by-step search. Understanding the search intent makes exception handling easier, and step-by-step search makes it easier and faster to obtain the desired information than integrated search. For future research, it is necessary to expand the range of information provided to users.