• 제목/요약/키워드: redundant data

검색결과 442건 처리시간 0.026초

Bandwidth Efficient Adaptive Forward Error Correction Mechanism with Feedback Channel

  • Ali, Farhan Azmat;Simoens, Pieter;de Meerssche, Wim Van;Dhoedt, Bart
    • Journal of Communications and Networks
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    • 제16권3호
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    • pp.322-334
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    • 2014
  • Multimedia content is very sensitive to packet loss and therefore multimedia streams are typically protected against packet loss, either by supporting retransmission requests or by adding redundant forward error correction (FEC) data. However, the redundant FEC information introduces significant additional bandwidth requirements, as compared to the bitrate of the original video stream. Especially on wireless and mobile networks, bandwidth availability is limited and variable. In this article, an adaptive FEC (A-FEC) system is presented whereby the redundancy rate is dynamically adjusted to the packet loss, based on feedback messages from the client. We present a statistical model of our A-FEC system and validate the proposed system under different packet loss conditions and loss probabilities. The experimental results show that 57-95%bandwidth gain can be achieved compared with a static FEC approach.

무선 인터넷 지역 방송에서 복수전송과 재전송기술의 효과 연구 (A Study on the Effect of Redundant and Repetitive Transmission for Wireless Internet Local Broadcasting)

  • 오종택
    • 한국통신학회논문지
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    • 제36권12B호
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    • pp.1468-1473
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    • 2011
  • 무선랜과 스마트폰이 활성화됨에 따라 IP 지역 방송 기술이 개발되고 있으며, 무선방송 채널 환경에서 오류발생시의 해결방법이 필요하다. 푸시 방송의 특성상 방송서버와 수신기가 일대일로 접속되는 것은 불가하며, 방송 채널 환경의 상태에 따라 방송 데이터 프레임의 길이 조정과 동일한 프레임을 여러 번 전송하는 횟수, 제한적인 재전송 요구 방법을 적용하여 방송 효율을 극대화시키는 기술이 본 논문에서 제안되었다.

패리티공간기법과 신경회로망을 이용한 원전 공정변수 추정 (Estimation of the Process Variable for Nuclear Power Plants Using the Parity Space Method and the Neural Network)

  • 오성헌;김대일;김건중
    • 대한전기학회논문지
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    • 제43권7호
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    • pp.1169-1177
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    • 1994
  • The function estimation characteristics of neural networks can be used sensor signal estimation of the nuclear power plants. In case of applying the neural network to the signal estimation of redundant sensors, it is an important problem that the redundant sensor signals used as the input signals of neural network should be validated. In this paper, we simplify the conventional parity space method in order to input the validated signal to the neural network and lso propose the sensor signal validation method, which estimates the reliable sensor output combining the neural network with the simplified parity space method. The acceptability of the proposed process variable estimation method is demonstrated by using the simulation data in safety injection accident of the nuclear power plant.

6축 아크 용접 로보트의 의사 역기구학적 동작 제어에 관한 연구 (A Study on the Pseudoinverse Kinematic Motion Control of 6-Axis Arc Welding Robot)

  • 최진섭;김동원;양성모
    • 한국정밀공학회지
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    • 제10권2호
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    • pp.170-177
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    • 1993
  • In robotic arc welding, the roll (rotation) of the torch about its direction vector does not have any effect on the welding operation. Thus we could use this redundant degree of greedom for the motion control of the robot manipulator. This paper presents an algorithm for the pseudo- inverse kinematic motion control of the 6-axis robot, which utilizes the above mentioned redunancy. The prototype welding operation and the tool path are also graphically simulated. Since the proposed algorithm requires only the position and normal vector of the weldine as an input data, it is useful for the CAD-based off-line programming of the arc welding robot. In addition, it also has the advantages of the redundant manipulator motion control, like singularity avoidance and collision free motion planning, when compared with the other motion control method based on the direct inverse kinematics.

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확장형 실시간 데이터 파이프라인 시스템 아키텍처 설계 (Design of Extended Real-time Data Pipeline System Architecture)

  • 신호승;강성원;이지현
    • 정보과학회 논문지
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    • 제42권8호
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    • pp.1010-1021
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    • 2015
  • 빅데이터 시스템은 대규모 로그 데이터를 수집하는 용도로 광범위하게 사용되고 있기 때문에 높은 성능을 갖는 것이 매우 중요하지만, 현재의 Hadoop 기반의 빅데이터 시스템은 중복 처리로 인하여 낮은 성능을 갖는 아키텍처적인 문제를 가지고 있다. 본 논문은 아키텍처 설계 개선을 통하여 Hadoop 기반 시스템의 낮은 성능 문제를 해결한다. 새로운 제안 아키텍처는 기존 아키텍처의 배치(Batch) 기반의 데이터 수집 방식을 개별처리 방식과 혼합한 수집 방법을 사용하고, 수집하는 데이터를 In-Memory 상에서 직접 분석하여 중복 처리를 배제하여 높은 성능을 제공하게 한다. 또한 제안 아키텍처는 기존 Hadoop 기반 아키텍처의 장점인 시스템 확장성을 가진다. 본 논문은 제안 아키텍처가 테스트 베드 환경에서 기존 아키텍처보다 데이터의 분석 처리 속도가 30%~35% 빠르고 확장성도 가진다는 것을 확인하였다.

역도 드는 동작의 조작도 해석 (Manipulability analysis of the weight lift)

  • 원경태;하인수;이지홍
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.1281-1284
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    • 1997
  • In this article, the configuration of weight lifer is analyzed using manipulibility polytope. After modeling body as 7-link redundant robot, optimal joint angles during first stage are searched by dynamic programmi technique and compared with standard reference data.

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철도차량 통신 네트워크(TCN)에서의 WTB 이중화에 대한 프로토콜 분석 플랫폼 (A Protocol Analysis Platform for the WTB Redundancy in Train Communication Network(TCN))

  • 최석인;손진근
    • 전기학회논문지P
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    • 제62권1호
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    • pp.23-29
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    • 2013
  • TCN(train communication network) standard was approved in 1999 by the IEC (IEC 61375-1) and IEEE (IEEE 1473-T) organizations to warrant a reliable train and equipment interoperability. TCN defines the set of communication vehicle buses and train buses. The MVB(multifunction vehicle bus) defines the data communication interface of equipment located in a vehicle and the WTB(wire train bus) defines the data communication interface between vehicles. The WTB and each MVB will be connected over a node acting as gateway. Also, to support applications demanding a high reliability, the standard defines a redundancy scheme in which the bus may be double-line and redundant-node implemented. In this paper we have presented protocol analysis platform for the WTB redundancy which is part of TCN system, to verify communication state of high-speed trains. As a confirmation of its validity, the technology described in this paper has been successfully applied to state monitoring and protocol verification of redundancy WTB based on TCN.

Proteomics Data Analysis using Representative Database

  • Kwon, Kyung-Hoon;Park, Gun-Wook;Kim, Jin-Young;Park, Young-Mok;Yoo, Jong-Shin
    • Bioinformatics and Biosystems
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    • 제2권2호
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    • pp.46-51
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    • 2007
  • In the proteomics research using mass spectrometry, the protein database search gives the protein information from the peptide sequences that show the best match with the tandem mass spectra. The protein sequence database has been a powerful knowledgebase for this protein identification. However, as we accumulate the protein sequence information in the database, the database size gets to be huge. Now it becomes hard to consider all the protein sequences in the database search because it consumes much computing time. For the high-throughput analysis of the proteome, usually we have used the non-redundant refined database such as IPI human database of European Bioinformatics Institute. While the non-redundant database can supply the search result in high speed, it misses the variation of the protein sequences. In this study, we have concerned the proteomics data in the point of protein similarities and used the network analysis tool to build a new analysis method. This method will be able to save the computing time for the database search and keep the sequence variation to catch the modified peptides.

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Privacy measurement method using a graph structure on online social networks

  • Li, XueFeng;Zhao, Chensu;Tian, Keke
    • ETRI Journal
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    • 제43권5호
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    • pp.812-824
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    • 2021
  • Recently, with an increase in Internet usage, users of online social networks (OSNs) have increased. Consequently, privacy leakage has become more serious. However, few studies have investigated the difference between privacy and actual behaviors. In particular, users' desire to change their privacy status is not supported by their privacy literacy. Presenting an accurate measurement of users' privacy status can cultivate the privacy literacy of users. However, the highly interactive nature of interpersonal communication on OSNs has promoted privacy to be viewed as a communal issue. As a large number of redundant users on social networks are unrelated to the user's privacy, existing algorithms are no longer applicable. To solve this problem, we propose a structural similarity measurement method suitable for the characteristics of social networks. The proposed method excludes redundant users and combines the attribute information to measure the privacy status of users. Using this approach, users can intuitively recognize their privacy status on OSNs. Experiments using real data show that our method can effectively and accurately help users improve their privacy disclosures.

구간데이터 정규화와 계층적 분석과정에의 활용 (Normalizing interval data and their use in AHP)

  • 김은영;안병석
    • 지능정보연구
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    • 제22권2호
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    • pp.1-11
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    • 2016
  • Entani and Tanaka(2007)는 불확실한 데이터를 처리하기에 적합한 구간 평가결과를 얻는 새로운 방법을 제시하였다. 무엇보다 그들의 방법은 구간 데이터를 정규화하여 redundant 데이터를 제거하는데 특징이 있다. 더 나가 정규화된 구간데이터를 활용하여 계층분석과정(AHP)에서 최종 구간 우선순위벡터를 도출한다. 이 논문에서는 구간 데이터의 정규화 목적을 달성하기 위해 구간 데이터의 꼭지점을 구하는 쉽고 간편한 휴리스틱 방법을 제시한다. 한편 간단한 검사법을 활용하여 정규화된 데이터를 활용하여 최종 구간 우선순위벡터를 도출하는 방법을 제시하고자 한다. 아울러 Entani and Tanaka(2007)가 제시한 대안간 지배관계 규명 방법을 확장한 지배관계 규명 방법을 제시하고자 한다.