• Title/Summary/Keyword: PR 성능향상

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A Dual Noise-Predictive Partial Response Decision-Feedback Equalizer for Perpendicular Magnetic Recording Channels (수직 자기기록 채널을 위한 쌍 잡음 예측 부분 응답 결정 궤환 등화기)

  • 우중재;조한규;이영일;홍대식
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.9C
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    • pp.891-897
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    • 2003
  • Partial response maxim likelihood (PRML) is a powerful and indispensable detection scheme for perpendicular magnetic recording channels. The performance of PRML can be improved by incorporating a noise prediction scheme into branch metric computations of Viterbi algorithm (VA). However, the systems constructed by VA have shortcomings in the form of high complexity and cost. In this connection, a new simple detection scheme is proposed by exploiting the minimum run-length parameter d=1 of RLL code. The proposed detection scheme have a slicer instead of Viterbi detector and a noise predictor as a feedback filter. Therefore, to improve BER performance, the proposed detection scheme is extended to dual detection scheme for improving the BER performance. Simulation results show that the proposed scheme has a comparable performance to noise-predictive maximum likelihood (NPML) detector with less complexity when the partial response (PR) target is (1,2,1).

Characteristic of Data Distribution and Data Replication based Model of LDAP System in High Performance Grid Environments (고성능 Grid 환경에서의 LDAP 시스템의 분산모델과 복제모델의 특성)

  • 권성호;김희철
    • Journal of Korea Society of Industrial Information Systems
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    • v.9 no.1
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    • pp.77-84
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    • 2004
  • Recently, as the number of entities participating in the Grid system increased, the response time of LDAP system became inadequate. Consequently, we have to design new LDAP that suitable for high performance Grid environments. For this, researches about analysis of performance LDAP system are needed firstly. However, because researches are focused mostly on read operation optimized environments, so these result of researches are not directly applied to high performance Grid environments that write operation occupies most. In this paper, we provide overall results of analysis of performance of LDAP system with respect to number of node, query arrival rate, probability of read and so on. The analysis is based on in analytic performance model by applying the M/M/1 queuing model. Finally, based on the results, we suggest the direction for the design of high performance LDAP system and this research results can be applied as basic materials to design of GIS in high performance Grid environments as well as.

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Design and Implementation of Assisted GPS Navigation Systems Using TPEG Protocol of Terrestrial DMB Data Services (지상파 DMB 데이터 서비스의 TPEG프로토콜을 이용한 Assisted GPS 항법 시스템의 설계 및 구현)

  • Kim, Byung-Soo;Min, Seung-Wook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.11B
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    • pp.1618-1623
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    • 2010
  • In this paper, we propose a new assisted global positioning system (A-GPS) using terrestrial digital multimedia broadcasting (T-DMB) data services. Because of the weak signal strength from GPS satellite and the signal blockage, it is difficult for the telematics terminal to determine the position in urban area. Proposed A-GPS system calculates pseudo range (PR) from timing information of GPS satellites and obtains the satellite information such as ephemeris from T-DMB station to determine the current position. Compared to conventional GPS system, the proposed system has better performance in terms of the fast time to first fix (TTFF), low horizontal dilution of precision (HDOP). Experimental results show that the proposed system is a feasible and robust solution.

Hallucination Detection for Generative Large Language Models Exploiting Consistency and Fact Checking Technique (생성형 거대 언어 모델에서 일관성 확인 및 사실 검증을 활 용한 Hallucination 검출 기법)

  • Myeong Jin;Gun-Woo Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.461-464
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    • 2023
  • 최근 GPT-3 와 LLaMa 같은 생성형 거대 언어모델을 활용한 서비스가 공개되었고, 실제로 많은 사람들이 사용하고 있다. 해당 모델들은 사용자들의 다양한 질문에 대해 유창한 답변을 한다는 이유로 주목받고 있다. 하지만 LLMs 의 답변에는 종종 Inconsistent content 와 non-factual statement 가 존재하며, 이는 사용자들로 하여금 잘못된 정보의 전파 등의 문제를 야기할 수 있다. 이에 논문에서는 동일한 질문에 대한 LLM 의 답변 샘플과 외부 지식을 활용한 Hallucination Detection 방법을 제안한다. 제안한 방법은 동일한 질문에 대한 LLM 의 답변들을 이용해 일관성 점수(Consistency score)를 계산한다. 거기에 외부 지식을 이용한 사실검증을 통해 사실성 점수(Factuality score)를 계산한다. 계산된 일관성 점수와 사실성 점수를 활용하여 문장 수준의 Hallucination Detection 을 가능하게 했다. 실험에는 GPT-3 를 이용하여 WikiBio dataset 에 있는 인물에 대한 passage 를 생성한 데이터셋을 사용하였으며, 우리는 해당 방법을 통해 문장 수준에서의 Hallucination Detection 성능이 baseline 보다 AUC-PR scores 에서 향상됨을 보였다.