• Title/Summary/Keyword: 알고리듬,특이현상

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Spacecraft Moment of Inertial Estimation by Modified Rodrigues Parameters (Modified Rodrigues Parameter 기반의 인공위성 관성모멘트 추정 연구)

  • Bang, Hyo-Choong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.3
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    • pp.243-248
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    • 2010
  • This study addresses spacecraft moment of inertial estimation approach using Modified Rodrigues Parameters(MRP). The MRP offer advantage by avoiding singularity in Kalman Filter design for attitude determination caused by the norm constraint of quaternion parameters. Meanwhile, MRP may suffer singularity for large angular displacement, so that we designed appropriate reference attitude motion for accurate estimation. The proposed approach is expected to provide stable error covariance update with accurate spacecraft mass property estimation results.

Recommender Systems using SVD with Social Network Information (사회연결망정보를 고려하는 SVD 기반 추천시스템)

  • Kim, Min-Gun;Kim, Kyoung-jae
    • Journal of Intelligence and Information Systems
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    • v.22 no.4
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    • pp.1-18
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    • 2016
  • Collaborative Filtering (CF) predicts the focal user's preference for particular item based on user's preference rating data and recommends items for the similar users by using them. It is a popular technique for the personalization in e-commerce to reduce information overload. However, it has some limitations including sparsity and scalability problems. In this paper, we use a method to integrate social network information into collaborative filtering in order to mitigate the sparsity and scalability problems which are major limitations of typical collaborative filtering and reflect the user's qualitative and emotional information in recommendation process. In this paper, we use a novel recommendation algorithm which is integrated with collaborative filtering by using Social SVD++ algorithm which considers social network information in SVD++, an extension algorithm that can reflect implicit information in singular value decomposition (SVD). In particular, this study will evaluate the performance of the model by reflecting the real-world user's social network information in the recommendation process.