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  1. 1 de sept. de 2021 · DOI: 10.1109/srds53918.2021.00042 Corpus ID: 244506279; Adaptive Erasure Coded Data Maintenance for Consensus in Distributed Networks @article{Jia2021AdaptiveEC, title={Adaptive Erasure Coded Data Maintenance for Consensus in Distributed Networks}, author={Yulei Jia and Guangping Xu and Chi Wan Sung and Salwa Mostafa}, journal={2021 40th International Symposium on Reliable Distributed Systems ...

  2. Guangping Xu. I am a teacher of School of Computer and Communication at Tianjin University of Technolog and a co-researcher at PDSD Lab of Nankai University. I received my Ph.D and M.S degree from Nankai University in 2009 and 2005, respectively. No.391 Binshui West Road, XiQing district, Tianjin, China.

  3. orcid.org › 0000/0001/5221-0331ORCID

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  4. Guangping Xu. Key Laboratory of Computer Vision and System (Ministry of Education), Tianjin University of Technology, Tianjin, China and Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin, China.

  5. Semantic Scholar extracted view of "Letters between two : correspondence between Lu Xun and Xu Guangping" by 魯迅 et al. Skip to search form Skip to main content Skip to account menu. Semantic Scholar's Logo. Search 218,698,836 papers from all fields of science. Search ...

  6. www.sandia.gov › research › 2022-winners2022 Winners – Research

    2022 Winners. Ultra-Stable Thermally Excellent Advancements in Material Strength. Guangping Xu, right, with his team of Sandia National Laboratories researchers, from left, Hongyou Fan, Haley Davis, Chad McCoy, Jens Schwarz and Melissa Mills, won an R&D 100 award for Ultra-Stable Thermally Excellent Advancements in Material Strength. Taking ...

  7. 25 de abr. de 2024 · Germano Resconi, Xiaolin Xu, Guanglin Xu: Introduction to Morphogenetic Computing. Studies in Computational Intelligence 703, Springer 2017, ISBN 978-3-319-57614-5, pp. 1-169. [j6] Guanglin Xu, Xiaolin Xu: Study on comprehensive evaluation model of attribute coordinate based on evaluation sample selection by K-means. J.