Search Results - "Zhao, Kairan"

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  1. 1

    Examining the influence of vegetation on slope hydrology in Hong Kong using the capacitive resistivity technique by Niu, Qifei, Zhao, Kairan, Wang, Yu-Hsing, Wu, Yuxin

    Published in Journal of applied geophysics (01-06-2016)
    “…Vegetation essentially has both beneficial and detrimental hydrological effects on slope stability, and the balance between these effects changes throughout…”
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    Journal Article
  2. 2

    Evaluation of the capacitively coupled resistivity (line antenna) method for the characterization of vadose zone dynamics by Niu, Qifei, Wang, Yu-Hsing, Zhao, Kairan

    Published in Journal of applied geophysics (01-07-2014)
    “…The electrical resistivity survey, traditionally realized by the direct current (DC) resistivity method, has shown great value for characterizing vadose zone…”
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    Journal Article
  3. 3

    A Secure Intra-Regional-Inter-Regional Peer-to-Peer Electricity Trading System for Electric Vehicles by Zhao, Kairan, Zhang, Meng, Lu, Rongxing, Shen, Chao

    Published in IEEE transactions on vehicular technology (01-12-2022)
    “…Peer-to-peer (P2P) trading is becoming a prominent topic and demonstrating the development trend of integration with other theories in order to achieve an…”
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    Journal Article
  4. 4

    Coupled system of liquid air energy storage and air separation unit: A novel approach for large-scale energy storage and industrial gas production by Wang, Zhikang, Fan, Xiaoyu, Li, Junxian, Li, Yihong, Gao, Zhaozhao, Ji, Wei, Zhao, Kairan, Ma, Yuan, Chen, Liubiao, Wang, Junjie

    Published in Journal of energy storage (01-07-2024)
    “…Liquid air energy storage (LAES) emerges as a promising solution for large-scale energy storage. However, challenges such as extended payback periods, direct…”
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    Journal Article
  5. 5

    Scalability of memorization-based machine unlearning by Zhao, Kairan, Triantafillou, Peter

    Published 21-10-2024
    “…Machine unlearning (MUL) focuses on removing the influence of specific subsets of data (such as noisy, poisoned, or privacy-sensitive data) from pretrained…”
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  6. 6

    What makes unlearning hard and what to do about it by Zhao, Kairan, Kurmanji, Meghdad, Bărbulescu, George-Octavian, Triantafillou, Eleni, Triantafillou, Peter

    Published 03-06-2024
    “…Machine unlearning is the problem of removing the effect of a subset of training data (the ''forget set'') from a trained model without damaging the model's…”
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    Journal Article
  7. 7