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Akademický článek

Seismogenic fault and it's rupture characteristics of the 21 May, 2021 Yangbi MS 6.4 earthquake: Analysis results from the relocation of the earthquake sequence

Autor: WANG Guangming, WU Zhonghai, PENG Guanling, LIU Zifeng, LUO Ruijie, HUANG Xiaolong, CHEN Haopeng

Publikováno v: Dizhi lixue xuebao, Vol 27, Iss 4, Pp 662-678 (2021)

According to China Earthquake Network Center (CENC), the MS 6.4 Yangbi earthquake struck northwestern Yunnan Province on 21 May, 2021 at 21:48(Beijing time). Figuring out the seismogenic fault and source rupture characteristics in time can provide a

Externí odkaz: https://doaj.org/article/6e5ba58b3768481bb9d98a9b851aeeb9

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Elementary School Students' and Teachers' Perceptions Towards Creative Mathematical Writing with Generative AI

Autor: Song, Yukyeong, Kim, Jinhee, Xing, Wanli, Liu, Zifeng, Li, Chenglu, Oh, Hyunju

While mathematical creative writing can potentially engage students in expressing mathematical ideas in an imaginative way, some elementary school-age students struggle in this process. Generative AI (GenAI) offers possibilities for supporting creati

Externí odkaz: http://arxiv.org/abs/2409.06723

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Students' Perceived Roles, Opportunities, and Challenges of a Generative AI-powered Teachable Agent: A Case of Middle School Math Class

Autor: Song, Yukyeong, Kim, Jinhee, Liu, Zifeng, Li, Chenglu, Xing, Wanli

Ongoing advancements in Generative AI (GenAI) have boosted the potential of applying long-standing learning-by-teaching practices in the form of a teachable agent (TA). Despite the recognized roles and opportunities of TAs, less is known about how Ge

Externí odkaz: http://arxiv.org/abs/2409.06721

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An Efficient and Multi-private Key Secure Aggregation for Federated Learning

Autor: Yang, Xue, Liu, Zifeng, Tang, Xiaohu, Lu, Rongxing, Liu, Bo

With the emergence of privacy leaks in federated learning, secure aggregation protocols that mainly adopt either homomorphic encryption or threshold secret sharing have been widely developed for federated learning to protect the privacy of the local

Externí odkaz: http://arxiv.org/abs/2306.08970

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