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pro vyhledávání: '"Liu, Ren"'
Nonlocal deformation sensing achieved by integrating atomic force microscopy indentation with nanodiamond-based orientation tracking features high precision and high spatial resolution, providing a useful technique for studying the mechanical propert
Externí odkaz:
http://arxiv.org/abs/2406.18577
Autor:
Liu, Ren, Shi, Dexin
Publikováno v:
Tutorials in Quantitative Methods for Psychology, Vol 16, Iss 5, Pp 442-456 (2020)
The purpose of this article is to demonstrate how to use diagnostic classification models (DCMs) in psychological rating scales and reflect on how DCMs differ from classical test theory (CTT) and item response theory (IRT) scoring approaches in terms
Externí odkaz:
https://doaj.org/article/8a794821823f4a50a3d090e65ad6f537
Autor:
Zhang, Zixu, Yu, Guangsheng, Sun, Caijun, Wang, Xu, Wang, Ying, Zhang, Ming, Ni, Wei, Liu, Ren Ping, Reeves, Andrew, Georgalas, Nektarios
Integrating sharded blockchain with IoT presents a solution for trust issues and optimized data flow. Sharding boosts blockchain scalability by dividing its nodes into parallel shards, yet it's vulnerable to the $1\%$ attacks where dishonest nodes ta
Externí odkaz:
http://arxiv.org/abs/2401.00632
Autor:
Cheung, Brian Chung Hang, Liu, Ren-Bao
The correlations of fluctuations are key to studying fundamental quantum physics and quantum many-body dynamics. They are also useful information for understanding and combating decoherence in quantum technology. Nonlinear spectroscopy and noise spec
Externí odkaz:
http://arxiv.org/abs/2309.00207
Autor:
Yu, Yong-Hong, Zhang, Rui-Zhi, Xu, Yue, Chen, Xiu-Qi, Zheng, Huijie, Li, Quan, Liu, Ren-Bao, Pan, Xin-Yu, Budker, Dmitry, Liu, Gang-Qin
As promising quantum sensors, nitrogen-vacancy (NV) centers in diamond have been widely used in frontier studies in condensed matter physics, material sciences, and life sciences. In practical applications, weak laser excitation is favorable as it re
Externí odkaz:
http://arxiv.org/abs/2308.13351
As a distributed learning, Federated Learning (FL) faces two challenges: the unbalanced distribution of training data among participants, and the model attack by Byzantine nodes. In this paper, we consider the long-tailed distribution with the presen
Externí odkaz:
http://arxiv.org/abs/2307.08324
Autor:
Jiang, Yanna, Ma, Baihe, Wang, Xu, Yu, Ping, Yu, Guangsheng, Wang, Zhe, Ni, Wei, Liu, Ren Ping
The demand for intelligent industries and smart services based on big data is rising rapidly with the increasing digitization and intelligence of the modern world. This survey comprehensively reviews Blockchained Federated Learning (BlockFL) that joi
Externí odkaz:
http://arxiv.org/abs/2305.04513
Autor:
Ma, Baihe, Wang, Xu, Lin, Xiaojie, Jiang, Yanna, Sun, Caijun, Wang, Zhe, Yu, Guangsheng, He, Ying, Ni, Wei, Liu, Ren Ping
Location privacy is critical in vehicular networks, where drivers' trajectories and personal information can be exposed, allowing adversaries to launch data and physical attacks that threaten drivers' safety and personal security. This survey reviews
Externí odkaz:
http://arxiv.org/abs/2305.04503
Learning various motor skills for quadrupedal robots is a challenging problem that requires careful design of task-specific mathematical models or reward descriptions. In this work, we propose to learn a single capable policy using deep reinforcement
Externí odkaz:
http://arxiv.org/abs/2303.15331
Extracting useful signals is key to both classical and quantum technologies. Conventional noise filtering methods rely on different patterns of signal and noise in frequency or time domains, thus limiting their scope of application, especially in qua
Externí odkaz:
http://arxiv.org/abs/2302.13530