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Enhanced Anomalous Hall Effect of Pt on an Antiferromagnetic Insulator with Fully Compensated Surface

Chinese Physics Letters 2022年第10期39卷 60-65页

作者： Yu Bai Zhe Wang Na Lei Wisal Muhammad Lifeng Xiang Qiang Li Huilin Lai Yinyan Zhu Wenbing Wang Hangwen Guo Lifeng Yin Ruqian Wu Jian Shen State Key Laboratory of Surface Physics and Institute for Nanoelectronics Devices and Quantum Computing Fudan UniversityShanghai 200433China Shanghai Qi Zhi Institute Shanghai 200232China Department of Physics Fudan UniversityShanghai 200433China Zhangjiang Fudan International Innovation Center Fudan UniversityShanghai 201210China Shanghai Research Center for Quantum Sciences Shanghai 201315China Fert Beijing Institute BDBCSchool of Electronic and Information EngineeringBeihang UniversityBeijing 100191China Department of Physics and Astronomy University of CaliforniaIrvineCalifornia 92697USA Collaborative Innovation Center of Advanced Microstructures Nanjing 210093China

We report a significantly enhanced anomalous Hall effect(AHE)of Pt on antiferromagnetic insulator thin film(3-unit-cell La_(0.7)Sr_(0.3)MnO_(3),abbreviated as LSMO),which is one order of magnitude larger than that of Pt on other ferromagnetic(e.g.Y_(3)Fe_(5)O_(12))and antiferromagnetic(***_(2)O_(3))insulator thin *** experiments demonstrate that the antiferromagnetic La_(0.7)Sr_(0.3)MnO_(3)with fully compensated surface suppresses the positive anomalous Hall resistivity induced by the magnetic proximity effect and facilitates the negative anomalous Hall resistivity induced by the spin Hall *** changing the substrate’s temperature during Pt deposition,we observed that the diffusion of Mn atoms into Pt layer can further enhance the *** anomalous Hall resistivity increases with increasing temperature and persists even well above the Neel temperature(T_(N))of *** Monte Carlo simulations manifest that the unusual rise of anomalous Hall resistivity above T_(N)originates from the thermal induced magnetization in the antiferromagnetic insulator.

关键词： effect ferromagnetic resistivity

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Expert with Outlier Exposure for Continual Learning of New Diseases

Expert with Outlier Exposure for Continual Learning of New D...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Zhengjing Xu Kanghao Chen Wei-Shi Zheng Zhijun Tan Xiaobo Yang Ruixuan Wang School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing MOE China State Key Laboratory of Dampness Syndrome of Chinese Medicine Guangzhou China Department of Network Intelligence Peng Cheng Laboratory Shenzhen China

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Current intelligent diagnosis systems struggle to continually learn to diagnose more and more diseases due to catastrophic forgetting of old knowledge when learning new knowledge. Although storing small old data for subsequent continual learning can effectively help alleviate the forgetting issue, the heavy data imbalance between old classes and to-be-learned new classes in classifier training often causes biased prediction towards the new classes just learned by the updated classifier. In this study, an outlier detection technique is novelly applied to train an additional expert classifier for new classes to help alleviate the class imbalance issue and discriminate the learned new classes from old classes during inference (instead of the training phase). Specially, the stored small data of old classes are considered as outliers during training the expert classifier, such that the output probability distributions from the expert classifier are expected to be obviously different between test data of the old classes and those of the new classes. Such difference between old classes and new classes can be used to fine-tune the original output from the updated classifier which is responsible for prediction of all learned (old and new) classes. During inference, a novel ensemble strategy is proposed to combine the predictions from the updated classifier, the expert classifier, and the previously learned old classifier. The proposed learning and inference framework can be easily combined with existing continual learning strategies. Empirical evaluations on three medical image datasets and one natural image dataset show that the proposed framework can effectively improve continual learning performance.

关键词： Training Biological system modeling Probability distribution Bioinformatics Anomaly detection Medical diagnostic imaging Diseases

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Application of Blockchain Based on Fabric Consensus Network Model in Secure Encryption of Educational Information

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Applied Mathematics and Nonlinear Sciences 2024年第1期9卷

作者： Yuan, Bo Wu, Faguo School of Computer Science and Engineering Beihang University Beijing100191 China State Key Laboratory of Software Development Environment Beihang University Beijing100191 China Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Beijing100191 China

This paper combines blockchain technology with an information encryption algorithm to design a blockchain-based educational information protection model. It focuses on the role of Fabric architecture and blockchain data structure for information security protection. A chaotic cipher is used to encrypt the information, combined with the iteration of nonlinear functions to generate pseudo-random numbers to realize the unpredictability of the information. Using symbolic dynamics to obtain the control parameter or initial value of the chaotic mapping, combining the sequence of symbols to solve for another value, and finally presenting it in the form of ciphertext in the client for the data accessor to query and access the data. The effectiveness and practicality of educational information security encryption are examined by applying the model of constructed information protection. The results show that the response time of the blockchain module changes depending on the information, and the response time is basically maintained between 2.2 seconds and 2.4 seconds, which is in a reasonable range. In educational information security defense, the information protection model is able to effectively defend the network against attacks, with the highest number of attacks against the attack named external, with the highest number close to 50 million. © 2023 Bo Yuan et al., published by Sciendo.

关键词： Cryptography

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HELCFL: high-efficiency and low-cost federated learning in heterogeneous mobile-edge computing 22

HELCFL: high-efficiency and low-cost federated learning in h...

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Proceedings of the 2022 Conference & Exhibition on Design, Automation & Test in Europe

作者： Yangguang Cui Kun Cao Junlong Zhou Tongquan Wei East China Normal University Shanghai China and State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Jinan University Guangzhou China Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9783981926361

Federated Learning (FL), an emerging distributed machine learning (ML), empowers a large number of embedded devices (e.g., phones and cameras) and a server to jointly train a global ML model without centralizing user private data on a server. However, when deploying FL in a mobile-edge computing (MEC) system, restricted communication resources of the MEC system, heterogeneity and constrained energy of user devices have a severe impact on FL training efficiency. To address these issues, in this article, we design a distinctive FL framework, called HELCFL, to achieve high-efficiency and low-cost FL training. Specifically, by analyzing the theoretical foundation of FL, our HELCFL first develops a utility-driven and greedy-decay user selection strategy to enhance FL performance and reduce training delay. Subsequently, by analyzing and utilizing the slack time in FL training, our HELCFL introduces a device operating frequency determination approach to reduce training energy costs. Experiments verify that our HELCFL can enhance the highest accuracy by up to 43.45%, realize the training speedup of up to 275.03%, and save up to 58.25% training energy costs compared to state-of-the-art baselines.

关键词： high efficiency user selection federated learning low costs mobile-edge computing frequency determination

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Variable Rate Syndrome-Trellis Codes for Steganography on Bursty Channels 19th

Variable Rate Syndrome-Trellis Codes for Steganography on Bu...

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19th International Workshop on Digital Forensics and Watermarking, IWDW 2020

作者： Feng, Bingwen Liu, Zhiquan Wei, Kaimin Lu, Wei Lin, Yuchun College of Information Science and Technology Jinan University Guangzhou510632 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Guangdong Key Laboratory of Intelligent Information Processing and Shenzhen Key Laboratory of Media Security Shenzhen518060 China School of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen University Guangzhou510006 China Guangzhou Institute of Science and Technology Guangzhou510006 China

ISBN: (纸本)9783030694487

This paper presents a type of variable rate syndrome-trellis codes (VR-STC) for bursty channels. It can embed message bits with two different embedding rates. In the embedding, a cover vector is sliced into segments, and the embedding rates for each segment depend on the local channel distribution. The parities of stego segments are exploited to indicate the selected embedding rates according to a mapping function between parities and embedding rates. The core of the VR-STC is the parity-aware encoder, which can simultaneously output two candidate stego segments with different embedding rates and opposite parities, either of which can be used to constitute the final stego vector. A Viterbi algorithm is also suggested to find the closed stego segments. Besides, the mapping function between parities and embedding rates is designed by minimizing the embedding costs on a down sampled version of the cover vector. It can further improve the undetectability of the VR-STC. Experimental results on artificial signals and binary images suggest that the proposed VR-STC can provide high success rate of embedding and reduce the embedding cost on bursty channels. © 2021, Springer Nature Switzerland AG.

关键词： Steganography

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Measurement-Based Non-Stationary Markov Tapped Delay Line Channel Model for 5G-Railways

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IEEE Antennas and Wireless Propagation Letters 2025年

作者： Zhang, Xuejian He, Ruisi Yang, Mi Ding, Jianwen Chen, Ruifeng Gao, Shuaiqi Qi, Ziyi Zhang, Zhengyu Ai, Bo Zhong, Zhangdui Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation The School of Electronics and Information Engineering The Frontiers Science Center for Smart High-speed Railway System Beijing100044 China Beijing Jiaotong University School of Electronics and Information Engineering Beijing100044 China Henan High Speed Railway Operation and Maintenance Engineering Research Center Zhengzhou451460 China China Academy of Railway Sciences Corporation Ltd. Institute of Computing Technology Beijing100081 China

5 G for Railways (5G-R) is globally recognized as a promising next-generation railway communication system designed to meet increasing demands. Channel modeling serves as foundation for communication system design, with tapped delay line (TDL) models widely utilized in system simulations due to their simplicity and practicality and serves as a crucial component of various standards like 3GPP. However, existing TDL models applicable to 5G-R systems are limited. Most fail to capture non-stationarity, a critical characteristic of railway communications, while others are unsuitable for the specific frequency bands and bandwidths of 5G-R. In this paper, a channel measurement campaign for 5G-R dedicated network is carried out, resulting in a measurement-based 5-tap TDL model utilizing a first-order two-state Markov chain to represent channel non-stationarity. key model parameters, including number of taps, statistical distribution of amplitude, phase and Doppler shift, and state transition probability matrix, are extracted. The correlation between tap amplitudes is also obtained. Finally, the accuracy of model is validated through comparisons with measurement data and 3GPP model. These findings are expected to offer valuable insights for design and link-level simulation of 5G-R systems. © 2025 IEEE.

关键词： Markov chains

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The Lattice Sieve Field Selection of Cado-NFS 2

The Lattice Sieve Field Selection of Cado-NFS

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2019 2nd International Conference on Computer Information Science and Artificial Intelligence, CISAI 2019

作者： Xue, Ping Chen, Shaozhen Fu, Zhixin Institute of Cyberspace Security PLA Information Engineering University Hennan450001 China State Key Laboratory of Mathematical Engineering and Advanced Computing Hennan450001 China

The software application of the discrete logarithms on the "large" finite field is studied. The most effective algorithm for the problem is the general number field sieve (GNFS). Focusing on the theory of GNFS of solving software Cado-NFS and lattice sieves, we find the selection of lattice sieve which improve efficiency of CADO-NFS. This is the first parameter modification suggest. The efficiency of our selection is better than the current by experiment. © Published under licence by IOP Publishing Ltd.

关键词： Sieves

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Continual Reinforcement Learning for Digital Twin Synchronization Optimization

arXiv

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arXiv 2025年

作者： Tong, Haonan Chen, Mingzhe Zhao, Jun Hu, Ye Yang, Zhaohui Liu, Yuchen Yin, Changchuan The Beijing Key Laboratory of Network System Architecture and Convergence The Beijing Advanced Information Network Laboratory Beijing University of Posts and Telecommunications Beijing China Singapore The Department of Electrical and Computer Engineering Frost Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Department of Industrial and Systems Engineering University of Miami Coral GablesFL33146 United States The College of Information Science and Electronic Engineering Zhejiang University Zhejiang Hangzhou310027 China The Department of Computer Science North Carolina State University RaleighNC27695 United States The Beijing Key Laboratory of Network System Architecture and Convergence China The Beijing Advanced Information Network Laboratory Beijing University of Posts and Telecommunications Beijing100876 China

This article investigates the adaptive resource allocation scheme for digital twin (DT) synchronization optimization over dynamic wireless networks. In our considered model, a base station (BS) continuously collects factory physical object state data from wireless devices to build a real-time virtual DT system for factory event analysis. Due to continuous data transmission, maintaining DT synchronization must use extensive wireless resources. To address this issue, a subset of devices is selected to transmit their sensing data, and resource block (RB) allocation is optimized. This problem is formulated as a constrained Markov process (CMDP) problem that minimizes the long-term mismatch between the physical and virtual systems. To solve this CMDP, we first transform the problem into a dual problem that refines RB constraint impacts on device scheduling strategies. We then propose a continual reinforcement learning (CRL) algorithm to solve the dual problem. The CRL algorithm learns a stable policy across historical experiences for quick adaptation to dynamics in physical states and network capacity. Simulation results show that the CRL can adapt quickly to network capacity changes and reduce normalized root mean square error (NRMSE) between physical and virtual states by up to 55.2%, using the same RB number as traditional methods. © 2025, CC BY-NC-SA.

关键词： Markov processes

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computing Power in the Sky: Digital Twin-assisted Collaborative computing with Multi-UAV Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Wang, Chao Han, Yu Zhang, Long Jia, Ziye Zhang, Hongliang Hong, Choong Seon Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Jiangsu Nanjing211111 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Kyung Hee University Department of Computer Science and Engineering Gyeonggi-do Yongin-si17104 Korea Republic of University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

The collaboration of computing powers (CPs) among unmanned aerial vehicles (UAVs)-mounted edge servers is essential to handle data-intensive tasks of user equipments (UEs). This paper presents a multi-UAV computing power network (CPN) that orchestrates the CP resources of edge servers to cooperatively process tasks through collaborative computing. Due to the frequent interactions among edge servers and the increased complexities for large-scale task executions, we propose a digital twin (DT)-driven multi-UAV CPN framework, where the aerial DT network is created as a digital replica of the multi-UAV network to assist collaborative computing. A joint optimization problem of the service association, offloading power control, task partitions, CP allocation, and UAV trajectory design is formulated to minimize the long-term average delay of UEs. We use the Lyapunov technique to tackle the long-term energy constraint, forming a tractable optimization problem, which is modeled as a Markov decision process to balance the UAV's deficit queue stability and the UE's task completion delay. A hybrid soft actor-critic based deep reinforcement learning algorithm is developed to optimize the joint design by sampling the hybrid action from the Gumbel and Gaussian distributions. Simulation results verify that the multi-UAV CPN contributes to significant performance gains when supported by DTs. © 2025 IEEE.

关键词： Markov processes

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Rate-Overhead Tradeoff in Beam Training for RRS-Assisted Multi-User Communications

Rate-Overhead Tradeoff in Beam Training for RRS-Assisted Mul...

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IEEE Conference on Vehicular Technology (VTC)

作者： Shupei Zhang Yutong Zhang Boya Di Hongliang Zhang School of Electronics Engineering and Computing Science Peking University Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Beijing China Department of Electrical and Computer Engineering Princeton University NJ USA

ISBN: (纸本)9781665454698

Holographic multiple-input multiple-output (HMIMO) with a spatially continuous aperture is a promising solution for future radio access to handle the explosively increasing data demands. As a key enabler of HMIMO, the reconfigurable refractive surface (RRS) can serve as an antenna array with numerous programmable radiation elements. In this paper, we consider a multi-user system with an RRS-aided base station (BS) where the transmit signal is refracted by the RRS towards the users. A beamforming scheme is developed via codebook design and beam training. A larger codebook size implies more codewords, each corresponding to a directional beam. When the codebook size increases, the directivity of the refracted beam is enhanced, bringing a higher data rate. However, it also leads to an exponential growth of the training overhead. To achieve the critical tradeoff between the data rate and overhead, we evaluate the system throughput and model the relation between the codebook size of the RRS and the throughput mathematically. The optimal codebook size is then derived given different user distributions. Simulation results verify our theoretical analysis and show the influence of both codebook size and RRS size on the throughput.

关键词： Training Vehicular and wireless technologies Array signal processing Simulation System performance Transmitting antennas Throughput

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