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Current-Induced Magnetic Switching in an L1_(0) FePt Single Layer with Large Perpendicular Anisotropy Through Spin–Orbit Torque

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Engineering 2022年第5期8卷 55-61页

作者： Kaifeng Dong Chao Sun Laizhe Zhu Yiyi Jiao Ying Tao Xin Hu Ruofan Li Shuai Zhang Zhe Guo Shijiang Luo Xiaofei Yang Shaoping Li Long You School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of GeosciencesWuhan 430074China School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China China Resources Microelectronics Limited Shanghai 200072China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518000China Wuhan National High Magnetic Field Center Huazhong University of Science and TechnologyWuhan 430074China

In this study,current-induced partial magnetization-based switching was realized through the spin–orbit torque(SOT)in single-layer L1_(0) FePt with a perpendicular anisotropy(K_(u⊥))of 1.19×10^(7) erg·cm^(-3)(1 erg·cm^(-3)=0.1 J·m^(-3)),and its corresponding SOT efficiency(βDL)was 8×10^(-6) Oe·(A·cm^(-2))^(-1)(1 Oe=79.57747 A·m^(-1)),which is several times higher than that of the traditional Ta/CoFeB/MgO structure reported in past *** SOT in the FePt films originated from the structural inversion asymmetry in the FePt films since the dislocations and defects were inhomogeneously distributed within the ***,the FePt grown on MgO with a granular structure had a larger effective SOT field and effi-ciency than that grown on SrTiO_(3)(STO)with a continuous *** SOT efficiency was found to be considerably dependent on not only the sputtering temperature-induced chemical ordering but also the lattice mismatch-induced evolution of the *** findings can provide a useful means of efficiently electrically controlling a magnetic bit that is highly thermally stable via SOT.

关键词： L1_(0)FePt SOT Inversion asymmetry Magnetic switching Perpendicular anisotropy

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Deep Domain Adaptation Regression for Force Calibration of Optical Tactile Sensors

arXiv

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arXiv 2024年

作者： Chen, Zhuo Ou, Ni Jiang, Jiaqi Luo, Shan Robot Perception Lab Centre for Robotics Research Department of Engineering King’s College London LondonWC2R 2LS United Kingdom State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

Optical tactile sensors provide robots with rich force information for robot grasping in unstructured environments. The fast and accurate calibration of three-dimensional contact forces holds significance for new sensors and existing tactile sensors which may have incurred damage or aging. However, the conventional neural-network-based force calibration method necessitates a large volume of force-labeled tactile images to minimize force prediction errors, with the need for accurate Force/Torque measurement tools as well as a time-consuming data collection process. To address this challenge, we propose a novel deep domain-adaptation force calibration method, designed to transfer the force prediction ability from a calibrated optical tactile sensor to uncalibrated ones with various combinations of domain gaps, including marker presence, illumination condition, and elastomer modulus. Experimental results show the effectiveness of the proposed unsupervised force calibration method, with lowest force prediction errors of 0.102N (3.4% in full force range) for normal force, and 0.095N (6.3%) and 0.062N (4.1%) for shear forces along the x-axis and y-axis, respectively. This study presents a promising, general force calibration methodology for optical tactile sensors. Copyright © 2024, The Authors. All rights reserved.

关键词： Forecasting

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Capturing Spatial Information for sEMG-Based Gesture Recognition Using Graph Attention Networks

Capturing Spatial Information for sEMG-Based Gesture Recogni...

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Pervasive and intelligent computing (PICom), IEEE Conference on

作者： Tong Xia Feng Wang Seiichi Kawata Juan Zhao Jinhua She Daisuke Chugo School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan School of Engineering Kwansei Gakuin University Sanda Hyogo Japan

ISBN: (数字)9798331522742

ISBN: (纸本)9798331522759

Surface electromyography (sEMG) signals, known for their rich encapsulation of motion intention, have emerged as a promising avenue for human-computer interaction. Despite the advances in gesture recognition through machine learning, the omission of spatial information in sEMG signals has been identified as a limitation, often resulting in diminished accuracy and robustness of recognition systems. In this paper, we introduce the application of graph attention networks (GATs) to harness the spatial dynamics within sEMG signals. Initially, the sEMG signals are transformed into a graph-based structure through a meticulous preprocessing phase, where each electrode is represented as a node, and the spatial interplay among them is meticulously captured. Subsequently, the GATs are employed to conduct gesture recognition on this structured graph, with the networks adeptly adjusting the significance of weights between channels through the attention mechanism. This adaptive approach effectively captures the intricate spatial and temporal correlations embedded within the sEMG signals. On the CapgMyo dataset DB-a, our model demonstrates a consistent recognition accuracy of approximately 88.8%, surpassing previous machine learning models such as support vector machines (SVMs) and random forests (RFs) in recognition performance.

关键词： Electrodes Support vector machines Adaptation models Accuracy Computational modeling Gesture recognition Graph neural networks Electromyography Data models Topology

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A Multi-Time-Scale Prediction Method for Blast Furnace Gas Utilization Rate Based on Causality Analysis

A Multi-Time-Scale Prediction Method for Blast Furnace Gas U...

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Chinese Automation Congress (CAC)

作者： Guoyu Zhao Jianqi An Yunpeng Guo Chenglin Yang Yong He School of Future Technology China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Automation China University of Geosciences Wuhan China

Blast furnace operating parameters regulate the gas utilization rate (GUR), and different operating parameters affect the GUR on different time scales. However, the existing methods only analyze and model the prediction on a single-time scale, and the accuracy of the model needs to be improved. In this paper, a multi-time-scale prediction method of blast furnace gas utilization rate based on causality is proposed. Firstly, according to the production characteristics of the blast furnace, burden and blast supply are the operation means to regulate the blast furnace on different time scales. Then, this paper presents a blast furnace operation parameter extraction method fusing correlation coefficient and information entropy, and selects two most informative parameters to characterize the operation. On this basis, the causal analysis method is used to prove that the selected operation parameters affect the development trend of GUR. Finally, the long and short time scale prediction models of GUR are established, which are verified by the data of the actual blast furnace production process, improving the prediction accuracy of the GUR efficiently.

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Utilizing semantically enhanced self-supervised graph convolution and multi-head attention fusion for herb recommendation

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Artificial Intelligence in Medicine 2025年 164卷 103112-103112页

作者： Tang, Xianlun Tang, Yuze Liu, Xinran Zhang, Haochuan Dang, Xiaoyuan Wang, Ying Xu, Zihui Chongqing Key Laboratory of Complex Systems and Autonomous Control Chongqing University of Posts and Telecommunications Chongqing400065 China School of Intelligent Engineering Chongqing College of Mobile Communication Chongqing401520 China Big Data and Internet of Things School Chongqing Vocational Institute of Engineering Chongqing402260 China Xinqiao Hospital Army Medical University Chongqing400037 China

Traditional Chinese herbal medicine has long been recognized as an effective natural therapy. Recently, the development of recommendation systems for herbs has garnered widespread academic attention, as these systems significantly impact the application of traditional Chinese medicine. However, existing herb recommendation systems are limited by data sparsity, insufficient correlation between prescriptions, and inadequate representation of symptoms and herb characteristics. To address these issues, this paper introduces an approach to herb recommendation based on semantically enhanced self-supervised graph convolution and multi-head attention fusion (BSGAM). This method involves efficient embedding of entities following fine-tuning of BERT;leveraging the attributes of herbs to optimize feature representation through a residual graph convolution network and self-supervised learning;and ultimately employing a multi-head attention mechanism for feature integration and recommendation. Experiments conducted on a publicly available traditional Chinese medicine prescription dataset demonstrate that our method achieves improvements of 6.80%, 7.46%, and 6.60% in F1-Score@5, F1-Score@10, and F1-Score@20, respectively, compared to baseline methods. These results confirm the effectiveness of our approach in enhancing the accuracy of herb recommendations. © 2025 Elsevier B.V.

关键词： Self-supervised learning

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Preassigned-Time Synchronization of Memristive Chaotic Circuit via Intermittent Control

Preassigned-Time Synchronization of Memristive Chaotic Circu...

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Neuromorphic computing (ICNC), International Conference on

作者： Qiming Wang Leimin Wang Genping Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China

In this paper, the preassigned-time synchronization (PTS) problem for a fifth-order memristive chaotic circuit (MCC) is investigated by designing a time-dependent intermittent controller. First, the dynamic characteristics of the MCC, especially the existence and occurrence of chaos, are investigated by simulation experiments. Besides, the stability of the equilibrium points is discussed by using Routh-Hurwitz criterion. Then, a time-dependent intermittent controller is designed and the PTS of MCC is realized via the presented controller. Finally, the effectiveness of theoretical results is verified by means of numerical simulations.

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TransForce: Transferable Force Prediction for Vision-based Tactile Sensors with Sequential Image Translation

arXiv

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arXiv 2024年

作者： Chen, Zhuo Ou, Ni Zhang, Xuyang Luo, Shan The Robot Perception Lab Centre for Robotics Research Department of Engineering King's College London LondonWC2R 2LS United Kingdom The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

Vision-based tactile sensors (VBTSs) provide high-resolution tactile images crucial for robot in-hand manipulation. However, force sensing in VBTSs is underutilized due to the costly and time-intensive process of acquiring paired tactile images and force labels. In this study, we introduce a transferable force prediction model, TransForce, designed to leverage collected image-force paired data for new sensors under varying illumination colors and marker patterns while improving the accuracy of predicted forces, especially in the shear direction. Our model effectively achieves translation of tactile images from the source domain to the target domain, ensuring that the generated tactile images reflect the illumination colors and marker patterns of the new sensors while accurately aligning the elastomer deformation observed in existing sensors, which is beneficial to force prediction of new sensors. As such, a recurrent force prediction model trained with generated sequential tactile images and existing force labels is employed to estimate higher-accuracy forces for new sensors with lowest average errors of 0.69N (5.8% in full work range) in x-axis, 0.70N (5.8%) in y-axis, and 1.11N (6.9%) in z-axis compared with models trained with single images. The experimental results also reveal that pure marker modality is more helpful than the RGB modality in improving the accuracy of force in the shear direction, while the RGB modality show better performance in the normal direction. Copyright © 2024, The Authors. All rights reserved.

关键词： RGB color model

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Distributed Coverage Control of Multi-Agent systems with Load Balancing in Non-convex Environments

arXiv

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arXiv 2022年

作者： Zhai, Chao Fan, Pengyang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

It is always a challenging task to service sudden events in non-convex and uncertain environments, and multi-agent coverage control provides a powerful theoretical framework to investigate the deployment problem of mobile robotic networks for minimizing the cost of handling random events. Inspired by the divide-and-conquer methodology, this paper proposes a novel coverage formulation to control multi-agent systems in the non-convex region while equalizing the workload among subregions. Thereby, a distributed coverage controller is designed to drive each agent towards the desired configurations that minimize the service cost by integrating with the rotational partition strategy. In addition, a circular search algorithm is proposed to identify optimal solutions to the problem of lowering service cost. Moreover, it is proved that this search algorithm enables to approximate the optimal configuration of multi-agent systems with the arbitrary small tolerance. Finally, numerical simulations are implemented to substantiate the efficacy of proposed coverage control approach. Copyright © 2022, The Authors. All rights reserved.

关键词： Multi agent systems

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A distributed high-density resistivity meter working on a two-wire cable 3

A distributed high-density resistivity meter working on a tw...

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2020 3rd International Symposium on Power Electronics and Control Engineering, ISPECE 2020

作者： Dong, Xiquan Luo, Wang Wang, Hongpeng Ge, Jian Liu, Huan Dong, Haobin School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Hubei430074 China

High-density resistivity meter is a common instrument used in shallow geophysical exploration. At present, the structure of the centralized high-density resistivity meter is bulky, while the distributed instrument needs more than 7 core cables, and the long measuring line needs to relay power supply to the intelligent electrode to provide enough voltage, so it is not convenient to use in the field. Aiming at the above problems, a new type of distributed high-density meter is developed, which can realize the power supply, communication, and measurement functions of distributed high-density meter and carry out multi-channel measurement through the time-division multiplexing of a two-wire cable and the short-time power supply of supercapacitor. Finally, the performance of the instrument was verified by experiments. © Published under licence by IOP Publishing Ltd.

关键词： Cables

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Engineering single-molecule fluorescence withasymmetric nano-antennas

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Light(Science & Applications) 2021年第5期10卷 858-866页

作者： Wenqi Zhao Xiaochaoran Tian Zhening Fang Shiyi Xiao Meng Qiu Qiong He Wei Feng Fuyou Li Yuanbo Zhang Lei Zhou Yan-Wen Tan State Key Laboratory of Surface Physics and Department of Physics Fudan UniversityShanghai 200433China Shanghai Institute for Advanced Communication and Data Science Shanghai UniversityShanghai 200444China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced CommunicationShanghai UniversityShanghai 200444China Department of Chemistry and State Key Laboratory of Molecular Engineering of Polymers Fudan UniversityShanghai 200433China Institute for Nanoelectronic Devices and Quantum Computing Fudan UniversityShanghai 200433China Collaborative Innovation Center of Advanced Microstructures Nanjing 210093China Multiscale Research Institute of Complex Systems Fudan UniversityShanghai 200433China

As a powerful tool for studying molecular dynamics in bioscience,single-molecule fluorescence detection providesdynamical information buried in ensemble *** in the near-infrared(NIR)is particularly usefulbecause it offers higher signal-to-noise ratio and increased penetration depth in tissue compared with *** low quantum yield of most NIR fluorophores,however,makes the detection of single-moleculefluorescence ***,we use asymmetric plasmonic nano-antenna to enhance the fluorescence intensity ofAlEE1000,a typical NIR dye,by a factor up to *** asymmetric nano-antenna achieve such an enhancement mainlyby increasing the quantum yield(to~80%)rather than the local field,which degrades the molecules'*** coupled-mode-theory analysis reveals that the enhancements stem from resonance-matching between antennaand molecule and,more importantly,from optimizing the coupling between the near-and far-ield modes withdesigner asymmetric *** work provides a universal scheme for engineering single-molecule fluorescence inthe near-infrared regime.

关键词： stability. asymmetric quantum

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