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Chinese Control Conference (CCC)

作者： Weidong Yan Zhaoliang Xu Yang Li The Department of Automation Science and Electrical Engineering Beihang University Beijing China The Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Advanced Institute of Information Technology Peking University Hangzhou China

In this study, a multi-degree-of-freedom (Multi-DOF) robot (MDR) system based on a LightGBM-driven electroencephalogram (EEG) decoding model is designed and developed to assist subjects with hand motor dysfunction in their daily activities and neurorehabilitation. The system mainly consists of a motor imagery electroencephalogram (MI-EEG) evoking layer, an intention decoding layer, and an interaction executive layer. The MI-EEG evoking layer initially displays a virtual reality (VR) motion imagination scenario, instructing the subjects to imagine a real hand gripping movement, simultaneously collecting the electrical EEG signals and preprocessing the EEG signals. Secondly, in the intention decoding layer, a network combining temporal-spectral feature fusion and LightGBM (TSFF-LightGBM) for MI-BCI classification is used to more effectively boost brain decoding accuracy and decrease decoding time. Finally, in the interaction executive layer, the Multi-DOF wearable robot is developed to offer hand grasp motion kinesthetic feedback and visual feedback synced with MI. The following are the key benefits of the proposed MDR system: (1) We propose a new lightweight network structure more suitable for brain computer interface (BCI) interaction systems, achieving more accurate decoding and shorter identification time in different data sets, which helps to improve the practicability of the system and promote the practical clinical application of BCI rehabilitation technology. (2) We integrate BCI, VR, a wearable Multi-DOF robot, motion kinesthetic feedback, and visual feedback to improve human-machine interaction. Compared to the most recent investigations, the average accuracy of the MDR system on the publicly accessible datasets BCI IV 2a and HGD reached 75.89% and 93.53%, respectively.

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A Group Theory Based Topology Optimization Scheme for the Design of Inhomogeneous Waveguides with Dihedral Group Symmetries

SSRN

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SSRN 2024年

作者： Chu, Peiwen Li, Yifan He, Zhicheng Li, Eric Ozgun, Ozlem Vandenbosch, Guy A.E. Zheng, Xuezhi State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle the college of Mechanical and Transportation Engineering Hunan university Changsha410082 China ESAT-WaveCoRE Research Division Department of Electrical Engineering KU Leuven Leuven3001 Belgium School of Computing Engineering & Digital Technologies Teesside University United Kingdom Electrical and Electronics Engineering Hacettepe University Beytepe AnkaraTR 06800 Turkey

In this paper, we introduce a novel topology optimization scheme dedicated to designing waveguides with inhomogeneities holding rotation and reflection symmetries. At begining, we build the scheme by first developing a new computational algorithm that combines the Finite Element Method with the group representation theory. This combination allows the decomposition of the eigenvalue problem in a classic FEM to orthogonal (decoupled) subproblems, which therefore leads to an improved solver efficiency by order of magnitude. For a targeted mode profile, the involvement of the GRT does not only enable a pre-selection of the subproblems that are to be optimized, which further improves the computational speed, but also completely avoids potential mode degeneracies, which adversely affects the convergence of the optimization. To validate, the GRT – FEM algorithm is first tested against the results from a full FEM simulation for a guide with inhomogeneities with six-fold rotation and reflection symmetries. Then, the entire scheme is applied to achieve a desired eigenmode with a targeted propagation constant. The proposed scheme does not only provide an efficient design tool for exploiting interesting wave phenomena in waveguiding structures, but also lays down a theoretical foundation for systematically integrating symmetries with classic Computational Electromagnetics algorithms. © 2024, The Authors. All rights reserved.

关键词： Finite element method

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SPECWANDS: An Efficient Priority-based Scheduler Against Speculation Contention Attacks

arXiv

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arXiv 2023年

作者： Tang, Bowen Wu, Chenggang Yew, Pen-Chung Zhang, Yinqian Xie, Mengyao Lai, Yuanming Kang, Yan Wang, Wei Wei, Qiang Wang, Zhe SKLP Institute of Computing Technology CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Zhongguancun Laboratory Beijing China Computer Science & Engineering Department The University of Minnesota-Twin Cities MN55455 United States Department of Computer Science and Engineering The Southern University of Science and Technology Shenzhen518055 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000 China

Transient Execution Attacks (TEAs) have gradually become a major security threat to modern high-performance processors. They exploit the vulnerability of speculative execution to illegally access private data, and transmit them through timing-based covert channels. While new vulnerabilities are discovered continuously, the covert channels can be categorised to two types: 1) Persistent Type, in which covert channels are based on the layout changes of buffering, e.g. through caches or TLBs;2) Volatile Type, in which covert channels are based on the contention of sharing resources, e.g. through execution units or issuing ports. The defenses against the persistent-type covert channels have been well addressed, while those for the volatile-type are still rather inadequate. Existing mitigation schemes for the volatile type such as Speculative Compression and Time-Division-Multiplexing will introduce significant overhead due to the need to stall the pipeline or to disallow resource sharing. In this paper, we look into such attacks and defenses with a new perspective, and propose a scheduling-based mitigation scheme, called SPECWANDS. It consists of three priority-based scheduling policies to prevent an attacker from transmitting the secret in different contention situations. SPECWANDS not only can defend against both inter-thread and intra-thread based attacks, but also can keep most of the performance benefit from speculative execution and resource-sharing. We evaluate its runtime overhead on SPEC 2017 benchmarks and realistic programs. The experimental results show that SPECWANDS has a significant performance advantage over the other two representative schemes. Copyright © 2023, The Authors. All rights reserved.

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A Multi-Head Convolution Network with Attention Consistency for Facial Expression Recognition

A Multi-Head Convolution Network with Attention Consistency ...

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Chinese Control Conference (CCC)

作者： Wenkang Liu Mingyi Sun Yang Li the Department of Automation Science and Electrical Engineering Beihang University Beijing China the Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Advanced Institute of Information Technology Peking University Hangzhou China

In recent years, the demand for facial expression recognition applications has increased rapidly, and its research has received extensive attention from researchers. However, the current recognition methods based on deep learning ignore the idea of multiple head attention and semantic consistency, resulting in the model only paying attention to the local area of the feature map. In addition, the model's inconsistent attention to the images before and after the flip, resulting the poor robustness, poor interpretation, and other shortcomings in the model. To address the above problems, we propose an Affinity Separation Loss (ASLoss), which improves the separability of samples through clustering. Moreover, a Separate Multi-head Attention block (SMA), and a Zonal Loss (ZLoss) are also designed to decentralize the model's attention. Experimental results demonstrate that our proposed MACNet method achieves competitive recognition performance on two public datasets RAF-DB and FERPlus.

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Optimal Bilinear Equalizer for Cell-Free Massive MIMO Systems over Correlated Rician Channels

arXiv

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arXiv 2024年

作者： Wang, Zhe Zhang, Jiayi Björnson, Emil Niyato, Dusit Ai, Bo State Key Laboratory of Advanced Rail Autonomous Operation China School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China Department of Computer Science KTH Royal Institute of Technology Stockholm114 28 Sweden College of Computing & Data Science Nanyang Technological University 639798 Singapore

In this paper, we explore the low-complexity optimal bilinear equalizer (OBE) combining scheme design for cell-free massive multiple-input multiple-output networks with spatially correlated Rician fading channels. We provide a spectral efficiency (SE) performance analysis framework for both the centralized and distributed processing schemes with bilinear equalizer (BE)-structure combining schemes applied. The BE-structured combining is a set of schemes that are constructed by the multiplications of channel statistics-based BE matrices and instantaneous channel estimates. Notably, we derive closed-form achievable SE expressions for centralized and distributed BE-structured combining schemes. We propose one centralized and two distributed OBE schemes: Centralized OBE (C-OBE), Distributed OBE based on Global channel statistics (DG-OBE), and Distributed OBE based on Local channel statistics (DL-OBE), which maximize their respective SE expressions. OBE matrices in these schemes are tailored based on varying levels of channel statistics. Notably, we obtain new and insightful closed-form results for the C-OBE, DG-OBE, and DL-OBE combining schemes. Numerical results demonstrate that the proposed OBE schemes can achieve excellent SE, even in scenarios with severe pilot contamination. Copyright © 2024, The Authors. All rights reserved.

关键词： Fading channels

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Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第7期47卷 5520-5537页

作者： Jian Liu Wei Sun Hui Yang Pengchao Deng Chongpei Liu Nicu Sebe Hossein Rahmani Ajmal Mian National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics and the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China Department of Information Engineering and Computer Science University of Trento Trento Italy School of Computing and Communications Lancaster University Lancaster U.K. Department of Computer Science The University of Western Australia Crawley WA Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance.

关键词： Shape Solid modeling Three-dimensional displays Pose estimation Training Robots Grasping Diffusion models Real-time systems Point cloud compression

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NGDcrm:a numeric graph dependency-based conflict resolution method for knowledge graph

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High Technology Letters 2021年第2期27卷 153-162页

作者： Ma Jiangtao Wang Yanjun Chen Xueting Qiao Yaqiong College of Computer and Communication Engineering Zhengzhou Universily of Lighl IndustryZhengzhou 450002P.R.China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450002P.R.China School of Computer&Communication Engineering University of Science and Technology BeijingBeijing 100083P.R.China School of Information Engineering North China University of W ater Resources and Electric PowerZhengzhou 450046P.R.China

Knowledge graph(KG)conflict resolution is to solve knowledge conflicts problem in the construction of *** at the problem of KG conflict resolution,a KG conflict resolution algorithm NGDcrm is proposed,which is a numeric graph dependency-based conflict resolution *** utilizes the dependency graph to perform arithmetic calculation and predicate comparison of numerical entity knowledge in the *** first uses a parallel segmentation method to segment the KG;then,it extracts the features of the KG according to KG embedding;finally,it uses numerical graph dependencies to detect and correct the wrong facts in the KG based on the extracted *** experimental results on real data show that NGDcrm is better than the state-of-the-art knowledge conflict resolution *** them,the AUC value of NGDcrm on the DBpedia dataset is 15.4%higher than the state-of-the-art method.

关键词： dependency graph knowledge conflict resolution knowledge graph(KG) numeric graph dependency(NGD)

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A Neighbor Immunization Strategy to Block Virus Spreading on Networks

A Neighbor Immunization Strategy to Block Virus Spreading on...

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Information Communication Technologies Conference (ICTC)

作者： Hao Yaohui Liu Yingze Zhao Baole Wang Qingxian State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou China Information Engineering University Zhengzhou China

In order to achieve better effect on blocking virus propagation, a neighbor immunization strategy was proposed and verified in this paper. On email-EU real networks and on scale-free model network, the efficiencies of the neighbor immunization strategy and the random immunization strategy in SIR and SEIR virus spreading models were compared and analyzed by simulation experiment. The result indicates that the neighbor immunization strategy is a feasible and effective. This phenomenon shows that neighbor immunization strategy can improve to the future virus and effectively prevent the virus spreading.

关键词： Analytical models Communications technology Viruses (medical) Immune system

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Creation of Magnetic Skyrmions in Two-Dimensional Van Der Waals Ferromagnets by Lattice Distortion

SSRN

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SSRN 2025年

作者： Zhang, Tingjia Yang, Chendi Lv, Xiaowei Zhao, Tuoyu Shi, Wu Li, Wei Liang, Jia Che, Renchao School of Materials and Chemistry University of Shanghai for Science and Technology Shanghai200093 China Laboratory of Advanced Materials Shanghai Key Lab of Molecular Catalysis and Innovative Materials Academy for Engineering and Technology Advanced Coatings Research Center of Ministry of Education of China Fudan University Shanghai200438 China State Key Laboratory of Surface Physics Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China Zhangjiang Fudan International Innovation Center Fudan University Shanghai201210 China Department of Physics Fudan University Shanghai200433 China Department of Materials Science State Key Laboratory of Photovoltaic Science and Technology Fudan University Shanghai200433 China

Two-dimensional (2D) van der Waals (vdW) ferromagnets provide an excellent platform for exploring exotic physical phenomena such as magnetic skyrmions and quantum topological phases. However, the centrosymmetric crystal structure inherent in these 2D vdW ferromagnets theoretically precludes the formation of magnetic skyrmions and topological phases. In this study, we investigate the origin of the absence of magnetic skyrmions in 2D vdW ferromagnets and propose an effective strategy to induce lattice distortion through doping, thereby enabling the formation of magnetic skyrmions. Specifically, we demonstrate that Co doping in Fe3GeTe2 leads to significant lattice distortion, transforming the original centrosymmetric crystal structure into a non-centrosymmetric one. This structural modification enables the emergence of a considerable Dzyaloshinskii-Moriya interaction (DMI), giving rise to Néel-type skyrmions. Additionally, the scalar spin chirality of these magnetic skyrmions acts as a virtual magnetic field, thereby inducing the topological Hall effect (THE) in Co-doped Fe3GeTe2. Our findings present a reliable method to manipulate spin textures and induce the THE in 2D vdW ferromagnets with non-zero DMI through lattice distortion, offering a promising route for the development of vdW ferromagnet-based spintronic devices. © 2025, The Authors. All rights reserved.

关键词： Van der Waals forces

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IRS-Enhanced Anti-Jamming Precoding Against DISCO Physical Layer Jamming Attacks

arXiv

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arXiv 2024年

作者： Huang, Huan Zhang, Hongliang Cai, Yi Zhang, Yunjing Lee Swindlehurst, A. Han, Zhu Electronic Information School Soochow University Suzhou China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China Department of Electrical and Computer Engineering University of Houston Houston United States Center for Pervasive Communications and Computing University of California Irvine United States

Illegitimate intelligent reflective surfaces (IRSs) can pose significant physical layer security risks on multi-user multiple-input single-output (MU-MISO) systems. Recently, a DISCO approach has been proposed an illegitimate IRS with random and time-varying reflection coefficients, referred to as a "disco" IRS (DIRS). Such DIRS can attack MU-MISO systems without relying on either jamming power or channel state information (CSI), and classical anti-jamming techniques are ineffective for the DIRS-based fully-passive jammers (DIRS-based FPJs). In this paper, we propose an IRS-enhanced anti-jamming precoder against DIRS-based FPJs that requires only statistical rather than instantaneous CSI of the DIRS-jammed channels. Specifically, a legitimate IRS is introduced to reduce the strength of the DIRS-based jamming relative to the transmit signals at a legitimate user (LU). In addition, the active beamforming at the legitimate access point (AP) is designed to maximize the signal-to-jamming-plus-noise ratios (SJNRs). Numerical results are presented to evaluate the effectiveness of the proposed IRS-enhanced anti-jamming precoder against DIRS-based FPJs. Copyright © 2024, The Authors. All rights reserved.

关键词： Channel state information

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