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Reconfigurable Intelligent Surface-Aided Covert Communications: A Multi-User Scenario

IEEE Transactions on Vehicular Technology 2025年第6期74卷 10052-10057页

作者： Hu, Xiaoyan Zhao, Pengze Xiao, Han Zheng, Tong-Xing Wang, Wenjie Yang, Kun Xi'an Jiaotong University School of Information and Communications Engineering Xi'an710049 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Nanjing University State Key Laboratory of Novel Software Technology Nanjing210008 China School of Intelligent Software and Engineering Suzhou215163 China University of Essex School of Computer Science and Electronic Engineering United Kingdom

This paper explores a multi-user covert communication scenario with the assistance of a reconfigurable intelligent surface (RIS). Except a covert user monitored by the warden, there are multiple public users existing in the service area. For the purpose of evaluating the efficacy of the covert communication system, a covert constraint is derived measuring the minimum detection error probability of the warden through the Kullback-Leibler (KL) divergence. Then an optimization problem is formulated to maximize the convert rate, while ensuring the constraints of covertness, transmit power and quality of service (QoS) for public users. A two-step iterative algorithm jointly designing the active and passive beamforming, is put forth to efficiently resolve this non-convex optimization problem. Additionally, the numerical results clearly demonstrate that the proposed RIS-assisted scheme can significantly enhance the covert communication performance on the premise of guaranteeing the public communication performance of the system. © 1967-2012 IEEE.

关键词： Convex optimization

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SolarDesign:An online photovoltaic device simulation and design platform

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Chinese Physics B 2025年第1期34卷 135-141页

作者： Wei E.I.Sha Xiaoyu Wang Wenchao Chen Yuhao Fu Lijun Zhang Liang Tian Minshen Lin Shudi Jiao Ting Xu Tiange Sun Dongxue Liu College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027China State Key Laboratory of Integrated Optoelectronics Key Laboratory of Automobile Materials of MOEKey Laboratory of Material Simulation Methods&Software of MOESchool of Materials Science and EngineeringJilin UniversityChangchun 130012China ZJU-UIUC Institute International CampusZhejiang UniversityHaining 314400China Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchun 130012China College of Electrical Engineering Zhejiang UniversityHangzhou 310027China Science and Technology Research Institute China Three Gorges CorporationBeijing 101199China

Solar Design(https://***/)is an online photovoltaic device simulation and design platform that provides engineering modeling analysis for crystalline silicon solar cells,as well as emerging high-efficiency solar cells such as organic,perovskite,and tandem *** platform offers user-updatable libraries of basic photovoltaic materials and devices,device-level multi-physics simulations involving optical–electrical–thermal interactions,and circuit-level compact model simulations based on detailed balance *** internationally advanced numerical methods,the platform accurately,rapidly,and efficiently solves optical absorption,electrical transport,and compact circuit *** achieves multi-level photovoltaic simulation technology from“materials to devices to circuits”with fully independent intellectual property *** to commercial softwares,the platform achieves high accuracy and improves speed by more than an order of ***,it can simulate unique electrical transport processes in emerging solar cells,such as quantum tunneling,exciton dissociation,and ion migration.

关键词： photovoltaic device simulation silicon solar cells organic and perovskite solar cells multi-physics and circuit simulation

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Global video object segmentation with spatial constraint module

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Computational Visual Media 2023年第2期9卷 385-400页

作者： Yadang Chen Duolin Wang Zhiguo Chen Zhi-Xin Yang Enhua Wu Engineering Research Center of Digital Forensics Ministry of EducationSchool of Computer and SoftwareNanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Internet of Things for Smart City Department of Electromechanical EngineeringUniversity of MacaoMacao 999078China State Key Laboratory of Computer Science Institute of SoftwareUniversity of Chinese Academy of SciencesBeijing 100190China Faculty of Science and Technology University of MacaoMacao 999078China

We present a lightweight and efficient semisupervised video object segmentation network based on the space-time memory *** some extent,our method solves the two difficulties encountered in traditional video object segmentation:one is that the single frame calculation time is too long,and the other is that the current frame’s segmentation should use more information from past *** algorithm uses a global context(GC)module to achieve highperformance,real-time *** GC module can effectively integrate multi-frame image information without increased memory and can process each frame in real ***,the prediction mask of the previous frame is helpful for the segmentation of the current frame,so we input it into a spatial constraint module(SCM),which constrains the areas of segments in the current *** SCM effectively alleviates mismatching of similar targets yet consumes few additional *** added a refinement module to the decoder to improve boundary *** model achieves state-of-the-art results on various datasets,scoring 80.1%on YouTube-VOS 2018 and a J&F score of 78.0%on DAVIS 2017,while taking 0.05 s per frame on the DAVIS 2016 validation dataset.

关键词： video object segmentation semantic segmentation global context(GC)module spatial constraint

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UKF‐MOT:An unscented Kalman filter‐based 3D multi‐object tracker

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 1031-1041页

作者： Meng Liu Jianwei Niu Yu Liu Collective Intelligence&Collaboration Laboratory China North Artificial Intelligence and Innovation Research InstituteBeijingChina China North Vehicle Research Institute BeijingChina State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijingChina State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina School of Computer Science and Engineering Beihang UniversityBeijingChina

Multi‐object tracking in autonomous driving is a non‐linear *** better address the tracking problem,this paper leveraged an unscented Kalman filter to predict the object's *** the association stage,the Mahalanobis distance was employed as an affinity metric,and a Non‐minimum Suppression method was designed for *** the detections fed into the tracker and continuous‘predicting‐matching’steps,the states of each object at different time steps were described as their own continuous *** conducted extensive experiments to evaluate tracking accuracy on three challenging datasets(KITTI,nuScenes and Waymo).The experimental results demon-strated that our method effectively achieved multi‐object tracking with satisfactory ac-curacy and real‐time efficiency.

关键词： autonomous vehicle transportation

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Development of a Three-Dimensional Multiscale Octree SBFEM for Viscoelastic Problems of Heterogeneous Materials

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Computer Modeling in engineering & Sciences 2024年第8期140卷 1831-1861页

作者： Xu Xu Xiaoteng Wang Haitian Yang Zhenjun Yang Yiqian He State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDepartment of Engineering MechanicsDalian University of TechnologyDalian116024China Hubei Key Laboratory of Geotechnical and Structural Safety School of Civil EngineeringWuhan UniversityWuhan430072China Mechanik–Materialtheorie Ruhr-Universität BochumBochum44801Germany

The multiscale method provides an effective approach for the numerical analysis of heterogeneous viscoelastic materials by reducing the degree of freedoms(DOFs).A basic framework of the Multiscale Scaled Boundary Finite Element Method(MsSBFEM)was presented in our previous works,but those works only addressed two-dimensional *** order to solve more realistic problems,a three-dimensional MsSBFEM is further developed in this *** the proposed method,the octree SBFEM is used to deal with the three-dimensional calculation for numerical base functions to bridge small and large scales,the three-dimensional image-based analysis can be conveniently conducted in small-scale and coarse nodes can be flexibly adjusted to improve the computational ***,the Temporally Piecewise Adaptive Algorithm(TPAA)is used to maintain the computational accuracy of multiscale analysis by adaptive calculation in time *** results of numerical examples show that the proposed method can significantly reduce the DOFs for three-dimensional viscoelastic analysis with good *** instance,the DOFs can be reduced by 9021 times compared with Direct Numerical Simulation(DNS)with an average error of 1.87%in the third example,and it is very effective in dealing with three-dimensional complex microstructures directly based on images without any geometric modelling process.

关键词： Three-dimensionalmultiscale viscoelastic analysis numerical base functions octree SBFEM image-based analysis temporally piecewise adaptive algorithm

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A survey on federated learning:a perspective from multi-party computation

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Frontiers of Computer Science 2024年第1期18卷 93-103页

作者： Fengxia LIU Zhiming ZHENG Yexuan SHI Yongxin TONG Yi ZHANG Institute of Artificial Intelligence and Key Laboratory of Mathematics Informatics Behavioral Semantics Beihang UniversityBeijing 100191China State Key Laboratory of Software Development Environment and Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang UniversityBeijing 100191China Pengcheng Laboratory Shenzhen 518055China Zhongguancun Laboratory Beijing 100190China Institute for Mathematical Sciences and Engineering Research Center of Financial Computing and Digital Engineering Renmin University of ChinaBeijing 100872China

Federated learning is a promising learning paradigm that allows collaborative training of models across multiple data owners without sharing their raw *** enhance privacy in federated learning,multi-party computation can be leveraged for secure communication and computation during model *** survey provides a comprehensive review on how to integrate mainstream multi-party computation techniques into diverse federated learning setups for guaranteed privacy,as well as the corresponding optimization techniques to improve model accuracy and training *** also pinpoint future directions to deploy federated learning to a wider range of applications.

关键词： sfederated learning multi-party ycomputation privacy-preserving data mining distributed learning

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Neighborhood Subgraph-based Illicit Transaction Detection in Cryptocurrency Networks 12

Neighborhood Subgraph-based Illicit Transaction Detection in...

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12th IEEE International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2024

作者： Jin, Shenghao Yang, Qiwen Chen, Shengyu Zhang, Hui Beihang University State Key Laboratory of Complex & Critical Software Environment School of Computer Science & Engineering Beijing China

ISBN: (纸本)9798331510633

With the widespread adoption of cryptocurrencies, associated illicit activities such as money laundering, fraud, extortion, and Ponzi schemes have garnered significant attention. Traditional studies have extensively employed graph neural network technologies to identify illicit transactions, typically treating the entire transaction network as input to classify its nodes. Although these methods perform well on small-scale networks, they face performance limitations when processing large-scale blockchain transaction data. To address this issue, we propose a neighborhood subgraph-based method for detecting illicit transactions, integrating GCN and LSTM. In this approach, the GCN captures and integrates information from adjacent nodes for each transaction, facilitating a deep understanding of network structures. The LSTM is tasked with capturing the sequence and variations in fund flows, effectively tracking the direction and temporal characteristics of the money flow. Experimental results indicate that when using 3-hop neighborhood subgraphs, our model's performance surpasses other GCN-based methods. Compared to previous models that require considering the entire transaction network, our approach only needs to utilize information from an average of 80 nodes, significantly improving efficiency. © 2024 IEEE.

关键词： Graph neural networks

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SCaR: Refining Skill Chaining for Long-Horizon Robotic Manipulation via Dual Regularization 38

SCaR: Refining Skill Chaining for Long-Horizon Robotic Manip...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Chen, Zixuan Ji, Ze Huo, Jing Gao, Yang State Key Laboratory for Novel Software Technology Nanjing University China School of Engineering Cardiff University United Kingdom

Long-horizon robotic manipulation tasks typically involve a series of interrelated sub-tasks spanning multiple execution stages. Skill chaining offers a feasible solution for these tasks by pre-training the skills for each sub-task and linking them sequentially. However, imperfections in skill learning or disturbances during execution can lead to the accumulation of errors in skill chaining process, resulting in execution failures. In this paper, we investigate how to achieve stable and smooth skill chaining for long-horizon robotic manipulation tasks. Specifically, we propose a novel skill chaining framework called Skill Chaining via Dual Regularization (SCaR). This framework applies dual regularization to sub-task skill pre-training and fine-tuning, which not only enhances the intra-skill dependencies within each sub-task skill but also reinforces the inter-skill dependencies between sequential sub-task skills, thus ensuring smooth skill chaining and stable long-horizon execution. We evaluate the SCaR framework on two representative long-horizon robotic manipulation simulation benchmarks: IKEA furniture assembly and kitchen organization. Additionally, we conduct a simple real-world validation in tabletop robot pick-and-place tasks. The experimental results show that, with the support of SCaR, the robot achieves a higher success rate in long-horizon tasks compared to relevant baselines and demonstrates greater robustness to perturbations. © 2024 Neural information processing systems foundation. All rights reserved.

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Exploration of B-site alloying in partially reducing Pb toxicity and regulating thermodynamic stability and electronic properties of halide perovskites

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Science China(Physics,Mechanics & Astronomy) 2023年第3期66卷 130-138页

作者： Xinjiang Wang Muhammad Faizan Kun Zhou Hongshuai Zou Qiaoling Xu Yuhao Fu Lijun Zhang State Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchun 130012China State Key Laboratory of Integrated Optoelectronics Key Laboratory of Automobile Materials of MOECollege of Materials Science and EngineeringJilin UniversityChangchun 130012China College of Physics and Electronic Engineering Center for Computational SciencesSichuan Normal UniversityChengdu 610068China International Center of Computational Method and Software Jilin UniversityChangchun 130012China

Alloying strategies provide a high degree of freedom for reducing lead toxicity,improving thermodynamic stability, tuning the optoelectronic properties of ABX3 halide perovskites by varying the alloying element species and their *** the key role of B-site cations in contributing band edge states and modulating structure factors in halide perovskites,the partial replacement of Pb2+with different B-site metal ions has been *** several experimental attempts have been made to date,the effect of B-site alloying on the stability and electronic properties of halide perovskites has not been fully ***,we take cubic CsPbBr3 perovskite as the prototype material and systematically explore the effects of B-site alloying on Pb-containing *** to the presence or absence of the corresponding perovskite phase,the ten alloying elements investigated are classified into three types(i.e.,Type Ⅰ:Sn Ge,Ca,Sr;Type Ⅱ:Cd,Mg,Mn;Type Ⅲ:Ba,Zn,Cu).Based on the first-principles calculations,we obtain the following ***,these B-site alloys will exist as disordered solid solutions rather than ordered structures at room temperature throughout the composition ***,the alloying of Sn and Ge enhances the thermodynamic stability of the cubic perovskite host,whereas the alloying of the other elements has no remarkable effect on the thermodynamic stability of the cubic perovskite ***,the underlying physical mechanism for bandgap tuning can be attributed to the atomic orbital energy mismatch or quantum confinement ***,the alloying of different elements demonstrates the diversity in the regulation of crystal structure and electronic properties,indicating potential applications in photovoltaic s and self-trapped exciton-based light-emitting *** work provides theoretical guidance for using alloying strategies to reduce lead toxicity,enhance stability,and optimize the electronic properties of halide perovsk

关键词： lead-based halide perovskites alloying thermodynamic stability first-principles calculations optoelectronic applications

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An Uncertainty Quantization-Based Method for Anti-UAV Detection in Infrared Images

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Computers, Materials & Continua 2025年第4期83卷 1439-1458页

作者： Can Wu Wenyi Tang Yunbo Rao Yinjie Chen Hui Ding Shuzhen Zhu Yuanyuan Wang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu610054China State Key Laboratory of Air Traffic Management System Nanjing210000China National Airspace Management Center Beijing100094China

Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex *** methods,while effective in controlled environments,often fail in scenarios involving long-range targets,high noise levels,or intricate backgrounds,highlighting the need for more robust *** address these challenges,we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target *** framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty *** utilizing uncer-tainty predictions,our method refines segmentation outcomes,achieving superior detection ***,this marks the first application of uncertainty modeling within the context of infrared UAV target *** evaluations on three publicly available infrared UAV datasets demonstrate the effectiveness of the proposed *** results reveal significant improvements in both detection precision and robustness when compared to state-of-the-art deep learning *** approach also extends the capabilities of encoder-decoder convolutional neural networks by introducing uncertainty modeling,enabling the network to better handle the challenges posed by small targets and complex environmental *** bridging the gap between theoretical uncertainty modeling and practical detection tasks,our work offers a new perspective on enhancing model interpretability and *** codes of this work are available openly at https://***/general-learner/UQ_Anti_UAV(acceessed on 11 November 2024).

关键词： Object segmentation uncertainty quantification bayesian convolutional neural network

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