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Efficient centralized traffic grid signal control based on meta-reinforcement learning

IEEE/CAA Journal of Automatica Sinica 2023年 1-3页

作者： Wu, Jia Lou, Yican School of Information and Software University of Electronic Science and Technology of China Chengdu 610054 China

Dear Editor, This letter presents a novel method to tackle the two challenges of the centralized traffic control based on reinforcement learning (RL): the curse of dimensionality as the scale of traffic grid increases and the data-inefficiency problem that requires large amounts of samples to learn. First, we use a sequence-to-sequence (seq2seq) model and the attention mechanism to decompose the state-action space into sub-spaces, thus dealing with the first challenge. Second, we propose a new context-based meta-RL model that disentangles task inference and control, which improves the meta-training efficiency and accelerates the learning process in the new environment. We evaluate our approach on real-world datasets and the results demonstrate that our approach outperforms the state-of-the-art deep reinforcement learning (DRL)-based methods and the traditional control methods. IEEE

关键词： Decision making

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Diffusion model for adversarial attack against NLP models

Diffusion model for adversarial attack against NLP models

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2023 International Conference on Computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2023

作者： Qiu, Shilin Gou, Min Liang, Tao School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China

ISBN: (纸本)9781510677685

Current black-box adversarial attacks have proven to be highly effective in generating adversarial texts that can successfully deceive natural language processing models, thereby revealing potential weaknesses in these models. This research proposes an innovative transfer-based black-box attack method, which capitalizes on the combined generative and discriminative abilities of the diffusion model. To ensure semantic similarity and enhance the adversarial ability of generated texts, well-designed semantic-preserving and adversarial objectives are introduced to the training procedure of the diffusion model. The results show that the proposed method can generate adversarial texts that successfully attack text classification models. © 2024 SPIE.

关键词： Semantics

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Multi-parameter ultrasound imaging for musculoskeletal tissues based on a physics informed generative adversarial network

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Chinese Physics B 2025年第4期34卷 442-455页

作者： Pengxin Wang Heyu Ma Tianyu Liu Chengcheng Liu Dan Li Dean Ta Institute of Biomedical Engineering&Technology Academy for Engineering and TechnologyFudan UniversityShanghai 200433China State Key Laboratory of Integrated Chips and Systems Fudan UniversityShanghai 201203China Department of Electronic Engineering School of Information Science and TechnologyFudan UniversityShanghai 200438China Department of Biomedical Engineering School of Information Science and TechnologyFudan UniversityShanghai 200438China

Full waveform inversion(FWI)has showed great potential in the detection of musculoskeletal ***,FWI is an ill-posed inverse problem and has a high requirement on the initial model during the imaging *** inaccurate initial model may lead to local minima in the inversion and unexpected imaging results caused by cycle-skipping *** learning methods have been applied in musculoskeletal imaging,but need a large amount of data for *** by work related to generative adversarial networks with physical informed constrain,we proposed a method named as bone ultrasound imaging with physics informed generative adversarial network(BUIPIGAN)to achieve unsupervised multi-parameter imaging for musculoskeletal tissues,focusing on speed of sound(SOS)and *** the in-silico experiments using a ring array transducer,conventional FWI methods and BUIPIGAN were employed for multiparameter imaging of two musculoskeletal tissue *** results were evaluated based on visual appearance,structural similarity index measure(SSIM),signal-to-noise ratio(SNR),and relative error(RE).For SOS imaging of the tibia–fibula model,the proposed BUIPIGAN achieved accurate SOS imaging with best *** specific quantitative metrics for SOS imaging were SSIM 0.9573,SNR 28.70 dB,and RE 5.78%.For the multi-parameter imaging of the tibia–fibula and human forearm,the BUIPIGAN successfully reconstructed SOS and density distributions with SSIM above 94%,SNR above 21 dB,and RE below 10%.The BUIPIGAN also showed robustness across various noise levels(i.e.,30 dB,10 dB).The results demonstrated that the proposed BUIPIGAN can achieve high-accuracy SOS and density imaging,proving its potential for applications in musculoskeletal ultrasound imaging.

关键词： ultrasound image physics informed generative adversarial network musculoskeletal imaging

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A Broadband Vertical Transition from Waveguide to Microstrip Based on Narrow-Wall Excitation

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Progress in Electromagnetics Research C 2025年 154卷 105-109页

作者： Dong, Jun Zhong, Bingqing Zheng, Jing Yao, Feng Yin, Jinxin Peng, Hao College of Information Science and Engineering Hunan Normal University Changsha410081 China School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China

In this paper, a broadband vertical rectangular waveguide (RWG)-to-microstrip line (MSL) transition structure for millimeter-wave solid-state circuits is proposed. The planar circuit in this transition is composed of a V-shaped probe and tapered fin-line ground, and the probe is inserted into the waveguide through a slot on the narrow side of the RWG. To facilitate energy coupling from RWG to MSL, a back-short with a length of a quarter-wavelength is designed on the bottom side of the probe to achieve effective electric coupling. A back-to-back prototype module has been designed to verify the performance of the transition. The measurement results show that the return loss of the back-to-back transition structure is better than 13 dB across the entire Ka-band, with the insertion loss (IL) of a single transition better than 0.55 dB. The measurement results agree well with simulation ones, validating the feasibility of the proposed transition circuit. A tolerance analysis is performed through simulations to verify the reliability of this transition design. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Rectangular waveguides

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EPAAMap: Enhanced Parallel Attention Aggregation HD Semantic Map in Complex Traffic Scenarios 7

EPAAMap: Enhanced Parallel Attention Aggregation HD Semantic...

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7th International Conference on Data science and information technology, DSIT 2024

作者： Zhang, Jingtao Wang, Xiangxiang Yu, Yongbing Hu, Qinghua Xue, Lirui He, Qi Fan, Manping Ren, Liyong University of Electronic Science and Technology of China School of Information and Software Engineering Cheng Du China

ISBN: (纸本)9798350384093

This paper addresses the significant challenges posed by road safety due to rapid urbanization and increasing vehicular traffic. High-definition (HD) semantic maps are essential for improving decision-making and safety in autonomous vehicles and intelligent driver assistance systems, which require detailed road environment information. Current multi-camera perception systems face limitations in efficiently integrating data, resulting in inconsistent spatial understanding. To tackle these issues, this propose a novel multi-scale feature optimization mechanism EPPAMap, including the efficient depthwise separable feature network(EDSFN) to improve semantic understanding. Additionally, we introduce the parallel attention aggregation module (PAAM) to capture richer contextual information and enhance feature aggregation. Experimental results demonstrate superior adaptability and performance in complex road scenarios, providing a solid foundation for HD semantic map construction and real-time traffic perception. © 2024 IEEE.

关键词： Autonomous vehicles

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Identify information sources with different start times in complex networks based on sparse observers

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Chinese Physics B 2024年第11期33卷 467-479页

作者： Yuan-Zhang Deng Zhao-Long Hu Feilong Lin Chang-Bing Tang Hui Wang Yi-Zhen Huang School of Computer Science and Technology Zhejiang Normal UniversityJinhua 321004China School of Physics and Electronic Information Engineering Zhejiang Normal UniversityJinhua 321004China School of Information Engineering Jinhua PolytechnicJinhua 321016China

The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate dissemination at distinct initial *** there are many research results of multi-source identification,the challenge of locating sources with varying initiation times using a limited subset of observational nodes remains *** this study,we provide the backward spread tree theorem and source centrality theorem,and develop a backward spread centrality algorithm to identify all the information sources that trigger the spread at different start *** proposed algorithm does not require prior knowledge of the number of sources,however,it can estimate both the initial spread moment and the spread *** core concept of this algorithm involves inferring suspected sources through source centrality theorem and locating the source from the suspected sources with linear *** experiments from synthetic and real network simulation corroborate the superiority of our method in terms of both efficacy and ***,we find that our method maintains robustness irrespective of the number of sources and the average degree of *** with classical and state-of-the art source identification methods,our method generally improves the AUROC value by 0.1 to 0.2.

关键词： complex networks information spread source identification backward spread centricity

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Anomaly Detection in Spatial information Networks: A Security Knowledge Graph-based Approach

Anomaly Detection in Spatial Information Networks: A Securit...

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2024 International Conference on Intelligent Computing and Robotics, ICICR 2024

作者： Tan, Yayue Zhang, Yaqi Liu, Hui Tang, Yongqing College of Computer and Information Science School of Software Southwest University Chongqing China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350372274

Anomaly detection stands as a critical element in securing space information networks (SINs). This paper delves into the realm of anomaly detection within dynamic networks, shedding light on established methodologies. The focus lies on scrutinizing various anomaly detection strategies in space information networks, conducting a comprehensive assessment of their practical applications, advantages, and drawbacks. Moreover, it introduces a novel anomaly detection approach driven by deep learning principles. This innovative method merges graph convolution techniques with a network securityoriented knowledge graph, presenting a cutting-edge solution. As a final contribution, the paper extends its purview to the future landscape of anomaly detection within space information networks, offering valuable insights into potential advancements and forthcoming trends in this domain. This holistic investigation seeks to enhance the understanding of anomaly detection paradigms within the unique context of space information networks, aiming to fortify their security measures and operational resilience. ©2024 IEEE.

关键词： Knowledge graph

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Weighted sum power maximization for STAR-RIS-aided SWIPT systems with nonlinear energy harvesting

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science China(information sciences) 2024年第10期67卷 343-358页

作者： Weiping SHI Cunhua PAN Feng SHU Yongpeng WU Jiangzhou WANG Yongqiang BAO Jin TIAN School of Network and Communication Nanjing Vocational College of Information Technology National Mobile Communications Research Laboratory Southeast University School of Information and Communication Engineering Hainan University School of Electronic and Optical Engineering Nanjing University of Science and Technology Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong University School of Engineering University of Kent School of Information and Communication Engineering Nanjing Institute of Technology Engineering School of Networks and Telecommunications Jinling Institute of Technology

The conventional reconfigurable intelligent surface(RIS) is limited to reflecting incident signals,thereby imposing constraints on the placement of the transmitter and receiver, which hinders achieving comprehensive signal coverage across an entire area. This paper investigates a simultaneously transmitting and reflecting(STAR)-RIS-aided simultaneous wireless information and power transfer(SWIPT) system with a nonlinear energy harvesting model under three different RIS transmission protocols: energy splitting(ES),time switching(TS), and mode switching(MS). The objective of this paper is to maximize the weighted sum power(WSP) of all energy harvesting receivers(EHRs) while ensuring fairness in the collected power among them. This is achieved by jointly optimizing the transmit beamforming at the base station(BS)and the transmission and reflection coefficients at the STAR-RIS, subject to rate constraints for information decoding receivers(IDRs), transmit power constraint at the BS, and coefficient constraints of each element at the STAR-RIS corresponding to the three protocols. Solving this optimization problem poses challenges because of the complicated objective function and numerous coupled optimization variables of the ES STAR-RIS. To address this complexity, an efficient alternating optimization(AO) approach is proposed as an iterative solution method that achieves suboptimal results. The AO algorithm is then extended to MS STAR-RIS and TS STAR-RIS. Specifically, for MS STRA-RIS, binary constraints in the STAR-RIS coefficient optimization subproblem are handled using the first-order approximation technique along with the penalty function method. For TS STAR-RIS, apart from optimizing BS transmit beamforming and STAR-RIS coefficients subproblems, the transmission and reflection time allocation of STAR-RIS also needs *** findings demonstrate that compared to conventional RIS-aided systems, utilizing three different protocols in a STAR-RIS-aided sy

关键词： STAR-RIS beamforming SWIPT alternating optimization nonlinear energy harvesting

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BEV-Locator:an end-to-end visual semantic localization network using multi-view images

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science China(information sciences) 2025年第2期68卷 134-150页

作者： Zhihuang ZHANG Meng XU Wenqiang ZHOU Tao PENG Liang LI Stefan POSLAD School of Vehicle and Mobility Tsinghua University School of Information Technology & Management University of International Business and Economics Qcraft Inc. School of Electronic Engineering and Computer Science Queen Mary University of London

Accurate localization ability is fundamental in autonomous driving. Traditional visual localization frameworks approach the semantic map-matching problem with geometric models, which rely on complex parameter tuning and thus hinder large-scale deployment. In this paper, we propose BEV-Locator: an end-to-end visual semantic localization neural network using multi-view camera images. Specifically, a visual BEV(bird-eye-view) encoder extracts and flattens the multi-view images into BEV space. While the semantic map features are structurally embedded as map query sequences. Then a cross-model transformer associates the BEV features and semantic map queries. The localization information of ego-car is recursively queried out by cross-attention modules. Finally, the ego pose can be inferred by decoding the transformer outputs. This end-to-end model speaks to its broad applicability across different driving environments, including high-speed scenarios. We evaluate the proposed method in large-scale nuScenes and Qcraft datasets. The experimental results show that the BEV-Locator is capable of estimating the vehicle poses under versatile scenarios, which effectively associates the cross-model information from multi-view images and global semantic maps. The experiments report satisfactory accuracy with mean absolute errors of 0.052 m, 0.135 m and 0.251° in lateral, longitudinal translation and heading angle degree.

关键词： visual localization semantic map bird-eye-view transformer pose estimation

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Light-modulated graphene-based φ_(0) Josephson junction and -φ_(0) to φ_(0) transition

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Chinese Physics B 2024年第2期33卷 476-481页

作者：程任翔于苗汪洪曹德亮李兴鳌戚凤华周兴飞 New Energy Technology Engineering Laboratory of Jiangsu Province School of ScienceNanjing University of Posts and TelecommunicationsNanjing 210023China School of Electronic and Information Engineering Jinling Institute of TechnologyNanjing 211169China School of Electronic Engineering Nanjing Xiaozhuang UniversityNanjing 211171China

We investigate the chiral edge states-induced Josephson current–phase relation in a graphene-based Josephson junction modulated by the off-resonant circularly polarized light and the staggered sublattice *** solving the Bogoliubov–de Gennes equation,a φ_(0) Josephson junction is induced in the coaction of the off-resonant circularly polarized light and the staggered sublattice potential,which arises from the fact that the center of-mass wave vector of Cooper pair becomes finite and the opposite center of-mass wave vector to compensate is lacking in the nonsuperconducting ***,when the direction of polarization of light is changed,-φ_(0) to φ_(0) transition generates,which generalizes the concept of traditional 0–π*** findings provide a purely optical way to manipulate a phase-controllable Josephson device and guidelines for future experiments to confirm the presence of graphene-based φ_(0)Josephson junction.

关键词： graphene circularly polarized light staggered sublattice potential φ_(0)Josephson junction

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