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Blockchain-Assisted Revocable Cross-Domain Authentication for Vehicular Ad-Hoc Networks

IEEE Transactions on Dependable and Secure Computing 2025年

作者： Li, Ru Cui, Jie Zhang, Jing Wei, Lu Zhong, Hong He, Debiao Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230039 China Anhui University Anhui Engineering Laboratory of IoT Security Technologies Hefei230039 China Wuhan University School of Cyber Science and Engineering 430072 China

With the rapid development of vehicular ad-hoc networks (VANETs) and the increasing diversification of user demands, interactions between different management domains have become more frequent. Identity authentication is an effective way to establish cross-domain trust and secure communication. However, the existing cross-domain authentication schemes of VANETs are limited to the same management or authentication technology for each domain and rely on centralized cross-domain identity management. Even distributed management solutions encounter latency sensitivity, security and privacy challenges. To address these challenges, we propose a blockchain-assisted revocable cross-domain authentication scheme for VANETs. The proposed scheme can establish trust between domain entities by deploying different authentication methods and using distributed management to avoid single-point failures. In addition, the scheme can revoke the identity of malicious vehicles by updating the group public key, thereby ensuring the security and privacy of cross-domain Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication. This design avoids the additional impacts of blockchain technology constraints on the high mobility and real-time requirements of VANETs. Security analysis and performance evaluation show that our scheme can resist more attacks and has better security than other related schemes while also achieving a better balance between communication and computational cost. © 2025 IEEE.

关键词： Vehicular ad hoc networks

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A spectrum-enhanced attention model for semantic segmentation of remote sensing images

A spectrum-enhanced attention model for semantic segmentatio...

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2025 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Li, Xin Xu, Feng Tao, Feifei Tong, Yao Lyu, Xin Zhong, Jianyi Kaup, André College of Computer Science and Software Engineering Hohai University Nanjing China Key Laboratory of Water Big Data Technology Ministry of Water Resources Hohai University Nanjing China School of Computer Engineering Jiangsu Ocean University Lianyungang China School of Artificial Intelligence and Information Technology Nanjing University of Chinese Medicine Nanjing China Multimedia Communications and Signal Processing Friedrich-Alexander University Erlangen-Nuremberg Erlangen Germany

ISBN: (纸本)9798350368741

Semantic segmentation of remote sensing images (RSIs) is essential for applications such as environmental monitoring, urban planning, and disaster management. Convolutional Neural Networks (CNNs) and their variants struggle to capture comprehensive spectral context for learning discriminative representations. In this paper, we propose a Spectrum-Enhanced Network (SPENet) that leverages the Frequency Transformer Block (FTB) to capture rich spectral context. FTB integrates Spectrum-Enhanced Attention (SEA) with Multi-Head Frequency Self-Attention (MH-FSA), incorporating more informative contextual cues. Specifically, SEA aggregates spectral statistics through covariance matrix normalization before applying channel-wise attention. By projecting feature maps onto the frequency domain, MH-FSA provides the network with a broader context, extending beyond the low-frequency focus of standard self-attention mechanisms. Extensive experiments on the ISPRS Potsdam and LoveDA datasets show that SPENet significantly outperforms state-of-the-art methods. Besides, the proposed SEA module notably rises average F1-score/overall accuracy/mean insert over union wiht more than 2.5/2.6%/2.3%, as demonstrated by ablation study. © 2025 IEEE.

关键词： frequency transformer remote sensing images Semantic segmentation spectrum enhancement

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Millimeter-Wave Broadband Dual-Polarized Shorted Patch-Loaded Magnetoelectric-Dipole Antenna and Its Array

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IEEE Transactions on Antennas and Propagation 2025年

作者： Wang, Gan Zhang, Yan Southeast University State Key Laboratory of Millimeter Waves School of Information Science and Engineering Nanjing210096 China Southeast University School of Information Science and Engineering State Key Laboratory of Millimeter Waves Nanjing210096 China Guilin University of Electronic Technology Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory Guilin541004 China

A broadband dual-polarized antenna is proposed for millimeter-wave (mmW) application, which is composed of two pairs of magnetoelectric (ME) dipoles and a shorted patch. The ME dipoles are arranged into a square ring shape to enclose the shorted patch to generate multiple resonances, and they are fed through a cross-shaped slot by two orthogonally placed feeding strip lines for dual-polarization. The proposed antenna is fabricated and measured, which achieves an impedance bandwidth of 65.4% (21.3-42 GHz) for dual-polarization, with an in-band gain variation of less than 1 dB. A 1 × 8 array is further designed and implemented using two substrate-integrated coaxial line (SICL) feeding networks to excite eight uniformly distributed elements. The measured results show that an impedance bandwidth of 58.75 % (22.1-40.48 GHz) is achieved for dual-polarization, accompanying a peak gain of 15 dBi and gain fluctuation smaller than 3 dB. To break through the beam scanning limitation over the achieved octave bandwidth, an offset feeding scheme is introduced to the proposed antenna, and a smallscale 2×2 non-uniformly arranged array is proposed and numerically analyzed. The measured results indicate that a beam scanning range of ±30° can be achieved over the entire operating bandwidth, and the side-lobe levels (SLLs) remain below -10.46 dB, -11.5 dB, and -10.16 dB at 22, 30, and 38 GHz, respectively. The proposed antenna and its array have features of broad bandwidth, flat gain, stable radiation pattern, and wide-angle scanning, which are promising for mmW communication systems. © 1963-2012 IEEE.

关键词： Dipole antennas

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A 3D Wideband High-Gain Circularly-Polarized Array Antenna with Low RCS Using Simplified Sequential Rotation Topology

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IEEE Antennas and Wireless Propagation Letters 2025年

作者： Wang, Min Li, Xuan Ren, Yi Chen, Zhengchuan Zhao, Shiwei Chongqing University of Posts and Telecommunications School of Optoelectronic Engineering Chongqing400065 China Xidian University National Key Laboratory of Radar Detection and Sensing Shaanxi Xi'an710071 China Chongqing University School of Microelectronics and Communication Engineering Chongqing400044 China Guilin University of Electronic Technology Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory Guilin541004 China

A 3D wideband high-gain circularly-polarized array antenna (CPAA) with low radar cross section (RCS) is presented in this manuscript. Its element contains four 3D radiation structures fed by a low-loss CP feeding structure and four polarimetric rotating-reflecting staircases (PRRSs) designed in a quasi-I shape. Radiation structure is designed as palm-leaf shaped radiator excited by a fan-shaped line and dispersive bilayer director for bandwidth enhancement. Current inversion method is realized by mirroring fan-shaped line to enable a 180° phase change to be compensated by CP feeding structure. Then, a simplified sequential rotation topology is realized to allow CP feeding structure to reduce loss and space occupancy, further enhancing gain and AR bandwidth. By rotating PRRS 90°, current inversion method is achieved to obtain 1-bit phase quantization. Finally, 16 identical elements with unequal phase states of any two adjacent PRRSs are cascaded by a 1-to-16 power divider. The measured results exhibit that a wide -10 dB impendence bandwidth of 32.8% and a gain of 21.1 dBi at 5.8 GHz are achieved. The 3-dB gain bandwidth reaches 31.9% while 3-dB axial ratio bandwidth is 26.7%. Moreover, the measured 10-dB RCS reduction band covers 5.1 GHz – 11.0 GHz. © 2002-2011 IEEE.

关键词： Circular polarization

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GateM2Former: Gated Feature Selection and Expert Modeling in Multimodal Emotion Recognition

GateM2Former: Gated Feature Selection and Expert Modeling in...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Weixiang Xu Zhongren Dong Runming Wang Xinzhou Xu Zixing Zhang College of Computer Science and Electronic Engineering Hunan University China School of Information Science and Engineering Hunan Normal University China Signal Processing and Speech Communication Laboratory Graz University of Technology Austria Shenzhen Research Institute Hunan University China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In recent years, multimodal emotion recognition (MER) has gained significant attention due to its potential to integrate information from diverse signals. However, existing methods often struggle to effectively capture complex interactions and contextual information both inter- and intra-modalities, and even to extract the salient representations from pre-trained models. To address these issues, we propose a novel model, gated Mixture of Multimodal Experts (MoME) and Mixtral of Experts (MixMoE) models, namely GateM 2 Former. The gate mechanism is used to select the most relevant representations from pre-trained models. The MoME and MixMoE expert modules respectively learn the individual characteristics of each modality and the intrinsic alignment and potential interactions between modalities. Besides, we design a hierarchical merge structure to better suit the long sequence scenario (i. e., speech in our case). To verify the effectiveness of the introduced model, we conducted extensive experiments on the IEMOCAP and MELD datasets. The results show that GateM 2 Former, with a universal multimodal structure, is able to achieve the best results on IEMOCAP and MELD compared with other latest approaches.

关键词： Adaptation models Emotion recognition Semantics Speech recognition Logic gates signal processing Transformers Feature extraction Robustness Speech processing

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Boosting polyp screening with improved point-teacher weakly semi-supervised

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Computers in Biology and Medicine 2025年 191卷 109998-109998页

作者： Du, Xiuquan Zhang, Xuejun Chen, Jiajia Li, Lei Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China Department of Neurology Shuyang Affiliated Hospital of Nanjing University of Traditional Chinese Medicine Suqian China School of Computer Science and Technology Anhui University Hefei China

Polyps, like a silent time bomb in the gut, are always lurking and can explode into deadly colorectal cancer at any time. Many methods are attempted to maximize the early detection of colon polyps by screening, however, there are still face some challenges: (i) the scarcity of per-pixel annotation data and clinical features such as the blurred boundary and low contrast of polyps result in poor performance. (ii) existing weakly semi-supervised methods directly using pseudo-labels to supervise student tend to ignore the value brought by intermediate features in the teacher. To adapt the point-prompt teacher model to the challenging scenarios of complex medical images and limited annotation data, we creatively leverage the diverse inductive biases of CNN and Transformer to extract robust and complementary representation of polyp features (boundary and context). At the same time, a novel designed teacher–student intermediate feature distillation method is introduced rather than just using pseudo-labels to guide student learning. Comprehensive experiments demonstrate that our proposed method effectively handles scenarios with limited annotations and exhibits good segmentation performance. All code is available at https://***/dxqllp/WSS-Polyp. © 2025 Elsevier Ltd

关键词： Weakly semi-supervised Medical image segmentation Boundary extraction Feature distillation

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Stable Extended U-Net for Noise-Robust Speaker Verification

Stable Extended U-Net for Noise-Robust Speaker Verification

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Zonghui Wang Zhihua Fang Liang He School of Computer Science and Technology Xinjiang University Urumqi China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi China School of Intelligence Science and Technology Xinjiang University Urumqi China Department of Electronic Engineering Tsinghua University Beijing China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

With advancements in deep learning, speaker verification systems have significantly improved their performance in noisy environments. Researchers typically demonstrate the effectiveness of their improved models by comparing performance on specific datasets, such as the VoxCeleb benchmark. However, in diverse real-world noise conditions, the out-of-domain generalization ability is also a crucial factor in evaluating a model’s performance improvement. Research on stable learning indicates that eliminating the spurious correlation between training and testing data can enhance the generalization of the model. Building on this idea, we propose an improved speaker verification system with high generalization based on the extended U-Net (ExU-Net). It uses the sample reweighting method from stable learning to eliminate sample correlations and retains more effective speaker information through subpixel convolutions and coordinate attention mechanisms. We validate the effectiveness of this approach through extensive evaluations on VoxCeleb1, VOiCES, and other out-of-domain noise test sets, highlighting its generalization capability and model robustness.

关键词： Training Correlation Attention mechanisms Convolution Data models Stability analysis Robustness Noise measurement Speech processing signal to noise ratio

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Conditional Privacy-Preserving Transaction for the Unspent Transaction Output-Based Multi-Chain Blockchain System

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IEEE Transactions on Computers 2025年

作者： Cui, Jie Zhuang, Wenting Zhong, Hong Zhang, Qingyang Wang, Fengqun He, Debiao Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230039 China Anhui University Anhui Engineering Laboratory of IoT Security Technologies Hefei230039 China Wuhan University School of Cyber Science and Engineering Wuhan430072 China MatrixElements Technologies Shanghai Key Laboratory of Privacy Preserving Computation Shanghai201204 China

The anonymity of blockchain may be exploited by criminals for illegal fund transfers, thus a conditional privacy-preserving scheme is important for blockchain regulation. Currently, sharding technology under a multi-chain architecture is used to improve blockchain scalability. However, current conditional privacy-preserving schemes cannot work on this architecture. To protect the privacy of the transaction, we present a conditional privacy-preserving transaction scheme (MC-CPPT) for multi-chain blockchain system. In this system, we proposed a zero-knowledge proof based anonymous transaction, in terms of the identities of transaction participants and amounts, which also enables the unlinkability of transactions and indistinguishability between cross-chain and intra-chain transactions in multi-chain blockchain system. In addition, a multi-node regulatory agency is introduced to control the transaction amount and frequency in the system without a single point of failure. Moreover, an ECC-based encryption scheme is proposed to achieve the traceability of suspicious transactions. A security model is defined and the security of MC-CPPT is demonstrated to meet the expected security goals. Evaluating the prototype revealed acceptable performance and additional security features. © 1968-2012 IEEE.

关键词： Anonymity

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Experimental analysis of sea clutter using airborne circular scanning SAR in medium grazing angle

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Journal of Systems Engineering and Electronics 2019年第1期30卷 68-77页

作者： PAN Xueli LIAO Guisheng YANG Zhiwei DANG Hongxing National Laboratory of Radar Signal Processing Xidian University Academy of Space Electronic Information Technology

The theoretical statistical model of sea clutter is a key issue for maritime surveillance. In recent years, the statistical model of sea clutter has attracted much attention to design the detector well. Meanwhile, the circular scanning synthetic aperture radar(SAR) has been applied to wide surveillance of the sea ***, the paper analyzes the validity of available sea clutter models for range Doppler images from different scan angles for moderate sea state in the medium grazing angle. The parameter estimation method for different distribution models employs the method of logarithmic cumulant(MoLC) based on Mellin transform uniformly. By the analysis of the fitting performance between the histogram of real data and the amplitude probability density function(PDF) of empirical distribution models and the goodness-of-fit(GoF) test for real data from different scan angles, it is indicated the generalized K(GK) distribution with generalized Gamma texture distribution can fit the sea clutter well for different scan angles in the medium grazing angle.

关键词： range Doppler image method of logarithmic cumulant (MoLC) Mellin transform generalized Gamma distribution.

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Mining and Harvesting High Quality Topical Resources from the Web

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Chinese Journal of Electronics 2016年第1期25卷 48-57页

作者： ZHAO Wei GUAN Ziyu CAO Zhengwen LIU Zheng National Laboratory of Radar Signal Processing Xidian University College of Information and Technology Northwest University of China

Focused crawlers aim to effectively prioritize uncrawled URLs to harvest relevant pages while avoiding irrelevant ones. In practice, harvesting high quality topical Web resources is more important due to the explosion of Web information. Our study shows that the popular focused crawling strategy cannot achieve this *** this paper we develop a new focused crawler, namely On-line topical quality estimation(OTQE), which intelligently evaluates the topical quality of uncrawled pages by the observed link and content evidences and prioritize their URLs accordingly. The new crawler is scalable and requires fewer additional resources to do link-based analysis. The experimental results on crawling 3.6 million Web pages demonstrate the advantages of our proposed method over traditional focused crawlers.

关键词： Focused crawling Topical crawlers Clas sification Open directory project

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