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Enhancing Graph Structure Learning Via Motif-Driven Hypergraph Construction

IEEE Transactions on Network Science and Engineering 2025年第3期12卷 2333-2344页

作者： Zhao, Jia-Le Zhang, Xian-Jie Ding, Xiao Zhang, Xingyi Zhang, Hai-Feng Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Science Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230601 China

Graph neural networks (GNNs), as a cutting-edge technology in deep learning, perform particularly well in various tasks that process graph structure data. However, their foundation on pairwise graphs often limits their capacity to capture latent higher-order topological semantic information. Thus, it is crucial to find a way to extract the latent higher-order information of graphs without missing the lower-order information of the original graph. To address this issue, we here develop a method to construct hypergraph based on motifs, and then a novel neural network framework, named MD-HGNN, is proposed for enhanced graph learning. Specifically, we first utilize motifs of the original graph to construct the hypergraph and eliminate nested structures within the hypergraph to prevent information redundancy. Subsequently, GNNs and hypergraph neural networks (HGNNs) are employed separately to extract the lower-order and higher-order topological semantic information of the graph. Finally, the lower-order and higher-order information are integrated to obtain an embedded representation of graph. Extensive experimental results demonstrate that MD-HGNN preserves the original lower-order graph structure information while effectively extracting higher-order features. Moreover, its performance and robustness are validated across different downstream tasks. © 2025 IEEE. All rights reserved.

关键词： Graph neural networks

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An Improved Compressive Sensing-Based Model for Efficient Analysis of Monostatic Electromagnetic Scattering Problems

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IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 388-391页

作者： Qi, Qi Fan, Yunuo Cao, Xinyuan Liu, Yi Kong, Meng Huang, Zhixiang Wu, Xianliang Hefei Normal University Anhui Province Key Laboratory of Simulation Calculation and Design for Electronic Information System Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei230601 China

To further accelerate the analysis of monostatic electromagnetic (EM) scattering problems of objects, an improved compressive sensing (CS)-based model is proposed. First, an orthogonal subspace spanned by the wide-angle induced currents is identified by means of the wide-angle incident sources. Then, the sparse transform of the induced currents is replaced by the subspace projection. In addition, an optimal number of measurements is determined, only slightly larger than the dimension of the subspace. Finally, the recovery algorithm is simplified to the least-squares method to solve the resulting overdetermined system. Compared with the traditional CS-based model, the proposed model significantly improves the efficiency of the recovery step and optimizes both the requirement for and the way of determining the number of measurements. © 2023 IEEE.

关键词： Least squares approximations

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An Evolutionary Multitasking Algorithm for Efficient Multiobjective Recommendations

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第3期6卷 518-532页

作者： Tian, Ye Ji, Luke Hu, Yiwei Ma, Haiping Wu, Le Zhang, Xingyi Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230601 China Anhui University Institutes of Physical Science and Information Technology Hefei230601 China Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Hefei230029 China

Represented by evolutionary algorithms and swarm intelligence algorithms, nature-inspired metaheuristics have been successfully applied to recommender systems and amply demonstrated effectiveness, in particular, for multiobjective recommendation. Owing to the population-based search paradigm, these algorithms can produce a number of recommendation lists, making diverse tradeoffs between multiple metrics and meeting the requirements of accuracy, novelty, diversity, and other user preferences. However, these algorithms are criticized for the low efficiency of the optimization process, especially when the number of users is large. To address this issue, this article proposes an evolutionary multitasking-based recommendation method, where each task corresponds to a user and all the tasks are optimized simultaneously, thus highly improving the efficiency of recommendation. To enhance the convergence speed, all the users are divided into multiple populations according to the similarity between their preferences, where each population evolves with internal knowledge transfer between users, and all the populations evolve with external knowledge transfer between populations. Experimental results on various datasets verify that the proposed method can better balance between multiple metrics than classical and deep neural network-based recommendation methods and exhibits significantly higher efficiency than evolutionary multiobjective optimization-based recommendation methods. © 2024 IEEE. All rights reserved.

关键词： Multiobjective optimization

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Determining the covering radius of all generalized Zetterberg codes in odd characteristic

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IEEE Transactions on Information Theory 2025年第5期71卷 3602-3613页

作者： Shi, Minjia Li, Shitao Helleseth, Tor Özbudak, Ferruh Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Mathematical Sciences Hefei230601 China Anhui University School of Mathematical Sciences Anhui Hefei230601 China University of Bergen Department of Informatics Bergen Norway Sabanci University Faculty of Engineering and Natural Sciences Istanbul34956 Turkey

For an integer s ≥ 1, let Cs(q0) be the generalized Zetterberg code of length qs0 + 1 over the finite field Fq0 of odd characteristic. Recently, Shi, Helleseth, and Özbudak (IEEE Trans. Inf. Theory 69(11): 7025-7048, 2023) determined the covering radius of Cs(q0) for qs0 7 (mod 8), and left the remaining case as an open problem. In this paper, we develop a general technique involving arithmetic of finite fields and algebraic curves over finite fields to determine the covering radius of all generalized Zetterberg codes for qs0 ≡ 7 (mod 8), which therefore solves this open problem. We also introduce the concept of twisted half generalized Zetterberg codes of length qs0+1/2, and show the same results hold for them. As a result, we obtain some quasi-perfect codes. © 1963-2012 IEEE.

关键词： Turbo codes

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Dual Averaging for Distributed Unbalanced Optimization with Delayed Information

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IEEE Transactions on signal and Information processing over Networks 2025年 11卷 366-377页

作者： Huang, Qing Fan, Yuan Cheng, Songsong Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and Automation Anhui Hefei230601 China

In this paper, we study a category of distributed constrained optimization problems where each agent has access to local information, communicates with its neighbors, and cooperatively minimizes the aggregated cost functions over time-varying unbalanced graphs. To address the considered problems, we propose a distributed dual averaging algorithm based on a row-stochastic weighted matrix (DDAR), which improves the robustness of network topology compared to conventional push-sum algorithms. Moreover, we develop a modified version of DDAR with delayed information (DDARD), which considers the delays of both network communication and gradient calculation, enhancing the algorithm's flexibility in communication and iteration. Our analysis demonstrates that the DDAR and DDARD achieve the optimal value at rates of O(N/(1-λ)√T) and O(τ2N/(1-λ}})√T}), respectively. Finally, the theoretical results are confirmed by simulation on a logistic regression problem. © 2015 IEEE.

关键词： Cost functions

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Security-Enhanced Data Sharing Via Efficient Sanitization for VANETs

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IEEE Transactions on Mobile computing 2025年第06期24卷 4925-4938页

作者： Zhong, Hong Zhou, Dan Cui, Jie Wang, Li Zhang, Jing Bolodurina, Irina He, Debiao Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Computer Science and Technology Hefei230039 China Anhui University Anhui Engineering Laboratory of IoT Security Technologies Hefei230039 China Orenburg State University Faculty of Mathematics and Information Technologies Orenburg460018 Russia Wuhan University School of Cyber Science and Engineering Wuhan430072 China MatrixElements Technologies Shanghai Key Laboratory of Privacy Preserving Computation Shanghai201204 China

With the widespread deployment of vehicular ad-hoc networks (VANETs), data sharing has garnered considerable attention as a core feature of VANETs. Attribute-based proxy re-encryption (ABPRE) enables fine-grained access control and provides flexible ciphertext updates. The initially authorized vehicle generates the re-encryption key to enable ciphertext-to-ciphertext conversion in the cloud, allowing ciphertext to be shared with new recipients. However, initially authorized vehicles may not always be trustworthy and could share data with malicious receivers. In addition, the computation and communication overhead of ABPRE hinders its widespread application in VANETs. To address these issues, we propose a lightweight sanitizable scheme for edge-assisted VANETs based on ABPRE. In this scheme, the re-encryption key is verified by a sanitizer, to prevent the data from being shared with malicious data receivers. In addition, key-splitting techniques and edge computing are employed to reduce the communication and computation overhead of re-encryption. A comprehensive security analysis and performance evaluation demonstrate that the proposed scheme is efficient and practical. © 2002-2012 IEEE.

关键词： Ciphertext

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On the Performance of Active RIS-Assisted Mixed RF-THz Relaying Systems

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IEEE Internet of Things Journal 2025年第10期12卷 14938-14951页

作者： Yin, Yiyang Yang, Liang Li, Xingwang Liu, Hongwu Guo, Kefeng Li, Yingsong Hunan University College of Computer Science and Electronic Engineering Changsha410082 China Henan Polytechnic University School of Physics and Electronic Information Engineering Jiaozuo454000 China Shandong Jiaotong University School of Information Science and Electrical Engineering Jinan250357 China Space Engineering University School of Space Information Beijing101407 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei230601 China

We investigate the performance of an active reconfigurable intelligent surface (RIS)-assisted mixed radio frequency (RF)-terahertz (THz) relaying system, where the RF signal reaches the relay through the active RIS and is then transmitted to the user via the THz channel. Under this scenario, we analyze the system performance with the relay employing amplify-and-forward (AF) and decode-and-forward (DF) protocols. More specifically, we derive the exact expressions for the cumulative distribution function (CDF) of the end-to-end signal-to-noise ratio (SNR) for both relaying protocols. Based on this, we obtain the exact expressions for the outage probability, average bit error rate (ABER), and average channel capacity (ACC). Furthermore, to gain deeper insights, we derive the asymptotic expressions at high SNRs and obtain diversity order (DO) of the system. Moreover, we extend the analysis to the variable gain relaying scheme. The findings reveal that the DOs for both relaying protocols are determined by the THz channel parameters, and the DO under the AF relaying protocol is twice that of the DF relaying protocol. Finally, we validate that active RIS (A-RIS) can more effectively assist the performance of the mixed RF-THz relaying system compared to passive RIS. © 2014 IEEE.

关键词： Distribution functions

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A Tetrahedral Spectral Element Method for Thermo-Mechanical Analysis of Electronic Devices

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IEEE Transactions on Components, Packaging and Manufacturing Technology 2025年

作者： Feng, Naixing Zhang, Shuai Huang, Zhixiang Liu, Qi Qiang Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Laboratory of Electromagnetic Environmental Sensing of Anhui Higher Education Institutes Hefei China Hangzhou Dianzi University School of Electronics and Information Engineering Hangzhou310018 China

For the coupled thermo-mechanical simulation of complex electronic devices, we propose a Tetrahedral Spectral Element Method (TSEM), which truly combines the high accuracy of spectral methods with the strong geometric adaptability of Finite Element Methods (FEMs). The TSEM employs a collapse transformation method and successfully converts the orthogonal Gauss-Lobatto-Legendre (GLL) basis functions from a hexahedron to a tetrahedral reference element. This ensures numerical accuracy and stability for arbitrary high-order interpolation. We also generate non-equidistant GLL spectral interpolation nodes for tetrahedral elements through Warp&Blend transformation, enabling direct nodal numerical integration calculation through Vandermonde matrices. This approach replaces the classical Gaussian quadrature in the FEM, not only significantly enhancing the computational efficiency of element matrix but also avoiding potential numerical dissipation and dispersion associated with Gaussian integration, thus achieving rapid convergence. In the TSEM thermo-mechanical coupling, we further construct a separate solver based on the implicit Newmark-β method, which realizes unconditional stability for temporal integration for arbitrary time step increment. Moreover, it supports independent inversion of system matrices for temperature and stress fields, without increasing computational resource consumption due to the coupling of multi-physics equations. By quantitatively comparing with the COMSOL Multiphysics software, several typical case studies are used to demonstrate the significant advantages of the TSEM in numerical accuracy, efficiency, and stability. © 2025 IEEE. All rights reserved.

关键词： Orthogonal functions

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A Nonconformal SETI-DP Method for Transient Thermal Simulation

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IEEE Transactions on Components, Packaging and Manufacturing Technology 2025年

作者： Feng, Naixing Li, Hongyang Huang, Zhixiang Liu, Qi Qiang Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education The Information Materials and Intelligent Sensing Laboratory of Anhui Province The Key Laboratory of Electromagnetic Environmental Sensing of Anhui Higher Education Institutes Hefei China Hangzhou Dianzi University School of Electronics and Information Engineering Hangzhou310018 China

This paper proposes a novel nonconformal meshbased dual-primal spectral element tearing and interconnecting (SETI-DP) method designed for the efficient transient simulation of complex large-scale heat conduction problems utilizing a domain decomposition method (DDM). This method allows for the division of complex, large-scale problems into smaller subdomain problems. By applying Robin-type transmission conditions at the subdomain interfaces, rapid convergence of the global interface iterative solution is achieved for arbitrary non-conformal subdomain problems. This non-conformal DDM approach supports independent meshing of subdomains, eliminating the need to generate a globally continuous mesh for large-scale problems, thereby significantly enhancing meshing efficiency. In addition, this non-conformal meshing strategy enables high-contrast spatial discretization and mixed-order spectral interpolation between different subdomains. This significantly increases meshing flexibility, minimizes the number of degrees of freedom (DoF) in multi-scale problems, and reduces computational costs. In addition, by developing a subdomain-coupled time iteration scheme, the global corner problem of residual transfer is explicitly given, which greatly improves the versatility and flexibility of the algorithm. Finally, to demonstrate the accuracy, efficiency, and robustness of our algorithm, we conduct benchmark tests on several representative examples. © 2011-2012 IEEE.

关键词： Domain decomposition methods

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Enhancing bone-conducted speech with spectrum similarity metric in adversarial learning

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Speech Communication 2025年 170卷

作者： Pan, Yan Zhou, Jian Wang, Huabin Zheng, Wenming Tao, Liang Kwan, Hon Keung Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei230601 China Key Laboratory of Child Development and Learning Science Ministry of Education and School of Biological Science and Medical Engineering Southeast University Nanjing210096 China Department of Electrical and Computer Engineering University of Windsor Windsor Canada

Although bone-conducted (BC) speech offers the advantage of being insusceptible to background noise, its transmission path through bone tissue entails not only serious attenuation of high-frequency components but also speech distortion and the loss of unvoiced speech, resulting in a substantial degradation in both speech quality and intelligibility. Existing BC speech enhancement methods focus mainly on approaching high-frequency component restoration but overlook the restoration of missing unvoiced speech and the mitigation of speech distortion, resulting in a noticeable gap in speech quality and intelligibility compared to air-conducted (AC) speech. In this paper, a spectrum-similarity metric based adversarial learning method is proposed for bone-conducted speech enhancement. The acoustic features corresponding to source-excitation and filter-response are disentangled using the WORLD vocoder and mapped to its AC speech counterparts with logarithmic Gaussian normalization and a vocal tract converter, respectively. To reconstruct unvoiced speech from BC speech and decrease the nonlinear speech distortion in BC speech, the vocal tract converter predicts low-dimensional Mel-cepstral coefficients of AC speech using a generator which is supervised by a classification discriminator and a spectrum similarity discriminator. While the classification discriminator is used to distinguish between authentic AC speech and enhanced BC speech, the spectrum similarity discriminator is designed to evaluate the spectrum similarity between enhanced BC speech and its AC counterpart. To evaluate spectrum similarity, the correlation of time–frequency units in spectrum of long duration is captured within the self-attention layer embedded in the spectrum similarity discriminator. Experimental results on various speech datasets show that the proposed method is capable of restoring unvoiced speech segment and diminishing speech distortion, resulting in predicting accurate fine-grained AC spe

关键词： Speech intelligibility

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