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IAENG International Journal of computer Science 2025年第1期52卷 38-45页

作者： Li, Wanji Liu, Qiangbin Zhu, Yi School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China School of Computer Science and Communication Engineering the Dean of Department of Communication Engineering Jiangsu University Zhenjiang China

Named in-network computing service (NICS) is a potential computing paradigm emerged recently. Benefitted from the characteristics of named addressing and routing, NICS can be flexibly deployed on NDN router side and provide nearby computing service to Internet users. But the NICS feature of dynamic deployment also causes serious security risk of access control. How to independently check out the subscription relationship between requester and requested computing service on NICS side become a challenge. To solve this problem, we propose a novel certificateless signature-based access control scheme (CS-ACS) in this paper. In CS-ACS, the entire user public-private key pairs consist of two parts, user side and source server side. Where, the user public-private key pairs (server side) are generated according to the user ID, service subscription relationship and subscription expiration time. Based on this special design, when authorized user signs the interest packet of invoking specific service using its private key, the NICS can verify the signature then check out whether the requester is a valid subscriber and the subscription is expired or not. Simulation results show that, comparing with fundamental solutions, CS-ACS can avoid extra secret key storage cost on NICS side and markedly shorten authentication delay. © (2025), (International Association of Engineers). All rights reserved.

关键词： Authentication

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Low-profile,low sidelobe array antenna with ultrawide beam coverage for UAV communication

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Chinese Journal of Aeronautics 2025年第1期38卷 444-454页

作者： Mei LI Zhiliang SHANG Lin PU Ming-Chun TANG Lei ZHU School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China Department of Electrical and Computer Engineering University of MacaoMacao SAR 999078China

This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground *** array consists of ten broadside-radiating,ultrawide-beamwidth elements that are cascaded by a central-symmetry series-fed network with tapered currents following Dolph-Chebyshev distribution to provide low ***,an innovative design of end-fire Huygens source antenna that is compatible with metal ground is presented.A low-profile,half-mode Microstrip Patch Antenna(MPA)is utilized to serve as the magnetic dipole and a monopole is utilized to serves as the electric dipole,constructing the compact,end-fire,grounded Huygens source ***,two opposite-oriented end-fire Huygens source antennas are seamlessly integrated into a single antenna element in the form of monopole-loaded MPA to accomplish the ultrawide,broadside-radiating *** consideration has been applied into the design of series-fed network as well as antenna element to compensate the adverse coupling effects between elements on the radiation *** indicates an ultrawide Half-Power Beamwidth(HPBW)of 161°and a low SLL of-25 dB with a high gain of 12 d Bi under a single-layer *** concurrent ultrawide beamwidth and low SLL make it particularly attractive for applications of UAV air-to-ground communication.

关键词： Array antenna Broad beam Fan beam Low sidelobe level Chebyshev synthesis UAV communication

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Intelligent integrated sensing and communication:a survey

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Science China(Information Sciences) 2025年第3期68卷 5-46页

作者： Jifa ZHANG Weidang LU Chengwen XING Nan ZHAO Naofal AL-DHAHIR George K.KARAGIANNIDIS Xiaoniu YANG School of Information and Communication Engineering Dalian University of Technology College of Information Engineering Zhejiang University of Technology School of Information and Electronics Beijing Institute of Technology Department of Electrical and Computer Engineering The University of Texas at Dallas Department of Electrical and Computer Engineering Aristotle University of Thessaloniki

Integrated sensing and communication (ISAC) is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities. However, the traditional ISAC schemes are highly dependent on the accurate mathematical model and suffer from the challenges of high complexity and poor performance in practical scenarios. Recently, artificial intelligence (AI) has emerged as a viable technique to address these issues due to its powerful learning capabilities, satisfactory generalization capability, fast inference speed, and high adaptability for dynamic environments, facilitating a system design shift from model-driven to data-driven. Intelligent ISAC, which integrates AI into ISAC, has been a hot topic that has attracted many researchers to investigate. In this paper, we provide a comprehensive overview of intelligent ISAC, including its motivation, typical applications, recent trends, and challenges. In particular, we first introduce the basic principle of ISAC, followed by its key techniques. Then, an overview of AI and a comparison between model-based and AI-based methods for ISAC are provided. Furthermore, the typical applications of AI in ISAC and the recent trends for AI-enabled ISAC are reviewed. Finally, the future research issues and challenges of intelligent ISAC are discussed.

关键词： artificial intelligence deep learning deep reinforcement learning federated learning generative artificial intelligence integrated sensing and communication machine learning transfer learning

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Uplink MIMO communications with RIS-Integrated Base Station: Modeling and Experiments

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IEEE Internet of Things Journal 2025年第10期12卷 14150-14171页

作者： Park, Je Hyeon Kim, Su Hyun Amri, Muhammad Miftahul Tran, Nguyen Minh Kim, Dong In Choi, Kae Won School of Information and Communication Engineering Department of Electrical and Computer Engineering Suwon16419 Korea Republic of Department of Wireless Communications Hanoi Viet Nam

Reconfigurable intelligent surface (RIS) has gained significant momentum as a cost-effective and energy-efficient technology to enable the next generation of mobile communications. In this paper, we propose an RIS-integrated base station (BS) by deploying an RIS sufficiently close to the base station antennas (BAs), within its radiative near-field range. In the proposed RIS-integrated BS system, we utilize RIS as a passive array to reconfigure incoming signals from UEs without experiencing substantial path loss. The near-field channel model between the RIS and BAs is analyzed and applied to the RIS beam control model. Furthermore, we develop a practical algorithm to maximize the performance of the proposed RIS-integrated BS-based uplink multiple-input-multiple-output (MIMO) system with the aim of maintaining reasonable complexity. This goal is achieved by combining the two proposed algorithms, beam search and path-antenna pairing algorithms. The beam search algorithm identifies the radio paths of all UEs to the RIS by sweeping the beams of the RIS. Then the path-antenna pairing algorithm allocates the strongest radio path between each UE and the RIS to one of the BAs by controlling an RIS beam to direct the signal from that path to the BA. Finally, we have built a real-time testbed to experiment with the proposed RIS-integrated BS-based uplink MIMO system. Numerical results, including experimental data, validate the effectiveness of the proposed RIS-integrated BS-based uplink MIMO system. © 2025 IEEE.

关键词： Mobile telecommunication systems

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The Combined Enforcement of Normal and Tangential Boundary Conditions on the PEC-Material Interfaces in the Volume-Surface Integral Equation

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IEEE Transactions on Antennas and Propagation 2025年第5期73卷 3364-3369页

作者： Liu, Jinbo Li, Zengrui Song, Jiming Communication University of China School of Information and Communication Engineering Beijing100024 China Iowa State University Department of Electrical and Computer Engineering AmesIA50011 United States

In the moment method solution of the volume-surface integral equation (VSIE) modeling composite objects, the normal and tangential boundary conditions (BCs) of electric and magnetic fields are combined and collectively enforced on the perfect electric conductor (PEC)-material interfaces (PMIs). The numbers of both electric and magnetic volumetric unknowns are therefore significantly reduced. Based on the enforcement of the normal boundary condition, the SWG coefficients of the volume currents that are defined on the PEC-terminated tetrahedral faces can be straightforwardly calculated, which are no longer volumetric unknowns. Similarly, due to the enforcement of the tangential boundary condition, two coefficients of the four SWG bases defined on a tetrahedron, at least one of whose faces is PEC-terminated, can be determined by the other two using the weighted least-square (LS) method. Further, due to the explicit satisfaction of BCs, the proposed BCs-based VSIE improves the solution accuracy. Efficiency and validity of the proposed approach are verified by reliable numerical experiments, in which both the isotropic and anisotropic materials are involved. © 2025 IEEE.

关键词： Interfaces (materials)

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Privacy-preserving explainable AI: a survey

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Science China(Information Sciences) 2025年第1期68卷 23-56页

作者： Thanh Tam NGUYEN Thanh Trung HUYNH Zhao REN Thanh Toan NGUYEN Phi Le NGUYEN Hongzhi YIN Quoc Viet Hung NGUYEN School of Information and Communication Technology Griffith University School of Computer and Communication Sciences Ecole Polytechnique Federale de Lausanne Faculty of Mathematics and Computer Science University of Bremen Faculty of Information Technology HUTECH University Department of Computer Science Hanoi University of Science and Technology School of Electrical Engineering and Computer Science The University of Queensland

As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.

关键词： privacy-preserving explainable AI privacy attacks privacy defences PrivEx PPXAI

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On the Price of Decentralization in Decentralized Detection

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IEEE Transactions on Information Theory 2025年第4期71卷 2341-2359页

作者： Huang, Bruce Wang, I-Hsiang University of California Department of Electrical and Computer Engineering Los Angeles United States National Taiwan University Graduate Institute of Communication Engineering Department of Electrical Engineering Taipei Taiwan

Fundamental limits on the error probabilities of a family of decentralized detection algorithms (eg., the social learning rule proposed by Lalitha et al. [2]) over directed graphs are investigated. In decentralized detection, a network of nodes locally exchanging information about the samples they observe with their neighbors to collectively infer the underlying unknown hypothesis. Each node in the network weighs the messages received from its neighbors to form its private belief and only requires knowledge of the data generating distribution of its observation. In this work, it is first shown that while the original social learning rule of Lalitha et al. [2] achieves asymptotically vanishing error probabilities as the number of samples tends to infinity, it suffers a gap in the achievable error exponent compared to the centralized case. The gap is due to the network imbalance caused by the local weights that each node chooses to weigh the messages received from its neighbors. To close this gap, a modified learning rule is proposed and shown to achieve error exponents as large as those in the centralized setup. This implies that there is essentially no first-order penalty caused by decentralization in the exponentially decaying rate of error probabilities. To elucidate the price of decentralization, further analysis on the higher-order asymptotics of the error probability is conducted. It turns out that the price is at most a constant multiplicative factor in the error probability, equivalent to an o(1/t) additive gap in the error exponent, where t is the number of samples observed by each agent in the network and the number of rounds of information exchange. This constant depends on the network connectivity and captures the level of network imbalance. Results of simulation on the error probability supporting our learning rule are shown. Further discussions and extensions of results are also presented. © 1963-2012 IEEE.

关键词： Convergence Testing Vectors Error probability Network topology Directed graphs Training Symmetric matrices Iterative methods Internet of Things

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Utilization of Two Cross Two Switch for Bitonic Sorting Circuit

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Micro and Nanosystems 2025年第1期17卷 45-57页

作者： Bhattacharjee, Subhasree Sarkar, Soumyadip Das, Kunal Sadhu, Arindam Sarkar, Bikramjit Department of Computer Application Narula Institute of Technology Kolkata India Department of Computer Science Acharya Prafulla Chandra College Kolkata India Department of Electronics & Communication Engineering Greater Kolkata College of Engineering and Management West Bengal India Department of Computer Science & Engineering JIS College of Engineering West Bengal India

Background: The synthesis of reversible logic has gained prominence as a crucial research area, particularly in the context of post-CMOS computing devices, notably quantum computing. Objective: To implement the bitonic sorting circuit, 2x2 switch, is used. The overarching objective of implementing a reversible sorting circuit is to mitigate power consumption while promising secure communication. The successful implementation of the bitonic sorting circuit utilizing the proposed 2x2 switch is validated through simulations conducted in IBM Qiskit. Methods: This study begins by employing the control swap gate to implement a 2x2 switch, aimed at enabling concurrent computing operations within multiprocessor systems to enhance throughput. Subsequently, following the successful implementation of the 2x2 switch, the study proceeds to design a bitonic sorting circuit. Results: Bitonic sort using a 2x2 switch on the IBM Quantum Experience (IBMQ) platform via the QISKit SDK in Python 3.6. Specifically, Qiskit v0.29.0 is utilized, with OpenQASM. OpenQASM serves as the quantum assembly and instruction language. Conclusion: This work presents a methodology for constructing a 2x2 switch, utilizing a reversible control swap gate as its core component. Additionally, it demonstrates the intricate development and implementation of a bitonic sorting circuit, capitalizing on this innovative switch architecture. © 2025 Bentham Science Publishers.

关键词： Quantum computers

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Developing a photovoltaic energy generation forecast system using neural networks

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International Journal of Information Technology (Singapore) 2025年第2期17卷 969-973页

作者： Trrad, Issam Computer & amp Communication Engineering Department Faculty of Engineering Jadara University Irbid Jordan

Photovoltaic (PV) system is one of the trending and alternative sources of energy. Harnessing reliable energy in these PV panels is a cumbersome task equipped with several challenges such as continuous monitoring, adaptability in varying weather conditions, solar irradiance, wind speed and many more. It requires an optimized system to forecast solar energy efficiently. Thus, the given paper introduces a subnet-based feed forward neural network (SFFNN) to forecast solar PV energy generation based on varying weather conditions. The neural network is trained using Levenberg–Marquardt (LM) algorithm to discover connections among learning variables in the neural network. LM algorithm optimizes SFFNN by avoiding training failures and performing forward as well as backward computation for all neurons in the network layer thereby leading to faster convergence rate. Lastly, the performance of the proposed SFFNN is validated and compared with existing recent studies based on metrics such as root mean square error (RMSE) and mean absolute error (MAE). © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Deep learning Energy forecasting LM algorithm PV system SFFNN

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Verification of news and certificate, and plagiarism detector

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Multimedia Tools and Applications 2025年 1-28页

作者： Jain, Pushpak Anand, Dewansh Rajni Behal, Vansh Kapoor, Vipul Sharma, Neha Jindal, Neeru Department of Electronics and Communication Engineering Thapar Institute of Engineering and Technology Punjab Patiala India Department of Computer Science and Engineering Chitkara University Institute of Engineering and Technology Chitkara University Punjab Patiala India

Fake news, Fake certification, and Plagiarism are the most common issues arising these days. During this COVID-19 situation, there are a lot of rumors and fake news spreading and some of us are using fake certification to avoid vaccination and plagiarism became the most common topic during online studies. It is found that several apps and websites are present for the detection of false news and plagiarism. However, there is no single website for the detection of fake certificates. Moreover, nothing is made that consists of all these features in one platform. So, this proposed work develops a website for detecting fake news, Fake certificate, and plagiarism detector. The proposed method uses Natural Language Processing techniques for detecting NPC (news, plagiarism, and certificate). The proposed work uses image processing with some Python libraries like OpenCV in all the detections and that makes it quite interesting. For detecting NPC (news, plagiarism, and certificate) the algorithm is built using a k-mean model, logistic regression, and neural network. The proposed work uses the datasets that are trained using the count vectorizer method for the detection and to get its accuracy which will be tested using machine learning algorithms. The proposed method has shown an accuracy rate of 94.28% on Logistics Regression in comparison to existing methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Fake news Machine learning Natural language processing Plagiarism Social media platform

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