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arXiv 2025年

作者： Tang, Shunpu Chen, Yuhao Yang, Qianqian Zhang, Ruichen Niyato, Dusit Shi, Zhiguo College of Information Science and Electronic Engineering Zhejiang University Hangzhou China College of Control Science and Engineering China College of Computing and Data Science Nanyang Technological University Singapore

Semantic communication (SemCom) has emerged as a promising paradigm for enhancing communication efficiency in sixth-generation (6G) networks. However, the broadcast nature of wireless channels makes SemCom systems vulnerable to eavesdropping, which poses a serious threat to data privacy. Therefore, we investigate secure SemCom systems that preserve data privacy in the presence of eavesdroppers. Specifically, we first explore a scenario where eavesdroppers are intelligent and can exploit semantic information to reconstruct the transmitted data based on advanced artificial intelligence (AI) techniques. To counter this, we introduce novel eavesdropping attack strategies that utilize model inversion attacks and generative AI (GenAI) models. These strategies effectively reconstruct transmitted private data processed by the semantic encoder, operating in both glass-box and closed-box settings. Existing defense mechanisms against eavesdropping often cause significant distortions in the data reconstructed by eavesdroppers, potentially arousing their suspicion. To address this, we propose a semantic covert communication approach that leverages an invertible neural network (INN)-based signal steganography module. This module covertly embeds the channel input signal of a private sample into that of a non-sensitive host sample, thereby misleading eavesdroppers. Without access to this module, eavesdroppers can only extract host-related information and remain unaware of the hidden private content. We conduct extensive simulations under various channel conditions in image transmission tasks. Numerical results show that while conventional eavesdropping strategies achieve a success rate of over 80% in reconstructing private information, the proposed semantic covert communication effectively reduces the eavesdropping success rate to 0%. Furthermore, results demonstrate that eavesdroppers can reconstruct host images with relatively good quality, achieving a peak signal-to-noise ratio

关键词： Sensitive data

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Learning from Heterogeneity: A Dynamic Learning Framework for Hypergraphs

arXiv

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arXiv 2023年

作者： Zhang, Tiehua Liu, Yuze Shen, Zhishu Ma, Xingjun Qi, Peng Ding, Zhijun Jin, Jiong The School of Computer Science and Technology Tongji University Shanghai China Ant Group Shanghai China The School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China The School of Computer Science Fudan University Shanghai China The Department of Control Science and Engineering Tongji University Shanghai China The School of Science Computing and Engineering Technologies Swinburne University of Technology Melbourne Australia

Graph neural network (GNN) has gained increasing popularity in recent years owing to its capability and flexibility in modeling complex graph structure data. Among all graph learning methods, hypergraph learning is a technique for exploring the implicit higher-order correlations when training the embedding space of the graph. In this paper, we propose a hypergraph learning framework named Learning from Heterogeneity (LFH) that is capable of dynamic hyperedge construction and attentive embedding update utilizing the heterogeneity attributes of the graph. Specifically, in our framework, the high-quality features are first generated by the pairwise fusion strategy that utilizes explicit graph structure information when generating initial node embedding. Afterwards, a hypergraph is constructed through the dynamic grouping of implicit hyperedges, followed by the type-specific hypergraph learning process. To evaluate the effectiveness of our proposed framework, we conduct comprehensive experiments on several popular datasets with twelve state-of-the-art models on both node classification and link prediction tasks, which fall into categories of homogeneous pairwise graph learning, heterogeneous pairwise graph learning, and hypergraph learning. The experiment results demonstrate a significant performance gain (an average of 12.9% in node classification and 12.8% in link prediction) compared with recent state-of-the-art methods. © 2023, CC BY.

关键词： Contrastive Learning

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Foreign Material Detection and Localization in Stored Grain with Passive RFID Tag Arrays

Foreign Material Detection and Localization in Stored Grain ...

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IEEE International Conference on RFID-Technology and Applications (RFID-TA)

作者： Erbo Shen Weidong Yang Xuyu Wang Shiwen Mao Henan Key Laboratory of Grain Photoelectric Detection & Control Henan University of Technology Zhengzhou China Kaifeng University Kaifeng China College of Information Science & Engineering Henan University of Technology Zhengzhou China Knight Foundation School of Computing & Information Sciences Florida International University Miami FL USA Department of Electrical and Computer Engineering Auburn University Auburn AL USA

In the early stage of harvesting, transportation, and storage, the grain could be mingled with clods from the field, metal pieces from aging machines, and other objects of foreign material, which will greatly influence the grain quality and food security. In this paper, we propose a novel radio frequency (RF) sensing system termed TagSee, which leverages passive RFID tag arrays. The goal is to simultaneously sense the presence of foreign materials and locate their locations in the 3D space, to automatically monitor the stored grain. Specifically, we use RFID received signal strength (RSS) and phase as features for foreign material detection. To design the TagSee system, we first introduce a sensing space division method. Then, an Euclidean Distance Ratio (EDR) algorithm and a heuristic method are proposed to achieve high localization accuracy. Experimental results show that TagSee can effectively detect foreign materials in stored grain and achieve a centimeter-level localization accuracy.

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Research and Exploration on Innovation and Entrepreneurship Practice Education System for Railway Transportation Specialists 9th

Research and Exploration on Innovation and Entrepreneurship ...

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9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023

作者： Yong, Jiu Dang, Jianwu Wang, Yangping Wei, Jianguo Lu, Yan The National Virtual Simulation Experiment Teaching Center of Railway Traffic Information and Control Lanzhou Jiaotong University Lanzhou730070 China College of Intelligence and Computing Tianjin University Tianjin300350 China The School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou730070 China Key Laboratory of Four Electric BIM Engineering and Intelligent Application Railway Industry Lanzhou730070 China

ISBN: (纸本)9789819959709

With the background of concept of rail transit major engineering, guided by industry demand, and based on the cultivation of practical abilities for outstanding engineering and technology talents in rail transit characteristic majors, we are committed to creating a national strategic innovation and entrepreneurship practical education system for rail transit characteristic professionals, continuously improving the practical teaching mode. We will carry out the construction of a "matrix style" practical teaching system that integrates the four modernizations, the construction of a virtual simulation practical teaching platform that integrates expertise and innovation, and open sharing, as well as the reform and exploration of the entire chain of integrated practical education. The scheme focuses on improving students’ ability to solve complex engineering problems and their ability to apply composite knowledge and innovate and start businesses, cultivating a large number of outstanding rail transit engineering talents with solid professional foundations, outstanding practical abilities, and innovative and entrepreneurial qualities. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Light rail transit

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Design and development of embedded networked wireless digital controller for multiple plants using bit-representation data formation 16

Design and development of embedded networked wireless digita...

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16th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2019

作者： Mee-Im, Kritapras Nuratch, Santi Lenwari, Wanchak Faculty of Engineering KMUTT Embedded Computing and Control Laboratory

ISBN: (纸本)9781728133614

This paper proposes some powerful techniques to design and development data packages used for multiple plants embedded wireless digital controller. The system performs data exchanging using master-slave topology, the common one in industrial automation systems. The master and slaves are implemented on low-cost IoT-supported 32-bit microcontroller. The Free-RTOS is used as real-time operating system. All drivers of the master and slave controllers are implemented using C language and mainly preforms bitwise operations to obtain the speed and efficiency of the code execution. The plants used in this research are brushed dc-motors driven by PWM-based bidirectional H-bridge drivers. There are four types of the data packages are proposed. The data packages are designed using bit-representation data formation techniques. The data package design technique requires only one byte for the package header. It can reduce numbers of bytes of data exchanged over network. To archive the real-time control and monitoring capabilities of the system, the WebSockets protocol is selected implemented in all devices, master, slaves and computer. In addition, the proposed system is also evaluated on other protocols, the HTTP and MQTT. The experimental results show that the proposed techniques, system design and data package design, can perform on all communication protocols, no package loss. Using the WebSockets as communication protocol can archive the real-time capability of the system. It means that the proposed system can be implemented in real-world applications, the industrial real-time control monitoring and control systems. © 2019 IEEE.

关键词： Embedded systems

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Federated Reinforcement Learning for Electric Vehicles Charging control on Distribution Networks

arXiv

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arXiv 2023年

作者： Qian, Junkai Jiang, Yuning Liu, Xin Wang, Qiong Wang, Ting Shi, Yuanming Chen, Wei The MoE Engineering Research Center of Software/Hardware Co-design Technology and Application The Shanghai Key Lab. of Trustworthy Computing East China Normal University China The Automatic Control Laboratory EPFL Switzerland The School of Information Science and Technology ShanghaiTech University China The State Grid Beijing Electric Power Company China The Department of Electronic Engineering Tsinghua University China

With the growing popularity of electric vehicles (EVs), maintaining power grid stability has become a significant challenge. To address this issue, EV charging control strategies have been developed to manage the switch between vehicle-to-grid (V2G) and grid-to-vehicle (G2V) modes for EVs. In this context, multi-agent deep reinforcement learning (MADRL) has proven its effectiveness in EV charging control. However, existing MADRL-based approaches fail to consider the natural power flow of EV charging/discharging in the distribution network and ignore driver privacy. To deal with these problems, this paper proposes a novel approach that combines multi-EV charging/discharging with a radial distribution network (RDN) operating under optimal power flow (OPF) to distribute power flow in real time. A mathematical model is developed to describe the RDN load. The EV charging control problem is formulated as a Markov Decision Process (MDP) to find an optimal charging control strategy that balances V2G profits, RDN load, and driver anxiety. To effectively learn the optimal EV charging control strategy, a federated deep reinforcement learning algorithm named FedSAC is further proposed. Comprehensive simulation results demonstrate the effectiveness and superiority of our proposed algorithm in terms of the diversity of the charging control strategy, the power fluctuations on RDN, the convergence efficiency, and the generalization ability. © 2023, CC BY-NC-SA.

关键词： Reinforcement learning

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ESNet: evolution and succession network for high-resolution salient object detection 24

ESNet: evolution and succession network for high-resolution ...

引用

Proceedings of the 41st International Conference on Machine Learning

作者： Hongyu Liu Runmin Cong Hua Li Qianqian Xu Qingming Huang Wei Zhang Institute of Information Science Beijing Jiaotong University & Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing China School of Control Science and Engineering Shandong University & Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Computer Science and Technology Hainan University Hainan China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

Preserving details and avoiding high computational costs are the two main challenges for the High-Resolution Salient Object Detection (HRSOD) task. In this paper, we propose a two-stage HRSOD model from the perspective of evolution and succession, including an evolution stage with Low-resolution Location Model (LrLM) and a succession stage with High-resolution Refinement Model (HrRM). The evolution stage achieves detail-preserving salient objects localization on the low-resolution image through the evolution mechanisms on supervision and feature; the succession stage utilizes the shallow high-resolution features to complement and enhance the features inherited from the first stage in a lightweight manner and generate the final high-resolution saliency prediction. Besides, a new metric named Boundary-Detail-aware Mean Absolute Error (MAEBD) is designed to evaluate the ability to detect details in high-resolution scenes. Extensive experiments on five datasets demonstrate that our network achieves superior performance at real-time speed (49 FPS) compared to state-of-the-art methods. Our code is publicly available at: https://***/rmcong/ESNet_ICML24.

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Air Traffic Management and Communication over ATN/IPS for Future Datalink Communication

Air Traffic Management and Communication over ATN/IPS for Fu...

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Integrated Communications, Navigation and Surveillance Conference, ICNS

作者： Emre Aydoğan Sergun Özmen Fulya Aybek Cetek Rosa María Arnaldo Valdés Raquel Delgado-Aguilera Jurado Angel Ernesto Carmona Fernández Adrián Martínez Miralles Tommaso Vendruscolo Stefano Bonelli Daniel Delahaye Supatcha Chaimatanan Feng Chen Raouf Hamzaoui Air Traffic Control Department Faculty of Aeronautics and Astronautics Eskişehir Technical University Eskişehir Türkiye Turkish Airlines Îstanbul Türkiye Department of Aerospace Systems Air Transport and Airports Universidad Politėcnica de Madrid Madrid Spain Servicios Aeronáuticos Control y Navegación Madrid Spain Deep Blue srl Rome Italy OPTIM Lab École Nationale de l 'Aviation Civile (ENAC) Toulouse France Faculty of Computing Engineering and Media De Montfort University Leicester UK

ISBN: (数字)9798331534738

ISBN: (纸本)9798331534745

The growing demand for air traffic presents challenges in air traffic management, making seamless gate-to-gate communication essential. Traditional radio frequency communication faces limitations such as weather dependency and frequency restrictions. To address these issues, data link communications have gained importance, using VHF channels, satellite systems, and ATN/IPS-based networks. This study introduces the ATMACA (Air Traffic Management and Communication Over ATN/IPS) protocol, an advanced context management framework for ATN/IPS, designed to enhance aviation communications. ATMACA integrates instant messaging and software-defined nodes to improve connectivity, session continuity, and mobility management across networks and devices. It ensures seamless user interaction, reduces pilot workload, and enhances flight safety through automated Air Traffic control (ATC) sector handoff in controller-Pilot Data Link Communications (CPDLC) and Data Link Initiation Capability (DLIC) applications. Another key innovation of the ATMACA framework is Green Route Operations (GRO), which enables real-time trajectory prediction and optimization.

关键词： Wind Temperature distribution Technological innovation Surveillance Green products User centered design Routing protocols Real-time systems Trajectory Air traffic control

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One-Iteration-per-Update 94LVI Algorithm Solving Time-Varying Quadratic Programming in Real Time with Numerical and Graphical Results

One-Iteration-per-Update 94LVI Algorithm Solving Time-Varyin...

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第34届中国控制与决策会议

作者： Yunong Zhang Zhiwen Yuan Tangke Xu School of Computer Science and Engineering Sun Yat-sen University Guangdong Key Laboratory of Modern Control Technology Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Research Institute of Sun Yat-sen University in Shenzhen

Recently,there have been many methods to solve quadratic programming(QP) *** this work,on the basis of linear variational inequality(LVI),a simple and effective algorithmic method(i.e.,one-iteration-per-update 94 LVI algorithm)is proposed for solving the time-varying QP problem,which is subject to time-varying linear equality,inequality and bound constraints at the same *** that the normal 94 LVI algorithm is usually used to find the optimal solution of the static QP problem in the ***,we transform the QP problem into a piecewise-linear projection equation(PLPE).Then,the continuous time-varying QP problem is divided into many static QP problems via sampling time interval ***,we use the normal 94 LVI algorithm to update with only one iteration based on the solution of previous sampling time instant,and finally we get the solution of each sampling time *** numerical experiments,as a novel approach,the one-iterationper-update 94 LVI is able to get the solution of each sampling time instant much quickly and quite accurately when solving the time-varying QP problem.

关键词： time-varying QP problem linear variational inequality piecewise-linear projection equation one-iteration-perupdate 94LVI numerical algorithm

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Percolation Behavior Analysis of Weighted Edge-Coupled Interdependent Networks

SSRN

引用

SSRN 2022年

作者： Xie, Yufeng Sun, Shiwen Wang, Li Xia, Chengyi Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin300384 China Tianjin University of Technology Tianjin300384 China School of Control Science and Engineering Tiangong University Tianjin300387 China

The robustness of interdependent networks has received extensive attention from the inter-disciplinary fields. In reality, many interdependent systems have interdependence relationships not only between nodes but also between edges. Different from previous studies focusing on edge-coupled interdependent networks without consideration on coupling strength, in this paper, a weighted edge-coupled interdependent network model with coupling strength is proposed. Then, the cascading failure propagation mechanism caused by attacking a small percentage of edges is studied. Based on the self-consistent probability theory, theoretical framework is established to provide the mathematical analysis of robustness of weighted edge-coupled interdependent networks under edge attacks. The current results can help to understand the vulnerability of interdependent networks and provide useful suggestions for the protection and optimization of complex networked systems. © 2022, The Authors. All rights reserved.

关键词： Probability

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