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arXiv 2023年

作者： Chen, Zhimin Chen, Peng Zheng, Le Zhang, Yudong The School of Electronic and Information Shanghai Dianji University Shanghai201306 China The Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong The State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China State Key Laboratory of Integrated Services Networks Xidian University Xi’an710071 China The Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing100081 China The Chongqing Innovation Center Beijing Institute of Technology Chongqing401120 China The School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom

Reconfigurable intelligent surface (RIS) or intelligent reflecting surface (IRS) has been an attractive technology for future wireless communication and sensing systems. However, in the practical RIS, the mutual coupling effect among RIS elements, the reflection phase shift, and amplitude errors will degrade the RIS performance significantly. This paper investigates the two-dimensional direction-of-arrival (DOA) estimation problem in the scenario using a practical RIS. After formulating the system model with the mutual coupling effect and the reflection phase/amplitude errors of the RIS, a novel DNN-DANM method is proposed for the DOA estimation by combining the deep neural network (DNN) and the decoupling atomic norm minimization (DANM). The DNN step reconstructs the received signal from the one with RIS impairments, and the DANM step exploits the signal sparsity in the two-dimensional spatial domain. Additionally, a semi-definite programming (SDP) method with low computational complexity is proposed to solve the atomic minimization problem. Finally, both simulation and prototype are carried out to show estimation performance, and the proposed method outperforms the existing methods in the two-dimensional DOA estimation with low complexity in the scenario with practical RIS. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

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Reputation-based synergy and discounting mechanism promotes cooperation

arXiv

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arXiv 2023年

作者： Zhu, Wenqiang Wang, Xin Wang, Chaoqian Liu, Longzhao Zheng, Hongwei Tang, Shaoting Institute of Artificial Intelligence Beihang University Beijing100191 China Key laboratory of Mathematics Informatics and Behavioral Semantics Beihang University Beijing100191 China Zhongguancun Laboratory Beijing100094 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Beijing100191 China PengCheng Laboratory Shenzhen518055 China Institute of Medical Artificial Intelligence Binzhou Medical University Yantai264003 China State Key Lab of Software Development Environment Beihang University Beijing100191 China School of Mathematical Sciences Dalian University of Technology Dalian116024 China Department of Computational and Data Sciences George Mason University FairfaxVA22030 United States Beijing Academy of Blockchain and Edge Computing Beijing100085 China

A good group reputation often facilitates more efficient synergistic teamwork in production activities. Here we translate this simple motivation into a reputation-based synergy and discounting mechanism in the public goods game. Specifically, the reputation type of a group, either good or bad determined by a reputation threshold, modifies the nonlinear payoff structure described by a unified reputation impact factor. Results show that this reputation-based incentive mechanism could effectively promote cooperation compared with linear payoffs, despite the coexistence of synergy and discounting effects. Notably, the complicated interactions between reputation impact and reputation threshold result in a sharp phase transition from full cooperation to full defection. We also find that the presence of a few discounting groups could increase the average payoffs of cooperators, leading to an interesting phenomenon that when the reputation threshold is raised, the gap between the average payoffs of cooperators and defectors increases while the overall payoff decreases. Our work provides important insights into facilitating cooperation in social groups. Copyright © 2023, The Authors. All rights reserved.

关键词： Defects

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Malicious Code Detection Technology Based on A3C Algorithm

Malicious Code Detection Technology Based on A3C Algorithm

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IEEE International Conference on Software engineering and Service Sciences (ICSESS)

作者： Yi Xue Hui Shu Wenjuan Bu Wu Qu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Beijing Venustech Cybervision Co. Ltd. China Beijing China

ISBN: (数字)9781728165790

ISBN: (纸本)9781728165806

In the face of the explosive growth of malicious code, this paper proposes a malicious code detection technology based on the A3C algorithm. The technology constructs a malicious code anti-detection adversarial model through the A3C algorithm of the reinforcement learning. It can automatically generates anti-detection malicious samples that bypass the intelligent model on the existing malicious sample set, constructs the anti-detection sample training data set, uses the anti-detection sample training data set to iteratively train new intelligent detection models, continuously builds a reinforcement learning intelligent detection model with continuously enhanced capabilities.

关键词： Face recognition Software algorithms Training data Reinforcement learning Malware Data models Software engineering

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Skyrmions in nanorings: A versatile platform for skyrmionics

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Physical Review Applied 2023年第4期20卷 044039-044039页

作者： Dimitris Kechrakos Vito Puliafito Alejandro Riveros Jiahao Liu Wanjun Jiang Mario Carpentieri Riccardo Tomasello Giovanni Finocchio Physics Laboratory Department of Education School of Pedagogical and Technological Education (ASPETE) Athens Greece Department of Electrical and Information Engineering Technical University of Bari Bari 70125 Italy Escuela de Ingeniería Universidad Central de Chile Santiago 8330601 Chile Department of Mathematical and Computer Sciences Physical Sciences and Earth Sciences University of Messina Messina I-98166 Italy State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics Tsinghua University Beijing 100084 China Frontier Science Center for Quantum Information Tsinghua University Beijing 100084 China College of Advanced Interdisciplinary Studies & Hunan Provincial Key Laboratory of Novel Nano-Optoelectronic Information Materials and Devices National University of Defense Technology Changsha Hunan 410073 China

The dynamical properties of skyrmions can be exploited to build devices with new functionalities. Here, we first investigate a skyrmion-based ring-shaped device by means of micromagnetic simulations and Thiele’s equation. We subsequently show three application scenarios: (1) a clock with tunable frequency that is biased with an electrical current having a radial spatial distribution, (2) an alternator, where the skyrmion circular motion driven by an engineered anisotropy gradient is converted into an electrical signal, and (3) an energy harvester, where the skyrmion motion driven by a thermal gradient is converted into an electrical signal, thus providing a heat recovery operation. We also show how to precisely tune the frequency and amplitude of the output electrical signals by varying material parameters, geometrical parameters, and number and velocity of skyrmions, and we further prove the correct device functionality under realistic conditions of room temperature and internal material defects. Our results open an alternative route for the realization of energy efficient nanoscale clocks, generators, and energy harvesters.

关键词： Skyrmions Spintronics Ferromagnets Micromagnetic modeling Thiele equation

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Multi-Variant eXecution: state-of-the-Art and Research Challenges

Multi-Variant eXecution: State-of-the-Art and Research Chall...

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International Conference on Communication Software and Networks, ICCSN

作者： Gaofei Zhang Zheng Zhang Bolin Ma Jiang Wang State key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China National Digital Switching System Engineering & Technological R&D Center Zhengzhou China

ISBN: (数字)9781728198156

ISBN: (纸本)9781728198163

As Internet security issues are becoming increasingly serious, many scholars and experts are exploring new defense strategies. The availability of multi-core computers and cloud computing resources has brought back the original costly defense methods to people's vision. Among them, the Multi-Variant eXecution (MVX) defense has received widespread attention and is considered a security technology that may change the rules of cyberspace games. In this paper, we analyze and summarize the current MVX defense technology, focusing on the evolution of the architecture and the key technologies. Finally, we point out the challenges to MVX and discuss future research, which is of great significance for the next work.

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Joint Partial Offloading and Resource Allocation for Distributed Multi-access Edge computing Enabled Vehicular Network

TechRxiv

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TechRxiv 2022年

作者： Ma, Guifu Hu, Manjiang Wang, Xiaowei Wu, Di Li, Haoran Bian, Yougang Zhu, Konglin The State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body The College of Mechanical and Vehicle Engineering Hunan University Changsha410082 China Hunan University Wuxi214072 China The College of Design Hunan University Changsha410082 China The Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Changsha410082 China The College of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China

In the foreseeable Intelligent Transportation System (ITS), Intelligent Connected Vehicles (ICVs) will play an important role in improving travel efficiency and safety. However, it is challenging for ICVs to support the resource-hungry autonomous driving applications due to the limitation of hardware computing power. Fortunately, the emergence of Multi-access Edge computing (MEC) helps overcome this limitation effectively. In this paper, we investigate the vehicle and edge server collaborative computation offloading problem by jointly optimizing the partial offloading ratio and resource allocation ratio. Different from existing two-level centralized solution methods, we give a new perspective to deal with multi-variable non-convex optimization problem in a distributed manner. That is, by analyzing the feasibility conditions of the problem, we separate the coupling between variables and derive the bounds of partial offloading ratio and resource allocation ratio based on the constraints. We further separate the coupling variables among ICVs and transform the original problem into an equivalent form and decompose it into a two-level convex problem, where each sub-problem satisfies the task offloading requirements. We then develop two low-complexity distributed algorithms to obtain the optimal solution. Finally, extensive simulations demonstrate that our proposed algorithms can converge faster and significantly outperform the baseline schemes in terms of system cost. © 2022, CC BY.

关键词： Resource allocation

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A Regional Network Topology Construction Algorithm Based On Sampling Measurement

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Journal of Physics: Conference Series 2021年第1期1861卷

作者： Zhiyuan Tao Yan Liu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan 450001 China

Network topology construction is one of the basic means to study the target network. Whether it is the discovery of vital nodes, IP location or network characteristics mining, a complete and accurate network topology is needed. In this paper, a regional network topology construction algorithm based on sampling measurement is proposed to solve the problem of high time cost and resource waste of existing algorithms. Firstly, multiple vantage points located inside and outside the target area are selected to form a probing set. Then the IPes of the target area is extracted based on sampling to form the target IP set. Finally, the probing set is used to probe the target IP set periodically. The network topology of the target region was constructed based on the results of a 40-day internet measurement and compared with the existing database. The experimental results show that the coverage rate of routing nodes in the target area is improved by more than 90% compared with the measured data provided by CAIDA (Center for Applied Internet Data Analysis) and by more than 10% compared with the measured data provided by IPIP.

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Identifying topologies and system parameters of uncertaintime-varying delayed complex networks

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Science China(Technological Sciences) 2019年第1期62卷 94-105页

作者： WANG Xiong GU HaiBo WANG QianYao Lü JinHu LSC Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

Node dynamics and network topologies play vital roles in determining the network features and network dynamical *** it is of great theoretical significance and practical value to recover the topology structures and system parameters of uncertain complex networks with available information. This paper presents an adaptive anticipatory synchronization-based approach to identify the unknown system parameters and network topological structures of uncertain time-varying delayed complex networks in the presence of noise. Moreover, during the identification process, our proposed scheme guarantees anticipatory synchronization between the uncertain drive and constructed auxiliary response network simultaneously. Particularly, our method can be extended to several special cases. Furthermore, numerical simulations are provided to verify the effectiveness and applicability of our method for reconstructing network topologies and node parameters. We hope our method can provide basic insight into future research on addressing reconstruction issues of uncertain realistic and large-scale complex networks.

关键词： system parameters and network topologies identification anticipatory synchronization uncertain time-varying delayed complex networks noise-perturbed complex networks

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DRTaint: A Dynamic Taint Analysis Framework Supporting Correlation Analysis Between Data Regions

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Journal of Physics: Conference Series 2021年第1期1856卷

作者： Pan Yang Fei Kang Yuntian Zhao Hui Shu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan 450001 China

Taint analysis is a common technology for software analysis, which is widely used in the region of information security. Aiming at the problem that the existing binary program dynamic taint analysis framework does not support 'replay' analysis and the analysis efficiency is low, a taint analysis framework called DRTaint is proposed. DRTaint is a universal taint analysis framework that supports correlation analysis between data regions. Experiments show that DRTaint shows good performance advantages when performing taint analysis many times on one program. On the basis of DRTaint, this paper studies the malicious code behavior extraction method based on taint analysis, and the research finds that DRTaint can provide better support for malicious code behavior extraction.

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Evolutionary dynamics in stochastic nonlinear public goods games

arXiv

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arXiv 2024年

作者： Zhu, Wenqiang Wang, Xin Wang, Chaoqian Liu, Longzhao Hu, Jiaxin Zheng, Zhiming Tang, Shaoting Zheng, Hongwei Dong, Jin School of Artificial Intelligence Beihang University Beijing100191 China Key laboratory of Mathematics Informatics and Behavioral Semantics Beihang University Beijing100191 China Zhongguancun Laboratory Beijing100094 China Beijing Academy of Blockchain and Edge Computing Beijing100085 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Beijing100191 China State Key Lab of Software Development Environment Beihang University Beijing100191 China Institute of Medical Artificial Intelligence Binzhou Medical University Yantai264003 China School of Mathematical Sciences Dalian University of Technology Dalian116024 China Department of Computational and Data Sciences George Mason University FairfaxVA22030 United States Faculty of Business The Hong Kong Polytechnic University Hung Hom Kowloon999077 Hong Kong

Understanding the evolution of cooperation in multiplayer games is of vital significance for natural and social systems. An important challenge is that group interactions often leads to nonlinear synergistic effects. However, previous models mainly focus on deterministic nonlinearity where the arise of synergy or discounting effect is determined by certain conditions, ignoring uncertainty and stochasticity in real-world systems. Here, we develop a probabilistic framework to study the cooperative behavior in stochastic nonlinear public goods games. Through both analytical treatment and Monte Carlo simulations, we provide comprehensive understanding of social dilemmas with stochastic nonlinearity in both well-mixed and structured populations. We find that increasing the degree of nonlinearity makes synergy more advantageous when competing with discounting, thereby promoting cooperation. Interestingly, we show that network reciprocity loses effectiveness when the probability of synergy is small. Moreover, group size exhibits nonlinear effects on group cooperation regardless of the underlying structure. Our findings thus provide novel insights into how stochastic nonlinearity influences the emergence of prosocial behavior. Copyright © 2024, The Authors. All rights reserved.

关键词： Nonlinear simulations

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