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Ubiquitous Communication (Ucom), International Conference on

作者： Weijie Xiong Yuhan Zhang Jingran Lin Kai Zhong Jinfeng Hu University of Electronic Science and Technology of China Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

ISBN: (数字)9798350374216

ISBN: (纸本)9798350374223

The analog beamforming design with antenna selection from a beampattern matching perspective is a key technology in large-scale antenna arrays (LSAAs) wireless communication systems. Currently, most existing methods use the scaled analog beamforming (SAB) architecture with phase shifters (PS) at the transmitter side, leading to constrained degrees of freedom. To enhance performance, we leverage the phase-corrected analog beamforming (PCAB) architecture with PS both at the transmitter side and the receiver side. We further formulate the problem as a mixed-integer least-squares problem with both constant modulus constraints (CMCs) and binary constraints (BCs). Due to the CMCs and BCs, the problem is non-convex. Additionally, the coupling effect between variables further aggravates the difficulty. To handle the problem, a decoupled online learning network is proposed. In the network, we address the BCs by transforming them into a continuously differentiable function with different biases. Simultaneously, we maintain parameters under CMCs by representing them in exponential form and leveraging their phases. By transforming the biases and the phases into learnable parameters, the loss function is minimized by the deep learning optimizer.

关键词： Wireless communication Deep learning Couplings Array signal processing Transmitters Phase shifters Receivers Antenna arrays

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Constant Modulus IRS-Assisted Secure Beamforming for Massive MIMO

Constant Modulus IRS-Assisted Secure Beamforming for Massive...

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IEEE International Conference on Communications Workshops, ICC

ISBN: (数字)9798350304053

ISBN: (纸本)9798350304060

The physical layer (PHY) security is a key technology for constant modulus (CM) massive MIMO systems. In this paper, we consider using an intelligent reflecting surface (IRS) to provide the system with additional degrees of freedom, thus enhancing its performance. We approach the problem from an optimization perspective, aiming to maximize the security rate. The optimization problem presents significant challenges due to highly coupled variables, non-convex constraints and the non-concave objective function. To tackle these challenges, we propose an efficient alternating optimization (AO) method. This method guarantees convergence to a Karush-Kuhn-Tucker (KKT) point and separately optimizes the CM beamforming and phase shift coefficients at the IRS as two sub-problems. Both sub-problems are solved using similar frameworks of the Dinkelbach method and the alternating direction method of multipliers (ADMM). Simulation results show that the proposed method outperforms many other related methods.

关键词： Array signal processing Simulation Conferences Massive MIMO Physical layer Linear programming Convex functions

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Phishing detection on Ethereum via transaction subgraphs embedding

IET Blockchain

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IET Blockchain 2023年第4期3卷 194-203页

作者： Lv, Haifeng Ding, Yong Guangxi Key Laboratory of Machine Vision and Intelligent Control WuZhou University Wuzhou China Guangxi Key Laboratory of Cryptography and Information Security School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China Guangxi Colleges and Universities Key Laboratory of Industry Software Technology WuZhou University Wuzhou China

With the rapid development of blockchain technology in the financial sector, the security of blockchain is being put to the test due to an increase in phishing fraud. Therefore, it is essential to study more effective measures and better solutions. Graph models have been proven to provide abundant information for downstream assignments. In this study, a graph-based embedding classification method is proposed for phishing detection on Ethereum by modeling its transaction records using subgraphs. Initially, the transaction data of normal addresses and an equal number of confirmed phishing addresses are collected through web crawling. Multiple subgraphs using the collected transaction records are constructed, with each subgraph containing a target address and its nearby transaction network. To extract features of the addresses, a modified Graph2Vec model called imgraph2vec is designed, which considers block height, timestamp, and amount of transactions. Finally, the Extreme Gradient Boosting (XGBoost) algorithm is employed to detect phishing and normal addresses. The experimental results show that the proposed method achieves good performance in phishing detection, indicating the effectiveness of imgraph2vec in feature acquisition of transaction networks compared to existing models. © 2023 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and technology.

关键词： Graphic methods

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Deep Learning-based Serialized Model and Feature Extraction Algorithm for Solid Oxide Fuel Cell State Prediction 43

Deep Learning-based Serialized Model and Feature Extraction ...

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43rd Chinese control Conference, CCC 2024

作者： Wu, Jiajian Zhu, Kanglin Wu, Han Xiang, Guohui Li, Xi Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Hubei Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Guangdong Shenzhen China

ISBN: (纸本)9789887581581

Deep learning-based methods have shown their wide application prospects in the field of solid oxide fuel cell(SOFC) prediction. However, the irrationality of the prediction object and the lack of prediction accuracy have hindered the progress of the prediction methods for SOFC systems. Therefore, two algorithms are proposed in this study, a feature selection algorithm based on maximum information coefficient and Bayesian information criterion for identifying key variables that are sensitive to changes in the SOFC system, and a prediction model based on a genetic algorithm optimized for sequence to sequence architecture. The M/BIC algorithm reduces the number of features by 62.5% (from 40 to 15), which contributes to the acceleration of the algorithm training and the subsequent sensor layout optimization. The prediction model incorporates a two-dimensional convolutional neural network and a multi-head attention mechanism to capture more information in the input sequence, an encoder-decoder architecture and a Gated recurrent unit to better predict performance trends. Tests with real experimental data show significant changes in feature dimensionality reduction and prediction accuracy. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Dimensionality reduction

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Community Search Based on Containment control of Multi-Agent System with Opinion Leaders 43

Community Search Based on Containment Control of Multi-Agent...

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43rd Chinese control Conference, CCC 2024

作者： Liu, Siyang Li, Tong Shao, Jinliang Zheng, Wei Xing University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100089 China Western Sydney University School of Computer Data and Mathematical Sciences SydneyNSW2751 Australia

ISBN: (纸本)9789887581581

Community search is the problem of identifying the community in which a given node resides. Different from traditional community search methods based on specific topological structures, this paper proposes a community search algorithm based on containment control of multi-agent system by studying the influence of opinion leaders with competitive relationships in community formation. Firstly, the Breadth-First Search method is used to locally sample the network. Secondly, containment control of multi-agent system is applied to obtain the final state of each node for local community partitioning. Finally, grounded in practical considerations, an effective leadership transfer mechanism is proposed to update the results and enhance search precision. Through experiments on real-world networks and synthetic networks in comparison with three local community detection algorithms, the effectiveness and rationality of our algorithm are demonstrated. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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Joint Admission control and Beamformer Design for Mobile Users: Stay Here or Move to a Better Position?

Joint Admission Control and Beamformer Design for Mobile Use...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jingran Lin Weijie Xiong Qiang Li Xiangze Kong Yuhan Zhang University of Electronic Science and Technology of China Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

In this paper, we study the joint admission control and beamforming problem within a network where one multi-antenna base station tries to serve multiple single-antenna users. Unlike most existing studies which merely identify the users that should be denied, our work further suggest better positions in the neighbouring area for them where the previously-rejected users are allowed to access the network. To address this, we assume the knowledge of channel vectors within the network coverage area, and then jointly optimize the transmit beamformer and the channel vector associated with each user to minimize the network power cost, with a penalty measuring the mismatch between the optimized channel and the reference channel with current user position. Specifically, a non-zero mismatch means that the corresponding user is inadmissible at present, but may access network if moving to the position with the channel closest to the optimized result. Basically, this is a challenging non-convex problem, and we design a penalty dual decomposition (PDD)-based algorithm to iteratively achieve a stationary solution. The algorithm is highly efficient since a simple analytical solution is derived in each step.

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An Improved Machine Learning Model for Pure Component Property Estimation

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Engineering 2024年第8期39卷 61-73页

作者： Xinyu Cao Ming Gong Anjan Tula Xi Chen Rafiqul Gani Venkat Venkatasubramanian State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Department of Physics Bard College at Simon’s RockGreat BarringtonMA 01230USA PSE for SPEED Company Charlottenlund DK-2920Denmark Sustainable Energy and Environment Thrust The Hong Kong University of Science and Technology(Guangzhou)Guangzhou 510000China Department of Applied Sustainability Széchenyi István UniversityGyör 9026Hungary Complex Resilient Intelligent Systems Laboratory Department of Chemical EngineeringColumbia UniversityNew YorkNJ 10027USA

Information on the physicochemical properties of chemical species is an important prerequisite when performing tasks such as process design and product ***,the lack of extensive data and high experimental costs hinder the development of prediction techniques for these ***,accuracy and predictive capabilities still limit the scope and applicability of most property estimation *** paper proposes a new Gaussian process-based modeling framework that aims to manage a discrete and high-dimensional input space related to molecular structure representation with the group-contribution approach.A warping function is used to map discrete input into a continuous domain in order to adjust the correlation between different *** selection techniques,including prior elicitation and prior predictive checking,are also applied during the building procedure to provide the model with more information from previous research *** framework is assessed using datasets of varying sizes for 20 pure component *** 18 out of the 20 pure component properties,the new models are found to give improved accuracy and predictive power in comparison with other published models,with and without machine learning.

关键词： Group contribution Gaussian process Warping function Prior predictive checking

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A Hybrid SVM Based Real-Time Attack Classification Method for Cyber Network 42

A Hybrid SVM Based Real-Time Attack Classification Method fo...

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42nd Chinese control Conference, CCC 2023

作者： Qin, Xin Jin, Feng Han, Zhongyang Zhao, Jun Wang, Wei Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian116024 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9789887581543

The cyber network attacks on the Internet have the characteristics of diversity, uncertainty and real-time. This paper proposes a hybrid support vector machine (HSVM)-based classification method for real-time cyber network attack detection. In the supervised environment, a one-class classifier is built to divide the unknown attack traffic into 'other classes', and a new extension module is established for the identified unknown attacks, so as to improve the classification accuracy of unknown attacks. Then, an online training algorithm is used to enable the classifier to quickly distinguish cyber network attacks and improve the timeliness of the intrusion detection process. To verify the effectiveness of the proposed method is employed, three classifiers, i.e., the random forest, the support vector machine and the multi-layer perceptron are employed for comparative experiments based on the public data set KDDCup99. Results show that the proposed method has the advantages of higher classification accuracy and less time consumption. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Intrusion detection

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Microgrid energy management strategy considering microgrid economy and rSOC stability: A model-based study 43

Microgrid energy management strategy considering microgrid e...

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43rd Chinese control Conference, CCC 2024

作者： Huang, Haizhou Xia, Zhiping Shan, Xinkai Wang, Jie Li, Xi Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518055 China

ISBN: (纸本)9789887581581

Microgrids possess the ability to use renewable energy efficiently and play an increasingly significant role in environmental protection and sustainable development. Meanwhile, reversible solid oxide fuel cell (rSOC) is currently a new type of energy conversion and storage. Combining with microgrid systems is a great way to benefit from its high capacity, high efficiency, and cleanliness. However, rSOC's complex system of coupled heat, electricity, and gas presents a significant challenge in finding energy management strategies for microgrid applications containing rSOC. In this study, for a microgrid system combining rSOC, battery energy storage system (BESS), solar photovoltaic (PV), and wind turbine generator (WTG), we propose a model-based energy management strategy that simultaneously takes into account the economy of the microgrid system and the stability of the rSOC system. First of all, the microgrid is modeled with great detail, including the wind turbine, solar panels, battery storage system, and rSOC. In addition, the microgrid energy management problem is framed as a mathematical programming problem, with the attention focusing on the costs of BESS aging and operational energy loss of rSOC. In particular, this study also proposes a penalty strategy to reduce the power fluctuation amplitude of the rSOC system and reduce the mode switching frequency of the rSOC system. Using the solver, solving for each device's target power in a microgrid. The actual power operating curve is output by tracking the target power under slope constraints using the Simulink model. We then conduct a case study using data from Wuhan, China. Our research shows that compared with the control strategy based on rule control, the control strategy proposed in this study can reduce the power variation amplitude of the rSOC system by 79%, reduce the mode switching frequency by 85%, reduce the system operating cost by 4.5% and increase the energy self-sufficiency rate by 9%. © 2024 Techn

关键词： Wind turbines

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ESNet: Evolution and Succession Network for High-Resolution Salient Object Detection 41

ESNet: Evolution and Succession Network for High-Resolution ...

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41st International Conference on Machine Learning, ICML 2024

作者： Liu, Hongyu Cong, Runmin Li, Hua Xu, Qianqian Huang, Qingming Zhang, Wei 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. Copyright 2024 by the author(s)

关键词： Miocene

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