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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： Wu, Wen-Qiang Li, Ji-Gong Yang, Jing School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350356618

Concerning the problem of odor source search with robots in a large outdoor environment, an odor source search method based on the improved wolf pack algorithm (IWPA) is proposed, in which each wolf corresponds to an unmanned aerial vehicle (UAV). The environment is firstly traversed by the UAVs in partitions by using rectangular wave- shaped paths. Once odor plume is detected by any UAV, the WPA is applied to guide the UAVs towards the odor source. Considering the limited number of UAVs, in order to improve the utilization rate of UAVs, the wolf pack is simplified into two roles: the alpha wolf and other wolves. Meanwhile, to avoid collisions between UAVs and enable UAVs to fully sample around the suspected target position, a besieging algorithm based on a virtual force field is designed to calculate next flight direction for the UAVs. During this period, the odor source position is determined by the alpha wolf which is constantly elected by comparing the fitness values of all wolves. Simulation results show that the IWPA method can find the odor source in short time without falling into local extremum, demonstrating good convergence and being suitable for odor source search tasks in outdoor environments. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Microservice Deployment for Satellite Edge AI Inference via Deep Reinforcement Learning 35

Microservice Deployment for Satellite Edge AI Inference via ...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Yu, Zhiyong Cheng, Hei Victor Yang, Zhanpeng Liu, Xin Jiang, Yuning Zhou, Yong Shi, Yuanming ShanghaiTech University School of Information Science and Technology Shanghai201210 China Aarhus University Department of Electrical and Computer Engineering Denmark Automatic Control Laboratory Switzerland

ISBN: (纸本)9798350362244

Artificial intelligence (AI) is critical in evolving 5G and developing 6G networks, running on edge devices, and solving resource management challenges. The burgeoning number of edge devices draws attention to the potential of low-earth orbit (LEO) satellite networks with their onboard computing capabilities for edge inference. This paper explores LEO scenarios where multiple remote sensing edge AI inference tasks concurrently process data from a single source. However, due to there being parts with the same functions between different AI applications, traditional monolithic edge AI architecture must be deployed repeatedly and falls short in efficiently harnessing the heterogeneous resources of LEO satellite networks. To solve this problem, we utilize the microservice architecture to decouple a single AI application into several independent microservices to reuse these same functions. However, due to the high latency caused by multiple microservices' communication, we need to design a deployment strategy to fully utilize resources to reduce the service latency. We present a microservice deployment model to minimize the total service latency across all AI applications and meet resource constraints with the constraints of hardware, energy, and memory limitations. This latency optimization problem is rewritten as a Markov decision process (MDP) to effectively deal with the challenge posed by the time-varying transmission rate caused by satellite mobility. To increase the training data utilization, we employ a Proximal Policy Optimization (PPO) based reinforcement learning algorithm to meet the dynamic environment challenge. Finally, we obtain a sub-optimal solution with minimal accuracy loss and an acceptable solution time. © 2024 IEEE.

关键词： Markov processes

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Lag Synchronization and Lag H∞ Synchronization for Multiweighted Coupled Reaction-Diffusion Neural Networks Suffering Topology Attacks

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IEEE Transactions on control of Network Systems 2025年第2期12卷 1488-1499页

作者： Wang, Jin-Liang Zhao, Xin-Yu Ren, Shun-Yan Huang, Tingwen Tiangong University Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems School of Computer Science and Technology Tianjin300387 China Tiangong University School of Electronics & Information Engineering Tianjin300387 China University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu611731 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

This paper mainly discusses two kinds of coupled reaction-diffusion neural networks (CRNN) under topology attacks, that is, the cases with multistate couplings and with multiple spatial-diffusion couplings. On one hand, by adopting state feedback control scheme, the problem of the lag synchronization for the multistate coupled CRNN is addressed. Moreover, the influences of external disturbances for the lag synchronization of the CRNN with multistate couplings are also taken into consideration. On the other hand, several lag and lag H∞ synchronization conditions for CRNN with multiple spatial-diffusion couplings are derived under the help of the Kronecker product and the state feedback control method. Finally, two numerical examples are provided to verify the correctness of the derived criteria. © 2014 IEEE.

关键词： State feedback

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Diversified and compatible web APIs recommendation based on game theory in IoT

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Digital Communications and Networks 2024年第4期10卷 1198-1209页

作者： Wenwen Gong Huiping Wu Xiaokang Wang Xuyun Zhang Yawei Wang Yifei Chen Mohammad R.Khosravi College of Information and Electrical Engineering China Agricultural UniversityBeijing100000China Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyShouguang262700China Department of Computer Science St.Francis Xavier UniversityAntigonishNSCanada Department of Computing Macquarie UniversitySydneyNSW2122Australia Department of Computer Engineering Persian Gulf UniversityBushehr***Iran Department of Electrical and Electronic Engineering Shiraz University of TechnologyShiraz71557-13876Iran

With the ever-increasing popularity of Internet of Things(IoT),massive enterprises are attempting to encapsulate their developed outcomes into various lightweight Web Application Programming Interfaces(APIs)that can be accessible *** this context,finding and writing a list of existing Web APIs that can collectively meet the functional needs of software developers has become a promising approach to economically and easily develop successful mobile ***,the number and diversity of candidate IoT Web APIs places an additional burden on application developers’Web API selection decisions,as it is often a challenging task to simultaneously ensure the diversity and compatibility of the final set of Web APIs *** this challenge and latest successful applications of game theory in IoT,a Diversified and Compatible Web APIs Recommendation approach,namely DivCAR,is put forward in this *** of all,to achieve API diversity,DivCAR employs random walk sampling technique on a pre-built“API-API”correlation graph to generate diverse“API-API”correlation ***,with the diverse“API-API”correlation subgraphs,the compatible Web APIs recommendation problem is modeled as a minimum group Steiner tree search problem.A sorted set of multiple compatible and diverse Web APIs are returned to the application developer by solving the minimum group Steiner tree search *** last,a set of experiments are designed and implemented on a real dataset crawled from *** results validate the effectiveness and efficiency of our proposed DivCAR approach in balancing the Web APIs recommendation diversity and compatibility.

关键词： Internet of things Web APIs recommendation Game theory Diversity and compatibility

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Parameter Identification and control of Two-Wheel Balance Vehicle Model Based on Subspace Algorithm 2

Parameter Identification and Control of Two-Wheel Balance Ve...

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2nd Asia Conference on Electronics engineering, ACEE 2024

作者： Li, Xuehui Zhang, Yongli Geng, Lihui Yuan, Ruijian Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control School of Automation and Electrical Engineering Tianjin China

ISBN: (纸本)9798350375251

To address parameter uncertainty in the two-wheel balance vehicle (TWBV) system, a closed-loop subspace algorithm (CLSA) was employed to identify and correct uncertain structural parameters. This got in a more accurate system model. Based on the dynamics mechanism model of the TWBV, we designed a simple controller to achieve self-balancing control. We harvested the input and output sample data required for identification. The method used to filter out noise from the original signal and extract essential dynamic characteristics of the system is the input-output bias voltage function. The parameters of the dynamics model for the TWBV were subsequently identified and corrected using the CLSA. Finally, the linear quadratic regulator (LQR) controller is designed based on the model obtained from identification and compared with the original unidentified model. The results of the simulation and physical experiment show that the control system with the modified system after identification has better performance. This paper verifies the effectiveness of the proposed control strategy, which provides a reference scheme for solving model uncertainty in similar systems and improving control accuracy. © 2024 IEEE.

关键词： Vehicle wheels

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Robust control of two-wheeled bicycle robot under wind disturbance 2

Robust control of two-wheeled bicycle robot under wind distu...

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2nd Asia Conference on Electronics engineering, ACEE 2024

作者： Yuan, Ruijian Zhang, Yongli Geng, Lihui Li, Xuehui Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control School of Automation and Electrical Engineering Tianjin China

ISBN: (纸本)9798350375251

The two-wheeled bicycle robot (TWBR) is a new intelligent transportation, which can be used for special tasks such as forest operation and disaster relief. Although the TWBR is not structurally complex, the dynamics are very complex to model. It is extremely difficult to build an accurate mathematical model. Wind disturbance is, in principle, always present on open roads and influence on the driving stability increases. Aiming at mathematical modeling error caused by mass center of the TWBR frame and external disturbance caused by wind force, this paper introduces a suitable control method. Firstly, the Kane method is adopted for modeling. Secondly, robust control can provide stability and performance guarantee for both uncertainty and disturbance. Finally, the results of simulation and physical experiment show the effectiveness of the robust H∞ control for TWBR. In this paper, MATLAB/Simulink is used to establish a combined mathematical model of wind force as an experimental external disturbance. The robust H∞ controller based on linear matrix inequality (LMI) and Linear quadratic regulator(LQR) are realized. It is verified that the robust H∞ controller has better effectiveness than the LQR controller when facing the uncertainty and external disturbance. © 2024 IEEE.

关键词： Bicycles

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Optimized Complex Convolutional Neural Network for Steady-State Visual Evoked Potentials Signal classification 25

Optimized Complex Convolutional Neural Network for Steady-St...

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25th IEEE China Conference on System Simulation technology and its Application, CCSSTA 2024

作者： Li, Qingbin Han, Chunxiao Liu, Yanli Liu, Junxiu Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing & Intelligent Control School of Automation and Electrical Engineering Tianjin China

ISBN: (纸本)9798350366600

The steady-state visual evoked potential (SSVEP) is one of the most commonly used paradigms in the BCI system, which produces a significant response to visual stimuli of a specific frequency. How to better improve the classification performance of SSVEP signals is currently the main task. In this paper, a modified C-CNN-SVM model of EEG signal is proposed, aiming to enhance the precision of SSVEP signal classification. Firstly, spectral features are obtained from the SSVEP signal using fast fourier transform (FFT) as input to the model. FFT obtains 128 data lengths of the SSVEP signal, including 64 real part data and 64 complex part data. Then, CNN is used to further extract features, and finally, support vector machine (SVM) is used for classification. The experimental results show that the modified C-CNN-SVM model achieves an average accuracy of 93.86%, which is better than the traditional CCA, FBCCA and TRCA algorithms. © 2024 IEEE.

关键词： Convolutional neural networks

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A Reflectarray With Low Profile Based on the Method of Choosing the Certain Phase Constant

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IEEE Antennas and Wireless Propagation Letters 2025年第6期24卷 1397-1401页

作者： Li, Wenting Lin, Wenting Li, Ruiyang He, Yejun Gao, Yao Zhang, Chong Gao, Steven School of Electronic and Information Engineering Shenzhen University State Key Laboratory of Radio Frequency Heterogeneous Integration Shenzhen518000 China Zhengzhou University School of Electrical and Information Engineering Zhengzhou450000 China Chang'an University School of Information Engineering Xi'an710000 China Shenyang University of Technology School of Information Science and Engineering Shenyang710000 China Chinese University of Hong Kong Department of Electronic Engineering Hong Kong

In this letter, a reflectarray antenna with a small focal diameter ratio (F/D) is presented. It is found that when the F/D is extremely small, the phase constant used in calculating the required reflection phase on the reflecting surface significantly affects the radiation pattern. In certain cases, an unsuitable phase constant can even cause the main beam to split. The unit cell is implemented as a stacked patch, and the reflecting surface comprises 14 × 14 elements. The effect of the phase constant on the radiation pattern is analyzed, and two reflectarrays with phase constants of 90° and 180°, both operating at 10 GHz with an F/D of 0.05, are compared. These two reflectarrays are simulated, fabricated, and measured. The measured results show good agreement with the simulations. Within the operating band, the reflectarray with a phase constant of 90° achieves a maximum measured gain of 20.42 dBi, with the first sidelobe level (SLL1) below −10 dB. The radiation pattern of the reflectarray with a phase constant of 180° is totally distorted, resulting in a measured gain of 6.56 dBi at 10 GHz and an SLL1 of −5.8 dB. © 2002-2011 IEEE.

关键词： Reflection

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Detection of Perfect Stealthy Attacks on Cyber-Physical Systems Subject to Measurement Quantizations: A Watermark-Based Strategy

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 114-125页

作者： Yu-Ang Wang Zidong Wang Lei Zou Bo Shen Hongli Dong the College of Information Science and Technology Donghua University the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of Education IEEE the College of Electrical Engineering and Automation Shandong University of Science and Technology the Department of Computer Science Brunel University London Uxbridge the Sanya Offshore Oil and Gas Research Institute Northeast Petroleum University the Artificial Intelligence Energy Research Institute Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University

In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are quantized before transmission.A specific type of perfect stealthy attack, which meets certain rather stringent conditions, is taken into account. Such attacks could be injected by adversaries into both the sensor-toestimator and controller-to-actuator channels, with the aim of disrupting the normal data flow. For the purpose of defending against these perfect stealthy attacks, a novel scheme based on watermarks is developed. This scheme includes the injection of watermarks(applied to data prior to quantization) and the recovery of data(implemented before the data reaches the estimator).The watermark-based scheme is designed to be both timevarying and hidden from adversaries through incorporating a time-varying and bounded watermark signal. Subsequently, a watermark-based attack detection strategy is proposed which thoroughly considers the characteristics of perfect stealthy attacks,thereby ensuring that an alarm is activated upon the occurrence of such attacks. An example is provided to demonstrate the efficacy of the proposed mechanism for detecting attacks.

关键词： Attack detection cyber-physical systems (CPSs) perfect stealthy attacks watermark-based strategy

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Infrared Hot Spot Detection of Photovoltaic Arrays Based on Optimization and Improvement Using YOLOv8 1st

Infrared Hot Spot Detection of Photovoltaic Arrays Based on ...

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1st electrical Artificial Intelligence Conference, EAIC 2024

作者： Peng, ZiRan Wang, SiYua Xiao, Shenping Department of Electrical and Information Engineering Hunan University of Technology Zhuzhou412007 China Hunan Key Laboratory of Electric Drive Control and Intelligent Equipment Hunan University of Technology Zhuzhou412007 China

ISBN: (纸本)9789819640621

Detecting hot spots on solar cells in mountainous photovoltaic power plants is challenging due to high false and missed detection rates. This paper proposes S-YOLO, a lightweight model based on YOLOv8, for efficient hot spot detection. The model introduces a Spatial Confusion Backbone to reduce parameters and computational complexity while enhancing feature extraction with attention mechanisms. A Multi-scale Feature Pyramid Network (MSBFPN) improves small-target detection, and the SIoU loss function replaces CIoU for faster convergence and precise regression. Compared to YOLOv8, S-YOLO reduces weights by 41.3%, parameters by 21.2%, and increases accuracy by 2.3%. Its lightweight design and high accuracy make it ideal for drone-based inspections in complex environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Infrared detection Loss function SIoU Network model Solar cells YOLOv8

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