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7th IEEE International Conference on Electronic information and communication technology, ICEICT 2024

作者： Su, Hang Ye, Fang Su, Chunxia Sun, Xue Harbin Engineering University Key Laboratory of Advanced Marine Communication and Information Technology College of Information and Communication Engineering Harbin China Harbin Engineering University National Key Laboratory of Underwater Acoustic Technology College of Information and Communication Engineering Harbin China Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou China

ISBN: (纸本)9798350384437

With the popularity of emerging applications and the diversification of IoT device needs, wireless mesh networks (WMN) have been recognized as an effective way to solve "last mile"coverage. In the scenario where the network environment status is unknown, an adaptive channel allocation algorithm based on multi-agent reinforcement learning is proposed to solve the problem that static channel allocation in wireless mesh network cannot adapt well to traffic changes in the network environment, resulting in the degradation of link communication quality. Map the channel allocation problem as a multi-agent reinforcement learning process. The state space based on multiple factors such as interference and load is established, and the relationship between exploration and utilization in the algorithm is balanced by using the improved greedy action selection mechanism, and the return function based on link satisfaction is designed to guide the channel selection to improve the quality of link communication. The simulation results show that the proposed algorithm can effectively adapt to the dynamic changes of traffic and source nodes in the network to ensure the quality of user service. © 2024 IEEE.

关键词： MESH networking

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Determination of Geometry Parameters to Geostationary communication Satellite, Its Comparative Analysis for Mongolia

Determination of Geometry Parameters to Geostationary Commun...

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2023 International Conference on Electrical, Computer, communications and Mechatronics engineering, ICECCME 2023

作者： Yura, Otgonbaatar Shin, Kwangcheol Zundui, Buyankhishig Huree University of Information and Communication Technology Department of Information and Communication Ulaanbaatar Mongolia Huree University of Information and Communication Technology Department of Computer Science Engineering Ulaanbaatar Mongolia The School of Information and Communication Technology Must Department of Communication Engineering Technology Ulaanbaatar Mongolia

ISBN: (纸本)9798350322972

the countries of the world are using various communication services in all areas of society on based satellite networks. The International Telecommunication Union has allocated two kind of satellite position in space segment to Mongolia that are 113.6E longitude for Fixed Satellite Service-(FSS) and 74E longitude for Broadband Satellite Service-(BSS).Mongolia is planning to launch its national satellite in 2030. Therefore, there are studying many kind of science research including estimate satellite geometry parameters, rain attenuation, cloud attenuation and satellite network architecture based on national satellite that will be launched to space *** paper is described by detail that is the mathematical modelling of satellite geometry parameters particularly antenna look angles of the ground control *** this paper, aim of research work is determined the geometrical parameters of the national satellite 113.E and 74E to be launched in Mongolia by using a mathematical model to make a comparative analysis and to show some result. © 2023 IEEE.

关键词： Network architecture

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Focal Transfer Graph Network and Its Application in Cross-Scene Hyperspectral Image Classification

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4013-4025页

作者： Wang, Haoyu Liu, Xiaomin the Engineering Research Center of Intelligent Control for Underground Space Ministry of Education China University of Mining and Technology Xuzhou 221116 China and also with the School of Information and Control Engineering China University of Mining and Technology Xuzhou 221116 China

Affected by the sensor, shooting environment, and other aspects, hyperspectral images (HSIs) in the source and target domains exhibit phenomenon of difficult feature extraction and domain shift. The above phenomena pose challenges to the cross-scene HSI classification task. Therefore, a focal transfer graph network (FTGN) for cross-scene HSI classification is proposed. First, FTGN leverages graph sample and aggregate (GraphSAGE) to capture spatial-spectral features by aggregating partial adjacency nodes, ensuring the acquisition of contextual information. The neighbor weighting strategy based on spatial-spectral information is proposed to solve the information interference caused by excessive node aggregation. Second, a pseudolabel trimming strategy based on class metrics is proposed to reduce the adverse effects of pseudolabel noise in the transfer process. Then, a specification subdomain adaptation (SSA) module is proposed, which helps to achieve effective distribution alignment by reducing the feature distance of intraclass samples and widening the feature distance of interclass samples during the subdomain adaptation process. Finally, the focal loss is utilized to help FTGN focus on hard-to-classify samples. The experimental results on eight data pairs show that the proposed method outperforms several state-of-the-art methods. © 2020 IEEE.

关键词： Data mining

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Power equipment target detection algorithm based on improved YOLOV7 4

Power equipment target detection algorithm based on improved...

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4th International Conference on Machine Learning and Computer Application, ICMLCA 2023

作者： Yang, Jinglong Ji, Xiu Wu, Peng Li, Mingge School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin China School of Electrical and Information Engineering Changchun Institute of Technology Changchun China

ISBN: (数字)9781510680265

ISBN: (纸本)9781510680258

Aiming at some practical problems such as low inspection efficiency and high false detection rate of traditional manual transmission lines, we introduce an enhanced YOLOV7-based algorithm for infrared insulator target detection. The algorithm uses K-Means ++ clustering algorithm to regenerate the anchor frame on the self-made infrared insulator data set, which makes the algorithm converge faster. The algorithm substitutes the original YOLOV7 backbone with Efficientformerv2 to simplify the backbone network. Additionally, it eliminates redundant information from the feature map by incorporating the GhostConv module in the feature fusion network, and introducing the attention mechanism called SimAM. WIoU is used as the loss function of the improved model. Experiments on self-made infrared insulator data set show that when compared to the initial YOLOV7 algorithm, the refined algorithm demonstrates notable enhancements across multiple performance indicators. Particularly, the mAP@0.5 metric has seen a substantial improvement of 5.2%, elevating it to an impressive 98.3%. Concurrently, the number of parameters has experienced a significant reduction of 43.5%, dwindling to 20.5 million, and the computational workload has been markedly lowered by 66.2% to 35.0 GFPLOS. © 2024 SPIE.

关键词： Signal detection

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controlling a peristaltic robot inspired by inchworms

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Biomimetic Intelligence & Robotics 2024年第1期4卷 88-96页

作者： Yanhong Peng Hiroyuki Nabae Yuki Funabora Koichi Suzumori Department of Information and Communication Engineering Graduate School of EngineeringNagoya UniversityNagoya 464-8601Japan Department of Mechanical Engineering Tokyo Institute of TechnologyTokyo 152-8550Japan

This study presents an innovative approach in soft robotics,focusing on an inchworm-inspired robot designed for enhanced transport *** explore the impact of various parameters on the robot’s performance,including the number of activated sections,object size and material,supplied air pressure,and command execution *** a series of controlled experiments,we demonstrate that the robot can achieve a maximum transportation speed of 8.54 mm/s and handle loads exceeding 100 g,significantly outperforming existing models in both speed and load *** findings provide valuable insights into the optimization of soft robotic design for improved efficiency and adaptability in transport *** research not only contributes to the advancement of soft robotics but also opens new avenues for practical applications in areas requiring precise and efficient object *** study underscores the potential of biomimetic designs in robotics and sets a new benchmark for future developments in the field.

关键词： McKibben artificial muscles Bionics Soft robotics Soft actuator Bio-inspired robotics

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Intelligent proportioning model of converter scrap based on optimization algorithm

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Progress in Natural Science:Materials International 2024年第1期34卷 37-44页

作者： Chaojie Zhang Jinjun Cheng Liqiang Zhang Yingxue Wang Wei Zhang Jianwei Yuan Haichuan Wang School of Metallurgical Engineering Anhui University of Technology National Engineering Research Center for Public Safety Risk Perception and Control by Big Data(RPP) China Academic of Electronics and Information Technology Wuhu Xinxing Pipes Co. Ltd.

Scrap is one of the main raw materials in converter steelmaking. Due to the wide variety of scrap and the significant differences in its prices, the proportioning of scrap presents a challenge in converter steelmaking. This paper explores the optimal proportioning method of scrap for converters using an optimization mathematical model. Initially, the melting characteristics of scrap after being added to the converter's molten iron were investigated using finite element numerical simulations. The study found that when the weight of the scrap is fixed, both the shape and type of the scrap significantly influence the melting time. Subsequently, employing mathematical optimization methods and considering comprehensive process parameters of the 210t converter smelting, including the composition and unit price of the scrap, as well as the requirements of the converter steelmaking process for scrap, an optimization model for the proportioning of scrap in converters was *** model was solved using computer programming languages. Through this optimization model, it is possible to obtain the lowest cost per ton of molten steel in the converter smelting process by determining the optimal proportions of various types of scrap.

关键词： scrap proportioning Optimization model Converter steelmaking mathematical model numerical simulation

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Fault Prediction Method of Stage Lifts Based on Digital Twin

Fault Prediction Method of Stage Lifts Based on Digital Twin

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2024 International Conference on Culture-Oriented Science and technology, CoST 2024

作者： Wang, Huiqin Zhang, Chunxi Li, Zhen Xiao, Mengjiao Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China Communication University of China School of Information and Communication Engineering Beijing China

ISBN: (纸本)9798350380347

To improve the safety of stage lifts' operation and reduce the failure rate, a digital-twin assisted fault prediction method is proposed here. Signals such as vibration and temperature are collected from the virtual and physical models. A fault prediction model based on Graph Convolutional Networks (GCN) is constructed to identify the potential faults of stage lift. The experiment results illustrate the effectiveness of the proposed model. It would enhance the safety and stability of stage equipment, and provide reliable support for stage performances. © 2024 IEEE.

关键词： Prediction models

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controllability of heterogeneous networked sampled-data systems

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Science China(information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Convolutional Neural Networks based Defect Detection Method for Smart Meter LCD Screen 7

Convolutional Neural Networks based Defect Detection Method ...

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7th International Conference on Data Science and information technology, DSIT 2024

作者： Zhang, Dengke Wei, Pu Li, Xiaolong Yang, Jie Liu, Chuanqing Nanjing Institute of Technology School of Power Engineering Nanjing China Nanjing Institute of Technology School of Communications and Information Engineering Nanjing China Nanjing Institute of Technology School of Information and Communication Engineering Nanjing China

ISBN: (纸本)9798350384093

In this paper, we introduce and experimentally demonstrate a novel defect detection method for the LCD screen of the smart meter. The images from the camera firstly undergo a series of image processing, such as rotate, grayscale, binarization, denoise and region of interest (ROI) positioning. Thus, the information of the images, which are unrelated to defect detection, is effectively removed. And then, the Convolutional Neural Network (CNN), which includes four convolution layers, four pooling layers and two fully connected layers, is designed and trained to recognize the defects in the processed images. A testbench is made, in which four LCD screens can be tested simultaneously. The experimental results show that the Accuracy, Precision, Recall and F1-score of our method are 97.25%, 97.49%, 97% and 97.24%, respectively, which is better than support vector machine (SVM) model. The method can be widely applied in the defect detection of the LCD screen. © 2024 IEEE.

关键词： Convolutional neural networks

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AI Driven Transformation: Updated Technologies in 6G communication System 1

AI Driven Transformation: Updated Technologies in 6G Communi...

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1st International Conference on Advances in Computer Science, Electrical, Electronics, and communication Technologies, CE2CT 2025

作者： Mp, Sunil Das, Neeraj Department of Electronics and Communication Engineering Karnataka India School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331518578

The rollout of 5G systems has prompted standards bodies to begin the 6G system design process. The increased complexity of 6G networks will increase the time, money, and effort needed for implementation and administration. Conversely, in order to lower operating expenditures (OPEX), mobile network providers want these networks to be smart, self-organizing, and economical. A subfield of AI known as artificial intelligence (AI) offers practical answers to these problems and has the potential to radically alter the trajectory of wireless network technology in the future. Also rapidly reviewing the most important issues, with a focus on cellular networks' physical layer of operation and link layer where ML may provide substantial benefits by using a few case study examples. By analyzing the standardization efforts around ML in wireless networks and what the future holds for the preparedness of standards organizations to deal with these developments. Finally, by outlining some of the most pressing problems with ML in wireless tech and suggesting ways forward that wireless networks using 6G may address these concerns. © 2025 IEEE.

关键词： 5G mobile communication systems

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