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Design of 5G Multi-Frequency Antenna Based on Multi-Objective Sequential Domain Patching

Progress In Electromagnetics Research C 2024年 145卷 53-61页

作者： Zhu, Wenjian Chen, Jiayi Hu, Panshi Song, Zhi Xue, Yanbing School of Automation and Electrical Engineering Dalian Jiaotong University China School of Computer and Communication Engineering Dalian Jiaotong University Applied Basic Research Project of Liaoning Science and Technology Department Dalian116028 China

This paper introduces a 5G multi-frequency antenna design method based on multi-objective sequential domain patching. By etching helical metamaterials on radiation patches and loading asymmetric electric-inductive-capacitive metamaterials on the transmission line side, the antenna structure is designed and optimized using electromagnetic simulation software, HFSS, and MATLAB. The resulting multi-frequency antenna operates across multiple frequency bands: n1, n41, 3.5G, and 4.9G. To ensure antenna performance and radiation efficiency, the antenna multi-frequency bands are precisely controlled. The experimental results show that the error between each operating frequency band and target frequency bands of the antenna is within 7.2%. Compared with conventional antenna design methods, the use of metamaterials and intelligent algorithms to optimize the structural parameters and loading positions of metamaterials can improve antenna performance while shortening the design cycle. Overall, this research offers novel insights into the design of 5G high-performance antennas. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Metamaterials

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Skeleton-Based Action Recognition Using Graph Convolutional Network with Pose Correction and Channel Topology Refinement

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computers, Materials & Continua 2025年第4期83卷 701-718页

作者： Yuxin Gao Xiaodong Duan Qiguo Dai School of Engineering Guangzhou College of Technology and BusinessFoshan528138China School of Computer Science and Engineering Dalian Minzu UniversityDalian116000China SEAC key Laboratory of Big Data Applied Technology Dalian Minzu UniversityDalian116000China

Graph convolutional network(GCN)as an essential tool in human action recognition tasks have achieved excellent performance in previous ***,most current skeleton-based action recognition using GCN methods use a shared topology,which cannot flexibly adapt to the diverse correlations between joints under different motion *** video-shooting angle or the occlusion of the body parts may bring about errors when extracting the human pose coordinates with estimation *** this work,we propose a novel graph convolutional learning framework,called PCCTR-GCN,which integrates pose correction and channel topology refinement for skeleton-based human action ***,a pose correction module(PCM)is introduced,which corrects the pose coordinates of the input network to reduce the error in pose feature ***,channel topology refinement graph convolution(CTR-GC)is employed,which can dynamically learn the topology features and aggregate joint features in different channel dimensions so as to enhance the performance of graph convolution networks in feature ***,considering that the joint stream and bone stream of skeleton data and their dynamic information are also important for distinguishing different actions,we employ a multi-stream data fusion approach to improve the network’s recognition *** evaluate the model using top-1 and top-5 classification *** the benchmark datasets iMiGUE and Kinetics,the top-1 classification accuracy reaches 55.08%and 36.5%,respectively,while the top-5 classification accuracy reaches 89.98%and 59.2%,*** the NTU dataset,for the two benchmark RGB+Dsettings(X-Sub and X-View),the classification accuracy achieves 89.7%and 95.4%,respectively.

关键词： Pose correction multi-stream fusion GCN action recognition

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Resilient Distributed Optimization for Multi-Agent Cyberphysical Systems

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IEEE Transactions on Automatic Control 2025年第6期70卷 3952-3967页

作者： Yemini, Michal Nedic, Angelia Goldsmith, Andrea J. Gil, Stephanie Bar-Ilan University Faculty of Engineering Israel Arizona State University School of Electrical Computer and Energy Engineering TempeAZ85281 United States Princeton University Department of Electrical and Computer Engineering PrincetonNJ08544 United States Harvard University Computer Science Department School of Engineering and Applied Sciences CambridgeMA02139 United States

This work focuses on the problem of distributed optimization in multi-agent cyberphysical systems, where a legitimate agent's iterates are influenced both by the values it receives from potentially malicious neighboring agents, and by its own self-serving target function. We develop a new algorithmic and analytical framework to achieve resilience for the class of problems where stochastic values of trust between agents exist and can be exploited. In this case, we show that convergence to the true global optimal point can be recovered, both in mean and almost surely, even in the presence of malicious agents. Furthermore, we provide expected convergence rate guarantees in the form of upper bounds on the expected squared distance to the optimal value. Finally, numerical results are presented that validate our analytical convergence guarantees even when the malicious agents compose the majority of agents in the network and where existing methods fail to converge to the optimal nominal points. © 1963-2012 IEEE.

关键词： Multi agent systems

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Heterologous Image Matching Based on Salience Region

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2025年第4期52卷 894-900页

作者： Zhai, Jinlong Xu, Yang Yan, Xiaohu Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China Institute of Applied Artificial Intelligence of the Guangdong-Hong Kong-Macao Greater Bay Area Shenzhen Polytechnic University Shenzhen518055 China

To address the matching problem caused by the significant differences in spatial features, spectrum and contrast between heterologous images, a heterologous image matching method based on salience region is proposed in this paper. Firstly, texture features and corner features are detected. Secondly, the epanechnikov kernel function is used to calculate the point with the maximum kernel function value among all feature points, which is then defined as E-point. Thirdly, the salience region is defined and extracted according to the position of the E-point. Finally, six groups of heterologous images are used as data sources, and compared with HAPCG, HOWP, SIFT, and PSO_SIFT algorithms respectively. The results show that the comprehensive matching performance of the proposed method is better than the original algorithm without salience region processing. The root mean square error and the matching time are less than the original method while ensuring a similar number of matching points, which greatly improves the accuracy and speed of heterologous image matching. © (2025.0), (International Association of Engineers). All Rights Reserved.

关键词： Image matching

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SMS Spam Detection using Advance Naive-Bayes Approach

SMS Spam Detection using Advance Naive-Bayes Approach

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Arora, Yojna Gupta, Neha Rathore, Yogesh Singh Bansal, Nidhi Mehta, Aina Chadha, Shikha Kumar, Ashwani Sharda University Department of Computer Science and Engineering Greater Noida India Symbiosis University of Applied Sciences School of Computer Science & Information Technology Madhya Pradesh Indore India Sharda University School of Engineering and Technology Department of Computer Science and Applications Uttar Pradesh Greater Noida India School of Engineering and Technology Department of Computer Science & Engineering Haryana Faridabad India Bennett University School of Computer Science Engineering and Technology India

ISBN: (纸本)9798331508685

Recently, with increased use of mobile phones, it has transformed into a multibillion-dollar Short Message Service or SMS. However, the drop in the cost of messaging services has led to an increased number of unsolicited commercial messages, or spam, being delivered to mobile phones. Several reasons exist for which traditional algorithms used in email filtering may not efficiently classify the spam in SMS such as the absence of strong SMS spam databases, with the short length and features of the message, the informal language used, etc. This paper uses a real SMS spam database After preprocessing the data and extraction of relevant features, Naïve Bayes machine learning techniques is applied to get the results. Then it is analyzed using confusion matrix, accuracy, precision and recall values. A learning curve with clearly defined relationship between the training and testing data set and overall error at the end. © 2025 IEEE.

关键词： Adversarial machine learning

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A gecko-inspired adhesive robotic end effector for critical-contact manipulation

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science China(Information sciences) 2022年第8期65卷 120-133页

作者： Zhongyi CHU Jie DENG Lin SU Jing CUI Fuchun SUN School of Instrumentation and Optoelectronic Engineering Beihang University School of Mechanical Engineering and Applied Electronics Beijing University of Technology Department of Computer Science and Technology Tsinghua University

It is an emerging challenge for robots to achieve non-destructive pick-and-place manipulation for delicate objects under low normal preload, i.e., critical-contact manipulation. The prominent on-off controllable property of the gecko-inspired microwedge adhesive makes critical-contact manipulation possible for robotic end effectors. However, it is difficult for end effectors to actuate the micron-scale microwedge adhesive and detect the adhesion state. In this paper, a gecko-inspired adhesive robotic end effector for critical-contact manipulation is proposed, which consists of a half-scissor variable-scale actuator, a 3-axis high-sensitivity isotropic flexible capacitive tactile sensor, and the microwedge adhesive. The half-scissor variable-scale actuator is designed to provide pure large shear loading for the microwedge adhesive at micronscale displacement by merely controlling the normal macro-scale displacement of the actuator. Besides, the3-axis high-sensitivity isotropic flexible capacitive tactile sensor is designed for accurate detection of multiaxis contact forces and the adhesion state between the adhesive and objects to ensure the success of the critical-contact manipulation. The sensor can sense the shear and normal forces by detecting variations of the overlap and distance between electrodes, while the design of the finger-like electrodes improves the sensitivity. In addition, a set of experiments on manipulating objects are implemented and the results show that the proposed robotic end effector can provide pure large shear loading for the microwedge adhesive at micron-scale displacement and can detect the adhesion state between the microwedge adhesive and objects accurately to stably grasp delicate objects in critical-contact condition.

关键词： critical-contact manipulation gecko-inspired microwedge adhesive robotic end effector half-scissor variable-scale actuator tactile sensor

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Flexible Thin-Film Transistor and Integration Strategies for Future Intelligent Displays

IEEE Open Journal on Immersive Displays

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IEEE Open Journal on Immersive Displays 2024年 1卷 187-203页

作者： Zhang, Yuqing Wang, Xu Zhang, Sixin Wang, Chunxiu Zhang, Min Peking University School of Electronic and Computer Engineering Shenzhen518055 China Hong Kong Applied Science and Technology Research Institute Hong Kong

Future flexible intelligent displays are driving demands for greater flexibility, higher resolution, faster refresh rates, and enhanced functionality. This review mainly focuses on recent advances and ongoing challenges in flexible thin-film transistors (TFTs) based on low-temperature polycrystalline silicon (LTPS), amorphous oxide semiconductor (AOS), and low-temperature polysilicon and oxide (LTPO) for flexible backplane technologies. Furthermore, the developments of process and function integration techniques, including device scaling, device stacking, as well as functional circuits and applications, are discussed from the perspective of innovation and significance. Besides, the integration of intelligent systems is briefly introduced, emphasizing the role of synaptic transistors, including metal oxide and carbon nanotube-based ones, in real-time data processing and sensing functions. By providing insights into the status and future directions, this review provides a comprehensive perspective and discussion on the development of next-generation flexible intelligent display technologies. © 2024 IEEE.

关键词： Thin film transistors

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An Adaptive on Demand Modified Ant Colony Optimization Routing for VANETs 23th

An Adaptive on Demand Modified Ant Colony Optimization Routi...

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Kumari, J. Jesy Janet Thangam, S. Raja, A. Saleem Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Department of Computer Science and Engineering University of Technology and Applied Science-Shinas Shinas Oman

ISBN: (纸本)9783031648496

Around the world, vehicle accidents claim many priceless lives. To tackle this problem, the Vehicular ad hoc networks (VANETs) are the most effective solution. Effective communication between vehicular nodes in VANETs is extremely important because of the rapid mobility of vehicles and different network topology. Currently, VANET mostly serves the public security, stability, information for voyageurs, and traffic Management, control of congestion, guidance, etc. Chaos on roadways can occur at any moment, anyplace. It is a situation in which the flow of traffic regulations might cease to function. Collisions, maintaining roads, violation of legal rules, etc., so to evade the congestion in the surrounding region. VANETs represent a dynamic and challenging communication environment characterized by high mobility, intermittent connectivity, and rapid changes in network topology. Efficient and reliable routing is crucial for enabling diverse applications such as traffic management, safety communication, and infotainment services in VANETs. In this research, propose a multi-faceted approach to improve routing performance in VANETs. An adaptive routing algorithm that considers vehicle mobility patterns and dynamically adjusts communication routes based on the anticipated movement of neighboring vehicles such as Modified Ant Colony Optimization (MACO) technique. This adaptability enhances the robustness of the network against frequent topology changes and improves the overall packet delivery ratio, end-to-end delay, and network reliability compared to traditional routing protocols. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Vehicular ad hoc networks

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Clisp: A Robust Interactive Segmentation Framework for Pathological Images 46

Clisp: A Robust Interactive Segmentation Framework for Patho...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Wang, Hannan Shi, Jun Zhao, Minfan Qiao, Liang Wang, Zhaohui Dai, Yue Ma, Yuchen An, Hong University of Science and Technology of China School of Computer Science and Technology Hefei China University of Virginia School of Engineering & Applied Science Charlottesville United States

ISBN: (纸本)9798350371499

Recently, automatic segmentation algorithms based on deep learning have achieved promising results on various pathological image segmentation tasks. However, the inherent data-hungry nature of these methods and the high cost of annotating pathological images make them difficult to apply to practical clinical tasks. To address this problem, many studies have explored interactive segmentation methods to reduce the cost of annotating pathological images, which replace pixel-by-pixel annotation operations with clicks or other user instructions. Despite their effectiveness, most of these methods only utilize small-scale data resulting in poor generalization ability for different tasks or segmentation objects. In this paper, we propose a robust Click-based Interactive Segmentation framework for low-cost and interactive annotation of Pathological images, named Clisp. To improve the generalization ability, we construct a multi-source pathological image annotation dataset including around 79,000 images for supervised training of the proposed method. Besides, we adopt a heavy-parameter vision transformer as the image encoder to learn feature representations for large-scale data. We evaluate the proposed method on 7 open-source datasets, and the experimental results show that Clisp is superior to the baseline method in segmentation performance on most datasets and has outstanding generalization ability. © 2024 IEEE.

关键词： Image segmentation

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Multi-strategy Hybrid Coati Optimizer:A Case Study of Prediction of Average Daily Electricity Consumption in China

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Journal of Bionic engineering 2024年第5期21卷 2540-2568页

作者： Gang Hu Sa Wang Essam H.Houssein Department of Applied Mathematics Xi’an University of TechnologyXi’an710054China School of Computer Science and Engineering Xi’an University of TechnologyXi’an710048China Faculty of Computers and Information Minia UniversityMinia61519Egypt

The power sector is an important factor in ensuring the development of the national *** simulation and prediction of power consumption help achieve the balance between power generation and power *** this paper,a Multi-strategy Hybrid Coati Optimizer(MCOA)is used to optimize the parameters of the three-parameter combinatorial optimization model TDGM(1,1,r,ξ,Csz)to realize the simulation and prediction of China's daily electricity ***,a novel MCOA is proposed in this paper,by making the following improvements to the Coati Optimization Algorithm(COA):(ⅰ)Introduce improved circle chaotic mapping strategy.(ⅱ)Fusing Aquila Optimizer,to enhance MCOA's exploration capabilities.(ⅲ)Adopt an adaptive optimal neighborhood jitter learning *** improve MCOA escape from local optimal solutions.(ⅳ)Incorporating Differential Evolution to enhance the diversity of the ***,the superiority of the MCOA algorithm is verified by comparing it with the newly proposed algorithm,the improved optimiza-tion algorithm,and the hybrid algorithm on the CEC2019 and CEC2020 test ***,in this paper,MCOA is used to optimize the parameters of TDGM(1,1,r,ξ,Csz),and this model is applied to forecast the daily electricity consumption in China and compared with the predictions of 14 models,including seven intelligent algorithm-optimized TDGM(1,1,r,ξ,Csz),and seven forecasting *** experimental results show that the error of the proposed method is minimized,which verifies the validity of the proposed method.

关键词： Forecast of average daily electricity consumption in China Coati optimization algorithm Three-parameter combination optimization model Circle chaotic mapping

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