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Faster Convergence on Heterogeneous Federated Edge Learning: An Adaptive Clustered Data Sharing Approach

IEEE Transactions on Mobile Computing 2025年第6期24卷 5342-5356页

作者： Hu, Gang Teng, Yinglei Wang, Nan Han, Zhu Beijing Key Laboratory of Work Safety Intelligent Monitoring Beijing100876 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

Federated Edge Learning (FEL) emerges as a pioneering distributed machine learning paradigm for the 6 G Hyper-Connectivity, harnessing data from the IoT devices while upholding data privacy. However, current FEL algorithms struggle with non-independent and non-identically distributed (non-IID) data, leading to elevated communication costs and compromised model accuracy. To address these statistical imbalances, we introduce a clustered data sharing framework, mitigating data heterogeneity by selectively sharing partial data from cluster heads to trusted associates through sidelink-aided multicasting. The collective communication pattern is integral to FEL training, where both cluster formation and the efficiency of communication and computation impact training latency and accuracy simultaneously. To tackle the strictly coupled data sharing and resource optimization, we decompose the optimization problem into the clients clustering and effective data sharing subproblems. Specifically, a distribution-based adaptive clustering algorithm (DACA) is devised basing on three deductive cluster forming conditions, which ensures the maximum sharing yield. Meanwhile, we design a stochastic optimization based joint computed frequency and shared data volume optimization (JFVO) algorithm, determining the optimal resource allocation with an uncertain objective function. The experiments show that the proposed framework facilitates FEL on non-IID datasets with faster convergence rate and higher model accuracy in a resource-limited environment. © 2002-2012 IEEE.

关键词： Federated learning

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KINEMATICS ANALYSIS AND SIMULATION OF LASER WELDING ROBOT FOR SOLAR PANEL BUSBAR

International Journal of Mechatronics and Applied Mechanics

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International Journal of Mechatronics and Applied Mechanics 2025年第19期1卷 198-204页

作者： Peng, Wang Mingliang, Zheng School of Mechanical and Electrical Engineering Huainan Normal University Huainan232038 China Human-computer collaborative robot Joint Laboratory of Anhui Province Huainan232038 China

To overcome the insufficient quality stability of the overlap welding joints of solar panel busbar, using laser brazing technology, a new type of serial gantry robot with five degrees of freedom (three translations and two rotations) is designed. Firstly, the structure scheme of the gantry laser welding robot with five degrees of freedom for solar panel busbar is introduced. Secondly, the D-H linkage coordinate system of the welding robot is established, and the kinematics forward and inverse solutions and the velocity Jacobian matrix are solved. Finally, the kinematics forward and inverse solutions are verified by using Robotics toolbox in Matlab;the reachable space of the robot is calculated by Monte-Carlo method;the kinematics simulation of the laser welding robot end effector is carried out by using Adams software. The results show that the displacement of the end effector of the gantry laser welding robot with five degrees of freedom for solar panel busbar is non-interference and the velocity curves change smoothly, which verifies the rationality of this structural design. By making a prototype and building a test platform for experimental verification, the robot ran smoothly, the weld seam layout was efficient and accurate, and the error at the end of the robot welding gun was within 0.28 mm. © 2025 The Author(s).

关键词： MATLAB

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Controllability analysis of mechanical multibody dynamics control systems based on lie symmetry

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Alexandria engineering Journal 2025年 127卷 374-379页

作者： Mingliang, Zheng School of Mechanical and Electrical Engineering Huainan Normal University Huainan232038 China Human-computer collaborative robot Joint Laboratory of Anhui Province Huainan232038 China

To quantitatively characterize the dynamic controlled performance of mechanical multibody systems and design collaborative control strategies, this paper investigates the controllability of mechanical multibody dynamic control systems. Firstly, under the affine connection framework of Lagrange mechanical control systems, we establish the Euler-Poincaré equations of unconstrained mechanical multibody dynamics control systems by differential geometry method;Further, we transform the Euler-Poincaré equations into the classical state space form of nonlinear control systems by augmented vector method;Secondly, by introducing Lie group representation theory, the definition and the solution of generalized Lie symmetry for mechanical multibody dynamics control systems are given, and the necessary and sufficient conditions for state controllability (local controllability) are given by using Lie symmetry;Finally, an application example of dynamic control of a single degree of freedom manipulator with basic vibration is provided, it explains the effectiveness and correctness of the Lie symmetry method in this paper. The research has shown that using Lie symmetry to analyze the controllability problem of mechanical multibody dynamics control systems can be transformed into its low-dimensional quotient space analysis, and if the quotient space is controllable at a point, then the system can be controllable for all points on the orbit where that point at. © 2025

关键词： Controllability

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Contract-Based Incentive Mechanisms for UAV Networks in Covert Communications

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 7378-7391页

作者： Tian, Wen Fan, Hao Liu, Guangjie Du, Miao Liu, Yinqiu Niyato, Dusit Han, Zhu Nanjing University of Information Science and Technology School of Electronic and Information Engineering Nanjing University of Information Science and Technology Key Laboratory of Intelligent Support Technology In Complex Environment Ministry of Education Nanjing210044 China Southeat University School of Computer Science and Engineering China Southeast University Key Laboratory of Computer Network and Information Integration Ministry of Education Nanjing China Nanyang Technological University School of Computer Science and Engineering 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

Covert communication is considered a promising technology for hiding transmission processes and activities from malicious eavesdropping. With the development of detection technology, the traditional point-to-point covert communication method cannot effectively guarantee the reliability of covert communication. In order to solve this problem, unmanned aerial vehicle (UAV) are widely adopted in covert communication as common relay equipment. However, the UAV maximizes its benefits by taking advantage of the information asymmetry between itself and the covert communication sender. Therefore, it is necessary to encourage UAV-assisted potential users (UPU) to transmit covert data honestly by designing an information asymmetry-based incentive mechanism. In this paper, we propose a UAV-assisted contract-theoretic (UACT) model to improve the covert communication performance, where UPU honestly transmits covert data and the throughput of UACT can be increased. Specifically, we first divide UPU into finite types and model the data transfer contract between the sender, UPU, and receiver. Then, the contract feasibility of UACT is derived with sufficient and necessary conditions. Finally, we analyze the contract optimization in the continuous case of UPUs. Numerical simulations show that the UACT can incentivize UPUs to transmit covert data through UAV assistance and make covert communication performance close to the information symmetry case. © 1967-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Evaluation of OCT Image Synthesis for Choroidal and Retinal Layer Segmentation Using Denoising Diffusion Probabilistic Models

Evaluation of OCT Image Synthesis for Choroidal and Retinal ...

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18th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2025

作者： Yamauchi, Yudai Wu, Yuli Okada, Eiji Keio University Department of Electronics and Electrical Engineering Japan Institute of Imaging and Computer Vision RWTH Aachen University Germany

Machine learning can automatically conduct the layer segmentation task of retinal optical coherence tomog raphy (OCT) image, but annotated data is required to train these models. Synthetic retinal OCT images are generated using denoising diffusion probabilistic models (DDPMs), which can be used to train segmentation models effectively and automatically create annotated data. However, the extent to which these synthetic im ages contribute to segmentation accuracy compared to real data has not been investigated. In this study, we synthesized retinal OCT images from sketch images using DDPMs, trained a segmentation model using syn thetic and real images, and evaluated how the use of synthetic images influenced the accuracy of choroidal and retinal layer segmentation compared to results using only real images. Through a comparison of the Dice score, we confirmed that training with both synthetic and real OCT images led to higher Dice scores than train ing with only real OCT images. These findings suggest that using synthetic images can enhance segmentation accuracy, offering a promising approach to improving model performance in situations with limited annotated real data. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Image segmentation

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Elevating E-Service Standards in Bangladesh: Merging FAHP and TOPSIS for Strategic Online Business Solutions

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IEEE Access 2025年 13卷 83765-83780页

作者： Tasnim, Farzana Mahmud, Tanjim Johara Chowdhury, Shefayatuj Fahrin Choity, Tasnia Ahmed, Aisha Saeed Hasan Chowdhury, Mohammad Shahadat Hossain, Mohammad Andersson, Karl International Islamic University Chittagong Department of Computer Science and Engineering Chittagong4318 Bangladesh Rangamati Science and Technology University Department of Computer Science and Engineering Rangamati4500 Bangladesh International Islamic University Chittagong Department of Electrical and Electronic Engineering Chittagong4318 Bangladesh University of Chittagong Department of Computer Science and Engineering Chittagong4331 Bangladesh Luleå University of Technology Cybersecurity Laboratory Skellefteå931 87 Sweden

The rapid expansion of Bangladesh’s digital economy has unlocked new opportunities for online businesses, but it has also heightened the challenges of delivering high-quality e-services in an increasingly competitive environment. While previous studies have largely focused on customer satisfaction and consumer experiences, the perspective of business owners—those managing daily operations and strategic decisions—has been notably underexplored. Addressing this gap, the present study aims to identify and prioritize the critical success factors (CSFs) influencing the performance of online businesses in Bangladesh from the owners’ viewpoint.A structured survey has been conducted among 57 online business owners, collecting data across ten essential dimensions, including website infrastructure, information sharing, delivery practices, responsiveness, customization, customer service, reliability, payment security, return policies, and service quality challenges. To ensure a data-driven analysis, the Random Forest algorithm is utilized for feature importance extraction, followed by pairwise comparisons through fuzzy triangular matrices. Subsequently, FAHP and TOPSIS techniques are applied to systematically rank the factors and alternatives. Model validation using the XGBoost classifier results in 93% accuracy and a 93% F1-score, demonstrating the robustness of the proposed approach. The results reveal that service quality concerns, payment security, and effective customer support are the most influential determinants of business success. Beyond offering a methodological advancement that integrates machine learning with MCDM, this study delivers actionable insights for business owners, digital strategists, and policymakers aiming to enhance the competitiveness and resilience of Bangladesh’s e-commerce landscape. © 2013 IEEE.

关键词： Marketplaces

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Integrated Framework of Multisource Data Fusion for Outage Location in Looped Distribution Systems

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IEEE Transactions on Smart Grid 2025年第3期16卷 2635-2646页

作者： Liu, Liming Yuan, Yuxuan Wang, Zhaoyu Yao, Yiyun Ding, Fei Iowa State University Department of Electrical and Computer Engineering AmesIA50011 United States National Renewable Energy Laboratory Power System Engineering Center GoldenCO80214 United States

Accurate outage location is essential for expediting post-outage power restoration, minimizing outage duration, and enhancing the resilience of distribution networks. With the advent of advanced metering infrastructure, data-driven outage location methods have significantly advanced beyond traditional approaches that rely on manual inspections. However, existing methods still face critical challenges, like reliance on single-source data, limited ability to handle partially observable systems or difficulties with loop networks. To the best of our knowledge, no single approach has comprehensively addressed all of these challenges at once. To this end, this paper proposes a comprehensive multisource data fusion framework for outage locations via probabilistic graph networks. The framework consists of three key phases. First, a novel method for reconstituting distribution networks with loops is developed, transforming looped networks into multiple radial subnetworks that retain all outage causalities of the original network. Second, Bayesian network (BN) models are established for each subnetwork, integrating multiple data sources and network structures. Finally, a joint Gibbs sampling mechanism, featuring forward and backward information flow, is designed to merge data from separate BN models and maximize the utilization of limited evidence, ensuring accurate outage location identification. The framework was validated on two modified public test systems, and comparative studies confirmed its effectiveness. © 2010-2012 IEEE.

关键词： Soft sensors Data models Topology Probabilistic logic Data integration Accuracy Renewable energy sources Observability Government Support vector machines

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Distributed and networked analysis of volumetric image data for remote collaboration of microscopy image analysis

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Journal of Medical Imaging 2025年第2期12卷 024001页

作者： Chen, Alain Han, Shuo Lee, Soonam Fu, Chichen Yang, Changye Wu, Liming Winfree, Seth Dunn, Kenneth W. Salama, Paul Delp, Edward J. Purdue University School of Electrical and Computer Engineering Video and Image Processing Laboratory West LafayetteIN United States National Institute of Allergy and Infectious Diseases Rocky Mountain Laboratories HamiltonMT United States Indiana University School of Medicine IndianapolisIN United States Purdue University at Indianapolis School of Electrical and Computer Engineering IndianapolisIN United States

Purpose: The advancement of high-content optical microscopy has enabled the acquisition of very large three-dimensional (3D) image datasets. The analysis of these image volumes requires more computational resources than a biologist may have access to in typical desktop or laptop computers. This is especially true if machine learning tools are being used for image analysis. With the increased amount of data analysis and computational complexity, there is a need for a more accessible, easy-to-use, and efficient network-based 3D image processing system. The distributed and networked analysis of volumetric image data (DINAVID) system was developed to enable remote analysis of 3D microscopy images for biologists. Approach: We present an overview of the DINAVID system and compare it to other tools currently available for microscopy image analysis. DINAVID is designed using open-source tools and has two main sub-systems, a computational system for 3D microscopy image processing and analysis and a 3D visualization system. Results: DINAVID is a network-based system with a simple web interface that allows biologists to upload 3D volumes for analysis and visualization. DINAVID enables the image access model of a center hosting image volumes and remote users analyzing those volumes, without the need for remote users to manage any computational resources. Conclusions: The DINAVID system, designed and developed using open-source tools, enables biologists to analyze and visualize 3D microscopy volumes remotely without the need to manage computational resources. DINAVID also provides several image analysis tools, including pre-processing and several segmentation models. © 2025 Society of Photo-Optical Instrumentation Engineers (SPIE).

关键词： Photointerpretation

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Strategies for Effective EEG Preprocessing 22

Strategies for Effective EEG Preprocessing

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22nd International Learning and Technology Conference, L and T 2025

作者： Salem, Nema Alamoudi, Nora Mustafa, Lama Bagais, Fatima Effat University Electrical Research Laboratory College of Engineering Jeddah Saudi Arabia Effat University College of Engineering Department of Electrical and Computer Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798331532215

The administration of anesthesia is critical for ensuring the safety of surgical procedures, yet it comes with inherent risks associated with medication mistakes. Monitoring EEG signals during anesthesia is crucial for understanding patient physiology;however, the accuracy of this information heavily relies on effectively eliminating noise. Decreasing noise in EEG signals is vital for accurately interpreting data, ultimately enhancing patient safety and refining anesthesia management. This research concentrates on an advanced preprocessing technique for EEG signals, employing segmentation, detrending, variational mode decomposition (VMD), and noise reduction through Gaussian filtering, moving averages, Independent Component Analysis (ICA), and Discrete Wavelet Transform (DWT). The study utilized EEG data collected during surgeries and applied these preprocessing approaches to reduce noise and artifacts. Our results indicate that employing the Discrete Wavelet Transform (DWT) for denoising is robust and produces superior outcomes compared to other techniques investigated, achieving a high Signal-To-Noise Ratio (SNR) of 43.23 dB. © 2025 IEEE.

关键词： Anesthesia Discrete Wavelet Transform EEG preprocessing Gaussian Independent Component Analysis Moving average Noise removal SDG 17

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Broadband Impedance Matching for Wearable Magnetoinductive Waveguides

Broadband Impedance Matching for Wearable Magnetoinductive W...

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2025 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2025

作者： Jenkins, Connor Kiourti, Asimina ElectroScience Laboratory Department of Electrical and Computer Engineering The Ohio State University ColumbusOH43212 United States

ISBN: (纸本)9781946815200

Magnetoinductive Waveguides (MIWs) consist of coupled electrically small resonant elements that support the propagation of magnetoinductive waves. By exciting current on an element, a magnetic field is formed, leading to the generation of current on neighboring elements via Faraday's Law. This pattern continues to form a traveling wave. MIWs have been used in wireless power transfer applications, sub-wavelength imaging setups, and as data communication media for applications such as Magnetic Resonance Imaging (MRI) or in challenging Radio-Frequency (RF) environments such as underground, underwater or on the body. In particular, our previous work has focused on their application to wireless body area networks (WBANs) that seamlessly interconnect wearable devices and sensors. © 2025 USNC-URSI.

关键词： Inductive power transmission

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