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Over-the-air Wireless Federated Learning Model for Generative AI

IEEE Network 2025年

作者： Zheng, Jie Niyato, Dusit Zhang, Haijun Du, Hongyang Wang, Jiacheng Kang, Jiawen Xiong, Zehui Northwest University State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services School of Information Science and Technology Shaanxi 710127 China Nanyang Technological University School of Computer Science and Engineering Singapore639798 Singapore University of Science and Technology Beijing Institute of Artificial Intelligence Beijing100083 China University of Hong Kong Department of electrical and electronic engineering Hong Kong Hong Kong Guangdong University of Technology Automation of School Guangzhou510006 China Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore

Generative artificial intelligence (GenAI) technologies represent an important advancement in the field of AI, particularly for their capabilities in text and image generation. Over-the-air wireless federated learning (OA-WFL) can utilize the wireless waveform superposition property to achieve efficient model aggregation, thereby providing support for GenAI training and deployment. Therefore, this article investigates the support of OA-WFL for GenAI, focusing on potential applications and specific examples. We first discuss the OA-WFL and GenAI models, emphasizing their functionalities and the potential benefits arising from their interaction. We then explore its application in various GenAI scenarios, including large-scale edge device content generation, efficient distributed training of GenAI models, and reduction of bandwidth requirements and device load. Next, a framework is proposed to apply OA-WFL to diffusion models, such as those used in image generation, and validate its effectiveness through simulation results. Finally, we discuss prospective research directions for the application of OA-WFL for GenAI. © 2025 IEEE.

关键词： Federated learning

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High-performance UV polarization sensitive photodetector for a graphene(2D)/GaN(3D) junction with a non-centrosymmetric electric field

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Photonics Research 2025年第6期13卷 1544-1553页

作者： Zou, Can Liu, Qing Zhang, Lu Tang, Xiao Li, Xiaohang Li, Shuti Gao, Fangliang Guangdong Engineering Research Center of Optoelectronic Functional Materials and Devices School of Electronic Science and Engineering School of Microelectronics South China Normal University Guangzhou510631 China Advanced Semiconductor Laboratory Electrical and Computer Engineering Program CEMSE Division King Abdullah University of Science and Technology Thuwal239556900 Saudi Arabia

This study pioneers a high-performance UV polarization-sensitive photodetector by ingeniously integrating non-centrosymmetric metal nanostructures into a graphene (Gr)∕Al2O3∕GaN heterojunction. Unlike conventional approaches constrained by graphene’s intrinsic isotropy or complex nanoscale patterning, our design introduces asymmetric metal architectures (E-/T-type) to artificially create directional anisotropy. These structures generate plasmon-enhanced localized electric fields that selectively amplify photogenerated carrier momentum under polarized UV light (325 nm), synergized with Fowler-Nordheim tunneling (FNT) across an atomically thin Al2O3 barrier. The result is a breakthrough in performance: a record anisotropy ratio of 115.5 (E-type, −2 V) and exceptional responsivity (97.7 A/W), surpassing existing graphene-based detectors by over an order of magnitude. Crucially, by systematically modulating metal geometry and density, we demonstrate a universal platform adaptable to diverse 2D/3D systems. This study provides a valuable reference for developing and practically applying photodetectors with higher anisotropy than ultraviolet polarization sensitivity. © 2025 Chinese Laser Press.

关键词： Nanoparticles

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A Novel Robotic System Enabling Multiple Bilateral Upper Limb Rehabilitation Training via an Admittance Controller and Force Field

TechRxiv

引用

TechRxiv 2023年

作者： Jiao, Ran Liu, Wenjie Rashad, Ramy Li, Jianfeng Dong, Mingjie Stramigioli, Stefano Beijing Key Laboratory of Advanced Manufacturing Technology Faculty of Materials and Manufacturing Beijing University of Technology Beijing100124 China The Robotics and Mechatronics Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede7545VL Netherlands ITMO University Saint Petersburg Russia

Patients with hemiplegia are usually restricted to performing general bilateral activities of daily life (gbADLs). Bilateral training has been verified to contribute to the rehabilitation of physical functions. Although robotic systems are gradually being employed in the field of rehabilitation, few studies have performed simulations with regards to gbADLs for training. Therefore, a novel end-effector bilateral rehabilitation robotic system (EBReCS) for the upper limb is developed in this article for the task rendering of gbADLs, in which the gbADL-corresponding workspace is obtained via modularly designed bilateral parallelogram mechanisms, and interaction rendering of multiple bimanual modes (uncoupled, trans-soft-coupled, trans-semi-coupled, and rotation-coupled) is achieved by implementing the admittance model, the inner force field between robotic end-effectors, and the outer force field distributed around. Experiments of the proposed four rehabilitation training modes were carried out on the healthy subject, with the results showing a feasible method of the EBReCS in the simulation of multiple bimanual coordinated rehabilitation training tasks. In the future, the constructed EBReCS is expected to be clinically tested and exploited for home rehabilitation as a coordinated training device. © 2023, CC BY.

关键词： End effectors

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A Smart Capacity Enhancement and Estimation Model for Hybrid Buildings by using Light Weight Deep Learning Model

A Smart Capacity Enhancement and Estimation Model for Hybrid...

引用

Disruptive Technologies (ICDT), International Conference on

作者： Senthil Kumar Nageswara Rao Atyam Khadar Nawas K Shashank Awasthi M. Kotteeswaran K. S. Thirunavukkarasu KL School of Architecture Koneru Lakshmanan Education Foundation Guntur Andhra Pradesh India Electrical and Electronics Department CMR Institute of Technology Bengaluru Karnataka India School of Computing Science and Engineering Vellore Institute of Technolog Chennai Tamil Nadu India Department of Computer Science and Engineering GL Bajaj Institute of Technology and Management Greater Noida Uttar Pradesh India School of Management and Commerce Vels Institute of Science Technology and Advanced Studies (VISTAS) Pallavaram Chennai Tamil Nadu India School of Computing Science Vels Institute of Science Technology and Advanced Studies (VISTAS) Pallavaram Chennai Tamil Nadu India

Generally, for the buildings constructed in our areas, the conventional foundation known as 'shallow', i.e. from the ground level downwards, is set up in three dimensions such as length, width and depth. Foundations are not the same for all types of structures. The size and structure of the foundation varies depending on the nature of the prevailing soil, ground water level of the plot, type of building, and total load of the structure. In this paper an innovation estimation model was proposed based on light weigth deep learning technique. The proposed model introduces capacity estimation and energy efficiency plans and designs. These are all relating to commercial buildings, craft facilities and mass housing projects to enable design, construction. It also maintains the buildings under minimum energy consumption without stressing the operation of buildings. The health and comfort of the occupants are establishing compliance standards and ensure the maximum standards for energy efficiency in the plans or designs of commercial buildings. The proposed model also focuses the capacity estimation and energy efficiency programs beyond maximum standards.

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Observation of charge to spin conversion in p-orbital InBi alloy

arXiv

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arXiv 2025年

作者： Li, Gen Zhang, Ying Xu, Xiaoguang Shen, Lei Feng, Zheng Meng, Kangkang Li, Ang Cheng, Lu He, Kang Tan, Wei Wu, Yong Wu, Yihong Jiang, Yong Key Laboratory of Advanced Materials and Devices for Post-Moore Chips Ministry of Education School of Materials Science and Engineering University of Science and Technology Beijing Beijing100083 China Department of Electrical and Computer Engineering National University of Singapore 117576 Singapore Research Institute Chongqing Liang Jiang New Area Chongqing401123 China Department of Mechanical Engineering National University of Singapore 117575 Singapore Microsystem & Terahertz Research Center CAEP Chengdu610200 China Faculty of Materials and Manufacturing Beijing Key Lab of Microstructure and Properties of Advanced Materials Beijing University of Technology Beijing100124 China Institute of Quantum Materials and Devices School of Electronic and Information Engineering State Key Laboratory of Separation Membranes and Membrane Processes Tiangong University Tianjin300387 China

High density data storage and spin-logic devices require highly efficient all-electric control of spin moment. So far, charge-to-spin conversion through the spin Hall effect limits to d-orbital materials associated with strong spin-orbit coupling, especially heavy metals. However, d-orbital heavy metals with strong spin-orbit coupling results in a short spin diffusion length, which restricts the spin transport and accumulation in spintronic devices. Therefore, the conflict between charge-to-spin conversion efficiency and spin transport ability is irreconcilable in d-orbital materials. Here, we report a large charge to spin conversion experimentally observed in the p-orbital In2Bi alloy, exhibiting the coexistence of a large spin Hall angle comparable to heave metal Pt and a long spin diffusion length (4 times that of Pt). First-principles calculations reveal that topological symmetry-protected gap opening near the Fermi level results in large Berry curvature-related spin Hall conductivity. Due to the delocalized nature of p-orbitals and semimetal properties of In2Bi, its spin current can overcome the physical barriers between spin Hall angle and spin diffusion length in d-orbital metals, thereby advancing the development of high-performance spintronic devices. Copyright © 2025, The Authors. All rights reserved.

关键词： Heavy metals

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Physics-informed Inverse Design of Multi-bit Programmable Metasurfaces

arXiv

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arXiv 2024年

作者： Xu, Yucheng Yang, Jia-Qi Fan, Kebin Wang, Sheng Wu, Jingbo Zhang, Caihong Zhan, De-Chuan Padilla, Willie J. Jin, Biaobing Chen, Jian Wu, Peiheng Key Laboratory of Optoelectronic Devices and Systems with Extreme Performances of MOE School of Electronic Science and Engineering Nanjing University Nanjing210023 China Purple Mountain Laboratories Nanjing211111 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China Department of Electrical and Computer Engineering Duke University Box 90291 DurhamNC27708 United States

Emerging reconfigurable metasurfaces offer various possibilities in programmatically manipulating electromagnetic waves across spatial, spectral, and temporal domains, showcasing great potential for enhancing terahertz applications. However, they are hindered by limited tunability, particularly evident in relatively small phase tuning over 270o, due to the design constraints with time-intensive forward design methodologies. Here, we demonstrate a multi-bit programmable metasurface capable of terahertz beam steering, facilitated by a developed physics-informed inverse design (PIID) approach. Through integrating a modified coupled mode theory (MCMT) into residual neural networks, our PIID algorithm not only significantly increases the design accuracy compared to conventional neural networks but also elucidates the intricate physical relations between the geometry and the modes. Without decreasing the reflection intensity, our method achieves the enhanced phase tuning as large as 300o. Additionally, we experimentally validate the inverse designed programmable beam steering metasurface, which is adaptable across 1-bit, 2-bit, and tri-state coding schemes, yielding a deflection angle up to 68o and broadened steering coverage. Our demonstration provides a promising pathway for rapidly exploring advanced metasurface devices, with potentially great impact on communication and imaging technologies. © 2024, CC0.

关键词： Tuning

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DNA serial dilution: an investigation toward accurate broadband plasmonic signature 22

DNA serial dilution: an investigation toward accurate broadb...

引用

Plasmonics in Biology and Medicine XXII 2025

作者： Dehzangi, Arash Ghasemi, Masih Choudhury, P.K. Department of Electrical and Computer Engineering University of Texas at Dallas RichardsonTX United States Laser and Plasma Research Institute Shahid Beheshti University Daneshju Blvd.Evin Tehran Iran College of Optical Science and Engineering International Research Center for Advanced Photonics Zhejiang University Building 1A 718 East Haizhou Rd. Zhejiang Haining China

ISBN: (纸本)9781510684225

Serial dilution of Balb/c rat DNA in the visible broadband plasmonic spectroscopy was explored as a promising technique to reduce this genomic substance concentration in the nanoscale. The physical DNA of a living creature, after extraction from the resources (such as blood, nail, hair, tissue, and other possible organs) assumes amorphous pile of strands in the microscale or larger. The serial dilution technique was exploited to exponentially decrease the DNA concentration of BALB/c rat - the target living mammal - in the nanoscale, and the diluted DNA was deposited over a thin film of gold (for fixturing and removing moisture). Plasmonic surface waves of different frequencies were found to promote wave propagation more efficiently when lower thickness of unstructured-nanoscale-DNA layer was deposited (over gold thin film). The results manifest that the most diluted DNA sample reveals distinguishable plasmonic conditions. The sensitivity of the configuration was enhanced in the presence of a DNA sample (as compared to the case of non-existing measurand), which was further increased for larger incidence angles. © 2025 SPIE.

关键词： Surface plasmon resonance

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Optimization for Deep Learning:An Overview

引用

Journal of the Operations Research Society of China 2020年第2期8卷 249-294页

作者： Ruo-Yu Sun Department of Industrial and Enterprise Systems Engineering and affiliated to Coordinated Science LaboratoryUniversity of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of Electrical and Computer Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA

Optimization is a critical component in deep *** think optimization for neural networks is an interesting topic for theoretical research due to various ***,its tractability despite non-convexity is an intriguing question and may greatly expand our understanding of tractable ***,classical optimization theory is far from enough to explain many ***,we would like to understand the challenges and opportunities from a theoretical perspective and review the existing research in this ***,we discuss the issue of gradient explosion/vanishing and the more general issue of undesirable spectrum and then discuss practical solutions including careful initialization,normalization methods and skip ***,we review generic optimization methods used in training neural networks,such as stochastic gradient descent and adaptive gradient methods,and existing theoretical ***,we review existing research on the global issues of neural network training,including results on global landscape,mode connectivity,lottery ticket hypothesis and neural tangent kernel.

关键词： Deep learning Non-convex optimization Neural networks Convergence Landscape

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A Data-Informed Analysis of Scalable Supervision for Safety in Autonomous Vehicle Fleets

arXiv

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arXiv 2024年

作者： Hickert, Cameron Yan, Zhongxia Wu, Cathy The Institute for Data Systems and Society Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States The Laboratory for Information & Decision Systems The Institute for Data Systems and Society The Department of Civil and Environmental Engineering Massachusetts Institute of Technology CambridgeMA02139 United States

Autonomous driving is a highly anticipated approach toward eliminating roadway fatalities. At the same time, the bar for safety is both high and costly to verify. This work considers the role of remotely-located human operators supervising a fleet of autonomous vehicles (AVs) for safety. Such a 'scalable supervision' concept was previously proposed to bridge the gap between still-maturing autonomy technology and the pressure to begin commercial offerings of autonomous driving. The present article proposes DISCES, a framework for Data-Informed Safety-Critical Event Simulation, to investigate the practicality of this concept from a dynamic network loading standpoint. With a focus on the safety-critical context of AVs merging into mixed-autonomy traffic, vehicular arrival processes at 1,097 highway merge points are modeled using microscopic traffic reconstruction with historical data from interstates across three California counties. Combined with a queuing theoretic model, these results characterize the dynamic supervision requirements and thereby scalability of the teleoperation approach. Across all scenarios we find reductions in operator requirements greater than 99% as compared to in-vehicle supervisors for the time period analyzed. The work also demonstrates two methods for reducing these empirical supervision requirements: (i) the use of cooperative connected AVs - which are shown to produce an average 3.67 orders-of-magnitude system reliability improvement across the scenarios studied - and (ii) aggregation across larger regions. Copyright © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Electron Confinement-Induced Plasmonic Breakdown in Metals

arXiv

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arXiv 2024年

作者： Das, Prasanna Rudra, Sourav Rao, Dheemahi Banerjee, Souvik Indiradevi, Ashalatha Pillai, Kamalasanan Garbrecht, Magnus Boltasseva, Alexandra Bondarev, Igor V. Shalaev, Vladimir M. Saha, Bivas Chemistry and Physics of Materials Unit International Centre for Materials Science Jawaharlal Nehru Centre for Advanced Scientific Research Bangalore560064 India Sydney Microscopy and Microanalysis The University of Sydney CamperdownNSW2006 Australia Elmore Family School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States Department of Mathematics & Physics North Carolina Central University DurhamNC27707 United States School of Advanced Materials and Sheikh Saqr Laboratory Jawaharlal Nehru Centre for Advanced Scientific Research Bangalore560064 India

Plasmon resonance in metals represents the collective oscillation of the free electron gas density and enables enhanced light-matter interactions in nanoscale dimensions 1–4. Traditionally, the classical Drude model describes the plasmonic excitation, wherein the plasma frequency exhibits no spatial dispersion 5. Here, we show conclusive experimental evidence of the breakdown of the plasmon resonance and a consequent photonic metal-insulator transition in an ultrathin archetypal refractory plasmonic material, hafnium nitride (HfN). Epitaxial HfN thick films exhibit a low-loss and high-quality Drude-like plasmon resonance in the visible spectral range 6,7. However, as the film thickness is reduced to nanoscale dimensions, the Coulomb interaction among electrons increases due to the electron confinement, leading to the spatial dispersion of the plasma frequency 8,9. Importantly, with the further decrease in thickness, electrons lose their ability to shield the incident electric field, turning the medium into a dielectric. The breakdown of the plasmon resonance in epitaxial ultrathin metals could be useful for fundamental physics studies in transdimensional regimes 10 and novel photonic device applications. © 2024, CC BY.

关键词： Electrons

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