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Over-the-Air Computation via 2D Movable Antenna Array

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arXiv 2024年

作者： Li, Nianzu Wu, Peiran Ning, Boyu Zhu, Lipeng Mei, Weidong The School of Electronics and Information Technology Sun Yat-sen University Guangzhou510006 China National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

Movable antenna (MA) has emerged as a promising technology for improving the performance of wireless communication systems, which enables local movement of the antennas to create more favorable channel conditions. In this letter, we advance its application for over-the-air computation (AirComp) network, where an access point is equipped with a two-dimensional (2D) MA array to aggregate wireless data from massive users. We aim to minimize the computation mean square error (CMSE) by jointly optimizing the antenna position vector (APV), the receive combining vector at the access point and the transmit coefficients from all users. To tackle this highly non-convex problem, we propose a two-loop iterative algorithm, where the particle swarm optimization (PSO) approach is leveraged to obtain a suboptimal APV in the outer loop while the receive combining vector and transmit coefficients are alternately optimized in the inner loop. Numerical results demonstrate that the proposed MA-enhanced AirComp network outperforms the conventional network with fixed-position antennas (FPAs). Copyright © 2024, The Authors. All rights reserved.

关键词： Mean square error

Pitfalls of defacing whole-head MRI: re-identification risk with diffusion models and compromised research potential

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arXiv 2025年

作者： Gao, Chenyu Xu, Kaiwen Kim, Michael E. Zuo, Lianrui Li, Zhiyuan Archer, Derek B. Hohman, Timothy J. Moore, Ann Zenobia Ferrucci, Luigi Beason-Held, Lori L. Resnick, Susan M. Davatzikos, Christos Prince, Jerry L. Landman, Bennett A. Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN United States Department of Computer Science Vanderbilt University NashvilleTN United States Vanderbilt Memory and Alzheimer’s Center Vanderbilt University Medical Center NashvilleTN United States Department of Neurology Vanderbilt University Medical Center NashvilleTN United States Translational Gerontology Branch National Institute on Aging National Institutes of Health BaltimoreMD United States Laboratory of Behavioral Neuroscience National Institute on Aging National Institutes of Health BaltimoreMD United States AI2D Center for AI and Data Science University of Pennsylvania Philadelphia United States Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD United States

Defacing is often applied to head magnetic resonance image (MRI) datasets prior to public release to address privacy concerns. The alteration of facial and nearby voxels has provoked discussions about the true capability of these techniques to ensure privacy as well as their impact on downstream tasks. With advancements in deep generative models, the extent to which defacing can protect privacy is uncertain. Additionally, while the altered voxels are known to contain valuable anatomical information, their potential to support research beyond the anatomical regions directly affected by defacing remains uncertain. To evaluate these considerations, we develop a refacing pipeline that recovers faces in defaced head MRIs using cascaded diffusion probabilistic models (DPMs). The DPMs are trained on images from 180 subjects and tested on images from 484 unseen subjects, 469 of whom are from a different dataset. To assess whether the altered voxels in defacing contain universally useful information, we also predict computed tomography (CT)-derived skeletal muscle radiodensity from facial voxels in both defaced and original MRIs. The results show that DPMs can generate high-fidelity faces that resemble the original faces from defaced images, with surface distances to the original faces significantly smaller than those of a population average face (p -4). For shin muscle, the correlation is statistically significant (p 0.05) when any defacing method is applied, suggesting that defacing might not only fail to protect privacy but also eliminate valuable information. We advocate two solutions for data sharing that comply with privacy: 1) share skull-stripped images along with measurements of facial and cranial features extracted before skull-stripping for public access, while acknowledging that this approach inherently compromises many research potentials;or 2) share the unaltered images with privacy enforced through policy restrictions. © 2025, CC BY-NC-ND.

关键词： Magnetic resonance imaging

Fully integrated and broadband Si-rich silicon nitride wavelength converter based on Bragg scattering intermodal four-wave mixing

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Photonics Research 2024年第S1期12卷 I0001-I0010页

作者： VALERIO VITALI THALÍA DOMÍNGUEZ BUCIO HAO LIU JOSÉMANUEL LUQUE GONZÁLEZ FRANCISCO JURADO-ROMERO ALEJANDRO ORTEGA-MOÑUX GLENN CHURCHILL JAMES C.GATES JAMES HILLIER NIKOLAOS KALFAGIANNIS DANIELE MELATI JENS H.SCHMID ILARIA CRISTIANI PAVEL CHEBEN J.GONZALO WANGÜEMERT-PÉREZ ÑIGO MOLINA-FERNÁNDEZ FREDERIC GARDES COSIMO LACAVA PERIKLIS PETROPOULOS Optoelectronics Research Centre University of SouthamptonSouthampton SO171BJUK Electrical Computer and Biomedical Engineering DepartmentUniversity of PaviaPavia 27100Italy Telecommunication Research Institute(TELMA) Universidad de MálagaCEI Andalucı´a TECHE.T.S.I.Telecomunicación29010 MálagaSpain School of Science and Technology Nottingham Trent UniversityNottingham NG118NSUK Department of Electrical Engineering Eindhoven University of TechnologyEindhoven 5600 MBThe Netherlands Department of Materials Science and Engineering University of IoanninaIoannina 45110Greece Centre de Nanosciences et de Nanotechnologies UniversitéParis-SaclayCNRS91120 PalaiseauFrance Advanced Electronics and Photonics Research Center National Research Council CanadaOttawaOntario K1A 0R6Canada

Intermodal four-wave mixing(FWM)processes have recently attracted significant interest for all-optical signal processing applications thanks to the possibility to control the propagation properties of waves exciting distinct spatial modes of the same *** allows,in principle,to place signals in different spectral regions and satisfy the phase matching condition over considerably larger bandwidths compared to intramodal ***,the demonstrations reported so far have shown a limited bandwidth and suffered from the lack of on-chip components designed for broadband manipulation of different *** demonstrate here a silicon-rich silicon nitride wavelength converter based on Bragg scattering intermodal FWM,which integrates mode conversion,multiplexing and de-multiplexing functionalities *** system enables wavelength conversion between pump waves and a signal located in different telecommunication bands(separated by 60 nm)with a 3 dB bandwidth exceeding 70 nm,which represents,to our knowledge,the widest bandwidth ever achieved in an intermodal FWM-based system.

关键词： scattering pump modal

A High-Performance Infrared Imaging System with Adaptive Contrast Enhancement 11

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A High-Performance Infrared Imaging System with Adaptive Con...

11th International Conference on Electronics, Communications and Networks, CECNet 2021

作者： Deng, Feng Su, Zhong Wang, Rui Liu, Jun Wang, Yanzhi Beijing Key Laboratory of High Dynamic Navigation Technology Beijing Information Science and Technology University Beijing China State Key Laboratory of Nickel and Cobalt Resources Comprehensive Utilization Jinchang China Robotics Institute School of Computer Science Carnegie Mellon University PittsburghPA United States Department of Electrical and Computer Engineering College of Engineering Northeastern University BostonMA United States

ISBN: (纸本)9781643682402

Most of the existing infrared imaging systems employ the scheme of FPGA/FPGA+DSP with numerous peripheral circuits, which leads to complex hardware architecture, limited system versatility, and low computing performance. It has become an intriguing technical problem worldwide to simplify the system structure while improving the imaging performance. In this paper, we present a novel real-time infrared imaging system based on the Rockchip's RV1108 visual processing SoC (system on chip). Moreover, to address the problem of low contrast and dim details in infrared images with a high dynamic range, an adaptive contrast enhancement method based on bilateral filter is proposed and implemented on the system. First, the infrared image is divided into a base layer and a detail layer through bilateral filter, then the base layer is compressed by an adaptive bi-plateau histogram equalization algorithm, and finally a linear-weighted method is used to integrate the detail layer to obtain the image with enhanced details. The experimental results indicate that compared with traditional algorithms, our method can effectively improve the overall contrast of the image, while effectively retaining the image details without noise magnification. For an image of 320*240 pixels, the real-time processing rate of the system is 68 frames/s. The system has the characteristics of simplified structure, perceptive image details, and high computing performance. © 2022 The authors and IOS Press.

关键词： System-on-chip

PIFON-EPT: MR-Based electrical Property Tomography Using Physics-Informed Fourier Networks

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arXiv 2023年

作者： Yu, Xinling Serralles, Jose E.C. Giannakopoulos, Ilias I. Liu, Ziyue Daniel, Luca Lattanzi, Riccardo Zhang, Zheng Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Research Laboratory of Electronics Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Bernard and Irene Schwartz Center for Biomedical Imaging Department of Radiology New York University Grossman School of Medicine NY10016 United States Bernard and Irene Schwartz Center for Biomedical Imaging Department of Radiology New York University Grossman School of Medicine NY10016 United States Department of Computer Science University of California Santa BarbaraCA93106 United States

We propose Physics-Informed Fourier Networks for electrical Properties (EP) Tomography (PIFON-EPT), a novel deep learning-based method for EP reconstruction using noisy and/or incomplete magnetic resonance (MR) measurements. Our approach leverages the Helmholtz equation to constrain two networks, responsible for the denoising and completion of the transmit fields, and the estimation of the object's EP, respectively. We embed a random Fourier features mapping into our networks to enable efficient learning of high-frequency details encoded in the transmit fields. We demonstrated the efficacy of PIFONEPT through several simulated experiments at 3 and 7 tesla (T) MR imaging, and showed that our method can reconstruct physically consistent EP and transmit fields. Specifically, when only 20% of the noisy measured fields were used as inputs, PIFON-EPT reconstructed the EP of a phantom with ≤ 5% error, and denoised and completed the measurements with ≤ 1% error. Additionally, we adapted PIFON-EPT to solve the generalized Helmholtz equation that accounts for gradients of EP between inhomogeneities. This yielded improved results at interfaces between different materials without explicit knowledge of boundary conditions. PIFON-EPT is the first method that can simultaneously reconstruct EP and transmit fields from incomplete noisy MR measurements, providing new opportunities for EPT research. © 2023, CC BY-NC-SA.

关键词： Magnetic resonance imaging

A Tutorial on Six-Dimensional Movable Antenna Enhanced Wireless Networks: Synergizing Positionable and Rotatable Antennas

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arXiv 2025年

作者： Shao, Xiaodan Mei, Weidong You, Changsheng Wu, Qingqing Zheng, Beixiong Wang, Cheng-Xiang Li, Junling Zhang, Rui Schober, Robert Zhu, Lipeng Zhuang, Weihua Shen, Xuemin Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Chengdu611731 China Shenzhen518055 China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China School of Microelectronics South China University of Technology Guangzhou511442 China National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing211189 China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen518172 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Erlangen91054 Germany

Six-dimensional movable antenna (6DMA) is a new and revolutionary technique that fully exploits the wireless channel spatial variations at the transmitter/receiver by flexibly adjusting the three-dimensional (3D) positions and/or 3D rotations of antennas/antenna surfaces (sub-arrays), thereby improving the performance of wireless networks cost-effectively without the need to deploy additional antennas. It is thus expected that the integration of new 6DMAs into future sixth-generation (6G) wireless networks will fundamentally enhance antenna agility and adaptability, and introduce new degrees of freedom (DoFs) for system design. Despite its great potential, 6DMA faces new challenges to be efficiently implemented in wireless networks, including corresponding architectures, antenna position and rotation optimization, channel estimation, and system design from both communication and sensing perspectives. In this paper, we provide a tutorial on 6DMA-enhanced wireless networks to address the above issues by unveiling associated new channel models, hardware implementations and practical position/rotation constraints, as well as various appealing applications in wireless networks. Moreover, we discuss two special cases of 6DMA, namely, rotatable 6DMA with fixed antenna position and positionable 6DMA with fixed antenna rotation, and highlight their respective design challenges and applications. We further present prototypes developed for 6DMA-enhanced communication along with experimental results obtained with these prototypes. Finally, we outline promising directions for further investigation. Copyright © 2025, The Authors. All rights reserved.

关键词： Channel estimation

Open-Vocabulary Audio-Visual Semantic Segmentation

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arXiv 2024年

作者： Guo, Ruohao Qu, Liao Niu, Dantong Qi, Yanyu Yue, Wenzhen Shi, Ji Xing, Bowei Ying, Xianghua National Key Laboratory of General Artificial Intelligence School of Intelligence Science and Technology Peking University Beijing China Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA United States Berkeley AI Research University of California Berkeley BerkeleyCA United States College of Information and Electrical Engineering China Agricultural University Beijing China

Audio-visual semantic segmentation (AVSS) aims to segment and classify sounding objects in videos with acoustic cues. However, most approaches operate on the close-set assumption and only identify pre-defined categories from training data, lacking the generalization ability to detect novel categories in practical applications. In this paper, we introduce a new task: open-vocabulary audio-visual semantic segmentation, extending AVSS task to open-world scenarios beyond the annotated label space. This is a more challenging task that requires recognizing all categories, even those that have never been seen nor heard during training. Moreover, we propose the first open-vocabulary AVSS framework, OV-AVSS, which mainly consists of two parts: 1) a universal sound source localization module to perform audio-visual fusion and locate all potential sounding objects and 2) an open-vocabulary classification module to predict categories with the help of the prior knowledge from large-scale pre-trained vision-language models. To properly evaluate the open-vocabulary AVSS, we split zero-shot training and testing subsets based on the AVSBench-semantic benchmark, namely AVSBench-OV. Extensive experiments demonstrate the strong segmentation and zero-shot generalization ability of our model on all categories. On the AVSBench-OV dataset, OV-AVSS achieves 55.43% mIoU on base categories and 29.14% mIoU on novel categories, exceeding the state-of-the-art zero-shot method by 41.88%/20.61% and open-vocabulary method by 10.2%/11.6%. The code is available at https://***/ruohaoguo/ovavss. © 2024, CC BY-NC-SA.

关键词： Semantic Segmentation

Real-time 3D human pose estimation without skeletal a priori structures

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Image and Vision Computing 2023年 132卷

作者： Bai, Guihu Luo, Yanmin Pan, Xueliang Wang, Jia Guo, Jing-Ming College of Computer Science and Technology Huaqiao University 668 Jimei Avenue Jimei District Fujian Xiamen361021 China Key Laboratory for Computer Vision and Pattern Recognition Huaqiao University 668 Jimei Avenue Jimei District Fujian Xiamen361021 China The Department of Electrical Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan

This study is about real-time 2D-3D human pose estimation without using the a priori structure of the skeleton and with a low number of parameters for regression tasks. Current graph convolution-based 3D human pose tasks require structural knowledge of the skeleton, which limits the exploration of pose estimation for unknown structures. Inspired by tyre rotation and circular convolution, weights rotation is used to fully learn the potential connections between the human joints. We refer to this process as the weight cyclic sharing mechanism, a novel method for updating features. It does not require knowledge of the structure of the human skeleton and learns different constraints between joints with a low number of parameters. We propose an end-to-end weight circular sharing network (WCirSNet) based on the weight circular sharing mechanism. We propose a simple and efficient weighted residual block in this WCirSNet. The superiorities of the weight circular sharing mechanism and weighted residual block were verified by abundant ablation studies. Extensive evaluations on two challenging benchmark datasets (Human 3.6 M, MPI-INF-3DHP) show that the performance and generalization capabilities of our framework are superior to the results of many previously advanced methods. © 2023 Elsevier B.V.

关键词： Benchmarking

Broadband nonvolatile electrically programmable silicon photonic switches

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arXiv 2022年

作者： Chen, Rui Fang, Zhuoran Fröch, Johannes E. Xu, Peipeng Zheng, Jiajiu Majumdar, Arka Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States Faculty of Electrical Engineering and Computer Science Key Laboratory of Photoelectric Materials and Devices of Zhejiang Province Ningbo University Ningbo315211 China Department of Physics University of Washington SeattleWA98195 United States

Programmable photonic integrated circuits (PICs) have recently gained significant interest due to their potential in creating next-generation technologies ranging from artificial neural networks and microwave photonics to quantum information processing. The fundamental building block of such programmable PICs is a tunable 2 × 2 switch, traditionally controlled by the thermo-optic or free-carrier dispersion. Yet, these implementations are power-hungry, volatile, and have a large footprint (typically > 100 µm). Therefore, a truly 'set-and-forget' type 2 × 2 switch with zero static power consumption is highly desirable for large-scale PICs. Here, we report a broadband nonvolatile electrically programmable 2 × 2 silicon photonic switch based on the phase-change material Ge2Sb2Te5. The directional coupler switch exhibits a compact coupling length (64 µm), small insertion loss ( © 2022, CC BY.

关键词： Photonic devices