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arXiv 2020年

作者： Guo, Yunfan Lin, Yuxuan Xie, Kaichen Yuan, Biao Zhu, Jiadi Shen, Pin-Chun Lu, Ang-Yu Su, Cong Shi, Enzheng Zhang, Kunyan Cai, Zhengyang Park, Jihoon Ji, Qingqing Wang, Jiangtao Dai, Xiaochuan Tian, Xuezeng Huang, Shengxi Dou, Letian Li, Ju Yu, Yi Idrobo, Juan-Carlos Cao, Ting Palacios, Tomás Kong, Jing Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science & Engineering University of Washington SeattleWA98195 United States School of Physical Science and Technology ShanghaiTech University Shanghai201210 China Department of Nuclear and Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Davidson School of Chemical Engineering Purdue University West LafayetteIN47907 United States Department of Electrical Engineering The Pennsylvania State University University ParkPA16802 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States

Manipulating materials with atomic-scale precision is essential for the development of next-generation material design toolbox1-3. Tremendous efforts have been made to advance the compositional4,5, structural6,7 and spatial accuracy of material deposition and patterning, including molecular beam epitaxy8, atomic-layer deposition/etching9, electron-beam lithography (EBL)10, etc. The family of two-dimensional (2D) materials provides an ideal platform to realize atomic-level material architectures11-13. The wide and rich physics of these materials have led to fabrication of heterostructures14-18, superlattices19-21, and twisted structures22-24 with breakthrough discoveries and applications. Here, we report a novel atomic-scale material design tool that selectively breaks and forms chemical bonds of 2D materials at room temperature, called atomic-layer substitution (ALS), through which we can substitute the top layer chalcogen atoms within the three-atom-thick transition-metal dichalcogenides (TMDs) using arbitrary patterns. Flipping the layer via transfer allows us to perform the same procedure on the other side, yielding programmable in-plane multiheterostructures with different out-of-plane crystal symmetry and electric polarization. First-principle calculations elucidate how the ALS process is overall exothermic in energy and only has a small reaction barrier, facilitating the reaction to occur at room temperature. Optical characterizations confirm the fidelity of this design approach, while transmission electron microscopy shows the direct evidence of Janus structure and suggests the atomic transition at the interface of designed heterostructure. Finally, transport and Kelvin probe measurements on MoXY (X, Y = S or Se;X and Y corresponding to the bottom and top layers) lateral multi-heterostructures reveal the surface potential and dipole orientation of each region, and the barrier height between them. Our approach for designing artificial 2D landscape down to a si

关键词： Atoms

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Compressive sampling for array cameras

arXiv

引用

arXiv 2019年

作者： Yan, Xuefei Brady, David J. Wang, Jianqiang Huang, Chao Li, Zian Yan, Songsong Liu, Di May, Zhan Camputer Laboratory Kunshan China Department of Electrical and Computer Engineering Duke University Durham United States Nanjing University School of Electronic Science and Engineering Nanjing China Camputer Laboratory Kunshan China

While design of high performance lenses and image sensors has long been the focus of camera development, the size, weight and power of image data processing components is currently the primary barrier to radical improvements in camera resolution. Here we show that Deep-Learning-Aided Compressive Sampling (DLACS) can reduce operating power on camera-head electronics by 20x. Traditional compressive sampling has to date been primarily applied in the physical sensor layer, we show here that with aid from deep learning algorithms, compressive sampling offers unique power management advantages in digital layer compression. Copyright © 2019, The Authors. All rights reserved.

关键词： Compressed sensing

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Image Fusion via Domain and Feature Transfer

Image Fusion via Domain and Feature Transfer

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Yicheng Yang Huabing Zhou Wei Zhang Changcai Yang Zhenghong Yu Computer Science and Engineering School Hubei Provincial Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China College of Computer and Information Sciences College of Mechanical and Electrical Engineering Fujian Agriculture and Forestry University FuZhou China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

The infrared and visible images fusion technique is designed to simultaneously preserve the thermal radiation information of the infrared image and the detailed texture information of the visible image. Therefore, the fused image with rich detail information and a clear target area in order to find it more efficiently. Inspired by the powerful GANs technology in recent years, we proposed a novel method for fusing infrared and visible images that based on domain and feature transfer. First, it is designated as an optimization problem with a latent encoding which can be mapped into a pixel intensity consistent image on the latent image. We employ generative adversarial network, which can capture content characteristics of one image dataset and figure out how these characteristics could be translated into the domain of another image dataset, to transfer the appearance of an image from visible image to infrared one. And then we use the feature consistent constrains to enhance the features of the fused image. Moreover, by adding gradient constraints to preserve the details of visible image, therefore we combine the fused image with a similar gradient to the visible image. Qualitative and quantitative comparisons on public datasets demonstrate our proposed method is superior to the state-of-the-art technology. The fused image we have generated is more like a high-resolution enhanced infrared image, which is more efficient for discovering the target and tracking.

关键词： Image fusion Generative adversarial networks Feature extraction Gallium nitride Imaging Convolutional neural networks Manifolds

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Near-field manipulation of terahertz surface waves by metasurfaces [Invited]

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Chinese Optics Letters 2018年第5期16卷 2-6页

作者： Quan Xu Xueqian Zhang Yuehong Xu Chunmei Ouyang Yanfeng Li Jiaguang Han Weili Zhang Center for Terahertz Waves and College of Precision Instrument and Optoelectronics Engineering Key Laboratory of Opto-electronics Information and Technical Science Ministry of Education Tianjin University Tianjin 300072 China School of Electrical and Computer Engineering Oklahoma State University Stillwater Oklahoma 71078 USA

Surface waves（SWs） are a special form of electromagnetic waves that travel along the boundary between a metal and a dielectric. The special optical properties of SWs render them very attractive in applications, such as subdiffractional lithography, novel biochemical sensors, and ultrafast integrated circuitries. Herein, we present a review of our recent progress in excitation and manipulation of terahertz SWs due to interference or coupling between a pair of slit resonators in metasurfaces, showing the ability to devise ultrathin and compact plasmonic components.

关键词： SW Near-field manipulation of terahertz surface waves by metasurfaces

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Malicious behaviour identification for android based on an RBF neural network

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International Journal of Security and Networks 2020年第3期15卷 148-154页

作者： Chen, Tianwei Qiang, Yongjun Tang, Chunming Wang, Zairong Luo, Ping Peng, Lingxi School of Information Engineering Urban Vocational College of Sichuan Chengdu610110 China Information and Network Management Office Sichuan Normal University Chengdu610068 China College of Mathematics Guangzhou University Guangzhou510006 China Data Recovery Key Laboratory of Sichuan Province School of Computer Science Neijiang Normal University Sichuan641100 China College of Economics and Statistics Guangzhou University Guangzhou510006 China College of Mechanical and Electrical Engineering Guangzhou University Guangzhou510006 China

A malicious behaviour identification approach for Android that is inspired by radial basis function neural networks is proposed. First, this method takes samples of the malicious behaviour on Android, extracts behaviour features, and integrates data, enabling the use of a radial basis function neural network for identification. Second, the characteristics of the radial basis function neural network's local approximation are used to improve the learning speed, which enhances the quality of the output result. Next, the sum of squares of the distance from each sample in all feature sets to the centre of feature sets is obtained by the k-means clustering algorithm;the minimum value of the distance is used to calculate the weights of the hidden layer node to the output layer node with the least squares recursive method. Further, when the radial basis function neural network training is completed, accurate identification of the malicious behaviour is realised. Finally, the experimental results fully demonstrate that our method improves the accuracy and efficiency of malicious behaviour recognition for Android. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Behavioral research

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Coverage analysis of integrated Sub-6GHz-mmWave cellular networks with hotspots

arXiv

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arXiv 2019年

作者： Shi, Minwei Yang, Kai Han, Zhu Niyato, Dusit School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Fractional Signals and Systems Beijing China Department of Electrical and Computer Engineering University of Houston Houston United States Department of Computer Science and Engineering Kyung Hee University Seoul Korea Republic of School of Computer Science and Engineering Nanyang Technological University Singapore Singapore

Deploying Sub-6GHz networks together with millimeter wave (mmWave) is a promising solution to achieve high data rates in traffic hotspots while guaranteeing sufficient coverage, where mmWave small cells are densely deployed to provide high quality of service. In this paper, we propose an analytical framework to investigate the integrated Sub-6GHz-mmWave cellular networks, in which the Sub-6GHz base stations (BSs) are modeled as a Poisson point process, and the mmWave BSs are clustered following a Poisson cluster process in traffic hotspots. We conduct stochastic geometry-based analysis and derive the performance metrics including the association probability, signal-to-interference-plus-noise ratio coverage probability and average achievable rate, which are validated to be accurate by Monte Carlo simulations. We analyze the impact of various deployment parameters on the network performance to give insights on the network design. In particular, it is shown that deploying mmWave small cells in traffic hotspots will outperform both traditional Sub-6GHz heterogeneous network and isolated mmWave system in terms of the coverage probability. It can also be shown that extremely high and extremely small association weight for mmWave BSs will deteriorate the performance for cell edge users and cell interior users, respectively. Moreover, there exists an optimal pre-decided dispersion parameter of mmWave BSs that contributes to the maximum coverage probability. Copyright © 2019, The Authors. All rights reserved.

关键词： Heterogeneous networks

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Smart cameras

arXiv

引用

arXiv 2020年

作者： Brady, David Hu, Minghao Wang, Chengyu Yan, Xuefei Fang, Lu Zhu, Yinheng Tan, Yang Cheng, Ming Ma, Zhan Department of Electrical and Computer Engineering Duke University P.O. Box 90291 DurhamNC27705 Camputer Laboratory 1699 South Zuchongzhi RD. Kunshan Jiangsu215347 China Tsinghua-Berkeley Shenzhen Institute Tsinghua University Shenzhen Guangdong518055 China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu210009 China

We review camera architecture in the age of artificial intelligence. Modern cameras use physical components and software to capture, compress and display image data. Over the past 5 years, deep learning solutions have become superior to traditional algorithms for each of these functions. Deep learning enables 10-100x reduction in electrical sensor power per pixel, 10x improvement in depth of field and dynamic range and 10-100x improvement in image pixel count. Deep learning enables multiframe and multiaperture solutions that fundamentally shift the goals of physical camera design. Here we review the state of the art of deep learning in camera operations and consider the impact of AI on the physical design of cameras. Copyright © 2020, The Authors. All rights reserved.

关键词： Cameras

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Magnetic Control of Soft Chiral Phonons in PbTe

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Physical Review Letters 2022年第7期128卷 075901-075901页

作者： Andrey Baydin Felix G. G. Hernandez Martin Rodriguez-Vega Anderson K. Okazaki Fuyang Tay G. Timothy Noe, II Ikufumi Katayama Jun Takeda Hiroyuki Nojiri Paulo H. O. Rappl Eduardo Abramof Gregory A. Fiete Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Smalley-Curl Institute Rice University Houston Texas 77005 USA Instituto de Física Universidade de São Paulo São Paulo São Paulo 05508-090 Brazil Theoretical Division Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Laboratório Associado de Sensores e Materiais Instituto Nacional de Pesquisas Espaciais São José dos Campos São Paulo 12201-970 Brazil Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas 77005 USA Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama 240-8501 Japan Institute for Materials Research Tohoku University Sendai 980-8577 Japan Department of Physics Northeastern University Boston Massachusetts 02115 USA Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics and Astronomy Rice University Houston Texas 77005 USA Department of Material Science and NanoEngineering Rice University Houston Texas 77005 USA

PbTe crystals have a soft transverse optical phonon mode in the terahertz frequency range, which is known to efficiently decay into heat-carrying acoustic phonons, resulting in anomalously low thermal conductivity. Here, we studied this phonon via polarization-dependent terahertz spectroscopy. We observed softening of this mode with decreasing temperature, indicative of incipient ferroelectricity, which we explain through a model including strong anharmonicity with a quartic displacement term. In magnetic fields up to 25 T, the phonon mode splits into two modes with opposite handedness, exhibiting circular dichroism. Their frequencies display Zeeman splitting together with an overall diamagnetic shift with increasing magnetic field. Using a group-theoretical approach, we demonstrate that these observations are the result of magnetic field-induced morphic changes in the crystal symmetries through the Lorentz force exerted on the lattice ions. Thus, our Letter reveals a novel process of controlling phonon properties in a soft ionic lattice by a strong magnetic field.

关键词： Chirality Diamagnetism Magneto-dielectric effect Optical phonons Thermal conductivity Zeeman effect Terahertz time-domain spectroscopy

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Consensus Statement on Brillouin Light Scattering Microscopy of Biological Materials

arXiv

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arXiv 2024年

作者： Bouvet, Pierre Bevilacqua, Carlo Ambekar, Yogeshwari Antonacci, Giuseppe Au, Joshua Caponi, Silvia Chagnon-Lessard, Sophie Czarske, Juergen Dehoux, Thomas Fioretto, Daniele Fu, Yujian Guck, Jochen Hamann, Thorsten Heinemann, Dag Jähnke, Torsten Jean-Ruel, Hubert Kabakova, Irina Koski, Kristie Koukourakis, Nektarios Krause, David La Cavera, Salvatore Landes, Timm Li, Jinhao Margueritat, Jeremie Mattarelli, Maurizio Monaghan, Michael Overby, Darryl R. Perez-Cota, Fernando Pontecorvo, Emanuele Prevedel, Robert Ruocco, Giancarlo Sandercock, John Scarcelli, Giuliano Scarponi, Filippo Testi, Claudia Török, Peter Vovard, Lucie Weninger, Wolfgang Yakovlev, Vladislav Yun, Seok-Hyun Zhang, Jitao Palombo, Francesca Bilenca, Alberto Elsayad, Kareem Center for Anatomy and Cell Biology Medical University of Vienna Austria Cell Biology and Biophysics Unit European Molecular Biology Laboratory Germany Fischell Department of Bioengineering University of Maryland United States Specto Srl. Milan Italy Unità di Perugia Italy LightMachinery Inc. Canada Departement of Electronics Carleton University Canada TU Dresden Germany Cluster of Excellence Physics of Life TU Dresden Germany Competence Center for Biomedical Computational Laser Systems TU Dresden Germany Institut Lumière Matière UMR5306 Université Lyon 1 CNRS Université de Lyon France Dipartimento di Fisica e Geologia Università di Perugia Italy Max Planck Institute for the Science of Light Erlangen Germany Department of Biology Norwegian University of Science and Technology Trondheim Norway Hannover Centre for Optical Technologies Leibniz University Hannover Germany CellSense Technologies GmbH Berlin Germany School of Mathematical and Physical Sciences University of Technology Sydney Australia Department of Chemistry University of California Davis United States Optics & Photonics Group Faculty of Engineering University of Nottingham United Kingdom Discipline of Mechanical Manufacturing & Biomedical Engineering Trinity College Dublin Ireland Department of Bioengineering Imperial College London United Kingdom CREST Optics S.p.A. Rome Italy Heidelberg Germany Center for Life Nano- & Neuro-Science Istituto Italiano di Tecnologia Rome Italy The Table Stable Ltd. Mettmenstetten Switzerland School of Physical & Mathematical Sciences Nanyang Technological University Singapore Nanyang Technological University Singapore Institute for Digital Molecular Analytics & Sciences Nanyang Technological University Singapore Department of Biomedical Engineering Texas A&M University United States Department of Electrical and Computer Engineering Texas A&M University United States Department of Physics and Astronomy Texas A&M University United States Harvard Me

Brillouin Light Scattering (BLS) spectroscopy is a non-invasive, non-contact, label-free optical technique that can provide information on the mechanical properties of a material on the sub-micron scale. Over the last decade it has seen increased applications in the life sciences, driven by the observed significance of mechanical properties in biological processes, the realization of more sensitive BLS spectrometers and its extension to an imaging modality. As with other spectroscopic techniques, BLS measurements not only detect signals characteristic of the investigated sample, but also of the experimental apparatus, and can be significantly affected by measurement conditions. The aim of this consensus statement is to improve the comparability of BLS studies by providing reporting recommendations for the measured parameters and detailing common artifacts. Given that most BLS studies of biological matter are still at proof-of-concept stages and use different-often self-built-spectrometers, a consensus statement is particularly timely to assure unified advancement. © 2024, CC BY.

关键词： Brillouin scattering

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Spectral-energy efficiency trade-off-based beamforming design for MISO non-orthogonal multiple access systems

arXiv

引用

arXiv 2020年

作者： Al-Obiedollah, Haitham Cumanan, Kanapathippillai Thiyagalingam, Jeyarajan Tang, Jie Burr, Alister G. Ding, Zhiguo Dobre, Octavia A. Electrical Engineering Department Hashemite University Zarqa Jordan Department of Electronic Engineering University of York YorkYO10 5DD United Kingdom Scientific Computing Department of Rutherford Appleton Laboratory Science and Technology Facilities Council Harwell Campus Oxford United Kingdom School of Electronic and Information Engineering South China University of Technology Guangzhou China School of Electrical and Electronic Engineering University of Manchester Manchester United Kingdom Department of Electrical and Computer Engineering Memorial University St. JohnsNLA1B 3X5 Canada

Energy efficiency (EE) and spectral efficiency (SE) are two of the key performance metrics in future wireless networks, covering both design and operational requirements. For previous conventional resource allocation techniques, these two performance metrics have been considered in isolation, resulting in severe performance degradation in either of these metrics. Motivated by this problem, in this paper, we propose a novel beamforming design that jointly considers the trade-off between the two performance metrics in a multiple-input single-output non-orthogonal multiple access system. In particular, we formulate a joint SE-EE based design as a multi-objective optimization (MOO) problem to achieve a good trade-off between the two performance metrics. However, this MOO problem is not mathematically tractable and, thus, it is difficult to determine a feasible solution due to the conflicting objectives, where both need to be simultaneously optimized. To overcome this issue, we exploit a priori articulation scheme combined with the weighted sum approach. Using this, we reformulate the original MOO problem as a conventional single objective optimization (SOO) problem. In doing so, we develop an iterative algorithm to solve this non-convex SOO problem using the sequential convex approximation technique. Simulation results are provided to demonstrate the advantages and effectiveness of the proposed approach over the available beamforming designs. Copyright © 2020, The Authors. All rights reserved.

关键词： Beamforming

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