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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yawei Li Kai Zhang Jiezhang Cao Radu Timofte Michele Magno Luca Benini Luc Van Goo Computer Vision Lab D-ITET ETH Zurich Switzerland Center for Artificial Intelligence and Data Science (CAIDAS) University of Wurzburg Germany Center for Project-Based Learning D-ITET ETH Zurich Switzerland Integrated Systems Laboratory D-ITET ETH Zurich Switzerland Department of Electrical Electronic and Information Engineering University of Bologna Italy Processing Speech and Images (PSI) KU Leuven Belgium

The aim of this paper is to study the influence of locality mechanisms in vision transformers. Transformers originated from machine translation and are particularly good at modelling long-range dependencies within a long sequence. Although the global interaction between the token embeddings could be well modelled by the self-attention mechanism of transformers, what is lacking is a locality mechanism for infor-mation exchange within a local region. In this paper, locality mechanism is systematically investigated by carefully designed controlled experiments. We add locality to vision transformers into the feed-forward network. This seemingly simple solution is inspired by the comparison between feed-forward networks and inverted residual blocks. The importance of locality mechanisms is validated in two ways: 1) A wide range of design choices (activation function, layer placement, expansion ratio) are available for incorporating locality mechanisms and proper choices can lead to a performance gain over the baseline, and 2) The same locality mechanism is successfully applied to vision transformers with different architecture designs, which shows the generalization of the locality concept. For ImageNet2012 classification, the locality-enhanced transformers outperform the baselines Swin-T [1], DeiT-T [2] and PVT-T [3] by 1.0%, 2.6 % and 3.1 % with a negligible increase in the number of parameters and computational effort. Code is available at https://***/ofsoundof/LocalViT.

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Migration Enhanced Epitaxy of GaAs Studied by Reflection High Energy Electron Diffraction and Scanning Tunneling Microscopy

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MRS Online Proceedings Library 2020年第1期312卷 339-344页

作者： Mignming Fu D. L. Miller J. Kim M. C. Gallagher R. F. Willis Department of Physics The Pennsylvania State University University Park USA Department of Electrical & Computer Engineering Electronic Materials and Processing Research Laboratory USA

Migration enhanced epitaxy (MEE) of GaAs on (001) GaAs substrates was studied by reflection high energy electron diffraction (RHEED) and scanning tunneling microscopy (STM). In MEE, Ga and As species are alternately deposited on the growing surface. Ga adatom migration can be enhanced by the low arsenic pressure environment The STM study was performed ex-situ by the arsenic capping and decapping procedure. We have demonstrated the correlation between the peak RHEED specular intensity during MEE growth and the variation of the lateral step density on the surface, even though the surface stoichiometry changes repetitively during MEE. The peak RHEED intensity during MEE is inversely dependent on the surface step density. The MEE surface exhibited a lower step density than the MBE surface, as shown by both RHEED and STM. However, the MEE surface still exhibited a much higher step density than a well-annealed surface. Consequently we believe that to achieve an atomically flat interface, annealing at high temperature in an arsenic flux is still necessary even if MEE is employed.

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Energy Management for Zones-Based Isolated DC Multi-microgrids 3rd

Energy Management for Zones-Based Isolated DC Multi-microgri...

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3rd EAI International Conference on Smart Grid and Internet of Things, SGIoT 2019

作者： Nawaz, Arshad Wu, Jing Long, Chengnian Lin, Yi Bing Department of Automation School of Electronic Information and Electrical Engineering Key Laboratory of System Control and Information Processing Ministry of China Shanghai Jiao Tong University Shanghai China Department of Computer Science and Information Engineering National Chiao Tung University Hsinchu300 Taiwan

ISBN: (纸本)9783030496098

In this paper, zones based distributed energy management for isolated multi-microgrids is proposed. Loads are categorized into different zones to form zonal multi-microgrids. Each microgrid has own energy management system which can locally manages the supply and demand of its zonal load and minimize the operational cost. Distributed Network Operator (DNO) act as central controller to facilitate the energy exchange between zonal microgrids and balancing the overall system-wide supply and demand in economic way. Demand Response Program (DRP) is also utilized for peak load shifting within the scheduling horizon. In addition to minimization of operation cost, the utilization of DR will also assure the reliability of supply. In the proposed distributed energy management, each microgrid balances its supply and demand locally and exchange surplus and deficit power with other microgrids through DNO. The performance of proposed scheme is demonstrated through case study simulation of radial multi-microgrid structure. © 2020, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Energy management

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TomoSAR-ALISTA: Efficient TomoSAR imaging via deep unfolded network

TomoSAR-ALISTA: Efficient TomoSAR imaging via deep unfolded ...

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International Conference on Radar Systems (RADAR 2022)

作者： M. Wang Z. Zhang Y. Wang S. Gao X. Qiu Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing 100190 People's Republic of China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou 215123 People's Republic of China Electrical and Computer Engineering Department George Mason University Fairfax VA 22030 USA

ISBN: (数字)9781839537776

Synthetic aperture radar (SAR) tomography (TomoSAR) has attracted remarkable interest for its ability in achieving threedimensional reconstruction along the elevation direction from multiple observations. In recent years, compressed sensing (CS) technique has been introduced into TomoSAR considering for its super-resolution ability with limited samples. Whereas, the CS-based methods suffer from several drawbacks, including weak noise resistance, high computational complexity and complex parameter fine-tuning. Among the different CS algorithms, iterative soft-thresholding algorithm (ISTA) is widely used as a robust reconstruction approach, however, the parameters in the ISTA are manually chosen, which usually requires a time-consuming fine-tuning process to achieve the best performance. Aiming at efficient TomoSAR imaging, a novel sparse unfolding network named analytic learned ISTA (ALISTA) is proposed towards the TomoSAR imaging problem in this paper, and the key parameters of ISTA are learned from training data via deep learning to avoid complex parameter fine-tuning and significantly relieves the training burden. In addition, experiments verify that it is feasible to use traditional CS algorithms as training labels, which provides a tangible supervised training method to achieve better 3D reconstruction performance even in the absence of labeled data in real applications.

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Recent advances in photonics of threedimensional Dirac semimetal Cd_(3)As_(2)

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Advanced Photonics Nexus 2022年第2期1卷 1-19页

作者： Renlong Zhou Kaleem Ullah Naveed Hussain Mohammed M.Fadhali Sa Yang Qiawu Lin Muhammad Zubair Muhammad Faisal Iqbal Guangdong University of Education School of Physics and Information EngineeringGuangzhouChina University of Delaware Department of Electrical and Computer EngineeringNewarkDelawareUnited States University of California Department of Electrical Engineering and Computer ScienceIrvineCaliforniaUnited States Jazan University Faculty of ScienceDepartment of PhysicsJazanSaudi Arabia Ibb University Faculty of ScienceDepartment of PhysicsIbbYemen Institute of Energy and Climate Research Materials Synthesis and Processing(IEK-1)Forschungszentrum Jülich GmbHJülichGermany University of Science and Technology of China Hefei National Laboratory for Physical Sciences at the MicroscaleHefeiChina Riphah International University Faisalabad Department of PhysicsFaisalabadPakistan

Due to their unusual features in condensed matter physics and their applicability in optical and optoelectronic applications,three-dimensional Dirac semimetals(3D DSMs)have garnered substantial interest in recent *** contrast to monolayer graphene,3D DSM exhibits linear band dispersion despite its macroscopic ***,being a bulk material,it is easy to make nanostructures with 3D DSM,just as one normally does with metals such as gold and *** 3D DSMs,cadmium arsenide(Cd_(3)As_(2))is quite famous and considered an excellent 3D DSM due to its chemical stability in air and extraordinary optical *** this review,advances in 3D DSM Cd_(3)As_(2)fabrication techniques and recent progress in the photonics of 3D DSM Cd_(3)As_(2)are given and briefly *** photonic features,including linear and nonlinear plasmonics,optical absorption,optical harmonic generation,and ultrafast dynamics,have been explored in *** is expected that Cd_(3)As_(2)would share an excellent tunable photonic response like *** envision that this article may serve as a concise overview of the recent progress of photonics in 3D DSM Cd_(3)As_(2)and provides a compact reference for young researchers.

关键词： Three-dimensional Dirac semimetal Cd_(3)As_(2) photonics tunable nanostructures

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A Pricing Rule for Third-Party Platoon Coordination Service Provider

A Pricing Rule for Third-Party Platoon Coordination Service ...

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Asian Control Conference

作者： Ting Bai Alexander Johansson Shaoyuan Li Karl Henrik Johansson Jonas Må rtensson Integrated Transport Research Lab Digital Futures and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China

We model a platooning system including trucks and a third-party service provider that performs platoon coordination, distributes the platooning profit within platoons, and charges the trucks in exchange for its services. This paper studies one class of pricing rules, where the third-party service provider keeps part of the platooning profit each time a platoon is formed. Furthermore, we propose a platoon coordination solution based on distributed model predictive control in which the pricing rule is integrated. To evaluate the effect of the pricing on the platooning system, we perform a simulation over the Swedish road network. The simulation shows that the platooning rate and profit highly depend on the pricing. This suggests that pricing needs to be set carefully to obtain a satisfactory platooning system in the future.

关键词： Roads Pricing Predictive control

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Mechanically reprogrammable Pancharatnam-Berry metasurface for microwaves

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Advanced Photonics 2022年第1期4卷 69-79页

作者： Quan Xu Xiaoqiang Su Xueqian Zhang Lijuan Dong Lifeng Liu Yunlong Shi Qiu Wang Ming Kang Andrea Alù Shuang Zhang Jiaguang Han Weili Zhang Tianjin University Center for Terahertz Waves and College of Precision Instrument and Optoelectronics EngineeringKey Laboratory of Optoelectronic Information Technology(Ministry of Education of China)TianjinChina Shanxi Datong University Institute of Solid State Physics and College of Physics and Electronic ScienceShanxi Province Key Laboratory of Microstructure Electromagnetic Functional MaterialsDatongChina Wuhan University of Technology School of Information EngineeringWuhanChina Tianjin Normal University College of Physics and Materials ScienceTianjinChina City University of New York Advanced Science Research CenterPhotonics InitiativeNew YorkUnited States City University of New York Graduate CenterPhysics ProgramNew YorkUnited States University of Hong Kong Faculty of ScienceDepartment of PhysicsHong KongChina University of Hong Kong Department of Electrical and Electronic EngineeringHong KongChina Guilin University of Electronic Technology Guangxi Key Laboratory of Optoelectronic Information ProcessingSchool of Optoelectronic EngineeringGuilinChina Oklahoma State University School of Electrical and Computer EngineeringStillwaterOklahomaUnited States

Metasurfaces have enabled the realization of several optical functionalities over an ultrathin platform,fostering the exciting field of flat *** metasurfaces are achieved by arranging a layout of static meta-atoms to imprint a desired operation on the impinging wavefront,but their functionality cannot be *** and programmability of metasurfaces are the next important step to broaden their impact,adding customized on-demand functionality in which each meta-atom can be individually *** demonstrate a mechanical metasurface platform with controllable rotation at the meta-atom level,which can implement continuous Pancharatnam–Berry phase control of circularly polarized *** the proof-of-concept experiments,we demonstrate metalensing,focused vortex beam generation,and holographic imaging in the same metasurface template,exhibiting versatility and superior *** dynamic control of electromagnetic waves using a single,low-cost metasurface paves an avenue towards practical applications,driving the field of reprogrammable intelligent metasurfaces for a variety of applications.

关键词： reprogrammable metasurfaces Pancharatnam-Berry phase mechanical metasurfaces microwaves

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Multi-Slot Distributed Measurement Selection: A Sparsity Learning Approach

Multi-Slot Distributed Measurement Selection: A Sparsity Lea...

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作者： Xia, Qian Wang, Wei Ran, Rong Gong, Yi Zhang, Zhaoyang College of Information Science and Electronic Engineering Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking Zhejiang University Hangzhou310027 China School of Electrical and Computer Engineering Ajou University Suwon16499 Korea Republic of Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China

When only a part of measurements are collected sequentially in large-scale Internet of Things (IoT) networks, it is motivated to extract significant information from the collected data for utilizing the communication resources over incoming slots more efficiently. In this article, we study the successive measurement selection problem for sparse parameter estimation and its distributed implementation in large-scale networks. Specifically, we transform the intractable multi-slot measurement selection problem into per-slot subproblems, and in each slot we select the uncollected measurements that are more 'useful' for parameter estimation based on sparse Bayesian learning. In order to deal with the combinatorial problem with distributed implementation, we relax the subproblem and propose an enhanced subgradient method to solve the Boolean constraint. The proposed distributed scheme needs only a common information broadcast by the centralized controller, where the communication overheads only depend on the number of sparse active sources rather than the number of sensors which is always huge. Simulation results demonstrate the performance gain of our proposed measurement selection method compared to the conventional schemes. When the total communication overheads are limited with the network scale, our scheme presents extreme practicability and applicability for the large-scale networks. © 2015 IEEE.

关键词： Wireless sensor networks

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Asymmetry Total Variation and Framelet Regularized Nonconvex Low-Rank Tensor Completion

SSRN

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SSRN 2022年

作者： Chen, Yongyong Zhao, Xiaojia Xu, Tingting Zeng, Haijin Xu, Yanhui Chen, Junxing The School of Computer Science and Technology Harbin Institute of Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies Shenzhen518055 China Image Processing and Interpretation Imec Research Group Ghent University Belgium Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China The College of Medicine and Biological Information Engineering Northeastern University Shenyang110004 China

The low-rank tensor representation has shown enormous potential and advantages in diverse applications. However, (1) due to the inherent limitations of the low-rank tensor model, the tensor nuclear norm is utilized yet as a biased estimate of the tensor rank, which limits the image recovery performance. (2) most current low-rank approximation-based methods focus on the preservation of global information, while ignoring the local details preservation such as the spatial piece-wise smoothness and sharp edges. To overcome he above obstacles, we propose a novel asymmetry three-dimensional total variation and framelet regularized nonconvex low-rank tensor completion (ATV-FNTC) model, which integrates the nonconvex penalty function and asymmetric three-dimensional total variation into one unified model. Specifically, ATV-FNTC introduces one nonconvex penalty function as a tighter regularizer to approximate the tensor rank. Different from existing methods, the asymmetric three-dimensional total variation regularization is developed to achieve more accurate recovery of detailed information and flexibly control the smoothing strength of different dimensions of tensor data. Furthermore, we design an iterative algorithm to solve the nonconvex ATV-FNTC model by the alternating direction methods of multipliers. Experimental results reveal the superiority of the proposed method compared with several state-of-the-art methods when handling different completion tasks. © 2022, The Authors. All rights reserved.

关键词： Tensors

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Correction to: Multi-level context-driven interaction modeling for human future trajectory prediction

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Neural Computing and Applications 2023年第27期35卷 20441-20441页

作者： He, Zhiquan Sun, Hao Cao, Wenming He, Henry Z. Guangdong Multimedia Information Service Engineering Technology Research Center Shenzhen University Shenzhen China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen China Video Processing and Communication Laboratory Department of Electrical and Computer Engineering University of Missouri Columbia USA

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