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Real-time programmable metasurface for terahertz multifunctional wave front engineering

Light(science & Applications) 2023年第9期12卷 1795-1806页

作者： Feng Lan Luyang Wang Hongxin Zeng Shixiong Liang Tianyang Song Wenxin Liu Pinaki Mazumder Ziqiang Yang Yaxin Zhang Daniel M.Mittleman Sichuan THz Communication Technology Engineering Research Center School of Electronic Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengdu 611731China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313000China Zhangjiang Laboratory Shanghai 201204China National Key Laboratory of Solid-State Microwave Devices and Circuits Hebei Semiconductor Research InstituteShijiazhuang 050051China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China University of Chinese Academy of Sciences School of ElectronicElectrical and Communication EngineeringBeijing 101408China Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMI 48109USA School of Engineering Brown UniversityProvidenceRI 02912USA

Terahertz(THz)technologies have become a focus of research in recent years due to their prominent role in envisioned future communication and sensing *** of the key challenges facing the field is the need for tools to enable agile engineering of THz wave ***,we describe a reconfigurable metasurface based on GaN technology with an array-of-subarrays *** subwavelength-spaced array,under the control of a 1-bit digital coding sequence,can switch between an enormous range of possible configurations,providing facile access to nearly arbitrary wave front control for signals near 0.34 *** demonstrate wide-angle beam scanning with 1°of angular precision over 70 GHz of bandwidth,as well as the generation of multi-beam and diffuse wave fronts,with a switching speed up to 100 *** device,offering the ability to rapidly reconfigure a propagating wave front for beam-forming or diffusively scattered wide-angle coverage of a scene,will open new realms of possibilities in sensing,imaging,and networking.

关键词： wave scattered arbitrary

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Green Concerns in Federated Learning over 6G

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China Communications 2022年第3期19卷 50-69页

作者： Borui Zhao Qimei Cui Shengyuan Liang Jinli Zhai Yanzhao Hou Xueqing Huang Miao Pan Xiaofeng Tao National Engineering Laboratory for Mobile Network Technologies Beijing University of Posts and TelecommunicationsBeijing100876China Department of Computer Science New York Institute of TechnologyOld WestburyNY11568USA Department of Electrical and Computer Engineering University of HoustonHoustonTX77204USA

As Information,Communications,and Data technology(ICDT)are deeply integrated,the research of 6G gradually ***,federated learning(FL)as a distributed artificial intelligence(AI)framework is generally believed to be the most promising solution to achieve“Native AI”in *** the adoption of energy as a metric in AI and wireless networks is emerging,most studies still focused on obtaining high levels of accuracy,with little consideration on new features of future networks and their possible impact on energy *** address this issue,this article focuses on green concerns in FL over *** first analyze and summarize major energy consumption challenges caused by technical characteristics of FL and the dynamical heterogeneity of 6G networks,and model the energy consumption in FL over 6G from aspects of computation and *** classify and summarize the basic ways to reduce energy,and present several feasible green designs for FL-based 6G network architecture from three *** to the simulation results,we provide a useful guideline to researchers that different schemes should be used to achieve the minimum energy consumption at a reasonable cost of learning accuracy for different network scenarios and service requirements in FL-based 6G network.

关键词： 6G native AI federated learning radio access network green communications

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Nodes2STRNet for structural dense displacement recognition by deformable mesh model and motion representation

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International Journal of Mechanical system Dynamics 2023年第3期3卷 229-250页

作者： Jin Zhao Hui Li Yang Xu Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of TechnologyHarbinChina Key Lab of Structures Dynamics Behavior and Control of the Ministry of Education Harbin Institute of TechnologyHarbinChina School of Civil Engineering Harbin Institute of TechnologyHarbinChina Department of System Design and Simulation Goldwind Science and Technology Co.Ltd.BeijingChina

Displacement is a critical indicator for mechanical systems and civil *** vision-based displacement recognition methods mainly focus on the sparse identification of limited measurement points,and the motion representation of an entire structure is very *** study proposes a novel Nodes2STRNet for structural dense displacement recognition using a handful of structural control nodes based on a deformable structural three-dimensional mesh model,which consists of control node estimation subnetwork(NodesEstimate)and pose parameter recognition subnetwork(Nodes2PoseNet).NodesEstimate calculates the dense optical flow field based on FlowNet 2.0 and generates structural control node ***2PoseNet uses structural control node coordinates as input and regresses structural pose parameters by a multilayer perceptron.A self-supervised learning strategy is designed with a mean square error loss and L2 regularization to train *** effectiveness and accuracy of dense displacement recognition and robustness to light condition variations are validated by seismic shaking table tests of a four-story-building *** studies with image-segmentation-based Structure-PoseNet show that the proposed Nodes2STRNet can achieve higher accuracy and better robustness against light condition *** addition,NodesEstimate does not require retraining when faced with new scenarios,and Nodes2PoseNet has high self-supervised training efficiency with only a few control nodes instead of fully supervised pixel-level segmentation.

关键词： structural dense displacement recognition deformable structural mesh model deep-learning-based monocular vision self-supervised learning

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Adaptive energy-preserving algorithms for guiding center system

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Plasma science and technology 2023年第4期25卷 11-22页

作者：朱贝贝刘健张嘉炜祝爱卿唐贻发 Department of Applied Mathematics School of Mathematics and PhysicsUniversity of Science and Technology BeijingBeijing 100083Peopleʼs Republic of China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230026Peopleʼs Republic of China Advanced algorithm Joint Lab Shandong Computer Science CenterQilu University of TechnologyJinan 250014Peopleʼs Republic of China The State Key Laboratory of Scientific and Engineering Computing The Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190Peopleʼs Republic of China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049Peopleʼs Republic of China

We develop two types of adaptive energy preserving algorithms based on the averaged vector field for the guiding center dynamics,which plays a key role in magnetized *** adaptive scheme is applied to the Gauss Legendre’s quadrature rules and time stepsize respectively to overcome the energy drift problem in traditional energy-preserving *** new adaptive algorithms are second order,and their algebraic order is carefully *** results show that the global energy errors are bounded to the machine precision over long time using these adaptive algorithms without massive extra computation cost.

关键词： guiding center system energy-preserving methods adaptive energy conservation

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Autoencoder and Teaching-learning-based Optimizer for Mobile Edge Computing system Optimization Problems

Autoencoder and Teaching-learning-based Optimizer for Mobile...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Xu, Dian Zhou, Mengchu Yuan, Haitao Institute of Systems Engineering Macau University of Science and Technology Macao China New Jersey Institute of Technology Department of Electrical and Computer Engineering Newark United States School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (纸本)9798350337020

By using an autoencoder as a dimension reduction tool, an Autoencoder-embedded Teaching-Learning Based Optimization (ATLBO) has been proved to be effective in solving high-dimensional computationally expensive problems through several widely used function problems. However, the following two crucial issues have not been resolved, 1) ATLBO should be verified by solving real-life optimization problems;and 2) how autoencoder parameters and structures impact AEO's performance. In this work, ATLBO is verified by an energy consumption minimization problem (ECM) in mobile edge computing systems. To design an effective autoencoder for ATLBO, this work proposes a parameter tuning optimization strategy for autoencoders. By using the proposed Autoencoder Parameter Tuning (APT) strategy, ATLBO can enjoy higher robustness than those without it. The experimental results show that it is three to six times better than state-of-the-art methods in solving ECM. We consider the strategy-induced overhead and take the execution time as the primary criterion to evaluate them. In addition, the experimental results show that, against the conventional wisdom that higher-accuracy auto encoders bring higher system performance, lower-accuracy ones can actually assist ATLBO in locating the best solutions. This work promotes a novel application of autoencoders in optimization theory and practice. © 2023 IEEE.

关键词： autoencoder Autoencoder-embedded teaching-learning based optimization (ATLBO) High-dimensional expensive problems (HEPs) Mobile edge computing systems

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A Joint Scheme on Spectrum Sensing and Access with Partial Observation: A Multi-Agent Deep Reinforcement Learning Approach

A Joint Scheme on Spectrum Sensing and Access with Partial O...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Zhang, Yulong Li, Xuanheng Ding, Haichuan Fang, Yuguang Dalian University of Technology School of Information and Communication Engineering Dalian China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing China City University of Hong Kong Department of Computer Science Hong Kong

ISBN: (纸本)9798350345384

Dynamic spectrum access (DSA) has been regarded as a promising solution to mitigate the serious spectrum shortage problem in the 6G networks, in which secondary users (SUs) are allowed to opportunistically access the licensed bands when primary users (PUs) are inactive. Due to the hardware limitation, partial spectrum sensing with a suitable sensing window (SW) is considered as an effective way to find the idle bands to access. It is noteworthy that the SW selection could determine how many bands are available to access, and the network performance after the access could be used to guide the SW selection. Thus, a sophisticated joint design on both spectrum sensing and access is necessary, which, however, is not an easy task considering the uncertainty and dynamics of the spectrum environment, and also the mutual impacts among SUs. In this paper, we propose a joint partial spectrum sensing and power allocation (PA) scheme to help each SU make the best SW and PA decisions that can optimize the network throughput. To achieve the best decision under the dynamic and uncertain of the environment, considering the mutual interference issue, we develop a multi-agent deep reinforcement learning approach to enable each SU to obtain the best SW and PA decisions autonomously and adaptively. © 2023 IEEE.

关键词： Reinforcement learning

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Automation 5.0: The Key to systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

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Million-scale data integrated deep neural network for phonon properties of heuslers spanning the periodic table

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npj Computational Materials 2023年第1期9卷 2155-2166页

作者： Alejandro Rodriguez Changpeng Lin Hongao Yang Mohammed Al-Fahdi Chen Shen Kamal Choudhary Yong Zhao Jianjun Hu Bingyang Cao Hongbin Zhang Ming Hu Department of Mechanical Engineering University of South CarolinaColumbiaSC 29208USA Theory and Simulation of Materials(THEOS) École Polytechnique Fédérale de LausanneCH-1015 LausanneSwitzerland Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Engineering MechanicsTsinghua UniversityBeijing 100084China Institute of Materials Science Technical University of DarmstadtDarmstadt 64287Germany Materials Science and Engineering Division National Institute of Standards and TechnologyGaithersburgMD 20899USA Department of Computer Science and Engineering University of South CarolinaColumbiaSC 29208USA

Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-materialbasis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottleneckwith the developed Elemental Spatial Density Neural Network Force Field, namely Elemental-SDNNFF. The effectiveness andprecision of our Elemental-SDNNFF approach are demonstrated on 11,866 full, half, and quaternary Heusler structures spanning 55elements in the periodic table by prediction of complete phonon properties. Self-improvement schemes including active learningand data augmentation techniques provide an abundant 9.4 million atomic data for training. Deep insight into predicted ultralowlattice thermal conductivity (<1 Wm^(−1) K^(−1)) of 774 Heusler structures is gained by p–d orbital hybridization analysis. Additionally, aclass of two-band charge-2 Weyl points, referred to as “double Weyl points”, are found in 68% and 87% of 1662 half and 1550quaternary Heuslers, respectively.

关键词： properties phonon spanning

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Leidenfrost droplet billiard balls

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Physical Review Fluids 2024年第11期9卷 L111601-L111601页

作者： Yukai Lin Canjun Zhao Fuqiang Chu Xiaomin Wu Nenad Miljkovic Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Energy and Power Engineering Tsinghua University Beijing 100084 China School of Energy and Environmental Engineering University of Science and Technology Beijing Beijing 100083 China Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign Urbana Illinois 61801 USA Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana Illinois 61801 USA Materials Research Laboratory University of Illinois at Urbana-Champaign Urbana Illinois 61801 USA Institute for Sustainability Energy and Environment (iSEE) University of Illinois Urbana Illinois USA International Institute for Carbon Neutral Energy Research (WPI-I2CNER) Kyushu University 744 Moto-oka Nishi-ku Fukuoka 819-0395 Japan

We report the observation of two identical Leidenfrost droplets rebounding from each other after a head-on collision on a hot surface, resembling billiard ball collision. The observed phenomenon contradicts the established understanding that predicts the coalescence of two colliding Leidenfrost droplets. The collision dynamics of the Leidenfrost droplets is investigated using pressure and energy balance analysis at the macroscale, and a molecular interaction analysis at the nanoscale. The results suggest that droplet properties and the temperature of the hot surface determine the state of the gas film between the colliding droplets. Droplets with lower surface tension form thicker gas films, while lower surface temperatures mitigate the interaction of vapor molecules within the gas film, both facilitating droplet rebound after their collision. The discovered Leidenfrost droplet phenomenon is highly controllable, and has potential for a variety of applications, such as the selective chemical synthesis as explored in this work.

关键词： Drop & bubble phenomena Heat transfer Multiphase flows Surface & interfacial phenomena

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On the chronological understanding of the homogeneous dielectric barrier discharge

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High Voltage 2023年第6期8卷 1132-1150页

作者： Xinpei Lu Zhi Fang Dong Dai Tao Shao Feng Liu Cheng Zhang Dawei Liu Lanlan Nie Chunqi Jiang State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhanChina College of Electrical Engineering and Control Science Nanjing Tech TechnologyNanjingChina School of Electric Power South China University of TechnologyGuangzhouChina Institute of Electrical Engineering Chinese Academy of SciencesBeijingChina Frank Reidy Research Center for Bioelectrics Old Dominion UniversityNorfolkVirginiaUSA Department of Electrical and Computer Engineering Old Dominion UniversityNorfolkVirginiaUSA

Dielectric barrier discharges(DBD)are widely utilised non‐equilibrium atmospheric pressure plasmas with a diverse range of applications,such as material processing,surface treatment,light sources,pollution control,and *** the course of several decades,extensive research has been dedicated to the generation of homogeneous DBD(H‐DBD),focussing on understanding the transition from H‐DBD to filamentary DBD and exploring strategies to create and sustain H‐*** paper first discusses the in-fluence of various parameters on DBD,including gas flow,dielectric material,surface conductivity,and mesh ***,a chronological literature review is presented,highlighting the development of H‐DBD and the associated understanding of its un-derlying *** encompasses the generation of H‐DBD in helium,nitrogen,and ***,the paper provides a brief overview of multiple‐current‐pulse(MCP)behaviours in H‐*** objective of this article is to provide a chronological un-derstanding of homogeneous dielectric barrier discharge(DBD).This understanding will aid in the design of new experiments aimed at better comprehending the mechanisms behind H‐DBD generation and ultimately assist in achieving large‐volume H‐DBD in an air environment.

关键词： dielectric barrier pollution

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