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arXiv 2024年

作者： Nie, Zan Nambu, Noa Marsh, Kenneth A. Matteo, Daniel Patel, C. Kumar Zhang, Chaojie Wu, Yipeng Carlström, Stefanos Morales, Felipe Patchkovskii, Serguei Smirnova, Olga Ivanov, Misha Joshi, Chan Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA90095 United States Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan430074 China Max Born Institute Max-Born-Str. 2A BerlinD-12489 Germany

Cavity-free lasing in atmospheric air has stimulated intense research towards fundamental understanding of underlying physical mechanisms. In this Letter, we identify a new mechanism – third harmonic photon mediated resonant energy transfer pathway leading to population inversion in argon via initial three-photon excitation of nitrogen molecules irradiated by intense 261 nm pulses – that enables bidirectional two-color cascaded lasing in atmospheric air. By making pump-probe measurements, we conclusively show that such cascaded lasing results from superfluorescence (SF) rather than amplified spontaneous emission (ASE). Such cascaded lasing with the capability of producing bidirectional multicolor coherent pulses opens additional possibilities for remote sensing applications. © 2024, CC BY.

关键词： Argon

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Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition

arXiv

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arXiv 2022年

作者： Chen, Zhan Li, Sicheng Yang, Bing Li, Qinghan Liu, Hong Key Laboratory of Machine Perception Shenzhen Graduate School Peking University China Institute of Information and Communication Engineering Zhejiang University China Department of Electrical Engineering and Computer Science Syracuse University United States

Graph convolutional networks have been widely used for skeleton-based action recognition due to their excellent modeling ability of non-Euclidean data. As the graph convolution is a local operation, it can only utilize the short-range joint dependencies and short-term trajectory but fails to directly model the distant joints relations and long-range temporal information that are vital to distinguishing various actions. To solve this problem, we present a multi-scale spatial graph convolution (MS-GC) module and a multi-scale temporal graph convolution (MT-GC) module to enrich the receptive field of the model in spatial and temporal dimensions. Concretely, the MS-GC and MT-GC modules decompose the corresponding local graph convolution into a set of subgraph convolution, forming a hierarchical residual architecture. Without introducing additional parameters, the features will be processed with a series of sub-graph convolutions, and each node could complete multiple spatial and temporal aggregations with its neighborhoods. The final equivalent receptive field is accordingly enlarged, which is capable of capturing both short- and long-range dependencies in spatial and temporal domains. By coupling these two modules as a basic block, we further propose a multi-scale spatial temporal graph convolutional network (MST-GCN), which stacks multiple blocks to learn effective motion representations for action recognition. The proposed MST-GCN achieves remarkable performance on three challenging benchmark datasets, NTU RGB+D, NTU-120 RGB+D and Kinetics-Skeleton, for skeleton-based action recognition. Copyright © 2022, The Authors. All rights reserved.

关键词： Convolution

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Contrastive Bayesian Analysis for Deep Metric Learning

arXiv

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arXiv 2022年

作者： Kan, Shichao He, Zhiquan Cen, Yigang Li, Yang Mladenovic, Vladimir He, Zhihai School of Computer Science and Engineering Central South University Hunan Changsha410083 China Institute of Information Science School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China Guangdong Multimedia Information Service Engineering Technology Research Center Shenzhen University 518060 China Department of Electrical Engineering and Computer Science University of Missouri ColumbiaMO65211 United States Faculty of Technical Sciences University of Kragujevac Cacak Serbia Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen China Pengcheng Lab Shenzhen518066 China

Recent methods for deep metric learning have been focusing on designing different contrastive loss functions between positive and negative pairs of samples so that the learned feature embedding is able to pull positive samples of the same class closer and push negative samples from different classes away from each other. In this work, we recognize that there is a significant semantic gap between features at the intermediate feature layer and class labels at the final output layer. To bridge this gap, we develop a contrastive Bayesian analysis to characterize and model the posterior probabilities of image labels conditioned by their features similarity in a contrastive learning setting. This contrastive Bayesian analysis leads to a new loss function for deep metric learning. To improve the generalization capability of the proposed method onto new classes, we further extend the contrastive Bayesian loss with a metric variance constraint. Our experimental results and ablation studies demonstrate that the proposed contrastive Bayesian metric learning method significantly improves the performance of deep metric learning in both supervised and pseudo-supervised scenarios, outperforming existing methods by a large margin. © 2022, CC0.

关键词： Distance education

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Spiking Neural Network-Based Control of an Unmanned Aerial System Implemented on a Customized Neural Flight Simulation Environment

Spiking Neural Network-Based Control of an Unmanned Aerial S...

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American Control Conference (ACC)

作者： Omar A. Garcia A. Diego Chavez Arana Eduardo S. Espinoza Ignacio Rubio Scola Luis Rodolfo Garcia Carrillo Andrew T. Sornborger Center for Research and Advanced Studies of the National Polytechnic Institute in Mexico City Mexico Klipsch School of Electrical and Computer Engineering New Mexico State University Las Cruces NM USA Conahcyt Center for Research and Advanced Studies of the National Polytechnic Institute in Mexico City Mexico Department of Industrial Products Engineering of the National Institute of Industrial Technology CONICET and National University of Rosario Argentina Los Alamos National Laboratory Los Alamos NM USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

A prototyping environment for the development of Spiking Neural Networks (SNN) is integrated with a physics-based flight simulator with the objective of stabilizing a quad rotorcraft Unmanned Aerial System (UAS) via neuromorphic controllers. Making use of the Neural engineering Framework (NEF), SNN-based Proportional+Derivative (PD) controllers are designed for the translational and rotational dynamics of the UAS. An online Model in the Loop (MIL) evaluation scenario was implemented, showing that the proposed neuromorphic controllers are capable of stabilizing the quad rotorcraft UAS in both regulation and trajectory tracking tasks.

关键词： Trajectory tracking Neuromorphics Heuristic algorithms Aerospace simulation Spiking neural networks Stability analysis Regulation

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Effects of Multimodal Alarms on the Performance of Mental Available Resources in Complex Monitoring Task

SSRN

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SSRN 2024年

作者： Cun, Wenzhe Yu, Suihuai Chu, Jianjie Jianhua, Sun Jiang, Ao Fan, Hao Key Laboratory of Industrial Design and Ergonomics Ministry of Industry and Information Technology Northwestern Polytechnical University China School of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics China Department of Design Southeast University China College of Computer Science and Technology Zhejiang University China Northwestern Polytechnical University China

Due to the extensive information presented in complex monitoring task, visual and auditory channels may become overwhelmed and incapable of efficiently conveying the necessary information for response tasks to alarms. This overload can lead to a significant rise in the operators' mental workload. This study aims to investigate the performance of multimodal alarms under different levels of mental available resources (MARs) in complex monitoring task. The effectiveness of three multimodal alarms—VA (Visual and Auditory) mode, VT (Visual and Tactile) mode, and VAT (Visual, Auditory, and Tactile) mode—across three levels of MAR (MAR-L1, MAR-L2, and MAR-L3) were investigated while operators engaged in complex monitoring tasks. Specifically, simulated experiments of flight take-offs in a civil aircraft cockpit during emergency scenarios were conducted in this investigation. The results showed that the VAT alarm was superior to the VA and VT alarm under MAR-L1 and MAR-L3 conditions, whereas the performance of VA and VAT alarm had no significant difference. As operators who are engaged in complex monitoring task are generally under heavy workload and lower MAR conditions, the VAT alarm is considered to hold significant potential for practical engineering applications. © 2024, The Authors. All rights reserved.

关键词： Cockpits (aircraft)

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Phonon Screening of Excitons in Atomically Thin Semiconductors

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Physical Review Letters 2024年第20期133卷 206901-206901页

作者： Woncheol Lee Antonios M. Alvertis Zhenglu Li Steven G. Louie Marina R. Filip Jeffrey B. Neaton Emmanouil Kioupakis Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor Michigan 48109 USA KBR Inc. NASA Ames Research Center Moffett Field California 94035 USA Materials Sciences Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Department of Physics University of California Berkeley Berkeley California 94720 USA Mork Family Department of Chemical Engineering and Materials Science University of Southern California Los Angeles California 90089 USA Department of Physics University of Oxford Oxford OX1 3PJ United Kingdom Kavli Energy NanoScience Institute at Berkeley Berkeley California 94720 USA Department of Materials Science and Engineering University of Michigan Ann Arbor Michigan 48109 USA

Atomically thin semiconductors, encompassing both 2D materials and quantum wells, exhibit a pronounced enhancement of excitonic effects due to geometric confinement. Consequently, these materials have become foundational platforms for the exploration and utilization of excitons. Recent ab initio studies have demonstrated that phonons can substantially screen electron-hole interactions in bulk semiconductors and strongly modify the properties of excitons. While excitonic properties of atomically thin semiconductors have been the subject of extensive theoretical investigations, the role of phonon screening on excitons in atomically thin structures remains unexplored. In this Letter, we demonstrate via ab initio GW-Bethe-Salpeter equation calculations that phonon screening can have a significant impact on optical excitations in atomically thin semiconductors. We further show that the degree of phonon screening can be tuned by structural engineering. We focus on atomically thin GaN quantum wells embedded in AlN and identify specific phonons in the surrounding material, AlN, that dramatically alter the lowest-lying exciton in monolayer GaN via screening. Our studies provide new intuition beyond standard models into the interplay among structural properties, phonon characteristics, and exciton properties in atomically thin semiconductors, and have implications for future experiments.

关键词： Bethe-Salpeter equation Electron-phonon coupling Excitons Phonons 2-dimensional systems Ab initio calculations Density functional theory

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A Method for Measuring the Three-Dimensional Profile of Moving Objects Based on Neural Network Position Transformation

SSRN

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SSRN 2023年

作者： Wu, Yibo Guo, Bingquan Di, Rui Hu, Hailing Zhang, Peiqing Shen, Xiang Song, Baoan Faculty of Electrical Engineering and Computer Science Ningbo University 315211 China The Research Institute of Advanced Technologies Ningbo University 315211 China Key Laboratory of Photoelectric Detecting Materials and Devices of Zhejiang Province Ningbo315211 China Ningbo Institute of Oceanography Ningbo University Ningbo315211 China Engineering Research Center for Advanced Infrared Photoelectric Materials and Devices of Zhejiang Province Ningbo315211 China

To eliminate motion-induced errors, a Multi-Step Fitting Position Transformation (MFPT) method is proposed for measuring three-dimensional(3D) profile of an object. The method employs a neural network to perform position transformation on the objects in the captured motion phase-shifting fringe projection images, aligning them to the same position, and then uses the phase-shifting method to obtain the 3D profile of the objects. Theoretically, the rigid body motion transformation matrix is used to deduce the change of points on the objects in the fringe pattern under different motion conditions, and the 3D profile measurement results of randomly moving objects are simulated and analyzed. Experimentally, a neural network model was trained by using 5000 sets of data obtained from experiments to eliminate motion-induced errors in various motion states. Simulation and experimental results show that this method significantly reduces the motion-induced errors that occur when measuring moving objects using traditional phase-shifting method. It has broad application prospects in the field of real-time measurement of moving objects’ 3D profile. © 2023, The Authors. All rights reserved.

关键词： Errors

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A secure image protection algorithm by steganography and encryption using the 2D-TSCC

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Chinese Physics B 2021年第11期30卷 274-285页

作者： Qi Li Xingyuan Wang He Wang Xiaolin Ye Shuang Zhou Suo Gao Yunqing Shi School of Information Science and Technology Dalian Maritime UniversityDalian 116026China Guangxi Key Laboratory of Multi-source Information Mining&Security Guangxi Normal UniversityGuilin 541004China Dalian Hongwen Middle School Dalian 116000China School of Mathematical Sciences Chongqing Normal UniversityChongqing 401331China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102USA

Based on the two-dimensional(2D)tan-sin-cos-coupling(2D-TSCC),a new image protection method is designed,this method includes steganography and ***,a 2D-TSCC system is *** 2D-TSCC has a large parameter space in a hyperchaotic *** chaotic trajectory fills the entire *** chaotic sequence generated by the 2D-TSCC has a good pseudorandomness,so it can be used in steganography and ***,the amount of information contained in each bit of the cover image is analyzed,and the three bits which carry the least amount of information are *** secret image is hidden in these three bits base on the ***,the carrier image is scrambled and diffused by the *** ciphertext is generated in this *** the ciphertext to the recipient through channel transmission,and the recipient obtains the secret image by decrypting twice.

关键词： 2D-TSCC steganography image encryption mod diffuse chaos

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Johnsen-Rahbek Capstan Clutch: A High Torque Electrostatic Clutch

arXiv

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arXiv 2023年

作者： Amish, Timothy E. Auletta, Jeffrey T. Kessens, Chad C. Smith, Joshua R. Lipton, Jeffrey I. Dept of Electrical and Computer Engineering University of Washington SeattleWA98195 United States US Army Research Directorate DEVCOM Army Research Laboratory Aberdeen Proving GroundMD21005 United States Paul G Allen School of Computer Science and Engineering University of Washington SeattleWA98195 United States Mechanical and Industrial Engineering Department Northeastern University BostonMA02115 United States

In many robotic systems, the holding state consumes power, limits operating time, and increases operating costs. Electrostatic clutches have the potential to improve robotic performance by generating holding torques with low power consumption. A key limitation of electrostatic clutches has been their low specific shear stresses which restrict generated holding torque, limiting many applications. Here we show how combining the Johnsen-Rahbek (JR) effect with the exponential tension scaling capstan effect can produce clutches with the highest specific shear stress in the literature. Our system generated 31.3 N/cm2 sheer stress and a total holding torque of 7.1 N·m while consuming only 2.5 mW/cm2 at 500 V. We demonstrate a theoretical model of an electrostatic adhesive capstan clutch and demonstrate how large angle (θ > 2π) designs increase efficiency over planar or small angle (θ Copyright © 2023, The Authors. All rights reserved.

关键词： Electrostatics

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Broadband and repetition rate tunable frequency comb based on electro-optic time lens with AlGaAsOI waveguide

Broadband and repetition rate tunable frequency comb based o...

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49th European Conference on Optical Communications (ECOC 2023)

作者： C. Ma C. Wang Y. Pi L. Wang Z. He J. E. Bowers L. Chang Z. Cao S. Yu Research Center of Circuits and Systems Peng Cheng Laboratory Shenzhen 518055 Guangdong People's Republic of China Department of Electrical and Computer Engineering University of California Santa Barbara CA 93106 USA State Key Laboratory of Advanced Optical Communications System and Networks Peking University Beijing 100871 People's Republic of China

We present a tunable repetition rate frequency comb realized by cascaded electro-optical modulators with a high nonlinear AlGaAs-on-isolator waveguide. 18-26.5 GHz comb spacing tunability with broadband spectra was achieved. All the devices can be integrated onto a single chip, which makes this work useful for many applications.

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