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arXiv 2022年

作者： Li, Wenjie Li, Juncheng Gao, Guangwei Deng, Weihong Zhou, Jiantao Yang, Jian Qi, Guo-Jun The Intelligent Visual Information Perception Laboratory Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210046 China The Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China The School of Communication and Information Engineering Shanghai University Shanghai200444 China Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing210094 China The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China The State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science Faculty of Science and Technology University of Macau 999078 China The School of Computer Science and Technology Nanjing University of Science and Technology Nanjing210094 China The Research Center for Industries of the Future The School of Engineering Westlake University Hangzhou310024 China OPPO Research SeattleWA98101 United States

Recently, Transformer-based methods have shown impressive performance in single image super-resolution (SISR) tasks due to the ability of global feature extraction. However, the capabilities of Transformers that need to incorporate contextual information to extract features dynamically are neglected. To address this issue, we propose a lightweight Cross-receptive Focused Inference Network (CFIN) that consists of a cascade of CT Blocks mixed with CNN and Transformer. Specifically, in the CT block, we first propose a CNN-based Cross-Scale Information Aggregation Module (CIAM) to enable the model to better focus on potentially helpful information to improve the efficiency of the Transformer phase. Then, we design a novel Cross-receptive Field Guided Transformer (CFGT) to enable the selection of contextual information required for reconstruction by using a modulated convolutional kernel that understands the current semantic information and exploits the information interaction within different self-attention. Extensive experiments have shown that our proposed CFIN can effectively reconstruct images using contextual information, and it can strike a good balance between computational cost and model performance as an efficient model. Source codes will be available at https://***/IVIPLab/CFIN. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

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An Improved UAV Path Optimization Algorithm for Target Accurately and Quickly Localization

An Improved UAV Path Optimization Algorithm for Target Accur...

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International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Rui Liang Kai Wu Sheng Xu Tiantian Xu Xiaoyi Ma Lianyu Fu City West Power Supply Branch State Grid Tianjin Electric Power Company Tianjin China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen China State Grid Tianjin Information & Telecommunication Company Tianjin China

ISBN: (纸本)9781665402460

Angle-of-arrival (AOA) target localization using the unmanned aerial vehicle (UAV) has been widely applied in many practical applications. To localize an invasive target quickly and accurately, both the estimation and UAV path optimization algorithms are required. This paper focuses on developing a path optimization method to improve the target estimation performance. Firstly, the problem formulation of AOA target localization is introduced. Secondly, the classical pseudolinear Kalman filter (PLKF) and the gradient-based path optimization are presented. Thirdly, we analyze the problems that existed in the previous methods and propose an improved gradient-descent path optimization algorithm combined with a simple grid search method. Finally, the simulation examples verify the effectiveness of the proposed methods.

关键词： Location awareness Adaptation models Three-dimensional displays Target tracking Search methods Estimation Optimization methods

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Global Dynamics and Optimal Design of a New Highly Efficient Nonlinear Energy Sink Based on Magnetic-Elastic Impacts with Negative Stiffness

Research Square

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Research Square 2021年

作者： Li, Shuangbao Wang, Tingting Chen, Jianen Research Institute of Science and Technology Innovation Civil Aviation University of China Tianjin300300 China College of Science Civil Aviation University of China Tianjin300300 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China

A new highly efficient elastic-impact bistable nonlinear energy sink (EI-BNES) based on magnetic-elastic impacts with negative stiffness and bistability is proposed and optimized through global dynamical analysis. The EI-BNES has better robustness and higher energy dissipation rates with nearly more than 96.5% for broadband impulsive excitations than the traditional cubic NESs and single bistable NESs. The structure of negative stiffness impacts is realized by reasonable layout of permanent ring magnets and springs. A two-degree-of-freedom (two-DOF) elastic-impact system is established to describe the coupled nonlinear interaction between the main structure and the attached EI-BNES. A global Melnikov reduction analysis (GMRA) is proposed to study global dynamics and homoclinic bifurcations of the reduced two-dimensional subsystem, which is used to explain the mechanism of nonlinear targeted energy transfer (TET) and detect the threshold of impulsive amplitudes of EI-BNES for in-well and compound motions between in-well and cross-well resonance responses. A special type of saddle-center equilibrium points is also found in the non-smooth system of the EI-BNES and can be used to effectively increase the energy dissipation rates. The optimal design criterion of the tuned EI-BNES for better dissipation performance is also first discussed based on the GMRA and numerical techniques for calculating the Melnikov function of the non-smooth systems. The effectiveness of the analytical GMRA is also verified by numerical simulations. © 2021, CC BY.

关键词： Stiffness

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Design and test of ceramic knife-edge seal for in-situ heating system of extracting volatile matter from lunar soil

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Advances in Space Research 2025年

作者： Yinchao Wang Yuanling Sun Jianbo Zhou Bowei Wang Junyue Tang Zixiao Lu Huazhi Chen Bo Wang Xiaobo Su Shengyuan Jiang School of Mechatronics and Engineering Shenyang Aerospace University Shenyang 110136 China Key Laboratory of Rapid Development & Manufacturing Technology for Aircraft (Shenyang Aerospace University) Ministry of Education Shenyang 110136 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China Nanometer Intelligent Sensor Lab National Center for Nanoscience and Technology Beijing 100190 China China Academy of Space Technology Beijing 100190 China Sichuan boffins robotic and robotizatian Co. LTD Chengdu 610052 China

In the pursuit of accurate lunar soil volatile exploration, in-situ deep space sampling analysis offers unparalleled preservation of sample integrity. A critical challenge lies in ensuring a secure sealing environment. This paper introduces an innovative sealing method utilising a ceramic blade to compress a non-metallic seal. Initially, following a comprehensive multidimensional evaluation of sealing configurations, the ceramic knife-edge compression non-metallic sealing ring solution was determined to be optimal. This approach involves positioning the sealing ring within a grooved cylindrical heating furnace body, where radial compression is achieved through an annular ceramic knife-edge interface, thereby ensuring hermetic integrity. Subsequently, a sealing leakage model grounded in Roth theory was developed to elucidate micro-leakage mechanisms. ANSYS simulation software was utilised to investigate the influence of blade tip radius and temperature, revealing correlations with average stress and contact width, as well as the impact of temperature extremes on sealing efficacy. These findings provided the theoretical underpinning for subsequent ground tests. A dedicated test platform was established, adhering to the industry standard QJ3089A-2018, to evaluate the sealing performance of various seal and blade tip radius combinations under diverse conditions. Results indicated that, under a force of 500N, PTFE seals compressed by an R0.5mm blade and PVMQ seals compressed by an R0.6mm blade achieved leakage rates on the order of 10 -8 Pa·m 3 ·s -1 , aligning with theoretical predictions and demonstrating repeatable sealing capability. This study presents a novel and reliable sealing solution for the precise exploration of lunar soil volatiles, offering a technical breakthrough and robust sealing strategy for future deep space missions.

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Lightweight and conformal acousto-ultrasonic sensing network for multi-scale structural health monitoring: A review

FlexMat

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FlexMat 2024年

作者： Yehai Li Shifeng Guo Zhongqing Su Keqin Ding Xian Jun Loh Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China The Key Laboratory of Biomedical Imaging Science and System Chinese Academy of Sciences Shenzhen China Department of Mechanical Engineering The Hong Kong Polytechnic University Kowloon Hong Kong Technology Innovation Center of Structural Health Monitoring of State Market Regulation China Special Equipment Inspection & Research Institute Beijing China Institute of Materials Research and Engineering (IMRE) Agency for Science Technology and Research (A*STAR) Singapore Singapore

Structural health monitoring (SHM) has been increasingly investigated for decades. Different physical principles have been developed for damage identification, such as electronics, mechanics, magnetics, etc., with different coverage (i.e., global, large-area, and local monitoring) and sensitivity. Mechanical acousto-ultrasonic-based methods have formed a big family in SHM technologies. Multiple wave/resonance modes have been utilized for versatile SHM tasks. The permanently integrated sensing networks play a significant role in achieving a cost-effective and reliable SHM system, with major concerns including weight increase for large-scale deployment and conformity for complex geometry structures. In this review, typical acousto-ultrasonic sensors made of different material systems are discussed, along with advantages and limitations. Moreover, advanced network installation methods have been introduced, including surface-mounting with pre-integrated networks on substrates and in situ printing, and embedding with composite layup and metal additive manufacturing. Sensor versatility and usage in multi-scale SHM techniques are then highlighted. Different wave/resonance modes are transmitted and received with corresponding elements and network designs. In conclusion, this systematic review mainly covers a collection of acousto-ultrasonic sensors, two modalities of network installation, and their employment with various SHM methods, hopefully providing a useful guide to building lightweight and conformal networks with passive or active-passive sensors, and developing complete and reliable SHM strategies by integrating different damage identification methods on multiple scales.

关键词： acousto-ultrasonic conformal installation lightweight sensing networks structural health monitoring

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Semidiscrete optical vortex droplets in quasi-phase-matched photonic crystals

arXiv

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arXiv 2023年

作者： Xu, Xiaoxi Zhao, Feiyan Huang, Jiayao He, Hexiang Zhang, Li Chen, Zhaopin Nie, Zhongquan Malomed, Boris A. Li, Yongyao School of Physics and Optoelectronic Engineering Foshan University Foshan528000 China School of Electronic and Computer Engineering Peking University Shenzhen518055 China Physics Department Solid-State Institute Technion Haifa32000 Israel Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan030024 China Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Tel Aviv University Tel Aviv69978 Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology Foshan University Foshan528000 China

A new scheme for producing semidiscrete self-trapped vortices ("swirling photon droplets") in photonic crystals with competing quadratic (χ(2)) and self-defocusing cubic (χ(3)) nonlinearities is proposed. The photonic crystal is designed with a striped structure, in the form of spatially periodic modulation of the χ(2) susceptibility, which is imposed by the quasi-phase-matching technique. Unlike previous realizations of semidiscrete optical modes in composite media, built as combinations of continuous and arrayed discrete waveguides, the semidiscrete vortex "droplets" are produced here in the fully continuous medium. This work reveals that the system supports two types of semidiscrete vortex droplets, viz., onsite- and intersite-centered ones, which feature, respectively, odd and even numbers of stripes, N. Stability areas for the states with different values of N are identified in the system's parameter space. Some stability areas overlap with each other, giving rise to the multistability of states with different N. The coexisting states are mutually degenerate, featuring equal values of the Hamiltonian and propagation constant. An experimental scheme to realize the droplets is outlined, suggesting new possibilities for the long-distance transmission of nontrivial vortex beams in nonlinear media. © 2023, CC BY.

关键词： Photonic crystals

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Few-Shot Semantic Segmentation with Democratic Attention Networks 16th

Few-Shot Semantic Segmentation with Democratic Attention Net...

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16th European Conference on Computer Vision, ECCV 2020

作者： Wang, Haochen Zhang, Xudong Hu, Yutao Yang, Yandan Cao, Xianbin Zhen, Xiantong Beihang University Beijing China Key Laboratory of Advanced Technology of Near Space Information System Ministry of Industry and Information Technology of China Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beijing China AIM Lab University of Amsterdam Amsterdam Netherlands Inception Institute of Artificial Intelligence Abu Dhabi United Arab Emirates YouKu Cognitive and Intelligent Lab Alibaba Group Hangzhou China

ISBN: (纸本)9783030586003

Few-shot segmentation has recently generated great popularity, addressing the challenging yet important problem of segmenting objects from unseen categories with scarce annotated support images. The crux of few-shot segmentation is to extract object information from the support image and then propagate it to guide the segmentation of query images. In this paper, we propose the Democratic Attention Network (DAN) for few-shot semantic segmentation. We introduce the democratized graph attention mechanism, which can activate more pixels on the object to establish a robust correspondence between support and query images. Thus, the network is able to propagate more guiding information of foreground objects from support to query images, enhancing its robustness and generalizability to new objects. Furthermore, we propose multi-scale guidance by designing a refinement fusion unit to fuse features from intermediate layers for the segmentation of the query image. This offers an efficient way of leveraging multi-level semantic information to achieve more accurate segmentation. Extensive experiments on three benchmarks demonstrate that the proposed DAN achieves the new state-of-the-art performance, surpassing the previous methods by large margins. The thorough ablation studies further reveal its great effectiveness for few-shot semantic segmentation. © 2020, Springer Nature Switzerland AG.

关键词： Semantic Segmentation

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An Accurate Dynamic Model Identification Method for Industrial Robots Based on Improved Excitation Trajectory

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International Journal of Numerical Modelling: Electronic Networks, Devices and Fields 2025年第3期38卷

作者： Xiao Lin Junyang Li Yankui Song Yogendra Arya Yu Xia State Key Laboratory of Mechanical Transmissions for Advanced Equipment Chongqing University Chongqing China Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China Department of Electrical Engineering J.C. Bose University of Science and Technology YMCA Faridabad Haryana India State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai China

This article focuses on dynamic parameter identification for industrial robots and proposes a parameter identification method based on an improved excitation trajectory. First, a complex nonlinear friction model is adopted and modified according to joint friction characteristics, with a genetic algorithm utilized to determine its six parameters. Second, a weighted optimal excitation trajectory is designed to address nonlinear friction requirements and smooth operation constraints. Then, a global parameter optimization algorithm based on the least squares method and the modified sparrow search algorithm is proposed. Finally, the proposed method is validated on a self-developed six-axis industrial robot. Experimental results demonstrate that the proposed method achieves higher identification accuracy compared with two representative identification approaches.

关键词： dynamic parameter identification industrial robots least squares method modified sparrow search algorithm optimal excitation trajectory

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A Bioinspired retinal neural network for accurately extracting small-target motion information in cluttered backgrounds

arXiv

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arXiv 2021年

作者： Huang, Xiao Qiao, Hong Li, Hui Jiang, Zhihong School of Mechatronical Engineering Advanced Innovation Center for Intelligent Robots and Systems Key Laboratory of Biomimetic Robots and Systems of Chinese Ministry of Education Beijing Institute of Technology Beijing100081 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Beijing Key Laboratory of Research and Application for Robotic Intelligence of’Hand-Eye-Brain’ Interaction Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

—Robust and accurate detection of small moving targets in cluttered moving backgrounds is a significant and challenging problem for robotic visual systems to perform search and tracking tasks. Inspired by the neural circuitry of elementary motion vision in the mammalian retina, this paper proposes a bioinspired retinal neural network based on a new neurodynamics-based temporal filtering and multiform 2-D spatial Gabor filtering. This model can estimate motion direction accurately via only two perpendicular spatiotemporal filtering signals, and respond to small targets of different sizes and velocities through adjusting the dendrite field size of spatial filter. Meanwhile, an algorithm of directionally selective inhibition is proposed to suppress the target-like features in the moving background, which can reduce the influence of background motion effectively. Extensive synthetic and real-data experiments show that the proposed model works stably for small targets of a wider size and velocity range, and has better detection performance than other bioinspired models. Additionally, it can also extract the information of motion direction and motion energy accurately and rapidly. Copyright © 2021, The Authors. All rights reserved.

关键词： Ophthalmology

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A Bioinspired approach-sensitive neural network for collision detection in cluttered and dynamic backgrounds

arXiv

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arXiv 2021年

—Rapid, accurate and robust detection of looming objects in cluttered moving backgrounds is a significant and challenging problem for robotic visual systems to perform collision detection and avoidance tasks. Inspired by the neural circuit of elementary motion vision in the mammalian retina, this paper proposes a bioinspired approach-sensitive neural network (ASNN) that contains three main contributions. Firstly, a direction-selective visual processing module is built based on the spatiotemporal energy framework, which can estimate motion direction accurately via only two mutually perpendicular spatiotemporal filtering channels. Secondly, a novel approach-sensitive neural network is modeled as a push-pull structure formed by ON and OFF pathways, which responds strongly to approaching motion while insensitivity to lateral motion. Finally, a method of directionally selective inhibition is introduced, which is able to suppress the translational backgrounds effectively. Extensive synthetic and real robotic experiments show that the proposed model is able to not only detect collision accurately and robustly in cluttered and dynamic backgrounds but also extract more collision information like position and direction, for guiding rapid decision making. © 2021, CC BY.

关键词： Mammals

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