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Adaptive Dead Zone Compensation Control Method for Electro-Hydrostatic Actuators Under Low-Speed Conditions

Chinese Journal of Mechanical engineering 2024年第6期37卷 199-211页

作者： Haoyi Jiang Zhenfei Ling Fengqi Zhou Maowen Sun Hao Liu Lilin Xu Yeming Yao Xiaoping Ouyang Huayong Yang State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing Engineering Institute of Aircraft SystemNanjing 210000China

This study proposes an accurate dead zone compensation control method for electro-hydrostatic actuators(EHAs)under low-speed ***,the nonlinear dead zone characteristics under low-speed conditions are summarized based on numerous EHA *** adaptive compensation function(ACF)is then constructed for the dead ***,this study proposes an adaptive dead zone compensation control method for EHAs by integrating the ACF with a virtual decomposition controller(VDC)based on the established EHA *** stability of the proposed control method is also ***,the proposed control method is verified using an EHA *** test results show that the dead zone trajectory tracking errors of EHAs are significantly reduced when combined with the ***,since most EHAs are controlled by adjusting the motor speed,the method presented in this study is simpler and easier to use than methods that employ flow compensation.

关键词： Electro-hydrostatic actuator Dead zone Compensation Control Low-speed

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Quantum public-key crypto via EPR pairs

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science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 54-59页

作者： Xiang-Qun Fu Hong-Wei Li Jian-Hong Shi Tan Li Wan-Su Bao Henan Key Laboratory of Quantum Information and Cryptography Information Engineering UniversityZhengzhou 450004China Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China

With the development of quantum computing technology,quantum public-key cryptography is gradually becoming an alternative to the existing classical public-key *** paper designs a quantum trapdoor one-way function via EPR pairs and quantum *** on this,a new quantum public-key cryptosystem is presented,which offers forward security,and can resist the chosen-plaintext attack and chosen-ciphertext *** with the existing quantum public-key cryptos,eavesdropping can be automatically detected in this new quantum public-key cryptosystem under a necessary condition,which is also detailed in the paper.

关键词： quantum public-key crypto trapdoor one-way function EPR pairs

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Seeking a Sense of Meaning and Companionship in Life: Informal Learning on Douyin Among Chinese Older Adults

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Proceedings of the ACM on Human-Computer Interaction 2025年第2期9卷 1-24页

作者： Qian, Zhigu Fu, Jiaojiao Zhou, Yangfan School of Computer Science Fudan University Shanghai Key Laboratory of Intelligent Information Processing China School of Information Science and Engineering East China University of Science and Technology China

This study examines how Chinese older adults leverage Douyin, a short video platform, for informal learning purposes, analyzing their usage patterns, motivations, and encountered challenges. Although Douyin was not explicitly designed with educational features, it has emerged as a significant informal learning platform for this demographic. Through a qualitative investigation comprising participant observations and semi-structured interviews with 17 participants, we reveal the distinctive learning experience that Douyin facilitates. The platform’s unique combination of short-form videos, live streaming capabilities, and interactive community features creates an engaging learning environment that particularly resonates with older adults. Our findings demonstrate that participants derive substantial social-emotional benefits beyond knowledge acquisition, including strengthened social connections, enhanced companionship, and a reinforced sense of purpose through their Douyin engagement. These social-emotional aspects emerge as crucial factors driving older adults’ selection of Douyin as their preferred learning platform. By providing comprehensive insights into older adults’ engagement with digital platforms for lifelong learning, this research offers valuable implications for HCI, particularly in understanding how technology can be optimized to support the learning needs of older populations. © 2025 Association for Computing Machinery. All rights reserved.

关键词： Social aspects

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Dual control of amplitude and phase in a multilayer terahertz metasurface for transmission and reflection modulation

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Applied Optics 2025年第9期64卷 2276-2286页

作者： Zhang, Yuping Zheng, Siyu Hao, Xiaoyu Wang, Yu Liu, Yang Zhang, Min Liu, Meng Zhang, Huiyun Qingdao Key Laboratory of Terahertz Technology College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China

Current metasurfaces encounter challenges in achieving precise control over transmittance-reflection mode conversion. This study presents a multilayer metasurface structure that incorporates dual amplitude and phase control, utilizing vanadium dioxide (VO2) and Dirac semimetals (DSMs) as tunable materials. By adjusting the orientation angle of the split-ring resonator (SRR) in the intermediate layer and modifying the Fermi energy level of the DSMs, precise dual control of amplitude and phase can be attained. When VO2 is in its insulating phase with a DSM Fermi level of 500 meV, the metasurface exhibits notable transmission characteristics, enabling refraction and focusing at 0.6 THz while demonstrating remarkable insensitivity to the incident angle. Conversely, when VO2 transitions to the metallic phase and the Fermi level of the DSMs is decreased to 1 meV, the metasurface displays significant reflection characteristics, facilitating the generation of vortex beam and multi-beam vortices. This multilayer metasurface holds considerable promise for applications in terahertz. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Vanadium dioxide

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Algorithms and statistical analysis for linear structured weighted total least squares problem

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Geodesy and Geodynamics 2024年第2期15卷 177-188页

作者： Jian Xie Tianwei Qiu Cui Zhou Dongfang Lin Sichun Long School of Earth Science and Spatial Information Engineering Hunan University of Science and TechnologyXiangtan 411201China College of Science Central South University of Forestry and TechnologyChangsha 410018China National-Local Joint Engineering Laboratory of Geo-spatial Information Technology Hunan University of Science and TechnologyXiangtan 411201China

Weighted total least squares(WTLS)have been regarded as the standard tool for the errors-in-variables(EIV)model in which all the elements in the observation vector and the coefficient matrix are contaminated with random ***,in many geodetic applications,some elements are error-free and some random observations appear repeatedly in different positions in the augmented coefficient *** is called the linear structured EIV(LSEIV)*** kinds of methods are proposed for the LSEIV model from functional and stochastic *** the one hand,the functional part of the LSEIV model is modified into the errors-in-observations(EIO)*** the other hand,the stochastic model is modified by applying the Moore-Penrose inverse of the cofactor *** algorithms are derived through the Lagrange multipliers method and linear *** estimation principles and iterative formula of the parameters are proven to be *** first-order approximate variance-covariance matrix(VCM)of the parameters is also derived.A numerical example is given to compare the performances of our proposed three algorithms with the STLS ***,the least squares(LS),total least squares(TLS)and linear structured weighted total least squares(LSWTLS)solutions are compared and the accuracy evaluation formula is proven to be feasible and ***,the LSWTLS is applied to the field of deformation analysis,which yields a better result than the traditional LS and TLS estimations.

关键词： Linear structured weighted total least squares Errors-in-variables Errors-in-observations Functional modelmodification Stochastic model modification Accuracyevaluation

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A Large-Scale Scheduling Method for Multiple Agile Optical Satellites

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Computer Modeling in engineering & sciences 2023年第8期136卷 1143-1163页

作者： Zheng Liu Wei Xiong Minghui Xiong Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering UniversityBeijing101416China

This study investigates the scheduling problem ofmultiple agile optical satelliteswith large-scale *** problem is difficult to solve owing to the time-dependent characteristic of agile optical satellites,complex constraints,and considerable solution *** solve the problem,we propose a scheduling method based on an improved sine and cosine algorithm and a task merging *** first establish a scheduling model with task merging constraints and observation action constraints to describe the ***,an improved sine and cosine algorithm is proposed to search for the optimal solution with the maximum profit *** adaptive cosine factor and an adaptive greedy factor are adopted to improve the ***,a taskmerging method with a task reallocation mechanism is developed to improve the scheduling *** results demonstrate the superiority of the proposed algorithm over the comparison algorithms.

关键词： Multiple agile optical satellites scheduling task merging sine and cosine algorithm task reallocation

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Image Enhancement via Associated Perturbation Removal and Texture Reconstruction Learning

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2253-2269页

作者： Kui Jiang Ruoxi Wang Yi Xiao Junjun Jiang Xin Xu Tao Lu IEEE the School of Computer Science and Technology Harbin Institute of Technology Zhengzhou Research Institute Harbin Institute of Technology the School of Artificial Intelligence Jianghan University the School of Geodesy and Geomatics Wuhan University the Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology the School of Computer Science and Engineering and also with the Hubei Province Key Laboratory of Intelligent Robot Wuhan Institute of Technology

Degradation under challenging conditions such as rain, haze, and low light not only diminishes content visibility, but also results in additional degradation side effects, including detail occlusion and color distortion. However, current technologies have barely explored the correlation between perturbation removal and background restoration, consequently struggling to generate high-naturalness content in challenging scenarios. In this paper, we rethink the image enhancement task from the perspective of joint optimization: Perturbation removal and texture reconstruction. To this end, we advise an efficient yet effective image enhancement model, termed the perturbation-guided texture reconstruction network(PerTeRNet). It contains two subnetworks designed for the perturbation elimination and texture reconstruction tasks, respectively. To facilitate texture recovery,we develop a novel perturbation-guided texture enhancement module(PerTEM) to connect these two tasks, where informative background features are extracted from the input with the guidance of predicted perturbation priors. To alleviate the learning burden and computational cost, we suggest performing perturbation removal in a sub-space and exploiting super-resolution to infer high-frequency background details. Our PerTeRNet has demonstrated significant superiority over typical methods in both quantitative and qualitative measures, as evidenced by extensive experimental results on popular image enhancement and joint detection tasks. The source code is available at https://***/kuijiang94/PerTeRNet.

关键词： Association learning attention mechanism image enhancement perturbation modeling

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Multi-parameter ultrasound imaging for musculoskeletal tissues based on a physics informed generative adversarial network

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Chinese Physics B 2025年第4期34卷 442-455页

作者： Pengxin Wang Heyu Ma Tianyu Liu Chengcheng Liu Dan Li Dean Ta Institute of Biomedical Engineering&Technology Academy for Engineering and TechnologyFudan UniversityShanghai 200433China State Key Laboratory of Integrated Chips and Systems Fudan UniversityShanghai 201203China Department of Electronic Engineering School of Information Science and TechnologyFudan UniversityShanghai 200438China Department of Biomedical Engineering School of Information Science and TechnologyFudan UniversityShanghai 200438China

Full waveform inversion(FWI)has showed great potential in the detection of musculoskeletal ***,FWI is an ill-posed inverse problem and has a high requirement on the initial model during the imaging *** inaccurate initial model may lead to local minima in the inversion and unexpected imaging results caused by cycle-skipping *** learning methods have been applied in musculoskeletal imaging,but need a large amount of data for *** by work related to generative adversarial networks with physical informed constrain,we proposed a method named as bone ultrasound imaging with physics informed generative adversarial network(BUIPIGAN)to achieve unsupervised multi-parameter imaging for musculoskeletal tissues,focusing on speed of sound(SOS)and *** the in-silico experiments using a ring array transducer,conventional FWI methods and BUIPIGAN were employed for multiparameter imaging of two musculoskeletal tissue *** results were evaluated based on visual appearance,structural similarity index measure(SSIM),signal-to-noise ratio(SNR),and relative error(RE).For SOS imaging of the tibia–fibula model,the proposed BUIPIGAN achieved accurate SOS imaging with best *** specific quantitative metrics for SOS imaging were SSIM 0.9573,SNR 28.70 dB,and RE 5.78%.For the multi-parameter imaging of the tibia–fibula and human forearm,the BUIPIGAN successfully reconstructed SOS and density distributions with SSIM above 94%,SNR above 21 dB,and RE below 10%.The BUIPIGAN also showed robustness across various noise levels(i.e.,30 dB,10 dB).The results demonstrated that the proposed BUIPIGAN can achieve high-accuracy SOS and density imaging,proving its potential for applications in musculoskeletal ultrasound imaging.

关键词： ultrasound image physics informed generative adversarial network musculoskeletal imaging

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Unsupervised Meteorological Downscaling Based on Dual Learning and Subgrid-scale Auxiliary information

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Advances in Atmospheric sciences 2025年第1期42卷 53-66页

作者： Jing HU Jialing MU Xiaomeng HUANG Xi WU Department of Computer Science Chengdu University of Information TechnologyChengdu 610225China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China

Climate downscaling is used to transform large-scale meteorological data into small-scale data with enhanced detail,which finds wide applications in climate modeling,numerical weather forecasting,and renewable *** deeplearning-based downscaling methods effectively capture the complex nonlinear mapping between meteorological data of varying scales,the supervised deep-learning-based downscaling methods suffer from insufficient high-resolution data in practice,and unsupervised methods struggle with accurately inferring small-scale specifics from limited large-scale inputs due to small-scale *** article presents DualDS,a dual-learning framework utilizing a Generative Adversarial Network–based neural network and subgrid-scale auxiliary information for climate *** a learning method is unified in a two-stream framework through up-and downsamplers,where the downsampler is used to simulate the information loss process during the upscaling,and the upsampler is used to reconstruct lost details and correct errors incurred during the *** dual learning strategy can eliminate the dependence on high-resolution ground truth data in the training process and refine the downscaling results by constraining the mapping *** findings demonstrate that DualDS is comparable to several state-of-the-art deep learning downscaling approaches,both qualitatively and ***,for a single surface-temperature data downscaling task,our method is comparable with other unsupervised algorithms with the same dataset,and we can achieve a 0.469 dB higher peak signal-to-noise ratio,0.017 higher structural similarity,0.08 lower RMSE,and the best correlation *** summary,this paper presents a novel approach to addressing small-scale uncertainty issues in unsupervised downscaling processes.

关键词： downscaling unsupervised deep learning dual learning auxiliary information

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Unsupervised Low-Light Image Enhancement Based on Explicit Denoising and Knowledge Distillation

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Computers, Materials & Continua 2025年第2期82卷 2537-2554页

作者： Wenkai Zhang Hao Zhang Xianming Liu Xiaoyu Guo Xinzhe Wang Shuiwang Li College of Computer Science and Engineering Guilin University of TechnologyGuilin541006China Guangxi Key Laboratory of Embedded Technology and Intelligent System Guilin University of TechnologyGuilin541004China

Under low-illumination conditions, the quality of image signals deteriorates significantly, typically characterized by a peak signal-to-noise ratio (PSNR) below 10 dB, which severely limits the usability of the images. Supervised methods, which utilize paired high-low light images as training sets, can enhance the PSNR to around 20 dB, significantly improving image quality. However, such data is challenging to obtain. In recent years, unsupervised low-light image enhancement (LIE) methods based on the Retinex framework have been proposed, but they generally lag behind supervised methods by 5–10 dB in performance. In this paper, we introduce the Denoising-Distilled Retine (DDR) method, an unsupervised approach that integrates denoising priors into a Retinex-based training framework. By explicitly incorporating denoising, the DDR method effectively addresses the challenges of noise and artifacts in low-light images, thereby enhancing the performance of the Retinex framework. The model achieved a PSNR of 19.82 dB on the LOL dataset, which is comparable to the performance of supervised methods. Furthermore, by applying knowledge distillation, the DDR method optimizes the model for real-time processing of low-light images, achieving a processing speed of 199.7 fps without incurring additional computational costs. While the DDR method has demonstrated superior performance in terms of image quality and processing speed, there is still room for improvement in terms of robustness across different color spaces and under highly resource-constrained conditions. Future research will focus on enhancing the model’s generalizability and adaptability to address these challenges. Our rigorous testing on public datasets further substantiates the DDR method’s state-of-the-art performance in both image quality and processing speed.

关键词： Deep learning low-light image enhancement real-time processing knowledge distillation

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