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Photostriction effect and electric properties of La-doped PMN-PT transparent ferroelectric ceramics

International Journal of Smart and Nano Materials 2024年第2期15卷 296-311页

作者： Zhiqiang Song Zhuo Zhang Yirong Yu Dabin Lin Department of Automation and Robotics Engineering School of AutomationWuxi UniversityWuxiChina School of Optoelectronic Engineering Xian Technological UniversityXi'anChina

Ferroelectric ceramics display a remarkable photostriction effect,which could facilitate the prevention of electromagnetic interference and promote the integration and miniaturization of actuator systems,indicating potential applications in glim-mer *** this work,highly transparent La-doped 0.9Pb(Mg1/3Nb2/3)O3-0.1PbTiO3(0.9PMN-0.1PT)ceramicswere synthesized using a solid-state reaction method in an oxyge-nated *** and SEM were used to analyze the phase structure of the dense samples,which displayed a pure perovskite structure,with no trace of a pyrochlore *** La doping,the phase transitiontemperature shows a decreasing trend,and its dielectric constant could reach up to 20,*** P-E loop of the samples was gradually refined into a straight line with an increase in the doping *** La doping,the transparency of the 0.9PMN-0.1PT cera-mics was significantly enhanced and reached up to 61%at the near-infrared ***,the photogenerated voltage and deformation of the La-doped 0.9PMN-0.1PT ceramics were investigated under ultraviolet light of various *** 20 s of irradiation at an intensity of 800 mW/cm²,the max-imum voltage and deformation,with values of 40 V and 250 nm,respectively,were both found in the 1%La-doped 0.9PMN-0.1PT ceramics.

关键词： Photostriction ferroelectric Raman piezoelectric

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Neural Network Algorithm Based on LVQ for Myocardial Infarction Detection and Localization Using Multi-Lead ECG Data

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Computers, Materials & Continua 2025年第3期82卷 5257-5284页

作者： Kassymbek Ozhikenov Zhadyra Alimbayeva Chingiz Alimbayev Aiman Ozhikenova Yeldos Altay Department of Robotics and Engineering Tools of Automation Satbayev UniversityAlmaty050010Kazakhstan Joldasbekov Institute of Mechanics and Engineering Almaty050010Kazakhstan

Myocardial infarction(MI)is one of the leading causes of death globally among cardiovascular diseases,necessitating modern and accurate diagnostics for cardiac patient *** the available functional diagnostic methods,electrocardiography(ECG)is particularly well-known for its ability to detect ***,confirming its accuracy—particularly in identifying the localization of myocardial damage—often presents challenges in *** study,therefore,proposes a new approach based on machine learning models for the analysis of 12-lead ECG data to accurately identify the localization of *** particular,the learning vector quantization(LVQ)algorithm was applied,considering the contribution of each ECG lead in the 12-channel system,which obtained an accuracy of 87%in localizing damaged *** developed model was tested on verified data from the PTB database,including 445 ECG recordings from both healthy individuals and MI-diagnosed *** results demonstrated that the 12-lead ECG system allows for a comprehensive understanding of cardiac activities in myocardial infarction patients,serving as an essential tool for the diagnosis of myocardial conditions and localizing their damage.A comprehensive comparison was performed,including CNN,SVM,and Logistic Regression,to evaluate the proposed LVQ *** results demonstrate that the LVQ model achieves competitive performance in diagnostic tasks while maintaining computational efficiency,making it suitable for resource-constrained *** study also applies a carefully designed data pre-processing flow,including class balancing and noise removal,which improves the reliability and reproducibility of the *** aspects highlight the potential application of the LVQ model in cardiac diagnostics,opening up prospects for its use along with more complex neural network architectures.

关键词： Electrocardiography 12-lead electrocardiogram myocardial infarction heart disease learning vector quantization algorithm machine learning

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Underwater RGB-D imaging system with millimetric precision

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Science China(Information Sciences) 2024年第10期67卷 383-385页

作者： Yajun GAO Yang CONG Xu TANG Mingxue LI State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences College of Automation Science and Engineering South China University of Technology

In recent years, underwater fine three-dimensional reconstruction technology has emerged as a focal point in research, exhibiting extensive potential applications, particularly in underwater archaeology and resource e...

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A trajectory-level robot skill learning method based on fuzzy systems

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Science China(Information Sciences) 2025年第5期68卷 38-52页

作者： Chao ZENG Zhen DENG Boyang TI Yongsheng GAO Department of Computer Science University of Liverpool School of Mechanical Engineering and Automation Fuzhou University State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics and System Harbin Institute of Technology

Learning from demonstration(LfD) allows for the effective transfer of human manipulation skills to a robot by building a model that represents these skills based on a limited number of demonstrated ***,a skilllearning model that can comprehensively satisfy multiple requirements,such as computational complexity,modeling accuracy,trajectory smoothness,and robustness,is still ***,this work aims to provide such a model by employing fuzzy ***,we introduce an LfD model named Takagi-Sugeno-Kang fuzzy system-based movement primitives(TSKFMPs),which exploits the advantages of the fuzzy theory for effective robotic imitation learning of human *** work formulates the TSK fuzzy system and gradient descent(GD) as imitation learning models,leveraging recent advancements in GD-based optimization for fuzzy *** study takes a two-step strategy.(ⅰ) The input-output relationships of the model are established using TSK fuzzy systems based on demonstration *** this way,the skill is encoded by the model parameter in the latent space.(ⅱ) GD is used to optimize the model parameter to increase the modeling accuracy and trajectory *** further explain how learned trajectories are adapted to new task scenarios through local *** conduct multiple tests using an open dataset to validate our method,and the results demonstrate performance comparable with those of other ***,we implement it in a real-world case study.

关键词： robot skill learning movement primitives TSK fuzzy systems gradient descent robotics

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Smart Rear Underrun Safety Shield (Sruss) for Hybrid Vehicles to Prevent Collisions with the Rear of Heavy Trailers

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Journal of engineering Science and Technology Review 2024年第4期17卷 83-98页

作者： Patil, Rajesh V. Department of Mechanical – Robotics & Automation Engineering MIT World Peace University Maharashtra Pune India

The deadliest accident ratio for cars and trucks on highways occurs when vehicles are running underneath trucks, causing serious and even fatal injuries to the occupants of the vehicle. When heavyweight trucks collide with automobiles, passengers in the car are not shielded from potentially deadly injuries by the back safety shield's improper geometry. A Smart Rear Underrun Safety Shield (SRUSS) for rear impact and rear underrunning of hybrid passenger cars and heavyduty trailers was created because of this work. According to testing conducted by the Vehicle Research and Development Establishment (VRDE), the current safety shield has higher distortion. Finite element analysis was used to model and test the cleverly adapted safety shield under Indian Standard 14812-2005 regulatory circumstances. Additionally, it was produced and tested internally with the same regulatory requirements. A certified testing setup was used to effectively confirm the safety shield. Through accreditation from the Automobile Research Association of India (ARAI) and real-world verification testing at VRDE, the performance of a proposed Smart Rear Underrun Safety Shield (SRUSS) for hybrid vehicles was examined. The results obtained have satisfied the road transport safety standards of the Indian Standard 14812-2005. © 2024 School of Science, DUTH. All rights reserved.

关键词： Trucks

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Teleoperation with automatic posture regulation and broad learning control for assembly tasks

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Science China(Information Sciences) 2024年第11期67卷 359-360页

作者： Liwen SITU Zhenyu LU Chenguang YANG School of Automation Science and Engineering South China University of Technology Bristol Robotics Laboratory University of the West of England

In recent years, robot teleoperation systems have been widely used in assembly tasks due to their ability to combine human control with robotic execution, addressing limitations in precision, perception, and intelligence faced by fully automated robots. However, robot teleoperation for assembly tasks still encounters several challenges. In complex and unstructured environments, telerobots must regulate the posture of their manipulators to avoid obstacles and singularities, ensuring the safety of human operators [1].

关键词： Remote control

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Theoretical Model Construction and Static Performance Analysis of Multi-Leaf Journal Foil Bearings

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Journal of Tribology 2025年第7期147卷 074101页

作者： Hu, Yang Ding, Pengjing School of Mechatronic Engineering and Automation Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai200072 China

Multi-leaf journal foil bearing (MLJFB) structures are complex, making performance prediction challenging, and the accurate prediction of gas film thickness and pressure distributions is crucial. In this study, comsol finite-element software was used to establish an initial foil assembly and structural deformation simulation model for an MLJFB with bump foils. Using matlab, a compressible gas lubrication model was established and solved using the finite volume method. Real-time data transfer between comsol and matlab enabled a fully coupled fluid-structure interaction simulation. This model meticulously accounts for the pre-tension force in the multi-leaf bearing assembly, contact friction between adjacent foils, and the interaction between the top foil and gas film pressure. The effects of journal movement distance, direction, and top foil overlapping ratio on the bearing capacity as well as the effects of different external load directions on the journal equilibrium position were analyzed based on this model. The results indicate that increasing the top foil overlapping ratio enhances the bearing capacity of the MLJFB. Furthermore, compared to the direction of the top foil overlap position, external loads applied in the direction of the top foil midpoint are more beneficial for bearing operational stability. Copyright © 2024 by ASME.

关键词： MATLAB

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JADFER: Exploring Spatial-Contextual Interaction With Joint Attention Dropping for Facial Expression Recognition

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IEEE Transactions on Affective Computing 2025年第2期16卷 655-668页

作者： Gao, Yu Ren, Weihong Jiang, Weibo Dong, Qian Nie, Wei Wu, Wenhao Liu, Honghai Harbin Institute of Technology State Key Lab of Robotics and Systems School of Mechanical Engineering and Automation Shenzhen518055 China

Facial Expression Recognition (FER) aims to cate-gorize emotional expressions depicted on a human face, and isa challenging task under unconstrained conditions, such as faceocclusions and pose variations. Recent methods usually adopt selfattention or cross attention to explore global or local relationshipsamong different level features. However, these methods are inclinedto focus on the redundant facial regions, causing model *** address this problem, we propose a new FER model namedJADFER, which drops the joint attention in the weight matrix toadaptively enhance facial expression representations. Specifically,our JADFER model consists of three components: Spatial Branch(SB), Contextual Branch (CB), and Spatial-Contextual Interaction(SCI). First, SB runs N paths in parallel, where a Variety loss is de-signed to guide the paths of SB to focus on different discriminativeregions. Meanwhile, CB abstracts the contextual facial represen-tations using self attention with Joint Attention Dropping (JAD).Then, the SCI adopts the spatial features from SB to query thecontextual representations from CB through cross attention withJAD, which regulates the attention weights by dropping the similaractivations to further enhance the facial embeddings. Experimen-tal results demonstrate that the proposed model outperforms thestate-of-the-art methods on several FER benchmarks. © 2010-2012 IEEE.

关键词： Face recognition

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Application of Optimal-Jerk Trajectory Planning in Gait-balance Training Robot

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Chinese Journal of Mechanical engineering 2022年第1期35卷 50-61页

作者： Fu Yuan Diansheng Chen Chenghang Pan Jun Du Xiaodong Wei Min Wang Robotics Institute Mechanical Engineering and AutomationBeihang UniversityBeijing 100191China

To accommodate the gait and balance disorder of the elderly with age progression and the occurrence of various senile diseases,this paper proposes a novel gait balance training robot(G-Balance)based on a six degree-of-freedom parallel *** the platform movement and IMU wearable sensors,two training modes,i.e.,active and passive,are developed to achieve vestibular *** reality technology is applied to achieve visual *** the active training mode,the elderly actively exercises to control the posture change of the platform and the switching of the virtual *** the passive training mode,the platform movement is combined with the virtual scene to simulate bumpy environments,such as earthquakes,to enhance the human anti-interference *** achieve a smooth switching of the scene,continuous speed and acceleration of the platform motion are required in some scenarios,in which a trajectory planning algorithm is *** paper describes the application of the trajectory planning algorithm in the balance training mode and the optimization of jerk(differential of acceleration)based on cubic spline planning,which can reduce impact on the joint and enhance stability.

关键词： Gait and balance training robot Balance training mode Optimal trajectory planning

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Enhancing retinal fundus image classification through Active Gradient Deep Convolutional Neural Network and Red Spider Optimization

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Neural Computing and Applications 2024年第26期36卷 16607-16619页

作者： Subramaniam, Krishnakumar Naganathan, Archana Department of Robotics and Automation Sri Ramakrishna Engineering College Coimbatore India Department of Electrical and Electronics Engineering PSG College of Technology Coimbatore India

Retinal fundus image classification is pivotal for the early detection of various eye disorders. Leveraging advancements in deep learning, this research introduces a robust framework for retinal fundus image classification. In this research paper, we introduce a novel methodology that integrates the Active Gradient Deep Convolutional Neural Network (AG-DCNN) architecture with the Red Spider Optimization (RSO) algorithm. Extensive evaluations conducted on well-established retinal image datasets such as DRIVE, STARE, CHASE DB1, HRF, DRISHTI-GS, and RFMiD illustrate substantial enhancements in classification accuracy, sensitivity, and specificity when compared to conventional approaches. The AG-DCNN with RSO exhibits superior performance and remarkable generalization abilities across diverse datasets. This novel approach not only enhances the latest advances in retinal image classification but also holds promise for early disease diagnosis and improved patient care. Through extensive examinations, our proposed method consistently outperforms established techniques, establishing itself as the benchmark in retinal fundus image classification. The integration of AG-DCNN and RSO showcases its efficacy and potential impact in advancing the field of medical image analysis. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Image classification

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