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Dynamic modeling and RBF neural network compensation control for space flexible manipulator with an underactuated hand

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Chinese Journal of Aeronautics 2024年第3期37卷 417-439页

作者： Dongyang SHANG Xiaopeng LI Meng yin Fanjie LI School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China

In space operation,flexible manipulators and gripper mechanisms have been widely used because of light weight and ***,the vibration caused by slender structures in manipulators and the parameter perturbation caused by the uncertainty derived from grasping mass variation cannot be *** existence of vibration and parameter perturbation makes the rotation control of flexible manipulators difficult,which seriously affects the operation accuracy of ***’s more,the complex dynamic coupling brings great challenges to the dynamics modeling and vibration *** solve this problem,this paper takes the space flexible manipulator with an underactuated hand(SFMUH)as the research *** dynamics model considering flexibility,multiple nonlinear elements and disturbance torque is established by the assumed modal method(AMM)and Hamilton’s principle.A dynamic modeling simplification method is proposed by analyzing the nonlinear ***’s more,a sliding mode control(SMC)method combined with the radial basis function(RBF)neural network compensation is ***,the control law is designed using a saturation function in the control method to weaken the chatter *** the help of neural networks to identify the uncertainty composition in the SFMUH,the tracking accuracy is *** results of ground control experiments verify the advantages of the control method for vibration suppression of the SFMUH.

关键词： Space flexible manipulator RBF neural network Underactuated hand Dynamic models Model simplification

Research on Credit Regulation Mechanism of E-commerce Platform Based on Evolutionary Game Theory

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Journal of Systems Science and Systems Engineering 2024年第3期33卷 330-359页

作者： Zeguo Qiu Yuchen yin Yao Yuan Yunhao Chen School of Computer and Information Engineering Harbin University of CommerceHarbin150028China School of Management Harbin University of CommerceHarbin150028China

In the growing e-commerce industry,the problem of malicious business operations has become increasingly prominent,exposing many problems such as weak supervision of e-commerce platforms and no way for consumers to *** order to solve the problems of counterfeit and shoddy products on e-commerce platforms and promote the sustainable development of the e-commerce industry in China,this paper constructs a three-party evolutionary game model of e-commerce platforms,merchants,and consumers,investigates the influence of each influencing factor on each party’s strategy choice,and provides targeted suggestions to e-commerce platforms based on relevant ***,the impact of several important parameters on the equilibrium solution is discussed through sensitivity *** results show that:1)the smaller the cost difference between active and negative regulation,the more the e-commerce platform tends to active regulation strategy,but increasing fines for dishonest merchants and consumer complaints have little impact on the e-commerce platform;2)increasing consumer compensation,creating an honest business environment,and reducing the cost of honest business all help companies tend to operate in good faith;3)the only factor that affects the tendency of consumer complaint strategies is the cost of *** loss suffered by silence and the compensation given to consumers have little effect on consumers’tendency to complain *** results can provide theoretical guidance for participants to make useful strategic decisions in the e-commerce market.

关键词： Evolutionary game e-commerce data simulation

A Dual-Task Learning Approach for Bearing Anomaly Detection and State Evaluation of Safe Region

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Chinese Journal of Mechanical Engineering 2024年第1期37卷 229-241页

作者： Yuhua yin Zhiliang Liu Bin Guo Mingjian Zuo School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Qingdao International Academician Park Research Institute Qingdao 266041China

Predictive maintenance has emerged as an effective tool for curbing maintenance costs,yet prevailing research predominantly concentrates on the abnormal *** the ostensibly stable healthy phase,the reliance on anomaly detection to preempt equipment malfunctions faces the challenge of sudden anomaly *** address this challenge,this paper proposes a dual-task learning approach for bearing anomaly detection and state evaluation of safe *** proposed method transforms the execution of the two tasks into an optimization issue of the hypersphere *** leveraging the monotonicity and distinguishability pertinent to the tasks as the foundation for optimization,it reconstructs the SVDD model to ensure equilibrium in the model’s performance across the two *** experiments verify the proposed method’s effectiveness,which is interpreted from the perspectives of parameter adjustment and enveloping *** the meantime,experimental results also show two deficiencies in anomaly detection accuracy and state evaluation *** theoretical analysis inspires us to focus on feature extraction and data collection to achieve *** proposed method lays the foundation for realizing predictive maintenance in a healthy stage by improving condition awareness in safe regions.

关键词： Bearing condition monitoring Anomaly detection Safe region Support vector data description

New structure transistors for advanced technology node CMOS ICs

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National Science Review 2024年第3期11卷 24-41页

作者： Qingzhu Zhang Yongkui Zhang Yanna Luo Huaxiang yin Integrated Circuit Advanced Process R&D Center Institute of Microelectronics of Chinese Academy of Sciences(IMECAS) State key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics of Chinese Academy of Sciences School of Integrated Circuits University of Chinese Academy of Sciences

Over recent decades, advancements in complementary metal-oxide-semiconductor integrated circuits(ICs)have mainly relied on structural innovations in transistors. From planar transistors to the fin field-effect transistor(FinFET) and gate-all-around FET(GAAFET), more gate electrodes have been added to three-dimensional(3D) channels with enhanced control and carrier conductance to provide higher electrostatic integrity and higher operating currents within the same device footprint. Beyond the 1-nm node, Moore's law scaling is no longer expected to be applicable to geometrical shrinkage. Vertical transistor stacking, e.g. in complementary FETs(CFET), 3D stack(3DS) FETs and vertical-channel transistors(VFET), for enhanced density and variable circuit or system design represents a revolutionary scaling approach for sustained IC development. Herein, innovative works on specific structures, key process breakthroughs, shrinking cell sizes and design methodologies for transistor structure research and development are reviewed. Perspectives on future innovations in advanced transistors with new channel materials and operating theories are also discussed.

关键词： transistor CMOS GAAFET CFET 3DS FET

Bioinspired nanomaterials for wearable sensing and human–machine interfacing

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Nano Research 2024年第2期17卷 445-461页

作者： Vishesh Kashyap Junyi yin Xiao Xiao Jun Chen Department of Bioengineering University of CaliforniaLos AngelesLos AngelesCA 90095USA Department of Mechanical and Aerospace Engineering University of CaliforniaLos AngelesLos AngelesCA 90095USA

The inculcation of bioinspiration in sensing and human–machine interface(HMI)technologies can lead to distinctive characteristics such as conformability,low power consumption,high sensitivity,and unique properties like self-healing,self-cleaning,and *** sensing and HMI are fields rife with opportunities for the application of bioinspired nanomaterials,particularly when it comes to wearable sensory systems where biocompatibility is an additional *** review discusses recent development in bioinspired nanomaterials for wearable sensing and HMIs,with a specific focus on state-of-the-art bioinspired capacitive sensors,piezoresistive sensors,piezoelectric sensors,triboelectric sensors,magnetoelastic sensors,and electrochemical *** also present a comprehensive overview of the challenges that have hindered the scientific advancement in academia and commercialization in the industry.

关键词： bioinspired nanomaterials human–machine interface wearable sensors wearable bioelectronics

Neural network modeling and prediction of HfO2 thin film properties tuned by thermal annealing

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High Power Laser Science and Engineering 2024年第2期12卷 79-86页

作者： Min Gao Chaoyi yin Jianda Shao Meiping Zhu School of Microelectronics Shanghai UniversityShanghaiChina Laboratory of Thin Film Optics Key Laboratory of Materials for High Power LaserShanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghaiChina Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijingChina Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhouChina

Plasma-enhanced atomic layer deposition (PEALD) is gaining interest in thin films for laser applications, and post-annealing treatments are often used to improve thin film properties. However, research to improve thin film properties is often based on an expensive and time-consuming trial-and-error process. In this study, PEALD-HfO2 thin film samples were deposited and treated under different annealing atmospheres and temperatures. The samples were characterized in terms of their refractive indices, layer thicknesses and O/Hf ratios. The collected data were split into training and validation sets and fed to multiple back-propagation neural networks with different hidden layers to determine the best way to construct the process–performance relationship. The results showed that the three-hidden-layer back-propagation neural network (THL-BPNN) achieved stable and accurate fitting. For the refractive index, layer thickness and O/Hf ratio, the THL-BPNN model achieved accuracy values of 0.99, 0.94 and 0.94, respectively, on the training set and 0.99, 0.91 and 0.90, respectively, on the validation set. The THL-BPNN model was further used to predict the laser-induced damage threshold of PEALD-HfO2 thin films and the properties of the PEALD-SiO2 thin films, both showing high accuracy. This study not only provides quantitative guidance for the improvement of thin film properties but also proposes a general model that can be applied to predict the properties of different types of laser thin films, saving experimental costs for process optimization.

关键词： laser-induced damage threshold laser thin film neural network plasma-enhanced atomic layer deposition

A multiscale differential-algebraic neural network-based method for learning dynamical systems

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International Journal of Mechanical System Dynamics 2024年第1期4卷 77-87页

作者： yin Huang Jieyu Ding College of Computer Science&Technology Qingdao UniversityQingdaoChina School of Mathematics and Statistics Qingdao UniversityQingdaoChina Center for Computational Mechanics and Engineering Simulation Qingdao UniversityQingdaoChina

The objective of dynamical system learning tasks is to forecast the future behavior of a system by leveraging observed ***,such systems can sometimes exhibit rigidity due to significant variations in component parameters or the presence of slow and fast variables,leading to challenges in *** overcome this limitation,we propose a multiscale differential-algebraic neural network(MDANN)method that utilizes Lagrangian mechanics and incorporates multiscale information for dynamical system *** MDANN method consists of two main components:the Lagrangian mechanics module and the multiscale *** Lagrangian mechanics module embeds the system in Cartesian coordinates,adopts a differential-algebraic equation format,and uses Lagrange multipliers to impose constraints explicitly,simplifying the learning *** multiscale module converts high-frequency components into low-frequency components using radial scaling to learn subprocesses with large differences in *** results demonstrate that the proposed MDANN method effectively improves the learning of dynamical systems under rigid conditions.

关键词： dynamical systems learning multibody system dynamics differential-algebraic equation neural networks multiscale structures

Dynamic Scene Graph Generation of Point Clouds with Structural Representation Learning

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Tsinghua Science and Technology 2024年第1期29卷 232-243页

作者： Chao Qi Jianqin yin Zhicheng Zhang Jin Tang School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China Standard and Metrology Research Institute China Academy of Railway Sciences Corporation LimitedBeijing 100081China

Scene graphs of point clouds help to understand object-level relationships in the 3D *** graph generation methods work on 2D structured data,which cannot be used for the 3D unstructured point cloud *** point-cloud-based methods generate the scene graph with an additional graph structure that needs labor-intensive manual *** address these problems,we explore a method to convert the point clouds into structured data and generate graphs without given ***,we cluster points with similar augmented features into groups and establish their relationships,resulting in an initial structural representation of the point ***,we propose a Dynamic Graph Generation Network(DGGN)to judge the semantic labels of targets of different *** dynamically splits and merges point groups,resulting in a scene graph with high *** show that our methods outperform other baseline *** output reliable graphs describing the object-level relationships without additional manual labeled data.

关键词： scene graph generation structural representation point cloud

Soluble ST2:A Novel Biomarker for Diagnosis and Prognosis of Cardiovascular Disease

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当代医学科学（英文） 2024年第4期44卷 669-679页

作者： yin FENG Li-qun HE Department of Cardiology Traditional Chinese and Western Medicine Hospital of WuhanTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030China

The increasing incidence of cardiovascular disease(CVD)is a significant global health concern,affecting millions of individuals each *** diagnosis of acute CVD poses a formidable challenge,as misdiagnosis can significantly decrease patient survival *** biomarkers have played a vital role in the diagnosis and prognosis of CVDs,but they can be influenced by various factors,such as age,sex,and renal *** ST2(sST2)is a novel biomarker that is closely associated with different *** low reference change value makes it suitable for continuous measurement,unaffected by age,kidney function,and other confounding factors,facilitating risk stratification of ***,the combination of sST2 with other biomarkers can enhance diagnostic accuracy and prognostic *** review aims to provide a comprehensive overview of sST2,focusing on its diagnostic and prognostic value as a myocardial marker for different types of CVDs and discussing the current limitations of sST2.

关键词： cardiovascular disease combined biomarker diagnosis and prognosis limitations soluble ST2