检索结果-内蒙古大学图书馆

Regulating Hydrogen/Oxygen Species Adsorption via Built-in Electric Field -Driven Electron Transfer Behavior at the Heterointerface for Efficient Water Splitting

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Angewandte Chemie 2024年第16期136卷

作者： Wenjie Zhang Prof. Lei Yang Zhi Li Guangzhi Nie Xuejie Cao Zizheng Fang Prof. Xiaojun Wang Prof. Seeram Ramakrishna Prof. Yunze Long Prof. Lifang Jiao Collaborative Innovation Center for Nanomaterials & Devices College of Physics Qingdao University Qingdao 266071 China Research Center for Smart Intelligent and Wearable Technology College of Textiles and Clothing Qingdao University Qingdao 266071 China Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education) College of Chemistry Nankai University Tianjin 300071 China College of Electromechanical Engineering Qingdao University of Science & Technology Qingdao 266061 China Center for Nanotechnology & Sustainability Department of Mechanical Engineering College of Design and Engineering National University of Singapore 9 Engineering Drive 1 Singapore 117576

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Vibration Absorption Efficiency and Higher Branches Elimination of Variable-Stiffness Nonlinear Energy Sink

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Journal of Harbin Institute of Technology 2020年第1期

作者： Rui Zhong Jian’en Chen Weimin Ge Jun Liu Xiaofeng Wang Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System National Demonstration Center for Experimental Mechanical and Electrical Engineering Education

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Dynamic Constructing 3D Electronic Technical Manual of Mechanical Products Based on Publishing Rules

Dynamic Constructing 3D Electronic Technical Manual of Mecha...

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第二届人工智能、网络与信息技术国际研讨会

作者： Feng Zhao Aijian Wu Lijuan Yan Shen li State Key Laboratory of Intelligent Manufacturing of Advanced Construction Machinery Jiangsu XCMG Construction Machinery Research Institute Ltd. Key Laboratory of Electronic Equipment Structure Design of Ministry of Education School of Mechano-electronic EngineeringXidian Univ.

In order to solve the different contents of 3D Electronic Technical Manual(3DETM) for classified users in the Process of Publishing Mechanical Products, a method of dynamic constructing 3DETM is presented based on publishing rules. Firstly, the object data of 3DETM was extracted automatically;then the publishing behavior of 3DETM was encapsulated by CAD API method. Finally, the dynamic mapping between different classified users and the publishing contents modes of 3DETM was realized by defining Publishing Rules. Validation in the prototype software developed shows that the 3DETM was constructed dynamically for classified users.

关键词： API CAD Dynamic Constructing 3D Electronic Technical Manual of Mechanical Products Based on Publishing Rules

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Research on Fast Error Calibration Methods for Flexible Measuring Arm

Research on Fast Error Calibration Methods for Flexible Meas...

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International Conference on Artificial Intelligence and advanced Manufacturing (AIAM)

作者： Xinhua Zhao Lei Zhao Liangping Ji Jiaxing Zhang School of Mechanical Engineering Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

Based on the structure of the joint coordinate measuring machine, the error calibration of the flexible measuring arm is systematically and deeply researched. The straightness error data of the two linear guide rails are obtained by measuring the high-precision square box. Then, the slope of the straightness error curve is obtained by least squares method, and the verticality error can be also calculated. The parallelism error for two rotation axes can be calibrated by test a precision flat. Its result can be quickly compute based on the sampling data. The proposing calibration methods have low cost, easy operation, high efficiency and small environmental restrictions than external calibration by expensive instruments. The experiment has proved the validity and feasibility of the above method.

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DeepACE: Automated chromosome enumeration in metaphase cell images using deep convolutional neural networks

arXiv

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arXiv 2019年

作者： Xiao, Li Luo, Chunlong Luo, Yufan Yu, Tianqi Tian, Chan Qiao, Jie Zhao, Yi Key Laboratory of Intelligent Information Processing Advanced Computer Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing China Peking University Third Hospital Beijing China Beijing China

Chromosome enumeration is an important but tedious procedure in karyotyping analysis. In this paper, to automate the enumeration process, we developed a chromosome enumeration framework, DeepACE, based on the region based object detection scheme. Firstly, the ability of region proposal network is enhanced by a newly proposed Hard Negative Anchors Sampling to extract unapparent but important information about highly confusing partial chromosomes. Next, to alleviate serious occlusion problems, we novelly introduced a weakly-supervised mechanism by adding a Template Module into classification branch to heuristically separate overlapped chromosomes. The template features are further incorporated into the NMS procedure to further improve the detection of overlapping chromosomes. In the newly collected clinical dataset, the proposed method outperform all the previous method, yielding an mAP with respect to chromosomes as 99.45, and the error rate is about 2.4%. Copyright © 2019, The Authors. All rights reserved.

关键词： Chromosomes

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Open set recognition of radar specific emitter based on adversarial reciprocal point learning

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Signal Processing 2026年 238卷

作者： Wenxu Zhang Lin An Wencheng Yang Zhongkai Zhao Feiran Liu College of Information and Communication Engineering Harbin Engineering University Harbin 150001 China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin Engineering University Harbin 150001 China AVIC United Technology Center for Electromagnetic Spectrum Collaborative Detection and Intelligent Cognition Harbin Engineering University Harbin 150001 China Yantai Research Institute Harbin Engineering University Yantai 264001 China School of Mathematics Physics and Computing University of Southern Queensland Toowoomba QLD 4350 Australia Department of Electrical Engineering Wright State University Dayton OH 45435 USA

Radar specific emitter identification (SEI) is a key technology in electromagnetic spectrum control. Although the emergence of deep learning has promoted the development of SEI, there are still many shortcomings in the current research results. Most of the traditional deep learning algorithms are applicable to closed-set identification and can only be used when the database is complete. In addition, individual differences in radar signals are susceptible to noise interference, but traditional denoising methods are usually independent of the feature extraction process, making it difficult to ensure that certain individual information is not lost. Therefore, in this paper, we propose a new radar emitter open set recognition method called adversarial reciprocal point learning with adaptive denoising (ARPLAD). Firstly, we design a new feature extraction network for one-dimensional signals, which combines deep residual shrinkage network with efficient attention mechanism to autonomously denoise signals and focus on important parts of signal features. Secondly, we train the network using adversarial reciprocal point learning combined with center loss to extract discriminative features with compact intraclass distances and separable interclass distances, which can efficiently discriminate unknown signals and reduce the risk of open set identification. The experimental results show that ARPLAD exhibits excellent performance in different conditions, providing an effective solution for SEI in open electromagnetic environments.

关键词： Deep learning Radar specific emitter identification Open set recognition Adversarial reciprocal point learning

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Simulation of crystal plasticity of P92 heat resistant steel considering martensitic lath structure

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Journal of Physics: Conference Series 2021年第1期2079卷

作者： Xinyu Wang Junjie Shen Xiangru Guo Jixin Qiao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin 300384 China

Based on the theory of crystal plasticity, coupled with dislocation and lath hardening models, this paper establishes a crystal plasticity finite element model describing the high temperature creep of P92 steel. Open source software was used to generate lath models with an average size of 350nm, 650nm and 950nm to explore the effect of lath coarsening on the high-temperature creep behavior of P92 steel. The results show that the roughening of the slats increases the rate of creep deformation, resulting in a decrease in the service life of the material. Observing the slat model, it can be seen that the roughening of the slats enlarges the numerical gradient of stress and strain, and aggravates the overall plastic strain of the model. The coarsening of the slats accelerates the movement of dislocations, causing the density of movable dislocations to increase, and at the same time the shear strain amplitude of the slip system increases, thereby reducing the hardening behavior of the material.

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DPANet: Depth potentiality-aware gated attention network for RGB-D salient object detection

arXiv

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arXiv 2020年

作者： Chen, Zuyao Cong, Runmin Xu, Qianqian Huang, Qingming The School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100190 China The Institute of Information Science Beijing Jiaotong University Beijing100044 China The Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China The Department of Computer Science City University of Hong Kong Hong Kong Hong Kong The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing101408 China Peng Cheng Laboratory Shenzhen518055 China

There are two main issues in RGB-D salient object detection: (1) how to effectively integrate the complementarity from the cross-modal RGB-D data;(2) how to prevent the contamination effect from the unreliable depth map. In fact, these two problems are linked and intertwined, but the previous methods tend to focus only on the first problem and ignore the consideration of depth map quality, which may yield the model fall into the sub-optimal state. In this paper, we address these two issues in a holistic model synergistically, and propose a novel network named DPANet to explicitly model the potentiality of the depth map and effectively integrate the cross-modal complementarity. By introducing the depth potentiality perception, the network can perceive the potentiality of depth information in a learning-based manner, and guide the fusion process of two modal data to prevent the contamination occurred. The gated multi-modality attention module in the fusion process exploits the attention mechanism with a gate controller to capture long-range dependencies from a cross-modal perspective. Experimental results compared with 16 state-of-the-art methods on 8 datasets demonstrate the validity of the proposed approach both quantitatively and qualitatively. Copyright © 2020, The Authors. All rights reserved.

关键词： Modal analysis

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Augmented Reality and Quick Response Code Technology in Engineering Drawing Course

Augmented Reality and Quick Response Code Technology in Engi...

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IEEE International Conference on Mechatronics and Automation

作者： Xiaofei Wang Chenfei Chen Zhaotong Li Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin China School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin China School of Mechanical Engineering Tianjin University of Technology Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

Augmented reality (AR) technology is a cutting technology. It can enhance the perception of reality and provide more information of the real world. AR technology is used in many fields, like medical, industry, and education. In this paper, AR is introduced into engineering drawing course. Engineering drawing course is difficult to learn as it is a knowledge that students rarely contact with. To have a close contact with the models and the views, a convenient AR application (AR app) is proposed in the paper. With the help of the AR app, virtual models and real views are combined well. The models can be moved and rotated by touching the screen. Some videos of model assembly and disassembly can be obtained when scanning the quick response code (QR code). Thus, it is convenient for students to use mobile phone to study engineering drawing effectively. The interactive teaching environment enhances students' spatial thinking and cultivates their sense of innovation.

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Jacobi Spectral Collocation Method Based on Lagrange Interpolation Polynomials for Solving Nonlinear Fractional Integro-Differential Equations

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Advances in Applied Mathematics and Mechanics 2018年第6期10卷 1440-1458页

作者： Xingfa Yang Yin Yang Yanping Chen Jie Liu State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan UniversityChangsha 410082HunanChina Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing&Information Processing of Ministry of EducationSchool of Mathematics and Computational ScienceXiangtan UniversityXiangtan 411105HunanChina School of Mathematical Sciences South China Normal UniversityGuangzhou 510631GuangdongChina Center for Research on Leading Technology of Special Equipment School of Mechanical and Electric EngineeringGuangzhou UniversityGuangzhou 510006GuangdongChina

In this paper,we study a class of nonlinear fractional integro-differential equations,the fractional derivative is described in the Caputo *** the properties of the Caputo derivative,we convert the fractional integro-differential equations into equivalent integral-differential equations of Volterra type with singular kernel,then we propose and analyze a spectral Jacobi-collocation approximation for nonlinear integro-differential equations of Volterra *** provide a rigorous error analysis for the spectral methods,which shows that both the errors of approximate solutions and the errors of approximate fractional derivatives of the solutions decay exponentially in L^(∞)-norm and weighted L^(2)-norm.

关键词： Spectral method nonlinear fractional derivative Volterra integro-differential equations Caputo derivative

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