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Single-gait crawling robot:A solution for improving mobility and payload of soft locomotor via simple structure and easy control

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Science China(Technological Sciences) 2024年第11期67卷 3626-3628页

作者： MA Hao HAO TianZe MA JiChao SUN ZhenHao LI Xiang LIU YiBo XIAO HuaPing LIU ShuHai College of Mechanical and Transportation Engineering China University of Petroleum-BeijingBeijing 102249China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin 300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education(Tianjin University of Technology) Tianjin 300384China

Motion performance,including movement speed,adaptability to various environments,and load-carrying capability,is crucial for soft crawling robots,tasked with field exploration and the transporting material in often complex and unstructured environments.A wide variety of soft crawling robots,which are driven by electricity[1],chemical power[2],and pressurized fluid[3]to move forward via cyclic deformation,have thus far been inspired by the mobile patterns of soft-bodied animals,such as worms[4],snake[5],octopus[6],*** performance of soft robots in terms of speed and load has developed impressively in recent years.

关键词： robot payload environments

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Development and Implementation of a Wisdom Course Utilizing the "teaching-Innovation-Competition" Model within the Virtual Teaching and Research Section of Mechatronic Engineering Major in China 24

Development and Implementation of a Wisdom Course Utilizing ...

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3rd International Conference on Artificial Intelligence and Education, ICAIE 2024

作者： Chen, Wei Ma, Wenpeng Hu, Wenhua Liu, Fulong Zhang, Xiaotao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China Tianjin University of Technology Tianjin China

ISBN: (纸本)9798400712692

A new teaching model of teaching-innovation-competition is presented and a wisdom course based on this model is developed for mechatronics engineering majors, mainly to deal with several existing problems such as limited experimentation and lack of innovative inspiration in Chinese universities. This study elaborates the course objectives and structure of curriculum system, including digitalized teaching content, project-driven teaching means, innovation platform, web-based resource support, team competition and diversified evaluation method. Through a teaching case study within mechatronic engineering major, the teaching mechanism and achievements are demonstrated. The study results indicate that the proposed teaching mode based on the virtual teaching and research section, significantly improves students' innovation ability and the teaching effects, compared to traditional teaching methods. This teaching mode can also be extended to other majors for reference. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Teaching

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EKIGCN: External Knowledge Injected Graph Convolutional Networks for Aspect-based Sentiment Analysis 9

EKIGCN: External Knowledge Injected Graph Convolutional Netw...

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9th IEEE International Conference on Cloud computing and Intelligence Systems, CCIS 2023

作者： Shi, Xuefeng Hu, Min Ren, Fuji Shi, Piao Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei230000 China University of Electronic Science and Technology of China Sichuan Chengdu611731 China

ISBN: (纸本)9798350304428

Aspect-based sentiment analysis (ABSA) is a challenging subtask in the natural language processing community, which aims to determine the sentiment polarity about the corresponding specific aspect terms. In existing works, external knowledge has been proven effective to improve the ABSA tasks' performance. However, it is still essential to study further to find a universal method for ABSA tasks. Therefore, we propose an external knowledge-injected graph convolutional network (EKIGCN) to enhance the sentiment representation with commonsense. Specifically, Sentic Net is leveraged to provide external knowledge to construct an affective dependency graph. In order to fully exploit the effectiveness of affective knowledge, a shallow mutual interaction is utilized to fuse the learned contextual representation and the graph. Besides, to make EKIGCN sensitive to aspect terms, an aspect-aware multi-head attention module is also employed to enhance the corresponding relations between aspect and contextual words. Extensive experiments are conducted on three popular datasets to validate the effectiveness of our proposed model, and the results outperform the mentioned state-of-the-art methods in ABSA tasks. © 2023 IEEE.

关键词： Sentiment analysis

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Reliability prediction model of bolted connection based on uncertainty 10

Reliability prediction model of bolted connection based on u...

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2024 10th International Conference on Applied Materials and Manufacturing Technology, ICAMMT 2024

作者： Niu, Nana Zhao, Yongsheng Zhang, Caixia Machinery Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Technology Beijing University of Technology Beijing100124 China Institute of Advanced Manufacturing and Intelligent Technology Beijing University of Technology Beijing100124 China

During the service of bolts, their preload exhibits a random decreasing trend due to external loads, affecting contact stiffness and connection reliability. System uncertainties can also lead to preload variations within the same group of bolts. In this paper, we use the Wiener process to model this preload decrease, incorporating drift and wave coefficients to capture temporal variability and system uncertainty. This approach accounts for monotonic preload reduction and random fluctuations, enabling accurate calculations. By integrating the time-varying preload uncertainty into the bolted structure's contact stiffness model, we establish a limit state function for structural failure and assess the reliability of the bolted connection over time. © Published under licence by IOP Publishing Ltd.

关键词： Bolted joints

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Virtual Models for Operating on Mobile Devices 3

Virtual Models for Operating on Mobile Devices

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3rd International Conference on Mechatronics and Automation Technology, ICMAT 2024

作者： Wang, Xiaofei Xu, Jinyou Xue, Yahong Zhang, Runfeng Hao, Tianze Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China

ISBN: (纸本)9781643685649

In recent years, the virtual reality technique has been widely used in many fields. One of the most popular applications is for generating virtual models that can be operated on the screen. In the paper, three methods of obtaining virtual models are introduced. One method is by scanning the quick response code. Another method is the use of CADbro software. The third way is to develop an app to help the digital world emerge in real-life scenarios. With the help of virtual technology, ways of teaching, modes of production, and film production are changing. The three methods mentioned in the paper make it easy to generate virtual models for people to operate on mobile devices. Virtual models generated by the three methods can be operated by touching the screen or operating the mouse, whenever and wherever. © 2024 The Authors.

关键词： Virtual environments

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Flow and thermal modeling of liquid metal in expanded microchannel heat sink

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Frontiers in Energy 2023年第6期17卷 796-810页

作者： Mingkuan ZHANG Xudong ZHANG Luna GUO Xuan LI Wei RAO Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin 300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of TechnologyTianjin 300384China Key Laboratory for Thermal Science and Power Engineering of the Ministry of Education Department of Engineering MechanicsTsinghua UniversityBeijing 100084China School of Mechanical Engineering Tianjin University of CommerceTianjin 300134China Institute of Refrigeration and Cryogenics Shanghai Jiao Tong UniversityShanghai 200240China Beijing Key Laboratory of CryoBiomedical Engineering and Key Laboratory of Cryogenics Beijing 100190China

Liquid metal-based microchannel heat sinks (MCHSs) suffer from the low heat capacity of coolant, resulting in an excessive temperature rise of coolant and heat sink when dealing with high-power heat dissipation. In this paper, it was found that expanded space at the top of fins could distribute the heat inside microchannels, reducing the temperature rise of coolant and heat sink. The orthogonal experiments revealed that expanding the top space of channels yielded similar temperature reductions to changing the channel width. The flow and thermal modeling of expanded microchannel heat sink (E-MCHS) were analyzed by both using the 3-dimensional (3D) numerical simulation and the 1-dimensional (1D) thermal resistance model. The fin efficiency of E-MCHS was derived to improve the accuracy of the 1D thermal resistance model. The heat conduction of liquid metal in Z direction and the heat convection between the top surface of fins and the liquid metal could reduce the total thermal resistance (Rt). The above process was effective for microchannels with low channel aspect ratio, low mean velocity (Um) or long heat sink length. The maximum thermal resistance reduction in the example of this paper reached 36.0%. The expanded space endowed the heat sink with lower pressure, which might further reduce the pumping power (P). This rule was feasible both when fins were truncated (h_(2) < 0, h_(2) is the height of expanded channel for E-MCHS) and when over plate was raised (h_(2) > 0).

关键词： liquid metal cooling heat sink expanded microchannel flow and thermal modeling

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AlphaFold2 and its applications in the fields of biology and medicine

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Signal Transduction and Targeted Therapy 2023年第4期8卷 1630-1643页

作者： Zhenyu Yang Xiaoxi Zeng Yi Zhao Runsheng Chen West China Biomedical Big Data Center West China HospitalSichuan UniversityChengdu 610041China Key Laboratory of Intelligent Information Processing Advanced Computer Research CenterInstitute of Computing TechnologyChinese Academy of SciencesBeijing 100190China Key Laboratory of RNA Biology Center for Big Data Research in HealthInstitute of BiophysicsChinese Academy of SciencesBeijing 100101China Pingshan Translational Medicine Center Shenzhen Bay LaboratoryShenzhen 518118China

AlphaFold2(AF2)is an artificial intelligence(AI)system developed by DeepMind that can predict three-dimensional(3D)structures of proteins from amino acid sequences with atomic-level *** structure prediction is one of the most challenging problems in computational biology and chemistry,and has puzzled scientists for 50 *** advent of AF2 presents an unprecedented progress in protein structure prediction and has attracted much *** release of structures of more than 200 million proteins predicted by AF2 further aroused great enthusiasm in the science community,especially in the fields of biology and ***2 is thought to have a significant impact on structural biology and research areas that need protein structure information,such as drug discovery,protein design,prediction of protein function,et *** the time is not long since AF2 was developed,there are already quite a few application studies of AF2 in the fields of biology and medicine,with many of them having preliminarily proved the potential of *** better understand AF2 and promote its applications,we will in this article summarize the principle and system architecture of AF2 as well as the recipe of its success,and particularly focus on reviewing its applications in the fields of biology and *** of current AF2 prediction will also be discussed.

关键词： system fields Fold

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Theoretical and experimental study of amorphization and lattice transformation of pure magnesium by ultra-precision cutting method

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Journal of Magnesium and Alloys 2025年

作者： He, Chunlei Wang, Shuqi Xia, Siyu Ren, Chengzu Tianjin Key Laboratory of Equipment Design and Manufacturing Technology Tianjin University Tianjin300354 China Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System Tianjin University of Technology Tianjin300384 China

Pure magnesium is a very promising material in the fields of biomedical and engineering. Obtaining pure magnesium with superior mechanical properties has consistently been a significant challenge in the area of materials science. This study focuses on investigating the processing method and strengthening mechanism of pure magnesium by ultra-precision cutting. The research results show that the pure magnesium grains were significantly refined after ultra-precision cutting. The average grain size reduced from ∼24 µm to nanometers, and the average nano-hardness increased from 1.02 GPa to 2.82 GPa. Amorphous pure magnesium structure and body-centered cubic (BCC) lattice pure magnesium were reported. Molecular dynamics (MD) simulation confirmed that the high shear strain and hydrostatic pressure during ultra-precision cutting was the origin of amorphization and lattice transformation. The amorphous phase and a significant number of long-period stacking-ordered (LPSO) phases inside the pure magnesium were responsible for the high hardness after ultra-precision cutting. © 2025

关键词： Shear strain

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Research on Practical Teaching System of intelligent Manufacturing Engineering: A Case Study of Major design 24

Research on Practical Teaching System of Intelligent Manufac...

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2024 International Conference on Artificial Intelligence and Future Education, AIFE 2024

作者： Yang, Lu Wu, Yining Li, Zeyu Zhang, Guobin Tian, He Tianjin Key Laboratory for Advanced Mechanical 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

ISBN: (纸本)9798400710650

Based on the construction requirements of the "Emerging Engineering"major in intelligent manufacturing engineering and the characteristics of interdisciplinary integration, the cultivation of high-quality interdisciplinary talents has been established as the primary objective. By coordinating multiple on-campus and off-campus resources and fostering cohesion within the entire discipline supervisor team, the "academic supervisor system"training mode has been established, and the continuous training mechanism for "undergraduate and master's"programs has been effectively developed. Additionally, school-enterprise collaborations have been implemented, and practical bases have been successfully established. With the support of the entire discipline supervisor team and the closed-loop integrated laboratory, the practical teaching system characterized by cross-integration and systematic progression has been developed at our university. By creating a step-by-step, planned, and systematic practical course system, the issues of standardization, randomization, and fragmentation within practical courses have been effectively resolved. Through the integration of project-based courses and school-enterprise co-constructed courses, students' innovative abilities are further enhanced. It then describes the design and implementation methods of major design, and analyzes its practical effects. It holds significant reference and demonstrative value for the construction of practical courses, laboratories, and the talent cultivation model of the "Emerging Engineering"major. © 2024 Copyright held by the owner/author(s).

关键词： Smart manufacturing

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A Novel Feature Selection Strategy Based on Salp Swarm Algorithm for Plant Disease Detection

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Plant Phenomics 2023年第2期5卷 209-225页

作者： Xiaojun Xie Fei Xia Yufeng Wu Shouyang Liu Ke Yan Huanliang Xu Zhiwei Ji College of Artificial Intelligence Nanjing Agricultural UniversityNanjingJiangsu 210095China Center for Data Science and Intelligent Computing Nanjing Agricultural UniversityNanjingJiangsu 210095China State Key Laboratory for Crop Genetics and Germplasm Enhancement Bioinformatics CenterAcademy for Advanced Interdisciplinary StudiesNanjing Agricultural UniversityNanjingJiangsu 210095China Academy for Advanced Interdisciplinary Studies Nanjing Agricultural UniversityNanjingJiangsu 210095China Department of the Built Environment College of Design and EngineeringNational University of Singapore4 Architecture DriveSingapore 117566Singapore

Deep learning has been widely used for plant disease recognition in smart agriculture and has proven to be a powerful tool for image classification and pattern ***,it has limited interpretability for deep *** the transfer of expert knowledge,handcrafted features provide a new way for personalized diagnosis of plant ***,irrelevant and redundant features lead to high *** this study,we proposed a swarm intelligence algorithm for feature selection[salp swarm algorithm for feature selection(SSAFS)]in image-based plant disease *** is employed to determine the ideal combination of handcrafted features to maximize classification success while minimizing the number of *** verify the effectiveness of the developed SSAFS algorithm,we conducted experimental studies using SSAFS and 5 metaheuristic *** evaluation metrics were used to evaluate and analyze the performance of these methods on 4 datasets from the UCI machine learning repository and 6 plant phenomics datasets from *** results and statistical analyses validated the outstanding performance of SSAFS compared to existing state-of-the-art algorithms,confirming the superiority of SSAFS in exploring the feature space and identifying the most valuable features for diseased plant image *** computational tool will allow us to explore an optimal combination of handcrafted features to improve plant disease recognition accuracy and processing time.

关键词： Plant image redundant

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