检索结果-内蒙古大学图书馆

AIGC-empowered smart manufacturing: Prospects and challenges

robotics and Computer-Integrated manufacturing 2026年 97卷

作者： Jiewu Leng keyou Zheng Rongjie Li Chong Chen Baicun Wang Qiang Liu Xin Chen Weiming Shen State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangdong University of Technology Guangzhou 510006 China Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing Guangdong University of Technology Guangzhou 510006 China School of Computer Science and Technology Guangdong University of Technology Guangzhou 510006 China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou 310027 China State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan 430074 China

Generative AI (GenAI), the technology behind Artificial Intelligence Generated Content (AIGC), has emerged as a transformative technology in smart manufacturing. However, its full potential and integration within manufacturing processes remain unexplored. This paper presents a comprehensive framework that aligns a GenAI-centered approach with Product Lifecycle Management (PLM), systematically examining the AIGC landscape and its applications across various manufacturing phases. To ensure accuracy and relevance, a human-in-the-loop pipeline is employed to curate and analyze cutting-edge research. key contributions of this study include: 1) a holistic perspective on AIGC-empowered smart manufacturing, 2) an in-depth analysis of the current technological landscape, and 3) the identification of critical research challenges and future directions. Additionally, the paper considers Industry 5.0 principles, emphasizing human-centricity, sustainability, and resilience. By fostering discussion and collaboration, this review aims to advance innovation and unlock the full potential of AIGC in smart manufacturing.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Achieving Injection Molding Interlayer Strength Via Powder Assisted Hot Isostatic Pressing in Material Extrusion Polyetheretherketone

SSRN

引用

SSRN 2023年

作者： Wu, Weidong Xin, Junzhe Hu, Bin Chen, Rong Huang, Dengfeng Huang, Zhongxin Feng, Jiangtao Du, Chun Shan, Bin State Key Laboratory of Material Processing and Die & Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology Wuhan430000 China State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430000 China Wuhan CONSTANT Technology Co. Ltd. No. 818 Gaoxin Avenue Donghu New Technical Development Zone Wuhan430000 China Changzhou LAMBDA Electronic Co. Ltd. Wujin West Taihu Lake Science and Technology Industrial Zone No.56 Guoxiang Road Jiangsu Changzhou213161 China

Polyetheretherketone (PEEK), as fabricated by material extrusion, has the unique advantages of strength-to-mass ratio and biocompatibility in medical applications, yet its practical application is severely hindered by the insufficient interlayer adhesion, typically in the ranges of 5-20 MPa, far below the strength requirement of bone replacement of ~100MPa. In this study, we present a novel powder based hot isostatic pressing (PHIP) treatment to enhance the tensile strength of PEEK manufactured through the material extrusion method. By combining it with material extrusion printing parameters optimization, we successfully achieved a remarkable improvement in interlayer adhesion and tensile strength. In detail, the tensile strength in the Z-axis was measured as 102.6±0.7 MPa, 423.5% higher than those of the state-of-the-art material extrusion PEEK samples and comparable to the tensile strength of injection molding PEEK. The improvement in mechanical properties was attributed to the improved molecular diffusion and crystallinity of PEEK, as observed through scanning electron microscope (SEM) and differential scanning calorimetry (DSC) analysis. Microcomputer tomography (micro-CT) results confirmed the extensive and deep fusion between the extruded filaments and the elimination of most voids. Additionally, the PHIP method demonstrated superior shape retention stability compared to regular thermal annealing. These findings demonstrate the viability of significantly improving the mechanical properties of material extrusion PEEK via PHIP towards its bulk limit and offer a promising solution for enhancing the practical applications of PEEK manufactured through material extrusion. © 2023, The Authors. All rights reserved.

关键词： Tensile strength

来源：评论

学校读者我要写书评

暂无评论

Opt2ada: An Universal Method for Single-Image Low-Light Enhancement

SSRN

引用

SSRN 2022年

作者： Guo, Xiaoyong Zhang, Kai Peng, Jiahan Chen, Xiaoyan Guo, Guangjie College of Electronic Information and Automation Tianjin University of Science and Technology Tianjin300457 China Xingtai Key Laboratory for Research and Application of Robot Intelligent Detection and Sorting Technology Xingtai054001 China College of Mechanical Engineering Tianjin University of Science and Technology Tianjin300457 China School of Physics and Electrical Engineering Xingtai University Xingtai054001 China

In this paper, it is proposed that the task of single-image low-light enhancement can be accomplished by a straightforward method named Opt2Ada in which a series of operations are integrated including an \textbf{opt}imized illuminance map generation, an \textbf{ada}ptive illuminance enhancement, and an \textbf{ada}ptive global scaling. A rich variety of criteria is used for the evaluation, including full-reference, no-reference, and semantic metrics. Extensive experiments on real-world low-light images clearly verify the superiority of Opt2Ada against recently proposed state-of-the-art enhancing algorithms in RGB color space including both traditional and deep learning methods. Opt2Ada neither relies on specific architecture engineering nor dataset collection and preparation. It is not data-driven and its parameters are universal resulting to a generalization capability better than that of the data-driven methods. Moreover, we deploy Opt2Ada on various mobile phones, and find that a native CPU implementation can reach 3-9 frames per second. Since our method is simple and effective, this makes it convenient to be developed by any programming language and imbedded into the pre-processing subroutines for high-level machine vision tasks. © 2022, The Authors. All rights reserved.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Personal Thermal Management by Radiative Cooling and Heating

引用

Nano-Micro Letters 2024年第8期16卷 225-267页

作者： Shidong Xue Guanghan Huang Qing Chen Xungai Wang Jintu Fan Dahua Shou School of Fashion and Textiles The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong 999077People’s Republic of China Future Intelligent Wear Centre The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong 999077People’s Republic of China State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangdong University of TechnologyGuangzhou 510006People’s Republic of China Shanghai International Fashion Innovation Center Donghua UniversityShanghai 200051People’s Republic of China Research Centre of Textiles for Future Fashion The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong 999077People’s Republic of China Research Institute for Smart Energy The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong 999077People’s Republic of China

Maintaining thermal comfort within the human body is crucial for optimal health and overall *** merely broadening the setpoint of indoor temperatures,we could significantly slash energy usage in building heating,ventilation,and air-conditioning *** recent years,there has been a surge in advancements in personal thermal management(PTM),aiming to regulate heat and moisture transfer within our immediate surroundings,clothing,and *** advent of PTM is driven by the rapid development in nano/micro-materials and energy science and *** emerging research area in PTM is personal radiative thermal management(PRTM),which demonstrates immense potential with its high radiative heat transfer efficiency and ease of ***,it is less taken into account in traditional textiles,and there currently lies a gap in our knowledge and understanding of *** this review,we aim to present a thorough analysis of advanced textile materials and technologies for ***,we will introduce and discuss the underlying radiation heat transfer mechanisms,fabrication methods of textiles,and various indoor/outdoor applications in light of their different regulation functionalities,including radiative cooling,radiative heating,and dual-mode ***,we will shine a light on the current hurdles,propose potential strategies,and delve into future technology trends for PRTM with an emphasis on functionalities and applications.

关键词： Personal thermal management Radiative cooling and heating Thermal comfort Dynamic thermoregulation

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Clustering-Based State Grouping Reinforcement Learning for Switching Decision of Autonomous Vehicles

Hierarchical Clustering-Based State Grouping Reinforcement L...

引用

IEEE International Conference on Unmanned Systems (ICUS)

作者： Wenjie Ouyang Yiwen Jiao Yang Liu Yang Li Manjiang Hu Hongmao Qin College of Mechanical and Vehicle Engineering Hunan University Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China College of Electrical Mechanical and Computer Science Delft University of Technology Delft The Netherlands State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle College of Mechanical and Vehicle Engineering Hunan University Changsha China Wuxi Intelligent Control Research Institute of Hunan University Wuxi China

Reinforcement learning (RL) has gained wide attention, but its implementation in autonomous vehicles is still limited by insufficient sample efficiency and heavy training costs. The training efficiency of RL agents is influenced by the dimension of the state space, which can be partitioned to reduce the complexity of sampling and computation. This study proposes a hierarchical clustering-based state grouping reinforcement learning (HCSG-RL) method for the switching decision of autonomous vehicles. First, we partition the base state space into groups and generate a hierarchical tree of state space groups. Then, we train multiple sub-agents for each node in the hierarchical tree. Finally, we add these trained-well sub-model into master policy. This method allows us to fully explore all state spaces and improve the training efficiency of individual agents, which handles the “long-tail” issue and the curse of dimensionality issue. We conduct experiments in a simulation environment and results show that the proposed method has 16–72% reward improvement compared to the tree model in different road length.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Designing of Highly-Efficient Oxygen Evolution Reaction Electrocatalyst-Transition Metal Hydroxyl Phosphates: Theory and Experiment

SSRN

引用

SSRN 2022年

作者： Xia, Junyi Li, Can Gong, Yinyan Niu, Lengyuan Chen, Miaogen Xu, Shiqing Institute of Optoelectronic Materials and Devices College of Optical and Electronic Technology China Jiliang University Hangzhou310018 China School of Electronic Science & Engineering Southeast University Nanjing210096 China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province College of Science China Jiliang University Hangzhou310018 China

The development of a physical factor to correlate the experimental methods and catalytic activity of catalysts is quite important for the design of highly-efficient catalysts. In this work, with the aid of our pre-designed correlation factor of d electron density, a new oxygen evolution reaction electrocatalyst of FeCoPO4 was designed on account of the higher electronegativity of Co atom than Fe atom. The foreign Co atom would enhance the combining capacities of the neighbouring Fe-O bonds, increase the d electron density and reduce the chemical activity of host Fe ions, and thus improve the catalytic activity of Fe based active centers. Based on the theoretical guidance, the prepared FeCoPO4 specimen exhibited low ηexp of 241 mV, fast charge transfer rate and stable electrocatalytic activity. This strategy would be adopted to design highly-efficient catalyst by altering the d electron density of transition metal ions with suitable preparation methods. © 2022, The Authors. All rights reserved.

关键词： Electrocatalysts

来源：评论

学校读者我要写书评

暂无评论

2-D GCANet Applied to Denoise 1-D EEG Signals in Online Remote Teaching Scenarios

Journal of Network Intelligence

引用

Journal of Network Intelligence 2023年第4期8卷 1289-1302页

作者： Huang, Ting-Qing Wang, Chuan-Sheng Chen, Zhao-Qi Zhang, Fu-Quan Meng, Xiang-Long Grau, Antoni Chen, Yang Huang, Jing-Wei College of Computer and Control Engineering Minjiang University Fuzhou University Town No. 200 Xiyuangong Road Fuzhou China Department of Automatic Control Technical Polytechnic University of Catalonia Autonomous Region of Catalonia Barcelona Spain College of Computer and Big Data Fuzhou University Fuzhou University Town No. 2 Wulong Jiangbei Avenue Fuzhou China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music No. 2 Wannianchang Street Chenghua District Sichuan Province Chengdu City China Fuzhou Technology Innovation Center of intelligent Manufacturing information System Minjiang University Fuzhou University Town NO. 200 Xiyuangong Road Fuzhou China Fujian Province University No. 599 Quanxiu Road Juyuanzhou Ecological Civilization District Fujian Province Fuzhou City China College of Electronic Engineering Shandong University of Science and Technology No. 579 Qianwangang Road Huangdao District Qingdao China School of Mechanical and Automotive Engineering Fujian University of Technology No. 33 Xuefu South Road University New District Fujian Province Fuzhou City China

When EEG signals are used to assess the level of student engagement in online teaching tasks, they are often interfered by noise. It is a challenge to effectively remove these noises. Currently, deep learning methods have been applied to the field of EEG denoising. However, existing methods still have some problems. The denoised signals still have obvious noise residue, or the original EEG signals are damaged, and the model fitting speed is too slow. Image dehazing, as a typical denoising task in the field of image enhancement, has achieved great success in recent years. Therefore, inspired by advanced models in this field, we introduce CNN into EEG denoising tasks. In this paper, we take GCANet, an excellent image enhancement model, as an example. The dilated convolutions and gate fusion subnetworks included in GCANet enable more efficient EEG signal denoising. The results demonstrate that the proposed model effectively reduces noise while preserving essential features. Furthermore, in comparison to other state-of-the-art models, our proposed model exhibits enhanced robustness and faster convergence, as evidenced by achieving lower loss values after five epochs. Its good performance provides a new development idea for the field of EEG denoising. © 2023, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

A green and efficient disassembly line balancing with human-robot collaboration and destructive disassembly

引用

robotics and Computer-Integrated manufacturing 2026年 97卷

作者： Wei Zhang Yibing Li Kaipu Wang Wenjun Xu Liang Gao Hubei Digital Manufacturing Key Laboratory School of Mechanical and Electronic Engineering Wuhan University of Technology Wuhan 430070 China School of Information Engineering Wuhan University of Technology Wuhan 430070 China State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Human-robot collaboration combines the strengths of both humans and robots to enhance disassembly line efficiency. Considering the indivisibility and recovery value of certain components, this study incorporates destructive disassembly into a human-robot collaborative disassembly line. A mixed-integer linear programming model of the disassembly line balancing problem is constructed. The model accounts for task precedence relationships, task attributes, disassembly modes, human-robot collaboration, and the configuration of humans and robots. The objective is to minimize cycle time, smoothness index, and disassembly energy consumption while maximizing disassembly profit. The algorithm uses a three-layer encoding strategy based on task sequence, task operators, and disassembly modes, with an optimization-driven initialization to improve the initial solution quality. Five selection strategies and two neighborhood search strategies are designed, and during the iterative process, the strategy is dynamically adjusted through Q-learning to enhance both global search and local search capabilities. The effectiveness and superiority of the proposed algorithm are validated through three types of test case experiments, compared with the five latest algorithms. Finally, the model and algorithm are applied to a real-world laptop disassembly case. The results show that the introduction of collaborative robots in disassembly significantly reduces disassembly costs. Compared to manual disassembly, the cycle time of the disassembly line can be reduced by 24.39%, and idle time can be reduced by 33.64% in the human-robot collaborative disassembly mode. Compared to non-destructive disassembly, destructive disassembly can reduce energy consumption by 28.20%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Novel Design Method of COG Measurement System Via Supporting Reaction Method

引用

Journal of Beijing Institute of technology 2020年第2期29卷 251-259页

作者： Qirong Zhang Xin Jin Kai Zhou Zhongqing Zhang Dongmei Liu School of Mechatronic Engineering Beijing Institute of TechnologyBeijing 100081China Lu’nan Research Institute of Beijing Institute of Technology TengzhouShandong 277500China The 31st Research Third Academy of CASICBeijing 100074China State Key Laboratory of Intelligent Manufacturing System Technology for Complex Products Beijing Institute of Electronic EngineeringBeijing 100854China

Center of gravity(COG)is an important parameter of projectiles and rockets,for which supporting reaction method(or support reaction method)is an important COG measurement *** on this supporting reaction method a novel design method is proposed to determine the key design parameters of the COG measurement *** method can quantitatively analyze the influence of the design parameters on the COG accuracy,in the measurement system designed with supporting reaction *** the principle of static balance,the error propagation theory,and the system accuracy analysis method,the equal-range required sensor precision(RSP)surface and non-equal-range required sensor pair precision(RSPP)adapted surface are *** influence of random errors(like sensor accuracy and distance calibration accuracy)is *** selection strategy of equal-range and non-equal-range sensors is chosen,and then the recommended calibration accuracy values are *** the quality detection accuracy of±0.6 kg and the axial COG detection accuracy of±1.5 mm,the RSP surface is drawn by the proposed method,and the force sensor with±0.23 kg detection accuracy is *** experimental verification meets the accuracy requirements and verifies the effectiveness of the proposed design method for the system parameters of the COG measurement equipment.

关键词： center of gravity(COG) supporting reaction method required sensor precision(RSP)surface accuracy analysis parameter design

来源：评论

学校读者我要写书评

暂无评论

NTIRE 2023 Image Shadow Removal Challenge Report

NTIRE 2023 Image Shadow Removal Challenge Report

引用

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Vasluianu, Florin-Alexandru Seizinger, Tim Timofte, Radu Cui, Shuhao Huang, Junshi Tian, Shuman Fan, Mingyuan Zhang, Jiaqi Zhu, Li Wei, Xiaoming Wei, Xiaolin Luo, Ziwei Gustafsson, Fredrik K. Zhao, Zheng Sjölund, Jens Schön, Thomas B. Dong, Xiaoyi Zhang, Xi Sheryl Li, Chenghua Leng, Cong Yeo, Woon-Ha Oh, Wang-Taek Lee, Yeo-Reum Ryu, Han-Cheol Luo, Jinting Jiang, Chengzhi Han, Mingyan Wu, Qi Lin, Wenjie Yu, Lei Li, Xinpeng Jiang, Ting Fan, Haoqiang Liu, Shuaicheng Xu, Shuning Song, Binbin Chen, Xiangyu Zhang, Shile Zhou, Jiantao Zhang, Zhao Zhao, Suiyi Zheng, Huan Gao, Yangcheng Wei, Yanyan Wang, Bo Ren, Jiahuan Luo, Yan Kondo, Yuki Miyata, Riku Yasue, Fuma Naruki, Taito Ukita, Norimichi Chang, Hua-En Yang, Hao-Hsiang Chen, Yi-Chung Chiang, Yuan-Chun Huang, Zhi-Kai Chen, Wei-Ting Chen, I-Hsiang Hsieh, Chia-Hsuan Kuo, Sy-Yen Xianwei, Li Fu, Huiyuan Liu, Chunlin Ma, Huadong Fu, Binglan He, Huiming Wang, Mengjia She, Wenxuan Liu, Yu Nathan, Sabari Kansal, Priya Zhang, Zhongjian Yang, Huabin Wang, Yan Zhang, Yanru Phutke, Shruti S. Kulkarni, Ashutosh Khan, Md Raqib Murala, Subrahmanyam Vipparthi, Santosh Kumar Ye, Heng Liu, Zixi Yang, Xingyi Liu, Songhua Wu, Yinwei Jing, Yongcheng Yu, Qianhao Zheng, Naishan Huang, Jie Long, Yuhang Yao, Mingde Zhao, Feng Zhao, Bowen Ye, Nan Shen, Ning Cao, Yanpeng Xiong, Tong Xia, Weiran Li, Dingwen Xia, Shuchen Computer Vision Lab Ifi Caidas University of Würzburg Germany Computer Vision Lab Eth Zürich Switzerland Meituan Group China Department of Information Technology Uppsala University Sweden Institute of Automation Chinese Academy of Sciences Beijing China Nanjing China Maicro Nanjing China Department of Artificial Intelligence Convergence Sahmyook University Seoul Korea Republic of Megvii Technology China University of Electronic Science and Technology of China China University of Macau China China Toyota Technological Institute Japan Graduate Institute of Electronics Engineering National Taiwan University Taiwan Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan ServiceNow United States Beijing University of Post and Teleconmunication Beijing China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education China Couger Inc. Computer Vision and Pattern Recognition Lab Indian Institute of Technology Ropar Punjab Rupnagar India Research Institute Singapore National University of Singapore Singapore Research Institute Singapore University of Sydney Australia Brain-Inspired Vision Laboratory Information Science and Technology Institution University of Science and Technology of China China State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province School of Mechanical Engineering Zhejiang University Hangzhou310027 China South China University of Technology China

ISBN: (纸本)9798350302493

This work reviews the results of the NTIRE 2023 Challenge on Image Shadow Removal. The described set of solutions were proposed for a novel dataset, which captures a wide range of object-light interactions. It consists of 1200 roughly pixel aligned pairs of real shadow free and shadow affected images, captured in a controlled environment. The data was captured in a white-box setup, using professional equipment for lights and data acquisition sensors. The challenge had a number of 144 participants registered, out of which 19 teams were compared in the final ranking. The proposed solutions extend the work on shadow removal, improving over the performance level describing state-of-the-art methods. © 2023 IEEE.

关键词： Data acquisition

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：