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第三十四届中国控制会议

作者： LU Xiao WANG Linglong WANG Haixia PU Qiong DONG Xin Key Laboratory for Robot & Intelligent Technology of Shandong Province Shandong University of Science and Technology

ISBN: (纸本)9781467374439

In the brief, the optimal FSL(fixed-small-lag) smoother for descriptor systems is considered, where there are instantaneous and single delayed measurement, and the above two series of measurements have been corrupted by multiplicative *** value decomposition and projection theorem are used to deal with such a difficult problem, the fixed-small-lag smoother is presented for the case of the fixed-lag m being smaller than the delay d.

关键词： Singular,FSL Smoother,Delay,Projection Theorem

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AHLNet:Adaptive Multihead Structure and Lightweight Feature Pyramid Network for Detection of Live Working in Substations

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Machine Intelligence Research 2024年第5期21卷 983-992页

作者： Mengle Peng Xiaoyong Jiang Langyue Huang Zhongyi Li Haiteng Wu Xiaotang Geng Zhejiang University of Science and Technology Hangzhou310023China Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Hangzhou311100China

With the increasing demand for power in society,there is much live equipment in substations,and the safety and standardization of live working of workers are facing *** at these problems of scene complexity and object diversity in the real-time detection of the live working safety of substation workers,an adaptive multihead structure and lightweight feature pyramid-based network(AHLNet)is proposed in this study,which is based on ***,we take AH-Darknet53 as the backbone network of YOLOV3,which can introduce an adaptive multihead(AMH)structure,reduce the number of network parameters,and improve the feature extraction ability of the backbone ***,to reduce the number of convolution layers of the deeper feature map,a lightweight feature pyramid network(LFPN)is proposed,which can perform feature fusion in advance to alleviate the problem of feature imbalance and gradient ***,the proposed AHLNet is evaluated on the datasets of 16 categories of substation safety operation scenarios,and the average prediction accuracy MAP_(50)reaches 82.10%.Compared with YOLOV3,MAP_(50)is increased by 2.43%,and the number of parameters is 90 M,which is only 38%of the number of parameters of *** addition,the detection speed is basically the same as that of YOLOV3,which can meet the real-time and accurate detection requirements for the safe operation of substation staff.

关键词： Adaptive multihead structure lightweight feature pyramid substation feature imbalance multiobject detection

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Distributed Source Localization under Anchor Position Uncertainty

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Chinese Journal of Electronics 2014年第1期23卷 93-96页

作者： LIU Hongqing WU Yuntao Department of Electronic and Computer Engineering National University of Singapore Key Laboratory of Intelligent Robot in Hubei Province Wuhan Institute of Technology

In this work, a distributed source positioning approach is developed based on Alternating direction method of multipliers(ADMM). First, a centralized positioning method is developed under case of the anchor uncertainty. And then, the method is realized in a distributed way using ADMM. Simulation results show that the centralized one is robust to the anchor errors and distributed one has similar performance as the centralized one.

关键词： Target positioning Anchor uncertainty Distributed Computation

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High strength, low modulus, and ductile metastable beta Ti-Nb-Zr-Fe alloys by laser powder bed fusion in-situ alloying

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Journal of Materials Science & technology 2026年 241卷 270-283页

作者： Yue Li Liuyong Wang Haoyue Wu Feng Ding Min Lei Jin Yang J.P. Oliveira Ming Yan Wei Guo Yulong Li Jiangxi Key Laboratory of Intelligent Robot School of Advanced Manufacturing Nanchang University Nanchang 330031 China Department of Physics School of Physics and Materials Science Nanchang University Nanchang 330031 China School of Materials Science and Engineering Shanghai University of Engineering Science Shanghai 201620 China CENIMAT | I3N Department of Materials Science School of Science and Technology NOVA University Lisbon Caparica 1099-085 Portugal Department of Materials Science and Engineering Southern University of Science and Technology Shenzhen 518055 China School of Mechanical Engineering and Automation Beihang University Beijing 100191 China

A novel, high strength, low modulus, and ductile metastable β Ti-14Nb-6Zr-3Fe (TNZF) alloy was manufactured via laser powder bed fusion (LPBF) in-situ alloying. Process parameter optimization resulted in near-fully dense samples (< 0.1% porosity) under optimal conditions. The microstructure and mechanical properties of TNZF alloy were then tailored using two chessboard scanning strategies and a simple scanning strategy. Samples fabricated using the chessboard scanning strategy (CS-TNZF) benefited from a lower thermal gradient, the high growth restriction factor associated with the addition of Fe, and constitutional supercooling around residual Nb particles, resulting in a near-equiaxed grain structure (average aspect ratio: 2.0) compared to the AS-TNZF (fabricated using the simple scanning strategy). The microstructure consisted of a β-Ti matrix with 2–5 nm sized ω precipitates. Due to the addition of Zr, the transition from β to ω was suppressed during thermal cycling associated with LPBF, resulting in the presence of a partially collapsed ω phase. Without post-processing heat treatments, the AS-TNZF condition exhibited a yield strength (YS) of 1091 MPa, an elastic modulus (E) of 68 GPa, and an elongation (EL) of 16.8%, while the CS-TNZF counterpart achieved a higher YS of 1147 MPa and E of 71 GPa, but a lower EL of 10.8% due to a higher volume fraction of ω phase. Both AS-TNZF and CS-TNZF demonstrated high elastic admissible strain values (YS/E ratio) of 1.60 and 1.62, respectively, achieving high strength, low modulus, and good ductility, which indicates their suitability for biomedical implant materials.

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COMPACT COMPOSITION OPERATORS ON GENERALIZED LIPSCHITZ SPACES

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Acta Mathematica Scientia 2011年第4期31卷 1347-1356页

作者：戴济能欧阳才衡 School of Science Hubei Province Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan Institute of Physics and Mathematics the Chinese Academy of Science

In this paper, boundedness and compactness of the composition operator on the generalized Lipschitz spaces Λα （α 〉 1） of holomorphic functions in the unit disk are characterized.

关键词： composition operator Lipschitz space Bloch-type space angular derivative

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Semi-supervised Counting of Grape Berries in the Field Based on Density Mutual Exclusion

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Plant Phenomics 2023年第4期5卷 825-835页

作者： Yanan Li Yuling Tang Yifei Liu Dingrun Zheng School of Computer Science and Engineering School of Artificial IntelligenceWuhan Institute of TechnologyWuhan 430205China Hubei Key Laboratory of Intelligent Robot Wuhan Institute of TechnologyWuhan 430073China

Automated counting of grape berries has become one of the most important tasks in grape yield ***,dense distribution of berries and the severe occlusion between berries bring great challenges to counting algorithm based on deep *** collection of data required for model training is also a tedious and expensive *** address these issues and cost-effectively count grape berries,a semi-supervised counting of grape berries in the field based on density mutual exclusion(CDMENet)is *** algorithm uses VGG16 as the backbone to extract image *** tasks based on density mutual exclusion are *** tasks exploit the spatial distribution pattern of grape berries in density levels to make full use of unlabeled *** addition,a density difference loss is *** feature representation is enhanced by amplifying the difference of features between different density *** experimental results on the field grape berry dataset show that CDMENet achieves less counting *** with the state of the arts,coefficient of determination(R^(2))is improved by 6.10%,and mean absolute error and root mean square error are reduced by 49.36%and 54.08%,*** code is available at.

关键词： Grape mutual backbone

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Agent collaboration in intelligent parking lot systems: Dynamic generation of commitment protocol 18

Agent collaboration in intelligent parking lot systems: Dyna...

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18th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2017

作者： Wang, Jing Liu, Wei Li, Shuang Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China

ISBN: (纸本)9781538631515

Agent collaboration is a fundamental part of multi-agent systems when an agent cannot accomplish a goal by itself. Such collaborations are usually regulated by commitment protocols, which are typically defined at design-time. However, in many situations a protocol may not exist or be predefined at design-time which may not fit the needs of the agents when environment changes. In order to deal with such situations, agents should be able to generate protocols at run-time. In this paper, we combined commitment with capability. Firstly, we proposed the capability matching method to generate commitment protocols dynamically at run-time. Secondly, we combined capability with commitment and extended its traditional definition. Thirdly, we compared the forms, generation time and execution time of typical and extended commitments. At last, we introduced the criteria of profit to select the optimal protocol. The application of our approach will be demonstrated in intelligent parking lot systems. © 2017 IEEE.

关键词： Multi agent systems

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Development and evaluation of digital twin model for rack and pinion drive vegetable seedling transmission device using Adams/MATLAB co-simulation

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Simulation Modelling Practice and Theory 2025年 142卷

作者： Ahmad, Ibrar Siddique, Bushra Islam, Muhammad Adnan Haq, Zia Ul Niu, Ziang Waqas, Muhammad Mohsin Yang, Qizhi Qiu, Zhengjun College of Biosystems Engineering and Food Science Zhejiang University Hangzhou310058 China Key Laboratory of Spectroscopy Sensing Ministry of Agriculture Hangzhou310058 China School of Food Science and Technology Henan University of Technology Henan Province Zhengzhou450001 China NARC Pakistan Agricultural Research Council Islamabad Pakistan Department of Farm Machinery and Precision Engineering Faculty of Agricultural Engineering and Technology Pir Mehr Ali Shah Arid Agriculture University Rawalpindi Pakistan Department of Agricultural Engineering Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan Pakistan School of Agricultural Equipment Engineering Jiangsu University Zhenjiang212013 China Institute of Intelligent Robot Jiangsu University Zhenjiang212013 China

A sustainable design and optimized control system for the vegetable seedling transmission device is crucial for enhancing the operational speed and precision of fully automatic vegetable seedling transplanters. The incorporation of virtual prototype modeling for optimizing the design and control of these seedling devices has not been sufficiently explored in prior studies. Goal of this research is to develop and validate a digital twin model that will serve as a foundation for optimizing the design and control of seedling devices used in robotic transplanters. This study presents a state-of-the-art digital twin model of rack and pinion drive seedling transmission device utilizing Adams/MATLAB co-simulation. The findings demonstrate a robust correspondence between digital twin model and physical prototype, exhibiting a maximum linear positioning error discrepancy of 0.95 mm, a maximum relative positioning error of 3.17 and coefficient of determination (R2) values approximately equal to 1. Angular positioning error ranged from 3.73° to 7.98° as seedling rates increased from 90 to 140 seedlings/mi. Furthermore, precise activation and deactivation of the seedling cups opening mechanism was observed during the seedling transmission schedule. This digital twin model accurately represents the physical model of seedling device which can be utilized for design and control optimization. Potential future applications of this digital twin model include enhancing efficiency of robotic transplanters and mitigating environmental impacts. © 2025 Elsevier B.V.

关键词： MATLAB

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Automatic face replacement in photographs based on active shape models

Automatic face replacement in photographs based on active sh...

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2009 2nd Asia-Pacific Conference on Computational Intelligence and Industrial Applications, PACIIA 2009

作者： Min, Feng Lu, Tongwei Zhang, Yanduo Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology China

ISBN: (纸本)9781424446070

In this paper, we present an automatic face replacement approach in photographs based on Active Shape Models (ASM). Our replacement algorithm has three main modules: face alignment, face morph, and seamless blending. First, given an input and target image, we automatically implement face alignment using ASM Second, we fit a morphable 2D model to the input face, and warp its shape to match the target face shape. Last, we adjust the lighting and color of the target face image to match those of the input face image, and seamlessly blend the target face image into the input image. Our approach is 2D model-based, fully automatic, and generates natural results. The improved results demonstrate the effectiveness of our approach. ©2009 IEEE.

关键词： Photography

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TransAnno-Net: A Deep Learning Framework for Accurate Cell Type Annotation of Mouse Lung Tissue Using Self-supervised Pretraining

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Computer Methods and Programs in Biomedicine 2025年 267卷 108809-108809页

作者： Zhang, Qing Wu, Xiaoxiao Li, Xiang Ma, Wei Wu, Tongquan Li, Liuyue Hu, Fan Xie, Yicheng Wu, Xinglong School of Computer Science and Engineering Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Hubei Wuhan430205 China School of Mechanical Engineering Hefei University of Technology Hefei China Faculty of Applied Science and Engineering University of Toronto Canada UNISKIN Research Institute on Skin Aging Inertia Shanghai Biotechnology Co. Ltd Shanghai China DermaHealth Shanghai Biotechnology Co. Ltd. Shanghai China Department of Dermatology Children's Hospital Zhejiang University School of Medicine National Clinical Research Center for Child Health Zhejiang Province Hangzhou310052 China

Background: Single-cell RNA sequencing (scRNA-seq) has become a significant tool for addressing complex issuess in the field of biology. In the context of scRNA-seq analysis, it is imperative to accurately determine the type of each cell. However, conventional supervised or semi-supervised methodologies are contingent on expert labels and incur substantial labeling costs, In contrast self-supervised pre-training strategies leverage unlabeled data during the pre-training phase and utilise a limited amount of labeled data in the fine-tuning phase, thereby greatly reducing labor costs. Furthermore, the fine-tuning does not need to learn the feature representations from scratch, enhancing the efficiency and transferability of the model. Methods: The proposed methodology is outlined below. The deep learning framework, TransAnno-Net, is based on transfer learning and a Transformer architecture. It has been designed for efficient and accurate cell type annotations in large-scale scRNA-seq datasets of mouse lung organs. Specifically, TransAnno-Net is pre-trained on the scRNA-seq lung data of approximately 100,000 cells to acquire gene-gene similarities via self-supervised learning. It is then migrated to a relatively small number of datasets to fine-tune specific cell type annotation tasks. To address the issue of imbalance in cell types commonly observed in scRNA-seq data, we applied a random oversampling technique is applied to the fine-tuned dataset. This is done to mitigate the impact of distributional imbalance on the annotation outcomes. Results: The experimental findings demonstrate that TransAnno-Net exhibits superior performance with an AUC of 0.979, 0.901, and 0.982, respectively, on three mouse lung datasets, outperforming eight state-of-the-art (SOTA) methods. In addition, TransAnno-Net demonstrates robust performance on cross-organ, cross-platform datasets, and is competitive with the fully supervised learning-based method. Conclusion: The TransAnno-Net method

关键词： Self-supervised learning

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