检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Yang, Xiaohong Liwang, Minghui Fu, Liqun Su, Yuhan Hosseinalipour, Seyyedali Wang, Xianbin Hong, Yiguang School of Informatics Xiamen University Fujian China Department of Control Science and Engineering The National Key Laboratory of Autonomous Intelligent Unmanned Systems China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University Shanghai China School of Electronic Science and Engineering Xiamen University Xiamen China Department of Electrical Engineering University at Buffalo-SUNY BuffaloNY United States Department of Electrical and Computer Engineering Western University ON Canada

Hierarchical Federated Learning (HFL) introduces intermediate aggregation layers, addressing the limitations of conventional Federated Learning (FL) in geographically dispersed environments with limited communication infrastructure. An application of HFL is in smart IoT systems, such as remote monitoring, disaster response, and battlefield operations, where cellular connectivity is often unreliable or unavailable. In these scenarios, UAVs serve as mobile aggregators, providing connectivity to the terrestrial IoT devices. This paper studies an HFL architecture for energy-constrained UAVs in smart IoT systems, pioneering a solution to minimize global training cost increased caused by UAV disconnection. In light of this, we formulate a joint optimization problem involving learning configuration, bandwidth allocation, and device-to-UAV association, and perform global aggregation in time before UAV drops disconnect and redeployment of UAVs. The problem explicitly accounts for the dynamic nature of IoT devices and their interruptible communications and is unveiled to be NP-hard. To address this, we decompose it into three subproblems. First, we optimize the learning configuration and bandwidth allocation using an augmented Lagrangian function to reduce training costs. Second, we propose a device fitness score, integrating data heterogeneity (via Kullback-Leibler divergence), device-to-UAV distances, and IoT device resources, and develop a twin-delayed deep deterministic policy gradient (TD3)-based algorithm for dynamic device-to-UAV assignment. Third, We introduce a low-complexity two-stage greedy strategy for finding the location of UAVs redeployment and selecting the appropriate global aggregator UAV. Experiments on real-world datasets demonstrate significant cost reductions and robust performance under communication interruptions. © 2025, CC BY-NC-ND.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Synthesis of TiO_(2) Nanospikes for Dual Antibacterial Activity

引用

Biomedical and Environmental Sciences 2023年第10期36卷 983-986页

作者： LI Ze Ping CHEN Zhi Yuan YANG Ming Yan YI Wei Song School of Electronic and Information Engineering Hubei University of Science and TechnologyXianning 437100HubeiChina Key Laboratory of Optoelectronic Information and Intelligent Control Hubei University of Science and TechnologyXianning 437100HubeiChina School of Nuclear Technology and Chemistry&Biology Hubei University of Science and TechnologyXianning 437100HubeiChina Department of Rehabilitation Xianning Hospital of Traditional Chinese MedicineXianning 437100HubeiChina College of Science Huazhong Agricultural UniversityWuhan 430070HubeiChina

Bacterial infections on medical and public surfaces have caused considerable harm to human life and have gained widespread *** surface coating strategies,including the use of antibiotics,metal ions,quaternary ammonium... 详细信息

关键词： gained coating quaternary

来源：评论

学校读者我要写书评

暂无评论

Bi-AM-RRT*: A Fast and Efficient Sampling-Based Motion Planning Algorithm in Dynamic Environments

arXiv

引用

arXiv 2023年

作者： Zhang, Ying Wang, Heyong Yin, Maoliang Wang, Jiankun Hua, Changchun The School of Electrical Engineering The Key Laboratory of Intelligent Rehabilitation Neromodulation of Hebei Province Yanshan University Qinhuangdao066004 China The Shenzhen Key Laboratory of Robotics Perception and Intelligence Shenzhen518055 China The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China

The efficiency of sampling-based motion planning brings wide application in autonomous mobile robots. The conventional rapidly exploring random tree (RRT) algorithm and its variants have gained significant successes, but there are still challenges for the optimal motion planning of mobile robots in dynamic environments. In this paper, based on Bidirectional RRT and the use of an assisting metric (AM), we propose a novel motion planning algorithm, namely Bi-AM-RRT*. Different from the existing RRT-based methods, the AM is introduced in this paper to optimize the performance of robot motion planning in dynamic environments with obstacles. On this basis, the bidirectional search sampling strategy is employed to reduce the search time. Further, we present a new rewiring method to shorten path lengths. The effectiveness and efficiency of the proposed Bi-AM-RRT* are proved through comparative experiments in different environments. Experimental results show that the Bi-AM-RRT* algorithm can achieve better performance in terms of path length and search time, and always finds near-optimal paths with the shortest search time when the diffusion metric is used as the AM. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Environment-Driven Online LiDAR-Camera Extrinsic Calibration

arXiv

引用

arXiv 2025年

作者： Huang, Zhiwei Li, Jiaqi Zhong, Ping Fan, Rui The Department of Control Science & Engineering The College of Electronics & Information Engineering Tongji University Shanghai201804 China The School of Computer Science and Engineering Central South University Hunan Changsha410083 China The National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Hunan Changsha410073 China The Department of Control Science & Engineering The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China The National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Shaanxi Xi’an710049 China

LiDAR-camera extrinsic calibration (LCEC) is the core for data fusion in computer vision. Existing methods typically rely on customized calibration targets or fixed scene types, lacking the flexibility to handle variations in sensor data and environmental contexts. This paper introduces EdO-LCEC, the first environment-driven, online calibration approach that achieves human-like adaptability. Inspired by the human perceptual system, EdO-LCEC incorporates a generalizable scene discriminator to actively interpret environmental conditions, creating multiple virtual cameras that capture detailed spatial and textural information. To overcome cross-modal feature matching challenges between LiDAR and camera, we propose dual-path correspondence matching (DPCM), which leverages both structural and textural consistency to achieve reliable 3D-2D correspondences. Our approach formulates the calibration process as a spatial-temporal joint optimization problem, utilizing global constraints from multiple views and scenes to improve accuracy, particularly in sparse or partially overlapping sensor views. Extensive experiments on real-world datasets demonstrate that EdO-LCEC achieves state-of-the-art performance, providing reliable and precise calibration across diverse, challenging environments. Copyright © 2025, The Authors. All rights reserved.

关键词： Spatio-temporal data

来源：评论

学校读者我要写书评

暂无评论

Parametric Transformation of Timed Weighted Marked Graphs:Applications in Optimal Resource Allocation

引用

IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 179-188页

作者： Zhou He Ziyue Ma Zhiwu Li Alessandro Giua the College of Mechanical and Electrical Engineering Shaanxi University of Science and TechnologyXi’an 710021China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048China the School of Electro-Mechanical Engineering Xidian UniversityXi’an 710071China Institute of Systems Engineering Macao University of Science and TechnologyTaipa 999078MacaoChina the Department of Electrical and Electronic Engineering University of CagliariCagliari 09124Italy

Timed weighted marked graphs are a subclass of timed Petri nets that have wide applications in the control and performance analysis of flexible manufacturing *** to the existence of multiplicities(i.e.,weights)on edges,the performance analysis and resource optimization of such graphs represent a challenging *** this paper,we develop an approach to transform a timed weighted marked graph whose initial marking is not given,into an equivalent parametric timed marked graph where the edges have unitary *** order to explore an optimal resource allocation policy for a system,an analytical method is developed for the resource optimization of timed weighted marked graphs by studying an equivalent ***,we apply the proposed method to a flexible manufacturing system and compare the results with a previous heuristic *** analysis shows that the developed approach is superior to the heuristic approach.

关键词： Discrete event system resource allocation timed Petri net weighted marked graph

来源：评论

学校读者我要写书评

暂无评论

HP-KPConv: Point Cloud Registration Evaluation via Local Feature Distribution Similarity

HP-KPConv: Point Cloud Registration Evaluation via Local Fea...

引用

IEEE International Conference on robotics and Biomimetics

作者： Yaling Pan Li He Yisheng Guan Hong Zhang Ministry of Industry and Information Technology Key Laboratory of Quality and Reliability Engineering Technology of Civil Aircraft and Aero-Engine Chinese Electronic Product Reliability and Environmental Testing Research Institute Guangzhou China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Biomimetic and Intelligent Robotics Lab (BIRL) Guangdong University of Technology Guangzhou China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

ICP is one of the most popular solutions for point cloud registration. However, the evaluation metric of the ICP algorithm, based on point-wise Euclidean distances, falls short in meeting the demands of high-precision alignment. In this paper, we propose a point cloud registration evaluation method based on local feature distribution to assess alignment quality, in particular the translation errors among matched point clouds. Rather than comparing the point-to-point Euclidean distance as adopted in ICP, our main idea is that the spatial distribution of one local region pre- and post-alignment should be similar. We design a filter to calculate local region similarity and find out outliers according to the similarity. This high-precision filter is integrated into the KPConv network, denoted as HP-KPConv. Finally, after conducting extensive experiments on Dingo robots and LiDAR, we validate the ability of HP-KPConv to effectively detect subtle alignment errors, proving its applicability in robot localization evaluations.

关键词： Point cloud compression Measurement Matched filters Graphical models Translation Robot localization Trajectory Quality assessment Robots Distribution functions

来源：评论

学校读者我要写书评

暂无评论

Effects of pulsation ratio on center temperature and drying characteristics of pineapple slices with pulsed vacuum drying

引用

International Journal of Agricultural and Biological engineering 2022年第6期15卷 242-253页

作者： Dalong Jiang Congcong Li Zifan Lin Yuntian Wu Hongjuan Pei School of Computer and Control Engineering Yantai UniversityYantai 264005ShandongChina Hebei Agricultural University Baoding 071001HebeiChina Hebei Key Laboratory of Agricultural Big Data Baoding 071001HebeiChina Department of Electrical and Electronic Engineering University of Western AustraliaPerth 6000Australia BeiGene Guangzhou Biologics Manufacturing Co. LtdGuangzhou 510555China Neuroscience and Intelligent Media Institute Communication University of ChinaBeijing 100024China

This research explored the application of pulsed vacuum technology on the drying(PVD)of pineapple *** of drying temperature and pulsed vacuum ratio(PVR)on drying characteristics and pineapple quality(color,rehydration characteristics,microstructure,and texture)were *** expected,increasing the drying temperature resulted in a higher drying rate and effective moisture *** optimal PVR of 5:5 was beneficial in accelerating the drying rate of pineapple slices and the corresponding effective moisture diffusion coefficient(8.9601×10^(-10))was higher than other PVR conditions based on material center *** material temperature increased during the normal pressure period and decreased rapidly when the pressure dropped to the vacuum condition,which indirectly reflected the moisture transfer that occurred during the vacuum holding period,while moisture diffusion happened during the atmospheric pressure holding *** optimal pulsed vacuum drying process(PVR of 5:5)could expand air and water vapor and create a looser structure so as to obtain better rehydration performance(rehydration ratio(RR)was 5.43).High drying temperature led to the decrease of L^(*)value,the increase ofΔE value,and even the formation of surface scorch at 80℃.At the same drying temperature,the color quality depended on the drying time,and the color difference increased with the extension of the drying *** chewiness and hardness of pineapple slices dried by PVD were significantly higher than those of fresh samples,which was conducive to the chewing taste.

关键词： pulsed vacuum drying pineapple slices color rehydration ratio texture center temperature

来源：评论

学校读者我要写书评

暂无评论

State Estimation for Discrete-Time Semi-Markovian Jump Piecewise-Affine Systems with Complex Semi-Markovian Kernel

State Estimation for Discrete-Time Semi-Markovian Jump Piece...

引用

IEEE Conference on Decision and control

作者： Qi Tang Tao Liu Xi-Ming Sun Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong SAR Shenzhen Institute of Research and Innovation. The University of Hong Kong Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper addresses state estimation for discretetime semi-Markovian jump piecewise-affine (PWA) systems. To handle uncertainties caused by unknown disturbances, we propose an analysis method that considers all transfer paths between different regions within the same mode. We then examine the mean-square exponential stability and ${\mathcal{L}}_{\infty}$ performance of the error dynamic system by constructing Lyapunov functions that depend on mode, region, and sojourn time. The related criteria are derived using ellipsoidal outer approximation. Based on these criteria, we design ${\mathcal{L}}_{\infty}$ observers. Finally, we demonstrate the applicability of our method through a numerical example.

关键词： Uncertainty Stability Buildings Observers control theory Computational efficiency Complexity theory Kernel Dynamical systems Lyapunov methods

来源：评论

学校读者我要写书评

暂无评论

Learning Assisted Optimal Scheduling of Integrated Gas and Electricity Networks Under High Penetration of Renewable Energy

SSRN

引用

SSRN 2024年

作者： Sun, Xianzhuo Bai, Runze Zhang, Wen Qiu, Jing Tao, Yuechuan Lai, Shuying School of Electrical and Information Engineering The University of Sydney Camperdown2006 Australia Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University 999077 Hong Kong Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Shandong University Jinan250061 China

The growing integration of renewable energy sources into the power grid necessitates innovative approaches to energy system management. Integrated gas and electricity networks offer a promising solution to this challenge, enabling the efficient, reliable, and sustainable operation of energy systems. This paper presents a novel approach to the optimal scheduling of integrated gas and electricity networks, addressing the challenges posed by high penetration of renewable energy ***, a learning-assisted methodology is proposed to leverage Graph Convolutional Networks (GCNs) and Bayesian-based uncertainty models to enhance the accuracy and efficiency of scheduling integrated energy systems. The proposed GCN model effectively captures the complex interactions within the integrated network, facilitating accurate power and gas flow predictions. Meanwhile, the Bayesian-based model adeptly manages the inherent uncertainties associated with renewable energy generation, employing a chance-constrained approach to ensure system reliability. The effectiveness of the proposed methodology is demonstrated through extensive simulations on an IEEE 39-bus electricity network coupled with a 22-node hydrogen network. Results indicate significant improvements in computational efficiency and predictive accuracy compared to traditional model-based methods and existing data-driven techniques. © 2024, The Authors. All rights reserved.

关键词： Renewable energy

来源：评论

学校读者我要写书评

暂无评论

NeRF in robotics: A Survey

arXiv

引用

arXiv 2024年

作者： Wang, Guangming Pan, Lei Peng, Songyou Liu, Shaohui Xu, Chenfeng Miao, Yanzi Zhan, Wei Tomizuka, Masayoshi Pollefeys, Marc Wang, Hesheng The University of Cambridge ETH Zurich Switzerland The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education of China China Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China ETH Zurich Zurich Switzerland Mechanical Systems Control Laboratory University of California Berkeley United States

Meticulous 3D environment representations have been a longstanding goal in computer vision and robotics fields. The recent emergence of neural implicit representations has introduced radical innovation to this field as implicit representations enable numerous capabilities. Among these, the Neural Radiance Field (NeRF) has sparked a trend because of the huge representational advantages, such as simplified mathematical models, compact environment storage, and continuous scene representations. Apart from computer vision, NeRF has also shown tremendous potential in the field of robotics. Thus, we create this survey to provide a comprehensive understanding of NeRF in the field of robotics. By exploring the advantages and limitations of NeRF, as well as its current applications and future potential, we hope to shed light on this promising area of research. Our survey is divided into two main sections: The Application of NeRF in robotics and The Advance of NeRF in robotics, from the perspective of how NeRF enters the field of robotics. In the first section, we introduce and analyze some works that have been or could be used in the field of robotics from the perception and interaction perspectives. In the second section, we show some works related to improving NeRF's own properties, which are essential for deploying NeRF in the field of robotics. In the discussion section of the review, we summarize the existing challenges and provide some valuable future research directions for reference. © 2024, CC BY-NC-ND.

关键词： robotics

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：