检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Doodeman, Sander Tang, Zhiqi Jacinto, Marcelo Cunha, Rita Silvestre, Carlos Department of Mechanical Engineering TU/e Eindhoven University of Technology Eindhoven Netherlands Division of Decision and Control Systems KTH Royal Institute of Technology Sweden Instituto Superior Técnico University of Lisbon Portugal Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China

This work addresses the practical problem of distributed formation tracking control of a group of quadrotor vehicles in a relaxed sensing graph topology with a very limited sensor set, where only one leader vehicle can access the global position. Other vehicles in the formation are assumed to only have access to inter-agent bearing (direction) measurements and relative velocities with respect to their neighbor agents. A hierarchical control architecture is adopted for each quadrotor, combining a high-gain attitude inner-loop and an outer-loop bearing-based formation controller with collision avoidance augmentation. The proposed method enables a group of quadrotors to track arbitrary bearing persistently exciting desired formations, including time-varying shapes and rotational maneuvers, such that each quadrotor only requires relative measurements to at least one neighboring quadrotor. The effective performance of the control strategy is validated by numerical simulations in MATLAB and real-world experiments with three quadrotors. © 2025, CC BY-NC-ND.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

A Feature Extraction and Analysis Method for Battery Health Monitoring

A Feature Extraction and Analysis Method for Battery Health ...

引用

IEEE International Symposium on Industrial Electronics (ISIE)

作者： Jilun Tian Jiusi Zhang Hao Luo Congsheng Huang Mo-Yuen Chow Yuchen Jiang Shen Yin Department of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan R.O.C Department of Electrical and Computer Engineering North Carolina State University Raleigh NC U.S.A Faculty of Engineering Norwegian University of Science and Technology Trondheim Norway

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

Batteries are widely applied in industrial systems, promoting industrial production efficiency. The system prognosis needs to establish a battery health monitoring model and maintain regular maintenance, improving reliability and safety while reducing unnecessary economic losses. An accurate data-driven state-of-health (SOH) estimation method is crucial, as it mainly relies on the information related to battery SOH values in the extracted features. Therefore, we propose a statistical-based feature extraction method, which makes it physically meaningful and effective. To explore more information, we propose a feature analysis framework to analyze battery features, including visualization, correlation, and importance analysis. We utilize a random forest regression model as an effective learner and validate it based on NASA’s real-world dataset. The feature analysis contents are beneficial for understanding the role and importance of features in SOH estimation tasks, which can also provide an extended scenario for feature extraction of batteries.

关键词： Training Visualization Correlation Estimation Voltage Feature extraction Batteries

来源：评论

学校读者我要写书评

暂无评论

RDA: An Accelerated Collision Free Motion Planner for Autonomous Navigation in Cluttered Environments

arXiv

引用

arXiv 2022年

作者： Han, Ruihua Wang, Shuai Wang, Shuaijun Zhang, Zeqing Zhang, Qianru Eldar, Yonina C. Hao, Qi Pan, Jia The Department of Computer Science and Engineering Southern University of Science and Technology Guangdong Shenzhen China The Department of Computer Science The University of Hong Kong Hong Kong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China The Department of Computer Science and Engineering Harbin Institute of Technology Guangdong Shenzhen China The Weizmann Institute of Science Rehovot Israel The Department of Computer Science and Engineering The Shenzhen Key Laboratory of Robotics and Computer Vision The Sifakis Research Institute for Trustworthy Autonomous Systems Southern University of Science and Technology Guangdong Shenzhen China

Autonomous motion planning is challenging in multi-obstacle environments due to nonconvex collision avoidance constraints. Directly applying numerical solvers to these nonconvex formulations fails to exploit the constraint structures, resulting in excessive computation time. In this paper, we present an accelerated collision-free motion planner, namely regularized dual alternating direction method of multipliers (RDADMM or RDA for short), for the model predictive control (MPC) based motion planning problem. The proposed RDA addresses nonconvex motion planning via solving a smooth biconvex reformulation via duality and allows the collision avoidance constraints to be computed in parallel for each obstacle to reduce computation time significantly. We validate the performance of the RDA planner through path-tracking experiments with car-like robots in both simulation and real-world settings. Experimental results show that the proposed method generates smooth collision-free trajectories with less computation time compared with other benchmarks and performs robustly in cluttered environments. The source code is available at https://***/hanruihua/ RDA_planner. Copyright © 2022, 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

Decentralized Optimal control for Linear Stochastic Systems with control Signals subject to Unknown Noises

Decentralized Optimal Control for Linear Stochastic Systems ...

引用

International Conference on control and Automation (ICCA)

作者： Zhaorong Zhang Juanjuan Xu Minyue Fu Xun Li School of Computer Science and Technology Shandong University Qingdao China School of Control Science and Engineering Shandong University Jinan China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China Department of Applied Mathematics the Hong Kong Polytechnic University Hong Kong SAR China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Decentralized strategies have been extensively applied to LQ optimal control problems, whereas, stochastic systems with unknown random parameters have not been comprehensively studied. In this paper, we consider a class of stochastic systems with a decentralized configuration consisting of multiple controllers which have access to Gaussian noises with unknown statistical information. The stabilizing and optimal control strategies are acquired by designing a novel stochastic approximation algorithm recursively evaluating the zero points of certain matrix equations, which is confirmed to be equivalent with solving the corresponding Riccati equations. The proof of convergence and boundness of the proposed algorithm is presented.

关键词： Q-learning Automation Stochastic systems Gaussian noise Riccati equations Optimal control Approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Multi-Unit Floor Plan Recognition and Reconstruction Using Improved Semantic Segmentation of Raster-Wise Floor Plans

arXiv

引用

arXiv 2024年

作者： Kratochvila, Lukas de Jong, Gijs Arkesteijn, Monique Bilík, Šimon Zemčík, Tomáš Horak, Karel Rellermeyer, Jan S. Department of Control and Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Brno Czech Republic Department of Software Technology Faculty of Electrical Engineering Mathematics and Computer Science TU Delft Delft Netherlands Department of Management in the Built Environment Faculty of Architecture and the Built Environment TU Delft Delft Netherlands Computer Vision and Pattern Recognition Laboratory Department of Computational Engineering Lappeenranta-Lahti University of Technology LUT Lappeenranta Finland Dependable and Scalable Software Systems Institute of Systems Engineering Faculty of Electrical Engineering and Computer Science Leibniz University Hannover Hannover Germany

Digital twins have a major potential to form a significant part of urban management in emergency planning, as they allow more efficient designing of the escape routes, better orientation in exceptional situations, and faster rescue intervention. Nevertheless, creating the twins still remains a largely manual effort, due to a lack of 3D-representations, which are available only in limited amounts for some new buildings. Thus, in this paper we aim to synthesize 3D information from commonly available 2D architectural floor plans. We propose two novel pixel-wise segmentation methods based on the MDA-Unet and MACU-Net architectures with improved skip connections, an attention mechanism, and a training objective together with a reconstruction part of the pipeline, which vectorizes the segmented plans to create a 3D model. The proposed methods are compared with two other state-of-the-art techniques and several benchmark datasets. On the commonly used CubiCasa benchmark dataset, our methods have achieved the mean F1 score of 0.86 over five examined classes, outperforming the other pixel-wise approaches tested. We have also made our code publicly available to support research in the field. © 2024, CC BY.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

FGRL-Net: Fine-Grained Personalized Patient Representation Learning for Clinical Risk Prediction Based on EHRs

FGRL-Net: Fine-Grained Personalized Patient Representation L...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： KaKit Chio Wenhao Zhu Lihua He Dian Zhang Xu Yang Wuman Luo Faculty of Applied Sciences Macao Polytechnic University Macao S.A.R China School of Information and Communication Engineering University of Electronic Science and Technology of China Sichuan Province China Department of Computer Science and Software Engineering Shenzhen University Shenzhen China

Personalized patient representation learning (PPRL) is a critical element in clinical risk prediction. It aims to obtain a complete portrait of each patient based on Electronic Health Records (EHR). Although existing works have achieved remarkable progress in healthcare prediction, there are still three major issues. First, feature correlation is crucial for risk prediction, but it has not yet been fully exploited by existing works. Second, variation pattern of dynamic feature contains useful information about patient's physical status, but adaptive pattern recognition is still a challenge. Third, existing works usually adopt a two-stage embedding process to process each dimension of the EHR data. However, some useful low-level information for PPRL will be lost. To address these issues, in this paper, we propose a fine-grained PPRL architecture named FG RL- N et for clinical risk prediction based on EHR. Specifically, we propose a Medical Feature Correlation Detection Module (FCM) to effectively learn the feature correlations for each patient and a Temporal Variation Pattern Recognition Module (TVM) to effectively detect the variation patterns of each dynamic feature. Moreover, we design a Fine-Grained Representation Mechanism (FGRM) to preserve the low-level information (from both feature and visit dimensions) useful for risk prediction. In addition, in the stage of data preprocessing, We utilize generic medical classification knowledge to classify numerical dynamic data. We conduct the in-hospital mortality experiment and the decompensation experiment on a real-world dataset. The experiment results show that the FGRL-Net outperforms state-of-the-art approaches. The source code is provided in github https://***/JackyChio/FGRL-Net.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Review of recent designs, performance, and configurations for the pyramid solar still

引用

International Journal of Energy and Water Resources 2025年第2期9卷 1145-1176页

作者： Hussein, A. Kadhim Rashid, F. Lafta Abed, A.M. Sultan, H.S. Togun, H. Attia, M. El Hadi Manokar, A. Muthu Hamida, M. Bechir Ben Ali, B. Younis, O. Khutar, N. Murad Mechanical Engineering Department College of Engineering University of Babylon Babylon City Hilla Iraq Petroleum Engineering Department College of Engineering University of Kerbala Karbala Iraq Air Conditioning and Refrigeration Techniques Engineering Department Al-Mustaqbal University College Babylon 51001 Iraq College of Engineering University of Warith Al-Anbiyaa Karbalaa 56001 Iraq Biomedical Engineering Department University of Thi-Qar Nassiriya 64001 Iraq Physics Department Faculty of Exact Sciences University of El Oued El Oued 3900 Algeria Department of Mechanical Engineering B.S. Abdur Rahman Crescent Institute of Science and Technology Tamil Nadu Chennai 600048 India Department of Chemical Engineering College of Engineering Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh Saudi Arabia Research Laboratory of Ionized Backgrounds and Reagents Studies (EMIR) Preparatory Institute for Engineering Studies of Monastir (IPEIM) University of Monastir Monastir City Tunisia Higher School of Sciences and Technology of Hammam Sousse Department of Physics University of Sousse Sousse Tunisia School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen 518055 China Department of Mechanical Engineering College of Engineering in Wadi Addwasir Prince Sattam Bin Abdulaziz University Al-Kharj 11942 Saudi Arabia Department of Mechanical Engineering Faculty of Engineering University of Khartoum Khartoum Sudan Department of Computer Technical Engineering Technical Engineering College Al-Ayen University Thi-Qar Iraq

Fresh water is essential for day-to-day survival. The primary issue facing undeveloped nations is the continuous scarcity of clean water, and drinking contaminated water to survive may harm one’s health. Due to population expansion, there is less fresh water available. Boring wells, rainwater, and water from rivers or lakes are among the potential water sources. For isolated, arid, and semiarid regions, solar distillation is appropriate. Where there is a severe drinking water deficit and intense solar radiation. With free energy, straightforward, affordable technology, and a clean atmosphere, solar still (SS) partly meets man’s demand for drinking water, especially in distant locations. This review focuses on pyramid solar stills (PSS), highlighting their potential to meet drinking water demands with free, clean energy and simple technology. This paper comprehensively reviews numerical, experimental, and combined (numerical and experimental), discussing various setups, parameters, and results. Key advancements, performance improvements, and future research directions are outlined, emphasizing the importance of innovative designs and optimization for enhanced efficiency and freshwater production. © The Author(s), under exclusive licence to Iranian Society of Environmentalists (IRSEN) and science and Research Branch, Islamic Azad university 2024.

关键词： Comprehensive review Pyramid solar still Remote regions Water desalination

来源：评论

学校读者我要写书评

暂无评论

Enhancing Recommendation Representations Through Alignment and Uniformity with Integrated Contrastive Learning and Collaborative Filtering

Enhancing Recommendation Representations Through Alignment a...

引用

IEEE International Conference on Smart Internet of Things (SmartIoT)

作者： Linxian Li Yuzhu Hu Yulong Zhao Xiaoqian Xi Jiaxin Chen Wei Wang School of Computer Science Beijing Institute of Technology Beijing China Guangdong-Hong Kong-Macao Joint Laboratory for Emotion Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU - BIT University Shenzhen China School of Intelligent Systems Engineering Sun Vat-sen University Shenzhen China Faculty of Engineering Shenzhen MSU-BIT University Shenzhen China

ISBN: (数字)9798350366440

ISBN: (纸本)9798350366457

Collaborative Filtering(CF) is a widely studied recommendation method, and learning high-quality representations is crucial for it. Recent research has focused on improving the quality of learned representations by designing better optimization objectives, such as optimizing alignment and uniformity, which enhance recommendation performance. However, supervised learning alone cannot address inherent issues like sparse supervision signals in recommendation systems. Therefore, many studies use contrastive learning (CL) from self-supervised learning to provide additional self-supervised signals, and often jointly optimize InfoNCE loss from CL and BPR loss from CF. Considering that both InfoNCE and BPR losses can be analyzed through the key properties of alignment and uniformity, we propose a loss function that integrates CL and CF into alignment and uniformity. This integration ensures that the learned representations are both representative and suitable for recommendation tasks. Specifically, we use LightGCN to extract high-order collaborative signals from the user-item interaction graph, and to enable self-supervised learning, we add uniform noise perturbations at each layer. We then optimize the learned representations using our proposed loss function. We conduct experiments on a benchmark dataset to demonstrate the superiority of our framework.

关键词： Collaborative filtering Perturbation methods Supervised learning Noise Collaboration Contrastive learning Information filters Internet of Things Recommender systems Optimization

来源：评论

学校读者我要写书评

暂无评论

NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Results

NTIRE 2023 Challenge on Light Field Image Super-Resolution: ...

引用

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

作者： Wang, Yingqian Wang, Longguang Liang, Zhengyu Yang, Jungang Timofte, Radu Guo, Yulan Jin, Kai Wei, Zeqiang Yang, Angulia Guo, Sha Gao, Mingzhi Zhou, Xiuzhuang Van Duong, Vinh Huu, Thuc Nguyen Yim, Jonghoon Jeon, Byeungwoo Liu, Yutong Cheng, Zhen Xiao, Zeyu Xu, Ruikang Xiong, Zhiwei Liu, Gaosheng Jin, Manchang Yue, Huanjing Yang, Jingyu Gao, Chen Zhang, Shuo Chang, Song Lin, Youfang Chao, Wentao Wang, Xuechun Wang, Guanghui Duan, Fuqing Xia, Wang Wang, Yan Xia, Peiqi Wang, Shunzhou Lu, Yao Cong, Ruixuan Sheng, Hao Yang, Da Chen, Rongshan Wang, Sizhe Cui, Zhenglong Chen, Yilei Lu, Yongjie Cai, Dongjun An, Ping Salem, Ahmed Ibrahem, Hatem Yagoub, Bilel Kang, Hyun-Soo Zeng, Zekai Wu, Heng National University of Defense Technology China Aviation University of Air Force China University of Würzburg Germany Eth Zürich Switzerland Sun Yat-sen University The Shenzhen Campus of Sun Yat-sen University China Bigo Technology Pte. Ltd. Singapore Smart Medical Innovation Lab Beijing University of Posts and Telecommunications China Global Explorer Ltd. Suzhou China National Engineering Research Center of Visual Technology School of Computer Science Peking University China School of Artificial Intelligence Beijing University of Posts and Telecommunications China Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of University of Science and Technology of China China School of Electrical and Information Engineering Tianjin University China Beijing Key Lab of Traffic Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University China Beijing Normal University China Toronto Metropolitan University Canada Beijing Institute of Technology China Shenzhen MSU-BIT University China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China Beihang Hangzhou Innovation Institute Yuhang China Faculty of Applied Sciences Macao Polytechnic University China School of Communication and Information Engineering Shanghai University China School of Information and Communication Engineering Chungbuk National University Korea Republic of Guangdong University of Technology China

ISBN: (纸本)9798350302493

In this report, we summarize the first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4. This challenge develops a new LF dataset called NTIRE-2023 for validation and test, and provides a toolbox called BasicLFSR to facilitate model development. Compared with single image SR, the major challenge of LF image SR lies in how to exploit complementary angular information from plenty of views with varying disparities. In total, 148 participants have registered the challenge, and 11 teams have successfully submitted results with PSNR scores higher than the baseline method LF-InterNet [1]. These newly developed methods have set new state-of-the-art in LF image SR, e.g., the winning method achieves around 1 dB PSNR improvement over the existing state-of-the-art method DistgSSR [2]. We report the solutions proposed by the participants, and summarize their common trends and useful tricks. We hope this challenge can stimulate future research and inspire new ideas in LF image SR. © 2023 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface

Optical Evanescent Field for Direct Observation of Sub-100nm...

引用

Robotics, engineering, science, and technology (RESTCON), International Conference on

作者： Panart Khajornrungruang Thitipat Permpatdechakul Keisuke Suzuki Aran Blattler Yutaka Terayama Daiki Goto Pipat Phaisalpanumas Natthaphon Bun-Athuek Amornphun Phunopas Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Mechanical Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Mechanical Information Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Production and Robotics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Mechanical Science and Technology Course Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Industiral Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Mechanical Engineering Technology College of Industrial Technology King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes.

关键词：

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：