检索结果-内蒙古大学图书馆

Towards Energy-Efficiency: Integrating MATD3 Reinforcement Learning Method for Computational Offloading in RIS-Aided UAV-MEC Environments

引用

IEEE Internet of Things Journal 2025年

作者： Wu, Liangshun Zhang, Cong Zhang, Bin Du, Jianbo Qu, Junsuo Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai201804 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai201210 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Xi'an Key Laboratory of Advanced Control and Intelligent Process School of Automation Xi'an University of Posts & Telecommunications Xi'an710061 China Xinjiang University of Political Science and Law Tumushuke832003 China School of Remote Sensing and Information Engineering Wuhan University Wuhan430079 China Department of Computer City University of Hong Kong 999077 Hong Kong School of Communications and Information Engineering Xi'an University of Posts & Telecommunications Xi'an710061 China

With the proliferation of IoT devices, there is an escalating demand for enhanced computing and communication capabilities. Mobile Edge computing (MEC) addresses this need by relocating computing resources to the network edge, thereby delivering swifter and more efficient services. This paper introduces a computation offloading and energy consumption optimization framework that leverages Reconfigurable intelligent Surfaces (RIS), Unmanned Aerial Vehicles (UAVs), and MEC. The scheme aims to maximize energy efficiency through the optimization of task allocation, RIS phase shifts, and UAV trajectories. By employing the Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3) reinforcement learning algorithm, the paper further refines UAV trajectories and RIS configurations. The simulation results indicate that the proposed method surpasses the traditional Concave-Convex Procedure (CCCP) algorithm in both UAV trajectory control and RIS configuration, demonstrating quicker convergence and enhanced stability. The method proves to be adaptable to diverse environments and tasks, showcasing notable benefits in RIS-assisted interference suppression, particularly with large RIS, thereby enhancing UAV data reception rates. Additionally, MATD3 exhibits faster and smoother convergence for extended task durations and smaller RIS scenarios. Simulation results reveal that UAVs tend to move closer to RIS, with energy efficiency falling as IoT tasks increase, affirming the proposed algorithm's high energy efficiency and effectiveness. © 2025 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Exploring the Reform of Mechanical Drawing Teaching and Undergraduate Training Based on the “Integration of Competition-Oriented Education and Industry-University Collaboration”

Exploring the Reform of Mechanical Drawing Teaching and Unde...

引用

International Conference on Educational and Information Technology (ICEIT)

作者： Zhang Runfeng Ming Yankun Liu Zhenzhong Wu Jianguo Wang Xiaofei Sun Yanfang Tianjin Key Laboratory for Advanced Mechatronic 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 Hanhailanfan Marine Technology Co. Ltd. Tianjin China

ISBN: (数字)9798350372663

ISBN: (纸本)9798350372670

This study aims to explore the reform of mechanical drawing teaching and the undergraduate training model with the goal of cultivating high-quality mechanical engineering undergraduate students. Grounded in the concepts of “synergy between science and education” and “integration of competition-oriented education and industry-university collaboration,” this research places talent cultivation as the central focus, linking it with discipline construction and emphasizing scientific research. The study promotes the reform of a collaborative education mechanism known as “integration of competition-oriented education and industry-university collaboration,” effectively establishing a multi-level and multi-dimensional undergraduate training model for mechanical engineering students that incorporates the “dual mentor system” and integrates theory, practice, and application. To apply this model in teaching practice, this research has undertaken the reform of traditional engineering drawing education, specifically addressing the issue of the gap between theory and practice in conventional teaching approaches. The proposed training program not only facilitates the development of innovative mechanical engineering professionals but also offers insights for the reform of undergraduate teaching models in the context of constructing “new engineering disciplines”.

关键词： Training Couplings Technological innovation Engineering drawings Collaboration Mechanical engineering Machinery

来源：评论

学校读者我要写书评

暂无评论

Modeling, Simulation, and Parameter design of Actuation Mechanisms Based on New Magnetic Control Materials

Modeling, Simulation, and Parameter Design of Actuation Mech...

引用

System Simulation Technology and its Application (CCSSTA), IEEE China Conference on

作者： Ruixuan Shen He Tian Guanqiao Zhao Ziliang Zhu Jiangping Li Chao Liang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin China Tianjin Sanyuan Power Equipment Manufacturing Co. Ltd Tianjin China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

With the rapid advancement of technology, the reliability and efficiency of power systems have become increasingly critical. In power systems, pole-mounted circuit breakers play a vital role. This paper presents a design scheme for an actuation mechanism of a pole-mounted circuit breaker based on new magnetic control materials. By analyzing the working principle of this actuation mechanism, a mathematical model was constructed, and a corresponding virtual prototype model was established using multi-body dynamics simulation software ADAMS and the dynamics mathematical model of this type of actuation mechanism. key performance parameters of the circuit breaker were optimized using a quantum genetic algorithm. Simulation experiments verified that the proposed parameter settings achieved a closing time of 7.6 ms, demonstrating significant improvements in circuit breaker performance. The results of this study are of great importance for the optimization design and performance enhancement of circuit breakers in power systems.

关键词： Vacuum systems Circuit breakers Power system dynamics Mathematical models Software Systems simulation Integrated circuit modeling Magnetic circuits Optimization Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

design of Multi-Channel Gas Sensor Circuit with Large Dynamic Range and High-Precision

Design of Multi-Channel Gas Sensor Circuit with Large Dynami...

引用

Electrical Engineering and Mechatronics Technology (ICEEMT), IEEE International Conference on

作者： Kun Li Jiaheng Meng Yuzhe Liu Jingli Shi Kaicheng Liu Qing Liu Tianjin Key Laboratory of Film Electronic and Communication Device Tianjin University of Technology Tianjin China Tianjin Space Power Technology Co. Ltd Tianjin China Tianjin Lantian Solar Tech Co. Ltd. Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin China

In order to realize a multi-channel exhalation detection device with large dynamic range and high precision, a well designed signal processing and sampling circuit is essential for gas sensors. In this paper, a particular circuit is designed to meet above requirement. The proposed circuit uses a constant current source to achieve linear transformation of resistance value and output voltage, and uses a voltage follower for impedance transformation to minimize the impact of the AD acquisition on the front-end circuit. Since the gas sensor can be regarded as a variable resistor, the proposed circuit is tested with variable resistors varying from 10k$\Omega$ to 50M$\Omega$, over three orders of magnitude. In order to increase the sensitivity of the gas sensors, it is need to heat the sensor. Then a multi-channel heating circuit is designed with independent adjustable heating current in each channel, which can be controlled with multi-channel PWM signal from the MCU. With simulation and experiment, the performance of the proposed circuit has been verified to be excellent. Furthermore, the circuit has the advantage of being used in various fields.

关键词：

来源：评论

学校读者我要写书评

暂无评论

RobNODDI: Robust NODDI Parameter Estimation with Adaptive Sampling under Continuous Representation

arXiv

引用

arXiv 2024年

作者： Xiao, Taohui Cheng, Jian Fan, Wenxin Yang, Jing Li, Cheng Dong, Enqing Wang, Shanshan School of Mechanical Electrical & Information Engineering Shandong University Weihai264209 China State Key Laboratory of Software Development Environment Beihang University Beijing China Key Laboratory of Data Science and Intelligent Computing Institute of International Innovation Beihang University Zhejiang Hangzhou China Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Peng Cheng Laboratory Guangdong Shenzhen China

Neurite Orientation Dispersion and Density Imaging (NODDI) is an important imaging technology used to evaluate the microstructure of brain tissue, which is of great significance for the discovery and treatment of various neurological diseases. Current deep learning-based methods perform parameter estimation through diffusion magnetic resonance imaging (dMRI) with a small number of diffusion gradients. These methods speed up parameter estimation and improve accuracy. However, the diffusion directions used by most existing deep learning models during testing needs to be strictly consistent with the diffusion directions during training. This results in poor generalization and robustness of deep learning models in dMRI parameter estimation. In this work, we verify for the first time that the parameter estimation performance of current mainstream methods will significantly decrease when the testing diffusion directions and the training diffusion directions are inconsistent. A robust NODDI parameter estimation method with adaptive sampling under continuous representation (RobNODDI) is proposed. Furthermore, long short-term memory (LSTM) units and fully connected layers are selected to learn continuous representation signals. To this end, we use a total of 100 subjects to conduct experiments based on the Human Connectome Project (HCP) dataset, of which 60 are used for training, 20 are used for validation, and 20 are used for testing. The test results indicate that RobNODDI improves the generalization performance and robustness of the deep learning model, enhancing the stability and flexibility of deep learning NODDI parameter estimatimation applications. Copyright © 2024, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fundus Image Quality Assessment and Enhancement: a Systematic Review

arXiv

引用

arXiv 2025年

作者： Li, Heng Li, Haojin Ou, Mingyang Yu, Xiangyang Zhang, Xiaoqing Niu, Ke Fu, Huazhu Liu, Jiang Research Institute of Trustworthy Autonomous Systems SUSTech Shenzhen China Department of Computer Science and Engineering SUSTech Shenzhen China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Computer School Beijing Information Science and Technology University Beijing China Singapore

As an affordable and convenient eye scan, fundus photography holds the potential for preventing vision impairment, especially in resource-limited regions. However, fundus image degradation is common under intricate imaging environments, impacting following diagnosis and treatment. Consequently, image quality assessment (IQA) and enhancement (IQE) are essential for ensuring the clinical value and reliability of fundus images. While existing reviews offer some overview of this field, a comprehensive analysis of the interplay between IQA and IQE, along with their clinical deployment challenges, is lacking. This paper addresses this gap by providing a thorough review of fundus IQA and IQE algorithms, research advancements, and practical applications. We outline the fundamentals of the fundus photography imaging system and the associated interferences, and then systematically summarize the paradigms in fundus IQA and IQE. Furthermore, we discuss the practical challenges and solutions in deploying IQA and IQE, as well as offer insights into potential future research directions. Copyright © 2025, The Authors. All rights reserved.

关键词： Photography

来源：评论

学校读者我要写书评

暂无评论

Analysis of Strengthening Mechanism and Thermal Stability of M23c6 and Laves Phase in a Ferrite Matrix

SSRN

引用

SSRN 2023年

作者： Jin, Tiejian Shen, Junjie Ruan, Taotao Zhang, Dechang Xu, Yu Ren, He Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

The strengthening of ferrite matrix steel depends on the strengthening mechanism and thermal stability of M23C6 and Laves phases. This study investigated M23C6(Fe,Cr)23C6 and Laves(Fe2Nb) phase-strengthened ferritic steels. The creep microstructure, the interface structure, and the nanoindentation creep behavior of the second phase were studied. Results showed that the dislocation density in (Fe,Cr)23C6 strengthened ferritic steel after creep is lower than Fe2Nb strengthened ferritic steel. The dislocations in the crept (Fe,Cr)23C6 strengthened ferritic steel are straight without accumulation, significantly bending. The dislocations bend and entangle, forming dislocation walls in the crept Fe2Nb-strengthened ferritic steel. The orientation relationships between (Fe,Cr)23C6/Fe2Nb and ferrite matrix are [001]α-Fe//[011](Fe,Cr)23C6, (020)α-Fe//(71[[EQUATION]])(***)23C6,[001]α-Fe//[5[[EQUATION]]]Fe2Nb,(01[[EQUATION]])α-Fe//(03[[EQUATION]])Fe2Nb. The atomic interface mismatch between M23C6/Fe2Nb and the ferrite matrix is 20% of the semi-coherent interface and 1.6% of the coherent interface. The thermal stability of Fe2Nb is better than (Fe,Cr)23C6. The creep stress exponents of (Fe,Cr)23C6 and Fe2Nb in the ferrite matrix are 4.4 and 12.2, respectively. The alloy’s creep deformation follows dislocation climbing over the second phase. Second-phase Fe2Nb strengthening played a more significant role than (Fe,Cr)23C6 in enhancing the ferrite matrix. The results provide a theoretical foundation for developing ferritic heat-resistant steel based on Laves (Fe2Nb) phase strengthening. © 2023, The Authors. All rights reserved.

关键词： Creep

来源：评论

学校读者我要写书评

暂无评论

Landmark Detection using Transformer Toward Robot-assisted Nasal Airway Intubation

Landmark Detection using Transformer Toward Robot-assisted N...

引用

2023 International Conference on Biomimetic Intelligence and Robotics

作者： Liu, Tianhang Li, Hechen Bai, Long Wu, Yanan Wang, An Islam, Mobarakol Ren, Hongliang Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong College of Medicine and Biological Information Engineering Northeastern University Shenyang China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang China University College London London United Kingdom Department of Biomedical Engineering National University of Singapore Singapore Shun Hing Institute of Advanced Engineering The Chinese University of Hong Kong Hong Kong Shenzhen Research Institute The Chinese University of HongKong Shenzhen China

Robot-assisted airway intubation application needs high accuracy in locating targets and organs. Two vital landmarks, nostrils and glottis, can be detected during the intubation to accommodate the stages of nasal intubation. Automated landmark detection can provide accurate localization and quantitative evaluation. The Detection Transformer (DeTR) leads object detectors to a new paradigm with long-range dependence. However, current DeTR requires long iterations to converge, and does not perform well in detecting small objects. This paper proposes a transformer-based landmark detection solution with deformable DeTR and the semantic-aligned-matching module for detecting landmarks in robot-assisted intubation. The semantics aligner can effectively align the semantics of object queries and image features in the same embedding space using the most discriminative features. To evaluate the performance of our solution, we utilize a publicly accessible glottis dataset and automatically annotate a nostril detection dataset. The experimental results demonstrate our competitive performance in detection accuracy. Our code can be accessible at https://***/ConorLTH/airway intubation landmarks detection. © 2023 The Authors. Published by Elsevier B.V.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

3D ANATOMICAL STRUCTURE-GUIDED DEEP LEARNING FOR ACCURATE DIFFUSION MICROSTRUCTURE IMAGING

arXiv

引用

arXiv 2025年

作者： Ma, Xinrui Cheng, Jian Fan, Wenxin Wu, Ruoyou Ye, Yongquan Wang, Shanshan Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Software Development Environment Beihang University Beijing China Key Laboratory of Data Science and Intelligent Computing Institute of International Innovation Beihang University Zhejiang Hangzhou China Pengcheng Laboratory Guangdong Shenzhen China United Imaging Healthcare HoustonTX United States

Diffusion magnetic resonance imaging (dMRI) is a crucial noninvasive technique for exploring the microstructure of the living human brain. Traditional hand-crafted and model-based tissue microstructure reconstruction methods often require extensive diffusion gradient sampling, which can be time-consuming and limits the clinical applicability of tissue microstructure information. Recent advances in deep learning have shown promise in microstructure estimation;however, accurately estimating tissue microstructure from clinically feasible dMRI scans remains challenging without appropriate constraints. This paper introduces a novel framework that achieves high-fidelity and rapid diffusion microstructure imaging by simultaneously leveraging anatomical information from macro-level priors and mutual information across parameters. This approach enhances time efficiency while maintaining accuracy in microstructure estimation. Experimental results demonstrate that our method outperforms four state-of-the-art techniques, achieving a peak signal-to-noise ratio (PSNR) of 30.51±0.58 and a structural similarity index measure (SSIM) of 0.97±0.004 in estimating parametric maps of multiple diffusion models. Notably, our method achieves a 15× acceleration compared to the dense sampling approach, which typically utilizes 270 diffusion gradients. © 2025, CC BY-NC-ND.

关键词： Tissue

来源：评论

学校读者我要写书评

暂无评论

Synthesis of Decoherence-Free Modes in Linear Quantum Passive Systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Zibo Miao Yu Pan Qing Gao Guangdong Key Laboratory of Intelligent Morphing Mechanisms School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Shenzhen China State Key Laboratory of Industrial Control Technology The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique.

关键词： Perturbation methods design methodology Quantum optics Robustness Feedback control Closed loop systems Tuning Cybernetics

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：