检索结果-内蒙古大学图书馆

Light-driven high-precision cell adhesion kinetics

Light(Science & Applications) 2022年第10期11卷 2256-2257页

作者： Zhiyuan Zhang Daniel Ahmed Acoustic Robotics Systems Laboratory Institute of Robotics and Intelligent SystemsDepartment of Mechanical and Process EngineeringETH ZurichS?umerstrasse 4CH-8803 ZurichSwitzerland

Existing single-cell adhesion kinetics methods are performed under conditions highly unlike the physiological cell adhesion ***,researchers have developed a new optical technique for high-precision measurement of cell... 详细信息

关键词： conditions. kinetics formed

来源：评论

学校读者我要写书评

暂无评论

Towards AI-Powered Edge Intelligence for Object Detection in Self-Driving Cars: Enhancing IoV Efficiency and Safety

引用

IEEE Internet of Things Journal 2025年

作者： Ahmed, Imran Ahmad, Misbah Siddiqi, Muftooh Ur Rehman Chehri, Abdellah Jeon, Gwangill Anglia Ruskin University School of Computing and Information Science Cambridge United Kingdom University of West of England Centre for Machine Vision Bristol Robotics Laboratory Bristol United Kingdom Hartpury University Department of Animal and Agriculture Gloucester United Kingdom Aston University College of Engineering and Physical Sciences Birmingham United Kingdom Department of Mathematics and Computer Science Canada Incheon National University Department of Embedded Systems Engineering Incheon Korea Republic of

In the rapidly advancing field of intelligent transportation systems, integrating Artificial Intelligence (AI) with edge computing presents a promising way to enhance the safety and efficiency of the Internet of Vehicles (IoV). This study explores and presents a deep learning based object detection model within an edge computing framework which aims to facilitate real time object detection in self driving cars. Using an urban traffic scenarios based dataset, our research shows the ability of the model to accurately detect and classify various objects important for autonomous driving. The YOLOv8 model is used in this work due to its optimal balance between accuracy and computational efficiency. This model has also demonstrated its worth by achieving good performance results, including an average precision of 0.79, a recall of 0.62, and an F1-score of 0.69. The results are demonstrated by a detailed confusion matrix, highlighting the model's effectiveness in complex driving environments and underscoring its reliability for in-vehicle deployment. By implementing AI directly on edge devices within vehicles, our approach might be helpful in significantly reducing latency, boosting decision-making speed, and enhancing data privacy by minimising dependence on cloud processing. The findings not only support the model's capabilities but also illustrate the practical benefits of edge intelligence in autonomous vehicles. These benefits, such as faster decision-making and improved data privacy, contribute effectively to the IoV infrastructure. This study marks a substantial step towards recognising the possibility of AI-enhanced edge computing in driving the next generation of autonomous vehicle technology. © 2025 IEEE.

关键词： Artificial Intelligence Autonomous Vehicles Deep leaning Edge Computing Internet of Vehicles

来源：评论

学校读者我要写书评

暂无评论

Fundamental insights into Brønsted acid-induced adduction improve small metabolite profiling in mass spectrometry

引用

Chemical engineering Journal 2025年 515卷

作者： Liu, Wanshan Chen, Wei Li, Yanyan Yang, Shouzhi Cao, Jing Wu, Jiao Huang, Yida Wang, Ruimin Chen, Xiaonan Huang, Lin Wang, Jiayi Qian, Kun Wan, Jingjing State Key Laboratory of Systems Medicine for Cancer School of Biomedical Engineering Institute of Medical Robotics and Shanghai Academy of Experimental Medicine Shanghai Jiao Tong University Shanghai200030 China Division of Cardiology Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai200127 China School of Chemistry and Molecular Engineering East China Normal University Shanghai200241 China Department of Clinical Laboratory Medicine Shanghai Institute of Thoracic Oncology Shanghai Chest Hospital Shanghai Jiao Tong University Shanghai200030 China

Mass spectrometry (MS) is the primary tool to detect small metabolite ions for profiling bio-systems. However, small metabolite profiling in MS still needs to be improved and calls for new rules in ionization. Herein, we studied the Brønsted acid-induced multiple alkali metal cation adductions (BAI-mAMCA) in laser desorption/ionization MS, with annotation of BAI-mAMCA in complex bio-samples and improved profiling of small metabolites. Firstly, we engineered the enhanced mAMCA (relative intensities increased from 0.1–4.6 % to 76.1–89.9 %, p 2 = 0.989–0.997, p © 2025

关键词： Metabolites

来源：评论

学校读者我要写书评

暂无评论

Toward AI-Powered Edge Intelligence for Object Detection in Self-Driving Cars: Enhancing IoV Efficiency and Safety

引用

IEEE Internet of Things Journal 2025年第11期12卷 16990-16997页

作者： Imran Ahmed Misbah Ahmad Muftooh Ur Rehman Siddiqi Abdellah Chehri Gwangill Jeon School of Computing and Information Science Anglia Ruskin University Cambridge U.K. Centre for Machine Vision Bristol Robotics Laboratory University of the West of England Bristol U.K. Department of Animal and Agriculture Hartpury University Gloucester U.K. College of Engineering and Physical Sciences Aston University Birmingham U.K. Department of Mathematics and Computer Science Royal Military College of Canada Kingston ON Canada Department of Embedded Systems Engineering Incheon National University Incheon South Korea

In the rapidly advancing field of intelligent transportation systems, integrating artificial intelligence (AI) with edge computing presents a promising way to enhance the safety and efficiency of the Internet of Vehicles (IoV). This study explores and presents a deep learning-based object detection model within an edge computing framework which aims to facilitate real time object detection in self driving cars. Using an urban traffic scenarios-based dataset, our research shows the ability of the model to accurately detect and classify various objects important for autonomous driving. The YOLOv8 model is used in this work due to its optimal balance between accuracy and computational efficiency. This model has also demonstrated its worth by achieving good performance results, including an average precision of 0.79, a recall of 0.62, and an F1-score of 0.69. The results are demonstrated by a detailed confusion matrix, highlighting the model’s effectiveness in complex driving environments and underscoring its reliability for in-vehicle deployment. By implementing AI directly on edge devices within vehicles, our approach might be helpful in significantly reducing latency, boosting decision-making speed, and enhancing data privacy by minimising dependence on cloud processing. The findings not only support the model’s capabilities but also illustrate the practical benefits of edge intelligence in autonomous vehicles. These benefits, such as faster decision making and improved data privacy, contribute effectively to the IoV infrastructure. This study marks a substantial step toward recognizing the possibility of AI-enhanced edge computing in driving the next generation of autonomous vehicle technology.

关键词： Computational modeling Object detection Edge computing Image edge detection Artificial intelligence Computer architecture Data models Accuracy Servers Safety

来源：评论

学校读者我要写书评

暂无评论

TReCiM: Lower Power and Temperature-Resilient Multibit 2FeFET-1T Compute-in-Memory Design

arXiv

引用

arXiv 2025年

作者： Zhou, Yifei Kämpfe, Thomas Ni, Kai Amrouch, Hussam Zhuo, Cheng Yin, Xunzhao Zhejiang University Hangzhou China Fraunhofer IPMS Dresden Germany Department of Electrical Engineering University of Notre Dame Notre Dame United States Technical University of Munich TUM School of Computation Information and Technology Munich Institute of Robotics and Machine Intelligence Munich Germany Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province China

Compute-in-memory (CiM) emerges as a promising solution to solve hardware challenges in artificial intelligence (AI) and the Internet of Things (IoT), particularly addressing the"memory wall" issue. By utilizing nonvolatile memory (NVM) devices in a crossbar structure, CiM efficiently accelerates multiply-accumulate (MAC) computations, the crucial operations in neural networks and other AI models. Among various NVM devices, Ferroelectric FET (FeFET) is particularly appealing for ultra-low-power CiM arrays due to its CMOS compatibility, voltage-driven write/read mechanisms and high ION/IOFF ratio. Moreover, subthreshold-operated FeFETs, which operate at scaling voltages in the subthreshold region, can further minimize the power consumption of CiM array. However, subthreshold-FeFETs are susceptible to temperature drift, resulting in computation accuracy degradation. Existing solutions exhibit weak temperature resilience at larger array size and only support 1-bit. In this paper, we propose TReCiM, an ultra-low-power temperature-resilient multibit 2FeFET-1T CiM design that reliably performs MAC operations in the subthreshold-FeFET region with temperature ranging from 0°C to 85°C at scale. We benchmark our design using NeuroSim framework in the context of VGG-8 neural network architecture running the CIFAR-10 dataset. Benchmarking results suggest that when considering temperature drift impact, our proposed TReCiM array achieves 91.31% accuracy, with 1.86% accuracy improvement compared to existing 1-bit 2T-1FeFET CiM array. Furthermore, our proposed design achieves 48.03 TOPS/W energy efficiency at system level, comparable to existing designs with smaller technology feature sizes. Copyright © 2025, The Authors. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Data fusion: Color edge detection and surface reconstruction through regularization

引用

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 1996年第3期43卷 355-363页

作者： Salinas, RA Richardson, C Abidi, MA Gonzalez, RC Imaging Robotics and Intelligent Systems Laboratory Department of Electrical Engineering University of Tennessee Knoxville TN USA Imaging Robotics and Intelligent Systems LaboratoryDepartment of Electrical Engineering University of Tennessee Knoxville TN USA

Data fusion provides tools for solving problems which are characterized by distributed and diverse information sources. In this paper rye focus on the problem of extracting features such as image discontinuities from both synthetic and real images. Since edge detection and surface reconstruction are ill-posed problems in the sense of Hadamard, Tikhonov's regularization paradigm is proposed as the basic tool for solving this inversion problem and restoring well-posedness. The proposed framework includes 1) a systematic view of one- and two-dimensional regularization, 2) extension of the standard Tikhonov regularization method by allowing space-variant regularization parameters, and 3) further extension of the regularization paradigm by adding multiple data sources to allow for data fusion. The theoretical approach is complemented by developing a series of algorithms, then solving the early vision problems of color edge detection and surface reconstruction, An evaluation of these methods reveals that this new analytical data fusion technique output is consistently better than each of the individual RGB edge maps, and noisy corrupted images are reconstructed into smooth noiseless surfaces.

关键词： Image edge detection Surface reconstruction Image reconstruction Intelligent robots Data mining Data analysis Intelligent sensors Intelligent systems Entropy Brightness

来源：评论

学校读者我要写书评

暂无评论

Conceptualizing UAM: Technologies and Methods for Safe and Efficient Urban Air Transportation

引用

Green Energy and Intelligent Transportation 2025年

作者： Lidia Zewde Ioannis A. Raptis North Carolina A&T State University Department of Electrical and Computer Engineering Autonomous Robotics Systems Laboratory Greensboro USA

The effective integration of Urban Air Mobility (UAM) hinges upon the adoption of a comprehensive approach that harmoniously melds various network components, placing paramount importance on the pillars of safety, sustainability, and efficiency. Existing technologies are currently undergoing a transformative evolution to cater to the distinctive requirements of UAM, with an unwavering commitment to enhancing safety, sustainability, and efficiency. This paper meticulously elucidates the extant technologies and methodologies that pertain to the safe and efficient realm of air transportation while delving into the perspective of key UAM network components: (1) Aircraft classification, dimensions, and operational technology; (2) Airspace typology and structural intricacies; and (3) Air Traffic Management (ATM) services. In conclusion, this paper culminates by offering insights into prospective research directions in this burgeoning field.

关键词： Urban Aerial Mobility Electric Vertical Takeoff and Landing Urban Airspace Aircraft Traffic Management Aircraft Communication Navigation and Surveillance Ground Infrastructure Concept of Operations

来源：评论

学校读者我要写书评

暂无评论

LMI-Based Robust Control of a Knee Rehabilitation Exoskeleton Robot Using a Nonlinear Composite Controller

LMI-Based Robust Control of a Knee Rehabilitation Exoskeleto...

引用

Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Sahar Jenhani Hassène Gritli Jyotindra Narayan Laboratory of Robotics Informatics and Complex Systems (RISC Lab - LR16ES07) National Engineering School of Tunis (ENIT) University of Tunis El Manar Tunis Tunisia RISC Lab (LR16ES07) ENIT University of Tunis El Manar Tunis Tunisia ISTIC University of Carthage Tunis Tunisia Department of Mechanical Engineering Indian Institute of Technology Patna Patna India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

The present study proposes a control approach designed to achieve robust stabilization of a 1-DoF knee joint exoskeleton system intended for rehabilitation purposes. The proposed method combines a linear state-feedback control law with a nonlinear control law to address the nonlinear dynamics of the knee-joint exoskeleton, addressing parameter uncertainties and external disturbances. The model simplifies the nonlinear function by assuming it to be bounded by linear constraints. By considering two different expressions of the term existing in the nonlinear controller, two design methods for LMI conditions are developed. These methods use a quadratic Lyapunov function to ensure stability and robustness. The controller’s performance is assessed through simulations under external disturbances, and a comparative analysis confirms its efficacy in maintaining stability despite parametric uncertainties.

关键词： Robust control Uncertain systems Technological innovation Uncertainty Exoskeletons Position control Stability analysis Robustness Nonlinear dynamical systems Robots

来源：评论

学校读者我要写书评

暂无评论

Topological dependence of mechanical responses of solidification microstructures in aluminum brazed joints

引用

中国有色金属学会会刊：英文版 2003年第6期13卷 1296-1300页

作者：高峰钱乙余 D.P.Sekulic 马鑫 F.Yoshida State Key Laboratory of Advanced Production Technology Center for Robotics and Manufacturing Systems Department of Mechanical System Engineering

The main objective is to provide an evidence of spatial dependence of mechanical responses of a heterogeneous aluminum brazed joint re-solidified clad, and to confirm a sufficient sensitivity of a nano-indentation—load curve method for identifying the dependence. Topological features of a network of solidification microstructures(α phase and eutectic), formed during quench in a brazing process of aluminum alloy, influence significantly dynamic mechanical responses of resulting heterogeneous material. Nano/micro indentation depth vs load characteristics of differing phases suggest a spatially sensitive mechanical response of a re-solidified fillet in the joint zone. Hence, a spatial distribution, pattern formations and other morphological characteristics of microstructures have a direct impact on an ultimate joint integrity. Topology-induced variations of indentation—load curves was presented. A hypothesis involving microstructures’ spatial distribution vs mechanical response was formulated.

关键词：铝铜焊显微结构凝固拓扑相关机械响应焊接铝合金

来源：评论

学校读者我要写书评

暂无评论

Internal force-based impedance control for cooperating manipulators

引用

IEEE TRANSACTIONS ON robotics AND AUTOMATION 1996年第1期12卷 78-89页

作者： Bonitz, RG Hsia, TC Systems Controland Robotics LaboratoryDepartment of Electrical and Computer Engineering University of California Davis CA USA

An internal force-based impedance control scheme for cooperating manipulators is introduced which controls the motion of the objects being manipulated and the internal force on the objects. The controller enforces a relationship between the velocity of each manipulator and the internal force on the manipulated objects. Each manipulator is directly given the properties of an impedance by the controller;thus, eliminating the gain limitation inherent in the structure of previously proposed schemes. The controller uses the forces sensed at the robot end effecters to compensate for the effects of the objects' dynamics and to compute the internal force using only kinematic relationships. Thus, knowledge of the objects' dynamics is not required. Stability of the system is proven using Lyapunov theory and simulation results are presented validating the proposed concepts. The effect of computational delays in digital control implementations is analyzed vis-a-vis stability and a lower bound derived on the size of the desired manipulator inertia relative to the actual manipulator endpoint inertia. The bound is independent of the sample time.

关键词： Impedance Force control Motion control Manipulator dynamics Velocity control Robot sensing systems End effectors Kinematics Stability Computational modeling

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：