检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Kumar, Deepak Prakash Darbha, Swaroop Manyam, Satyanarayana G. Casbeer, David W. Pachter, Meir Mechanical Engineering 3123 TAMU College StationTX77843 United States DCS Corporation 4023 Col. Glenn Hwy DaytonOH United States Control Science Center AFRL AIAA United States Department of Electrical and Computer Engineering Air Force Institute of Technology United States

In this article, two methods of addressing path planning for a Dubins vehiclemoving on a sphere are considered, wherein either spherical coordinates or amoving frame are considered to describe the vehicle's motion. The primarycontribution of this article is to show the equivalence of these twoapproaches, which in turn shows that the results known for the movingframe-based description transfer to the model utilizing spherical coordinates. Copyright © 2024, The Authors. All rights reserved.

关键词： Spheres

来源：评论

学校读者我要写书评

暂无评论

Cache Replacement Strategy of Cooperative Edge Caching Based on Discrete Maddpg

SSRN

引用

SSRN 2023年

作者： Wei, Zhenchun Fu, Yu Yuan, Xiaohui Lyu, Zengwei Zhang, Yu Shi, Lei School of Computer Science and Information Engineering Hefei University of Technology 193 Tunxi Road Anhui Hefei230009 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology 193 Tunxi Road Anhui Hefei230009 China Department of Computer Science and Engineering University of North Texas 3940 N. Elm DentonTX76203 United States

Cooperative edge caching has emerged as a promising solution to alleviate the traffic burden of backhaul and improve the Quality of Service (QoS) of 5G applications in the 5G era. Several cooperative edge caching methods alleviate the traffic burden of backhaul by transmitting contents between edge nodes cooperatively, thereby reducing the delay of content transmission. However, they only consider the cooperation on content transmission and do not consider the cooperation on cache replacement, which can not control content redundancy in the cooperative edge caching system and reduce the utilization of cache space. In this paper, we propose the cache replacement strategy of cooperative edge caching based on the Discrete Multi-Agent Deep Deterministic Policy Gradient (Discrete MADDPG) algorithm. We first propose a cooperative edge caching model to maximize the system throughput. Then we formulate the cache replacement process of the cooperative edge caching system to a Markov Game (MG) model. Finally, we use the cache replacement strategy based on the Discrete MADDPG algorithm to solve the MG model and control content redundancy. The simulation results show that the proposed algorithm achieves a higher system throughput and can control content redundancy. © 2023, The Authors. All rights reserved.

关键词： Redundancy

来源：评论

学校读者我要写书评

暂无评论

Defining, measuring, and modeling passenger's in-vehicle experience and acceptance of automated vehicles

arXiv

引用

arXiv 2023年

作者： Bhide, Neeraja Hashimoto, Nanami Dokurno, Kazimierz Van der Hoorn, Chris Hoogendoorn-Lanser, Sascha Nordhoff, Sina Delft Center for Systems and Control Delft University of Technology Netherlands Department of Cognitive Robotics Delft University of Technology Netherlands Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands Department Transport & Planning Delft University of Technology Netherlands

Automated vehicle acceptance (AVA) has been measured mostly subjectively by questionnaires and interviews, with a main focus on drivers inside automated vehicles (AVs). To ensure that AVs are widely accepted by the public, ensuring the acceptance by both drivers and passengers is key. The in-vehicle experience of passengers will determine the extent to which AVs will be accepted by passengers. A comprehensive understanding of potential assessment methods to measure the passenger experience in AVs is needed to improve the in-vehicle experience of passengers and thereby the acceptance. The present work provides an overview of assessment methods that were used to measure a driver's behavior, and cognitive and emotional states during (automated) driving. The results of the review have shown that these assessment methods can be classified by type of data-collection method (e.g., questionnaires, interviews, direct input devices, sensors), object of their measurement (i.e., perception, behavior, state), time of measurement, and degree of objectivity of the data collected. A conceptual model synthesizes the results of the literature review, formulating relationships between the factors constituting the in-vehicle experience and AVA acceptance. It is theorized that the in-vehicle experience influences the intention to use, with intention to use serving as predictor of actual use. The model also formulates relationships between actual use and well-being. A combined approach of using both subjective and objective assessment methods is needed to provide more accurate estimates for AVA, and advance the uptake and use of AVs. © 2023, CC BY.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

Preventive-Corrective Cyber-Defense: Attack-Induced Region Minimization and Cybersecurity Margin Maximization

arXiv

引用

arXiv 2023年

作者： Hou, Jiazuo Teng, Fei Yin, Wenqian Song, Yue Hou, Yunhe The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong The University of Hong Kong Shenzhen Institute of Research and Innovation Shenzhen518057 China The Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom The Department of Control Science and Engineering Tongji University Shanghai201804 China The National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai201210 China The Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai200120 China

False data injection (FDI) cyber-attacks on power systems can be prevented by strategically selecting and protecting a sufficiently large measurement subset, which, however, requires adequate cyber-defense resources for measurement protection. With any given cyber-defense resource, this paper proposes a preventive-corrective cyber-defense strategy, which minimizes the FDI attack-induced region in a preventive manner, followed by maximizing the cybersecurity margin in a corrective manner. First, this paper proposes a preventive cyber-defense strategy that minimizes the volume of the FDI attack-induced region via preventive allocation of any given measurement protection resource. Particularly, a sufficient condition for constructing the FDI unattackable lines is proposed, indicating that the FDI cyber-attack could be locally rather than globally prevented. Then, given a non-empty FDI attack-induced region, this paper proposes a corrective cyber-defense strategy that maximizes the cybersecurity margin, leading to a trade-off between the safest-but-expensive operation point (i.e., Euclidean Chebyshev center) and the cheapest-but-dangerous operation point. Simulation results on a modified IEEE 14 bus system verify the effectiveness and cost-effectiveness of the proposed preventive-corrective cyber-defense strategy. Copyright © 2023, The Authors. All rights reserved.

关键词： Cost effectiveness

来源：评论

学校读者我要写书评

暂无评论

Adaptive Estimation for Environmental Monitoring Using an autonomous Underwater Vehicle

Adaptive Estimation for Environmental Monitoring Using an Au...

引用

IEEE Conference on Decision and control

作者： Ziwen Yang Joana Fonseca Shanying Zhu Cailian Chen Xinping Guan Karl H. Johansson Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Digital Futures

This paper considers the problem of monitoring and adaptively estimating an environmental field, such as temperature or salinity, using an autonomous underwater vehicle (AUV). The AUV moves in the field and persistently measures environmental scalars and its position in its local coordinate frame. The environmental scalars are approximately linearly distributed over the region of interest, and an adaptive estimator is designed to estimate the gradient. By orthogonal decomposition of the velocity of the AUV, a linear time-varying system is equivalently constructed, and the sufficient conditions on the motion of the AUV are established, under which the global exponential stability of the estimation error system is rigorously proved. Furthermore, an estimate of the exponential convergence rate is given, and a reference trajectory that maximizes the estimate of the convergence rate is obtained for the AUV to track. Numerical examples verify the stability and efficiency of the system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Efficientfacev2s: A Lightweight Model and a Benchmarking Approach for Drone-Captured Face Recognition

SSRN

引用

SSRN 2024年

作者： Alansari, Mohamad Alnuaimi, Khaled Ganapathi, Iyyakutti Iyappan Alansari, Sara Javed, Sajid Shoufan, Abdulhadi Zweiri, Yahya Werghi, Naoufel Department of Electrical Engineering College Of Computing And Mathematical Sciences Department of Computer Science Khalifa University Abu Dhabi United Arab Emirates Center for Autonomous Robotic Systems Khalifa University Abu Dhabi United Arab Emirates Center for Cyber-Physical Systems Khalifa University Abu Dhabi United Arab Emirates Department of Aerospace Engineering Khalifa University Abu Dhabi United Arab Emirates Khalifa University Abu Dhabi United Arab Emirates

Face Recognition (FR) in aerial imagery encounters distinctive challenges, notably stemming from Low Resolution (LR) and varying pitch angles. The influence of image quality, particularly resolution, on the performance of contemporary FR systems is well-established. However, limited exploration exists regarding the performance of FR models on drone-captured images, primarily due to the scarcity of suitable *** address this gap, our study investigates the efficacy of FR models when applied to drone-captured facial images. We utilize state-of-the-art (SOTA) lightweight and large FR models, evaluating them across three drone-captured FR benchmarks and one dataset focused on LR FR. To ensure a comprehensive evaluation, additional seven widely recognized benchmarks are adopted and artificially downsampled and rotated to simulate the impact of distance and altitude on the view from a drone to a *** highlight a substantial decrease in accuracy across all FR models in these scenarios. In response to this challenge, we introduce a novel FR model, EfficientFaceV2S, demonstrating consistent SOTA performance across all benchmarks while imposing minimal computational demands. This characteristic makes it particularly suitable for real-time and resource-constrained applications. © 2024, The Authors. All rights reserved.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Constrained Reinforcement Learning for Dynamic Material Handling

Constrained Reinforcement Learning for Dynamic Material Hand...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Chengpeng Hu Ziming Wang Jialin Liu Junyi Wen Bifei Mao Xin Yao Research Institute of Trustworthy Autonomous Systems (RITAS) Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Guangdong Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China Trustworthiness Theory Research Center Huawei Technologies Co. Ltd Shenzhen China

As one of the core parts of flexible manufacturing systems, material handling involves storage and transportation of materials between workstations with automated vehicles. The improvement in material handling can impulse the overall efficiency of the manufacturing system. However, the occurrence of dynamic events during the optimisation of task arrangements poses a challenge that requires adaptability and effectiveness. In this paper, we aim at the scheduling of automated guided vehicles for dynamic material handling. Motivated by some real-world scenarios, unknown new tasks and unexpected vehicle breakdowns are regarded as dynamic events in our problem. We formulate the problem as a constrained Markov decision process which takes into account tardiness and available vehicles as cumulative and instantaneous constraints, respectively. An adaptive constrained reinforcement learning algorithm that combines Lagrangian relaxation and invalid action masking, named RCPOM, is proposed to address the problem with two hybrid constraints. Moreover, a gym-like dynamic material handling simulator, named DMH-GYM, is developed and equipped with diverse problem instances, which can be used as benchmarks for dynamic material handling. Experimental results on the problem instances demonstrate the outstanding performance of our proposed approach compared with eight state-of-the-art constrained and non-constrained reinforcement learning algorithms, and widely used dispatching rules for material handling.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Electroencephalogram and Event-Related Potential in Mild Cognitive Impairment: Recent Developments in Signal Processing, Machine Learning, and Deep Learning

IEEE Journal of Selected Areas in Sensors

引用

IEEE Journal of Selected Areas in Sensors 2025年 2卷 162-184页

作者： Azami, Hamed Mirjalili, Mina Rajji, Tarek K. Wu, Chien-Te Humeau-Heurtier, Anne Jung, Tzyy-Ping Wei, Chun-Shu Trinh, Thanh-Tung Liu, Yi-Hung University of Toronto Centre for Addiction and Mental Health TorontoONM5S 1A1 Canada University of Texas Southwestern Medical Center DallasTX75390 United States University of Florida Department of Occupational Therapy GainesvilleFL32611 United States University of Florida Center for Cognitive Aging and Memory McKnight Brain Institute GainesvilleFL32611 United States University of Angers LARIS SFR MATHSTIC AngersF-49000 France University of California Institute for Neural Computation Institute of Engineering in Medicine La Jolla CA92093 United States National Yang Ming Chiao Tung University Department of Computer Science Hsinchu City30010 Taiwan National Taipei University of Technology Graduate Institute of Manufacturing Technology College of Mechanical and Electrical Engineering Taipei10608 Taiwan Vietnam National University Department of Information and Communication Technology Faculty of Nontraditional Security HSB Hanoi720325 Viet Nam National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Hsinchu City30010 Taiwan

Mild cognitive impairment (MCI) is an early stage of non-age-related cognitive decline with an increased risk of progressing to dementia. Early detection of MCI is essential for implementing preventative strategies that can delay or prevent the onset of dementia, ultimately improving patient outcomes and reducing healthcare costs. Electroencephalograms (EEGs) and event-related potentials (ERPs) have shown significant promise in detecting MCI due to their affordability, real-time monitoring capabilities, and noninvasiveness. EEG provides continuous brain activity data, while ERPs offer insights into specific cognitive processes by analyzing brain responses to stimuli. These methods can complement each other in MCI diagnosis by providing a comprehensive view of overall brain function and detailed information on specific cognitive processes. However, EEG and ERP are susceptible to noise and interindividual variability, which can hinder their reliability. In addition, applying machine learning models on EEG or ERP for MCI detection presents challenges such as the risk of overfitting and difficulties in interpreting the underlying decision-making process. This review emphasizes recent advancements in signal processing and feature extraction methods applied to EEG and ERP data and explores the use of machine learning and deep learning techniques to enhance diagnostic accuracy and interpretative depth. By integrating these methodologies, the review highlights how EEG and ERP can contribute to a more effective understanding and monitoring of cognitive changes associated with MCI, underscoring the importance of early diagnosis for timely intervention and improved patient care. Finally, the review focuses on future research directions, including the development of advanced analytical techniques and multimodal integration approaches involving EEG and ERP to further improve diagnostic accuracy and clinical application. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

引用

European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, computer Retrospective Study

来源：评论

学校读者我要写书评

暂无评论

Communication and control in Collaborative UAVs: Recent Advances and Future Trends

arXiv

引用

arXiv 2023年

作者： Javaid, Shumaila Saeed, Nasir Qadir, Zakria Fahim, Hamza He, Bin Song, Houbing Bilal, Muhammad The Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China Al Ain15551 United Arab Emirates The School of Engineering Design and Built Environment Western Sydney University Locked Bag 1797 PenrithNSW2751 Australia Embry-Riddle Aeronautical University Daytona BeachFL32114 United States The Department of Computer Engineering Hankuk University of Foreign Studies Gyeonggido Yongin-si17035 Korea Republic of

The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains. Nevertheless, the challenges of establishing high-speed communication links, flexible control strategies, and developing efficient collaborative decision-making algorithms for a swarm of UAVs limit their autonomy, robustness, and reliability. Thus, a growing focus has been witnessed on collaborative communication to allow a swarm of UAVs to coordinate and communicate autonomously for the cooperative completion of tasks in a short time with improved efficiency and reliability. This work presents a comprehensive review of collaborative communication in a multi-UAV system. We thoroughly discuss the characteristics of intelligent UAVs and their communication and control requirements for autonomous collaboration and coordination. Moreover, we review various UAV collaboration tasks, summarize the applications of UAV swarm networks for dense urban environments and present the use case scenarios to highlight the current developments of UAV-based applications in various domains. Finally, we identify several exciting future research direction that needs attention for advancing the research in collaborative UAVs. © 2023, CC BY.

关键词： Unmanned aerial vehicles (UAV)

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：