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Key Agreement and Management Scheme Based on Blockchain for 5G-Enabled Vehicular Networks

China Communications 2025年第3期22卷 270-287页

作者： Wang Zhihua Wang Shuaibo Wang Haofan Li Jiaze Yao Yizhe Wang Yongjian Yang Xiaolong School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China School of Cyber Science and Engineering Zhengzhou UniversityZhengzhou 449001China Lab of National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing 100029China

5G technology has endowed mobile communication terminals with features such as ultrawideband access,low latency,and high reliability transmission,which can complete the network access and interconnection of a large number of devices,thus realizing richer application scenarios and constructing 5G-enabled vehicular ***,due to the vulnerability of wireless communication,vehicle privacy and communication security have become the key problems to be solved in vehicular ***,the large-scale communication in the vehicular networks also makes the higher communication efficiency an inevitable *** order to achieve efficient and secure communication while protecting vehicle privacy,this paper proposes a lightweight key agreement and key update scheme for 5G vehicular networks based on ***,the key agreement is accomplished using certificateless public key cryptography,and based on the aggregate signature and the cooperation between the vehicle and the trusted authority,an efficient key updating method is proposed,which reduces the overhead and protects the privacy of the vehicle while ensuring the communication ***,by introducing blockchain and using smart contracts to load the vehicle public key table for key management,this meets the requirements of vehicle traceability and can dynamically track and revoke misbehaving ***,the formal security proof under the eck security model and the informal security analysis is conducted,it turns out that our scheme is more secure than other authentication schemes in the vehicular *** analysis shows that our scheme has lower overhead than existing schemes in terms of communication and computation.

关键词： blockchain certificateless public key cryptography 5G vehicular networks key agreement key management

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End-to-End Deep Learning Models for Estimating Stride Length in Frail Older Adults 24

End-to-End Deep Learning Models for Estimating Stride Length...

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2nd International Conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Zhang, Yan Cai, Jinghao Li, Xiang Wu, Chuanyan Ma, Xin Li, Yibin Song, Rui Zhang, Huanghe School of Control Science and Engineering Shandong University Shandong China The Center for Robotics School of Control Science and Engineering Shandong University Shandong China School of Intelligent Engineering Shandong Management University Shandong China

ISBN: (纸本)9798400710681

Accurate estimation of spatial gait parameters is crucial for assessing fall risk in older adults, helping to identify potential movement impairments and prevent falls. Traditionally, extracting stride length from wearable sensors relies on the double integration of accelerometer data combined with the zero-velocity update (ZUPT) technique. However, this method may not be suitable for older adults, as their zero-velocity phases might be absent. To address this limitation, we propose three fundamental end-to-end deep learning models—deep neural networks (DNN), deep convolutional neural networks (DCNN), and long short-term memory (LSTM)—to estimate stride length from inertial sensor data corresponding to specific strides. These models are trained on a publicly available dataset (i.e., GSTRIDE) comprising 165,694 strides from 155 elderly patients and are evaluated using hold-out and 10-fold cross-validation methodologies. The DCNN model achieved the best results, with a mean absolute error (MAE) of 8.9 cm using the hold-out method. Compared to the traditional double integration method, the proposed deep learning models do not require zero-velocity phase detection. Instead, they rely on initial contact detection, making them more suitable for older adults, where initial contacts can be reliably detected even when they do not occur under the hindfoot. © 2024 Copyright held by the owner/author(s).

关键词： Convolutional neural networks

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MESSI: Task Mapping and Scheduling Strategy for FPGA-based Heterogeneous Real-Time Systems

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ACM Transactions on Design Automation of Electronic Systems 2025年第3期30卷 1-29页

作者： Ahmadi-Pour, Sallar Saha, Sangeet Mcdonald-Maier, Klaus Drechsler, Rolf Institute of Computer Science University of Bremen Faculty 3 Mathematics and Computer Science Bremen Bremen Germany Robotics and Embedded Systems Research Group University of Essex School of Computer Science and Electronic Engineering Colchester United Kingdom Cyber-Physical Systems DFKI Rheinland-Pfalz Kaiserslautern Germany

Continuous demands for improved performance within constrained resource budgets are driving a move from homogeneous to heterogeneous processing platforms for the implementation of today's Real-Time (RT) embedded systems. The applications executing on such systems are typically represented as a Precedence Task Graph (PTG), where a node represents a task or algorithm for one functionality and edges represent the complex interactions between multiple functionalities. Due to RT constraints, the task graph needs to be executed within a specified deadline. Although some existing studies have looked into solving this challenge, comprehensive studies that combine the theoretical features of RT task-graph mapping and scheduling with practical runtime architectural characteristics have mostly been ignored to date. Hence, in this article, we consider the challenge of scheduling an RT application modeled as a single PTG, with the objective of minimizing the overall execution time under Hardware (HW) resource and deadline constraints for heterogeneous Central Processing Unit (CPU) + Field Programmable Gate Array (FPGA) architectures. First, we introduce an optimal solution using Integer Linear Programming (ILP). However, this ILP-based optimal solution suffers from computational complexity and does not scale well even for moderately large problem sizes. Hence, we additionally propose heuristic algorithms for task mapping and scheduling. The efficiency of the proposed scheme, named MESSI, has been evaluated through experiments using PTG on a practical CPU+FPGA system regarding current technology restrictions. Our experiments demonstrate that performance gains of 55.6% and area usage reductions of 46.3% are possible compared to full Software (SW) and HW execution, respectively. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Integer programming

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A Reinforcement Learning-Based Method for Wing Grid Optimization 9

A Reinforcement Learning-Based Method for Wing Grid Optimiza...

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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Wu, Pin Xu, Liji Tu, Zekai Feng, Weibing He, Yaolong School of Computer Engineering and Science Shanghai University Shanghai Frontier Science Center of Mechanoinformatics Shanghai China School of Computer Engineering and Science Shanghai University Shanghai China

ISBN: (纸本)9798350376548

This study investigates enhancing airfoil grid generation's automation and computational efficiency in aerospace engineering using reinforcement learning and Graph Convolutional Networks (GCNs). Traditional grid generation methods, often cumbersome and inefficient, have been transcended by the introduction of GCNs and reinforcement learning, which effectively handle high-dimensional and nonlinear challenges. These technologies have improved the grid design of the NACA0012 airfoil by optimizing node relationships and strategy execution, leading to improved grid quality and reduced node numbers while maintaining flow field data accuracy. © 2024 IEEE.

关键词： Reinforcement learning

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Research on Robotic multi-layer multi-pass welding planning of Intersecting pipe 3

Research on Robotic multi-layer multi-pass welding planning ...

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3rd International Conference on Control and Intelligent robotics, ICCIR 2023

作者： Zhao, Xingwang Wang, Zhongyi Tian, Xincheng Center for Robotics School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9781510671867

In the multi-layer multi-pass welding of intersecting pipe fittings, the traditional teaching method is labor-intensive and has low welding accuracy. To weld more intelligently and accurately, this paper proposes a robotic multi-layer multi-pass welding filling strategy, determines the layout points of the weld passes, and plans the pose of the welding torch. In addition, this paper gives the transformation relationship between the welding seam coordinate system and the welding torch coordinate system, and finally simulates the weld passes. © 2023 SPIE.

关键词： Seam welding

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Continuous Query-based Data Trading

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Performance Evaluation Review 2024年第1期52卷 73-74页

作者： Cheng, Jin Ding, Ningning Lui, John C.S. Huang, Jianwei School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Shenzhen Shenzhen China Department of Electrical and Computer Engineering Northwestern University Evanston United States Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Hong Kong

In the era of big data, traditional data trading methods designed for one-time queries on static databases fail to meet the demands of continuous query-based trading on streaming data, often resulting in repeated and inaccurate charges due to neglecting computation sharing in continuous query execution. To address this, we introduce CQTrade, the first trading framework tailored for continuous queries, which incorporates computation sharing across different time windows and queries, enhancing integration with existing trading systems. Our contributions include a theoretical analysis of computation-sharing techniques, the development of a general optimization problem to maximize seller revenue adaptable to various techniques, and the proposal of a branch-and-price algorithm to handle the problem's complexity. Our evaluation shows that the proposed framework improves the success rate of data trading by 12.8% and boosts the seller's revenue by an average of 28.7%, compared to the one-time query-based data trading methods used in the current data market. © 2024 Owner/Author.

关键词： Integer programming

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Research on Trajectory Planning Method Applied to Intersecting Line Smooth Cutting 5

Research on Trajectory Planning Method Applied to Intersecti...

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5th International Conference on Intelligent Control, Measurement and Signal Processing, ICMSP 2023

作者： Wang, Zhongyi Zhao, Xingwang Tian, Xincheng School of Control Science and Engineering Center for Robotics Shandong University Jinan China

ISBN: (纸本)9798350336030

The cutting quality of intersecting lines can be affected by cutting model and cutting process. To improve that, this paper builds a round pipe-intersecting cutting model connected by branch pipe internally without groove according to the principle of intersecting, and it uses the smooth transition algorithm for the cutting start point to avoid the generation of cutting gaps. Finally, the model's trajectory planning algorithm is verified through robot simulation experiments. The result shows that this method can improve the cutting quality by the established model and has good significance in reality. © 2023 IEEE.

关键词： Trajectories

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A color image encryption scheme based on a 2D coupled chaotic system and diagonal scrambling algorithm

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Chinese Physics B 2024年第7期33卷 233-243页

作者：苏静明方士辉洪炎温言 Anhui Mining Machinery and Electrical Equipment Coordination Innovation Center Anhui University of Science and TechnologyHuainan 232001China School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230009China

A novel color image encryption scheme is developed to enhance the security of encryption without increasing the complexity. Firstly, the plain color image is decomposed into three grayscale plain images, which are converted into the frequency domain coefficient matrices(FDCM) with discrete cosine transform(DCT) operation. After that, a twodimensional(2D) coupled chaotic system is developed and used to generate one group of embedded matrices and another group of encryption matrices, respectively. The embedded matrices are integrated with the FDCM to fulfill the frequency domain encryption, and then the inverse DCT processing is implemented to recover the spatial domain signal. Eventually,under the function of the encryption matrices and the proposed diagonal scrambling algorithm, the final color ciphertext is obtained. The experimental results show that the proposed method can not only ensure efficient encryption but also satisfy various sizes of image encryption. Besides, it has better performance than other similar techniques in statistical feature analysis, such as key space, key sensitivity, anti-differential attack, information entropy, noise attack, etc.

关键词： color image encryption discrete cosine transform two-dimensional(2D)coupled chaotic system diagonal scrambling

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Adversarial Geometric Attacks for 3D Point Cloud Object Tracking

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IEEE Transactions on Multimedia 2025年 27卷 3144-3157页

作者： Yao, Rui Zhang, Anqi Zhou, Yong Zhao, Jiaqi Liu, Bing El Saddik, Abdulmotaleb China University of Mining and Technology School of Computer Science and Technology Mine Digitization Engineering Research Center of the Ministry of Education Xuzhou221116 China University of Ottawa School of Electrical Engineering and Computer Science OttawaONK1N 6N5 Canada

3D point cloud object tracking (3D PCOT) plays a vital role in applications such as autonomous driving and robotics. Adversarial attacks offer a promising approach to enhance the robustness and security of tracking models. However, existing adversarial attack methods for 3D PCOT seldom leverage the geometric structure of point clouds and often overlook the transferability of attack strategies. To address these limitations, this paper proposes an adversarial geometric attack method tailored for 3D PCOT, which includes a point perturbation attack module (non-isometric transformation) and a rotation attack module (isometric transformation). First, we introduce a curvature-aware point perturbation attack module that enhances local transformations by applying normal perturbations to critical points identified through geometric features such as curvature and entropy. Second, we design a Thompson sampling-based rotation attack module that applies subtle global rotations to the point cloud, introducing tracking errors while maintaining imperceptibility. Additionally, we design a fused loss function to iteratively optimize the point cloud within the search region, generating adversarially perturbed samples. The proposed method is evaluated on multiple 3D PCOT models and validated through black-box tracking experiments on benchmarks. For P2B, white-box attacks on KITTI reduce the success rate from 53.3% to 29.6% and precision from 68.4% to 37.1%. On NuScenes, the success rate drops from 39.0% to 27.6%, and precision from 39.9 to 26.8%. Black-box attacks show a transferability, with BAT showing a maximum 47.0% drop in success rate and 47.2% in precision on KITTI, and a maximum 22.5% and 27.0% on NuScenes. © 1999-2012 IEEE.

关键词： Iterative methods

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Recognition of carrier-based aircraft flight deck operations based on dynamic graph

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Chinese Journal of Aeronautics 2025年第3期38卷 474-490页

作者： Xingyu GUO Jiaxin LI Hua WANG Junnan LIU Yafei LI Mingliang XU School of Computer Science and Artificial Intelligence Zhengzhou UniversityZhengzhou 450001China Engineering Research Center of Intelligent Swarm Systems Ministry of EducationZhengzhou 450001China National Supercomputing Center in Zhengzhou Zhengzhou 450001China School of Geo-Science&Technology Zhengzhou UniversityZhengzhou 450001China

Accurate recognition of flight deck operations for carrier-based aircraft, based on operation trajectories, is critical for optimizing carrier-based aircraft performance. This recognition involves understanding short-term and long-term spatial collaborative relationships among support agents and positions from long spatial–temporal trajectories. While the existing methods excel at recognizing collaborative behaviors from short trajectories, they often struggle with long spatial–temporal trajectories. To address this challenge, this paper introduces a dynamic graph method to enhance flight deck operation recognition. First, spatial–temporal collaborative relationships are modeled as a dynamic graph. Second, a discretized and compressed method is proposed to assign values to the states of this dynamic graph. To extract features that represent diverse collaborative relationships among agents and account for the duration of these relationships, a biased random walk is then conducted. Subsequently, the Swin Transformer is employed to comprehend spatial–temporal collaborative relationships, and a fully connected layer is applied to deck operation recognition. Finally, to address the scarcity of real datasets, a simulation pipeline is introduced to generate deck operations in virtual flight deck scenarios. Experimental results on the simulation dataset demonstrate the superior performance of the proposed method.

关键词： Carrier-based aircraft Flight deck operation Operation recognition Long spatial-temporal trajectories Dynamic graph Biased random walk Graph embeddings

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