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intelligent energy management in hybrid electric cycling work vehicles: A multi-task learning approach

Energy 2025年 326卷

作者： Zhang, Wei Li, Jinchen Ma, Hongfeng Niu, Chengyong Wang, Jixin Yang, Zhiyu Li, Lijun Huang, Linsen Chongqing Key Laboratory of Green Design and Manufacturing of Intelligent Equipment Chongqing Technology and Business University Chongqing 400067 China State Key Laboratory of Intelligent Manufacturing of Advanced Construction Machinery Xuzhou221004 China Vehicle and Intelligent Driving Testing and Research Department China Merchants Testing Vehicle Technology Research Institute Co. Ltd. Chongqing 401329 China School of Mechanical and Aerospace Engineering Jilin University Changchun130012 China School of Transportation Science and Engineering Beihang University Beijing100191 China

Learning-based approaches have become mainstream solutions for achieving intelligent energy management in hybrid electric vehicles (HEVs). For hybrid electric cycling work vehicles (HECWVs), predictable driving routes facilitate model learning. Nevertheless, effectively tailoring and deploying learning-based energy management strategies specifically for HECWVs encounters significant hurdles. These primarily involve substantial data requirements to capture diverse operational tasks, achieving robust generalization across heterogeneous scenarios, and ensuring the interpretability of the resultant control policies. To address these issues in HECWVs, this study pioneers the introduction of a multi-task learning mechanism and presents a customized energy management approach. Specifically, a work condition clustering module using Self-Organizing Maps (SOM) enables efficient dimensionality reduction and intuitive visual clustering. Additionally, the prioritized sweeping method is introduced within the multi-task learning framework to enhance learning efficiency and establish an efficient cross-task sharing mechanism. Finally, this study introduces an asymmetric sharing mechanism to accommodate diverse working conditions among HECWVs, thereby enhancing strategic decision-making responsiveness. This enhancement is achieved by guiding targeted interactions among tasks through an asymmetric parameter-sharing structure aligned with the proportion of working conditions. Real data analysis demonstrates improved model interpretability and adaptability in sparse data scenarios. Additionally, it outperforms traditional model-based learning approaches in both optimality and strategic response speed in environments with heterogeneous driving characteristics. Notably, fuel economy is improved by 5.3 %, and the learning response speed is enhanced by 388 %. © 2025 Elsevier Ltd

关键词： Multi-task learning

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VFLMonitor: Defending One-Party Hijacking Attacks in Vertical Federated Learning

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IEEE Transactions on Information Forensics and Security 2025年 20卷 4828-4843页

作者： Xiangrui Xu Yiwen Zhao Yufei Han Yongsheng Zhu Zhen Han Guangquan Xu Bin Wang Shouling Ji Wei Wang School of Information Science and Technology Qingdao University of Science and Technology Qingdao China Thomas Lord Department of Computer Science University of Southern California Los Angeles CA USA INRIA Rennes Brittany France Institute of Computing Technologies China Academy of Railway Sciences Corporation Ltd. Beijing China Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing China Tianjin Key Laboratory of Advanced Networking (TANK) College of Intelligence and Computing Tianjin University Tianjin China Zhejiang Key Laboratory of Artificial Intelligence of Things (AIoT) Network and Data Security Hangzhou China College of Computer Science and Technology Zhejiang University Zhejiang China Ministry of Education Key Laboratory for Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an China

Vertical Federated Learning (VFL) is susceptible to various one-party hijacking attacks, such as Replay and Generation attacks, where a single malicious client can manipulate the model to produce attacker-specified results, thereby compromising its reliability in real-world deployments. In this paper, we first uncover the underlying mechanisms of these attacks and observe that successful attacks induce significant discrepancies in the embedding-label associations across different clients. We establish a theoretical framework demonstrating how these discrepancies can serve as reliable indicators for detecting hijacking attempts. Building upon this insight, we propose VFLMonitor, a robust defense mechanism that leverages these embedding-label discrepancies to detect and mitigate hijacking attacks. Specifically, VFLMonitor identifies suspicious queries by analyzing differences in label estimations from multiple clients and applies a majority voting rule to correct or filter out these malicious queries. Moreover, VFLMonitor introduces a novel regularization strategy during training to reduce intra-class variance in embeddings, thereby enhancing their discriminative power and improving defense effectiveness. Extensive experiments were conducted on 5 real-world datasets against 2 different attack types under 3 attack scenarios. The results demonstrate that VFLMonitor can effectively identify and exclude potential hijacked requests in all types of one-party hijacking attacks, while maintaining a meager false positive rate for legitimate queries.

关键词： Training Servers Electronic mail Artificial intelligence Reliability theory Predictive models Federated learning Data models Computational modeling Collaboration

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Joint design of Radar Receive Filter and Unimodular ISAC Waveform with Sidelobe Level Control

arXiv

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arXiv 2025年

作者： Zhang, Kecheng Liu, Ya-Feng Wang, Zhongbin Yuan, Weijie Keskin, Musa Furkan Wymeersch, Henk Xia, Shuqiang School of System Design and Intelligent Manufacturing The Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Electrical Engineering Chalmers University of Technology Gothenburg41296 Sweden ZTE Corporation The State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518055 China

Integrated sensing and communication (ISAC) has been considered a key feature of next-generation wireless networks. This paper investigates the joint design of the radar receive filter and dual-functional transmit waveform for the multiple-input multiple-output (MIMO) ISAC system. While optimizing the mean square error (MSE) of the radar receive spatial response and maximizing the achievable rate at the communication receiver, besides the constraints of full-power radar receiving filter and unimodular transmit sequence, we control the maximum range sidelobe level, which is often overlooked in existing ISAC waveform design literature, for better radar imaging performance. To solve the formulated optimization problem with convex and nonconvex constraints, we propose an inexact augmented Lagrangian method (ALM) algorithm. For each subproblem in the proposed inexact ALM algorithm, we custom-design a block successive upper-bound minimization (BSUM) scheme with closed-form solutions for all blocks of variable to enhance the computational efficiency. Convergence analysis shows that the proposed algorithm is guaranteed to provide a stationary and feasible solution. Extensive simulations are performed to investigate the impact of different system parameters on communication and radar imaging performance. Comparison with the existing works shows the superiority of the proposed algorithm. © 2025, CC BY-NC-SA.

关键词： Mean square error

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Single-cell technologies: current and near future

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Science China(Life Sciences) 2025年第1期68卷 1-4页

作者： Chenfei Wang Qi Liu Xiaohui Fan Tieliu Shi KeyLaboratory of Spine and Spinal CordInjury Repairand Regeneration Ministry of EducationOrthopedics DepartmentTongji HospitalBioinformatics DepartmentSchoolofLifeSciencesandTechnologyTongji UniversityShanghai 200082China Frontier Science Center for Stem Cells School of Life Sciences and TechnologyTongji UniversityShanghai 200092China Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji UniversityShanghai 200082China Research Institute of Intelligent Computing Zhejiang LabHangzhou 311121China Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang UniversityJiaxing 314103China Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghai 200241China Key Laboratory of Advanced Theory and Application in Statistics and Data Science(MOE) School of StatisticsEast China Normal UniversityShanghai 200062China

Single-cell technologies enable the indepth exploration of multiple biological hierarchies at the scale of individual cells,which have deepened our knowledge of cellular diversity,tissue organization,and overall organism function(Sun et al.,2024).In 2009,single-cell RNA sequencing(scRNA-seq)was first developed as a powerful tool to dissect gene expression and uncover transcriptional *** the rapid advancement of technology,single-cell approaches have expanded to encompass other omics,such as genomics,epigenomics,proteomics,and ***,multimodal technologies including spatially resolved transcriptomics and clustered regularly interspaced short palindromic repeats(CRISPR)screening at the single-cell level further advanced our ability to comprehensively understand cellular ***-cell methods provide deeper insights into disease mechanisms across various conditions,including cancer,developmental disorders,and aging-associated *** this issue,we focus on topics related to single-cell methods,covering the following four aspects:(i)single-cell multi-omic sequencing technology;(ii)single-cell spatial technology;(iii)singlecell CRISPR screening technology;(iv)applications of single-cell technology.

关键词： expanded enable insight

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A Novel Tunable Stiffness Method Using Gecko Setae-Inspired Adhesive Interlayer Films for Soft Actuator

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Journal of Bionic Engineering 2025年 1-16页

作者： Wang, Zhihuan Xu, Linsen Ye, Liangzhi Wang, Mingming Zhang, Zhihua Wu, Tao College of Mechanical and Electrical Engineering Hohai University Changzhou China Changzhou Key Laboratory of Intelligent Manufacturing Technology and Equipment Changzhou China Suzhou Research Institute Hohai University Suzhou China Changzhou Institute of Advanced Manufacturing Technology Changzhou China Wuhan Second Ship Design and Research Institute Wuhan China

Soft actuators are inherently flexible and compliant, traits that enhance their adaptability to diverse environments and tasks. However, their low structural stiffness can lead to unpredictable and uncontrollable complex deformations when substantial force is required, compromising their load-bearing capacity. This work proposes a novel method that uses gecko setae-inspired adhesives as interlayer films to construct a layer jamming structure to adjust the stiffness of soft actuators. The mechanical behavior of a single tilted microcylinder was analyzed using the energy method to determine the adhesion force of the adhesives. The gecko-inspired adhesive was designed under the guidance of the adhesion force model. Testing under various loads and directions revealed that the tilted characteristic of microcylinders can enhance the adhesion force in its grasping direction. The adhesive demonstrated excellent adhesion performance compared to other typical adhesives. A tunable stiffness actuator using gecko setae-inspired adhesives (TSAGA), was developed with these adhesives serving as interlayer films. The stiffness model of TSAGA was derived by analyzing its axial compression force. The results of stiffness test indicate that the adhesives serve as interlayer films can adjust the stiffness in response to applied load. TSAGA was compared with other typical soft actuators in order to evaluate the stiffness performance, and the results indicate that TSAGA exhibits the highest stiffness and the widest tunable stiffness range. This demonstrates the superior performance of the setae-inspired adhesives as interlayer films in terms of stiffness adjustment.

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NavG: Risk-Aware Navigation in Crowded Environments Based on Reinforcement Learning with Guidance Points

arXiv

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arXiv 2025年

作者： Zhang, Qianyi Luo, Wentao Liu, Boyi Zhang, Ziyang Wang, Yaoyuan Liu, Jingtai Institute of Robotics and Automatic Information System Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin China Advanced Computing and Storage Lab Huawei 2012 Lab China Department of Electronic and Computer Engineering The Kong Kong University of Science and Technology Hong Kong

Motion planning in navigation systems is highly susceptible to upstream perceptual errors, particularly in human detection and tracking. To mitigate this issue, the concept of guidance points—a novel directional cue within a reinforcement learning-based framework—is introduced. A structured method for identifying guidance points is developed, consisting of obstacle boundary extraction, potential guidance point detection, and redundancy elimination. To integrate guidance points into the navigation pipeline, a perception-to-planning mapping strategy is proposed, unifying guidance points with other perceptual inputs and enabling the RL agent to effectively leverage the complementary relationships among raw laser data, human detection and tracking, and guidance points. Qualitative and quantitative simulations demonstrate that the proposed approach achieves the highest success rate and near-optimal travel times, greatly improving both safety and efficiency. Furthermore, real-world experiments in dynamic corridors and lobbies validate the robot’s ability to confidently navigate around obstacles and robustly avoid pedestrians. © 2025, CC BY.

关键词： Travel time

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Motion Planning for Minimizing Base Disturbance of Space Manipulators

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Journal of Donghua University(English Edition) 2015年第2期32卷 252-256页

作者：纪路周东生张强 Key Laboratory of Advanced Design and Intelligent Computing(Dalian University) Ministry of Education

A simulated annealing particle swarm optimization(PSO)algorithm is utilized in this paper to plan the motion of space manipulators with minimized base disturbance,not only its attitude but also its *** space manipulators must meet the Law of Momentum Conservation,any motion of manipulators will disturb the spacecraft which is free-float in the space *** paper tries to limit this effect to the ***,this paper establishes the mathematical model for space manipulators by generalized Jacobian matrix(GJM) and analyzes its inverse kinematics by Theory of ***,a polynomial function of seventh degree is used to parameterize the joint motion and quaternion representation is also used to represent attitude of ***,this paper designs a proper objective function and depicts this algorithm detailedly and ***,the results of numerical simulation are verified by the proposed algorithm.

关键词： utilized kinematics verified disturbance inverse annealing attitude polynomial effector spacecraft

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A Bi-selection Method Based on Consistent Matrix for Large-Scale Datasets

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IEEE Transactions on Fuzzy Systems 2025年

作者： Quan, Jinsheng Qiao, Fengcai Yang, Tian Shen, Shuo Qian, Yuhua Hunan Normal University Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Institute of Interdisciplinary Studies Changsha410081 China National University of Defense Technology College of Advanced Interdisciplinary Studies Changsha410081 China Shanxi University Institute of Big Data Science and Industry Taiyuan030006 China

Biselection (feature and sample selection) enhances the efficiency and accuracy of machine learning models when handling large-scale data. Fuzzy rough sets, an uncertainty mathematics model known for its excellent interpretability, are widely used in machine learning, particularly for feature selection. While the consistent matrix has significantly improved the computational efficiency and scalability of feature selection, like most fuzzy rough set-based methods, it focuses only on feature selection and seldom incorporates sample selection. This feature-centric approach can limit classification performance, particularly in noisy and large-scale datasets where both features and samples require judicious selection. To overcome these limitations, this article explores the integration of sample selection with feature selection. First, we introduce a β-consistent granulation method to generate more accurate and concise fuzzy information granules, reducing the impact of noisy samples. In addition, a novel membership function is employed to distinguish noise while simultaneously evaluating both features and samples. As a result, a biselection algorithm with linear computation complexity is proposed to select high-quality features and samples. Numerical experiments demonstrate that, compared to eleven representative algorithms, our proposed method achieves an average accuracy improvement of 9.66% and a 933-fold increase in efficiency. © 2025 IEEE.

关键词： Biselection consistent matrix (CM) fuzzy sets granular computing rough sets

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Development and Implementation of a Wisdom Course Utilizing the “Teaching-Innovation-Competition” Model within the Virtual Teaching and Research Section of Mechatronic Engineering Major in China 24

Development and Implementation of a Wisdom Course Utilizing ...

引用

Proceedings of the 2024 3rd International Conference on Artificial Intelligence and Education

作者： Wei Chen Wenpeng Ma Wenhua Hu Fulong Liu Xiaotao Zhang 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 University of Technology Tianjin China

ISBN: (纸本)9798400712692

A new teaching model of teaching-innovation-competition is presented and a wisdom course based on this model is developed for mechatronics engineering majors, mainly to deal with several existing problems such as limited experimentation and lack of innovative inspiration in Chinese universities. This study elaborates the course objectives and structure of curriculum system, including digitalized teaching content, project-driven teaching means, innovation platform, web-based resource support, team competition and diversified evaluation method. Through a teaching case study within mechatronic engineering major, the teaching mechanism and achievements are demonstrated. The study results indicate that the proposed teaching mode based on the virtual teaching and research section, significantly improves students' innovation ability and the teaching effects, compared to traditional teaching methods. This teaching mode can also be extended to other majors for reference.

关键词： Construction and Practice of Wisdom Course

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Cooperative driving of mixed autonomy vehicles: A delay-compensating MPC approach

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Fundamental Research 2025年

作者： Wang, Xuan Bian, Yougang Hu, Mangjiang Qin, Hongmao Ding, Rongjun The State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle College of Mechanical and Vehicle Engineering Hunan University Changsha 410082 China Wuxi Intelligent Control Research Institute (WICRI) of Hunan University Wuxi 214115 China

The era of mixed autonomy when connected automated vehicles and human-driven vehicles co-exist will last a long time. Communication time delays are inevitable and may highly deteriorate the safety and stability of mixed vehicle platoons in dynamic tracking scenarios. To address this challenge, this paper proposes a model predictive control (MPC) method for cooperative control of mixed platoons with time-varying communication delays. The detriments of time delay to cooperative control are analyzed and two delay compensation mechanisms are established, based on which a dual-mode MPC controller is designed. The feasibility, closed-loop stability, and head-to-tail string stability are theoretically proved. Furthermore, numerical simulations are conducted to verify the effectiveness of the proposed MPC controller. Simulation results show that the proposed controller outperforms the state-of-the-art consensus-based controller with 4.5 %-5.8 % fuel consumption reduction and 28.1 %-33.1 % average velocity error reduction. © 2025

关键词： Communication delays Cooperative control Human-driven vehicles Mixed autonomy Model predictive control Vehicle platoon

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