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ETFIDS: An Entropy-Driven, Time-Frequency Analysis Framework for In-Vehicle CAN Signal Intrusion Detection

IEEE Internet of Things Journal 2025年第12期12卷 21507-21522页

作者： Liu, Wanning Qin, Guihe Liang, Yanhua Song, Jiaru Liu, Qingxin Zhou, Xue Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Changchun130012 China

In recent years, cyberattacks against automobiles have exposed significant security threats to in-vehicle networks. The vulnerability of communication signals to malicious interference and manipulation can lead to serious system failures or abnormal behavior. The existing in-vehicle network intrusion detection methods do not fully exploit the time-frequency characteristics of Controller Area Network (CAN) signals. This limitation reduces their effectiveness in capturing subtle changes and signal complexity. Based on the above motivation, from the perspective of signal perception, we propose an entropy-driven, time-frequency analysis framework for in-vehicle network intrusion detection. The framework integrates a signal sampler, a frequency-domain detector, and a time-domain detector. The signal sampler, as the system's front-end module, extracts real-time physical signal data streams from CAN messages. The frequency-domain detector identifies frequency components, detecting high-frequency disturbances and cyclic variations. Meanwhile, the time-domain detector captures instantaneous changes and sudden anomalies. It analyzes signal complexity and anomalies through both stream and block detection. Experimental results demonstrate that the proposed method performs well under various attack scenarios, offering superior detection and real-time performance. It effectively senses multiple signal anomalies, providing a robust intrusion detection solution for modern in-vehicle networks. © 2025 IEEE.

关键词： Network intrusion

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Lagrangian eddies in the Northwestern Pacifi c Ocean

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Journal of Oceanology and Limnology 2022年第1期40卷 66-77页

作者： Qiu HE Fenglin TIAN Xiaokun YANG Ge CHEN Department of Marine Technology College of Information Science and EngineeringOcean University of ChinaQingdao 266100China Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and Technology(Qingdao)Qingdao 266237China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034China

The Lagrangian eddies in the western Pacifi c Ocean are identifi ed and analysed based on Maps of Sea Level Anomaly(MSLA)data from 1998 to *** calculating the Lagrangian eddy advected by the AVISO velocity fi eld,we analyzed the variations in Lagrangian eddies and the average transport eff ects on diff erent time *** introducing the Niño coeffi cient,the lag response of the Lagrangian eddy to El Niño is *** data are helpful to further explore the role of mesoscale eddies in ocean energy *** normalized chlorophyll data,we observed chlorophyll aggregation and hole eff ects caused by Lagrangian *** fi ndings demonstrate the important role of Lagrangian eddies in material *** transportation volume of the Lagrangian eddy is calculated quantitatively,and several major transport routes have been identifi ed,which helps us to more accurately and objectively estimate the transport capacity of Lagrangian eddies in the western Pacifi c Ocean.

关键词： Lagrangian coherent structure(LCS) mesoscale eddy distribution character material transport

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Positive and Unlabeled Learning with Controlled Probability Boundary Fence 41

Positive and Unlabeled Learning with Controlled Probability ...

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41st International Conference on Machine Learning, ICML 2024

作者： Li, Changchun Dai, Yuanchao Feng, Lei Li, Ximing Wang, Bing Ouyang, Jihong College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore

Positive and Unlabeled (PU) learning refers to a special case of binary classification, and technically, it aims to induce a binary classifier from a few labeled positive training instances and loads of unlabeled instances. In this paper, we derive a theorem indicating that the probability boundary of the asymmetric disambiguation-free expected risk of PU learning is controlled by its asymmetric penalty, and we further empirically evaluated this theorem. Inspired by the theorem and its empirical evaluations, we propose an easy-to-implement two-stage PU learning method, namely Positive and Unlabeled Learning with Controlled Probability Boundary Fence (PUL-CPBF). In the first stage, we train a set of weak binary classifiers concerning different probability boundaries by minimizing the asymmetric disambiguation-free empirical risks with specific asymmetric penalty values. We can interpret these induced weak binary classifiers as a probability boundary fence. For each unlabeled instance, we can use the predictions to locate its class posterior probability and generate a stochastic label. In the second stage, we train a strong binary classifier over labeled positive training instances and all unlabeled instances with stochastic labels in a self-training manner. Extensive empirical results demonstrate that PUL-CPBF can achieve competitive performance compared with the existing PU learning baselines. Copyright 2024 by the author(s)

关键词： Contrastive Learning

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Learning Stable Task-Level Manifold for Few-Shot Learning

Learning Stable Task-Level Manifold for Few-Shot Learning

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2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023

作者： Yu, Siyi Luo, Wei Li, Gang Yang, Bo Jilin University College of Computer Science and Technology China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China Deakin University School of Information Technology Geelong Australia

ISBN: (纸本)9798350382204

Few-shot learning (FSL) aims to learn to new concepts based on very limited data. One of the main challenges in FSL is the use of pretrained embeddings whose dimension is too high for the small sample size. While the large dimensionality helps capture diverse features in the training example, not all the features are relevant to the task at hand. Such task-irrelevant features from pre-trained embeddings can negatively impact the performance of the FSL model. To address this challenge, we propose a simple yet effective way to learn task-level manifolds that explicitly eliminate the negative effect of nuisance features. One key novelty of our approach is to address class imbalance in the training data by injecting supervised information through key virtual samples, which we named Manifold Support Points. Empirically, we demonstrate that the stability of the learnt task-level manifolds and their effectiveness in challenging tasks in FSL. Our approach shows competitive performance on several benchmark datasets, including tieredImageNet and CUB. © 2023 IEEE.

关键词： Embeddings

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Analysis of a two-grid method for semiconductor device problem

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Applied Mathematics and Mechanics(English Edition) 2021年第1期42卷 143-158页

作者： Ying LIU Yanping CHEN Yunqing HUANG Qingfeng LI School of Mathematics and Computational Science Hunan Key Laboratory for Computation and Simulation in Science and EngineeringXiangtan UniversityXiangtan 411105Hunan ProvinceChina College of Information and Intelligence Hunan Agricultural UniversityChangsha 410128China School of Mathematical Sciences South China Normal UniversityGuangzhou 510631China

The mathematical model of a semiconductor device is governed by a system of quasi-linear partial differential *** electric potential equation is approximated by a mixed finite element method,and the concentration equations are approximated by a standard Galerkin *** estimate the error of the numerical solutions in the sense of the *** linearize the full discrete scheme of the problem,we present an efficient two-grid method based on the idea of Newton *** main procedures are to solve the small scaled nonlinear equations on the coarse grid and then deal with the linear equations on the fine *** estimation for the two-grid solutions is analyzed in *** is shown that this method still achieves asymptotically optimal approximations as long as a mesh size satisfies H=O(h^1/2).Numerical experiments are given to illustrate the efficiency of the two-grid method.

关键词： two-grid method semiconductor device mixed finite element method Galerkin method L^q error estimate

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The Schur complements for SDD1 matrices and their application to linear complementarity problems

arXiv

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arXiv 2025年

作者： Hu, Yang Liu, Jianzhou Zeng, Wenlong School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan China Department of Mathematics Shanghai University Shanghai200444 China

In this paper we propose a new scaling method to study the Schur complements of SDD1 matrices. Its core is related to the non-negative property of the inverse M-matrix, while numerically improving the Quotient formula. Based on the Schur complement and a novel norm splitting manner, we establish an upper bound for the infinity norm of the inverse of SDD1 matrices, which depends solely on the original matrix entries. We apply the new bound to derive an error bound for linear complementarity problems of B1-matrices. Additionally, new lower and upper bounds for the determinant of SDD1 matrices are presented. Numerical experiments validate the effectiveness and superiority of our results. © 2025, CC BY.

关键词： Matrix algebra

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A novel graph oversampling framework for node classification in class-imbalanced graphs

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science China(Information sciences) 2024年第6期67卷 214-229页

作者： Riting XIA Chunxu ZHANG Yan ZHANG Xueyan LIU Bo YANG Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University College of Artificial Intelligence Jilin University College of Computer Science and Technology Jilin University College of Communication Engineering Jilin University

Graph neural network(GNN) is a promising method to analyze graphs. Most existing GNNs adopt the class-balanced assumption, which cannot deal with class-imbalanced graphs well. The oversampling technique is effective in alleviating class-imbalanced problems. However, most graph oversampling methods generate synthetic minority nodes and their edges after applying GNNs. They ignore the problem that the representations of the original and synthetic minority nodes are dominated by majority nodes caused by aggregating neighbor information through GNN before oversampling. In this paper, we propose a novel graph oversampling framework, termed distribution alignment-based oversampling for node classification in classimbalanced graphs(named Graph-DAO). Our framework generates synthetic minority nodes before GNN to avoid the dominance of majority nodes caused by message passing in GNNs. Additionally, we introduce a distribution alignment method based on the sum-product network to learn more information about minority nodes. To our best knowledge, it is the first to use the sum-product network to solve the class-imbalanced problem in node classification. A large number of experiments on four real datasets show that our method achieves the optimal results on the node classification task for class-imbalanced graphs.

关键词： graph neural network class-imbalanced graphs sum-product network oversampling node classification

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High-Efficiency and Low-Energy-Loss Organic Solar Cells Enabled by Tuning Conformations of Dimeric Electron Acceptors

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CCS Chemistry 2023年第11期5卷 2576-2588页

作者： Xiaobin Gu Yanan Wei Na Yu Jiawei Qiao Ziyang Han Qijie Lin Xiao Han Jinhua Gao Congqi Li Jianqi Zhang Xiaotao Hao Zhixiang Wei Zheng Tang Yunhao Cai Xin Zhang Hui Huang College of Materials Science and Opto-Electronic Technology Center of Materials Science and Optoelectronics EngineeringCAS Center for Excellence in Topological Quantum ComputationCAS Key Laboratory of Vacuum PhysicsUniversity of Chinese Academy of SciencesBeijing 100049 Center for Advanced Low-Dimension Materials State Key Laboratory for Modification of Chemical Fibers and Polymer MaterialsCollege of Materials Science and EngineeringDonghua UniversityShanghai 201620 School of Physics State Key Laboratory of Crystal MaterialsShandong UniversityJinan 250100 Center for Excellence in Nanoscience(CAS) Key Laboratory of Nanosystem and Hierarchical Fabrication(CAS)National Center for Nanoscience and TechnologyBeijing 100190

Dimeric fused-ring electron acceptors(DFREAs)have attracted much attention due to the combined advantages of their monomeric and polymeric acceptors,including a well-defined molecular structure,excellent repeatability,and stable ***,the additionally introduced single-bonds during dimerization may result in a twisted backbone of DFREAs,which is detrimental to intermolecular packing and charge ***,three DFREAs are designed and synthesized,in which DFREA conformations were systematically tuned via adjusting the intensities of intramolecular noncovalent interactions(INIs)to achieve high-performance organic solar cells(OSCs).Theoretical and experimental results show that the gradual introduction of S…F INIs can continuously improve molecular planarity and rigidity,resulting in reduced reorganization energies,ordered packing mode,and enhanced crystallization of *** from the incorporation of fourfold S…F INIs,DYF-TF-based binary OSCs show a record high efficiency of 18.26%with an extremely low energy loss(0.493 eV)for DFREAbased *** addition,DYF-TF-based OSCs exhibited good long-term stability with a T_(80%)lifetime of 2681 h,and the power conversion efficiency of the DYF-TF-based ternary device is further enhanced to 18.73%.This contribution demonstrates the great potential of the INIs strategy in achieving excellent DFREAs materials.

关键词： organic solar cells dimeric fused-ring electron acceptors intramolecular noncovalent interactions molecular planarity and rigidity reorganization energies

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On the stability and exponential decay of the 3D MHD system with mixed partial dissipation near a equilibrium state

arXiv

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arXiv 2024年

作者： Deng, Xuemin Xiao, Yuelong Zang, Aibin Hunan Key Laboratory for Computation and Simulation in Science and Engineering School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411100 China The Center of Applied Mathematics Yichun University Jiangxi Yichun336000 China

A main result of this paper establishes the global stability of the 3D MHD equations with mixed partial dissipation near a background magnetic field in the domain Ω = T2 × R with T2 = [0, 1]2. More precisely, each velocity equation lacks its own directional dissipation, and the magnetic equation lacks vertical dissipation in the MHD system. The key point to obtain the stability result is that we decompose the solution (u, b) into the zeroth horizontal mode and the non-zeroth modes and complete the desired bound with the strong Poincaré type inequalities in the treatment of several nonlinear terms. Then we focus on the large-time behavior of the solution, where the non-zeroth modes decay exponentially in H2, and the solution converges to its zeroth horizontal mode. Copyright © 2024, The Authors. All rights reserved.

关键词： Magnetohydrodynamics

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Measuring Zak phase in room-temperature atoms

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Light(science & Applications) 2022年第10期11卷 2530-2539页

作者： Ruosong Mao Xingqi Xu Jiefei Wang Chenran Xu Gewei Qian Han Cai Shi-Yao Zhu Da-Wei Wang Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentationand Zhejiang Province Key Laboratory of Quantum Technology and DeviceSchool of PhysicsZhejiang UniversityHangzhou 310027China College of Optical Science and Engineering Zhejiang UniversityHangzhou 310027China Hefei National Laboratory Hefei 230088China CAS Center of Excellence in Topological Quantum Computation 100190 BeijingChina

Cold atoms provide a flexible platform for synthesizing and characterizing topological matter,where geometric phases play a central ***,cold atoms are intrinsically prone to thermal noise,which can overwhelm the topological response and hamper promised *** the other hand,geometric phases also determine the energy spectra of particles subjected to a static force,based on the polarization relation between Wannier-Stark ladders and geometric Zak *** exploiting this relation,we develop a method to extract geometric phases from energy spectra of room-temperature superradiance lattices,which are momentum-space lattices of timed Dicke *** such momentum-space lattices the thermal motion of atoms,instead of being a source of noise,provides effective forces which lead to spectroscopic signatures of the Zak *** measure Zak phases directly from the anti-crossings between Wannier-Stark ladders in the Doppler-broadened absorption spectra of superradiance *** approach paves the way of measuring topological invariants and developing their applications in room-temperature atoms.

关键词： topological momentum invariants

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