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33rd ACM Web Conference, WWW 2024

作者： Liu, Yonghao Huang, Lan Cao, Bowen Li, Ximing Giunchiglia, Fausto Feng, Xiaoyue Guan, Renchu College of Computer Science and Technology Jilin University Changchun China Department of Information Engineering and Computer Science University of Trento Trento Italy Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education China

ISBN: (纸本)9798400701719

Graphs, as a fundamental data structure, have proven efficacy in modeling complex relationships between objects and are therefore found in wide web applications. Graph classification is an essential task in graph data analysis, which can effectively assist in extracting information and mining content from the web. Recently, few-shot graph classification, a more realistic and challenging task, has garnered great research interest. Existing few-shot graph classification models are all supervised, assuming abundant labeled data in base classes for meta-training. However, sufficient annotation is often challenging to obtain in practice due to high costs or demand for expertise. Moreover, they commonly adopt complicated meta-learning algorithms via episodic training to transfer prior knowledge from base classes. To break free from these constraints, in this paper, we propose a simple yet effective approach named SMART for unsupervised few-shot graph classification without using any labeled data. SMART employs transfer learning philosophy instead of the previously prevailing meta-learning paradigm, avoiding the need for sophisticated meta-learning algorithms. Additionally, we adopt a novel mixup strategy to augment the original graph data and leverage unsupervised pretraining on these data to obtain the expressive graph encoder. We also utilize the prompt tuning technique to alleviate the overfitting and low fine-tuning efficiency caused by the limited support samples of novel classes. Extensive experimental results demonstrate the superiority of our proposed approach, significantly surpassing even leading supervised few-shot graph classification models. Our code is available here. © 2024 ACM.

关键词： Graph neural networks

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A critical review of sulfate aerosol formation mechanisms during winter polluted periods

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Journal of Environmental sciences 2023年第1期123卷 387-399页

作者： Can Ye Keding Lu Huan Song Yujing Mu Jianmin Chen Yuanhang Zhang State Key Joint Laboratory of Environmental Simulation and Pollution Control College of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention Department of Environmental Science and EngineeringInstitute of Atmospheric SciencesFudan UniversityShanghai 200438China

Sulfate aerosol contributes to particulate matter pollution and plays a key role in aerosol radiative forcing,impacting human health and climate *** models tend to substantially underestimate sulfate concentrations during haze episodes,indicating that there are still missing mechanisms not considered by the *** recent good progress in understanding the missing sulfate sources,knowledge on different sulfate formation pathways during polluted periods still involves large uncertainties and the dominant mechanism is under heated debate,calling for more field,laboratory,and modeling ***,we review the traditional sulfate formation mechanisms in cloud water and also discuss the potential factors affecting multiphase S(Ⅳ)*** recent progress in multiphase S(Ⅳ)oxidation mechanisms is *** formation rates by different prevailing oxidation pathways under typical winter-haze conditions are also calculated and *** on the literature reviewed,we put forward control of the atmospheric oxidation capacity as a means to abate sulfate aerosol ***,we conclude with a concise set of research priorities for improving our understanding of sulfate formation mechanisms during polluted periods.

关键词： Sulfate aerosol Formation mechanisms Multiphase oxidation Transition metal ions Reactive oxygen species

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Unconditional error estimate of a linearized variable-time-step BDF2 nonconforming virtual element method for nonlinear coupled predator–prey equations

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Mathematics and Computers in simulation 2026年 239卷 505-524页

作者： Shanshan Peng Yanping Chen School of Mathematics and Computational Science Xiangtan University Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan 411105 China School of Science Nanjing University of Posts and Telecommunications Nanjing 210023 China

In this paper, we introduce the Nonconforming Virtual Element Method (NVEM) to solve nonlinear coupled prey–predator equations on general polygonal meshes, employing a linearized variable two-step backward differentiation formula (BDF2) for time discretization. The analysis of boundedness and error estimates for the time discrete system is conducted using discrete orthogonal convolution kernels and discrete complementary convolution kernels. Then, the time–space error splitting technique and the projection operator are integrated to establish the L ∞ -norm boundedness of the fully discrete solution, independent of any grid ratio conditions, thereby naturally deriving the unconditionally optimal error estimate. The analytical method presented herein is not restricted to the NVEM and can be readily extended to other numerical techniques. Finally, the theoretical results are validated through numerical examples, demonstrating the scheme’s effectiveness across various grid configurations.

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A preconditioned iteration method for solving saddle point problems

arXiv

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arXiv 2024年

作者： Zhang, Juan Luo, Yiyi Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University China

This paper introduces a preconditioned method designed to comprehensively address the saddle point system with the aim of improving convergence efficiency. In the preprocessor construction phase, a technical approach for solving the approximate inverse matrix of sparse matrices is presented. The effectiveness of the proposed method is demonstrated through numerical examples, emphasizing its efficacy in approximating the inverse matrix. Furthermore, the preprocessing technology includes a low-rank processing step, effectively reducing algorithmic complexity. Numerical experiments validate the effectiveness and feasibility of PSLR-GMRES in solving the saddle point system. © 2024, CC BY.

关键词： Iterative methods

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Preprocessed GMRES for fast solution of linear equations

arXiv

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arXiv 2024年

The article mainly introduces preprocessing algorithms for solving linear equation systems. This algorithm uses three algorithms as inner iterations, namely RPCG algorithm, ADI algorithm, and Kaczmarz algorithm. Then, it uses BA-GMRES as an outer iteration to solve the linear equation system. These three algorithms can indirectly generate preprocessing matrices, which are used for solving equation systems. In addition, we provide corresponding convergence analysis and numerical examples. Through numerical examples, we demonstrate the effectiveness and feasibility of these preprocessing methods. Furthermore, in the Kaczmarz algorithm, we introduce both constant step size and adaptive step size, and extend the parameter range of the Kaczmarz algorithm to α ∈ (0, ∞). We also study the solution rate of linear equation systems using different step sizes. Numerical examples show that both constant step size and adaptive step size have higher solution efficiency than the solving algorithm without preprocessing. © 2024, CC BY.

关键词： Linear equations

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Harmfully Manipulated Images Matter in Multimodal Misinformation Detection 24

Harmfully Manipulated Images Matter in Multimodal Misinforma...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Wang, Bing Wang, Shengsheng Li, Changchun Guan, Renchu Li, Ximing College of Computer Science and Technology Jilin University Jilin Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Jilin University China

ISBN: (纸本)9798400706868

Nowadays, misinformation is widely spreading over various social media platforms and causes extremely negative impacts on society. To combat this issue, automatically identifying misinformation, especially those containing multimodal content, has attracted growing attention from the academic and industrial communities, and induced an active research topic named Multimodal Misinformation Detection (MMD). Typically, existing MMD methods capture the semantic correlation and inconsistency between multiple modalities, but neglect some potential clues in multimodal content. Recent studies suggest that manipulated traces of the images in articles are non-trivial clues for detecting misinformation. Meanwhile, we find that the underlying intentions behind the manipulation, e.g., harmful and harmless, also matter in MMD. Accordingly, in this work, we propose to detect misinformation by learning manipulation features that indicate whether the image has been manipulated, as well as intention features regarding the harmful and harmless intentions of the manipulation. Unfortunately, the manipulation and intention labels that make these features discriminative are unknown. To overcome the problem, we propose two weakly supervised signals as alternatives by introducing additional datasets on image manipulation detection and formulating two classification tasks as positive and unlabeled learning problems. Based on these ideas, we propose a novel MMD method, namely Harmfully Manipulated Images Matter in MMD (Hami-m3d). Extensive experiments across three benchmark datasets can demonstrate that Hami-m3d can consistently improve the performance of any MMD baselines. © 2024 ACM.

关键词： image manipulation

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Comments and extensions on "State-equivalent form and minimum-order compensator design for rectangular descriptor systems"

arXiv

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arXiv 2025年

作者： Shi, Shuo Zhang, Juan Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing Ministry of Education School of Mathematics and Computational Science Xiangtan University Xiangtan411105 China

This technical note presents a counterexample showing that the equivalence conditions proposed by Geng et al. (IEEE Trans. Automat. Control, 2024), which use a minimum-order compensator (MOC) to achieve desired designs, including generalized regularity or both generalized regularity and free of impulse, are sufficient but not necessary. Furthermore, revised equivalence conditions are introduced, along with an equivalence condition ensuring the closed-loop system remains generalized regular, impulse-free, and stable using MOC. Additionally, it is shown that output feedback can replace the MOC, achieving the same design without increasing dimensionality. These findings are validated through a circuit *** Codes 93B05, 93B52, 15A03 Copyright © 2025, The Authors. All rights reserved.

关键词： Feedback

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Enhanced breakdown strength and energy storage density of AgNbO_(3)ceramics via tape casting

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Rare Metals 2023年第2期42卷 495-502页

作者： Ming-Yuan Zhao Jing Wang Lin Chen Hao Yuan Mao-Hua Zhang Su-Wei Zhang Lei Zhao Key Laboratory of High-Precision Computation and Application of Quantum Field Theory of Hebei Province College of Physics Science and TechnologyHebei UniversityBaoding071002China State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace EngineeringNanjing University of Aeronautics and AstronauticsNanjing210016China Department of Materials and Earth Sciences Nonmetallic Inorganic MaterialsTechnical University of DarmstadtDarmstadt64287Germany State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijing100084China

Antiferroelectric materials are promising candidates for energy-storage applications due to their double hysteresis loops,which can deliver high power *** the antiferroelectric materials,AgNbO_(3)is proved attractive due to its environmental-friendliness and high potential for achieving excellent energy storage ***,the recoverable energy storage density of AgNbO_(3)ceramics is limited by their relatively low breakdown ***,the breakdown strength of the pure AgNbO_(3)ceramics prepared using the tape casting method is enhanced to 307 kV·cm^(-1),which is,to the best of our knowledge,among the highest values reported for pure AgNbO-3bulk *** high breakdown strength may be due to its dense microstructure and good crystallinity obtained by the tape casting method and the optimized sintering *** to its enhanced breakdown strength,AgNbO_(3)ceramics show high recoverable energy storage density of 2.8 J·cm^(-3).These results have led to the development of lead-free antiferroelectric materials and devices with high energy storage density.

关键词： AgNbO_(3) Energy storage performance Antiferroelectric Tape casting

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Strengthened Initialization of Adaptive Cross-Generation Differential Evolution

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Computer Modeling in engineering & sciences 2022年第3期130卷 1495-1516页

作者： Wei Wan Gaige Wang Junyu Dong Department of Computer Science of Technology Ocean University of ChinaQingdao266100China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun130012China Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis Guangxi University for NationalitiesNanning530006China

Adaptive Cross-Generation Differential Evolution(ACGDE)is a recently-introduced algorithm for solving multiobjective problems with remarkable performance compared to other evolutionary algorithms(EAs).However,its convergence and diversity are not satisfactory compared with the latest *** order to adapt to the current environment,ACGDE requires improvements in many aspects,such as its initialization and mutant *** this paper,an enhanced version is proposed,namely *** incorporates a strengthened initialization strategy and optimized parameters in contrast to its *** improvements make the direction of crossgeneration mutation more clearly and the ability of searching more *** experiments show that the new algorithm has better diversity and improves convergence to a certain *** the same time,SIACGDE outperforms other state-of-the-art algorithms on four metrics of 24 test problems.

关键词： Differential Evolution(DE) multi-objective optimization(MO) opposition-based learning parameter adaptation

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A novel hybrid butterfly optimization algorithm for feature selection with sine cosine velocity in the high-dimensional classification data

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Journal of Intelligent and Fuzzy Systems 2024年第5-6期47卷 369-391页

作者： Zhang, Li Chen, Xiaobo Key Laboratory of Data Science and Intelligence Education Hainan Normal University Ministry of Education Haikou Hainan China School of Computer Engineering Jiangsu University of Technology Changzhou Jiangsu China Changzhou City Center Branch People's Bank of China Changzhou Jiangsu China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

Aiming at the shortcomings of the traditional butterfly optimization algorithm in solving the high-dimensional classification feature selection problem, which has low convergence and is prone to fall into local optimal solutions, a new hybrid butterfly optimization algorithm is proposed, i.e., HBOA-SCV (A novel hybrid butterfly optimization algorithm with sine cosine velocity). The algorithm is applied to solve a high-dimensional classification feature selection problem. Firstly, the algorithm's global exploration and local exploitation ability can be dynamically balanced by introducing inertia weight coefficients w based on multiple learning strategies. Secondly, using the updated speed position formula of the sine-cosine acceleration strategy, individual butterflies' autonomous search ability and convergence speed can be further improved. Finally, according to the fitness value of each butterfly individual, the moving step length and direction of the butterfly individual are automatically adjusted better to fit the actual search process of the butterfly individual, increase the search ability in the global range, and avoid the algorithm from falling into the local optimum. To verify the algorithm's effectiveness, 18 high-dimensional classification numbers are selected to carry out simulation and comparison experiments between HBOA-SCV and traditional BOA algorithm, five improved BOA algorithms and other comparative algorithms for high-dimensional classification data successively. The experimental results show that the average fitness value and classification accuracy of the HBOA-SCV algorithm are better than the comparison algorithm, thus verifying the superiority of the HBOA-SCV algorithm. © 2024 - IOS Press. All rights reserved.

关键词： Optimization algorithms

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