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arXiv 2025年

作者： Qin, Yuzhe Wang, Cheng Key Laboratory of Complex Systems and Data Science of Ministry of Education School of Mathematical Sciences Shanxi University Taiyuan030006 China Mathematics Department University of Massachusetts North DartmouthMA02747 United States

In this paper, we propose and analyze a second order accurate (in both time and space) numerical scheme for the Poisson-Nernst-Planck-Navier-Stokes system, which describes the ion electro-diffusion in fluids. In particular, the Poisson-Nernst-Planck equation is reformulated as a non-constant mobility gradient flow in the Energetic Variational Approach. The marker and cell finite difference method is chosen as the spatial discretization, which facilitates the analysis for the fluid part. In the temporal discretization, the mobility function is computed by a second order extrapolation formula for the sake of unique solvability analysis, while a modified Crank-Nicolson approximation is applied to the singular logarithmic nonlinear term. Nonlinear artificial regularization terms are added in the chemical potential part, so that the positivity-preserving property could be theoretically proved. Meanwhile, a second order accurate, semi-implicit approximation is applied to the convective term in the PNP evolutionary equation, and the fluid momentum equation is similarly computed. In addition, an optimal rate convergence analysis is provided, based on the higher order asymptotic expansion for the numerical solution, the rough and refined error estimate techniques. The following combined theoretical properties have been established for the second order accurate numerical method: (i) second order accuracy, (ii) unique solvability and positivity, (iii) total energy stability, and (iv) optimal rate convergence. A few numerical results are displayed to validate the theoretical analysis. © 2025, CC0.

关键词： Navier Stokes equations

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Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-Resolution 27

Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Xu, Tianyi Zhou, Yijie Hu, Xiaotao Zhang, Kai Zhang, Anran Qiu, Xingye Xu, Jun School of Statistics and Data Science Nankai University Tianjin China College of Computer Science Nankai University Tianjin China School of Intelligence Science and Technology Nanjing University Suzhou China Tencent Data Platform Beijing China Zhejiang University Hangzhou China Systems Engineering Research Institute China State Shipbuilding Corporation Limited Beijing China Guangdong Provincial Key Laboratory of Big Data Computing The Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781643685489

Arbitrary-scale super-resolution (ASSR) aims to learn a single model for image super-resolution at arbitrary magnifying scales. Existing ASSR networks typically comprise an off-the-shelf scale-agnostic feature extractor and an arbitrary scale upsampler. These feature extractors often use fixed network architectures to address different ASSR inference tasks, each of which is characterized by an input image and an upsampling scale. However, this overlooks the difficulty variance of super-resolution on different inference scenarios, where simple images or small SR scales could be resolved with less computational effort than difficult images or large SR scales. To tackle this difficulty variability, in this paper, we propose a Task-Aware Dynamic Transformer (TADT) as an input-adaptive feature extractor for efficient image ASSR. Our TADT consists of a multi-scale feature extraction backbone built upon groups of Multi-Scale Transformer Blocks (MSTBs) and a Task-Aware Routing Controller (TARC). The TARC predicts the inference paths within feature extraction backbone, specifically selecting MSTBs based on the input images and SR scales. The prediction of inference path is guided by a new loss function to trade-off the SR accuracy and efficiency. Experiments demonstrate that, when working with three popular arbitrary-scale upsamplers, our TADT achieves state-of-the-art ASSR performance when compared with mainstream feature extractors, but with relatively fewer computational costs. The code is available at https://***/Tillyhere/TADT. © 2024 The Authors.

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Integrated Inspection of QoM, QoP, and QoS for AOI Industries in Metaverses

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IEEE/CAA Journal of Automatica Sinica 2022年第12期9卷 2071-2078页

作者： Yutong Wang Yonglin Tian Jiangong Wang Yansong Cao Shixing Li Bin Tian IEEE The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China North Automatic Control Technology Institute in Taiyuan ShanxiChina Qingdao Academy of Intelligent Industries Shandong 266109China

With the rapid development of information technologies such as digital twin, extended reality, and blockchain,the hype around "metaverse" is increasing at astronomical speed. However, much attention has been paid to its entertainment and social functions. Considering the openness and interoperability of metaverses, the market of quality inspection promises explosive growth. In this paper, taking advantage of metaverses, we first propose the concept of Automated Quality Inspection(Auto QI), which performs integrated inspection covering the entire manufacturing process, including Quality of Materials, Quality of Manufacturing(Qo M), Quality of Products, Quality of Processes(Qo P), Quality of systems, and Quality of Services(Qo S). Based on the scenarios engineering theory, we discuss how to perform interactions between metaverses and the physical world for virtual design instruction and physical validation feedback. Then we introduce a bottomup inspection device development workflow with productivity tools offered by metaverses, making development more effective and efficient than ever. As the core of quality inspection,we propose Quality Transformers to complete detection task,while federated learning is integrated to regulate data *** summary, we point out the development directions of quality inspection under metaverse tide.

关键词： Automated Optical Inspection Metaverses Quality Inspection Transformers

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Sustainability Forecasting for Deep Learning Packages 31

Sustainability Forecasting for Deep Learning Packages

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31st IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2024

作者： Han, Junxiao Wang, Yunkun Liu, Zhongxin Bao, Lingfeng Liu, Jiakun Lo, David Deng, Shuiguang School of Computer & Computing Science Hangzhou City University Hangzhou China College of Computer Science and Technology Zhejiang University Hangzhou China Zhejiang University The State Key Laboratory of Blockchain and Data Security Hangzhou China School of Computing and Information Systems Singapore Management University Singapore Singapore

ISBN: (纸本)9798350330663

Deep Learning (DL) technologies have been widely adopted to tackle various tasks. In this process, through software dependencies, a multi-layer DL supply chain (SC) is formed, with DL frameworks acting as the root, DL packages acting as the bridge nodes, and downstream DL projects acting as the periphery. However, most Open Source Software (OSS) projects may fail. Considering the crucial position of DL packages in the DL SC, to foster the sustainable development of DL SCs and DL packages, we aim to forecast the long-term sustainability of DL packages. Here, sustained activity is adopted as the main proxy of sustainability, and the sustainability status is classified as 'sus-tainable' or 'dormant'. Relatedly, a DL package is considered as 'sustainable' if it has sustained activity in its last 12 months. Otherwise, it is deemed as 'dormant'. To this end, we propose an approach that begins with obtaining longitudinal features for each DL package in each month. Then, we develop a model to forecast the sustainability of DL packages by incorporating the longitudinal features, which can aptly predict sustainability with an accuracy of up to 0.81. Subsequently, an interpretable module is developed to interpret the determinants (i.e., important features) that impact the sustainability of DL packages. Finally, we generate sustainability trajectories for each DL package to better understand the monthly changes of their sustainability status. Our findings uncover that for most DL packages, fewer but more centralized developers and a balanced collaboration are more likely to help sustain the DL packages. Furthermore, although some DL packages are sustainable, their sustainability trajectories present statistically decreasing trends over time. Based on the findings, we shed light on the dynamic sustainability of DL packages, highlight future research directions, and provide practical suggestions to DL package maintainers, developers, users, and software engineering researchers. ©

关键词： Open source software

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Valuation and comparison of the actual and optimal control strategy in an emerging infectious disease:Implication from a COVID-19 transmission model

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Infectious Disease Modelling 2024年第2期9卷 354-372页

作者： Lili Liu Xi Wang Ou Liu Yazhi Li Zhen Jin Sanyi Tang Xia Wang Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention Complex Systems Research CenterShanxi UniversityTaiyuan030006China School of Mathematical Sciences Shanxi UniversityTaiyuan030006China School of Mathematics and Statistics Qiannan Normal University for NationalitiesGuizhouDuyun558000China School of Mathematics and Statistics Shaanxi Normal UniversityXi'an710119China

To effectively combat emerging infectious diseases like COVID-19,it is crucial to adopt strict prevention and control measures promptly to effectively contain the spread of the *** this paper,we propose a transmission model to investigate the influence of two control strategies:reducing contact numbers and improving medical *** examine these strategies in terms of constant control and time-varying *** sensitivity analysis on two reproduction numbers of the model with constant control,we demonstrate that reducing contact numbers is more effective than improving medical ***,these two constant controls significantly influence the peak values and timing of ***,intensifying control measures can reduce peak values,albeit at the expense of delaying the peak *** the model with time-varying control,we initially explore the corresponding optimal control problem and derive the characteristic expression of optimal ***,we utilize real data from January 10th to April 12th,2020,in Wuhan city as a case study to perform parameter estimation by using our proposed improved *** findings illustrate that implementing optimal control measures can effectively reduce infections and deaths,and shorten the duration of the ***,we numerically explore that implementing control measures promptly and increasing intensity to reduce contact numbers can make actual control be more closer to optimized ***,we utilize the real data from October 31st to November 18th,2021,in Hebei province as a second case study to validate the feasibility of our proposed suggestions.

关键词： Emerging epidemic Transmission model Sensitivity analysis Actual control Optimal control

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Parallel Driving with Big Models and Foundation Intelligence in Cyber-hysical-ocial Spaces

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Research 2024年第2期2024卷 1-17页

作者： Xiao Wang Jun Huang Yonglin Tian Chen Sun Lie Yang Shanhe Lou Chen Lv Changyin Sun Fei-Yue Wang School of Artificial Intelligence Anhui UniversityHefeiChina Macao University of Science and Technology MacaoChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina MVSLab Department of Mechanical and Mechatronics EngineeringUniversity of Waterloo200 University Ave WestWaterlooON N2L3G1Canada School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingaporeSingapore

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs);on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the ?S?goals of parallel driving.

关键词： breakthrough integrate corners

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Dynamic Locomotion of Quadruped Robot in Sloping Terrain 6

Dynamic Locomotion of Quadruped Robot in Sloping Terrain

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6th International Symposium on Autonomous systems, ISAS 2023

作者： Chen, Donglin Cong, Dehong Song, Xiangman Northeastern University National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang110819 China Northeastern University Ministry of Education Key Laboratory of Data Analytics and Optimization for Smart Industry Shenyang110819 China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Shenyang110819 China

ISBN: (纸本)9798350316155

In order to improve the locomotion capability of quadruped robot in the sloping terrain and enhance whose adaptability to the environment, this paper proposes a method to realize dynamic locomotion of quadruped robot in sloping terrain completely based on model predictive control (MPC) and proprioception. According to the foot contact signal and the robot body posture information measured by inertial measurement unit (IMU), quadruped robot actively changes whose body posture to adapt to different sloping terrains. This paper builds quadruped robot virtual prototype and test terrain in Webots simulation environment. The experimental results show that with this method, the roll angle fluctuation range of the quadruped robot is less than 0.05rad and the yaw angle fluctuation range is not more than 0.003rad. At the same time, when the angle of slope changes, the terrain adaptation time of the quadruped robot is less than 1.8s. The above results show that quadruped robot has excellent movement ability in sloping terrain and environmental adaptability under the condition of ensuring stability with the method proposed in this paper. © 2023 IEEE.

关键词： Model predictive control

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Steel Defect Detection Algorithm Based on Multiobjective ENAS Sharing Strategy 24

Steel Defect Detection Algorithm Based on Multiobjective ENA...

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

作者： Zhao, Tianchen Dong, Zhiming Wang, Xianpeng National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang China Ministry of Education Shenyang China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang China Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Northeastern University Shenyang China

ISBN: (纸本)9798400710681

When employing the network architecture search approach for designing a steel surface defect detector, there are issues with conflicting evaluation metrics and limited computational resources. To address this challenge, we propose a multiobjective evolutionary sharing strategy-based network architecture search method (MESNAS). MESNAS defines network architecture search as a bi-level multiobjective optimization problem combined with a weight sharing acceleration strategy designed to quickly and simultaneously optimize the accuracy and complexity of classification models. A refined search space suitable for different image classification and detection tasks is designed. Using the MOEA/D algorithm, which incorporates a variable-length encoding scheme, the search space is co-utilized and explored through targeted improvements to the crossover and mutation operators in the offspring generation process. The optimal network architecture obtained from the search is tested on the concrete surface defect classification task, and the steel continuous casting slab surface defect detection task. The experimental results show that the proposed algorithm has good model performance and portability in image classification as well as defect detection tasks with different data complexities and different categories. © 2024 Copyright held by the owner/author(s).

关键词： Continuous casting

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Learning impedance control of robots with enhanced transient and steady-state control performances

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science China(Information sciences) 2020年第9期63卷 204-216页

作者： Tairen SUN Long CHENG Liang PENG Zengguang HOU Yongping PAN State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Data and Computer Science Sun Yat-sen University

This study proposes a learning impedance controller comprising a proportional feedback control term, a composite-learning-based uncertainty estimation term, and a robot-environment interaction control term. The impedance control problem is converted into a particular reference-trajectory tracking problem based on a generated reference trajectory. The proposed controller ensures the exponential convergence of the auxiliary tracking error and the uncertainty estimation error. The interaction control term improves the transient control performance through suppression/encouragement of the incorrect/correct robot *** composite-learning update law enhances the transient and steady-state control performances based on the exponential convergence of the uncertainty estimation error and auxiliary tracking error. Finally, the effectiveness and advantages of the proposed impedance controller are validated by theoretical analysis and simulations on a parallel robot.

关键词： robot adaptive control neural network impedance control parameter convergence

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Integrating multi-omics data of childhood asthma using a deep association model

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Fundamental Research 2024年第4期4卷 738-751页

作者： Kai Wei Fang Qian Yixue Lia Tao Zeng Tao Huang Bio-Med Big Data Center CAS Key Laboratory of Computational BiologyShanghai Institute of Nutrition and HealthUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200031China Guoke Ningbo Life Science and Health Industry Research Institute Ningbo 315000China Guangzhou National Laboratory Guangzhou 510000China GMU-GIBH Joint School of Life Sciences The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and DiseasesGuangzhou LaboratoryGuangzhou Medical UniversityGuangzhou 510000China Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China

Childhood asthma is one of the most common respiratory diseases with rising mortality and *** multi-omics data is providing a new chance to explore collaborative biomarkers and corresponding diagnostic models of childhood *** capture the nonlinear association of multi-omics data and improve interpretability of diagnostic model,we proposed a novel deep association model(DAM)and corresponding efficient analysis ***,the Deep Subspace Reconstruction was used to fuse the omics data and diagnostic information,thereby correcting the distribution of the original omics data and reducing the influence of unnecessary data ***,the Joint Deep Semi-Negative Matrix Factorization was applied to identify different latent sample patterns and extract biomarkers from different omics data ***,our newly proposed Deep Orthogonal Canonical Correlation Analysis can rank features in the collaborative module,which are able to construct the diagnostic model considering nonlinear correlation between different omics data *** DAM,we deeply analyzed the transcriptome and methylation data of childhood *** effectiveness of DAM is verified from the perspectives of algorithm performance and biological significance on the independent test dataset,by ablation experiment and comparison with many baseline methods from clinical and biological *** DAM-induced diagnostic model can achieve a prediction AUC of o.912,which is higher than that of many other alternative ***,relevant pathways and biomarkers of childhood asthma are also recognized to be collectively altered on the gene expression and methylation *** an interpretable machine learning approach,DAM simultaneously considers the non-linear associations among samples and those among biological features,which should help explore interpretative biomarker candidates and efficient diagnostic models from multi-omics data analysis for human complexdiseases.

关键词： Deepsub space reconstruction Deepnon-negative matrix factorization Deepcanonical correlationanalysis Multi-omics Interpretable machine learning Childhood asthma

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