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arXiv 2025年

作者： Cheng, Sibo Bocquet, Marc Ding, Weiping Finn, Tobias Sebastian Fu, Rui Fu, Jinlong Guo, Yike Johnson, Eleda Li, Siyi Liu, Che Moro, Eric Newton Pan, Jie Piggott, Matthew Quilodran, Cesar Sharma, Prakhar Wang, Kun Xiao, Dunhui Xue, Xiao Zeng, Yong Zhang, Mingrui Zhou, Hao Zhu, Kewei Arcucci, Rossella CEREA ENPC EDF R&D Institut Polytechnique de Paris Île-de-France France School of Artificial Intelligence and Computer Science Nantong University Jiangsu Nantong226019 China School of Mathematical Sciences Key Laboratory of Intelligent Computing and Applications Tongji University Shanghai200092 China School of Engineering and Materials Science Faculty of Science and Engineering Queen Mary University of London LondonE1 4NS United Kingdom Zienkiewicz Centre for Modelling Data and AI Faculty of Science and Engineering Swansea University SwanseaSA1 8EN United Kingdom Department of Computer Science and Engineering Hong Kong university of science and technology Hong Kong Department of Earth Science & Engineering Imperial College London LondonSW7 2AZ United Kingdom Tianjin Key Laboratory of Imaging and Sensing Microelectronics Technology School of Microelectronics Tianjin University Tianjin300072 China Centre for Health Informatics Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Department of Community Health Sciences Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Undaunted Grantham Institute for Climate Change and the Environment Imperial College London LondonSW7 2AZ United Kingdom Culham Campus AbingdonOX14 3DB United Kingdom Centre for Computational Science Department of Chemistry University College London LondonWC1E 6BT United Kingdom Concordia Institute for Information Systems Engineering Concordia University MontrealQCH3G 1M8 Canada School of Mechanical Medical and Process Engineering Faculty of Engineering Queensland University of Technology BrisbaneQLD Australia Department of Chemical Engineering University College London LondonWC1E 6BT United Kingdom

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques. This paper provides a comprehensive review of advanced ML methodologies designed to handle unstructured grid data in high-dimensional dynamical systems. Key approaches discussed include graph neural networks, transformer models with spatial attention mechanisms, interpolation-integrated ML methods, and meshless techniques such as physics-informed neural networks. These methodologies have proven effective across diverse fields, including fluid dynamics and environmental simulations. This review is intended as a guidebook for computational scientists seeking to apply ML approaches to unstructured grid data in their domains, as well as for ML researchers looking to address challenges in computational physics. It places special focus on how ML methods can overcome the inherent limitations of traditional numerical techniques and, conversely, how insights from computational physics can inform ML development. To support benchmarking, this review also provides a summary of open-access datasets of unstructured grid data in computational physics. Finally, emerging directions such as generative models with unstructured data, reinforcement learning for mesh generation, and hybrid physics-data-driven paradigms are discussed to inspire future advancements in this evolving field. © 2025, CC BY-NC-SA.

关键词： Mesh generation

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Enhancing Scientific Knowledge Graph Generation Pipelines with LLMs and Human-in-the-Loop 4

Enhancing Scientific Knowledge Graph Generation Pipelines wi...

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4th International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment, Sci-K 2024

作者： Tsaneva, Stefani Dessì, Danilo Osborne, Francesco Sabou, Marta Institute of Data Process and Knowledge Management Vienna University of Economics and Business Austria Computer Science Department College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Knowledge Media Institute The Open University United Kingdom Department of Business and Law University of Milano Bicocca Italy

Scientific Knowledge Graphs have recently become a powerful tool for exploring the research landscape and assisting scientific inquiry. It is crucial to generate and validate these resources to ensure they offer a comprehensive and accurate representation of specific research fields. However, manual approaches are not scalable, while automated methods often result in lower-quality resources. In this paper, we investigate novel validation techniques to improve the accuracy of automated KG generation methodologies, leveraging both a human-in-the-loop (HiL) and a large language model (LLM)-in-the-loop. Using the automated generation pipeline of the Computer science Knowledge Graph as a case study, we demonstrate that precision can be increased by 12% (from 75% to 87%) using only LLMs. Moreover, a hybrid approach incorporating both LLMs and HiL significantly enhances both precision and recall, resulting in a 4% increase in the F1 score (from 77% to 81%). © 2022 Copyright for this paper by its authors.

关键词： Knowledge graph

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Effective Timing for Reserving Fog Computational Resources for Time-Sensitive Vehicular Applications

Effective Timing for Reserving Fog Computational Resources f...

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International Conference on Fog and Mobile Edge Computing (FMEC)

作者： Ahmed Chebaane Abdelmajid Khelil Makki Ben Salem Bchira Ben Mabrouk CS Department Institute for Data and Process Science Landshut University of Applied Sciences Germany Higher Institute of Applied Science and Technology of Mateur University of Carthage Tunisia

ISBN: (数字)9798350366488

ISBN: (纸本)9798350366495

Fog computing has garnered significant attention, particularly for time-critical applications. Numerous techniques have been proposed to minimize offloading latency and optimize resource utilization. Unfortunately, these techniques are insufficient for safety-critical applications, which require deterministic/guaranteed access to Fog computational resources for clients at any time. Fog resources are perse limited, making the reservation of computation resources mandatory for time-sensitive applications. As resource pricing is dynamic, it is essential to carefully schedule when to make a needed reservation. This work proposes a novel approach for predicting the optimized timing to reserve a certain Fog computation resource with minimal costs. Experimental results with real-world traffic data reveal the effectiveness of our proposed technique for reducing resource costs compared to related reservation schemes. Additionally, our solution is frugal so that resource-constrained clients, such as a vehicle on-board computer, can easily operate it.

关键词： Schedules Costs Uncertainty Pricing Reliability engineering Timing Smart grids Time factors Resource management Vehicle dynamics

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Implementing DevOps Practices in CPPS Using Microservices and GitOps 28

Implementing DevOps Practices in CPPS Using Microservices an...

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28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Koren, István Rinker, Felix Meixner, Kristof Kröger, Moritz Zeng, Michael RWTH Aachen University Process and Data Science Germany Technische Universität Wien CDL SQI Institute of Information Systems Engineering Austria RWTH Aachen University Laser Technology Germany RWTH Aachen University Laboratory for Machine Tools and Production Engineering Germany

ISBN: (纸本)9798350339918

As digitalization shapes Industry 4.0, integrating software engineering practices into the manufacturing domain becomes a key focus. DevOps is such a practice and methodology that enhances collaboration and automates processes in software development and IT operations. In previous work, we discussed challenges and opportunities of applying the DevOps paradigm in Cyber-Physical Production Systems (CPPS) engineering, which are complex systems that integrate physical components with computer-controlled operations. This paper instantiates our DevOps4CPPS framework, spotlighting the application of GitOps and microservices in a CPPS environment. A real-world case study from laser ultra short pulse manufacturing illustrates how the approach effectively addresses the inherent challenges of CPPS, boosting agility and operational performance, while reducing downtime. The paper provides guidance to researchers and practitioners on applying DevOps practices to CPPS, and suggests future research directions. © 2023 IEEE.

关键词： Software design

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Dynamic Topic Analysis in Academic Journals using Convex Non-negative Matrix Factorization Method

arXiv

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arXiv 2025年

作者： Yang, Yang Zhang, Tong Wu, Jian Su, Lijie National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang China China Criminal Police University Shenyang China Center for Advanced Process Decision-making Carnegie Mellon University PittsburghPA United States Beijing Institute for General Artificial Intelligence Beijing China Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Northeastern University ChinaShenyang Shenyang110819 China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang China

With the rapid advancement of large language models, academic topic identification and topic evolution analysis are crucial for enhancing AI’s understanding capabilities. Dynamic topic analysis provides a powerful approach to capturing and understanding the temporal evolution of topics in large-scale datasets. This paper presents a two-stage dynamic topic analysis framework that incorporates convex optimization to improve topic consistency, sparsity, and interpretability. In Stage 1, a two-layer non-negative matrix factorization (NMF) model is employed to extract annual topics and identify key terms. In Stage 2, a convex optimization algorithm refines the dynamic topic structure using the convex NMF (cNMF) model, further enhancing topic integration and stability. Applying the proposed method to IEEE journal abstracts from 2004 to 2022 effectively identifies and quantifies emerging research topics, such as COVID-19 and digital twins. By optimizing sparsity differences in the clustering feature space between traditional and emerging research topics, the framework provides deeper insights into topic evolution and ranking analysis. Moreover, the NMF-cNMF model demonstrates superior stability in topic consistency. At sparsity levels of 0.4, 0.6, and 0.9, the proposed approach improves topic ranking stability by 24.51%, 56.60%, and 36.93%, respectively. The source code is available at https://***/meetyangyang/CDNMF. © 2025, CC BY.

关键词： Non-negative matrix factorization

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Three-Dimensional Collision Avoidance Method for Robot-Assisted Minimally Invasive Surgery

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Cyborg and Bionic Systems 2023年第1期4卷 121-135页

作者： Ling Li Xiaojian Li Bo Ouyang Hangjie Mo Hongliang Ren Shanlin Yang School of Management Hefei University of TechnologyHefeiChina Key Laboratory of Process Optimization and Intelligent Decision-Making(Ministry of Education) Hefei University of TechnologyHefeiChina Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance(Ministry of Education) Hefei University of TechnologyHefeiChina Department of Biomedical Engineering Faculty of EngineeringNational University of SingaporeSingaporeSingapore Department of Electronic Engineering Shun Hing Institute of Advanced EngineeringThe Chinese University of Hong KongHong KongChina National Engineering Laboratory for Big Data Distribution and Exchange Technologies ShanghaiChina

In the robot-assisted minimally invasive surgery,if a collision occurs,the robot system program could be damaged,and normal tissues could be *** avoid collisions during surgery,a 3-dimensional collision avoidance method is proposed in this *** proposed method is predicated on the design of 3 strategic vectors:the collision-with-instrument-avoidance(CI)vector,the collision-with-tissues-avoidance(CT)vector,and the constrained-control(CC)*** CI vector demarcates 3 specific directions to forestall collision among the surgical *** CT vector,on the other hand,comprises 2 components tailored to prevent inadvertent contact between the robot-controlled instrument and nontarget ***,the CC vector is introduced to guide the endpoint of the robot-controlled instrument toward the desired position,ensuring precision in its movements,in alignment with the surgical *** results verify the proposed collision avoidance method for robot-assisted minimally invasive *** code and data are available at https://***/cynerelee/collision-avoidance.

关键词： collision desired verify

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A Layered Strategy for Reducing Offloading Latency in Fog Computing

A Layered Strategy for Reducing Offloading Latency in Fog Co...

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International Conference on Fog and Mobile Edge Computing (FMEC)

作者： Ahmed Chebaane Muhammad Kamran Arshad Florian Burger Abdelmajid Khelil CS Department Institute for Data and Process Science Landshut University of Applied Sciences Landshut Germany CS Department University of Salerno Fisciano Italy

ISBN: (数字)9798350366488

ISBN: (纸本)9798350366495

Moving applications from the local Internet of Things devices to neighboring infrastructures has been the highlight of the current distributed Computing era. Due to high latency and network bottlenecks, Cloud Computing has become rather problematic for real-time applications. Accordingly, Fog Computing has been presented as the missing piece to provide along with cloud Computing for virtually all applications. Application virtualization through containers has become more and more popular in the context of Fog Computing as it simplifies live migration and, in particular, offloading of time-critical applications or their selected tasks. However, the measurement study of the overall offloading latency in Fog Computing has not been sufficiently investigated. This article proposes a measurement analysis of the offloading latency of time-critical application tasks from the end device, such as a vehicle, to surrounding Fog nodes based on Docker containers, Kubernetes, and checkpointing. Based on our layered offloading framework, several offloading scenarios have been studied. The experimental results show that by preparing the Fog nodes in advance through careful, easy arrangements, considerable time can be saved when offloading the application to the Fog node within the Fog cluster. We further consider Vehicular Fog Computing (VFC) as a popular example of time-critical Fog computing and assess the suitability of various offloading strategies for VFC use cases.

关键词： Cloud computing Multi-access edge computing Atmospheric measurements Prefetching Containers Particle measurements Real-time systems Time factors Internet of Things Edge computing

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Quality assessment of Affymetrix GeneChip data using the EM algorithm and a naïve Bayes classifier

Quality assessment of Affymetrix GeneChip data using the EM ...

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Howard, Brian E. Sick, Beate Perera, Imara Yang, Ju Im Winter-Sederoff, Heike Heber, Steffen Bioinformatics Research Center North Carolina State University Raleigh NC United States Institute of Data Analysis and Process Design Zurich University of Applied Science Winterthur Winterthur Switzerland Department of Plant Biology North Carolina State University Raleigh NC United States Department of Computer Science North Carolina State University Raleigh NC United States

ISBN: (纸本)1424415098

Recent research has demonstrated the utility of using supervised classification systems for automatic identification of low quality microarray data. However, this approach requires annotation of a large training set by a qualified expert. In this paper we demonstrate the utility of an unsupervised classification technique based on the Expectation-Maximization (EM) algorithm and naïve Bayes classification. On our test set, this system exhibits performance comparable to that of an analogous supervised learner constructed from the same training data. ©2007 IEEE.

关键词： Maximum principle

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Probing Temperature at Nanoscale through Thermal Vibration Characterization using Scanning Precession Electron Diffraction

arXiv

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arXiv 2025年

作者： Yang, Kun Zhang, Chao Wu, Chengwei Du, Qian Li, Bingzhi Fang, Zhen Li, Liang Wu, Jianbo Wu, Tianru Wang, Hui Deng, Tao Gao, Wenpei State Key Laboratory of Metal Matrix Composites School of Materials Science and Engineering Future Material Innovation Center Zhangjiang Institute for Advanced Study Shanghai Jiao Tong University Shanghai200240 China School of Physics and Electronics Hunan Key Laboratory of Super Microstructure and Ultrafast Process State Key Laboratory of Powder Metallurgy Central South University Changsha410083 China Research Center for Scientific Data Hub Zhejiang Lab Hangzhou310000 China SKLPPC Shanghai200240 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China

Accurate, non-contact temperature measurement with high spatial resolution is essential for understanding thermal behavior in integrated nanoscale devices and heterogeneous interfaces. However, existing techniques are often limited by the need for physical contact or insufficient spatial resolution for the measurement of local temperature and mapping its distribution. Here, we showcase the direct temperature measurement of graphene with nanometer spatial resolution in transmission electron microscopy. In experiments, combining a scanning nanobeam with precession electron diffraction offers the collection of kinemetic diffraction from a local area at the nanometer scale. In analysis, we use a pre-calculated, sample-specific structure-factor-based correction method to enable the linear fitting of the diffraction intensities, allowing the determination of the Debye-Waller factor as a function of temperature at the precision of 10-4Å2/C. With the high spatial resolution and measurement precision, the temperature and thermal vibration mapping further reveal the influence of graphene lattice parameters and thickness on the Debye-Waller factor, providing valuable insights into the vibrational properties impacted by temperature, lattice structure, and graphene layer thickness. Copyright © 2025, The Authors. All rights reserved.

关键词： Crystal lattices

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Non-invasive estimation of the powder size distribution from a single speckle image

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Light(science & Applications) 2024年第10期13卷 2221-2230页

作者： Qihang Zhang Ajinkya Pandit Zhiguang Liu Zhen Guo Shashank Muddu Yi Wei Deborah Pereg Neda Nazemifard Charles Papageorgiou Yihui Yang Wenlong Tang Richard D.Braatz Allan S.Myerson George Barbastathis Department of Electrical Engineering and Computer Science Massachusetts Institute of TechnologyCambridgeMA 02139USA Singapore-MIT Alliance for Research and Technology(SMART)Centre Singapore 117543Singapore Department of Chemical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Process Chemistry Development Takeda Pharmaceuticals International Co40 Landsdowne StCambridgeMA 02139USA ShinrAI Center for AI/ML Data Sciences InstitutesTakeda Pharmaceuticals International Co650 E Kendall StCambridgeMA 02142USA Present address:Department of Precision Instruments Tsinghua UniversityBeijing 100084China

Non-invasive characterization of powders may take one of two approaches:imaging and counting individual particles;or relying on scattered light to estimate the particle size distribution(PSD)of the *** former approach runs into practical difficulties,as the system must conform to the working distance and other restrictions of the imaging *** latter approach requires an inverse map from the speckle autocorrelation to the particle *** principle relies on the pupil function determining the basic sidelobe shape,whereas the particle size spread modulates the sidelobe *** recently showed that it is feasible to invert the speckle autocorrelation and obtain the PSD using a neural network,trained efficiently through a physics-informed semi-generative *** this work,we eliminate one of the most time-consuming steps of our previous method by engineering the pupil *** judiciously blocking portions of the pupil,we sacrifice some photons but in return we achieve much enhanced sidelobes and,hence,higher sensitivity to the change of the size *** result is a 60×reduction in total acquisition and processing time,or 0.25 seconds per frame in our *** real-time operation in our system is not only more appealing toward rapid industrial adoption,it also paves the way for quantitative characterization of complex spatial or temporal dynamics in drying,blending,and other chemical and pharmaceutical manufacturing processes.

关键词： speckle size distribution

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