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11th Vienna International conference on mathematical modelling, MATHMOD 2025

作者： Mike Huynh, Gia Huy Fahse, Niklas Kneifl, Jonas Linn, Joachim Fehr, Jörg Institute of Engineering and Computational Mechanics University of Stuttgart Germany Fraunhofer Institute for Industrial Mathematics ITWM Kaiserslautern Germany

It has been shown that working with databases from heterogeneous sources of varying fidelity can be leveraged in multi-fidelity surrogate models to enhance the high-fidelity prediction accuracy or, equivalently, to reduce the amount of high-fidelity data and thus computational effort required while maintaining accuracy. In contrast, this contribution leverages low-fidelity data queried on a larger feature space to realize data-driven multi-fidelity surrogate models with a fallback option in regimes where high-fidelity data is unavailable. Accordingly, methodologies are introduced to fulfill this task and effectively resolve the contradictions, that inherently arise in multi-fidelity databases. In particular, the databases considered in this contribution feature two levels of fidelity with a defined hierarchy, where data from a high-fidelity source is, when available, prioritized over low-fidelity data. The proposed surrogate model architectures are illustrated first with a toy problem and further examined in the context of an engineering use case in autonomous driving, where the human-seat interaction is evaluated using a data-driven surrogate model, that is trained through an active learning approach. It is shown, that two proposed architectures achieve an improvement in accuracy on high-fidelity data while simultaneously performing well where high-fidelity data is unavailable compared to a naive approach. Copyright © 2025 The Authors.

关键词： Database systems

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Oxygen Extraction and Blood Transport in the human Retina: A mathematical modelling and Analysis

Oxygen Extraction and Blood Transport in the Human Retina: A...

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2025 International conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Kumar, Aadesh Awasthy, Neeta Singh, Bholey Deolia, Rajesh Kumar Kumar, Satendra Sengar, R.S. Gl Bajaj Group of Institutions Department of Applied Science and Humanities Mathura India Gl Bajaj Group of Institutions Department of Computer Science and Engineering Mathura India

ISBN: (纸本)9798331527495

This study aims to describe the intricate flow of blood within the retinal tissue. The main findings of this research are the introduction of a quantitative method to calculate total oxygen extraction using retinal measurements of total blood flow, providing a crucial link between blood flow dynamics and oxygen transport. To analyze the problem, the authors employ a perturbation procedure, a mathematical approach that simplifies complex systems by introducing small changes to the variables. This approach facilitates a deeper understanding of the interplay between flow mechanics and oxygen delivery in the retina. The study's findings hold potential for advancing knowledge in retinal physiology and could pave the way for improved diagnostic and therapeutic strategies for retinal vascular diseases. © 2025 IEEE.

关键词： Perturbation techniques

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Advancing Robotic Jumping with CVT Enhanced SEA 25th

Advancing Robotic Jumping with CVT Enhanced SEA

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25th Annual conference on Towards Autonomous Robotic Systems, TAROS 2024

作者： Sun, Jingcheng Zhou, Chengxu School of Mechanical Engineering University of Leeds Leeds United Kingdom Department of Computer Science University College London London United Kingdom

ISBN: (纸本)9783031720611

Series-elastic actuation (SEA) is widely employed on hopping robots due to its capability to diminish energy consumption and peak torque requirements. However, scant attention has been given in existing studies to the jump height achieved by robots utilizing SEA. To maximise jump height while retaining SEA’s benefits, a solution to improve the actuator involves having a variable mechanical advantage (MA) gearbox between the elastic element and the end-effector. Continuously variable transmission (CVT) can produce such a precise MA profile with relatively straightforward structures. Although previous studies have incorporated CVT in robotics, with a predominant focus on wheeled robots, the potential advantages of using CVT on jumping robots have been overlooked. In this study, mathematical modelling is utilized to simulate and analyse the advantages of having a CVT-enhanced SEA (C-SEA) in terms of achieving higher jumps and protecting structural integrity for hopping robots. The results indicate that the C-SEA manages to reduce the peak ground reaction force by approximately 50% compared to the regular SEA. Moreover, C-SEA demonstrates superior performance in most cases with higher motor rotor mass and viscous damping coefficient when actuated by a motor with linear behaviour. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： End effectors

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A New Advanced and Simple Procedure for the Nonlinear Static Analysis of Curved Masonry Structures 5th

A New Advanced and Simple Procedure for the Nonlinear Static...

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5th International conference on Protection of Historical Constructions, PROHITECH 2025

作者： Buzzetti, Martina Gandolfi, Alessandro Pingaro, Natalia Milani, Gabriele Department of Architecture Built Environment and Construction Engineering Politecnico di Milano Piazza Leonardo da Vinci 32 Milan Italy

ISBN: (纸本)9783031873157

In many countries, a large part of the building stock is constructed in masonry. Despite the numerous advantages of this material, when it comes to resisting large foundation displacements or seismic actions, the capacity of such structures is not always ensured. In fact, it depends on many factors like the mutual connection between technical elements, the box behaviour, and the interlocking between single units. Moreover, the conditions of the external supports and dead weights matter, as in masonry structures, especially curved ones, they are tightly bonded to the geometry. However, modelling all those interactions in a simplified manner, together with the heterogeneous and nonlinear material properties is quite challenging. This led to the development of a novel procedure involving Elastic Body and Spring models for masonry nonlinear static analysis in Finite Elements. The springs constitute the interfaces between the bodies and allow a Distinct Element-like analysis. The innovation brought by this contribution is the automatization of interface meshing by a Ruled Explicit Meshing tool, intending to diminish the occurrence of human errors and the time demanded for the operation. The general objective is to provide engineers with a straightforward tool to evaluate the (residual) capacity of masonry structures in relation to imposed displacements. This will assist the final user in designing conservation or reinforcement measures when necessary. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Mesh generation

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A Probabilistic Reasoning Framework to Detect Fake News on Social Media 19

A Probabilistic Reasoning Framework to Detect Fake News on S...

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19th International conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Rashid, Mehreen Anber, Fabliha Samiullah, Md Ahmed, Chowdhury Farhan Leung, Carson K. Pazdor, Adam G.M. Department of Computer Science and Engineering University of Dhaka Dhaka Bangladesh Department of Computer Science University of Manitoba WinnipegMB Canada

ISBN: (纸本)9798331507817

The rapid growth of social media has made the Internet a critical platform for spreading misinformation, which shapes public opinion and harms society. Despite significant research in fake news detection, most probabilistic efforts rely heavily on Naive Bayes, with limited exploration of other probabilistic models. This paper introduces a Bayesian network (BN) modelling-based framework for fake news detection, offering a probabilistic estimate of the likelihood of news being false. Unlike binary classification, this approach reflects human decision-making by evaluating three key questions: "who", "what", and "when". Each module corresponds to a specific feature set, enabling nuanced reasoning about the news’s credibility. The framework is flexible, allowing adjustments through expert input, knowledge bases, or real-world data. We validate the approach using a semi-synthetic dataset containing features from news content, user behaviour, and social context. The results highlight the framework’s capacity to leverage expert knowledge, providing a more reliable and adaptive solution compared to traditional classifiers. The BN-based method demonstrates enhanced robustness, positioning it as a promising tool for tackling misinformation in an evolving digital landscape. © 2025 IEEE.

关键词： Bayesian network Credibility Fake news Information management Social media

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44th SGAI International conference on Innovative Techniques and Applications of Artificial Intelligence, SGAI 2024

44th SGAI International Conference on Innovative Techniques ...

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44th SGAI International conference on Innovative Techniques and Applications of Artificial Intelligence, SGAI 2024

ISBN: (纸本)9783031779176

The proceedings contain 52 papers. The special focus in this conference is on Innovative Techniques and Applications of Artificial Intelligence. The topics include: Semantic Segmentation for Landslide Detection Using Segformer;vision-Based human Fall Detection Using 3D Neural Networks;Drone-Assisted Infrared Thermography and Machine Learning for Enhanced Photovoltaic Defect Detection: A Comparative Study of Vision Transformers and YOLOv8;evaluating Algorithms for Missing Value Imputation in Real Battery Data;using Pseudo Cases and Stratified Case-Based Reasoning to Generate and Evaluate Training Adjustments for Marathon Runners;Emotion Detection in Hindi Language Using GPT and BERT;Classification and Recommendation of Mental Health Assistance Events Using an RNN-LSTM, Fast-And-Frugal Trees and Weighted Sum System;digit Detection: Localizing and Convoluting;djinn—Data Journalism Interface for Newsgathering and Notifications;advancing Financial Text Sentiment Analysis with Deep Learning and Ensemble Models;explaining a Staff Rostering Problem Using Partial Solutions;formalise Regulations for Autonomous Vehicles with Right-Open Temporal Deontic Defeasible Logic;SLANGO - The Initial Blueprint of Privacy-Oriented Legal Query Assistance: Exploring the Potential of Retrieval-Augmented Generation for German Law Using SPR;an Ensemble modelling of Feature engineering and Predictions for Enhanced Fake News Detection;a Child-Robot Interaction Experiment to Analyze Gender Stereotypes in the Perception of mathematical Abilities;reinforcement Learning for Patient Scheduling with Combinatorial Optimisation;nursing Activity Recognition for Automated Care Documentation in Clinical Settings;exploring Efficient Job Shop Scheduling Using Deep Reinforcement Learning;respiratory Disease Detection Using Deep Convolutional Transformer Models;Evaluating the Performance of LLMs When Translating Saudi Arabic as Low Resource Language;Bi-directional LSTM Applied to the Maritime Target Motion Ana

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44th SGAI International conference on Innovative Techniques and Applications of Artificial Intelligence, SGAI 2024

44th SGAI International Conference on Innovative Techniques ...

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44th SGAI International conference on Innovative Techniques and Applications of Artificial Intelligence, SGAI 2024

ISBN: (纸本)9783031779145

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Consistent multi-animal pose estimation in cattle using dynamic Kalman filter based tracking

arXiv

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arXiv 2025年

作者： Perneel, Maarten Adriaens, Ines Aernouts, Ben Verwaeren, Jan Department of Biosystems Division of Animal and Human Health Engineering KU Leuven Campus Geel Kleinhoefstraat 4 Geel2440 Belgium Department of Data Analysis and Mathematical Modelling Faculty of Bioscience Engineering Ghent University Coupure Links 653 Ghent9000 Belgium

Over the past decade, studying animal behaviour with the help of computer vision has become more popular. Replacing human observers by computer vision lowers the cost of data collection and therefore allows to collect more extensive datasets. However, the majority of available computer vision algorithms to study animal behaviour is highly tailored towards a single research objective, limiting possibilities for data reuse. In this perspective, pose-estimation in combination with animal tracking offers opportunities to yield a higher level representation capturing both the spatial and temporal component of animal behaviour. Such a higher level representation allows to answer a wide variety of research questions simultaneously, without the need to develop repeatedly tailored computer vision algorithms. In this paper, we therefore first cope with several weaknesses of current pose-estimation algorithms and thereafter introduce KeySORT (Keypoint Simple and Online Realtime Tracking). KeySORT deploys an adaptive Kalman filter to construct tracklets in a bounding-box free manner, significantly improving the temporal consistency of detected keypoints. In this paper, we focus on pose estimation in cattle, but our methodology can easily be generalised to any other animal species. Our test results indicate our algorithm is able to detect up to 80% of the ground truth keypoints with high accuracy, with only a limited drop in performance when daylight recordings are compared to nightvision recordings. Moreover, by using KeySORT to construct skeletons, the temporal consistency of generated keypoint coordinates was largely improved, offering opportunities with regard to automated behaviour monitoring of animals. © 2025, CC BY-SA.

关键词： Kalman filters

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Oxygen Extraction and Blood Transport in the human Retina: A mathematical modelling and Analysis

Oxygen Extraction and Blood Transport in the Human Retina: A...

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Intelligent Control, Computing and Communications (IC3), International conference on

作者： Aadesh Kumar Neeta Awasthy Bholey Singh Rajesh Kumar Deolia Satendra Kumar RS Sengar Department of Applied Science and Humanities GL Bajaj Group of Institutions Mathura India Department of Computer Science and Engineering GL Bajaj Group of Institutions Mathura India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

关键词： Pathology Oxygen Perturbation methods Retina mathematical models Blood Monitoring Blood flow Diseases Intelligent control

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Research on space immigration program and strategy based on multiple optimization algorithms 24

Research on space immigration program and strategy based on ...

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Proceedings of the 2024 4th International conference on Computational Modeling, Simulation and Data Analysis

作者： Zehui Jiang College of Mechanical Engineering Quzhou University Quzhou Zhejiang China

ISBN: (纸本)9798400711831

With the continuous development of technology, scientists predict that the day of human migration to space is getting closer and closer. Based on the space migration programme, this paper constructs various mathematical models. Based on data assumptions, this paper focuses on three problems and solves them separately by constructing appropriate mathematical models. For Problem 1, the number of transported spacecraft is optimised by a linear programming model. For problem 2, a simulated annealing algorithm is used to optimise the allocation of workers to maximise resource efficiency. For problem 3, a BP neural network optimised by a genetic algorithm is used to predict and optimise the strategy for dealing with random personnel and material losses. By meticulously and skillfully solving these three key problems, our research not only contributes to the smooth implementation of future space immigration programs, but also expands the field of mathematical modelling, demonstrating its unlimited potential to revolutionise all aspects of life.

关键词： BP neural network

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