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arXiv 2025年

作者： Herty, Michael Veneruso, Sara RWTH Aachen University Institute of Geometry and Applied Mathematics Aachen Germany University of Ferrara Department of Mathematics and Computer Science Ferrara Italy

Solving non-convex minimization problems using multi-particle metaheuristic derivative-free optimization methods is still active area of research. Popular methods are Particle Swarm Optimization (PSO) methods, that iteratively update a population of particles according to dynamics inspired by social interactions between individuals. We present a modification to include constrained minimization problems using exact penalization. Additionally, we utilize the hierarchical structure of PSO to introduce a micro-macro decomposition of the algorithm. The probability density of particles is written as a convex combination of microscopic and macroscopic contributions, and both parts are propagated separately. The decomposition is dynamically updated based on heuristic considerations. Numerical examples compare the results obtained using the algorithm in the microscopic scale, in the macroscopic scale, and, using the new micro-macro *** Codes 35Q70, 35Q84, 35Q93, 49M41, 90C56 Copyright © 2025, The Authors. All rights reserved.

关键词： Particle swarm optimization (PSO)

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One- and two-sided prediction intervals for future Pareto record values with applications

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Journal of Statistical Theory and Applications 2025年 1-26页

作者： Schmiedt, Anja B. Empacher, Christina Kamps, Udo Department of Computer Science and Mathematics Regensburg University of Applied Sciences Regensburg 93053 Germany Institute of Statistics RWTH Aachen University Aachen 52056 Germany

Based on upper record values in a series of observations over time from a Pareto distribution, an exact and several approximate one-sided and two-sided prediction intervals for the next record value (or for another future record value) to appear are studied and compared by means of an extensive simulation study. The performances of the prediction intervals are evaluated and recommendations are proposed for what method should be used in a given situation with respect to the form of the prediction interval on the one hand and to the tail behaviour on the other. The proposed methods are applied to insurance, environmental and sports data, where the respectively fitted Pareto distributions show a different tail behaviour. As a result, it is seen that although the number of observed record values in the presented real data applications is rather small, as it is usually the case, the selected prediction intervals are of practical use. © The Author(s) 2025.

关键词： Interval prediction Pareto distribution Real data analyses Record values Simulation study

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AI-Powered Healthcare with Advanced Graph Convolutional Neural Networks and SVM for Diagnosis 3

AI-Powered Healthcare with Advanced Graph Convolutional Neur...

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3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Mahendran, A. Nalla, Sridhar Babu Trivedi, Lalit Mohan Mohankumar, S. Williams, D.R. Mohan Renuka, Manne Sona College of Arts and Science Department of Computer Science Salem India Sr University Department of Computer Science and Engineering Hyderabad India Moradabad Institute of Technology Department of Ash Mathematics Moradabad India Erode Sengunthar Engineering College Department of Computer Science and Engineering Perundurai India College of Computing and Information Sciences University of Technology and Applied Science-Sohar Department of Information Technology Sohar Oman Vidya Jyothi Institute of Technology Department of Electronics and Communication Engineering Hyderabad India

ISBN: (纸本)9798331508456

Medical treatment costs are rising for many reasons. These include an increasing world population, an aging population, greater healthcare needs, more diseases, and inflation. With AI's emergence in navigation, voice recognition, image lesion segmentation, ride-sharing, and smartphone personal assistants, the healthcare industry has quickly adopted it. Initial preprocessing includes standardization, missing values, and discarding anomalies. Next, the model is trained using the obtained features. Spearman correlation, a rank-based nonparametric statistic, can quantify monotonic correlation strength and direction. Even with missing values, the Graph Convolutional Network (GCN) performs well in model training. The suggested model outperformed state-of-the-art alternatives with 93.48% accuracy. It outperformed TransLSTM and GraphSAGE on complex datasets. This research stresses the system's ability to improve healthcare forecast accuracy through preprocessing, feature extraction, and GCN model training. Results show that AI can improve healthcare analytics despite lacking data. © 2025 IEEE.

关键词： Patient treatment

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Sequential Solution Strategies for the Cahn-Hilliard-Biot Model

Sequential Solution Strategies for the Cahn-Hilliard-Biot ...

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European Conference on Numerical mathematics and Advanced Applications, ENUMATH 2023

作者： Storvik, Erlend Riethmüller, Cedric Both, Jakub W. Radu, Florin Adrian Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Bergen Norway Institute of Applied Analysis and Numerical Simulation University of Stuttgart Stuttgart Germany Centre for Modeling of Coupled Subsurface Dynamics Department of Mathematics University of Bergen Bergen Norway

ISBN: (纸本)9783031861680

This paper presents a study of solution strategies for the Cahn-Hilliard-Biot equations, a complex mathematical model for understanding flow in deformable porous media with changing solid phases. Solving the Cahn-Hilliard-Biot system poses significant challenges due to its coupled, nonlinear and non-convex nature. We explore various solution algorithms, comparing monolithic and splitting strategies, focusing on both their computational efficiency and robustness. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Computational efficiency

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On the Security Related Properties of Randomly Constructed Combinatorial Structures 8th

On the Security Related Properties of Randomly Constructed...

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8th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2024

作者： Liagkou, V. Nastou, P.E. Spirakis, P. Stamatiou, Y.C. Computer Technology Institute and Press - "Diophantus" University of Patras Campus Patras26504 Greece Department of Computer Science University of Liverpool Liverpool United Kingdom Department of Business Administration University of Patras Patras26504 Greece Department of Informatics and Telecommunications University of Ioannina Koatakioi Arta47100 Greece Department of Mathematics Applied Mathematics and Mathematical Modeling Laboratory University of the Aegean Samos Greece

ISBN: (纸本)9783031769337

This paper explores the interplay between randomly generated structures, namely set families as well as second-order logic 0-1 laws, in security-related settings. The paper investigates how randomly generated structures can serve as powerful models for representing security properties of complex systems. By examining the 0-1 properties of these structures, conditions are stated which determine the presence or absence of specific security issues. The stated results provide a generic framework for studying insights into the probabilistic behavior of security attributes modeled by set families and mathematical logic with application potential in designing more robust systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： computer circuits

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Fuzzy Logic-Based Deep Learning for Human-Machine Interaction and Gesture Recognition in Uncertain and Noisy Environments 1

Fuzzy Logic-Based Deep Learning for Human-Machine Interactio...

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1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Anand, John Thamilarasi, V. Rayal, Ashish Gupta, Himanshu Kumar Jyothi, Kamboji Vishwakarma, Pramatma Greater Noida201310 India Department of Computer Science & Engineering Tamilnadu Salem-16 India School of Applied and Life Sciences Uttaranchal University Department of Mathematics Dehradun248007 India Bipin Tripathi Kumaon Institute of Technology Department of Electrical Engineering Almora Dwarahat India Chaitanya Bharathi Institute of Technology Department of Mathematics AP Proddatur India Lovely Professional University Department of Computer Aplication Punjab 144411 India

ISBN: (纸本)9798331518578

Conventional deep learning methods have considerable hurdles when it comes to Human-Machine Interaction (HMI) and gesture identification in noisy and uncertain situations. A Fuzzy Logic-Based Deep Learning (Fuzzy DL) method is presented in this work to improve the resilience, accuracy, and adaptability of human gesture recognition in a variety of scenarios. We test several algorithms on various datasets, lighting situations, and noise levels, such as CNN, LSTM, Transformer, and Fuzzy DL. The outcomes show that Fuzzy DL functions better than other systems, retaining 91.0% accuracy at high noise levels and reaching 97.5% accuracy under typical circumstances. In comparison to traditional structures, it also shows faster inference times and a lower mean squared error. Its superiority is further demonstrated by comparative analysis on precision, recall, and F1-score. This study presents a robust and noise-resilient solution for real-world HMI applications, including as assistive systems and virtual interfaces. The outcomes indicate that incorporating fuzzy logic with DL substantially enhances gesture recognition in difficult environments. © 2025 IEEE.

关键词： Contrastive Learning

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Matrix Structure of Classical Z2×Z2 Graded Lie Algebras

Matrix Structure of Classical Z2×Z2 Graded Lie Algebras

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International Workshop on Lie Theory and Its Applications in Physics, LT 2023

作者： Stoilova, N.I. Van der Jeugt, J. Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Boul. Tsarigradsko Chaussee 72 Sofia1784 Bulgaria Department of Applied Mathematics Computer Science and Statistics Ghent University Krijgslaan 281-S9 Gent9000 Belgium

ISBN: (纸本)9789819764525

A Z2×Z2-graded Lie algebra g is a Z2×Z2-graded algebra g with a bracket [[·,·]] that satisfies certain graded versions of the symmetry and Jacobi identity. In particular, despite the common terminology, g is not a Lie algebra. We construct classes of Z2×Z2-graded Lie algebras corresponding to the classical Lie algebras, in terms of their defining matrices. For the Z2×Z2-graded Lie algebra of type A, the construction coincides with the previously known class. For the Z2×Z2-graded Lie algebra of type B, C and D our construction is new and gives rise to interesting defining matrices closely related to the classical ones but undoubtedly different. We also give some examples and possible applications to parastatistics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Matrix algebra

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Deep Reinforcement Learning of Robotic Manipulation for Whip Targeting

Deep Reinforcement Learning of Robotic Manipulation for Whip...

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2025 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots, SIMPAR 2025

作者： Bai, Xiang Wang, Junyi Xiong, Xiaofeng Boukas, Evangelos Technical University of Denmark Applied Mathematics and Computer Science Copenhagen Denmark Technical University of Denmark Automation and Control Group Electrical and Photonics Engineering Copenhagen Denmark University of Southern Denmark Sdu Biorobotics Mærsk Mc-Kinney Moller Institute Odense Denmark

ISBN: (纸本)9798331516857

关键词： Robotic arms

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Polyp image segmentation based on improved planet optimization algorithm using reptile search algorithm

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Neural Computing and Applications 2025年第8期37卷 6327-6349页

作者： Abd Elaziz, Mohamed Al-qaness, Mohammed A. A. Al-Betar, Mohammed Azmi Ewees, Ahmed A. Department of Mathematics Faculty of Science Zagazig University Zagazig Egypt College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua321004 China Zhejiang Institute of Optoelectronics Jinhua321004 China Faculty of Computer Science and Engineering Galala University Suze435611 Egypt Ajman University Ajman346 United Arab Emirates College of Computing and Information Technology University of Bisha Bisha Saudi Arabia Department of Computer Damietta University Damietta Egypt Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan

To recognize the potential for colon polyps to develop into cancer over time, early diagnosis is crucial for preventative healthcare. Timely identification significantly improves the prognosis and treatment outcomes for colorectal cancer patients. Image segmentation is crucial in medical image analysis for accurate diagnosis and treatment planning. Therefore, in this study, we present an alternative multilevel thresholding polyp segmentation method (MPOA) to enhance the segmentation of polyp images. The proposed method is based on enhancing the planet optimization algorithm (POA) by integrating operators from the reptile search algorithm (RSA). The evaluation of the developed MPOA is tested with different polyp images and compared with other image segmentation approaches. The results highlight the superior capability of MPOA, as evidenced by various performance measures in effectively segmenting polyp images. Furthermore, metrics such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and fitness values demonstrate that MPOA outperforms the basic version of POA and other methods. The evaluation outcomes underscore the significant impact of RSA in enhancing the performance of POA for the segmentation of polyp images. © The Author(s) 2025.

关键词： Diseases

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Invariance properties of the solution operator for measure-valued semilinear transport equations

arXiv

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arXiv 2025年

作者： Hille, Sander C. Lyons, Rainey Muntean, Adrian Mathematical Institute Leiden University Netherlands Department of Applied Mathematics University of Colorado Boulder United States Department of Mathematics and Computer Science Karlstad University Sweden

We provide conditions under which we prove for measure-valued transport equations with nonlinear reaction term in the space of finite signed Radon measures, that positivity is preserved, as well as absolute continuity with respect to Lebesgue measure, if the initial condition has that property. Moreover, if the initial condition has Lp regular density, then the solution has the same *** Codes 35Q49 © 2025, CC BY.

关键词： Nonlinear equations

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