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Federated Blockchain-Based Clustering Protocol for Enhanced Security and Connectivity in FANETs With CF-mMIMO

IEEE Internet of Things Journal 2025年第10期12卷 14016-14035页

作者： Pramitarini, Yushintia Perdana, Ridho Hendra Yoga Shim, Kyusung An, Beongku Hongik University Graduate School Department of Software and Communications Engineering Sejong30016 Korea Republic of Hankyong National University School of Computer Engineering and Applied Mathematics Korea Republic of Hongik University Department of Software and Communications Engineering Sejong30016 Korea Republic of

In this paper, we propose a novel federated blockchain (FedChain)-based clustering protocol to enhance network security and connectivity in flying ad hoc networks (FANETs) with cell-free massive MIMO (CF-mMIMO). By leveraging blockchain technology and federated learning (FL), the cluster can be protected against Sybil attacks, enabling secure cluster formation without increasing the number of control packets. We formulate the cost function maximization problem based on cross-layer design, which integrates physical layer information (mobility, position, channel capacity, and remaining energy) and network layer parameters (connectivity) to optimize the formation of stable clusters with minimal control overhead. Furthermore, we select the optimal cluster heads (CHs) based on the highest remaining energy and velocity-constrained criteria, ensuring long-term stability. To solve the security issue, blockchain technology is adopted to validate transactions among nodes and ensure secure formation by distinguishing legitimate users and Sybil attack nodes. Additionally, we develop a novel FL framework to predict and distinguish node status in real time without additional control packets, improving security and control overhead performance during cluster formation. Simulation results demonstrate that the proposed FedChain-based clustering protocol outperforms the lowest ID (LI), high connectivity degree (HCD), and conventional blockchain-based clustering (CBC) protocols in terms of connectivity, control overhead, and security performance. The results highlight that the FedChain-based clustering protocol provides robust security and connectivity, making it well-suited for dynamic FANET environments. © 2014 IEEE.

关键词： Cost functions

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MOCBOA:Multi-Objective Chef-Based Optimization Algorithm Using Hybrid Dominance Relations for Solving engineering Design Problems

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computer Modeling in engineering & Sciences 2025年第4期143卷 967-1008页

作者： Nour Elhouda Chalabi Abdelouahab Attia Abdulaziz S.Almazyad Ali Wagdy Mohamed Frank Werner Pradeep Jangir Mohammad Shokouhifar Computer Science Department University of M’silaIchebiliaM’sila28000Algeria Computer ScienceDepartment Mohamed El Bachir El IbrahimiUniversity of Bordj BouArreridjBordj BouArreridj34000Algeria Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan Faculty of Mathematics Otto-von-Guericke UniversityMagdeburg39016Germany University Centre for Research and Development Chandigarh UniversityMohali140413India Department of Electrical and Computer Engineering Shahid Beheshti UniversityTehran14399Iran DTU AI and Data Science Hub(DAIDASH) Duy Tan UniversityDa Nang550000Vietnam

Multi-objective optimization is critical for problem-solving in engineering,economics,and *** study introduces the Multi-Objective Chef-Based Optimization Algorithm(MOCBOA),an upgraded version of the Chef-Based Optimization Algorithm(CBOA)that addresses distinct *** approach is unique in systematically examining four dominance relations—Pareto,Epsilon,Cone-epsilon,and Strengthened dominance—to evaluate their influence on sustaining solution variety and driving convergence toward the Pareto *** comparison investigation,which was conducted on fifty test problems from the CEC 2021 benchmark and applied to areas such as chemical engineering,mechanical design,and power systems,reveals that the dominance approach used has a considerable impact on the key optimization measures such as the hypervolume *** paper provides a solid foundation for determining themost effective dominance approach and significant insights for both theoretical research and practical applications in multi-objective optimization.

关键词： Multi-objective optimization chef-based optimization algorithm(CBOA) pareto dominance epsilon dominance cone-epsilon dominance strengthened dominance

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Early Parkinson's Disease Detection and Classification using Machine Learning and Neutrosophic Sets

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Neutrosophic Sets and Systems 2025年 82卷 873-886页

作者： Oudah, Hasan H. Metwaly, Ahmed A. Eassa, Mohamed Abdelhafeez, Ahmed Nagm, Ahmad M. Salama, Ahmed S. College of Arts Department of Journalism Ahl Al Bayt University Karbala Iraq Department of Computer Science Faculty of Computers and Informatics Zagazig University Zagazig44519 Egypt Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Engineering and Electronics Cairo Higher Institute for Engineering Computer Science and Management New Cairo Egypt

Optimizing therapy and rehabilitation for Parkinson's disease (PD) requires early identification and precise evaluation of the illness's course. However, there is disagreement about the best way to use gait analysis to categorize the severity of motor symptoms and identify early-stage Parkinson's disease. The precision of machine learning (ML) models in identifying early and intermediate stages of Parkinson's disease was assessed in this study. Six ML models are used in this study for the prediction of PD. Different metrics are used to evaluate ML models such as accuracy, precision, recall, f1-score, and AUC score. Then we propose a multi-criteria decision-making methodology (MCDM) to evaluate the ML models and select the best one. Two MCDM methods are used such as CRITIC method to compute the criteria weights and the TOPSIS method to rank the alternatives. These methods are used under the bipolar neutrosophic sets (BNSs) to deal with uncertainty information. The results show the support vector machine is the best ML model for the prediction of PD. © 2025, University of New Mexico. All rights reserved.

关键词： Neurodegenerative diseases

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Machine Learning Approaches to Explore Important Features behind Bird Flight Modes

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IPSJ Transactions on Bioinformatics 2025年 18卷 1-7页

作者： Kawai, Yukino Hisada, Tatsuya Shiomi, Kozue Hayamizu, Momoko Department of Pure and Applied Mathematics Graduate School of Fundamental Science and Engineering Waseda University Shinjuku Tokyo169–8555 Japan Frontier Research Institute for Interdisciplinary Sciences Tohoku University Miyagi Sendai980–8578 Japan Department of Applied Mathematics Faculty of Fundamental Science and Engineering Waseda University Shinjuku Tokyo169–8555 Japan

Birds exhibit a variety of flight styles, primarily classified as flapping, which is characterized by rapid up-and-down wing movements, and soaring, which involves gliding with wings outstretched. Each species usually performs specific flight styles, and this has been argued in terms of morphological and physiological adaptation. However, it remains a challenge to evaluate the contribution of each factor to the difference in flight styles. In this study, using phenotypic data from 635 migratory bird species, such as body mass, wing length, and breeding periods, we quantified the relative importance of each feature using Feature Importance and SHAP values, and used them to construct weighted L1 distance matrices and construct NJ trees. Comparison with traditional phylogenetic logistic regression revealed similarity in top-ranked features, but also differences in overall weight distributions and clustering patterns in NJ trees. Our results highlight the complexity of constructing a biologically useful distance matrix from correlated phenotypic features, while the complementary nature of these weighting methods suggests the potential utility of multi-faceted approaches to assessing feature contributions. © 2025 Information Processing Society of Japan.

关键词： Logistic regression

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Some Results on Ricci-Yamabe Soliton and Its Cosmological Models

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IAENG International Journal of applied mathematics 2025年第4期55卷 979-983页

作者： Pandey, Pankaj Yadav, Santosh Kumar Sharma, Kamakshi Chaturvedi, Braj Bhushan Department of Mathematics School of Chemical Engineering and Physical Sciences Lovely Professional University Punjab Phagwara144411 India Department of Mathematics School of Computer Science & Artificial Intelligence SR University Telangana Warangal506371 India Department of Pure & Applied Mathematics Guru Ghasidas Vishwavidyalaya Chhattisgarh Bilaspur495009 India

This article aims to investigate the characteristics of Ricci-Yamabe Soliton (briefly: (RYS)n). We study the cosmological models on (RYS)4 under Lorentzian para Sasakian (LPS)4 spacetime. Parallel Ricci tensor, Poisson structure and gradient property also reveal on (RYS)n. Example of (RYS)4 constructed to verify the results. © (2025), (International Association of Engineers). All rights reserved.

关键词： Solitons

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A folding preprocess for the max k-cut problem

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Optimization Letters 2025年第5期19卷 899-917页

作者： Fakhimi, Ramin Validi, Hamidreza Hicks, Illya V. Terlaky, Tamás Zuluaga, Luis F. Department of Industrial and Systems Engineering Lehigh University Bethlehem United States Department of Industrial Manufacturing & Systems Engineering Texas Tech University Lubbock United States Department of Computational Applied Mathematics & Operations Research Rice University Houston United States

Given graph G=(V,E) with vertex set V and edge set E, the max k-cut problem seeks to partition the vertex set V into at most k subsets that maximize the weight (number) of edges with endpoints in different parts. This paper proposes a graph folding procedure (i.e., a procedure that reduces the number of the vertices and edges of graph G) for the weighted max k-cut problem that may help reduce the problem’s dimensionality. While our theoretical results hold for any k≥2, our computational results show the effectiveness of the proposed preprocess only for k=2 and on two sets of instances. Furthermore, we observe that the preprocess improves the performance of a MIP solver on a set of large-scale instances of the max cut problem. © The Author(s) 2025.

关键词： Network theory (graphs)

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A genetic algorithm approach based on spline quasi-interpolation for solving Fredholm integral equations

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mathematics and computers in Simulation 2025年 229卷 725-742页

作者： Mokhtari, F. El Lamnii, M. Barrera, D. LANO Laboratory FSO University Mohammed First Oujda Morocco Department of Applied Mathematics University of Granada Spain Research Center High Studies of Engineering School EHEI Oujda Morocco

This paper focuses on the approximation of solutions of second kind Fredholm integral equations using non-uniform spline quasi-interpolation. Our aim is to determine the most effective non-uniform partition that provides an optimal numerical solution to the integral equation. To achieve this, we introduce a solution approach based on genetic algorithms, using right approximation of the integral equation's kernel. We present some numerical examples to show the method's performance. © 2024 International Association for mathematics and computers in Simulation (IMACS)

关键词： Fredholm integral equations

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On Error-Based Step Size Control for Discontinuous Galerkin Methods for Compressible Fluid Dynamics

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应用数学与计算数学学报 2025年第1期7卷 3-39页

作者： Hendrik Ranocha Andrew R.Winters Hugo Guillermo Castro Lisandro Dalcin Michael Schlottke-Lakemper Gregor J.Gassner Matteo Parsani Applied Mathematics University of HamburgBundesstr.5520146 HamburgGermany Department of Mathematics Applied Mathematics Linköping UniversityLinköpingSweden Extreme Computing Research Center(ECRC) Computer Electrical and Mathematical Science and Engineering Division(CEMSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Applied and Computational Mathematics RWTH Aachen UniversityAachenGermany High-Performance Computing Center Stuttgart University of StuttgartStuttgartGermany Department of Mathematics and Computer Science University of CologneCologneGermany Center for Data and Simulation Science University of CologneCologneGermany Extreme Computing Research Center(ECRC) Computer Electrical and Mathematical Science and Engineering Division(CEMSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Physical Science and Engineering Division(PSE) King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia

We study a temporal step size control of explicit Runge-Kutta(RK)methods for com-pressible computational fluid dynamics(CFD),including the Navier-Stokes equations and hyperbolic systems of conservation laws such as the Euler *** demonstrate that error-based approaches are convenient in a wide range of applications and compare them to more classical step size control based on a Courant-Friedrichs-Lewy(CFL)*** numerical examples show that the error-based step size control is easy to use,robust,and efficient,e.g.,for(initial)transient periods,complex geometries,nonlinear shock captur-ing approaches,and schemes that use nonlinear entropy *** demonstrate these properties for problems ranging from well-understood academic test cases to industrially relevant large-scale computations with two disjoint code bases,the open source Julia pack-ages *** with *** and the C/Fortran code SSDC based on PETSc.

关键词： Explicit Runge-Kutta(RK)methods Step size control Compressible fluid dynamics Adaptivity in space and time Shock capturing

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SEPARABLE PHYSICS-INFORMED NEURAL NETWORKS FOR SOLVING THE BGK MODEL OF THE BOLTZMANN EQUATION

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SIAM Journal on Scientific Computing 2025年第2期47卷 C451-C474页

作者： Oh, Jaemin Cho, Seung Yeon Yun, Seok-Bae Park, Eunbyung Hong, Youngjoon Department of Electrical and Computer Engineering Texas A&M University United States Department of Mathematics Gyeongsang National University Jinju Korea Republic of Department of Mathematics Sungkyunkwan University Suwon Korea Republic of Department of Artificial Intelligence Yonsei University Korea Republic of Department of Mathematical Sciences Research Institute of Mathematics Seoul National University Korea Republic of

In this study, we present a new approach based on separable physics-informed neural networks (SPINNs), specifically designed to efficiently solve the Bhatnagar-Gross-Krook (BGK) model. While the mesh-free nature of physics-informed neural networks (PINNs) offers significant advantages for handling high-dimensional partial differential equations, applying quadrature rules for accurate integral evaluation in the BGK operator can compromise these benefits and increase computational costs. To address this issue, we leverage the canonical polyadic decomposition structure of SPINNs and the linear nature of moment calculation to significantly reduce the computational expense associated with quadrature rules. However, the multiscale nature of the particle density function poses challenges for precisely approximating macroscopic moments using neural networks. To overcome this, we introduce SPINN-BGK, a specialized variant of SPINNs that fuses SPINNs with Gaussian functions and utilizes a relative loss approach. This modification enables SPINNs to decay as rapidly as Maxwellian distributions, enhancing the accuracy of macroscopic moment approximations. The relative loss design ensures that both large- and small-scale features are effectively captured by the SPINNs. The effectiveness of our approach is validated through six numerical experiments, including a complex three-dimensional Riemann problem. These experiments demonstrate the potential of our method to efficiently and accurately tackle intricate challenges in computational physics, offering significant improvements in computational efficiency and solution accuracy. © 2025 Society for Industrial and applied mathematics.

关键词： Boltzmann equation

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Applications of variable thermal features for the bioconvective flow of Jeffrey nanofluids due to stretching surface with masssuction effects:Cattaneo-Christov model

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applied mathematics and Mechanics(English Edition) 2025年第2期46卷 391-402页

作者： S.U.KHAN M.GARAYEV ADNAN K.RAMESH M.EL MELIGY D.ABDUVALIEVA M.I.KHAN Department of Mathematics Namal UniversityMianwali 42250Pakistan Department of Mathematics College of ScienceKing Saud UniversityRiyadh 11421Saudi Arabia Department of Mathematics Mohi-ud-Din Islamic UniversityNerian Sharif 12080Pakistan Department of Pure and Applied Mathematics School of Mathematical SciencesSunway UniversityPetaling Jaya 47500Malaysia Department of Mathematics Graphic Era(Deemed to be University)DehradunUttarakhand 248002India Department of Mathematics School of Chemical Engineering and Physical SciencesLovely Professional UniversityPunjab 144411India Jadara University Research Center Jadara UniversityIrbid 21110Jordan Applied Science Research Center Applied Science Private UniversityAmman 11937Jordan Department of Mathematics and Information Technologies Tashkent State Pedagogical UniversityTashkent 100070Uzbekistan Department of Mechanics and Engineering Science Peking UniversityBeijing 100871China

The thermal nanofluids have garnered widespread attention for their use in multiple thermal systems,including heating processes,sustainable energy,and nuclear *** on nanofluids has revealed that the thermal efficiencies of such materials are adversely affected by various thermal *** purpose of the current work is to demonstrate the thermal analysis of Jeffrey nanofluids with the suspension of microorganisms in the presence of variable thermal *** variable effects of thermal conductivity,Brownian diffusivity,and motile density are *** investigated model also reveals the contributions of radiation phenomena and chemical reactions.A porous,saturated,moving surface with a suction phenomenon promotes *** modeling of the problem is based on the implementation of the Cattaneo-Christov *** convective thermal constraints are used to promote the heat transfer features.A simplified form of the governing model is treated with the assistance of a shooting *** physical effects of different parameters for the problem are *** current problem justifies its applications in heat transfer,coating processes,heat exchangers,cooling systems in microelectronics,solar systems,chemical processes,etc.

关键词： Jeffrey nanofluid bioconvection effect variable thermal consequence chemical reaction numerical simulation

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