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Computational simulations of radiative magnetic micropolar nanofluid flow on curved surface: carbon nanotubes and heat transfer

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International Journal of Ambient Energy 2024年第1期45卷

作者： Farooq, Umar Liu, Tao Alshamrani, Ali Rafique, Khadija State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China Department of Mechanical Engineering College of Engineering Taif University Taif Saudi Arabia Department of Mathematics and Statistics Hazara University Mansehra Pakistan

The thermal properties of nanofluids are crucial across various industries, particularly for efficient heat dissipation, which is key to optimising performance. This study examines the heat transfer characteristics of a steady, two-dimensional radiative flow of blood-containing carbon nanotube particles along a curved, stretched surface. The analysis emphasises the behaviour of a magnetised micropolar nanofluid, favouring hybrid nanofluid flow over an extended, curved surface. A mathematical formulation for the flow equations is developed using curvilinear coordinates. The non-similarity method reduces the governing partial differential equations to nonlinear ordinary differential equations. These are solved numerically using the BVP4C solver, which applies a three-stage Lobatto method. Results for the skin friction coefficient and local Nusselt number are presented in tabular form. The study reveals that the temperature profile increases with higher values of magnetic field, Eckert numbers, radiation, and heat source parameters. As the heat source (Q) increases, the Nusselt number for SWCNT + Blood increases. As Q increases from 0.5 to 1.0, the Nusselt number increases by 12.16%;from Q = 1.0 to Q = 1.5 increases by 7.84%, and from Q = 1.5 to Q = 2.0 increases by 7.40%. For SWCNT + MWCNT + Blood, the Nusselt number also rises by around 5.10%, 4.42% and 4.43%. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Nusselt number

Fractional fuzzy sets and their aggregation operators and applications

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Artificial Intelligence Review 2024年第12期57卷 1-29页

作者： Gulistan, Muhammad Hongbin, Ying Pedrycz, Witold Rahim, Muhammad Amin, Fazli Khalifa, Hamiden Abd El-Wahed Department of Electrical and Computer Engineering University of Alberta Edmonton Canada School of Economics and Management Zhejiang Normal University Jinhua China Department of Mathematics and Statistics Hazara University Mansehra Pakistan Department of Mathematics College of Science Qassim University Buraydah Saudi Arabia Department of Operations and Management Research Faculty of Graduate Studies for Statistical Research Cairo University Giza Egypt

Using $$p,q,r-$$ fractional fuzzy sets ( $$p,q,r-$$ FFS) to demonstrate the stability of cryptocurrencies is considered due to the complex and volatile nature of cryptocurrency markets, where traditional models may fall short in capturing nuances and uncertainties. $$p,q,r-$$ FFS provides a flexible framework for modeling cryptocurrency stability by accommodating imprecise data, multidimensional analysis of various market factors, and adaptability to the unique characteristics of the cryptocurrency space, potentially offering a more comprehensive understanding of the factors influencing stability. Existing studies have explored Picture Fuzzy Sets and Spherical Fuzzy Sets, built on membership, neutrality, and non-membership grades. However, these sets can’t reach the maximum value (equal to $$1$$ ) due to grade constraints. For example, when considering $$\wp =(h,\langle \text{0.9,0.8,1.0}\rangle \left|h\in H\right.)$$ , these sets fall short. This is obvious when a decision-maker possesses complete confidence in an alternative, they have the option to assign a value of 1 as the assessment score for that alternative. This signifies that they harbor no doubts or uncertainties regarding the chosen option. To address this, $$p,q,r-$$ Fractional Fuzzy Sets ( $$p,q,r-$$ FFSs) are introduced, using new parameters $$p$$ , $$q$$ , and $$r$$ . These parameters abide by $$p$$ , $$q\ge 1$$ and $$r$$ as the least common multiple of $$p$$ and $$q$$ . We establish operational laws for $$p,q,r-$$ FFSs. Based on these operational laws, we proposed a series of aggregation operators (AOs) to aggregate the information in context of $$p,q,r-$$ fractional fuzzy numbers. Furthermore, we constructed a novel multi-criteria group decision-making (MCGDM) method to deal with real-world decision-making problems. A numerical example is provided to demonstrate the proposed approach.

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Dynamic nonlinear control strategies for resilient heterogeneous vehicle platooning and handling Byzantine attacks in communication networks

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Heliyon 2025年第2期11卷 e41574页

作者： Alsinai, Ammar Piqueira, José Roberto Castilho Hassan, Waqar Ul Niazi, Azmat Ullah Khan Safder, Farida Department of mathematics CV Raman Global University Odisha India Systems engineering Escola Politécnica da USP São Paulo Brazil Department of Mathematics and Statistics The University of Lahore Sargodha 40100 Pakistan

This paper addresses the challenges of maintaining stability in heterogeneous vehicle platooning under the influence of communication disruptions caused by Byzantine attacks within a leader-follower framework. To enhance resilience, we propose a nonlinear control strategy tailored for a third-order heterogeneous dynamic model, integrating leader-follower interconnections with adaptable control gains. Utilizing a constant time headway spacing policy with gap adjustments, we derive control gains that secure internal platoon stability. A Lyapunov-based stability approach is employed to mitigate the destabilizing effects of Byzantine attacks, ensuring robust performance even in adverse conditions. Numerical simulations validate the controller's effectiveness, showing rapid convergence to stable platoon behavior within 10 seconds and maintaining a tracking error below 10 percent, despite simulated attacks. These results demonstrate the practical feasibility of the proposed controller in ensuring stability and resilience in real-world platooning scenarios where communication integrity is compromised. © 2025 The Author(s)

关键词： Byzantine attacks Constant time headway spacing policy Heterogeneous dynamic model Inter-linkage between cars (leader-follower framework) Lyapunov function approach Nonlinear control method

High Reliability Radar and Communications Based on Random Stepped Frequency Waveforms

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High Reliability Radar and Communications Based on Random St...

IEEE International Conference on Communications Workshops, ICC

作者： Shalanika Dayarathna Rajitha Senanayake Jamie Evans Peter Smith Department of Electrical and Electronic Engineering University of Melbourne Australia School of Mathematics and Statistics Victoria University of Wellington New Zealand

This paper is on the waveform design of joint radar and communication systems. Focusing on permutation code based random stepped frequency waveforms, we present a new joint radar and communication system that has improved communication error rate performance when compared to existing approaches. More specifically, we propose a subset selection process to improve the Hamming distance between communication waveforms. An efficient encoding scheme is proposed to map the information symbols to selected permutations. Further, an optimal communication receiver based on integer programming followed by a more efficient sub-optimal receiver based on the Hungarian algorithm is also proposed. Considering the optimum maximum likelihood detection, the block error probability is analyzed under both additive white Gaussian noise channels and Rician fading channels. Finally, we discuss the radar performance under the new system and highlight that it has negligible effect on the radar local and global accuracy.

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CT scans without X-rays: parallel-beam imaging from nonlinear current flows

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arXiv 2024年

作者： Alsaker, Melody Rautio, Siiri Moura, Fernando Agnelli, Juan Pablo Murthy, Rashmi Lassas, Matti Mueller, Jennifer L. Siltanen, Samuli Department of Mathematics Gonzaga University SpokaneWA99258 United States Department of Mathematics and Statistics University of Helsinki Helsinki Finland Engineering Modeling and Applied Social Sciences Center Federal University of ABC São Paulo Brazil FaMAF National University of Córdoba Córdoba Argentina Argentina Department of Mathematics Bangalore University Bangalore India Department of Mathematics School of Biomedical Engineering Colorado State University Fort CollinsCO80521 United States

Parallel-beam X-ray computed tomography (CT) and electrical impedance tomography (EIT) are two imaging modalities which stem from completely different underlying physics, and for decades have been thought to have little in common either practically or mathematically. CT is only mildly ill-posed and uses straight X-rays as measurement energy, which admits simple linear mathematics. However, CT relies on exposing targets to ionizing radiation and requires cumbersome setups with expensive equipment. In contrast, EIT uses harmless electrical currents as measurement energy and can be implemented using simple low-cost portable setups. But EIT is burdened by nonlinearity stemming from the curved paths of electrical currents, as well as extreme ill-posedness which causes characteristic low spatial resolution. In practical EIT reconstruction methods, nonlinearity and ill-posedness have been considered intertwined in a complicated fashion. In this work we demonstrate a surprising connection between CT and EIT which partly unravels the main problems of EIT and leads directly to a proposed imaging modality which we call virtual hybrid parallel-beam tomography (VHPT). We show that hidden deep within EIT data is information which possesses the same linear geometry as parallel-beam CT data. This admits a fundamental restructuring of EIT, separating ill-posedness and nonlinearity into simple modular sub-problems, and yields "virtual radiographs" and CT-like images which reveal previously concealed information. Furthermore, as proof of concept we present VHPT images of real-world objects. © 2024, CC BY.

关键词： Computerized tomography

Ride-sharing Determinants: Spatial and Spatio-temporal Bayesian Analysis for Chicago Service in 2022

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arXiv 2024年

作者： Elkhouly, Mohamed Alhadidi, Taqwa Department of Mathematics and Statistics Cleveland State University ClevelandOH44115 United States Civil Engineering Department Al-Ahliyya Amman University Amman19111 Jordan

Ridesharing services have revolutionized transportation, transforming the manner in which individuals navigate urban environments. The estimation of ride-sharing demand is crucial for enhancing service utilization, reliability, and mitigating traffic congestion. In this research, we employ spatial and spatiotemporal Bayesian models to estimate ride-sharing demand in the 77 Chicago community areas. We investigate various explanatory variables, including demographic, socio-economic, transportation, and land-use features. The Bayesian models adjust for random and structured errors to account for spatial correlations. Additionally, we utilize spatially correlated priors for explanatory variables to improve model precision. Model diagnostics demonstrate the absence of residual spatial structure in the spatial regression, confirming effective management of spatial correlation. The spatiotemporal model yields a squared correlation of 0.95 between observed ride-shares and fitted values, indicating robust predictive power. Demographic factors, including population size and crime rate, emerge as the primary determinants positively influencing ride-sharing demand. Higher income levels, increased numbers of economically active citizens, and higher proportions of car-free households are associated with increased demand. Public transit availability and walkability also play significant roles in ride-sharing patterns in Chicago. Our study demonstrates that ride-sharing demand recovered in 2022 following COVID-19-related closures, particularly during weekends. This research provides planners and policymakers with insights to enhance first and last mile services, identify underserved areas, and enable ride-sharing to address public transportation gaps. Such knowledge has the potential to enhance mobility for individuals with disabilities and those residing in rural areas. This study, utilizing Bayesian models, offers deeper insights into ridesharing demand, thereby contributing to i

关键词： Urban transportation

ACCELERATING ILL-CONDITIONED HANKEL MATRIX RECOVERY VIA STRUCTURED NEWTON-LIKE DESCENT∗

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arXiv 2024年

作者： Cai, Hanqin Huang, Longxiu Lu, Xiliang You, Juntao Department of Statistics and Data Science Department of Computer Science University of Central Florida OrlandoFL32816 United States Department of Computational Mathematics Science and Engineering Department of Mathematics Michigan State University East LansingMI48823 United States School of Mathematics and Statistics Hubei Key Laboratory of Computational Science Wuhan University Wuhan430072 China Institute for Advanced Study Shenzhen University Shenzhen518000 China

This paper studies the robust Hankel recovery problem, which simultaneously removes the sparse outliers and fulfills missing entries from the partial observation. We propose a novel non-convex algorithm, coined Hankel Structured Newton-Like Descent (HSNLD), to tackle the robust Hankel recovery problem. HSNLD is highly efficient with linear convergence, and its convergence rate is independent of the condition number of the underlying Hankel matrix. The recovery guarantee has been established under some mild conditions. Numerical experiments on both synthetic and real datasets show the superior performance of HSNLD against state-of-the-art *** Codes 15A29, 15A83, 47B35, 90C17, 90C26, 90C53 Copyright © 2024, The Authors. All rights reserved.

关键词： Recovery

Bibliometric Analysis: Research Trends in Leaf Image Segmentation and Classification

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Bibliometric Analysis: Research Trends in Leaf Image Segment...

Artificial Intelligence and Mechatronics Systems (AIMS), International Conference on

作者： Eka Puji Agustini Rahmad Gernowo Kurnianingsih Adi Wibowo Budi Warsito Doctoral Program of Information System School of Postgraduated Studies Diponegoro University Semarang Indonesia Doctoral Program of Information System Diponegoro University Semarang Indonesia Master of Applied Science Program Polytechnic Semarang Indonesia Department of Informatics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia Department of Statistics Faculty of Science and Mathematics Diponegoro Universitty Semarang Indonesia

Exploring various phenomena and issues related to leaf images is paramount, particularly in segmentation and classification of such images. This study employs bibliometric analysis to delve into two overarching themes: the trends in publication and the evolution of publications, along with a keyword-based analysis. The research methodology unfolds in two stages: (1) data collection and (2) analysis. The dataset comprises 1,248 articles sourced from the Scopus database, covering the period from 1988 to 2023. The research findings unveil a noteworthy surge in publication trends, peaking at 231 documents in 2023. An in-depth examination of journal names demonstrates that studies on the segmentation and classification of leaf images are predominantly featured in computer science journals, exemplified by the publication of 589 documents. Furthermore, an analysis of frequently used keywords highlights “Extraction” as the predominant term, employed a total of 364 times. This underscores that the research focus on leaf image segmentation and classification presents ample opportunities for researchers to delve more profoundly into the subject.

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Knowledge Distillation for Feature Extraction in Underwater VSLAM

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arXiv 2023年

作者： Yang, Jinghe Gong, Mingming Nair, Girish Lee, Jung Hoon Monty, Jason Pu, Ye The Department of Electrical and Electronic Engineering The University of Melbourne Australia The School of Mathematics and Statistics The University of Melbourne Australia The Department of Mechanical Engineering The University of Melbourne Australia

In recent years, learning-based feature detection and matching have outperformed manually-designed methods in in-air cases. However, it is challenging to learn the features in the underwater scenario due to the absence of annotated underwater datasets. This paper proposes a cross-modal knowledge distillation framework for training an underwater feature detection and matching network (UFEN). In particular, we use in-air RGBD data to generate synthetic underwater images based on a physical underwater imaging formation model and employ these as the medium to distil knowledge from a teacher model SuperPoint pretrained on in-air images. We embed UFEN into the ORB-SLAM3 framework to replace the ORB feature by introducing an additional binarization layer. To test the effectiveness of our method, we built a new underwater dataset with groundtruth measurements named EASI (https://***/Jinghe-mel/UFEN-SLAM), recorded in an indoor water tank for different turbidity levels. The experimental results on the existing dataset and our new dataset demonstrate the effectiveness of our method. Copyright © 2023, The Authors. All rights reserved.

关键词： Distillation