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arXiv 2025年

作者： Herman, Allen Kaur, Surinder Department of Mathematics and Statistics University of Regina Saskatchewan Canada Department of Mathematics School of Engineering and Sciences SRM University-AP Andhra Pradesh 522502 India

Assume F is a finite field of order pf and q is an odd prime for which pf − 1 = sqm, where m ≥ 1 and (s, q) = 1. In this article, we obtain the order of symmetric and unitary subgroup of the semisimple group algebra F Cq. Further, for the extension G of Cq = hbi by an abelian group A of order pn with CA(b) = {e}, we prove that if m > 1, or (s + 1) ≥ q and 2n ≥ f (q − 1), then G does not have a normal complement in V (F G).MSC Codes 16U60 (Primary) 20C05, 20E45 (Secondary) © 2025, CC BY-NC-ND.

关键词： Algebra

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-norm Estimates of the Bergman Projection on the Monomial Polyhedra

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The Journal of Geometric Analysis 2025年第3期35卷 1-47页

作者： Qin, Chuan Wang, Maofa Zhang, Shuo Department of Mathematics School of Electronics and Information Engineering Taizhou University Taizhou China School of Mathematics and Statistics Wuhan University Wuhan China College of Science Tianjin University of Technology Tianjin China

Monomial polyhedra are a class of bounded singular Reinhardt domains defined as sublevel sets of holomorphic monomials. The purpose of this paper is twofold. We first establish an $$L^p$$ -norm estimate for the Bergman projection on the monomial polyhedra $${\mathcal {U}}_{B}$$ , which can be viewed as a complement of the recent work of the $$L^p$$ regularity for the Bergman projection on monomial polyhedra by Bender et al. (Can J Math 74:732–772, 2022). Then, if $${\mathcal {U}}_{B}$$ is a monomial polyhedron associated to the matrix $$B\in {\mathbb {Z}}^{n\times n}$$ satisfying $$\det \,B=1$$ , we obtain a sharp weighted version of $$L^p$$ -norm estimate for the Bergman projection on $${\mathcal {U}}_{B}$$ .

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Review of cutting-edge weed management strategy in agricultural systems

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International Journal of Agricultural and Biological engineering 2025年第1期18卷 25-42页

作者： Narayan R.Gatkal Sachin M.Nalawade Mohini S.Shelke Ramesh K.Sahni Avdhoot A.Walunj Pravin B.Kadam Musrrat Ali Department of Farm Machinery and Power Engineering Dr.Annasaheb College of Agricultural Engineering and TechnologyMahatma Phule Krishi VidyapeethRahuri 413722AhmednagarMHIndia Department of Soil Science and Agricultural Chemistry Vasantrao Naik Marathwada Agricultural UniversityParbhaniMaharashtra 431402India Central Institute of Agricultural Engineering Bhopal 462038Madya PradeshIndia Department of Mathematics and Statistics College of ScienceKing Faisal UniversityAl-Ahsa 31982Saudi Arabia

Weed control in agricultural systems is of the utmost *** reduce crop yields by up to 30%to 40%.Different methods are used to control weeds,such as manual,chemical,mechanical,and precision weed *** are managed more effectively by using the hand weeding method,which nevertheless falls short due to the unavailability of labor during peak periods and increasing labor ***,manual weeding tools have higher weeding efficiency(72%to 99%)but lower field capacity(0.001 to 0.033 hm2/h).Use of chemicals to control weeds is the most efficient and cost-effective *** weedicides have been used excessively and inappropriately,which has over time resulted in many issues with food and environmental *** weed control improves soil aeration,increases water retention capacity,slows weed growth,and has no negative effects on *** weed management techniques have been gaining importance *** in agriculture has significantly enhanced mechanization inputs for weed *** development of precision weed management techniques offers an efficient way to control weeds,contributing to greater sustainability and improved agricultural *** for agricultural automated navigation have been built on the rapid deployment of sensors,microcontrollers,and computing technologies into the *** automated system saves time and reduces labor requirements and health risks associated with drudgery,all of which contribute to more effective farm *** new era of agriculture demands highly efficient and effective autonomous weed control *** such as remote sensing,multispectral and hyperspectral imaging,and the use of robots or UAVs(drones)can significantly reduce labor requirements,enhance food production speed,maintain crop quality,address ecological imbalances,and ensure the precise application of *** monitoring is made more effective and safer for the enviro

关键词： hyperspectral multispectral precision weed management robot remote sensing unmanned aerial vehicle weeds weeder

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Comparative Analysis of Deep Learning Approaches for Predicting Thermomechanical Behavior of Shape Memory Polymers

Comparative Analysis of Deep Learning Approaches for Predict...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Mahmud, Khan Raqib Wang, Lingxiao Chen, Jinyuan Liu, Xiyuan Hassan, Sunzid Louisiana Tech University Department of Computer Science Ruston United States Louisiana Tech University Department of Electrical Engineering Ruston United States Louisiana Tech University Department of Mathematics and Statistics Ruston United States

ISBN: (纸本)9798331504847

Thermomechanical constitutive modeling is crucial for understanding and designing shape memory polymers (SMPs) for advanced engineering applications. Traditional approaches are often time-consuming and computationally expensive which requires the development of more efficient and accurate methods. In this paper, we propose a Transformer-based deep learning model to predict the thermomechanical behavior of semicrys-talline two-way shape memory polymers (2W-SMPs) under thermomechanical cycles. By leveraging its ability to capture complex, time-dependent patterns, the framework accurately models the intricate relationships between polymer strain, time, temperature, and stress. A comparative analysis with other deep learning models demonstrates that the Transformer excels in accuracy and robustness by capturing intricate dependencies and non-linearities in the data. The test results demonstrate that our proposed Transformer model achieved a root mean squared error (RMSE) of 0.3365, outperforms the traditional deep learning models such as the feedforward neural network (FNN), convolutional neural network (CNN), and long short-term memory (LSTM) models which achieved RMSE values of 6.78, 17.35, and 13.85, respectively. This study highlights the potential of the Transformer model as a powerful tool for predicting material behavior and reducing the time and resources required for constitutive modeling. © 2025 IEEE.

关键词： Mean square error

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Heat transfer in a dual wavy wall squared enclosure saturated by non-Newtonian fluid: a numerical investigation of mixed convection and application to concentrated solar power collectors (CSPC)

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The European Physical Journal Special Topics 2025年 1-22页

作者： Elnaqeeb, Thanaa Dutta, Shantanu Shah, Nehad Ali Department of Mathematics and Statistics Faculty of Science Taif University Taif Saudi Arabia Department of Mathematics Faculty of Science Zagazig University Zagazig Egypt Mechanical Engineering Department Sanaka Educational Trust’s Group of Institutions (Affiliated to MAKAUT) Durgapur India Department of Mathematics and Statistics College of Science Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh Saudi Arabia

In this research paper, the two-dimensional mixed convection heat transfer through a square, wavy walled enclosure adopted from a novel Concentrated Solar Power collector configuration with undulations in the left and right walls is investigated numerically. The left wall is subjected to a constant high temperature, while the right wall has a variable low temperature that depends on a sinusoidal function of dimensionless length. The horizontal top and bottom sides are kept adiabatic and non-slipped walls. The enclosure is saturated with non-Newtonian fluid that can be either shear thinning or shear thickening. The numerical computations are performed using COMSOL Multiphysics. The effects of important parameters on streamlines, isotherms, velocity contours, and Nusselt numbers are introduced through plots, tables, and graphs. Solar energy systems, particularly solar thermal collectors, often require efficient heat transfer mechanisms. The wavy wall design of our work can enhance heat transfer by inducing more heat transfer enhancement and increasing the surface area for heat exchange. The results reveal that by increasing the Richardson number, the fluid mixing improves and the velocity increases along the enclosure walls for the shear-thinning case. Moreover, this study highlights that the highest values of local Nusselt numbers are obtained at Richardson number, Ri = 10 for both left and right sides of the enclosure at power-law index n = 0.6. Moreover, the velocity increases as Re and Ri increase and the recirculation zone grows as Re increases. This novel geometry enhances the surface area and fluid mixing, making it more applicable to optimizing heat transfer in practical applications like CSP collectors.

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Compact ultrametric spaces generated by labeled star graphs

arXiv

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arXiv 2025年

作者： Dovgoshey, Oleksiy Cantor, Omer Rovenska, Olga Department of Function Theory Institute of Applied Mathematics and Mechanics of NASU Slovyansk Ukraine Department of Mathematics and Statistics University of Turku Turku Finland Department of Mathematics University of Haifa Haifa Israel Department of Mathematics and Modelling Donbas State Engineering Academy Kramatorsk Ukraine

Let US be the class of all ultrametric spaces generated by labeled star graphs. We prove that compact US-spaces are the completions of totally bounded ultrametric spaces generated by decreasingly labeled rays. We characterize the ultrametric spaces which are weakly similar to finite US-spaces and describe these spaces by certain four-point *** Codes Primary 54E35, Secondary 54E4 © 2025, CC BY.

关键词： Stars

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Self-supervised Instance Segmentation of Diabetic Foot Ulcers via Feature Correspondence Distillation 4th

Self-supervised Instance Segmentation of Diabetic Foot Ulce...

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4th Diabetic Foot Ulcers Grand Challenge, DFUC 2024 held in Conjunction 27th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024

作者： Zhang, Wenhui Banerjee, Abhirup Ray, Surajit School of Mathematics and Statistics University of Glasgow GlasgowG12 8QQ United Kingdom Institute of Biomedical Engineering Department of Engineering Science University of Oxford OxfordOX3 7DQ United Kingdom

ISBN: (纸本)9783031808708

Diabetic foot ulcers (DFUs) are a serious complication of diabetes that can often lead to infection, amputation, and even death if not properly managed. Accurate segmentation of DFUs in medical images is crucial for effective treatment planning. In the DFUC2024 challenge, which emphasizes self-supervised learning techniques for DFU segmentation, we investigate two approaches. The first approach utilizes a DINO (self-distillation with no labels) model combined with a trainable clustering probe to map unsupervised features into discrete segmentation labels. The second approach involves modifying the STEGO model, specifically designed to distill unsupervised features into meaningful segmentation labels, by integrating self-attention features from the ViT backbone to enhance spatial information. To further improve segmentation accuracy, we propose a coarse-to-fine instance prediction framework, where initial coarse predictions are refined through focused reprocessing of detected ulcer regions. After optimizing the hyperparameters for the DFU dataset, the modified STEGO model achieves a Dice coefficient of 0.4362 and Jaccard coefficient of 0.3358. Although the proposed approach yields competitive results, the challenge of self-supervision in DFU segmentation remains significant. The implementation of this work is available at https://***/Wenhui-Zhang-5/DFUC2024-challenge. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Self-supervised learning

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A Neutrosophic Logic Ruled Based Machine Learning Approaches for Chronic Kidney Disease Risk Prediction

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Neutrosophic Sets and Systems 2025年 79卷 76-95页

作者： Mohanty, Bhabani S. Krishna Priya, R. Alias, Liya Vijaya Kumar Reddy, R. Raut, Prasanta Kumar Isaac, Samson Manibharathi, D. Saravanakumar, C. Panda, Nihar Ranjan Broumi, Said Department of Statistics and Applied Mathematics Central University of Tamil Nadu India Research and Consultancy Department University of Technology and Applied Sciences P.O. Box: 12 Khasab Governorate of Musandam Musandam811 Oman College of Engineering and Technology University of Technology and Applied Science Shinas Oman Department of CSE Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur AP India Department of Mathematics Trident Academy of Technology Odisha Bhubaneswar India Division of Biomedical Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Electronics and Communication Engineering Government College of Engineering Tamilnadu Salem India Department of Electronics and Communication Engineering SRM Valliammai Engineering College Kattankulathur Tamilnadu Chengalpattu India Department of Medical Research IMS & SUM Hospital SOA Deemed to be university India Laboratory of Information Processing Faculty of Science Ben M’Sik University Hassan II Casablanca Morocco

Chronic kidney disease (CKD) represents a significant global health challenge in society, and early detection of risk is essential for on-time treatment and intervention. This research suggests a novel machine-learning technique to create a reliable and accurate CKD risk prediction model by combining neutrosophic logic with various classification algorithms. We use neutrosophic logic to address the inherent imprecision and uncertainty in medical data, resulting in a more realistic portrayal of real-world scenarios. We measure the effectiveness of the proposed neutrosophic logic-based models using various metrics, including precision, specificity, and sensitivity. The results show that the neutrosophic logic method is better than traditional machine learning methods at finding people who are likely to develop CKD because it is more accurate and stable. This study illustrates the potential for incorporating neutrosophic logic into machine learning frameworks to improve risk prediction in medical fields. © 2025, University of New Mexico. All rights reserved.

关键词： Prediction models

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IMPACT OF FEAR AND HARVESTING EFFORT ON A DIFFERENTIAL-ALGEBRAIC PREY-PREDATOR MODEL BASED ON SQUARE ROOT FUNCTIONAL RESPONSE

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Journal of Mathematical Sciences (United States) 2025年 1-21页

作者： Elsadany, A.A. Mahapatra, G.S. Santra, P.K. Pal, D. Elsonbaty, A. Al-khedhairi, A. Department of Mathematics College of Science and Humanities in Al-Kharj Prince Sattam Bin Abdulaziz University Al-Kharj 11942 Saudi Arabia Department of Basic Science Faculty of Computers and Informatics Suez Canal University Ismailia 41522 Egypt Department of Mathematics National Institute of Technology Puducherry Karaikal 609609 India Maulana Abul Kalam Azad University of Technology Kolkata 700064 India Indian Institute of Engineering Science and Technology Shibpur Howrah 711103 India Department of Mathematics and Engineering Physics Faculty of Engineering Mansoura University Mansoura 35516 Egypt Department of Statistics and Operations Research College of Science King Saud University P.O. Box 2455 Riyadh 11451 Saudi Arabia

An economic differential-algebraic prey-predator model incorporating square root functional response and fear of predators is presented in this current paper. The article is developing a prey-predator structure on the intention to an economic viewpoint through harvesting on prey species. The equilibrium points and stability status of both the differential-only model and differential-algebraic model are identified and examined. Impacts of fear effect on the stabilities of the model equilibrium points are studied. The Hopf bifurcation analysis is carried out concerning the prey species’ intensity of fear and growth rate. The singularity-induced bifurcation for zero and non-zero economic profits is discussed for the proposed system. A state feedback controller is constructed for zero economic profit to keep the persistence property of the prey-predator model. Numerical simulations and graphical presentations are provided in support of our analytical findings. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Bifurcation Bioeconomics Differential-algebraic Fear effect Prey-predator

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Optimal Estimation in Spatially Distributed Systems: How Far to Share Measurements From?

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IEEE Transactions on Automatic Control 2025年第5期70卷 3226-3239页

作者： Arbelaiz, Juncal Bamieh, Bassam Hosoi, Anette E. Jadbabaie, Ali Massachusetts Institute of Technology Department of Applied Mathematics CambridgeMA02139 United States Princeton University Center for Statistics and Machine Learning PrincetonNJ08542 United States University of California Department of Mechanical Engineering Santa BarbaraCA93106 United States Massachusetts Institute of Technology Department of Mechanical Engineering CambridgeMA02139 United States Massachusetts Institute of Technology Department of Civil and Environmental Engineering Institute for Data Systems and Society CambridgeMA02139 United States

In this article, we consider the centralized optimal estimation problem in spatially distributed systems. We use the setting of spatially invariant systems as an idealization for which concrete and detailed results are given. Such estimators are known to have a degree of spatial localization in the sense that the estimator gains decay in space, with the spatial decay rates serving as a proxy for how far measurements need to be shared in an optimal distributed estimator. In particular, we examine the dependence of spatial decay rates on problem specifications such as system dynamics, measurement, and process noise variances, as well as their spatial autocorrelations. We propose nondimensional parameters that characterize the decay rates as a function of problem specifications. In particular, we find an interesting matching condition between the characteristic lengthscale of the dynamics and the measurement noise correlation lengthscale for which the optimal centralized estimator is completely decentralized. A new graphical technique—termed the branch point locus—is introduced to quantify spatial decay rates in terms of analyticity regions in the complex spatial frequency plane. Our results are illustrated through two case studies of systems with dynamics modeled by diffusion and the Swift–Hohenberg equation, respectively. © 1963-2012 IEEE.

关键词： Uncertain systems

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