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Irreversibility analysis of magnetized flow of engine oil hybrid nanofluid (Ti6Al4V-ZnO/EO) over a stretching surface

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Alexandria engineering Journal 2025年 127卷 214-227页

作者： Hussain, Syed M. Faridi, Aftab Ahmed Ahmad, Hijaz Ali, Kashif Iqbal, Muhammad Rashid Jamshed, Wasim Guedri, Kamel Almaliki, Abdulrazak H. Department of Mathematics Faculty of Science Islamic University of Madinah Madinah42351 Saudi Arabia Department of Mathematics The Islamia University of Bahawalpur Bahawalpur63100 Pakistan Near East University Operational Research Center in Healthcare TRNC Mersin 10 Nicosia99138 Turkey Department of Technical Sciences Western Caspian University Baku1001 Azerbaijan Department of Mathematics College of Science Korea University 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of Department of Basic Sciences and Humanities Muhammad Nawaz Sharif University of Engineering and Technology Multan60000 Pakistan Department of Mathematics and Statistics Institute of Southern Punjab Multan32100 Pakistan Islamabad44000 Pakistan College of Engineering Al-Ayen Iraqi University An Nasiriyah64001 Iraq Department of Computer Engineering Biruni University Topkapi Istanbul Turkey Mechanical Engineering Department College of Engineering and Architecture Umm Al-Qura University P. O. Box 5555 Makkah21955 Saudi Arabia Department of Civil Engineering college of Engineering Taif University Taif21944 Saudi Arabia

This article analyzes the irreversibility of hydro-magnetic dynamics of hybridized nanofluid comprising of titanium alloy (Ti6Al4V) and zinc-oxide (ZnO) submerged into engine oil (used as a fuel) through a porous stretching sheet with multipart effects of viscous dissipation and non-uniform heat source. An induced magnetic field exists in the flow field due to the conducting nature of the hybrid nanofluid. The equations of the flow model are transformed by the similarity transformations and then simulated through a numerical scheme constructed with a formulation of central differences that adopts successive over-relaxation methodology. In this thermodynamic system, entropy and Bejan number profiles corresponding to the prominent parameters are simultaneously analysed for both the nanofluid case and hybrid nanofluid case in the Cartesian coordinates. A comparison table is constructed to validate the numerical results with existing literature. The impacts of various parameters on Nusselt number and skin friction coefficient are graphed with reference to the magnetic field parameter. A significant reduction in irreversibility and a remarkable improvement in thermal characteristics of engine oil are observed due to induced magnetism effects. The engine oil hybrid nanofluid (Ti6Al4V-ZnO/EO) exhibits a 13.89 % higher heat transfer rate over a porous stretching surface compared to the engine oil nanofluid (Ti6Al4V/EO). © 2025 The Authors

关键词： Magnetic levitation

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An advance computational intelligent approach to solve the third kind of nonlinear pantograph Lane–Emden differential system

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Evolving Systems 2023年第3期14卷 393-412页

作者： Sabir, Zulqurnain Raja, Muhammad Asif Zahoor Ali, Mohamed R. Sadat, R. Department of Mathematics and Statistics Hazara University Mansehra Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Faculty of Engineering Benha National University Obour Campus Egypt Department of Mathematics Faculty of Engineering at Zagazig Zagazig University Zagazig Egypt Faculty of Engineering and Technology Future University Cairo Egypt

This study presents an advanced computational Levenberg–Marquardt backpropagation (LMB) neural network for the novel third order (NTO) pantograph Emden–Fowler system (PEFS), i.e., (NTO-PEFS) together with its two forms. The designed novel NTO-PEFS is achieved using the pantograph system and standard form of the Emden–Fowler system. The detail of each form of the NTO-PEFS based on the singular points, pantographs and shape factors is also provided. The numerical performance using the LMB neural network is tested for three different variants of the model and obtained results will be compared through the designed dataset based exact solutions. To assess the approximate solutions of the NTO-PEFS for both forms of each example, the process of testing, authentication and training are implemented to reduce the mean square error (MSE) based on the LMB. One can find the values based absolute error are close to 10–04 to 10–08 for each problem to solve the NTO-PEFS using the stochastic computing paradigms. The relative studies and performance investigations for the error histograms, regression, correlation and MSE enhance the effectiveness as well as the exactness of the designed LMB neural network scheme. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Pantographs

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Deep Contrastive Learning Network for Small-Sample Hyperspectral Image Classification

Journal of Remote Sensing

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Journal of Remote Sensing 2023年第1期3卷 74-90页

作者： Quanyong Liu Jiangtao Peng Genwei Zhang Weiwei Sun Qian Du Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and StatisticsHubei UniversityWuhanChina Department of Gas Sensors and Chemometrics State Key Laboratory of NBC Protection for CivilianBeijingChina Department of Geography and Spatial Information Techniques Ningbo UniversityNingboChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateUSA

Recently,deep learning methods have been widely used in hyperspectral image(HSI)classification and achieved good ***,the performance of these methods may be limited because of the scarcity of labeled samples in HSI *** solve the small-sample classification problem,a deep contrastive learning network(DCLN)method is proposed in this *** proposed DCLN method first constructs contrastive groups and trains the network through contrastive ***,it uses the trained network to extract spectral-spatial features of HSI pixels and generates pseudo-label for each unlabeled sample based on the spatial-spectral mixing ***,the pseudo-labeled samples with higher confidence are selected and added to the original training set to retrain the *** gradually increasing pseudo-labeled samples and refining the contrastive learning network,the model shows good feature learning ability and classification performance with the limited labeled *** results on 4 public HSI datasets demonstrate that the proposed DCLN method can achieve better performance than existing state-of-the-art methods.

关键词： DCL Deep network

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Assessing the Prosperity of European Nations: A Cluster Analysis Based Approach

Assessing the Prosperity of European Nations: A Cluster Anal...

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2024 IEEE International Conference on Technology Management, Operations and Decisions, ICTMOD 2024

作者： Junu Jahana, C. Joseph, Tania M Alzaatreh, Ayman College of Engineering American University of Sharjah Department of Industrial Engineering Sharjah United Arab Emirates College of Arts and Sciences American University of Sharjah Department of Mathematics and Statistics Sharjah United Arab Emirates

ISBN: (纸本)9798350367355

This study employs a multifaceted analytical approach to evaluate prosperity indicators across European countries, utilizing data from EUROSTAT spanning 2017 to 2022. Applying variable clustering and hierarchical clustering techniques, the research identifies three distinct clusters based on social, economic, and environmental indicators. The results are justifiable, with slight variations from real-case scenarios attributed to factors such as differences in considered factors across studies and variations in the study periods. The comprehensive methodology provides a step-by-step account of the hierarchical clustering and heatmap generation process, ensuring transparency and clarity in the analysis of Social, Environmental, and Economic indicators among different European countries. The study's insights provide valuable implications for policymakers, guiding targeted interventions to address unique challenges and opportunities within each cluster, thereby contributing to a more equitable and sustainable future across European countries. © 2024 IEEE.

关键词： European nations Hierarchical Clustering Prosperity Sustainability Variable clustering

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Innovative Agricultural Solutions: Utilizing Machine Learning to Combat Rice Leaf Disease in Indonesia

Innovative Agricultural Solutions: Utilizing Machine Learnin...

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2024 International of Seminar on Application for Technology of Information and Communication, iSemantic 2024

作者： Kurniawan, Avip Soeprobowati, Tri Retnaningsih Warsito, Budi Universitas Diponegoro Informatics Departement Semarang Indonesia Universitas Krisnadwipayana Faculty of Engineering Department of Informatics Jakarta Indonesia Universitas Diponegoro Faculty of Science and Mathematics Department of Biology Semarang Indonesia Semarang Indonesia Universitas Diponegoro Faculty of Science and Mathematics Department of Statistics Semarang Indonesia

ISBN: (纸本)9798350366648

Advances in machine learning and image processing technology offer promising solutions for identifying diseases in rice plants. This study, which utilizes 80 data samples and trains on 20 data points from available datasets, proposes a novel approach using the Random Forest algorithm to efficiently classify leaf diseases. This method assists farmers, especially newcomers, in quickly identifying diseases via smartphone devices. By integrating various feature extraction techniques such as color, texture, and shape, the approach enhances accuracy in disease recognition, which is crucial for timely preventive measures. The process includes stages of data acquisition, preprocessing, feature extraction, and model evaluation to ensure robustness and reliability. By harnessing the power of machine learning, this research contributes to addressing the challenges faced in rural agriculture, aligning with Indonesia's development goals outlined in the third Nawacita program. Through systematic analysis and evaluation, this approach highlights the potential of technology to empower farming communities, promote sustainable agricultural practices, and enhance food security in the region. © 2024 IEEE.

关键词： Smart agriculture

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Stretched non-negative matrix factorization

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npj Computational Materials 2024年第1期10卷 1248-1262页

作者： Ran Gu Yevgeny Rakita Ling Lan Zach Thatcher Gabrielle E.Kamm Daniel O’Nolan Brennan Mcbride Allison Wustrow James R.Neilson Karena W.Chapman Qiang Du Simon J.L.Billinge NITFID School of Statistics and Data ScienceNankai UniversityTianjinChina Department of Applied Physics and Applied Mathematics Fu Foundation School of Engineering&Applied SciencesColumbia UniversityNew YorkNYUSA Department of Chemistry Stony Brook UniversityStony BrookNYUSA Department of Chemistry Colorado State UniversityFort CollinsCOUSA

A novel algorithm,STRETCHEDNMF,is introduced for non-negative matrix factorization(NMF),accounting for signal stretching along the independent variable’s *** addresses signal variability caused by stretching,proving beneficial for analyzing data such as powder diffraction at varying *** approach provides a more meaningful decomposition,particularly when the component signals resemble those from chemical components in the *** STRETCHEDNMF model introduces a stretching factor to accommodate signal expansion,solved using discretization and Block Coordinate Descent *** experimental results indicate that the STRETCHEDNMF model outperforms conventional NMF for datasets exhibiting such *** enhanced version,SPARSE-STRETCHEDNMF,optimized for powder diffraction data from crystalline materials,leverages signal sparsity for accurate extraction,especially with small *** results showcase its effectiveness in analyzing diffraction data,including success in real-time chemical reaction experiments.

关键词： signal stretching matrix

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F-transforms determined by overlap and grouping maps over a complete lattice

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Soft Computing 2024年第19期28卷 10781-10800页

作者： Tripathi, Abha Tiwari, S.P. Jacob, Kavikumar Mahato, Sutapa Dhanbad826004 India Department of Mathematics and Statistics Faculty of Applied Sciences and Technology Universiti Tun Hussein Onn Malaysia Johor Pagoh84600 Malaysia Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai600077 India

This work examines F-transforms based on overlap and grouping maps, residual, and co-residual implicator over complete lattice from constructive and axiomatic approaches, wherein the results highly depend upon the negator. Specifically, (i) we initiate the study of F-transforms using the concepts of the overlap and grouping maps, which can be viewed as a new structure of classical logic’s intersection and union operations on the unit interval [0, 1], (ii) we show that the proposed F-transforms generalize the existing such transforms, and (iii) some of the results do not hold for general implicators. Further, we study the concept of fuzzy transformation systems and examine the duality. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Knowledge based systems

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Product(α1,α2)-modulation spaces Dedicated to the Memory of Michel Marias

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Science China mathematics 2022年第8期65卷 1599-1640页

作者： Galatia Cleanthous Athanasios G.Georgiadis Department of Mathematics and Statistics National University of IrelandMaynooth W 23 F 2K8Ireland Faculty of Engineering Mathematics and ScienceTrinity College of DublinDublin D02 PN40Ireland

We study fundamental properties of product(α,α)-modulation spaces built by(α,α)-coverings of R× *** we prove embedding theorems between these spaces with different parameters and other classical ***,we specify their *** characterization of product modulation spaces via the short time Fourier transform is also *** of tight frames are constructed and discrete representations in terms of corresponding sequence spaces are *** multipliers are studied and as applications we extract lifting properties and the identification of our spaces with(fractional) Sobolev spaces with mixed smoothness.

关键词： product(α1,α2)-modulation space product space mixed smoothness short time Fourier transform embedding dual tight frame discrete decomposition

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Structured Legal Argumentation with LLMs: A Study in Landlord-Tenant Law 37

Structured Legal Argumentation with LLMs: A Study in Landlor...

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37th Annual Conference on Legal Knowledge and Information Systems, JURIX 2024

作者： Fournier, Gregoire Linna, Daniel W. Department of Mathematics Statistics and Computer Science University of Illinois Chicago United States Pritzker School of Law & McCormick School of Engineering Northwestern University United States

ISBN: (纸本)9781643685625

Large Language Models (LLMs) have demonstrated capabilities across a wide range of tasks, including natural language understanding, language generation and generating basic reasoning. To improve the accuracy and reliability of these models, various prompting, augmentation, and fine-tuning strategies have been employed. In this paper, we use context augmentation and Chain-of-Thought (CoT) instructions to generate legal arguments for specific landlord-tenant problems using OpenAI’s GPT-4o. We test this approach using ten hypothetical landlord-tenant scenarios, five provided by a legal aid organization, four generated with Anthropic’s Claude, and one crafted by us. We evaluate each argument for accuracy, factuality, comprehensiveness, and relevance to the scenario. This method of generating legal reasoning with LLMs offers the advantage of being verifiable by legal professionals, while also providing valuable assistance to laypersons in drafting documents such as demand letters, which can help expand access to justice. © 2024 The Authors.

关键词： BASIC (programming language)

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Preparation of Peanut Shell Cellulose Double-Network Hydrogel and Its Adsorption Capacity for Methylene Blue

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Journal of Renewable Materials 2023年第7期11卷 3001-3023页

作者： Yalin Li Lei Liu Wenbao Huang Junpu Xie Zhaoxia Song Shuna Guo Enci Wang Department of College of Environment and Bioengineering Henan University of EngineeringZhengzhou451191China School of Mathematics and Statistics Carleton UniversityOntarioK1S 5B6Canada

To achieve optimal recovery and value-added utilisation of cellulose in peanut shells,the cellulose in peanut shells was first extracted using the sodium hydroxide-sodium chlorite ***,cellulose hydrogel was prepared by graft copolymerisation using N,N’-methylenebisacrylamide as the cross-linking agent,sodium persulfate as the initiator,and acrylic acid as the *** optimisation experiments were designed to obtain optimal process parameters for hydrogel preparation with the cellulose dosage of 0.40 g,initiator dosage of 0.20 g,polymerisation temperature of 70°C,cross-linking agent of 0.25 g,and monomer dosage of 3.0 *** effect of initiator dosage on hydrogel synthesis was the most significant,followed by monomer dosage and reaction *** using X-ray diffraction analysis and scanning electron microscopy revealed that the hydrogel was amorphous and exhibited a distinct three-dimensional double network *** swelling kinetic analysis showed that the hydrogel swelling process was divided into three stages,and fitted the Schott secondary swelling kinetic *** prepared hydrogel had a good adsorption effect on methylene blue;the adsorption of methylene blue by the hydrogel was 1.259 mg/g at 25°C when the initial concentration of methylene blue was 5 mg/*** adsorption kinetics of the hydrogel fit the pseudo-first-order kinetic model,pseudo-secondorder kinetic model,Eovich model and particle diffusion *** best fitting effect was obtained with the pseudo-second-order kinetic *** adsorption isotherm analysis of methylene blue on hydrogel showed that the adsorption process was consistent with Langmuir and Freundlich *** correlation coefficient of the Freundlich isotherm model was higher,indicating that the adsorption of methylene blue on hydrogel was mainly chemisorption.

关键词： Cellulose hydrogel graft copolymerisation cross-linking polymerisation swelling property

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