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Global Piecewise Analysis of HIV Model with Bi-Infectious Categories under Ordinary Derivative and Non-Singular Operator with Neural Network Approach

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Computer Modeling in Engineering & sciences 2025年第1期142卷 609-633页

作者： Ghaliah Alhamzi Badr Saad TAlkahtani Ravi Shanker Dubey Mati ur Rahman Department of mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh13318Saudi Arabia Department of mathematics College of ScienceKing Saud UniversityRiyadh11989Saudi Arabia Department of mathematics Amity School of Applied SciencesAmity University RajasthanJaipur302002India school of Mathematical sciences Jiangsu UniversityZhenjiang212013China Department of Computer science and mathematics Lebanese American UniversityBeirut13-5053Lebanon

This study directs the discussion of HIV disease with a novel kind of complex dynamical generalized and piecewise operator in the sense of classical and Atangana Baleanu(AB)derivatives having arbitrary *** HIV infection model has a susceptible class,a recovered class,along with a case of infection divided into three sub-different levels or categories and the recovered *** total time interval is converted into two,which are further investigated for ordinary and fractional order operators of the AB derivative,*** proposed model is tested separately for unique solutions and existence on bi *** numerical solution of the proposed model is treated by the piece-wise numerical iterative scheme of Newtons *** proposed method is established for piece-wise derivatives under natural order and non-singular Mittag-Leffler *** cross-over or bending characteristics in the dynamical system of HIV are easily examined by the aspect of this research having a memory effect for controlling the said *** study uses the neural network(NN)technique to obtain a better set of weights with low residual errors,and the epochs number is considered *** obtained figures represent the approximate solution and absolute error which are tested with NN to train the data accurately.

关键词： HIV infection model qualitative scheme approximate solution piecewise global operator neural network

Impact of Pollutant Concentration and Particle Deposition on the Radiative Flow of Casson-Micropolar Fluid between Parallel Plates

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Computer Modeling in Engineering & sciences 2025年第1期142卷 665-690页

作者： Ghaliah Alhamzi Badr Saad T.Alkahtani Ravi Shanker Dubey Vinutha Kalleshachar Neelima Nizampatnam Department of mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11564Saudi Arabia Department of mathematics College of ScienceKing Saud UniversityRiyadh11989Saudi Arabia Department of mathematics Amity School of Applied SciencesAmity University RajasthanJaipur302002RajasthanIndia Department of Studies in mathematics Davangere UniversityDavangere577002India Department of Electronics and Communication Engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluru560035India

Assessing the behaviour and concentration of waste pollutants deposited between two parallel plates is essential for effective environmental *** the effectiveness of treatment methods in reducing pollution scales is made easier by analysing waste discharge *** waste discharge concentration analysis is useful for assessing how effectively wastewater treatment techniques reduce pollution *** study aims to explore the Casson micropolar fluid flow through two parallel plates with the influence of pollutant concentration and thermophoretic particle *** explore the mass and heat transport features,thermophoretic particle deposition and thermal radiation are *** governing equations are transformed into ordinary differential equations with the help of suitable similarity *** Runge-Kutta-Fehlberg’s fourthfifth order technique and shooting procedure are used to solve the reduced set of equations and boundary *** integration of a neural network model based on the Levenberg-Marquardt algorithm serves to improve the accuracy of predictions and optimize the analysis of *** outcomes are displayed to analyze the characteristics of the relevant dimensionless parameters in the current *** reveal that concentration upsurges as the micropolar parameter *** concentration reduces with an upsurge in the thermophoretic *** upsurge in the external pollutant source variation and the local pollutant external source parameters enhances mass *** surface drag force declines for improved values of porosity and micropolar parameters.

关键词： Micropolar fluid thermal radiation porous medium thermophoretic particle deposition waste discharge concentration

Characteristics of gut microbiota dysbiosis in patients with colorectal polyps

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World Journal of Gastrointestinal Oncology 2025年第1期17卷 13-21页

作者： Xian-Rong Wu Xiao-Hong He Yong-Fang Xie school of Life Health information science and Engineering Chongqing Post and Communications UniversityChongqing 400065China

This editorial,inspired by a recent study published in the World Journal of Gastrointestinal Oncology,covers the research findings on microbiota changes in various *** recurrent colorectal polyps,the abundances of Klebsiella,Parvimonas,and Clostridium increase,while those of Bifidobacterium and Lactoba-cillus *** dysbiosis may promote the formation and recurrence of *** microbial changes have also been observed in colorectal cancer,inflammatory bowel disease,autism spectrum disorder,and metabolic syndrome,indicating the role of increased pathogens and decreased probiotics in these *** the gut microbiota,particularly by increasing probiotic levels,may help prevent polyp recurrence and promote gut *** microbial intervention strategy holds promise as an adjunctive treatment for patients with colorectal polyps.

关键词： Recurrent colorectal polyps Gut microbiota dysbiosis Klebsiella Probiotics Intestinal inflammation Microbial intervention strategy

The Crank-Nicolson/Explicit Scheme for the Natural Convection Equations with Nonsmooth Initial Data

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Advances in Applied mathematics and Mechanics 2020年第6期12卷 1481-1519页

作者： Jinting Yang Hongxia Liang Tong Zhang school of mathematics&information science Henan Polytechnic UniversityJiaozuoHenan 454003China

In this article,a Crank-Nicolson/Explicit scheme is designed and analyzed for the time-dependent natural convection problem with nonsmooth initial *** Galerkin finite element method(FEM)with stable MINI element is used for the velocity and pressure and linear polynomial for the *** time discretization is based on the Crank-Nicolson *** order to simplify the computations,the nonlinear terms are treated by the explicit *** advantages of our numerical scheme can be list as follows:(1)The original problem is split into two linear subproblems,these subproblems can be solved in each time level in parallel and the computational sizes are smaller than the origin one.(2)A constant coefficient linear discrete algebraic system is obtained in each subproblem and the computation becomes *** main contributions of this work are the stability and convergence results of numerical solutions with nonsmooth initial ***,some numerical results are presented to verify the established theoretical results and show the performances of the developed numerical scheme.

关键词： Natural-Convection equations Crank-Nicolson/Explicit scheme nonsmooth initial data error estimates

Two-Level Stabilized Finite Volume Methods for the Stationary Navier-Stokes Equations

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Advances in Applied mathematics and Mechanics 2013年第1期5卷 19-35页

作者： Tong Zhang Shunwei Xu school of mathematics&information science Henan Polytechnic UniversityJiaozuo 454003HenanChina

In this work,two-level stabilized finite volume formulations for the 2D steady Navier-Stokes equations are *** methods are based on the local Gauss integration technique and the lowest equal-order finite element ***,the two-level stabilized finite volume methods involve solving one small NavierStokes problem on a coarse mesh with mesh size H,a large general Stokes problem for the Simple and Oseen two-level stabilized finite volume methods on the fine mesh with mesh size h=O(H^(2))or a large general Stokes equations for the Newton two-level stabilized finite volume method on a fine mesh with mesh size h=O(|logh|^(1/2)H^(3)).These methods we studied provide an approximate solution(ue v h,pe v h)with the convergence rate of same order as the standard stabilized finite volume method,which involve solving one large nonlinear problem on a fine mesh with mesh size ***,our methods can save a large amount of computational time.

关键词： Stationary Navier-Stokes equations finite volume method two-level method error estimate

A Better Semi-online Algorithm for Q3/s_1=s_2≤s_3/C_(min) with the Known Largest Size

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Acta Mathematicae Applicatae Sinica 2012年第1期28卷 111-116页

作者： Sheng-yi CAI Qi-fan YANG Department of mathematics Zhejiang UniversityHangzhou 310027China school of mathematics&information science Wenzhou UniversityWenzhou 325035China

This paper investigates the semi-online machine covering problem on three special uniform machines with the known largest size. Denote by sj the speed of each machine, j = 1, 2, 3. Assume 0 〈 s1 = s2 = r 〈 t = s3, and let s = t/r be the speed ratio. An algorithm with competitive ratio max（2, 3s＋6/s＋6 is presented. We also show the lower bound is at least max（2, 38 3s/s＋6）. For s ≤ 6, the algorithm is an optimal algorithm with the competitive ratio 2. Besides, its overall competitive ratio is 3 which matches the overall lower bound. The algorithm and the lower bound in this paper improve the results of Luo and Sun.

关键词： analysis of algorithms scheduling machine covering semi-online competitive ratio

Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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Computer Modeling in Engineering & sciences 2025年第1期142卷 357-384页

作者： Mohd Anjum Naoufel Kraiem Hong Min Ashit Kumar Dutta Yousef Ibrahim Daradkeh Department of Computer Engineering Aligarh Muslim UniversityAligarh202002India College of Computer science King Khalid UniversityAbha61413Saudi Arabia school of Computing Gachon UniversitySeongnam13120Republic of Korea Department of Computer science and information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Engineering and information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： Computer vision feature selection machine learning region detection texture analysis image classification medical images

An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

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Computer Modeling in Engineering & sciences 2025年第1期142卷 835-867页

作者： Sumaia Mohamed Elhassan Saad Mohamed Darwish Saleh Mesbah Elkaffas Department of information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt College of Computing and information Technology Arab Academy for ScienceTechnology and Maritime TransportAlexandriaP.O.Box 1029Egypt

Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic *** detection of lung tumors significantly increases the chances of successful treatment and ***,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung ***-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate ***,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor *** overcome these disadvantages,dual-model or multi-model approaches can be *** research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of *** automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung ***8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single *** is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to ***,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive *** combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applicati

关键词： Lung cancer detection dual-model deep learning technique data augmentation CNN YOLOv8

Numerical analysis of a Neumann boundary control problem with a stochastic parabolic equation

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science China mathematics 2023年第9期66卷 2133-2156页

作者： Qin Zhou Binjie Li school of mathematics Sichuan UniversityChengdu 610064China school of mathematics&information China West Normal UniversityNanchong 637002China

We analyze the discretization of a Neumann boundary control problem with a stochastic parabolic equation, where additive noise occurs in the Neumann boundary condition. The convergence is established for general filtr... 详细信息

关键词： Neumann boundary control stochastic parabolic equation Q-Wiener process boundary noise discretization convergence