Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (935)
  • Open Access

    ARTICLE

    Computational Investigation of Brownian Motion and Thermophoresis Effect on Blood-Based Casson Nanofluid on a Non-linearly Stretching Sheet with Ohmic and Viscous Dissipation Effects

    Haris Alam Zuberi1, Madan Lal1, Shivangi Verma1, Nurul Amira Zainal2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1137-1163, 2024, DOI:10.32604/cmes.2024.055493

    Abstract Motivated by the widespread applications of nanofluids, a nanofluid model is proposed which focuses on uniform magnetohydrodynamic (MHD) boundary layer flow over a non-linear stretching sheet, incorporating the Casson model for blood-based nanofluid while accounting for viscous and Ohmic dissipation effects under the cases of Constant Surface Temperature (CST) and Prescribed Surface Temperature (PST). The study employs a two-phase model for the nanofluid, coupled with thermophoresis and Brownian motion, to analyze the effects of key fluid parameters such as thermophoresis, Brownian motion, slip velocity, Schmidt number, Eckert number, magnetic parameter, and non-linear stretching parameter on… More > Graphic Abstract

    Computational Investigation of Brownian Motion and Thermophoresis Effect on Blood-Based Casson Nanofluid on a Non-linearly Stretching Sheet with Ohmic and Viscous Dissipation Effects

  • Open Access

    ARTICLE

    Far and Near Optimization: A New Simple and Effective Metaphor-Less Optimization Algorithm for Solving Engineering Applications

    Tareq Hamadneh1,2, Khalid Kaabneh3, Omar Alssayed4, Kei Eguchi5,*, Zeinab Monrazeri6, Mohammad Dehghani6

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1725-1808, 2024, DOI:10.32604/cmes.2024.053236

    Abstract In this article, a novel metaheuristic technique named Far and Near Optimization (FNO) is introduced, offering versatile applications across various scientific domains for optimization tasks. The core concept behind FNO lies in integrating global and local search methodologies to update the algorithm population within the problem-solving space based on moving each member to the farthest and nearest member to itself. The paper delineates the theory of FNO, presenting a mathematical model in two phases: (i) exploration based on the simulation of the movement of a population member towards the farthest member from itself and (ii)… More >

  • Open Access

    ARTICLE

    Importance-Weighted Transfer Learning for Fault Classification under Covariate Shift

    Yi Pan1, Lei Xie2,*, Hongye Su2

    Intelligent Automation & Soft Computing, Vol.39, No.4, pp. 683-696, 2024, DOI:10.32604/iasc.2023.038543

    Abstract In the process of fault detection and classification, the operation mode usually drifts over time, which brings great challenges to the algorithms. Because traditional machine learning based fault classification cannot dynamically update the trained model according to the probability distribution of the testing dataset, the accuracy of these traditional methods usually drops significantly in the case of covariate shift. In this paper, an importance-weighted transfer learning method is proposed for fault classification in the nonlinear multi-mode industrial process. It effectively alters the drift between the training and testing dataset. Firstly, the mutual information method is… More >

  • Open Access

    ARTICLE

    Numerical Study of Temperature-Dependent Viscosity and Thermal Conductivity of Micropolar Ag–MgO Hybrid Nanofluid over a Rotating Vertical Cone

    Mekonnen S. Ayano1,*, Thokozani N. Khumalo1, Stephen T. Sikwila2, Stanford Shateyi3

    Frontiers in Heat and Mass Transfer, Vol.22, No.4, pp. 1153-1169, 2024, DOI:10.32604/fhmt.2024.048474

    Abstract The present paper examines the temperature-dependent viscosity and thermal conductivity of a micropolar silver ()−Magnesium oxide () hybrid nanofluid made of silver and magnesium oxide over a rotating vertical cone, with the influence of transverse magnetic field and thermal radiation. The physical flow problem has been modeled with coupled partial differential equations. We apply similarity transformations to the non-dimensionalized equations, and the resulting nonlinear differential equations are solved using overlapping grid multidomain spectral quasilinearization method. The flow behavior for the fluid is scrutinized under the impact of diverse physical constraints, which are illustrated graphically. The More >

  • Open Access

    ARTICLE

    Analysis of Extended Fisher-Kolmogorov Equation in 2D Utilizing the Generalized Finite Difference Method with Supplementary Nodes

    Bingrui Ju1,2, Wenxiang Sun2, Wenzhen Qu1,2,*, Yan Gu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 267-280, 2024, DOI:10.32604/cmes.2024.052159

    Abstract In this study, we propose an efficient numerical framework to attain the solution of the extended Fisher-Kolmogorov (EFK) problem. The temporal derivative in the EFK equation is approximated by utilizing the Crank-Nicolson scheme. Following temporal discretization, the generalized finite difference method (GFDM) with supplementary nodes is utilized to address the nonlinear boundary value problems at each time node. These supplementary nodes are distributed along the boundary to match the number of boundary nodes. By incorporating supplementary nodes, the resulting nonlinear algebraic equations can effectively satisfy the governing equation and boundary conditions of the EFK equation. More >

  • Open Access

    ARTICLE

    Fine-Tuning Cyber Security Defenses: Evaluating Supervised Machine Learning Classifiers for Windows Malware Detection

    Islam Zada1,*, Mohammed Naif Alatawi2, Syed Muhammad Saqlain1, Abdullah Alshahrani3, Adel Alshamran4, Kanwal Imran5, Hessa Alfraihi6

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2917-2939, 2024, DOI:10.32604/cmc.2024.052835

    Abstract Malware attacks on Windows machines pose significant cybersecurity threats, necessitating effective detection and prevention mechanisms. Supervised machine learning classifiers have emerged as promising tools for malware detection. However, there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware detection. Addressing this gap can provide valuable insights for enhancing cybersecurity strategies. While numerous studies have explored malware detection using machine learning techniques, there is a lack of systematic comparison of supervised classifiers for Windows malware detection. Understanding the relative effectiveness of these classifiers can inform the selection of… More >

  • Open Access

    ARTICLE

    Research on Improved MobileViT Image Tamper Localization Model

    Jingtao Sun1,2, Fengling Zhang1,2,*, Huanqi Liu1,2, Wenyan Hou1,2

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3173-3192, 2024, DOI:10.32604/cmc.2024.051705

    Abstract As image manipulation technology advances rapidly, the malicious use of image tampering has alarmingly escalated, posing a significant threat to social stability. In the realm of image tampering localization, accurately localizing limited samples, multiple types, and various sizes of regions remains a multitude of challenges. These issues impede the model’s universality and generalization capability and detrimentally affect its performance. To tackle these issues, we propose FL-MobileViT-an improved MobileViT model devised for image tampering localization. Our proposed model utilizes a dual-stream architecture that independently processes the RGB and noise domain, and captures richer traces of tampering… More >

  • Open Access

    ARTICLE

    Exploring Capillary Fringe Flow: Quasilinear Modeling with Kirchhoff Transforms and Gardner Model

    Rachid Karra1,*, Abdelatif Maslouhi2

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1611-1631, 2024, DOI:10.32604/fdmp.2024.048447

    Abstract Recent studies have underscored the significance of the capillary fringe in hydrological and biochemical processes. Moreover, its role in shallow waters is expected to be considerable. Traditionally, the study of groundwater flow has centered on unsaturated-saturated zones, often overlooking the impact of the capillary fringe. In this study, we introduce a steady-state two-dimensional model that integrates the capillary fringe into a 2-D numerical solution. Our novel approach employs the potential form of the Richards equation, facilitating the determination of boundaries, pressures, and velocities across different ground surface zones. We utilized a two-dimensional Freefem++ finite element model… More >

  • Open Access

    ARTICLE

    Analysis of the Influence of Oxygen Enrichment in the Blast on Temperature Field and NO Generation near the Burner in Reheating Furnace

    Xiaojun Li, Fuyong Su*

    Frontiers in Heat and Mass Transfer, Vol.22, No.3, pp. 719-732, 2024, DOI:10.32604/fhmt.2024.051950

    Abstract In order to study the effect of oxygen-enriched combustion technology on the temperature field and NO emission in the continuous heating furnace, this paper studies the oxygen-enriched combustion of a pushing steel continuous heating furnace in a domestic company. This study utilizes numerical simulation method, establishes the mathematical models of flow, combustion and NO generation combustion process in the furnace and analyzes the heat transfer process and NO generation in the furnace under different air oxygen content and different wind ratio. The research results show that with the increase of oxygen content in the air, More > Graphic Abstract

    Analysis of the Influence of Oxygen Enrichment in the Blast on Temperature Field and NO Generation near the Burner in Reheating Furnace

  • Open Access

    ARTICLE

    Bayesian and Non-Bayesian Analysis for the Sine Generalized Linear Exponential Model under Progressively Censored Data

    Naif Alotaibi1, A. S. Al-Moisheer2, Ibrahim Elbatal1, Mohammed Elgarhy3,4, Ehab M. Almetwally1,5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2795-2823, 2024, DOI:10.32604/cmes.2024.049188

    Abstract This article introduces a novel variant of the generalized linear exponential (GLE) distribution, known as the sine generalized linear exponential (SGLE) distribution. The SGLE distribution utilizes the sine transformation to enhance its capabilities. The updated distribution is very adaptable and may be efficiently used in the modeling of survival data and dependability issues. The suggested model incorporates a hazard rate function (HRF) that may display a rising, J-shaped, or bathtub form, depending on its unique characteristics. This model includes many well-known lifespan distributions as separate sub-models. The suggested model is accompanied with a range of More >

Displaying 1-10 on page 1 of 935. Per Page