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  • Open Access

    ARTICLE

    Numerical Assessments on Flow Topology and Heat Transfer Behavior in a Round Tube Inserted with Three Sets of V-Ribs

    Amnart Boonloi1, Withada Jedsadaratanachai2,*

    Frontiers in Heat and Mass Transfer, Vol., , DOI:10.32604/fhmt.2023.041547

    Abstract Simulation of fluid-flow topology and thermal behavior in a round tube heat exchanger (RTHX) installed by three V-rib sets is reported. The expected phenomena for the rib installation are the generated vortex flow, impinging flow, greater fluid blending and thermal boundary layer disturbance (TBLD). These phenomena are key causes of the augmentation of heat transfer potentiality and thermal efficiency of the RTHX. Effects of rib height (b1 = 0.05D – 0.25D and b2 = 0.05D – 0.25D), rib pitch or rib spacing (P = D, 1.5D and 2D) and fluid directions (positive x (+x flow direction) and negative x (–x… More >

  • Open Access

    ARTICLE

    Initial steps on the analysis of the underlying pharmacological mechanisms of Wendan decoction on sudden deafness using network pharmacology and molecular docking

    SHIMING YE1,2,#, YUFENG ZHANG3,#, TING LIU4, CONG WANG3, ZHENG YAN5, WANDONG SHE2,*, HAIBING HUA4,*

    BIOCELL, Vol., , DOI:10.32604/biocell.2023.029333

    Abstract Background: Despite its widespread therapeutic use and effectiveness, the underlying pharmacologic mechanisms of Wendan decoction (WDD) and how it works to treat sudden deafness (SD) remain unclear. In this study, the pharmacological mechanisms of WDD underlying SD were analyzed using network pharmacology and molecular docking. Methods: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was employed to identify the active compounds and target genes of WDD, and genes associated with SD were screened on five databases. RGUI conducted Gene Ontology (GO) functional and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A compound-target network was… More >

  • Open Access

    ARTICLE

    Novel Early-Warning Model for Customer Churn of Credit Card Based on GSAIBAS-CatBoost

    Yaling Xu, Congjun Rao*, Xinping Xiao, Fuyan Hu*

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.029023

    Abstract As the banking industry gradually steps into the digital era of Bank 4.0, business competition is becoming increasingly fierce, and banks are also facing the problem of massive customer churn. To better maintain their customer resources, it is crucial for banks to accurately predict customers with a tendency to churn. Aiming at the typical binary classification problem like customer churn, this paper establishes an early-warning model for credit card customer churn. That is a dual search algorithm named GSAIBAS by incorporating Golden Sine Algorithm (GSA) and an Improved Beetle Antennae Search (IBAS) is proposed to optimize the parameters of the… More >

  • Open Access

    ARTICLE

    Modeling and Validation of Base Pressure for Aerodynamic Vehicles Based on Machine Learning Models

    Jaimon Dennis Quadros1, Sher Afghan Khan2, Abdul Aabid3,*, Muneer Baig3

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.028925

    Abstract The application of abruptly enlarged flows to adjust the drag of aerodynamic vehicles using machine learning models has not been investigated previously. The process variables (Mach number (M), nozzle pressure ratio (η), area ratio (α), and length to diameter ratio (γ )) were numerically explored to address several aspects of this process, namely base pressure (β) and base pressure with cavity (βcav). In this work, the optimal base pressure is determined using the PCA-BAS-ENN based algorithm to modify the base pressure presetting accuracy, thereby regulating the base drag required for smooth flow of aerodynamic vehicles. Based on the identical dataset,… More >

  • Open Access

    ARTICLE

    On a New Version of Weibull Model: Statistical Properties, Parameter Estimation and Applications

    Hassan Okasha1,2, Mazen Nassar1,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.028783

    Abstract In this paper, we introduce a new four-parameter version of the traditional Weibull distribution. It is able to provide seven shapes of hazard rate, including constant, decreasing, increasing, unimodal, bathtub, unimodal then bathtub, and bathtub then unimodal shapes. Some basic characteristics of the proposed model are studied, including moments, entropies, mean deviations and order statistics, and its parameters are estimated using the maximum likelihood approach. Based on the asymptotic properties of the estimators, the approximate confidence intervals are also taken into consideration in addition to the point estimators. We examine the effectiveness of the maximum likelihood estimators of the model’s… More >

  • Open Access

    ARTICLE

    Dynamical Analysis of the Stochastic COVID-19 Model Using Piecewise Differential Equation Technique

    Yu-Ming Chu1, Sobia Sultana2, Saima Rashid3,*, Mohammed Shaaf Alharthi4

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.028771

    Abstract Various data sets showing the prevalence of numerous viral diseases have demonstrated that the transmission is not truly homogeneous. Two examples are the spread of Spanish flu and COVID-19. The aim of this research is to develop a comprehensive nonlinear stochastic model having six cohorts relying on ordinary differential equations via piecewise fractional differential operators. Firstly, the strength number of the deterministic case is carried out. Then, for the stochastic model, we show that there is a critical number that can predict virus persistence and infection eradication. Because of the peculiarity of this notion, an interesting way… More >

  • Open Access

    ARTICLE

    Brain Functional Network Generation Using Distribution-Regularized Adversarial Graph Autoencoder with Transformer for Dementia Diagnosis

    Qiankun Zuo1,4, Junhua Hu2, Yudong Zhang3,*, Junren Pan4, Changhong Jing4, Xuhang Chen5, Xiaobo Meng6, Jin Hong7,8,*

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.028732

    Abstract The topological connectivity information derived from the brain functional network can bring new insights for diagnosing and analyzing dementia disorders. The brain functional network is suitable to bridge the correlation between abnormal connectivities and dementia disorders. However, it is challenging to access considerable amounts of brain functional network data, which hinders the widespread application of data-driven models in dementia diagnosis. In this study, a novel distribution-regularized adversarial graph auto-Encoder (DAGAE) with transformer is proposed to generate new fake brain functional networks to augment the brain functional network dataset, improving the dementia diagnosis accuracy of data-driven models. Specifically, the label distribution… More >

  • Open Access

    ARTICLE

    Airfoil Shape Optimisation Using a Multi-Fidelity Surrogate-Assisted Metaheuristic with a New Multi-Objective Infill Sampling Technique

    Cho Mar Aye1, Kittinan Wansaseub2, Sumit Kumar3, Ghanshyam G. Tejani4, Sujin Bureerat1, Ali R. Yildiz5, Nantiwat Pholdee1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.028632

    Abstract This work presents multi-fidelity multi-objective infill-sampling surrogate-assisted optimization for airfoil shape optimization. The optimization problem is posed to maximize the lift and drag coefficient ratio subject to airfoil geometry constraints. Computational Fluid Dynamic (CFD) and XFoil tools are used for high and low-fidelity simulations of the airfoil to find the real objective function value. A special multi-objective sub-optimization problem is proposed for multiple points infill sampling exploration to improve the surrogate model constructed. To validate and further assess the proposed methods, a conventional surrogate-assisted optimization method and an infill sampling surrogate-assisted optimization criterion are applied with multi-fidelity simulation, while their… More >

  • Open Access

    ARTICLE

    Optimization of Engine Control Strategies for Low Fuel Consumption in Heavy-Duty Commercial Vehicles

    Shuilong He1,2, Yang Liu1, Shanchao Wang2,*, Liangying Hu1, Fei Xiao2, Chao Li2

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.028631

    Abstract The reduction of fuel consumption in engines is always considered of vital importance. Along these lines, in this work, this goal was attained by optimizing the heavy-duty commercial vehicle engine control strategy. More specifically, at first, a general first principles model for heavy-duty commercial vehicles and a transient fuel consumption model for heavy-duty commercial vehicles were developed and the parameters were adjusted to fit the empirical data. The accuracy of the proposed model was demonstrated from the stage and the final results. Next, the control optimization problem resulting in low fuel consumption in heavy commercial vehicles was described, with minimal… More >

  • Open Access

    ARTICLE

    Fairness-Aware Harvested Energy Efficiency Algorithm for IRS-Aided Intelligent Sensor Networks with SWIPT

    Yingying Chen1, Weiqiang Tan2, Shidang Li3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.028533

    Abstract In this paper, a novel fairness-aware harvested energy efficiency-based green transmission scheme for wireless information and power transfer (SWIPT) aided sensor networks is developed for active beamforming of multiantenna transmitter and passive beamforming at intelligent reflecting surfaces (IRS). By optimizing the active beamformer assignment at the transmitter in conjunction with the passive beamformer assignment at the IRS, we aim to maximize the minimum harvested energy efficiency among all the energy receivers (ER) where information receivers (IR) are bound to the signal-interference-noise-ratio (SINR) and the maximum transmitted power of the transmitter. To handle the non-convex problem, both semi-definite relaxation (SDR) and… More >

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