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  • Open Access

    ARTICLE

    Forecasting the Academic Performance by Leveraging Educational Data Mining

    Mozamel M. Saeed*

    Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 213-231, 2024, DOI:10.32604/iasc.2024.043020

    Abstract The study aims to recognize how efficiently Educational Data Mining (EDM) integrates into Artificial Intelligence (AI) to develop skills for predicting students’ performance. The study used a survey questionnaire and collected data from 300 undergraduate students of Al Neelain University. The first step’s initial population placements were created using Particle Swarm Optimization (PSO). Then, using adaptive feature space search, Educational Grey Wolf Optimization (EGWO) was employed to choose the optimal attribute combination. The second stage uses the SVM classifier to forecast classification accuracy. Different classifiers were utilized to evaluate the performance of students. According to… More >

  • Open Access

    ARTICLE

    Cardiovascular Disease Prediction Using Risk Factors: A Comparative Performance Analysis of Machine Learning Models

    Adil Hussain1,*, Ayesha Aslam2

    Journal on Artificial Intelligence, Vol.6, pp. 129-152, 2024, DOI:10.32604/jai.2024.050277

    Abstract The diagnosis and prognosis of cardiovascular diseases are critical medical responsibilities that assist cardiologists in correctly classifying patients and treating them accordingly. The utilization of machine learning in the medical domain has witnessed a notable surge due to its ability to discern patterns from vast amounts of data. Machine learning algorithms that can categorize cases of cardiovascular illness may help doctors reduce the number of wrong diagnoses. This research investigates the efficacy of different machine learning algorithms in predicting cardiovascular disease in accordance with risk factors. This study utilizes a variety of machine learning models, More >

  • Open Access

    ARTICLE

    A Comprehensive Investigation on Shear Performance of Improved Perfobond Connector

    Caiping Huang*, Zihan Huang, Wenfeng You

    Structural Durability & Health Monitoring, Vol.18, No.3, pp. 299-320, 2024, DOI:10.32604/sdhm.2024.047850

    Abstract This paper presents an easily installed improved perfobond connector (PBL) designed to reduce the shear concentration of PBL. The improvement of PBL lies in changing the straight penetrating rebar to the Z-type penetrating rebar. To study the shear performance of improved PBL, two PBL test specimens which contain straight penetrating rebar and six improved PBL test specimens which contain Z-type penetrating rebars were designed and fabricated, and push-out tests of these eight test specimens were carried out to investigate and compare the shear behavior of PBL. Additionally, Finite Element Analysis (FEA) models of the PBL… More >

  • Open Access

    ARTICLE

    Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

    Norah Abdullah Al-Johany1,*, Sanaa Abdullah Sharaf1,2, Fathy Elbouraey Eassa1,2, Reem Abdulaziz Alnanih1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3139-3173, 2024, DOI:10.32604/cmc.2024.047392

    Abstract The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed memory systems. However, MPI implementations can contain defects that impact the reliability and performance of parallel applications. Detecting and correcting these defects is crucial, yet there is a lack of published models specifically designed for correcting MPI defects. To address this, we propose a model for detecting and correcting MPI defects (DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blocking point-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defects addressed by… More >

  • Open Access

    ARTICLE

    Research on Performance Optimization of Spark Distributed Computing Platform

    Qinlu He1,*, Fan Zhang1, Genqing Bian1, Weiqi Zhang1, Zhen Li2

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2833-2850, 2024, DOI:10.32604/cmc.2024.046807

    Abstract Spark, a distributed computing platform, has rapidly developed in the field of big data. Its in-memory computing feature reduces disk read overhead and shortens data processing time, making it have broad application prospects in large-scale computing applications such as machine learning and image processing. However, the performance of the Spark platform still needs to be improved. When a large number of tasks are processed simultaneously, Spark’s cache replacement mechanism cannot identify high-value data partitions, resulting in memory resources not being fully utilized and affecting the performance of the Spark platform. To address the problem that… More >

  • Open Access

    ARTICLE

    Analyze the Performance of Electroactive Anticorrosion Coating of Medical Magnesium Alloy Using Deep Learning

    Yashan Feng1, Yafang Tian1, Yongxin Yang1, Yufang Zhang1, Haiwei Guo1, Jing’an Li2,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 263-278, 2024, DOI:10.32604/cmc.2024.047004

    Abstract Electroactive anticorrosion coatings are specialized surface treatments that prevent or minimize corrosion. The study employs strategic thermodynamic equilibrium calculations to pioneer a novel factor in corrosion protection. A first-time proposal, the total acidity (TA) potential of the hydrogen (pH) concept significantly shapes medical magnesium alloys. These coatings are meticulously designed for robust corrosion resistance, blending theoretical insights and practical applications to enhance our grasp of corrosion prevention mechanisms and establish a systematic approach to coating design. The groundbreaking significance of this study lies in its innovative integration of the TA/pH concept, which encompasses the TA/pH… More >

  • Open Access

    ARTICLE

    Multi-Stage Multidisciplinary Design Optimization Method for Enhancing Complete Artillery Internal Ballistic Firing Performance

    Jipeng Xie1,2, Guolai Yang1,*, Liqun Wang1, Lei Li1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 793-819, 2024, DOI:10.32604/cmes.2024.048174

    Abstract To enhance the comprehensive performance of artillery internal ballistics—encompassing power, accuracy, and service life—this study proposed a multi-stage multidisciplinary design optimization (MS-MDO) method. First, the comprehensive artillery internal ballistic dynamics (AIBD) model, based on propellant combustion, rotation band engraving, projectile axial motion, and rifling wear models, was established and validated. This model was systematically decomposed into subsystems from a system engineering perspective. The study then detailed the MS-MDO methodology, which included Stage I (MDO stage) employing an improved collaborative optimization method for consistent design variables, and Stage II (Performance Optimization) focusing on the independent optimization More >

  • Open Access

    ARTICLE

    A Random Fusion of Mix3D and PolarMix to Improve Semantic Segmentation Performance in 3D Lidar Point Cloud

    Bo Liu1,2, Li Feng1,*, Yufeng Chen3

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 845-862, 2024, DOI:10.32604/cmes.2024.047695

    Abstract This paper focuses on the effective utilization of data augmentation techniques for 3D lidar point clouds to enhance the performance of neural network models. These point clouds, which represent spatial information through a collection of 3D coordinates, have found wide-ranging applications. Data augmentation has emerged as a potent solution to the challenges posed by limited labeled data and the need to enhance model generalization capabilities. Much of the existing research is devoted to crafting novel data augmentation methods specifically for 3D lidar point clouds. However, there has been a lack of focus on making the… More >

  • Open Access

    ARTICLE

    Blade Wrap Angle Impact on Centrifugal Pump Performance: Entropy Generation and Fluid-Structure Interaction Analysis

    Hayder Kareem Sakran1,2, Mohd Sharizal Abdul Aziz1,*, Chu Yee Khor3

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 109-137, 2024, DOI:10.32604/cmes.2024.047245

    Abstract The centrifugal pump is a prevalent power equipment widely used in different engineering patterns, and the impeller blade wrap angle significantly impacts its performance. A numerical investigation was conducted to analyze the influence of the blade wrap angle on flow characteristics and energy distribution of a centrifugal pump evaluated as a low specific speed with a value of 69. This study investigates six impeller models that possess varying blade wrap angles (95°, 105°, 115°, 125°, 135°, and 145°) that were created while maintaining the same volute and other geometrical characteristics. The investigation of energy loss… More > Graphic Abstract

    Blade Wrap Angle Impact on Centrifugal Pump Performance: Entropy Generation and Fluid-Structure Interaction Analysis

  • Open Access

    ARTICLE

    Effect of Synthesis Parameters on Phosphoric Acid Doped Polybenzimidazole Membranes: A Parametric Evaluation from Microstructural Level to Fuel Cell Performance

    ÇAĞLA GÜL GÜLDİKEN, LEVENT AKYALÇIN, HASAN FERDİ GERÇEL*

    Journal of Polymer Materials, Vol.36, No.4, pp. 337-349, 2019, DOI:10.32381/JPM.2019.36.04.4

    Abstract In the present study, polybenzimidazole (PBI) polymer which has a great importance in polymer electrolyte membrane (PEM) research was synthesized via the solution polycondensation method, under various synthesis conditions to put forward the effect of the synthesis parameters on the properties of the synthesized polymer and consequently to the quality of the prepared polymer electrolyte membrane. The synthesized polymers were characterized in terms of their chemical structure, thermal degradation behaviour, and molecular weight by Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance spectroscopy (1 H NMR), thermogravimetric analysis (TGA). The Mechanical properties, acid-doping level capacity, proton More >

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