Thaer Thaher^1,*, Majdi Mafarja², Muhammed Saffarini³, Abdul Hakim H. M. Mohamed⁴, Ayman A. El-Saleh⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2615-2673, 2025, DOI:10.32604/cmes.2025.064857 - 30 June 2025

Abstract Detecting faces under occlusion remains a significant challenge in computer vision due to variations caused by masks, sunglasses, and other obstructions. Addressing this issue is crucial for applications such as surveillance, biometric authentication, and human-computer interaction. This paper provides a comprehensive review of face detection techniques developed to handle occluded faces. Studies are categorized into four main approaches: feature-based, machine learning-based, deep learning-based, and hybrid methods. We analyzed state-of-the-art studies within each category, examining their methodologies, strengths, and limitations based on widely used benchmark datasets, highlighting their adaptability to partial and severe occlusions. The review… More >

Mohammed Alshahrani¹, Mohammed Al-Jabbar^1,*, Ebrahim Mohammed Senan^2,3, Fatima Ali Amer jid Almahri⁴, Sultan Ahmed Almalki¹, Eman A. Alshari^3,5

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3639-3675, 2025, DOI:10.32604/cmes.2025.064668 - 30 June 2025

Abstract Multiple Sclerosis (MS) poses significant health risks. Patients may face neurodegeneration, mobility issues, cognitive decline, and a reduced quality of life. Manual diagnosis by neurologists is prone to limitations, making AI-based classification crucial for early detection. Therefore, automated classification using Artificial Intelligence (AI) techniques has a crucial role in addressing the limitations of manual classification and preventing the development of MS to advanced stages. This study developed hybrid systems integrating XGBoost (eXtreme Gradient Boosting) with multi-CNN (Convolutional Neural Networks) features based on Ant Colony Optimization (ACO) and Maximum Entropy Score-based Selection (MESbS) algorithms for early… More >

Jungpil Shin^1,*, Md. Al Mehedi Hasan², Md. Maniruzzaman³, Satoshi Nishimura¹, Sultan Alfarhood⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3615-3638, 2025, DOI:10.32604/cmes.2025.064588 - 30 June 2025

Abstract Activity recognition is a challenging topic in the field of computer vision that has various applications, including surveillance systems, industrial automation, and human-computer interaction. Today, the demand for automation has greatly increased across industries worldwide. Real-time detection requires edge devices with limited computational time. This study proposes a novel hybrid deep learning system for human activity recognition (HAR), aiming to enhance the recognition accuracy and reduce the computational time. The proposed system combines a pre-trained image classification model with a sequence analysis model. First, the dataset was divided into a training set (70%), validation set… More > Graphic Abstract

Sergio Cassese¹, Riccardo Guida^2,3,*, Daniele Trincone¹, Stefano Mungiguerra¹, Raffaele Savino¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.6, pp. 1299-1337, 2025, DOI:10.32604/fdmp.2025.065605 - 30 June 2025

Abstract Robust numerical tools are essential for enabling the use of hybrid rocket engines (HREs) in future space applications. In this context, Computational Fluid Dynamics (CFD) transient simulations can be employed to analyse and predict relevant fluid dynamics phenomena within the thrust chamber of small-scale HREs. This work applies such techniques to investigate two unexpected behaviours observed in a 10 N-class hydrogen peroxide-based hybrid thruster: an uneven regression rate during High-Density Polyethylene (HDPE) and Acrylonitrile Butadiene Styrene (ABS) fuel tests, and non-negligible axial consumption in the ABS test case. The present study seeks to identify their… More >

Ans Ahmed Memon¹, Laveet Kumar^1,2,*, Abdul Ghafoor Memon¹, Khanji Harijan¹, Ahmad K. Sleiti²

Frontiers in Heat and Mass Transfer, Vol.23, No.3, pp. 833-856, 2025, DOI:10.32604/fhmt.2025.064805 - 30 June 2025

Abstract Climate change, rising fuel prices, and fuel security are some challenges that have emerged and have grown worldwide. Therefore, to overcome these obstacles, highly efficient thermodynamic devices and heat recovery systems must be introduced. According to reports, much industrial waste heat is lost as flue gas from boilers, heating plants, etc. The primary objective of this study is to investigate and compare unary (Al₂O₃) thermodynamically, binary with three different combinations of nanoparticles namely (Al₂O₃ + TiO₂, TiO₂ + ZnO, Al₂O₃ + ZnO) and ternary (Al₂O₃ + TiO₂ + ZnO) as a heat transfer fluid. Initially, three different types of… More > Graphic Abstract

Shamim Ara Bagum¹, Mahbub Ul Islam², M Shalim Uddin^2,*, Sripati Sikder³, Ahmed Gaber⁴, Akbar Hossain^5,*

Phyton-International Journal of Experimental Botany, Vol.94, No.6, pp. 1897-1919, 2025, DOI:10.32604/phyton.2025.065607 - 27 June 2025

Abstract The yield of maize (Zea mays L.) is highly influenced by nitrogen fertilization. This study investigated the impact of nitrogen fertilization on morphophysiological traits in maize (Zea mays L.) and developed algorithms to relate manual phenotyping and digital phenotyping of maize with leaf nitrogen and digital field image traits. The experiment included three hybrid maize varieties, V1 (Hybrid 981), V2 (BARI Hybrid maize-9), and V3 (Hybrid P3396), which were evaluated across three nitrogen levels (N1 = 100 kg N ha⁻¹, N2 = 200 kg N ha⁻¹, N3 = 300 kg N ha⁻¹) in a split-plot design with three replications.… More >

Ibrahim T. Teke^1,2, Ahmet H. Ertas^2,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 243-264, 2025, DOI:10.32604/cmc.2025.066086 - 09 June 2025

Abstract This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting, runner system optimization, and structural analysis to significantly enhance the performance of injection-molded parts. At its core, the framework employs a greedy algorithm that generates runner systems based on adjacency and shortest path principles, leading to improvements in both mechanical strength and material efficiency. The design optimization is validated through a series of rigorous experimental tests, including three-point bending and torsion tests performed on key-socket frames, ensuring that the optimized designs meet practical performance requirements. A critical innovation of… More >

Salman A. Khan^1,*, Mohamed Mohandes^2,3, Shafiqur Rehman³, Ali Al-Shaikhi^2,4, Kashif Iqbal¹

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 553-581, 2025, DOI:10.32604/cmc.2025.064560 - 09 June 2025

Abstract Wind energy has emerged as a potential replacement for fossil fuel-based energy sources. To harness maximum wind energy, a crucial decision in the development of an efficient wind farm is the optimal layout design. This layout defines the specific locations of the turbines within the wind farm. The process of finding the optimal locations of turbines, in the presence of various technical and technological constraints, makes the wind farm layout design problem a complex optimization problem. This problem has traditionally been solved with nature-inspired algorithms with promising results. The performance and convergence of nature-inspired algorithms… More >

Junbin He^1,2, Wuxia Zhang³, Xianyi Liu¹, Jinping Liu^2,*, Guangyi Yang⁴

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1227-1252, 2025, DOI:10.32604/cmc.2025.064402 - 09 June 2025

Abstract The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System (ICPS), enhancing intelligence and autonomy. However, this transition also expands the attack surface, introducing critical security vulnerabilities. To address these challenges, this article proposes a hybrid intrusion detection scheme for securing ICPSs that combines system state anomaly and network traffic anomaly detection. Specifically, an improved variation-Bayesian-based noise covariance-adaptive nonlinear Kalman filtering (IVB-NCA-NLKF) method is developed to model nonlinear system dynamics, enabling optimal state estimation in multi-sensor ICPS environments. Intrusions within the physical sensing system are identified by More >

Tehreem Fatima¹, Kewen Xia^1,*, Wenbiao Yang², Qurat Ul Ain¹, Poornima Lankani Perera¹

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 811-826, 2025, DOI:10.32604/cmc.2025.063686 - 09 June 2025

Abstract The rising prevalence of diabetes in modern society underscores the urgent need for precise and efficient diagnostic tools to support early intervention and treatment. However, the inherent limitations of existing datasets, including significant class imbalances and inadequate sample diversity, pose challenges to the accurate prediction and classification of diabetes. Addressing these issues, this study proposes an innovative diabetes prediction framework that integrates a hybrid Convolutional Neural Network-Bidirectional Gated Recurrent Unit (CNN-BiGRU) model for classification with Adaptive Synthetic Sampling (ADASYN) for data augmentation. ADASYN was employed to generate synthetic yet representative data samples, effectively mitigating class… More >