Shaha Al-Otaibi¹, Rahim Khan^2,*, Hashim Ali², Aftab Ahmed Khan², Amir Saeed³, Jehad Ali^4,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3805-3823, 2024, DOI:10.32604/cmc.2024.049017

Abstract The Internet of Things (IoT) is a smart networking infrastructure of physical devices, i.e., things, that are embedded with sensors, actuators, software, and other technologies, to connect and share data with the respective server module. Although IoTs are cornerstones in different application domains, the device’s authenticity, i.e., of server(s) and ordinary devices, is the most crucial issue and must be resolved on a priority basis. Therefore, various field-proven methodologies were presented to streamline the verification process of the communicating devices; however, location-aware authentication has not been reported as per our knowledge, which is a crucial metric, especially in scenarios where… More >

Shu-Chuan Chu¹, Xiaomeng Yang¹, Li Zhang², Václav Snášel³, Jeng-Shyang Pan^1,4,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3763-3786, 2024, DOI:10.32604/cmc.2024.048594

Abstract The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance; however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of… More >

Changfeng Feng¹, Chunping Wang², Dongdong Zhang¹, Renke Kou¹, Qiang Fu^1,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3993-4013, 2024, DOI:10.32604/cmc.2024.048351

Abstract Transformer-based models have facilitated significant advances in object detection. However, their extensive computational consumption and suboptimal detection of dense small objects curtail their applicability in unmanned aerial vehicle (UAV) imagery. Addressing these limitations, we propose a hybrid transformer-based detector, H-DETR, and enhance it for dense small objects, leading to an accurate and efficient model. Firstly, we introduce a hybrid transformer encoder, which integrates a convolutional neural network-based cross-scale fusion module with the original encoder to handle multi-scale feature sequences more efficiently. Furthermore, we propose two novel strategies to enhance detection performance without incurring additional inference computation. Query filter is designed… More >

K. B. Ajeyprasaath, P. Vetrivelan^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3195-3213, 2024, DOI:10.32604/cmc.2023.046911

Abstract Video streaming applications have grown considerably in recent years. As a result, this becomes one of the most significant contributors to global internet traffic. According to recent studies, the telecommunications industry loses millions of dollars due to poor video Quality of Experience (QoE) for users. Among the standard proposals for standardizing the quality of video streaming over internet service providers (ISPs) is the Mean Opinion Score (MOS). However, the accurate finding of QoE by MOS is subjective and laborious, and it varies depending on the user. A fully automated data analytics framework is required to reduce the inter-operator variability characteristic… More >

Rahul Gupta¹, Kapil Sharma^1,*, R. K. Garg²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4283-4301, 2024, DOI:10.32604/cmc.2024.046890

Abstract The prevalence of smartphones is deeply embedded in modern society, impacting various aspects of our lives. Their versatility and functionalities have fundamentally changed how we communicate, work, seek entertainment, and access information. Among the many smartphones available, those operating on the Android platform dominate, being the most widely used type. This widespread adoption of the Android OS has significantly contributed to increased malware attacks targeting the Android ecosystem in recent years. Therefore, there is an urgent need to develop new methods for detecting Android malware. The literature contains numerous works related to Android malware detection. As far as our understanding… More >

Rashmi Sharma¹, Ashok Pal¹, Nitin Mittal², Lalit Kumar², Sreypov Van³, Yunyoung Nam^3,*, Mohamed Abouhawwash^4,5

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3489-3510, 2024, DOI:10.32604/cmc.2024.046606

Abstract This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm (MOALO) which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm (ALO) and the Genetic Algorithm (GA). MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions. The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO. A first-time hybrid of these algorithms is employed to solve… More >

Haitao Liu^1,2,*, Jiaming Wang¹, Xiuliang Zhang¹, Yanji Jiang², Qian Xiao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2747-2772, 2024, DOI:10.32604/cmes.2024.047129

Abstract The expansion chamber serves as the primary silencing structure within the exhaust pipeline. However, it can also act as a sound-emitting structure when subjected to airflow. This article presents a hybrid method for numerically simulating and analyzing the unsteady flow and aerodynamic noise in an expansion chamber under the influence of airflow. A fluid simulation model is established, utilizing the Large Eddy Simulation (LES) method to calculate the unsteady flow within the expansion chamber. The simulation results effectively capture the development and changes of the unsteady flow and vorticity inside the cavity, exhibiting a high level of consistency with experimental… More > Graphic Abstract

Muhammad Shoaib Arif^1,2,*, Kamaleldin Abodayeh¹, Yasir Nawaz²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3417-3434, 2024, DOI:10.32604/cmes.2024.046944

Abstract This study focuses on the urgent requirement for improved accuracy in disease modeling by introducing a new computational framework called the Hybrid SIR-Fuzzy Model. By integrating the traditional Susceptible-Infectious-Recovered (SIR) model with fuzzy logic, our method effectively addresses the complex nature of epidemic dynamics by accurately accounting for uncertainties and imprecisions in both data and model parameters. The main aim of this research is to provide a model for disease transmission using fuzzy theory, which can successfully address uncertainty in mathematical modeling. Our main emphasis is on the imprecise transmission rate parameter, utilizing a three-part description of its membership level.… More >

S. Jayanthi^*, S. Prasanna Devi

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2137-2158, 2024, DOI:10.32604/cmc.2024.045975

Abstract In healthcare, the persistent challenge of arrhythmias, a leading cause of global mortality, has sparked extensive research into the automation of detection using machine learning (ML) algorithms. However, traditional ML and AutoML approaches have revealed their limitations, notably regarding feature generalization and automation efficiency. This glaring research gap has motivated the development of AutoRhythmAI, an innovative solution that integrates both machine and deep learning to revolutionize the diagnosis of arrhythmias. Our approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection, effectively bridging the gap between data preprocessing and model selection. To validate our system, we have rigorously… More >

Yixuan Yu, Yulin Wang^*, Qingcheng Li, Bowen Jiao

Energy Engineering, Vol.121, No.3, pp. 769-788, 2024, DOI:10.32604/ee.2023.044042

Abstract The plug-in hybrid vehicles (PHEV) technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks. Meanwhile, plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies (EMS). Therefore, a series hybrid system is constructed based on a 100-ton mining dump truck in this paper. And inspired by the dynamic programming (DP) algorithm, a predictive equivalent consumption minimization strategy (P-ECMS) based on the DP optimization result is proposed. Based on the optimal control manifold and the SOC reference trajectory obtained by the DP algorithm, the P-ECMS strategy… More >