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  • Open Access

    ARTICLE

    Generalized nth-Order Perturbation Method Based on Loop Subdivision Surface Boundary Element Method for Three-Dimensional Broadband Structural Acoustic Uncertainty Analysis

    Ruijin Huo1,2,3, Qingxiang Pei1,2,3, Xiaohui Yuan1,*, Yanming Xu3

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.049185

    Abstract In this paper, a generalized th-order perturbation method based on the isogeometric boundary element method is proposed for the uncertainty analysis of broadband structural acoustic scattering problems. The Burton-Miller method is employed to solve the problem of non-unique solutions that may be encountered in the external acoustic field, and the th-order discretization formulation of the boundary integral equation is derived. In addition, the computation of loop subdivision surfaces and the subdivision rules are introduced. In order to confirm the effectiveness of the algorithm, the computed results are contrasted and analyzed with the results under Monte Carlo simulations (MCs) through several… More >

  • Open Access

    REVIEW

    A Review of Hybrid Cyber Threats Modelling and Detection Using Artificial Intelligence in IIoT

    Yifan Liu1, Shancang Li1,*, Xinheng Wang2, Li Xu3

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.046473

    Abstract The Industrial Internet of Things (IIoT) has brought numerous benefits, such as improved efficiency, smart analytics, and increased automation. However, it also exposes connected devices, users, applications, and data generated to cyber security threats that need to be addressed. This work investigates hybrid cyber threats (HCTs), which are now working on an entirely new level with the increasingly adopted IIoT. This work focuses on emerging methods to model, detect, and defend against hybrid cyber attacks using machine learning (ML) techniques. Specifically, a novel ML-based HCT modelling and analysis framework was proposed, in which regularisation and Random Forest were used to… More >

  • Open Access

    REVIEW

    Towards Blockchain-Based Secure BGP Routing, Challenges and Future Research Directions

    Qiong Yang1, Li Ma1,2,*, Shanshan Tu1, Sami Ullah3, Muhammad Waqas4,5, Hisham Alasmary6

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049970

    Abstract Border Gateway Protocol (BGP) is a standard inter-domain routing protocol for the Internet that conveys network layer reachability information and establishes routes to different destinations. The BGP protocol exhibits security design defects, such as an unconditional trust mechanism and the default acceptance of BGP route announcements from peers by BGP neighboring nodes, easily triggering prefix hijacking, path forgery, route leakage, and other BGP security threats. Meanwhile, the traditional BGP security mechanism, relying on a public key infrastructure, faces issues like a single point of failure and a single point of trust. The decentralization, anti-tampering, and traceability advantages of blockchain offer… More >

  • Open Access

    REVIEW

    Federated Learning on Internet of Things: Extensive and Systematic Review

    Meenakshi Aggarwal1, Vikas Khullar1, Sunita Rani2, Thomas André Prola3,4,5, Shyama Barna Bhattacharjee6, Sarowar Morshed Shawon7, Nitin Goyal8,*

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049846

    Abstract The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data generation. However, FL development for IoT is still in its infancy and needs to be explored in various areas to understand the key challenges for deployment in real-world scenarios. The paper systematically reviewed the available literature using the PRISMA guiding principle. The study aims to provide a detailed overview of the increasing use of FL in IoT networks, including the architecture and challenges. A systematic review approach is used to collect, categorize and analyze FL-IoT-based articles. A search was performed in… More >

  • Open Access

    ARTICLE

    Appropriate Combination of Crossover Operator and Mutation Operator in Genetic Algorithms for the Travelling Salesman Problem

    Zakir Hussain Ahmed1,*, Habibollah Haron2, Abdullah Al-Tameem3

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049704

    Abstract Genetic algorithms (GAs) are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems. A simple GA begins with a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes. It uses a crossover operator to create better offspring chromosomes and thus, converges the population. Also, it uses a mutation operator to explore the unexplored areas by the crossover operator, and thus, diversifies the GA search space. A combination of crossover and mutation operators makes the GA search strong… More >

  • Open Access

    ARTICLE

    CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

    Mahmood Ul Haq1, Muhammad Athar Javed Sethi1, Najib Ben Aoun2,3, Ala Saleh Alluhaidan4,*, Sadique Ahmad5,6, Zahid farid7

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049645

    Abstract Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security, authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neural networks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since they do not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networks as a more robust design capable of retaining pose information and spatial correlations to recognize objects more like the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, and so on, which are routed to higher-level capsules via… More >

  • Open Access

    ARTICLE

    CMAES-WFD: Adversarial Website Fingerprinting Defense Based on Covariance Matrix Adaptation Evolution Strategy

    Di Wang, Yuefei Zhu, Jinlong Fei*, Maohua Guo

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049504

    Abstract Website fingerprinting, also known as WF, is a traffic analysis attack that enables local eavesdroppers to infer a user’s browsing destination, even when using the Tor anonymity network. While advanced attacks based on deep neural network (DNN) can perform feature engineering and attain accuracy rates of over 98%, research has demonstrated that DNN is vulnerable to adversarial samples. As a result, many researchers have explored using adversarial samples as a defense mechanism against DNN-based WF attacks and have achieved considerable success. However, these methods suffer from high bandwidth overhead or require access to the target model, which is unrealistic. This… More >

  • Open Access

    ARTICLE

    Model Agnostic Meta-Learning (MAML)-Based Ensemble Model for Accurate Detection of Wheat Diseases Using Vision Transformer and Graph Neural Networks

    Yasir Maqsood1, Syed Muhammad Usman1,*, Musaed Alhussein2, Khursheed Aurangzeb2,*, Shehzad Khalid3, Muhammad Zubair4

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049410

    Abstract Wheat is a critical crop, extensively consumed worldwide, and its production enhancement is essential to meet escalating demand. The presence of diseases like stem rust, leaf rust, yellow rust, and tan spot significantly diminishes wheat yield, making the early and precise identification of these diseases vital for effective disease management. With advancements in deep learning algorithms, researchers have proposed many methods for the automated detection of disease pathogens; however, accurately detecting multiple disease pathogens simultaneously remains a challenge. This challenge arises due to the scarcity of RGB images for multiple diseases, class imbalance in existing public datasets, and the difficulty… More >

  • Open Access

    ARTICLE

    Blood Pressure Estimation with Phonocardiogram on CNN-Based Approach

    Kasidit Kokkhunthod1, Khomdet Phapatanaburi2, Wongsathon Pathonsuwan1, Talit Jumphoo1, Patikorn Anchuen3, Porntip Nimkuntod4, Monthippa Uthansakul1, Peerapong Uthansakul1,*

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049276

    Abstract Monitoring blood pressure is a critical aspect of safeguarding an individual’s health, as early detection of abnormal blood pressure levels facilitates timely medical intervention, ultimately leading to a reduction in mortality rates associated with cardiovascular diseases. Consequently, the development of a robust and continuous blood pressure monitoring system holds paramount significance. In the context of this research paper, we introduce an innovative deep learning regression model that harnesses phonocardiogram (PCG) data to achieve precise blood pressure estimation. Our novel approach incorporates a convolutional neural network (CNN)-based regression model, which not only enhances its adaptability to spatial variations but also empowers… 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., , 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 the DC_MPI model include illegal… More >

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