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  • Open Access

    ARTICLE

    WebFLex: A Framework for Web Browsers-Based Peer-to-Peer Federated Learning Systems Using WebRTC

    Mai Alzamel1,*, Hamza Ali Rizvi2, Najwa Altwaijry1, Isra Al-Turaiki1

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4177-4204, 2024, DOI:10.32604/cmc.2024.048370

    Abstract Scalability and information personal privacy are vital for training and deploying large-scale deep learning models. Federated learning trains models on exclusive information by aggregating weights from various devices and taking advantage of the device-agnostic environment of web browsers. Nevertheless, relying on a main central server for internet browser-based federated systems can prohibit scalability and interfere with the training process as a result of growing client numbers. Additionally, information relating to the training dataset can possibly be extracted from the distributed weights, potentially reducing the privacy of the local data used for training. In this research paper, we aim to investigate… More >

  • Open Access

    ARTICLE

    Computation Tree Logic Model Checking of Multi-Agent Systems Based on Fuzzy Epistemic Interpreted Systems

    Xia Li1, Zhanyou Ma1,*, Zhibao Mian2, Ziyuan Liu1, Ruiqi Huang1, Nana He1

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4129-4152, 2024, DOI:10.32604/cmc.2024.047168

    Abstract Model checking is an automated formal verification method to verify whether epistemic multi-agent systems adhere to property specifications. Although there is an extensive literature on qualitative properties such as safety and liveness, there is still a lack of quantitative and uncertain property verifications for these systems. In uncertain environments, agents must make judicious decisions based on subjective epistemic. To verify epistemic and measurable properties in multi-agent systems, this paper extends fuzzy computation tree logic by introducing epistemic modalities and proposing a new Fuzzy Computation Tree Logic of Knowledge (FCTLK). We represent fuzzy multi-agent systems as distributed knowledge bases with fuzzy… More >

  • Open Access

    ARTICLE

    Machine-Learning Based Packet Switching Method for Providing Stable High-Quality Video Streaming in Multi-Stream Transmission

    Yumin Jo1, Jongho Paik2,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4153-4176, 2024, DOI:10.32604/cmc.2024.047046

    Abstract Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream. However, when the transmission environment is unstable, problems such as reduction in the lifespan of equipment due to frequent switching and interruption, delay, and stoppage of services may occur. Therefore, applying a machine learning (ML) method, which is possible to automatically judge and classify network-related service anomaly, and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as… More >

  • Open Access

    ARTICLE

    Adaptation of Federated Explainable Artificial Intelligence for Efficient and Secure E-Healthcare Systems

    Rabia Abid1, Muhammad Rizwan2, Abdulatif Alabdulatif3,*, Abdullah Alnajim4, Meznah Alamro5, Mourade Azrour6

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3413-3429, 2024, DOI:10.32604/cmc.2024.046880

    Abstract Explainable Artificial Intelligence (XAI) has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning (ML) and Deep Learning (DL) based algorithms. In this paper, we chose e-healthcare systems for efficient decision-making and data classification, especially in data security, data handling, diagnostics, laboratories, and decision-making. Federated Machine Learning (FML) is a new and advanced technology that helps to maintain privacy for Personal Health Records (PHR) and handle a large amount of medical data effectively. In this context, XAI, along with FML, increases efficiency and improves the security of e-healthcare systems. The… More >

  • Open Access

    ARTICLE

    MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

    Rashmi Sharma1, Ashok Pal1, Nitin Mittal2, Lalit Kumar2, Sreypov Van3, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    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 >

  • Open Access

    ARTICLE

    CL2ES-KDBC: A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

    Talal Albalawi, P. Ganeshkumar*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3511-3528, 2024, DOI:10.32604/cmc.2024.046396

    Abstract The Internet of Things (IoT) is a growing technology that allows the sharing of data with other devices across wireless networks. Specifically, IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks. In this framework, a Covariance Linear Learning Embedding Selection (CL2ES) methodology is used at first to extract the features highly associated with the IoT intrusions. Then, the Kernel Distributed Bayes Classifier (KDBC) is created to forecast attacks based on the probability distribution value precisely. In addition, a… More >

  • Open Access

    ARTICLE

    A Health State Prediction Model Based on Belief Rule Base and LSTM for Complex Systems

    Yu Zhao, Zhijie Zhou*, Hongdong Fan, Xiaoxia Han, Jie Wang, Manlin Chen

    Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 73-91, 2024, DOI:10.32604/iasc.2024.042285

    Abstract In industrial production and engineering operations, the health state of complex systems is critical, and predicting it can ensure normal operation. Complex systems have many monitoring indicators, complex coupling structures, non-linear and time-varying characteristics, so it is a challenge to establish a reliable prediction model. The belief rule base (BRB) can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities. Since each indicator of the complex system can reflect the health state to some extent, the BRB is built based on the causal relationship between system indicators and the… More >

  • Open Access

    ARTICLE

    PREDICTION OF BINARY MIXTURE BOILING HEAT TRANSFER IN SYSTEMS WITH STRONG MARANGONI EFFECTS

    Kenneth M. Armijo, Van P. Carey*

    Frontiers in Heat and Mass Transfer, Vol.1, No.2, pp. 1-6, 2010, DOI:10.5098/hmt.v1.2.3003

    Abstract This paper investigates the impact of Marangoni phenomena for low concentrations of 2-propanol/water and methanol/water mixtures. In real systems the addition of small levels of surface-active contaminants can affect the surface tension of the liquid-vapor interface and thermodynamic conditions in this region. Analysis was performed for three widely accepted binary mixture correlations to predict heat flux and superheat values for subatmospheric experimental data using bulk fluid and film thermodynamic properties. Due to the non-ideal nature of these alcohol/water mixtures, this study also employs an average pseudo single-component (PSC) coefficient in place of an ideal heat transfer coefficient (HTC) to improve… More >

  • Open Access

    ARTICLE

    SYSTEMATIC STRATEGY FOR MODELING AND OPTIMIZATION OF THERMAL SYSTEMS WITH DESIGN UNCERTAINTIES

    Po Ting Lin, Hae Chang Gea, Yogesh Jaluria*

    Frontiers in Heat and Mass Transfer, Vol.1, No.1, pp. 1-20, 2010, DOI:10.5098/hmt.v1.1.3003

    Abstract Thermal systems play significant roles in the engineering practice and our lives. To improve those thermal systems, it is necessary to model and optimize the design and the operating conditions. More importantly, the design uncertainties should be considered because the failures of the thermal systems may be very dangerous and produce large loss. This review paper focuses on a systematic strategy of modeling and optimizing of the thermal systems with the considerations of the design uncertainties. To demonstrate the proposed strategy, one of the complicated thermal systems, Chemical Vapor Deposition (CVD), is simulated, parametrically modeled, and optimized. The operating conditions,… More >

  • Open Access

    ARTICLE

    ANALYTICAL SOLUTION FOR A CLASS OF FLAT PLATE CONJUGATE CONVECTIVE HEAT TRANSFER PROBLEMS

    Antti Lehtinena, Reijo Karvinenb,∗

    Frontiers in Heat and Mass Transfer, Vol.2, No.4, pp. 1-6, 2011, DOI:10.5098/hmt.v2.4.3004

    Abstract Analytical solutions for three different flat plate conjugate heat transfer cases are presented. The cases are as follows:transient heat transfer of a thin plate with uniform heat generation; the Luikov problem in which one plate surface is kept in a constant temperature and the other one is cooled by forced convection ; and a modified Luikov problem with heat generation on one surface and convection on both surfaces of the plate. All the cases are solved for both laminar and turbulent flows with P r ≥ 1. The solutions in the paper are based on the superposition principle and analytical… More >

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