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  • Open Access

    ARTICLE

    Blockchain-Based SQKD and IDS in Edge Enabled Smart Grid Network

    Abdullah Musaed Alkhiari1, Shailendra Mishra2,*, Mohammed AlShehri1

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2149-2169, 2022, DOI:10.32604/cmc.2022.019562

    Abstract Smart Grid is a power grid that improves flexibility, reliability, and efficiency through smart meters. Due to extensive data exchange over the Internet, the smart grid faces many security challenges that have led to data loss, data compromise, and high power consumption. Moreover, the lack of hardware protection and physical attacks reduce the overall performance of the smart grid network. We proposed the BLIDSE model (Blockchain-based secure quantum key distribution and Intrusion Detection System in Edge Enables Smart Grid Network) to address these issues. The proposed model includes five phases: The first phase is blockchain-based… More >

  • Open Access

    ARTICLE

    Neural Network and Fuzzy Control Based 11-Level Cascaded Inverter Operation

    Buddhadeva Sahoo1,*, Sangram Keshari Routray2, Pravat Kumar Rout2, Mohammed M. Alhaider3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2319-2346, 2022, DOI:10.32604/cmc.2022.019559

    Abstract This paper presents a combined control and modulation technique to enhance the power quality (PQ) and power reliability (PR) of a hybrid energy system (HES) through a single-phase 11-level cascaded H-bridge inverter (11-CHBI). The controller and inverter specifically regulate the HES and meet the load demand. To track optimum power, a Modified Perturb and Observe (MP&O) technique is used for HES. Ultra-capacitor (UCAP) based energy storage device and a novel current control strategy are proposed to provide additional active power support during both voltage sag and swell conditions. For an improved PQ and PR, a… More >

  • Open Access

    ARTICLE

    Fast Intra Mode Selection in HEVC Using Statistical Model

    Junaid Tariq1,*, Ayman Alfalou2, Amir Ijaz1, Hashim Ali3, Imran Ashraf1, Hameedur Rahman1, Ammar Armghan4, Inzamam Mashood1, Saad Rehman1

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3903-3918, 2022, DOI:10.32604/cmc.2022.019541

    Abstract Comprehension algorithms like High Efficiency Video Coding (HEVC) facilitates fast and efficient handling of multimedia contents. Such algorithms involve various computation modules that help to reduce the size of content but preserve the same subjective viewing quality. However, the brute-force behavior of HEVC is the biggest hurdle in the communication of multimedia content. Therefore, a novel method will be presented here to accelerate the encoding process of HEVC by making early intra mode decisions for the block. Normally, the HEVC applies 35 intra modes to every block of the frame and selects the best among… More >

  • Open Access

    ARTICLE

    Optimized Convolutional Neural Network Models for Skin Lesion Classification

    Juan Pablo Villa-Pulgarin1, Anderson Alberto Ruales-Torres1,2, Daniel Arias-Garzón1, Mario Alejandro Bravo-Ortiz1, Harold Brayan Arteaga-Arteaga1, Alejandro Mora-Rubio1, Jesus Alejandro Alzate-Grisales1, Esteban Mercado-Ruiz1, M. Hassaballah3, Simon Orozco-Arias4,5, Oscar Cardona-Morales1, Reinel Tabares-Soto1,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2131-2148, 2022, DOI:10.32604/cmc.2022.019529

    Abstract Skin cancer is one of the most severe diseases, and medical imaging is among the main tools for cancer diagnosis. The images provide information on the evolutionary stage, size, and location of tumor lesions. This paper focuses on the classification of skin lesion images considering a framework of four experiments to analyze the classification performance of Convolutional Neural Networks (CNNs) in distinguishing different skin lesions. The CNNs are based on transfer learning, taking advantage of ImageNet weights. Accordingly, in each experiment, different workflow stages are tested, including data augmentation and fine-tuning optimization. Three CNN models More >

  • Open Access

    ARTICLE

    Cross-Layer Hidden Markov Analysis for Intrusion Detection

    K. Venkatachalam1, P. Prabu2, B. Saravana Balaji3, Byeong-Gwon Kang4, Yunyoung Nam4,*, Mohamed Abouhawwash5,6

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3685-3700, 2022, DOI:10.32604/cmc.2022.019502

    Abstract Ad hoc mobile cloud computing networks are affected by various issues, like delay, energy consumption, flexibility, infrastructure, network lifetime, security, stability, data transition, and link accomplishment. Given the issues above, route failure is prevalent in ad hoc mobile cloud computing networks, which increases energy consumption and delay and reduces stability. These issues may affect several interconnected nodes in an ad hoc mobile cloud computing network. To address these weaknesses, which raise many concerns about privacy and security, this study formulated clustering-based storage and search optimization approaches using cross-layer analysis. The proposed approaches were formed by cross-layer analysis based… More >

  • Open Access

    ARTICLE

    Applying Apache Spark on Streaming Big Data for Health Status Prediction

    Ahmed Ismail Ebada1, Ibrahim Elhenawy2, Chang-Won Jeong3, Yunyoung Nam4,*, Hazem Elbakry1, Samir Abdelrazek1

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3511-3527, 2022, DOI:10.32604/cmc.2022.019458

    Abstract Big data applications in healthcare have provided a variety of solutions to reduce costs, errors, and waste. This work aims to develop a real-time system based on big medical data processing in the cloud for the prediction of health issues. In the proposed scalable system, medical parameters are sent to Apache Spark to extract attributes from data and apply the proposed machine learning algorithm. In this way, healthcare risks can be predicted and sent as alerts and recommendations to users and healthcare providers. The proposed work also aims to provide an effective recommendation system by… More >

  • Open Access

    ARTICLE

    Deep Reinforcement Learning Model for Blood Bank Vehicle Routing Multi-Objective Optimization

    Meteb M. Altaf1,*, Ahmed Samir Roshdy2, Hatoon S. AlSagri3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3955-3967, 2022, DOI:10.32604/cmc.2022.019448

    Abstract The overall healthcare system has been prioritized within development top lists worldwide. Since many national populations are aging, combined with the availability of sophisticated medical treatments, healthcare expenditures are rapidly growing. Blood banks are a major component of any healthcare system, which store and provide the blood products needed for organ transplants, emergency medical treatments, and routine surgeries. Timely delivery of blood products is vital, especially in emergency settings. Hence, blood delivery process parameters such as safety and speed have received attention in the literature, as well as other parameters such as delivery cost. In… More >

  • Open Access

    ARTICLE

    VISPNN: VGG-Inspired Stochastic Pooling Neural Network

    Shui-Hua Wang1, Muhammad Attique Khan2, Yu-Dong Zhang3,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3081-3097, 2022, DOI:10.32604/cmc.2022.019447

    Abstract Aim Alcoholism is a disease that a patient becomes dependent or addicted to alcohol. This paper aims to design a novel artificial intelligence model that can recognize alcoholism more accurately. Methods We propose the VGG-Inspired stochastic pooling neural network (VISPNN) model based on three components: (i) a VGG-inspired mainstay network, (ii) the stochastic pooling technique, which aims to outperform traditional max pooling and average pooling, and (iii) an improved 20-way data augmentation (Gaussian noise, salt-and-pepper noise, speckle noise, Poisson noise, horizontal shear, vertical shear, rotation, Gamma correction, random translation, and scaling on both raw image and… More >

  • Open Access

    ARTICLE

    Database Recovery Technique for Mobile Computing: A Game Theory Approach

    Magda M. Madbouly1, Yasser F. Mokhtar2, Saad M. Darwish1,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3205-3219, 2022, DOI:10.32604/cmc.2022.019440

    Abstract Contact between mobile hosts and database servers presents many problems in the Mobile Database System (MDS). It is harmed by a variety of causes, including handoff, inadequate capacity, frequent transaction updates, and repeated failures, both of which contribute to serious issues with the information system’s consistency. However, error tolerance technicality allows devices to continue performing their functions in the event of a failure. The aim of this paper is to identify the optimal recovery approach from among the available state-of-the-art techniques in MDS by employing game theory. Several of the presented recovery protocols are chosen More >

  • Open Access

    ARTICLE

    A Real-Time Automatic Translation of Text to Sign Language

    Muhammad Sanaullah1,*, Babar Ahmad2, Muhammad Kashif2, Tauqeer Safdar2, Mehdi Hassan3, Mohd Hilmi Hasan4, Norshakirah Aziz4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2471-2488, 2022, DOI:10.32604/cmc.2022.019420

    Abstract Communication is a basic need of every human being; by this, they can learn, express their feelings and exchange their ideas, but deaf people cannot listen and speak. For communication, they use various hands gestures, also known as Sign Language (SL), which they learn from special schools. As normal people have not taken SL classes; therefore, they are unable to perform signs of daily routine sentences (e.g., what are the specifications of this mobile phone?). A technological solution can facilitate in overcoming this communication gap by which normal people can communicate with deaf people. This… More >

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