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  • Open Access

    ARTICLE

    State-of-Charge Estimation of Lithium-Ion Battery for Electric Vehicles Using Deep Neural Network

    M. Premkumar1, R. Sowmya2, S. Sridhar3, C. Kumar4, Mohamed Abbas5,6, Malak S. Alqahtani7, Kottakkaran Sooppy Nisar8,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6289-6306, 2022, DOI:10.32604/cmc.2022.030490

    Abstract It is critical to have precise data about Lithium-ion batteries, such as the State-of-Charge (SoC), to maintain a safe and consistent functioning of battery packs in energy storage systems of electric vehicles. Numerous strategies for estimating battery SoC, such as by including the coulomb counting and Kalman filter, have been established. As a result of the differences in parameter values between each cell, when these methods are applied to high-capacity battery packs, it has difficulties sustaining the prediction accuracy of overall cells. As a result of aging, the variation in the parameters of each cell is higher as more time… More >

  • Open Access

    ARTICLE

    Residual Autoencoder Deep Neural Network for Electrical Capacitance Tomography

    Wael Deabes1,2,*, Kheir Eddine Bouazza1,3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6307-6326, 2022, DOI:10.32604/cmc.2022.030420

    Abstract Great achievements have been made during the last decades in the field of Electrical Capacitance Tomography (ECT) image reconstruction. However, there is still a need to make these image reconstruction results faster and of better quality. Recently, Deep Learning (DL) is flourishing and is adopted in many fields. The DL is very good at dealing with complex nonlinear functions and it is built using several series of Artificial Neural Networks (ANNs). An ECT image reconstruction model using DNN is proposed in this paper. The proposed model mainly uses Residual Autoencoder called (ECT_ResAE). A large-scale dataset of 320 k instances have… More >

  • Open Access

    ARTICLE

    Numerical Simulations of One-Directional Fractional Pharmacokinetics Model

    Nursyazwani Mohamad Noor1, Siti Ainor Mohd Yatim1,*, Nur Intan Raihana Ruhaiyem2

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4923-4934, 2022, DOI:10.32604/cmc.2022.030414

    Abstract In this paper, we present a three-compartment of pharmacokinetics model with irreversible rate constants. The compartment consists of arterial blood, tissues and venous blood. Fick’s principle and the law of mass action were used to develop the model based on the diffusion process. The model is modified into a fractional pharmacokinetics model with the sense of Caputo derivative. The existence and uniqueness of the model are investigated and the positivity of the model is established. The behaviour of the model is investigated by implementing numerical algorithms for the numerical solution of the system of fractional differential equations. MATLAB software is… More >

  • Open Access

    ARTICLE

    Chaotic Krill Herd with Deep Transfer Learning-Based Biometric Iris Recognition System

    Harbi Al-Mahafzah1, Tamer AbuKhalil1, Bassam A. Y. Alqaralleh2,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5703-5715, 2022, DOI:10.32604/cmc.2022.030399

    Abstract Biometric verification has become essential to authenticate the individuals in public and private places. Among several biometrics, iris has peculiar features and its working mechanism is complex in nature. The recent developments in Machine Learning and Deep Learning approaches enable the development of effective iris recognition models. With this motivation, the current study introduces a novel Chaotic Krill Herd with Deep Transfer Learning Based Biometric Iris Recognition System (CKHDTL-BIRS). The presented CKHDTL-BIRS model intends to recognize and classify iris images as a part of biometric verification. To achieve this, CKHDTL-BIRS model initially performs Median Filtering (MF)-based preprocessing and segmentation for… More >

  • Open Access

    ARTICLE

    Brain Tumor Detection and Classification Using PSO and Convolutional Neural Network

    Muhammad Ali1, Jamal Hussain Shah1, Muhammad Attique Khan2, Majed Alhaisoni3, Usman Tariq4, Tallha Akram5, Ye Jin Kim6, Byoungchol Chang7,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4501-4518, 2022, DOI:10.32604/cmc.2022.030392

    Abstract Tumor detection has been an active research topic in recent years due to the high mortality rate. Computer vision (CV) and image processing techniques have recently become popular for detecting tumors in MRI images. The automated detection process is simpler and takes less time than manual processing. In addition, the difference in the expanding shape of brain tumor tissues complicates and complicates tumor detection for clinicians. We proposed a new framework for tumor detection as well as tumor classification into relevant categories in this paper. For tumor segmentation, the proposed framework employs the Particle Swarm Optimization (PSO) algorithm, and for… More >

  • Open Access

    ARTICLE

    A Locality-Sensitive Hashing-Based Jamming Detection System for IoT Networks

    P. Ganeshkumar*, Talal Albalawi

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5943-5959, 2022, DOI:10.32604/cmc.2022.030388

    Abstract

    Internet of things (IoT) comprises many heterogeneous nodes that operate together to accomplish a human friendly or a business task to ease the life. Generally, IoT nodes are connected in wireless media and thus they are prone to jamming attacks. In the present scenario jamming detection (JD) by using machine learning (ML) algorithms grasp the attention of the researchers due to its virtuous outcome. In this research, jamming detection is modelled as a classification problem which uses several features. Using one/two or minimum number of features produces vague results that cannot be explained. Also the relationship between the feature and… More >

  • Open Access

    ARTICLE

    A Beamforming Technique Using Rotman Lens Antenna for Wireless Relay Networks

    Samer Alabed*, Mohammad Al-Rabayah, Wael Hosny Fouad Aly

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5641-5653, 2022, DOI:10.32604/cmc.2022.030371

    Abstract Rotman lens, which is a radio frequency beam-former that consists of multiple input and multiple output beam ports, can be used in industrial, scientific, and medical applications as a beam steering device. The input ports collect the signals to be propagated through the lens cavity toward the output ports before being transmitted by the antenna arrays to the destination in order to enhance the error performance by optimizing the overall signal to noise ratio (SNR). In this article, a low-cost Rotman lens antenna is designed and deployed to enhance the overall performance of the conventional cooperative communication systems without needing… More >

  • Open Access

    ARTICLE

    Code-based Sequential Aggregate Signature Scheme

    Bennian Dou1,*, Lei Xu1, Xiaoling Yu2, Lin Mei1, Cong Zuo3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5219-5231, 2022, DOI:10.32604/cmc.2022.030270

    Abstract This paper proposes the first code-based quantum immune sequential aggregate signature (SAS) scheme and proves the security of the proposed scheme in the random oracle model. Aggregate signature (AS) schemes and sequential aggregate signature schemes allow a group of potential signers to sign different messages respectively, and all the signatures of those users on those messages can be aggregated into a single signature such that the size of the aggregate signature is much smaller than the total size of all individual signatures. Because of the aggregation of many signatures into a single short signature, AS and SAS schemes can reduce… More >

  • Open Access

    ARTICLE

    Cluster Representation of the Structural Description of Images for Effective Classification

    Yousef Ibrahim Daradkeh1,*, Volodymyr Gorokhovatskyi2, Iryna Tvoroshenko2, Medien Zeghid3,4

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6069-6084, 2022, DOI:10.32604/cmc.2022.030254

    Abstract The problem of image recognition in the computer vision systems is being studied. The results of the development of efficient classification methods, given the figure of processing speed, based on the analysis of the segment representation of the structural description in the form of a set of descriptors are provided. We propose three versions of the classifier according to the following principles: “object–etalon”, “object descriptor–etalon” and “vector description of the object–etalon”, which are not similar in level of integration of researched data analysis. The options for constructing clusters over the whole set of descriptions of the etalon database, separately for… More >

  • Open Access

    ARTICLE

    An Approximation for the Entropy Measuring in the General Structure of SGSP3

    Kamel Jebreen1,2,3,*, Muhammad Haroon Aftab4, Mohammad Issa Sowaity5, Zeeshan Saleem Mufti4, Muhammad Hussain6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4455-4463, 2022, DOI:10.32604/cmc.2022.030246

    Abstract In this article, we calculate various topological invariants such as symmetric division degree index, redefined Zagreb index, VL index, first and second exponential Zagreb index, first and second multiplicative exponential Zagreb indices, symmetric division degree entropy, redefined Zagreb entropy, VL entropy, first and second exponential Zagreb entropies, multiplicative exponential Zagreb entropy. We take the chemical compound named Proanthocyanidins, which is a very useful polyphenol in human’s diet. They are very beneficial for one’s health. These chemical compounds are extracted from grape seeds. They are tremendously anti-inflammatory. A subdivision form of this compound is presented in this article. The compound named… More >

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