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  • Research Article

    BEST PAPER 2021

    Intelligent Disease Diagnosis Model for Energy Aware Cluster Based IoT Healthcare Systems

    Wafaa Alsaggaf1,*, Felwa Abukhodair1, Amani Tariq Jamal2, Sayed Abdel-Khalek3, Romany F. Mansour4 CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1189-1203, 2022, DOI:10.32604/cmc.2022.022469
    Abstract In recent days, advancements in the Internet of Things (IoT) and cloud computing (CC) technologies have emerged in different application areas, particularly healthcare. The use of IoT devices in healthcare sector often generates large amount of data and also spent maximum energy for data transmission to the cloud server. Therefore, energy efficient clustering mechanism is needed to effectively reduce the energy consumption of IoT devices. At the same time, the advent of deep learning (DL) models helps to analyze the healthcare data in the cloud server for decision making. With this motivation, this paper presents an intelligent disease diagnosis model… More >

  • Research Article

    BEST PAPER 2021

    Denoising Letter Images from Scanned Invoices Using Stacked Autoencoders

    Samah Ibrahim Alshathri1,*, Desiree Juby Vincent2, V. S. Hari2 CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1371-1386, 2022, DOI:10.32604/cmc.2022.022458
    Abstract Invoice document digitization is crucial for efficient management in industries. The scanned invoice image is often noisy due to various reasons. This affects the OCR (optical character recognition) detection accuracy. In this paper, letter data obtained from images of invoices are denoised using a modified autoencoder based deep learning method. A stacked denoising autoencoder (SDAE) is implemented with two hidden layers each in encoder network and decoder network. In order to capture the most salient features of training samples, a undercomplete autoencoder is designed with non-linear encoder and decoder function. This autoencoder is regularized for denoising application using a combined… More >

  • Research Article

    BEST PAPER 2021

    Takagi–Sugeno Fuzzy Modeling and Control for Effective Robotic Manipulator Motion

    Izzat Al-Darraji1,2, Ayad A. Kakei2, Ayad Ghany Ismaeel3, Georgios Tsaramirsis4, Fazal Qudus Khan5, Princy Randhawa6, Muath Alrammal4, Sadeeq Jan7,* CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1011-1024, 2022, DOI:10.32604/cmc.2022.022451
    Abstract Robotic manipulators are widely used in applications that require fast and precise motion. Such devices, however, are prompt to nonlinear control issues due to the flexibility in joints and the friction in the motors within the dynamics of their rigid part. To address these issues, the Linear Matrix Inequalities (LMIs) and Parallel Distributed Compensation (PDC) approaches are implemented in the Takagy–Sugeno Fuzzy Model (T-SFM). We propose the following methodology; initially, the state space equations of the nonlinear manipulator model are derived. Next, a Takagy–Sugeno Fuzzy Model (T-SFM) technique is used for linearizing the state space equations of the nonlinear manipulator.… More >

  • Research Article

    BEST PAPER 2021

    Fleet Optimization of Smart Electric Motorcycle System Using Deep Reinforcement Learning

    Patikorn Anchuen, Peerapong Uthansakul*, Monthippa Uthansakul, Settawit Poochaya CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1925-1943, 2022, DOI:10.32604/cmc.2022.022444
    Abstract Smart electric motorcycle-sharing systems based on the digital platform are one of the public transportations that we use in daily lives when the sharing economy is considered. This transportation provides convenience for users with low-cost systems while it also promotes an environmental conservation. Normally, users rent the vehicle to travel from the origin station to another station near their destination with a one-way trip in which the demand of renting and returning at each station is different. This leads to unbalanced vehicle rental systems. To avoid the full or empty inventory, the electric motorcycle-sharing rebalancing with the fleet optimization is… More >

  • Research Article

    BEST PAPER 2021

    Multi-Path Service Function Chaining for Mobile Surveillance of Animal Husbandry

    Xi Chen1,3, Tao Wu2,*, Mehtab Afzal4 CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1959-1971, 2022, DOI:10.32604/cmc.2022.022344
    Abstract Animal husbandry is the pillar industry in some ethnic areas of China. However, the communication/networking infrastructure in these areas is often underdeveloped, thus the difficulty in centralized management, and challenges for the effective monitoring. Considering the dynamics of the field monitoring environment, as well as the diversity and mobility of monitoring targets, traditional WSN (Wireless Sensor Networks) or IoT (Internet of Things) is difficult to meet the surveillance needs. Mobile surveillance that features the collaboration of various functions (camera, sensing, image recognition, etc.) deployed on mobile devices is desirable in a volatile wireless environment. This paper proposes the service function… More >

  • Research Article

    BEST PAPER 2021

    Fed-DFE: A Decentralized Function Encryption-Based Privacy-Preserving Scheme for Federated Learning

    Zhe Sun1, Jiyuan Feng1, Lihua Yin1,*, Zixu Zhang2, Ran Li1, Yu Hu1, Chongning Na3 CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1867-1886, 2022, DOI:10.32604/cmc.2022.022290
    Abstract Federated learning is a distributed learning framework which trains global models by passing model parameters instead of raw data. However, the training mechanism for passing model parameters is still threatened by gradient inversion, inference attacks, etc. With a lightweight encryption overhead, function encryption is a viable secure aggregation technique in federation learning, which is often used in combination with differential privacy. The function encryption in federal learning still has the following problems: a) Traditional function encryption usually requires a trust third party (TTP) to assign the keys. If a TTP colludes with a server, the security aggregation mechanism can be… More >

  • Research Article

    BEST PAPER 2021

    Gain Enhancement of Dielectric Resonator Antenna Using Electromagnetic Bandgap Structure

    Amor Smida1,2,* CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1613-1623, 2022, DOI:10.32604/cmc.2022.022289
    Abstract High gain antennas are highly desirable for long-range wireless communication systems. In this paper, a compact, low profile, and high gain dielectric resonator antenna is proposed, fabricated, experimentally tested, and verified. The proposed antenna system has a cylindrical dielectric resonator antenna with a height of 9 mm and a radius of 6.35 mm as a radiating element. The proposed dielectric resonator antenna is sourced with a slot while the slot is excited with a rectangular microstrip transmission line. The microstrip transmission line is designed for a 50 Ω impedance to provide maximum power to the slot. As a result, the… More >

  • Research Article

    BEST PAPER 2021

    Optimal Cooperative Spectrum Sensing Based on Butterfly Optimization Algorithm

    Noor Gul1,2, Saeed Ahmed1,3, Atif Elahi4, Su Min Kim1, Junsu Kim1,* CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 369-387, 2022, DOI:10.32604/cmc.2022.022260
    Abstract Since the introduction of the Internet of Things (IoT), several researchers have been exploring its productivity to utilize and organize the spectrum assets. Cognitive radio (CR) technology is characterized as the best aspirant for wireless communications to augment IoT competencies. In the CR networks, secondary users (SUs) opportunistically get access to the primary users (PUs) spectrum through spectrum sensing. The multipath issues in the wireless channel can fluster the sensing ability of the individual SUs. Therefore, several cooperative SUs are engaged in cooperative spectrum sensing (CSS) to ensure reliable sensing results. In CSS, security is still a major concern for… More >

  • Research Article

    BEST PAPER 2021

    Decagonal C-Shaped CSRR Textile-Based Metamaterial for Microwave Applications

    Kabir Hossain1,2, Thennarasan Sabapathy1,2,*, Muzammil Jusoh1,2, Ping Jack Soh1,3, Samir Salem Al-Bawri4, Mohamed Nasrun Osman1,2, Hasliza A. Rahim1,2, Danai Torrungrueng5, Prayoot Akkaraekthalin6 CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1677-1693, 2022, DOI:10.32604/cmc.2022.022227
    Abstract This paper introduces a decagonal C-shaped complementary split-ring resonator (CSRR) textile-based metamaterial (MTM). The overall size of the proposed sub-wavelength MTM unit cell is 0.28λ0 × 0.255λ0 at 3 GHz. Its stopband behaviour was first studied prior analysing the negative index properties of the proposed MTM. It is worth noting that in this work a unique way the experiments were completed. For both simulations and measurements, the proposed MTM exhibited negative-permittivity and negative-refractive index characteristics with an average bandwidth of more than 3 GHz (considering 1.7 to 8.2 GHz as the measurements were carried out within this range). In simulations, the MTM… More >

  • Research Article

    BEST PAPER 2021

    Design of Nonlinear Components Over a Mordell Elliptic Curve on Galois Fields

    Hafeez ur Rehman1,*, Tariq Shah1, Amer Aljaedi2, Mohammad Mazyad Hazzazi3, Adel R. Alharbi2 CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1313-1329, 2022, DOI:10.32604/cmc.2022.022224
    Abstract Elliptic curve cryptography ensures more safety and reliability than other public key cryptosystems of the same key size. In recent years, the use of elliptic curves in public-key cryptography has increased due to their complexity and reliability. Different kinds of substitution boxes are proposed to address the substitution process in the cryptosystems, including dynamical, static, and elliptic curve-based methods. Conventionally, elliptic curve-based S-boxes are based on prime field but in this manuscript; we propose a new technique of generating S-boxes based on mordell elliptic curves over the Galois field . This technique affords a higher number of possibilities to generate… More >

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