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  • Open Access

    ARTICLE

    Enhancing Blockchain Security Using Ripple Consensus Algorithm

    A. Baseera1, Abeer Abdullah Alsadhan2,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4713-4726, 2022, DOI:10.32604/cmc.2022.029538

    Abstract In the development of technology in various fields like big data analysis, data mining, big data, cloud computing, and blockchain technology, security become more constrained. Blockchain is used in providing security by encrypting the sharing of information. Blockchain is applied in the peer-to-peer (P2P) network and it has a decentralized ledger. Providing security against unauthorized breaches in the distributed network is required. To detect unauthorized breaches, there are numerous techniques were developed and those techniques are inefficient and have poor data integrity. Hence, a novel technique needs to be implemented to tackle the new breaches in the distributed network. This… More >

  • Open Access

    ARTICLE

    Optimum Design for the Magnification Mechanisms Employing Fuzzy Logic–ANFIS

    Ngoc Thai Huynh1, Tien V. T. Nguyen2, Quoc Manh Nguyen3,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5961-5983, 2022, DOI:10.32604/cmc.2022.029484

    Abstract To achieve high work performance for compliant mechanisms of motion scope, continuous work condition, and high frequency, we propose a new hybrid algorithm that could be applied to multi-objective optimum design. In this investigation, we use the tools of finite element analysis (FEA) for a magnification mechanism to find out the effects of design variables on the magnification ratio of the mechanism and then select an optimal mechanism that could meet design requirements. A poly-algorithm including the Grey-Taguchi method, fuzzy logic system, and adaptive neuro-fuzzy inference system (ANFIS) algorithm, was utilized mainly in this study. The FEA outcomes indicated that… More >

  • Open Access

    ARTICLE

    NOMA-Based Cooperative Relaying Transmission for the Industrial Internet of Things

    Yinghua Zhang1,*, Rui Cao1, Lixin Tian1, Rong Dai2, Zhennan Cao2, Jim Feng3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6513-6534, 2022, DOI:10.32604/cmc.2022.029467

    Abstract With the continuous maturity of the fifth generation (5G) communications, industrial Internet of Things (IIoT) technology has been widely applied in fields such as smart factories. In smart factories, 5G-based production line monitoring can improve production efficiency and reduce costs, but there are problems with limited monitoring coverage and insufficient wireless spectrum resources, which restricts the application of IIoT in the construction of smart factories. In response to these problems, we propose a hybrid spectrum access mechanism based on Non-Orthogonal Multiple Access (NOMA) cooperative relaying transmission to improve the monitoring coverage and spectrum efficiency. As there are a large number… More >

  • Open Access

    ARTICLE

    Swarming Computational Techniques for the Influenza Disease System

    Sakda Noinang1, Zulqurnain Sabir2, Gilder Cieza Altamirano3, Muhammad Asif Zahoor Raja4, Manuel Jesús Sànchez-Chero5, María-Verónica Seminario-Morales5, Wajaree Weera6,*, Thongchai Botmart6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4851-4868, 2022, DOI:10.32604/cmc.2022.029437

    Abstract The current study relates to designing a swarming computational paradigm to solve the influenza disease system (IDS). The nonlinear system’s mathematical form depends upon four classes: susceptible individuals, infected people, recovered individuals and cross-immune people. The solutions of the IDS are provided by using the artificial neural networks (ANNs) together with the swarming computational paradigm-based particle swarm optimization (PSO) and interior-point scheme (IPA) that are the global and local search approaches. The ANNs-PSO-IPA has never been applied to solve the IDS. Instead a merit function in the sense of mean square error is constructed using the differential form of each… More >

  • Open Access

    ARTICLE

    Flexible Strain Sensor Based on 3D Electrospun Carbonized Sponge

    He Gong1,2,3, Zilian Wang1,3, Zhiqiang Cheng4, Lin Chen1,3, Haohong Pan1,3, Daming Zhang2, Tianli Hu1,3,*, Thobela Louis Tyasi5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4971-4980, 2022, DOI:10.32604/cmc.2022.029433

    Abstract Flexible strain sensor has attracted much attention because of its potential application in human motion detection. In this work, the prepared strain sensor was obtained by encapsulating electrospun carbonized sponge (CS) with room temperature vulcanized silicone rubber (RTVS). In this paper, the formation mechanism of conductive sponge was studied. Based on the combination of carbonized sponge and RTVS, the strain sensing mechanism and piezoresistive properties are discussed. After research and testing, the CS/RTVS flexible strain sensor has excellent fast response speed and stability, and the maximum strain coefficient of the sensor is 136.27. In this study, the self-developed CS/RTVS sensor… More >

  • Open Access

    ARTICLE

    A Prototype for Diagnosis of Psoriasis in Traditional Chinese Medicine

    Hai Long1, Zhe Wang1, Yidi Cui2,3, Junhui Wang4, Bo Gao5, Chao Chen5, Yan Zhu5,*, Heinrich Herre1

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5197-5217, 2022, DOI:10.32604/cmc.2022.029365

    Abstract Psoriasis is a chronic, non-communicable, painful, disfiguring and disabling disease for which there is no cure, with great negative impact on patients’ quality of life (QoL). Diagnosis and treatment with traditional Chinese medical technique based on syndrome differentiation has been used in practice for a long time and proven effective, though, up to now, there are only a few available studies about the use of semantic technologies and the knowledge systems that use Traditional Chinese Medicine (TCM)-syndrome differentiation for information retrieval and automated reasoning. In this paper we use semantic techniques based on ontologies to develop a prototypical system for… More >

  • Open Access

    ARTICLE

    Coverage Control for Underwater Sensor Networks Based on Residual Energy Probability

    Jinglin Liang1,2, Qian Sun1,2,*, Xiaoyi Wang3,2, Jiping Xu1,2, Huiyan Zhang1,2, Li Wang1,2, Jiabin Yu1,2, Jing Li4, Ruichao Wang5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5459-5471, 2022, DOI:10.32604/cmc.2022.029362

    Abstract Underwater sensor networks have important application value in the fields of water environment data collection, marine environment monitoring and so on. It has some characteristics such as low available bandwidth, large propagation delays and limited energy, which bring new challenges to the current researches. The research on coverage control of underwater sensor networks is the basis of other related researches. A good sensor node coverage control method can effectively improve the quality of water environment monitoring. Aiming at the problem of high dynamics and uncertainty of monitoring targets, the random events level are divided into serious events and general events.… More >

  • Open Access

    ARTICLE

    Performance Enhancement of Praseodymium Doped Fiber Amplifiers

    Abdullah G. Alharbi1, Jawad Mirza2, Mehak Raza3, Salman Ghafoor4,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5411-5422, 2022, DOI:10.32604/cmc.2022.029317

    Abstract In this paper, we report a simulation study on the performance enhancement of Praseodymium doped silica fiber amplifiers (PDFAs) in O-band (1270–1350 nm) in terms of small signal gain, power conversion efficiency (PCE), and output optical power by employing bidirectional pumping. The PDFA performance is examined by optimizing the length of Praseodymium doped silica fiber (PDF), its mode-field diameter (MFD) and the concentration of Pr3+. A small-signal peak gain of 56.4 dB, power conversion efficiency (PCE) of 47%, and output optical power of around 1.6 W (32 dBm) is observed at optimized parameters for input signal wavelength of 1310 nm.… More >

  • Open Access

    ARTICLE

    Wind Turbine Efficiency Under Altitude Consideration Using an Improved Particle Swarm Framework

    Haykel Marouani1,*, Fahad Awjah Almehmadi1, Rihem Farkh2, Habib Dhahri3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4981-4994, 2022, DOI:10.32604/cmc.2022.029315

    Abstract

    In this work, the concepts of particle swarm optimization-based method, named non-Gaussian improved particle swarm optimization for minimizing the cost of energy (COE) of wind turbines (WTs) on high-altitude sites are introduced. Since the COE depends on site specification constants and initialized parameters of wind turbine, the focus was on the design optimization of rotor radius, hub height and rated power. Based on literature, the COE is converted to the Saudi Arabia context. Thus, the constrained wind turbine optimization problem is developed. Then, non-Gaussian improved particle swarm optimization is provided and compared with the conventional particle swarm optimization for solving… More >

  • Open Access

    ARTICLE

    MIoT Based Skin Cancer Detection Using Bregman Recurrent Deep Learning

    Nithya Rekha Sivakumar1,*, Sara Abdelwahab Ghorashi1, Faten Khalid Karim1, Eatedal Alabdulkreem1, Amal Al-Rasheed2

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6253-6267, 2022, DOI:10.32604/cmc.2022.029266

    Abstract Mobile clouds are the most common medium for aggregating, storing, and analyzing data from the medical Internet of Things (MIoT). It is employed to monitor a patient’s essential health signs for earlier disease diagnosis and prediction. Among the various disease, skin cancer was the wide variety of cancer, as well as enhances the endurance rate. In recent years, many skin cancer classification systems using machine and deep learning models have been developed for classifying skin tumors, including malignant melanoma (MM) and other skin cancers. However, accurate cancer detection was not performed with minimum time consumption. In order to address these… More >

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