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  • Open Access

    ARTICLE

    FSE2R: An Improved Collision-Avoidance-based Energy Efficient Route Selection Protocol in USN

    Prasant Ku. Dash1, Lopamudra Hota2, Madhumita Panda3, N. Z. Jhanjhi4,*, Kshira Sagar Sahoo5, Mehedi Masud6

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2225-2242, 2023, DOI:10.32604/csse.2023.024836

    Abstract The 3D Underwater Sensor Network (USNs) has become the most optimistic medium for tracking and monitoring underwater environment. Energy and collision are two most critical factors in USNs for both sparse and dense regions. Due to harsh ocean environment, it is a challenge to design a reliable energy efficient with collision free protocol. Diversity in link qualities may cause collision and frequent communication lead to energy loss; that effects the network performance. To overcome these challenges a novel protocol Forwarder Selection Energy Efficient Routing (FSE2R) is proposed. Our proposal’s key idea is based on computation of node distance from the… More >

  • Open Access

    ARTICLE

    Data-Driven Load Forecasting Using Machine Learning and Meteorological Data

    Aishah Alrashidi, Ali Mustafa Qamar*

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1973-1988, 2023, DOI:10.32604/csse.2023.024633

    Abstract Electrical load forecasting is very crucial for electrical power systems’ planning and operation. Both electrical buildings’ load demand and meteorological datasets may contain hidden patterns that are required to be investigated and studied to show their potential impact on load forecasting. The meteorological data are analyzed in this study through different data mining techniques aiming to predict the electrical load demand of a factory located in Riyadh, Saudi Arabia. The factory load and meteorological data used in this study are recorded hourly between 2016 and 2017. These data are provided by King Abdullah City for Atomic and Renewable Energy and… More >

  • Open Access

    ARTICLE

    Efficient Grad-Cam-Based Model for COVID-19 Classification and Detection

    Saleh Albahli1,*, Ghulam Nabi Ahmad Hassan Yar2,3

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2743-2757, 2023, DOI:10.32604/csse.2023.024463

    Abstract Corona Virus (COVID-19) is a novel virus that crossed an animal-human barrier and emerged in Wuhan, China. Until now it has affected more than 119 million people. Detection of COVID-19 is a critical task and due to a large number of patients, a shortage of doctors has occurred for its detection. In this paper, a model has been suggested that not only detects the COVID-19 using X-ray and CT-Scan images but also shows the affected areas. Three classes have been defined; COVID-19, normal, and Pneumonia for X-ray images. For CT-Scan images, 2 classes have been defined COVID-19 and non-COVID-19. For… More >

  • Open Access

    ARTICLE

    Swarm Intelligence Based Routing with Black Hole Attack Detection in MANET

    S. A. Arunmozhi*, S. Rajeswari, Y. Venkataramani

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2337-2347, 2023, DOI:10.32604/csse.2023.024340

    Abstract Mobile Ad hoc Network (MANET) possesses unique characteristics which makes it vulnerable to security threats. In MANET, it is highly challenging to protect the nodes from cyberattacks. Power conservation improves both life time of nodes as well as the network. Computational capabilities and memory constraints are critical issues in the implementation of cryptographic techniques. Energy and security are two important factors that need to be considered for improving the performance of MANET. So, the incorporation of an energy efficient secure routing protocol becomes inevitable to ensure appropriate action upon the network. The nodes present in a network are limited due… More >

  • Open Access

    ARTICLE

    Process Discovery and Refinement of an Enterprise Management System

    Faizan Ahmed Khan1, Farooq Ahmad1, Arfat Ahmad Khan2, Chitapong Wechtaisong2,*

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2019-2032, 2023, DOI:10.32604/csse.2023.023490

    Abstract The need for the analysis of modern businesses is rapidly increasing as the supporting enterprise systems generate more and more data. This data can be extremely valuable for executing organizations because the data allows constant monitoring, analyzing, and improving the underlying processes, which leads to the reduction of cost and the improvement of the quality. Process mining is a useful technique for analyzing enterprise systems by using an event log that contains behaviours. This research focuses on the process discovery and refinement using real-life event log data collected from a large multinational organization that deals with coatings and paints. By… More >

  • Open Access

    ARTICLE

    Design of Online Vitals Monitor by Integrating Big Data and IoT

    E. Afreen Banu1,*, V. Rajamani2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2469-2487, 2023, DOI:10.32604/csse.2023.021332

    Abstract In this work, we design a multisensory IoT-based online vitals monitor (hereinafter referred to as the VITALS) to sense four bedside physiological parameters including pulse (heart) rate, body temperature, blood pressure, and peripheral oxygen saturation. Then, the proposed system constantly transfers these signals to the analytics system which aids in enhancing diagnostics at an earlier stage as well as monitoring after recovery. The core hardware of the VITALS includes commercial off-the-shelf sensing devices/medical equipment, a powerful microcontroller, a reliable wireless communication module, and a big data analytics system. It extracts human vital signs in a pre-programmed interval of 30 min… More >

  • Open Access

    ARTICLE

    Heart Disease Risk Prediction Expending of Classification Algorithms

    Nisha Mary1, Bilal Khan1, Abdullah A. Asiri2, Fazal Muhammad3,*, Salman Khan3, Samar Alqhtani4, Khlood M. Mehdar5, Hanan Talal Halwani4, Muhammad Irfan6, Khalaf A. Alshamrani2

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6595-6616, 2022, DOI:10.32604/cmc.2022.032384

    Abstract Heart disease prognosis (HDP) is a difficult undertaking that requires knowledge and expertise to predict early on. Heart failure is on the rise as a result of today’s lifestyle. The healthcare business generates a vast volume of patient records, which are challenging to manage manually. When it comes to data mining and machine learning, having a huge volume of data is crucial for getting meaningful information. Several methods for predicting HD have been used by researchers over the last few decades, but the fundamental concern remains the uncertainty factor in the output data, as well as the need to decrease… More >

  • Open Access

    ARTICLE

    Blockchain Driven Metaheuristic Route Planning in Secure Vehicular Adhoc Networks

    Siwar Ben Haj Hassine1, Saud S. Alotaibi2, Hadeel Alsolai3, Reem Alshahrani4, Lilia Kechiche5, Mrim M. Alnfiai6, Amira Sayed A. Aziz7, Manar Ahmed Hamza8,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6461-6477, 2022, DOI:10.32604/cmc.2022.032353

    Abstract Nowadays, vehicular ad hoc networks (VANET) turn out to be a core portion of intelligent transportation systems (ITSs), that mainly focus on achieving continual Internet connectivity amongst vehicles on the road. The VANET was utilized to enhance driving safety and build an ITS in modern cities. Driving safety is a main portion of VANET, the privacy and security of these messages should be protected. In this aspect, this article presents a blockchain with sunflower optimization enabled route planning scheme (BCSFO-RPS) for secure VANET. The presented BCSFO-RPS model focuses on the identification of routes in such a way that vehicular communication… More >

  • Open Access

    ARTICLE

    Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in Metamaterial Antenna

    Doaa Sami Khafaga1, El-Sayed M. El-kenawy2,3, Faten Khalid Karim1,*, Sameer Alshetewi4, Abdelhameed Ibrahim5, Abdelaziz A. Abdelhamid6,7

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5771-5788, 2022, DOI:10.32604/cmc.2022.032229

    Abstract Metamaterial Antennas are a type of antenna that uses metamaterial to enhance performance. The bandwidth restriction associated with small antennas can be solved using metamaterial antennas. Machine learning is gaining popularity as a way to improve solutions in a range of fields. Machine learning approaches are currently a big part of current research, and they’re likely to be huge in the future. The model utilized determines the accuracy of the prediction in large part. The goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and gain. The basic models employed in the… More >

  • Open Access

    ARTICLE

    Deep Learning Prediction Model for NiCrAlY Diffusion Barrier Thickness for Tungsten Wires

    Amal H. Alharbi, Hanan A. Hosni Mahmoud*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5755-5769, 2022, DOI:10.32604/cmc.2022.032212

    Abstract In the last decades, technology has used Copper for IC interconnect and it has been the best material used in the wire downsizing. However, Copper is now showing inefficiency as downscaling is getting deeper. Recent research starts to show Tungsten (W) as a possible replacement, for its better downsizing characteristic. The scaling-down of interconnects dimension has to be augmented with thin diffusion layers. It is crucial to subdue tungsten diffusion in the nickel-based thermal spray Flexicord (NiCrAlY) coating layers. Inappropriately, diffusion barriers with thicknesses less than 4.3 nm do not to execute well. With the introduction of two dimensional layers,… More >

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