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  • Open Access

    ARTICLE

    Intelligent Feature Selection with Deep Learning Based Financial Risk Assessment Model

    Thavavel Vaiyapuri1, K. Priyadarshini2, A. Hemlathadhevi3, M. Dhamodaran4, Ashit Kumar Dutta5, Irina V. Pustokhina6,*, Denis A. Pustokhin7

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2429-2444, 2022, DOI:10.32604/cmc.2022.026204

    Abstract Due to global financial crisis, risk management has received significant attention to avoid loss and maximize profit in any business. Since the financial crisis prediction (FCP) process is mainly based on data driven decision making and intelligent models, artificial intelligence (AI) and machine learning (ML) models are widely utilized. This article introduces an intelligent feature selection with deep learning based financial risk assessment model (IFSDL-FRA). The proposed IFSDL-FRA technique aims to determine the financial crisis of a company or enterprise. In addition, the IFSDL-FRA technique involves the design of new water strider optimization algorithm based feature selection (WSOA-FS) manner to… More >

  • Open Access

    ARTICLE

    Embedded Coded Relay System for Molecular Communications

    Eman S. Attia1, Ashraf A. M. Khalaf1, Fathi E. Abd El-Samie2, Saied M. Abd El-atty2, Konstantinos A. Lizos3, Osama Alfarraj4, Farid Shawki2, Imran Khan5, Ki-Il Kim6,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2729-2748, 2022, DOI:10.32604/cmc.2022.026197

    Abstract With the emergence of the COVID-19 pandemic, the World Health Organization (WHO) has urged scientists and industrialists to explore modern information and communication technology (ICT) as a means to reduce or even eliminate it. The World Health Organization recently reported that the virus may infect the organism through any organ in the living body, such as the respiratory, the immunity, the nervous, the digestive, or the cardiovascular system. Targeting the abovementioned goal, we envision an implanted nanosystem embedded in the intra living-body network. The main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or… More >

  • Open Access

    ARTICLE

    A Sparse Optimization Approach for Beyond 5G mmWave Massive MIMO Networks

    Waleed Shahjehan1, Abid Ullah1, Syed Waqar Shah1, Imran Khan1, Nor Samsiah Sani2, Ki-Il Kim3,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2797-2810, 2022, DOI:10.32604/cmc.2022.026185

    Abstract Millimeter-Wave (mmWave) Massive MIMO is one of the most effective technology for the fifth-generation (5G) wireless networks. It improves both the spectral and energy efficiency by utilizing the 30–300 GHz millimeter-wave bandwidth and a large number of antennas at the base station. However, increasing the number of antennas requires a large number of radio frequency (RF) chains which results in high power consumption. In order to reduce the RF chain's energy, cost and provide desirable quality-of-service (QoS) to the subscribers, this paper proposes an energy-efficient hybrid precoding algorithm for mmWave massive MIMO networks based on the idea of RF chains… More >

  • Open Access

    ARTICLE

    Resistance to Malicious Packet Droppers Through Enhanced AODV in a MANET

    Shirina Samreen*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4087-4106, 2022, DOI:10.32604/cmc.2022.026141

    Abstract Packet dropping in a mobile ad hoc network can manifest itself as the data plane attacks as well as control plane attacks. The former deal with malicious nodes performing packet drop on the data packets following the route formation and the latter deal with those malicious nodes which either drop or manipulate the control packets to degrade the network performance. The idea of the proposed approach is that during the route establishment, each of the on-path nodes is provided with pre-computed hash values which have to be used to provide a unique acknowledgement value to the upstream neighbor which acts… More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Prostate Cancer Classification Model Using Biomedical Images

    Areej A. Malibari1, Reem Alshahrani2, Fahd N. Al-Wesabi3,*, Siwar Ben Haj Hassine3, Mimouna Abdullah Alkhonaini4, Anwer Mustafa Hilal5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3799-3813, 2022, DOI:10.32604/cmc.2022.026131

    Abstract Medical image processing becomes a hot research topic in healthcare sector for effective decision making and diagnoses of diseases. Magnetic resonance imaging (MRI) is a widely utilized tool for the classification and detection of prostate cancer. Since the manual screening process of prostate cancer is difficult, automated diagnostic methods become essential. This study develops a novel Deep Learning based Prostate Cancer Classification (DTL-PSCC) model using MRI images. The presented DTL-PSCC technique encompasses EfficientNet based feature extractor for the generation of a set of feature vectors. In addition, the fuzzy k-nearest neighbour (FKNN) model is utilized for classification process where the… More >

  • Open Access

    ARTICLE

    Enhance Vertical Handover Security During Execution Phase in Mobile Networks

    Omar Khattab*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3863-3875, 2022, DOI:10.32604/cmc.2022.026102

    Abstract The Vertical Handover (VHO) is one of the most vital features provided for the heterogeneous mobile networks. It allows Mobile Users (MUs) to keep ongoing sessions without disruption while they continuously move between different Radio Access Technologies (RATs) such as Wireless Fidelity (Wi-Fi), Global System for Mobile Communication (GSM), Universal Mobile Telecommunications System (UMTS), Long Term Evolution (LTE) and Fifth Generation (5G). In order to fulfill this goal, the VHO must comply to three main phases: starting of collecting the required information and then passing it for decision phase to obtain the best available RAT for performing VHO by execution… More >

  • Open Access

    ARTICLE

    Sustainable Energy Management with Traffic Prediction Strategy for Autonomous Vehicle Systems

    Manar Ahmed Hamza1,*, Masoud Alajmi2, Jaber S. Alzahrani3, Siwar Ben Haj Hassine4, Abdelwahed Motwakel1, Ishfaq Yaseen1

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3465-3479, 2022, DOI:10.32604/cmc.2022.026066

    Abstract Recent advancements of the intelligent transportation system (ITS) provide an effective way of improving the overall efficiency of the energy management strategy (EMSs) for autonomous vehicles (AVs). The use of AVs possesses many advantages such as congestion control, accident prevention, and etc. However, energy management and traffic flow prediction (TFP) still remains a challenging problem in AVs. The complexity and uncertainties of driving situations adequately affect the outcome of the designed EMSs. In this view, this paper presents novel sustainable energy management with traffic flow prediction strategy (SEM-TPS) for AVs. The SEM-TPS technique applies type II fuzzy logic system (T2FLS)… More >

  • Open Access

    ARTICLE

    Heart Disease Diagnosis Using the Brute Force Algorithm and Machine Learning Techniques

    Junaid Rashid1, Samina Kanwal2, Jungeun Kim1,*, Muhammad Wasif Nisar2, Usman Naseem3, Amir Hussain4

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3195-3211, 2022, DOI:10.32604/cmc.2022.026064

    Abstract Heart disease is one of the leading causes of death in the world today. Prediction of heart disease is a prominent topic in the clinical data processing. To increase patient survival rates, early diagnosis of heart disease is an important field of research in the medical field. There are many studies on the prediction of heart disease, but limited work is done on the selection of features. The selection of features is one of the best techniques for the diagnosis of heart diseases. In this research paper, we find optimal features using the brute-force algorithm, and machine learning techniques are… More >

  • Open Access

    ARTICLE

    An Eco-Friendly Approach for Reducing Carbon Emissions in Cloud Data Centers

    Mohammad Aldossary1,*, Hatem A. Alharbi2

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3175-3193, 2022, DOI:10.32604/cmc.2022.026041

    Abstract Based on the Saudi Green initiative, which aims to improve the Kingdom's environmental status and reduce the carbon emission of more than 278 million tons by 2030 along with a promising plan to achieve net-zero carbon by 2060, NEOM city has been proposed to be the “Saudi hub” for green energy, since NEOM is estimated to generate up to 120 Gigawatts (GW) of renewable energy by 2030. Nevertheless, the Information and Communication Technology (ICT) sector is considered a key contributor to global energy consumption and carbon emissions. The data centers are estimated to consume about 13% of the overall global… More >

  • Open Access

    ARTICLE

    An Efficient Scheme for Data Pattern Matching in IoT Networks

    Ashraf Ali*, Omar A. Saraereh

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2203-2219, 2022, DOI:10.32604/cmc.2022.025994

    Abstract The Internet has become an unavoidable trend of all things due to the rapid growth of networking technology, smart home technology encompasses a variety of sectors, including intelligent transportation, allowing users to communicate with anybody or any device at any time and from anywhere. However, most things are different now. Background: Structured data is a form of separated storage that slows down the rate at which everything is connected. Data pattern matching is commonly used in data connectivity and can help with the issues mentioned above. Aim: The present pattern matching system is ineffective due to the heterogeneity and rapid… More >

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