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  • Open Access

    ARTICLE

    Powering Mobile Networks with Optimal Green Energy for Sustainable Development

    Mohammed H. Alsharif1, Mahmoud A. Albreem2, Abu Jahid3, Kannadasan Raju4, Peerapong Uthansakul5,*, Jamel Nebhen6, Venkatesan Chandrasekaran4, Ayman A. Aly7

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 661-677, 2021, DOI:10.32604/cmc.2021.017059

    Abstract Green wireless networking is an emerging area for many societies, especially academia and industry, in light of economic and ecological perspectives. Empowering wireless infrastructures exploiting green power sources can enhance sustainability due to the adverse effects of conventional power sources and atmospheric circumstances. Moreover, the specific power supply requirements for a base station (BS), such as cost effectiveness, efficiency, sustainability, and reliability, can be met by utilizing technological advances in renewable energy. Numerous drivers and motivators are involved in the deployment of renewable energy technologies and the transition toward green energy. Renewable energy is free, clean, and abundant in most… More >

  • Open Access

    ARTICLE

    Detecting Man-in-the-Middle Attack in Fog Computing for Social Media

    Farouq Aliyu1,*, Tarek Sheltami1, Ashraf Mahmoud1, Louai Al-Awami1, Ansar Yasar2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1159-1181, 2021, DOI:10.32604/cmc.2021.016938

    Abstract Fog computing (FC) is a networking paradigm where wireless devices known as fog nodes are placed at the edge of the network (close to the Internet of Things (IoT) devices). Fog nodes provide services in lieu of the cloud. Thus, improving the performance of the network and making it attractive to social media-based systems. Security issues are one of the most challenges encountered in FC. In this paper, we propose an anomaly-based Intrusion Detection and Prevention System (IDPS) against Man-in-the-Middle (MITM) attack in the fog layer. The system uses special nodes known as Intrusion Detection System (IDS) nodes to detect… More >

  • Open Access

    ARTICLE

    Efficient MAC Protocols for Brain Computer Interface Applications

    Shams Al Ajrawi1,*, Ramesh Rao2, Mahasweta Sarkar3

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 589-605, 2021, DOI:10.32604/cmc.2021.016930

    Abstract Brain computer interface (BCI) systems permit individuals with motor disorders to utilize their thoughts as a mean to control external devices. BCI is a promising interdisciplinary field that gained the attention of many researchers. Yet, the development of BCI systems is facing several challenges, such as network lifetime. The Medium Access Control (MAC) Protocol is the bottle- neck of network reliability. There are many MAC protocols that can be utilized for dependable transmission in BCI applications by altering their control parameters. However, modifying these parameters is another source of concern due to the scarcity in knowledge about the effect of… More >

  • Open Access

    ARTICLE

    Sentiment Analysis of Short Texts Based on Parallel DenseNet

    Luqi Yan1, Jin Han1,*, Yishi Yue2, Liu Zhang2, Yannan Qian3

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 51-65, 2021, DOI:10.32604/cmc.2021.016920

    Abstract Text sentiment analysis is a common problem in the field of natural language processing that is often resolved by using convolutional neural networks (CNNs). However, most of these CNN models focus only on learning local features while ignoring global features. In this paper, based on traditional densely connected convolutional networks (DenseNet), a parallel DenseNet is proposed to realize sentiment analysis of short texts. First, this paper proposes two novel feature extraction blocks that are based on DenseNet and a multi-scale convolutional neural network. Second, this paper solves the problem of ignoring global features in traditional CNN models by combining the… More >

  • Open Access

    ARTICLE

    Parametric Methods for the Regional Assessment of Cardiac Wall Motion Abnormalities: Comparison Study

    Narjes Benameur1,*, Mazin Abed Mohammed2, Ramzi Mahmoudi3,4, Younes Arous5, Begonya Garcia-Zapirain6, Karrar Hameed Abdulkareem7, Mohamed Hedi Bedoui3

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1233-1252, 2021, DOI:10.32604/cmc.2021.016860

    Abstract Left ventricular (LV) dysfunction is mainly assessed by global contractile indices such as ejection fraction and LV Volumes in cardiac MRI. While these indices give information about the presence or not of LV alteration, they are not able to identify the location and the size of such alteration. The aim of this study is to compare the performance of three parametric imaging techniques used in cardiac MRI for the regional quantification of cardiac dysfunction. The proposed approaches were evaluated on 20 patients with myocardial infarction and 20 subjects with normal function. Three parametric images approaches: covariance analysis, parametric images based… More >

  • Open Access

    ARTICLE

    COVID19 Classification Using CT Images via Ensembles of Deep Learning Models

    Abdul Majid1, Muhammad Attique Khan1, Yunyoung Nam2,*, Usman Tariq3, Sudipta Roy4, Reham R. Mostafa5, Rasha H. Sakr6

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 319-337, 2021, DOI:10.32604/cmc.2021.016816

    Abstract The recent COVID-19 pandemic caused by the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a significant impact on human life and the economy around the world. A reverse transcription polymerase chain reaction (RT-PCR) test is used to screen for this disease, but its low sensitivity means that it is not sufficient for early detection and treatment. As RT-PCR is a time-consuming procedure, there is interest in the introduction of automated techniques for diagnosis. Deep learning has a key role to play in the field of medical imaging. The most important issue in this area is the… More >

  • Open Access

    ARTICLE

    Immersion Analysis Through Eye-Tracking and Audio in Virtual Reality

    Jihoon Lee, Nammee Moon*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 647-660, 2021, DOI:10.32604/cmc.2021.016712

    Abstract In this study, using Head Mounted Display (HMD), which is one of the biggest advantage of Virtual Reality (VR) environment, tracks the user’s gaze in 360° video content, and examines how the gaze pattern is distributed according to the user’s immersion. As a result of analyzing the gaze pattern distribution of contents with high user immersion and contents with low user immersion through a questionnaire, it was confirmed that the higher the immersion, the more the gaze distribution tends to be concentrated in the center of the screen. Through this experiment, we were able to understand the factors that make… More >

  • Open Access

    ARTICLE

    Evolution-Based Performance Prediction of Star Cricketers

    Haseeb Ahmad1, Shahbaz Ahmad1, Muhammad Asif1, Mobashar Rehman2,*, Abdullah Alharbi3, Zahid Ullah4

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1215-1232, 2021, DOI:10.32604/cmc.2021.016659

    Abstract Cricket databases contain rich and useful information to examine and forecasting patterns and trends. This paper predicts Star Cricketers (SCs) from batting and bowling domains by employing supervised machine learning models. With this aim, each player’s performance evolution is retrieved by using effective features that incorporate the standard performance measures of each player and their peers. Prediction is performed by applying Bayesian-rule, function and decision-tree-based models. Experimental evaluations are performed to validate the applicability of the proposed approach. In particular, the impact of the individual features on the prediction of SCs are analyzed. Moreover, the category and model-wise feature evaluations… More >

  • Open Access

    ARTICLE

    Mining Software Repository for Cleaning Bugs Using Data Mining Technique

    Nasir Mahmood1, Yaser Hafeez1, Khalid Iqbal2, Shariq Hussain3, Muhammad Aqib1, Muhammad Jamal4, Oh-Young Song5,*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 873-893, 2021, DOI:10.32604/cmc.2021.016614

    Abstract Despite advances in technological complexity and efforts, software repository maintenance requires reusing the data to reduce the effort and complexity. However, increasing ambiguity, irrelevance, and bugs while extracting similar data during software development generate a large amount of data from those data that reside in repositories. Thus, there is a need for a repository mining technique for relevant and bug-free data prediction. This paper proposes a fault prediction approach using a data-mining technique to find good predictors for high-quality software. To predict errors in mining data, the Apriori algorithm was used to discover association rules by fixing confidence at more… More >

  • Open Access

    ARTICLE

    Mobility Management in Small Cell Cluster of Cellular Network

    Adeel Rafiq, Muhammad Afaq, Khizar Abbas, Wang-Cheol Song*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 627-645, 2021, DOI:10.32604/cmc.2021.016529

    Abstract The installation of small cells in a 5G network extends the maximum coverage and provides high availability. However, this approach increases the handover overhead in the Core Network (CN) due to frequent handoffs. The variation of user density and movement inside a region of small cells also increases the handover overhead in CN. However, the present 5G system cannot reduce the handover overhead in CN under such circumstances because it relies on a traditionally rigid and complex hierarchical sequence for a handover procedure. Recently, Not Only Stack (NO Stack) architecture has been introduced for Radio Access Network (RAN) to reduce… More >

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