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  • Open Access

    ARTICLE

    Investigating and Modelling of Task Offloading Latency in Edge-Cloud Environment

    Jaber Almutairi1, Mohammad Aldossary2,*,*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4143-4160, 2021, DOI:10.32604/cmc.2021.018145

    Abstract Recently, the number of Internet of Things (IoT) devices connected to the Internet has increased dramatically as well as the data produced by these devices. This would require offloading IoT tasks to release heavy computation and storage to the resource-rich nodes such as Edge Computing and Cloud Computing. However, different service architecture and offloading strategies have a different impact on the service time performance of IoT applications. Therefore, this paper presents an Edge-Cloud system architecture that supports scheduling offloading tasks of IoT applications in order to minimize the enormous amount of transmitting data in the network. Also, it introduces the… More >

  • Open Access

    ARTICLE

    Virtual Reality-Based Random Dot Kinematogram

    Jun Ma1, Hyo-Jung Kim2, Ji-Soo Kim3,4, Eek-Sung Lee5, Min Hong6,*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4205-4213, 2021, DOI:10.32604/cmc.2021.018080

    Abstract This research implements a random dot kinematogram (RDK) using virtual reality (VR) and analyzes the results based on normal subjects. Visual motion perception is one of visual functions localized to a specific cortical area, the human motion perception area (human analogue for the middle temporal/middle superior temporal area) located in the parieto–occipito–temporal junction of the human brain. The RDK measures visual motion perception capabilities. The stimuli in conventional RDK methods are presented using a monitor screen, so these devices require a spacious dark room for installation and use. Recently, VR technology has been implemented in different medical domains. The test… More >

  • Open Access

    ARTICLE

    Bit Rate Reduction in Cloud Gaming Using Object Detection Technique

    Daniyal Baig1, Tahir Alyas1, Muhammad Hamid2, Muhammad Saleem3, Saadia Malik4, Nadia Tabassum5,*, Natash Ali Mian6

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3653-3669, 2021, DOI:10.32604/cmc.2021.017948

    Abstract The past two decades witnessed a broad-increase in web technology and on-line gaming. Enhancing the broadband confinements is viewed as one of the most significant variables that prompted new gaming technology. The immense utilization of web applications and games additionally prompted growth in the handled devices and moving the limited gaming experience from user devices to online cloud servers. As internet capabilities are enhanced new ways of gaming are being used to improve the gaming experience. In cloud-based video gaming, game engines are hosted in cloud gaming data centers, and compressed gaming scenes are rendered to the players over the… More >

  • Open Access

    ARTICLE

    A Secure Intrusion Detection System in Cyberphysical Systems Using a Parameter-Tuned Deep-Stacked Autoencoder

    Nojood O. Aljehane*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3915-3929, 2021, DOI:10.32604/cmc.2021.017905

    Abstract Cyber physical systems (CPSs) are a networked system of cyber (computation, communication) and physical (sensors, actuators) elements that interact in a feedback loop with the assistance of human interference. Generally, CPSs authorize critical infrastructures and are considered to be important in the daily lives of humans because they form the basis of future smart devices. Increased utilization of CPSs, however, poses many threats, which may be of major significance for users. Such security issues in CPSs represent a global issue; therefore, developing a robust, secure, and effective CPS is currently a hot research topic. To resolve this issue, an intrusion… More >

  • Open Access

    ARTICLE

    Mobile Memory Management System Based on User’s Application Usage Patterns

    Jaehwan Lee, Sangoh Park*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4031-4050, 2021, DOI:10.32604/cmc.2021.017872

    Abstract Currently, the number of functions to improve user convenience in smartphone applications is increasing. In addition, more mobile applications are being loaded into mobile operating system memory for faster launches, thus increasing the memory requirements for smartphones. The memory used by applications in mobile operating systems is managed using software; allocated memory is freed up by either considering the usage state of the application or terminating the least recently used (LRU) application. As LRU-based memory management schemes do not consider the application launch frequency in a low memory situation, currently used mobile operating systems can lead to the termination of… More >

  • Open Access

    ARTICLE

    DTLM-DBP: Deep Transfer Learning Models for DNA Binding Proteins Identification

    Sara Saber1, Uswah Khairuddin2,*, Rubiyah Yusof2, Ahmed Madani1

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3563-3576, 2021, DOI:10.32604/cmc.2021.017769

    Abstract The identification of DNA binding proteins (DNABPs) is considered a major challenge in genome annotation because they are linked to several important applied and research applications of cellular functions e.g., in the study of the biological, biophysical, and biochemical effects of antibiotics, drugs, and steroids on DNA. This paper presents an efficient approach for DNABPs identification based on deep transfer learning, named “DTLM-DBP.” Two transfer learning methods are used in the identification process. The first is based on the pre-trained deep learning model as a feature’s extractor and classifier. Two different pre-trained Convolutional Neural Networks (CNN), AlexNet 8 and VGG… More >

  • Open Access

    ARTICLE

    Research on Forecasting Flowering Phase of Pear Tree Based on Neural Network

    Zhenzhou Wang1, Yinuo Ma1, Pingping Yu1,*, Ning Cao2, Heiner Dintera3

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3431-3446, 2021, DOI:10.32604/cmc.2021.017729

    Abstract Predicting the blooming season of ornamental plants is significant for guiding adjustments in production decisions and providing viewing periods and routes. The current strategies for observation of ornamental plant booming periods are mainly based on manpower and experience, which have problems such as inaccurate recognition time, time-consuming and energy sapping. Therefore, this paper proposes a neural network-based method for predicting the flowering phase of pear tree. Firstly, based on the meteorological observation data of Shijiazhuang Meteorological Station from 2000 to 2019, three principal components (the temperature factor, weather factor, and humidity factor) with high correlation coefficient with the flowering phase… More >

  • Open Access

    ARTICLE

    Arabic Feature-Based Text Watermarking Technique for Sensitive Detecting Tampering Attack

    Fahd N. Al-Wesabi1,2,*, Huda G. Iskandar2,3, Saleh Alzahrani4, Abdelzahir Abdelmaboud4, Mohammed Abdul4, Nadhem Nemri4, Mohammad Medani4, Mohammed Y. Alghamdi5

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3789-3806, 2021, DOI:10.32604/cmc.2021.017674

    Abstract In this article, a high-sensitive approach for detecting tampering attacks on transmitted Arabic-text over the Internet (HFDATAI) is proposed by integrating digital watermarking and hidden Markov model as a strategy for soft computing. The HFDATAI solution technically integrates and senses the watermark without modifying the original text. The alphanumeric mechanism order in the first stage focused on the Markov model key secret is incorporated into an automated, null-watermarking approach to enhance the proposed approach’s efficiency, accuracy, and intensity. The first-level order and alphanumeric Markov model technique have been used as a strategy for soft computing to analyze the text of… More >

  • Open Access

    ARTICLE

    Enhanced Deep Autoencoder Based Feature Representation Learning for Intelligent Intrusion Detection System

    Thavavel Vaiyapuri*, Adel Binbusayyis

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3271-3288, 2021, DOI:10.32604/cmc.2021.017665

    Abstract In the era of Big data, learning discriminant feature representation from network traffic is identified has as an invariably essential task for improving the detection ability of an intrusion detection system (IDS). Owing to the lack of accurately labeled network traffic data, many unsupervised feature representation learning models have been proposed with state-of-the-art performance. Yet, these models fail to consider the classification error while learning the feature representation. Intuitively, the learnt feature representation may degrade the performance of the classification task. For the first time in the field of intrusion detection, this paper proposes an unsupervised IDS model leveraging the… More >

  • Open Access

    ARTICLE

    Hybrid Nanofluid Flow with Homogeneous-Heterogeneous Reactions

    Iskandar Waini1,2, Anuar Ishak2,*, Ioan Pop3

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3255-3269, 2021, DOI:10.32604/cmc.2021.017643

    Abstract This study examines the stagnation point flow over a stretching/shrinking sheet in a hybrid nanofluid with homogeneous-heterogeneous reactions. The hybrid nanofluid consists of copper (Cu) and alumina (Al2O3) nanoparticles which are added into water to form Cu-Al2O3/water hybrid nanofluid. The similarity equations are obtained using a similarity transformation. Then, the function bvp4c in MATLAB is utilised to obtain the numerical results. The dual solutions are found for limited values of the stretching/shrinking parameter. Also, the turning point arises in the shrinking region (λ < 0). Besides, the presence of hybrid nanoparticles enhances the heat transfer rate, skin friction coefficient, and… More >

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