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  • Open Access

    ARTICLE

    Intelligent Deep Learning Model for Privacy Preserving IIoT on 6G Environment

    Anwer Mustafa Hilal1,*, Jaber S. Alzahrani2, Ibrahim Abunadi3, Nadhem Nemri4, Fahd N. Al-Wesabi5,6, Abdelwahed Motwakel1, Ishfaq Yaseen1, Abu Sarwar Zamani1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 333-348, 2022, DOI:10.32604/cmc.2022.024794 - 24 February 2022

    Abstract In recent times, Industrial Internet of Things (IIoT) experiences a high risk of cyber attacks which needs to be resolved. Blockchain technology can be incorporated into IIoT system to help the entrepreneurs realize Industry 4.0 by overcoming such cyber attacks. Although blockchain-based IIoT network renders a significant support and meet the service requirements of next generation network, the performance arrived at, in existing studies still needs improvement. In this scenario, the current research paper develops a new Privacy-Preserving Blockchain with Deep Learning model for Industrial IoT (PPBDL-IIoT) on 6G environment. The proposed PPBDL-IIoT technique aims… More >

  • Open Access

    ARTICLE

    Encryption with Image Steganography Based Data Hiding Technique in IIoT Environment

    Mahmoud Ragab1,2,3,*, Samah Alshehri4, Hani A. Alhadrami5,6,7, Faris Kateb1, Ehab Bahaudien Ashary8, S. Abdel-khalek9,10

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1323-1338, 2022, DOI:10.32604/cmc.2022.024775 - 24 February 2022

    Abstract Rapid advancements of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) pose serious security issues by revealing secret data. Therefore, security data becomes a crucial issue in IIoT communication where secrecy needs to be guaranteed in real time. Practically, AI techniques can be utilized to design image steganographic techniques in IIoT. In addition, encryption techniques act as an important role to save the actual information generated from the IIoT devices to avoid unauthorized access. In order to accomplish secure data transmission in IIoT environment, this study presents novel encryption with image steganography based… More >

  • Open Access

    ARTICLE

    Machine Learning Enabled e-Learner Non-Verbal Behavior Detection in IoT Environment

    Abdelzahir Abdelmaboud1, Fahd N. Al-Wesabi1,2,3, Mesfer Al Duhayyim4, Taiseer Abdalla Elfadil Eisa5, Manar Ahmed Hamza6,*, Mohammed Rizwanullah6, Abu Serwar Zamani6, Radwa Marzouk7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 679-693, 2022, DOI:10.32604/cmc.2022.024240 - 24 February 2022

    Abstract Internet of Things (IoT) with e-learning is widely employed to collect data from various smart devices and share it with other ones for efficient e-learning applications. At the same time, machine learning (ML) and data mining approaches are presented for accomplishing prediction and classification processes. With this motivation, this study focuses on the design of intelligent machine learning enabled e-learner non-verbal behaviour detection (IML-ELNVBD) in IoT environment. The proposed IML-ELNVBD technique allows the IoT devices such as audio sensors, cameras, etc. which are then connected to the cloud server for further processing. In addition, the More >

  • Open Access

    ARTICLE

    Hybrid Deep Learning Enabled Air Pollution Monitoring in ITS Environment

    Ashit Kumar Dutta1, Jenyfal Sampson2, Sultan Ahmad3, T. Avudaiappan4, Kanagaraj Narayanasamy5,*, Irina V. Pustokhina6, Denis A. Pustokhin7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1157-1172, 2022, DOI:10.32604/cmc.2022.024109 - 24 February 2022

    Abstract Intelligent Transportation Systems (ITS) have become a vital part in improving human lives and modern economy. It aims at enhancing road safety and environmental quality. There is a tremendous increase observed in the number of vehicles in recent years, owing to increasing population. Each vehicle has its own individual emission rate; however, the issue arises when the emission rate crosses a standard value. Owing to the technological advances made in Artificial Intelligence (AI) techniques, it is easy to leverage it to develop prediction approaches so as to monitor and control air pollution. The current research… More >

  • Open Access

    ARTICLE

    Computer-Vision Based Object Detection and Recognition for Service Robot in Indoor Environment

    Kiran Jot Singh1, Divneet Singh Kapoor1,*, Khushal Thakur1, Anshul Sharma1, Xiao-Zhi Gao2

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 197-213, 2022, DOI:10.32604/cmc.2022.022989 - 24 February 2022

    Abstract The near future has been envisioned as a collaboration of humans with mobile robots to help in the day-to-day tasks. In this paper, we present a viable approach for a real-time computer vision based object detection and recognition for efficient indoor navigation of a mobile robot. The mobile robotic systems are utilized mainly for home assistance, emergency services and surveillance, in which critical action needs to be taken within a fraction of second or real-time. The object detection and recognition is enhanced with utilization of the proposed algorithm based on the modification of You Look… More >

  • Open Access

    ARTICLE

    Weighted-adaptive Inertia Strategy for Multi-objective Scheduling in Multi-clouds

    Mazen Farid1,3,*, Rohaya Latip1,2, Masnida Hussin1, Nor Asilah Wati Abdul Hamid1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1529-1560, 2022, DOI:10.32604/cmc.2022.021410 - 24 February 2022

    Abstract One of the fundamental problems associated with scheduling workflows on virtual machines in a multi-cloud environment is how to find a near-optimum permutation. The workflow scheduling involves assigning independent computational jobs with conflicting objectives to a set of virtual machines. Most optimization methods for solving non-deterministic polynomial-time hardness (NP-hard) problems deploy multi-objective algorithms. As such, Pareto dominance is one of the most efficient criteria for determining the best solutions within the Pareto front. However, the main drawback of this method is that it requires a reasonably long time to provide an optimum solution. In this… More >

  • Open Access

    ARTICLE

    Intelligent Control of Cabin Environment Using Computational Fluid Dynamics for Intelligent Manufacturing

    Xi Wang*, Guangping Zeng

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.3, pp. 563-576, 2022, DOI:10.32604/fdmp.2022.017884 - 22 February 2022

    Abstract An efficient and versatile intelligent algorithm is developed for the control of the cabin environment of wind power generators. The method can be used to monitor and solve wind power generation problems at the same time. It also provides several advantages with respect to other traditional methods which imply significant workload and maintenance personnel. The functional requirements of the intelligent control system are analyzed, and a control algorithm for the stepping motor is selected and evaluated. Through the comparative analysis of the active power and internal temperature curve for three kinds of output power of More >

  • Open Access

    ARTICLE

    Cost Effective Optimal Task Scheduling Model in Hybrid Cloud Environment

    M. Manikandan1,*, R. Subramanian2, M. S. Kavitha3, S. Karthik3

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 935-948, 2022, DOI:10.32604/csse.2022.021816 - 08 February 2022

    Abstract In today’s world, Cloud Computing (CC) enables the users to access computing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located in remote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and task scheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud is employed since it is a capable solution to process large-scale… More >

  • Open Access

    REVIEW

    Microenvironment promotes cytoskeleton remodeling and adaptive phenotypic transition

    MARIANO BIZZARRI*, PAOLA PONTECORVI

    BIOCELL, Vol.46, No.6, pp. 1357-1362, 2022, DOI:10.32604/biocell.2022.018471 - 07 February 2022

    Abstract The cytoskeleton includes three main classes of networked filaments behaving as a coherent and complex structure that confers stability to cell shape while serving as sensor of internal/extracellular changes. Microenvironmental stimuli interfere with the non-linear dynamics that govern cytoskeleton architecture, namely by fostering symmetry breakings and transitions across different phenotypic states. Such process induces a wholecoherent adaptive response, involving the reprogramming of biochemical and gene-expression patterns. These characteristics are especially relevant during development, and in those conditions in which a deregulated crosstalk between cells and the stroma is at the core of the pathological process. More >

  • Open Access

    ARTICLE

    Strategy for Creating AR Applications in Static and Dynamic Environments Using SLAM- and Marker Detector-Based Tracking

    Chanho Park1,2, Hyunwoo Cho1, Sangheon Park1, Sung-Uk Jung1, Suwon Lee3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 529-549, 2022, DOI:10.32604/cmes.2022.019214 - 24 January 2022

    Abstract Recently, simultaneous localization and mapping (SLAM) has received considerable attention in augmented reality (AR) libraries and applications. Although the assumption of scene rigidity is common in most visual SLAMs, this assumption limits the possibilities of AR applications in various real-world environments. In this paper, we propose a new tracking system that integrates SLAM with a marker detection module for real-time AR applications in static and dynamic environments. Because the proposed system assumes that the marker is movable, SLAM performs tracking and mapping of the static scene except for the marker, and the marker detector estimates… More >

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