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  • Open Access

    ARTICLE

    Chaos-Based Cryptographic Mechanism for Smart Healthcare IoT Systems

    Muhammad Samiullah1, Waqar Aslam1, Arif Mehmood1, Muhammad Saeed Ahmad2, Shafiq Ahmad3, Adel M. Al-Shayea3, Muhammad Shafiq4,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 753-769, 2022, DOI:10.32604/cmc.2022.020432

    Abstract Smart and interconnected devices can generate meaningful patient data and exchange it automatically without any human intervention in order to realize the Internet of Things (IoT) in healthcare (HIoT). Due to more and more online security and data hijacking attacks, the confidentiality, integrity and availability of data are considered serious issues in HIoT applications. In this regard, lightweight block ciphers (LBCs) are promising in resource-constrained environment where security is the primary consideration. The prevalent challenge while designing an LBC for the HIoT environment is how to ascertain platform performance, cost, and security. Most of the existing LBCs primarily focus on… More >

  • Open Access

    ARTICLE

    AGWO-CNN Classification for Computer-Assisted Diagnosis of Brain Tumors

    T. Jeslin1,*, J. Arul Linsely2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 171-182, 2022, DOI:10.32604/cmc.2022.020255

    Abstract Brain cancer is the premier reason for cancer deaths all over the world. The diagnosis of brain cancer at an initial stage is mediocre, as the radiologist is ineffectual. Different experiments have been conducted and demonstrated clearly that the algorithms for nodule segmentation are unsuccessful. Therefore, the research has consolidated incremental clustering focused on superpixel segmentation as an appropriate optimization approach for the accurate segmentation of pulmonary nodules. The key aim of the research is to refine brain CT images to accurately distinguish tumors and the segmentation of small-scale anomalous nodules in the brain region. In the beginning stage, an… More >

  • Open Access

    ARTICLE

    IoT & AI Enabled Three-Phase Secure and Non-Invasive COVID 19 Diagnosis System

    Anurag Jain1, Kusum Yadav2, Hadeel Fahad Alharbi2, Shamik Tiwari1,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 423-438, 2022, DOI:10.32604/cmc.2022.020238

    Abstract Corona is a viral disease that has taken the form of an epidemic and is causing havoc worldwide after its first appearance in the Wuhan state of China in December 2019. Due to the similarity in initial symptoms with viral fever, it is challenging to identify this virus initially. Non-detection of this virus at the early stage results in the death of the patient. Developing and densely populated countries face a scarcity of resources like hospitals, ventilators, oxygen, and healthcare workers. Technologies like the Internet of Things (IoT) and artificial intelligence can play a vital role in diagnosing the COVID-19… More >

  • Open Access

    ARTICLE

    A Quantum Algorithm for Evaluating the Hamming Distance

    Mohammed Zidan1,2,*, Manal G. Eldin3, Mahmoud Y. Shams4, Mohamed Tolan5,6, Ayman Abd-Elhamed2,7, Mahmoud Abdel-Aty8

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1065-1078, 2022, DOI:10.32604/cmc.2022.020103

    Abstract We present a novel quantum algorithm to evaluate the hamming distance between two unknown oracles via measuring the degree of entanglement between two ancillary qubits. In particular, we use the power of the entanglement degree based quantum computing model that preserves at most the locality of interactions within the quantum model structure. This model uses one of two techniques to retrieve the solution of a quantum computing problem at hand. In the first technique, the solution of the problem is obtained based on whether there is an entanglement between the two ancillary qubits or not. In the second, the solution… More >

  • Open Access

    REVIEW

    Optimization of Reliability–Redundancy Allocation Problems: A Review of the Evolutionary Algorithms

    Haykel Marouani1,2, Omar Al-mutiri1,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 537-571, 2022, DOI:10.32604/cmc.2022.020098

    Abstract The study of optimization methods for reliability–redundancy allocation problems is a constantly changing field. New algorithms are continually being designed on the basis of observations of nature, wildlife, and humanity. In this paper, we review eight major evolutionary algorithms that emulate the behavior of civilization, ants, bees, fishes, and birds (i.e., genetic algorithms, bee colony optimization, simulated annealing, particle swarm optimization, biogeography-based optimization, artificial immune system optimization, cuckoo algorithm and imperialist competitive algorithm). We evaluate the mathematical formulations and pseudo-codes of each algorithm and discuss how these apply to reliability–redundancy allocation problems. Results from a literature survey show the best… More >

  • Open Access

    ARTICLE

    Benchmarking Performance of Document Level Classification and Topic Modeling

    Muhammad Shahid Bhatti1,*, Azmat Ullah1, Rohaya Latip2, Abid Sohail1, Anum Riaz1, Rohail Hassan3

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 125-141, 2022, DOI:10.32604/cmc.2022.020083

    Abstract Text classification of low resource language is always a trivial and challenging problem. This paper discusses the process of Urdu news classification and Urdu documents similarity. Urdu is one of the most famous spoken languages in Asia. The implementation of computational methodologies for text classification has increased over time. However, Urdu language has not much experimented with research, it does not have readily available datasets, which turn out to be the primary reason behind limited research and applying the latest methodologies to the Urdu. To overcome these obstacles, a medium-sized dataset having six categories is collected from authentic Pakistani news… More >

  • Open Access

    ARTICLE

    FPGA Implementation of Deep Leaning Model for Video Analytics

    P. N. Palanisamy*, N. Malmurugan

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 791-808, 2022, DOI:10.32604/cmc.2022.019921

    Abstract In recent years, deep neural networks have become a fascinating and influential research subject, and they play a critical role in video processing and analytics. Since, video analytics are predominantly hardware centric, exploration of implementing the deep neural networks in the hardware needs its brighter light of research. However, the computational complexity and resource constraints of deep neural networks are increasing exponentially by time. Convolutional neural networks are one of the most popular deep learning architecture especially for image classification and video analytics. But these algorithms need an efficient implement strategy for incorporating more real time computations in terms of… More >

  • Open Access

    ARTICLE

    Fuzzy Based Hybrid Focus Value Estimation for Multi Focus Image Fusion

    Muhammad Ahmad1,*, M. Arfan Jaffar1, Fawad Nasim1, Tehreem Masood1, Sheeraz Akram2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 735-752, 2022, DOI:10.32604/cmc.2022.019691

    Abstract

    Due to limited depth-of-field of digital single-lens reflex cameras, the scene content within a limited distance from the imaging plane remains in focus while other objects closer to or further away from the point of focus appear as blurred (out-of-focus) in the image. Multi-Focus Image Fusion can be used to reconstruct a fully focused image from two or more partially focused images of the same scene. In this paper, a new Fuzzy Based Hybrid Focus Measure (FBHFM) for multi-focus image fusion has been proposed. Optimal block size is very critical step for multi-focus image fusion. Particle Swarm Optimization (PSO) algorithm… More >

  • Open Access

    ARTICLE

    Malicious Traffic Detection in IoT and Local Networks Using Stacked Ensemble Classifier

    R. D. Pubudu L. Indrasiri1, Ernesto Lee2, Vaibhav Rupapara3, Furqan Rustam4, Imran Ashraf5,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 489-515, 2022, DOI:10.32604/cmc.2022.019636

    Abstract Malicious traffic detection over the internet is one of the challenging areas for researchers to protect network infrastructures from any malicious activity. Several shortcomings of a network system can be leveraged by an attacker to get unauthorized access through malicious traffic. Safeguard from such attacks requires an efficient automatic system that can detect malicious traffic timely and avoid system damage. Currently, many automated systems can detect malicious activity, however, the efficacy and accuracy need further improvement to detect malicious traffic from multi-domain systems. The present study focuses on the detection of malicious traffic with high accuracy using machine learning techniques.… More >

  • Open Access

    ARTICLE

    Novel Architecture of OneM2M-Based Convergence Platform for Mixed Reality and IoT

    Seungwoon Lee1, Woogeun Kil1, Byeong-hee Roh1,*, SJ Kim2, Jin-suk Kang3

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 51-69, 2022, DOI:10.32604/cmc.2022.019635

    Abstract There have been numerous works proposed to merge augmented reality/mixed reality (AR/MR) and Internet of Things (IoT) in various ways. However, they have focused on their specific target applications and have limitations on interoperability or reusability when utilizing them to different domains or adding other devices to the system. This paper proposes a novel architecture of a convergence platform for AR/MR and IoT systems and services. The proposed architecture adopts the oneM2M IoT standard as the basic framework that converges AR/MR and IoT systems and enables the development of application services used in general-purpose environments without being subordinate to specific… More >

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