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  • Open Access

    ARTICLE

    Water Wave Optimization with Deep Learning Driven Smart Grid Stability Prediction

    Anwer Mustafa Hilal1,2,*, Aisha Hassan Abdalla Hashim1, Heba G. Mohamed3, Mohammad Alamgeer4,5, Mohamed K. Nour6, Anas Abdelrahman7, Abdelwahed Motwakel2

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6019-6035, 2022, DOI:10.32604/cmc.2022.031425

    Abstract Smart Grid (SG) technologies enable the acquisition of huge volumes of high dimension and multi-class data related to electric power grid operations through the integration of advanced metering infrastructures, control systems, and communication technologies. In SGs, user demand data is gathered and examined over the present supply criteria whereas the expenses are then informed to the clients so that they can decide about electricity consumption. Since the entire procedure is valued on the basis of time, it is essential to perform adaptive estimation of the SG’s stability. Recent advancements in Machine Learning (ML) and Deep Learning (DL) models enable the… More >

  • Open Access

    ARTICLE

    Generalization of Advanced Encryption Standard Based on Field of Any Characteristic

    Nabilah Abughazalah1, Majid Khan2,*, Noor Munir2, Ammar S. Alanazi3, Iqtadar Hussain4,5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6121-6138, 2022, DOI:10.32604/cmc.2022.031417

    Abstract Nowadays most communications are done by utilizing digital transmission mechanisms. The security of this digital information transmitted through different communication systems is quite important. The secrecy of digital data is one of the burning topics of the digitally developed world. There exist many traditional algorithms in the literature to provide methods for robust communication. The most important and recent modern block cipher named the advanced encryption standard (AES) is one of the extensively utilized encryption schemes with binary based. AES is a succession of four fundamental steps: round key, sub-byte, shift row, and mix column. In this work, we will… More >

  • Open Access

    ARTICLE

    Innovative Fungal Disease Diagnosis System Using Convolutional Neural Network

    Tahir Alyas1,*, Khalid Alissa2, Abdul Salam Mohammad3, Shazia Asif4, Tauqeer Faiz5, Gulzar Ahmed6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4869-4883, 2022, DOI:10.32604/cmc.2022.031376

    Abstract Fungal disease affects more than a billion people worldwide, resulting in different types of fungus diseases facing life-threatening infections. The outer layer of your body is called the integumentary system. Your skin, hair, nails, and glands are all part of it. These organs and tissues serve as your first line of defence against bacteria while protecting you from harm and the sun. The It serves as a barrier between the outside world and the regulated environment inside our bodies and a regulating effect. Heat, light, damage, and illness are all protected by it. Fungi-caused infections are found in almost every… More >

  • Open Access

    ARTICLE

    Metaheuristics Enabled Clustering with Routing Scheme for Wireless Sensor Networks

    Mashael M. Asiri1, Saud S. Alotaibi2, Dalia H. Elkamchouchi3, Amira Sayed A. Aziz4, Manar Ahmed Hamza5,*, Abdelwahed Motwakel5, Abu Sarwar Zamani5, Ishfaq Yaseen5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5491-5507, 2022, DOI:10.32604/cmc.2022.031345

    Abstract Wireless Sensor Network (WSN) is a vital element in Internet of Things (IoT) as the former enables the collection of huge quantities of data in energy-constrained environment. WSN offers independent access to the target region and performs data collection in an effective manner. But energy constraints remain a challenging issue in WSN since it operates on in-built battery. The studies conducted earlier recommended that the energy spent on communication process must be considerably reduced to improve the efficiency of WSN. Cluster organization and optimal selection of the routes are considered as NP hard optimization problems which can be resolved with… More >

  • Open Access

    ARTICLE

    Biomedical Osteosarcoma Image Classification Using Elephant Herd Optimization and Deep Learning

    Areej A. Malibari1, Jaber S. Alzahrani2, Marwa Obayya3, Noha Negm4,5, Mohammed Abdullah Al-Hagery6, Ahmed S. Salama7, Anwer Mustafa Hilal8,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6443-6459, 2022, DOI:10.32604/cmc.2022.031324

    Abstract Osteosarcoma is a type of malignant bone tumor that is reported across the globe. Recent advancements in Machine Learning (ML) and Deep Learning (DL) models enable the detection and classification of malignancies in biomedical images. In this regard, the current study introduces a new Biomedical Osteosarcoma Image Classification using Elephant Herd Optimization and Deep Transfer Learning (BOIC-EHODTL) model. The presented BOIC-EHODTL model examines the biomedical images to diagnose distinct kinds of osteosarcoma. At the initial stage, Gabor Filter (GF) is applied as a pre-processing technique to get rid of the noise from images. In addition, Adam optimizer with MixNet model… More >

  • Open Access

    ARTICLE

    An Improved Transfer-Learning for Image-Based Species Classification of Protected Indonesians Birds

    Chao-Lung Yang1, Yulius Harjoseputro2,3, Yu-Chen Hu4, Yung-Yao Chen2,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4577-4593, 2022, DOI:10.32604/cmc.2022.031305

    Abstract This research proposed an improved transfer-learning bird classification framework to achieve a more precise classification of Protected Indonesia Birds (PIB) which have been identified as the endangered bird species. The framework takes advantage of using the proposed sequence of Batch Normalization Dropout Fully-Connected (BNDFC) layers to enhance the baseline model of transfer learning. The main contribution of this work is the proposed sequence of BNDFC that can be applied to any Convolutional Neural Network (CNN) based model to improve the classification accuracy, especially for image-based species classification problems. The experiment results show that the proposed sequence of BNDFC layers outperform… More >

  • Open Access

    ARTICLE

    Hyperparameter Tuned Deep Learning Enabled Intrusion Detection on Internet of Everything Environment

    Manar Ahmed Hamza1,2,*, Aisha Hassan Abdalla Hashim1, Heba G. Mohamed3, Saud S. Alotaibi4, Hany Mahgoub5,6, Amal S. Mehanna7, Abdelwahed Motwakel2

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6579-6594, 2022, DOI:10.32604/cmc.2022.031303

    Abstract Internet of Everything (IoE), the recent technological advancement, represents an interconnected network of people, processes, data, and things. In recent times, IoE gained significant attention among entrepreneurs, individuals, and communities owing to its realization of intense values from the connected entities. On the other hand, the massive increase in data generation from IoE applications enables the transmission of big data, from context-aware machines, into useful data. Security and privacy pose serious challenges in designing IoE environment which can be addressed by developing effective Intrusion Detection Systems (IDS). In this background, the current study develops Intelligent Multiverse Optimization with Deep Learning… More >

  • Open Access

    ARTICLE

    Outage Probability Analysis of Free Space Communication System Using Diversity Combining Techniques

    Hasnain Kashif*, Muhammad Nasir Khan

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6001-6017, 2022, DOI:10.32604/cmc.2022.031291

    Abstract Recently, free space optical (FSO) communication is gaining much attention towards the research community. The reason for this attention is the promises of high data-rate, license-free deployment, and non-interfering links. It can, however, give rise to major system difficulties concerning alignment and atmospheric turbulence. FSO is the degradation in the signal quality because of atmospheric channel impairments and conditions. The worst effect is due to fog particles. Though, Radio Frequency (RF) links are able to transmit the data in foggy conditions but not in rain. To overcome these issues related to both the FSO and RF links. A free space… More >

  • Open Access

    ARTICLE

    Intelligent Medical Diagnostic System for Hepatitis B

    Dalwinder Singh1, Deepak Prashar1, Jimmy Singla1, Arfat Ahmad Khan2, Mohammed Al-Sarem3,4,*, Neesrin Ali Kurdi3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6047-6068, 2022, DOI:10.32604/cmc.2022.031255

    Abstract The hepatitis B virus is the most deadly virus, which significantly affects the human liver. The termination of the hepatitis B virus is mandatory and can be done by taking precautions as well as a suitable cure in its introductory stage; otherwise, it will become a severe problem and make a human liver suffer from the most dangerous diseases, such as liver cancer. In this paper, two medical diagnostic systems are developed for the diagnosis of this life-threatening virus. The methodologies used to develop these models are fuzzy logic and the neuro-fuzzy technique. The diverse parameters that assist in the… More >

  • Open Access

    ARTICLE

    Hyperparameter Tuning Bidirectional Gated Recurrent Unit Model for Oral Cancer Classification

    K. Shankar1, E. Laxmi Lydia2, Sachin Kumar1,*, Ali S. Abosinne3, Ahmed alkhayyat4, A. H. Abbas5, Sarmad Nozad Mahmood6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4541-4557, 2022, DOI:10.32604/cmc.2022.031247

    Abstract Oral Squamous Cell Carcinoma (OSCC) is a type of Head and Neck Squamous Cell Carcinoma (HNSCC) and it should be diagnosed at early stages to accomplish efficient treatment, increase the survival rate, and reduce death rate. Histopathological imaging is a wide-spread standard used for OSCC detection. However, it is a cumbersome process and demands expert’s knowledge. So, there is a need exists for automated detection of OSCC using Artificial Intelligence (AI) and Computer Vision (CV) technologies. In this background, the current research article introduces Improved Slime Mould Algorithm with Artificial Intelligence Driven Oral Cancer Classification (ISMA-AIOCC) model on Histopathological images… More >

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