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  • Open Access

    ARTICLE

    Automated Machine Learning for Epileptic Seizure Detection Based on EEG Signals

    Jian Liu1, Yipeng Du1, Xiang Wang1,*, Wuguang Yue2, Jim Feng3

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1995-2011, 2022, DOI:10.32604/cmc.2022.029073

    Abstract Epilepsy is a common neurological disease and severely affects the daily life of patients. The automatic detection and diagnosis system of epilepsy based on electroencephalogram (EEG) is of great significance to help patients with epilepsy return to normal life. With the development of deep learning technology and the increase in the amount of EEG data, the performance of deep learning based automatic detection algorithm for epilepsy EEG has gradually surpassed the traditional hand-crafted approaches. However, the neural architecture design for epilepsy EEG analysis is time-consuming and laborious, and the designed structure is difficult to adapt to the changing EEG collection… More >

  • Open Access

    ARTICLE

    Analysis of Eigenvalues for Molecular Structures

    Muhammad Haroon Aftab1, Kamel Jebreen2,*, Mohammad Issa Sowaity3, Muhammad Hussain4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1225-1236, 2022, DOI:10.32604/cmc.2022.029009

    Abstract In this article, we study different molecular structures such as Polythiophene network, for and , Orthosilicate (Nesosilicate) , Pyrosilicates (Sorosilicates) , Chain silicates (Pyroxenes), and Cyclic silicates (Ring Silicates) for their cardinalities, chromatic numbers, graph variations, eigenvalues obtained from the adjacency matrices which are square matrices in order and their corresponding characteristics polynomials. We convert the general structures of these chemical networks in to mathematical graphical structures. We transform the molecular structures of these chemical networks which are mentioned above, into a simple and undirected planar graph and sketch them with various techniques of mathematics. The matrices obtained from these… More >

  • Open Access

    ARTICLE

    Sensitive Information Protection Model Based on Bayesian Game

    Yuzhen Liu1,2, Zhe Liu3, Xiaoliang Wang1,2,*, Qing Yang4, Guocai Zuo5, Frank Jiang6

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 883-898, 2022, DOI:10.32604/cmc.2022.029002

    Abstract

    A game measurement model considering the attacker's knowledge background is proposed based on the Bayesian game theory aiming at striking a balance between the protection of sensitive information and the quality of service. We quantified the sensitive level of information according to the user's personalized sensitive information protection needs. Based on the probability distribution of sensitive level and attacker's knowledge background type, the strategy combination of service provider and attacker was analyzed, and a game-based sensitive information protection model was constructed. Through the combination of strategies under Bayesian equilibrium, the information entropy was used to measure the leakage of sensitive… More >

  • Open Access

    ARTICLE

    A Novel Hybrid Machine Learning Approach for Classification of Brain Tumor Images

    Abdullah A. Asiri1, Amna Iqbal2, Javed Ferzund2, Tariq Ali2,*, Muhammad Aamir2, Khalaf A. Alshamrani1, Hassan A. Alshamrani1, Fawaz F. Alqahtani1, Muhammad Irfan3, Ali H. D. Alshehri1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 641-655, 2022, DOI:10.32604/cmc.2022.029000

    Abstract Abnormal growth of brain tissues is the real cause of brain tumor. Strategy for the diagnosis of brain tumor at initial stages is one of the key step for saving the life of a patient. The manual segmentation of brain tumor magnetic resonance images (MRIs) takes time and results vary significantly in low-level features. To address this issue, we have proposed a ResNet-50 feature extractor depended on multilevel deep convolutional neural network (CNN) for reliable images segmentation by considering the low-level features of MRI. In this model, we have extracted features through ResNet-50 architecture and fed these feature maps to… More >

  • Open Access

    ARTICLE

    Computer Vision Technology for Fault Detection Systems Using Image Processing

    Abed Saif Alghawli*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1961-1976, 2022, DOI:10.32604/cmc.2022.028990

    Abstract In the period of Industries 4.0, cyber-physical systems (CPSs) were a major study area. Such systems frequently occur in manufacturing processes and people’s everyday lives, and they communicate intensely among physical elements and lead to inconsistency. Due to the magnitude and importance of the systems they support, the cyber quantum models must function effectively. In this paper, an image-processing-based anomalous mobility detecting approach is suggested that may be added to systems at any time. The expense of glitches, failures or destroyed products is decreased when anomalous activities are detected and unplanned scenarios are avoided. The presently offered techniques are not… More >

  • Open Access

    ARTICLE

    Single and Mitochondrial Gene Inheritance Disorder Prediction Using Machine Learning

    Muhammad Umar Nasir1, Muhammad Adnan Khan1,2, Muhammad Zubair3, Taher M. Ghazal4,5, Raed A. Said6, Hussam Al Hamadi7,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 953-963, 2022, DOI:10.32604/cmc.2022.028958

    Abstract One of the most difficult jobs in the post-genomic age is identifying a genetic disease from a massive amount of genetic data. Furthermore, the complicated genetic disease has a very diverse genotype, making it challenging to find genetic markers. This is a challenging process since it must be completed effectively and efficiently. This research article focuses largely on which patients are more likely to have a genetic disorder based on numerous medical parameters. Using the patient’s medical history, we used a genetic disease prediction algorithm that predicts if the patient is likely to be diagnosed with a genetic disorder. To… More >

  • Open Access

    ARTICLE

    Dynamics of Fractional Differential Model for Schistosomiasis Disease

    Thongchai Botmart1, Wajaree Weera1,*, Muhammad Asif Zahoor Raja2, Zulqurnain Sabir3, Qusain Hiader4, Gilder Cieza Altamirano5, Plinio Junior Muro Solano6, Alfonso Tesen Arroyo6

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 981-999, 2022, DOI:10.32604/cmc.2022.028921

    Abstract In the present study, a design of a fractional order mathematical model is presented based on the schistosomiasis disease. To observe more accurate performances of the results, the use of fractional order derivatives in the mathematical model is introduce based on the schistosomiasis disease is executed. The preliminary design of the fractional order mathematical model focused on schistosomiasis disease is classified as follows: uninfected with schistosomiasis, infected with schistosomiasis, recovered from infection, susceptible snail unafflicted with schistosomiasis disease and susceptible snail afflicted with this disease. The solutions to the proposed system of the fractional order mathematical model will be presented… More >

  • Open Access

    ARTICLE

    A Highly Secured Image Encryption Scheme using Quantum Walk and Chaos

    Muhammad Islam Kamran1, Muazzam A. Khan1, Suliman A. Alsuhibany2, Yazeed Yasin Ghadi3, Arshad4, Jameel Arif1, Jawad Ahmad5,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 657-672, 2022, DOI:10.32604/cmc.2022.028876

    Abstract The use of multimedia data sharing has drastically increased in the past few decades due to the revolutionary improvements in communication technologies such as the 4th generation (4G) and 5th generation (5G) etc. Researchers have proposed many image encryption algorithms based on the classical random walk and chaos theory for sharing an image in a secure way. Instead of the classical random walk, this paper proposes the quantum walk to achieve high image security. Classical random walk exhibits randomness due to the stochastic transitions between states, on the other hand, the quantum walk is more random and achieve randomness due… More >

  • Open Access

    ARTICLE

    Deer Hunting Optimization with Deep Learning Model for Lung Cancer Classification

    Mahmoud Ragab1,2,3,*, Hesham A. Abdushkour4, Alaa F. Nahhas5, Wajdi H. Aljedaibi6

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 533-546, 2022, DOI:10.32604/cmc.2022.028856

    Abstract Lung cancer is the main cause of cancer related death owing to its destructive nature and postponed detection at advanced stages. Early recognition of lung cancer is essential to increase the survival rate of persons and it remains a crucial problem in the healthcare sector. Computer aided diagnosis (CAD) models can be designed to effectually identify and classify the existence of lung cancer using medical images. The recently developed deep learning (DL) models find a way for accurate lung nodule classification process. Therefore, this article presents a deer hunting optimization with deep convolutional neural network for lung cancer detection and… More >

  • Open Access

    ARTICLE

    A Secure and Lightweight Chaos Based Image Encryption Scheme

    Fadia Ali Khan1, Jameel Ahmed1, Fehaid Alqahtani2, Suliman A. Alsuhibany3, Fawad Ahmed4, Jawad Ahmad5,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 279-294, 2022, DOI:10.32604/cmc.2022.028789

    Abstract In this paper, we present an image encryption scheme based on the multi-stage chaos-based image encryption algorithm. The method works on the principle of confusion and diffusion. The proposed scheme containing both confusion and diffusion modules are highly secure and effective as compared to the existing schemes. Initially, an image (red, green, and blue components) is partitioned into blocks with an equal number of pixels. Each block is then processed with Tinkerbell Chaotic Map (TBCM) to get shuffled pixels and shuffled blocks. Composite Fractal Function (CFF) change the value of pixels of each color component (layer) to obtain a random… More >

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