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  • Open Access


    Encephalitis Detection from EEG Fuzzy Density-Based Clustering Model with Multiple Centroid

    Hanan Abdullah Mengash1, Alaaeldin M. Hafez2, Hanan A. Hosni Mahmoud3,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3129-3140, 2023, DOI:10.32604/iasc.2023.030836

    Abstract Encephalitis is a brain inflammation disease. Encephalitis can yield to seizures, motor disability, or some loss of vision or hearing. Sometimes, encephalitis can be a life-threatening and proper diagnosis in an early stage is very crucial. Therefore, in this paper, we are proposing a deep learning model for computerized detection of Encephalitis from the electroencephalogram data (EEG). Also, we propose a Density-Based Clustering model to classify the distinctive waves of Encephalitis. Customary clustering models usually employ a computed single centroid virtual point to define the cluster configuration, but this single point does not contain adequate information. To precisely extract accurate… More >

  • Open Access


    An Adaptive Anomaly Detection Algorithm Based on CFSFDP

    Weiwu Ren1,*, Xiaoqiang Di1, Zhanwei Du2, Jianping Zhao1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2057-2073, 2021, DOI:10.32604/cmc.2021.016678

    Abstract CFSFDP (Clustering by fast search and find of density peak) is a simple and crisp density clustering algorithm. It does not only have the advantages of density clustering algorithm, but also can find the peak of cluster automatically. However, the lack of adaptability makes it difficult to apply in intrusion detection. The new input cannot be updated in time to the existing profiles, and rebuilding profiles would waste a lot of time and computation. Therefore, an adaptive anomaly detection algorithm based on CFSFDP is proposed in this paper. By analyzing the influence of new input on center, edge and discrete… More >

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