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Search Results (5)
  • Open Access

    ARTICLE

    A Cyber-Attack Detection System Using Late Fusion Aggregation Enabled Cyber-Net

    P. Shanmuga Prabha*, S. Magesh Kumar

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3101-3119, 2023, DOI:10.32604/iasc.2023.034885

    Abstract Today, securing devices connected to the internet is challenging as security threats are generated through various sources. The protection of cyber-physical systems from external attacks is a primary task. The presented method is planned on the prime motive of detecting cybersecurity attacks and their impacted parameters. The proposed architecture employs the LYSIS dataset and formulates Multi Variant Exploratory Data Analysis (MEDA) through Principle Component Analysis (PCA) and Singular Value Decomposition (SVD) for the extraction of unique parameters. The feature mappings are analyzed with Recurrent 2 Convolutional Neural Network (R2CNN) and Gradient Boost Regression (GBR) to identify the maximum correlation. Novel… More >

  • Open Access

    ARTICLE

    Rice (Oryza sativa L.) Breeding among Hassawi Landrace and Egyptian Genotypes for Stem Borer (Chilo agamemnon Bles.) Resistance and Related Quantitative Traits

    Mohammed I. Al-Daej1, Mohamed M. El-Malky2, Muhammad N. Sattar3, Adel A. Rezk1,4, Muhammad N. Naqqash5, Jameel M. Al-Khayri1,*

    Phyton-International Journal of Experimental Botany, Vol.91, No.9, pp. 1905-1922, 2022, DOI:10.32604/phyton.2022.020629

    Abstract Rice stem borer (Chilo agamemnon Bles.) is a primary insect pest of rice and is a major limiting factor to rice production. Breeding for insect-resistant crop varieties has been an economic way of integrated pest management (IPM) as it offers a viable and ecologically acceptable approach. This study was aimed to evaluate rice genotypes for their resistance against rice stem borer. Seven parental genotypes with twenty one F1 crosses were evaluated for genotypic variation in field experiments. Analysis of variance revealed significant differences for the studied traits in almost all crosses and parents. In addition, the mean squares of parents… More >

  • Open Access

    ARTICLE

    Detection of Parkinson’s Disease with Multiple Feature Extraction Models and Darknet CNN Classification

    G. Prema Arokia Mary1,*, N. Suganthi2

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 333-345, 2022, DOI:10.32604/csse.2022.021164

    Abstract Parkinson’s disease (PD) is a neurodegenerative disease in the central nervous system. Recently, more researches have been conducted in the determination of PD prediction which is really a challenging task. Due to the disorders in the central nervous system, the syndromes like off sleep, speech disorders, olfactory and autonomic dysfunction, sensory disorder symptoms will occur. The earliest diagnosing of PD is very challenging among the doctors community. There are techniques that are available in order to predict PD using symptoms and disorder measurement. It helps to save a million lives of future by early prediction. In this article, the early… More >

  • Open Access

    ARTICLE

    Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing

    D. Jerusha*, T. Jaya

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1121-1132, 2022, DOI:10.32604/csse.2022.022997

    Abstract Edge Computing is one of the radically evolving systems through generations as it is able to effectively meet the data saving standards of consumers, providers and the workers. Requisition for Edge Computing based items have been increasing tremendously. Apart from the advantages it holds, there remain lots of objections and restrictions, which hinders it from accomplishing the need of consumers all around the world. Some of the limitations are constraints on computing and hardware, functions and accessibility, remote administration and connectivity. There is also a backlog in security due to its inability to create a trust between devices involved in… More >

  • Open Access

    ARTICLE

    A Novel Atlas-Based Strategy for Understanding Cardiac Dysfunction in Patients with Congenital Heart Disease

    Sara Salehyar1, †, Nickolas Forsch1,†,*, Kathleen Gilbert2,3, Alistair A. Young3,4, James C. Perry5, Sanjeet Hegde5, Jeffrey H. Omens1,6, Andrew D. McCulloch1,6

    Molecular & Cellular Biomechanics, Vol.16, No.3, pp. 179-183, 2019, DOI:10.32604/mcb.2019.07384

    Abstract Tetralogy of Fallot (TOF) is the most common form of cyanotic congenital heart disease. Infants diagnosed with TOF require surgical interventions to survive into adulthood. However, as a result of postoperative structural malformations and long-term ventricular remodeling, further interventions are often required later in life. To help identify those at risk of disease progression, serial cardiac magnetic resonance (CMR) imaging is used to monitor these patients. However, most of the detailed information on cardiac shape and biomechanics contained in these large four-dimensional (4D) data sets goes unused in clinical practice for lack of efficient and comprehensive quantitative analysis tools. While… More >

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