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Search Results (7)
  • Open Access

    ARTICLE

    A Novel Multi-Stage Bispectral Deep Learning Method for Protein Family Classification

    Amjed Al Fahoum*, Ala’a Zyout, Hiam Alquran, Isam Abu-Qasmieh

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1173-1193, 2023, DOI:10.32604/cmc.2023.038304

    Abstract Complex proteins are needed for many biological activities. Folding amino acid chains reveals their properties and functions. They support healthy tissue structure, physiology, and homeostasis. Precision medicine and treatments require quantitative protein identification and function. Despite technical advances and protein sequence data exploration, bioinformatics’ “basic structure” problem—the automatic deduction of a protein’s properties from its amino acid sequence—remains unsolved. Protein function inference from amino acid sequences is the main biological data challenge. This study analyzes whether raw sequencing can characterize biological facts. A massive corpus of protein sequences and the Globin-like superfamily’s related protein families generate a solid vector representation.… More >

  • Open Access

    ARTICLE

    An Innovative Bispectral Deep Learning Method for Protein Family Classification

    Isam Abu-Qasmieh, Amjed Al Fahoum*, Hiam Alquran, Ala’a Zyout

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3971-3991, 2023, DOI:10.32604/cmc.2023.037431

    Abstract Proteins are essential for many biological functions. For example, folding amino acid chains reveals their functionalities by maintaining tissue structure, physiology, and homeostasis. Note that quantifiable protein characteristics are vital for improving therapies and precision medicine. The automatic inference of a protein’s properties from its amino acid sequence is called “basic structure”. Nevertheless, it remains a critical unsolved challenge in bioinformatics, although with recent technological advances and the investigation of protein sequence data. Inferring protein function from amino acid sequences is crucial in biology. This study considers using raw sequencing to explain biological facts using a large corpus of protein… More >

  • Open Access

    ARTICLE

    Spectral Analysis and Validation of Parietal Signals for Different Arm Movements

    Umashankar Ganesan1,*, A. Vimala Juliet2, R. Amala Jenith Joshi3

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2849-2863, 2023, DOI:10.32604/iasc.2023.033759

    Abstract Brain signal analysis plays a significant role in attaining data related to motor activities. The parietal region of the brain plays a vital role in muscular movements. This approach aims to demonstrate a unique technique to identify an ideal region of the human brain that generates signals responsible for muscular movements; perform statistical analysis to provide an absolute characterization of the signal and validate the obtained results using a prototype arm. This can enhance the practical implementation of these frequency extractions for future neuro-prosthetic applications and the characterization of neurological diseases like Parkinson’s disease (PD). To play out this handling… More >

  • Open Access

    ARTICLE

    Investigation on the Indeterminate Information of Rock Joint Roughness through a Neutrosophic Number Approach

    Changshuo Wang1, Liangqing Wang2,*, Shigui Du1, Jun Ye1,3, Rui Yong1

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 973-991, 2021, DOI:10.32604/cmes.2021.017453

    Abstract To better estimate the rock joint shear strength, accurately determining the rock joint roughness coefficient (JRC) is the first step faced by researchers and engineers. However, there are incomplete, imprecise, and indeterminate problems during the process of calculating the JRC. This paper proposed to investigate the indeterminate information of rock joint roughness through a neutrosophic number approach and, based on this information, reported a method to capture the incomplete, uncertain, and imprecise information of the JRC in uncertain environments. The uncertainties in the JRC determination were investigated by the regression correlations based on commonly used statistical parameters, which demonstrated the… More >

  • Open Access

    ARTICLE

    Detection and Discrimination of Tea Plant Stresses Based on Hyperspectral Imaging Technique at a Canopy Level

    Lihan Cui1, Lijie Yan1, Xiaohu Zhao1, Lin Yuan2, Jing Jin3, Jingcheng Zhang1,*

    Phyton-International Journal of Experimental Botany, Vol.90, No.2, pp. 621-634, 2021, DOI:10.32604/phyton.2021.015511

    Abstract Tea plant stresses threaten the quality of tea seriously. The technology corresponding to the fast detection and differentiation of stresses is of great significance for plant protection in tea plantation. In recent years, hyperspectral imaging technology has shown great potential in detecting and differentiating plant diseases, pests and some other stresses at the leaf level. However, the lack of studies at canopy level hampers the detection of tea plant stresses at a larger scale. In this study, based on the canopy-level hyperspectral imaging data, the methods for identifying and differentiating the three commonly occurred tea stresses (i.e., the tea leafhopper,… More >

  • Open Access

    REVIEW

    A Survey on Machine Learning in Chemical Spectral Analysis

    Dongfang Yu, Jinwei Wang*

    Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 165-174, 2020, DOI:10.32604/jihpp.2020.010466

    Abstract Chemical spectral analysis is contemporarily undergoing a revolution and drawing much attention of scientists owing to machine learning algorithms, in particular convolutional networks. Hence, this paper outlines the major machine learning and especially deep learning methods contributed to interpret chemical images, and overviews the current application, development and breakthrough in different spectral characterization. Brief categorization of reviewed literatures is provided for studies per application apparatus: X-Ray spectra, UV-Vis-IR spectra, Micro-scope, Raman spectra, Photoluminescence spectrum. End with the overview of existing circumstances in this research area, we provide unique insight and promising directions for the chemical imaging field to fully couple… More >

  • Open Access

    ARTICLE

    Measurements in Situ and Spectral Analysis of Wind Flow Effects on Overhead Transmission Lines

    Maciej Dutkiewicz1,*, Marcela R. Machado2

    Sound & Vibration, Vol.53, No.4, pp. 161-175, 2019, DOI:10.32604/sv.2019.04803

    Abstract In the paper an important issue of vibrations of the transmission line in real conditions was analyzed. Such research was carried out by the authors of this paper taking into account the cross-section of the cable being in use on the transmission line. Analysis was performed for the modern ACSR high voltage transmission line with span of 213.0 m. The purpose of the investigation was to analyze the vibrations of the power transmission line in the natural environment and compare with the results obtained in the numerical simulations. Analysis was performed for natural and wind excited vibrations. The numerical model… More >

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