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  • Open Access


    A Three-Dimensional Real-Time Gait-Based Age Detection System Using Machine Learning

    Muhammad Azhar1,*, Sehat Ullah1, Khalil Ullah2, Habib Shah3, Abdallah Namoun4, Khaliq Ur Rahman5

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 165-182, 2023, DOI:10.32604/cmc.2023.034605

    Abstract Human biometric analysis has gotten much attention due to its widespread use in different research areas, such as security, surveillance, health, human identification, and classification. Human gait is one of the key human traits that can identify and classify humans based on their age, gender, and ethnicity. Different approaches have been proposed for the estimation of human age based on gait so far. However, challenges are there, for which an efficient, low-cost technique or algorithm is needed. In this paper, we propose a three-dimensional real-time gait-based age detection system using a machine learning approach. The proposed system consists of training… More >

  • Open Access


    Experimental Analysis of Methods Used to Solve Linear Regression Models

    Mua’ad Abu-Faraj1,*, Abeer Al-Hyari2, Ziad Alqadi3

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5699-5712, 2022, DOI:10.32604/cmc.2022.027364

    Abstract Predicting the value of one or more variables using the values of other variables is a very important process in the various engineering experiments that include large data that are difficult to obtain using different measurement processes. Regression is one of the most important types of supervised machine learning, in which labeled data is used to build a prediction model, regression can be classified into three different categories: linear, polynomial, and logistic. In this research paper, different methods will be implemented to solve the linear regression problem, where there is a linear relationship between the target and the predicted output.… More >

  • Open Access


    Characterization and Prediction of Nonlinear Stress-Strain Relation of Geostructures for Seismic Monitoring

    Abdoullah Namdar1,2,3,*

    Structural Durability & Health Monitoring, Vol.15, No.2, pp. 167-182, 2021, DOI:10.32604/sdhm.2021.011127

    Abstract The nonlinearity of the strain energy at an interval period of applying seismic load on the geostructures makes it difficult for a seismic designer to makes appropriate engineering judgments timely. The nonlinear stress and strain analysis of an embankment is needed to evaluate by using a combination of suitable methods. In this study, a large-scale geostructure was seismically simulated and analyzed using the nonlinear finite element method (NFEM), and linear regression method which is a soft computing technique (SC) was applied for evaluating the results of NFEM, and it supports engineering judgment because the design of the geostructures is usually… More >

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