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Research Article

BEST PAPER 2021

Applications of Machine Learning for Big Data


Submission Deadline: 31 August 2021 (closed)

Abstract

This article has no abstract.

Keywords

Augmented Reality
Cloud Data Storage using Machine Learning
Computer Vision
Deep Learning
IoT Data analytics and Big Data
Large-scale processing and distributed/parallel computing
Online Recommender Systems
Real-Time Anomaly, Failure, image manipulation and fake detection
Semi-supervised and weakly supervised learning
Streaming Analytics
  • Research Article

    BEST PAPER 2021

    Prediction of Cardiovascular Disease Using Machine Learning Technique—A Modern Approach

    Visvasam Devadoss Ambeth Kumar1, Chetan Swarup2, Indhumathi Murugan1, Abhishek Kumar3, Kamred Udham Singh4, Teekam Singh5, Ramu Dubey6,* CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 855-869, 2022, DOI:10.32604/cmc.2022.021582
    Abstract Cardio Vascular disease (CVD), involving the heart and blood vessels is one of the most leading causes of death throughout the world. There are several risk factors for causing heart diseases like sedentary lifestyle, unhealthy diet, obesity, diabetes, hypertension, smoking and consumption of alcohol, stress, hereditary factory etc. Predicting cardiovascular disease and improving and treating the risk factors at an early stage are of paramount importance to save the precious life of a human being. At present, the highly stressful life with bad lifestyle activities causes heart disease at a very young age. The main aim of this research is… More >

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  • Research Article

    BEST PAPER 2021

    Piezoresistive Prediction of CNTs-Embedded Cement Composites via Machine Learning Approaches

    Jinho Bang1, SongEe Park2, Haemin Jeon2,* CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1503-1519, 2022, DOI:10.32604/cmc.2022.020485
    Abstract Conductive cementitious composites are innovated materials that have improved electrical conductivity compared to general types of cement, and are expected to be used in a variety of future infrastructures with unique functionalities such as self-heating, electromagnetic shielding, and piezoelectricity. In the present study, machine learning methods that have been recently applied in various fields were proposed for the prediction of piezoelectric characteristics of carbon nanotubes (CNTs)-incorporated cement composites. Data on the resistivity change of CNTs/cement composites according to various water/binder ratios, loading types, and CNT content were considered as training values. These data were applied to numerous machine learning techniques… More >

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  • Research Article

    BEST PAPER 2021

    A Hybrid Deep Learning-Based Unsupervised Anomaly Detection in High Dimensional Data

    Amgad Muneer1,2,*, Shakirah Mohd Taib1,2, Suliman Mohamed Fati3, Abdullateef O. Balogun1, Izzatdin Abdul Aziz1,2 CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5363-5381, 2022, DOI:10.32604/cmc.2022.021113
    Abstract Anomaly detection in high dimensional data is a critical research issue with serious implication in the real-world problems. Many issues in this field still unsolved, so several modern anomaly detection methods struggle to maintain adequate accuracy due to the highly descriptive nature of big data. Such a phenomenon is referred to as the “curse of dimensionality” that affects traditional techniques in terms of both accuracy and performance. Thus, this research proposed a hybrid model based on Deep Autoencoder Neural Network (DANN) with five layers to reduce the difference between the input and output. The proposed model was applied to a… More >

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