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  • Open Access

    ARTICLE

    Short Term Traffic Flow Prediction Using Hybrid Deep Learning

    Mohandu Anjaneyulu, Mohan Kubendiran*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1641-1656, 2023, DOI:10.32604/cmc.2023.035056 - 06 February 2023

    Abstract Traffic flow prediction in urban areas is essential in the Intelligent Transportation System (ITS). Short Term Traffic Flow (STTF) prediction impacts traffic flow series, where an estimation of the number of vehicles will appear during the next instance of time per hour. Precise STTF is critical in Intelligent Transportation System. Various extinct systems aim for short-term traffic forecasts, ensuring a good precision outcome which was a significant task over the past few years. The main objective of this paper is to propose a new model to predict STTF for every hour of a day. In… More >

  • Open Access

    ARTICLE

    Home Automation-Based Health Assessment Along Gesture Recognition via Inertial Sensors

    Hammad Rustam1, Muhammad Muneeb1, Suliman A. Alsuhibany2, Yazeed Yasin Ghadi3, Tamara Al Shloul4, Ahmad Jalal1, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2331-2346, 2023, DOI:10.32604/cmc.2023.028712 - 06 February 2023

    Abstract Hand gesture recognition (HGR) is used in a numerous applications, including medical health-care, industrial purpose and sports detection. We have developed a real-time hand gesture recognition system using inertial sensors for the smart home application. Developing such a model facilitates the medical health field (elders or disabled ones). Home automation has also been proven to be a tremendous benefit for the elderly and disabled. Residents are admitted to smart homes for comfort, luxury, improved quality of life, and protection against intrusion and burglars. This paper proposes a novel system that uses principal component analysis, linear More >

  • Open Access

    ARTICLE

    Chi-Square and PCA Based Feature Selection for Diabetes Detection with Ensemble Classifier

    Vaibhav Rupapara1, Furqan Rustam2, Abid Ishaq2, Ernesto Lee3, Imran Ashraf4,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1931-1949, 2023, DOI:10.32604/iasc.2023.028257 - 05 January 2023

    Abstract Diabetes mellitus is a metabolic disease that is ranked among the top 10 causes of death by the world health organization. During the last few years, an alarming increase is observed worldwide with a 70% rise in the disease since 2000 and an 80% rise in male deaths. If untreated, it results in complications of many vital organs of the human body which may lead to fatality. Early detection of diabetes is a task of significant importance to start timely treatment. This study introduces a methodology for the classification of diabetic and normal people using… More >

  • Open Access

    ARTICLE

    3D Face Reconstruction from a Single Image Using a Combined PCA-LPP Method

    Jee-Sic Hur1, Hyeong-Geun Lee1, Shinjin Kang2, Yeo Chan Yoon3, Soo Kyun Kim1,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6213-6227, 2023, DOI:10.32604/cmc.2023.035344 - 28 December 2022

    Abstract In this paper, we proposed a combined PCA-LPP algorithm to improve 3D face reconstruction performance. Principal component analysis (PCA) is commonly used to compress images and extract features. One disadvantage of PCA is local feature loss. To address this, various studies have proposed combining a PCA-LPP-based algorithm with a locality preserving projection (LPP). However, the existing PCA-LPP method is unsuitable for 3D face reconstruction because it focuses on data classification and clustering. In the existing PCA-LPP, the adjacency graph, which primarily shows the connection relationships between data, is composed of the e-or k-nearest neighbor techniques. More >

  • Open Access

    ARTICLE

    Investigation of Android Malware with Machine Learning Classifiers using Enhanced PCA Algorithm

    V. Joseph Raymond1,2,*, R. Jeberson Retna Raj1

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2147-2163, 2023, DOI:10.32604/csse.2023.028227 - 01 August 2022

    Abstract Android devices are popularly available in the commercial market at different price levels for various levels of customers. The Android stack is more vulnerable compared to other platforms because of its open-source nature. There are many android malware detection techniques available to exploit the source code and find associated components during execution time. To obtain a better result we create a hybrid technique merging static and dynamic processes. In this paper, in the first part, we have proposed a technique to check for correlation between features and classify using a supervised learning approach to avoid… More >

  • Open Access

    ARTICLE

    Wireless Sensor Network-based Detection of Poisonous Gases Using Principal Component Analysis

    N. Dharini1,*, Jeevaa Katiravan2, S. M. Udhaya Sankar3

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 249-264, 2023, DOI:10.32604/csse.2023.024419 - 01 June 2022

    Abstract This work utilizes a statistical approach of Principal Component Analysis (PCA) towards the detection of Methane (CH4)-Carbon Monoxide (CO) Poisoning occurring in coal mines, forest fires, drainage systems etc. where the CH4 and CO emissions are very high in closed buildings or confined spaces during oxidation processes. Both methane and carbon monoxide are highly toxic, colorless and odorless gases. Both of the gases have their own toxic levels to be detected. But during their combined presence, the toxicity of the either one goes unidentified may be due to their low levels which may lead to an… More >

  • Open Access

    ARTICLE

    Prediction of distant recurrence in breast cancer using a deep neural network

    Balqis Mohd Azman1,2, Saiful Izzuan Hussain1,2, Nor Aniza Azmi3, Muhammad Zahin Athir Abd Ghani3, Nor Irfan Danial Norlen3

    Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.38, No.1, pp. 1-10, 2022, DOI:10.23967/j.rimni.2022.03.006 - 22 March 2022

    Abstract Breast cancer is the most common cancer diagnosed in women, and it is ranked as the second highest cancer with high mortality rate. Breast-cancer recurrence is the cancerous tumor that returned after treatment. Cancer treatments such as radiotherapy are performed mainly to kill cancer cells; however, some cells may have survived and multiply themselves at the same area as the original cancer (local recurrence) or to any other part (distant recurrence). Distant recurrence occurs when cancer cells spread to other parts of the body, most commonly to bone, breast, liver, and lungs. This study employed More >

  • Open Access

    ARTICLE

    Text-Independent Algorithm for Source Printer Identification Based on Ensemble Learning

    Naglaa F. El Abady1,*, Mohamed Taha1, Hala H. Zayed1,2

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1417-1436, 2022, DOI:10.32604/cmc.2022.028044 - 18 May 2022

    Abstract Because of the widespread availability of low-cost printers and scanners, document forgery has become extremely popular. Watermarks or signatures are used to protect important papers such as certificates, passports, and identification cards. Identifying the origins of printed documents is helpful for criminal investigations and also for authenticating digital versions of a document in today’s world. Source printer identification (SPI) has become increasingly popular for identifying frauds in printed documents. This paper provides a proposed algorithm for identifying the source printer and categorizing the questioned document into one of the printer classes. A dataset of 1200… More >

  • Open Access

    ARTICLE

    Hyper-Parameter Optimization of Semi-Supervised GANs Based-Sine Cosine Algorithm for Multimedia Datasets

    Anas Al-Ragehi1, Said Jadid Abdulkadir1,2,*, Amgad Muneer1,2, Safwan Sadeq3, Qasem Al-Tashi4,5

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2169-2186, 2022, DOI:10.32604/cmc.2022.027885 - 18 May 2022

    Abstract Generative Adversarial Networks (GANs) are neural networks that allow models to learn deep representations without requiring a large amount of training data. Semi-Supervised GAN Classifiers are a recent innovation in GANs, where GANs are used to classify generated images into real and fake and multiple classes, similar to a general multi-class classifier. However, GANs have a sophisticated design that can be challenging to train. This is because obtaining the proper set of parameters for all models-generator, discriminator, and classifier is complex. As a result, training a single GAN model for different datasets may not produce… More >

  • Open Access

    ARTICLE

    Agro-Morphological Characterization and Genetic Dissection of Linseed (Linum usitatissimum L.) Genotypes

    A. K. M. Golam Sarwar1, Md. Sabibul Haque1,*, Md. Ekramul Haque2, Md. Amir Hossain3, Md. Golam Azam4, Md. Nesar Uddin1, Eldessoky S. Dessoky5, Mahmoud A. Basry6, Md. Alamgir Hossain1

    Phyton-International Journal of Experimental Botany, Vol.91, No.8, pp. 1721-1743, 2022, DOI:10.32604/phyton.2022.021069 - 14 April 2022

    Abstract Linseed is a multipurpose crop and the crop needs further improvement to increase production and yield due to its high value and demand. This study aimed to assess the extent and pattern of genetic variability of forty linseed genotypes based on diverse agro–morphological and yield attributes. The field experiment was conducted following a Randomized Complete Block Design with three replications. Linseed germplasm showed a wide range of phenotypic expression, genetic variability and heritability for 30 studied traits. A low to high phenotypic coeffi- cient of variation (PCV) and genotypic coefficient of variation (GCV) were observed.… More >

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