Khadijah Mohammad Alfadli, Alaa Omran Almagrabi^*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5871-5883, 2023, DOI:10.32604/cmc.2023.033603

Abstract Heart diseases are the undisputed leading causes of death globally. Unfortunately, the conventional approach of relying solely on the patient’s medical history is not enough to reliably diagnose heart issues. Several potentially indicative factors exist, such as abnormal pulse rate, high blood pressure, diabetes, high cholesterol, etc. Manually analyzing these health signals’ interactions is challenging and requires years of medical training and experience. Therefore, this work aims to harness machine learning techniques that have proved helpful for data-driven applications in the rise of the artificial intelligence era. More specifically, this paper builds a hybrid model as a tool for data… More >

Khalid Masood¹, Mahmoud M. Al-Sakhnini^2,3, Waqas Nawaz^4,*, Tauqeer Faiz^5,6, Abdul Salam Mohammad⁷, Hamza Kashif⁸

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5417-5430, 2023, DOI:10.32604/cmc.2023.033590

Abstract Generally, conventional methods for anomaly detection rely on clustering, proximity, or classification. With the massive growth in surveillance videos, outliers or anomalies find ingenious ways to obscure themselves in the network and make conventional techniques inefficient. This research explores the structure of Graph neural networks (GNNs) that generalize deep learning frameworks to graph-structured data. Every node in the graph structure is labeled and anomalies, represented by unlabeled nodes, are predicted by performing random walks on the node-based graph structures. Due to their strong learning abilities, GNNs gained popularity in various domains such as natural language processing, social network analytics and… More >

Badriyya B. Al-onazi¹, Saud S. Alotaib², Saeed Masoud Alshahrani^3,*, Najm Alotaibi⁴, Mrim M. Alnfiai⁵, Ahmed S. Salama⁶, Manar Ahmed Hamza⁷

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5447-5465, 2023, DOI:10.32604/cmc.2023.033564

Abstract The text classification process has been extensively investigated in various languages, especially English. Text classification models are vital in several Natural Language Processing (NLP) applications. The Arabic language has a lot of significance. For instance, it is the fourth mostly-used language on the internet and the sixth official language of the United Nations. However, there are few studies on the text classification process in Arabic. A few text classification studies have been published earlier in the Arabic language. In general, researchers face two challenges in the Arabic text classification process: low accuracy and high dimensionality of the features. In this… More >

M. M. Alqarni¹, Muhammad Rafiq², Fazal Dayan^3,*, Jan Awrejcewicz⁴, Nauman Ahmed⁵, Ali Raza⁶, Muhammad Ozair Ahmad⁵, Witold Pawłowski⁷, Emad E. Mahmoud⁸

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6371-6388, 2023, DOI:10.32604/cmc.2023.033553

Abstract Amoebiasis is a parasitic intestinal infection caused by the highly pathogenic amoeba Entamoeba histolytica. It is spread through person-to-person contact or by eating or drinking food or water contaminated with feces. Its transmission rate depends on the number of cysts present in the environment. The traditional models assumed a homogeneous and contradictory transmission with reality. The heterogeneity of its transmission rate is a significant factor when modeling disease dynamics. The heterogeneity of disease transmission can be described mathematically by introducing fuzzy theory. In this context, a fuzzy SEIR Amoebiasis disease model is considered in this study. The equilibrium analysis and… More >

Ibrahim Noaman¹, Abd El Fattah El Atik², Tamer Medhat^3,*, Manal E. Ali⁴

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6893-6908, 2023, DOI:10.32604/cmc.2023.033539

Abstract This article focuses on the relationship between mathematical morphology operations and rough sets, mainly based on the context of image retrieval and the basic image correspondence problem. Mathematical morphological procedures and set approximations in rough set theory have some clear parallels. Numerous initiatives have been made to connect rough sets with mathematical morphology. Numerous significant publications have been written in this field. Others attempt to show a direct connection between mathematical morphology and rough sets through relations, a pair of dual operations, and neighborhood systems. Rough sets are used to suggest a strategy to approximate mathematical morphology within the general… More >

Mohammed Maray¹, Badriyya B. Al-onazi², Jaber S. Alzahrani³, Saeed Masoud Alshahrani^4,*, Najm Alotaibi⁵, Sana Alazwari⁶, Mahmoud Othman⁷, Manar Ahmed Hamza⁸

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5467-5482, 2023, DOI:10.32604/cmc.2023.033534

Abstract The recognition of the Arabic characters is a crucial task in computer vision and Natural Language Processing fields. Some major complications in recognizing handwritten texts include distortion and pattern variabilities. So, the feature extraction process is a significant task in NLP models. If the features are automatically selected, it might result in the unavailability of adequate data for accurately forecasting the character classes. But, many features usually create difficulties due to high dimensionality issues. Against this background, the current study develops a Sailfish Optimizer with Deep Transfer Learning-Enabled Arabic Handwriting Character Recognition (SFODTL-AHCR) model. The projected SFODTL-AHCR model primarily focuses… More >

Khalid A. Alissa¹, Mohammed Maray², Areej A. Malibari³, Sana Alazwari⁴, Hamed Alqahtani⁵, Mohamed K. Nour⁶, Marwa Obbaya⁷, Mohamed A. Shamseldin⁸, Mesfer Al Duhayyim^9,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5349-5367, 2023, DOI:10.32604/cmc.2023.033532

Abstract Emerging technologies such as edge computing, Internet of Things (IoT), 5G networks, big data, Artificial Intelligence (AI), and Unmanned Aerial Vehicles (UAVs) empower, Industry 4.0, with a progressive production methodology that shows attention to the interaction between machine and human beings. In the literature, various authors have focused on resolving security problems in UAV communication to provide safety for vital applications. The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification (CSODL-SUAVC) model for Industry 4.0 environment. The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image… More >

Mudassir Shams¹, Nasreen Kausar^2,*, Shams Forruque Ahmed³, Irfan Anjum Badruddin⁴, Syed Javed⁴

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5331-5347, 2023, DOI:10.32604/cmc.2023.033528

Abstract A fifth-order family of an iterative method for solving systems of nonlinear equations and highly nonlinear boundary value problems has been developed in this paper. Convergence analysis demonstrates that the local order of convergence of the numerical method is five. The computer algebra system CAS-Maple, Mathematica, or MATLAB was the primary tool for dealing with difficult problems since it allows for the handling and manipulation of complex mathematical equations and other mathematical objects. Several numerical examples are provided to demonstrate the properties of the proposed rapidly convergent algorithms. A dynamic evaluation of the presented methods is also presented utilizing basins… More >

Mutiullah Jamil¹, Hafeez ul Rehman¹, SaleemUllah¹, Imran Ashraf^2,*, Saqib Ubaid¹

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5545-5557, 2023, DOI:10.32604/cmc.2023.033449

Abstract Wheat species play important role in the price of products and wheat production estimation. There are several mathematical models used for the estimation of the wheat crop but these models are implemented without considering the wheat species which is an important independent variable. The task of wheat species identification is challenging both for human experts as well as for computer vision-based solutions. With the use of satellite remote sensing, it is possible to identify and monitor wheat species on a large scale at any stage of the crop life cycle. In this work, nine popular wheat species are identified by… More >

Ibrahim M. Almanjahie^1,2,*, Omar Fetitah³, Mohammed Kadi Attouch³, Tawfik Benchikh^3,4

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6307-6319, 2023, DOI:10.32604/cmc.2023.033441

Abstract Functional statistics is a new technique for dealing with data that can be viewed as curves or images. Parallel to this approach, the Near-Infrared Reflectance (NIR) spectroscopy methodology has been used in modern chemistry as a rapid, low-cost, and exact means of assessing an object’s chemical properties. In this research, we investigate the quality of corn and cookie dough by analyzing the spectroscopic technique using certain cutting-edge statistical models. By analyzing spectral data and applying functional models to it, we could predict the chemical components of corn and cookie dough. Kernel Functional Classical Estimation (KFCE), Kernel Functional Quantile Estimation (KFQE),… More >