Shynar Mussiraliyeva¹, Batyrkhan Omarov^1,*, Paul Yoo^1,2, Milana Bolatbek¹

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 915-934, 2022, DOI:10.32604/cmc.2022.019189 - 07 September 2021

Abstract In this research paper, we propose a corpus for the task of detecting religious extremism in social networks and open sources and compare various machine learning algorithms for the binary classification problem using a previously created corpus, thereby checking whether it is possible to detect extremist messages in the Kazakh language. To do this, the authors trained models using six classic machine-learning algorithms such as Support Vector Machine, Decision Tree, Random Forest, K Nearest Neighbors, Naive Bayes, and Logistic Regression. To increase the accuracy of detecting extremist texts, we used various characteristics such as Statistical More >

Nora Shoaip¹, Amira Rezk¹, Shaker EL-Sappagh^2,3, Tamer Abuhmed^4,*, Sherif Barakat¹, Mohammed Elmogy⁵

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3531-3548, 2021, DOI:10.32604/cmc.2021.019069 - 24 August 2021

Abstract Alzheimer’s disease (AD) is a very complex disease that causes brain failure, then eventually, dementia ensues. It is a global health problem. 99% of clinical trials have failed to limit the progression of this disease. The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms. Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction. In this regard, the need becomes more urgent for biomarker-based detection. A key issue in understanding AD is the need… More >

Mohammad Tabrez Quasim¹, Saad Alhuwaimel^2,*, Asadullah Shaikh³, Yousef Asiri³, Khairan Rajab³, Rihem Farkh^4,5, Khaled Al Jaloud⁴

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4169-4181, 2021, DOI:10.32604/cmc.2021.015984 - 24 August 2021

Abstract Heart disease is the leading cause of death worldwide. Predicting heart disease is challenging because it requires substantial experience and knowledge. Several research studies have found that the diagnostic accuracy of heart disease is low. The coronary heart disorder determines the state that influences the heart valves, causing heart disease. Two indications of coronary heart disorder are strep throat with a red persistent skin rash, and a sore throat covered by tonsils or strep throat. This work focuses on a hybrid machine learning algorithm that helps predict heart attacks and arterial stiffness. At first, we More >

Naeem Ali^1,*, Alia Ahmed¹, Leena Anum², Taher M. Ghazal^3,4, Sagheer Abbas⁵, Muhammad Adnan Khan^6,7, Haitham M. Alzoubi⁸, Munir Ahmad⁵

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 243-257, 2021, DOI:10.32604/iasc.2021.018983 - 26 July 2021

Abstract Information Collaboration of the supply chain is the domination and control of product flow information from the producer to the customer. The data information flow is correlated with demand fill-up, a role delivering service, and feedback. The collaboration of supply chain information is a complex contrivance that impeccably manages the efficiency flow and focuses on its vulnerable area. As there is always room for growth in the current century, major companies have shown a growing tendency to improve their supply chain’s productivity and sustainability to increase customer consumption in complying with environmental regulations. Therefore, in… More >

Faseeha Matloob¹, Shabib Aftab^1,2, Munir Ahmad², Muhammad Adnan Khan^3,*, Areej Fatima⁴, Muhammad Iqbal², Wesam Mohsen Alruwaili⁵, Nouh Sabri Elmitwally^5,6

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 403-421, 2021, DOI:10.32604/iasc.2021.017562 - 16 June 2021

Abstract Software defect prediction (SDP) is the process of detecting defect-prone software modules before the testing stage. The testing stage in the software development life cycle is expensive and consumes the most resources of all the stages. SDP can minimize the cost of the testing stage, which can ultimately lead to the development of higher-quality software at a lower cost. With this approach, only those modules classified as defective are tested. Over the past two decades, many researchers have proposed methods and frameworks to improve the performance of the SDP process. The main research topics are More >

Omer Ali^1,2, Mohamad Khairi Ishak^1,*, Muhammad Kamran Liaquat Bhatti²

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 747-766, 2021, DOI:10.32604/cmc.2021.018098 - 04 June 2021

Abstract The COVID-19 virus exhibits pneumonia-like symptoms, including fever, cough, and shortness of breath, and may be fatal. Many COVID-19 contraction experiments require comprehensive clinical procedures at medical facilities. Clinical studies help to make a correct diagnosis of COVID-19, where the disease has already spread to the organs in most cases. Prompt and early diagnosis is indispensable for providing patients with the possibility of early clinical diagnosis and slowing down the disease spread. Therefore, clinical investigations in patients with COVID-19 have revealed distinct patterns of breathing relative to other diseases such as flu and cold, which… More >

Saleem Ibraheem Saleem^1,*, Adnan Mohsin Abdulazeez¹, Zeynep Orman²

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2727-2754, 2021, DOI:10.32604/cmc.2021.016447 - 13 April 2021

Abstract The writer identification (WI) of handwritten Arabic text is now of great concern to intelligence agencies following the recent attacks perpetrated by known Middle East terrorist organizations. It is also a useful instrument for the digitalization and attribution of old text to other authors of historic studies, including old national and religious archives. In this study, we proposed a new affective segmentation model by modifying an artificial neural network model and making it suitable for the binarization stage based on blocks. This modified method is combined with a new effective rotation model to achieve an… More >

Ornela Bardhi^1,2,*, Begonya Garcia Zapirain¹

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1595-1613, 2021, DOI:10.32604/cmc.2021.015326 - 13 April 2021

Abstract Breast cancer (BCa) and prostate cancer (PCa) are the two most common types of cancer. Various factors play a role in these cancers, and discovering the most important ones might help patients live longer, better lives. This study aims to determine the variables that most affect patient survivability, and how the use of different machine learning algorithms can assist in such predictions. The AURIA database was used, which contains electronic healthcare records (EHRs) of 20,006 individual patients diagnosed with either breast or prostate cancer in a particular region in Finland. In total, there were 178… More >

R. Praveena^*, T. R. GaneshBabu

Molecular & Cellular Biomechanics, Vol.18, No.2, pp. 69-86, 2021, DOI:10.32604/mcb.2021.014622 - 09 April 2021

Abstract The cup nerve head, optic cup, optic disc ratio and neural rim configuration are observed as important for detecting glaucoma at an early stage in clinical practice. The main clinical indicator of glaucoma optic cup to disc ratio is currently determined manually by limiting the mass screening was potential. This paper proposes the following methods for an automatic cup to disc ratio determination. In the first part of the work, fundus image of the optic disc region is considered. Clustering means K is used automatically to extract the optic disc whereas K-value is automatically selected… More >

Mangena Venu Madhavan¹, Dang Ngoc Hoang Thanh², Aditya Khamparia^1,*, Sagar Pande¹, Rahul Malik¹, Deepak Gupta³

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2939-2955, 2021, DOI:10.32604/cmc.2021.012466 - 28 December 2020

Abstract Disease recognition in plants is one of the essential problems in agricultural image processing. This article focuses on designing a framework that can recognize and classify diseases on pomegranate plants exactly. The framework utilizes image processing techniques such as image acquisition, image resizing, image enhancement, image segmentation, ROI extraction (region of interest), and feature extraction. An image dataset related to pomegranate leaf disease is utilized to implement the framework, divided into a training set and a test set. In the implementation process, techniques such as image enhancement and image segmentation are primarily used for identifying More >