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 >

Suhas S. Aralikatti¹, K. N. Ravikumar¹, Hemantha Kumar^1,*, H. Shivananda Nayaka¹, V. Sugumaran²

Structural Durability & Health Monitoring, Vol.14, No.2, pp. 127-145, 2020, DOI:10.32604/sdhm.2020.07595 - 23 June 2020

Abstract The state of cutting tool determines the quality of surface produced on the machined parts. A faulty tool produces poor surface, inaccurate geometry and non-economic production. Thus, it is necessary to monitor tool condition for a machining process to have superior quality and economic production. In the present study, fault classification of single point cutting tool for hard turning has been carried out by employing machine learning technique. Cutting force and vibration signals were acquired to monitor tool condition during machining. A set of four tooling conditions namely healthy, worn flank, broken insert and extended… More >

R. Agalya¹, R. Muthaiah^2,*, D. Muralidharan³

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.1, pp. 25-43, 2019, DOI:10.32604/cmes.2019.05616

Abstract In today’s modern design technology, post-silicon validation is an expensive and composite task. The major challenge involved in this method is that it has limited observability and controllability of internal signals. There will be an issue during execution how to address the useful set of signals and store it in the on-chip trace buffer. The existing approaches are restricted to particular debug set-up where all the components have equivalent prominence at all the time. Practically, the verification engineers will emphasis only on useful functional regions or components. Due to some constraints like clock gating, some… More >