Hairul Aysa Abdul Halim Sithiq^1,*, Liyana Shuib^1,*, Muneer Ahmad², Chermaine Deepa Antony³

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-25, 2026, DOI:10.32604/cmc.2025.067781 - 10 November 2025

Abstract Honeycombing Lung (HCL) is a chronic lung condition marked by advanced fibrosis, resulting in enlarged air spaces with thick fibrotic walls, which are visible on Computed Tomography (CT) scans. Differentiating between normal lung tissue, honeycombing lungs, and Ground Glass Opacity (GGO) in CT images is often challenging for radiologists and may lead to misinterpretations. Although earlier studies have proposed models to detect and classify HCL, many faced limitations such as high computational demands, lower accuracy, and difficulty distinguishing between HCL and GGO. CT images are highly effective for lung classification due to their high resolution,… More >

Xiaoping Yang^1,2,3, Jinku Qiu^2,3,4, Xifa Gong⁵, Jin Ye⁵, Fei Yao^5,*, Jiaqiao Chen⁶, Xianzan Luo⁶, Da Qin⁶

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1515-1539, 2025, DOI:10.32604/cmc.2025.067518 - 29 August 2025

Abstract In contemporary society, rapid and accurate optical cable fault detection is of paramount importance for ensuring the stability and reliability of optical networks. The emergence of novel faults in optical networks has introduced new challenges, significantly compromising their normal operation. Machine learning has emerged as a highly promising approach. Consequently, it is imperative to develop an automated and reliable algorithm that utilizes telemetry data acquired from Optical Time-Domain Reflectometers (OTDR) to enable real-time fault detection and diagnosis in optical fibers. In this paper, we introduce a multi-scale Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN-BiLSTM) deep… More >

Adnan Hussein¹, Abdulwahab Ali Almazroi^2,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3853-3866, 2023, DOI:10.32604/cmc.2023.040856 - 26 December 2023

Abstract The advances in technology increase the number of internet systems usage. As a result, cybersecurity issues have become more common. Cyber threats are one of the main problems in the area of cybersecurity. However, detecting cybersecurity threats is not a trivial task and thus is the center of focus for many researchers due to its importance. This study aims to analyze Twitter data to detect cyber threats using a multiclass classification approach. The data is passed through different tasks to prepare it for the analysis. Term Frequency and Inverse Document Frequency (TFIDF) features are extracted… More >

Amit Saxena¹, Smita Saxena^2,*

Journal of Quantum Computing, Vol.5, pp. 1-13, 2023, DOI:10.32604/jqc.2023.044555 - 09 November 2023

Abstract Quantum computing is a promising new approach to tackle the complex real-world computational problems by harnessing the power of quantum mechanics principles. The inherent parallelism and exponential computational power of quantum systems hold the potential to outpace classical counterparts in solving complex optimization problems, which are pervasive in machine learning. Quantum Support Vector Machine (QSVM) is a quantum machine learning algorithm inspired by classical Support Vector Machine (SVM) that exploits quantum parallelism to efficiently classify data points in high-dimensional feature spaces. We provide a comprehensive overview of the underlying principles of QSVM, elucidating how different… More >

Kuntha Pin¹, Jee Ho Chang², Yunyoung Nam^3,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5821-5834, 2022, DOI:10.32604/cmc.2022.021943 - 11 October 2021

Abstract While the usage of digital ocular fundus image has been widespread in ophthalmology practice, the interpretation of the image has been still on the hands of the ophthalmologists which are quite costly. We explored a robust deep learning system that detects three major ocular diseases: diabetic retinopathy (DR), glaucoma (GLC), and age-related macular degeneration (AMD). The proposed method is composed of two steps. First, an initial quality evaluation in the classification system is proposed to filter out poor-quality images to enhance its performance, a technique that has not been explored previously. Second, the transfer learning… More >