Kwabena Owusu-Mensah^*, Edward Danso Ansong , Kofi Sarpong Adu-Manu, Winfred Yaokumah

Journal of Cyber Security, Vol.8, pp. 33-92, 2026, DOI:10.32604/jcs.2026.074265 - 20 January 2026

Abstract The rapid growth of digital payment systems and remote financial services has led to a significant increase in Card-Not-Present (CNP) fraud, which is now the primary source of card-related losses worldwide. Traditional rule-based fraud detection methods are becoming insufficient due to several challenges, including data imbalance, concept drift, privacy concerns, and limited interpretability. In response to these issues, a systematic review of twenty-four CNP fraud detection frameworks developed between 2014 and 2025 was conducted. This review aimed to identify the technologies, strategies, and design considerations necessary for adaptive solutions that align with evolving regulatory standards.… More >

Katerina Ondraskova^1,2, Matous Cwik³, Ondrej Horky⁴, Jitka Berkovcova⁴, Jitka Holcakova¹, Martin Bartosik¹, Tomas Kazda⁵, Klara Mrazova^1,6, Michal Uher⁷, Igor Kiss³, Roman Hrstka^1,3,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.070116 - 19 January 2026

Abstract Objectives: Cancer treatment relies heavily on accurate diagnosis and effective monitoring of the disease. These processes often involve invasive procedures, such as colonoscopy, to detect malignant tissues, followed by molecular analyses to determine relevant biomarkers. This study aimed to evaluate the clinical performance of droplet digital PCR (ddPCR) for detecting Kirsten Rat Sarcoma Viral Proto-Oncogene (KRAS), Neuroblastoma RAS Viral Oncogene Homolog (NRAS), and B-Raf Murine Sarcoma Viral Oncogene Homolog B (BRAF) mutations in circulating tumor DNA (ctDNA) from colorectal cancer patients using liquid biopsy. Methods: ctDNA was isolated from colorectal cancer (CRC) patients (n = 110) and analyzed for KRAS, BRAF,… More >

Nur Afikah Juhari, Khairul Nizam Tahar^*

Revue Internationale de Géomatique, Vol.35, pp. 1-11, 2026, DOI:10.32604/rig.2026.070991 - 19 January 2026

Abstract The use of Unmanned Aerial Vehicles (UAVs) in photogrammetry has grown rapidly due to enhanced flight stability, high-resolution imaging, and advanced Structure from Motion (SfM) algorithms. This study investigates the potential of UAVs as a cost-effective alternative to Terrestrial Laser Scanners (TLS) for 3D building reconstruction. A 3D model of Bangunan Sarjana was generated in Agisoft Metashape Professional v.2.0.2 using 492 aerial images captured at flying altitudes of 40, 50, and 60 m. Ground control points were established using GNSS (RTK-VRS), and Total Station measurements were employed for accuracy validation. The results indicate that the 60 More >

Md Minhazul Islam^1,2, Yunfei Yin^1,2,*, Md Tanvir Islam^1,2, Zheng Yuan^1,2, Argho Dey^1,2

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072550 - 12 January 2026

Abstract Automatic segmentation of landslides from remote sensing imagery is challenging because traditional machine learning and early CNN-based models often fail to generalize across heterogeneous landscapes, where segmentation maps contain sparse and fragmented landslide regions under diverse geographical conditions. To address these issues, we propose a lightweight dual-stream siamese deep learning framework that integrates optical and topographical data fusion with an adaptive decoder, guided multimodal fusion, and deep supervision. The framework is built upon the synergistic combination of cross-attention, gated fusion, and sub-pixel upsampling within a unified dual-stream architecture specifically optimized for landslide segmentation, enabling efficient… More >

Zixuan Guo¹, Houbin Wang², Sameer Kumar^1,*, Yuanfang Chen³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072064 - 12 January 2026

Abstract With the rapid development of digital culture, a large number of cultural texts are presented in the form of digital and network. These texts have significant characteristics such as sparsity, real-time and non-standard expression, which bring serious challenges to traditional classification methods. In order to cope with the above problems, this paper proposes a new ASSC (ALBERT, SVD, Self-Attention and Cross-Entropy)-TextRCNN digital cultural text classification model. Based on the framework of TextRCNN, the Albert pre-training language model is introduced to improve the depth and accuracy of semantic embedding. Combined with the dual attention mechanism, the… More >

Ahmed Abdel-Wahab¹, Mohammad Alkhatib^2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-34, 2026, DOI:10.32604/cmc.2025.070010 - 09 December 2025

Abstract Deepfake is a sort of fake media made by advanced AI methods like Generative Adversarial Networks (GANs). Deepfake technology has many useful uses in education and entertainment, but it also raises a lot of ethical, social, and security issues, such as identity theft, the dissemination of false information, and privacy violations. This study seeks to provide a comprehensive analysis of several methods for identifying and circumventing Deepfakes, with a particular focus on image-based Deepfakes. There are three main types of detection methods: classical, machine learning (ML) and deep learning (DL)-based, and hybrid methods. There are… More >

Abdullah Alourani¹, Mehtab Alam^2,*, Ashraf Ali³, Ihtiram Raza Khan⁴, Chandra Kanta Samal²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-32, 2026, DOI:10.32604/cmc.2025.070161 - 10 November 2025

Abstract The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management. Earlier approaches have often advanced one dimension—such as Internet of Things (IoT)-based data acquisition, Artificial Intelligence (AI)-driven analytics, or digital twin visualization—without fully integrating these strands into a single operational loop. As a result, many existing solutions encounter bottlenecks in responsiveness, interoperability, and scalability, while also leaving concerns about data privacy unresolved. This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing, distributed intelligence, and simulation-based decision support. The… More >

Huixin Wei, Baopeng Liao^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.012367

Abstract Friction behavior at soft-hard material interfaces plays a pivotal role in applications spanning biomedical devices, robotics, and tactile systems. While theoretical frameworks and experimental characterization methods have advanced, it is still difficult to unravel interfacial mechanisms. In this study, a theoretical model is firstly developed to predict static-to-sliding transitions by analyzing geometric evolution and stick-slip dynamics at soft material interfaces. The model quantitatively determines the threshold force for slip initiation, offering predictive insights into The sliding behavior of the interface. Second, an innovative tribometry platform is introduced, combining synchronized optical visualization, mechanical loading, and automated More >

Pengfei Cui^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.010832

Abstract With the continuous advancement of aerospace equipment, in addition to performance, function, and reliability requirements, durability is playing an increasingly crucial role. For instance, the objective of China's new - generation space transportation system is to achieve a reliability of 0.9999 or higher for manned flights, and a single rocket is expected to be capable of up to 100 flights. In high - temperature load - bearing structures, nickel - based alloys are extensively used because of their outstanding strength, fatigue resistance, and creep properties. In advanced aerospace engines, their mass fraction can reach as… More >

Yulong Zhao¹, Yang Luo^1,*, Yuming Luo², Yulai Pang², Ruihan Zhang¹, Zihan Zhao³

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.12, pp. 3073-3090, 2025, DOI:10.32604/fdmp.2025.070685 - 31 December 2025

Abstract The development of underground gas storage (UGS) systems is vital for maintaining stability between energy supply and demand. This study explores the dynamic response mechanisms of carbonate reservoirs subjected to intense injection–production cycling during UGS operations. By integrating three-dimensional digital core technology with a coupled poro-mechanical model, we simulate the pore-scale behavior of a representative Huangcaoxia UGS carbonate core. The results demonstrate that fluid–solid coupling effects markedly amplify permeability reduction, far exceeding the influence of porosity variations alone. More significantly, gas production leads to a pronounced decline in permeability driven by rising effective stress, arising More >