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  • Open Access

    REVIEW

    A Systematic Review of Frameworks for the Detection and Prevention of Card-Not-Present (CNP) Fraud

    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 >

  • Open Access

    ARTICLE

    The FN1-ITGB4 Axis Drives Acquired Chemoresistance in Bladder Cancer by Activating FAK Signaling

    Xiaoyu Zhang1,#, RenFei Zong1,#, Yan Sun1, Nan Chen2, Kunyao Zhu1, Hang Tong1, Tinghao Li1, Junlong Zhu1, Zijia Qin1, Linfeng Wu1, Aimin Wang1, Weiyang He1,*

    Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.072084 - 19 January 2026

    Abstract Objective: While cisplatin-based chemotherapy is pivotal for advanced bladder cancer, acquired resistance remains a major obstacle. This study investigates key molecular drivers of this resistance and potential reversal strategies. Methods: We established GC (Gemcitabine and Cisplatin)-resistant T24-R and UC3-R cell lines from T24 and UM-UC-3 (UC3) cells. Transcriptomic and proteomic analyses identified differentially expressed molecules. Apoptosis and cell viability were assessed by flow cytometry and CCK-8 (Cell Counting Kit-8) assays, while RT-qPCR (Reverse Transcription Quantitative Polymerase Chain Reaction) and Western blot analyzed gene and protein expression. Immunofluorescence evaluated FAK (Focal Adhesion Kinase) phosphorylation, and a… More >

  • Open Access

    ARTICLE

    Enhancing Anomaly Detection with Causal Reasoning and Semantic Guidance

    Weishan Gao1,2, Ye Wang1,2, Xiaoyin Wang1,2, Xiaochuan Jing1,2,*

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073850 - 12 January 2026

    Abstract In the field of intelligent surveillance, weakly supervised video anomaly detection (WSVAD) has garnered widespread attention as a key technology that identifies anomalous events using only video-level labels. Although multiple instance learning (MIL) has dominated the WSVAD for a long time, its reliance solely on video-level labels without semantic grounding hinders a fine-grained understanding of visually similar yet semantically distinct events. In addition, insufficient temporal modeling obscures causal relationships between events, making anomaly decisions reactive rather than reasoning-based. To overcome the limitations above, this paper proposes an adaptive knowledge-based guidance method that integrates external structured… More >

  • Open Access

    ARTICLE

    CamSimXR: eXtended Reality (XR) Based Pre-Visualization and Simulation for Optimal Placement of Heterogeneous Cameras

    Juhwan Kim1, Gwanghyun Jo2, Dongsik Jo1,*

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072664 - 12 January 2026

    Abstract In recent years, three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly, enabling remote collaboration among users in extended Reality (XR) environments. In addition, methods for deploying multiple cameras for motion capture of users (e.g., performers) are widely used in computer graphics. As the need to minimize and optimize the number of cameras grows to reduce costs, various technologies and research approaches focused on Optimal Camera Placement (OCP) are continually being proposed. However, as most existing studies assume homogeneous camera setups, there is a growing demand for studies on heterogeneous camera setups.… More >

  • Open Access

    ARTICLE

    Research on Deformation Mechanism of Rolled AZ31B Magnesium Alloy during Tension by VPSC Model Computational Simulation

    Xun Chen1, Jinbao Lin1,2,*, Zai Wang1

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072495 - 12 January 2026

    Abstract This work investigates the effects of deformation mechanisms on the mechanical properties and anisotropy of rolled AZ31B magnesium alloy under uniaxial tension, combining experimental characterization with Visco-Plastic Self Consistent (VPSC) modeling. The research focuses particularly on anisotropic mechanical responses along transverse direction (TD) and rolling direction (RD). Experimental measurements and computational simulations consistently demonstrate that prismatic <a> slip activation significantly reduces the strain hardening rate during the initial stage of tensile deformation. By suppressing the activation of specific deformation mechanisms along RD and TD, the tensile mechanical behavior of the magnesium alloy was further investigated. More >

  • Open Access

    ARTICLE

    FAIR-DQL: Fairness-Aware Deep Q-Learning for Enhanced Resource Allocation and RIS Optimization in High-Altitude Platform Networks

    Muhammad Ejaz1, Muhammad Asim2,*, Mudasir Ahmad Wani2,3, Kashish Ara Shakil4,*

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072464 - 12 January 2026

    Abstract The integration of High-Altitude Platform Stations (HAPS) with Reconfigurable Intelligent Surfaces (RIS) represents a critical advancement for next-generation wireless networks, offering unprecedented opportunities for ubiquitous connectivity. However, existing research reveals significant gaps in dynamic resource allocation, joint optimization, and equitable service provisioning under varying channel conditions, limiting practical deployment of these technologies. This paper addresses these challenges by proposing a novel Fairness-Aware Deep Q-Learning (FAIR-DQL) framework for joint resource management and phase configuration in HAPS-RIS systems. Our methodology employs a comprehensive three-tier algorithmic architecture integrating adaptive power control, priority-based user scheduling, and dynamic learning mechanisms. More >

  • Open Access

    ARTICLE

    BearFusionNet: A Multi-Stream Attention-Based Deep Learning Framework with Explainable AI for Accurate Detection of Bearing Casting Defects

    Md. Ehsanul Haque1, Md. Nurul Absur2, Fahmid Al Farid3, Md Kamrul Siam4, Jia Uddin5,*, Hezerul Abdul Karim3,*

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071771 - 12 January 2026

    Abstract Manual inspection of onba earing casting defects is not realistic and unreliable, particularly in the case of some micro-level anomalies which lead to major defects on a large scale. To address these challenges, we propose BearFusionNet, an attention-based deep learning architecture with multi-stream, which merges both DenseNet201 and MobileNetV2 for feature extraction with a classification head inspired by VGG19. This hybrid design, figuratively beaming from one layer to another, extracts the enormity of representations on different scales, backed by a pre-preprocessing pipeline that brings defect saliency to the fore through contrast adjustment, denoising, and edge… More >

  • Open Access

    ARTICLE

    Support Vector–Guided Class-Incremental Learning: Discriminative Replay with Dual-Alignment Distillation

    Moyi Zhang, Yixin Wang*, Yu Cheng

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071021 - 12 January 2026

    Abstract Modern intelligent systems, such as autonomous vehicles and face recognition, must continuously adapt to new scenarios while preserving their ability to handle previously encountered situations. However, when neural networks learn new classes sequentially, they suffer from catastrophic forgetting—the tendency to lose knowledge of earlier classes. This challenge, which lies at the core of class-incremental learning, severely limits the deployment of continual learning systems in real-world applications with streaming data. Existing approaches, including rehearsal-based methods and knowledge distillation techniques, have attempted to address this issue but often struggle to effectively preserve decision boundaries and discriminative features… More >

  • Open Access

    ARTICLE

    Building Regulatory Confidence with Human-in-the-Loop AI in Paperless GMP Validation

    Manaliben Amin*

    Journal on Artificial Intelligence, Vol.8, pp. 1-18, 2026, DOI:10.32604/jai.2026.073895 - 07 January 2026

    Abstract Artificial intelligence (AI) is steadily making its way into pharmaceutical validation, where it promises faster documentation, smarter testing strategies, and better handling of deviations. These gains are attractive, but in a regulated environment speed is never enough. Regulators want assurance that every system is reliable, that decisions are explainable, and that human accountability remains central. This paper sets out a Human-in-the-Loop (HITL) AI approach for Computer System Validation (CSV) and Computer Software Assurance (CSA). It relies on explainable AI (XAI) tools but keeps structured human review in place, so automation can be used without creating… More >

  • Open Access

    ARTICLE

    A Temperature-Indexed Concrete Damage Plasticity Model Incorporating Bond-Slip Mechanism for Thermo-Mechanical Analysis of Reinforced Concrete Structures

    Wu Feng1,2,*, Tengku Anita Raja Hussin1, Xu Yang3

    Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.071664 - 08 January 2026

    Abstract This study investigates the thermo–mechanical behavior of C40 concrete and reinforced concrete subjected to elevated temperatures up to 700°C by integrating experimental testing and advanced numerical modeling. A temperature-indexed Concrete Damage Plasticity (CDP) framework incorporating bond–slip effects was developed in Abaqus to capture both global stress–strain responses and localized damage evolution. Uniaxial compression tests on thermally exposed cylinders provided residual strength data and failure observations for model calibration and validation. Results demonstrated a distinct two-stage degradation regime: moderate stiffness and strength reduction up to ~400°C, followed by sharp deterioration beyond 500°C–600°C, with residual capacity at… More >

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