Junwen Huo, Haicheng Liang, Weiye Dong, Xiaoming Du^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.073285 - 09 December 2025

Abstract With the rapid advancement of electromagnetic launch technology, enhancing the structural stability and thermal resistance of armatures has become essential for improving the overall efficiency and reliability of railgun systems. Traditional aluminum alloy armatures often suffer from severe ablation, deformation, and uneven current distribution under high pulsed currents, which limit their performance and service life. To address these challenges, this study employs the Johnson–Cook constitutive model and the finite element method to develop armature models of aluminum matrix composites with varying heterogeneous graphene volume fractions. The temperature, stress, and strain of the armatures during operation… More >

Chenxi Xiu^1,2,*, Xihua Chu², Ao Mei¹, Liangfei Gong¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-39, 2026, DOI:10.32604/cmc.2025.073193 - 09 December 2025

Abstract Granular materials exhibit complex macroscopic mechanical behaviors closely related to their micro-scale microstructural features. Traditional macroscopic phenomenological elasto-plastic models, however, usually have complex formulations and lack explicit relations to these microstructural features. To avoid these limitations, this study proposes a micromechanics-based softening hyperelastic model for granular materials, integrating softening hyperelasticity with microstructural insights to capture strain softening, critical state, and strain localization behaviors. The model has two key advantages: (1) a clear conceptualization, straightforward formulation, and ease of numerical implementation (via Abaqus UMAT subroutine in this study); (2) explicit incorporation of micro-scale features (e.g., contact… More >

Shaojie Min¹, Yaxiao Luo¹, Kebing Liu¹, Qingyuan Gong², Yang Chen^1,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-23, 2026, DOI:10.32604/cmc.2025.073175 - 09 December 2025

Abstract User identity linkage (UIL) across online social networks seeks to match accounts belonging to the same real-world individual. This cross-platform mapping enables accurate user modeling but also raises serious privacy risks. Over the past decade, the research community has developed a wide range of UIL methods, from structural embeddings to multimodal fusion architectures. However, corresponding adversarial and defensive approaches remain fragmented and comparatively understudied. In this survey, we provide a unified overview of both mapping and anti-mapping methods for UIL. We categorize representative mapping models by learning paradigm and data modality, and systematically compare them… More >

Salahudin Robo^1,2, Triyanna Widiyaningtyas^1,*, Wahyu Sakti Gunawan Irianto¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.073011 - 09 December 2025

Abstract Recommendation systems are an integral and indispensable part of every digital platform, as they can suggest content or items to users based on their respective needs. Collaborative filtering is a technique often used in various studies, which produces recommendations by analyzing similarities between users and items based on their behavior. Although often used, traditional collaborative filtering techniques still face the main challenge of sparsity. Sparsity problems occur when the data in the system is sparse, meaning that only a portion of users provide feedback on some items, resulting in inaccurate recommendations generated by the system.… More >

Chuang-Chieh Lin¹, Yung-Shen Huang², Shih-Yeh Chen^2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.072890 - 09 December 2025

Abstract With the rapid development of generative artificial intelligence (GenAI), the task of story visualization, which transforms natural language narratives into coherent and consistent image sequences, has attracted growing research attention. However, existing methods still face limitations in balancing multi-frame character consistency and generation efficiency, which restricts their feasibility for large-scale practical applications. To address this issue, this study proposes a modular cloud-based distributed system built on Stable Diffusion. By separating the character generation and story generation processes, and integrating multi-feature control techniques, a caching mechanism, and an asynchronous task queue architecture, the system enhances generation… More >

Chia-Hui Liu^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-18, 2026, DOI:10.32604/cmc.2025.072887 - 09 December 2025

Abstract The Industrial Internet of Things (IIoT) has emerged as a cornerstone of Industry 4.0, enabling large-scale automation and data-driven decision-making across factories, supply chains, and critical infrastructures. However, the massive interconnection of resource-constrained devices also amplifies the risks of eavesdropping, data tampering, and device impersonation. While digital signatures are indispensable for ensuring authenticity and non-repudiation, conventional schemes such as RSA and ECC are vulnerable to quantum algorithms, jeopardizing long-term trust in IIoT deployments. This study proposes a lightweight, stateless, hash-based signature scheme that achieves post-quantum security while addressing the stringent efficiency demands of IIoT. The… More >

Bindi Saurabh Thakkar¹, Pradeep Kumar Karsh^2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-22, 2026, DOI:10.32604/cmc.2025.072839 - 09 December 2025

Abstract This study investigates the uncertain dynamic characterization of hybrid composite plates by employing advanced machine-assisted finite element methodologies. Hybrid composites, widely used in aerospace, automotive, and structural applications, often face variability in material properties, geometric configurations, and manufacturing processes, leading to uncertainty in their dynamic response. To address this, three surrogate-based machine learning approaches like radial basis function (RBF), multivariate adaptive regression splines (MARS), and polynomial neural networks (PNN) are integrated with a finite element framework to efficiently capture the stochastic behavior of these plates. The research focuses on predicting the first three natural frequencies… More >

Alexander V. Savin^1,2, Elena A. Korznikova^3,4, Sergey V. Dmitriev^5,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.072786 - 09 December 2025

Abstract Due to their chiral structure, carbon nanosprings possess unique properties that are promising for nanotechnology applications. The structural transformations of carbon nanosprings in the form of spiral macromolecules derived from planar coronene and kekulene molecules (graphene helicoids and spiral nanoribbons) are analyzed using molecular dynamics simulations. The interatomic interactions are described by a force field including valence bonds, bond angles, torsional and dihedral angles, as well as van der Waals interactions. While the tension/compression of such nanosprings has been analyzed in the literature, this study investigates other modes of deformation, including bending and twisting. Depending… More >

Hong Zhao, Hongbin Chen^*, Zhihui Guo, Ling Zhan, Shichao Li

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-25, 2026, DOI:10.32604/cmc.2025.072776 - 09 December 2025

Abstract UAV-mounted intelligent reflecting surface (IRS) helps address the line-of-sight (LoS) blockage between sensor nodes (SNs) and the fusion center (FC) in Internet of Things (IoT). This paper considers an IoT assisted by multiple UAVs-mounted IRS (U-IRS), where the data from ground SNs are transmitted to the FC. In practice, energy efficiency (EE) and mission completion time are crucial metrics for evaluating system performance and operational costs. Recognizing their importance during data collection, we formulate a multi-objective optimization problem to maximize EE and minimize total mission completion time simultaneously. To characterize this tradeoff while considering optimization… More >

Meenakshi Aggarwal¹, Vikas Khullar^2,*, Nitin Goyal³

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-31, 2026, DOI:10.32604/cmc.2025.072673 - 09 December 2025

Abstract The Internet of Vehicles, or IoV, is expected to lessen pollution, ease traffic, and increase road safety. IoV entities’ interconnectedness, however, raises the possibility of cyberattacks, which can have detrimental effects. IoV systems typically send massive volumes of raw data to central servers, which may raise privacy issues. Additionally, model training on IoV devices with limited resources normally leads to slower training times and reduced service quality. We discuss a privacy-preserving Federated Split Learning with Tiny Machine Learning (TinyML) approach, which operates on IoV edge devices without sharing sensitive raw data. Specifically, we focus on… More >