Di Xiao^*, Wenting Jiang, Min Li

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.079808 - 09 April 2026

Abstract The rapid advancement of the Internet of Things (IoT) has transformed edge devices from simple data collectors into intelligent units capable of local processing and collaborative learning. However, the vast amounts of sensitive data generated by these devices face severe constraints from “data silos” and risks of privacy breaches. Federated learning (FL), as a distributed collaborative paradigm that avoids sharing raw data, holds great promise in the IoT domain. Nevertheless, it remains vulnerable to gradient leakage threats. While traditional differential privacy (DP) techniques mitigate privacy risks, they often come at the cost of significantly reduced… More >

Kuen-Suan Chen^1,2,3, Tsai-Sung Lin⁴, Ruey-Chyn Tsaur^4,*, Minh T. N. Nguyen⁵

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.079476 - 09 April 2026

Abstract As artificial intelligence, the Internet of Things, edge computing, and blockchain are increasingly integrated into long-term care (LTC) services, policymakers face complex and often non-compensatory trade-offs among affordability, workforce sustainability, service reliability, and data governance. Conventional compensatory evaluation models tend to mask critical structural weaknesses and limiting their usefulness for Smart LTC policy assessment. This study proposes and applies a Fuzzy Trade-Off-Aware Scoring with Conflicts (Fuzzy TASC) framework to evaluate Smart LTC system performance. Four digital-integration configurations—conventional cloud-based LTC, AI+IoT, AI+Edge, and AI+Blockchain—were compared across 12 OECD countries. A Monte Carlo perturbation procedure was incorporated… More >

Mohammed Shamar Yadkar¹, Sefer Kurnaz¹, Saadaldeen Rashid Ahmed^2,3,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.079408 - 09 April 2026

Abstract This advanced research describes CycleGAN-RRW, a new reversible watermarking system for secure image ownership authentication. It uses Cycle-Consistent Generative Adversarial Networks with adaptive feature encoding. In areas such as law, forensics, and telemedicine, digital images usually contain private info that may be changed or used without authorization. Existing watermarking methods may decrease image quality, may not be reversible, or need outside keys. To address these problems, our model embeds metadata into intermediate feature maps with Adaptive Instance Normalization (AdaIN), based on adversarial and perceptual loss. The dual-generator design permits two-way translation between original and watermarked… More >

Yan-Hao Huang^*, Chung-Ming Kao

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.079381 - 09 April 2026

Abstract Photovoltaic (PV) equivalent-circuit models are widely used for performance evaluation and diagnostics, but their usefulness relies on both accurate calibration and interpretable understanding of how parameters shape current–voltage (I–V) behavior. For nonlinear and strongly coupled PV models, conventional global sensitivity analysis can be computationally demanding and offer limited insight into effect direction and operating-point dependence. This study presents an method-oriented framework that integrates nature-inspired optimization with surrogate-based explainable global sensitivity analysis under a specified operating condition. The Starfish Optimization Algorithm (SFOA) is first used for parameter identification by searching for the optimal parameter set that… More >

Semih Nart¹, Emre Güler², Melek Güler², Gökay Uğur^3,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.079045 - 09 April 2026

Abstract Fluoride materials are renowned for their exceptional optical transparency, ionic conductivity, and chemical stability, making them indispensable in a wide range of technological applications. Despite the previous extensive research on simple metal fluorides, the complex metal fluoride family—particularly compounds with AB₂F₈ stoichiometry—remains largely unexplored. In this work, we present the first comprehensive density functional theory (DFT) investigation of the rare and formerly unreported MgAu₂F₈ complex metal fluoride, systematically revealing its electronic, optical, and thermoelectric properties under varying hydrostatic pressures. Our results reveal that MgAu₂F₈ undergoes a remarkable transformation from a wide-bandgap semiconductor at ambient conditions to a More >

Simona-Vasilica Oprea, Adela Bâra^*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.078985 - 09 April 2026

Abstract Quantization has emerged as an important technique for enabling efficient deployment of large language models (LLMs) by reducing their memory and computational requirements. This research conducts an evaluation of INT8 quantization on several state-of-the-art LLMs, GPT-2, LLaMA-2-7B-Chat and Qwen1.5-1.8B-Chat, across two hardware configurations: NVIDIA RTX4070 Laptop GPU and RTX4080 Laptop GPU and two tasks: text and code generation. By comparing quantized INT8 models with their FP16 counterparts and a human-written reference, we quantify the trade-offs between performance and efficiency using standard natural language generation metrics (BLEU, ROUGE-1, ROUGE-L) and semantic analysis via GPT-4o and Gemini… More >

Osamah Mohammed Alyasiri^1,2, Yu-N Cheah^1,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.078927 - 09 April 2026

Abstract Term weighting scheme and feature selection are two fundamental components in text classification (TC) systems, particularly in high-dimensional, multi-class, and imbalanced settings. Term weighting schemes aim to improve document representation by emphasizing discriminative terms across classes, while feature selection (FS) seeks to reduce dimensionality, eliminate irrelevant and redundant features, and enhance classification efficiency and effectiveness. However, most existing studies focus on FS independently of the term-weighting strategy used during document representation, thereby limiting the potential benefits of their interaction. This study addresses this gap by pursuing two main objectives. First, it employs an enhanced supervised… More >

Ziang Wu¹, Xuanyu Zhang², Yinbo Yu³, Qi Zhu³, Jerry Chun-Wei Lin⁴, Chunwei Tian^5,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.078842 - 09 April 2026

Abstract Image super-resolution is a significant area in the field of image processing, with broad applications across multiple domains. In recent years, advancements in Generative Adversarial Networks (GANs) have led to an increased adoption of GAN-based methods in image super-resolution, yielding remarkable results. However, there is still a limited amount of research that systematically and comprehensively summarizes the various GAN-based techniques for image super-resolution. This paper provides a comparative study that elucidates the application differences of GANs in this field. We begin by reviewing the development of GANs and introducing their popular variants used in image… More >

Mahmoud M. A. Kamel^1,2, Yu Fu³, S. Z. Abeer⁴, Zaman Mohamed Al-Delfi⁴, Yijiang Peng^1,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.078775 - 09 April 2026

Abstract Crumb rubber concrete (CRC) has emerged as a sustainable solution to the environmental challenges posed by rubber waste. This study introduces an advanced mixed-random-aggregate mesoscale model for CRC based on the Base Force Element Method (BFEM) and the complementary energy principle. The model incorporates different rubber substitution ratios (0%–30%), rubber particle sizes (2 mm and 4 mm), and specimen dimensions (edge lengths of 100, 150, and 300 mm). These parameters are considered to investigate their effects on the mechanical properties and failure mechanisms of CRC. Accordingly, the numerical results include stress–strain responses, elastic modulus, and… More >

Xiaoming Du¹, Jiahui Guo¹, Gaohan Liao¹, Tianfu Li^2,*, Haicheng Liang^1,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.078760 - 09 April 2026

Abstract Graphene has excellent mechanical, electrical and optical properties, which make it an ideal reinforcement phase for aluminum matrix composites. However, graphene is easy to agglomerate and has poor wettability with the aluminum matrix, resulting in unsatisfactory effects when added to the aluminum matrix. In this paper, the effects of transition metals (Cu, Ni, Co) on the bonding properties at the graphene/aluminum interface were systematically investigated using first-principles calculations. The computational results reveal significant differences in the effects of various metals and their crystal plane orientations on interface stability and bonding strength. Among Cu, Ni, Co… More >