Raed Alotaibi^1,*, Muhammad Atta Othman Ahmed², Omar Reyad^3,4,*, Nahla Fathy Omran⁵

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076156 - 09 April 2026

Abstract The widespread use of social media has made assessing users’ tastes and preferences increasingly complex and important. At the same time, the rapid dissemination of misinformation on these platforms poses a critical challenge, driving significant efforts to develop effective detection methods. This study offers a comprehensive analysis leveraging advanced Machine Learning (ML) techniques to classify news articles as fake or true, contributing to discourse on media integrity and combating misinformation. The suggested method employed a diverse dataset encompassing a wide range of topics. The method evaluates the performance of five ML models: Artificial Neural Networks… More >

Ans D. Alghamdi^*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.075985 - 09 April 2026

Abstract How can AI assist doctors in generating clinical reports without compromising patient privacy? This question motivates our development of PrivLLM-Guard, a novel framework for differentially private large language models (LLMs) tailored to real-time confidential medical text generation and summarization. While LLMs have shown promise in automating clinical documentation, the sensitivity of healthcare data demands rigorous privacy protections. PrivLLM-Guard addresses this need by combining advanced—differential privacy techniques with adaptive noise calibration, ensuring robust privacy guarantees without sacrificing utility. The framework integrates bidirectional transformer encoders with autoregressive decoders, further enhanced by privacy-aware attention and gradient perturbation mechanisms. Extensive More >

Ruida Liu, Dan Wang^*, Jiaming Chen, Meng Xu

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.074554 - 09 April 2026

Abstract Accurate prediction of shoulder joint angles based on surface electromyography (sEMG) signals is critical in human–machine interaction and rehabilitation engineering. However, due to the shoulder joint’s complex degrees of freedom, dynamically varying muscle coordination patterns, and the susceptibility of sEMG signals to cross-talk and noise interference, achieving high-precision prediction remains challenging. In this study, LASENet (BiLSTM–Attention–SE Network) is proposed as an end-to-end deep learning framework that integrates a bidirectional long short-term memory network (BiLSTM), a multi-head self-attention (MHSA) mechanism, and a squeeze-and-excitation (SE) block to predict shoulder joint angles across three degrees of freedom directly More >

Hatim Madkhali^1,2,*, Abdullah Sheneamer², Linh Nguyen³, Gnana Bharathy¹, Ritu Chauhan⁴, Mukesh Prasad^1,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.074444 - 09 April 2026

Abstract Consumer electronics, with 62 million tons of electronic waste (e-waste) generated in 2022 and e-waste expected to grow to 82 million tons annually by 2030, pose critical challenges when it comes to national infrastructure and circular economy policies. This paper compares forecasting approaches using sparse panel data for 32 European countries (2005–2018, Eurostat/Waste Electrical and Electronic Equipment (WEEE) Directive), focusing on leakage-safe prospective validation to guarantee true predictive performance. We make one-step-ahead predictions with conservative features (primarily lagged values) to account for temporal autocorrelation but with reduced multicollinearity (Variance Inflation Factor (VIF) ≈ 1.0). Cross-paradigm comparisons… More >

Arifur Rahman¹, MD Azam Khan¹, Farhad Uddin Mahmud¹, Kanchon Kumar Bishnu², Ashifur Rahman³, M. F. Mridha^4,*, Md. Jakir Hossen^5,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.071029 - 09 April 2026

Abstract Generative Artificial Intelligence (AI) is reshaping digital marketing by creating automated content, personalizing campaigns, and offering new ways to engage consumers. This systematic review examines research on generative AI, highlighting both its technological progress and the ethical, technical, and organizational hurdles that could limit its use. We used a PRISMA-based method to search major databases (ACM Digital Library, IEEE Xplore, and Scopus) for peer-reviewed studies published from 2018 to 2025. Our findings reveal major gains in text creation, image generation, and multimodal campaigns, which can lower costs and spark creative thinking. Still, data privacy, bias More >

Lin Jia, Qiang He^*

Journal of Polymer Materials, Vol.43, No.1, 2026, DOI:10.32604/jpm.2026.077807 - 03 April 2026

Abstract Aerogels, renowned as ultra-lightweight solids with exceptional porosity and specific surface area, have emerged as pivotal materials for thermal insulation, catalysis, energy storage, and biomedicine. This review comprehensively evaluates the recent strides in sustainable, high-performance cellulose-based aerogels, emphasizing their fabrication, functionalization, and application prospects. It details the extraction of cellulose from diverse sources and its subsequent processing into nanocellulose (e.g., cellulose nanofibrils and nanocrystals), which serves as the fundamental building block for aerogel synthesis. The critical sol-gel transition, solvent selection, and the pivotal role of drying techniques—freeze-drying, supercritical drying, and ambient pressure drying—in determining final… More >

Junping Wang^1,2, Mingbiao Xu^3,*, Wei Xiao^1,*

Journal of Polymer Materials, Vol.43, No.1, 2026, DOI:10.32604/jpm.2026.077100 - 03 April 2026

Abstract Formulating oil-based drilling fluids (OBDFs) with an ultra-low oil-to-water ratio (OWR ≤ 60:40) presents a formidable stability challenge due to the maximized interfacial area and intensified stress on the interfacial film under high-temperature, high-density conditions. To address this, we engineered a synergistic stabilization system through molecular and colloidal design. A novel hyperbranched polyamide emulsifier (epoxidized soybean oil polyamide) (ESOP), synthesized from epoxidized soybean oil, exhibits superior thermal stability and interfacial activity due to its hyperbranched architecture. Combined with calcium petroleum sulfonate (CPS) and hydrophobic nanosilica (HNs), it enables a high-performance OBDF with an ultra-low OWR… More >

Chin-Wen Liao^1,2,3, En-Shiuh Lin¹, Wei-Lun Huang^4,5,6, I-Chi Wang⁷, Bo-Siang Chen^8,*, Wei-Sho Ho^1,2,9,*

Journal of Polymer Materials, Vol.43, No.1, 2026, DOI:10.32604/jpm.2026.076807 - 03 April 2026

Abstract The demand for extended electric vehicle (EV) range necessitates advanced lightweighting strategies. This study introduces a materials genome approach, augmented by machine learning (ML), for optimizing lightweight composite designs for EVs. A comprehensive materials genome database was developed, encompassing composites based on carbon, glass, and natural fibers. This database systematically records critical parameters such as mechanical properties, density, cost, and environmental impact. Machine learning models, including Random Forest, Support Vector Machines, and Artificial Neural Networks, were employed to construct a predictive system for material performance. Subsequent material composition optimization was performed using a multi-objective genetic More >

Yujie Zhang, Yankai Zhao, Zhuang Zhao, Mengmeng Shan, Bochen Xu, Haoquan Xue, Junxuan Xu, Fan Wu, Qiang He^*

Journal of Polymer Materials, Vol.43, No.1, 2026, DOI:10.32604/jpm.2026.076617 - 03 April 2026

Abstract This study presents a sustainable approach for the valorization of spent coffee grounds (CG) by converting them into carboxylated cellulose nanofibrils (CG-TCNF) via formic acid/hydrogen peroxide pretreatment followed by TEMPO/NaClO/NaClO₂-mediated oxidation. The pretreatment efficiently removed lignin, hemicellulose, and other non-cellulosic components, yielding purified cellulose (CG-C) with high crystallinity (CrI = 84%). Subsequent regioselective oxidation introduced carboxyl groups at the C6 position of cellulose chains, achieving a high carboxylate content of 1.4 mmol/g. The resulting CG-TCNF exhibited a well-dispersed nanofibrillar morphology with an average width of 3.57 nm and a high specific surface area of 265 m²/g. More >

T. Subash^1,*, M. Sekar², R. Selvabharathi³

Journal of Polymer Materials, Vol.43, No.1, 2026, DOI:10.32604/jpm.2026.075026 - 03 April 2026

Abstract The two distinct types of composite materials (5% to 10%) were developed using recycled polyvinyl alcohol fiber (RPA), silicon nitride fiber (SN), and reduced carbon nanoparticles (RCN). Enhanced microstructural properties and mechanical strength were attained through the application of the 3-glycidoxypropyltrimethoxysilane coupling method. The combination of the resin-like properties of RPA-SN fiber resulted in the formation of robust outer strength and a high bonding structure. RPA-RCN composite materials with a weight percentage of 10% exhibited a tensile strength of 42 MPa. In contrast, RPA-SN-RCN composite materials containing 5% to 10% demonstrated enhanced tensile, bending, and… More >