Do Young Pyun¹, Bingjie Wang², Kyong Keun Choi^3,*, Sungjae Kim⁴, Taeyeon Koo^5,*

International Journal of Mental Health Promotion, Vol.28, No.5, 2026, DOI:10.32604/ijmhp.2026.078956 - 28 May 2026

Abstract Backgrounds: South Korea is one of the world’s fastest-aging societies, facing significant challenges in maintaining healthcare quality and accessibility for its rapidly growing elderly population. This study extends the Technology Acceptance Model (TAM) by integrating health empowerment to examine its influence on digital healthcare device adoption among Korean older adults. Specifically, this study aims to investigate how health empowerment is associated with perceived usefulness and perceived ease of use, and how these perceptions subsequently relate to attitude and intention to use digital healthcare devices. Methods: Data were collected from 342 Korean older adults. The analysis followed… More >

Chun-Chieh Hu^1,*, Meixuan Li^1,2, Ruize Gao^1,2

International Journal of Mental Health Promotion, Vol.28, No.5, 2026, DOI:10.32604/ijmhp.2026.078559 - 28 May 2026

Abstract Backgrounds: The mental health consequences of social media use remain debated. Drawing on the “rich-get-richer” perspective, this study examines whether social media access interacts with perceived social resources to shape depression risk among Chinese students. Methods: We analyze nationally representative data from the 2020 and 2022 waves of the China Family Panel Studies (CFPS), constructing a two-period unbalanced student panel. High-dimensional fixed effects linear probability models are estimated with province and year fixed effects and province-specific linear trends. Mediation analyses follow the Baron and Kenny framework and are supplemented by Sobel-Goodman and bootstrap tests. Heterogeneity is… More >

Megabi Adane Yizengaw^1,*, Alehegn Atalay Birlie¹, Tamerat Tesfaye², Rajan Katrikan¹, Eldana Bizuneh Cheklie¹, Zelalem Girma¹

Journal of Renewable Materials, Vol.14, No.5, 2026, DOI:10.32604/jrm.2025.02025-0175 - 28 May 2026

Abstract Grape by-product of the wine industry, rich in polyphenols, tannins, lignin, and natural waxes, the chemical constituents grape skins 45%–55%, seeds 25%–35%, and stems or stalks 25%–35% weight of grape provide intrinsic cross-linking, mechanical reinforcement, antioxidant activity, and water resistance, closely replicating the effects of conventional vegetable tanning without using toxic chemicals. This review comprehensively examines current eco-friendly extraction methods to isolate bioactive compounds, as well as fiber modification techniques to improve polymer compatibility. Composite fabrication involves blending processed grape waste fibers with bio-based polymers and renewable plasticizers to produce materials exhibiting competitive tensile strength,… More >

Hyeonsoo Yu¹, Hwankuk Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.082095 - 27 May 2026

Abstract The introduction of the Open Radio Access Network (O-RAN) architecture enhances network flexibility but introduces novel security threats targeting open interfaces and the RAN Intelligent Controller (RIC). Particularly in the Near-RT RIC environment, an effective Intrusion Detection System (IDS) that satisfies strict near-real-time constraints of within 1 s is essential to defend against cyber attacks. This paper proposes an Artificial Intelligence (AI)-based IDS xApp designed for real-time cyber attack monitoring in the O-RAN Near-RT RIC environment, and quantitatively analyzes its anomaly detection performance and inference latency characteristics against multi-layer security threats utilizing Open RAN Centralized… More >

Yenjou Wang¹, Chihtan Cheng², Jia-Wei Chang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080888 - 27 May 2026

Abstract As large language models (LLMs) become increasingly integrated into enterprise decision-making processes, structural pressures such as version drift, cross-source evidence integration, and regulatory accountability have shifted the primary challenge from isolated generative performance to system-level consistency, traceability, and governability. This paper systematically reviews key technological developments relevant to enterprise requirements, including document perception, retrieval-augmented generation (RAG), hybrid RAG-KG architectures, fine-grained attribution evaluation, and multi-agent coordination. The analysis demonstrates that the main obstacle to enterprise LLM adoption is not model capability, but rather the structural gap between fragmented technical modules and the need for high-reliability decision-making. More >

Shuvodeep De^1,*, Agnivo Gosai^2,#, Karun Thankachan^3,#, Ramadan A. ZeinEldin⁴, Abdulaziz T. Almaktoom⁵, Mustafa Bayram⁶, Ali Wagdy Mohamed^7,8,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080601 - 27 May 2026

Abstract Sentiment analysis (SA) has evolved from a niche text-classification task into a central problem in natural language processing, spanning multiple domains, modalities, and languages. This survey provides a comprehensive review of sentiment analysis methods from their origins in lexicon-based approaches through classical machine learning, deep learning architectures, pre-trained transformers, and the current era of large language models (LLMs). We formalize the SA problem across multiple granularity levels (document, sentence, and aspect) and present a taxonomy that encompasses classification, regression, aspect-based sentiment analysis (ABSA), emotion detection, and stance detection tasks across diverse domains including movie reviews,… More >

Natalia Prieto-Fernández¹, Martín Bayón-Gutiérrez^1,*, Sergio Fernández-Blanco¹, Álvaro Fernández-Blanco¹, Francisco Carro-De-Lorenzo², José Alberto Benítez-Andrades¹

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080540 - 27 May 2026

Abstract Feature-based Simultaneous Localization and Mapping (SLAM) using 2D Light Detection and Ranging (LiDAR) in structured indoor environments commonly relies on the extraction of straight segments and corners from raw scan data. The quality of these landmarks depends not only on the fitting algorithm, but also on how uncertainty is modeled and propagated from line estimates to derived corner features. Although the magnitude of LiDAR uncertainty has been widely studied, the influence of line parameterization and geometric conditioning on uncertainty propagation has received less attention. In particular, the scale ambiguity inherent to implicit line representations can… More >

Ezz El-Din Hemdan¹, Haitham Elwahsh^2,3, Samah Alshathri^4,*, Amged Sayed^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.079305 - 27 May 2026

Abstract Ensuring robust methods for maintaining high levels of medical data security is crucial in the Medical Internet of Things (IoT) for the protection of sensitive patient data during real-time transmission and analysis. Electroencephalography (EEG) signals in medical IoT systems are transmitted through cloud and edge networks, which create risks of cyber threats, unauthorized access, and data breaches. Consequently, there is an urgent need for efficient encryption methods to ensure the confidentiality of EEG signals during classification and prediction processes, as several state-of-the-art models either neglect security during classification or suffer from increased computational overhead that… More >

Yousra Abudaqqa^*, Zulaiha Ali Othman, Azuraliza Abu Bakar

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.079034 - 27 May 2026

Abstract Signal categorization is a critical component of the Dendritic Cell Algorithm (DCA), as it directly influences its anomaly detection capability. Conventional DCA implementations typically rely on heuristic or optimization-based approaches, such as Grouping Particle Swarm Optimization (GPSO), Grouping Genetic Algorithms (GGA), Principal Component Analysis (PCA), and Support Vector Machines (SVM), to determine mappings between input features and the three immunological signal categories: Pathogen-Associated Molecular Patterns (PAMP), Danger Signals (DS), and Safe Signals (SS). These approaches depend heavily on domain expertise and predefined rules, making the resulting signal mappings static and often dataset specific. Consequently, the… More >

Ghadi Almaktoom, Suliman Aladhadh, Salim El Khediri^*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.078774 - 27 May 2026

Abstract The rapid growth of phishing attempts in the enterprise could potentially lead to bankruptcy. The primary focus of the research is on detecting phishing attacks, with no interest in how the data is processed. Attackers use fraudulent methods to obtain valuable, confidential information, resulting in billions of dollars in financial losses for enterprises. In our review, we examined the methods used in phishing-detection studies. We concluded that the two main sections, centralized and decentralized methods, were the centralized ones, which aggregate data in a central server and thus violate data protection regulations, such as GDPR.… More >