Priyanka Halder, Gopikrishnan Sundaram^*

Journal on Internet of Things, Vol.8, pp. 127-153, 2026, DOI:10.32604/jiot.2026.073962 - 29 May 2026

Abstract The need for intelligent learning frameworks that can function under stringent limitations relating to privacy, energy, scalability, and trust has increased due to the Internet of Things’ (IoT) and the Internet of Artificial Things’ (IoAT) explosive expansion. Federated Learning (FL), which allows collaborative model training without sharing raw data, has become a potential approach. Non-IID data delivery, inconsistent client engagement, vulnerability to poisoning assaults, and low resource knowledge are among of the significant obstacles that FL alone must overcome. Blockchain integration adds extra overhead in terms of latency, energy consumption, and scalability, but it has… More >

Basma Souayeh^*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.081163 - 27 May 2026

Abstract This study conducts a comprehensive numerical investigation of magnetohydrodynamic (MHD) mixed convection and entropy generation in a two-dimensional square cavity filled with a ternary hybrid nanofluid. The working fluid consists of Multi-Walled Carbon Nanotubes (MWCNT), Copper (Cu), and Ferric Oxide (Fe₃O₄) nanoparticles dispersed in water, selected for their superior thermal properties. Two vertically aligned, saw-tooth-shaped cooling structures are embedded along the left and right walls of the cavity, with four distinct configurations considered based on their vertical positioning. An externally imposed uniform magnetic field is applied to assess its influence on fluid flow, heat transfer, and… 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 >

Qilong Wang¹, Ning Wang¹, Shuhan Luo¹, Xiang Gao², Yuqian Lu³, Min He^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080372 - 27 May 2026

Abstract Tunnel environments often suffer from GPS denial, uneven illumination, and structural uniformity, which lead to feature degradation, loop closure failure, and long-distance drift in SLAM systems. To solve these problems, this study aims to propose a high-precision SLAM method suitable for tunnel structural health monitoring. Firstly, an ABA-CLAHE image enhancement algorithm is proposed, which adopts cascaded processing of nonlinear brightness adjustment in HSV space and CLAHE local contrast optimization to improve low-light image quality and enhance feature stability. Then, SURF feature matching combined with the RANSAC algorithm is used to ensure feature matching accuracy. Finally, More >

Bahareh Ramzikhalesi^1,*, Ali Rakhsh-Mahpour¹, Josep Claramunt-Blanes², Ernest Bernat-Maso³

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080138 - 27 May 2026

Abstract The mechanical behavior of nonwoven fabrics as reinforcement in cementitious composites remains insufficiently explored, particularly from a numerical modeling perspective, despite their growing interest as sustainable alternatives to conventional textiles. This study presents a simplified, engineering-oriented numerical modeling framework for reproducing the flexural mechanical response of cementitious composites reinforced with flax nonwoven fabric. Four-point bending (flexural) behavior of nonwoven fabric–reinforced cementitious composites was numerically simulated using ANSYS software. The model is developed using Finite Element Analysis (FEA) and incorporates a Representative Volume Element (RVE) approach to account for the heterogeneous fiber–matrix interaction. The required material… More >

Angel Prado^1,*, Alejandro Alañón², Ricardo Castedo³, Anastasio Pedro Santos³, Lina María López³, María Chiquito³

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.079804 - 27 May 2026

Abstract This study presents a numerical investigation into the influence of reinforcement layout on the blast response of a reinforced concrete (RC) slab subjected to a close-in explosion. The reference scenario is based on a blast test from the SEGTRANS project using a 15 kg TNT equivalent charge. A validated LS-DYNA model was used, applying the Load Blast Enhanced method and the Continuous Surface Cap Model for concrete behaviour. Forty-nine reinforcement configurations were assessed, all with constant steel mass but varying numbers of longitudinal bars and stirrups. Damage metrics such as eroded elements and internal energy… 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 >

Oluwatosin Ahmed Amodu¹, Zurina Mohd Hanapi^1,*, Chedia Jarray², Huda Althumali³, Faten A. Saif ⁴, Raja Azlina Raja Mahmood¹, Mohammed Sani Adam⁵, Nor Fadzilah Abdullah⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.077054 - 27 May 2026

Abstract Non-terrestrial networks (NTNs)—including UAVs, HAPs, and satellite systems—are rapidly becoming key enablers of wide-area, resilient connectivity for large-scale IoT applications. As these platforms integrate with terrestrial networks to form space–air–ground architectures, optimization challenges related to trajectory, resource management, energy efficiency, and security become increasingly complex. Machine learning (ML) has emerged as a central tool for addressing these challenges by enabling adaptive, data-driven decision-making under uncertainty. This survey presents an optimization-centric review of ML-based NTN-assisted IoT systems focusing on aspect-specific datasets. Using a structured methodology involving dataset curation, keyword filtering, metadata analysis, and citation-based paper selection,… More >

Guansi Liu¹, Hui Jin^1,*, Keqin Ding², Hao Wang³, Violeta Mircevska⁴, Maosen Cao⁵

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.079074 - 18 May 2026

Abstract In response to the dynamic changes in fatigue damage location of crane welding structures under lifting loads and the difficulty in accurately obtaining the stress concentration factor of welds, which results in limited effetiveness of traditional health monitoring sensor placement. This paper proposes aa sensor placement optimization method that integrates damage prediction and risk assessment. Firstly, the influence of weld geometry on fatigue performance is analyzed, and a rapid estimation model for the stress concentration factor is established using a radial basis function support vector machine. Furthermore, a fatigue damage prediction model for the welded… More >

Mustapha Hatoum¹, Alessandro P. Fantilli^1,*, Bernardino Chiaia¹, Georgios Kalamaras²

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.076141 - 18 May 2026

Abstract This study investigates the contribution of fibers to the durability of reinforced concrete tunnel linings. Two cast-in-situ tunnels are herein analyzed after twenty years of service. Tunnel #1, made with plain concrete and steel rebar, has shown significant spalling at joints between two consecutive tunnel panels, caused by poor workmanship and construction details. Conversely, in Tunnel #2, close to Tunnel #1 on the same motorway, fiber-reinforced concrete (FRC) was used in combination with steel rebar. During the service life, the amount of FRC spalled from the cold joints of this lining has been significantly lower than More >