Wael A. Altabey^*

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1529-1545, 2025, DOI:10.32604/sdhm.2025.069003 - 17 November 2025

Abstract This paper aims to study a novel smart self-powered wireless lightweight (SPWL) bridge health monitoring sensor, which integrates key technologies such as large-scale, low-power wireless data transmission, environmental energy self-harvesting, and intelligent perception, and can operate stably for a long time in complex and changing environments. The self-powered system of the sensor can meet the needs of long-term bridge service performance monitoring, significantly improving the coverage and efficiency of monitoring. By optimizing the sensor system design, the maximum energy conversion of the energy harvesting unit is achieved. In order to verify the function and practicality More > Graphic Abstract

Md Sabir Hossain¹, Md Mahfuzur Rahman^1,2,*, Mufti Mahmud^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 1087-1116, 2025, DOI:10.32604/cmes.2025.068779 - 30 October 2025

Abstract This article presents a human fall detection system that addresses two critical challenges: privacy preservation and detection accuracy. We propose a comprehensive framework that integrates state-of-the-art machine learning models, multimodal data fusion, federated learning (FL), and Karush-Kuhn-Tucker (KKT)-based resource optimization. The system fuses data from wearable sensors and cameras using Gramian Angular Field (GAF) encoding to capture rich spatial-temporal features. To protect sensitive data, we adopt a privacy-preserving FL setup, where model training occurs locally on client devices without transferring raw data. A custom convolutional neural network (CNN) is designed to extract robust features from More > Graphic Abstract

Sara I. Abdelsalam^1,2,*, W. Abbas³, Ahmed M. Megahed⁴, Hassan M. H. Sadek⁵, M. S. Emam⁵

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1511-1527, 2025, DOI:10.32604/fhmt.2025.069359 - 31 October 2025

Abstract This study rigorously examines the interplay between viscous dissipation, magnetic effects, and thermal radiation on the flow behavior of a non-Newtonian Carreau squeezed fluid passing by a sensor surface within a micro cantilever channel, aiming to deepen our understanding of heat transport processes in complex fluid dynamics scenarios. The primary objective is to elucidate how physical operational parameters influence both the velocity of fluid flow and its temperature distribution, utilizing a comprehensive numerical approach. Employing a combination of mathematical modeling techniques, including similarity transformation, this investigation transforms complex partial differential equations into more manageable ordinary… More >

Anna Elisa Silva, Eduardo Thiago Formigari, João Pedro Mayer Camacho Araújo, Dagoberto de Oliveira Silva, Jürgen Andreaus, Eduardo Guilherme Cividini Neiva^*

Journal of Renewable Materials, Vol.13, No.10, pp. 1899-1912, 2025, DOI:10.32604/jrm.2025.02025-0130 - 22 October 2025

Abstract Here, we report a comprehensive study on the characterization of cotton biomass residue, its conversion into carbon-based materials via pyrolysis, and its application as an electrochemical sensor for ascorbic acid (AA). The compositions, morphologies, and structures of the resulting materials were investigated using XRD, FTIR, TGA, SEM, and EDS. Pyrolysis was carried out in an air atmosphere at different temperatures (300°C and 400°C) and durations (1, 60, and 240 min), leading to the transformation of lignocellulosic cotton residue into carbon-based materials embedded with inorganic nanoparticles, including carbonates, sulfates, chlorates, and phosphates of potassium, calcium, and… More > Graphic Abstract

J. S. V. Siva Kumar¹, Mahmad Mustafa², Sk. M. Unnisha Begum³, Badugu Suresh⁴, Rajanand Patnaik Narasipuram^5,*

Energy Engineering, Vol.122, No.10, pp. 3891-3904, 2025, DOI:10.32604/ee.2025.070052 - 30 September 2025

Abstract Electric vehicle (EV) monitoring systems commonly depend on IoT-based sensor measurements to track key performance parameters such as vehicle speed, state of charge (SoC), battery temperature, power consumption, motor RPM, and regenerative braking. While these systems enable real-time data acquisition, they are often hindered by sensor noise, communication delays, and measurement uncertainties, which compromise their reliability for critical decision-making. To overcome these limitations, this study introduces a comparative framework that integrates reference signals, a digital twin model emulating ideal system behavior, and real-time IoT measurements. The digital twin provides a predictive and noise-resilient representation of More >

Siwakorn Banluesapy, Mahasak Ketcham^*, Montean Rattanasiriwongwut

Energy Engineering, Vol.122, No.10, pp. 4261-4296, 2025, DOI:10.32604/ee.2025.068422 - 30 September 2025

Abstract Traditional agricultural irrigation systems waste significant amounts of water and energy due to inefficient scheduling and the absence of real-time monitoring capabilities. This research developed a comprehensive IoT-based smart irrigation control system to optimize water and energy management in agricultural greenhouses while enhancing crop productivity. The system employs a sophisticated four-layer Internet of Things (IoT) architecture based on an ESP32 microcontroller, integrated with multiple environmental sensors, including soil moisture, temperature, humidity, and light intensity sensors, for comprehensive environmental monitoring. The system utilizes the Message Queuing Telemetry Transport (MQTT) communication protocol for reliable data transmission and… More >

Raj Sonani¹, Reham Alhejaili^2,*, Pushpalika Chatterjee³, Khalid Hamad Alnafisah⁴, Jehad Ali^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3169-3189, 2025, DOI:10.32604/cmes.2025.070225 - 30 September 2025

Abstract Healthcare networks are transitioning from manual records to electronic health records, but this shift introduces vulnerabilities such as secure communication issues, privacy concerns, and the presence of malicious nodes. Existing machine and deep learning-based anomalies detection methods often rely on centralized training, leading to reduced accuracy and potential privacy breaches. Therefore, this study proposes a Blockchain-based-Federated Learning architecture for Malicious Node Detection (BFL-MND) model. It trains models locally within healthcare clusters, sharing only model updates instead of patient data, preserving privacy and improving accuracy. Cloud and edge computing enhance the model’s scalability, while blockchain ensures More >

Ramadan Abdul-Rashid¹, Mohd Amiruddin Abd Rahman^1,*, Abdulaziz Yagoub Barnawi²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3213-3250, 2025, DOI:10.32604/cmes.2025.066589 - 30 September 2025

Abstract Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks (WSNs), especially in security-critical, time-sensitive applications. However, most existing protocols degrade substantially under malicious interference. We introduce iSTSP, an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust, precise synchronization even in hostile environments: (1) trust preprocessing that filters node participation using behavioral trust scoring; (2) anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time; (3) reliability-weighted consensus that prioritizes high-trust nodes during time aggregation; and (4) convergence-optimized synchronization… More >

Ana M. Vela-AlcáNtara¹, Diego J. HernáNdez-SáNchez^1,2, Elisa Tamariz^1,*

BIOCELL, Vol.49, No.9, pp. 1663-1695, 2025, DOI:10.32604/biocell.2025.066201 - 25 September 2025

Abstract Cells are exposed to various mechanical forces, including extracellular and intracellular forces such as stiffness, tension, compression, viscosity, and shear stress, which regulate cell biology. The process of transducing mechanical stimuli into biochemical signals is termed mechanotransduction. These mechanical forces can regulate protein and gene expression, thereby impacting cell morphology, adhesion, proliferation, apoptosis, and migration. During cancer development, significant changes in extracellular and intracellular mechanical properties occur, resulting in altered mechanical inputs to which cells are exposed. MicroRNAs (miRNAs), key post-transcriptional regulators of gene and protein expression, are increasingly recognized as mechanosensitive molecules involved in More >

Valentin Stangaciu^*, Mihai-Vladimir Ghimpau, Adrian-Gabriel Sztanarec

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3213-3229, 2025, DOI:10.32604/cmc.2025.068844 - 23 September 2025

Abstract Along with process control, perception represents the main function performed by the Edge Layer of an Internet of Things (IoT) network. Many of these networks implement various applications where the response time does not represent an important parameter. However, in critical applications, this parameter represents a crucial aspect. One important sensing device used in IoT designs is the accelerometer. In most applications, the response time of the embedded driver software handling this device is generally not analysed and not taken into account. In this paper, we present the design and implementation of a predictable real-time More >