Rashid Jahangir^1,*, Nazik Alturki², Muhammad Asif Nauman³, Faiqa Hanif¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.071574 - 09 December 2025

Abstract Human activity recognition (HAR) is a method to predict human activities from sensor signals using machine learning (ML) techniques. HAR systems have several applications in various domains, including medicine, surveillance, behavioral monitoring, and posture analysis. Extraction of suitable information from sensor data is an important part of the HAR process to recognize activities accurately. Several research studies on HAR have utilized Mel frequency cepstral coefficients (MFCCs) because of their effectiveness in capturing the periodic pattern of sensor signals. However, existing MFCC-based approaches often fail to capture sufficient temporal variability, which limits their ability to distinguish… More >

Moneerah Alotaibi^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.069195 - 10 November 2025

Abstract Advanced traffic monitoring systems encounter substantial challenges in vehicle detection and classification due to the limitations of conventional methods, which often demand extensive computational resources and struggle with diverse data acquisition techniques. This research presents a novel approach for vehicle classification and recognition in aerial image sequences, integrating multiple advanced techniques to enhance detection accuracy. The proposed model begins with preprocessing using Multiscale Retinex (MSR) to enhance image quality, followed by Expectation-Maximization (EM) Segmentation for precise foreground object identification. Vehicle detection is performed using the state-of-the-art YOLOv10 framework, while feature extraction incorporates Maximally Stable Extremal… More >

A. W. Jabbar^a, N. K. Abbas^b,*

Chalcogenide Letters, Vol.22, No.8, pp. 735-752, 2025, DOI:10.15251/CL.2025.228.735

Abstract Nanostructured CdS and CdS: Cu thin films were synthesized by pulsed laser deposition with a Nd: YAG laser of different energies, 0.1, 0.5, and 1 W. The number of pulses was 300, and the frequency was 20 kHz. The CdS nanoparticles were deposited on a glass substrate. The optical, structural, and morphological properties were investigated utilized X-ray diffraction, UV-Vis spectrophotometry, and field emission scanning electron microscopy. From 2.25 to 2.1 eV, the results demonstrate that the band gap energy reduces as laser energy increases. Morphological investigations reveal that the laser energy has a significant impact More >

Yu Tao¹, Tian Yin², Yang Jie^1,*

Journal on Artificial Intelligence, Vol.7, pp. 549-570, 2025, DOI:10.32604/jai.2025.072727 - 01 December 2025

Abstract To address the issue of insufficient accuracy in attitude estimation using Inertial Measurement Units (IMU), this paper proposes a multi-sensor fusion attitude estimation method based on an improved Error-State Kalman Filter (ESKF). Several adaptive mechanisms are introduced within the standard ESKF framework: first, the process noise covariance is dynamically adjusted based on gyroscope angular velocity to enhance the algorithm’s adaptability under both static and dynamic conditions; second, the Sage-Husa algorithm is employed to estimate the measurement noise covariance of the accelerometer and magnetometer in real-time, mitigating disturbances caused by external accelerations and magnetic fields. Additionally,… More >

Farhad Mortezapour Shiri^*, Thinagaran Perumal, Norwati Mustapha, Raihani Mohamed

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1389-1485, 2025, DOI:10.32604/cmes.2025.071858 - 26 November 2025

Abstract Human Activity Recognition (HAR) represents a rapidly advancing research domain, propelled by continuous developments in sensor technologies and the Internet of Things (IoT). Deep learning has become the dominant paradigm in sensor-based HAR systems, offering significant advantages over traditional machine learning methods by eliminating manual feature extraction, enhancing recognition accuracy for complex activities, and enabling the exploitation of unlabeled data through generative models. This paper provides a comprehensive review of recent advancements and emerging trends in deep learning models developed for sensor-based human activity recognition (HAR) systems. We begin with an overview of fundamental HAR… More > Graphic Abstract

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

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 >

Nadhmi A. Gazem¹, Sultan Noman Qasem^2,3, Umair Naeem⁴, Shahid Latif⁵, Ibtehal Nafea⁶, Faisal Saeed⁷, Mujeeb Ur Rehman^8,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 407-427, 2025, DOI:10.32604/cmes.2025.066517 - 31 July 2025

Abstract Falls are a leading cause of injury and morbidity among older adults, especially those with Alzheimer’s disease (AD), who face increased risks due to cognitive decline, gait instability, and impaired spatial awareness. While wearable sensor-based fall detection systems offer promising solutions, their effectiveness is often hindered by domain shifts resulting from variations in sensor placement, sampling frequencies, and discrepancies in dataset distributions. To address these challenges, this paper proposes a novel unsupervised domain adaptation (UDA) framework specifically designed for cross-dataset fall detection in Alzheimer’s disease (AD) patients, utilizing advanced transfer learning to enhance generalizability. The… More >

Asaad Algarni¹, Iqra Aijaz Abro², Mohammed Alshehri³, Yahya AlQahtani⁴, Abdulmonem Alshahrani⁴, Hui Liu^5,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5879-5896, 2025, DOI:10.32604/cmc.2025.064601 - 30 July 2025

Abstract Inertial Sensor-based Daily Activity Recognition (IS-DAR) requires adaptable, data-efficient methods for effective multi-sensor use. This study presents an advanced detection system using body-worn sensors to accurately recognize activities. A structured pipeline enhances IS-DAR by applying signal preprocessing, feature extraction and optimization, followed by classification. Before segmentation, a Chebyshev filter removes noise, and Blackman windowing improves signal representation. Discriminative features—Gaussian Mixture Model (GMM) with Mel-Frequency Cepstral Coefficients (MFCC), spectral entropy, quaternion-based features, and Gammatone Cepstral Coefficients (GCC)—are fused to expand the feature space. Unlike existing approaches, the proposed IS-DAR system uniquely integrates diverse handcrafted features using… More >

Kunlin Wu, Jingcheng Xiao, Junwei Li, Yifan Wang^*

Journal of Polymer Materials, Vol.42, No.2, pp. 277-305, 2025, DOI:10.32604/jpm.2025.065269 - 14 July 2025

Abstract The integration of 3D-printed hydrogels in soft robotics enables the creation of flexible, adaptable, and biocompatible systems. Hydrogels, with their high-water content and responsiveness to stimuli, are suitable for actuators, sensors, and robotic systems that require safe interaction and precise manipulation. Unlike traditional techniques, 3D printing offers enhanced capabilities in tailoring structural complexity, resolution, and integrated functionality, enabling the direct fabrication of hydrogel systems with programmed mechanical and functional properties. In this perspective, we explore the evolving role of 3D-printed hydrogels in soft robotics, covering their material composition, fabrication techniques, and diverse applications. We highlight More >