Kaiwei Tang^1,2,*, Xiufeng Wang^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.010499

Abstract The prolonged health monitoring using wearable technology faces challenges stemming from perspiration, including bacterial proliferation, compromised adhesion, signal quality deterioration, and user discomfort. Notably, excessive sweat fosters bacterial colonization, escalating infection risks, and compromising biomarker analysis. Existing antibacterial approaches, unfortunately, risk disrupting the delicate balance of skin microbiota. To address this, we’ve developed a Janus patch featuring Zn-Al layered double hydroxide (LDH) modification, which boasts sustained antibacterial properties while preserving the epidermal microecology. It integrates a hydrophobic LDH fabric that mechanically eradicate bacteria via a nanoknife effect, and a laser-engraved medical adhesive with microholes for 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 >

Sandra Gajević¹, Slavica Miladinović¹, Jelena Jovanović¹, Onur Güler², Serdar Özkaya², Blaža Stojanović^1,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4341-4361, 2025, DOI:10.32604/cmc.2025.065645 - 30 July 2025

Abstract This paper presents an investigation of the tribological performance of AA2024–B₄C composites, with a specific focus on the influence of reinforcement and processing parameters. In this study three input parameters were varied: B₄C weight percentage, milling time, and normal load, to evaluate their effects on two output parameters: wear loss and the coefficient of friction. AA2024 alloy was used as the matrix alloy, while B₄C particles were used as reinforcement. Due to the high hardness and wear resistance of B₄C, the optimized composite shows strong potential for use in aerospace structural elements and automotive brake components. 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 >

Li Wang¹, Haipeng Mu¹, Jiming Zhu^2,*, Zhongchang Wang³

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.4, pp. 989-1005, 2025, DOI:10.32604/fdmp.2025.057931 - 06 May 2025

Abstract To elucidate the relationship between pipeline erosion and wear during slurry transportation, this study considers three key influencing parameters, namely, the ratio of inlet to outlet pipe diameter, the length of the variable diameter section, and the roughness of the pipe wall. The impact of these factors on pipeline erosion and wear is analyzed using a single-factor analysis approach. In particular, the Fluent software is employed to conduct the required numerical simulations for variable diameter elbows of varying morphologies. The results indicate that as the inlet to outlet diameter ratio increases, the wear on… More >

Vitor F. C. Sousa¹, Jorge Gil¹, Tiago E. F. Silva¹, Abílio M. P. de Jesus^1,2, Francisco J. G. Silva^1,3, João Manuel R. S. Tavares^1,2,*

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 177-199, 2025, DOI:10.32604/cmc.2025.062133 - 26 March 2025

Abstract The machining process remains relevant for manufacturing high-quality and high-precision parts, which can be found in industries such as aerospace and aeronautical, with many produced by turning, drilling, and milling processes. Monitoring and analyzing tool wear during these processes is crucial to assess the tool’s life and optimize the tool’s performance under study; as such, standards detail procedures to measure and assess tool wear for various tools. Measuring wear in machining tools can be time-consuming, as the process is usually manual, requiring human interaction and judgment. In the present work, an automated offline flank wear… More >

Hariharasakthisudhan Ponnarengan^1,*, Sivakumar Rajendran², Vikas Khalkar³, Gunapriya Devarajan⁴, Logesh Kamaraj⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 1-48, 2025, DOI:10.32604/cmes.2024.056605 - 17 December 2024

Abstract The purpose of this review is to explore the intersection of computational engineering and biomedical science, highlighting the transformative potential this convergence holds for innovation in healthcare and medical research. The review covers key topics such as computational modelling, bioinformatics, machine learning in medical diagnostics, and the integration of wearable technology for real-time health monitoring. Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems, while machine learning algorithms have improved the accuracy of disease prediction and diagnosis. The synergy between bioinformatics and computational techniques has led to breakthroughs in More >

F. L. Kong^a,b, L. Zhang^c, W. J. Zhao^d, D. S. Zheng^b, T. J. Sui^b, G. L. Zhu^a, C. A. Guo^a,*

Chalcogenide Letters, Vol.21, No.8, pp. 665-674, 2024, DOI:10.15251/CL.2024.218.665

Abstract A Ni/C-MoS₂ coating was electrospark deposited by using an electrode made of sinered Ni-C-MoS₂ composite on a CrNi3MoVA steel substrate, and its nano-mechanical properties and tribological properties were obtained by utilizing nano-indenter and friction-abrasion testing machine. The results showed that the phase constitution of the as-deposited Ni/C-MoS₂ coating mainly includes graphite, MoS₂, γ-Ni, MoO₂, NixS and MoC. Compared with the CrNi3MoVA steel and Ni/MoS2 coating, the Ni/C-MoS₂ coating exhibits better tribological properties due to the matrix strengthened by MoO₂ and MoC, and the synergistic lubrication effect of graphite and MoS₂ in the Ni/C-MoS₂ coating. More >

Muhammad Faiz Aizamddin^1,2,*, Nazreen Che Roslan², Ayu Natasha Ayub², Awis Sukarni Mohmad Sabere³, Zarif Mohamed Sofian⁴, Yee Hui Robin Chang⁵, Mohd Ifwat Mohd Ghazali^6,7, Kishor Kumar Sadasivuni⁸, Mohamad Arif Kasri⁹, Muhamad Saipul Fakir¹⁰, Mohd Muzamir Mahat^2,*

Journal of Polymer Materials, Vol.41, No.4, pp. 239-261, 2024, DOI:10.32604/jpm.2024.057420 - 16 December 2024

Abstract Poly-3,4-ethylenedioxythiophene: polystyrene sulfonate (PEDOT/PSS) has revolutionized the field of smart textiles as an advanced conductive polymer, offering an unprecedented combination of high electrical conductivity, solution processability, and mechanical conformability. Despite extensive research in PEDOT/PSS-coated fabrics over the past decade, a critical challenge remains in finding the delicate balance between enhanced conductivity and washing durability required for real-world wearable applications. Hence, this study investigates the electrical conductivity and durability properties of PEDOT/PSS-based conductive fabrics for wearable electronics. By carefully controlling the doping concentration of dimethyl sulfoxide (DMSO), an optimal conductivity of 8.44 ± 0.21 × 10⁻³ S… More >

Meixin Zhou¹, Jia Shin Lee², Kun Zhou^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011064

Abstract 3D printing of metamaterials has garnered significant attention in recent years, as metamaterials, especially the triple periodic minimal surface (TPMS) structures, are engineered to exhibit extraordinary properties. However, challenges such as limited structural designs and lack of real-world applications have restrained the development of 3D printed metamaterials. Herein, a series of TPMS structures were designed and printed via selective laser sintering, and their mechanical energy absorption capabilities under the quasi-static compression condition were compared. Novel TPMS structures were then designed by blending the investigated TPMS structures, and their compressive properties and deformation mechanism were explored. More >