Duo Li¹, Shuhao Kang¹, Yukun Liu², Yang Shen², Ruihan Li³, Yuhu Liu¹, Shujun Huang⁴, Xin Wu⁵, Huan Liu^2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078734 - 08 May 2026

Abstract Tungsten plays a critical role in semiconductor electrical interconnects, and a thorough understanding of its mechanical properties is essential for optimizing its processing and performance. However, few studies have explored the effect of grain refinement on the mechanical behavior of tungsten. The work indicates a phenomenological transition around ~7.3 nm within the tested grain-size range that governs the nanoindentation response of tungsten. To establish this, we performed molecular dynamics (MD) simulations of nanoindentation for different grain sizes and analyzed surface pile-up, elastic recovery, atomic displacement, loading force, hardness, stress/strain behavior, dislocation density, and dislocation evolution. More >

Mengqi Liu, Haiqing Yao^*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078181 - 08 May 2026

Abstract For the wide-coverage application scenarios, wireless rechargeable sensor networks are normally divided into multiple clusters to support the diversity and flexibility for monitoring, and use the mobile charger (MC) to support the sustainable charging of the network. Many efforts focus on optimizing the cluster head selection and mobile charger scheduling to improve the network energy efficiency and reliability. However, the existing work tends to use fixed triggering mechanism for cluster head (CH) rotation, and may trigger the rotation either too early or too late. Besides, the existing charging triggering mechanisms cannot track the changes in… More >

Xian Wu, Liang Wan^*, Jingxia Ren, Bangfeng Zhang

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077928 - 08 May 2026

Abstract Traditional malware detection models rely on a single feature source for detection, resulting in high false positive or false negative rates due to incomplete information. In addition, conventional models depend on manual feature engineering, which is inefficient and hard to adapt to new malware variants. To address these challenges, this paper proposes a malware detection model called WAFDect based on a self-attention mechanism with multi-source feature fusion. The model consists of two key designs. First, we construct a multi-source feature extraction model that analyzes multi-source data such as API call sequences, registry operation logs, file… More >

Rabie Mezouar^1,2, Fouad Okba³, Dejan Zagorac^4,5,*, Salah Daoud², Abdelfateh Benmakhlouf ²

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077724 - 08 May 2026

Abstract The compression effects on the thermoelastic and thermodynamic properties of cubic zincblende silicon–tin alloy (SiSn) were explored using a multi-methodological approach, deploying data mining methods, theoretical equation-of-state parameters, and the Quasi-Harmonic Debye Model. We analyze the relative volume, isothermal bulk modulus, thermal expansion coefficient, Debye temperature, sound velocity, and microhardness of the SiSn compound under pressures up to 8 GPa. The study commences with the data mining-based searches for a structural model and continues with an analysis of the pressure dependence of the relative volume using the Vinet equation of state, followed by an investigation… More >

Lijuan Huang^1,2, Zhixian Liu³, Xinyu Zhou⁴, Jinping Liu^4,*, Kunyi Zheng⁴, Yimei Yang^2,4,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077655 - 08 May 2026

Abstract Many occluded and ambiguous ground truths exist in object detection, making detectors unable to obtain optimal training samples. In this article, we revisit the suboptimal sample issue in label assignment for object detection and propose a novel detector-agnostic strategy, termed FSS, to address it. FSS reformulates label assignment as the process of selecting high-quality sub-optimal samples and progressively transforming them into optimal ones. Specifically, for each candidate, we estimate the probability of being an optimal sample by jointly considering localization quality and classification confidence, thereby constructing an instance-wise probability matrix. Based on the spatial distribution More >

Akmalbek Abdusalomov¹, Mukhriddin Mukhiddinov^2,3, Kamola Abdurashidova², Alpamis Kutlimuratov⁴, Avazjon Marakhimov⁵, Kuanishbay Seytnazarov⁶, Young-Im Cho^1,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077057 - 08 May 2026

Abstract Human emotions are intricate and difficult to decipher through various modalities. Current methodologies frequently employ inflexible fusion strategies that do not consider the dynamic and context-sensitive characteristics of emotional expressions in both visual and textual mediums. This paper presents SYMPHONIA (Synchronizing Facial and Textual Modalities for Emotion Understanding), an innovative architecture engineered to capture and amalgamate emotional signals from facial expressions and language, attuned to contextual and modality interactions. There are two parts to SYMPHONIA: a Facial Emotion Branch that uses Vision Transformers and facial landmarks, and a Textual Emotion Branch that uses RoBERTa embeddings… More >

Wei-Chen Tang, Xin Chen, Fei Dong^*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.4, 2026, DOI:10.32604/fdmp.2026.079861 - 07 May 2026

Abstract Boiling heat transfer remains a cornerstone of efficient thermal management, with far-reaching implications for energy systems and industrial processes. Advances in this field not only deepen fundamental scientific understanding but also enable transformative improvements in energy efficiency, equipment performance, and operational safety. Contemporary research in this area focuses on accurate parameter prediction, intelligent image analysis, and quantitative characterization of bubble dynamics, collectively advancing both mechanistic insight and engineering optimization. In this context, artificial intelligence (AI), encompassing machine learning and deep learning techniques, has emerged as a powerful paradigm, offering significant advantages in predictive accuracy, data-driven… More >

Lyu Guanghua¹, Dingxiao Jiao², Abdulrahman AlKassem³, Dakan Ying¹, Rizwan Arshad¹, Jiahua Ni¹, Zhe Liu¹, Syed Hadi Hussain Shah^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.4, 2026, DOI:10.32604/fdmp.2026.077648 - 07 May 2026

Abstract Desert photovoltaic, PV, installations experience significant efficiency losses due to dust accumulation, which also promotes localized overheating, known as hotspots, caused by uneven solar irradiance and partial cell shading. These hotspots can accelerate material degradation and increase the risk of permanent panel damage. This study presents an autonomous maintenance strategy based on a cooperative swarm of unmanned aerial vehicles, UAVs, enabling contactless dust removal and active hotspot cooling. The approach combines high-fidelity computational fluid dynamics to characterize aerodynamic downwash for effective dust detachment with fluid–structure interaction analysis to verify the structural integrity of PV panels… More >

Abdou Alzubaidi¹, Khalid Mahmud², Rashid Mehmood^2,*, Siddra Rana³, Mohammed Alkinidri⁴

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.4, 2026, DOI:10.32604/fdmp.2026.075928 - 07 May 2026

Abstract Flows over rotating disks are central to numerous engineering applications, including turbines, rotating sensors, and advanced cooling devices, where the incoming fluid often strikes the disk at an angle. This study examines magnetohydrodynamic (MHD) oblique slip flow toward a rotating disk, accounting for critical effects such as velocity slip, thermal slip and thermal radiation. In particular, the Cattaneo–Christov heat flux model is used to capture thermal relaxation phenomena, frequently overlooked in prior analyses, while employing a uniform transverse magnetic field to regulate both momentum and heat transfer. Using similarity transformations, the governing nonlinear equations are… More >

Ratan Kumar Chanda¹, Rakesh Bhowmick², Giulio Lorenzini^3,*, Rabindra Nath Mondal^1,*

Frontiers in Heat and Mass Transfer, Vol.24, No.2, 2026, DOI:10.32604/fhmt.2025.075311 - 30 April 2026

Abstract Due to ample engineering and industrial applications involving electrically conducting fluids, such as in magnetic flow control devices, thermal magnetic systems, magnetic filtration and separation, and fluid transport in curved rotating channels, the present study examines the impacts of pressure-induced instability characteristics and chaotic nature of Magneto-hydrodynamic fluid flow in a rotating curved square duct (CSD), incorporating Hall and ion-slip currents. The rotational speed (Ω_T) around the vertical axis of the duct is constant while a variable transverse magnetic field is applied perpendicular to the fluid. The numerical solutions are obtained through the spectral method as a… More >