Yonggang Tong^1,*, Kai Yang¹, Pengfei Li¹, Yongle Hu¹, Xiubing Liang^2,*, Jian Liu³, Yejun Li⁴, Jingzhong Fang¹

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-15, 2026, DOI:10.32604/cmc.2025.071890 - 10 November 2025

Abstract (NbZrHfTi)C high-entropy ceramics, as an emerging class of ultra-high-temperature materials, have garnered significant interest due to their unique multi-principal-element crystal structure and exceptional high-temperature properties. This study systematically investigates the mechanical properties of (NbZrHfTi)C high-entropy ceramics by employing first-principles density functional theory, combined with the Debye-Grüneisen model, to explore the variations in their thermophysical properties with temperature (0–2000 K) and pressure (0–30 GPa). Thermodynamically, the calculated mixing enthalpy and Gibbs free energy confirm the feasibility of forming a stable single-phase solid solution in (NbZrHfTi)C. The calculated results of the elastic stiffness constant indicate that the… More >

Junxiang Li^1,2, Zhipeng Dong², Ben Han³, Jianqiao Chen³, Xinxin Zhang^1,2,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-19, 2026, DOI:10.32604/cmc.2025.070816 - 10 November 2025

Abstract Owing to their global search capabilities and gradient-free operation, metaheuristic algorithms are widely applied to a wide range of optimization problems. However, their computational demands become prohibitive when tackling high-dimensional optimization challenges. To effectively address these challenges, this study introduces cooperative metaheuristics integrating dynamic dimension reduction (DR). Building upon particle swarm optimization (PSO) and differential evolution (DE), the proposed cooperative methods C-PSO and C-DE are developed. In the proposed methods, the modified principal components analysis (PCA) is utilized to reduce the dimension of design variables, thereby decreasing computational costs. The dynamic DR strategy implements periodic… More >

Zitong Zhao¹, Zixuan Zhang², Zhenxing Niu^3,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.069752 - 10 November 2025

Abstract Reliable traffic flow prediction is crucial for mitigating urban congestion. This paper proposes Attention-based spatiotemporal Interactive Dynamic Graph Convolutional Network (AIDGCN), a novel architecture integrating Interactive Dynamic Graph Convolution Network (IDGCN) with Temporal Multi-Head Trend-Aware Attention. Its core innovation lies in IDGCN, which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs, and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data. For 15- and 60-min forecasting on METR-LA, AIDGCN achieves MAEs of 0.75% and 0.39%, and RMSEs More >

Qin Hu, Hongshan Kong^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-31, 2026, DOI:10.32604/cmc.2025.069078 - 10 November 2025

Abstract To address the issues of frequent identity switches (IDs) and degraded identification accuracy in multi object tracking (MOT) under complex occlusion scenarios, this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling. By constructing a joint tracking model centered on “intra-class independent tracking + cross-category dynamic binding”, designing a multi-modal matching metric with spatio-temporal and appearance constraints, and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy, this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion, cross-camera tracking, and crowded environments. Experiments… More >

Qing Guo^1,2, Juwei Zhang^1,2,3,*, Bingyi Ren^1,2

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.069053 - 10 November 2025

Abstract Traffic sign detection is an important part of autonomous driving, and its recognition accuracy and speed are directly related to road traffic safety. Although convolutional neural networks (CNNs) have made certain breakthroughs in this field, in the face of complex scenes, such as image blur and target occlusion, the traffic sign detection continues to exhibit limited accuracy, accompanied by false positives and missed detections. To address the above problems, a traffic sign detection algorithm, You Only Look Once-based Skip Dynamic Way (YOLO-SDW) based on You Only Look Once version 8 small (YOLOv8s), is proposed. Firstly,… More >

Jizhao Liu, Yuanyuan Shao^*, Shuqin Zhang, Fangfang Shan, Jun Li

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.068998 - 10 November 2025

Abstract Lateral movement represents the most covert and critical phase of Advanced Persistent Threats (APTs), and its detection still faces two primary challenges: sample scarcity and “cold start” of new entities. To address these challenges, we propose an Uncertainty-Driven Graph Embedding-Enhanced Lateral Movement Detection framework (UGEA-LMD). First, the framework employs event-level incremental encoding on a continuous-time graph to capture fine-grained behavioral evolution, enabling newly appearing nodes to retain temporal contextual awareness even in the absence of historical interactions and thereby fundamentally mitigating the cold-start problem. Second, in the embedding space, we model the dependency structure among… More >

Chen-Xi Hu¹, Wu-Gui Jiang^1,*, Jin Wang¹, Tian-Yu He²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-21, 2026, DOI:10.32604/cmc.2025.068655 - 10 November 2025

Abstract THE mechanical response and deformation mechanisms of pure nickel under nanoindentation were systematically investigated using molecular dynamics (MD) simulations, with a particular focus on the novel interplay between crystallographic orientation, grain boundary (GB) proximity, and pore characteristics (size/location). This study compares single-crystal nickel models along [100], [110], and [111] orientations with equiaxed polycrystalline models containing 0, 1, and 2.5 nm pores in surface and subsurface configurations. Our results reveal that crystallographic anisotropy manifests as a 24.4% higher elastic modulus and 22.2% greater hardness in [111]-oriented single crystals compared to [100]. Pore-GB synergistic effects are found More >

Amina Mahreen¹, Fateh Mebarek-Oudina^2,3,4,*, Amna Ashfaq¹, Jawad Raza¹, Sami Ullah Khan⁵, Hanumesh Vaidya⁶

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2829-2853, 2025, DOI:10.32604/fdmp.2025.072492 - 01 December 2025

Abstract Understanding the complex interaction between heat and mass transfer in non-Newtonian microflows is essential for the development and optimization of efficient microfluidic and thermal management systems. This study investigates the magnetohydrodynamic (MHD) thermosolutal convection of a Casson fluid within an inclined, porous microchannel subjected to convective boundary conditions. The nonlinear, coupled equations governing momentum, energy, and species transport are solved numerically using the MATLAB bvp4c solver, ensuring high numerical accuracy and stability. To identify the dominant parameters influencing flow behavior and to optimize transport performance, a comprehensive hybrid optimization framework—combining a modified Taguchi design, Grey… More >

Yuxin Wang¹, Youjiang Wang², Jieping Wang², Chao Zhang^1,*, Fanguang Meng³, Linhua Zhang¹, Yongxing Song^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2761-2777, 2025, DOI:10.32604/fdmp.2025.072236 - 01 December 2025

Abstract High-pressure water jet technology has emerged as a highly effective method for removing industrial-scale deposits from pipelines, offering a clean, efficient, and environmentally sustainable alternative to conventional mechanical or chemical cleaning techniques. Among the many parameters influencing its performance, the geometry of the nozzle plays a decisive role in governing jet coherence, impact pressure distribution, and overall cleaning efficiency. In this study, a comprehensive numerical and experimental investigation is conducted to elucidate the influence of nozzle geometry on the behavior of high-pressure water jets. Using Computational Fluid Dynamics (CFD) simulations based on the Volume of… More >

Yan Wang^1,2,*, Fuqiang Zhang¹, Long An¹, Bo Wang¹, Xueya Yang¹, Jie Jin^3,4

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2651-2671, 2025, DOI:10.32604/fdmp.2025.070122 - 01 December 2025

Abstract A downburst is a strong downdraft generated by intense thunderstorm clouds, producing radially divergent and highly destructive winds near the ground. Its characteristic scales are expressed through random variations in jet height, velocity, and diameter during an event. In this study, a reduced-scale parked wind turbine is exposed to downburst wind fields to investigate the resulting extreme wind loads. The analysis emphasizes both the flow structure of downbursts and the variations of surface wind pressure on turbine blades under different jet parameters. Results show that increasing jet velocity markedly enhances the maximum horizontal wind speed,… More > Graphic Abstract