On the propeller wake evolution using large eddy simulations and physics-informed space-time decomposition by Zhan Zhang, Peng Sun, Long Pan, Teng Zhao

“…The findings indicate that the pi-SPDMD model enhances the efficiency of the sparse-promoting algorithm, producing modes that gravitate towards stability, and the resulting decomposition maintains commendable physical fidelity. …”
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The search for the holy grail in cavovarus foot by Lucas Furtado da Fonseca, Rodrigo Cortes Vicente, Leonardo Fernandez Maringolo

“…Conclusion: Successful reconstruction of the cavovarus foot depends on a dynamic, intraoperatively responsive algorithm that integrates functional muscle assessment, sequential releases, and appropriate structural correction. …”
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Validation Framework for Analyzing Complex Anatomical Structures: Application of L-System Models by Katarzyna Heryan, Jacek Tarasiuk, Janusz Skrzat

“…However, the complexity of renal vascular trees, particularly in corrosive endocasts, requires custom-designed algorithms to address unique challenges in reconstruction, segmentation, skeletonization, and graph-based representation. …”
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End-to-end deep learning pipeline for real-time Bragg peak segmentation: from training to large-scale deployment by Cong Wang, Valerio Mariani, Frédéric Poitevin, Matthew Avaylon, Jana Thayer

“…X-ray crystallography reconstruction, which transforms discrete X-ray diffraction patterns into three-dimensional molecular structures, relies critically on accurate Bragg peak finding for structure determination. …”
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Ultrasonic online monitoring method of internal defects inmetal additive manufacturing by Linzhao Jiang, Jun Zhang, Jingli Yan, Hui Ding

“…Defect characteristic signals were identified and integrated into a proposed signal classification and focusing imaging algorithm, facilitating defect signal extraction and reconstruction.  …”
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GAT-Enhanced YOLOv8_L with Dilated Encoder for Multi-Scale Space Object Detection by Haifeng Zhang, Han Ai, Donglin Xue, Zeyu He, Haoran Zhu, Delian Liu, Jianzhong Cao, Chao Mei

“…It mainly includes abandoning the original Feature Pyramid Network (FPN) structure, proposing an adaptive fusion strategy based on multi-level features of backbone network, enhancing the expression ability of multi-scale objects through upsampling and feature stacking, and reconstructing the FPN. The local features extracted by convolutional neural networks are mapped to graph-structured data, and the nodal attention mechanism of GAT is used to capture the global topological association of space objects, which makes up for the deficiency of the convolutional operation in weight allocation and realizes GAT integration. …”
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Removal mechanism and damage evolution of SiCp/Al composites based on FEM-MD model considering 3D random polyhedral particles in orthogonal cutting by Ming Li, Qingguang Li, Xianchao Pan, Jiaqi Wang, Zixuan Wang, Shengzhi Xu, Yunguang Zhou, Lianjie Ma, Tianbiao Yu

“…This study investigates the cutting mechanism and particle damage evolution of SiCp/Al composites using a coupled FEM-MD modeling approach. A Python-based algorithm was developed for generating representative volume element (RVE) through stochastic convex polyhedron modeling, enabling geometrically faithful reconstruction of particle morphologies. …”
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Automated Generation of Geometric FE Models for Timber Structures Using 3D Point Cloud Data by Lin Chen, Liufang Jiang, Haibei Xiong

“…The methodology first employs a region-growing algorithm for component segmentation. This is followed by the integration of geometric feature extraction techniques to robustly determine the position, orientation, boundaries, and dimensions of structural elements. …”
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Single-Shot Femtosecond Raster-Framing Imaging with High Spatio-Temporal Resolution Using Wavelength/Polarization Time Coding by Yang Yang, Yongle Zhu, Xuanke Zeng, Dong He, Li Gu, Zhijian Wang, Jingzhen Li

“…Finally, the target dynamics are recovered using a reconstruction algorithm based on the Nyquist–Shannon sampling theorem. …”
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Invertible Attention-Guided Adaptive Convolution and Dual-Domain Transformer for Pansharpening by Qun Song, Hangyuan Lu, Chang Xu, Rixian Liu, Weiguo Wan, Wei Tu

“…To address these challenges, we propose a novel detail injection algorithm and develop the invertible attention-guided adaptive convolution and dual-domain Transformer (IACDT) network. …”
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Efficacy of artificial intelligence-based FFR technology for coronary CTA stenosis detection in clinical management of coronary artery disease: a systematic review by Tong Liu, Ming Liu, Ailiyaerjiang Aisika, Palidanmu Wumaier, Abudukeyoumujiang Abulizi, Abudukeyoumujiang Abulizi, Jingru Wang, Mayidili Nijiati, Mayidili Nijiati

“…This review synthesizes recent developments in AI-based FFR technology for coronary stenosis detection via CCTA, focusing on AI-assisted quantitative coronary CTA (AI-QCT), deep learning algorithms, and their applications in three-dimensional coronary reconstruction and hemodynamic simulation. …”
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A multi-scale rotated ship targets detection network for remote sensing images in complex scenarios by Siyu Li, Fei Yan, Yunqing Liu, Yuzhuo Shen, Lan Liu, Ke Wang

“…Additionally, this paper proposes an Upsampling Feature Reconstruction Pyramid (ARFPN-C), based on Adaptive Rotated Convolution (ARC). …”
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Simulating fluvial sediment pulses using remote sensing and machine learning: Development of a modeling framework applicable to data rich and scarce regions by Abhinav Sharma, Celso Castro-Bolinaga, Natalie Nelson, Aaron Mittelstet

“…Overall, the inclusion of SDI in the model enhanced its efficiency and transferability. By enabling the reconstruction of fluvial sediment pulses in data-scarce regions following dam removals, this integrated approach contributes to advancing our understanding of how rivers respond quantitatively and predictively to these disturbances in sediment supply.…”
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Prediction for Coastal Wind Speed Based on Improved Variational Mode Decomposition and Recurrent Neural Network by Muyuan Du, Zhimeng Zhang, Chunning Ji

“…This study proposes a systematic framework, termed VMD-RUN-Seq2Seq-Attention, for noise reduction, outlier detection, and wind speed prediction by integrating Variational Mode Decomposition (VMD), the Runge–Kutta optimization algorithm (RUN), and a Sequence-to-Sequence model with an Attention mechanism (Seq2Seq-Attention). …”
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A non-sub-sampled shearlet transform-based deep learning sub band enhancement and fusion method for multi-modal images by Sudhakar Sengan, Praveen Gugulothu, Roobaea Alroobaea, Julian L. Webber, Abolfazl Mehbodniya, Amr Yousef

“…To address these limitations, this study proposes a novel fusion framework that integrates the Non-Subsampled Shearlet Transform (NSST) with a Convolutional Neural Network (CNN) for effective sub-band enhancement and image reconstruction. …”
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Ensemble deep learning-enabled single-shot composite structured illumination microscopy (eDL-cSIM) by Jiaming Qian, Chunyao Wang, Hongjun Wu, Qian Chen, Chao Zuo

“…Experimental results demonstrate that eDL-cSIM integrates the advantages of various state-of-the-art neural networks, enabling robust super-resolution image predictions across different specimen types or structures of interest, and outperforms classical physics-driven methods in terms of imaging speed, reconstruction quality and environmental robustness, while avoiding intricate and specialized algorithmic procedures. …”
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Hybrid Attention-Enhanced Xception and Dynamic Chaotic Whale Optimization for Brain Tumor Diagnosis by Aliyu Tetengi Ibrahim, Ibrahim Hayatu Hassan, Mohammed Abdullahi, Armand Florentin Donfack Kana, Amina Hassan Abubakar, Mohammed Tukur Mohammed, Lubna A. Gabralla, Mohamad Khoiru Rusydi, Haruna Chiroma

“…The methodology is built on a combination of preprocessing techniques, transfer learning architecture reconstruction, and dynamic fine-tuning strategies. To optimize key hyper-parameters, this study employed the Dynamic Chaotic Whale Optimization Algorithm. …”
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YOLO-SBA: A Multi-Scale and Complex Background Aware Framework for Remote Sensing Target Detection by Yifei Yuan, Yingmei Wei, Xiaoyan Zhou, Yanming Guo, Jiangming Chen, Tingshuai Jiang

“…On the DIOR dataset, YOLO-SBA improves mAP by 16.6% and single-category detection AP by 0.8–23.8% compared to the existing state-of-the-art algorithm.…”
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Industrial Computed Tomography Image Denoising Network Based on Channel Attention Mechanism by Yu HE, Chengxiang WANG, Wei YU

“…When the quality of projection data is poor, classical denoising and reconstruction algorithms are ineffective in removing the noise. …”
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A hybrid steganography framework using DCT and GAN for secure data communication in the big data era by Kaleem Razzaq Malik, Muhammad Sajid, Ahmad Almogren, Tauqeer Safdar Malik, Ali Haider Khan, Ayman Altameem, Ateeq Ur Rehman, Seada Hussen

“…This study introduces a novel and comprehensive steganography framework using the discrete cosine transform (DCT) and the deep learning algorithm, generative adversarial network. By leveraging deep learning techniques in both spatial and frequency domains, the proposed hybrid architecture offers a robust solution for applications requiring high levels of data integrity and security. …”
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