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  1. 2541

    A Hybrid Strategy for Forward Kinematics of the Stewart Platform Based on Dual Quaternion Neural Network and ARMA Time Series Prediction by Jie Tao, Huicheng Zhou, Wei Fan

    Published 2025-03-01
    “…The DQ-BPNN is partitioned into real and dual parts, composed of parameters such as driving-rod lengths, maximum and minimum lengths, to extract more features. …”
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  2. 2542
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    Comparative Analysis of Structural Differences in Progressive Collapsing Foot Deformities with and without Hallux Valgus by Chien-Shun Wang MD, Andrew Behrens BS, Grayson M. Talaski, Erik Jesus Huanuco Casas MD, Kepler A.M. Carvalho MD, Antoine Acker MD, Tommaso Forin Valvecchi MD, Karl M. Schweitzer MD, FAAOS, Mark E. Easley MD, Cesar de Cesar Netto MD, PhD

    Published 2024-12-01
    “…Talar-first metatarsal angle was the only traditional two-dimensional radiographic parameter that correlated with HV deformity. Based on our findings, PCFD patients displaying these features might need HV preventive measures. …”
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  5. 2545

    AI-Assisted Design of Drain-Extended FinFET With Stepped Field Plate for Multi-Purpose Applications by Xiaoyun Huang, Hongyu Tang, Chenggang Xu, Yuxuan Zhu, Yan Pan, Dawei Gao, Yitao Ma, Kai Xu

    Published 2025-01-01
    “…Fin Field-Effect-Transistor (FinFET) has become fundamental components in advanced integrated circuit, while the drain-extended FinFET (DE-FinFET) features a lightly doped drain extension region to improve the device’s breakdown voltage. …”
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  6. 2546

    Magnetic Resonance Imaging Brain Segmentation Using Bi-Directional Convolutional Long Short-Term Memory U-Net With Densely Connected Convolutions by Meshari D. Alanazi, Amna Maraoui, Imen Werda, Ahmed Ben Atitallah, Turki M. Alanazi, Mohammed Albekairi, Anis Sahbani, Amr Yousef

    Published 2025-01-01
    “…Our method enhances spatial feature learning employing dense connections, and catches complex temporal links across MRI slices. …”
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  9. 2549

    Multiscale simulations of amorphous and crystalline AgSnSe2 alloy for reconfigurable nanophotonic applications by Xueyang Shen, Siyu Zhang, Yihui Jiang, Tiankuo Huang, Suyang Sun, Wen Zhou, Jiangjing Wang, Riccardo Mazzarello, Wei Zhang

    Published 2025-03-01
    “…We study the structural features and optical properties of both crystalline and amorphous AgSnSe2 via density functional theory (DFT) calculations and DFT‐based ab initio molecular dynamic (AIMD) simulations. …”
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  10. 2550
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  12. 2552

    Artificial neural networks analysis of entropy generation in magnetic-micropolar nanofluid flow equipped with porous media and Darcy-Forchheimer law by Zahoor Iqbal, Md Fayz- Al- Asad, Huiying Xu, Xinzhong Zhu, Muhammad Sajjad Hossain, Ridha Selmi, M.M. Alqarni, Sharifah E. Alhazmi, Fahima Hajjej, M.M.H. Imran

    Published 2025-05-01
    “…Moreover, the coefficient of skin friction, Nusselt number and Sherwood number for different parameters are computed and depicted in the form of graphs also compared with the numerical solution and obtained absolute error for friction, Nusselt and Sherwood number are 1.6636e−04,3.1979e−03,1.2645e−04.…”
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  13. 2553

    A Lightweight YOLOv8s Algorithm for Ceiling Fan Blade Defect Detection With Optimized Pruning and Knowledge Distillation by Qinyuan Huang, Chen Fan, Yuqi Sun, Jiaxiong Huang, Wengziyang Jiang

    Published 2025-01-01
    “…Detecting these surface defects is crucial; however, accurate and rapid detection typically involves complex machine vision algorithms, such as You Only Look Once (YOLO) networks, that require considerable computing resources, which contradicts the industry’s preference for simpler algorithms that can be deployed using low-cost computing power. …”
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  14. 2554

    Accuracy evaluation of dental CBCT and scanned model registration method based on pulp horn mapping surface: an in vitro proof-of-concept by Dianhao Wu, Jingang Jiang, Jinke Wang, Shan Zhou, Kun Qian

    Published 2024-07-01
    “…Abstract Background and aim 3D fusion model of cone-beam computed tomography (CBCT) and oral scanned data can be used for the accurate design of root canal access and guide plates in root canal therapy (RCT). …”
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  15. 2555

    Multimodal deep learning for enhanced temperature prediction with uncertainty quantification in directed energy deposition (DED) process by Adrian Matias Chung Baek, Taehwan Kim, Minkyu Seong, Seungjae Lee, Hogyeong Kang, Eunju Park, Im Doo Jung, Namhun Kim

    Published 2025-12-01
    “…The proposed methodology implements multimodal data fusion, combining reproduced grayscale images of deposition strategy with numerical process variables, including process parameters, geometrical features, and printing process status. …”
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  16. 2556
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    Machine learning-assisted image analysis techniques for glaucoma detection by Vaibhav Yadav, Barnali Dey, Udayan Baruah, Saumya Das, Om Prakash

    Published 2025-05-01
    “…The comprehensive discussion offered in this review may assist researchers to choose the suitable dataset, extract anatomical features, decide on methods, and select performance evaluation metrics for glaucoma detection.…”
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  18. 2558
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    Efficient one-stage detection of shrimp larvae in complex aquaculture scenarios by Guoxu Zhang, Tianyi Liao, Yingyi Chen, Ping Zhong, Zhencai Shen, Daoliang Li

    Published 2025-06-01
    “…Firstly, different from the ordinary detection methods, it exploits an efficient FasterNet backbone, constructed with partial convolution, to extract effective multi-scale shrimp larvae features. Meanwhile, we construct an adaptively bi-directional fusion neck to integrate high-level semantic information and low-level detail information of shrimp larvae in a matter that sufficiently merges features and further mitigates noise interference. …”
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  20. 2560

    Lightweight coal miners and manned vehicles detection model based on deep learning and model compression techniques: A case study of coal mines in Guizhou region by Beijing XIE, Heng LI, Zheng LUAN, Zhen LEI, Xiaoxu LI, Zhuo LI

    Published 2025-02-01
    “…Results on a self-built coal mine pedestrian-vehicle detection dataset show that the proposed model has parameters, computational load, and model size of 2.3 M, 4.0 GFLOPs, and 6.0 MB, respectively, achieving compression ratios of 4.9 times, 4.7 times, and 4.4 times compared to the baseline model. …”
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