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  1. 17181

    Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation by S. Rashmi, S. Srinath, R. Rakshitha, B. V. Poornima

    Published 2024-11-01
    “…The methodology is strategically designed to address the complexities and variations in cephalometric images through a dual learning process: building base learners using end-to-end regression approaches and then constructing a meta-learner that ensembles the output of the base models to obtain collective predictions. Two primary approaches are followed to design base learners: an end-to-end single model and a multi-model strategy for localizing landmarks. …”
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  2. 17182

    The use of ridge regression for estimating the severity of acute pancreatitis by D. V. Cherdantsev, A. V. Stroev, E. S. Mangalova, N. V. Kononova, O. V. Chubarova

    Published 2019-10-01
    “…Ridge regression was used in combination with an algorithm for sequential reduction of attribute space.Results. …”
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  3. 17183

    Multi-fidelity modelling of a high bypass ratio turbofan engine with variable area nozzle by Andrea Magrini, Ernesto Benini

    Published 2025-06-01
    “…Low-speed mission points are confirmed to be those that benefit the most from an enlarged fan nozzle area, with a possible improvement of 3% in terms of thrust and specific fuel consumption at take-off and approach using a 10% larger area, similarly predicted by both 2D and 3D models. A preliminary acoustic evaluation based on semi-empirical noise models indicates a modest effect on noise emissions, with up to 1 dB reduction in microphone signature at the sideline for a nozzle area increased by 10%.…”
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  4. 17184

    A Case Study on Integrating an AI System into the Fuel Blending Process in a Chemical Refinery by Abdul Gani Abdul Jameel

    Published 2025-01-01
    “…AI-based blending systems are more flexible and will enable the refineries to meet the product specifications regularly and result in cost reduction owing to the fall in quality giveaways. The AI-powered process discussed can predict, with much better accuracy, critical combustion properties of gasoline such as the Research Octane Number (RON), Motor Octane Number (MON), and Antiknock Index (AKI), compared to the classical LP models, with the added advantage of optimization of the blend ratio in real time. …”
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  5. 17185

    Multi-objective optimization of residential energy-saving design based on fuzzy multi-criteria decision-making behavior model by Suzhen Pei, Gaoxiang Chen, Jian Yao, Yichen Dang

    Published 2025-10-01
    “…Traditional building energy simulation models often neglect the stochastic nature of occupant behavior and multi-device interaction, leading to discrepancies between predicted and actual energy consumption. This study introduces a multi-objective optimization framework based on a Fuzzy Multi-Criteria Decision-Making (FMCDM) behavioral model. …”
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  6. 17186

    An Elderly-Oriented Form Design of Low-Speed New Energy Vehicles Based on Rough Set Theory and Support Vector Regression by Zimo Chen

    Published 2024-08-01
    “…Second, the cars’ appearances are deconstructed by morphological analysis, and the key design features affecting elderly-oriented satisfaction are identified by a rough set attribute reduction algorithm. Finally, support vector regression is used to establish a mapping model of elderly-oriented Kansei factors and the key design features to predict the elderly-oriented form design of optimal low-speed NEVs. …”
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  7. 17187

    A deep operator network for Bayesian parameter identification of self-oscillators by Tobias Sugandi, Bayu Dharmaputra, Nicolas Noiray

    Published 2024-01-01
    “…The proposed approach can directly predict the finite-time KM coefficients, eliminating the intermediate computation of the solution field of the adjoint Fokker–Planck equation. …”
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  8. 17188

    Optimizing chemotherapeutic targets in non-small cell lung cancer with transfer learning for precision medicine. by Varun Malik, Ruchi Mittal, Deepali Gupta, Sapna Juneja, Khalid Mohiuddin, Swati Kumari

    Published 2025-01-01
    “…This makes it possible to extract deep features that address the issue of false alarms. For dimensionality reduction, the modified Rime optimization (MRO) algorithm is used to select the best features among multiples. …”
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  10. 17190

    Few-shot crop disease recognition using sequence- weighted ensemble model-agnostic meta-learning by Junlong Li, Quan Feng, Junqi Yang, Jianhua Zhang, Jianhua Zhang, Sen Yang

    Published 2025-08-01
    “…The SWE-MAML framework employs meta-learning to sequentially train a set of base learners, followed by a weighted sum of their predictions for classifying plant disease images. This method integrates ensemble learning with Model-Agnostic Meta-Learning (MAML), allowing the effective training of multiple classifiers within the MAML framework. …”
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  13. 17193

    Effect of Achieving Sustained SDAI Remission on Erosion Healing in Early Rheumatoid Arthritis - A One-year Prospective HR-pQCT Study by Qihan Wu, Ho So, Tsz-Ho Cheng, Yingzhao Jin, Sze-Lok Lau, Lai-shan Tam

    Published 2024-01-01
    “…After 12 months, a significant reduction in erosion volume and marginal osteosclerosis was observed in both groups. …”
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  14. 17194

    The Influence of Process and Slag Parameters on the Liquid Slag Layer in Continuous Casting Mold for Large Billets by Zhijun Ding, Chao Wang, Xin Wang, Pengcheng Xiao, Liguang Zhu, Shuhuan Wang

    Published 2025-04-01
    “…Increasing argon flow rate from 0.50 L·min<sup>−1</sup> to 1.00 L·min<sup>−1</sup> leads to 350 mm deeper bubble penetration, 10 mm reduction in jet penetration depth, 0.002 m·s<sup>−1</sup> increase in meniscus velocity, and decreased meniscus temperature due to bubble cooling. …”
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  15. 17195

    Applying the Block-Based Programming Language ALICE for Developing Programming Competencies in University Students by Mariuxi Vinueza-Morales, Jesennia Cardenas-Cobo, Jessica Cabezas-Quinto, Cristian Vidal-Silva

    Published 2025-01-01
    “…The information society is part of modern life, and algorithmic thinking and programming are relevant to everybody, regardless of educational background. …”
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    Neuropsychological Principles of Rehabilitation Training in the Therapy of Patients with Facial Nerve Palsy by L. B. Zavaliy, G. R. Ramazanov, M. V. Kalantarova, A. A. Rakhmanina, A. B. Kholmogorova, S. S. Petrikov

    Published 2022-10-01
    “…Specialists of the Research Institute developed a six-step rehabilitation education program for patients with FNP, aimed at lifestyle correction, prevention of complications, and also directly at teaching methods of daily physical impact (rehabilitation) at home. …”
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