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    A novel intelligent fault diagnosis method for gearbox based on multi-dimensional attention denoising convolution by Wei Liu, Zeqiao Zhang, Zhiwei Ye, Qiyi He

    Published 2024-10-01
    “…Consequently, the effective suppression of extraneous noise and accurate extraction of multi-scale fault features are crucial issues. To address these challenges, this study proposes a novel deep neural network framework, termed the Multidimensional Fusion Residual Attention Network (MFRANet), for gearbox fault diagnosis. …”
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    Device Functionalities and Technology Acceptance for Innovations in Neonatal Ventilation and Enhanced, Immediate Newborn Care: International, Multicenter, Web-Based Survey Study by Anna-Sophie Käferböck, Meggy Hayotte, Daniel Sieber, Martin Pillei, Martin Wald

    Published 2025-05-01
    “… Abstract BackgroundA substantial number of newborns face postdelivery respiratory issues annually. Current ventilation devices in immediate newborn care lack integrated sensors and supporting mechanisms for medical professionals. …”
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    Predicting Social Media Popularity With Large Language Models: Transforming Metadata Into Semantic-Enriched and Contextualized Text by Tianjian Chen, Jiang Huang, Xuetong Wu, Changcheng Shao

    Published 2024-01-01
    “…Disregarding this relationship leads to issues such as loss of context, incomplete feature representation, difficulty in feature engineering, and lack of domain knowledge integration. …”
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    An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration by Junwei Zhang, Liangqing Lyu

    Published 2025-04-01
    “…This study also designs an example application of the algorithm to a space engineering mission based on a collaborative sky and earth control system to demonstrate the usability of the algorithm. …”
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    Stakeholder Relationships in the Framework of R&D-based Startups: Evidence from Turkey by Elif Kalayci

    Published 2017-09-01
    “…The task becomes more difficult for recent engineering school graduates who are neither scientists nor business people. …”
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