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  1. 1481

    Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

    Published 2025-07-01
    “…ObjectiveThe movement of sediment particles significantly affects riverbed evolution, establishing it as a central concern and ongoing challenge in fluvial dynamics research. Although image processing methods provide efficient means for acquiring and analyzing data on sediment transport characteristics, their accuracy is often compromised by water waves, bubbles, and threshold errors. …”
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  2. 1482

    The Use of Technology in Evaluation Practice by Vanessa Jamieson, Tarek Azzam

    Published 2012-06-01
    “…Intervention: This was an exploratory research on evaluation study with no intervention. …”
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  3. 1483

    Some hypotheses regarding the mobile telecommunications services marketing and consumers rights from Romania by Nicu Marcu, Georgeta-Mădălina Meghişan

    Published 2013-06-01
    “…The current research analysis consumers’ rights concerning personal data processing and confidentiality protection within the public communications sector as they are stated in the 2002/58/CE Directive of the European Parliament and Council from 12th of July 2002. …”
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    Research of the Method of Chamfering Tooth Crest for Spiral Bevel Gear Using Spherical Cutter by Wei Wei, Zhang Lianhong

    Published 2017-01-01
    “…A quantitative measuring method for shape error is proposed in order to satisfy shape accuracy requirement of tooth crest. …”
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    Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

    Published 2025-05-01
    “…By comparing the prediction accuracy of the seven models, the results show that the Grid Search Method optimized SVR model performs the best in the light of prediction accuracy, with a Mean Absolute Percentage Error (MAPE) of 2.96%, a Mean Absolute Error (MAE) of 0.028 mm, a Root Mean Square Error (RMSE) of 0.032 mm, and a coefficient of determination (R2) of 0.995. …”
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