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George Papageorgiou, Vangelis Sarlis and Christos Tjortjis
This study utilized advanced data mining and machine learning to examine player injuries in the National Basketball Association (NBA) from 2000?01 to 2022?23. By analyzing a dataset of 2296 players, including sociodemographics, injury records, and financ...
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Zhi Dou, Xin Huang, Weifeng Wan, Feng Zeng and Chaoqi Wang
Hydraulic conductivity generally decreases with depth in the Earth?s crust. The hydraulic conductivity?depth relationship has been assessed through mathematical models, enabling predictions of hydraulic conductivity in depths beyond the reach of direct m...
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Xiaotian Luo, Cong Yin, Yueqiang Sun, Weihua Bai, Wei Li and Hongqing Song
Deep soil moisture data have wide applications in fields such as engineering construction and agricultural production. Therefore, achieving the real-time monitoring of deep soil moisture is of significant importance. Current soil monitoring methods face ...
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Danial Khojasteh, Tej Vibhani, Hassan Shafiei, William Glamore and Stefan Felder
Estuaries worldwide are experiencing increasing threats from climate change, particularly from the compounding effects of sea level rise (SLR) and varying magnitude of river inflows. Understanding the tidal response of estuaries to these effects can guid...
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Aristeidis Karras, Christos Karras, Nikolaos Schizas, Markos Avlonitis and Spyros Sioutas
The field of automated machine learning (AutoML) has gained significant attention in recent years due to its ability to automate the process of building and optimizing machine learning models. However, the increasing amount of big data being generated ha...
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