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Sarra Bel Haj Salem, Aissam Gaagai, Imed Ben Slimene, Amor Ben Moussa, Kamel Zouari, Krishna Kumar Yadav, Mohamed Hamdy Eid, Mostafa R. Abukhadra, Ahmed M. El-Sherbeeny, Mohamed Gad, Mohamed Farouk, Osama Elsherbiny, Salah Elsayed, Stefano Bellucci and Hekmat Ibrahim
In the Zeroud basin, a diverse array of methodologies were employed to assess, simulate, and predict the quality of groundwater intended for irrigation. These methodologies included the irrigation water quality indices (IWQIs); intricate statistical anal...
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Ali Mirzazade, Cosmin Popescu and Björn Täljsten
The aim of this study was to find strains in embedded reinforcement by monitoring surface deformations. Compared with analytical methods, application of the machine learning regression technique imparts a noteworthy reduction in modeling complexity cause...
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Mohan Kumar Gajendran, Ijaz Fazil Syed Ahmed Kabir, Sudhakar Vadivelu and E. Y. K. Ng
As wind energy continues to be a crucial part of sustainable power generation, the need for precise and efficient modeling of wind turbines, especially under yawed conditions, becomes increasingly significant. Addressing this, the current study introduce...
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Annwesha Banerjee Majumder, Somsubhra Gupta, Dharmpal Singh, Biswaranjan Acharya, Vassilis C. Gerogiannis, Andreas Kanavos and Panagiotis Pintelas
Heart disease is a leading global cause of mortality, demanding early detection for effective and timely medical intervention. In this study, we propose a machine learning-based model for early heart disease prediction. This model is trained on a dataset...
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Alejandro Jiménez Rios
In this paper, the results obtained from a series of parametric analyses, where the influence that geometric and mechanical parameters have in the structural response of existing vernacular cob walls within an Irish context, are presented. A design of ex...
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