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Mirko Dinulovic, Aleksandar Benign and Bo?ko Ra?uo
In the present work, the potential application of machine learning techniques in the flutter prediction of composite materials missile fins is investigated. The flutter velocity data set required for different fin aerodynamic geometries and materials is ...
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Sofía Ramos-Pulido, Neil Hernández-Gress and Gabriela Torres-Delgado
Current research on the career satisfaction of graduates limits educational institutions in devising methods to attain high career satisfaction. Thus, this study aims to use data science models to understand and predict career satisfaction based on infor...
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Ishanka Prabhath Wimalaweera, Yuansong Wei, Tharindu Ritigala, Yawei Wang, Hui Zhong, Rohan Weerasooriya, Shameen Jinadasa and Sujithra Weragoda
The efficiency of magnetic seed coagulation (MSC) with pH adjustment by NaOH and Ca(OH)2 as a pretreatment for high-strength natural rubber industrial wastewater (NRIWW) was compared in this study. The high content of suspended solids (SSs) and other inh...
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Intisar Omar, Muhammad Khan and Andrew Starr
Crack propagation in materials is a complex phenomenon that is influenced by various factors, including dynamic load and temperature. In this study, we investigated the performance of different machine learning models for predicting crack propagation in ...
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Iris Viana dos Santos Santana, Álvaro Sobrinho, Leandro Dias da Silva and Angelo Perkusich
This study compares the performance of machine learning models for selecting COVID-19 and influenza tests during coexisting outbreaks in Brazil, avoiding the waste of resources in healthcare units. We used COVID-19 and influenza datasets from Brazil to t...
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