Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
How Carleton is using simulation and visualization to improve training, design and human performance
At Carleton University, researchers are addressing a growing demand for advanced systems that enable learners to practice ...
Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...
Abstract: Access to safe and potable water is critical for public health and socioeconomic development. Traditional methods for predicting water quality often lack accuracy and robustness due to ...
In an era where artificial intelligence drives critical business decisions, Nikhil Dodda emphasizes that maintaining machine learning model performance is as crucial as building them. Model deployment ...
Nanotechnology and machine learning are transforming energy systems by enhancing engine efficiency and sustainability. The integration of advanced nanomaterials, such as gold nanoparticles (AuNPs), ...
Objective: To develop an automated machine learning (AutoML)-based prognostic prediction model and visualization system for autologous costal cartilage rhinoplasty (ACCR), addressing the clinical ...
We begin this tutorial to demonstrate how to harness TPOT to automate and optimize machine learning pipelines practically. By working directly in Google Colab, we ensure the setup is lightweight, ...
ABSTRACT: Facing increased energy demand which surpasses national grid supply capacity due to rapid population growth, urbanization, and economic activities, developing countries such as Cameroon are ...
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