This project focuses on building and evaluating machine learning (ML) classification models to predict whether a person has diabetes based on medical and demographic features. It was developed as an ...
Self-mixing interferometry (SMI) is an emerging optical sensing technique for detecting and classifying microparticles in non-contact and label-free flowmetry applications. High precision and ...
Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...
Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...
Abstract: Weather conditions directly affect sectors such as agriculture and transport. With climate change, unpredictability is increasing and traditional calculation methods may not be sufficient.
ABSTRACT: Background and Theoretical Dilemma: The United States of America (USA) is the world’s largest consumer of crude oil in the world. Ensuring the sustainability of the role of crude oil in the ...
Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...
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