Objectives: This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold ...

Scientists have incorporated key computing components into a single, flexible fiber that you can run through your washing machine. The researchers hope to one day weave together many of these fibers ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

Abstract: This study provides a comprehensive analysis of the effectiveness of eight different machine learning algorithms for predicting water quality. The algorithms, which include Gaussian Naive ...

For his research in machine learning-based electron density prediction, Michigan Tech researcher Susanta Ghosh has been recognized with one of the National Science Foundation's highest honors. The NSF ...

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 ...

Existing datasets collected in 2018 (Weller et al., 2020b) and 2017 (Weller et al., 2020c) were used as the training and testing data, respectively, in the analyses reported here. Although the present ...

Abstract: This paper focus on exploring the possibilities for prediction of energy prices using various machine learning (ML) algorithms. Earlier, this problem has been tackled using various numerical ...