This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within open-pit mining. Since hauling accounts for up to 60% of total operational costs, ...

Franz Inc. expands graph, vector, and Neuro-Symbolic capabilities for enterprise-scale AI systems LAFAYETTE, CA, UNITED ...

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...

Read more about AI and machine learning drive digital transformation across global mining operations on Devdiscourse ...

Incorporating marble dust and polypropylene fibers in concrete boosts strength and durability, highlighting the role of machine learning in mix optimization.

Abstract: Existing machine learning-based methods for series arc fault (SAF) identification still suffer from slow training speed when dealing with large-scale SAF datasets. For this reason, we ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Abstract: To address the challenges in network anomaly detection, such as data label imbalance and the poor performance of traditional Support Vector Machines (SVM) in fitting high-dimensional, ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The aim of this study was to analyze the proteomic differences in bone marrow aspirate ...

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...

A project is trying to cut the cost of making machine learning applications for Nvidia hardware, by developing on an Apple Silicon Mac and exporting it to CUDA. Machine learning is costly to enter, in ...