Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and ...

Machine learning holds promise for optimizing treatment strategies and potentially improving outcomes in respiratory failure ...

The accurate estimation of bearing stratum depth, the subsurface soil or rock layer depth that can support a foundation, is ...

Artificial Intelligence systems powered by deep learning are changing how we work, communicate, and make decisions. If we ...

Supervised learning is a machine learning approach in which algorithms are trained on labelled datasets—that is, data that already includes the correct outputs or classifications. The model learns to ...

Wild fire is a serious environmental and socioeconomic menace and therefore any effort aimed at the early and accurate detection of wild fire has to be very useful. This paper proposes a novel machine ...

Vehicle emissions are a leading source of greenhouse gases, yet conventional modeling tools assume symmetrical and proportional relationships between fuel use, engine size, and emissions. This ...

Background Cancer survivors have an increased risk of heart failure, but this is balanced by the risk of death from other ...

New research reveals AI tsunami warning systems can improve accuracy if trained on real-world data, and equipped with good ...

Blasting is considered an indispensable process in mining excavation operations. Generally, only a small percentage of the total energy of blasting is consumed in the fragmentation and displacement of ...

Electric vehicle (EV) technology is an emerging eco-friendly solution that has reshaped the transportation sector. This paper aims to design a controller for EV speed tracking using three ...

Artificial Intelligence (AI) and Machine Learning (ML) are popular terms in the tech industry, but many people mistakenly use them as if they mean the same thing. This confusion can lead to ...