This studentship will develop physics-informed Edge AI methods for predictive health management of batteries and power electronics in electrified vehicles under real-world driving conditions.
Their findings are detailed in the study “Efficient Energy Consumption: Leveraging AI Models for Appliance Detection,” published in the Journal of Low Power Electronics and Applications, where the ...
Abstract: Effective fault identification and diagnosis are critical in modern power systems to ensure operational reliability and reduce economic losses. This research describes a novel approach that ...
In response to escalating environmental challenges and the global energy crisis, Europe has established ambitious targets to reduce greenhouse gas emissions and increase the production of renewable ...
Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as the Framingham ...
In the race to develop artificial intelligence, tech giants are building data centers that guzzle up water. That has led to problems for people who live nearby. In the race to develop artificial ...
Abstract: Power transformers are critical components in ensuring the continuous and stable operation of power systems. Failures in these units can lead to significant power outages and costly downtime ...
The integration of artificial intelligence (AI) and machine learning (ML) in oncology clinical trials is rapidly evolving alongside the broader field. For example, AI-driven adaptive trial designs may ...
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