Abstract: Optimizing experimental parameters in complex, high-dimensional systems pose significant challenges due to nonlinear interactions and resource constraints. This study presents a ...

Cerebral palsy (CP) represents the most prevalent motor disability in childhood, with spastic cerebral palsy (SCP) constituting the predominant subtype. However, systematic characterization of ...

You're probably a little tired of reading or hearing about AI, right? Well, if that's the case, then you're in the right place because here, we're going to talk about machine learning (ML). Yes, it's ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Advanced machine learning (ML) models are essential for power system forecasting, yet their performance critically depends on architecture structure and parameter definition. Manual parameter tuning ...

Operational data such as torque, vibration, and temperature are vital for refining machine design and predicting failure modes. Feedback from real-world machines reduces over-engineering, cuts costs, ...

Osaka Metropolitan University researchers introduced a technique to enhance the reliability of gravitational wave parameter estimation results produced by machine learning. The team developed two ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.