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Abstract: With the increasing complexity of power systems, the need for system data visualization and fault condition recognition has become increasingly important. This study proposes a method for ...

It seems like everyone wants to get an AI tool developed and deployed for their organization quickly—like yesterday. Several customers I’m working with are rapidly designing, building and testing ...

LAS VEGAS, Sept. 22, 2025 /PRNewswire/ -- Hyperscale Data, Inc. (NYSE American: GPUS), a diversified holding company ("Hyperscale Data," or the "Company"), announces that it plans to issue a special ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Four teams of researchers have won a prize competition aimed at integrating eye care and ocular imaging data into studies using large healthcare data sets in biomedical research. The selected teams ...

Seoul National University Hospital and its affiliate hospitals have consolidated their common data model platforms. The consolidated, cloud-based platform enables collaboration among SNUH, Seoul ...

Managing context effectively is a critical challenge when working with large language models, especially in environments like Google Colab, where resource constraints and long documents can quickly ...

In the rapidly evolving landscape of modern manufacturing and engineering, a new technology is emerging as a crucial enabler-Data-Model Fusion (DMF). A recent review paper published in Engineering ...

The analysis of multi-environment trials (MET) data in plant breeding and agricultural research is inherently challenging, with conventional ANOVA-based methods exhibiting limitations as the ...