Welcome to this week’s Food Exec Brief, a roundup of the most important news shaping food and beverage manufacturing, from AI ...

As organizations increasingly rely on digital infrastructure to manage sensitive information, understanding how DSPM integrates with broader risk management and compliance strategies becomes essential ...

According to the authors, this evolution marks a clear transition from traditional rule-based security toward data-driven, ...

A multinational collaboration at Eitri medical innovation center in Bergen, Norway, has used machine learning models to identify patient groups at risk of being mistreated.

A multinational collaboration at Eitri medical innovation center in Bergen, Norway, has used machine learning models to identify patient groups at risk of being mistreated.

Data Encoding Stage: The MNIST dataset contains grayscale handwritten digit images. Each image is scaled and normalized, then mapped to eight qubits through Angle Encoding or Amplitude Encding. This ...

Together, the Gordian and Itron platforms can detect, analyze and classify millions of data events within milliseconds. For the utility, this unlocks even greater value from their smart infrastructure ...

CNN and random forest model to detect multiple faults in bifacial PV systems, including dust, shading, aging, and cracks. Using simulated I-V curves and a 180-day synthetic dataset, the model achieved ...

Miniaturized electronics and intricate objects require a certain finesse. Researchers have looked into the development of a ...

While nanopore technologies have revolutionized DNA and RNA analysis, their application to proteins has been limited due to ...

Abstract: This study addresses the classification of migraine headaches using advanced machine learning techniques, specifically ensemble models and boosting methods. We employed data augmentation to ...