Additionally, the expansion of bioinformatic resources such as the Protein Circular Dichroism Data Bank (PCDDB) has provided researchers with well-curated spectral data and metadata, enabling ...

Circular economy initiatives often rely on data-intensive, AI-driven technologies to optimize waste sorting, material reuse, ...

In this letter, an algorithm for synthetic aperture radar imaging of electrically small targets embedded in multilayered cylindrical geometries (e.g., pipes) using nonuniform measurement points is ...

Analytical chemistry researchers at the University of Amsterdam's Van 't Hoff Institute for Molecular Sciences (HIMS) have ...

The strategic advantage of QML continues to expand its presence in industries that deal with complex, high-dimensional data.

The bookshelf problem (which computer scientists call the “list labeling” problem) is one of the most basic topics in the field of data structures. “It’s the kind of problem you’d teach to freshman or ...

This useful study presents a biologically realistic, large-scale cortical model of the rat's non-barrel somatosensory cortex, investigating synaptic plasticity of excitatory connections under varying ...

The carbon neutral data centers market is expanding as sustainability becomes integral to IT strategy, regulatory compliance, and brand differentiation. These facilities represent a convergence of ...

Some types of predictive analytics software use machine learning to revise algorithms based on learnings from the data collected over time, continuously improving prediction accuracy.

In this article, we focus on the scalable distributed data-driven state estimation problem using Gaussian processes (GPs). The framework includes two parts: 1) the data-driven training approach and 2) ...