A Delft University of Technology team has improved agrivoltaic light-simulation methods by making atmospheric and canopy ...
Accurate and interpretable bearing fault diagnosis remains challenging because fault-related spectral signatures are often weak, distributed across multiple frequency bands, and easily affected by ...
Mapping peripheral to central pressure waveforms offers a promising approach for noninvasive assessment of the aortic pressure waveform. Traditional methods rely on population-based averaging, which ...
Hyperspectral imaging empowers machine vision systems with the distinct capability of identifying materials through recording their spectral signatures. Recent efforts in data-driven spectral ...
X-ray Diffraction analysis is crucial for understanding material structures but is hindered by complex patterns and the need for expert interpretation. Deep learning offers automation in phase ...
We introduce an open-source Python package for the analysis of large-scale electrophysiological data, named SyNCoPy, which stands for Systems Neuroscience Computing in Python. The package includes ...
Spectroscopic techniques generate one-dimensional spectra with distinct peaks and specific widths in the frequency domain. These features act as unique identities for material characteristics. Deep ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Label-free living cell separation represents a significant ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The present study attempts to address these limitations by ...
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