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Spectrum Analysis

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Rapid proximate analysis of coal based on reflectance spectroscopy and deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Proximate analysis of coal is of profound significance for understanding coal quality and promoting rational utilization of coal resources. Traditional coal proximate analysis mainly uses chemical analysis methods, which have the disadvantages of slo...

Examining unsupervised ensemble learning using spectroscopy data of organic compounds.

Journal of computer-aided molecular design
One solution to the challenge of choosing an appropriate clustering algorithm is to combine different clusterings into a single consensus clustering result, known as cluster ensemble (CE). This ensemble learning strategy can provide more robust and s...

Characterizing viral samples using machine learning for Raman and absorption spectroscopy.

MicrobiologyOpen
Machine learning methods can be used as robust techniques to provide invaluable information for analyzing biological samples in pharmaceutical industries, such as predicting the concentration of viral particles of interest in biological samples. Here...

Interpretable artificial neural networks for retrospective QbD of pharmaceutical tablet manufacturing based on a pilot-scale developmental dataset.

International journal of pharmaceutics
As the pharmaceutical industry increasingly adopts the Pharma 4.0. concept, there is a growing need to effectively predict the product quality based on manufacturing or in-process data. Although artificial neural networks (ANNs) have emerged as power...

Interpretable machine learning assisted spectroscopy for fast characterization of biomass and waste.

Waste management (New York, N.Y.)
The combination of machine learning and infrared spectroscopy was reported as effective for fast characterization of biomass and waste (BW). However, this characterization process is lack of interpretability towards its chemical insights, leading to ...

Neural network-based optimization of sub-diffuse reflectance spectroscopy for improved parameter prediction and efficient data collection.

Journal of biophotonics
In this study, a general and systematical investigation of sub-diffuse reflectance spectroscopy is implemented. A Gegenbauer-kernel phase function-based Monte Carlo is adopted to describe photon transport more efficiently. To improve the computationa...

Elucidating the Role of Hydrogen Bonding in the Optical Spectroscopy of the Solvated Green Fluorescent Protein Chromophore: Using Machine Learning to Establish the Importance of High-Level Electronic Structure.

The journal of physical chemistry letters
Hydrogen bonding interactions with chromophores in chemical and biological environments play a key role in determining their electronic absorption and relaxation processes, which are manifested in their linear and multidimensional optical spectra. Fo...

In-situ and fast classification of origins of Baishao (Radix Paeoniae Alba) slices based on auto-focus laser-induced breakdown spectroscopy.

Optics letters
In this Letter, a rapid origin classification device and method for Baishao (Radix Paeoniae Alba) slices based on auto-focus laser-induced breakdown spectroscopy (LIBS) is proposed. The enhancement of spectral signal intensity and stability through a...

Efficient Photoacoustic Image Synthesis with Deep Learning.

Sensors (Basel, Switzerland)
Photoacoustic imaging potentially allows for the real-time visualization of functional human tissue parameters such as oxygenation but is subject to a challenging underlying quantification problem. While in silico studies have revealed the great pote...

Artificial Intelligence-Aided Massively Parallel Spectroscopy of Freely Diffusing Nanoscale Entities.

Analytical chemistry
Massively parallel spectroscopy (MPS) of many single nanoparticles in an aqueous dispersion is reported. As a model system, bioconjugated photon-upconversion nanoparticles (UCNPs) with a near-infrared excitation are prepared. The UCNPs are doped eith...