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Rapid detection of ionic contents in water through sensor fusion and convolutional neural network.

Chemosphere
Salt contents in soil or groundwater are one of the primary indicators to evaluate contamination levels. Electrical conductivity (EC) or salinity information from the conventional laboratory analysis is typically inefficient in delineating contaminat...

Photoacoustic identification of blood authenticity based on quantum-behaved particle swarm optimized wavelet neural network.

Journal of biophotonics
To accurately identify the blood authenticity, a set of photoacoustic detection system was established. In experiments, five kinds of blood in total of 125 groups were used, the time-resolved photoacoustic signals and peak-to-peak spectra were obtain...

Coal identification based on a deep network and reflectance spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The rapid identification of coal types in the field is an important task. This research combines spectroscopy with deep learning algorithms and proposes a method for quickly identifying coal types in the field. First, we collect field spectral data o...

A new method for detecting mixed bacteria based on multi-wavelength transmission spectroscopy technology.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Previously, we successfully realized the identification of a single species of bacteria based on the multi-wavelength transmission spectrum of bacteria. The current research is focused on realizing the spectral analysis of mixed bacteria. Principal c...

HyperSeed: An End-to-End Method to Process Hyperspectral Images of Seeds.

Sensors (Basel, Switzerland)
High-throughput, nondestructive, and precise measurement of seeds is critical for the evaluation of seed quality and the improvement of agricultural productions. To this end, we have developed a novel end-to-end platform named to provide hyperspectr...

Interpreting support vector machines applied in laser-induced breakdown spectroscopy.

Analytica chimica acta
Laser-induced breakdown spectroscopy is often combined with a multivariate black box model-such as support vector machines (SVMs)-to obtain desirable quantitative or qualitative results. This approach carries obvious risks when practiced in high-stak...

Few-fs resolution of a photoactive protein traversing a conical intersection.

Nature
The structural dynamics of a molecule are determined by the underlying potential energy landscape. Conical intersections are funnels connecting otherwise separate potential energy surfaces. Posited almost a century ago, conical intersections remain t...

Performing sequential forward selection and variational autoencoder techniques in soil classification based on laser-induced breakdown spectroscopy.

Analytical methods : advancing methods and applications
The feasibility and accuracy of several combination classification models, , quadratic discriminant analysis (QDA), random forest (RF), Bernoulli naïve Bayes (BNB), and support vector machine (SVM) classification models combined with either sequentia...

Towards Intraoperative Quantification of Atrial Fibrosis Using Light-Scattering Spectroscopy and Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Light-scattering spectroscopy (LSS) is an established optical approach for characterization of biological tissues. Here, we investigated the capabilities of LSS and convolutional neural networks (CNNs) to quantitatively characterize the composition a...

Davis Computational Spectroscopy Workflow-From Structure to Spectra.

Journal of chemical information and modeling
We describe an automated workflow that connects a series of atomic simulation tools to investigate the relationship between atomic structure, lattice dynamics, materials properties, and inelastic neutron scattering (INS) spectra. Starting from the at...