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Rapid quantification of royal jelly quality by mid-infrared spectroscopy coupled with backpropagation neural network.

Food chemistry
Royal jelly is rich in nutrients but its quality is greatly affected by storage conditions. To determine the quality of royal jelly accurately and quickly, a qualitative discrimination model was established based on the fusion of conventional paramet...

Machine Learning for Prediction, Classification, and Identification of Immobilized Enzymes for Biocatalysis.

Pharmaceutical research
BACKGROUND: Enzyme immobilization is a beneficial component involved in biocatalytic strategies. Understanding and evaluating the enzyme immobilization system plays an important role in the successful development and implementation of the biocatalysi...

Hybrid Feature Fusion-Based High-Sensitivity Fire Detection and Early Warning for Intelligent Building Systems.

Sensors (Basel, Switzerland)
High-sensitivity early fire detection is an essential prerequisite to intelligent building safety. However, due to the small changes and erratic fluctuations in environmental parameters in the initial combustion phase, it is always a challenging task...

Quantitative Mass Spectrometry Imaging Using Multivariate Curve Resolution and Deep Learning: A Case Study.

Journal of the American Society for Mass Spectrometry
In the present contribution, a novel approach based on multivariate curve resolution and deep learning (DL) is proposed for quantitative mass spectrometry imaging (MSI) as a potent technique for identifying different compounds and creating their dist...

Rapid simultaneous analysis of anti human immunodeficiency virus drugs in pharmaceutical formulation by smart spectrophotometry based on multivariate calibration and least squares support vector machine methods.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this study, two chemometrics methods, including partial least squares regression (PLS) and least squares support vector machine (LS-SVM) were applied for the simultaneous determination of zidovudine (ZDV) and lamivudine (LMV) in synthetic mixtures...

A deep learning method for predicting lead content in oilseed rape leaves using fluorescence hyperspectral imaging.

Food chemistry
The purpose of this study was to develop a deep learning method involving wavelet transform (WT) and stacked denoising autoencoder (SDAE) for extracting deep features of heavy metal lead (Pb) detection of oilseed rape leaves. Firstly, the standard no...

A soft sensing method of billet surface temperature based on ILGSSA-LSSVM.

Scientific reports
It is difficult to measure the surface temperature of continuous casting billet, which results in the lack of important feedback parameters for further scientific control of the billet quality. This paper proposes a sparrow search algorithm to optimi...

Comfort Prediction of Office Chair Surface Material Based on the ISSA-LSSVM.

Sensors (Basel, Switzerland)
This study serves the purpose of assisting users in selecting a comfortable seat surface material for office chairs and enhancing users' comfort while using office chairs. To address the issue that the selection of traditional seat surface material i...

Several machine learning techniques comparison for the prediction of the uniaxial compressive strength of carbonate rocks.

Scientific reports
In engineering practices, it is critical and necessary to either measure or estimate the uniaxial compressive strength (UCS) of the rock. Measuring the UCS of rocks requires comprehensive studies in the field and in the laboratory for the rock block ...

Identification of agricultural quarantine materials in passenger's luggage using ion mobility spectroscopy combined with a convolutional neural network.

Analytical methods : advancing methods and applications
As economic globalization intensifies, the recent increase in agricultural products and travelers from abroad has led to an increase in the probability of invasive alien species. A major pathway for invasive alien species is agricultural quarantine m...