AIMC Topic: Least-Squares Analysis

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Trace detection of antibiotics in wastewater using tunable core-shell nanoparticles SERS substrate combined with machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 5, 2025
Surface-enhanced Raman scattering (SERS) show great potential for rapid and highly sensitive detection of trace amounts of contamination from the environment in the surface aquatic ecosystem. The widespread use of antibiotics has resulted in serious ...
Anti-Bacterial Agents Spectrum Analysis, Raman Support Vector Machine Machine Learning Wastewater Algorithms Water Pollutants, Chemical Principal Component Analysis Metal Nanoparticles Least-Squares Analysis Discriminant Analysis Silver Ciprofloxacin
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Machine learning driven benchtop Vis/NIR spectroscopy for online detection of hybrid citrus quality.

Food research international (Ottawa, Ont.) Jan 2, 2025
The aim of this study was to explore application of visible and near-infrared (Vis/NIR) spectroscopy combined with machine learning models for SSC and TA prediction of hybrid citrus. The Vis/NIR spectra of samples including navel-region, equator-regi...
Neural Networks, Computer Support Vector Machine Machine Learning Least-Squares Analysis Spectroscopy, Near-Infrared Citrus
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Fault diagnosis of nonlinear analog circuits using generalized frequency response function and LSSVM.

PloS one Dec 30, 2024
A fault diagnosis method of nonlinear analog circuits is proposed that combines the generalized frequency response function (GFRF) and the simplified least squares support vector machine (LSSVM). In this study, the harmonic signal is used as an input...
Support Vector Machine Algorithms Least-Squares Analysis Computer Simulation Nonlinear Dynamics Models, Theoretical
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Determination and visualization of moisture content in Camellia oleifera seeds rapidly based on hyperspectral imaging combined with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 27, 2024
Moisture content (MC) is crucial for the storage, transportation, and processing of Camellia oleifera seeds. The purpose of this study was to investigate the feasibility for detecting MC in Camellia oleifera seeds using visible near-infrared hyperspe...
Deep Learning Neural Networks, Computer Water Camellia Algorithms Seeds Support Vector Machine Least-Squares Analysis Hyperspectral Imaging Spectroscopy, Near-Infrared
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Identification of Phosphodiesterase type 5 inhibitors (PDE5is) analogues using surface-enhanced Raman scattering and machine learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 27, 2024
Phosphodiesterase type 5 inhibitors (PDE5is), primarily used for the treatment of erectile dysfunction, have been severely misused in recent years, posing a threat to public health and safety. This study developed a method that combines Surface-enhan...
Principal Component Analysis Gold Metal Nanoparticles Least-Squares Analysis Discriminant Analysis Algorithms Phosphodiesterase 5 Inhibitors Spectrum Analysis, Raman Humans Support Vector Machine Machine Learning
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Rapid detection of microplastics in chicken feed based on near infrared spectroscopy and machine learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 20, 2024
The main objective of this study was to evaluate the potential of near infrared (NIR) spectroscopy and machine learning in detecting microplastics (MPs) in chicken feed. The application of machine learning techniques in building optimal classificatio...
Food Contamination Principal Component Analysis Least-Squares Analysis Discriminant Analysis Animal Feed Microplastics Spectroscopy, Near-Infrared Chickens Support Vector Machine Machine Learning Algorithms Animals
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A rapid, non-destructive, and accurate method for identifying citrus granulation using Raman spectroscopy and machine learning.

Journal of food science Dec 10, 2024
Citrus fruits are widely consumed for their nutritional value and taste; however, juice sac granulation during fruit storage poses a significant challenge to the citrus industry. This study used Raman spectroscopy coupled with machine learning algori...
Principal Component Analysis Least-Squares Analysis Discriminant Analysis Machine Learning Algorithms Spectrum Analysis, Raman Fruit Fruit and Vegetable Juices Citrus
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Using three-dimensional fluorescence spectroscopy and machine learning for rapid detection of adulteration in camellia oil.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 3, 2024
Camellia oil had been widely utilized in the realms of cooking, healthcare, and beauty. Nevertheless, merchants frequently adulterated pure camellia oil with low-priced oils to cut costs. This study was aimed at identifying the authenticity of camell...
Neural Networks, Computer Machine Learning Support Vector Machine Least-Squares Analysis Food Contamination Discriminant Analysis Plant Oils Camellia Spectrometry, Fluorescence
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A non-linear modelling approach to predict the dissolution profile of extended-release tablets.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences Nov 28, 2024
This study proposes a novel non-linear modelling approach to predict the dissolution profiles of extended-release tablets, by combining a full-factorial design, curve fitting to the dissolution profiles, and artificial neural networks (ANN), with lin...
Chemistry, Pharmaceutical Neural Networks, Computer Delayed-Action Preparations Nonlinear Dynamics Least-Squares Analysis Excipients Tablets Carboxymethylcellulose Sodium Linear Models Solubility Hypromellose Derivatives Drug Liberation
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Preventing mislabeling of organic white button mushrooms (Agaricus bisporus) combining NMR-based foodomics, statistical, and machine learning approach.

Food research international (Ottawa, Ont.) Nov 19, 2024
Organic foods are among the most susceptible to fraud and mislabeling since the differentiation between organic and conventionally grown food relies on a paper-trail-based system. This study aimed to develop a differentiation model that combines nucl...
Neural Networks, Computer Magnetic Resonance Spectroscopy Machine Learning Food, Organic Least-Squares Analysis Principal Component Analysis Food Labeling Discriminant Analysis Agaricus
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