AIMC Topic: Least-Squares Analysis

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Discrimination of internal crack for rice seeds using near infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jun 1, 2024
It is an important thing to identify internal crack in seeds from normal seeds for evaluating the quality of rice seeds (Oryza sativa L.). In this study, non-destructive discrimination of internal crack in rice seeds using near infrared spectroscopy ...
Spectroscopy, Near-Infrared Least-Squares Analysis Discriminant Analysis Oryza Support Vector Machine Seeds Principal Component Analysis
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Growth period determination and color coordinates visual analysis of tomato using hyperspectral imaging technology.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy May 28, 2024
Growth period determination and color coordinates prediction are essential for comparing postharvest fruit quality. This paper proposes a tomato growth period judgment and color coordinates prediction model based on hyperspectral imaging technology. ...
Color Algorithms Solanum lycopersicum Support Vector Machine Fruit Hyperspectral Imaging Principal Component Analysis Linear Models Least-Squares Analysis Discriminant Analysis
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Data fusion of near-infrared and Raman spectroscopy: An innovative tool for non-destructive prediction of the TVB-N content of salmon samples.

Food research international (Ottawa, Ont.) May 27, 2024
Total volatile basic nitrogen (TVB-N) serves as a crucial indicator for evaluating the freshness of salmon. This study aimed to achieve accurate and non-destructive prediction of TVB-N content in salmon fillets stored in multiple temperature settings...
Spectroscopy, Near-Infrared Spectrum Analysis, Raman Support Vector Machine Temperature Animals Salmon Least-Squares Analysis Nitrogen Seafood
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Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal.

IEEE transactions on bio-medical engineering May 20, 2024
OBJECTIVE: Magnetic Resonance Spectroscopy (MRS) is an important technique for biomedical detection. However, it is challenging to accurately quantify metabolites with proton MRS due to serious overlaps of metabolite signals, imperfections because of...
Signal-To-Noise Ratio Magnetic Resonance Spectroscopy Least-Squares Analysis Humans Signal Processing, Computer-Assisted Algorithms Macromolecular Substances Brain Deep Learning
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Geographical origin identification of Khao Dawk Mali 105 rice using combination of FT-NIR spectroscopy and machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy May 19, 2024
The mislabelled Khao Dawk Mali 105 rice coming from other geographical region outside the Thung Kula Rong Hai region is extremely profitable and difficult to detect; to prevent retail fraud (that adversely affects both the food industry and consumers...
Thailand Spectroscopy, Near-Infrared Principal Component Analysis Least-Squares Analysis Discriminant Analysis Oryza Neural Networks, Computer Geography Machine Learning Algorithms
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Predicting drug solubility in organic solvents mixtures: A machine-learning approach supported by high-throughput experimentation.

International journal of pharmaceutics May 18, 2024
A novel approach based on supervised machine-learning is proposed to predict the solubility of drugs and drug-like molecules in mixtures of organic solvents. Similar to quantitative structure-property relationship (QSPR) models, different solvent typ...
Solubility Solvents High-Throughput Screening Assays Quantitative Structure-Activity Relationship Organic Chemicals Machine Learning Least-Squares Analysis Temperature Pharmaceutical Preparations
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Modeling risk assessment of soil heavy metal pollution using partial least squares and fuzzy logic: A case study of a gully type coal-based solid waste dumpsite.

Environmental pollution (Barking, Essex : 1987) May 10, 2024
Continuous release and migration of heavy metals from coal-based solid waste (CSW) dumpsites often results in significant encroachment on ecological lands and pollution of natural environments. As a result, there is an urgent need for long-term and r...
Solid Waste Metals, Heavy Waste Disposal Facilities Least-Squares Analysis Soil Pollutants Coal Environmental Monitoring Fuzzy Logic Soil Risk Assessment
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Modeling and Optimization of an Enhanced Soft Sensor for the Fermentation Process of .

Sensors (Basel, Switzerland) May 9, 2024
This paper proposes a novel soft sensor modeling approach, MIC-TCA-INGO-LSSVM, to address the decline in performance of soft sensor models during the fermentation process of , caused by changes in working conditions. Initially, the transfer component...
Pichia Saccharomycetales Support Vector Machine Algorithms Least-Squares Analysis Fermentation
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Rapid determination of starch and alcohol contents in fermented grains by hyperspectral imaging combined with data fusion techniques.

Journal of food science May 8, 2024
Starch and alcohol serve as pivotal indicators in assessing the quality of lees fermentation. In this paper, two hyperspectral imaging (HSI) techniques (visible-near-infrared (Vis-NIR) and NIR) were utilized to acquire separate HSI data, which were t...
Starch Fermentation Fermented Foods Principal Component Analysis Least-Squares Analysis Edible Grain Hyperspectral Imaging Alcohols Algorithms Spectroscopy, Near-Infrared Support Vector Machine
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Bias-reduced neural networks for parameter estimation in quantitative MRI.

Magnetic resonance in medicine May 4, 2024
PURPOSE: To develop neural network (NN)-based quantitative MRI parameter estimators with minimal bias and a variance close to the Cramér-Rao bound.
Neural Networks, Computer Algorithms Brain Humans Least-Squares Analysis Neuroimaging Image Processing, Computer-Assisted Computer Simulation Magnetic Resonance Imaging Reproducibility of Results Bias
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