AIMC Topic: Least-Squares Analysis

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Tomato ripeness prediction using low resolution portable spectrometer and machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Tomato ripeness assessment is critical to ensure optimal product quality. This study proposes a novel approach to predict total soluble solids (TSS) and firmness, and classify tomato ripeness using a low-resolution AS7265x portable spectrometer combi...

Machine learning-assisted spectroscopic methods for detecting adulteration in Barrantes wine from Folla Redonda grapes.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The present study explores the application of advanced machine learning algorithms combined with vis-NIRS and FTIR spectroscopy to detect and quantify adulteration in Barrantes wine, produced from the Folla Redonda grape, a variety exclusive to the G...

Rapid classification of bacteria by a portable Raman spectrometer and machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Efficient, accurate, and early identification of plant pathogens is crucial for reducing disease spread and ensuring food security. The development of rapid diagnostic methods based on Raman spectroscopy (RS) coupled with machine learning (ML) holds ...

Spectral markers and machine learning: Revolutionizing Rice evaluation with near infrared spectroscopy.

Food chemistry
The evaluation of rice varieties is a complex, time-consuming process requiring advanced equipment. This study aimed to discriminate 22 commercial rice varieties from six types by analyzing biochemical, physicochemical, and cooking properties. Near-i...

MAMSI: Integration of Multiassay Liquid Chromatography-Mass Spectrometry Metabolomics Data Using Multiview Machine Learning.

Analytical chemistry
Liquid chromatography-mass spectrometry (LC-MS) is a commonly used analytical technique in untargeted metabolomics. However, the diverse chemical and physical properties of metabolites often require the use of several different analytical assays for ...

Saliency-enhanced infrared and visible image fusion via sub-window variance filter and weighted least squares optimization.

PloS one
This paper proposes a novel method for infrared and visible image fusion (IVIF) to address the limitations of existing techniques in enhancing salient features and improving visual clarity. The method employs a sub-window variance filter (SVF) based ...

Detection of bone infections using Vis-NIR and SWIR hyperspectral imaging coupled with machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Bone infections, such as fracture-related and periprosthetic joint infections, present significant diagnostic and therapeutic challenges in orthopaedic surgery. Current diagnosic standards rely primarily on tissue cultures of intraoperatively obtaine...

Implementing partial least squares and machine learning regressive models for prediction of drug release in targeted drug delivery application.

Scientific reports
A combined methodology was performed based on chemometrics and machine learning regressive models in estimation of polysaccharide-coated colonic drug delivery. The release of medication was measured using Raman spectroscopy and the data was used for ...

A study on time-series prediction and analysis of acidity of Daqu based on multivariate data fusion and KNN-Attention-LSTM-XGBoost modeling.

Bioprocess and biosystems engineering
Daqu is a traditional Chinese brewing ingredient that serves dual functions of saccharification and fermentation during the brewing process. The acidity content during the Daqu fermentation process directly affects the quality of the Daqu. Traditiona...

Multivariate and Machine Learning-Derived Virtual Staining and Biochemical Quantification of Cancer Cells through Raman Hyperspectral Imaging.

Analytical chemistry
Advances in virtual staining and spatial omics have revolutionized our ability to explore cellular architecture and molecular composition with unprecedented detail. Virtual staining techniques, which rely on computational algorithms to map molecular ...