AIMC Topic: Least-Squares Analysis

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Comparing visible and near infrared 'point' spectroscopy and hyperspectral imaging techniques to visualize the variability of apple firmness.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Apr 24, 2024
In this work, visible and near-infrared 'point' (Vis-NIR) spectroscopy and hyperspectral imaging (Vis-NIR-HSI) techniques were applied on three different apple cultivars to compare their firmness prediction performances based on a large intra-variabi...
Hyperspectral Imaging Malus Spectroscopy, Near-Infrared Least-Squares Analysis Support Vector Machine Fruit
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Machine learning-assisted chromium speciation using a single-well ratiometric fluorescent nanoprobe.

Chemosphere Apr 11, 2024
Chromium is widely recognized as a significant pollutant discharged into the environment by various industrial activities. The toxicity of this element is dependent on its oxidation state, making speciation analysis crucial for monitoring the quality...
Spectrometry, Fluorescence Least-Squares Analysis Carbon Environmental Monitoring Tellurium Quantum Dots Water Pollutants, Chemical Discriminant Analysis Cadmium Compounds Machine Learning Chromium Fluorescent Dyes
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Research on the chemical oxygen demand spectral inversion model in water based on IPLS-GAN-SVM hybrid algorithm.

PloS one Apr 11, 2024
Spectral collinearity and limited spectral datasets are the problems influencing Chemical Oxygen Demand (COD) modeling. To address the first problem and obtain optimal modeling range, the spectra are preprocessed using six methods including Standard ...
Biological Oxygen Demand Analysis Support Vector Machine Least-Squares Analysis Spectroscopy, Near-Infrared Water Algorithms
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Precision in wheat flour classification: Harnessing the power of deep learning and two-dimensional correlation spectrum (2DCOS).

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Mar 5, 2024
Wheat flour is a ubiquitous food ingredient, yet discerning its various types can prove challenging. A practical approach for identifying wheat flour types involves analyzing one-dimensional near-infrared spectroscopy (NIRS) data. This paper introduc...
Algorithms Least-Squares Analysis Triticum Flour Spectroscopy, Near-Infrared Deep Learning
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NIR spectroscopy-CNN-enabled chemometrics for multianalyte monitoring in microbial fermentation.

Biotechnology and bioengineering Feb 23, 2024
As the biopharmaceutical industry looks to implement Industry 4.0, the need for rapid and robust analytical characterization of analytes has become a pressing priority. Spectroscopic tools, like near-infrared (NIR) spectroscopy, are finding increasin...
Chemometrics Glucose Fermentation Neural Networks, Computer Escherichia coli Least-Squares Analysis Spectroscopy, Near-Infrared
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Enhancing forensic investigations: Identifying bloodstains on various substrates through ATR-FTIR spectroscopy combined with machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 10, 2023
The forensic analysis of bloodstains on various substrates plays a crucial role in criminal investigations. This study presents a novel approach for analyzing bloodstains using Attenuated Total Reflectance Fourier Transform Infrared spectroscopy (ATR...
Bayes Theorem Least-Squares Analysis Swine Algorithms Discriminant Analysis Ataxia Telangiectasia Mutated Proteins Humans Spectroscopy, Fourier Transform Infrared Animals Machine Learning
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Rapid detection of colored and colorless macro- and micro-plastics in complex environment via near-infrared spectroscopy and machine learning.

Journal of environmental sciences (China) Dec 8, 2023
To better understand the migration behavior of plastic fragments in the environment, development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary. However, most of the studies had focu...
Least-Squares Analysis Discriminant Analysis Machine Learning Color Environmental Monitoring Spectroscopy, Near-Infrared Plastics
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Increased interpretation of deep learning models using hierarchical cluster-based modelling.

PloS one Dec 7, 2023
Linear prediction models based on data with large inhomogeneity or abrupt non-linearities often perform poorly because relationships between groups in the data dominate the model. Given that the data is locally linear, this can be overcome by splitti...
Least-Squares Analysis Molecular Weight Neural Networks, Computer Deep Learning Spectroscopy, Fourier Transform Infrared
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Combining Feature Selection Techniques and Neurofuzzy Systems for the Prediction of Total Viable Counts in Beef Fillets Using Multispectral Imaging.

Sensors (Basel, Switzerland) Nov 27, 2023
In the food industry, quality and safety issues are associated with consumers' health condition. There is a growing interest in applying various noninvasive sensorial techniques to obtain quickly quality attributes. One of them, hyperspectral/multisp...
Least-Squares Analysis Meat Animals Neural Networks, Computer Spectroscopy, Near-Infrared Algorithms Cattle
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Development of a PAT platform for the prediction of granule tableting properties.

International journal of pharmaceutics Nov 15, 2023
In this work, the feasibility of implementing a process analytical technology (PAT) platform consisting of Near Infrared Spectroscopy (NIR) and particle size distribution (PSD) analysis was evaluated for the prediction of granule downstream processab...
Spectroscopy, Near-Infrared Least-Squares Analysis Calibration Neural Networks, Computer Temperature
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