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Least-Squares Analysis

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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
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...

NIR spectroscopy-CNN-enabled chemometrics for multianalyte monitoring in microbial fermentation.

Biotechnology and bioengineering
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...

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
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...

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)
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...

Increased interpretation of deep learning models using hierarchical cluster-based modelling.

PloS one
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...

Combining Feature Selection Techniques and Neurofuzzy Systems for the Prediction of Total Viable Counts in Beef Fillets Using Multispectral Imaging.

Sensors (Basel, Switzerland)
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...

Development of a PAT platform for the prediction of granule tableting properties.

International journal of pharmaceutics
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...

Rapid analysis of hydrogen cyanide in fresh cassava roots using NIRSand machine learning algorithms: Meeting end user demand for low cyanogenic cassava.

The plant genome
This study focuses on meeting end-users' demand for cassava (Manihot esculenta Crantz) varieties with low cyanogenic potential (hydrogen cyanide potential [HCN]) by using near-infrared spectrometry (NIRS). This technology provides a fast, accurate, a...

Understanding consumers' intentions to purchase smart clothing using PLS-SEM and fsQCA.

PloS one
With the advancement of artificial intelligence (AI) and the Internet of Things (IoT), smart clothing, which has enormous growth potential, has developed to suit consumers' individualized demands in various areas. This paper aims to construct a model...

Deviation of peak hours for metro stations based on least square support vector machine.

PloS one
The station-level ridership during the peak hour is one of the key indicators for the design of station size and relevant facilities. However, with the operation of metro system, it cannot be ignored that, in many cities, the station peak and the cit...