Chemometric methods in data processing of mass spectrometry-based metabolomics: A review

L Yi, N Dong, Y Yun, B Deng, D Ren, S Liu… - Analytica chimica acta, 2016 - Elsevier
This review focuses on recent and potential advances in chemometric methods in relation to
data processing in metabolomics, especially for data generated from mass spectrometric …

Quantification of food bioactives by NIR spectroscopy: Current insights, long-lasting challenges, and future trends

W Tian, Y Li, C Guzman, MI Ibba, M Tilley… - Journal of Food …, 2023 - Elsevier
Conventional wet-chemistry methods for quantitative analysis of food bioactives are time-
consuming, costly, and generate hazardous waste. Near-infrared (NIR) spectroscopy …

[HTML][HTML] Improvement of the machine learning-based corrosion rate prediction model through the optimization of input features

Y Diao, L Yan, K Gao - Materials & Design, 2021 - Elsevier
The corrosion resistance of low-alloy steel seriously influences its performance, particularly
as a class of materials widely used in marine environments. In this study, we collected the …

Machine learning prediction of corrosion rate of steel in carbonated cementitious mortars

H Ji, H Ye - Cement and Concrete Composites, 2023 - Elsevier
Corrosion rate (ie, corrosion current density), a crucial kinetic parameter for predicting and
modeling service-life performance of reinforced concrete structures, can be estimated using …

A selective ensemble preprocessing strategy for near-infrared spectral quantitative analysis of complex samples

X Bian, K Wang, E Tan, P Diwu, F Zhang… - … and Intelligent Laboratory …, 2020 - Elsevier
Preprocessing of raw near-infrared (NIR) spectra is typically required prior to multivariate
calibration since the measured spectra of complex samples are often subject to …

A bootstrapping soft shrinkage approach for variable selection in chemical modeling

BC Deng, YH Yun, DS Cao, YL Yin, WT Wang… - Analytica chimica …, 2016 - Elsevier
In this study, a new variable selection method called bootstrapping soft shrinkage (BOSS)
method is developed. It is derived from the idea of weighted bootstrap sampling (WBS) and …

Near infrared spectroscopic variable selection by a novel swarm intelligence algorithm for rapid quantification of high order edible blend oil

X Bian, R Zhang, P Liu, Y Xiang, S Wang… - Spectrochimica Acta Part A …, 2023 - Elsevier
The quantification of single oil in high order edible blend oil is a challenging task. In this
research, a novel swarm intelligence algorithm, discretized whale optimization algorithm …

[HTML][HTML] Prediction of mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning

MG Jiménez, SA Babayan, P Khazaeli… - Wellcome open …, 2019 - ncbi.nlm.nih.gov
Despite the global efforts made in the fight against malaria, the disease is resurging. One of
the main causes is the resistance that Anopheles mosquitoes, vectors of the disease, have …

UPLC–Orbitrap–MS/MS combined with chemometrics establishes variations in chemical components in green tea from Yunnan and Hunan origins

Z Xin, S Ma, D Ren, W Liu, B Han, Y Zhang, J Xiao, L Yi… - Food chemistry, 2018 - Elsevier
Multi-components of green tea from different origins were identified by UPLC–Orbitrap–
MS/MS, including alkaloids, amino acids, catechins, flavones, flavone glycosides, phenolic …

[HTML][HTML] Building extraction using orthophotos and dense point cloud derived from visual band aerial imagery based on machine learning and segmentation

AD Schlosser, G Szabó, L Bertalan, Z Varga, P Enyedi… - Remote Sensing, 2020 - mdpi.com
Urban sprawl related increase of built-in areas requires reliable monitoring methods and
remote sensing can be an efficient technique. Aerial surveys, with high spatial resolution …