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Application of the Lasso regularisation technique in mitigating overfitting in air quality prediction models.
Sci Rep
January 2025
Department of Statistics, Faculty of Science, Fasa University, Fasa, 74616-86131, Iran.
As a significant global concern, air pollution triggers enormous challenges in public health and ecological sustainability, necessitating the development of precise algorithms to forecast and mitigate its impacts, which has led to the development of many machine learning (ML)-based models for predicting air quality. Meanwhile, overfitting is a prevalent issue with ML algorithms that decreases their efficacy and generalizability. The present investigation, using an extensive collection of data from 16 sensors in Tehran, Iran, from 2013 to 2023, focuses on applying the Least Absolute Shrinkage and Selection Operator (Lasso) regularisation technique to enhance the forecasting precision of ambient air pollutants concentration models, including particulate matter (PM and PM), CO, NO, SO, and O while decreasing overfitting.
View Article and Find Full Text PDFUp-Conversion Photoluminescence Reconfiguration in Silicon by Inner Microstructure Control of Hybrid Plasmonic-Semiconductor Nanoparticles.
J Phys Chem Lett
December 2024
ITMO University, Department of Physics and Engineering, 197101, 49 Kronverkskiy av., St. Petersburg, Russian Federation.
Hybrid metal-semiconductor nanostructures unifying plasmonic and high-refractive-index materials in a single resonant system demonstrate a wide set of unique optical properties. Such systems are a perspective for a broad palette of applications, but the link between their inner structure and optical properties is a very sensitive issue, which is still not revealed. Here, we describe the influence of internal microstructure of a hybrid gold-silicon nanoparticle (the gold nanoparticle with embedded silicon nanograins) on the up-conversion white-light photoluminescence.
View Article and Find Full Text PDFGeneration of synthetic microstructures containing casting defects: a machine learning approach.
Sci Rep
July 2023
Mines Paris, PSL University, Centre des matériaux (MAT), UMR7633 CNRS, 91003, Evry, France.
This paper presents a new strategy to generate synthetic samples containing casting defects. Four samples of Inconel 100 containing casting defects such as shrinkages and pores have been characterized using X-ray tomography and are used as reference for this application. Shrinkages are known to be tortuous in shape and more detrimental for the mechanical properties of materials, especially metal fatigue, whereas pores can be of two types: broken shrinkage pores with arbitrary shape and gaseous pores of spherical shape.
View Article and Find Full Text PDFProcedure of Eliminating Porosity in Grey Cast Iron with Low Sulphur Content.
Materials (Basel)
September 2022
Faculty of Foundry Engineering, AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Kraków, Poland.
This study shows that the inoculation process of a molten alloy is crucial in disposing of porosity-type defects. A thermal analysis is used to assess the physico-chemical state of a molten alloy, which can be an indicator of the inoculation effect. A modern thermal analysis should be able to perform a quick data-analysis and provide information about any possible problems in a casting if it is poured with the analysed alloy.
View Article and Find Full Text PDFConstruction and Nanostructure of Chitosan/Nanocellulose Hybrid Aerogels.
Biomacromolecules
August 2021
Jiangxi University of Science and Technology, Ganzhou 341000, Jiangxi, PR China.
Biomass aerogels have received extensive attention due to their unique natural characteristics. However, biomass-based chitosan aerogels are often confronted with the traditional issue concerning a weak skeleton structure, namely, the corresponding huge shrinkage for chitosan aerogels in the stage from the final gel to the aerogel. Herein, we put forward a new approach to enhance chitosan aerogels by introducing natural biomaterial cellulose nanocrystal (CNC).
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