AIMC Topic: Oils
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Energy consumption forecasting for oil and coal in China based on hybrid deep learning.
PloS one
Jan 6, 2025
The consumption forecasting of oil and coal can help governments optimize and adjust energy strategies to ensure energy security in China. However, such forecasting is extremely challenging because it is influenced by many complex and uncertain facto...
Rapid identification of horse oil adulteration based on deep learning infrared spectroscopy detection method.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Dec 30, 2024
As a natural oil, horse oil has unique biological activity ingredients and therapeutic characteristics, which has important application value and market potential in healthcare, food, skin care and other fields. However, fraud is rampant in the horse...
A machine learning-guided modeling approach to the kinetics of α-tocopherol and myricetin synergism in bulk oil oxidation.
Food chemistry
Sep 27, 2024
The shelf-life and quality of food products depend heavily on antioxidants, which protect lipids from free radical degradation. α-Tocopherol and myricetin, two potent antioxidants, synergistically enhance the prevention of oxidative rancidity in bulk...
Ultrasensitive SERS quantitative detection of antioxidants via diazo derivatization reaction and deep learning for signal fluctuation mitigation.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Feb 25, 2024
Synthetic antioxidants serve as essential protectors against oxidation and deterioration of edible oils, however, prudent evaluation is necessary regarding potential health risks associated with excessive intake. The direct adsorption of antioxidants...
The monitoring of oil production process by deep learning based on morphology in oleaginous yeasts.
Applied microbiology and biotechnology
Dec 28, 2022
BACKGROUND: Monitoring jar fermenter-cultured microorganisms in real time is important for controlling productivity of bioproducts in large-scale cultivation settings. Morphological data is used to understand the growth and fermentation states of the...
Artificial neural network (ANN) and response surface methodology (RSM) algorithm-based improvement, kinetics and isotherm studies of electrocoagulation of oily wastewater.
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Jun 22, 2022
The work reported here focuses on the oil and grease removal from wastewater by the electrocoagulation process and using modeling and optimization for obtaining the results considering four major operating parameters, viz. current density, pH, electr...
Genetic algorithm based artificial neural network and partial least squares regression methods to predict of breakdown voltage for transformer oils samples in power industry using ATR-FTIR spectroscopy.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Feb 5, 2022
The current study proposes a novel analytical method for calculating the breakdown voltage (BV) of transformer oil samples considered as a significant method to assess the safe operation of power industry. Transformer oil samples can be analyzed usin...
Formulation and physicochemical stability of oil-in-water nanoemulsion loaded with α-terpineol as flavor oil using Quillaja saponins as natural emulsifier.
Food research international (Ottawa, Ont.)
Dec 15, 2021
Alpha-terpineol (α-TOH) is a promising monoterpenoid detaining several biological activities. However, as a volatile molecule, the incorporation of α-TOH within formulated products poses several challenges related to its stability. In this sense, nan...
Modelling of transmembrane pressure using slot/pore blocking model, response surface and artificial intelligence approach.
Chemosphere
Dec 15, 2021
This work investigates the application of empirical, statistical and machine learning methods to appraise the prediction of transmembrane pressure (TMP) by oscillating slotted pore membrane for the treatment of two kinds of deformable oil drops. Here...
Optimization of running-in surface morphology parameters based on the AutoML model.
PloS one
Oct 4, 2021
Running-in is an important and relatively complicated process. The surface morphology prior to running-in affects the surface morphology following the running-in process, which in turn influences the friction and wear characteristics of the workpiece...
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