AIMC Topic: Water

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ATR-FTIR spectroscopy and machine/deep learning models for detecting adulteration in coconut water with sugars, sugar alcohols, and artificial sweeteners.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jul 3, 2024
Packaged coconut water offers various options, from pure to those with added sugars and other additives. While the purity of coconut water is esteemed for its health benefits, its popularity also exposes it to potential adulteration and misrepresenta...
Sweetening Agents Cocos Sugar Alcohols Principal Component Analysis Sugars Machine Learning Spectroscopy, Fourier Transform Infrared Food Contamination Deep Learning Water
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Clivia biosensor: Soil moisture identification based on electrophysiology signals with deep learning.

Biosensors & bioelectronics Jun 25, 2024
Research has shown that plants have the ability to detect environmental changes and generate electrical signals in response. These electrical signals can regulate the physiological state of plants and produce corresponding feedback. This suggests tha...
Biosensing Techniques Environmental Monitoring Deep Learning Water Plants Neural Networks, Computer Soil
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Advancing deep learning-based acoustic leak detection methods towards application for water distribution systems from a data-centric perspective.

Water research Jun 24, 2024
Against the backdrop of severe leakage issue in water distribution systems (WDSs), numerous researchers have focused on the development of deep learning-based acoustic leak detection technologies. However, these studies often prioritize model develop...
Acoustics Water Supply Deep Learning Water Neural Networks, Computer
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Towards transferable metamodels for water distribution systems with edge-based graph neural networks.

Water research Jun 20, 2024
Data-driven metamodels reproduce the input-output mapping of physics-based models while significantly reducing simulation times. Such techniques are widely used in the design, control, and optimization of water distribution systems. Recent research h...
Water Supply Neural Networks, Computer Computer Simulation Water Models, Theoretical
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Comparison of water and terrestrial jumping in natural and robotic insects.

Annals of the New York Academy of Sciences Jun 19, 2024
Jumping requires high actuation power for achieving high speed in a short time. Especially, organisms and robots at the insect scale jump in order to overcome size limits on the speed of locomotion. As small jumpers suffer from intrinsically small po...
Animals Water Biomechanical Phenomena Locomotion Robotics Insecta
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Predicting Odor Sensory Attributes of Unidentified Chemicals in Water Using Fragmentation Mass Spectra with Machine Learning Models.

Environmental science & technology Jun 15, 2024
Knowing odor sensory attributes of odorants lies at the core of odor tracking when addressing waterborne odor issues. However, experimental determination covering tens of thousands of odorants in authentic water is not pragmatic due to the complexity...
Water Mass Spectrometry Odorants Machine Learning
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Detection of milk adulteration using coffee ring effect and convolutional neural network.

Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment May 30, 2024
A low-cost and effective method is reported to identify water and synthetic milk adulteration of cow's milk using coffee ring patterns. The cow's milk samples were diluted with tap water (TW), distilled water (DW) and mineral water (MW) and drop cast...
Milk Neural Networks, Computer Cattle Animals Food Contamination Water
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The use of image analysis to study the effect of moisture content on the physical properties of grains.

Scientific reports May 22, 2024
Designing machines and equipment for post-harvest operations of agricultural products requires information about their physical properties. The aim of the work was to evaluate the possibility of introducing a new approach to predict the moisture cont...
Neural Networks, Computer Water Zea mays Edible Grain Image Processing, Computer-Assisted Seeds
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Prediction of Individual Gas Yields of Supercritical Water Gasification of Lignocellulosic Biomass by Machine Learning Models.

Molecules (Basel, Switzerland) May 16, 2024
Supercritical water gasification (SCWG) of lignocellulosic biomass is a promising pathway for the production of hydrogen. However, SCWG is a complex thermochemical process, the modeling of which is challenging via conventional methodologies. Therefor...
Neural Networks, Computer Gases Biomass Hydrogen Water Carbon Dioxide Machine Learning Lignin Algorithms Support Vector Machine Methane
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Measuring volume fractions of a three-phase flow without separation utilizing an approach based on artificial intelligence and capacitive sensors.

PloS one May 16, 2024
Many different kind of fluids in a wide variety of industries exist, such as two-phase and three-phase. Various combinations of them can be expected and gas-oil-water is one of the most common flows. Measuring the volume fraction of phases without se...
Electric Capacitance Water Gases Neural Networks, Computer Artificial Intelligence
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