AIMC Topic: Water

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Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms.

Scientific reports
Evaporation is the primary aspect causing water loss in the hydrological cycle; therefore, water loss must be precisely measured. Evaporation is an intricate nonlinear process occurring as a result of several climatic aspects. The purpose of this res...

Aquabots.

ACS nano
Soft robots, made from elastomers, easily bend and flex, but deformability constraints severely limit navigation through and within narrow, confined spaces. Using aqueous two-phase systems we print water-in-water constructs that, by aqueous phase-sep...

Predicting the oxidation states of Mn ions in the oxygen-evolving complex of photosystem II using supervised and unsupervised machine learning.

Photosynthesis research
Serial Femtosecond Crystallography at the X-ray Free Electron Laser (XFEL) sources enabled the imaging of the catalytic intermediates of the oxygen evolution reaction of Photosystem II (PSII). However, due to the incoherent transition of the S-states...

Research on water meter reading recognition based on deep learning.

Scientific reports
At present, there are still many old-fashioned water meters in the society, and the water department needs to send staff to read the water meter after arriving at the scene with a handheld all-in-one machine. However, there are many problems in this ...

Deep neural network prediction of modified stepped double-slope solar still with a cotton wick and cobalt oxide nanofluid.

Environmental science and pollution research international
This research work intends to enhance the stepped double-slope solar still performance through an experimental assessment of combining linen wicks and cobalt oxide nanoparticles to the stepped double-slope solar still to improve the water evaporation...

Underwater robot coordination using a bio-inspired electrocommunication system.

Bioinspiration & biomimetics
Due to the challenging communication and control systems, few underwater multi-robot coordination systems are currently developed. In nature, weakly electric fish can organize their collective activities using electrocommunication in turbid water. In...

Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners.

European journal of nuclear medicine and molecular imaging
PURPOSE: Attenuation correction is a critically important step in data correction in positron emission tomography (PET) image formation. The current standard method involves conversion of Hounsfield units from a computed tomography (CT) image to cons...

Well Performance Classification and Prediction: Deep Learning and Machine Learning Long Term Regression Experiments on Oil, Gas, and Water Production.

Sensors (Basel, Switzerland)
In the oil and gas industries, predicting and classifying oil and gas production for hydrocarbon wells is difficult. Most oil and gas companies use reservoir simulation software to predict future oil and gas production and devise optimum field develo...

Non-Intrusive Fish Weight Estimation in Turbid Water Using Deep Learning and Regression Models.

Sensors (Basel, Switzerland)
Underwater fish monitoring is the one of the most challenging problems for efficiently feeding and harvesting fish, while still being environmentally friendly. The proposed 2D computer vision method is aimed at non-intrusively estimating the weight o...

Research on water seepage detection technology of tunnel asphalt pavement based on deep learning and digital image processing.

Scientific reports
To improve the safety of road tunnel pavement, the research established road tunnel pavement water seepage recognition models based on deep learning technology, and a water seepage area extraction model based on image processing technology to finally...