AIMC Topic: Water

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Lemongrass-Incorporated Tissue Conditioner with Adjustable Inhibitory Effect Against Candida albicans: An In Vitro Study.

The International journal of prosthodontics
PURPOSE: To develop and assess lemongrass-incorporated tissue conditioners (LG-TCs) with a potent and long-lasting inhibitory effect against Candida albicans cultures to control the accumulation of fungi.

Optimized Design of Neural Networks for a River Water Level Prediction System.

Sensors (Basel, Switzerland)
In this paper, a Multi-Objective Genetic Algorithm (MOGA) framework for the design of Artificial Neural Network (ANN) models is used to design 1-step-ahead prediction models of river water levels. The design procedure is a near-automatic method that,...

The assessment of emerging data-intelligence technologies for modeling Mg and SO surface water quality.

Journal of environmental management
The concentration of soluble salts in surface water and rivers such as sodium, sulfate, chloride, magnesium ions, etc., plays an important role in the water salinity. Therefore, accurate determination of the distribution pattern of these ions can imp...

Using Neural Network Force Fields to Ascertain the Quality of Simulations of Liquid Water.

The journal of physical chemistry. B
Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the level, inc...

Predicting evaporation with optimized artificial neural network using multi-objective salp swarm algorithm.

Environmental science and pollution research international
Evaporation is a crucial component to be established in agriculture management and water engineering. Evaporation prediction is thus an essential issue for modeling researchers. In this study, the multilayer perceptron (MLP) was used for predicting d...

Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.

PloS one
The study is aimed at the frosting problem of the air source heat pump in the low temperature and high humidity environment, which reduces the service life of the system. First, the frosting characteristics at the evaporator side of the air source he...

Machine learning for manually-measured water quality prediction in fish farming.

PloS one
Monitoring variables such as dissolved oxygen, pH, and pond temperature is a key aspect of high-quality fish farming. Machine learning (ML) techniques have been proposed to model the dynamics of such variables to improve the fish farmer's decision-ma...

Predicting polycyclic aromatic hydrocarbons in surface water by a multiscale feature extraction-based deep learning approach.

The Science of the total environment
Accurate and effective prediction of polycyclic aromatic hydrocarbons (PAHs) in surface water remains a substantial challenge due to the limited understanding of the dynamic processes. To assist integrated surface water management, a novel hybrid sur...

Predicting moisture content during maize nixtamalization using machine learning with NIR spectroscopy.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Moisture content during nixtamalization can be accurately predicted from NIR spectroscopy when coupled with a support vector machine (SVM) model, is strongly modulated by the environment, and has a complex genetic architecture. Lack of high-throughpu...

Deep-learning based monitoring of FOG layer dynamics in wastewater pumping stations.

Water research
Accumulation of fat, oil and grease (FOG) in the sumps of wastewater pumping stations is a common failure cause for these facilities. Floating solids are often not transported by the pump suction inlets and the individual solids can accumulate to sti...