AI Medical Compendium Topic:
Environmental Monitoring

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Machine-learned modeling of PM exposures in rural Lao PDR.

The Science of the total environment
This study presents a machine-learning-enhanced method of modeling PM personal exposures in a data-scarce, rural, solid fuel use context. Data collected during a cookstove (Africa Clean Energy (ACE)-1 solar-battery-powered stove) intervention program...

Identifying floating plastic marine debris using a deep learning approach.

Environmental science and pollution research international
Estimating the volume of macro-plastics which dot the world's oceans is one of the most pressing environmental concerns of our time. Prevailing methods for determining the amount of floating plastic debris, usually conducted manually, are time demand...

Mine landslide susceptibility assessment using IVM, ANN and SVM models considering the contribution of affecting factors.

PloS one
The fragile ecological environment near mines provide advantageous conditions for the development of landslides. Mine landslide susceptibility mapping is of great importance for mine geo-environment control and restoration planning. In this paper, a ...

Vehicular traffic noise prediction and propagation modelling using neural networks and geospatial information system.

Environmental monitoring and assessment
This study proposes a neural network (NN) model to predict and simulate the propagation of vehicular traffic noise in a dense residential area at the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia. The proposed model comprises of two main ...

Comparative study of different wavelet-based neural network models to predict sewage sludge quantity in wastewater treatment plant.

Environmental monitoring and assessment
In this study, artificial neural networks (ANNs) including feed forward back propagation neural network (FFBP-NN) and the radial basis function neural network (RBF-NN) were applied to predict daily sewage sludge quantity in wastewater treatment plant...

An ensemble long short-term memory neural network for hourly PM concentration forecasting.

Chemosphere
To protect public health by providing an early warning, PM concentration forecasting is an essential and effective work. In this paper, an ensemble long short-term memory neural network (E-LSTM) is proposed for hourly PM concentration forecasting. Th...

Hydrochemical Analysis and Fuzzy Logic Method for Evaluation of Groundwater Quality in the North Chengdu Plain, China.

International journal of environmental research and public health
Groundwater is a major water resource in the North Chengdu Plain, China. The research objective is to determine the quality and suitability of groundwater for drinking purposes within the vicinity of a shallow, unconsolidated aquifer of Quaternary ag...

Gradients of three coastal environments off the South China Sea and their impacts on the dynamics of heterotrophic microbial communities.

The Science of the total environment
Heterotrophic fungus-like marine protists are recognized to contribute significantly to the coastal carbon cycling largely due to their high biomass and ability to decompose recalcitrant organic matter. Yet, little is known about their dynamics at po...

Determination of 17 potential endocrine-disrupting chemicals in human saliva by dispersive liquid-liquid microextraction and liquid chromatography-tandem mass spectrometry.

Talanta
Endocrine-disrupting chemicals are a group of emerging contaminants that alters the function of the endocrine system, causing possible adverse health effects. In this study, a dispersive liquid-liquid microextraction method coupled with liquid chroma...

Long short-term memory - Fully connected (LSTM-FC) neural network for PM concentration prediction.

Chemosphere
People have been suffering from air pollution for a decade in China, especially from PM (particulate matter with a diameter of less than 2.5 μm). Accurate prediction of air quality has great practical significance. In this paper, we propose a data-dr...