AIMC Topic: Water

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Stacked Ensemble with Machine Learning Regressors on Optimal Features (SMOF) of hyperspectral sensor PRISMA for inland water turbidity prediction.

Environmental science and pollution research international
Leveraging hyperspectral data across various domains yields substantial benefits, yet managing many spectral bands and identifying the essential ones poses a formidable challenge. This study identifies the most relevant bands within a hyperspectral d...

Machine learning models for prediction of nutrient concentrations in surface water in an agricultural watershed.

Journal of environmental management
Prediction and quantification of nutrient concentrations in surface water has gained substantial attention during recent decades because excess nutrients released from agricultural and urban watersheds can significantly deteriorate surface water qual...

Microscopic water dispersion and hydrogen-bonding structures in margarine spreads with Raman hyperspectral imaging and machine learning.

Food chemistry
Margarine, a water-in-oil (W/O) emulsion, offers advantages such as lower costs in comparison to similar products, but large amounts of saturated fats pose health risks. Reduction of saturated fat content is difficult and often leads to "oil-off," i....

Water-Stable Magnetic Lipiodol Micro-Droplets as a Miniaturized Robotic Tool for Drug Delivery.

Advanced materials (Deerfield Beach, Fla.)
Magnetic microrobots, designed to navigate the complex environments of the human body, show promise for minimally invasive diagnosis and treatment. However, their clinical adoption faces hurdles such as biocompatibility, precise control, and intellig...

Assessing long-term water storage dynamics in Afghanistan: An integrated approach using machine learning, hydrological models, and remote sensing.

Journal of environmental management
Assessment of Terrestrial Water Storage (TWS) components is crucial for understanding regional climate and water resources, particularly in arid and semi-arid regions like Afghanistan. Given the scarcity of ground-based data, this study leverages rem...

Quantitative investigation and intelligent forecasting of thermal conductivity in lime-modified red clay.

PloS one
This paper delves into the engineering applications of lime-stabilized red clay, a highly water-sensitive material, particularly in the context of the climatic conditions prevalent in the Dalian region. We systematically investigate the impact of wat...

Acoustic leak localization for water distribution network through time-delay-based deep learning approach.

Water research
Water leakage within water distribution networks (WDNs) presents significant challenges, encompassing infrastructure damage, economic losses, and public health risks. Traditional methods for leak localization based on acoustic signals encounter inher...

Evaluating machine learning performance in predicting sodium adsorption ratio for sustainable soil-water management in the eastern Mediterranean.

Journal of environmental management
Soil salinization is a critical global issue for sustainable agriculture, impacting crop yields and posing a threat to achieving the Sustainable Development Goal (SDG) of ensuring food security. It is necessary to monitor it in detail and uncover its...

Evaluation of crop water stress index of wheat by using machine learning models.

Environmental monitoring and assessment
The Crop Water Stress Index (CWSI), a pivotal indicator derived from canopy temperature, plays a crucial role in irrigation scheduling for water conservation in agriculture. This study focuses on determining CWSI (by empirical method) for wheat crops...

Artificial Neural Network analysis on the effect of mixed convection in triangular-shaped geometry using water-based Al2O3 nanofluid.

PloS one
The objective of the study is to investigate the fluid flow and heat transfer characteristics applying Artificial Neural Networks (ANN) analysis in triangular-shaped cavities for the analysis of magnetohydrodynamics (MHD) mixed convection with varyin...