AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Methane

Showing 11 to 20 of 45 articles

Clear Filters

Enhancing corn stalk-based anaerobic digestion with different types of zero-valent iron added during the acidification stage: Performance and mechanism.

Journal of environmental sciences (China)
Anaerobic digestion has been defined as a competitive approach to facilitate the recycling of corn stalks. However, few studies have focused on the role of direct interspecies electron transfer (DIET) pathway in the acidification stage under the addi...

Approaches for predicting dairy cattle methane emissions: from traditional methods to machine learning.

Journal of animal science
Measuring dairy cattle methane (CH4) emissions using traditional recording technologies is complicated and expensive. Prediction models, which estimate CH4 emissions based on proxy information, provide an accessible alternative. This review covers th...

Prediction of Individual Gas Yields of Supercritical Water Gasification of Lignocellulosic Biomass by Machine Learning Models.

Molecules (Basel, Switzerland)
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...

Automated machine learning-aided prediction and interpretation of gaseous by-products from the hydrothermal liquefaction of biomass.

The Science of the total environment
Hydrothermal liquefaction (HTL) is a thermochemical conversion technology that produces bio-oil from wet biomass without drying. However, by-product gases will inevitably be produced, and their formation is unclear. Therefore, an automated machine le...

IoT-based monitoring system and air quality prediction using machine learning for a healthy environment in Cameroon.

Environmental monitoring and assessment
This paper is aimed at developing an air quality monitoring system using machine learning (ML), Internet of Things (IoT), and other elements to predict the level of particulate matter and gases in the air based on the air quality index (AQI). It is a...

Early Detection of Pipeline Natural Gas Leakage from Hyperspectral Imaging by Vegetation Indicators and Deep Neural Networks.

Environmental science & technology
The timely detection of underground natural gas (NG) leaks in pipeline transmission systems presents a promising opportunity for reducing the potential greenhouse gas (GHG) emission. However, existing techniques face notable limitations for prompt de...

Machine learning-aided unveiling the relationship between chemical pretreatment and methane production of lignocellulosic waste.

Waste management (New York, N.Y.)
Chemical pretreatment is a common method to enhance the cumulative methane yield (CMY) of lignocellulosic waste (LW) but its effectiveness is subject to various factors, and accurate estimation of methane production of pretreated LW remains a challen...

Neural Network Based Aliasing Spectral Decoupling Algorithm for Precise Mid-Infrared Multicomponent Gases Sensing.

ACS sensors
Owing to the overlapping and cross-interference of absorption lines in multicomponent gases, the simultaneous measurement of such gases via laser absorption spectroscopy frequently necessitates the use of supplementary pressure sensors to distinguish...

Sludge bound-EPS solubilization enhance CH bioconversion and membrane fouling mitigation in electrochemical anaerobic membrane bioreactor: Insights from continuous operation and interpretable machine learning algorithms.

Water research
Bound extracellular polymeric substances (EPS) are complex, high-molecular-weight polymer mixtures that play a critical role in pore clogging, foulants adhesion, and fouling layer formation during membrane filtration, owing to their adhesive properti...

Microbial-Guided prediction of methane and sulfide production in Sewers: Integrating mechanistic models with Machine learning.

Bioresource technology
Accurate modeling of methane (CH) and sulfide (HS) production in sewer systems was constrained by insufficient consideration of microbial processes under dynamic environmental conditions. This study introduces a microbial-guided machine learning (ML)...