Computer vision and machine learning methods for heat transfer and fluid flow in complex structural microchannels: A review
Heat dissipation in high-heat flux micro-devices has become a pressing issue. One of the
most effective methods for removing the high heat load of micro-devices is boiling heat …
most effective methods for removing the high heat load of micro-devices is boiling heat …
Community-engaged artificial intelligence research: A sco** review
TJ Loftus, JA Balch, KL Abbott, D Hu… - PLOS Digital …, 2024 - journals.plos.org
The degree to which artificial intelligence healthcare research is informed by data and
stakeholders from community settings has not been previously described. As communities …
stakeholders from community settings has not been previously described. As communities …
Analyzing spatio-temporal dynamics of dissolved oxygen for the River Thames using superstatistical methods and machine learning
By employing superstatistical methods and machine learning, we analyze time series data of
water quality indicators for the River Thames (UK). The indicators analyzed include …
water quality indicators for the River Thames (UK). The indicators analyzed include …
Electrical conductivity as a reliable indicator for assessing land use effects on stream N2O concentration
While it is widely acknowledged that different categories of terrestrial land use significantly
affect N 2 O emissions from streams and rivers, a suitable indicator to comprehensively …
affect N 2 O emissions from streams and rivers, a suitable indicator to comprehensively …
Smarter water quality monitoring in reservoirs using interpretable deep learning models and feature importance analysis
This study utilized datasets from an ongoing monitoring project conducted in Wadi Dayqah
Dam, the largest reservoir in Oman. The dataset comprises information on ten water quality …
Dam, the largest reservoir in Oman. The dataset comprises information on ten water quality …
Leveraging explainable machine learning for enhanced management of lake water quality
Freshwater lakes worldwide suffer from eutrophication caused by excessive nutrient loads,
particularly nitrogen (N) and phosphorus (P) from wastewater and runoff, affecting aquatic …
particularly nitrogen (N) and phosphorus (P) from wastewater and runoff, affecting aquatic …
Machine learning-based design and monitoring of algae blooms: Recent trends and future perspectives–A short review
Abstract Machine learning (ML) models are widely used methods for analyzing data from
sensors and satellites to monitor climate change, predict natural disasters, and protect …
sensors and satellites to monitor climate change, predict natural disasters, and protect …
Response time of fast flowing hydrologic pathways controls sediment hysteresis in a low-gradient watershed, as evidenced from tracer results and machine learning …
Hydrologic controls on the timing of sediment transport and sediment hysteresis patterns
remain an open area of investigation in hydrology, especially for low-gradient watersheds …
remain an open area of investigation in hydrology, especially for low-gradient watersheds …
Machine learning-based monitoring and design of managed aquifer rechargers for sustainable groundwater management: scope and challenges
Managed aquifer recharge (MAR) replenishes groundwater by artificially entering water into
subsurface aquifers. This technology improves water storage, reduces over-extraction, and …
subsurface aquifers. This technology improves water storage, reduces over-extraction, and …
The role of industry 4.0 enabling technologies for predicting, and managing of algal blooms: Bridging gaps and unlocking potential
Recent advancements in data analytics, predictive modeling, and optimization have
highlighted the potential of integrating algal blooms (ABs) with Industry 4.0 technologies …
highlighted the potential of integrating algal blooms (ABs) with Industry 4.0 technologies …