AIMC Topic: Ecosystem
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Enhancing eco-sensing in aquatic environments: Fish jumping behavior automatic recognition using YOLOv5.
Aquatic toxicology (Amsterdam, Netherlands)
Nov 1, 2024
Contemporary research on ichthyological behavior predominantly investigates underwater environments. However, the intricate nature of aquatic ecosystems often hampers subaqueous observations of fish behavior due to interference. Transitioning the obs...
Integration of SPEI and machine learning for assessing the characteristics of drought in the middle ganga plain, an agro-climatic region of India.
Environmental science and pollution research international
Oct 29, 2024
Drought, as a natural and intricate climatic phenomenon, poses challenges with implications for both natural ecosystems and socioeconomic conditions. Evaluating the characteristics of drought is a significant endeavor aimed at mitigating its impact o...
Can artificial intelligence improve enterprise environmental performance: Evidence from China.
Journal of environmental management
Oct 28, 2024
Artificial intelligence needs to be embraced urgently by enterprises as a means to achieve green development and address the efficiency quagmire in the context of green, low-carbon and sustainable development. To estimate a corporation's pioneering p...
Hypoxia extreme events in a changing climate: Machine learning methods and deterministic simulations for future scenarios development in the Venice Lagoon.
Marine pollution bulletin
Oct 3, 2024
Climate change pressures include the dissolved oxygen decline that in lagoon ecosystems can lead to hypoxia, i.e. low dissolved oxygen concentrations, which have consequences to ecosystem functioning including biogeochemical cycling from mild to seve...
Understanding the mechanism of microplastic-associated antibiotic resistance genes in aquatic ecosystems: Insights from metagenomic analyses and machine learning.
Water research
Oct 2, 2024
The pervasive presence of microplastics (MPs) in aquatic systems facilitates the transmission of antibiotic resistance genes (ARGs), thereby posing risks to ecosystems and human well-being. However, owing to variations in environmental backgrounds an...
Machine learning algorithms for the evaluation of risk by tick-borne pathogens in Europe.
Annals of medicine
Sep 30, 2024
BACKGROUND: Tick-borne pathogens pose a major threat to human health worldwide. Understanding the epidemiology of tick-borne diseases to reduce their impact on human health requires models covering large geographic areas and considering both the abio...
Leveraging machine learning algorithms in dynamic modeling of urban expansion, surface heat islands, and carbon storage for sustainable environmental management in coastal ecosystems.
Journal of environmental management
Sep 20, 2024
Climate change and rapid urbanization are dramatically altering coastal ecosystems worldwide, with significant implications for land surface temperatures (LST) and carbon stock concentration (CSC). This study investigates the impacts of day and night...
Identifying the habitat suitability of Pteris vittata in China and associated key drivers using machine learning models.
The Science of the total environment
Sep 18, 2024
Pteris vittata (P. vittata) possesses significant potential in remediating arsenic (As) soil pollution. Understanding the habitat suitability of P. vittata in China and pinpointing the key drivers that influence its distribution can facilitate the id...
Comparison of conventional and machine learning regression models for accurate prediction of selected optical active components - A case study: The Gulf of Izmit.
Marine pollution bulletin
Sep 14, 2024
This study hypothesizes that advanced machine learning (ML) models can more accurately predict certain critical water quality parameters in marine environments compared to conventional regression techniques. We specifically evaluated the spatio-tempo...
Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region.
Scientific reports
Sep 8, 2024
This paper presents the design and development of a coastal fisheries monitoring system that harnesses artificial intelligence technologies. Application of the system across the Pacific region promises to revolutionize coastal fisheries management. T...
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