Results 151 to 160 of about 120,804 (272)

AI‐driven circular economy optimization in waste management: A review of current evidence

open access: yesEnvironmental Progress &Sustainable Energy, EarlyView.
Abstract The integration of artificial intelligence (AI) and machine learning (ML) in waste management has the potential to significantly advance circular economy objectives by enhancing efficiency, reducing waste, and optimizing resource recovery. However, realising these benefits depends on addressing significant technical, economic, and systemic ...
David Bamidele Olawade   +3 more
wiley   +1 more source

Digital Rights Activism in Multilevel Governance

open access: yesEuropean Policy Analysis, EarlyView.
ABSTRACT Multilevel governance (MLG) without a clear hierarchical structure can create power imbalances among various actors, particularly in settings with overlapping jurisdictions and policy areas. This dynamic is especially pronounced in Internet governance, which faces a complex interplay of domestic laws, state interdependence, and heightened ...
Alison Harcourt
wiley   +1 more source

Identification of fraudulent products using blockchain technology

open access: green
Adediran, Oluwaseyi Segun   +5 more
openalex   +1 more source

Energy Storage System in Microgrids: Challenges and Opportunities

open access: yesEnergy Science &Engineering, EarlyView.
Hybrid integration of multiple Energy Storage Systems (ESSs) within renewable‐powered microgrids enhances reliability, flexibility, and economic sustainability. Lithium‐ion batteries, flow batteries, hydrogen storage, and thermal systems complement each other through coordinated control via Energy Management Systems.
Mohamed G. Moh Almihat, Josiah L. Munda
wiley   +1 more source

Comparison of recent blockchain frameworks in healthcare.

open access: green
Lulu Hao (10576560)   +5 more
openalex   +1 more source

Performance Monitoring of Photovoltaic Modules Using Machine‐Learning‐Based Solutions: A Survey of Current Trends

open access: yesEnergy Science &Engineering, EarlyView.
The graphical abstract presents the concept of applying machine‐learning algorithms to assess the performance of photovoltaic modules. Data from solar panels are fed to surrogates of intelligent models, to assess the following performance metrics: identifying faults, quantifying energy production and trend degradation over time. The combination of data
Nangamso Nathaniel Nyangiwe   +3 more
wiley   +1 more source

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