A new machine learning framework designed to detect malicious interference in unmanned aerial vehicles (UAVs), commonly known as drones, has shown strong performance in identifying both sudden and ...
Abstract: Illicit activities and coordinated manipulations in the Non-Fungible Tokens (NFT) market remain significant concerns, driven by the pseudonymous and publicly transparent nature of blockchain ...
The research “Detecting Financial Fraud in Real-Time Transactions Using Graph Neural Networks and Anomaly Detection Techniques” presents an AI-driven system for real-time fraud detection in digital ...
Sleep Cycle and CMU's Delphi Group have announced a research collaboration focused on understanding how privacy-preserved data and sleep-based signals, such as nighttime cough patterns, may complement ...
Abstract: Unsupervised cross-sensor change detection (CSCD) is a significant yet challenging task in remote sensing, primarily due to substantial domain shifts across heterogeneous images and the ...
We have compared the four temporal modes of the gravity field with the six temporal modes of the magnetic field one by one. The main principal components of the core magnetic and gravity signals ...
Cell cycle progression in Sulfolobales. The depicted lengths of the cell cycle phases are not proportional to their actual duration. The regulatory checkpoint described by Parham et al. (2) is ...
Chinese researchers have successfully predicted lithium metal anode failures with the help of a predictive model. The tool uses electrochemical data from the initial cycles of lithium metal batteries ...
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