A new study by Justin Grandinetti of the University of North Carolina at Charlotte challenges one of the most dominant narratives in artificial intelligence: that modern AI systems are inherently ...
Automated decision making is basically when computers make choices on their own, using data and rules instead of a person.
Explore how AI in high-throughput screening improves drug discovery through advanced data analysis, hit identification and ...
Researchers have developed a hybrid surrogate model for iso-octanol oxidation to iso-octanal that integrates data-driven approaches with chemical equations grounded in mass transfer, heat transfer, ...
Abstract: This study focuses on improving the precision and global search capabilities of the Harris Hawk Optimization algorithm when dealing with debris flow disasters. The enhanced algorithm, called ...
In this episode of eSpeaks, Jennifer Margles, Director of Product Management at BMC Software, discusses the transition from traditional job scheduling to the era of the autonomous enterprise. eSpeaks’ ...
Abstract: Urban traffic congestion remains a critical challenge for smart city development, necessitating innovative approaches to improve traffic flow and reduce delays. This study presents a novel ...
Background Current automatic software uses a fixed apparent diffusion coefficient (ADC) threshold (≤620×10⁻⁶ mm²/s) to ...
This paper presents the application of the unscented Kalman filter (UKF) for estimating the dynamic states of a maneuvering tank using a second-order Gauss-Markov process model. The proposed method is ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results