Results 161 to 170 of about 753,715 (297)

Explainable AI with fine-tuned large language models for sustainable cultural heritage management. [PDF]

Sci Rep
Zhou K, Chen W, Sheng W, Hu B, Yang Y, Yang L, Lu H.   +6 more
europepmc   +1 more source

On implementation aspects of implicit MPM for 3D analysis.

, 2019
An implicit MPM program has been developed to model the 3D installation of screw piles for offshore wind turbine foundations as part of a UK EPSRC-funded project. The program is to be used to study the torque and vertical force requirements during installation of screw piles for different geometries and soil conditions, and has required the development
Wang, Lei, Cortis, Michael, Coombs, William M., Augarde, Charles, Brown, Michael, Knappett, Jonathan, Brennan, Andrew, Davidson, Craig, Richards, David, Blake, Anthony   +9 more
openaire   +1 more source

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Explicit Features Versus Implicit Spatial Relations in Geomorphometry: A Comparative Analysis for DEM Error Correction in Complex Geomorphological Regions. [PDF]

Sensors (Basel)
Zhou S, Xie M, Ju N, Feng C, Lin Q, Shu Z.   +5 more
europepmc   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

LM-SODP: Language Model Self-Optimizing Discrete Prompt for Aspect Based Sentiment Analysis. [PDF]

Entropy (Basel)
Bu K, Liu Y.
europepmc   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Explainable AI and echo state networks calibrate trust in human machine interaction. [PDF]

Sci Rep
Hao S, Teng F, Hou R, Zhang L, Wu H, Qi J.   +5 more
europepmc   +1 more source

“It Is Much Safer to Be Sparse than Connected”: Safe Control of Robotic Swarm Density Dynamics with PDE Optimization with State Constraints

Advanced Intelligent Systems, EarlyView.
This paper proposes a novel control framework to ensure safety of a robotic swarm. A feedback optimization controller is capable of driving the swarm toward a target density while keeping risk‐zone exposure below a safety threshold. Theory and experiments show how safety is more effectively achieved for sparsely connected swarms.
Longchen Niu, Gennaro Notomista
wiley   +1 more source

ATEdrug: A reliable human-in-the-loop annotation scheme for aspect term extraction and polarity detection in drug reviews. [PDF]

PLoS One
Ansari G, Saxena C, Sohail SS, Hussain Z, Sheikh A, Hussain A.   +5 more
europepmc   +1 more source