Results 301 to 310 of about 6,488,772 (380)
This study analyzed log data from the Japanese hinotori surgical robot to characterize manipulation performed by experienced surgeons in robotic surgery. Compared with less‐experienced surgeons, the experienced group demonstrated shorter task durations, reduced travel distances with the right instrument (Arm3), faster and more dynamically modulated ...
Masaki Saito +11 more
wiley +1 more source
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob +2 more
wiley +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source
Language improvement schemes in teacher training programmes as seen by teachers and teacher trainers
Jan Rusiecki
openalex +1 more source
Integrating AI and IoT into STEM teacher training: A case study of secondary education in Vietnam
Huy Le Thanh +6 more
openalex +2 more sources

