Results 211 to 220 of about 3,481,136 (300)

Deep learning for robust orbit control of Elettra 2.0 storage ring. [PDF]

Sci Rep
Yazdani MS, Masoudi SF, Rahighi J, Dastan S.   +3 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
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

Some novel optical pulses in hydrodynamical nonlinear complex equation using M-truncated fractional derivative. [PDF]

Sci Rep
Ilhan E, Rehman SU, Bilal M, Baskonus HM, Alawaideh YM.   +4 more
europepmc   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

A wideband coaxial-to-waveguide transition devised with topology optimization. [PDF]

Sci Rep
Hossain MS, Lehr JM, Fierro A, Schamiloglu E.   +3 more
europepmc   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
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, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Exploiting Polynomial Chaos Expansion for Rapid Assessment of the Impact of Tissue Property Uncertainties in Low-Intensity Focused Ultrasound Stimulation. [PDF]

Bioelectromagnetics
Sumser K, Mestrom R, Tuysuz YE, Paulides MM.   +3 more
europepmc   +1 more source

Applied Computational Electromagnetics [PDF]

, 2000
openaire   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Cole-Cole Model for the Dielectric Characterization of Healthy Skin and Basal Cell Carcinoma at THz Frequencies. [PDF]

IEEE Open J Eng Med Biol
Mattana E, Lodi MB, Simone M, Mazzarella G, Fanti A.   +4 more
europepmc   +1 more source