The incorporation of physical information in machine learning frameworks is opening and
transforming many application domains. Here the learning process is augmented through …

In recent decades, 3D bioprinting has garnered significant research attention due to its
ability to manipulate biomaterials and cells to create complex structures precisely. However …

Guided wave propagation (GWP) is commonly employed for the design of SHM systems.
However, GWP is sensitive to variations in the material properties, often leading to false …

The principle of electrohydrodynamics (EHD) processes relies on manipulating fluids using
electric forces. The advantage of EHD over other fluid manipulation approaches, such as …

Melt electrowriting (MEW) is an emerging high-resolution 3D printing technology used in
biomedical engineering, regenerative medicine, and soft robotics. Its transition from …

Generalization remains a significant challenge in the application of deep learning methods,
particularly in predicting mooring line tension for moored floating structures. The dynamic …

Electrohydrodynamic (EHD) printing has been used in various applications (eg, sensors,
batteries, photonic crystals). Currently, research on studying the relationships between EHD …

Direct printing methods are widely recognized as efficient techniques for manufacturing
printed electronics. However, several challenges arise when printing on nonplanar surfaces …

Bayesian optimization is a stochastic, global black-box optimization algorithm. By combining
Machine Learning with decision-making, the algorithm can optimally utilize information …

Melt electrowriting (MEW) is an emerging high-resolution 3D printing technology applied in
many fields including biomedical engineering, regenerative medicine, and soft robotics. The …