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pro vyhledávání: '"Turner Kevin"'
Mechanical metamaterials utilize geometry to achieve exceptional mechanical properties, including those not typically possible for traditional materials. To achieve these properties, it is necessary to identify the proper structures and geometries, w
Externí odkaz:
http://arxiv.org/abs/2410.07213
Mechanical metamaterials with engineered failure properties typically rely on periodic unit cell geometries or bespoke microstructures to achieve their unique properties. We demonstrate that intelligent use of disorder in metamaterials leads to distr
Externí odkaz:
http://arxiv.org/abs/2407.07223
The heterogeneous micromechanical properties of biological tissues have profound implications across diverse medical and engineering domains. However, identifying full-field heterogeneous elastic properties of soft materials using traditional enginee
Externí odkaz:
http://arxiv.org/abs/2402.10741
Autor:
Dillavou, Sam, Hanlan, Jesse M., Chieco, Anthony T., Xiao, Hongyi, Fulco, Sage, Turner, Kevin T., Durian, Douglas J.
The conversion of raw images into quantifiable data can be a major hurdle in experimental research, and typically involves identifying region(s) of interest, a process known as segmentation. Machine learning tools for image segmentation are often spe
Externí odkaz:
http://arxiv.org/abs/2309.00058
Material identification is critical for understanding the relationship between mechanical properties and the associated mechanical functions. However, material identification is a challenging task, especially when the characteristic of the material i
Externí odkaz:
http://arxiv.org/abs/2211.15423
Publikováno v:
In Surgical Clinics of North America October 2024 104(5):1083-1093
Autor:
Turner, Kevin M., Patel, Sameer H.
Publikováno v:
In Surgical Clinics of North America October 2024 104(5):951-964