Zobrazeno 1 - 10
of 13
pro vyhledávání: '"John Grezmak"'
Autor:
John Grezmak, Kathryn A. Daltorio
Publikováno v:
Sensors, Vol 24, Iss 5, p 1579 (2024)
Shallow underwater environments around the world are contaminated with unexploded ordnances (UXOs). Current state-of-the-art methods for UXO detection and localization use remote sensing systems. Furthermore, human divers are often tasked with confir
Externí odkaz:
https://doaj.org/article/1ff1903989be4de2979becf1751dad9f
Autor:
Yifeng Gong, Ge Sun, Aditya Nair, Aditya Bidwai, Raghuram CS, John Grezmak, Guillaume Sartoretti, Kathryn A. Daltorio
Publikováno v:
Frontiers in Mechanical Engineering, Vol 9 (2023)
Legged robots can have a unique role in manipulating objects in dynamic, human-centric, or otherwise inaccessible environments. Although most legged robotics research to date typically focuses on traversing these challenging environments, many legged
Externí odkaz:
https://doaj.org/article/7eff03d57b354c05b2fab3e05f0b2fc9
Publikováno v:
IEEE Sensors Journal. 21:23308-23316
Characterization of terrain in real time allows autonomous legged robots to modify their gait to better suit their environment and recognize hazardous conditions. We present a novel approach for terrain classification for legged robots with passively
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f1249dfb8dd2ee5ac4284f99a6dd724
https://doi.org/10.1109/jsen.2021.3109864
https://doi.org/10.1109/jsen.2021.3109864
Publikováno v:
IEEE Sensors Journal. 20:3172-3181
As a state-of-the-art pattern recognition technique, convolutional neural networks (CNNs) have been increasingly investigated for machine fault diagnosis, due to their ability in analyzing nonlinear and nonstationary high-dimensional data that are ty
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66a70322dac03451f1becae97493b76d
https://doi.org/10.1109/jsen.2019.2958787
https://doi.org/10.1109/jsen.2019.2958787
Publikováno v:
Procedia Manufacturing. 43:511-518
Fault detection and diagnosis of induction motors in variable frequency drive (VFD) applications is essential for minimizing unexpected downtime, material waste and equipment damage, ultimately contributing to sustainable manufacturing. This paper pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d241294ed7acea2c2e9bbda8144e51bc
https://doi.org/10.1016/j.promfg.2020.02.181
https://doi.org/10.1016/j.promfg.2020.02.181
Publikováno v:
Procedia CIRP. 80:476-481
The rapid advancement of data analytics has opened up new opportunities for improving the life cycle of engineered products and enhancing sustainability by intelligent monitoring and fault diagnosis of the related manufacturing processes and systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46e89290edf2931a9ed916f616008b90
https://doi.org/10.1016/j.procir.2018.12.008
https://doi.org/10.1016/j.procir.2018.12.008
Publikováno v:
Physical Review B. 92
We have demonstrated coupling between a pair of ultrastrong light-matter coupled microcavities composed of neat glassy organic dye films between metallic (silver) mirrors at room temperature. Based upon our modified coupled oscillator model, we have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7e60bb53e5857bcf1cb5c3434fe5d44
https://doi.org/10.1103/physrevb.92.155301
https://doi.org/10.1103/physrevb.92.155301
Autor:
Grezmak, John1 (AUTHOR) john.grezmak@case.edu, Daltorio, Kathryn A.1 (AUTHOR)
Publikováno v:
Sensors (14248220). Mar2024, Vol. 24 Issue 5, p1579. 16p.
Coupling of exciton-polaritons in low-Q coupled microcavities beyond the rotating wave approximation
Publikováno v:
Scopus-Elsevier
We demonstrate coupling between two ultrastrong exciton-photon coupled low-Q organic microcavities at room temperature. We propose a modified coupled oscillator model to explain the broken degeneracy of Rabi splittings in the ultrastrong coupling reg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d1c53fce6dd810d93df1380af616787
http://www.scopus.com/inward/record.url?eid=2-s2.0-85010633358&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-85010633358&partnerID=MN8TOARS
Publikováno v:
IEEE Sensors Journal; Oct2021, Vol. 21 Issue 20, p23308-23316, 9p