Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Aniket, M."'
Publikováno v:
Journal of Krishna Institute of Medical Sciences University, Vol 13, Iss 2, Pp 31-43 (2024)
Background: The shoulder pain etiology is diverse and many disorders present with similar symptoms and signs. Magnetic Resonance Imaging (MRI) provides good multiplanar delineation even without contrast and absence of radiation hazards. Aim and Objec
Externí odkaz:
https://doaj.org/article/a82b6bfb47b34c1a9057a3935dc53c46
Publikováno v:
In Innovative Food Science and Emerging Technologies May 2024 93
Publikováno v:
Journal of Krishna Institute of Medical Sciences (JKIMSU). Apr-Jun2024, Vol. 13 Issue 2, p31-43. 13p.
Akademický článek
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Autor:
Swaraj, Aniket M., Suresh, Shanti
Publikováno v:
Library of Progress-Library Science, Information Technology & Computer; Jul-Dec2024, Vol. 44 Issue 3, p4411-4417, 7p
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-14 (2020)
Abstract We demonstrate a novel technique to achieve highly surface active, functional, and tunable hierarchical porous coated surfaces with high wickability using a combination of ball milling, salt-templating, and sintering techniques. Specifically
Externí odkaz:
https://doaj.org/article/feff6c58b7834586a031dc0764cf7425
Publikováno v:
In International Journal of Heat and Mass Transfer April 2019 132:462-472
Publikováno v:
Frontiers in Mechanical Engineering, Vol 7 (2021)
In this work, we present an exceptionally high heat transfer coefficient (HTC) and critical heat flux (CHF) achieved by graphene nanoplatelets (GNPs) and copper composite coatings with tunable surface properties. These coatings were created by a comb
Externí odkaz:
https://doaj.org/article/2d3163936cdd4969aa8a1d366d3ed1ca
Publikováno v:
In Applied Thermal Engineering 25 July 2018 140:406-414
Autor:
Prof. Ravirai Chaudhary, Aniket M. Wazarkar, Shubham A. Patil, Nikhil S. Pokale, Prathamesh V. Mali
Publikováno v:
International Journal for Research in Applied Science and Engineering Technology. 10:920-923
We examine opinion mining using supervised learning techniques to discover the sentiment of student inputs supported by labeled teaching and learning decisions. The exams conducted included undergraduate input data collected from VR Siddhartha Engine
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b82d274c284ded0d2d414ff14c1989d
https://doi.org/10.22214/ijraset.2022.47479
https://doi.org/10.22214/ijraset.2022.47479