Zobrazeno 1 - 10
of 31
pro vyhledávání: '"K. Chellamuthu"'
Autor:
V. Vijayan, T. Sathish, R. Saravanan, Kuldeep Kumar, Ganesh K. Jadhav, V. Sharun, R. Elangovan, K. Chellamuthu, Mandeep Singh, Aklilu Teklemariam
Publikováno v:
Advances in Materials Science and Engineering, Vol 2023 (2023)
This research aims to increase the utility of globally and abundantly available waste natural fibres of Gallus-Gallus fibres coir waste from mattress and car seat manufacturing factories. The composite samples were prepared with a rally round of poly
Externí odkaz:
https://doaj.org/article/221cc716598348d6be9095b2c98d26b7
Autor:
N. Parthipan, G. Navaneethakrishnan, K. Chellamuthu, A. Thirukumaran, L. Vigneshwaran, K.R. Arvindha karthik
Publikováno v:
Materials Today: Proceedings. 69:674-678
Publikováno v:
Materials Today: Proceedings. 69:821-826
Publikováno v:
Materials Today: Proceedings. 69:1213-1217
Publikováno v:
Materials Today: Proceedings. 69:962-966
Publikováno v:
Mathematics, Vol 7, Iss 10, p 910 (2019)
The generalized monotone iterative technique for sequential 2 q order Caputo fractional boundary value problems, which is sequential of order q, with mixed boundary conditions have been developed in our earlier paper. We used Green’s function repre
Externí odkaz:
https://doaj.org/article/42c836bdf9df4d21adc0b16cae0e4e58
Autor:
K. Chellamuthu, A. Vasanthanathan
Publikováno v:
Materials Today: Proceedings. 47:7030-7034
Utilization of polymers, particularly Fiber Reinforced Plastics (FRP) offers a few benefits to accomplish powerful and solid constructions which is more significant for current natural circumstance. In this present investigations, the impact energy c
Publikováno v:
Journal of Emerging Sport Studies.
Critical Commentary
Autor:
A. Vasanthanathan, K. Chellamuthu
Publikováno v:
Materials Today: Proceedings. 21:658-662
Upgraded engineering materials were increased day to day. High performance and lightweight composite materials were required for different sectors. Through literature survey it was found that high strength to weight ratio were obtained through fiber
Autor:
Vinodh K. Chellamuthu, Cesar Vasquez
Publikováno v:
Curiosity: Interdisciplinary Journal of Research and Innovation. 2
Support vector learning machines are supervised models that analyze data for classification analysis. However, with modifications these models can be extended for regression estimation. In this paper, we use Dean De Cock’s Iowa house price dataset,