Zobrazeno 1 - 7
of 7
pro vyhledávání: '"K S Neethu"'
Publikováno v:
eXPRESS Polymer Letters, Vol 8, Iss 2, Pp 107-115 (2014)
In this paper, we are reporting a novel strategy for the preparation of conductive polyaniline-clay nanocomposite in Polyvinylchloride (PVC) matrix by admicellar emulsion polymerization using a low cost renewable resource based surfactant cum dopant.
Externí odkaz:
https://doaj.org/article/62fd67c188994d939984355aabc01cc1
Publikováno v:
Journal of Dental Research and Review, Vol 7, Iss 3, Pp 124-127 (2020)
Aim: To determine the prevalence of malocclusion in the district of Dakshina Kannada, India. Methodology: The study had a total of 3500 children within the age group of 8–14 years, and they were classified into four groups of normal occlusion, Angl
Publikováno v:
Journal of Materials Chemistry A. 5:16636-16645
Self-assembled polyaniline nanowires stippled graphene nanocomposites (PGPCs) were prepared by in situ polymerisation of aniline in the presence of 3-pentadecylphenyl phosphate (3-PDPP) modified graphene sheets. 3-PDPP is an amphiphilic dopant derive
Autor:
Dany Varghese, K. S. Neethu
Publikováno v:
2017 International Conference on Communication and Signal Processing (ICCSP).
The general focus of domain adaptation methodology is transferring learned knowledge from labeled train domain to unlabeled test domain. Domain adaptation tries to minimize the domain shift problem by modeling a classifier using labeled training doma
Autor:
C. K. Chandrakanth, Rajaraman Ramakrishnan, S. Sivakala, J. D. Sudha, K. S. Neethu, K. N. Rohini
Publikováno v:
eXPRESS Polymer Letters, Vol 8, Iss 2, Pp 107-115 (2014)
In this paper, we are reporting a novel strategy for the preparation of conductive polyaniline-clay nanocomposite in Polyvinylchloride (PVC) matrix by admicellar emulsion polymerization using a low cost renewable resource based sur- factant cum dopan
Publikováno v:
2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT).
Classification systems adapts many machine learning techniques for quality performance in data classification. The neural networks has some unique characteristics and features which can handle high dimensional features and documents with noise and co
Publikováno v:
Journal of Dental Research and Reviews; September 2020, Vol. 7 Issue: 3 p124-127, 4p