Zobrazeno 1 - 10
of 4 655
pro vyhledávání: '"Kumari R"'
Publikováno v:
Journal of Medical and Scientific Research, Vol 11, Iss 2, Pp 96-103 (2023)
Background: Depression is among the most common mental health problems among people with chronic complications like type 2 diabetes mellitus is brought on by flaws in insulin secretion and activity; however, genetic factors also play a role in both i
Externí odkaz:
https://doaj.org/article/d625aee9daf64920a7bd465d210a2ca2
Autor:
Sand Tangri, Kumari R.
Publikováno v:
BIO Web of Conferences, Vol 86, p 01018 (2024)
A major class of water pollutants emerging as a threat to human health, particularly women's health, is Per-and-poly-fluoroalkyl substances (PFAS). PFAS belongs to a group of fluorine-containing frequently used synthetic chemicals in consumers and pr
Externí odkaz:
https://doaj.org/article/6ffd54c6c8cf4689adb1852b63ab1a16
Publikováno v:
Indian Journal of Gerontology. 2024, Vol. 38 Issue 3, p326-336. 11p.
Autor:
Awere, Collince Omondi, Sneha, Anbalagan, Rakkammal, Kasinathan, Muthui, Martin Mwaura, Kumari R, Anitha, Govindan, Suresh, Batur Çolak, Andaç, Bayrak, Mustafa, Muthuramalingam, Pandiyan, Anadebe, Valentine Chikaodili, Archana, Pandi, Sekar, Chinnathambi, Ramesh, Manikandan
Publikováno v:
In Plant Physiology and Biochemistry November 2024 216
Autor:
Divya, R., Shantha Selva Kumari, R.
Publikováno v:
In Brain Research 1 November 2024 1842
Publikováno v:
In Clinical Epidemiology and Global Health July-August 2024 28
Autor:
Awere, Collince Omondi, Rakkammal, Kasinathan, Ram, P.S. Jeevan, Kumar, K. Pavan, Ragavan, Kaliraj, Anitha Kumari, R., Govindan, Suresh, Kher, Mafatlal M., Drori, Elyashiv, Ramesh, Manikandan
Publikováno v:
In Industrial Crops & Products July 2024 213
Publikováno v:
In Sustainable Cities and Society February 2024 101
Publikováno v:
Journal of Sensors,Volume 2021, Article ID 6625421
Fabric defect detection is a crucial quality control step in the textile manufacturing industry. In this article, machine vision system based on the Sylvester Matrix Based Similarity Method (SMBSM) is proposed to automate the defect detection process
Externí odkaz:
http://arxiv.org/abs/2012.05800
Akademický článek
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