Zobrazeno 1 - 10
of 238
pro vyhledávání: '"S K RAY"'
Autor:
L K BAISHYA, NINGSHIYANGERLA WALLING, TEMJENNA JAMIR, S K RAY, MANOJ KUMAR, CHRISTY SANGMA, D J RAJKHOWA
Publikováno v:
The Indian Journal of Agricultural Sciences, Vol 92, Iss 2 (2022)
A field experiment was conducted in shifting cultivated lands of Nagaland (Wokha and Longleng) during pre-kharif season of 2017 and 2018. Experimental results revealed that combined application of organic manure with bio-fertilizer and micro-dosing o
Externí odkaz:
https://doaj.org/article/28eebbf7fce745f8ac1eb8354e570a70
Autor:
RAKESH KUMAR, M K PATRA, A THIRUGNANAVEL, BIDYUT C DEKA, DIBYENDU CHATTERJEE, T R BORAH, G RAJESHA, H D TALANG, S K RAY, MANOJ KUMAR, PRAVIN KUMAR UPADHYAY
Publikováno v:
The Indian Journal of Agricultural Sciences, Vol 88, Iss 11 (2018)
Integrated farming system (IFS) ensures efficient utilization of available farm resources, increases unit productivity and income that are pre-requisite for sustainable livelihood of small and marginal farmers. The present study was conducted to eval
Externí odkaz:
https://doaj.org/article/7900eb086f0b45968b7b90bb4c9d6a6a
Publikováno v:
Environment Conservation Journal, Vol 22, Iss 3 (2021)
Assessment of organic carbon fractions in soil provides the basis to ascertain vulnerability of an ecosystem to climate change. In the present study, we assessed SOC fractions in four pedons under contrasting landforms i.e., denudational low hill, up
Externí odkaz:
https://doaj.org/article/571bf59a6fbe476698be320859a330aa
Publikováno v:
Mining, Metallurgy & Exploration. 39:1429-1443
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::421395cb764c809ac66f335c8828c4f3
https://doi.org/10.1007/s42461-022-00639-4
https://doi.org/10.1007/s42461-022-00639-4
Publikováno v:
Journal of the Indian Society of Remote Sensing. 50:1915-1930
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24f28771f299fafc01d74ec2c8d06d56
https://doi.org/10.1007/s12524-022-01579-8
https://doi.org/10.1007/s12524-022-01579-8
Autor:
S. K. Ray
Publikováno v:
International Journal of Environmental Science and Technology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::293b76f0175b6fd3fb9fe407ccb3e33f
https://doi.org/10.1007/s13762-023-04923-8
https://doi.org/10.1007/s13762-023-04923-8
Publikováno v:
Journal of the Geological Society of India. 98:402-410
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4111ab09ac29bfbdbd1fff0a5966d6fc
https://doi.org/10.1007/s12594-022-1992-3
https://doi.org/10.1007/s12594-022-1992-3
Autor:
S. K. Ray, Prasanjit Dey, Chandan Kumar, D. Pandit, G.M. Prasad, S.K. Chaulya, S. K. Mandal, K. Saurabh
Publikováno v:
Soft Computing. 25:14183-14207
A deep learning network is introduced to predict concentrations of gases in the underground coal mine enclosed region using various IoT-enabled gas sensors installed in a metallic gas chamber. The air is sucked automatically at specific intervals fro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5685d7efc0f6c1fbde12ff593698ac33
https://doi.org/10.1007/s00500-021-06261-8
https://doi.org/10.1007/s00500-021-06261-8
Autor:
Asfar Mobin Khan, Somu Mondal, N.K. Mohalik, Jai Krishna Pandey, S. K. Ray, Debashish Mishra, R.V.K. Singh
Publikováno v:
International Journal of Coal Preparation and Utilization. 42:3173-3184
Spontaneous combustion of coal in stockpiles of power plants has a significant problem worldwide which leads to several health hazards, environmental pollution and coal loss. Spontaneous combustion...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0aa344ea643ec37a26fe75616f36cc39
https://doi.org/10.1080/19392699.2021.1964489
https://doi.org/10.1080/19392699.2021.1964489
Autor:
Chandan Kumar, Prasanjit Dey, S. K. Ray, Vikash Kisku, G.M. Prasad, K. Kumari, Dewangshu Pandit, S.K. Chaulya, Sreelekha Mishra
Publikováno v:
Process Safety and Environmental Protection. 146:837-852
A uniform manifold approximation and projection (UMAP) and long short-term memory (LSTM) deep learning model have been proposed to forecast a sealed-off area's fire status in underground coal mines. It protects miners' life by providing early warning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80d0ea6fe8768d4a6ad525ea7f71c167
https://doi.org/10.1016/j.psep.2020.12.019
https://doi.org/10.1016/j.psep.2020.12.019