Zobrazeno 1 - 10
of 17
pro vyhledávání: '"S. K. Pani"'
Publikováno v:
Atmospheric Chemistry and Physics, Vol 23, Pp 4727-4740 (2023)
Dry conditions associated with the El Niño–Southern Oscillation (ENSO) and a positive Indian Ocean Dipole (IOD) are known to have caused major fire pollution events and intense carbon emissions over a vast spatial expanse of Indonesia in October 2
Externí odkaz:
https://doaj.org/article/4315c424de2046d4883a16111843743b
Autor:
M. C.-G. Ooi, M.-T. Chuang, J. S. Fu, S. S. Kong, W.-S. Huang, S.-H. Wang, S. Pimonsree, A. Chan, S. K. Pani, N.-H. Lin
Publikováno v:
Atmospheric Chemistry and Physics, Vol 21, Pp 12521-12541 (2021)
Plumes from the boreal spring biomass burning (BB) in northern peninsular Southeast Asia (nPSEA) are lifted into the subtropical jet stream and transported and deposited across nPSEA, South China, Taiwan and even the western North Pacific Ocean. This
Externí odkaz:
https://doaj.org/article/e28e079cf061425284def6fad3efe210
Publikováno v:
Atmospheric Chemistry and Physics, Vol 21, Pp 5533-5547 (2021)
A weak El Niño during 2014–2015 boreal winter developed as a strong boreal summer event in 2015 which continued and even enhanced during the following winter. In this work, the detailed changes in the structure, dynamics, and trace gases within th
Externí odkaz:
https://doaj.org/article/03d63ba9a8f84193a97bda02fbf8cb87
Publikováno v:
Materials Research Letters, Vol 8, Iss 4, Pp 151-157 (2020)
The opportunities for wrought magnesium products in a wide range of structural and functional materials for transportation, energy generation, energy storage and propulsion are increasing due to their light-weighting benefits, high specific strength
Externí odkaz:
https://doaj.org/article/11e2dd0901ce46c0bb9c322da28403f3
Autor:
O. A. Lytvynenko, S. K. Panishko
Publikováno v:
Odessa Astronomical Publications, Vol 33, Iss 0, Pp 72-74 (2020)
Effect of scintillations arises in the result of interaction of radio signal from the cosmic radio source with irregularities of ionosphere plasma which appears at the registration of observations as amplitude fluctuations. Wherein fluctuations of th
Externí odkaz:
https://doaj.org/article/78ab8e3156da4624b151311f48d6d912
Autor:
S. K. Panishko, O. A. Lytvynenko
Publikováno v:
Radio Physics and Radio Astronomy, Vol 24, Iss 1, Pp 44-54 (2019)
Purpose: With relation to radio astronomy, ionospheric scintillation of discrete cosmic radio sources is an undesirable effect. At the same time, ionospheric scintillations carry information on the ionospheric turbulence and are a separate object of
Externí odkaz:
https://doaj.org/article/39ecc4d4491a49a9bfb9a3d0f91974a2
Autor:
O. A. Lytvynenko, S. K. Panishko
Publikováno v:
Radio Physics and Radio Astronomy, Vol 22, Iss 4, Pp 304-309 (2017)
Purpose: Variations of ionospheric scintillation index of the power cosmic radio sources (3С144, 3С274, 3С405, and 3С461) observed for the year-to-day time intervals with the radio telescope at the decameter wavelengths are analyzed. Design/me
Externí odkaz:
https://doaj.org/article/4a798f47c63a4d88a69f1e6253a0036c
Publikováno v:
Radio Physics and Radio Astronomy, Vol 22, Iss 4, Pp 294-303 (2017)
Purpose: Investigation of the effects of the influence of solar and geomagnetic activity on the state of the Earth’s upper atmosphere by the method of “transmission through” it with the radiation of cosmic radio sources. Design/Methodology/a
Externí odkaz:
https://doaj.org/article/23ade96b9a524a918659c0187caf83eb
Autor:
Sunil Tyagi, S. K. Panigrahi
Publikováno v:
Applied Artificial Intelligence, Vol 31, Iss 7-8, Pp 593-612 (2017)
An Artificial Neural Network (ANN) classifier trained by a hybrid GA-BP method for diagnosis of gear faults is presented here that can be incorporated in an online fault diagnostic system of vital gearboxes. The distinctive features obtained from vib
Externí odkaz:
https://doaj.org/article/3e56afbc8cbe4393902f2e8331693662
Autor:
Sunil Tyagi, S. K. Panigrahi
Publikováno v:
Journal of Applied and Computational Mechanics, Vol 3, Iss 1, Pp 80-91 (2017)
A classification technique using Support Vector Machine (SVM) classifier for detection of rolling element bearing fault is presented here. The SVM was fed from features that were extracted from of vibration signals obtained from experimental setup co
Externí odkaz:
https://doaj.org/article/143eab07a77c43babbbb6f2757b43841