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Institution

Jadavpur University

EducationKolkata, India
About: Jadavpur University is a education organization based out in Kolkata, India. It is known for research contribution in the topics: Population & Schiff base. The organization has 10856 authors who have published 27678 publications receiving 422069 citations. The organization is also known as: JU & Jadabpur University.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a singularity free solution of Einstein's field equations for compact stellar objects, precisely strange (quark) stars, was found, considering Schwarzschild metric as the exterior spacetime.

97 citations

Journal ArticleDOI
TL;DR: In this paper, the dark energy models with variable equation of state parameter ω are investigated by using law of variation of Hubble's parameter that yields the constant value of deceleration parameter.
Abstract: The dark energy models with variable equation of state parameter ω are investigated by using law of variation of Hubble’s parameter that yields the constant value of deceleration parameter. Here the equation of state parameter ω is found to be time dependent and its existing range for this model is consistent with the recent observations of SN Ia data, SN Ia data (with CMBR anisotropy) and galaxy clustering statistics. The physical significance of the dark energy models have also been discussed.

96 citations

Journal ArticleDOI
TL;DR: In the Chhotanagpur Gneissic Complex (CGC) as mentioned in this paper, three deformation events were identified (D1, D2 and D3) in granulite facies gneisses that were intruded by anorthosites and expansive granites.

96 citations

Journal ArticleDOI
TL;DR: In this article, the authors investigated desulfurization and hydrogenation of aromatics in diesel oil in an isothermally operated trickle-bed reactor with a 19mm ID, using commercial bifunctional NiMo/Al2O3 catalysts.
Abstract: Desulfurization and hydrogenation of aromatics in diesel oil were investigated in an isothermally operated trickle-bed reactor 500 mm long and with a 19-mm ID, using commercial bifunctional NiMo/Al2O3 catalysts. The operating temperature, pressure, liquid hourly space velocity, gas/oil ratio, and the initial concentration of H2S were 300–380°C, 2–8 MPa, 1–4 h−1, 100–500 m3(NTP)/m3 and 0–8 vol %, respectively. The increase in pressure and decrease in liquid hourly space velocity lead to deeper desulfurization and hydrogenation of both aromatics. Although a higher gas-to-oil ratio and lower initial concentration of H2S enhance the desulfurization reaction, these parameters play almost no role for hydrogenation. Desulfurization increases sharply with increased temperature, but with the same change in temperature the conversion of aromatics increases only up to 360°C, above which it falls sharply. This behavior is explained by the approaching of chemical equilibria by the reversible hydrogenation reactions of the aromatics at higher temperatures. A mechanistic mathematical model was developed for a two-phase flow reactor, considering both mass transfer and chemical reaction in the reactor. The kinetic equations for desulfurization and for the hydrogenation of mono-, di- and polyaromatics were established. Simulated results are compared satisfactorily with the experimental observations.

96 citations

Proceedings ArticleDOI
01 Dec 2011
TL;DR: Experiments reveal that the proposed optimization scheme outperforms two well-known algorithms with respect to standard metrics, called average total path deviation and average uncovered target distance.
Abstract: Path-planning is an interesting problem in mobile robotics. This paper proposes an alternative approach to path-planning of mobile robots using the artificial bee colony (ABC) optimization algorithm. The problem undertaken here attempts to determine the trajectory of motion of the robots from predefined starting positions to fixed goal positions in the world map with an ultimate objective to minimize the path length of all the robots. A local trajectory planning scheme has been developed with ABC optimization algorithm to optimally obtain the next positions of all the robots in the world map from their current positions, so that the paths to be developed locally for n-robots are sufficiently small with minimum spacing with the obstacles, if any, in the world map. Experiments reveal that the proposed optimization scheme outperforms two well-known algorithms with respect to standard metrics, called average total path deviation and average uncovered target distance.

96 citations


Authors

Showing all 10999 results

NameH-indexPapersCitations
Subir Sarkar1491542144614
Amartya Sen149689141907
Susumu Kitagawa12580969594
Praveen Kumar88133935718
Rodolphe Clérac7850622604
Rajesh Gupta7893624158
Santanu Bhattacharya6740014039
Swagatam Das6437019153
Anupam Bishayee6223711589
Michael G. B. Drew61131524747
Soujanya Poria5717513352
Madeleine Helliwell543709898
Tapas Kumar Maji542539804
Pulok K. Mukherjee5429610873
Dipankar Chakraborti5411512078
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202385
2022332
20211,949
20201,936
20191,737
20181,807