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Institution

Birla Institute of Technology, Mesra

EducationRanchi, India
About: Birla Institute of Technology, Mesra is a education organization based out in Ranchi, India. It is known for research contribution in the topics: Dielectric & Microstrip antenna. The organization has 2801 authors who have published 4789 publications receiving 52426 citations. The organization is also known as: BIT.


Papers
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Journal ArticleDOI
TL;DR: This review describes the abiotic and biotic stresses and current developing methods for the acclimatization of microshoots, focused on the control of both physical and chemical environment and biohardening of micropropagated plantlets.
Abstract: The ultimate success of micropropagation on a commercial scale depends on the ability to transfer plants out of culture on a large scale, at low cost and with high survival rates. During field transfer the in vitro grown plantlets are unable to compete with soil microbes and to cope with the environmental conditions. The in vitro culture conditions result in the plantlets with altered morphology, anatomy and physiology. In order to increase growth and reduce mortality in plantlets at the acclimatisation stage, efforts are focused on the control of both physical and chemical environment and biohardening of micropropagated plantlets. This review describes the abiotic and biotic stresses and current developing methods for the acclimatization of microshoots.

277 citations

Journal ArticleDOI
TL;DR: The present manuscript to the best of the authors' knowledge is the first compilation on synthesis and medicinal aspects including structure-activity relationships of benzimidazole reported to date.

277 citations

Journal ArticleDOI
TL;DR: In this article, the formation of PANI/Agnanocomposite was characterized by UV-vis spectroscopy, energy dispersion X-ray (EDX) and transmis-sion electron microscopy (TEM).
Abstract: Polyaniline/silver (PANI/Ag) nanocomposites were prepared by in-situ oxidative polymerization of ani-line monomer in the presence of different concentrations of Ag nanoparticles. The formation of PANI/Agnanocomposite was characterized by UV–vis spectroscopy, energy dispersion X-ray (EDX) and transmis-sion electron microscopy (TEM). TEM images showed that the particle size increased with increasing Agconcentrationinthecomposite,owingtotheaggregationeffect.TheACconductivityanddielectricprop-erties of pure PANI and PANI/Ag nanocomposites were measured in the frequency range of 10 3 –10 6 Hz.Higherconductivity,dielectricconstantanddielectriclossofPANI/AgnanocompositesthanthoseofpurePANIwereobserved.TheconductivityofthenanocompositesincreasedwithincreasingAgconcentration.The gas-responses of the PANI/Ag nanocomposite towards low concentrations of ethanol was examinedand compared with that of the pure PANI. The nanocomposite was found to possess superior ethanolsensing capacity compared to pure PANI and it showed linear relationship between the responses andthe ethanol and/or Ag concentration. The Fourier transform infrared (FT-IR) spectroscopy was used toexplain the sensing mechanism.© 2009 Elsevier B.V. All rights reserved.

275 citations

Journal ArticleDOI
01 Dec 2010-Energy
TL;DR: In this paper, the performance analysis of a waste heat recovery system based on organic rankine cycle, using R-12, R-123 and R-134a as working fluids for power generation have been studied.

264 citations

Journal ArticleDOI
TL;DR: This paper attempts to make the first formal review of state-of-art of vision-based defect detection and classification of steel surfaces as they are produced from steel mills using vision- based techniques.
Abstract: Steel is the material of choice for a large number and very diverse industrial applications. Surface qualities along with other properties are the most important quality parameters, particularly for flat-rolled steel products. Traditional manual surface inspection procedures are awfully inadequate to ensure guaranteed quality-free surface. To ensure stringent requirements of customers, automated vision-based steel surface inspection techniques have been found to be very effective and popular during the last two decades. Considering its importance, this paper attempts to make the first formal review of state-of-art of vision-based defect detection and classification of steel surfaces as they are produced from steel mills. It is observed that majority of research work has been undertaken for cold steel strip surfaces which is most sensitive to customers' requirements. Work on surface defect detection of hot strips and bars/rods has also shown signs of increase during the last 10 years. The review covers overall aspects of automatic steel surface defect detection and classification systems using vision-based techniques. Attentions have also been drawn to reported success rates along with issues related to real-time operational aspects.

236 citations


Authors

Showing all 2858 results

NameH-indexPapersCitations
Bharat Bhushan116127662506
Santosh Kumar80119629391
Ramesh Chandra6662016293
J. Paulo Davim6438213403
Manish Kumar61142521762
Sandeep Singh5267011566
Ajar Nath Yadav481476090
Indranil Manna462639306
Anant Paradkar431956260
Sagar Pal401415271
Pratyoosh Shukla391944373
Neha Gupta362134782
Prasanta K. Jana351694135
Sumit Basu341234275
Pradeep Sharma334364825
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202330
202280
2021590
2020476
2019465
2018406