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Sanjay Yadav

Researcher at University of Delhi

Publications -  60
Citations -  786

Sanjay Yadav is an academic researcher from University of Delhi. The author has contributed to research in topics: Pressure measurement & Portfolio. The author has an hindex of 14, co-authored 54 publications receiving 613 citations. Previous affiliations of Sanjay Yadav include All India Institute of Medical Sciences & AIIMS, New Delhi.

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Experimental Investigation of Centrifugal Pump Working as Turbine for Small Hydropower Systems

TL;DR: In this paper, an experimental investigation of a centrifugal pump has been carried out to study its characteristics in pump and turbine mode operation, and new correlations have been developed by using its best efficiency and specific speed in pump mode.
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Multiobjective Fuzzy Portfolio Performance Evaluation Using Data Envelopment Analysis Under Credibilistic Framework

TL;DR: A frontier improvement technique existing in the literature is used to rebalance the inefficient random sample portfolios to make them efficient, so that an investor may have more avenues to select efficient portfolios.
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Final Report on Key Comparison CCM.P-K7 in the range 10 MPa to 100 MPa of hydraulic gauge pressure

TL;DR: In this article, the CCM key comparison of hydraulic pressure standards of nine National Metrology Institutes was carried out in the period from November 2002 to June 2004 in order to determine their degrees of equivalence in the range 10 MPa to 100 MPa of the gauge pressure.
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Redefined SI Units and Their Implications

TL;DR: In this article, the authors present a brief status report and apprise the readers about these historical events and the implications of these changes in our daily life, which is referred to as World Metrology Day.
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Data envelopment analysis based fuzzy multi-objective portfolio selection model involving higher moments

TL;DR: This work studies the portfolio selection problem from the perspective of incorporating more information about the non-normality of asset returns by considering the mean-variance-skewness-kurtosis framework, and proposes a fuzzy multi-objective linear programming model which is solved through a weighted max-min approach.