M
Mani Bhushan
Researcher at Indian Institute of Technology Bombay
Publications - 103
Citations - 1330
Mani Bhushan is an academic researcher from Indian Institute of Technology Bombay. The author has contributed to research in topics: Kalman filter & Wireless sensor network. The author has an hindex of 17, co-authored 89 publications receiving 1115 citations. Previous affiliations of Mani Bhushan include University of Alberta & Purdue University.
Papers
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A duality based framework for integrating reliability and precision for sensor network design
TL;DR: In this paper, Ali et al. show that the problems of maximizing reliability and maximizing precision (or minimizing variance) for linear processes are dual of each other and propose transformations which can be used to convert sensor failure probabilities into equivalent sensor variances and vice versa.
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Multi-objective optimization of glycopeptide antibiotic production in batch and fed batch processes.
TL;DR: In this paper, econstraint approach was used to generate the pareto solutions for two objectives: product concentration and product per unit cost of media, for batch and fed batch operations.
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A framework for setting up a country-wide network of regional surface PM2.5 sampling sites utilising a satellite-derived proxy – The COALESCE project, India
TL;DR: In this paper, the authors used satellite-derived PM2.5 data to identify the optimal regionally representative monitoring sites (RRMS) for air quality management and assessment of aerosol climate effects over a large area.
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Modified Unscented Recursive Nonlinear Dynamic Data Reconciliation for Constrained State Estimation
TL;DR: In this article, a modified URNDDR algorithm is proposed for solving large scale state estimation problems at relatively low computational cost, where the true states satisfy certain constraints resulting from the physics of the problem, that need to be incorporated and satisfied during the estimation procedure.
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Design of robust, reliable sensor networks using constraint programming
TL;DR: This article presents two novel formulations that incorporate robustness to uncertainties in the reliability data in sensor network design problem as explicit-optimization (MINLP) problem using failure rates of sensors which have better scaling properties instead of sensor reliabilities.