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Gade Pandu Rangaiah

Researcher at National University of Singapore

Publications -  282
Citations -  6739

Gade Pandu Rangaiah is an academic researcher from National University of Singapore. The author has contributed to research in topics: Multi-objective optimization & Global optimization. The author has an hindex of 42, co-authored 277 publications receiving 5737 citations. Previous affiliations of Gade Pandu Rangaiah include Indian Institute of Technology Kanpur & Nanyang Technological University.

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Optimal intra-dialytic exercise protocol for improving the toxin removal in hemodialysis patients

TL;DR: Simulation studies reveal that during the 3 bouts of optimal intermittent exercise, remotely sequestered solutes can be removed from the low flow region and more toxins are removed in the dialyzer which consistently results in a decrease in percentage rebound during the post-dialysis period for both urea and creatinine.
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Concentration Control of a Continuous Stirred Tank Reactor by Improved IMC Strategies

TL;DR: In this paper, two strategies (adaptive internal model control, AdIMC and augmented internal model controller, AuIMC) are described for concentration control of a continuous stirred tank reactor.
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Partial Least Squares (PLS) Model for Prediction of Definitive and Intermediate Treatment Outcomes in Diabetes Ketoacidosis (DKA) Patients

TL;DR: Ten predictor variables were found to be important in PLS model with manipulated variables, out of which total intravenous insulin before conversion to subcutaneous insulin was found toBe the most important predictor.
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Multi-loop Control System Design for Biodiesel Process using Waste Cooking Oil

TL;DR: Xiong et al. as mentioned in this paper developed a multi-loop control system design for a comprehensive biodiesel process using waste cooking oil, which uses steady state gain and bandwidth information of the process open loop transfer function to determine input-output pairings.
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Effect of intra-patient variability on personalized parameters of glucose-insulin dynamic models for exercise, meal, and insulin interventions

TL;DR: In this paper, the effect of intra-patient variations on the personalized parameters of the modified exercise minimal model by re-estimating them from the clinical data measured after several days of first estimation was studied.