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Satyasaran Changdar
Satyasaran Changdar
Machine Learning, Department of Computer Science, University of Copenhagen, Denmark
Verified email at di.ku.dk - Homepage
Title
Cited by
Cited by
Year
Investigation of nanoparticle as a drug carrier suspended in a blood flowing through an inclined multiple stenosed artery
S Changdar, S De
Bionanoscience 8 (1), 166-178, 2018
272018
Analytical investigation of nanoparticle as a drug carrier suspended in a MHD blood flowing through an irregular shape stenosed artery
S Changdar, S De
Iranian Journal of Science and Technology, Transactions A: Science 43, 1259-1272, 2019
252019
A survey of data mining applications and techniques
S Mukherjee, R Shaw, N Haldar, S Changdar
International journal of Computer Science and information Technologies 6 (5 …, 2015
252015
Analytical solution of mathematical model of magnetohydrodynamic blood nanofluid flowing through an inclined multiple stenosed artery
S Changdar, S De
Journal of Nanofluids 6 (6), 1198-1205, 2017
242017
Analysis of non-linear pulsatile blood flow in artery through a generalized multiple stenosis
S Changdar, S De
Arabian Journal of Mathematics 5, 51-61, 2016
202016
EFFECT OF A VARIABLE MAGNETIC FIELD ON PERISTALTIC SLIP FLOW OF BLOOD-BASED HYBRID NANOFLUID THROUGH A NONUNIFORM ANNULAR CHANNEL
S Dolui, B Bhaumik, S De, S Changdar
Journal of Mechanics in Medicine and Biology 23 (01), 2250070, 2023
162023
Study of nanoparticle as a drug carrier through stenosed arteries using Bernstein polynomials
A Chatterjee, S Changdar, S De
International Journal for Computational Methods in Engineering Science and …, 2020
152020
Combined impact of Brownian motion and thermophoresis on nanoparticle distribution in peristaltic nanofluid flow in an asymmetric channel
B Bhaumik, S Changdar, S De
International Journal of Ambient Energy 43 (1), 5064-5075, 2022
142022
Physics-based smart model for prediction of viscosity of nanofluids containing nanoparticles using deep learning
S Changdar, B Bhaumik, S De
Journal of Computational Design and Engineering 8 (2), 600-614, 2021
132021
Prediction of the stability number of conventional rubble-mound breakwaters using machine learning algorithms
S Saha, S Changdar, S De
Journal of Ocean Engineering and Science, 2022
102022
Transport of spherical nanoparticles suspended in a blood flowing through stenose artery under the influence of Brownian motion
S Changdar, S De
Journal of Nanofluids 6 (1), 87-96, 2017
102017
An optimized hyper kurtosis based modified duo-histogram equalization (HKMDHE) method for contrast enhancement purpose of low contrast human brain CT scan images
S Mukhopadhyay, N Ghosh, R Burman, PK Panigrahi, S Pratiher, ...
2015 International Conference on Advances in Computing, Communications and …, 2015
102015
A smart model for prediction of viscosity of nanofluids using deep learning
S Changdar, S Saha, S De
Smart Science 8 (4), 242-256, 2020
92020
A unique physics-aided deep learning model for predicting viscosity of nanofluids
B Bhaumik, S Chaturvedi, S Changdar, S De
International Journal for Computational Methods in Engineering Science and …, 2023
82023
An expert model based on physics-aware neural network for the prediction of thermal conductivity of nanofluids
B Bhaumik, S Changdar, S De
Journal of Heat Transfer 144 (10), 103501, 2022
62022
Biomedical simulations of hybrid nano fluid flow through a balloon catheterized stenotic artery with the effects of an inclined magnetic field and variable thermal conductivity
S Dolui, B Bhaumik, S De, S Changdar
Chemical Physics Letters 829, 140756, 2023
52023
Numerical simulation of nonlinear pulsatile Newtonian blood flow through a multiple stenosed artery
S Changdar, S De
International Scholarly Research Notices 2015, 2015
52015
Solution of Definite Integrals using Functional Link Artificial Neural Networks
S Changdar, S Bhattacharjee
arXiv preprint arXiv:1904.09656, 2019
42019
Analysis of blood flow through multi-irregular shape stenosed artery
S Das, S Das, S Changdar, S De
Int J Pharm Biol Sci 4 (2), 244-252, 2014
42014
An Application of Machine Learning Algorithms on the Prediction of the Damage Level of Rubble-Mound Breakwaters
S Saha, S De, S Changdar
Journal of Offshore Mechanics and Arctic Engineering 146 (1), 011202, 2024
32024
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