206
20
16481
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Title
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Faculty Publications
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Mandal, Ashmit; Hasan, Nafisa; Jain, Arumai; Mohanty, Jnyana Ranjan; Sharma, Vandana
Title
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Computational Relevance of Model Pruning and Quantization for Low-Powered AI
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01-01-2025
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2025 2nd International Conference on Multidisciplinary Research and Innovations in Engineering, MRIE 2025;pp.6-10
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<a href="https://doi.org/10.1109/MRIE66930.2025.11156676" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/MRIE66930.2025.11156676</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105018796606?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105018796606?origin=resultslist</a>
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Mandal A., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneshwar, India; Hasan N., School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneshwar, India; Jain A.; Mohanty J.R., School of Computer Application, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Sharma V., Christ University, Computer Science Department, Bengaluru, India
Description
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This study investigates how to make machine learning models more efficient for low-power devices by simplifying their structure and lowering size. Six models were evaluated: feed-forward neural networks (FNN), convolutional neural networks (CNN, notably VGG), decision trees, random forests, support vector machines (SVM), and auto encoders. Each was evaluated in its original form, after pruning and quantization, with a focus on model size, accuracy, and training time (as a measure of energy use). The results indicated that pruning for parameter like model size is greatly minimized with Decision Trees reducing by 95%, while it is observed quantization increases efficiency even more. In case of parameter, accuracy, it declined by about 7%. Results show that VGG model retain more accuracy than others after quantization. Pruning also increased training time, particularly for VGG and SVM models. This research thus provides insights into the trade-offs between model complexity, accuracy, and efficiency, guiding the selection for suitable models in resource-bounded environments. 2025 IEEE.
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Edge Computing; Low-Power AI; Model Compression; Pruning; Quantization
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Institute of Electrical and Electronics Engineers Inc.
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ISBN: 979-833158673-7;
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English
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Conference paper
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Restricted Access; Hardcopy may be available in the library
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Computational screening of natural compounds from Salvia plebeia R. Br. for inhibition of SARS-CoV-2 main protease
Subject
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ADMET; Main protease; Molecular docking; Molecular dynamic simulation; PASS; Plebeiosides B; Rutin; Salvia plebeia R. Br
Description
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The novel Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) has emerged to be the reason behind the COVID-19 pandemic. It was discovered in Wuhan, China and then began spreading around the world, impacting the health of millions. Efforts for treatment have been hampered as there are no antiviral drugs that are effective against this virus. In the present study, we have explored the phytochemical constituents of Salvia plebeia R. Br., in terms of its binding affinity by targeting COVID-19 main protease (Mpro) using computational analysis. Molecular docking analysis was performed using PyRx software. The ADMET and drug-likeness properties of the top 10 compounds showing binding affinity greater than or equal to ? 8.0kcal/mol were analysed using pkCSM and DruLiTo, respectively. Based on the docking studies, it was confirmed that Rutin and Plebeiosides B were the most potent inhibitors of the main protease of SARS-CoV-2 with the best binding affinities of ? 9.1kcal/mol and ? 8.9kcal/mol, respectively. Further, the two compounds were analysed by studying their biological activity using the PASS webserver. Molecular dynamics simulation analysis was performed for the selected proteinligand complexes to confirm their stability at 300ns. MM-PBSA provided the basis for analyzing the affinity of the phytochemicals towards Mpro by calculating the binding energy, and secondary structure analysis indicated the stability of protease structure when it is bound to Rutin and Plebeiosides B. Altogether, the study identifies Rutin and Plebeiosides B to be potent Mpro inhibitors of SARS-CoV-2. Graphic abstract: [Figure not available: see fulltext.] 2021, Society for Plant Research.
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Zackria A.A.; Pattabiraman R.; Murthy T.P.K.; Kumar S.B.; Mathew B.B.; Biju V.G.
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Vegetos, Vol-35, No. 2, pp. 345-359.
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Springer
Date
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2022-01-01
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<a href="https://doi.org/10.1007/s42535-021-00304-z" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s42535-021-00304-z</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117313884&doi=10.1007%2Fs42535-021-00304-z&partnerID=40&md5=547a75b74071a11893d6a340c6346703" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117313884&doi=10.1007%2fs42535-021-00304-z&partnerID=40&md5=547a75b74071a11893d6a340c6346703</a>
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All Open Access; Green Open Access; Hybrid Gold Open Access
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ISSN: 9704078
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Online
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English
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Article
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Zackria A.A., Department of Biotechnology, M S Ramaiah Institute of Technology, Karnataka, Bengaluru, 560054, India; Pattabiraman R., Department of Biotechnology, M S Ramaiah Institute of Technology, Karnataka, Bengaluru, 560054, India; Murthy T.P.K., Department of Biotechnology, M S Ramaiah Institute of Technology, Karnataka, Bengaluru, 560054, India; Kumar S.B., Department of Biotechnology, M S Ramaiah Institute of Technology, Karnataka, Bengaluru, 560054, India; Mathew B.B., Department of Biotechnology, Dayananda Sagar College of Engineering, Karnataka, Bengaluru, 560078, India; Biju V.G., Department of Computer Science and Engineering, Christ (Deemed-to-be University), Karnataka, Bengaluru, 560060, India
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Computational simulation of surface tension and gravitation-induced convective flow of a nanoliquid with cross-diffusion: An optimization procedure
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Boundary layer flow; Inclined magnetic field; Marangoni convection; Nanoliquid; RSM; Sensitivity analysis; Thermal radiation
Description
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The control of heat transfer in the hydromagnetic semiconductor crystal involves Marangoni convection with buoyancy forces. In this study, the conventional thermo-solutal Marangoni mixed flow model is modified by incorporating the solutal buoyancy effects that are significant in the flow phenomenon. The heat and mass transfer (HMT) characteristics of the Marangoni convective flow of a Cu ? H2O nanofluid subjected to the assisting/resisting buoyancy forces and cross-diffusion are numerically studied. The homogeneous single-phase nanoliquid model is used in conjunction with experimental data of dynamic viscosity and thermal conductivity. The Dufour and Soret effects are considered. Governing equations are solved using the finite difference-based algorithm. The problem is analyzed in a unified way considering the cases of buoyancy-assisted flow and buoyancy-opposed flow. The response surface methodology (RSM) based on the face-centered composite design (CCD) is used to optimize the heat and mass transfer rates. A multivariate regression model is proposed and authenticated prior to optimization. Additionally, sensitivity analysis is performed using the full quadratic regression model. The increase in the temperature profile is more significant due to the radiative heat flux than the inclined magnetic field. Heat transfer has a high sensitivity to the appearance of thermal radiation, while mass transfer has a high sensitivity to the Soret effect. Simultaneous optimization of HMT rates is achieved with the high level of thermal radiation and low levels of the cross-diffusion aspects. 2022
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Mackolil J.; Mahanthesh B.
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Applied Mathematics and Computation, Vol-425
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Elsevier Inc.
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2022-01-01
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<a href="https://doi.org/10.1016/j.amc.2022.127108" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.amc.2022.127108</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127209052&doi=10.1016%2Fj.amc.2022.127108&partnerID=40&md5=e78a60c498645bd33e5ebbfa752128dc" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127209052&doi=10.1016%2fj.amc.2022.127108&partnerID=40&md5=e78a60c498645bd33e5ebbfa752128dc</a>
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ISSN: 963003; CODEN: AMHCB
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Online
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English
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Article
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Mackolil J., Department of Mathematics, Centre for Mathematical Needs, CHRIST (Deemed to be University), Bengaluru, 560029, India; Mahanthesh B., Department of Mathematics, Centre for Mathematical Needs, CHRIST (Deemed to be University), Bengaluru, 560029, India
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Book Chapter
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Computational statistics of data science for secured software engineering
Description
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The chapter focuses on exploring the work done for applying data science for software engineering, focusing on secured software systems development. With requirements management being the first stage of the life cycle, all the approaches that can help security mindset right at the beginning are explored. By exploring the work done in this area, various key themes of security and its data sources are explored, which will mark the setup of base for advanced exploration of the better approaches to make software systems mature. Based on the assessments of some of the work done in this area, possible prospects are explored. This exploration also helps to emphasize the key challenges that are causing trouble for the software development community. The work also explores the possible collaboration across machine learning, deep learning, and natural language processing approaches. The work helps to throw light on critical dimensions of software development where security plays a key role. 2021, IGI Global.
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Althar R.R.; Samanta D.
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Methodologies and Applications of Computational Statistics for Machine Intelligence, pp. 81-96.
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IGI Global
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2021-01-01
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<a href="https://doi.org/10.4018/978-1-7998-7701-1.ch005" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/978-1-7998-7701-1.ch005</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124797202&doi=10.4018%2F978-1-7998-7701-1.ch005&partnerID=40&md5=08fd2433a75779442f4ae6c963cf1eed" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124797202&doi=10.4018%2f978-1-7998-7701-1.ch005&partnerID=40&md5=08fd2433a75779442f4ae6c963cf1eed</a>
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ISBN: 978-179987703-5; 978-179987701-1
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Online
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English
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Book chapter
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Althar R.R., Christ (Deemed to be University), QMS, First American India, Bangalore, India; Samanta D., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India
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Computational studies into the chemical nature, thermal behaviour, solvent role, reactivity and biological evaluation of Rigidin E A marine alkaloid with potent liver cancer inhibition
Subject
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ADMET; Anti-cancer; DFT; Docking; Marine alkaloid
Description
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The current work includes theoretical studies of Rigidin E (marine alkaloid) molecule with the DFT technique and evaluation of its biological properties in silico. DFT calculations in different media were performed for the title molecule. Gradual changes were noticed in the properties of the title compound when subjected to solvation in polar solvents. Electron density distribution, interaction and excitation were demonstrated using topological studies (ELF, LOL, RDG, and charge transfer) done using Multiwfn software. From FMO analysis, methanol is the solvent in which the title compound has the highest band gap value (3.8972 eV) compared to other solvents, and in the gas phase it has a band gap value of 3.6886 eV. Theoretical UV studies show that n ->?* and n ->?* electronic transitions are significant in Rigidin E. In water, the title molecule has a first-order hyperpolarizability about 100 times that of the reference substance urea, indicating its powerful NLO potential in aqueous medium. ADMET profile was generated using online tools (ADMET lab 2.0, PreADMET, and SwissADME). For the title molecule, docking was done against select liver cancer targets using AutoDock Tools and the lowest binding affinity was obtained ?4.62 kcal/mol against 4H6J protein. 2023 Elsevier B.V.
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Hammad W.; Parakkal S.C.; Datta R.; Muthu S.; Alharbi N.S.; Abbas G.
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Journal of Molecular Liquids, Vol-392
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Elsevier B.V.
Date
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2023-01-01
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<a href="https://doi.org/10.1016/j.molliq.2023.123514" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.molliq.2023.123514</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175848353&doi=10.1016%2Fj.molliq.2023.123514&partnerID=40&md5=b252379d86a472b43f8b02701b9a8145" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175848353&doi=10.1016%2fj.molliq.2023.123514&partnerID=40&md5=b252379d86a472b43f8b02701b9a8145</a>
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ISSN: 1677322; CODEN: JMLID
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Online
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English
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Article
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Hammad W., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Parakkal S.C., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Datta R., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Muthu S., Department of Physics, Arignar Anna Govt. Arts College, Tamil Nadu, Cheyyar, 604407, India; Alharbi N.S., Department of Botany and Microbiology, College of Science, King Saud University, P.O Box 2455, Riyadh, 11451, Saudi Arabia; Abbas G., Institute of Inorganic Chemistry, Karlsruhe Institute of Technology, Engesserstr 15, Karlsruhe, 76131, Germany
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Computational study of charge transfer iso-surface in first three excited states, electron-hole transition effects, chemical nature and bond order analysis investigations of chrysogine
Subject
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ADMET; DFT; Docking; Lung cancer; Topology
Description
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This work presents the theoretical DFT (Density Functional Theory) studies and the biological application of chrysogine, a marine alkaloid. Energy minimisation and additional DFT evaluations were performed for vacuum and solvent media. It has been observed that solvation with polar solvents has resulted in a slight variation in the molecule's properties. The Multiwfn software was employed to carry out various topological analyses. Among these, the charge transfer studies show that the second and third excited states are the most significant. From the reactivity analysis, the least energy gap (4.9624 eV) is obtained in water, indicating that chrysogine is most reactive in aqueous media. Theoretical UV studies show that the trends in ?max values correspond to n >?* and n >?* electronic transitions within the molecule. An increase in medium polarity has demonstrated in the MEP (Molecular Electrostatic Potential) maps an increase in the potential range from ?6.619 10?2 a.u. to 6.619 10?2 a.u. in the gas phase, to a sharp rise to ?8.036 10?2 a.u. to 8.036 10?2 a.u. in ethanol, ?8.098 10?2 a.u. to 8.098 10?2 a.u. in methanol, ?8.130 10?2 a.u. to 8.130 10?2 a.u. in DMSO, and ?8.127 10-2 a.u. to 8.127 10?2 a.u. in water. The most significant transition contributing to molecular stability from NBO (Natural Bond Orbital) analysis is: (O2-C9) ?* ? ?* (C7-C8) with the energy of 258.13 kcal mol?1. The ADMET profile for the molecule was assimilated with the help of online servers. The molecule was docked against lung cancer target proteins (PDB ID: 1NTK, 3QFB) using software such as AutoDock Tools and PyMOL. The respective illustrations and data were visualised using Discovery Studio Visualizer. Good binding affinities (?5.69 kcal mol?1 for 1NTK and ?6.64 kcal mol?1 for 3QFB proteins) and interactions were achieved with the selected targets. 2024 Elsevier B.V.
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Bhargiri J.J.; Parakkal S.C.; Datta R.; Alharbi N.S.; Kadaikunnan S.; Muthu S.
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Computational and Theoretical Chemistry, Vol-1237
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Elsevier B.V.
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2024-01-01
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<a href="https://doi.org/10.1016/j.comptc.2024.114649" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.comptc.2024.114649</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193487312&doi=10.1016%2Fj.comptc.2024.114649&partnerID=40&md5=aaaf9ab39fb482adfb5437b8b0eb6b6b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193487312&doi=10.1016%2fj.comptc.2024.114649&partnerID=40&md5=aaaf9ab39fb482adfb5437b8b0eb6b6b</a>
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Restricted Access
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ISSN: 2210271X
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Online
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English
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Article
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Bhargiri J.J., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Parakkal S.C., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Datta R., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Alharbi N.S., Department of Botany and Microbiology, College of Science, King Saud University, P.O Box 2455, Riyadh, 11451, Saudi Arabia; Kadaikunnan S., Department of Botany and Microbiology, College of Science, King Saud University, P.O Box 2455, Riyadh, 11451, Saudi Arabia; Muthu S., Department of Physics, Arignar Anna Govt. Arts College, Tamil Nadu, Cheyyar, 604407, India
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Article
Faculty Publications -Articles
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Computational Study of MHD Nanofluid Flow with Effects of Variable Viscosity and Non-uniform Heat Generation
Subject
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Entropy generation; Non-uniform heat source; Spectral quasilinearization technique; Unsteady flow; Variable; Viscosity
Description
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The thermodynamic study of an unsteady two-dimensional nanofluid flow through a permeable stretched sheet is looked at. Water is used as the primary fluid, along with four different nanoparticles, including copper (Cu), titanium dioxide (TiO2), copper oxide (CuO), and aluminium oxide (Al2O3). The heat transfer phenomenon is explained by an outside source. Additionally considered are the impacts of heat generation and absorption. A similarity transformation is used to convert the considered set of mathematical equations into a system of ODEs. The BVP4C method is then mathematically applied, coupled with shooting fashion. The results are given for cases involving copper nanoparticles. The effects of various physical parameters on the profiles of the dimensionless flow field, temperature, average entropy generation function, skin friction, and the Nusselt number are examined with illustrations and thorough explanations. As exceptional circumstances of the current inquiry, there is a strong agreement between the current conclusion and the findings of the other researchers. The average entropy generation number, temperature, and velocity profiles are shown to be strongly influenced by regulating factors. The authors conclude that the average entropy production number decreased in the existence of a temperature- and space-dependent heat source/sink, but it increased with increasing the viscosity parameter. 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited.
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Seethamahalakshmi V.; Babitha; Rao T.S.; Reddy G.V.R.
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International Journal of Applied and Computational Mathematics, Vol-9, No. 6
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Springer
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2023-01-01
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<a href="https://doi.org/10.1007/s40819-023-01600-9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s40819-023-01600-9</a>
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ISSN: 23495103
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Online
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English
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Article
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Seethamahalakshmi V., Department of Mathematics, PVP Siddartha Institute of Technology, Kanuru, Vijayawada, 520007, India; Babitha, Department of Mathematics, Christ (Deemed to Be) University, Bengaluru, Yeshwanthpur, India; Rao T.S., Department of Mathematics, Koneru Lakshmaiah Education Foundation, Vaddeswaram, 522302, India; Reddy G.V.R., Department of Mathematics, Koneru Lakshmaiah Education Foundation, Vaddeswaram, 522302, India
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Book Chapter
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Computational techniques for sustainable green procurement and production
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Computational techniques; computing; green procurement; procurement
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Computational techniques are used to generate, solve, analyze, explain, or manage any simple or complex task. The use of environmentally responsible techniques to meet demand for resources, commodities, utilities, and services is known as green procurement. Computational technique in green procurement and production is one of the components of sustainable procurement, along with a commitment to social responsibility and good corporate behavior. Some solutions for this kind of issue are low-maintenance, energy-efficient, and long-lasting. Several experts and researchers provided their findings on the environmental impact of ICT with the use of computational techniques. Also, the importance of energy-efficient information technology for environmentally conscious and feasible information technology is a hot topic because a computer faces environmental challenges at every stage of its life, from development to use to disposal. Due to changing environmental conditions, corporations have prioritized carbon emissions in procurement and transportation, which have the highest carbon impact. To encourage potential suppliers to adopt environmentally friendly practices, green criteria should be introduced into public procurement. Environmentally friendly corporate practices and environmental conservation are considered significant tools through public procurement. Techniques for green procurement and production procedures have recently been correlated with the concept of computational techniques of green procurement and production, owing to the increased emphasis on the concept of computational approaches. For eco-friendly procurement and production operations, computational approaches are inculcated and presented in the same way that they are for green procurement and manufacturing. From this perspective, this chapter presents a methodology for merging computational techniques into green procurement and production in public procurement in the form of green computing. 2024 by Elsevier Inc. All rights reserved, including those for text and data mining, AI training, and similar technologies.
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Parashar B.; Kautish S.; Chaurasia A.
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Computational Intelligence Techniques for Sustainable Supply Chain Management, pp. 275-300.
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Elsevier
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2024-01-01
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<a href="https://doi.org/10.1016/B978-0-443-18464-2.00004-2" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/B978-0-443-18464-2.00004-2</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203220793&doi=10.1016%2FB978-0-443-18464-2.00004-2&partnerID=40&md5=4c1266557460fa6e3a63f35e67491e2d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203220793&doi=10.1016%2fB978-0-443-18464-2.00004-2&partnerID=40&md5=4c1266557460fa6e3a63f35e67491e2d</a>
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ISBN: 978-044318464-2; 978-044318465-9
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Online
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English
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Book chapter
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Parashar B., VIT-Bhopal University, Madhya Pradesh, Bhopal, India; Kautish S., LBEF Campus (APU Malaysia) Kathmandu, Nepal, Model Institute of Engineering and Technology, Jammu and Kashmir, Jammu, India; Chaurasia A., School of Commerce, Finance and Accountancy Christ (Deemed to be University), Uttar Pradesh, Ghaziabad, India
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Articles
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Faculty Publications -Articles
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Computational techniques to study the dynamics of generalized unstable nonlinear Schringer equation
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Laplace transform; Modified sardar sub-equationmethod; q-Homotopy analysis method; Solitons; Unstable nonlinear Schringer equation
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In this paper, a more general form of unstable nonlinear Schringer equation which describe the time evolution of disturbances in marginally stable or unstable media is studied. A new modification of the Sardar sub-equation method is discussed and employed to retrieve solitons and other solutions of the suggested nonlinear model. A variety of solutions, including bright solitons, dark solitons, singular solitons, combo bright-singular solitons, periodic, exponential, and rational solutions are provided with considerable physical perspective. Using the q-homotopy analysis algorithm in combination with the Laplace transform, we present the approximate solutions of the bright and dark solitons, including the physical nature of the attained solutions. The computation complexity and results indicate that the given techniques are simple, effective, uncomplicated, and that they may be used to a wide range of unstable and stable nonlinear evolution equations encountered in mathematics, mathematical physics, and other applied disciplines. 2022
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Akinyemi L.; Akpan U.; Veeresha P.; Rezazadeh H.; Inc M.
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Journal of Ocean Engineering and Science
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Shanghai Jiaotong University
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2022-01-01
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<a href="https://doi.org/10.1016/j.joes.2022.02.011" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.joes.2022.02.011</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126326359&doi=10.1016%2Fj.joes.2022.02.011&partnerID=40&md5=95cf7048838507f90005246c048d49eb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126326359&doi=10.1016%2fj.joes.2022.02.011&partnerID=40&md5=95cf7048838507f90005246c048d49eb</a>
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All Open Access; Gold Open Access
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ISSN: 24680133
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Online
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English
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Article
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Akinyemi L., Department of Mathematics, Lafayette College, Easton, PA, United States; Akpan U., Department of Mathematics, Drexel University, Philadelphia, PA, United States; Veeresha P., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Rezazadeh H., Faculty of Engineering Technology, Amol University of Special Modern Technologies, Amol, Iran; Inc M., Biruni University, Department of Computer Engineering, Istanbul, Turkey, F?rat University, Science Faculty, Department of Mathematics, Elazig, 23119, Turkey, Department of Medical Research, China Medical University Hospital, China Medical University Taichung, Taiwan
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Conference Papers
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Faculty Publications- Conference Papers
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Computationally Efficient Machine Learning Methodology for Indian Nobel Laureate Classification
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Convolutional Neural Networks (CNNs); Feature Engineering; Haar cascade style; Image Classification; Logistic Regression; Machine Learning (ML); Similarity Checker; Supervised Learning
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A computationally efficient methodology for Indian Nobel Laureate classification is proposed in this study, emphasizing the optimization of image categorization through supervised learning techniques. Leveraging advancements in Convolutional Neural Networks (CNNs), the research aims to enhance the efficiency and precision of image classification tasks. The study utilizes Logistic Regression for dataset analysis, initially employing browser extensions for mass downloading categorized image data. Haar cascade classifiers are then used for data wrangling, focusing on facial, nose, and mouth recognition. Following this, feature engineering through wavelet transformation reduces image dimensionality, preparing the dataset for the chosen ML model, Logistic Regression. The primary focus is to simplify technology for improved image categorization. Support Vector Machines (SVM), Random Forest, and Logistic Regression are examined, with Logistic Regression emerging as the most effective model, achieving an accuracy rate of 87.5%. A thorough evaluation using Confusion Matrices reveals Logistic Regression's superior performance in classifying images of Indian Nobel laureates. A strategic up-sampling approach is implemented to address dataset inconsistencies, ensuring balanced representation across classes. The Haar wavelet transform is then applied for feature extraction, optimizing the dataset for ML models. The dataset is split into training and testing sets (80-20), and the three models are trained and evaluated for accuracy. Logistic Regression proves to be the best performer, offering insights into prominent leaders' identification. The research offers a detailed pipeline for data preprocessing, feature engineering, and model assessment, culminating in a robust image categorization system. Logistic Regression emerges as a reliable method for biographical picture identification, demonstrating superior accuracy over SVM and Random Forest. This research underscores the importance of efficient and accurate image classification methodologies for practical applications in real-world scenarios, particularly in recognizing influential leaders. 2024 IEEE.
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Banerjee S.; Joy H.K.
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RAICS - IEEE Recent Advances in Intelligent Computational Systems, No. 2024
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Institute of Electrical and Electronics Engineers Inc.
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2024-01-01
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<a href="https://doi.org/10.1109/RAICS61201.2024.10689993" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/RAICS61201.2024.10689993</a>
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ISSN: 27695565; ISBN: 979-835038168-9
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Online
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English
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Conference paper
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Banerjee S., Artificial Intelligence & Machine Learning, Christ Deemed to be University, Department of Computer Science, Bengaluru, India; Joy H.K., Christ Deemed to be University, Department of Computer Science, Bengaluru, India
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Conference Papers
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Computationally efficient wavelet domain solver for florescence diffuse optical tomography
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Estrogen receptor; Inverse solving; Multi-resolution; NIRf dye; Parallel processing; Wavelet transform
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Estrogen induced proliferation of mutant cells is a growth signal hallmark of breast cancer. Fluorescent molecule that can tag Estrogen Receptor (ER) can be effectively used for detecting cancerous tissue at an early stage. A novel targetspecific NIRf dye conjugate aimed at measuring ER status was synthesized by ester formation between 17-? estradiol and a hydrophilic derivative of ICG, cyanine dye, bis-1,1-(4-sulfobutyl) indotricarbocyanine-5-carboxylic acid, sodium salt. In-vitro studies provided specific binding on ER+ve [MCF-7] cells clearly indicating nuclear localization of the dye for ER+ve as compared to plasma level staining for MDAMB-231. Furthermore, cancer prone cells showed 4.5-fold increase in fluorescence signal intensity compared to control.; A model of breast phantom was simulated to study the in-vivo efficiency of dye with the parameters of dye obtained from photo-physical and in-vitro studies. The excitation (754 nm) and emission (787 nm) equation are solved independently using parallel processing strategies. The results were obtained by carrying out wavelet transformation on forward and the inverse data sets. An improvisation of the Information content of system matrix was suggested in wavelet domain. The inverse problem was addressed using LevenbergMarquardt (LM) procedure with the minimization of objective function using Tikhonov approach. The multi resolution property of wavelet transform was explored in reducing error and increasing computational efficiency. Our results were compared with the single resolution approach on various parameters like computational time, error function, and Normalized Root Mean Square (NRMS) error. A model with background absorption coefficient of 0.01 mm-1 with anomalies of 0.02 mm-1 with constant reduced scattering of 2.0 mm for different concentration of dye was compared in the result. The reconstructed optical properties were in concurrence with the tissue property at 787 nm. We intend our future plans on in-vivo study on developing a complete instrumentation for imaging a target specific lipophilic dye. Springer International Publishing Switzerland 2014.
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Francis K.J.; Jose I.
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Springer Proceedings in Mathematics and Statistics, Vol-92, pp. 457-469.
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Springer New York LLC
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2014-01-01
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<a href="https://doi.org/10.1007/978-3-319-08105-2__31" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-319-08105-2__31</a>
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ISSN: 21941009; ISBN: 978-331908104-5
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Online
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English
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Conference paper
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Francis K.J., Christ University, Bangalore, 560060, Karnataka, India; Jose I., Christ University, Bangalore, 560060, Karnataka, India
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Conference Papers
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Computer Assisted Unsupervised Extraction and Validation Technique for Brain Images from MRI
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Brain anomalies; Brain extraction; Contrast limited; average filtering; Pixel intensity
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Magnetic Resonance Imaging (MRI) of human is a developing field in medical research because it assists in considering the brain anomalies. To identify and analyze brain anomalies, the research requires brain extraction. Brain extraction is a significant clinical image handling method for quick conclusion with clinical perception for quantitative assessment. Automated methods of extracting brain from MRI are challenging, due to the connected pixel intensity information for various regions such as skull, sub head and neck tissues. This paper presents a fully automated extraction of brain area from MRI. The steps involved in developing the method to extract brain area, includes image contrast limited using histogram, background suppression using average filtering, pixel region growing method by finding pixel intensity similarity and filling discontinuity inside brain region. Twenty volumes of brain slices are utilized in this research method. The outcome is achieved by this method is approved by comparing with manually extracted slices. The test results confirm the performance of this strategy can effectively section brain from MRI. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Vijayalakshmi S.; Genish T.; Gayathri S.P.
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Lecture Notes in Networks and Systems, Vol-462, pp. 365-372.
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Springer Science and Business Media Deutschland GmbH
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2022-01-01
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<a href="https://doi.org/10.1007/978-981-19-2211-4_32" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_32</a>
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ISSN: 23673370; ISBN: 978-981192210-7
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Online
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English
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Conference paper
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Vijayalakshmi S., Department of Data Science, ChristDeemed to be University, Pune, India; Genish T., School of Computing Science, KPR College of Arts Science and Research, Coimbatore, India; Gayathri S.P., Department of Computer Science and Applications, The Gandhigram Rural InstituteDeemed to be University, Gandhigram, India
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https://archives.christuniversity.in/files/original/ce2136dc56827747bfe4b32cc7c5741c.png
ae8597b1fb62da5294ca14f6fc0ece85
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Patents
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Patent
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Patent
Patent
Patents
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Title
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Computer implemented method for generating notification during call without using internet in wireless communication /
Subject
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Electronics
Description
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"Patent Number: 201911047977, Applicant: Asik Rahaman Jamader.
The present invention disclosure is related to a computer implemented method for generating notification during calls without usinginternet in wireless communication. The present invention provides an internet free method for advance notification system from the caller. This advance notification generated by calling time on calling partys devise. The incoming calls getting an assigned text as subject of calling from a caller. Caller party can recognize the caller identity and a picture on the incoming telephone call."
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Samanta, Debabrata.
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<a href="https://drive.google.com/file/d/187peZX_N3yvvaCEpVtxPqd7qaRyYkw-K/view" target="_blank" title="Computer implemented method for generating notification during call without using internet in wireless communication /" rel="noreferrer noopener">https://drive.google.com/file/d/187peZX_N3yvvaCEpVtxPqd7qaRyYkw-K/view</a>
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Intellectual Property India
Date
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2019-03-14
Language
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English
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Patent
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Articles
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Computer modelling of trace SO2 and NO2 removal from flue gases by utilizing Zn(ii) MOF catalysts
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SO2 and NO2 capture and conversion have been investigated via density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations using a novel hydrogen-bonded 3D metal-organic framework (MOF) containing a Zn(ii) centre and a partially fluorinated (polar -CF3) long-chain dicarboxylate ligand with a melamine (basic -NH2) co-ligand. Initially, computational single-component isotherms have been determined for SO2 and NO2 gases. These simulations have shown exothermic adsorption enthalpies of ?36.4 and ?28.6 kJ mol?1 for SO2 and NO2, respectively. They have also indicated that SO2 has a high affinity for polar -CF3 and basic -NH2 binding sites of the ligand in the framework pore walls. The lower adsorption capacity of NO2 compared with SO2 is due to weaker electrostatic interactions with the framework. Furthermore, MOF adsorbent selectivity for removing trace amounts of SO2 and NO2 in flue gases has been estimated through the co-adsorption of ternary gas mixtures (SO2/CO2/N2 and NO2/CO2/N2). Together with DFT, the climbing image nudged elastic band (CI-NEB) method has been used for investigating the plausible mechanisms for HbMOF1 catalyzed cycloadditions of SO2 and NO2 with epoxides leading to the formation of cyclic sulphites and nitrates, respectively. 2023 The Royal Society of Chemistry.
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Muthukumar D.; Nagaraja C.M.; Badawi M.; Pillai R.S.
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New Journal of Chemistry, Vol-47, No. 38, pp. 18086-18095.
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Royal Society of Chemistry
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2023-01-01
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<a href="https://doi.org/10.1039/d3nj01805a" target="_blank" rel="noreferrer noopener">https://doi.org/10.1039/d3nj01805a</a>
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ISSN: 11440546; CODEN: NJCHE
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Online
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English
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Article
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Muthukumar D., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India, Laboratoire de Physique et Chimie Thriques UMR CNRS 7019 Universitde Lorraine, Nancy, France; Nagaraja C.M., Department of Chemistry, Indian Institute of Technology, Ropar, Punjab, Rupnagar, 140001, India; Badawi M., Laboratoire de Physique et Chimie Thriques UMR CNRS 7019 Universitde Lorraine, Nancy, France; Pillai R.S., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, India, Analytical and Spectroscopy Division, ASCG/PCM, Vikram Sarabhai Space Centre, Indian Space Research Organization, Kerala, Thiruvananthapuram - 695 022, India
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Conference Papers
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Computer simulation of diesel fueled engine processes using matlab and experimental investigations on research engine
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The depletion of conventional fuel source at a fast rate and increasing environmental pollution have motivated extensive research in combustion modeling and energy efficient engine design. In the present work, a computer simulation incorporating progressive combustion model using thermodynamic equations has been carried out using MATLAB to evaluate the performance of a diesel engine. Simulations at constant speed and variable load have been carried out for the experimental engine available in the laboratory. For simulation, speed and Air/Fuel ratios, which are measured during the experiment, have been used as input apart from other geometrical details. A state-of-the-art experimental facility has been developed in-house. The facility comprises of a hundred horsepower water cooled eddy current dynamometer with appropriate electronic controllers. A normal load test has been carried out and the required parameters were measured. A six gas analyzer was used for the measurement of NOx, HC, CO2, O2, CO and SOx. and a smoke meter was used for smoke opacity. The predicted Pressure-Volume (PV) diagram was compared with measurements and found to match closely. It is concluded that the developed simulation software could be used to get quick results for parametric studies. Copyright 2017 ASME.
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Venkataraman S.; Ramawarrier R.; Satheesh V.K.; Mundupalam N.M.; Bhure S.
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American Society of Mechanical Engineers, Power Division (Publication) POWER, Vol-1
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American Society of Mechanical Engineers (ASME)
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2017-01-01
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<a href="https://doi.org/10.1115/POWER-ICOPE2017-3498" target="_blank" rel="noreferrer noopener">https://doi.org/10.1115/POWER-ICOPE2017-3498</a>
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ISBN: 978-079185760-1; CODEN: AMEPE
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Online
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English
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Conference paper
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Venkataraman S., Diesel Engine R and D Laboratory, Mechanical Engineering, Faculty of Engineering, Christ University, Bangalore, 560074, India; Ramawarrier R., Diesel Engine R and D Laboratory, Mechanical Engineering, Faculty of Engineering, Christ University, Bangalore, 560074, India; Satheesh V.K., Diesel Engine R and D Laboratory, Mechanical Engineering, Faculty of Engineering, Christ University, Bangalore, 560074, India; Mundupalam N.M., Diesel Engine R and D Laboratory, Mechanical Engineering, Faculty of Engineering, Christ University, Bangalore, 560074, India; Bhure S., Diesel Engine R and D Laboratory, Mechanical Engineering, Faculty of Engineering, Christ University, Bangalore, 560074, India
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Title
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Articles
Article
Faculty Publications -Articles
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Title
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Computer Vision Based Automatic Margin Computation Model for Digital Document Images
Subject
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Computer vision; Digital image processing; Margin detection; Text localization
Description
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Margin, in typography, is described as the space between the text content and the document edges and is often essential information for the consumer of the document, digital or physical. In the present age of digital disruption, it is customary to store and retrieve documents digitally and retrieve information automatically from the documents when necessary. Margin is one such non-textual information that becomes important for some business processes, and the demand for computing margins algorithmically mounts to facilitate RPA. We propose a computer vision-based text localization model, utilizing classical DIP techniques such as smoothing, thresholding, and morphological transformation to programmatically compute the top, left, right, and bottom margins within a digital document image. The proposed model has been experimented with different noise filters and structural elements of various shapes and size to finalize the bilateral filter and lines and structural elements for the removal of noises most commonly occurring due to scans. The proposed model is targeted towards text document images and not the natural scene images. Hence, the existing benchmark models developed for text localization in natural scene images have not performed with the expected accuracy. The model is validated with 485 document images of a real-time business process of a reputed TI company. The results show that 91.34 % of the document images have conferred more than 90 % IoU value which is well beyond the accuracy range determined by the company for that specific process. 2023, Crown.
Creator
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Guha A.; Samanta D.; Sengar S.S.
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SN Computer Science, Vol-4, No. 3
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Springer
Date
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2023-01-01
Identifier
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<a href="https://doi.org/10.1007/s42979-023-01693-5" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s42979-023-01693-5</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150171922&doi=10.1007%2Fs42979-023-01693-5&partnerID=40&md5=153905902498c35e46288fbcddde7c44" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150171922&doi=10.1007%2fs42979-023-01693-5&partnerID=40&md5=153905902498c35e46288fbcddde7c44</a>
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All Open Access; Hybrid Gold Open Access
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ISSN: 2662995X
Format
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Online
Language
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English
Type
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Article
Coverage
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Guha A., Department of Data Science, CHRIST (Deemed to be) University, Karnataka, Bengaluru, India, R &D Scientist, First American India Private Limited, Karnataka, Bengaluru, India; Samanta D., Department of Data Science, CHRIST (Deemed to be) University, Karnataka, Bengaluru, India, Department of Computational Information Technology, Rochester Institute of Technology, Germia Campus, Prishtina, Kosovo, 10000; Sengar S.S., Department of Computer Science, Cardiff Metropolitan University, Cardiff, CF5 2YB, United Kingdom
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Title
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PHD
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PhD Thesis
Dublin Core
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61000202
Title
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Computer Vision Based Indian Sign Language Recognition Using Deep Learning
Subject
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Computer Science
Description
An account of the resource
Speech is a human default and unique modality for language development and communication which is essential for memory and overall cognitive development. Excellency in language permits a child to be extrovert enriching the development of cognitive and psychosocial skills; whereas, for auditory deprived children, the misalignment of the brain and ear makes them impotent to communicate with the society which creates a central dogma that hearing-loss is a disability which further ignores their psycho-social identity. To fill such gaps and make their community more freewheeling in India, Indian Sign Language (ISL) - a complete language with its own linguistic and verbal elements was framed. Though ISL is appropriate and absolute in every linguistic approach, lack of prerequisite and proficiency enforces dedicated teachers to teach the curriculum through contrived signs for the sake of convenience that not only diminishes the distinctiveness of ISL but also dislodges the idea of learning their mother tongue. This creates an imbalance in the analogous learning of communication and curriculum language. In order to balance the level in learning, effective vision-based days of the week ISL model is developed through Convolution Neural Network (CNN) architecture which boasts independent learning of ISL. The proposed model comprises of six stages: dataset creation, preprocessing, splitting dataset into train, validation and test, applying various types of image augmentation techniques according to split, constructing CNN model for feature extraction and classification and finally evaluating the result through evaluation measures. Initially, an image dataset is created as there is a scarcity of standard ISL datasets in internet sources. The images are created on vision-based technique to avoid of carrying additional superfluous hardware gadgets for human computer interaction.
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J, Sagaya Mary.
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Author's Submission
Publisher
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Christ(Deemed to be University)
Date
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2022-01-01
Contributor
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M, Nachmai
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Open Access
Format
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PDF
Language
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English
Type
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PhD
Identifier
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<a href="http://hdl.handle.net/10603/420563" target="_blank" rel="noreferrer noopener">http://hdl.handle.net/10603/420563</a>
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https://archives.christuniversity.in/files/original/7288164c143abb86bd5800472831da57.pdf
dce3f5540cb683b1d698bcfb85d8ea37
Dublin Core
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Title
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Thesis
PhD
PhD Thesis
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Title
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Computer Vision Based Indian Sign Language Recognition Using Deep Learning /
Subject
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Computer Science
Creator
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J, Sagaya Mary. - 1540073
Publisher
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CHRIST (Deemed to be University)
Date
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2022-12-22
Language
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English
Type
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PhD
-
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Title
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Faculty Publications
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
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Creator
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Jacob, Ann Mariya; Resmi, K.R.; Vineetha, K.R.
Title
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Computer Vision for Real-Time Nutrition Scanning in Polycystic Ovary Syndrome Management
Date
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01-01-2026
Source
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2026 IEEE International Students' Conference on Electrical, Electronics and Computer Science, SCEECS 2026;
Identifier
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<a href="https://doi.org/10.1109/SCEECS68810.2026.11429906" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/SCEECS68810.2026.11429906</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105037934873?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105037934873?origin=resultslist</a>
Coverage
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Jacob A.M., Christ University, Department of Computer Science, Karnataka, Bengaluru, India; Resmi K.R., Christ University, Department of Computer Science, Karnataka, Bengaluru, India; Vineetha K.R., Christ University, Department of Computer Science, Karnataka, Bengaluru, India
Description
An account of the resource
PCOS stands for polycystic ovary syndrome and it is widely known to be one of the leading causes of insulin resistance and hormonal imbalance among women within the reproductive age spanning from 8 to 13%. Although integrating a healthy diet is a crucial step while managing PCOS, the outdated and frustrating method of manually food logging slows the process and still lacks accuracy. Improving performance feedback is one of the key areas to ensure adherence to a healthy plan. This is the driving reason behind the development of 'NutriScan-PCOS.' In the PCOS focused Streamlit App, the PCOS diet MobileNet application nutrition model helps to do just that. It is trained on 4000 images of 80 diverse Indian foods for quick identification and portion size estimation with OpenCV. The driving function of the app is to track meals and overall nutrition value, scoring on a dynamic scale on 5 parameters focused on the impact on PCOS. It is designed to be user-centric, with a clear green-yellowred traffic system to ensure guidance is instantaneous and easy. NutriScan-PCOS runs on a Streamlit interface with options like photo upload, live camera, barcode scan, and daily logs-making it easy and practical for everyday use. 2026 IEEE.
Subject
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Glycemic Index; MobileNetV2; OpenCV; Polycystic Ovary Syndrome (PCOS); Streamlit
Publisher
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Institute of Electrical and Electronics Engineers Inc.
Relation
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ISBN: 979-833157116-0;
Language
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English
Type
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Conference paper
Rights
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Restricted Access; Hardcopy may be available in the library
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https://archives.christuniversity.in/files/original/10a96c588c2d626ea6ef705c4a53299b.png
fc734b1df9b899a189ad67485ea778d1
Dublin Core
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Title
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Patents
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Patent
Description
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Patent
Patent
Patents
Dublin Core
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Title
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Computer-aided drug design and green synthesis of novel pyrazole analogues as potential sars-cov-2 main protease inhabitors against anti-covid-19 protein targets /
Subject
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Bio-Medical
Description
An account of the resource
Patent Number: 202141026750, Applicant: Santhosh Govindaraju.
COVID-19 pandemic has significantly increased high deaths, infectivity and hospitalizations. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a foremost problem in the world presently. Currently, all research institutions and pharmaceutical industries are keen in developing new vaccines and more effective drugs that could inhibit the SARS-CoV-2 virus and help in the treatment of patients. This provoked us to design medicinally effective drug candiadates which can prevent the SARS-CoV-2 virus of the infected patients.
Creator
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Govindaraju, Santhosh.
Source
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<a href="https://drive.google.com/file/d/1xvdxgTkF2um5nmHtuBv83nzwzrWZzhKT/view" target="_blank" title="Computer-aided drug design and green synthesis of novel pyrazole analogues as potential sars-cov-2 main protease inhabitors against anti-covid-19 protein targets /" rel="noreferrer noopener">https://drive.google.com/file/d/1xvdxgTkF2um5nmHtuBv83nzwzrWZzhKT/view</a>
Publisher
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World Intellectual Propert Organization
Date
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2021-03-29