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1,130 results on '"Venkatraman B"'

1. Theoretical simulation on evolution of suspended sodium combustion aerosols characteristics in a closed chamber

Author

Sujatha Pavan Narayanam, Amit Kumar, Usha Pujala, Subramanian V., Srinivas C.V., Venkatesan R., Athmalingam S., and Venkatraman B.

Subjects
Sodium aerosols, Aerosol modeling, HAARM code, Aerosol size growth, Method of moments, Nuclear engineering. Atomic power, TK9001-9401
Abstract

In the unlikely event of core disruptive accident in sodium cooled fast reactors, the reactor containment building would be bottled up with sodium and fission product aerosols. The behavior of these aerosols is crucial to estimate the in-containment source term as a part of nuclear reactor safety analysis. In this work, the evolution of sodium aerosol characteristics (mass concentration and size) is simulated using HAARM-S code. The code is based on the method of moments to solve the integro-differential equation. The code is updated to FORTRAN-77 and run in Microsoft FORTRAN PowerStation 4.0 (on Desktop). The sodium aerosol characteristics simulated by HAARM-S code are compared with the measured values at Aerosol Test Facility. The maximum deviation between measured and simulated mass concentrations is 30% at initial period (up to 60 min) and around 50% in the later period. In addition, the influence of humidity on aerosol size growth for two different aerosol mass concentrations is studied. The measured and simulated growth factors of aerosol size (ratio of saturated size to initial size) are found to be matched at reasonable extent. Since sodium is highly reactive with atmospheric constituents, the aerosol growth factor depends on the hygroscopic growth, chemical transformation and density variations besides coagulation. Further, there is a scope for the improvement of the code to estimate the aerosol dynamics in confined environment.

Published
2022
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2. Parameter Estimation in Quantum Metrology Technique for Time Series Prediction

Author

Sharma, Vaidik A, Meenachi, N. Madurai, and Venkatraman, B.

Subjects
Quantum Physics, Computer Science - Neural and Evolutionary Computing
Abstract

The paper investigates the techniques of quantum computation in metrological predictions, with a particular emphasis on enhancing prediction potential through variational parameter estimation. The applicability of quantum simulations and quantum metrology techniques for modelling complex physical systems and achieving high-resolution measurements are proposed. The impacts of various parameter distributions and learning rates on predictive accuracy are investigated. Modelling the time evolution of physical systems Hamiltonian simulation and the product formula procedure are adopted. The time block method is analyzed in order to reduce simulation errors, while the Schatten-infinite norm is used to evaluate the simulation precision. Methodology requires estimation of optimized parameters by minimizing loss functions and resource needs. For this purpose, the mathematical formulations of Cramer Rao Bound and Fischer Information are indispensable requirements. The impact of learning rates on regulating the loss function for various parameter values. Using parameterized quantum circuits, the article outlines a four-step procedure for extracting information. This method involves the preparation of input states, the evolution of parameterized quantum states, the measurement of outputs, and the estimation of parameters based on multiple measurements. The study analyses variational unitary circuits with optimized parameter estimation for more precise predictions. The findings shed light on the effects of normal parameter distributions and learning rates on attaining the most optimal state and comparison with classical Long Short Term Memory (LSTM) predictions, providing valuable insights for the development of more appropriate approaches in quantum computing., Comment: conference. arXiv admin note: substantial text overlap with arXiv:2406.05767

Published
2024

9. Extraction of Blood Vessels in Fundus Images of Retina through Hybrid Segmentation Approach

Author

Ramakrishnan Sundaram, Ravichandran KS, Premaladha Jayaraman, and Venkatraman B

Subjects
segmentation, blood vessels, morphology, bottom hat, fusion, Mathematics, QA1-939
Abstract

A hybrid segmentation algorithm is proposed is this paper to extract the blood vessels from the fundus image of retina. Fundus camera captures the posterior surface of the eye and the captured images are used to diagnose diseases, like Diabetic Retinopathy, Retinoblastoma, Retinal haemorrhage, etc. Segmentation or extraction of blood vessels is highly required, since the analysis of vessels is crucial for diagnosis, treatment planning, and execution of clinical outcomes in the field of ophthalmology. It is derived from the literature review that no unique segmentation algorithm is suitable for images of different eye-related diseases and the degradation of the vessels differ from patient to patient. If the blood vessels are extracted from the fundus images, it will make the diagnosis process easier. Hence, this paper aims to frame a hybrid segmentation algorithm exclusively for the extraction of blood vessels from the fundus image. The proposed algorithm is hybridized with morphological operations, bottom hat transform, multi-scale vessel enhancement (MSVE) algorithm, and image fusion. After execution of the proposed segmentation algorithm, the area-based morphological operator is applied to highlight the blood vessels. To validate the proposed algorithm, the results are compared with the ground truth of the High-Resolution Fundus (HRF) images dataset. Upon comparison, it is inferred that the proposed algorithm segments the blood vessels with more accuracy than the existing algorithms.

Published
2019
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10. Numerical Study on the Jet Breakup of Molten Nuclear Fuel in the Coolant in Dripping Regime

Author

Chandra Kumar, M., Jasmin Sudha, A., Subramanian, V., Venkatraman, B., Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Singh, Krishna Mohan, editor, Dutta, Sushanta, editor, Subudhi, Sudhakar, editor, and Singh, Nikhil Kumar, editor

Published
2024
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11. CFD Modeling of Hydrodynamic Jet Breakup of Molten Nuclear Fuel in the Coolant

Author

Rawat, Ajay, Jasmin Sudha, A., Subramanian, V., Venkatraman, B., Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Singh, Krishna Mohan, editor, Dutta, Sushanta, editor, Subudhi, Sudhakar, editor, and Singh, Nikhil Kumar, editor

Published
2024
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22. A Study on Rayleigh Plateau Instability in Slender Jets of Nuclear Materials

Author

Chandra Kumar, M., Jasmin Sudha, A., Subramanian, V., Venkatesan, R., Athmalingam, S., Venkatraman, B., Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Haddar, Mohamed, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Sivaram, N. M., editor, Sankaranarayanasamy, K., editor, and Davim, J. Paulo, editor

Published
2023
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23. Simulation Experiments on Sodium Leak Through Pipe Cracks

Author

Avinash, Ch. S. S. S., Hemanth Rao, E., Nani Babu, M., Malarvizhi, B., Das, Sanjay Kumar, Ponraju, D., Venkatraman, B., Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Haddar, Mohamed, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Bhattacharyya, Suvanjan, editor, and Benim, Ali Cemal, editor

Published
2023
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28. NukeBERT: A Pre-trained language model for Low Resource Nuclear Domain

Author

Jain, Ayush, Meenachi, N. M., and Venkatraman, B.

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Significant advances have been made in recent years on Natural Language Processing with machines surpassing human performance in many tasks, including but not limited to Question Answering. The majority of deep learning methods for Question Answering targets domains with large datasets and highly matured literature. The area of Nuclear and Atomic energy has largely remained unexplored in exploiting non-annotated data for driving industry viable applications. Due to lack of dataset, a new dataset was created from the 7000 research papers on nuclear domain. This paper contributes to research in understanding nuclear domain knowledge which is then evaluated on Nuclear Question Answering Dataset (NQuAD) created by nuclear domain experts as part of this research. NQuAD contains 612 questions developed on 181 paragraphs randomly selected from the IGCAR research paper corpus. In this paper, the Nuclear Bidirectional Encoder Representational Transformers (NukeBERT) is proposed, which incorporates a novel technique for building BERT vocabulary to make it suitable for tasks with less training data. The experiments evaluated on NQuAD revealed that NukeBERT was able to outperform BERT significantly, thus validating the adopted methodology. Training NukeBERT is computationally expensive and hence we will be open-sourcing the NukeBERT pretrained weights and NQuAD for fostering further research work in the nuclear domain.

Published
2020

37. Investigation of CT Linearity and Establishing the Density Calibration Curve for the Gamma Ray CT System

Author

Ramar, R., Menaka, M., Subramanian, V., Venkatesan, R., Athmalingam, S., Venkatraman, B., Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, di Mare, Francesca, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, Mandayam, Shyamsunder, editor, and Sagar, Sarmishtha Palit, editor

Published
2022
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38. Quantitative Analysis of Breast Thermograms Using BM3D Denoising Method and Features Extraction

Author

Sriraam, N., Kavya, N., Usha, N., Sharath, D., Venkatraman, B., Menaka, M., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Kumar, Amit, editor, Senatore, Sabrina, editor, and Gunjan, Vinit Kumar, editor

Published
2022
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