Search

Your search keyword '"Radhika, N."' showing total 816 results
Start Over Author "Radhika, N."
816 results on '"Radhika, N."'

3. Predicting and Evaluating Anomaly Detection and Traffic Analysis on Software Defined Networks Using a Hybrid Machine Learning Approach

Author

Darshan, S., Radhika, N., Radhika, G., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, 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, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, 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, Tan, Kay Chen, Series Editor, M. Thampi, Sabu, editor, Siarry, Patrick, editor, Atiquzzaman, Mohammed, editor, Trajkovic, Ljiljana, editor, and Lloret Mauri, Jaime, editor

Published
2025
Full Text
View/download PDF

6. Optimizing tool offset in static shoulder friction stir welding of Al6061 to Ti6Al4V for enhanced joint integrity

Author

Saravana Sundar A, Radhika N, and Adepu Kumar

Subjects
Tool offset, Texture analysis, Microhardness, Dissimilar joints, Fracture analysis, Mining engineering. Metallurgy, TN1-997
Abstract

The precise control of tool offset in static shoulder friction stir welding (SSFSW) is vital for enhancing the mechanical properties and overall effectiveness of dissimilar metal joints. The present study investigates the impact of tool offset on the development of microstructural features, intermetallic compound formation, texture analysis, and mechanical characteristics of SSFSWed Al6061 to Ti6Al4V joints. The results demonstrate that a 2.5 mm tool offset results in an average grain size of 2.65 μm, compared to larger grains of about 4.76 μm and 7.31 μm observed at 2.0 mm and 1.5 mm offsets, respectively. The percentage of low-angle grain boundaries also varies, reaching up to 42.2% at a 2.5 mm offset compared to 48.6% at 2.0 mm and 64.1% at 1.5 mm, indicating enhanced homogeneity in the microstructural properties. Moreover, the ultimate tensile strength at the 2.5 mm tool offset reaches 279 MPa, which is 5.7% higher than at the 2.0 mm offset and 13.4% higher than at the 1.5 mm offset. This improvement is attributed to more uniform distribution of Ti particles over the stir zone. Texture analysis further supports these findings, with the development of alpha fibre at 2.5 mm offset enhancing ductility, thereby underscoring the critical role of tool offset in achieving sound dissimilar metal weldments.

Published
2024
Full Text
View/download PDF

16. Analysis on Detecting Cardiac Arrhythmia Using Advanced Technologies

Author

Radhika, N., Sujatha, D., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Bhateja, Vikrant, editor, Lin, Hong, editor, Simic, Milan, editor, Tang, Jinshan, editor, and Sivakumar Reddy, Vustikayala, editor

Published
2024
Full Text
View/download PDF

27. Diagnosis of sickle cell anemia using AutoML on UV-Vis absorbance spectroscopy data

Author

Srivastava, Sarthak, K., Radhika N., Srinivasan, Rajesh, Nambison, Nishanth K M, and Gorthi, Sai Siva

Subjects
Quantitative Biology - Quantitative Methods, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Sickle cell anemia is a genetic disorder that is widespread in many regions of the world. Early diagnosis through screening and preventive treatments are known to reduce mortality in the case of sickle cell disease (SCD). In addition, the screening of individuals with the largely asymptomatic condition of sickle cell trait (SCT) is necessary to curtail the genetic propagation of the disease. However, the cost and complexity of conventional diagnostic methods limit the feasibility of early diagnosis of SCD and SCT in resource-limited areas worldwide. Recently, our group developed a low-cost UV-Vis absorbance spectroscopy based diagnostic test for SCD and SCT. Here, we propose an AutoML based approach to classify the raw spectra data obtained from the developed UV-Vis spectroscopy technique with high accuracy. The proposed approach can detect the presence of sickle hemoglobin with 100% sensitivity and 93.84% specificity. This study demonstrates the potential utility of the machine learning-based absorbance spectroscopy test for deployment in mass screening programs in resource-limited settings.

Published
2021

39. Movement Analysis of Mentally Challenged Individuals Using Cloud and Machine Learning Model

Author

Mathew, Ashams, Radhika, N., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Gupta, Deepak, editor, Kansal, Vineet, editor, Fortino, Giancarlo, editor, and Hassanien, Aboul Ella, editor

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results