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Your search keyword '"Sarma Dhulipala, V. R."' showing total 13 results
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13 results on '"Sarma Dhulipala, V. R."'

3. Machine Learning Model for Anomaly Detection in Big Data for Health Care Applications

Author

Sharavana Kumar, M. G., Sarma Dhulipala, V. R., 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, 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, Zhang, Junjie James, Series Editor, Bindhu, V., editor, Tavares, João Manuel R. S., editor, Boulogeorgos, Alexandros-Apostolos A., editor, and Vuppalapati, Chandrasekar, editor

Published
2021
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9. AEECA for Reliable Communication to Enhance the Network Life Time for WSN.

Author

Jayaraman, Ganesh and Sarma Dhulipala, V. R.

Subjects
TELECOMMUNICATION systems, WIRELESS sensor networks, SENSOR networks, ROUTING algorithms, WIRELESS communications, GATEWAYS (Computer networks)
Abstract

Nowadays, wireless sensor networks play a vital role in our day to day life. Wireless communication is preferred for many sensing applications due its convenience, flexibility and effectiveness. The sensors to sense the environmental factor are versatile and send sensed data to central station wirelessly. The cluster based protocols are provided an optimal solution for enhancing the lifetime of the sensor networks. In this paper, modified K-means ++ algorithm is used to form the cluster and cluster head in an efficient way and the Advanced Energy-Efficient Cluster head selection Algorithm (AEECA) is used to calculate the weighted factor of the transmission path and effective data collection using gateway node. The experimental results show the proposed algorithm outperforms the existing routing algorithms. [ABSTRACT FROM AUTHOR]

Published
2023
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13. Maintaining Security and Privacy in Health Care System Using Learning Based Deep-Q-Networks.

Author

Mohamed Shakeel, P., Baskar, S., Sarma Dhulipala, V. R., Mishra, Sukumar, and Jaber, Mustafa Musa

Subjects
COMPUTER viruses, COMPUTERS, MACHINE learning, MANAGEMENT information systems, MEDICAL ethics, ARTIFICIAL neural networks, PRIVACY, RELIABILITY (Personality trait), DATA analysis, DATA security, ELECTRONIC health records, INTERNET of things
Abstract

In the recent past, Internet of Things (IoT) plays a significant role in different applications such as health care, industrial sector, defense and research etc.… It provides effective framework in maintaining the security, privacy and reliability of the information in internet environment. Among various applications as mentioned health care place a major role, because security, privacy and reliability of the medical information is maintained in an effective way. Even though, IoT provides the effective protocols for maintaining the information, several intermediate attacks and intruders trying to access the health information which in turn reduce the privacy, security and reliability of the entire health care system in internet environment. As a result and to solve the issues, in this research Learning based Deep-Q-Networks has been introduced for reducing the malware attacks while managing the health information. This method examines the medical information in different layers according to the Q-learning concept which helps to minimize the intermediate attacks with less complexity. The efficiency of the system has been evaluated with the help of experimental results and discussions. [ABSTRACT FROM AUTHOR]

Published
2018
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