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18 results on '"Pugalenthi, R."'

6. RANC-CROP Recommendation Attributed to Soil Nutrients and Stock Analysis Using Machine Learning.

Author

Daniel, Jesline, Shyamala, R., Pugalenthi, R., and Mohan Kumar, P.

Subjects
ARTIFICIAL neural networks, MACHINE learning, ORGANIC fertilizers, STOCKS (Finance), WEB-based user interfaces
Abstract

Agriculture is India's greatest wealth, which also contributes to the country's economic development and defines the standard of living for more than 50 percent of the Indian population. In addition to this conventional crop, more are grown and have high dependency, such as wheat and rice. Farmers face many problems where sustainability is of primary importance in agriculture. To solve the issue, we propose to develop a "RANC (Recommendation Analysis by Soil Nutrients of Crops) Crop Recommendation Tool" web application that will help farmers generate their high income with effective crop cultivation along with the suggestion of organic fertilizer by providing up-to - date stock information, Soil Test Report, crop yield time and nutritional value of each crop. The RANC algorithm is used to pick crops and the Deep Neural Network is used for price prediction to improve the farmer's choice of crops for cultivation with a high benefit. In the case of crop selection, an existing model uses the Soil Test Report to generate the quantity of fertilizers needed to expand. We use SVM for linear data regressions and ANN, RNN, RBM for non-linear data in the case of price estimation in stock analysis. From the experimental results, the prediction accuracy over 90% has been achieved for the proposed approach. [ABSTRACT FROM AUTHOR]

Published
2023
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16. AN EFFICIENT AND VARIABLE INTERVAL REKEYING FOR DYNAMIC AD HOC MULTICAST GROUP USING KEY PATH REDUCTION

Author

Pugalenthi R, Dr.Pugalenthi R, and Gopal Tadepalli

Subjects
Multicast, Computer Networks and Communications, business.industry, Wireless ad hoc network, Computer science, Distributed computing, Key distribution, Encryption, Artificial Intelligence, Scalability, Rekeying, Key server, business, Software, Group key, Computer network
Abstract

Key distribution is one of the major issues in secure ad hoc multicast group communication. There has been an extensive research on rekeying, to reduce cost. In this study, we propose an efficient and scalable batch rekeying for dynamic ad hoc multicast group, with variable interval and key path reduction techniques. The proposed scheme overcomes the major existing issues like inefficiency in using the keys that are generated and distributed, the sync issue in which a user tries to decrypt a data using an irrelevant key, imbalance in network traffic and latency in the key server response to the user request, for leaving and joining at once. Generally, a central key server is used to govern all the above issues. The proposed scheme excludes the usage of a central key server by generating the group key in the individual nodes, which minimizes the communication overhead and the number of keys that each user possesses. The proposed scheme also reduces the depth of the tree very effectively, when a user joins or leaves the group, using key path reduction technique and ensures forward and backward secrecy. The simulation result shows better performance when compared to individual, regular batch and periodic rekeying.

Published
2014

17. Energy management of grid connected PV with efficient inverter based wireless electric vehicle battery charger: A hybrid CSA-QNN technique

Author

Meenalochini, P., Priya, R.A., Pugalenthi, R., and Jagadeeshwaran, A.

Abstract

A Hybrid CSA-QNN approach is proposed in this manuscript for grid-connected PV with an efficient inverter-based wireless electric vehicle (EV) battery charger. The proposed hybrid method combines the performance of both the circle search algorithm (CSA) and quantum neural networks (QNN), commonly named the CSA-QNN technique. The Circle Search Algorithm helps find the best charging spot by creating a virtual circle, while the Quantum Neural Network optimizes the overall power flow and charging efficiency. Together, these technologies contribute to making wireless charging for EVs more efficient and convenient. The major goal of the manuscript is the design of a wireless EV battery charger with PV integration. Wireless EV charging systems (WEVCS) may be a feasible alternative technology for charging EVs without a plug-in problem. The CSA-QNN method is performed in the MATLAB platform and it is compared to different existing approaches. The CSA-QNN method shows better results than the existing approaches like the Salp Swarm Algorithm (SSA), Wild horse optimizer (WHO), and Particle Swarm optimization (PSO).

Published
2023
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