Titlebook: Artificial Intelligence and Data Science Based R&D Interventions; Proceedings of NERC Ratnajit Bhattacharjee,Debanga Raj Neog,Santosh Ku C

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https://doi.org/10.1007/978-3-662-69594-4bsea construction. High-resolution cameras, sonar technology, battery technology, better manipulators, and other advances in UUV technologies have led to reduced computational time and effort for underwater inspection and exploration. But the dynamic underwater environment like underwater currents a

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Ratnajit Bhattacharjee,Debanga Raj Neog,Santosh KuSelected peer-reviewed papers presented in NERC 2022.Enriches understanding by including contributions from policy makers, industrialist and academicians.Showcase the best R&D activities from all the

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Negation in a Language, found in Bengali negation and most of these are in linguistic aspect. This work is dedicated to a corpus-based study of Bengali negation that explores their frequencies at word level as well as sentence level and also explores various unexplored features from the computational point of view. The ou

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,COVID-19 Neologism in the Assamese Language,ted newly coined terms are retrieved from that corpus. Algorithm point of view, set-difference operation and frequency analysis are used to identify the neologism. As far as we are aware, this work is the first to identify the neologism in the Assamese language. It is also a pioneering attempt in th

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A Computational Approach for the Tonal Identification in Bodo Language,oted that the tone depends on the context of the sentence and hence needs the context information. Now this problem is quite similar to the word sense disambiguation (WSD) and can be adopted for this problem with suitable changes. In these particular cases, we have used the modified Lesk algorithm.

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Multi-objective Optimization in NOMA-IoT Networks,propagation while Evolution strategies can rival gradient-based algorithm. In this work, we omit the use of backpropagation and replace it with genetic algorithm. It is a challenging task when considering long-term reward maximization in the network. Reinforcement learning with Markov decision proce

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Prediction and Forecasting Municipal Solid Waste Generation of Northeastern Cities by Retrofitting uild the models. Additionally, moving average (MA) approaches were adapted for forecasting the MSWG rate. Experimental results showed that ML algorithms can be efficaciously applied to learn waste models with good prediction performance. Further, GB was taking more computation time because of its hi

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Prediction of Transient Bed Profiles in an Aggrading Stream Using ANN,ure, the approach of trial and error is used. After fixing, the number of iteration training of the networks for different activation functions is calculated. The statistical parameters like coefficient of correlation (R), determination coefficient (R.), mean square error (MSE), root mean square err