Sentiment analysis is crucial in understanding and analyzing public opinions, feedback, and social media data. In this study, we propose a modified Bayesian Boosting algorithm with weight-guided optimal feature selection for sentiment analysis. The goal is to improve the accuracy and efficiency...

In recent decades, India's environment has been severely compromised by riverine pollution combined with large-scale dams and exacerbated by diversion for irrigation. Most prominent among the rivers so affected has been the Ganges and its tributaries in northern India, which for Hindus include...

We propose the river pollution claims problem to distribute a pollution budget among agents located along a river. A key distinction with the standard claims problem is that agents are ordered exogenously. For environmental reasons, the location of pollution along the river is an important...

We provide a theoretical framework to analyze how climate change influences the Ganges and how this influence affects pollution in the river caused by tanneries in Kanpur, India. We focus on two tanneries, A and B, that are situated on the same bank of the Ganges in Kanpur. Both produce leather...