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Abstract Advances in AI have transformed the traditional Internet of Things (IoT) into smarter, more versatile next-generation devices. Enhanced connectivity among sensors, actuators, and appliances boosts data availabil...

Abstract This paper investigates the extent to which dishonest behavior can be predicted using behavioral personality traits and physiological information. An interpretable machine learning approach, SHapley Additive exP...

Abstract Skeletal fluorosis (SF) is a chronic metabolic bone disease resulting from long-term excessive fluoride exposure, affecting millions worldwide. Conventional diagnosis relies on radiographic evidence, which often...

Abstract Proposed research presents a data-driven framework for forecasting municipal solid waste (MSW) generation and emission dynamics in Erode City, India, by employing supervised machine learning algorithms. Leveragi...

Abstract Roadside areas are major sources of traffic-related air pollutant emissions. This study identified the spatial distribution of roadside pollutants using Unmanned Aerial Vehicle (UAV) measurements and predicted t...

Abstract Alzheimer’s disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of accessible early diagnostic methods. Even though it has en...