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This dataset emerges from an educational experiment designed to evaluate the effectiveness of a Blockly-based tool in teaching Solidity, the predominant language for the creation of smart contracts on the Ethereum blockchain. Students from a Master's degree in Information Systems Engineering participated and used this tool with the aim of mitigating the learning curve of Solidity. The dataset includes metrics on student satisfaction with using the tool.

This dataset abstract presents findings from a comprehensive survey conducted to investigate the impact of social media on high school students in Bangladesh. With the pervasive influence of social media platforms in contemporary society, particularly among the younger demographic, understanding its effects on adolescent behavior, mental health, academic performance, and social interactions is of paramount importance.

In situations when the precise position of a machine is unknown, localization becomes crucial. It is crucial to identify and ascertain the machine's position. This research focuses on improving the position prediction accuracy over long-range networks using a unique machine learning-based technique. In order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting approach using LoRa technology, this study suggested an ML-based algorithm.

Abstract— Objective: Pulse oximetry is widely used to measure photoplethysmographic (PPG) signals and blood oxygen saturation but is susceptible to motion artifacts. This is a particular challenge for the growing field of wearable health devices. Independent component analysis (ICA) offers a solution for artifact removal without additional sensors. As there are different approaches for performing an ICA and because artifacts can take many forms, the optimal configuration is unknown.