No abstract

In this paper, a novel metric is defined that will allow one to compare the performance of 3-D pattern recognition systems. Any real object is inherently, three-dimensional. Therefore, any input object for an automated target recognition system should be ideally compared to the 3-D information about the object. The proposed metric captures the essence of such comparisons.

The advancements in technology, as well as the digitization of relationships, had a significant impact on the centennials' decision to maintain a social media account. Despite the entertainment provided by social media, cyberbullying has been identified as a real issue all over the world, with many centennials becoming victims. However, a few studies have been reported in detecting cyberbullying attempts on social media. As a result, a solution that employs appropriate data science techniques to detect cyberbullying attempts on social media would be ideal. The suspicious tweets dataset from Kaggle was used in this study to build three supervised learning predictive models, namely Naive Bayes, which were tuned using Random Grid Search and Keras tuner to indicate a suitable solution.