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Twitter is one of the most popular social networks for sentiment analysis. This data set of tweets are related to the stock market. We collected 943,672 tweets between April 9 and July 16, 2020, using the S&P 500 tag (#SPX500), the references to the top 25 companies in the S&P 500 index, and the Bloomberg tag (#stocks). 1,300 out of the 943,672 tweets were manually annotated in positive, neutral, or negative classes. A second independent annotator reviewed the manually annotated tweets.

This dataset consists of realistic simulated inverse synthetic aperture radar (ISAR) images of five commonly found automotive targets- a full-size car, a mid-size car, a bicycle, an auto-rickshaw, and a four-wheel truck.

WITH the advancement in sensor technology, huge amounts of data are being collected from various satellites. Hence, the task of target-based data retrieval and acquisition has become exceedingly challenging. Existing satellites essentially scan a vast overlapping region of the Earth using various sensing techniques, like multi-spectral, hyperspectral, Synthetic Aperture Radar (SAR), video, and compressed sensing, to name a few.

This dataset supports the manuscript entitled "Beam Diffraction by the Tip of a Cone and Creeping Beam Waves: Phenomenology Analysis Via the Generalized Complex-Source Method", accepted for publication in the IEEE Transactions on Antennas and Publication. The dataset consists of movies in both formats .avi and .mp4, which show time-domain representations of figures presented in the publication. They are intented to give a further insight into the wave physics and particularly to give evidence that the results are causal.