Standards Research Data

Extensive use of unmanned aerial vehicles (UAVs) is expected to raise privacy and security concerns among individuals and
communities. In this context, detection and localization of UAVs will be critical for maintaining safe and secure airspace in the
future. In this work, Keysight N6854A radio frequency (RF) sensors are used to detect and locate a UAV by passively monitoring
the signals emitted from the UAV. First, the Keysight sensor detects the UAV by comparing the received RF signature with various

Air travel is one of the most used ways of transit in our daily lives. So it's no wonder that more and more people are sharing their experiences with airlines and airports using web-based online surveys. This dataset aims to do topic modeling and sentiment analysis on Skytrax (airlinequality.com) and Tripadvisor (tripadvisor.com) postings where there is a lot of interest and engagement from people who have used it or want to use it for airlines.

Several works attempted to establish procedures to individuate bugs, defects or anomalies during the different phases of software development, especially in the implementation phase. The mere detection of anomalies is not sufficient, though, at least until they get fixed. Corrective actions can be formulated to remove anomalies and enhance the software quality. Preventive actions are equally important in as much as they avoid the emergence and recurrence of anomalies in the future.

Some novel methods for imaging based on synthetic aperture radar can result in images contaminated by artifacts as a consequence of pushing the limits of the algorithms. In order to mitigate the impact of this artifacts, image translation techniques can be exploited enabling to turn the SAR image into a cleaner one. For this purpose, multiple techniques can be used such as convolutional neural networks or generative adversial networks. However, the training of those systems can require a high number of images, which can be computationally expensive to generate.