Abstract: A malware classification is generated for an input data set with a human-readable explanation of the classification. An input data set having a hierarchical structure is received in a neural network that has an architecture based on a schema determined from a plurality of second input data sets and that is trained to classify received input data sets into one or more of a plurality of classes. An explanation is provided with the output of the neural network, the explanation comprising a subset of at least one input data set that caused the at least one input data set to be classified into a certain class using the schema of the generated neural network. The explanation may further be derived from the statistical contribution of one or more features of the input data set that caused the at least one input data set to be classified into a certain class.

Abstract: A system and method for planning/replanning collision free flight plans in real-time (or accelerated-time) including planning individual flight plans for each flying asset, executing (or simulating) the planned individual flight plans, detecting violations of safety zones of each of the flying assets by negotiation and by other assets monitoring (radar sensing), and repairing the individual flight plans by real-time replanning.

Abstract: A system and method for planning/replanning collision free flight plans in real-time (or accelerated-time) including planning individual flight plans for each flying asset, executing (or simulating) the planned individual flight plans, detecting violations of safety zones of each of the flying assets by negotiation and by other assets monitoring (radar sensing), and repairing the individual flight plans by real-time replanning.