Download JAR files tagged by signal with all dependencies

The chart-fx charting library is an extension in the spirit of Oracle's XYChart and performance/time-proven JDataViewer charting functionalities. Emphasis was put on plotting performance for both large number of data points and real-time displays, as well as scientific accuracies leading to error bar/surface plots, and other scientific plotting features (parameter measurements, fitting, multiple axes, zoom, ...). The library also contains a small set of math routines that can operate directly on the DataSet primitive for fitting, computing spectra, linear algebra, FIR/IIR filtering, and other functionalities common to signal processing.

Virgil Security is presenting an implementation of the [Double Ratchet](https://signal.org/docs/specifications/doubleratchet/) algorithm, which is used by parties to exchange encrypted messages based on a shared secret key. The implementation includes: - **Virgil Perfect Forward Secrecy (PFS) service** – a standalone web-service that is dedicated to managing one-time keys and long-time keys that are based on their Identity Public Keys (public keys that are contained in user cards published on Virgil Cards service); - **Ratchet SDK** – interacts with PFS service for publishing and managing one-time keys and long-time keys and interacts with Virgil Cards service for retrieving user's indentity cards which the OTK and LTK are based on. The parties derive new keys for every Double Ratchet message so that previous private keys cannot be calculated from new ones. The parties that participate in the communication also send Diffie-Hellman public values attached to their messages. The results of Diffie-Hellman calculations are mixed into the derived keys so that the new private keys cannot be calculated from the previous ones.

Virgil Security is presenting an implementation of the [Double Ratchet](https://signal.org/docs/specifications/doubleratchet/) algorithm, which is used by parties to exchange encrypted messages based on a shared secret key. The implementation includes: - **Virgil Perfect Forward Secrecy (PFS) service** – a standalone web-service that is dedicated to managing one-time keys and long-time keys that are based on their Identity Public Keys (public keys that are contained in user cards published on Virgil Cards service); - **Ratchet SDK** – interacts with PFS service for publishing and managing one-time keys and long-time keys and interacts with Virgil Cards service for retrieving user's indentity cards which the OTK and LTK are based on. The parties derive new keys for every Double Ratchet message so that previous private keys cannot be calculated from new ones. The parties that participate in the communication also send Diffie-Hellman public values attached to their messages. The results of Diffie-Hellman calculations are mixed into the derived keys so that the new private keys cannot be calculated from the previous ones.

An empty artifact that Guava depends on to signal that it is providing ListenableFuture -- but is also available in a second "version" that contains com.google.common.util.concurrent.ListenableFuture class, without any other Guava classes. The idea is: - If users want only ListenableFuture, they depend on listenablefuture-1.0. - If users want all of Guava, they depend on guava, which, as of Guava 27.0, depends on listenablefuture-9999.0-empty-to-avoid-conflict-with-guava. The 9999.0-... version number is enough for some build systems (notably, Gradle) to select that empty artifact over the "real" listenablefuture-1.0 -- avoiding a conflict with the copy of ListenableFuture in guava itself. If users are using an older version of Guava or a build system other than Gradle, they may see class conflicts. If so, they can solve them by manually excluding the listenablefuture artifact or manually forcing their build systems to use 9999.0-....

The rooster crows immediately before sunrise, the rooster causes the sun to rise. Using GraphX to detect possible causes and effects between time related events. We observe a true causation signal by generating random correlations over same events at different time and back propagate these scores to their most connected events. Finally, we extract the most probable causes and effects together with a score of aggressiveness (how likely an event could explain downstream effects) and sensitivity (how likely an event results from an upstream cause).