Abstract: In some aspects, the techniques described herein relate to a method including: providing, on a peer-to-peer distributed network, an aggregation server; implementing, at a first node of the peer-to-peer distributed network, a machine learning (ML) model, wherein the ML model is trained on a first private data set; sending the ML model to the aggregation server; replicating the ML model to a second node of the peer-to-peer distributed network, wherein the ML model is retrained on a second private data set to generate a retrained model; sending the retrained model to the aggregation server; aggregating the ML model and the retrained model to generate an aggregated model; and replicating the aggregated model to the first node of the peer-to-peer distributed network, wherein the ML model is promoted to a production model at the first node of the peer-to-peer distributed network.

Abstract: A system for propelling a nanosatellite, including a pair of separated electrodes defining an ignition space therebetween a power source operationally connected to the pair of separated electrodes. Also included is a liquid propellant reservoir a pump reconnected in fluidic communication with reservoir and the ignition space and an electronic controller operationally corrected to the power source and to the pump.

Abstract: A system for propelling a nanosatellite, including a pair of separated electrodes defining an ignition space therebetween a power source operationally connected to the pair of separated electrodes. Also included is a liquid propellant reservoir a pump reconnected in fluidic communication with reservoir and the ignition space and an electronic controller operationally corrected to the power source and to the pump.