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Average-time-computation
The tracking framework is event based, so the App sends events the instant they happen: to evaluate the average time spent in a lesson we need to run a calculation. Tracking is anonymous by design: the App does not require a login, so we donβt know anything about users. We do track a device id, but we know that in a school environment we will likely have multiple users using the same device. We track app launch events, steps in a lesson, pause and resume events and hub connection events. We attach a session_id to every event where we define a βsessionβ as the time interval when the App is active (sending events) with pauses not longer than 10 minutes, so if the user is not active on the App for more than 10 minutes, a new session is started.Prime-Power-Tester
Given a natural number as an input, we can check if this number is a prime power.Waterhouse-s-Theorem
Python Code for Waterhouse's classification theorem on Elliptic curves, defined over a finite fieldLove Open Source and this site? Check out how you can help us