tropess-notes
A practical guide to using TROPESS data products. Delivered as Jupyter Notebooks in Python
https://github.com/0xjepsen/modelingwormpropogation
The purpose of this program is to study the propagation of worm on the three different types of networks through simulation when no cure (that is, worm defense) is applied. In other words, the worm will continue to spread until no uninfected node remains.
https://github.com/0xjepsen/memorymanager
The memory management module is responsible for: Implementing the core functionality of this assignment. It is responsible for: 1. Allocating and de-allocating data structures 2. Populating elements in the data structure 3. Computing the median element within the data structure 4. Checking to see if the median number is divisible by 13 5. Maintaining a running count of median elements that were divisible by 13.
https://github.com/hyperledger-caliper/caliper-benchmarks
Sample benchmark files for Hyperledger Caliper https://wiki.hyperledger.org/display/caliper
https://github.com/0xjepsen/lean-riemann-hypothesis
Riemann Hypothesis in Lean
ucum_agri-food_units
A table of UCUM units commonly used in agri-food research which helps with data documentation and interoperability.
ProxAL
Proximal Augmented Lagrangian solver for solving multiperiod contingency-constrained ACOPF
https://github.com/0xjepsen/linear_regresssion
This is a simple model of reducing error for linear regression written in python as an exercise.
