Coursework for the course TIES451 (JYU)
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Updated
Mar 15, 2018 - Python
Coursework for the course TIES451 (JYU)
CYCASP is a methodology for investigating and understanding (C)olon(Y) growth and (C)ell (A)ttributes at the population level. It couples (SP)atiotemporal changes by relying on two novel data abstractions and a modular algorithm.
SeeVIS is a (S)egmentation-fr(ee) (VIS)ualization pipeline for time-lapse image data. It comprises three steps: 1. preprocessing, 2. feature extraction, and 3. an extended version of the space time cube with three novel color mappings adapted to cell colony growth.
Ministry of Random Walks
Turn a Christmas tree on/off using Siri, GCP, and a Particle Photon.
Using Particle Swarm Optimization to solve a real life problem of hostel room allocation. In this problem rooms need to be allocated to a group of people, each of whom have a different preference for each room.
particle-in-cell code for plasma modelling, in development
Particle filter in Python.
Bash completion for particle-cli
Procedures to identify stereo imaged particles and calculate particle size distributions
Calculation of the trajectory of a spinning particle around a black hole with an arbitrary metric tensor.
Particle Swarm Optimisation algorithm with visualization.
Arduino Uno moisture detection
Convert DazStudio hair to particle Hair in Blender. Fork of Blender Plugin created by Cinus.
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