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adm1

python codes for IWA ADM1

anaerobicdigestion

The purpose of this app is to optimize the model parameters in order to increase the profitability of the bioreactor. The user will be able to adjust initial bacteria concentrations, reactor temperature (both static and dynamic), etc., and see a visual representation of the outcome. Note that not all adjustable parameters will have an effect on every plot. As soon as the user loads the app, the model is compiled and run using the current parameter settings. As the user adjusts these parameters, the plots and tables will update according to the new settings once the "Re-simulate" button has been clicked (This button is on each of the table and plot tabs). The tabs on the left then allow the user to navigate the simulated reactor output and read more about the process. You can also specify the time in which to truncate the data and evaluate the output, though the minimum value is currently 100 h. The reactor that follows the anaerobic digestor is capable of removing small quantities left over. Ideally you would set a minimum acceptable concentration, and optimize parameters to decrease the time required to reduce the contaminants to that concentration, though this not been implemented due to the lack of observational data.

asrh

bayesianml-mcmc

Bayesian Model Inference using MCMC

covid-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

diffeqtutorials.jl

Tutorials for using the DiffEq ecosystem

gan-70-lines-of-julia

A Knet implementation of MLP GAN for MNIST data.

glmspiketools

Fitting and simulation of Poisson generalized linear model for single and multi-neuron spike trains (Pillow et al 2008).

graph-neural-network-review

hello-world

hfm

Hidden Fluid Mechanics

jadm1

A Java implementation of the Anaerobic Digestion Model No 1 (ADM1) with modifications

jadm1_bsm

A Java implementation of the Anaerobic Digestion Model No 1 (ADM1) that can be validated using the BSM2 Matlab code.

mcerp

Real-time latin-hypercube sampling-based Monte Carlo ERror Propagation

metagenome_analyses

Using IDBA-ud, this is how we assemble metagenomic reads into scaffolds on different projects

metagenome_emirge

model-sensitivity-analysis

Latin hypercube sampling and partial rank correlation coefficients

particleswarmoptimization

Matlab implementation of particle swarm optimization. Well documented with examples.

precintcon_pcp

precintcon is an R package with functions to analyze the precipitation intensity, concentration, and anomaly.

pydtmc

A framework for discrete-time Markov chains analysis.

stimulus_neural_populations

A framework for simulating mean-field neural mass models of spiking neurons, comparing them to large network simulations, and predicting electrical stimulation responses of neural populations.

thinkstats2

Text and supporting code for Think Stats, 2nd Edition