There are 0 repository under emission topic.
A Planetary Intensity Code for Atmospheric Spectroscopy Observations
Create WRF-Chem emission file from your local emissions disaggregated in space and time.
Utilities for pre-processing emission-excitation-matrix (EEM).
python apps to communicate between one server and multiple clients with the GUI Tkinter. Something like What'sApp but only with text messages
Learn how you can animate the elusive "Intensity" property on the color picker in this beginner friendly tutorial!
Contracts for WHF
[ECC 2022] Codebase for the paper titled "Learning Eco-Driving Strategies at Signalized Intersections".
An application to subtract the excitation source contribution from phosphorescent emission data
Strea - Emissions Supplychain Platform. First release during Energy Hackathon in Bern, Switzerland :snowflake: :chocolate_bar:
Real time volume rendering of large voxel data sets with support for global ambient occlusion and emission.
Turn off particle system emission and accelerate the remaining particles' lifetimes to ensure they all decay within a specified time.
This software provides an easily accessible, user-friendly tool to allow researchers to process and analyze photoluminescence spectra.
Basic Prediction regarding factors leading to the emission of CO2 from vehicles
R package for speedy emissions estimation using models trained on catserver data (MOVES default outputs)
Our code contribution to the DNV Hackathon of 2022.
My work during the Research Training program at Tampere University
Calculates emission, transition, and OOV frequencies for documents given a training dataset. From my undergraduate NLP class at NYU.
Author: Leopold Wambersie Thesis director: Claudiane Ouellet-Plamondon Department: Départment de genie de la construction, École de technologie supérieure, Montréal, Canada Funding from : Canada Research Chairs Programme This repository contains the code necessary to run the analyses presented in the paper "Developing a comprehensive account of em
Predict emission from transportation using machine learning