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  • This is the source code for developing the GUGPS (Global urban growth projection using SLEUTH urban growth model) published at Scientific Data. Please read the README.docx file inside carefully prior to use. The code consists of two R programming language scripts (version R 3.4.3; https://www.r-project.org/), which prepare simulation inputs and integrate outputs. The script is internally documented to assist understanding and customisation for further use.We have also shared the modified SLEUTH model, as well as the scenario.jinja file in the Python package sleuth-automation (version 1.0.2; https://pypi.org/project/sleuth-automation/).
    Data Types:
    • Software/Code
  • The Low Energy Building Assembly Selector was developed in collaboration between The University of Melbourne and Williams Boag Architects and supported by the Australian Research Council under project LP120200306. The tool provides a means for building designers and other construction industry professionals to make informed decisions regarding the selection of construction assemblies for optimising a building’s life cycle energy demand. The Low Energy Building Assembly Selector can be accessed here: http://bit.ly/assemblyselector
    Data Types:
    • Software/Code
  • This project contains codes for deploying MMD-GAN using the repulsive loss, for the following paper: Wei Wang, Yuan Sun, Saman Halgamuge. Improving MMD-GAN Training with Repulsive Loss Function. ICLR 2019. URL: https://openreview.net/forum?id=HygjqjR9Km. For more details, please refer to the paper and Github page.
    Data Types:
    • Software/Code
  • Written in Python 2.7.
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    • Software/Code
  • This is the Stata code used for the PLOS One paper 'Estimating the completeness of death registration: an empirical method'. The data used to produce the results for the paper can be found in figshare under the following title" 'Estimating the completeness of death registration: an empirical method - data'
    Data Types:
    • Software/Code
  • demonstration
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    • Software/Code
  • This repository contains the disease transmission and clinical pathways models used in our modelling study, "Reducing disease burden in an influenza pandemic by targeted delivery of neuraminidase inhibitors: mathematical models in the Australian context", and is distributed under the terms of the GNU General Public License (version 3 or any later version).
    Data Types:
    • Software/Code
  • Supplementary material for journal article.
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    • Software/Code
  • Simulation model used to evaluate the impact of Ebola outbreaks
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    • Software/Code
  • This code carries out the two calculations in Rubino et al., Nature Geoscience, 2016.
    Data Types:
    • Software/Code