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  • Droplet impact onto a spring-supported plate: analysis and simulations

    Authors: Michael J. Negus, Matthew R. Moore, James M. Oliver, Radu Cimpeanu
    DOI: https://doi.org/10.1007/s10665-021-10107-5
    Submitted by MNegus      
      Mean reproducibility score:   8.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    The direct numerical simulations (DNS) for this paper were conducted using Basilisk (http://basilisk.fr/). As Basilisk is a free software program written in C, it can be readily installed on any Linux machine, and it should be straightforward to then run the driver code to re-produce the DNS from this paper. Given this, the numerical solutions presented in this paper are a result of many high-fidelity simulations, which each took approximately 24 CPU hours running between 4 to 8 cores. Hence the difficulty in reproducing the results should mainly be in the amount of computational resources it would take, so HPC resources will be required. The DNS in this paper were used to validate the presented analytical solutions, as well as extend the results to a longer timescale. Reproducing these numerical results will build confidence in these results, ensuring that they are independent of the system architecture they were produced on.

  • REMoDNaV: robust eye-movement classification for dynamic stimulation

    Authors: Asim H. Dar, Adina S. Wagner, Michael Hanke
    DOI: https://doi.org/10.3758/s13428-020-01428-x
    Submitted by adswa    

    Why should we attempt to reproduce this paper?

    In theory, reproducing this paper should only require a clone of a public Git repository, and the execution of a Makefile (detailed in the README of the paper repository at https://github.com/psychoinformatics-de/paper-remodnav). We've set up our paper to be dynamically generated, retrieving and installing the relevant data and software automatically, and we've even created a tutorial about it, so that others can reuse the same setup for their work. Nevertheless, we've for example never tried it out across different operating systems - who knows whether it works on Windows? We'd love to share the tips and tricks we found to work, and even more love feedback on how to improve this further.

  • Hyperparameter importance Across Datasets

    Authors: Jan N van Rijn and Frank Hutter
    DOI: 10.1145/3219819.3220058
    Submitted by hub-admin    
      Mean reproducibility score:   7.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    I tried hard to make this paper as reproducible as possible, but as techniques and dependencies become more complex, it is hard to make it 100% clear. Any form of feedback is more than welcome.