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100 results for “Reproduction package”
Reproduction package to "Ultra-sensitive THz Microwave Kinetic Inductance Detectors for future space telescopes"
<p>This is a reproduction package to the paper "Ultra-sensitive THz Microwave Kinetic Inductance Detectors for future space telescopes", published in <a href="https://doi.org/10.1051/0004-6361/202243840">Astronomy and Astrophysics, 665, A17 (2022)</a>. It contains the data and code to reproduce the figures in this paper.</p> <p>This version 2 includes minor changes to make figures and code consistent with the published version of the manuscript after review.</p>
Reproduction package for the publication "Tidal disruption event AT2020ocn: early-time X-ray flares caused by a possible disc alignment process"
<p>This package contains the data analysed in the paper "Tidal disruption event AT2020ocn: early–time X–ray flares caused by a possible disc alignment process". The software XSPEC (Arnaud 1996) is needed to perform the spectral analysis and reproduce the results shown in the paper.</p> <p>The structure is as follows:</p> <p>./reproduction_ocn/nicer: contains all processed NICER data used in the paper, grouped by their epochs. "speclist-early.dat" lists all the early-time epochs before MJD 59130. "en_range.dat" lists the selected energy range at each epoch during the early-time period for X-ray spectral analysis. Within each epoch-specific folder, "src.fits" and "bkg.fits" are the source+background and background spectra re-binned using the FTOOL "ftgrouppha"; "*.arf" and "*.rmf" are ancillary file and response file for spectral analysis; rest files are direct products of the NICER data reduction process. See the paper for details.</p> <p>./reproduction_ocn/swift: contains all Swift/UVOT data used in the paper, grouped by their observation IDs. "m2.fits", "w1.fits", and "w2.fits" contain the UV lightcurves from three UV filters, produced by Swift task "uvotproduct". "swfxraypclc.dat" is the Swift/XRT lightcurve, produced by the online Swift pipeline: https://www.swift.ac.uk/user_objects/ (Evans et al. 2009). "./reproduction_ocn/MOSFiT-products/" includes MCMC products from the MOSFiT package (Mockler et al. 2019).</p> <p>./reproduction_ocn/xmm: contains the reduced XMM-Newton/EPIC-pn spectra of three epochs used in the paper. "1and2-slim.xcm" is fitting the XMM#1 and XMM#2 spectra using the slim disc model. "3-phenmnlgcl.xcm" and "3-relxillCp.xcm", are fitting the XMM#3 spectrum with, a powerlaw+zbbody model and a slim disc+relxillCp model, respectively.</p>
Reproduction package for the paper "Disk Evolution Study Through Imaging of Nearby Young Stars (DESTINYS): The SPHERE view of the Orion star-forming region"
Open the record for dataset details and reuse information.
Reproduction Package for Submission `A Literature Review on Verification and Abstraction of Neural Networks'
<div> <div>This artifact contains the aggregated data for the article "A Literature Review on Verification and Abstraction of Neural Networks".</div> <br> <div>The artifact contains the following data files:</div> <br> <div>|-- phase-1_search-space.csv</div> <div>|-- phase-2-3_process-title-abstract.csv</div> <div>|-- review_sheet.csv</div> <br> <h3>Search space for literature review</h3> <div>The file <code>phase-1_search-space.csv</code> contains the metadata of the papers published in our considered conferences during the observed years.</div> <br> <h3>Filtering process</h3> <div>In the file <code>phase-2-3_process-title-abstract.csv</code>, we include the files that contain our expected keywords.</div> <div>Depending on whether we decided to include the paper in our survey after reading the title and the abstract, we marked each of the papers with `accept` or `decline`.</div> <br> <h3>Review sheet</h3> <div>The file <code>review_sheet.csv</code> contains metadata describing our reviews for each of the publications.</div> <div>It holds information on our final review of each paper, including the group we assigned it to and the reasons for its exclusion.</div> <br> <h3>Generating numbers</h3> <div>The following commands can be executed to reproduce the numbers used in our literature review.</div> <br> <div><code># Change directory to the directory containing the CSV files of this artifact.</code></div> <br> <div><code># Number of papers in our search space.</code></div> <div><code>cat phase-1_search-space.csv | tail -n +2 | wc -l</code></div> <br> <div><code># Number of papers after keyword search.</code></div> <div><code>cat phase-2-3_process-title-abstract.csv | tail -n +2 | wc -l</code></div> <br> <div><code># Number of papers that are excluded based on abstracts and titles.</code></div> <div><code>cut -f9 phase-2-3_process-title-abstract.csv | tail -n +2 | sort | uniq -c</code></div> <br> <div><code># Number of papers in different classes.</code></div> <div><code>cut -f7 review_sheet.csv | tail -n +2 | sort | uniq -c</code></div> <div> </div> </div>
Reproduction package for the paper "The open-source sunbather code: Modeling escaping planetary atmospheres and their transit spectra"
<p>This is a reproduction package for the paper "The open-source sunbather code: modeling escaping planetary atmospheres and their transit spectra" by Dion Linssen, Jim Shih, Morgan MacLeod & Antonija Oklopčić (2024). It provides a front-to-end reproduction script to reproduce the results and Figures 1-5 of the paper. Figures 6&7 can be reproduced with the example notebook found in the sunbather installation.</p>
Reproduction package for the paper "Transient study using LoTSS – framework development and preliminary results"
<p>This is a basic reproduction package for the paper "Transient study using LoTSS – framework development and preliminary results" by <a href="https://doi.org/10.1093/mnras/stae1458" target="_blank" rel="noopener">de Ruiter et al. (2024).</a> The folders analysis, P164+55, simulations, source_finder and transient_rates have been compressed.</p> <p> </p> <h2>Raw Data</h2> <p>The visibilities that are used to create the subtraction images for the LoFAR Two-metre Sky Survey (LoTSS) can be found in the following <a href="https://repository.surfsara.nl/collection/lotss-dr2" target="_blank" rel="noopener">Surf repository</a>.</p> <p> </p> <h2>Software</h2> <p>A <a href="https://github.com/mhardcastle/ddf-pipeline/blob/master/scripts/sub-sources-outside-region.py" target="_blank" rel="noopener">script</a> to perform the sky model subtraction exists within the pipeline for the LoTSS processing. The imaging software WSClean can be downloaded <a href="https://gitlab.com/aroffringa/wsclean/" target="_blank" rel="noopener">here </a> and a manual to get started can be found <a href="https://wsclean.readthedocs.io/en/latest/" target="_blank" rel="noopener">here</a>. The command that was used to create the subtraction images is (as described in Table 1 of the paper):</p> <p> </p> <blockquote> <p>wsclean -name subtract_images_8sec_P164+55_pad/P164+55 -weight briggs -0.25 -padding 2.0 -no-reorder -niter 0 -size 2200 2200 -scale 6asec -pol I -intervalsout 3600 -no-dirty P164+55_object.dysco.sub.shift.avg.weights.ms.archive0</p> </blockquote> <p> </p> <p>The scripts for source finding and filtering of the transient candidates are given in source_finder/ and analysis/. A detailed description of how to use this is given in subtraction images transient pipeline.pdf. Also the required for python packages are described in detail here.</p> <p> </p> <p> </p> <h2>Figures and Tables</h2> <h3>simulations/</h3> <p>The jupyter notebook visualise_simulated_transients.ipynb can be used to visualize the 8 second and 1 hour simulated transient sources.</p> <p> </p> <h3>transient_rates/</h3> <p>The jupyter notebook transient_rates.ipynb can be used to recreate the limits on the transient surface density (Figure 13).</p> <p> </p> <p> </p> <h2>Intermediate data products </h2> <p>This subtraction images for a single pointing are available in this reproduction package in P164+55/ The subtraction images for all the pointings have a total size of 2.8 TB, therefore, we only include the P164+55 pointing. The subtraction images for the 1hr snapshots, 2 minute snapshots and most of the 8 second snapshots (up to 50 GB) have been included. The subtraction images for other pointings can be requested by sending an email to <a href="mailto:irisderuiter7@gmail.com">irisderuiter7@gmail.com</a></p> <p> The subtraction images with simulated transients are included in simulations/</p>
Reproduction Package for Bachelor's Thesis 'Evaluation of JVM Garbage Collectors for CPAchecker'
<h1>Reproduction Package</h1> <h2><br>Evaluation of JVM Garbage Collectors for CPAchecker</h2> <p><br>This is a reproduction artifact for the bachelor's thesis "Evaluation of JVM Garbage Collectors for CPAchecker" to reproduce our experimental evaluation. It includes the modified source code of CPAchecker used in our experiments, all benchmark definitions for BenchExec, tables with the complete results, and the raw measurement data. Additionally, we provide the scripts and programs used to process these results. The set of verifications tasks of SV-COMP24 is not included in this package. It can be downloaded from Zenodo under <a href="../doi/10.5281/zenodo.10669722">10.5281/zenodo.10669722</a>. </p> <p> </p> <p><strong>Contents: </strong></p> <ul> <li>benchmark/: this directory contains the determined subset of SV-COMP24 verification tasks, categorized by the different properties.</li> <li>benchmark-definitions/: this directory contains all benchmark definitions for BenchExec.</li> <li>cpachecker/: this directory contains the source code of CPAchecker, as modified for our experiments.</li> <li>results/: this directory contains all raw measurement data and tables with the complete results, organized according to the sections of the thesis.</li> <li>scripts/: this directory contains the programs and scripts used to process the data.</li> </ul> <p> </p> <p>The logs of garbage collection are provided in a separate file due to technical limitations, as the file names were too long.</p> <p> </p> <p><strong>Preparing the Evalutation: </strong></p> <p>Ensure that you use the version of CPAchecker included in this artifact, as we have removed the default 15 min CPU limit in the property settings. Additionally, we have slightly modified the cpa.sh script to include the flag "jvm-arguments", which allows multiple JVM flags to be passed as a string to BenchExec.</p> <p>Please ensure that BenchExec is set up correctly. Detailed setup instructions are available in the <a href="https://github.com/sosy-lab/benchexec">project repository</a>.</p> <p>To reproduce all experiments, it requires 8 CPU units and 15 GB of RAM. </p> <p> </p> <p><strong>Performing the Evalutation: </strong></p> <p>The benchmark definitions, provided as .xml files, can be executed using BenchExec through the benchmark.py script.</p> <p> </p> <p><strong>Processing the Results: </strong></p> <p>To process the data with TaskFilter.jar, ResultFilter.jar, and ResultFilterShort.jar, you can execute them via the command line. Each programm requires a path to a .csv file as input, passed directly as a flag. For instance, resultfilter.jar can be excecuted with the following command:</p> <blockquote> <p>java -jar ResultFilter.jar -"<../../ParallelGCTimeRatio19.table.csv>"</p> </blockquote> <p>TaskFilter.jar determines the subset from the SV-COMP24 verification tasks by excluding tasks that exceeded 1800 seconds of CPU time and those where the garbage collection time accounted for less than 2 percent of the wall time. It specifically requires AllVerificationTasks.table.csv as input because this file contains 8 columns, with the eighth column including the necessary gctime information.</p> <p>ResultFilter.jar und ResultFilterShort.jar process the CSV files from individual benchmark runs to determine the number of timeouts and "out of memory" errors. They calculate the average CPU time for all tasks, excluding those that resulted in an "out of memory" error and assuming a CPU time of 900 seconds for each timeout. ResultFilter.jar can be applied to CSV files with 9 columns, while ResultFilterShort.jar can be applied to CSV files with 7 columns.</p> <p> </p> <p>To process the data with age_distribution.py and gc_events.py, you can execute them via the command line. Each program requires GC logs as input, specifically the path to the directory .files. For instance, age_distribution.py can be executed with the following command:</p> <blockquote> <p>python age_distribution.py <../../AgeLoggingSubset900sAllLoggingsG1GC.files></p> </blockquote> <p> </p> <p>age_distribution.py generates a plot showing the age distribution of bytes.</p> <p>gc_events.py counts the total number of GC events. Independently of this, it also calculates the number of young collections, full collections, and concurrent marking cycles. For G1GC, additional concurrent undo cycles are included to verify that the total number of individual collection types adds up to the overall number of GC events.</p> <p> </p> <p>To determine the average values of the commonly solved subset, the union tables for each section must be reviewed. For all configurations, you have to select that only the correct tasks are displayed. The average values for each measure will then be provided by the table.</p> <p> </p> <p>categorial_regression_cputime.py, categorial_regression_walltime.py, and categorial_regression_memory.py can be executed without any additional input path. These scripts generate the results of the categorical linear regression.</p> <p> </p>
Reproduction Package: Using machine learning techniques to mitigate confidentiality violations
<p>Reproduction package for the masters thesis "Using machine learning techniques to mitigate confidentiality violations"</p>
Reproduction package for the paper "BH-BH mergers with & without EM counterpart: A model for stable tertiary mass transfer in hierarchical triple systems"
<p>This is a reproduction package for the paper "BH-BH mergers with & without EM counterpart: A model for stable tertiary mass transfer in hierarchical triple systems" by Kummer et al. (2024). It aims to provide the most important data products and reproduce the Figures of the paper.</p> <p> </p>
Reproduction Package to "Model and Measurements of an Optical Stack for Visible to Near-IR Absorption in TiN Optical LEKIDs"
<p>This is a reproduction package to the paper "Model and Measurements of an Optical Stack for Visible toNear-IR Absorption in TiN Optical LEKIDs [working title]". It contains all data and code to reproduce the figures in this paper.</p>
Reproduction package for publication 'Testing afterglow models of FRB 200428 with early post-burst observations of SGR 1935+2154'
<p>The scripts in this package allows for the reproduction of all figures and data within the publication. Observing data can be found in the LOFAR long-term archive. For further information about reproducing figures pertaining to observing data please contact the authors. </p> <p>X-ray data pertaining to Figure 4 is available from the public reproduction packages of the relevant cited publications. </p>
Reproduction Package to "Resolving Power of Visible--to--Near-Infrared Hybrid beta-Ta/(Nb,Ti)N Kinetic Inductance Detectors"
<p>Reproduction package for paper: Resolving Power of Visible--to--Near-Infrared Hybrid beta-Ta/(Nb,Ti)N Kinetic Inductance Detectors. This package contains the necessary scripts and data to reproduce the data and figures in the paper. In addition, it contains a python based KID response model that can be used to test the coordinate transformations used in the paper for different use cases.</p>
Reproduction package for the paper: "The effects of planetary day-night temperature gradients on He 1083 nm transit spectra"
<p>Material for the publication "The effects of planetary day-night temperature gradients on He 1083 nm transit spectra". <br>Hydrodynamic model snapshots (in Athena++ hdf5 format), as well as 3D post-processed species number densities (hdf5 format), and the synthetic spectra (in ascii format) of models A100%, A50%, and A10%. Also included, the radiative transfer post-processing software used in our study, the modified Athena++ setup files, and a notebook to replicate the presented figures.</p>
Reproduction Package: Geometry dependence of TLS noise and loss in a-SiC:H parallel plate capacitors for superconducting microwave resonators.
<p>Reproduction package</p><p>Version 1.0</p>
Reproduction Package (Docker container) for the ESEC/FSE 2022 Article `A Retrospective Study of one Decade of Artifact Evaluations`
<p>This is the artifact accompanying our study of artifact evaluations at SE/PL conferences and their effects, accepted for presentation at the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) 2022.<br> For ease of artifact evaluation and usage, we ship our artifact as a Docker container, which comprises our datasets, the tools we built to collect those datasets, and the scripts used to obtain the results presented in the paper.<br> It also contains the Dockerfile to create the submitted image in order to make the software dependencies for our artifact explicit.</p>
Reproduction package for the paper "Metal-poor atmosphere of a sub-Neptune planet progenitor"
<p>This is a basic reproduction package for the paper <a href="https://www.nature.com/articles/s41550-024-02257-0">Barat et al 2024</a></p>
Reproduction package for the paper: "Cold day-side winds shape large leading streams in evaporating exoplanet atmospheres"
<p>Supplementary material for the paper "Cold day-side winds shape large leading streams in evaporating exoplanet atmospheres" by Nail et al. (2024). <br><br>We provide the results of the 3D hydrodynamic simulation with Athena++, with key files including the input file and a snapshot from the simulation taken after 8 orbits for all models discussed in the paper. The post-processing is performed using a radiative transfer code found in the "post-process_HAT67" folder. This code, described by MacLeod & Oklopcic (2022), produces synthetic spectra from the simulation snapshots and has been enhanced for precise calculations in high-density regions. Additionally, a Jupyter notebook demonstrates how to analyze the data and create the figures presented in the paper.</p> <p>Note: In the new version of the paper, we use "dtaui = d['nhe3'] * d['dr'] * csi * Voigt(nu_cell, da1, natural_gamma)" in the Figures.ipynb notebook in cell 42. </p>
Reproduction package for: Intelligent Match Merging to Prevent Obfuscation Attacks on Software Plagiarism Detectors
<p>This repository serves as the reproduction package for the master's thesis titled 'Intelligent Match Merging to Prevent Obfuscation Attacks on Software Plagiarism Detectors'. It includes datasets, experimental results and the implementation of the proposed approach. For additional details on the motivation, methodology, and analysis, please refer to the corresponding thesis document.</p>
[Reproduction package] Test Code Refactoring: A Literature Review and Classification of Refactoring Operations
<p><strong>Abstract:</strong> Test code refactoring is a crucial activity in software development that aims to maintain the quality of test code and, consequently, software products. Although several approaches and tools have been proposed to tackle test code refactoring, a synthesis of existing work is lacking. This paper presents the findings of a systematic literature review on test code refactoring, covering anti-patterns, refactoring strategies, and tools. The review analyzed 42 primary studies and identified 190 test code problems. The majority of the studies presented generic refactorings suitable for both production and test code, while few studies focused exclusively on test code design. Some anti-patterns had multiple refactoring strategies, while others lacked a clear strategy. Existing tools have not evolved significantly since their inception, and many refactoring strategies have not been evaluated. This study highlights the need for more studies on recommending refactorings for test code and investigating the effectiveness and effects of each refactoring approach. The results can guide future research on test code refactoring, providing direction for new refactorings and tools to improve the quality of software products.</p> <p> </p>
Reproduction Package for the FSE 2024 Paper "EyeTrans: Merging Human and Machine Attention for Neural Code Summarization"
<p>This artifact accompanies our paper "EyeTrans: Merging Human and Machine Attention for Neural Code Summarization," which has been accepted for presentation at the ACM International Conference on the Foundations of Software Engineering (FSE) 2024.</p> <p>The artifact contains the dataset derived from a human study using eye-tracking for code comprehension, crucial for the development of the EyeTrans model. Additionally, it includes the source code related to the research questions addressed within our work.</p> <p>This includes the unprocessed data from the eye-tracking study, scripts for data processing, and the source code for the EyeTrans model, which merges human and machine attention within Transformer models. This resource is intended for researchers aiming to replicate our study, conduct further inquiry, or extend the techniques to new datasets in software engineering research.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.