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Model . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Model . 2025
License: CC BY
Data sources: Datacite
ZENODO
Model . 2025
License: CC BY
Data sources: Datacite
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Case studies of "DT-STARK: a Tool for the Evaluation the Effectiveness of Digital Twins through Feedback and Perturbations"

Authors: Castiglioni, Valentina; Lanotte, Ruggero; Loreti, Michele; Tini, Simone;

Case studies of "DT-STARK: a Tool for the Evaluation the Effectiveness of Digital Twins through Feedback and Perturbations"

Abstract

The .zip folder contains the essential files and classes for reproducing the DT-Stark models of the case studies presented in the paper V. Castiglioni, R. Lanotte, M. Loreti, S.Tini. DT-STARK: a Tool for the Evaluation of the Effectiveness of Digital Twins through Feedback and Perturbations. currently submitted for publication to International Journal on Software Tools for Technology Transfer, as part of the FMICS 2024 special issue. The case study specific scripts are included in the "examples" folder: follow the "industrial_plant" folder for the case study on the industrial plant, and the "smart_hospital" follow for the one on the smart hospital. The original files can be found in the DT-STARK repository In order to reproduce the experiments, please follow the guidlines in the README file in the .zip folder. We remark that you will need* A text editor or IDE (we used [IntelliJ IDEA](https://www.jetbrains.com/idea/))* A [Gradle](https://docs.gradle.org/current/userguide/userguide.html) distribution. We used version 7.4.2.* A JAVA Development Kit (JDK). We used version 19. To ensure compatibility with Gradle, please use any version between 8 and 19. Moreover, to obtain the plots, Python3 (>= 3.9) is needed. 

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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