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The attached zip contains both data and analysis scripts for the first two particle-in-cell examples in the associated paper. In particular,
(1) The BeamExpansion folder contains output z vs r phase space data from the quasi-Helmholtz FEMPIC code used in the paper at 3 ns (fempic.csv), as well as the equivalent data from an XOOPIC simulation (xoopic.txt). The analysis is done in the ipython notebook file in the folder. All of the plots in the paper was generated using this same script.
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This is the multimedia of the paper “Bearing-based collision-free formation control for spacecrafts under dynamic event-triggered input”, including datasets (in .xlsx format), presentations (in .pptx format), and illustrative videos.
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# ! Disclaimer!
- Add jar dependencies to build path : ( ~/OCLDependencies.zip, ~/ModiscoDependencies.zip, ~/PapyrusDependencies.zip).
- For evosuite : add dependencies to the pom file :
https://www.evosuite.org/documentation/maven-plugin/
# Content:
1. TSE co-evolution zip file :
* (data v1) folder : includes 10 projects that was used for the evaluation process, before the metamodel evolution, containing the generated tests.
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To evaluate the efficiency of the GA-SA3-opt algorithm, problems from the TSPLIB standard library are selected for simulation and testing. The computational environment is configured with an Intel i5-10200H 2.60GHz CPU and MATLAB 9.0.0.341360 (R2016a) 64-bit.
First, the convergence speed of the algorithms is tested using the eil101 problem from TSPLIB. The optimal paths for each algorithm applied to the Eil101 problem are shown in figure 9.
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Shoviv EDB to PST Converter is a powerful tool to convert EDB files to PST easily. It helps users recover and export EDB mailboxes without any hassle. This tool supports both public and private EDB files and works with corrupted or healthy EDB files. Along with PST, it also converts EDB files to different formats like EML, MSG, and HTML. Users can preview their emails before converting them. It supports all Exchange and Outlook versions.
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In this study, we analyzed the data on MLB pitchers data, using datasets derived from Statcast. Introduced in 2015, Statcast is an advanced tracking technology capable of capturing detailed information on pitch tracking, bat tracking, etc. in every MLB game. Currently, all 30 MLB ballparks are equipped with Statcast systems, and since the introduction of the Hawk-Eye technology in 2020, this system has achieved an impressive tracking rate of 99\% for batted balls.
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