Showing 161 - 180 results of 307 for search '(( ((python model) OR (python code)) implementation ) OR ( python from implementing ))', query time: 0.39s Refine Results
  1. 161

    Internal changes of the specimen of 0.7 to 0.75. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
  2. 162

    Internal changes of the specimen of 0.87 to 0.9. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
  3. 163

    Internal changes of the specimen of 0.74 to 0.76. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
  4. 164

    Internal changes of the specimen 1.55 to 1.60. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
  5. 165

    Internal changes of the specimen of 1.70 to 1.75. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
  6. 166

    Internal changes of the specimen of 0.89 to 1. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
  7. 167
  8. 168

    Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. by Adel Heydarabadipour (22290905)

    Published 2025
    “…<p>Log–log plot of median wall-clock time for SBMLNetwork’s C++-based auto-layout engine (blue circles, solid fit) and SBMLDiagrams’ implementation of the pure-Python NetworkX spring_layout algorithm (red squares, dashed fit), applied to synthetic SBML models containing 20–2,000 species, with a fixed 4:1 species-to-reaction ratio. …”
  9. 169

    <b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b> by Marly G F Costa (19812192)

    Published 2025
    “…<p dir="ltr"><b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b></p><p dir="ltr">The code was developed in the Google Collaboratory environment, using Python version 3.7.13, with TensorFlow 2.8.2. …”
  10. 170

    The Improved Hydro-Sediment Numerical Model and Machine Learning Models by Yuning Tan (20580932)

    Published 2025
    “…The hydro-sediment model was implemented in the C# programming language using Visual Studio, while the machine learning models were developed in Python.…”
  11. 171

    Advancing Solar Magnetic Field Modeling by Carlos António (21257432)

    Published 2025
    “…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …”
  12. 172

    High-Throughput Mass Spectral Library Searching of Small Molecules in R with NIST MSPepSearch by Andrey Samokhin (20282728)

    Published 2025
    “…Despite the availability of numerous library search algorithms, those developed by NIST and implemented in MS Search remain predominant, partly because commercial databases (e.g., NIST, Wiley) are distributed in proprietary formats inaccessible to custom code. …”
  13. 173

    Comparison data 7 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  14. 174

    Sample data for <i>Neolamprologus multifasciatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  15. 175

    Sample data for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  16. 176

    Comparison data 3 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  17. 177

    Sample data for <i>Telmatochromis temporalis</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  18. 178

    Comparison data 4 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  19. 179

    Comparison data 1 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  20. 180

    Comparison data 2 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”