Showing 41 - 60 results of 67 for search '(( python after implementation ) OR ( python practical implementation ))', query time: 0.26s Refine Results
  1. 41

    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. 42

    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. 43

    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. 44

    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. 45

    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. 46

    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. 47

    Executable Books in Robotics by Murilo Marinho (21508857)

    Published 2025
    “…In this work, to showcase the results of the Open Research Fellowship 24-25 in the field of Robotics, I show one way to help bridge the theory-practice gap creating a fully open CC BY-NC-SA 4.0 licensed executable textbook in Python, based on Jupyter notebooks. …”
  8. 48
  9. 49

    MSc Personalised Medicine at Ulster University by Steven Watterson (100045)

    Published 2025
    “…</b> Introducing computational approaches to studying genes, proteins or metabolites, this module teaches Python coding, data analysis and how to work with the databases that support data analysis.…”
  10. 50

    Demonstration of Isosteric Heat of Adsorption Calculation using AIFs and pyGAPs by Jack Evans (11275386)

    Published 2025
    “…</p><p dir="ltr">The calculation is performed using the Clausius-Clapeyron method as implemented in the <code><strong>pyGAPS</strong></code> Python library for adsorption science. …”
  11. 51

    Monte Carlo Simulation Code for Evaluating Cognitive Biases in Penalty Shootouts Using ABAB and ABBA Formats by Raul MATSUSHITA (10276562)

    Published 2024
    “…<p dir="ltr">This Python code implements a Monte Carlo simulation to evaluate the impact of cognitive biases on penalty shootouts under two formats: ABAB (alternating shots) and ABBA (similar to tennis tiebreak format). …”
  12. 52

    Table 3_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

    Published 2025
    “…Statistical analyses were conducted using Python and R, with significance set at p < 0.05.</p>Results<p>In this study, we developed an integrated predictive model for HER2 status in breast cancer by combining deep learning-based MRI features and clinical data. …”
  13. 53

    Table 2_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

    Published 2025
    “…Statistical analyses were conducted using Python and R, with significance set at p < 0.05.</p>Results<p>In this study, we developed an integrated predictive model for HER2 status in breast cancer by combining deep learning-based MRI features and clinical data. …”
  14. 54

    Table 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

    Published 2025
    “…Statistical analyses were conducted using Python and R, with significance set at p < 0.05.</p>Results<p>In this study, we developed an integrated predictive model for HER2 status in breast cancer by combining deep learning-based MRI features and clinical data. …”
  15. 55

    Data Sheet 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

    Published 2025
    “…Statistical analyses were conducted using Python and R, with significance set at p < 0.05.</p>Results<p>In this study, we developed an integrated predictive model for HER2 status in breast cancer by combining deep learning-based MRI features and clinical data. …”
  16. 56

    HCC Evaluation Dataset and Results by Jens-Rene Giesen (18461928)

    Published 2024
    “…</p><h3>Report Script</h3><p dir="ltr">On the top-level directory you find a <code>report.py</code> file, which is an executable Python script. The only requirement for running this script is a Python 3.6+ interpreter as well as an installation of the <code>numpy</code> package. …”
  17. 57

    Dataset for: Phylotranscriptomics reveals the phylogeny of Asparagales and the evolution of allium flavor biosynthesis, Nature Communications,DOI:10.1038/s41467-024-53943-6 by Xiao-Xiao Wang (2447920)

    Published 2024
    “…Extract the TPM.</p><p dir="ltr">After running Salmon, each species has three quant.sf files, renamed as quant1.sf, quant2.sf, quant3.sf.…”
  18. 58

    Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event by Thomas Clemens Carmine (19756929)

    Published 2025
    “…<br><br><b>Missing-Data Handling & Imputation:</b></p><p dir="ltr">The following sequential steps were applied to create a complete and consistent daily time series suitable for analysis (presented in the Imputed_AP_Data_Zurich_2010-25 sheet), particularly addressing the absence of routine PM₂.₅ measurements prior to January 2016. The full implementation is detailed in the accompanying Python script (Imputation_Air_Pollutants_NABEL.py). …”
  19. 59

    Comprehensive Fluid and Gravitational Dynamics Script for General Symbolic Navier-Stokes Calculations and Validation by Stylianos Touloumidis (19938747)

    Published 2024
    “…It provides a flexible foundation on which theoretical assumptions can be validated, and practical calculations performed. Implemented in Python with symbolic calculations, the script facilitates in-depth analysis of complex flow patterns and makes advanced mathematical computations more accessible. …”
  20. 60

    CNG-ARCO-RADAR.pdf by Alfonso Ladino (21447002)

    Published 2025
    “…This approach uses a suite of Python libraries, including Xarray (Xarray-Datatree), Xradar, and Zarr, to implement a hierarchical tree-like data model. …”