Showing 121 - 140 results of 204 for search '(( python assess implementation ) OR ( ((python model) OR (python code)) representing ))', query time: 0.37s Refine Results
  1. 121

    Global Research Dataset on Social Media in Entrepreneurial Startup (2009–2024) by Lucky Ario (22115884)

    Published 2025
    “…Analytical outputs are organized into multiple formats: CSV files for raw bibliometric data; PNG images for thematic maps, trend topic visualizations, and research flowcharts; and CSV and PNG outputs for annual publication trajectories and polynomial regression-based modeling projections. Visualization and analysis were conducted using Microsoft Excel for summary statistics, R Biblioshiny for thematic and trend mapping, and Python for projection modeling.…”
  2. 122

    Data Sheet 1_Establishing a real-time biomarker-to-LLM interface: a modular pipeline for HRV signal acquisition, processing, and physiological state interpretation via generative A... by Morris Gellisch (18627744)

    Published 2025
    “…</p>Discussion<p>This system represents an early prototype of bioadaptive AI, in which physiological signals are incorporated as part of the model's input context.…”
  3. 123

    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. …”
  4. 124

    Summary of Tourism Dataset. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  5. 125

    Segment-wise Spending Analysis. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  6. 126

    Hyperparameter Parameter Setting. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  7. 127

    Marketing Campaign Analysis. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  8. 128

    Visitor Segmentation Validation Accuracy. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  9. 129

    Integration of VAE and RNN Architecture. by Jing Zhang (23775)

    Published 2025
    “…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
  10. 130

    MYCroplanters can quantify the interaction between pathogenic and non-pathogenic bacteria and their effects on plant health. by Melissa Y. Chen (11301882)

    Published 2025
    “…(e) Figure showing data from (d) converted into binary health/disease scores. Each dot represents a single plant. Black lines with ribbons are Bayesian model predictions with 95% prediction intervals, respectively. …”
  11. 131

    GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

    Published 2025
    “…Here, <i>Genus</i> represents the rodent genus, <i>GCM</i> denotes the global climate model used, <i>Year</i> specifies the projected time period, <i>SSP-RCP</i> indicates the shared socioeconomic pathway and representative concentration pathway, and <i>Statistics</i> describes the file’s data characteristics. …”
  12. 132
  13. 133

    Overview of generalized weighted averages. by Nobuhito Manome (8882084)

    Published 2025
    “…GWA-UCB1 outperformed G-UCB1, UCB1-Tuned, and Thompson sampling in most problem settings and can be useful in many situations. The code is available at <a href="https://github.com/manome/python-mab" target="_blank">https://github.com/manome/python-mab</a>.…”
  14. 134

    <b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

    Published 2025
    “…In total, 75 % of the labelled observations were assigned to train and 25 % to test the model. To evaluate the model performance, the root mean squared root error (RMSE, the standard deviation of the residuals that represents the mean difference between the prediction and the real value for the test set) and <i>R</i><sup>2</sup> were used, which was calculated using r2_score() from <i>Scikit-learn</i> metrics. …”
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  16. 136

    Moulin distributions during 2016-2021 on the southwest Greenland Ice Sheet by Kang Yang (7323734)

    Published 2025
    “…</p><p><br></p><ul><li>00_Satellite-derived moulins: Moulins directly mapped from Sentinel-2 imagery, representing actual moulin positions;</li><li>01_Snapped moulins: Moulins snapped to DEM-modeled supraglacial drainage networks, primarily used for analyses;</li><li>02_Moulin recurrences: Recurring moulins determined from the snapped moulins;</li><li>03_Internally drained catchments: Internally drained catchment (IDC) associated with each moulin;</li><li>04_Surface meltwater runoff: surface meltwater runoff calculated from MAR for the study area, elevation bins, and IDCs; </li><li>05_DEM-derived: Topographic features modeled from ArcticDEM, including elevation bins, depressions and drainage networks;</li><li>06_GWR: Variables for conducting geographically weighted regression (GWR) analysis;</li></ul><p><br></p><ul><li>Code_01_Mapping moulins on the southwestern GrIS.ipynb: A Jupyter Notebook to analyze moulin distributions, reproducing most of the analyses and figures presented in the manuscript using the provided datasets;</li><li>Code_02_pre1_calculate Strain Rate from XY ice velocity.py: A preprocessing Python script to calculate strain rate for the GWR analysis;</li><li>Code_02_pre2_calculate Driving Stress from ice thickness and surface slope.py: A preprocessing Python script to calculate driving stress for the GWR analysis;</li><li>Code_02_GWR analysis.ipynb: A Jupyter Notebook to conduct the GWR analysis using the provided datasets.…”
  17. 137

    Audio Datasets of belt conveyor rollers in mines by Juan Liu (19687435)

    Published 2024
    “…</li><li><b>Python Code: </b>This code validates the accuracy and usability of the audio feature datasets in real-time monitoring of belt conveyor roller operational states.…”
  18. 138
  19. 139

    <b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> by Shubham Pawar (22471285)

    Published 2025
    “…</p><p dir="ltr"><b>Input:</b></p><ul><li><code>svi_module/svi_data/svi_info.csv</code> - Image metadata from Step 1</li><li><code>perception_module/trained_models/</code> - Pre-trained models</li></ul><p dir="ltr"><b>Command:</b></p><pre><pre>python -m perception_module.pred \<br> --model-weights .…”
  20. 140

    Supplementary material for "Euler inversion: Locating sources of potential-field data through inversion of Euler's homogeneity equation" by Leonardo Uieda (97471)

    Published 2025
    “…</p><h2>License</h2><p dir="ltr">All Python source code (including <code>.py</code> and <code>.ipynb</code> files) is made available under the MIT license. …”