Showing 221 - 235 results of 235 for search '(( python world implementation ) OR ( python model implementing ))', query time: 0.33s Refine Results
  1. 221

    Research Database by Ana Paula Fermiano (22439479)

    Published 2025
    “…</p><p dir="ltr">Statistical analysis was conducted through <b>multiple regression models</b> implemented in <b>Jamovi</b>, supported by Geographic Information System (GIS) tools to visualize spatial patterns. …”
  2. 222

    Data and code for: Automatic fish scale analysis by Christian Vogelmann (21646472)

    Published 2025
    “…<p dir="ltr">This dataset accompanies the publication:<br><b>"Automatic fish scale analysis: age determination, annuli and circuli detection, length and weight back-calculation of coregonid scales"</b><br></p><p dir="ltr">It provides all essential data and statistical outputs used for the <b>verification and validation</b> of the <i>Coregon Analyzer</i> – a Python-based algorithm for automated biometric fish scale measurement.…”
  3. 223

    MATH_code : False Data Injection Attack Detection in Smart Grids based on Reservoir Computing by Carl-Hendrik Peters (21530624)

    Published 2025
    “…</li><li><b>4_final_models_pipeline.ipynb</b><br>The final implementation pipeline that loads the data, applies preprocessing and encoding (e.g., latency or ISI), trains the detection models, and stores performance metrics.…”
  4. 224

    Online Resource: Reservoir Computing as a Promising Approach for False Data Injection Attack Detection in Smart Grids by Carl-Hendrik Peters (21530624)

    Published 2025
    “…</li><li><b>4_final_models_pipeline.ipynb</b><br>The final implementation pipeline that loads the data, applies preprocessing and encoding (e.g., latency or ISI), trains the detection models, and stores performance metrics.…”
  5. 225

    Table & Figure.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks by NORLIZA BINTI MOHAMED (20739875)

    Published 2025
    “…Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”
  6. 226

    Raw Data EEG.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks by NORLIZA BINTI MOHAMED (20739875)

    Published 2025
    “…Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”
  7. 227

    OHID-FF dataset for forest fire detection and classification by xin chen (20496938)

    Published 2025
    “…</p><p dir="ltr">- Pointed to the `train val scripts/` README for model-specific commands and dependencies.</p>…”
  8. 228

    IGD-cyberbullying-detection-AI by Bryan James (19921044)

    Published 2024
    “…[<a href="https://doi.org/10.6084/m9.figshare.27266961" rel="nofollow" target="_blank">https://doi.org/10.6084/m9.figshare.27266961</a>]</p><h2>Table of Contents</h2><ul><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#overview" target="_blank">Overview</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#requirements" target="_blank">Requirements</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#datasets" target="_blank">Datasets</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#installation" target="_blank">Installation</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#running-the-code" target="_blank">Running the Code</a></li><li><a href="https://github.com/BryanSJamesDev/IGD-cyberbullying-detection-AI#expected-results" target="_blank">Expected Results</a></li></ul><h2>Overview</h2><p dir="ltr">This repository provides the code for predicting mental health outcomes associated with Internet Gaming Disorder (IGD) and Cyberbullying using machine learning and deep learning models. Models like Logistic Regression, Random Forest, Ensemble Models, CNNs, and LSTMs are implemented to detect patterns from behavioral data.…”
  9. 229

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

    Published 2025
    “…This includes the economic models that underpin big pharma as well the importance of entrepreneurship and small medium enterprises in driving forward healthcare innovation.…”
  10. 230

    Microscopic Detection and Quantification of Microplastic Particles in Environmental Water Samples by Derek Lam (11944213)

    Published 2025
    “…Image processing algorithms, implemented in Python using adaptive thresholding techniques, were applied to segment particles from the background. …”
  11. 231

    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. …”
  12. 232

    Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 by Andrew Rogers (17623239)

    Published 2025
    “…</p><h2>Software and Spatial Resolution</h2><p dir="ltr">The VRE siting model is implemented using Python and relies heavily on ArcGIS for comprehensive spatial data handling and analysis.…”
  13. 233

    Code by Baoqiang Chen (21099509)

    Published 2025
    “…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”
  14. 234

    Core data by Baoqiang Chen (21099509)

    Published 2025
    “…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”
  15. 235

    Landscape Change Monitoring System (LCMS) Conterminous United States Cause of Change (Image Service) by U.S. Forest Service (17476914)

    Published 2025
    “…Scikit-learn: Machine Learning in Python. In Journal of Machine Learning Research (Vol. 12, pp. 2825-2830).Pengra, B. …”