Showing 101 - 120 results of 266 for search '(( python code representing ) OR ( python ((code implementation) OR (time implementation)) ))', query time: 0.39s Refine Results
  1. 101
  2. 102

    Testing Code for JcvPCA and JsvCRP. by Océane Dubois (21989812)

    Published 2025
    “…<p>This file contains the code that implements both metrics in python and apply them on a simulated dataset.…”
  3. 103

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

    Published 2025
    “…</p><h3>Includeed in this repository:</h3><ul><li><b>Raw data files:</b></li><li><code>comparison_all_scales.csv</code> – comparison_all_scales.csv - manually verified vs. automated measurements of 1095 coregonid scales</li></ul><ul><li><ul><li><code>Validation_data.csv</code> – manually measured scale data under binocular</li><li><code>Parameter_correction_numeric.csv</code> – calibration data (scale radius vs. fish length/weight)</li></ul></li><li><b>Statistical results:</b></li><li><ul><li><code>comparison_stats_core_variables.csv</code> – verification statistics (bias, relative error, limits of agreement)</li><li><code>Validation_statistics.csv</code> – summary statistics and model fits (manual vs. automated)</li></ul></li><li><b>Executable script (not GUI):</b></li><li><ul><li><code>Algorithm.py</code> – core processing module for scale feature extraction<br>→ <i>Note: The complete Coregon Analyzer application (incl. …”
  4. 104

    Efficient, Hierarchical, and Object-Oriented Electronic Structure Interfaces for Direct Nonadiabatic Dynamics Simulations by Sascha Mausenberger (22225772)

    Published 2025
    “…We present a novel, flexible framework for electronic structure interfaces designed for nonadiabatic dynamics simulations, implemented in Python 3 using concepts of object-oriented programming. …”
  5. 105

    Code and data for reproducing the results in the original paper of DML-Geo by Pengfei CHEN (8059976)

    Published 2025
    “…<p dir="ltr">This asset provides all the code and data for reproducing the results (figures and statistics) in the original paper of DML-Geo</p><h2>Main Files:</h2><p dir="ltr"><b>main.ipynb</b>: the main notebook to generate all the figures and data presented in the paper</p><p dir="ltr"><b>data_generator.py</b>: used for generating synthetic datasets to validate the performance of different models</p><p dir="ltr"><b>dml_models.py</b>: Contains implementations of different Double Machine Learning variants used in this study.…”
  6. 106

    Data for "A hollow fiber membrane permeance evaluation device demonstrating outside-in and inside-out performance differences" by Timothy Warner (20222838)

    Published 2025
    “…</li><li>Plot data derived from the above data sources.</li><li>Python code to generate figures from the plot data.…”
  7. 107

    Data sets and coding scripts for research on sensory processing in ADHD and ASD by Vesko Varbanov (9687029)

    Published 2025
    “…The repository includes raw and matched datasets, analysis outputs, and the full Python code used for the matching pipeline.</p><h4>Ethics and Approval</h4><p dir="ltr">All procedures were approved by the University of Sheffield Department of Psychology Ethics Committee (Ref: 046476). …”
  8. 108

    Graphical abstract of HCAP. by Mohanad Faeq Ali (21354273)

    Published 2025
    “…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
  9. 109

    Recall analysis. by Mohanad Faeq Ali (21354273)

    Published 2025
    “…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
  10. 110

    Convergence rate analysis. by Mohanad Faeq Ali (21354273)

    Published 2025
    “…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
  11. 111

    Computational efficiency. by Mohanad Faeq Ali (21354273)

    Published 2025
    “…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
  12. 112

    Analysis of IoMT data sources. by Mohanad Faeq Ali (21354273)

    Published 2025
    “…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
  13. 113

    Prediction accuracy on varying attack types. by Mohanad Faeq Ali (21354273)

    Published 2025
    “…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
  14. 114

    <b> </b> Precision analysis. by Mohanad Faeq Ali (21354273)

    Published 2025
    “…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
  15. 115

    Impact of cyberattack types on IoMT devices. by Mohanad Faeq Ali (21354273)

    Published 2025
    “…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
  16. 116

    Code for High-quality Human Activity Intensity Maps in China from 2000-2020 by Wenqi Xie (18273238)

    Published 2025
    “…<p dir="ltr">Code and remote sensing images and interpretation results of the samples for uncertainty analysis for "High-quality Human Activity Intensity Maps in China from 2000-2020"</p><p dir="ltr">“Mapping_HAI.py”:We generated the HAI maps using ArcGIS 10.8, and the geoprocessing tasks were implemented using Python 2.7 with the ArcPy library (ArcGIS 10.8 + Python 2.7 environment). …”
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    Computing speed and memory usage. by David Berling (22170661)

    Published 2025
    “…<b>(b)</b> Physical memory consumption depending on simulated plane in radial and depth direction. Color coding same as in (a). Memory consumption was recorded as the maximum resident size during simulation monitored with the Python built-in module resource. …”
  19. 119

    The codes and data for "Lane Extraction from Trajectories at Road Intersections Based on Graph Transformer Network" by Chongshan Wan (19247614)

    Published 2024
    “…Each lane includes 'geometry' and 'inter_id' attributes.</li></ul><h2>Codes</h2><p dir="ltr">This repository contains the following Python codes:</p><ul><li>`data_processing.py`: Contains the implementation of data processing and feature extraction. …”
  20. 120

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

    Published 2025
    “…</li><li><b>3_literature_analysis_and_mapping.ipynb</b><br>Contains the Python code used for executing the systematic mapping study (SMS), including automated processing of literature data and thematic clustering.…”