Showing 101 - 119 results of 119 for search '(( python time implementation ) OR ( python effective implementation ))', query time: 0.22s Refine Results
  1. 101

    kececilayout by Mehmet Keçeci (14301782)

    Published 2025
    “…<p dir="ltr"><b>Kececi Layout (Keçeci Yerleşimi)</b>: A deterministic graph layout algorithm designed for visualizing linear or sequential structures with a characteristic "zig-zag" or "serpentine" pattern.</p><p dir="ltr"><i>Python implementation of the Keçeci layout algorithm for graph visualization.…”
  2. 102

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

    Published 2025
    “…</p><p dir="ltr">MSc Personalised Medicine is a Master’s programme that can be taken in 1 year full-time or across 2 years part-time. Both full-time and part-time programmes have two intakes and can be started in September or January.…”
  3. 103

    Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis by Alan Glanz (22109698)

    Published 2025
    “…</b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.</p><h3><b>2. …”
  4. 104

    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

    Published 2025
    “…The proposed DIDS-BRBPNN-BBWOA-IoT method is implemented using Python. The performance of the DIDS-BRBPNN-BBWOA-IoT approach is examined using performance metrics like accuracy, precision, recall, f1-score, specificity, error rate; computation time, and ROC. …”
  5. 105

    The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

    Published 2025
    “…<h2>A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation</h2><p><br></p><p dir="ltr">This is the implementation for the paper "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation".…”
  6. 106

    The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

    Published 2025
    “…<h2>A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation</h2><p><br></p><p dir="ltr">This is the implementation for the paper "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation".…”
  7. 107

    Code by Baoqiang Chen (21099509)

    Published 2025
    “…</p><p><br></p><p dir="ltr">For the 5′ UTR library, we developed a Python script to extract sequences and Unique Molecular Identifiers (UMIs) from the FASTQ files. …”
  8. 108

    Core data by Baoqiang Chen (21099509)

    Published 2025
    “…</p><p><br></p><p dir="ltr">For the 5′ UTR library, we developed a Python script to extract sequences and Unique Molecular Identifiers (UMIs) from the FASTQ files. …”
  9. 109

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

    Published 2025
    “…Detecting trends in forest disturbance and recovery using yearly Landsat time series: 2. TimeSync - Tools for calibration and validation. …”
  10. 110

    ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation by Hong Zhu (109912)

    Published 2025
    “…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …”
  11. 111

    ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation by Hong Zhu (109912)

    Published 2025
    “…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …”
  12. 112

    Mapping Policy Coherence in National UK Food Systems (2008– 2024): Analysing the Integration of Climate Change Mitigation and Adaptation Strategies, LEAP 2025 conference, Oxford by Ronja Teschner (20974180)

    Published 2025
    “…</p><p dir="ltr">Data Screening inclusion criteria followed the Food Systems Countdown Initiative (FSCI).2</p><p><br></p><p dir="ltr">diets, nutrition and health</p><p dir="ltr">diet quality, food security, food environments, policies affecting</p><p dir="ltr">food environments</p><p dir="ltr">environment and climate</p><p dir="ltr">land use, greenhouse gas emissions, water use, pollution, biosphere integrity</p><p dir="ltr">livelihoods, poverty, and equity</p><p dir="ltr">poverty and income, employment, social protection, rights</p><p dir="ltr">governance</p><p dir="ltr">shared vision, strategic planning and policies, effective implementation, accountability</p><p dir="ltr">resilience and sustainability</p><p dir="ltr">exposure to shocks, resilience capacities, agrobiodiversity, food security stability</p><p><br></p><p dir="ltr">Findings</p><p dir="ltr">o N=157 policy documents integrate climate change considerations.…”
  13. 113

    Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds by Gloria Castañeda-Valencia (20758502)

    Published 2025
    “…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …”
  14. 114

    Research Database by Ana Paula Fermiano (22439479)

    Published 2025
    “…Data were processed using <b>Python-based automation scripts</b> for scraping, cleaning, geocoding, and calculating geodesic distances between each property and the nearest community garden. …”
  15. 115

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

    Published 2025
    “…</p><p dir="ltr"><b>ridge_gwr.py</b>: Implementations of a modified Geographically Weighted Regression (GWR) with ridge regression</p><p dir="ltr"><b>ridge_sel_bw.py</b>: Implementations of a modified selector of band width in GWR with ridge regression</p><p dir="ltr"><b>scenario_manager.py</b>: Functions to create simulation scenarios</p><p dir="ltr"><b>utility.py</b>: Functions for testing spatial causal effects using different models and placebo tests for inference.…”
  16. 116

    Image 1_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif by Xiaobing Li (291454)

    Published 2025
    “…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …”
  17. 117

    Image 2_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif by Xiaobing Li (291454)

    Published 2025
    “…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …”
  18. 118

    <b>Altered cognitive processes shape tactile perception in autism.</b> (data) by Ourania Semelidou (19178362)

    Published 2025
    “…</p><p dir="ltr">The perceptual decision-making data were collected from 5 different cohorts of mice at different time-points during their active phase of the day. …”
  19. 119

    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.…”