يعرض 81 - 100 نتائج من 103 نتيجة بحث عن '(( python effective implementation ) OR ( python tool implementing ))', وقت الاستعلام: 0.34s تنقيح النتائج
  1. 81

    World Heritage documents reveal persistent gaps between climate awareness and local action حسب Yang Chen (20756166)

    منشور في 2025
    "…The analysis section includes a GLM model implemented in R, along with evaluation tools such as correlation heatmaps, ICC agreement analysis, and MCC-based binary classification assessment. …"
  2. 82

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

    منشور في 2025
    "…This approach uses a suite of Python libraries, including Xarray (Xarray-Datatree), Xradar, and Zarr, to implement a hierarchical tree-like data model. …"
  3. 83

    Advancing Solar Magnetic Field Modeling حسب Carlos António (21257432)

    منشور في 2025
    "…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …"
  4. 84

    Knowledge Graph validation using SHACL Shapes حسب Ángel Iglesias Préstamo (19745767)

    منشور في 2024
    "…Leveraging Rust’s performance and safety features, rudof provides efficient validation tools and Python bindings for integration with data science workflows. …"
  5. 85

    Code حسب Baoqiang Chen (21099509)

    منشور في 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. …"
  6. 86

    Core data حسب Baoqiang Chen (21099509)

    منشور في 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. …"
  7. 87

    Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2) حسب Tahir Bhatti (20961974)

    منشور في 2025
    "…The pipeline integrates established open-source tools (fastp, BWA-MEM, samtools, iVar, bcftools) and implements <b>codon-aware mutation calling</b> at five canonical RBD positions (R346, S371, K444, F456, F486) relative to NC_045512.2. …"
  8. 88

    Probabilistic-QSR-GeoQA حسب Mohammad Kazemi (19442467)

    منشور في 2024
    "…Also we have written Python API for Probcog (ProbCog-API.py) and SparQ reasoners (SparQ-API.py).…"
  9. 89

    Elements: Streaming Molecular Dynamics Simulation Trajectories for Direct Analysis – Applications to Sub-Picosecond Dynamics in Microsecond Simulations حسب Matthias Heyden (17087794)

    منشور في 2025
    "…This eliminates the need for intermediate storage and allows immediate access to high-frequency fluctuations and vibrational signatures that would otherwise be inaccessible. We have implemented this streaming interface in the MD engines NAMD, LAMMPS, and GROMACS</p><p dir="ltr">On the client side, we developed the IMDClient Python package which receives the streamed data, stores into a custom buffer, and provides it to external tools as NumPy arrays, facilitating integration with scientific computing workflows. …"
  10. 90

    PTPC v1.0 Numerical Baseline: Stable Multi-Bounce Cosmology Simulation حسب David Lewis Stewart Parry (22188211)

    منشور في 2025
    "…The included Python scripts simulate a low-RAM cosmological oscillator that evolves through successive nonsingular “bounces,” demonstrating a self-consistent cyclic universe in which curvature, tension, and entropy reset in finite, periodic intervals. …"
  11. 91

    MCCN Case Study 3 - Select optimal survey locality حسب Donald Hobern (21435904)

    منشور في 2025
    "…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…"
  12. 92

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

    منشور في 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. …"
  13. 93

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

    منشور في 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. …"
  14. 94

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

    منشور في 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.…"
  15. 95

    Globus Compute: Federated FaaS for Integrated Research Solutions حسب eRNZ Admin (6438486)

    منشور في 2025
    "…</p><p dir="ltr">Globus Compute [2] is a Function-as-a-Service platform designed to provide a scalable, secure, and simple interface to HPC resources. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, from the edge to high performance computing (HPC) cluster, and they may then invoke Python functions on those endpoints via a reliable cloud-hosted service. …"
  16. 96

    Fast, FAIR, and Scalable: Managing Big Data in HPC with Zarr حسب Alfonso Ladino (21447002)

    منشور في 2025
    "…(NEXRAD), using open-source tools from the Python ecosystem such as Xarray, Xradar, and Dask to enable efficient parallel processing and scalable analysis. …"
  17. 97

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

    منشور في 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.…"
  18. 98

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

    منشور في 2025
    "…If you add scripts or tools that change dataset paths or formats, please update `YOLODataset/dataset.yaml` and this README accordingly.…"
  19. 99

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

    منشور في 2025
    "…Image processing algorithms, implemented in Python using adaptive thresholding techniques, were applied to segment particles from the background. …"
  20. 100

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

    منشور في 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. …"