يعرض 181 - 198 نتائج من 198 نتيجة بحث عن '(( python effective implementation ) OR ( ((python code) OR (python tool)) implementing ))', وقت الاستعلام: 0.41s تنقيح النتائج
  1. 181

    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. …"
  2. 182

    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. …"
  3. 183

    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. …"
  4. 184

    Hippocampal and cortical activity reflect early hyperexcitability in an Alzheimer's mouse model حسب Marina Diachenko (19739092)

    منشور في 2025
    "…</p><p dir="ltr">All data are available upon request. The standalone Python implementation of the fE/I algorithm is available under a CC-BY-NC-SA license at <a href="https://github.com/arthur-ervin/crosci" target="_blank">https://github.com/arthur-ervin/crosci</a>. …"
  5. 185

    Gene Editing using Transformer Architecture حسب Rishabh Garg (5261744)

    منشور في 2025
    "…., the H-Bot sequence), it facilitates on-screen gene editing, enabling targeted mutations or the insertion of desired genes. Implementation requires Python and deep learning frameworks like TensorFlow or PyTorch, with optional use of Biopython for genetic sequence handling. …"
  6. 186

    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. …"
  7. 187

    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. …"
  8. 188

    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. …"
  9. 189

    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. …"
  10. 190

    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.…"
  11. 191

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

    منشور في 2025
    "…</b> Introducing computational approaches to studying genes, proteins or metabolites, this module teaches Python coding, data analysis and how to work with the databases that support data analysis.…"
  12. 192

    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. …"
  13. 193

    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. …"
  14. 194

    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.…"
  15. 195

    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. …"
  16. 196

    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. …"
  17. 197

    Image 2_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. …"
  18. 198

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

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