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Showing 121 - 140 results of 297 for search '(((( algorithm iqa function ) OR ( algorithm sphere function ))) OR ( algorithm python function ))', query time: 0.92s Refine Results
  1. 121
    Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, the temporal molecular states <i>n</i> at specific time <i>t</i> will be generated for further visualization.

    Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

    Published 2025
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  2. 122
    Modeling with uniform <i>σ</i> values.

    Modeling with uniform <i>σ</i> values. by Giacomo Janson (8138517)

    Published 2019
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  3. 123
    Effect of <i>|Δd</i><sub><i>n</i></sub><i>|</i> perturbation on 3D modeling.

    Effect of <i>|Δd</i><sub><i>n</i></sub><i>|</i> perturbation on 3D modeling. by Giacomo Janson (8138517)

    Published 2019
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  4. 124
    Revisiting the “satisfaction of spatial restraints” approach of MODELLER for protein homology modeling

    Revisiting the “satisfaction of spatial restraints” approach of MODELLER for protein homology modeling by Giacomo Janson (8138517)

    Published 2019
    “…This program implements the “modeling by satisfaction of spatial restraints” strategy and its core algorithm has not been altered significantly since the early 1990s. …”
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  5. 125
    Example of use of the slightly off-axis strategies.

    Example of use of the slightly off-axis strategies. by Raul Castañeda (13932971)

    Published 2022
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  6. 126
    Example of the fully-compensated phase reconstruction package for off-axis DHM holograms recorded in telecentric configuration.

    Example of the fully-compensated phase reconstruction package for off-axis DHM holograms recorded in telecentric configuration. by Raul Castañeda (13932971)

    Published 2022
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  7. 127
    Comparison of edge detector and CHT in detecting droplets.

    Comparison of edge detector and CHT in detecting droplets. by Manibarathi Vaithiyanathan (6655274)

    Published 2019
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  8. 128
    <b>Algorithm Pseudocode</b>

    <b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

    Published 2025
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  9. 129
    Python code, input data, and outputs of Fourier analysis and Dynamic Time Warping from McGlasson et al.

    Python code, input data, and outputs of Fourier analysis and Dynamic Time Warping from McGlasson et al. by Riley McGlasson (13876874)

    Published 2024
    “…</p> <h4><strong>Python Function Files:</strong></h4> <p>radarfuncs.py: Holds three functions used for FFT and DTW analysis.…”
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  10. 130
    Table_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Table_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  11. 131
    Presentation_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Presentation_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  12. 132
    Table_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Table_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  13. 133
    Image_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Image_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  14. 134
    Presentation_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Presentation_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  15. 135
    Presentation_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Presentation_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  16. 136
    Table_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Table_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  17. 137
    ClaritySpectra: Raman spectra analysis tool

    ClaritySpectra: Raman spectra analysis tool by Aaron Celestian (9395696)

    Published 2025
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  18. 138
    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses

    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

    Published 2022
    “…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”
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  19. 139
    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses

    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

    Published 2022
    “…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”
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  20. 140
    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses

    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

    Published 2022
    “…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”
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