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Showing 41 - 60 results of 13,261 for search '(( ((algorithm step) OR (algorithm used)) function ) OR ( algorithm python function ))*', query time: 0.75s Refine Results
  1. 41
    Matlab code of a function used in S2 File.

    Matlab code of a function used in S2 File. by Hiroko Kato Solvang (5718250)

    Published 2024
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  2. 42
    Schematic diagram of dynamic step size expansion.

    Schematic diagram of dynamic step size expansion. by Zhenggang Wang (1753657)

    Published 2025
    Subjects: “…target gravitational function…”
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  3. 43
    Limitation of the conventional DBT reconstruction algorithm.

    Limitation of the conventional DBT reconstruction algorithm. by Yunsu Choi (11993484)

    Published 2022
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  4. 44
    Algorithm operation steps.

    Algorithm operation steps. by Junyan Wang (4738518)

    Published 2025
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  5. 45
    Average quality scores of the models of the analysis set as a function of the <i>w</i><sub><i>SP</i></sub> with which the DOPE potential has been included in the objective function of MODELLER.

    Average quality scores of the models of the analysis set as a function of the <i>w</i><sub><i>SP</i></sub> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

    Published 2019
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  6. 46
    Statistical results of various algorithms.

    Statistical results of various algorithms. by ZeSheng Lin (20501356)

    Published 2025
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  7. 47
    Flowchart outlining the spectral analysis reconstruction algorithm for quantitative phase imaging using non-telecentric DHM systems.

    Flowchart outlining the spectral analysis reconstruction algorithm for quantitative phase imaging using non-telecentric DHM systems. by Brian Bogue-Jimenez (16954568)

    Published 2023
    Subjects: “…developed computational algorithm…”
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  8. 48
    Listed python codes of our algorithm with explanations (Python 3.9 recommended).

    Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

    Published 2023
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  9. 49
    This appendix presents the flowchart used in the development of the particle swarm optimization algorithm for determining the optimal PID controller gain values.

    This appendix presents the flowchart used in the development of the particle swarm optimization algorithm for determining the optimal PID controller gain values. by Rafael Mendes Faria (18886798)

    Published 2024
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  10. 50
    The Pseudo-Code of the IRBMO Algorithm.

    The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

    Published 2025
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  11. 51
    Flowchart of improved FOX optimization algorithm.

    Flowchart of improved FOX optimization algorithm. by Mahmood A. Jumaah (22272371)

    Published 2025
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  12. 52
    Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen reference.

    Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

    Published 2021
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  13. 53
    Adaptive H-REMD simulation algorithm.

    Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

    Published 2021
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  14. 54
    Node matching step 1.

    Node matching step 1. by Shuwen Wang (457921)

    Published 2023
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  15. 55
    Network structure of perception fusion algorithm.

    Network structure of perception fusion algorithm. by Weilin Wu (13736)

    Published 2024
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  16. 56
    Instance count of all output steps based on schedulability.

    Instance count of all output steps based on schedulability. by Zhiqun Lin (1429501)

    Published 2023
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  17. 57
    Count comparison of all output steps based on time performance.

    Count comparison of all output steps based on time performance. by Zhiqun Lin (1429501)

    Published 2023
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  18. 58
    Parameters used to train the xgboost final models through the extreme gradient boosting algorithm in this work (n = 11,009 species).

    Parameters used to train the xgboost final models through the extreme gradient boosting algorithm in this work (n = 11,009 species). by Luis Javier Madrigal-Roca (17743035)

    Published 2024
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  19. 59
    Great machine learning performance with multiple classification algorithms.

    Great machine learning performance with multiple classification algorithms. by Sydney C. Weiser (15383531)

    Published 2023
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  20. 60
    Generating the PSC kernel using a double exponential function.

    Generating the PSC kernel using a double exponential function. by Alireza Ghadimi (13839874)

    Published 2022
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