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Showing 41 - 60 results of 7,200 for search '(( ((algorithm python) OR (algorithm b)) function ) OR ( algorithm design function ))', query time: 0.64s Refine Results
  1. 41
    Experimental design.

    Experimental design. by Anis Najar (9745561)

    Published 2020
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  2. 42
    IDEN algorithm and gene pair-based drug repurposing.

    IDEN algorithm and gene pair-based drug repurposing. by Yao Jiang (1469614)

    Published 2022
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  3. 43
    Experiment 2D and 5D: Progressive Sample Scaling Algorithm To Solve Many-Affine BBOB Functions.

    Experiment 2D and 5D: Progressive Sample Scaling Algorithm To Solve Many-Affine BBOB Functions. by Boris Almonacid (4110337)

    Published 2024
    “…</li></ul><p dir="ltr"><b>Limitations</b></p><ul><li>This algorithm is designed for Many-Affine BBOB problems of 2 and 5 dimensions.…”
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  4. 44
    The recurrent T3D algorithm.

    The recurrent T3D algorithm. by Neythen J. Treloar (8698251)

    Published 2022
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  5. 45
    Iteration versus fitness function.

    Iteration versus fitness function. by B. Venkatesh (17202747)

    Published 2024
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  6. 46
    a) DPR based Single Round MISTY1 / KASUMI, b) FI function.

    a) DPR based Single Round MISTY1 / KASUMI, b) FI function. by Huang Jiexian (17060975)

    Published 2023
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  7. 47
    Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart.

    Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

    Published 2025
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  8. 48
    Samples from IPPs with a mixture of squared exponential intensity function (<i>p</i> = 2).

    Samples from IPPs with a mixture of squared exponential intensity function (<i>p</i> = 2). by M. Hassan Tanveer (9596437)

    Published 2020
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  9. 49
    The GOR4 and SOPMA algorithm findings.

    The GOR4 and SOPMA algorithm findings. by Ahmad Abdullah Mahdeen (19704401)

    Published 2024
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  10. 50
    Python-based Monte Carlo Simulation Tool

    Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

    Published 2024
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  11. 51
    Fig 1 -

    Fig 1 - by Tuan Anh Pham (1346049)

    Published 2020
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  12. 52
    Fig 10 -

    Fig 10 - by Tuan Anh Pham (1346049)

    Published 2020
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  13. 53
    The relationship between dependent variables and salary.

    The relationship between dependent variables and salary. by Yangda Gong (12015173)

    Published 2022
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  14. 54
    Resume information distribution.

    Resume information distribution. by Yangda Gong (12015173)

    Published 2022
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  15. 55
    Adaptive H-REMD simulation algorithm.

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

    Published 2021
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  16. 56
    Regression function between network training, verification and prediction output values.

    Regression function between network training, verification and prediction output values. by Bo Yu (241082)

    Published 2021
    Subjects: “…facilitates manufactures designing…”
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  17. 57
    Synthesized construct and experimental design.

    Synthesized construct and experimental design. by Antoine L. Decrulle (11540003)

    Published 2021
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  18. 58
    A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction methods.

    A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)

    Published 2025
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  19. 59
    Detailed design of dynamic head.

    Detailed design of dynamic head. by Zhibo Fu (19009854)

    Published 2024
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  20. 60
    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results

    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

    Published 2025
    “…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”
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