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Showing 81 - 100 results of 289 for search '(( ((python model) OR (python code)) implementation ) OR ( python after implementing ))', query time: 0.35s Refine Results
  1. 81
    Flowchart of Random Aggregate Placement Process.

    Flowchart of Random Aggregate Placement Process. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  2. 82
    Splitting Specimen Aggregate Placement Area.

    Splitting Specimen Aggregate Placement Area. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  3. 83
    Specimen for the splitting test.

    Specimen for the splitting test. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  4. 84
    Example Diagram.

    Example Diagram. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  5. 85
    Aggregate Measurement Image in IPP.

    Aggregate Measurement Image in IPP. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  6. 86
    Internal changes of the specimen of 0.82 to 0.84.

    Internal changes of the specimen of 0.82 to 0.84. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  7. 87
    Internal changes of the specimen of 0.86 to 0.88.

    Internal changes of the specimen of 0.86 to 0.88. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  8. 88
    Internal changes of the specimen of 0.7 to 0.75.

    Internal changes of the specimen of 0.7 to 0.75. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  9. 89
    Internal changes of the specimen of 0.87 to 0.9.

    Internal changes of the specimen of 0.87 to 0.9. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  10. 90
    Internal changes of the specimen of 0.74 to 0.76.

    Internal changes of the specimen of 0.74 to 0.76. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  11. 91
    Internal changes of the specimen 1.55 to 1.60.

    Internal changes of the specimen 1.55 to 1.60. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  12. 92
    Internal changes of the specimen of 1.70 to 1.75.

    Internal changes of the specimen of 1.70 to 1.75. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  13. 93
    Internal changes of the specimen of 0.89 to 1.

    Internal changes of the specimen of 0.89 to 1. by Nan Ru (9594384)

    Published 2025
    “…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”
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  14. 94
    Schematic of the approach: This schematic illustrates the entire workflow of the project.

    Schematic of the approach: This schematic illustrates the entire workflow of the project. by Enock Niyonkuru (21246879)

    Published 2025
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  15. 95
    Text Transformation Pipeline: An example of the multi-stage text transformation pipeline applied to a sample abstract (PMID: 30609739).

    Text Transformation Pipeline: An example of the multi-stage text transformation pipeline applied to a sample abstract (PMID: 30609739). by Enock Niyonkuru (21246879)

    Published 2025
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  16. 96
    Comparison of window size for embedding with Wordnet synonym replacement (WN) and without (PM). While Table 1 compared the effects of different values of using a window size of 10, this Table shows the results for three different window sizes at a =. Abbreviations are the same as for Table 1.

    Comparison of window size for embedding with Wordnet synonym replacement (WN) and without (PM). While Table 1 compared the effects of different values of using a window size of 10,... by Enock Niyonkuru (21246879)

    Published 2025
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  17. 97
    Non-biomedical word replacement algorithm: This algorithm outlines the process for replacing non-biomedical words in a corpus using WordNet.

    Non-biomedical word replacement algorithm: This algorithm outlines the process for replacing non-biomedical words in a corpus using WordNet. by Enock Niyonkuru (21246879)

    Published 2025
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  18. 98
    Comparison of mean interconcept distance for embedding with WordNet synonym replacement (WN) and without (PM). The initial number of unique concepts in the total corpus was 3,018,918. The Table summarizes results for different thresholds () and categories of concept/gene sets (M,B,K,G,P). Columns: : Replacement threshold; replaced: Unique Replaced Concepts; Category: M = MeSH, B = Biocarta, K = KEGG, G = GP(bp), P = PID; # sets: Number of concept/gene sets in the categories; #Concepts: number of concept vectors in the category; <i>WN better</i><i>: The count and percentage of concept/gene sets for which the mean interconcept distance was smaller for WN than for PM. “Winners” are shown in bold.;</i> <i>PM better</i><i>: Analogous to “WN better” but for PM.</i>

    Comparison of mean interconcept distance for embedding with WordNet synonym replacement (WN) and without (PM). The initial number of unique concepts in the total corpus was 3,018,9... by Enock Niyonkuru (21246879)

    Published 2025
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  19. 99
    Comparative analysis of WN and PM methodologies: Figure (a) displays the bar chart comparing WN and PM across five distinct concept sets (Methods), highlighting the number of concept sets where the cluster mean distance is significantly lower, indicative of superior embeddings.

    Comparative analysis of WN and PM methodologies: Figure (a) displays the bar chart comparing WN and PM across five distinct concept sets (Methods), highlighting the number of conce... by Enock Niyonkuru (21246879)

    Published 2025
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  20. 100
    DeepB3Pred - code

    DeepB3Pred - code by Saleh Musleh (22263718)

    Published 2025
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