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processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
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Showing 121 - 140 results of 627 for search '(( element based algorithm ) OR ((( query processing algorithm ) OR ( level coding algorithm ))))', query time: 0.37s Refine Results
  1. 121
    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
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  2. 122
    Flowchart of Random Aggregate Placement Process.

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

    Published 2025
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  3. 123
    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
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  4. 124
    Splitting Specimen Aggregate Placement Area.

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

    Published 2025
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  5. 125
    Influence of Shape Parameters on the Compressive Performance of the Specimens.

    Influence of Shape Parameters on the Compressive Performance of the Specimens. by Nan Ru (9594384)

    Published 2025
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  6. 126
    Schematic diagram of the extension of vertices of large and small polygons.

    Schematic diagram of the extension of vertices of large and small polygons. by Nan Ru (9594384)

    Published 2025
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  7. 127
    Specimen for the splitting test.

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

    Published 2025
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  8. 128
    The influence of angularity on the splitting resistance performance of the specimens.

    The influence of angularity on the splitting resistance performance of the specimens. by Nan Ru (9594384)

    Published 2025
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  9. 129
    Example Diagram.

    Example Diagram. by Nan Ru (9594384)

    Published 2025
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  10. 130
    Influence of Shape Parameters on the Splitting Resistance Performance of the Specimens.

    Influence of Shape Parameters on the Splitting Resistance Performance of the Specimens. by Nan Ru (9594384)

    Published 2025
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  11. 131
    Aggregate Measurement Image in IPP.

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

    Published 2025
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  12. 132
    Influence of the Roundness Ratio on the Compressive Performance of the Specimens.

    Influence of the Roundness Ratio on the Compressive Performance of the Specimens. by Nan Ru (9594384)

    Published 2025
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  13. 133
    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
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  14. 134
    TSProm: Deciphering the Genomic Context of Tissue Specificity

    TSProm: Deciphering the Genomic Context of Tissue Specificity by Pallavi Surana (8921885)

    Published 2025
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  15. 135
    Whole slide images classification code.

    Whole slide images classification code. by Yaëlle Bellahsen-Harrar (22139194)

    Published 2025
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  16. 136
    a. How various statistical models account for modulation classification performance across the entire dataset.

    a. How various statistical models account for modulation classification performance across the entire dataset. by Chris Scholes (3309477)

    Published 2025
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  17. 137
    Code snippet from “Netty/Buffer” Maven artefact.

    Code snippet from “Netty/Buffer” Maven artefact. by Matthew Yit Hang Yeow (20721206)

    Published 2025
    “…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”
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  18. 138
    Horizontal coding of milling parameters.

    Horizontal coding of milling parameters. by Nanqi Li (11640083)

    Published 2025
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  19. 139
    Model code

    Model code by Waltraud Schulze (20695250)

    Published 2025
    “…The latter provides insights into the inherent texture complexity of the image data due to the lossless coding. For classification of leaf surfaces from tree species based on the computed features, we utilized the k-nearest neighbors (kNN) algorithm with k=3. …”
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  20. 140
    A classification scheme of bipartite randomization algorithms, based on whether the matrix row and columns sums are preserved exactly (Fixed, <i>F</i>), preserved on average (Proportional, <i>P</i>), or unconstrained (Equiprobable, <i>E</i>).

    A classification scheme of bipartite randomization algorithms, based on whether the matrix row and columns sums are preserved exactly (Fixed, <i>F</i>), preserved on average (Propo... by Zachary P. Neal (9946331)

    Published 2024
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