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complement based » complement past (Expand Search), complement cascade (Expand Search), complement system (Expand Search)
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Showing 81 - 100 results of 667 for search '(((( elements based algorithm ) OR ( complement based algorithm ))) OR ( level coding algorithm ))', query time: 0.62s Refine Results
  1. 81
    F1 score of a given number of selected edges on the random graph dataset.

    F1 score of a given number of selected edges on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  2. 82
    F1 score of edges selected through cross-validation on the random graph dataset.

    F1 score of edges selected through cross-validation on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  3. 83
    RealBench: A Repo-Level Code Generation Benchmark Aligned with Real-World Software Development Practices

    RealBench: A Repo-Level Code Generation Benchmark Aligned with Real-World Software Development Practices by RealBench RealBench (22275393)

    Published 2025
    “…<br>│ └── level4/ # Level 4 projects (expert complexity).<br>├── src/ # Main source code for the RealBench framework.…”
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  4. 84
    Temperature measurement at the wire tip during TSE MRI using the standard bases (“Channel coordinate”), low-SAR bases and safe-mode PTX MRI with channel settings determined in the existing and proposed workflows.

    Temperature measurement at the wire tip during TSE MRI using the standard bases (“Channel coordinate”), low-SAR bases and safe-mode PTX MRI with channel settings determined in the... by Maryam Arianpouya (12299222)

    Published 2024
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  5. 85
    Mean values of different benchmark functions.

    Mean values of different benchmark functions. by Jalal- ud-Din (21474307)

    Published 2025
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  6. 86
    Detail of benchmark functions comparison.

    Detail of benchmark functions comparison. by Jalal- ud-Din (21474307)

    Published 2025
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  7. 87
    Average execution time (in seconds) of different benchmark functions.

    Average execution time (in seconds) of different benchmark functions. by Jalal- ud-Din (21474307)

    Published 2025
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  8. 88
    Stander deviation values of different benchmark functions.

    Stander deviation values of different benchmark functions. by Jalal- ud-Din (21474307)

    Published 2025
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  9. 89
    Comparison of different crossover operators.

    Comparison of different crossover operators. by Jalal- ud-Din (21474307)

    Published 2025
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  10. 90
    <b>Codes for "Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control"</b>

    <b>Codes for "Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control"</b> by Yize Wang (19535173)

    Published 2024
    “…<p dir="ltr">The farm-level yaw control optimization algorithm Codes for "Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control"</p>…”
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  11. 91
    Accuracy of different electrical and optical neural networks for various input noise levels.

    Accuracy of different electrical and optical neural networks for various input noise levels. by Reyhane Ahmadi (14857363)

    Published 2024
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  12. 92
    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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  13. 93
    Computational Micromechanics and Machine Learning-Informed Design of Composite Carbon Fiber-Based Structural Battery for Multifunctional Performance Prediction

    Computational Micromechanics and Machine Learning-Informed Design of Composite Carbon Fiber-Based Structural Battery for Multifunctional Performance Prediction by Mohamad A. Raja (19640297)

    Published 2025
    Subjects: “…bayesian optimization algorithm…”
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  14. 94
    Code

    Code by Baoqiang Chen (21099509)

    Published 2025
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  15. 95
    (A) Illustration of grouping and segmentation based on the global similarity structure when the number of elements is small. A, B, C, and D represent stimulus elements at different spatial locations. The physical pairwise similarities are assumed to be high between A and B and between C and D, while they are relatively low for the other four pairs, as indicated by the physical similarity matrix. This configuration potentially leads to the grouping of {A, B} and {C, D}, as depicted by the dashed red squares. Following neural processing that incorporates the global similarity structure, similar pairs are grouped, whereas dissimilar pairs are segregated, as reflected in the perceptual connection matrix. (B) Demonstration of how computational complexity increases with stimulus size. The left panel presents the physical similarity matrix for 3 × 6 and 4 × 8 element stimuli, respectively. The right panel illustrates the exponential growth in the number o

    (A) Illustration of grouping and segmentation based on the global similarity structure when the number of elements is small. A, B, C, and D represent stimulus elements at different... by Yen-Ju Chen (354876)

    Published 2025
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  16. 96
    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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  17. 97
    Pan-Cancer Analysis of G Protein-Coupled Receptors as Cancer Driver Genes and Drug Repurposing Targets

    Pan-Cancer Analysis of G Protein-Coupled Receptors as Cancer Driver Genes and Drug Repurposing Targets by Yue Hou (2562085)

    Published 2025
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  18. 98
    Pan-Cancer Analysis of G Protein-Coupled Receptors as Cancer Driver Genes and Drug Repurposing Targets

    Pan-Cancer Analysis of G Protein-Coupled Receptors as Cancer Driver Genes and Drug Repurposing Targets by Yue Hou (2562085)

    Published 2025
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  19. 99
    Whole slide images classification code.

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

    Published 2025
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  20. 100
    Simulated B<sub>1</sub><sup>+</sup> maps using the standard and the low-SAR bases and the experimental maps for CH1-CH4.

    Simulated B<sub>1</sub><sup>+</sup> maps using the standard and the low-SAR bases and the experimental maps for CH1-CH4. by Maryam Arianpouya (12299222)

    Published 2024
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