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Showing 61 - 80 results of 274 for search '(( element update algorithm ) OR ((( fluent processing algorithm ) OR ( level coding algorithm ))))', query time: 0.36s Refine Results
  1. 61
    Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived from the 3-level wavelet transform (WT) at four resolutions. These features were used as inputs for traditional ML algorithms. The left map demonstrates the correlation matrix of 52 features crafted from 4 resolutions of the 3-level WT, which are used as inputs for traditional ML algorithms. The heat map (on the right) is the correlation matrix after feature selection, in which features whose Pearson’s correlation coefficient is higher than 0.8 are considered highly correlated. We keep only one representative feature and remove its highly correlated features.

    Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived... by Quang Dung Dinh (20995766)

    Published 2025
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  2. 62
    Multi-material topology optimization using scaled boundary finite element method

    Multi-material topology optimization using scaled boundary finite element method by Mohammed Saif Zamiruddin Siddiqui (22384884)

    Published 2025
    “…SBFEM is implemented and its performance is tested across different density interpolation-based MMTO methods: the Alternating Active-Phase (AAP) algorithm, SIMP with mapping based interpolation, and polygonal mesh based MMTO, PolyMat which uses Discrete Material Optimization (DMO) combined with Zhang–Paulino–Ramos (ZPR) update scheme. …”
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  3. 63
    Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase algorithm for multi-material topology optimization [34]. (c) A new mapping based interpolation function for multi-material topology optimization [35]. (d) A material-field series expansion (MFSE) model for multi-material topology optimization [36].

    Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase... by Zhao Li (300229)

    Published 2025
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  4. 64
    Execution time comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset.

    Execution time comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset. by Liyan Sun (760586)

    Published 2024
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  5. 65
    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DNME 1000 dataset.

    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DNME 1000 dataset. by Liyan Sun (760586)

    Published 2024
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  6. 66
    Genes of the epistastic interactions detected on the seven GWAS data using Epi-SSA.

    Genes of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

    Published 2024
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  7. 67
    Power comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset.

    Power comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset. by Liyan Sun (760586)

    Published 2024
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  8. 68
    Execution time comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 100 dataset.

    Execution time comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 100 dataset. by Liyan Sun (760586)

    Published 2024
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  9. 69
    The brief description on the WTCCC dataset.

    The brief description on the WTCCC dataset. by Liyan Sun (760586)

    Published 2024
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  10. 70
    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset.

    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset. by Liyan Sun (760586)

    Published 2024
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  11. 71
    Power comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DNME 1000 dataset.

    Power comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DNME 1000 dataset. by Liyan Sun (760586)

    Published 2024
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  12. 72
    The overall structure and execution flow of Epi-SSA.

    The overall structure and execution flow of Epi-SSA. by Liyan Sun (760586)

    Published 2024
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  13. 73
    Gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA.

    Gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

    Published 2024
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  14. 74
    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DNME 1000 dataset.

    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DNME 1000 dataset. by Liyan Sun (760586)

    Published 2024
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  15. 75
    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset.

    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset. by Liyan Sun (760586)

    Published 2024
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  16. 76
    Part of gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA.

    Part of gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

    Published 2024
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  17. 77
    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 100 dataset.

    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 100 dataset. by Liyan Sun (760586)

    Published 2024
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  18. 78
    The strategy of sorting the sparrow population based on the rank.

    The strategy of sorting the sparrow population based on the rank. by Liyan Sun (760586)

    Published 2024
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  19. 79
    The gene network of the epistatic interactions detected for Bipolar Disorder.

    The gene network of the epistatic interactions detected for Bipolar Disorder. by Liyan Sun (760586)

    Published 2024
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  20. 80
    F-measure comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset.

    F-measure comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset. by Liyan Sun (760586)

    Published 2024
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