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Showing 1 - 20 results of 668 for search '(((( element processing algorithm ) OR ( element ii algorithm ))) OR ( level coding algorithm ))', query time: 0.55s Refine Results
  1. 1
    Process followed to develop and validate the MAMELI algorithm.

    Process followed to develop and validate the MAMELI algorithm. by Valentina Bollati (106778)

    Published 2025
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  2. 2
    Comparison of different optimization algorithms.

    Comparison of different optimization algorithms. by Hang Zhao (143592)

    Published 2025
    Subjects: “…crayfish optimization algorithm…”
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  3. 3
    Comparison of PSNR values of different algorithms.

    Comparison of PSNR values of different algorithms. by Xiaojun Wang (50332)

    Published 2025
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  4. 4
    Changes in FID values of different algorithms.

    Changes in FID values of different algorithms. by Xiaojun Wang (50332)

    Published 2025
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  5. 5
    Comparison of SSIM values of different algorithms.

    Comparison of SSIM values of different algorithms. by Xiaojun Wang (50332)

    Published 2025
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  6. 6
    Changes in loss values for different algorithms.

    Changes in loss values for different algorithms. by Xiaojun Wang (50332)

    Published 2025
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  7. 7
    Flowchart of Random Aggregate Placement Process.

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

    Published 2025
    “…The results show that: (1) As the irregularity of the RCA’s external shape increases, the ultimate failure load of the specimens shows an upward trend. (2) When the aspect ratio reaches 1.70 to 1.75, the shape parameter reaches 0.70 to 0.75, the roundness ratio is between 0.84 to 0.82, and the angularity reaches 0.76 to 0.74, the ultimate failure load of the specimens shows a downward trend. (3) The finite-element modeling algorithm can well reflect the morphology of coarse aggregates and accurately characterize the influence of aggregate morphology on the mechanical properties of asphalt mixtures.…”
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  8. 8
    Test of polymethyl methacrylate (C<sub>5</sub>O<sub>2</sub>H<sub>8</sub>) through algorithm: Curves of both objective function and fractional weight in the process of identifying third chemical constituent after H was assumed, i.e., step 2 in Figure 2.

    Test of polymethyl methacrylate (C<sub>5</sub>O<sub>2</sub>H<sub>8</sub>) through algorithm: Curves of both objective function and fractional weight in the process of identifying t... by Dong Hyeok Choi (12562048)

    Published 2025
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  9. 9
    A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density.

    A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density. by Hassan Mehboob (8960273)

    Published 2025
    “…<p>A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density.…”
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  10. 10
    The actual training effect of four algorithms on original photo data (All images are original images taken by the author).

    The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

    Published 2025
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  11. 11
    Action potential of sample points in model 2.

    Action potential of sample points in model 2. by Hang Zhao (143592)

    Published 2025
    Subjects: “…crayfish optimization algorithm…”
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  12. 12
    (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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  13. 13
    Analysis of elements of emergency resource scheduling model in chemical industry park.

    Analysis of elements of emergency resource scheduling model in chemical industry park. by Yuhang Wang (332111)

    Published 2025
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  14. 14
    Main code.

    Main code. by Jingguo Bi (21439766)

    Published 2025
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  15. 15
    Flowchart of the study.

    Flowchart of the study. by Usman Haider (12630481)

    Published 2025
    “…The RF chain is made to keep the beamforming weights of subarray antenna elements in a TDM fashion. In this paper, two dynamic clustering algorithms are proposed. …”
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  16. 16
    Channel capacity of MIMO system with variable .

    Channel capacity of MIMO system with variable . by Usman Haider (12630481)

    Published 2025
    “…The RF chain is made to keep the beamforming weights of subarray antenna elements in a TDM fashion. In this paper, two dynamic clustering algorithms are proposed. …”
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  17. 17
    Pareto optimal front result of MOCOA.

    Pareto optimal front result of MOCOA. by Hang Zhao (143592)

    Published 2025
    Subjects: “…crayfish optimization algorithm…”
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  18. 18
    Confusion matrix.

    Confusion matrix. by Hang Zhao (143592)

    Published 2025
    Subjects: “…crayfish optimization algorithm…”
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  19. 19
    Different patterns of electrocardio signals with Gaussian noise.

    Different patterns of electrocardio signals with Gaussian noise. by Hang Zhao (143592)

    Published 2025
    Subjects: “…crayfish optimization algorithm…”
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  20. 20
    Sensitivity analysis of parameter K and in VMD.

    Sensitivity analysis of parameter K and in VMD. by Hang Zhao (143592)

    Published 2025
    Subjects: “…crayfish optimization algorithm…”
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