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Showing 21 - 40 results of 112 for search '(( binary data derived optimization algorithm ) OR ( binary b process optimization algorithm ))*', query time: 0.35s Refine Results
  1. 21
    Image processing workflow.

    Image processing workflow. by Denis Tamiev (7404980)

    Published 2020
    “…<p>Raw fluorescent microscope images (a) were processed with a binary segmentation algorithm, and clusters of bacterial cells were manually annotated. …”
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  2. 22
    Performance Comparison of State-of-the-Art WPT-MEC Offloading Methods.

    Performance Comparison of State-of-the-Art WPT-MEC Offloading Methods. by Hend Bayoumi (22693738)

    Published 2025
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  3. 23
    CDF of task latency, approximated as the inverse of the achieved computation rate.

    CDF of task latency, approximated as the inverse of the achieved computation rate. by Hend Bayoumi (22693738)

    Published 2025
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  4. 24
    The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames.

    The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames. by Hend Bayoumi (22693738)

    Published 2025
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  5. 25
    An Example of a WPT-MEC Network.

    An Example of a WPT-MEC Network. by Hend Bayoumi (22693738)

    Published 2025
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  6. 26
    Related Work Summary.

    Related Work Summary. by Hend Bayoumi (22693738)

    Published 2025
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  7. 27
    Simulation parameters.

    Simulation parameters. by Hend Bayoumi (22693738)

    Published 2025
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  8. 28
    Training losses for N = 10.

    Training losses for N = 10. by Hend Bayoumi (22693738)

    Published 2025
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  9. 29
    Normalized computation rate for N = 10.

    Normalized computation rate for N = 10. by Hend Bayoumi (22693738)

    Published 2025
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  10. 30
    Summary of Notations Used in this paper.

    Summary of Notations Used in this paper. by Hend Bayoumi (22693738)

    Published 2025
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  11. 31
    Application of ABC SMC to the fitting of the binary flip with cusp model.

    Application of ABC SMC to the fitting of the binary flip with cusp model. by Elena Camacho-Aguilar (10906327)

    Published 2021
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  12. 32
    Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files

    Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files by Suchismita Behera (22027316)

    Published 2025
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  13. 33
    Schematic representation of semi-automated algorithm for organoids analyzing.

    Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

    Published 2025
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  14. 34
    Validation of image processing steps and metric results using images of a microfluidic device.

    Validation of image processing steps and metric results using images of a microfluidic device. by Gavrielle R. Untracht (11820311)

    Published 2021
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  15. 35
    Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.

    Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

    Published 2021
    “…P <0.05 was considered statistically significant. (B). The MCDM algorithm-Stage 2. Feature Ranking, this stage is the process of using the TOPSIS method to rank features. …”
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  16. 36
    Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx

    Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx by Yupeng Li (507508)

    Published 2023
    “…In bSRWPSO-FKNN, the core of which is to optimize the classification performance of FKNN through binary SRWPSO.…”
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  17. 37
    Experimental observation of gastruloids and shape quantification using LOCO-EFA.

    Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

    Published 2024
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  18. 38
    Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes

    Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes by Yu Y. (3096192)

    Published 2022
    “…Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …”
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  19. 39
    tUbenet Foundation Model Weights

    tUbenet Foundation Model Weights by Natalie Holroyd (7099391)

    Published 2025
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  20. 40
    Latent state estimations for experimental data with no stressors.

    Latent state estimations for experimental data with no stressors. by Samiul Alam (18563323)

    Published 2024
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