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utilization algorithm » optimization algorithm (Expand Search), initialization algorithm (Expand Search), optimization algorithms (Expand Search)
resource utilization » resource allocation (Expand Search)
estimation algorithm » optimization algorithm (Expand Search), optimization algorithms (Expand Search), maximization algorithm (Expand Search)
time resource » situ resource (Expand Search), firm resource (Expand Search), optimize resource (Expand Search)
binary time » binary image (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data pose » data posted (Expand Search), data phase (Expand Search), data base (Expand Search)
Showing 1 - 9 results of 9 for search '(( binary time resource utilization algorithm ) OR ( binary data pose estimation algorithm ))*', query time: 0.47s Refine Results
  1. 1
    Dynamic resource allocation process.

    Dynamic resource allocation process. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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  2. 2
    Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regions/organ systems.

    Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regio... by Michael D. Cobler-Lichter (22492930)

    Published 2025
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  3. 3
    Experimental setup and trajectory estimation methodology.

    Experimental setup and trajectory estimation methodology. by Nouman Javed (16624785)

    Published 2023
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  4. 4
    Confusion matrix.

    Confusion matrix. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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  5. 5
    Parameter settings.

    Parameter settings. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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  6. 6
    Event-driven data flow processing.

    Event-driven data flow processing. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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  7. 7
    ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for test data classification results across all folds.

    ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for te... by G. Christopher Marais (21492084)

    Published 2025
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  8. 8
    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things

    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

    Published 2025
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  9. 9
    GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios

    GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

    Published 2025
    “…Here, we present GridScopeRodents, a high-resolution global dataset projecting the distribution of 10 rodent genera from 2021 to 2100 under four CMIP6-based Shared Socioeconomic Pathway–Representative Concentration Pathway (SSP–RCP) scenario combinations. Using occurrence data and environmental variable, we employ the Maximum Entropy (MaxEnt) algorithm within the species distribution modeling (SDM) framework to estimate occurrence probability at a spatial resolution of 1/12° (~10 km). …”
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