Showing 1 - 20 results of 1,474 for search '(((( cloud ((map decrease) OR (_ decrease)) ) OR ( k mean decrease ))) OR ( a larger decrease ))', query time: 0.64s Refine Results
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    Displacement cloud maps. by Maogang Tian (21485116)

    Published 2025
    “…Furthermore, parametric studies reveal that the pile base displacement exhibits a non-linear trend of initially decreasing and then increasing with larger inclination angles of the inclined piles. …”
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    K-means++ clustering algorithm. by Zhen Zhao (159931)

    Published 2025
    “…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”
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    K-means results. by Fei Zhang (85787)

    Published 2025
    “…<div><p>This study aims to investigate the dynamics of basketball game pace and its influence on game outcomes through a novel intra-game segmentation approach. By employing K-means clustering on possession duration, we categorized possessions from 1,141 NBA games in the 2019–2020 season into high-frequency (HFS), low-frequency (LFS), and normal-frequency segments (NFS). …”
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    HDECO: A method for Decreasing energy and cost by using virtual machine migration by considering hybrid parameters by Arash GhorbanniaDelavar (22563696)

    Published 2025
    “…<h2>Summary</h2><p dir="ltr">This research introduces <b>HDECO</b> (Hybrid Decreasing Energy and Cost Optimization) — a method designed to reduce both energy consumption and execution cost in cloud datacenters through intelligent virtual machine migration. …”
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    Effects of GJE extract treatment decreased expression of NF-kB p65. by Natnicha Suttawong (22367172)

    Published 2025
    “…Brown color represents NF-kB p65 positive staining. The percentage of positive staining for NF-kB p65 (E). …”
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    Biases in larger populations. by Sander W. Keemink (21253563)

    Published 2025
    “…<p>(<b>A</b>) Maximum absolute bias vs the number of neurons in the population for the Bayesian decoder. …”
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