Showing 1 - 20 results of 2,514 for search '(((( cloud ((step decrease) OR (a decrease)) ) OR ( a marker decrease ))) OR ( six non decrease ))', query time: 0.38s Refine Results
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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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    A summary of the included study characteristics. by Zahra Tajik (20752452)

    Published 2025
    “…The results show that one month after the NSPT, there was no significant difference in the mean visfatin level of GCF (SMD: -3.91, 95%CI: -9.83, 2.01, p = 0.195, I-square, 96.6%, random effect model, n = 2) and serum (SMD: -0.33, 95%CI: -0.98, 0.33, p = 0.332, fixed effect model, n = 1), but 2, 3 and 6 months after NSPT, the mean visfatin level of GCF and serum decreased significantly. There is no significant difference one month after NSPT in diabetic patients (SMD: -5.83, 95%CI: -15.5, 3.83, p = 0.237, I-square, 97.4%, random effects model, n = 2), but three (SMD: -2.44, 95%CI: -3.37, -1.15, p = 0.001, I-square, 75.9%, random effects model, n = 3) and six months (SMD: -2.41, 95%CI: -3.81, -1.01, p = 0.001, I-square, 78.7%, random effects model, n = 2) after the treatment, a significant decrease is observed in the mean GCF visfatin level. …”
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    List of Included studies. by Zahra Tajik (20752452)

    Published 2025
    “…The results show that one month after the NSPT, there was no significant difference in the mean visfatin level of GCF (SMD: -3.91, 95%CI: -9.83, 2.01, p = 0.195, I-square, 96.6%, random effect model, n = 2) and serum (SMD: -0.33, 95%CI: -0.98, 0.33, p = 0.332, fixed effect model, n = 1), but 2, 3 and 6 months after NSPT, the mean visfatin level of GCF and serum decreased significantly. There is no significant difference one month after NSPT in diabetic patients (SMD: -5.83, 95%CI: -15.5, 3.83, p = 0.237, I-square, 97.4%, random effects model, n = 2), but three (SMD: -2.44, 95%CI: -3.37, -1.15, p = 0.001, I-square, 75.9%, random effects model, n = 3) and six months (SMD: -2.41, 95%CI: -3.81, -1.01, p = 0.001, I-square, 78.7%, random effects model, n = 2) after the treatment, a significant decrease is observed in the mean GCF visfatin level. …”
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    The search strategy in three databases. by Zahra Tajik (20752452)

    Published 2025
    “…The results show that one month after the NSPT, there was no significant difference in the mean visfatin level of GCF (SMD: -3.91, 95%CI: -9.83, 2.01, p = 0.195, I-square, 96.6%, random effect model, n = 2) and serum (SMD: -0.33, 95%CI: -0.98, 0.33, p = 0.332, fixed effect model, n = 1), but 2, 3 and 6 months after NSPT, the mean visfatin level of GCF and serum decreased significantly. There is no significant difference one month after NSPT in diabetic patients (SMD: -5.83, 95%CI: -15.5, 3.83, p = 0.237, I-square, 97.4%, random effects model, n = 2), but three (SMD: -2.44, 95%CI: -3.37, -1.15, p = 0.001, I-square, 75.9%, random effects model, n = 3) and six months (SMD: -2.41, 95%CI: -3.81, -1.01, p = 0.001, I-square, 78.7%, random effects model, n = 2) after the treatment, a significant decrease is observed in the mean GCF visfatin level. …”
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    NIH score. by Zahra Tajik (20752452)

    Published 2025
    “…The results show that one month after the NSPT, there was no significant difference in the mean visfatin level of GCF (SMD: -3.91, 95%CI: -9.83, 2.01, p = 0.195, I-square, 96.6%, random effect model, n = 2) and serum (SMD: -0.33, 95%CI: -0.98, 0.33, p = 0.332, fixed effect model, n = 1), but 2, 3 and 6 months after NSPT, the mean visfatin level of GCF and serum decreased significantly. There is no significant difference one month after NSPT in diabetic patients (SMD: -5.83, 95%CI: -15.5, 3.83, p = 0.237, I-square, 97.4%, random effects model, n = 2), but three (SMD: -2.44, 95%CI: -3.37, -1.15, p = 0.001, I-square, 75.9%, random effects model, n = 3) and six months (SMD: -2.41, 95%CI: -3.81, -1.01, p = 0.001, I-square, 78.7%, random effects model, n = 2) after the treatment, a significant decrease is observed in the mean GCF visfatin level. …”
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    List of excluded studies. by Zahra Tajik (20752452)

    Published 2025
    “…The results show that one month after the NSPT, there was no significant difference in the mean visfatin level of GCF (SMD: -3.91, 95%CI: -9.83, 2.01, p = 0.195, I-square, 96.6%, random effect model, n = 2) and serum (SMD: -0.33, 95%CI: -0.98, 0.33, p = 0.332, fixed effect model, n = 1), but 2, 3 and 6 months after NSPT, the mean visfatin level of GCF and serum decreased significantly. There is no significant difference one month after NSPT in diabetic patients (SMD: -5.83, 95%CI: -15.5, 3.83, p = 0.237, I-square, 97.4%, random effects model, n = 2), but three (SMD: -2.44, 95%CI: -3.37, -1.15, p = 0.001, I-square, 75.9%, random effects model, n = 3) and six months (SMD: -2.41, 95%CI: -3.81, -1.01, p = 0.001, I-square, 78.7%, random effects model, n = 2) after the treatment, a significant decrease is observed in the mean GCF visfatin level. …”
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    Relationship between the Gender Representation Disparity Index (GRDI) and average explicit sex markers in film criticism, illustrating a decrease in markers as the GRDI moves toward a female-dominated cast. by Jad Doughman (20636304)

    Published 2025
    “…<p>Relationship between the Gender Representation Disparity Index (GRDI) and average explicit sex markers in film criticism, illustrating a decrease in markers as the GRDI moves toward a female-dominated cast.…”
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    Point cloud fusion instance effect. by Hongliang Zou (20707270)

    Published 2025
    “…<div><p>The study proposes a multi-sensor localization and real-timeble mapping method based on the fusion of 3D LiDAR point clouds and visual-inertial data, which addresses the issue of decreased localization accuracy and mapping in complex environments that affect the autonomous navigation of robot dogs. …”
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