Proposed Algorithm. حسب Hend Bayoumi (22693738)

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Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

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Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30. حسب Hend Bayoumi (22693738)

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Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30. حسب Hend Bayoumi (22693738)

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

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Related Work Summary. حسب Hend Bayoumi (22693738)

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Simulation parameters. حسب Hend Bayoumi (22693738)

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

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

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

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

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

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Comparison between Bisection and Newton-Raphson in terms of (A) total time consumed, and (B) maximum computation rate. حسب Hend Bayoumi (22693738)

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

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<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

"…<b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …"

An example of a type of texture of binary preferred/non-preferred ranges of raw vegetation index values type feature. حسب Elise Varaela Voltura (17592996)

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

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

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

"…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. …"

Latent state estimations for experimental data with no stressors for subject 1. حسب Samiul Alam (18563323)