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Showing 1 - 20 results of 77 for search '(( elements method algorithm ) OR ((( joint scheduling algorithm ) OR ( data fitting algorithm ))))', query time: 0.13s Refine Results
  1. 1

    A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks by Saad, Walid

    Published 2012
    “…In this work, we propose a utility-based joint uplink/downlink scheduling algorithm suitable for wireless services involving pairwise communication among mobile users. …”
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  2. 2

    Joint BS Assignment and End-to-End Scheduling for Wireless Cellular Networks with Heterogeneous Services by Saad, Walid

    Published 2010
    “…In this work, we extend the end-to-end scheduling approach by designing and evaluating a joint scheduling and BS assignment algorithm in order to further improve the system performance. …”
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    A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

    Published 2025
    “…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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    On end-to-end scheduling in wireless cellular networks by Saad, Walid

    Published 2008
    “…By jointly considering the time varying channel conditions in both uplink and downlink directions, the proposed end-to-end scheduling algorithm achieves an increased number of active connections and a lower packet drop in comparison to other schemes. …”
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  11. 11

    Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study by Alkhodari, Mohanad Ahmed

    Published 2021
    “…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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    Design of adaptive arrays based on element position perturbations by Dawoud, M.M.

    Published 1993
    “…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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  15. 15

    Joint Planning of Smart EV Charging Stations and DGs in Eco-Friendly Remote Hybrid Microgrids by Shaaban, Mostafa

    Published 2019
    “…An outer sub-problem determines the locations and sizes of the DG units and charging stations using a non-dominated sorting Genetic algorithm (NSGA-II). Given the allocation and sizing decisions, an inner sub-problem ensures smart, reliable, and eco-friendly operation of the microgrid by solving a non-linear scheduling problem. …”
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    A Micro-Economics Approach for Scheduling in CDMA Networks with End-to-End QoS Guarantees by Saad, Walid

    Published 2007
    “…To efficiently utilize the available radio resources, we propose a new scheduling algorithm based on techniques from micro-economics. …”
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    A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems by Faria Nawshin (21841598)

    Published 2025
    “…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. However, the increasing adoption of FL in these devices exposes them to adversarial attacks that can compromise user data and device security. …”
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    Bee Colony Algorithm for Proctors Assignment. by Mansour, Nashat

    Published 2015
    “…The search accomplished by three types of bees over a number of iterations aiming to find the source with the highest nectar value (fitness value of a candidate solution). We apply the Bee Colony algorithm to previously published data. …”
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    A kernelization algorithm for d-Hitting Set by Abu-Khzam, Faisal N.

    Published 2010
    “…For 3-Hitting Set, an arbitrary instance is reduced into an equivalent one that contains at most 5k2+k elements. This kernelization is an improvement over previously known methods that guarantee cubic-order kernels. …”
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