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Showing 121 - 134 results of 134 for search '(( elements method algorithm ) OR ((( data points algorithm ) OR ( task scheduling algorithm ))))', query time: 0.10s Refine Results
  1. 121

    Could Petrol Stations Play a Key Role in Transportation Electrification? A GIS-Based Coverage Maximization of Fast EV Chargers in Urban Environment by Safak Bayram (16925975)

    Published 2022
    “…<p>To achieve net-zero in the transportation sector, there is a need to deploy public electric vehicle (EV) fast chargers to boost customer confidence. Currently, charge point operators and EV manufacturers focus on deploying chargers to cover highway networks and the progress in urban environments is inadequate. …”
  2. 122

    Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study by Alaa Abd-alrazaq (17058018)

    Published 2024
    “…</p><h3>Methods</h3><p dir="ltr">We conducted an analysis to identify research gaps in COVID-19 literature using the COVID-19 Open Research (CORD-19) data set, which comprises 1,121,433 papers related to the COVID-19 pandemic. …”
  3. 123

    Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying by Tekli, Joe

    Published 2023
    “…Many efforts have been deployed by the IR community to extend freetext query processing toward semi-structured XML search. Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. …”
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    article
  4. 124

    CEAP by Abdel Wahab, Omar

    Published 2016
    “…To reduce the overhead of the proposed detection model and make it feasible for the resource-constrained nodes, we reduce the size of the training dataset by (1) restricting the data collection, storage, and analysis to concern only a set of specialized nodes (i.e., Multi-Point Relays) that are responsible for forwarding packets on behalf of their clusters; and (2) migrating only few tuples (i.e., support vectors) from one detection iteration to another. …”
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    article
  5. 125

    Deepfakes Signatures Detection in the Handcrafted Features Space by Hamadene, Assia

    Published 2023
    “…In the Handwritten Signature Verification (HSV) literature, several synthetic databases have been developed for data-augmentation purposes, where new specimens and new identities were generated using bio-inspired algorithms, neuromotor synthesizers, Generative Adversarial Networks (GANs) as well as several deep learning methods. …”
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  6. 126
  7. 127

    Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates by Ratiba F. Ghachi (14152455)

    Published 2022
    “…The thin plate and the zigzag cutouts are modelled using the finite element method, and the optimal location and optimal tip mass of the zigzag cutouts are obtained using genetic algorithms through iterative simulations. …”
  8. 128

    Modelling of pollutant transport in compound open channels by Chatila, Jean Georges

    Published 1998
    “…The numerical computation of open-channel flows requires preparing and processing larger volumes of boundary and bathymetry data for computer inputs and the development of numerical algorithms for treating complex boundary condition, channel properties, and free surface effects. …”
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    masterThesis
  9. 129

    Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

    Published 2019
    “…At enrollment, this work predicts a student’s GPA in different majors using enrollment data such as high school average, placement test results, and IELTS score. …”
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  10. 130

    FoGMatch by Arisdakessian, Sarhad

    Published 2019
    “…In this context, the notion of fog computing has been projected to furnish data analytics and decision-making closer to the IoT devices. …”
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    masterThesis
  11. 131

    ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks by Muhammad Asif Khan (7367468)

    Published 2022
    “…In this paper, we propose data-driven machine learning (ML) schemes to efficiently solve these problems in wireless LAN (WLAN) networks. …”
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