Showing 1 - 20 results of 120 for search '(((( experiments showed algorithm ) OR ( complement ii algorithm ))) OR ( level coding algorithm ))', query time: 0.14s Refine Results
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    Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars by Abathar Al-Hamrani (16494884)

    Published 2023
    “…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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    Video features with impact on user quality of experience by Abbas, Nadine

    Published 2021
    “…One of the major challenges in wireless networks is to quantify and evaluate the user quality of experience (QoE). Hence, network operators are continuously working towards identifying the factors that most affect the user quality of experience for better network resource management. …”
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    Web Based Online Hybrid Teaching Method of Network Music Course by Abu Zitar, Raed

    Published 2022
    “…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …”
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    Deep learning-based user experience evaluation in distance learning by Rahim Sadigov (17714301)

    Published 2023
    “…<div><p>The Covid-19 pandemic caused uncertainties in many different organizations, institutions gained experience in remote working and showed that high-quality distance education is a crucial component in higher education. …”
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    Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems by Abualigah, Laith

    Published 2023
    “…The proposed method is based on enhancing the search process of the Prairie Dog Optimization Algorithm (PDOA) by using the primary updating mechanism of the Dwarf Mongoose Optimization Algorithm (DMOA). …”
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    Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

    Published 2024
    “…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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    A novel linear time corner detection algorithm by Sarfraz, M.

    Published 2005
    “…The experiments show that this method leads to good quality results and robustness to noise with low computational cost.…”
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    A hybrid graph representation for exact graph algorithms by Abu-Khzam, Faisal N.

    Published 2014
    “…Experiments on three well studied problems show consistent significant improvements over classical methods.…”
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    Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

    Published 2006
    “…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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    Burst Round Robin as a Proportional-Share Scheduling Algorithm by Helmy, Tarek

    Published 2020
    “…We present a novel weight adjustment for processes that are blocked for I/O and lose some CPU time to assure proportional fairness. Experiments on the implemented simulator showed that quickly knocking away shortest processes achieves better turnaround time, waiting time, and response time. …”
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    Properties of simulated annealing and genetic algorithms for mapping data to multicomputers by Mansour, Nashat

    Published 1997
    “…We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorithms (GA) for mapping data to multicomputers. …”
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    An enhanced k-means clustering algorithm for pattern discovery in healthcare data by Haraty, Ramzi A.

    Published 2015
    “…Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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