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Showing 201 - 220 results of 904 for search '(( elements update algorithm ) OR ((( data using algorithm ) OR ( designed using algorithm ))))', query time: 0.12s Refine Results
  1. 201

    Unsupervised outlier detection in multidimensional data by Atiq ur Rehman (14153391)

    Published 2022
    “…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …”
  2. 202

    Android Malware Detection Using Machine Learning by Al Ali, Shaikha

    Published 2024
    “…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …”
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    Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by Zakaria Tolba (16904718)

    Published 2022
    “…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …”
  5. 205

    Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

    Published 2023
    “…This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …”
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    Graph Contraction for Mapping Data on Parallel Computers by Mansour, N.

    Published 1994
    “…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
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  11. 211

    A New Parallel Genetic Algorithm Model by Al-Somani, Turki F.

    Published 2020
    “…The reduction of the implementation processing time is the basic motivation of genetic algorithms parallelization. In this work, parallel virtual machine (PVM), which is a portable message-passing programming system, designed to link separate host machines to form a virtual machine which is a single, manageable computing resource, is used in a distributed heterogeneous environment. …”
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  12. 212

    Mapping realistic data sets on parallel computers by Mansour, N.

    Published 1993
    “…The GC algorithm allows large-scale mapping to become efficient, especially when slow but high-quality mappers are used.…”
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  13. 213

    Parallel genetic algorithm for disease-gene association by Mansour, Nashat

    Published 2011
    “…In this work, we combine few successful strategies from the literature and present a parallel genetic algorithm for the Tag SNP Selection problem. Our results compared favorably with those of a recognized tag SNP selection algorithm using three different data sets from the HapMap project.…”
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  14. 214
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    Particle swarm optimization algorithm: review and applications by Abualigah, Laith

    Published 2024
    “…The main procedure of the PSO algorithm is presented. Future researchers can use the collected data in this survey as baseline information on the PSO and PSO's applications.…”
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  16. 216

    New enumeration algorithm for regular boolean functions by Nasrallah, Walid F.

    Published 2018
    “…This algorithm exploits the equivalence between regular Boolean functions and positive threshold functions that can be used to represent instances of the knapsack problem. …”
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  17. 217
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    The Effects of Data Mining on Small Businesses in Dubai by AlMutawa, Rasha

    Published 2011
    “…While there are numerous studies on the best data mining models and their uses, even on certain industries, this study focuses on the applications more than the algorithms and models and their usefulness for small businesses specifically. …”
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