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Showing 1 - 20 results of 79 for search '(((( elements data algorithm ) OR ( elements cscap algorithm ))) OR ( data groupings algorithm ))', query time: 0.13s Refine Results
  1. 1

    A novel encryption algorithm using multiple semifield S-boxes based on permutation of symmetric group by Iqtadar Hussain (14147850)

    Published 2023
    “…The presented algorithm is mainly based on the Shannon idea of substitution–permutation network where the process of substitution is performed by the proposed S<sub>8</sub> semifield substitution boxes and permutation operation is performed by the binary cyclic shift of substitution box transformed data. …”
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    Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

    Published 2024
    “…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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    article
  5. 5

    Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm by Abu Zitar, Raed

    Published 2022
    “…Researchers have scrutinized data hiding schemes in recent years. Data hiding in standard images works well, but does not provide satisfactory results in distortion-sensitive medical, military, or forensic images. …”
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    A Survey of Data Clustering Techniques by Sobeh, Salma

    Published 2023
    “…Clustering, an unsupervised learning technique, aims to identify a specific number of clusters to effectively categorize the data through data grouping. Hence, clustering is related to many fields and is used in various applications that deal with large datasets. …”
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    masterThesis
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    Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

    Published 2023
    “…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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    Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

    Published 2019
    “…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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    BUC algorithm for iceberg cubes by Nasr, George E.

    Published 2003
    “…The Iceberg-Cube problem restricts the computation of the data cube to only those group-by partitions satisfying a minimum threshold condition defined on a specified measure. …”
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    Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

    Published 2024
    “…<p dir="ltr">In this article, we present a novel deep learning-based group contribution framework for the targeted design of ionic liquids (ILs). …”
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    Social spider optimization algorithm: survey and new applications by Abualigah, Laith

    Published 2024
    “…One of the PSO algorithms or versions is the social spider optimization (SSO) algorithm, a simulation of the interaction between spider groups, males and females. …”
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  14. 14

    (k, l)-Clustering for Transactional Data Streams Anonymization by Tekli, Jimmy

    Published 2018
    “…In this paper, we address the correlation problem in the anonymization of transactional data streams. We propose a bucketization-based technique, entitled (k, l)-clustering to prevent such privacy breaches by ensuring that the same k individuals remain grouped together over the entire anonymized stream. …”
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    Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

    Published 2024
    “…Unsupervised machine learning is a powerful technique for performing clustering, which involves identifying patterns or similarities within a dataset and grouping them into distinct clusters or subgroups. …”
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    masterThesis
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    Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic by AL MANSOORI, MOUZA

    Published 2021
    “…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. In this study, we used twitter as our data source. …”
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    XBeGene: Scalable XML Documents Generator by Example Based on Real Data by Harazaki, Manami

    Published 2012
    “…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …”
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    conferenceObject
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    BioNetApp: An interactive visual data analysis platform for molecular expressions by Ali M. Roumani (18615124)

    Published 2019
    “…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”