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Showing 201 - 220 results of 483 for search '(((( data processing algorithm ) OR ( element new algorithm ))) OR ( levels using algorithm ))', query time: 0.13s Refine Results
  1. 201

    Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE by Mathew, Elezabeth

    Published 2020
    “…The data analytics maturity model is used as the conceptual model for evaluating both data analytics and data governance in this research. …”
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  2. 202

    A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method by Shahid Rahman (16904613)

    Published 2022
    “…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. …”
  3. 203
  4. 204

    Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

    Published 2023
    “…Cyberbullying involves the use of communication technology and data, including messages, photographs, and videos, to undertake aggressive negative actions to harm others. …”
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  5. 205
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  8. 208

    Efficient Seismic Volume Compression using the Lifting Scheme by Khene, M. F.

    Published 2000
    “…A separable 3-D discrete wavelet transform (DWT) using long biorthogonal filters is used. The computation efficiency of the DWT is improved by factoring the wavelet filters using the lifting scheme. …”
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    article
  9. 209

    C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments by Raun, Kristo

    Published 2023
    “…The aim of streaming conformance checking is to find dis crepancies between process executions on streaming data and the refer ence process model. …”
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  10. 210

    FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

    Published 2020
    “…Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. In this paper, the suitability of packet-level and flow-level features is validated using stepwise regression and random forest feature selection. …”
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    article
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    TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

    Published 2020
    “…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”
  13. 213
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    Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey by Faria Nawshin (21841598)

    Published 2024
    “…Researchers are also developing various techniques for detecting and analyzing <u>mobile malware</u> to overcome these issues. As new <u>malware</u> gets introduced frequently by <u>malware developers</u>, it is very challenging to come up with comprehensive algorithms to detect this malware. …”
  15. 215

    Modulation With Metaheuristic Approach for Cascaded-MPUC49 Asymmetrical Inverter With Boosted Output by Kaif Ahmed Lodi (16855518)

    Published 2020
    “…For the calculation of optimum angles, a meta-heuristic based Genetic Algorithm (GA) technique is employed. The generation of 49-level output requires 24 transitions in one quarter of a cycle. …”
  16. 216
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    Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation by Hariprasath Manoharan (14157966)

    Published 2023
    “…<p dir="ltr">The process of using robotic technology to examine underwater systems is still a difficult undertaking because the majority of automated activities lack network connectivity. …”
  18. 218
  19. 219

    Correlation Clustering with Overlaps by Fakhereldine, Amin

    Published 2020
    “…We present a heuristic algorithm and a semi-exact algorithm for the Multi-Parameterized Cluster Editing with Vertex Splitting problem. …”
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    masterThesis
  20. 220

    Defining quantitative rules for identifying influential researchers: Insights from mathematics domain by Ghulam Mustafa (458105)

    Published 2024
    “…Within each categorical grouping, we meticulously selected the five most pivotal parameters. This selection process was guided by an importance score, that was derived after assessing its influence on the model's performance in the classification of data pertaining to both awardees and non awardees. …”