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Showing 181 - 200 results of 389 for search '(((( data existing algorithm ) OR ( data processing algorithm ))) OR ( elements data algorithm ))', query time: 0.13s Refine Results
  1. 181

    Building power consumption datasets: Survey, taxonomy and future directions by Yassine Himeur (14158821)

    Published 2020
    “…The latter will be very useful for testing and training anomaly detection algorithms, and hence reducing wasted energy. Moving forward, a set of recommendations is derived to improve datasets collection, such as the adoption of multi-modal data collection, smart Internet of things data collection, low-cost hardware platforms and privacy and security mechanisms. …”
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    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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    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. …”
  9. 189

    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. …”
  10. 190

    Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las... by Masurkar, Faeez

    Published 2020
    “…In view of this, an innovative signal processing technique called a self-adaptive-smart algorithm (SASA) was designed and developed. …”
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  11. 191

    Information reconciliation through agent controlled graph model. (c2018) by Saba, Rita

    Published 2018
    “…Even though prevention techniques exist, they’re not enough to fully secure the data from malicious activities. …”
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    masterThesis
  12. 192

    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. …”
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    Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

    Published 2020
    “…A special consideration was given to data pre-processing and dimensionality reduction such Chi Squared (CS) and Recursive Feature Elimination (RFE) to improve progressively the proposed models performance. …”
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  15. 195

    Investigation of Forming a Framework to shortlist contractors in the tendering phase by DABASH, MOHANNAD SALAH

    Published 2022
    “…After obtaining the weights of the decision factors, a model using Machine Learning algorithm on Google Colab was written using the Python language. …”
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  16. 196

    Nested ensemble selection: An effective hybrid feature selection method by Kamalov, Firuz

    Published 2023
    “…The NES algorithm achieves perfect precision on the synthetic data and near optimal accuracy on the real-life data. …”
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    article
  17. 197

    Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring by Sakib Mahmud (15302404)

    Published 2024
    “…<h3>Background and Motivations</h3><p dir="ltr">Physiological signals, such as the Photoplethysmogram (PPG) collected through wearable devices, consistently encounter significant motion artifacts. Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …”
  18. 198

    Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

    Published 2022
    “…Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. …”
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