Showing 1 - 16 results of 16 for search '(((( complement mean algorithm ) OR ( element mesh algorithm ))) OR ( neural coding algorithm ))', query time: 0.15s Refine Results
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    A survey and comparison of wormhole routing techniques in a meshnetworks by Al-Tawil, K.M.

    Published 1997
    “…These multiprocessing systems consist of processing elements or nodes which are connected together by interconnection networks in various topologies. …”
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    Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review by Loay A. Salman (14150322)

    Published 2023
    “…</p><h3>Results</h3><p dir="ltr">A total of four observational studies comprised of at least 34,547 patients were included in this review. A mean MINORS score of 11 out of 16 was assigned to the review. …”
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    Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

    Published 2024
    “…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”
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    A Full-System Approach of the Elastohydrodynamic Line/Point Contact Problem by Habchi, Wassim

    Published 2008
    “…The use of the finite element method allows the use of variable unstructured meshing and different types of elements within the same model which leads to a reduced size of the problem. …”
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    Developing an online hate classifier for multiple social media platforms by Joni Salminen (7434770)

    Published 2020
    “…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”
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    Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

    Published 2019
    “…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …”
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