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Showing 41 - 60 results of 144 for search '(((( elements network algorithm ) OR ( recent data algorithm ))) OR ( query processing algorithm ))', query time: 0.12s Refine Results
  1. 41

    Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by Raad, M.W.

    Published 2006
    “…A fast waveform sampling facility has been recently developed and integrated into the VAX-based data acquisition system at the Center for Applied Physical Sciences (CAPS). …”
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  2. 42

    NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY by JINESH, PADIKKAPPARAMBIL

    Published 2022
    “…Various sensors and equipment are installed in the AAL context to collect a wide variety of data. Furthermore, AAL could be the motivating technique for the most recent care models by working as an adjunct. …”
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    Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization by Abrar, Shafayat

    Published 2002
    “…Stop-and-go decision-directed (S&G-DD) equalization is the most primitive blind equalization (BE) method for the cancelling of intersymbol-interference in data communication systems. Recently, this scheme has been applied to complex-valued multilayer feedforward neural network, giving robust results with a lower mean-square error at the expense of slow convergence. …”
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    The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

    Published 2023
    “…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …”
  9. 49

    PILE-UP FREE PARAMETER ESTIMATION AND DIGITAL ONLINE PEAK LOCALIZATION ALGORITHMS FOR GAMMA RAY SPECTROSCOPY by Noras, J.M.

    Published 2020
    “…A fast waveform sampling facility has been recently developed and integrated into the VAX-based data acquisition system at the Energy Research Laboratory (ERL). …”
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  10. 50

    Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights by Malekloo, Arman

    Published 2021
    “…In the age of the smart city, Internet of Things (IoT), and big data analytics, the complex nature of data-driven civil infrastructures monitoring frameworks has not been fully matured. …”
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    FarmTech: Regulating the use of digital technologies in the agricultural sector by Imad Antoine Ibrahim (14158998)

    Published 2023
    “…<p dir="ltr">Farming relies on the accurate collection and processing of data. Algorithms utilizing artificial intelligence can predict patterns and spot problems, helping farmers make more informed decisions. …”
  13. 53

    Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan by AL RAWASHDEH, HANEEN MOHAMMAD

    Published 2017
    “…Different classification algorithms were applied to the dataset using the Rapidminer tool. …”
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    Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

    Published 2023
    “…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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    Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

    Published 2023
    “…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”
  18. 58

    Simultaneous identification of robust synergistic subnetwork markers for effective cancer prognosis by Navadon Khunlertgit (3480926)

    Published 2014
    “…<p>Accurate prediction of cancer prognosis based on gene expression data is generally difficult, and identifying robust prognostic markers for cancer remains a challenging problem. …”
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