Showing 141 - 159 results of 159 for search '(( element mesh algorithm ) OR ((( data code algorithm ) OR ( e learning algorithm ))))', query time: 0.10s Refine Results
  1. 141
  2. 142

    Systematic reviews in sentiment analysis: a tertiary study by Alexander Ligthart (14150871)

    Published 2022
    “…According to this analysis, LSTM and CNN algorithms are the most used deep learning algorithms for sentiment analysis.…”
  3. 143

    Real-Time Social Robot’s Responses to Undesired Interactions Between Children and their Surroundings by Ahmad Yaser Alhaddad (7017434)

    Published 2022
    “…Additionally, we evaluate the performance of the best developed model with children. Machine learning algorithms experiments showed that XGBoost achieved the best performance across all metrics (e.g., accuracy of 90%) and provided fast predictions (i.e., 0.004 s) for the test samples. …”
  4. 144

    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). …”
  5. 145

    FoGMatch by Arisdakessian, Sarhad

    Published 2019
    “…Simulation results reveal that our solution outperforms the two common scheduling algorithms (i.e., Min-Min and Max-Min) in terms of IoT services execution makespan, fog nodes resource utilization efficiency and execution time.…”
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    masterThesis
  6. 146

    ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks by Muhammad Asif Khan (7367468)

    Published 2022
    “…Recently, cognitive network architectures using sophisticated learning techniques are increasingly being applied to such problems. …”
  7. 147
  8. 148

    Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition by Abboud, Ralph

    Published 2019
    “…In this paper, we introduce a new algorithmic framework for autonomous music sentiment-based expression and composition, titled MUSEC, that perceives an extensible set of six primary human emotions (e.g., anger, fear, joy, love, sadness, and surprise) expressed by a MIDI musical file and then composes (creates) new polyphonic (pseudo) thematic, and diversified musical pieces that express these emotions. …”
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    article
  9. 149

    From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors by Michael R. Giordano (9976173)

    Published 2021
    “…The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. …”
  10. 150

    User-centric strategies for resource management in heterogeneous wireless networks with QoS considerations by Abbas, Nadine Fawaz

    Published 2017
    “…We demonstrate their e↵ectiveness by presenting performance results and analysis for a wide range of network scenarios.…”
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    masterThesis
  11. 151
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  13. 153

    Current trends and future orientation in diagnosing lung pathologies: A systematic survey by Noorizadeh, Mohammad

    Published 2025
    “…The CV processing method involves the application of advanced imaging techniques and machine learning algorithms to scrutinize and diagnose lung pathologies and ventilator-associated pneumonia (VAP). …”
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    article
  14. 154

    PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits by Hind Almerekhi (7434776)

    Published 2022
    “…Therefore, in this study, we find the turning points (i.e., toxicity triggers) making conversations toxic. …”
  15. 155

    Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review by Hiba Alzoubi (18001609)

    Published 2025
    “…</p><h3>Conclusion</h3><p dir="ltr">AI algorithms show promise in detecting and subtyping medulloblastomas, but the findings are limited by overreliance on one dataset, small sample sizes, limited study numbers, and lack of meta-analysis Future research should develop larger, more diverse datasets and explore advanced approaches like deep learning and foundation models. …”
  16. 156

    Dynamic single node failure recovery in distributed storage systems by Itani, M.

    Published 2017
    “…With the emergence of many erasure coding techniques that help provide reliability in practical distributed storage systems, we use fractional repetition coding on the given data and optimize the allocation of data blocks on system nodes in a way that minimizes the system repair cost. …”
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    article
  17. 157

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

    Published 2000
    “…In addition, the lifting scheme offers: 1) a dramatic reduction of the required auxiliary memory, 2) an efficient combination with parallel rendering algorithms to perform arbitrary surface and volume rendering for interactive visualization, and 3) an easy integration in the parallel I/O seismic data loading routines. …”
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    article
  18. 158

    CubeSat Communication Subsystems: A Review of On-Board Transceiver Architectures, Protocols, and Performance by Amr Zeedan (17983750)

    Published 2023
    “…Nevertheless, several directions for improvements are proposed such as the use of improved channel coding algorithms, Field Programmable Gate Arrays (FPGAs), beamforming, advanced antennas, deployable solar panels, and transition to higher frequency bands. …”
  19. 159

    Comprehensive whole genome sequence analyses yields novel genetic and structural insights for Intellectual Disability by Farah R. Zahir (18892108)

    Published 2017
    “…The <i>de novo</i> assembly resulted in unmasking hidden genome instability that was missed by standard re-alignment based algorithms. We also interrogated regulatory sequence variation for known and hypothesized ID genes and present useful strategies for WGS data analyses for non-coding variation.…”