Showing 81 - 99 results of 99 for search 'differences novel algorithm', query time: 0.06s Refine Results
  1. 81

    Copy number variations in the genome of the Qatari population by Khalid A. Fakhro (3158862)

    Published 2015
    “…Up to 40 % of all CNVs affected genes, including novel CNVs affecting Mendelian disease genes, segregating at different frequencies in the 3 major Qatari subpopulations, including those with Bedouin, Persian/South Asian, and African ancestry. …”
  2. 82

    A genetic-based fuzzy logic power system stabilizer formultimachine power systems by Abido, M.A.

    Published 1997
    “…This paper presents a novel approach to combine genetic algorithms (GA) with fuzzy logic systems to design a genetic-based fuzzy logic power system stabilizer (GFLPSS) for multimachine power systems. …”
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    article
  3. 83

    Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures by JUMA, MAZEN GHAZI

    Published 2021
    “…The technology stack of the proposed solution was also implemented with four algorithms and eight protocols. The evaluation results of the proposed solution were compared to the results of standard solutions under different cyberattack scenarios using quantitative research methods involving computing simulations, emulation experiments, and analytical modeling. …”
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  4. 84

    Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

    Published 2023
    “…Therefore, in this study, we conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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  5. 85
  6. 86

    Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

    Published 2023
    “…Therefore, in this study, we conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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  7. 87

    Common weaving approach in mainstream languages for software security hardening by Alhadidi, Dima

    Published 2013
    “…We handle the correctness and the completeness of GIMPLE weaving in two different ways. In the first approach, we prove them according to the rules and algorithms provided in this paper. …”
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    article
  8. 88

    Decision-level fusion for single-view gait recognition with various carrying and clothing conditions by Al-Tayyan, Amer

    Published 2017
    “…Gait samples are fed into the MPCA and MPCALDA algorithms using a novel tensor-based form of the gait images. …”
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    article
  9. 89

    Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

    Published 2016
    “…In this thesis, we propose a novel heuristic based on Artificial Bee Colony (ABC) to optimize rule-based software quality prediction models. …”
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    masterThesis
  10. 90

    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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    article
  11. 91

    Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

    Published 2023
    “…<p>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. …”
  12. 92
  13. 93

    Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

    Published 2024
    “…In this research, a novel dataset of fake job postings is proposed, formed by the combination of job postings from three different sources. …”
  14. 94
  15. 95

    From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

    Published 2023
    “…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”
  16. 96

    DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

    Published 2025
    “…These algorithms were employed to distinguish and categorize bacterial endotoxins, following appropriate spectral pre-processing, which involved novel filtering techniques and advanced feature extraction methods. …”
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    article
  17. 97

    Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning by MEZAHEM, FATEMA HAMAD

    Published 2022
    “…In this paper we are focusing on DA Arabic since it is commonly used on social media The main dataset was the Arabic Sentiment Analysis Dataset (ASAD) which presented a novel large Twitter-based benchmark (Alharbi et al., 2020). …”
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  18. 98

    MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network by Sakib Mahmud (15302404)

    Published 2022
    “…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …”
  19. 99

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

    Published 2023
    “…In this study, I conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM, CNN-BILSTM-LSTM, and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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