يعرض 161 - 169 نتائج من 169 نتيجة بحث عن '(((( element based algorithm ) OR ( experiments showed algorithm ))) OR ( level coding algorithm ))', وقت الاستعلام: 0.08s تنقيح النتائج
  1. 161

    Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort حسب Sergio Márquez-Sánchez (19437985)

    منشور في 2023
    "…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …"
  2. 162

    Approximate XML structure validation technical report حسب Tekli, Joe

    منشور في 2014
    "…Our approach exploits the concept of tree edit distance, introducing a novel edit distance recurrence and dedicated algorithms to effectively compare XML documents and grammar structures, modeled as ordered labeled trees. …"
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  3. 163

    Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling حسب Armin, Amindari

    منشور في 2017
    "…However, implementation of this approach is difficult using custom built codes and algorithms. In this paper, we present an FSI modeling methodology for aortic valve hemodynamics using a commercial modeling software, ANSYS. …"
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  4. 164

    Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling حسب Amindari, Armin

    منشور في 2017
    "…However, implementation of this approach is difficult using custom built codes and algorithms. In this paper, we present an FSI modeling methodology for aortic valve hemodynamics using a commercial modeling software, ANSYS. …"
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  5. 165

    Enhancing e-learning through AI: advanced techniques for optimizing student performance حسب Rund Mahafdah (21399854)

    منشور في 2024
    "…This research highlights the ability of AI to develop adaptable, effective, and successful e-learning environments, promoting enhanced academic achievement and customized learning experiences. The findings demonstrate that CNN outperformed other deep learning and machine learning algorithms in terms of accuracy during the prediction phase, showcasing the advanced capabilities of AI in educational contexts. …"
  6. 166

    Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators حسب Abu Zitar, Raed

    منشور في 2021
    "…Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …"
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  7. 167

    Creating and detecting fake reviews of online products حسب Joni Salminen (7434770)

    منشور في 2022
    "…Using the better model, GPT-2, we create a dataset for a classification task of fake review detection. We show that a machine classifier can accomplish this goal near-perfectly, whereas human raters exhibit significantly lower accuracy and agreement than the tested algorithms. …"
  8. 168

    Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis حسب Hassan, Ali

    منشور في 2023
    "…Con-Detect can be deployed with any classifier without having to retrain it. We experiment with multiple attackers—Text-bugger, Text-fooler, PWWS—on several architectures—MLP, CNN, LSTM, Hybrid CNN-RNN, BERT—trained for different classification tasks—IMDB sentiment classification, fake-news classification, AG news topic classification—under different threat models—Con-Detect-blind attacks, Con-Detect-aware attacks, and Con-Detect-adaptive attacks—and show that Con-Detect can reduce the attack success rate (ASR) of different attacks from 100% to as low as 0% for the best cases and ≈70% for the worst case. …"
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  9. 169

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

    منشور في 2023
    "…Con-Detect can be deployed with any classifier without having to retrain it. We experiment with multiple attackers—Text-bugger, Text-fooler, PWWS—on several architectures—MLP, CNN, LSTM, Hybrid CNN-RNN, BERT—trained for different classification tasks—IMDB sentiment classification, fake-news classification, AG news topic classification—under different threat models—Con-Detect-blind attacks, Con-Detect-aware attacks, and Con-Detect-adaptive attacks—and show that Con-Detect can reduce the attack success rate (ASR) of different attacks from 100% to as low as 0% for the best cases and ≈70% for the worst case. …"