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  1. 221
    Regression testing web services-based applications

    Regression testing web services-based applications by Tarhini, Abbas

    Published 2006
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  2. 222
    Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework

    Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework by Tayyabah Hasan (18427887)

    Published 2022
    “…Firstly, the DL agent prioritizes caching contents via self organizing maps (SOMs) algorithm, and secondly, the prioritized contents are stored in QMM using a Two-Level Spin Quantum Phenomenon (TLSQP). …”
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  3. 223
    Reliability and fault tolerance based topological optimization of computer networks - part II: iterative techniques

    Reliability and fault tolerance based topological optimization of computer networks - part II: iterative techniques by Abd-El-Barr, Mostafa

    Published 2003
    “…We consider fault-tolerance to be an important network design aspect. We consider the use of three iterative techniques, namely tabu search, simulated annealing, and genetic algorithms, in solving the multiobjective topological optimization network design problem. …”
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  4. 224
    An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM

    An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM by Al-Naffouri, T.Y.

    Published 0000
    “…The algorithm makes a collective use of the data and channel constraints inherent in the communication problem. …”
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  5. 225
    A FeedForward–Convolutional Neural Network to Detect Low-Rate DoS in IoT

    A FeedForward–Convolutional Neural Network to Detect Low-Rate DoS in IoT by Harun Surej Ilango (17545728)

    Published 2022
    “…The Canadian Institute of Cybersecurity Denial of Service 2017 (CIC DoS 2017) dataset is used for the study. An iterative wrapper-based feature selection using Support Vector Machine (SVM) is used to derive the significant features required for detection. …”
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  6. 226
    Energy removal in dynamical systems through an optimal sequence of constraint application

    Energy removal in dynamical systems through an optimal sequence of constraint application by Issa, Jimmy

    Published 2017
    “…The optimization process is illustrated by means of simple mass-spring and membrane systems and the corresponding problems are solved using a genetic algorithm.…”
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  7. 227
    Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review

    Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review by Arfan Ahmed (17541309)

    Published 2022
    “…Wearable devices (WDs) make use of sensors historically reserved for hospital settings. …”
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  8. 228
    Adaptive false discovery rate for wavelet denoising of pavement continuous deflection measurements

    Adaptive false discovery rate for wavelet denoising of pavement continuous deflection measurements by Katicha, Samer W.

    Published 2016
    “…The algorithm minimizes the classification error of features in the wavelet transform domain by adaptively selecting the level at which to control the false discovery rate. …”
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  9. 229
    Reliability and fault tolerance based topological optimization of computer networks - part I: enumerative techniques

    Reliability and fault tolerance based topological optimization of computer networks - part I: enumerative techniques by Abd-El-Barr, Mostafa

    Published 2003
    “…Experimental results obtained from a set of randomly generated networks using the proposed algorithms are presented and compared to those obtained using existing techniques. …”
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  10. 230
    Swarm intelligence-based hyper-heuristic for the vehicle routing problem with prioritized customers

    Swarm intelligence-based hyper-heuristic for the vehicle routing problem with prioritized customers by Tarhini, Abbas

    Published 2020
    “…The results indicate that the solution selected by the Cuckoo Search-based hyper-heuristic outperformed the modified Clarke Wright algorithm while taking into consideration the customers’ priority and demands and the vehicle capacity.…”
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  11. 231
    Design and development of an embedded controller for roboticmanipulator

    Design and development of an embedded controller for roboticmanipulator by Bakhashwain, J.M.

    Published 1998
    “…MPA is capable of determining a simplified control law by selecting the most dominant terms from a library of nonlinear functions associated with the robot's equations of motion. …”
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  12. 232
    A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security

    A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

    Published 2023
    “…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”
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  13. 233
    Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018)

    Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018) by Tay, Bilal M.

    Published 2018
    “…In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. Our objective in this work is to propose machine learning models that can benefit from the historical data available in banking environment in order to improve and automate their business processes. …”
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  14. 234
    Machine Learning Model for a Sustainable Drilling Process

    Machine Learning Model for a Sustainable Drilling Process by Alsaidi, Ola

    Published 2023
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  15. 235
    Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying

    Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying by Tekli, Joe

    Published 2023
    “…We use a semantic-aware inverted index to allow semantic-aware search, result selection, and result ranking functionality. …”
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  16. 236
    Modelling of pollutant transport in compound open channels

    Modelling of pollutant transport in compound open channels by Chatila, Jean Georges

    Published 1998
    “…Longitudinal and transverse mixing coefficients were calculated using the method of moments and by estimation using empirical relationships. …”
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  17. 237
    Exploring new horizons in neuroscience disease detection through innovative visual signal analysis

    Exploring new horizons in neuroscience disease detection through innovative visual signal analysis by Nisreen Said Amer (17984077)

    Published 2024
    “…Our study demonstrates the effectiveness of the FBFT method, achieving impressive accuracies across multiple brain disorders using CNN-based classification. Specifically, we achieve accuracies of 99.82% for epilepsy, 95.91% for Alzheimer’s disease (AD), 85.1% for murmur, and 100% for mental stress using CNN-based classification. …”
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  18. 238
    Design of a TE-pass reflection mode optical polarizer

    Design of a TE-pass reflection mode optical polarizer by Khan, M.A.

    Published 2003
    “…A doubling and cascading algorithm is also utilized to efficiently account for the large number of grating periods forming the corrugated section of the filter.…”
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  19. 239
    A comparative study of regression testing methods. (c1996)

    A comparative study of regression testing methods. (c1996) by Baradhi, Ghinwa S.

    Published 1996
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  20. 240
    A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass

    A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

    Published 2025
    “…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…”
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