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  1. 121
  2. 122

    Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
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  3. 123

    Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
    Get full text
    article
  4. 124

    Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds.Examples are used for demonstration.…”
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    article
  5. 125

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

    Published 2024
    “…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”
  6. 126

    Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

    Published 2024
    “…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …”
  7. 127
  8. 128

    A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method by Shahid Rahman (16904613)

    Published 2022
    “…<p>Communication has become a lot easier in this era of technology, development of high-speed computer networks, and the inexpensive uses of Internet. Therefore, data transmission has become vulnerable to and unsafe from different external attacks. …”
  9. 129

    Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

    Published 2024
    “…<p dir="ltr">Fault detection and diagnosis (FDD) systems play a crucial role in maintaining the adequate execution of the monitored process. One of the widely used data-driven FDD methods is the Principal Component Analysis (PCA). …”
  10. 130

    Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence by Atiq Ur Rehman (8843024)

    Published 2020
    “…Keeping in view the need of an optimization algorithm with fast convergence speed, suitable for high dimensional data space, this article proposes a novel concept of Multi-Cluster Jumping PSO. …”
  11. 131

    Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

    Published 2023
    “…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”
  12. 132

    Data Redundancy Management in Connected Environments by Mansour, Elio

    Published 2020
    “…., building) equipped with sensors that produce and exchange raw data. Although the sensed data is considered to contain useful and valuable information, yet it might include various inconsistencies such as data redundancies, anomalies, and missing values. …”
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  13. 133

    Unsupervised outlier detection in multidimensional data by Atiq ur Rehman (14153391)

    Published 2022
    “…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …”
  14. 134

    Android Malware Detection Using Machine Learning by Al Ali, Shaikha

    Published 2024
    “…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …”
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    article
  15. 135

    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. …”
  16. 136

    Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by Zakaria Tolba (16904718)

    Published 2022
    “…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …”
  17. 137

    Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

    Published 2023
    “…This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …”
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    Graph Contraction for Mapping Data on Parallel Computers by Mansour, N.

    Published 1994
    “…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
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