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  1. 1

    Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

    Published 2025
    “…The application of machine learning (ML) and deep learning (DL) models in the field of toxicity has gained burgeoning interest. …”
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    On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise by Saab, Samer S.

    Published 2005
    “…Higher-Order Iterative Learning Control (HO-ILC) algorithms use past system control information from more than one past iterative cycle. …”
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  3. 3

    Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic by AL MANSOORI, MOUZA

    Published 2021
    “…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. …”
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    Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization by Abu Zitar, Raed

    Published 2022
    “…The IGOA was compared with several other proposed meta-heuristic algorithms. Moreover, the Wilcoxon signed-rank test further assessed the experimental results to conduct more systematic data analyses. …”
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    Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

    Published 2022
    “…In addition, the framework outperforms conventional detection algorithms in words of detection rate, the rate of the false positive, and calculation time, respectively.…”
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    Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

    Published 2022
    “…For this reason, this paper presents a systematic survey of literature for solving multiclass feature selection problems utilizing metaheuristic algorithms that can assist classifiers selects optima or near optima features faster and more accurately. …”
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    Classifying Maqams of Qur'anic Recitations Using Deep Learning by Shahriar, Sakib

    Published 2021
    “…Technological advancement can be utilized for automatic classification of these melodies which can then be used by students for self-learning. Using state-of-the-art deep learning algorithms, this research focuses on the classification of the eight popular maqamat (plural of maqam). …”
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    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”
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    Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System by Abu Zitar, Raed

    Published 2021
    “…It is believed that the evaluation of the outcomes of the course, based on grades, is necessary to improve the teaching and learning process. Our research processes and workflows supported by AI utilize machine learning technology in order to interpret big data, analyze broad data sets and recognize associations with more reliably. …”
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    Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT by Arumugam K (18456690)

    Published 2021
    “…This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. …”
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    Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques by Abu Zitar, Raed

    Published 2022
    “…This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. …”
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    Predicting Plasma Vitamin C Using Machine Learning by Daniel Kirk (17302798)

    Published 2022
    “…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”
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    Android Malware Detection Using Machine Learning by Al Ali, Shaikha

    Published 2024
    “…This paper presents a machine learning approach for Android malware detection. In this work, several machine learning algorithms were utilized, namely k-Nearest neighbor (KNN), Decision Trees (DT), Naive Bayes (NB), Support Vector Machine (SVM) and other ensemble classifiers including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM) and CatBoost. …”
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    Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

    Published 2019
    “…Our study also reveals that ensemble machine learning algorithms are more reliable and outperform standard algorithms.…”
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    An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

    Published 2011
    “…It can also be easily extended to work with software quality predictive problems involving more than two classification labels. Results Results show that our approach out-performs the machine learning algorithm C4.5 as well as random guessing. …”
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