A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

Optimizing Document Classification: Unleashing the Power of Genetic Algorithms by Ghulam Mustafa (458105)

“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”

Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

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CNN and HEVC Video Coding Features for Static Video Summarization by Issa, Obada

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Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

“…This approach uses other students’ grades to make a prediction. This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
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Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

“…Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

“…The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”

Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries by Assayed, Suha Khalil

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PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT by Khalil Assayed, Suha

“…In this paper, we propose a chatbot for detecting the students feeling by using machine-learning algorithms. …”
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PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT by Khalil Assayed, Suha

“…In this paper, we propose a chatbot for detecting the students feeling by using machine-learning algorithms. …”
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Classifying Maqams of Qur'anic Recitations Using Deep Learning by Shahriar, Sakib

“…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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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid (22047578)

Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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Predict Student Success and Performance factors by analyzing educational data using data mining techniques by ATIF, MUHAMMAD

“…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …”
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Competitive learning/reflected residual vector quantization for coding angiogram images by Mourn, W.A.H.

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Automatic Video Summarization Using HEVC and CNN Features by Issa, Obada

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Education Data Mining to Predict Student Exam Grades in Vocational Institutes by Saleh, Ashjan Ahmad

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Assessment of network module identification across complex diseases by Sarvenaz Choobdar (18602821)

“…Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. …”