FPGA-based Parallel Hardware Architecture for Real-time Object Classification by Qasaimeh, Murad Mohammad

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Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices by Neder Karmous (19743430)

“…Based on the performance metrics, such as confusion matrix, training time, prediction time, accuracy, and Area Under the Receiver Operating Characteristic curve (AUC-ROC), it was established that SDN-ML-IoT, when applied to RF, outperforms other ML algorithms, as well as similar approaches related to our work. …”

Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence by Al Rayhi, Nasser

“…Furthermore, more advanced algorithms can be used such as Support Vector machine (SVM) and XGBoost.…”
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Hybrid deep learning based threat intelligence framework for Industrial IoT systems by Jahanzaib Malik (23718816)

Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

“…Evolutionary algorithms have been effective in solving many search and optimization problems. …”
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Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches by Mohammad, Areej Osama

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

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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

“…<p dir="ltr">Much attention has been paid to the recognition of human emotions with the help of electroencephalogram (EEG) signals based on machine learning technology. Recognizing emotions is a challenging task due to the non-linear property of the EEG signal. …”

A parallel optimization algorithm for the maximum clique problem. (c2008) by Rizk, Mohamad A.

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Advancing Coherent Power Grid Partitioning: A Review Embracing Machine and Deep Learning by Mohamed Massaoudi (16888710)

“…Subsequently, state-of-the-art research that envisions the use of clustering-based machine learning and deep learning-based solutions for PGP is presented. …”

Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems by Mahmood, Lubna Syeda

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Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... by Tarik Elhadd (5480393)

“…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…”

Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis by Sami Elzeiny (16891521)

Tensile Test Optimization Using the Design of Experiment and Soft Computing by Mehdi Moayyedian (14880358)

“…This study employs a hybrid soft computing approach, integrating an adaptive network-based fuzzy inference system (ANFIS), genetic algorithm (GA) optimization, and design of experiments (DOE). …”

Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…The research work carried out, in relation to attack detection ensemble learning, mainly aims to increase the performance of machine learning algorithms by combining their results. …”
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Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method by Mohamed Massaoudi (16888710)

“…The proposed forecasting tool incorporates a base model and meta-model layers. The first-layer base learner combines extreme learning machines, extremely randomized trees, k-nearest neighbor, and mondrian forest models. …”