Network Threat Detection Using Machine/Deep Learning in SDN-Based Platforms: A Comprehensive Analysis of State-of-the-Art Solutions, Discussion, Challenges, and Future Research Dir... by Naveed Ahmed (2433958)

“…Much work has been done on NIDS but there are still improvements needed in reducing false alarms and increasing threat detection accuracy. Recently advanced approaches such as deep learning (DL) and machine learning (ML) have been implemented in SDN-based NIDS to overcome the security issues within a network. …”

Evaluation of Pre-Trained CNN Models for Geographic Fake Image Detection by Hadid, Abdenour

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Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review by Asma Alamgir (18288895)

Exploiting the Spatio-Temporal Patterns in IoT Data to Establish a Dynamic Ensemble of Distributed Learners by Mehdi Mohammadi (5024105)

“…This increase is 82% less than the 11.3 increase seen in the baseline model. …”

Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction by Yassine Himeur (14158821)

“…The latter can not only reduce feature dimensionality, but it can also effectively decrease the intra-class distances and increase the extra-class distances of appliance features; and (iii) a powerful decision bagging tree classifier is implemented to accurately classify electrical devices using the reduced features. …”

Ensemble Stacking Model for Sentiment Analysis of Emirati and Arabic Dialects by A. Al Shamsi, Arwa

“…Then, an ensemble stacking model was introduced to combine the best-performing deep learning models used in this study. The ensemble stacking deep learning model consisted of deep learning models with a meta learner layer of classifiers. …”
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Machine Learning-Based Management of Electric Vehicles Charging: Towards Highly-Dispersed Fast Chargers by Mostafa Shibl (18810412)

“…ML models used in this paper are (1) Decision Tree (DT), (2) Random Forest (RF), (3) Support Vector Machine (SVM), (4) Naïve Bayes (NB), (5) K-Nearest Neighbors (KNN), (6) Deep Neural Networks (DNN), and (7) Long Short-Term Memory (LSTM). …”

Visual Sentiment Analysis from Disaster Images in Social Media by Syed Zohaib Hassan (18387129)

“…<div><p>The increasing popularity of social networks and users’ tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content have opened new opportunities and challenges in sentiment analysis. …”

Blood Glucose Regulation Modelling and Intelligent Control by Nasar, Nabeel

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Electric Grid Resilience Enhancement During Natural Disasters: An Optimization-Based UAV Inspection and Dynamic Crew Dispatch Model by Serag, Yousef

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Artificial Intelligence for Detecting and Quantifying Fatty Liver in Ultrasound Images: A Systematic Review by Fahad Muflih Alshagathrh (18427950)

Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP by Abdelhafez, Nada

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Robust Prediction of Wildfire Spread in Australia by Michael Palk (17947841)

Theft Detection Unit For Photo-Votaic Generation in Smart Grid Networks by Almadani, Nouf Ahmad

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In-Between Projection Interpolation in Cone-Beam CT Imaging using Convolutional Neural Networks by Dweek, Samaa

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Electrochemical Studies on the Corrosion Behavior of Common Metals in Eutectic Ionic Liquids by Alhasan, Rami

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Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu by Ayesha Atif (22155133)

The use of multi-task learning in cybersecurity applications: a systematic literature review by Shimaa Ibrahim (22155739)

Decoding silent speech: a machine learning perspective on data, methods, and frameworks by Adiba Tabassum Chowdhury (19444792)

“…Examining state-of-the-art SSR frameworks, the paper covers important topics such signal processing, feature extraction, ML techniques for decoding and optimizing and assessing the performance of SSR models. We emphasize how deep learning (DL) and ML models have evolved to increase SSR resilience and accuracy. …”

Intelligent scaling for 6G IoE services for resource provisioning by Abdullah Alharbi (4173502)

“…IScaler is considered to be made for MEC in Deep Reinforcement Learning (DRL). The paper has considered several requirements for making service placement decisions. …”