Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic by Hassan Farhat (9000509)

Creating and detecting fake reviews of online products by Joni Salminen (7434770)

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

“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”

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

Get full text

Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data by Rajesh Kumar Dhanaraj (19646269)

Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)

A Survey of Machine Learning Innovations in Ambulance Services: Allocation, Routing, and Demand Estimation by Reem Tluli (22282702)

“…ML algorithms could play a pivotal role in dynamically allocating resources, devising efficient routes, and predicting demand patterns. …”

Application of Data Mining to Predict and Diagnose Diabetic Retinopathy by Haniyeh, Maryam

Get full text

VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems by Hisham A. Kholidy (18891802)

Generative AI revolution in cybersecurity: a comprehensive review of threat intelligence and operations by Mueen Uddin (4903510)

Mining airline data for CRM strategies. (c2006) by Maalouf, Lena

Get full text
Get full text

IntruSafe: a FCNN-LSTM hybrid IoMT intrusion detection system for both string and 2D-spatial data using sandwich architecture by Moutaz Alazab (17730060)

Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review by Zainab Jan (17306614)

“…Deep learning models were the most prominent branch of AI used for pancreatic cancer diagnosis in the studies, and the convolutional neural network was the most used algorithm (18/30, 60%). …”

Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…Machine Learning (ML) saw a great increase in general and domain specific research. …”
Get full text

Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas by Marwan Dhuheir (19170898)

“…In this context, we formulate the problem as a non-linear programming (NLP) optimization problem aimed at maximizing the total EH IoT devices and determining the optimal trajectory paths for UAVs while adhering to the constraints related to the maximum time duration, the UAVs’ maximum energy consumption, and the minimum data rate to achieve a reliable transmission. Due to the complexity of the problem, the combinatorial nature of the formulated problem, and the difficulty of obtaining the optimal solution using conventional optimization problems, we propose a lightweight meta-RL solution capable of solving the problem by learning the system dynamics. …”

DoFP-ML: A Machine Learning Approach to Food Quality Monitoring Using a DoFP Polarization Image Sensor by Maen Takruri (10873368)

Adaptive cooperative control of nonlinear multi-agent systems with uncertain time-varying control directions and dead-zone nonlinearity by Maryam Shahriari-kahkeshi (17269051)

Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE by Mathew, Elezabeth

“…The industry is yet to fully benefit from these big data by applying Machine Learning (ML) and Artificial Intelligence (AI). …”
Get full text

Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

“…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
Get full text
Get full text
Get full text

Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

“…To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
Get full text
Get full text
Get full text