Self-DSNet: A Novel Self-ONNs Based Deep Learning Framework for Multimodal Driving Distraction Detection by Mamun Or Rashid (21976373)

Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet by Vineet Dhanawat (22361395)

“…This paper proposes an efficient deep BiLSTMNet model to solve and mitigate these problems. …”

Two-Stage Deep Learning Solution for Continuous Arabic Sign Language Recognition Using Word Count Prediction and Motion Images by Shanableh, Tamer

“…CNN transfer learning is used to convert each of these motion images into a feature vector which is used for either model generation or sign language recognition. As such, two deep learning models are generated; one for predicting the number of words per sentence and the other for recognizing the meaning of the sign language sentences. …”
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AgroAId: A Mobile App System for Visual Classification of Plant Species and Diseases Using Deep Learning and TensorFlow Lite by Reda, Mariam

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Acute kidney injury requiring dialysis after endovascular intervention for acute deep venous thrombosis: A case report and literature review by Najlaa Essa A. H. Al‐Mannai (21841775)

“…<h3>Key Clinical Message</h3><p dir="ltr">Percutaneous precutaneous mechanical thrombectomy has been used for clot dissolution and removal in selected cases of iliofemoral deep vein thrombosis. Intravascular Hemolysis and hemoglobinuria caused by pharmachomechanical chather directed thrombolysis (PCDT) devices like the Angiojet is associated with an increased risk of acute kidney injury (AKI). …”

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. …”

Combining Saliency with Prediction for Endoscopic Diagnosis by Rezk, Mahmoud

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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

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The Impact of Arts Integration on the Learning and Social Abilities of Students with Disabilities: An Approach to an Inclusive Classroom by Shouma, Madiha

“…It is flexible and can be altered or modified to fit an individual student’s needs. This study aims to determine how AI can contribute to the academic and social development of students with disabilities in the classroom. …”
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Predicting COVID-19 in the UAE Using Machine Learning by Sankalpa, Donthi

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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. …”

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

“…Consequently, there is an urgent need to develop detection methods capable of distinguishing between real and fake satellite images. …”
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Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review by Asma Alamgir (18288895)

“…Artificial intelligence (AI) technologies and big data have been increasingly used to enhance the ability to predict and prepare for the patients at risk.…”

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. …”

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). …”

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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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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Challenges and practices identification in complex outsourcing relationships: A systematic literature review by Ghulam Murtaza Khan (12024573)

“…Furthermore, when compared to other types of outsourcing, complex outsourcing is extremely difficult because it necessitates a variety of control and coordination mechanisms for project management, which proportionally increases the risk of project failure. In order to overcome the failure of projects in complex outsourcing relationships, there is a need of robust systematic research to identify the key challenges and practices in this area. …”