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). …”

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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Deep learning-based modeling of land use/land cover changes impact on land surface temperature in Greater Amman Municipality, Jordan (1980–2030) by Khaled F. Alkaraki (22051967)

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. 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. …”

Food purchase and eating behavior during the COVID-19 pandemic: A cross-sectional survey of Russian adults by Tarek Ben Hassen (15742605)

“…Indeed, the survey results suggested (i) a change in the modality of acquiring food, consumers reduced the number of shopping trips and buying more on each trip to minimize store visits; (ii) a surge of stockpiling of non-perishable food items; (iii) a shift toward healthier diets; (iv) an increase in culinary capabilities; (v) a decrease of food waste. …”

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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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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