Deep learning-based cross-device standardization of surface-enhanced Raman spectroscopy for enhanced bacterial recognition by Sakib Mahmud (22652357)

“…Quantitative results show that SERS-D2DNet reduced mean absolute error to 0.01 and increased R² to over 98 % across devices, while SuperRaman achieved up to 100 % classification accuracy post-transformation. …”

Enhancing the properties and performance of polysulfone ultrafiltration membranes using citric acid based deep eutectic solvent additives by Yousef Elhamarnah (17869382)

“…<p>This study focuses on improving the performance of polysulfone (PSF) membranes through modification with a Deep Eutectic Solvent (DES) composed of Citric Acid (CA) and Choline Chloride (ChCl). …”

Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation by Mostafa M., Shibl

“…Deep RL is utilized to model the EV chargers and the EV users. …”
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Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation by Mostafa M. Shibl (17821382)

“…Deep RL is utilized to model the EV chargers and the EV users. …”

The effect of Dopamine Agonists on patients with advanced Parkinson's disease subjected to subthalamic deep brain stimulation. (c2000) by Jabre, Mazen Gerges

“…The mean levodopa dose was reduced by 90% (p < 0.01), while the mean dopamine agonist dose was increased by 15% from preoperative level. Reported adverse events were mild and transient. …”
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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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Surgical Management of Hepatic Benign Disease: Have the Number of Liver Resections Increased in the Era of Minimally Invasive Approach? Analysis from the I Go MILS (Italian Group o... by Ardito, Francesco

“…Although an evident growth of the use of MILS was observed during the time period analysis in Italy, this trend did not correspond to an increased number of MILS for BD, and the overall rate of resected BD was comparable to that reported in previous large open series.…”
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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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Five-Level MLI-Based Grid-Connected Photovoltaic Systems: A Review on Control Methodologies, Modulation Strategies and Recent Developments by Anurag Tiwari (3563561)

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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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. …”

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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