Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

“…This study offers a thorough examination of how AI can be utilized to enhance e-learning results by employing advanced predictive methods and performance optimization strategies. The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”

Cardiovascular health research priorities in the United Arab Emirates by Ghader, Nariman

“…The top research priority areas were: development of evidence-based, customized algorithms for CVD prevention and in-hospital emergency interventions; the availability, accessibility, and affordability of CVD treatment and rehabilitation; identification of relationships between CVDs, lifestyle factors, and mental health; efficacy and constraints in the management of cardiac emergencies; and epidemiological studies that trace CVD in the UAE. …”
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Deepfakes Signatures Detection in the Handcrafted Features Space by Hamadene, Assia

“…In the Handwritten Signature Verification (HSV) literature, several synthetic databases have been developed for data-augmentation purposes, where new specimens and new identities were generated using bio-inspired algorithms, neuromotor synthesizers, Generative Adversarial Networks (GANs) as well as several deep learning methods. …”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

“…This work proposes various machine learning methods, including transfer learning via fine-tuning, transfer learning via feature extraction, ensembles of deep convolutional neural network (CNN) models, and fusion of CNN features, to develop a preliminary dysgraphia diagnosis system based on handwritten images. …”
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The role of Reinforcement Learning in software testing by Amr Abo-eleneen (17032284)

“…</p><h3>Results</h3><p dir="ltr">This study highlights different software testing types to which RL has been applied, commonly used RL algorithms and architecture for learning, challenges faced, advantages and disadvantages of using RL, and the performance comparison of RL-based models against other techniques.…”

Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations by Md Mosarrof Hossen (21399056)

“…A comparative evaluation of three FL algorithms (FedAvg, FedProx, Mime-lite) identifies the most suitable aggregation strategy. …”

Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects by Mohamed Massaoudi (16888710)

“…Motivated by the outstanding success of DL-based prediction methods, this article attempts to provide a thorough review from a broad perspective on the state-of-the-art advances of DL in SG systems. …”

A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

“…However, traditional monitoring methods can be labor-intensive and costly, especially in complex underwater environments. …”

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth Kunhoth (14158908)

“…This work proposes various machine learning methods, including transfer learning via fine-tuning, transfer learning via feature extraction, ensembles of deep convolutional neural network (CNN) models, and fusion of CNN features, to develop a preliminary dysgraphia diagnosis system based on handwritten images. …”

Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

“…As a consequence, deep learning methods have become a potential solution for this situation. …”
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Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression by Alaa Abd-Alrazaq (17430900)

“…Until further research improve its performance, wearable AI should be used in conjunction with other methods for diagnosing and predicting depression. …”

Conceptual Design and Analysis of Concentrated Photovoltaic Thermal (CPVT) Solar Collectors with Different Configurations by Sharaf, Omar Z.

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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems by Mahmood, Lubna Syeda

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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”

Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

“…The first contribution of this thesis is conducting an in-depth meta-analysis of existing evaluation methods, classification techniques, and datasets related to ML for cyberbullying problems. …”
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Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review by Hiba Alzoubi (18001609)

“…</p><h3>Objective</h3><p dir="ltr">This systematic review evaluates the performance of AI models in detecting and subtyping medulloblastomas using histopathological images. </p><h3>Methods</h3><p dir="ltr">In this systematic review, we searched seven databases to identify English-language studies assessing AI-based detection or classification of medulloblastomas in patients under 18 years. …”

BioNetApp: An interactive visual data analysis platform for molecular expressions by Ali M. Roumani (18615124)

“…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications by Abdallah Falah Mohammad Aldwekat (22457821)

“…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …”

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

“…We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities.…”