Adaptive Video Streaming Over Cognitive Radio Networks حسب Mohamed, Ala Eldin Omer

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

"…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. …"

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

Study of the Impact of Land Use and Land Cover (LULC) Changes on local climate in Six Mega Global Cities in the 21st Century حسب Sabobeh, Lara Ali

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CFD Based Airfoil Shape Optimization for Aerodynamic Drag Reduction حسب Khot, Mohammed Taha Shafiq

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Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective حسب Zhitao Xu (2426023)

"…Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …"

Ensemble Deep Random Vector Functional Link Neural Network for Regression حسب Minghui Hu (2457952)

Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review حسب Rehaan Hussain (22302742)

"…In current literature, there are a number of papers that address all these faults using different methods, and this paper compiles the information from the written works for ease of access. Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …"

Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices حسب Aya Hasan Alkhereibi (17151070)

"…This study aims to classify the highest 50 global smart cities based on key livability and technology indices, using advanced <u>machine learning</u> (ML) models to assess city performance comprehensively. …"

Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study حسب Alaa Abd-alrazaq (17058018)

"…Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.…"

A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation حسب Khaled Dhibi (16891524)

"…In the proposed FDD approach, named interval reduced kernel PCA (IRKPCA)-based Random Forest (IRKPCA-RF), the feature extraction and selection phase is performed using the IRKPCA models while the fault classification is ensured using the RF algorithm. …"

Weak-coupling, strong-coupling and large-order parametrization of the hypergeometric-Meijer approximants حسب Abouzeid M. Shalaby (16810695)

"…We get accurate results for the whole coupling space and the precision is improved systematically in using higher orders. Precise results for the critical exponents of the O(4)-symmetric field model in three dimensions have been obtained from resummation of the recent six-loops order of the corresponding perturbation series. …"

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... حسب Tarik Elhadd (5480393)

"…Interestingly, the blood glucose level prediction by our model was influenced by use of SGLT2i.</p><h3>Conclusion</h3><p dir="ltr">XGBoost, a machine learning AI algorithm achieves high predictive performance for normal and hyperglycaemic excursions, but has limited predictive value for hypoglycaemia in patients on multiple therapies who fast during Ramadan.…"

An Event-Triggered Robust Attitude Control of Flexible Spacecraft With Modified Rodrigues Parameters Under Limited Communication حسب Syed Muhammad Amrr (16855557)

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

"…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …"

Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems حسب Tarek Berghout (16905132)

The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review حسب Zainab Jan (17306614)

"…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …"

On the Provisioning of Ultra-Reliable Low-Latency Services in IoT Networks with Multipath Diversity حسب Sweidan, Zahraa

"…Simulation results are presented for both parts of the thesis to illustrate the effectiveness of the proposed solutions and algorithms in comparison with optimal solutions and baseline algorithms.…"
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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series حسب Lasfer, Assia

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Deep and transfer learning for building occupancy detection: A review and comparative analysis حسب Aya Nabil Sayed (17317006)

"…This work investigates occupancy detection methods to develop an efficient system for processing sensor data while providing accurate occupancy information. …"