QU-GM: An IoT Based Glucose Monitoring System From Photoplethysmography, Blood Pressure, and Demographic Data Using Machine Learning حسب Md Nazmul Islam Shuzan (21842426)

"…Bagged Ensemble Trees outperform other algorithms in estimating blood glucose level with a correlation coefficient of 0.90. …"

Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE حسب Ben Romdhane, Haifa

"…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE حسب Ben-Romdhane, Haïfa

"…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
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CFD Based Airfoil Shape Optimization for Aerodynamic Drag Reduction حسب Khot, Mohammed Taha Shafiq

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A Novel Fault Diagnosis of Uncertain Systems Based on Interval Gaussian Process Regression: Application to Wind Energy Conversion Systems حسب Majdi Mansouri (16869885)

"…In the proposed IGPR-RF technique, the effective interval-valued nonlinear statistical features are extracted and selected using the IGPR model and then fed to the RF algorithm for fault classification purposes. …"

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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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. …"

A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity حسب Abdullah Al Siam (22304047)

"…We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. …"

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. …"

Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method حسب Mohamed Massaoudi (16888710)

"…The proposed model is thoroughly assessed through an empirical study using a real data set from Australia. …"

On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach حسب Md. Sihab Uddin (17542488)

"…The design is carried out based on the selection of the optimal model parameters using a search optimization algorithm called GridSearchCV. …"

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. …"

Sentiment visualization of correlation of loneliness mapped through social intelligence analysis حسب Hurmat Ali Shah (18192889)

"…</p><h3>Objectives</h3><p dir="ltr">This paper aims to visualize the frequency of loneliness-related themes and topics in Twitter data. By using natural language (NLP) processing, sentiment analysis, and topic modeling, we seek to understand prevalent sentiments and concerns. …"

Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE حسب Mathew, Elezabeth

"…The data analytics maturity model is used as the conceptual model for evaluating both data analytics and data governance in this research. …"
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Hybrid Interval Type-2 Fuzzy PID+I Controller for a Multi-DOF Oilwell Drill-String System حسب Abdelbaset Laib (16904688)

"…An optimal hybrid interval Type-2 fuzzy PID+I logic controller (OH-IT2FPID+I) using a practical swarm optimization algorithm for a multi-degree-of-freedom oil well drill-string system is proposed in this paper. …"

A multi-pretraining U-Net architecture for semantic segmentation حسب Cagla Copurkaya (22502042)

"…The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. For the validation of the proposed model, we used data from 21,000 cell nuclei at a resolution of 1000 by 1000 pixels. …"

Improving MRI Resolution: A Cycle Consistent Generative Adversarial Network-Based Approach for 3T to 7T Translation حسب Zakaria Shams Siam (22048001)

"…However, the exorbitant expenses associated with 7T MRI scanners hinder their broad use in research and clinical facilities. Efforts are underway to develop algorithms that can generate 7T MRI from 3T MRI to achieve better image quality without the need for 7T MRI machines. …"

ZigBee-Based Tangible Input Devices حسب Khan, Waqqas Munir

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Interval-Valued Reduced Ensemble Learning Based Fault Detection and Diagnosis Techniques for Uncertain Grid-Connected PV Systems حسب Khaled Dhibi (16891524)

A Survey of Machine Learning Innovations in Ambulance Services: Allocation, Routing, and Demand Estimation حسب Reem Tluli (22282702)

"…By thoroughly reviewing the existing literature and methodologies, this paper provides a comprehensive overview of the approaches used in ambulance allocation, routing, demand estimation and simulation models. …"