Deepfakes Signatures Detection in the Handcrafted Features Space حسب 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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Modelling of pollutant transport in compound open channels حسب Chatila, Jean Georges

"…The numerical computation of open-channel flows requires preparing and processing larger volumes of boundary and bathymetry data for computer inputs and the development of numerical algorithms for treating complex boundary condition, channel properties, and free surface effects. …"
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Conceptual Design and Analysis of Concentrated Photovoltaic Thermal (CPVT) Solar Collectors with Different Configurations حسب Sharaf, Omar Z.

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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. …"

DASSI: differential architecture search for splice identification from DNA sequences حسب Shabir Moosa (14153316)

"…This has been fueled through the development of new DL architectures. Yet genomics possesses unique challenges that requires customization and development of new DL models.…"

Enhancing building sustainability: A Digital Twin approach to energy efficiency and occupancy monitoring حسب Aya Nabil Sayed (17317006)

"…Our data-driven occupancy detection approach utilized Machine Learning (ML) algorithms to intelligently determine room occupancy, allowing for precise energy management based on real-time usage patterns. …"

A comparative analysis to forecast carbon dioxide emissions حسب Md. Omer Faruque (17545671)

"…This leads to the second step, which involves formulating the multivariate time series CO₂ emissions forecasting challenges considering its influential factors. Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN–LSTM), long short-term memory (LSTM), and dense neural network (DNN). …"

Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning حسب Far, Reza Davoodi

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Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning حسب MEZAHEM, FATEMA HAMAD

"…People are now able to share their opinions about specific topics because to the rapid development of technologies and social media platforms. …"
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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data حسب Arfan Ahmed (17541309)

"…The use of such biomarkers to monitor glycemic events represents a major shift in technology for self-monitoring and developing digital biomarkers using non-invasive WDs. …"

Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases حسب Muhammad Ali Muzammil (17910611)

"…Further study and development are required to fully realize AI's promise for improving cardiology practices and patient care as technology continues to advance.…"

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

"…This practice has spread substantially due to rapid technological development and has gained significant attention in several domains involving data exchange, such as e-commerce, digital marketing, social media platforms, and others. …"
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Machine Learning Model for a Sustainable Drilling Process حسب Alsaidi, Ola

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Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic حسب Hassan Farhat (9000509)

"…</p><h3>Results</h3><p dir="ltr">From June 2018 to July 2022, 334,392 non-transport cases were recorded. The random forest model demonstrated the best optimised predictive performance, with accuracy = 74.78%, F1 = 0.74, MCC = 0.35, ROC AUC = 0.81, kappa = 0.34, and R-squared = 0.81. …"

A Framework for Predictive Modeling in Sustainable Projects حسب Labban, Tarek

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