Developing a UAE-Based Disputes Prediction Model using Machine Learning حسب Abu Laila, Ibrahim Wasef Subhi

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The use of multi-task learning in cybersecurity applications: a systematic literature review حسب Shimaa Ibrahim (22155739)

"…Cybersecurity has become vital in information technology, with data protection being a major priority. Despite government and corporate efforts, cybersecurity remains a significant concern. …"

From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors حسب Michael R. Giordano (9976173)

"…The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. …"

A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method حسب Shahid Rahman (16904613)

"…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. …"

Stacking-based ensemble learning for remaining useful life estimation حسب Begum Ay Ture (17773170)

A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants حسب Khan, T.

"…The U-model utilizes only past data for plant modelling and standard root solving algorithm for control law formulation. …"
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Using artificial bee colony to optimize software quality estimation models. (c2015) حسب Abou Assi, Tatiana Antoine

"…In this thesis, we propose a novel heuristic based on Artificial Bee Colony (ABC) to optimize rule-based software quality prediction models. We validate our technique on data describing maintainability and reliability of classes in an Object-Oriented system. …"
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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning حسب Zeinab, Samira Jihad

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The Use of Microwave Tomography in Bone Healing Monitoring حسب Alkhodari, Mohanad Ahmed

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Modeling of Chlorophyll-a and Eutrophication Indicators in the Dubai Creek Area using Remote Sensing حسب Bachir, Abdallah Raafat

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Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models حسب AL SHAMSI, ARWA AHMED

"…For the basic machine learning algorithms, LR, NB, SVM, RF, DT, MLP, AdaBoost, GBoost, and an ensemble model of machine learning classifiers were used. …"
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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)

"…The methodology involves data preparation with <u>imputation</u> and normalization, followed by training 9 supervised ML models. …"

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …"

DAP: A dataset-agnostic predictor of neural network performance حسب Sui Paul Ang (18460605)

Information warfare recovery-fighting back through the matrix. (c2012) حسب Zbib, Mirna

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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System حسب Abougharib, Arwa

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Online dynamic ensemble deep random vector functional link neural network for forecasting حسب Ruobin Gao (16003195)

Single channel speech denoising by DDPG reinforcement learning agent حسب Sania Gul (18272227)

"…It achieves this performance by utilizing data that is 7 times smaller than that required by other models. …"

Integration of Textural and Material Information into BIM Using Spectrometry and Infrared Sensing حسب Zabin, Asem Ahmad

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Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper حسب Mutaz I. Othman (21186827)

"…<h3>Background</h3><p dir="ltr">Machine learning (ML) models can enhance patient–nurse assignments in healthcare organisations by learning from real data and identifying key capabilities. …"