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301
Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta
Published 2023“…Several dataset analysis models are utilised to study the data diversity. Further, this study demonstrates the application of neural network-based models to effectively predict the permeability. …”
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302
Developing a UAE-Based Disputes Prediction Model using Machine Learning
Published 2022Get full text
doctoralThesis -
303
The use of multi-task learning in cybersecurity applications: a systematic literature review
Published 2024“…Cybersecurity has become vital in information technology, with data protection being a major priority. Despite government and corporate efforts, cybersecurity remains a significant concern. …”
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304
From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors
Published 2021“…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. …”
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305
A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method
Published 2022“…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. …”
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306
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A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants
Published 2006“…The U-model utilizes only past data for plant modelling and standard root solving algorithm for control law formulation. …”
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308
Using artificial bee colony to optimize software quality estimation models. (c2015)
Published 2016“…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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masterThesis -
309
Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning
Published 2022Get full text
doctoralThesis -
310
Modeling of Chlorophyll-a and Eutrophication Indicators in the Dubai Creek Area using Remote Sensing
Published 2015Get full text
doctoralThesis -
311
Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models
Published 2023“…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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312
Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices
Published 2025“…The methodology involves data preparation with <u>imputation</u> and normalization, followed by training 9 supervised ML models. …”
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313
Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
Published 2025“…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. …”
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314
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315
Information warfare recovery-fighting back through the matrix. (c2012)
Published 2012Get full text
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masterThesis -
316
Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System
Published 2020Get full text
doctoralThesis -
317
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318
Single channel speech denoising by DDPG reinforcement learning agent
Published 2025“…It achieves this performance by utilizing data that is 7 times smaller than that required by other models. …”
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319
Integration of Textural and Material Information into BIM Using Spectrometry and Infrared Sensing
Published 2015Get full text
doctoralThesis -
320
Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper
Published 2025“…<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. …”