AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients by Azar, Danielle

“…Endocrinologists need to find a certain pattern in this data that would help them determine the optimal dosage of insulin to administer to each patient. …”
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Parameterization and compensation of friction forces using geneticalgorithms by Al-Duwaish, H.N.

“…A PI controller with parameters optimized using genetic algorithms is used to control the position of a DC motor with friction. …”
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Complexities of special matrix multiplication problems by Takche, J.

“…This paper develops optimal algorithms to multiply an n × n symmetric tridiagonal matrix by: (i) an arbitrary n × m matrix using 2nm − m multiplications; (ii) a symmetric tridiagonal matrix using 6n − 7 multiplications; and (iii) a tridiagonal matrix using 7n −8 multiplications. …”
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Tuning of a fuzzy logic power system stabilizer using geneticalgorithms by Abido, M.A.

“…The proposed approach uses genetic algorithms (GA) to search for optimal or near optimal settings of fuzzy logic power system stabilizer (FLPSS) parameters. …”
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Predicting the Release of Chemotherapeutics From the Core of Polymeric Micelles Using Ultrasound by Abdel-Hafez, Mamoun

“…The proposed algorithms are first tested using a simulation environment. …”
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Experimental evaluation of multi-agent reinforcement learning in real-world scale-free networks by Al Hashimi, Rashid

“…Multi-agent reinforcement learning is a common method for optimizing agents' local decision in a distributed and scalable manner. …”
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Towards Multimedia Fragmentation by Saad, Samir

“…In this paper, we address multimedia database fragmentation by extending existing fragmentation algorithms to take into account key characteristics of multimedia objects. …”
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Hybrid deep learning based threat intelligence framework for Industrial IoT systems by Jahanzaib Malik (23718816)

“…The proposed approach was also compared against several contemporary deep learning-based architectures and existing benchmark algorithms. The results indicate that the proposed method achieves superior detection accuracy, with only a minimal compromise in speed efficiency. …”

A Highly Efficient And Automated Approach To Identifying And Classifying Urban Traffic Images Using Self Organizing Maps and Artificial Intelligence. (c2006) by Bey, Hisham Mardam

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

“…We de ne the constraints of the problem, model it as a Markov Decision Process, and propose a reinforcement learning-based solution to optimize the UAV trajectory. 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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Hybridizing rule-based power system stabilizers with geneticalgorithms by Abido, M.A.

“…The proposed approach uses genetic algorithms (GA) to search for optimal settings of rule-based power system stabilizer (RBPSS) parameters. …”
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SemIndex: Semantic-Aware Inverted Index by Chbeir, Richard

“…Preliminary results have demonstrated the effectiveness, scalability and optimality of our approach.…”
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A fine-grained XML structural comparison approach by Tekli, Joe

“…A prototype has been developed to evaluate the optimality and performance of our method. Experimental results, on both real and synthetic XML data, demonstrate better performance with respect to alternative XML comparison methods.…”
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Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

“…Experimental results demonstrated that DL algorithms leveraging sampling methods perform significantly worse than the decision tree-based ensemble method. …”

Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning by Moussa, Mostafa Mohamed

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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

“…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …”
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Predicting Android Malware Using Evolution Networks by Chahine, Joy

“…We combine this model with genetic algorithms to optimize its parameters and return the best state transition probabilities, and we predict future malware accordingly. …”
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Enhancement of SAR Speckle Denoising Using the Improved Iterative Filter by Yahia, Mohamed

“…In this article, an effort is made to enhance the performance of the IMMSE filter in terms of speckle reduction and spatial detail preservation by refining the choice of the initial filter, optimizing its parameters, and improving the estimation of local statistics. …”
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Corrosion Monitoring Technologies for Reinforced Concrete Structures: A Review by SHEHADEH, KHADIJA

“…Irrespective of the adopted processes for corrosion monitoring, it was concluded that none of these methods represent an optimum solution by itself, where employing a combination of multiple systems is one way of optimizing its results. New technology, algorithms, data processing, and AI are new approaches to improving corrosion monitoring processes. …”
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A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques by SALLOUM, SAID

“…The findings include that the main research area in phishing detection studies is feature extraction and selection, followed by methods for classifying and optimizing the detection of phishing emails. Amongst the range of classification algorithms, support vector machines (SVMs) are heavily utilised for detecting phishing emails. …”
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