Dynamic multiple node failure recovery in distributed storage systems by Itani, May

“…We present a range of results for our proposed algorithms in several scenarios to assess the effectiveness of the solution approaches that are shown to generate results close to optimal.…”
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Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters by Farhan, Abid

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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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ISSP by Zouein, P.P.

“…The underlying algorithms optimize positions of resources by minimizing handling and rehandling costs of these on site. …”
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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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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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Barriers of Adopting Artificial Intelligence Tools in Engineering Construction Projects by ALKAABI, ABDULLA

“…AI algorithms depend on data for training and analysis. …”
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Artificial intelligence models for predicting the mode of delivery in maternal care by Rawan AlSaad (14159019)

“…<h3>Background</h3><p dir="ltr">Accurate prediction of the mode of delivery is critical in maternal care to improve prenatal counseling, optimize clinical decision-making, and reduce maternal and neonatal complications. …”

FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

“…In this paper, the suitability of packet-level and flow-level features is validated using stepwise regression and random forest feature selection. Moreover, the optimal percentage of packets considered within a flow while extracting flow-level features is determined. …”
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Defined Clinical Classifications Are Associated with Outcome of Patients with Anatomically Resectable Pancreatic Adenocarcinoma Treated with Neoadjuvant Therapy by Tzeng, Ching-Wei

“…It may be used with neoadjuvant therapy to predict outcomes, individualize treatment algorithms, and optimize survival.…”
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Hybrid deep learning based threat intelligence framework for Industrial IoT systems by Jahanzaib Malik (23718816)

“…To address this, the authors propose a hybrid threat intelligence framework that is not only highly scalable but also incorporates self-optimizing capabilities, enabling it to counteract a wide range of persistent cyber threats and attacks targeting IIoT systems. …”

Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid (22047578)

“…These processes begin with capturing speech in analog form and applying signal processing algorithms to ensure compatibility with devices like cochlear implants (CIs). …”

A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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