Artificial intelligence models for predicting the mode of delivery in maternal care by Rawan AlSaad (14159019)

“…</p><h3>Objectives</h3><p dir="ltr">This study aims to evaluate and compare the predictive accuracy of AI algorithms in predicting the mode of delivery (vaginal or cesarean) using routinely collected antepartum data from electronic health records (EHRs). …”

An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation by El-Maleh, Aiman H.

“…In this work, we propose a hybrid approach which uses a combination of evolutionary and deterministic algorithms for state justification. A new method based on Genetic algorithms is proposed, in which we engineer state justification sequences vector by vector. …”
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An evolutionary meta-heuristic for state justification insequential automatic test pattern generation by El-Maleh, A.H.

“…In this work, we propose a hybrid approach which uses a combination of evolutionary and deterministic algorithms for state justification. A new method based on Genetic Algorithms is proposed, in which we engineer state justification sequences vector by vector. …”
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Advancing Coherent Power Grid Partitioning: A Review Embracing Machine and Deep Learning by Mohamed Massaoudi (16888710)

“…By altering the network’s topology, partitioning aims to create areas within the PS that are not only robust but also have increased flexibility in generation and improved controllability over variable demand. This article provides an updated review of the cutting-edge machine learning and data-driven techniques used for PGP in networked PSs. …”

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ResultMost traditional machine learning algorithms achieved distinction accuracies of over 99 percent, whereas DeepRaman demonstrated an exceptional accuracy of 100 percent. …”
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DASSI: differential architecture search for splice identification from DNA sequences by Shabir Moosa (14153316)

“…The demand for robust algorithms over the recent years has brought huge success in the field of Deep Learning (DL) in solving many difficult tasks in image, speech and natural language processing by automating the manual process of architecture design. …”

LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications by Aldamani, Raghad

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Study of the Impact of Land Use and Land Cover (LULC) Changes on local climate in Six Mega Global Cities in the 21st Century by Sabobeh, Lara Ali

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Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique by Iqbal Hassan (22155274)

“…In this study, we harnessed the capabilities of a four-channel, wearable EEG device that captured brain activity data during two distinct CL states: Baseline (representing a non-CL, resting state) and the Stroop Test (a CL-inducing state). …”

Iterative Methods for the Solution of a Steady State Biofilter Model by Salih, Mubarak Sahal

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Approximate XML structure validation based on document–grammar tree similarity by Tekli, Joe

“…In this paper, we propose an original method for measuring the structural similarity between an XML document and an XML grammar (DTD or XSD), considering their most common operators that designate constraints on the existence, repeatability and alternativeness of XML elements/attributes (e.g., ?…”
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Approximate XML structure validation technical report by Tekli, Joe

“…In this paper, we propose an original method for measuring the structural similarity between an XML document and an XML grammar (DTD or XSD), considering their most common operators that designate constraints on the existence, repeatability and alternativeness of XML elements/attributes (e.g., ?…”
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An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure by Fahmy, Ahmed

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From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

“…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”

Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study by Muhammad Atif Butt (10849980)

“…Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. …”

Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices by Neder Karmous (19743430)

“…According to the latest available statistics, in 2023, there were approximately 17.2 billion connected IoT devices; this is expected to reach 25.4 billion IoT devices by 2030 and grow year over year for the foreseeable future. IoT devices share, collect, and exchange data via the internet, wireless networks, or other networks with one another. …”

The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions by Abdulmalik Alwarafy (17984104)

“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”

Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study by Alaa Abd-alrazaq (17058018)

“…The most prominent topic, observed in over half of the analyzed studies, was “the impact of COVID-19.”…”