Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare by Haraty, Ramzi A.

“…To make the process of damage assessment and recovery fast and efficient and in order not to scan the whole log, researchers have proposed different methods for segmenting the log, and accordingly presented different damage assessment and recovery algorithms. Since even segmenting the log into clusters may not solve the problem, as clusters/segments may grow to be humongous in size, this is in case of high data/transaction dependency, we suggest a method for segmenting the log into clusters and its sub-clusters; i.e, segmenting the cluster; based on exact data dependency [12], into sub-clusters; based on two different criteria: number of data items or space occupied. …”
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A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education by Abu Zitar, Raed

“…The main aim of this paper is to map the relationship between teaching practices and student learning based on emotional impact. Facial recognition algorithms extract helpful information from online platforms as image classification techniques are applied to detect the emotions of student and/or teacher faces. …”
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Comprehensive whole genome sequence analyses yields novel genetic and structural insights for Intellectual Disability by Farah R. Zahir (18892108)

“…The <i>de novo</i> assembly resulted in unmasking hidden genome instability that was missed by standard re-alignment based algorithms. We also interrogated regulatory sequence variation for known and hypothesized ID genes and present useful strategies for WGS data analyses for non-coding variation.…”

Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures by JUMA, MAZEN GHAZI

“…The technology stack was also enhanced with three new algorithms and five protocols. The proposed solution was optimized using the iterative four-objective cycle based on previous primary phase results. …”
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Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar (16904526)

“…In this regard, our study aims to predict the permeability of molecules across the placental barrier. Based on publicly available datasets, several machine learning models are comprehensively analysed across different fingerprints and toolkits to find the best suitable models. …”

LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …”

Applying urban parametric design optimisation processes to a hot climate: Case study of the UAE by Taleb, Hanan

“…An in-depth analysis was carried out between the base case and the optimised case. Future recommendations were drawn based on the findings and results. …”
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A low degree vertex elimination with high degree vertex selection heuristic for strongly connected dominating and absorbent sets in wireless Ad-Hoc networks. (c2011) by Markarian, Christine Hovsep

“…Experimental results show that our approach outperforms all previously known algorithms for the SCDAS problem.…”
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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. …”

Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by Wehbi, Osama

“…Based on our simulation findings, our strategy surpasses the VanillaF selection approach in terms of maximizing both the revenues of the client devices and accuracy of the global federated learning model.…”
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A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques by SALLOUM, SAID

“…Amongst the range of classification algorithms, support vector machines (SVMs) are heavily utilised for detecting phishing emails. …”
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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

“…The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”

Creating and detecting fake reviews of online products by Joni Salminen (7434770)

“…We show that a machine classifier can accomplish this goal near-perfectly, whereas human raters exhibit significantly lower accuracy and agreement than the tested algorithms. The model was also effective on detected human generated fake reviews. …”

Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”

Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach by Mohammad Taghi Dabiri (16904658)

“…Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …”

Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations by Md Mosarrof Hossen (21399056)

“…A comparative evaluation of three FL algorithms (FedAvg, FedProx, Mime-lite) identifies the most suitable aggregation strategy. …”

A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

“…This study not only examines the well-known challenges such as limited availability of data but provides a novel, structured taxonomy of deep learning techniques tailored for the monitoring of seagrass, highlighting their unique advantages and limitations within diverse marine environments. By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…”

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

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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

“…The data needs to be initially prepared so that deep learning algorithms may be trained on it before cyberbullying analysis can be done. …”
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A comparative analysis to forecast carbon dioxide emissions by Md. Omer Faruque (17545671)

“…This leads to the second step, which involves formulating the multivariate time series CO₂ emissions forecasting challenges considering its influential factors. Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN–LSTM), long short-term memory (LSTM), and dense neural network (DNN). …”