Secrecy Performance of Decode-and-Forward Based Hybrid RF/VLC Relaying Systems by Jaber Al-Khori (16855470)

“…We evaluate the system performance in terms of secrecy capacity (SC) and outage probability (OP) for two network scenarios, namely non-cooperative (NCPS) and cooperative power saving (CPS) models. The NCPS case assumes fixed power at both source and relay while the CPS case assumes total average power shared between the source and relay. …”

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

“…We experiment with multiple attackers—Text-bugger, Text-fooler, PWWS—on several architectures—MLP, CNN, LSTM, Hybrid CNN-RNN, BERT—trained for different classification tasks—IMDB sentiment classification, fake-news classification, AG news topic classification—under different threat models—Con-Detect-blind attacks, Con-Detect-aware attacks, and Con-Detect-adaptive attacks—and show that Con-Detect can reduce the attack success rate (ASR) of different attacks from 100% to as low as 0% for the best cases and ≈70% for the worst case. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…We experiment with multiple attackers—Text-bugger, Text-fooler, PWWS—on several architectures—MLP, CNN, LSTM, Hybrid CNN-RNN, BERT—trained for different classification tasks—IMDB sentiment classification, fake-news classification, AG news topic classification—under different threat models—Con-Detect-blind attacks, Con-Detect-aware attacks, and Con-Detect-adaptive attacks—and show that Con-Detect can reduce the attack success rate (ASR) of different attacks from 100% to as low as 0% for the best cases and ≈70% for the worst case. …”

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

“…To categorize electronic text in these two cases, deep learning models such as convolutional neural networks and recurrent neural networks and a combination of CNN-RNN were trained on this data. …”
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Condenser capacity and hyperbolic perimeterImage 1 by Mohamed M.S., Nasser

“…Our computational experiments demonstrate, for instance, sharpness of established inequalities. In the case of model problems with known analytic solutions, very high precision of computation is observed.…”
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Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort by Mohamed Adil Shah Khoodoruth (14589828)

“…Linear regression analysis revealed that MLR and clozapine treatment were significantly correlated with the severity of schizophrenia symptoms. The Random Forest model, a supervised machine learning algorithm, efficiently differentiated between cases and controls and between TRS and NTRS, with accuracies of 86.87 % and 88.41 %, respectively. …”

Condenser capacity and hyperbolic perimeter by Mohamed M.S. Nasser (16931772)

“…Our computational experiments demonstrate, for instance, sharpness of established inequalities. In the case of model problems with known analytic solutions, very high precision of computation is observed.…”

Identity and Aggregate Signature-Based Authentication Protocol for IoD Deployment Military Drone by Saeed Ullah Jan (9079260)

“…Both GPS and UAVN/FANET use open network channels for data broadcasting, which are exposed to several threats, thus making security risky and challenging. …”

Practical Multiple Node Failure Recovery in Distributed Storage Systems by Itani, M.

“…Fast convergence validates the efficacy of our algorithms for different system parameters. Simulation results are shown to be close to optimal for the case of newly arriving blocks.…”
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Machine Learning Techniques for Pharmaceutical Bioinformatics by SULTAN, AHMED ATTA AHMED

“…In this matrix, each drug is represented by a vector of attributes from all other drugs. A predictive model is developed to predict drug indication as well as to predict new DDIs using multiple machine learning algorithms. …”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

“…In the case of ensemble learning, soft voting ensembles of task-specific CNNs achieved an accuracy of 90.4%. …”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth Kunhoth (14158908)

“…In the case of ensemble learning, soft voting ensembles of task-specific CNNs achieved an accuracy of 90.4%. …”

Capillary trapping in mixed-wet porous media: Implications for subsurface carbon dioxide sequestration by Saideep Pavuluri (21792941)

“…Insights from this study can be used for improving pore network models and training machine learning algorithms.</p><h2>Other Information</h2><p dir="ltr">Published in: International Journal of Multiphase Flow<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ijmultiphaseflow.2025.105307" target="_blank">https://dx.doi.org/10.1016/j.ijmultiphaseflow.2025.105307</a></p>…”

Seasonal variations in feed-water chemistry and fouling dynamics of reverse-osmosis systems: A global climate lens by Nasser Zareei (22921226)

“…<p>Reverse osmosis desalination plants are built for worst-case conditions, yet seasonal variations in feed water quality often outpace their design assumptions, leading to avoidable membrane performance losses. …”

Connectionist technique estimates of hydrogen storage capacity on metal hydrides using hybrid GAPSO-LSSVM approach by Sina Maghsoudy (21393539)

“…In the present study, three machine learning algorithms including GA-LSSVM, PSO-LSSVM, and HGAPSO-LSSVM were employed. …”

Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning by Mohamed Elhadary (16329082)

“…With the significant advancements in machine learning (ML) and artificial intelligence (AI) in recent years, numerous models and algorithms have been proposed to support the diagnosis and classification of CLL. …”

Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices by Aya Hasan Alkhereibi (17151070)

“…Focusing on high-ranking cities ensures the study analyzes robust and reliable data, avoiding noise and inconsistencies arising from lower-performing or less-documented cases. Drawing on data from the Smart Cities Index (SCI) and other economic and sustainability competitiveness metrics, the study uses various <u>ML algorithms</u> to categorize cities into <u>performance classes</u>, ranging from high-achieving Class 1 to emerging Class 3 cities. …”

The role of Reinforcement Learning in software testing by Amr Abo-eleneen (17032284)

“…</p><h3>Results</h3><p dir="ltr">This study highlights different software testing types to which RL has been applied, commonly used RL algorithms and architecture for learning, challenges faced, advantages and disadvantages of using RL, and the performance comparison of RL-based models against other techniques.…”

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

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A Multi-Channel Convolutional Neural Network approach to automate the citation screening process by Raymon van Dinter (10521952)

“…It was shown that for 18 out of 20 review datasets, the proposed method achieved significant workload savings of at least 10%, while in several cases, our model yielded a statistically significantly better performance over two benchmark review datasets. …”