Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

“…For a large-sized data set, KPCA’s execution time and occupied storage space will increase drastically and the monitoring performance can also be affected in this case. …”

Ensemble Stacking Model for Sentiment Analysis of Emirati and Arabic Dialects by A. Al Shamsi, Arwa

“…Then, an ensemble stacking model was introduced to combine the best-performing deep learning models used in this study. The ensemble stacking deep learning model consisted of deep learning models with a meta learner layer of classifiers. …”
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Electric Grid Resilience Enhancement During Natural Disasters: An Optimization-Based UAV Inspection and Dynamic Crew Dispatch Model by Serag, Yousef

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Visual Sentiment Analysis from Disaster Images in Social Media by Syed Zohaib Hassan (18387129)

“…<div><p>The increasing popularity of social networks and users’ tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content have opened new opportunities and challenges in sentiment analysis. …”

Blood Glucose Regulation Modelling and Intelligent Control by Nasar, Nabeel

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Artificial Intelligence for Detecting and Quantifying Fatty Liver in Ultrasound Images: A Systematic Review by Fahad Muflih Alshagathrh (18427950)

Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP by Abdelhafez, Nada

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Theft Detection Unit For Photo-Votaic Generation in Smart Grid Networks by Almadani, Nouf Ahmad

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In-Between Projection Interpolation in Cone-Beam CT Imaging using Convolutional Neural Networks by Dweek, Samaa

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Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu by Ayesha Atif (22155133)

“…Furthermore, we present temporal abusive tweet probability analysis method to provide a nuanced analysis of the number of bullying and non-bullying tweets sent by individuals within a specific time interval. To evaluate the performance, we compare the GRU-based approach with other machine learning models. …”

Electrochemical Studies on the Corrosion Behavior of Common Metals in Eutectic Ionic Liquids by Alhasan, Rami

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The use of multi-task learning in cybersecurity applications: a systematic literature review by Shimaa Ibrahim (22155739)

“…<p dir="ltr">Cybersecurity is crucial in today’s interconnected world, as digital technologies are increasingly used in various sectors. The risk of cyberattacks targeting financial, military, and political systems has increased due to the wide use of technology. …”

Decoding silent speech: a machine learning perspective on data, methods, and frameworks by Adiba Tabassum Chowdhury (19444792)

“…Examining state-of-the-art SSR frameworks, the paper covers important topics such signal processing, feature extraction, ML techniques for decoding and optimizing and assessing the performance of SSR models. We emphasize how deep learning (DL) and ML models have evolved to increase SSR resilience and accuracy. …”

Intelligent scaling for 6G IoE services for resource provisioning by Abdullah Alharbi (4173502)

“…IScaler is considered to be made for MEC in Deep Reinforcement Learning (DRL). The paper has considered several requirements for making service placement decisions. …”

Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data by Alaa Awad Abdellatif (17151163)

“…<p dir="ltr">Federated Learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. …”

Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities by Md Golam Morshed (19420537)

“…One of the most challenging issues for computer vision is the automatic and precise identification of human activities. A significant increase in feature learning-based representations for action recognition has emerged in recent years, due to the widespread use of deep learning-based features. …”

Evaluating machine learning technologies for food computing from a data set perspective by Nauman Ullah Gilal (17302714)

“…Food computing benefits from technologies based on modern machine learning techniques, including deep learning, deep convolutional neural networks, and transfer learning. …”

A systematic review and meta-analysis on the impact of early vs. delayed pharmacological thromboprophylaxis in patients with traumatic brain injury by Muhammad Hamza Shuja (19748620)

“…Early PTP was categorized based on the timing of administration: 1) within 24 h, 2) within 48 h, and 3) within 72 h of hospital admission. …”

A New Flow-Based Approach for Enhancing Botnet Detection Efficiency Using Convolutional Neural Networks and Long Short-Term Memory by Mehdi Asadi (12566741)

“…<p dir="ltr">Despite the growing research and development of botnet detection tools, an ever-increasing spread of botnets and their victims is being witnessed. …”

Food fraud detection using explainable artificial intelligence by Okan Buyuktepe (17991493)

“…<div><p>Recently, the global food supply chain has become increasingly complex, and its scalability has grown. …”