Impact of birth weight to placental weight ratio and other perinatal risk factors on left ventricular dimensions in newborns: a prospective cohort analysis by Ashraf Gad (17040114)

“…Chi-squared and one-way analysis of variance were used to compare BW/PW groups and the best regression model was selected using a genetic and backward stepwise algorithm.…”

A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis by Alaa Abd-Alrazaq (17430900)

“…Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.…”

Adaptive Federated Learning Architecture To Mitigate Non-IID Through Multi-Objective GA-Based Efficient Client Selection by Ajaj, Mohamad

“…Existing solutions still have several constraints leading to suboptimal model performance and slow convergence. In this paper, we propose a novel approach that incorporates genetic algorithms with an enhanced client selection strategy, utilizing client metadata rather than raw data. …”
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A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications by Sharafeddine, Sanaa

“…However, the computational as well as memory access requirements of compression algorithms could consume more energy than simply transmitting data uncompressed. …”
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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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Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning by MEZAHEM, FATEMA HAMAD

“…The two movies are Wahed Tani which translates to (someone else) and Amahom which translate to (their uncle), Three datasets were employed, and several categorization models were compared across them. Prior to performing sentiment analysis, it is necessary to prepare the data so that it may be used to train machine learning (ML) algorithms. …”
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Image-CNN Based Process Control of Profile by Zeinab, Zeinab Jihad

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Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose by Atiq Ur Rehman (8843024)

“…These electronic instruments rely on Machine Learning (ML) algorithms for recognizing the sensed odors. The effect of long-term drift influences the performance of ML algorithms and the models those are trained on drift free data fail to perform on the drifted data. …”

Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology by Ajay Vikram Singh (204056)

“…As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. …”

Real-Time Social Robot’s Responses to Undesired Interactions Between Children and their Surroundings by Ahmad Yaser Alhaddad (7017434)

“…Testing the best model with data acquired from children performing interactions with toys produced a promising performance for the shake and throw behaviours. …”

Artificial Intelligence for Skin Cancer Detection: Scoping Review by Abdulrahman Takiddin (14153181)

“…Overall, studies that used smaller data sets reported higher accuracy.</p><h3>Conclusions</h3><p dir="ltr">This paper examined multiple AI-based skin cancer detection models. …”

Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates by Ratiba F. Ghachi (14152455)

“…The thin plate and the zigzag cutouts are modelled using the finite element method, and the optimal location and optimal tip mass of the zigzag cutouts are obtained using genetic algorithms through iterative simulations. …”

Face Flow: Constrained Optical Flow Framework for Faces by Alkaddour, Muhannad

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A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…This review synthesizes evidence from more than 500 peer-reviewed studies published between 2020 and 2026, mapping DRL applications across distributed generation, transmission, distribution, energy storage systems, energy markets, local energy management, grid security, and data privacy. We present a structured taxonomy covering value-based, policy-based, actor-critic, model-based, and advanced multi-agent and multi-objective approaches, and link algorithms to tasks such as dispatch, microgrid coordination, real-time pricing, load balancing, and demand–response. …”

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

“…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.…”

A Machine Learning Approach to Predicting Diabetes Complications by Jian, Yazan Khaled

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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization by Yassine Himeur (14158821)

“…While artificial intelligence (AI) smooths the path of computers to think like humans, machine learning (ML) and deep learning (DL) pave the way more, even by adding training and learning components. DL algorithms require data labeling and high-performance computers to effectively analyze and understand surveillance data recorded from fixed or mobile cameras installed in indoor or outdoor environments. …”

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

“…Nonetheless, the performance analysis section will be executed using the algorithmic big-O notation. The results show that these protocols are verifiably protected in the ROM and ROR model using the CDHP.…”

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

“…Leveraging FL enables efficient model training across diverse end-user applications while preserving data privacy. …”

Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants by Hamad Al Shamsi, Jawaher

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