High-order parametrization of the hypergeometric-Meijer approximants by Abouzeid M. Shalaby (16329062)

“…<p>In this work, we introduce an extension to the hypergeometric algorithm we developed before for the resummation of divergent series.The extension overcome the time-consuming problem we face in the parametrization process of the hypergeometric approximants. …”

Estimating Bridge Deterioration Age Using Artificial Neural Networks by AL HUSSEIN, ASEEL

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Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura, Habiba

“…A system architecture is designed for a cloud-based IoT framework to implement the proposed algorithm efficiently. The performance evaluation using standard datasets demonstrates that the proposed model provides an accuracy of up to 99.99%.…”
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Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura Habiba (17808302)

“…A system architecture is designed for a cloud-based IoT framework to implement the proposed algorithm efficiently. The performance evaluation using standard datasets demonstrates that the proposed model provides an accuracy of up to 99.99%.…”

A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer by M. Z. Yildiz (16855476)

“…Second, the pre- and post-processed images were encrypted with a new encryption algorithm in the microcomputer environment. …”

Mobile Robot Trajectory Tracking Using Neural Networks by Mohareri, Omid

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The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review by Uzair Shah (15740699)

“…The study selection process was carried out in three phases: study identification, study selection, and data extraction. …”

Topology and parameter estimation in power systems through inverter-based broadband stimulations by Margossian, Harag

“…Broadband stimulation signals are injected from distributed generators and their effects are measured at various locations in the grid. To process and evaluate this data, a novel aggregation method based on weighed least squares will be proposed in this study. …”
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Benchmark on a large cohort for sleep-wake classification with machine learning techniques by Joao Palotti (8479842)

“…However, the largest experiments conducted to date, have had only hundreds of participants. In this work, we processed the data of the recently published Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study to have both PSG and actigraphy data synchronized. …”

A Hybrid Transfer Learning Approach to Teeth Diagnosis Using Orthopantomogram Radiographs by Alabd-Aljabar, Ahmed

“…This highlights the approach’s effectiveness in improving performance without the need to use a deeper model, making it well-suited for clinical adoption where efficiency is important.…”
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An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems by Abdel-Salam, Mahmoud

“…Feature selection (FS) is the activity of defining the most contributing feature subset among all used features to improve the superiority of datasets with a large number of dimensions by selecting significant features and eliminating redundant and irrelevant ones. Therefore, this process can be seen as an optimization process. The primary goals of feature selection are to decrease the number of dimensions and enhance classification accuracy in many domains, such as text classification, large-scale data analysis, and pattern recognition. …”
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Random vector functional link network: Recent developments, applications, and future directions by A.K. Malik (16003193)

“…Moreover, we discuss the different hyperparameter optimization techniques followed in the literature to improve the generalization performance of the RVFL model. Finally, we present potential future research directions/opportunities that can inspire the researchers to improve the RVFL’s architecture and learning algorithm further. …”

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

“…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 hybrid neuro-fuzzy power system stabilizer for multimachine powersystems by Abido, M.A.

“…The orthogonal least squares (OLS) learning algorithm is developed for designing an adequate and parsimonious FBFN model. …”
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Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations by Md Mosarrof Hossen (21399056)

“…<p>Human behavior significantly impacts domestic energy consumption, making it essential to monitor and improve these consumption patterns. …”

Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles by Wadi, Ali

“…The identified a priori knowledge is used to implement an optimal Kalman filter, a multi-hypothesis Kalman filter, and a variant of the full information estimator (moving horizon estimator) to the problem at hand. The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. …”
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Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea by Issa, Leila

“…Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential ensemble data assimilation framework is challenging due to the exponential growth in the number of particles. …”
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Establishing Autonomous AUS-Quadrotor by Al Younes, Younes

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