Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

“…<p dir="ltr">The present study evaluates the effect of co-digestion of agricultural solid wastes (ASWs), cow manure (CM), and the application of chemical pre-treatment with NaHCO₃ on the performance of anaerobic digestion (AD) process. An Artificial neural network (ANN) algorithm was developed to model and optimize the cumulative methane production (CMP) from ASWs, CM, and their mixture under mesophilic and thermophilic conditions. …”

Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function by Boukas, EK

“…The performance is calculated first and an LMI-based algorithm is developed to design a state feedback control law with constant gain matrices which robustly stabilizes the system in the mean-square quadratically stable sense.…”
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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

“…The performance is calculated first and an LMI-based algorithm is developed to design a state feedback control law with constant gain matrices which robustly stabilizes the system in the mean-square quadratically stable sense.…”
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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

“…The performance is calculated first and an LMI-based algorithm is developed to design a state feedback control law with constant gain matrices which robustly stabilizes the system in the mean-square quadratically stable sense.…”
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Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR) by Elaine Beller (44602)

“…Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. …”

MoveSchedule by Zouein, Pierette

“…MoveSchedule is validated using realistic project data and its solution is qualitatively assessed by an experienced engineer on that project.…”
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Framework for rapid design and optimisation of immersive battery cooling system by Ali Almshahy (23544823)

“…A conjugate heat transfer model for a 3S2P pouch cell module (20 Ah LiFePO₄) is developed and validated against experimental data (< 2% error). The CFD model of a battery module is developed to train an ultra-fast metamodel for battery geometry optimisation. …”

Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review by Ruba Sulaiman (17734065)

“…Once the studies that meet the inclusion criteria were identified, data from these studies were retrieved and were further examined. 17 parameters relevant to TAVI outcomes were carefully identified for assessing the quality of the included studies. …”

Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks by Javed Butt , Usman

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Particle swarm optimization for multimachine power systemstabilizer design by Abido, A.A.

“…In this paper, a novel evolutionary algorithm based approach to optimal design of multimachine power system stabilizers (PSSs) is proposed. …”
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A fuzzy basis function network for generator excitation control by Abido, M.A.

“…The orthogonal least squares learning algorithm is developed for designing an adequate and parsimonious FBFN model. …”
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Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…Accordingly, a dataset containg 258 data points was extracted from the DFT method to use in machine learning method. …”

Adaptive Video Streaming Over Cognitive Radio Networks by Mohamed, Ala Eldin Omer

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A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity by Abdullah Al Siam (22304047)

“…We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. …”

Analysis of power system stability enhancement via excitation and FACTS-based stabilizers by Abido, M. A.

“…An eigenvalue-based objective function to increase the system damping and improve the system response is developed. Then, a real-coded genetic algorithm is employed to search for optimal controller parameters. …”
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CEAP by Abdel Wahab, Omar

“…The first challenge is related to the highly mobile nature of vehicles that complicates the processes of monitoring, buffering, and analyzing observations on these vehicles as they are continuously moving and changing their locations. …”
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Empowering IoT Resilience: Hybrid Deep Learning Techniques for Enhanced Security by Muhammad Maaz (5600600)

“…The aim is to demonstrate the robustness of the proposed algorithms in effectively identifying telnet, password, distributed denial of service (DDoS), injection, and backdoor vulnerabilities in IoT ecosystems. …”

Thermodynamic Analysis and Optimization of Densely-Packed Receiver Assembly Components in High-Concentration CPVT Solar Collectors by Sharaf, Omar Z.

“…Thermodynamic component-level analyses that avoid oversimplified as well as computationally-expensive modeling approaches and provide clear and robust simulation algorithms with reasonable accuracy are separately developed for the three addressed components. …”
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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)

“…This approach is necessary for understanding and replicating best practices in urban management and smart city development. 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. …”

Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges by Muhammad Mohsin Khan (22303366)

“…Still, challenges in adversarial attacks, algorithmic bias, and variable regulatory frameworks remain strong. …”