Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

“…The main novelty of this work is the computer-aided diagnosis scheme for detecting abnormalities in breast ultrasound images by integrating a wavelet neural network (WNN) and the grey wolf optimization (GWO) algorithm. Here, breast ultrasound (US) images are preprocessed with a sigmoid filter followed by interference-based despeckling and then by anisotropic diffusion. …”

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”

The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

Interval-Valued Reduced Ensemble Learning Based Fault Detection and Diagnosis Techniques for Uncertain Grid-Connected PV Systems by Khaled Dhibi (16891524)

Binary B-Hill Climbing Optimizer with S-shape Transfer Function for Feature Selection by Abou Doush, Iyad

“…In this paper, a β β -hill climbing optimizer is applied to solve the feature selection problem. β β -hill climbing is recently introduced as a local-search based algorithm that can obtain pleasing solutions for different optimization problems. …”
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Nonlinear clustering optimization for scalable data mining in cloud and quantum computing environments by Manjula, S.

“…The approach combines the dynamical systems analysis, PDE-based manifold models and quantum optimization mappings (QUBO/Ising), which ensure the theoretical soundness of the approach; specifically, the approach is coercive, has minimizers, and block-coordinate convergence guarantees. …”
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An Incentivized and Optimized Dynamic Mechanism for Demand Response for Managing Voltage in Distribution Networks by Md Moktadir Rahman (16904751)

“…An improved hybrid particle swarm optimization algorithm (IHPSO) is proposed for the load controller to provide fast convergence and robust optimization results. …”

A modified optimal design of a vibration absorber for ground motion isolation by Issa, Jimmy S.

“…The first is based on the genetic algorithm technique and the second on the downhill simplex method. …”
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Optimal location and sizing of renewable distributed generations and electric vehicle charging stations by Guindi, Marina

“…The study introduces several constraints, including the placement of EVCSs and RDGs at separate buses, and employs particle swarm optimization and cuckoo search algorithm to simultaneously determine the optimal locations and sizes of the RDGs and the optimal locations of the EVCSs. …”
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Hybrid quantum–cloud framework for nonlinear clustering optimization and intelligent resource management by Abdullayev, Ilyos

“…These weaknesses will be mitigated by the proposed framework that will integrate quantum-inspired algorithms (which will operate on variational quantum circuits and Quantum Approximate Optimization Algorithm (QAOA)) with cloud-native orchestration solutions, only that reinforcement learning-based scheduling will be integrated. …”
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Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review by Mohamed Sadok Massaoudi (17984071)

“…<p dir="ltr">The widespread penetration of inverter-based resources has profoundly impacted the electrical stability of power systems (PSs). …”

Assessment of Inventory and Transportation Collaboration in a Logistics Marketplace by Shahid, Saif Mohammad

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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

“…This study offers a thorough examination of how AI can be utilized to enhance e-learning results by employing advanced predictive methods and performance optimization strategies. The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”

Opportunistic Throughput Optimization in Energy Harvesting Dynamic Spectrum Sharing Wireless Networks by Amirhossein Taherpour (19273879)

“…Furthermore, we propose two algorithms designed to achieve optimal throughput for each scenario. …”

Learning-Based Automatic Modulation Classification by Abdelmutalab, Ameen Elsiddig

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Particle swarm optimization approach for protein structure prediction in the 3D HP model by Mansour, Nashat

“…In this paper, we present a particle swarm optimization (PSO) based algorithm for predicting protein structures in the 3D hydrophobic polar model. …”
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LOCATING DAMAGES IN THIN ALUMINIUM PLATES USING LAMB WAVES AND AGENETIC OPTIMIZATION APPROACH by A. Masurkar, Faeez

“…A new damage localization method based on Lamb waves is presented here for thin aluminium (Al) plate specimens using a Genetic optimization (GO) approach. …”
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Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks by Mohamed Massaoudi (16888710)

“…<p dir="ltr">The transient power grid stability is greatly affected by the unpredictability of inverter-based resources of today's interconnected power grids. …”

The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability by Abd-El-barr, Mostafa

“…In this paper, we propose one algorithm for optimizing the terminal reliability and another for optimizing the network reliability while improving the fault tolerance aspects of the designed networks. …”
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Enhanced Microgrid Reliability Through Optimal Battery Energy Storage System Type and Sizing by Mohammadreza Gholami (17032317)

“…To determine the optimized size, a firefly optimization algorithm is used as an efficient meta-heuristic approach. …”