A time-domain algorithm for the analysis of second-harmonicgeneration in nonlinear optical structures by Alsunaidi, M.A.

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YOLO-DefXpert: An Advanced Defect Detection on PCB Surfaces Using Improved YOLOv11 Algorithm by Prabu Selvam (22330264)

“…Second, the standard convolutional operations are replaced with Deformable Convolutional Networksv2 (DCNv2) in the neck section to improve robustness in identifying multi-scale defects. …”

Robust Variable Structure Control Approach of Two Series-Connected Five-Phase PMSMs Under Healthy and Faulty Operation Modes by Ali Ajmi (17983771)

L₂min^2/2s: Efficient Linear Reconstruction Filter for Incremental Delta-Sigma ADCs by Bo Wang (86769)

Second-order conic programming for data envelopment analysis models by Mourad, Nahia

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Hardening the ElGamal Cryptosystem in the Setting of the Second Group of Units by ElKassar, AbdulNasser

“…In this paper, we consider yet another extension to the Elgamal cryptosystem employing the second group of units of Zn and the second group of units of Z2[x]/<h(x)>, where h(x) is an irreducible polynomial. …”
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Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks by S. N. V. Bramareswara Rao (21768302)

“…Nowadays, deep learning algorithms are essential for ensuring the reliable, safe, and efficient operation of these complex energy systems. …”

A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

“…The evaluation criteria used in the algorithms of different neural network types and how they play a large role in the highly accurate classification of Arabic texts are discussed. …”
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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem by Denis Alicic (23073484)

“…We propose a twofold contribution: first, an adaptive greedy algorithm that generates high-quality initial solutions, achieving markedly better results than traditional constructive heuristics at comparable computational costs; and second, the adaptation of the Matheuristic Fixed Set Search (MFSS) to the TSCFLP. …”

Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

Soft Sensor for NOx Emission using Dynamical Neural Network by Shakil, M.

“…Lag space for the model is found by using genetic algorithm to find the best time delayed model. Lag space obtained from the linear model is then used for constriction of the dynamical neural network. …”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm by Ahmed, Khidir Galal Eldin Khidir

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A new genetic algorithm approach for unit commitment by Mantawy, A.H.

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A genetic algorithm approach for regrouping service sites by Mansour, Nashat

“…In the first phase, the graph is decomposed into the required number of subgraphs (regions) using a tuned hybrid genetic algorithm. The second phase finds a suitable center within each region by using a heuristic algorithm. …”
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Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks by Hassan, Yasmin Adel

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Tensile Test Optimization Using the Design of Experiment and Soft Computing by Mehdi Moayyedian (14880358)

Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers by Yousef, Hibba

“…Type II diabetes mellitus (T2DM) is a rising global health burden due to its rapidly increasing prevalence worldwide, and can result in serious complications. …”
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Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

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Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk by Mohamed Chaouch (17983846)

“…Receiver Operating Characteristic (ROC) analysis shows superior Area Under the Curve (AUC) for the offline classifier but at a significant computational cost. A second study on larger database of credit scoring confirms these findings, showing that the online classifier achieves an F1-score of 96.40% and an accuracy of 93.08%, closely matching the performance of neural networks (96.46%, 93.22%) and boosting (96.51%, 93.31%). …”