Genetic and heuristic algorithms for regrouping service sites. (c2000) حسب Tabbara, Hiba

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Defense against adversarial attacks: robust and efficient compressed optimized neural networks حسب Insaf Kraidia (19198012)

"…A cumulative updating loss function was employed for overall optimization, demonstrating remarkable superiority over traditional optimization techniques. …"

Cortical EEG Source Localization of Focal Epilepsy حسب Siyam, Wisal Elfatih Mohamed

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Autonomous Robot Navigation Based On Recurrent Neural Networks حسب Al-Sagban, Mariam Qusai

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

"…A fault tolerant network is able to function even in the presence of some faults in the network. …"
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Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network حسب 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. …"

Decision-level fusion for single-view gait recognition with various carrying and clothing conditions حسب Al-Tayyan, Amer

"…Gait samples are fed into the MPCA and MPCALDA algorithms using a novel tensor-based form of the gait images. …"
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Decision-level Gait Fusion for Human Identification at a Distance حسب Al-Tayyan, Amer

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Large language models for code completion: A systematic literature review حسب Rasha Ahmad Husein (19744756)

"…This is achieved by predicting subsequent tokens, such as keywords, variable names, types, function names, operators, and more. Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …"

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins حسب Samir Brahim, Belhaouari

"…ObjectiveThis study utilized various classical machine learning techniques, such as support vector machines, k-nearest neighbors, and random forests, in conjunction with a modified deep learning approach called DeepRaman. These algorithms were employed to distinguish and categorize bacterial endotoxins, following appropriate spectral pre-processing, which involved novel filtering techniques and advanced feature extraction methods. …"
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