A Fuzzy Low-Dimensional Intersection Graph Representation Approach for Graph Compression and Anonymization حسب Yamout, Youssef

"…The large amount of data represented as a network, or graph, sometimes exceeds the resources of a conventional computing device. …"
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Degree-Based Network Anonymization حسب Halawi, Ola

"…Our thorough experimental studies provide empirical evidence of the effectiveness of the new approach; by specifically showing that the introduced anonymization algorithm has a negligible effect on the way nodes are clustered, thereby preserving valuable network information while significantly improving the data privacy.…"
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Reinforcement Learning for Resilient Aerial-IRS Assisted Wireless Communications Networks in the Presence of Multiple Jammers حسب Zain Ul Abideen Tariq (17984107)

"…Experimental results demonstrate the effectiveness of our proposed DDPG-based approach in outperforming other RL algorithms. …"

Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations حسب Md Mosarrof Hossen (21399056)

"…To address this challenge, this study aims to optimize household energy consumption while preserving data privacy by proposing an innovative two-stage Federated Learning (FL) framework that delivers real-time micro-moment-based recommendations. …"

A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011) حسب Kozhaya, David Elias

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Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends حسب Abdellatif M. Sadeq (16931841)

"…<p dir="ltr">Studying the spatial and temporal evolution in turbulent flames represents one of the most challenging problems in the combustion community. Based on previous 3D numerical analyses, this study aims to develop data-driven machine learning (ML) models for predicting the flame radius evolution and turbulent flame speeds for diesel, gas-to-liquids (GTL), and their 50/50 blend (by volumetric composition) under different thermodynamic and turbulence operating conditions. …"

Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques حسب Hassan, Mahitab Alaaeldin

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An Adapted Load-Balancing implementation for Sharded Blockchains حسب Daou, David Halim

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Hybridizing rule-based power system stabilizers with geneticalgorithms حسب Abido, M.A.

"…The proposed approach uses genetic algorithms (GA) to search for optimal settings of rule-based power system stabilizer (RBPSS) parameters. …"
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Edge intelligence for network intrusion prevention in IoT ecosystem حسب Mansura, Habiba

"…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …"
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Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering حسب Saadia Jamil (22045946)

"…A self-organizing map is one of the well-known unsupervised neural network algorithms used for preserving typologies during mapping from the input space (high-dimensional) to the display (low-dimensional).An algorithm called Local Adaptive Receptive Field Dimension Selective Self-Organizing Map 2 is a modified form of a self-organizing Map to cater different data types in the dataset. …"

Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review حسب Asma Alamgir (18288895)

"…Machine learning models were the most prominent branch of AI used in the prediction of cardiac arrest in the studies (38/47, 81%), and the most used algorithm was the neural network (23/47, 49%). …"

Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers حسب Hamidreza Besharatifard (16904823)

"…<p dir="ltr">This paper addresses the localization of Partial Discharge through a 3D Finite Element Method analysis of acoustic wave propagation inside a 3-phase 35kV transformer with the help of COMSOL Multiphysics software. …"

Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks حسب Mohammed Almehdhar (22046597)

"…This survey paper offers an in-depth examination of advanced machine learning (ML) and deep learning (DL) approaches employed in developing sophisticated IDS for safeguarding IVNs against potential cyber-attacks. …"

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

"…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. …"

Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach حسب Mohammad Taghi Dabiri (16904658)

"…Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …"

The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions حسب Abdulmalik Alwarafy (17984104)

"…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …"

Random vector functional link network: Recent developments, applications, and future directions حسب A.K. Malik (16003193)

"…Generally, the back propagation (BP) based iterative approaches are used to train the neural networks, however, it results in the issues of local minima, sensitivity to learning rate and slow convergence. …"

Digital Image Watermarking Using Balanced Multiwavelets حسب Ghouti, L.

"…In this paper, a robust watermarking algorithm using balanced multiwavelet transform is proposed. …"
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Edge intelligence for network intrusion prevention in IoT ecosystem حسب Mansura Habiba (17808302)

"…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …"