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E-grāmata: Innovations of Intelligent Informatics, Networking, and Cybersecurity: Second International Conference, 3INC 2024, Babylon, Iraq, October 15-16, 2024, Proceedings

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This book constitutes the proceedings of the Second International Conference on Innovations of Intelligent Informatics, Networking and Cybersecurity, 3INC 2024, which took place in Babylon, Iraq, during October 15-16 2024. 





The 15 full papers included in this volume were carefully reviewed and selected from 69 submissions. They were organized in topical sections as follows: Information systems; computing methodologies; and security and privacy.

.- Information System.
.- Localization in WSNs Based On Machine Learning Approach.
.- Improved Clustering-Based Feature Selection Using Feature Extraction Based On Principal Component Analysis.
.- Computing Methodologies.
.- Real-Time Arabic Speech Recognition from Lips Movement Based On Deep Learning.
.- Parkinson's Disease Prediction and Progression Based On Voice Analysis: A Literature Survey.
.- BGWO-Based Classification of Parkinson's Disease Via MEG Signnals.
.- Enhancing Twitter Comment Classification Using Convolutional Neural Networks and Support Vector Machines.
.- High-Stakes Deception Detection Leveraging 3D Facial Landmarks.
.- Enhancement of Low Light Images Using Residual Deep Learning.
.- Hybrid Model for Hospital Services Quality Prediction Based On Patient Viewpoint.
.- Security and privacy.
.- Advanced Text Vectorization and Deep Learning Models for Enhanced Fake News Detection On Social Media.
.- Utilizing Graph Neural Networks for The Detection of Fake News Through Analysis of Relationships Among Various Social Media Entities.
.- Classification of Internet of Things Cybersecurity Attacks Using a Hybrid Deep Learning Approach.
.- Hybrid Multimodal Biometric Identification System: Integrating Face and Palmprint Traits Through Feature-Level Fusion.
.- Improving Machine Learning-Based Intrusion Detection Systems: A Comparative Study On NSL-KDD Dataset.
.- Enhancing Penetration Testing: Leveraging Machine Learning for Ethical Hacking.