Novel deep learning-enabled LSTM autoencoder architecture for discovering anomalous events from intelligent transportation systems

J Ashraf, AD Bakhshi, N Moustafa… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITS), especially Autonomous Vehicles (AVs), are
vulnerable to security and safety issues that threaten the lives of the people. Unlike manual …

Diagnostics and prognostics for complex systems: A review of methods and challenges

M Soleimani, F Campean… - Quality and Reliability …, 2021 - Wiley Online Library
Diagnostics and prognostics have a significant role in the reliability enhancement of systems
and are focused topics of active research. Engineered systems are becoming more complex …

IoTBoT-IDS: A novel statistical learning-enabled botnet detection framework for protecting networks of smart cities

J Ashraf, M Keshk, N Moustafa, M Abdel-Basset… - Sustainable Cities and …, 2021 - Elsevier
The rapid proliferation of the Internet of Things (IoT) systems, has enabled transforming
urban areas into smart cities. Smart cities' paradigm has resulted in improved quality of life …

Real-time monitoring and control of industrial cyberphysical systems: With integrated plant-wide monitoring and control framework

S Yin, JJ Rodriguez-Andina… - IEEE Industrial Electronics …, 2019 - ieeexplore.ieee.org
This article is focused on the realtime monitoring and control aspects of ICPSs. Advanced
approaches and potential challenges are illustrated in the following sections. Especially, an …

An enhanced multi-stage deep learning framework for detecting malicious activities from autonomous vehicles

IA Khan, N Moustafa, D Pi, W Haider… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITS), particularly Autonomous Vehicles (AVs), are
susceptible to safety and security concerns that impend people's lives. Nothing like manually …

Nonparametric bayesian framework for material and process optimization with nanocomposite fused filament fabrication

J Liu, J Ye, F Momin, X Zhang, A Li - Additive Manufacturing, 2022 - Elsevier
The convergence of polymer nanocomposite development and additive manufacturing
creates unprecedented opportunities for advancing novel materials design and product …

Machine learning augmented X-ray computed tomography features for volumetric defect classification in laser beam powder bed fusion

J Ye, A Poudel, J Liu, A Vinel, D Silva, S Shao… - … International Journal of …, 2023 - Springer
This study proposes a data-driven framework to augment low-resolution X-ray computed
tomography (LR-XCT) scanning with machine learning (ML) for efficient defect inspection …

FGMC-HADS: Fuzzy Gaussian mixture-based correntropy models for detecting zero-day attacks from linux systems

W Haider, N Moustafa, M Keshk, A Fernandez… - Computers & …, 2020 - Elsevier
As existing system calls-based Host Anomaly Detection Systems (HADSs) exclude hidden
patterns that can reside in the elapsed times of system calls with respect to the lifecycle of a …

Identifying unseen faults for smart buildings by incorporating expert knowledge with data

D Li, Y Zhou, G Hu, CJ Spanos - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Thanks to the development of sensor networks and information technology, data-driven fault
detection and diagnosis (FDD) is getting more and more popular with rich data. In the …

A Gaussian process model-guided surface polishing process in additive manufacturing

S **, A Iquebal… - Journal of …, 2020 - asmedigitalcollection.asme.org
Polishing of additively manufactured products is a multi-stage process, and a different
combination of polishing pad and process parameters is employed at each stage. Pad …