Safa Meraghni

TL;DR: Digital twin (DT), as a smart manufacturing technique, is applied in this paper to establish an ensemble remaining useful life prediction system and the predicted results are proved to be less affected even with limited measurement data.

TL;DR: In this paper, the authors presented a computer-aided diagnosis system based on convolutional neural networks as an alternative diagnosis methodology for breast cancer diagnosis with thermal images, which showed that lower false-positives and false-negatives classification rates are obtained when data pre-processing and data augmentation techniques are implemented in these thermal images.

TL;DR: It is demonstrated that a CAD system that implements data-augmentation techniques reach identical performance metrics in comparison with a system that uses a bigger database but without data-AUgmentation, and the influence of data pre-processing, data augmentation and database size on several CAD models is studied.

TL;DR: This paper offers a new architecture to provide Prognostics Health Manager solutions as a service in cloud computing environment (PHM-SaaS, PHM-PaaS), and defined the entities and actors as well as their behavior in this architecture.

TL;DR: A decision post-prognostics framework to help engineers to take the optimal decision for maintenance operation in order to minimize maintenance cost is proposed and a framework based on Iot technology for real-time sensing to collect data from equipment and Cloud computing paradigm for resources management and information processing is proposed.