Graph processing is increasingly popular given the wide range of phenomena represented as graphs (e.g., social media networks, pharmaceutical drug compounds, or fraud networks, among others). The increasing amount of data available requires new approaches to efficiently ingest and process such data...
The complex provider landscape in cloud computing makes incident handling difficult, as Cloud Service Providers (CSPs) with end-user customers do not necessarily get sufficient information about incidents that occur at upstream CSPs. In this paper, we argue the need for commonly agreed-upon incident...
This paper introduced a new deep learning framework for fault diagnosis in electrical power systems. The framework integrates the convolution neural network and different regression models to visually identify which faults have occurred in electric power systems. The approach includes three main...
In the light of rising sea level, scarcity of land-based resources and increasingly populated coastal areas, interest of project developers and countries turns towards the ocean, exploring the possibilities of utilizing this space for various purposes. With the oceans covering roughly 70% of the...
This research presents a new generic deep learning framework for anomaly detection in the Internet of Everything (IoE). It combines decomposition methods, deep neural networks, and evolutionary computation to better detect outliers in IoE environments. The dataset is first decomposed into clusters...