This repository contains the source code, scripts, and supplementary materials for the paper: "A New Hybrid Model for Improving Outlier Detection Using Combined Autoencoder and Variational Autoencoder ...

IC manufacturers are increasingly relying on intelligent data processing to prevent downtime, improve yields, and reduce scrap. They are integrating that with fault detection and classification (FDC) ...

The method inputs Doppler observations, satellite positions (from ephemeris), elevation angles, azimuth angles, and C/N₀ values. It groups potential multipath/NLOS faults using elevation, azimuth ...

Abstract: Outlier detection (OD) plays an important role in areas such as fraud detection, network security, and so on. In addition, traditional OD methods were limited to detecting a single type of ...

Abstract: In today's digital era cybersecurity landscape, endpoint security remains a critical concern due to the increasing sophistication of cyber threats. This study explores anomaly detection ...

ABSTRACT: In recent decades, the impact of climate change on natural resources has increased. However, the main challenges associated with the collection of meteorological data include the presence of ...

Laboratoire de Matériaux et Environnement (LAME), Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso. In recent decades, the impact of climate change on natural resources has increased. However, ...

The ability to build custom tools is critical for building customizable AI Agents. In this tutorial, we demonstrate how to create a powerful and intelligent data analysis tool using Python that can be ...

This project is a web interface for an outlier detection conducted on network traffic data with global and local detection methods.