Anomaly Detection is an unsupervised learning task aimed at detecting anomalous
behaviors with respect to historical data. In particular, multivariate Anomaly Detection has an …

The monitoring of rotating machinery is an essential task in today's production processes.
Currently, several machine learning and deep learning-based modules have achieved …

Abstract The Internet of Behaviour (IoB) is an effort to dissect behavioural patterns as
explained by data collection. IoB is an extension of the Internet of Things (IoT). Therefore …

Globally, cervical cancer remains as the foremost prevailing cancer in females. Hence, it is
necessary to distinguish the importance of risk factors of cervical cancer to classify potential …

Abstract Data-driven Anomaly Detection approaches have received increasing attention in
many application areas in the past few years as a tool to monitor complex systems in …

In the past recent years, Machine Learning methodologies have been applied in countless
application areas. In particular, they play a key role in enabling Industry 4.0. However, one of …

Development of communication technologies and e-commerce has made the credit card as
the most common technique of payment for both online and regular purchases. So, security …

Abstract Machine Learning (ML) has been categorized as a branch of Artificial Intelligence
(AI) under the Computer Science domain wherein programmable machines imitate human …

In this article, we review recently proposed, advanced methods, for the control of blood
glucose levels, in patients with type 1 diabetes. The proposed methods are based on …

Anomaly detection is an important field in data science that has been widely researched and
applied, generating many methods. Among these methods, the isolation forest algorithm is …