The Intrusion Detection System (IDS) is an effective tool utilized in cybersecurity systems to
detect and identify intrusion attacks. With the increasing volume of data generation, the …

In order to provide an accurate and timely response to different types of the attacks, intrusion
and anomaly detection systems collect and analyze a lot of data that may include personal …

The Internet of Drones (IoD) is built on the Internet of Things (IoT) by replacing “Things” with
“Drones” while retaining incomparable features. Because of its vital applications, IoD …

MicroRNAs (miRNA) play critical roles in diverse biological processes of diseases. Inferring
potential disease-miRNA associations enable us to better understand the development and …

Due to the extremely limited prior knowledge, machinery fault diagnosis under varying
working conditions with limited annotation data is a very challenging task in practical …

Activity and property prediction models are the central workhorses in drug discovery and
materials sciences, but currently, they have to be trained or fine-tuned for new tasks. Without …

Contrastive learning has achieved remarkable success in representation learning via self-
supervision in unsupervised settings. However, effectively adapting contrastive learning to …

Extracting generalized and robust representations is a major challenge in emotion
recognition in conversations (ERC). To address this, we propose a supervised adversarial …

The combination of class imbalance and overlap is currently one of the most challenging
issues in machine learning. While seminal work focused on establishing class overlap as a …

Security has been a concern in recent years, especially in the Internet of Things (IoT) system
environment, where security and privacy are of great importance. Our lives have significantly …