The adoption of machine learning (ML) and, more specifically, deep learning (DL)
applications into all major areas of our lives is underway. The development of trustworthy AI …

Machine learning (ML) technologies have become substantial in practically all aspects of
our society, and data quality (DQ) is critical for the performance, fairness, robustness, safety …

The rapid development of Internet of Things (IoT) networks has revealed multiple security
issues. On the other hand, machine learning (ML) has proven its efficiency in building …

The escalating complexity of cyber threats, coupled with the rapid evolution of digital
landscapes, poses significant challenges to traditional cybersecurity mechanisms. This …

In medical research, the rapid proliferation of condition-specific studies has led to an
information overload, making it challenging for researchers and practitioners to stay abreast …

This paper introduces a novel and cost-effective method for detecting adulterated diesel,
specifically targeting contamination with kerosene, by leveraging machine learning and the …

Nowadays, Internet-driven culture securing computer networks in Higher Learning
Institutions (HLIs) has become a major responsibility. Intrusion Detection Systems (IDS) are …

Data has become paramount in modern agriculture industry, empowering precision farming
practices, optimizing resource utilization, facilitating predictive analytics, and driving …

Machine learning (ML) technologies have become substantial in practically all aspects of
our society, and data quality (DQ) is critical for the performance, fairness, robustness, safety …

Advanced Persistent Threats (APTs) pose a significant security risk to organizations and
industries. These attacks often lead to severe data breaches and compromise the system for …