In the evolving landscape of cyber threats, phishing attacks pose significant challenges, particularly through deceptive webpages designed to extract sensitive information under the guise of legitimacy. Conventional and machine learning (ML)-based detection systems struggle to detect phishing...

In the burgeoning field of anomaly detection within attributed networks, traditional methodologies often encounter the intricacies of network complexity, particularly in capturing nonlinearity and sparsity. This study introduces an innovative approach that synergizes the strengths of graph...

Although generative conversational artificial intelligence (AI) can answer questions well and hold conversations as a person, the semantic ambiguity inherent in text-based communication poses challenges to effective use. Effective use reflects the users' utilization of generative conversational...

In the health field, longitudinal studies involve the recording of clinical observations of the same sample of patients over successive periods, referred to as waves. This type of database serves as a valuable source of information and insights, particularly when examining the temporal aspect,...

Skin cancer is the abnormal development of cells on the surface of the skin and is one of the most fatal diseases in humans. It usually appears in locations that are exposed to the sun, but can also appear in areas that are not regularly exposed to the sun. Due to the striking similarities...

Anomaly detection is an important research area in a diverse range of real-world applications. Although many algorithms have been proposed to address anomaly detection for numerical datasets, categorical and mixed datasets remain a significant challenge, primarily because a natural distance...

This study introduces an advanced recommender system for technology enhanced learning (TEL) that synergizes neural collaborative filtering, sentiment analysis, and an adaptive learning rate to address the limitations of traditional TEL systems. Recognizing the critical gap in existing...

Industrial robot application (IRA) provides an opportunity for the low-carbon development of trade. This study focuses on the green revolution of manufacturing export trade, analyzes the mechanism by which IRA affects CO2 emissions embodied in manufacturing exports (CIE), and conducts an...

The primary motivation for this study is the recent growth and increased interest in artificial intelligence (AI). Despite the widespread recognition of its critical importance, a discernible scientific gap persists within the extant scholarly discourse, particularly concerning exhaustive...

Public-and private-sector organizations have adopted artificial intelligence (AI) to meet the challenges of the Fourth Industrial Revolution. The successful implementation of AI is a challenging task, and previous research has advocated the need to explore key readiness before AI implementation....