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Adaptive learning systems require effective mechanisms to model students’ evolving learning states and provide personalized learning path recommendations. Traditional rule-based approaches are limited in capturing...

Heart disease is rapidly increasing. For early and accurate prediction, advanced machine learning (ML) models are needed. However, the sensitive nature of clinical data, along with strict regulatory constraints, creates ...

Efficient UAV path planning in large and dynamic environments requires adaptive strategies that account for varying regional importance. Traditional coverage or Reinforcement Learning-based methods often suffer from redu...

Forest growth and yield projection is essential for sustainable forest management planning. In Brazil, the Clutter model is widely applied for yield forecasting and commonly achieves prediction errors below 10%. However,...

Measurements from global navigation satellite system reflectometry (GNSS-R) have proven effective for applications in sea surface height (SSH). Deep learning-based methods for spaceborne GNSS-R SSH retrieval can effectiv...

Cybersecurity education often struggles to engage learners while effectively conveying complex web vulnerabilities. This challenge is particularly evident in topics such as cross-site scripting (XSS), where understanding...

Wildfires are among the most destructive natural disasters and pose significant risks to ecosystems, infrastructure, and human lives. This study focuses on wildfire susceptibility mapping in Los Angeles County, a region ...

Extensive research has demonstrated that music enhances cognitive functions, such as learning, reasoning, and memory. This study investigated the influence of music on short- and long-term memory while learning through t...