In the field of engineering systems—particularly in underground drilling and green
stormwater management—real-time predictions are vital for enhancing operational …

Velocity model building is crucial for seismic exploration, yet conventional methods struggle
with complex geological scenarios due to assumptions of horizontal layering. These …

The timely and precise prediction of winter wheat yield plays a critical role in understanding
food supply dynamics and ensuring global food security. In recent years, the application of …

The prevalence of zero values in zero-inflated time-series (ZI-TS) data poses significant
challenges for traditional LSTM networks in learning long-term dependencies and trends …

Personalized gamification seeks to address the limitations of the one-size-fits-all approach,
mostly by tailoring the selection of game elements to individual preferences. However, there …

Student performance prediction was deployed to predict learning performance to identify at-
risk students and provide interventions for them. However, prediction models should also …

Educational data mining (EDM) is a part of applied computing that focuses on automatically
analyzing data from learning contexts. Early prediction for identifying at-risk students is a …

Search and rescue (SAR) is an important part of joint operations and a key support for
combat effectiveness. Because of the complex composition of the SAR system of systems …

The traditional system of attendance requires maintaining an attendance register and
manually noting the attendance of every student. This system is prone to errors and marking …

In actual university education, students' performance prediction is important for assessing
their mastery of specific knowledge areas and providing feedback. To address the limitations …