Purpose With the in-depth application of machine learning (ML) in clinical practice, it has
been used to predict the mortality risk in patients with traumatic brain injuries (TBI). However …

Photosynthesis is a key process linking carbon and water cycles, and satellite-retrieved
solar-induced chlorophyll fluorescence (SIF) can be a valuable proxy for photosynthesis …

Simulation platforms facilitate the development of emerging Cyber-Physical Systems (CPS)
like self-driving cars (SDC) because they are more efficient and less dangerous than field …

Unmanned Aerial Vehicles (UAVs) are nowadays used in a variety of applications. Given the
cyber-physical nature of UAVs, software defects in these systems can cause issues with …

Learning Analytics aims to discover the class of students' performance over time. This helps
instructors make in-time interventions but, discovering the students' performance class in …

Adaptive learning is an approach toward personalized learning and places the concept of
“learner-centered education” into practice. With the rapid development of artificial …

Adaptive learning is an approach toward personalized learning and places the concept of
“learner-centered education” into practice. With the rapid development of artificial …

Accurate assessment of aboveground biomass (AGB) in tropical forests, particularly within a
biodiversity hotspot, is vital for sustainable resource management and the preservation of …

Objective Open surgical treatment options for aortoiliac occlusive disease carry significant
perioperative risks; however, outcome prediction tools remain limited. Using machine …

This study aims to improve the understanding of geomagnetic storms by utilizing machine
learning models and analyzing several heliophysical variables, such as the interplanetary …