Browse Articles

The authors looked at the ability to detect heart disease before the onset of severe clinical symptoms.

The authors looked at the ability of different machine learning algorithms to predict the level of financial corruption in different countries.

The authors used machine learning to predict the presence of anxiety and burnout in students based on facial expressions and demographic information.

The authors looked at different ways to build computational resources that would analyze shooting form for basketball players.

Improving the classifier of the difficulty level of Sudoku.

The authors developed and tested machine learning methods to diagnose tuberculosis from pulmonary X-ray scans.

This study examined the impact of erosion on the performance of a triangular aerofoil at a low Reynolds number (Re = 10,000), relevant for harsh conditions like those on Mars.

Depression affects millions globally, yet identifying symptoms remains challenging. This study explored detecting depression-related patterns in social media texts using natural language processing and machine learning algorithms, including decision trees and random forests. Our findings suggest that analyzing online text activity can serve as a viable method for screening mental disorders, potentially improving diagnosis accuracy by incorporating both physical and psychological indicators.

Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.

Dust accumulation on solar panels can reduce electricity output by 20–50%, posing a major challenge for solar energy collection. Instead of altering panel design, we explored a simpler approach by modifying surface energy through nanotexturing, predicting that hydrophobic surfaces would repel both water and dust. This study found that treating glass and silicone surfaces with potassium hydroxide (KOH) for 13 and 10 minutes, respectively, created optimal nanotextures (445 nm for glass, 205 nm for silicone), significantly reducing dirt accumulation and improving solar energy capture.