Abstract: Electroluminescence (EL) imaging is the most widely used diagnostic technique for identifying flaws at every stage of the production, installation, and operation of solar modules. This ...

Social media and algorithmic recommendations aren’t just reflecting our divisions — they’re driving them. According to a poll conducted by Siena University and The New York Times, “most voters think ...

Institute for Information Systems (WIN), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Introduction: The analysis of discrete sequential data, such as event logs and customer ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

Reaction to Morgan Wallen's new I'm the Problem album came immediately upon its release, with a few fans already declaring it the album of the summer — or even the album of the year. In other cases, ...

As organizations evolve, traditional data classification—typically designed for regulatory, finance or customer data—is being stretched to accommodate employee data. While classification processes and ...

Abstract: Effective disaster prediction is essential for disaster management and mitigation. This study addresses a multi-classification problem and proposes the Neural-XGBoost disaster prediction ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.

ABSTRACT: Mood and anxiety disorders are relatively common during pregnancy and postpartum. If these go unrecognized and untreated, a host of adverse outcomes can occur. Herein, we propose an approach ...