Removing human bias from predictive modeling

Predictive modeling is supposed to be neutral, a way to help remove personal prejudices from decision-making. But the algorithms are packed with the same biases that are built into the real-world data used to create them. ...

As cloud usage expands, so do security risks

Holding everything from highly personal medical and social media material to confidential financial and corporate documents, Internet-based cloud services are gathering an enormous trove of information - already a quarter ...

Combatting retail fraud using a simulator

Every year the retail industry lose billions of dollars to fraud in the US alone. To complicate the matter research in the field has been obstructed due to the sensitive nature of transactional data. To facilitate future ...

Ice Age testing reveals challenges in climate model sensitivity

Key to the usefulness of climate models as tools for both scientists and policymakers is the models' ability to connect changes in atmospheric greenhouse gas levels to corresponding shifts in temperature. Equilibrium climate ...

Climate sensitivity—reducing the uncertainty of uncertainty

Global warming is a reality – but just how bad will it be? A study published in January 2018 claims to halve the uncertainty around how much our planet's temperature will change in response to rising carbon dioxide (CO2) ...

A sensitization strategy achieves hyperfluorescence

Organic light-emitting diodes (OLEDs) play an important role in new-generation flat-panel displays. For ultra-high-definition displays presented in International Telecommunication Union (ITU) Recommendation BT 2020 standard, ...

page 34 from 40