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Media Contacts
![The D2U model categorizes user data by capturing behavior in all open programs throughout a user’s day. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-09/User%20Emulation%20Graphic%20v1_0.jpg?h=8f74817f&itok=kZiQWuZI)
Oak Ridge National Laboratory researchers have created a technology that more realistically emulates user activities to improve cyber testbeds and ultimately prevent cyberattacks.
![An algorithm developed and field-tested by ORNL researchers uses machine learning to maintain homeowners’ preferred temperatures year-round while minimizing energy costs. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-07/2019-P07408_2.jpg?h=8f9cfe54&itok=jBvKdqIv)
Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.
![A new computational approach by ORNL can more quickly scan large-scale satellite images, such as these of Puerto Rico, for more accurate mapping of complex infrastructure like buildings. Credit: Maxar Technologies and Dalton Lunga/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-02/Puerto_Rico_Resflow9.png?h=a0a1befd&itok=5n2fss_e)
A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.
![Heat impact map](/sites/default/files/styles/list_page_thumbnail/public/2019-07/Winter_HDD_Change_ORNL.gif?h=e87b941e&itok=8t83D_u_)
A detailed study by Oak Ridge National Laboratory estimated how much more—or less—energy United States residents might consume by 2050 relative to predicted shifts in seasonal weather patterns