First large-scale genomic prediction in the honey bee

no code implementations • 15 Jun 2022 • Richard Bernstein, Manuel Du, Zhipei G. Du, Anja S. Strauss, Andreas Hoppe, Kaspar Bienefeld

For the application of genomic selection in honey bees, this study analyses the predictive ability and bias of pedigree-based and genomic breeding values for honey yield, three workability traits and two traits for resistance against the parasite Varroa destructor.

Automatic Detection and Compression for Passive Acoustic Monitoring of the African Forest Elephant

no code implementations • 25 Feb 2019 • Johan Bjorck, Brendan H. Rappazzo, Di Chen, Richard Bernstein, Peter H. Wrege, Carla P. Gomes

In this work, we consider applying machine learning to the analysis and compression of audio signals in the context of monitoring elephants in sub-Saharan Africa.

Audio Compression

Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery

1 code implementation • 3 Oct 2016 • Yexiang Xue, Junwen Bai, Ronan Le Bras, Brendan Rappazzo, Richard Bernstein, Johan Bjorck, Liane Longpre, Santosh K. Suram, Robert B. van Dover, John Gregoire, Carla P. Gomes

A key problem in materials discovery, the phase map identification problem, involves the determination of the crystal phase diagram from the materials' composition and structural characterization data.

Vocal Bursts Intensity Prediction