Frontiers

Adaptive graph-theoretic localization of radiation sources via real-time density-aware clustering for IoT

The increasing complexity of Internet of Things and modern battlefield electromagnetic environments poses significant challenges to radiation source localization, especially under electronic ...
snmjournals.org

RadShap: An Explanation Tool for Highlighting the Contributions of Multiple Regions of Interest to the Prediction of Radiomic Models

Journal of Nuclear Medicine June 2024, jnumed.124.267434; DOI: https://doi.org/10.2967/jnumed.124.267434 These aggregative approaches raise an interesting question ...
GitHub

monte-carlo-localization

A ROS node to perform a probabilistic 3-D/6-DOF localization system for mobile robots with 3-D LIDAR(s). It implements pointcloud based Monte Carlo localization that uses a reference pointcloud as a ...
C&EN

Seq-RBPPred: Predicting RNA-Binding Proteins from Sequence

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The sequence-based approach primarily relies on amino acid ...
IEEE

Qinchen Wu

Detection Probability,Target State,Label Space,Motion Model,Standard Filter,Stochastic Differential Equations,Target Group,Transition Density,Computational Complexity ...
PNAS

Anomalous phase separation in a correlated electron system: Machine-learning–enabled large-scale kinetic Monte Carlo simulations

Phase separation is crucial to the functionalities of many correlated electron materials with notable examples including colossal magnetoresistance in manganites and high-T c superconductivity in ...