… a machine learning based situational awareness framework that detects existing and newly
introduced network-enabled entities, utilizing the real-time awareness … situational awareness …

… machine learning classification and ranking, based on the target vehicle’s situational awareness.
… This information is a natural part of the situational awareness exploited by connected …

… major challenges in achieving situational awareness in power … novel model-free situational
awareness framework for power … 1) A novel situational awareness framework is introduced for …

… In this paper, the machine learning model captures the relationship between the mmWave
channel and the situational awareness that is comprised of the geometry of different vehicles …

… pilot’s situational awareness regarding offensive situations, … machine learning algorithms
to generate responses concerning the tactical state to improve the pilot’s situational awareness …

… In this work, we focus on machine learning for noninvasive … Our approach is based on
learning to relate true load in T , in … using a proposed machine learning pipeline for supervised …

… Therefore, using machine learning techniques to automatically extract situational awareness
information is essential. Hence, we employed a CNN model, which is developed based on …

… The situational awareness aims to timely detect the jamming attacks and characterize the
information of the jamming signals for further response. Recently, machine learning (ML) …

… -time situational awareness. We attribute its successful adoption by many first responders
to its user-centered design, interactive (geo)visualizations and interactive machine learning, …

… This paper evaluates various out of the box Machine learning classifier algorithms (RF, DT,
NB, GBM, KNN) to solve for a binary problem to predict whether pilots are experiencing an …