… 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 …

… of situational awareness information to future autonomous vessels. This data can also be
used for training the machine learning … of realtime situational awareness provided by the on-…

… Text mining solutions using traditional machine learning … two traditional machine learning
methods: support vector machine (… to classify for an upcoming event for situational awareness. …

… of machine learning algorithms has gradually expanded, and a variety of machine learning
… extent, ATHM et al. used machine learning algorithm for systematic analysis and prediction …

… does not provide sufficient information for situation awareness. Hence, the detection of …
situation awareness. To address these limitations, this study proposed a hybrid machine learning …

… attack data information through machine learning algorithms can effectively improve the
accuracy of network attack intrusion detection. [6] trained a support vector machine (SVM) to …

… Learning-based and lexicon-based methods are two main approaches for sentiment analysis
[41]. The first approach uses machine learning classifiers when there is prior knowledge …

… Machine learning (ML) methods are fundamental to the philosophy of artificial intelligence
(AI… The basis of the integration of lowlevel analysis for AI/ML towards SDF situation awareness …

Situation awareness (SA) is an important constituent in human information processing and
essential in pilots' decision making processes. Acquiring and maintaining appropriate levels …