Abstract: A system and method of determining system status in a vehicle system. The method including collecting, by a computing system, a plurality of data associated with a test specimen and the vehicle system, selecting a relevant data set of the plurality of data, the selecting based on at least one correlation coefficient associated with the plurality of data, and transforming at least a portion of the selected relevant data to form a transformed data set, the transforming based on mathematical properties. The method also includes collecting statistics associated with the selected relevant data set and the transformed data set to form a statistics data set, classifying the selected relevant data set, transformed data set, and the statistics data set; and predicting a status of a system based on the classifying.

Abstract: A system and method of determining system status in a vehicle system. The method including collecting, by a computing system, a plurality of data associated with a test specimen and the vehicle system, selecting a relevant data set of the plurality of data, the selecting based on at least one correlation coefficient associated with the plurality of data, and transforming at least a portion of the selected relevant data to form a transformed data set, the transforming based on mathematical properties. The method also includes collecting statistics associated with the selected relevant data set and the transformed data set to form a statistics data set, classifying the selected relevant data set, transformed data set, and the statistics data set; and predicting a status of a system based on the classifying.

Abstract: A method for analyzing a content delivery network. The method includes obtaining network traffic flows corresponding to user nodes accessing contents from a set of servers of the content delivery network, extracting a timing attribute from each network traffic flow associated with a server, where the timing attribute is aggregated into a timing attribute dataset of the server based on all network traffic flows associated with the server, generating a statistical measure of the timing attribute dataset as a portion of a feature vector representing the server, where the feature vector is aggregated into a set of feature vectors representing the set of servers, analyzing the set of feature vectors based on a clustering algorithm to generate a set of clusters, and generating, based on the set of clusters, a representation of server groups in the content delivery network.