DARPA Grand ChallengeThe DARPA Grand Challenge is a prize competition for American autonomous vehicles, funded by the Defense Advanced Research Projects Agency, the most prominent research organization of the United States Department of Defense. Congress has authorized DARPA to award cash prizes to further DARPA's mission to sponsor revolutionary, high-payoff research that bridges the gap between fundamental discoveries and military use.
Optical transport networkAn optical transport network (OTN) is a digital wrapper that encapsulates frames of data, to allow multiple data sources to be sent on the same channel. This creates an optical virtual private network for each client signal. ITU-T defines an optical transport network as a set of optical network elements (ONE) connected by optical fiber links, able to provide functionality of transport, multiplexing, switching, management, supervision and survivability of optical channels carrying client signals.
Charter of Fundamental Rights of the European UnionThe Charter of Fundamental Rights of the European Union (CFR) enshrines certain political, social, and economic rights for European Union (EU) citizens and residents into EU law. It was drafted by the European Convention and solemnly proclaimed on 7 December 2000 by the European Parliament, the Council of Ministers and the European Commission. However, its then legal status was uncertain and it did not have full legal effect until the entry into force of the Treaty of Lisbon on 1 December 2009.
Factor analysisFactor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, it is possible that variations in six observed variables mainly reflect the variations in two unobserved (underlying) variables. Factor analysis searches for such joint variations in response to unobserved latent variables.
Linear discriminant analysisLinear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics and other fields, to find a linear combination of features that characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.