Abstract: A system, computer readable medium, and method for analyzing digital content of electronic media files includes presenting control media content to a set of control respondents for consumption and presenting test media content to a set of test respondents for consumption. The method includes receiving first responses to a survey related to topics of the control media content from the set of control respondents and second responses to the survey about the test media content from the set of test respondents. The method includes performing feature extraction on the test media content and performing feature extraction on the first responses and the second responses. The feature extraction obtains response features associated with the first responses and the second responses. The method includes training a regression machine learning model with the media content features and the response features.

Abstract: A system, computer readable medium, and method for analyzing digital content of electronic media files includes presenting control media content to a set of control respondents for consumption and presenting test media content to a set of test respondents for consumption. The method includes receiving first responses to a survey related to topics of the control media content from the set of control respondents and second responses to the survey about the test media content from the set of test respondents. The method includes performing feature extraction on the test media content and performing feature extraction on the first responses and the second responses. The feature extraction obtains response features associated with the first responses and the second responses. The method includes training a regression machine learning model with the media content features and the response features.

Abstract: A system, computer readable medium, and method for analyzing digital content of electronic media files includes presenting control media content to a set of control respondents for consumption and presenting test media content to a set of test respondents for consumption. The method includes receiving first responses to a survey related to topics of the control media content from the set of control respondents and second responses to the survey about the test media content from the set of test respondents. The method includes performing feature extraction on the test media content and performing feature extraction on the first responses and the second responses. The feature extraction obtains response features associated with the first responses and the second responses. The method includes training a regression machine learning model with the media content features and the response features.

Abstract: The method of pre-configuring the optical protect paths in an agile photonic network establishes a protection trail for each optical working path that may be set-up in the network. The pre-configuration is based on building an electrical layer (EXC) graph that takes into account all the connection demands in the network, and finding on this EXC graph a plurality of cycles. Next, the EXC cycles are validated at the optical layer, and are further validated against constraints. The method attempts to find an optimal cycles solution, without exhausting all possible variants.