Abstract: Data on a user interacting with a media presentation is collected at a client device. The data includes facial image data of the user. The facial image data is analyzed to extract cognitive state content of the user. One or more emotional intensity metrics are generated. The metrics are based on the cognitive state content. The media presentation is manipulated, based on the emotional intensity metrics and the cognitive state content. An engagement score for the media presentation is provided. The engagement score is based on the emotional intensity metric. A facial expression metric and a cognitive state metric are generated for the user. The manipulating includes optimization of the previously viewed media presentation. The optimization changes various aspects of the media presentation, including the length of different portions of the media presentation, the overall length of the media presentation, character selection, music selection, advertisement placement, and brand reveal time.

Abstract: Data on a user interacting with a media presentation is collected at a client device. The data includes facial image data of the user. The facial image data is analyzed to extract cognitive state content of the user. One or more emotional intensity metrics are generated. The metrics are based on the cognitive state content. The media presentation is manipulated, based on the emotional intensity metrics and the cognitive state content. An engagement score for the media presentation is provided. The engagement score is based on the emotional intensity metric. A facial expression metric and a cognitive state metric are generated for the user. The manipulating includes optimization of the previously viewed media presentation. The optimization changes various aspects of the media presentation, including the length of different portions of the media presentation, the overall length of the media presentation, character selection, music selection, advertisement placement, and brand reveal time.

Abstract: A method and system for providing a recovery sequence for a network from a state of disruption to a state of partial or complete functionality are provided. The method and system can measure the response of a network to one or multiple hazards and can generate and compare the effectiveness of multiple recovery strategies in a quantitative and generalizable manner, providing a user with practical tools to implement an efficient restoration of the network.

Abstract: A system and method for providing multivariate climate change forecasting are provided that obtain, from one or more climate model datasets, simulated historical and future climate model data, and from one or more climate observational datasets, historical observed climate data. A statistical distribution, using a Bayesian model, is provided of extremes or climate indices for one or more variable climate features using the simulated climate model data and the observed climate data. One or more metrics are determined, including a prediction of a future climate variable for a determined future time period, a confidence bound of the prediction of the future climate variable for the determined future time period, and a prediction bound for the future climate variable for the determined future time period. The metrics can be transmitted to a variety of applications in a variety of formats.

Abstract: A method and system for providing a recovery sequence for a network from a state of disruption to a state of partial or complete functionality are provided. The method and system can measure the response of a network to one or multiple hazards and can generate and compare the effectiveness of multiple recovery strategies in a quantitative and generalizable manner, providing a user with practical tools to implement an efficient restoration of the network.

Abstract: A method and system for providing a recovery sequence for a network from a state of disruption to a state of partial or complete functionality are provided. The method and system can measure the response of a network to one or multiple hazards and can generate and compare the effectiveness of multiple recovery strategies in a quantitative and generalizable manner, providing a user with practical tools to implement an efficient restoration of the network.

Abstract: An individual can exhibit one or more mental states when reacting to a stimulus. A camera or other monitoring device can be used to collect, on an intermittent basis, mental state data including facial data. The mental state data can be interpolated between the intermittent collecting. The facial data can be obtained from a series of images of the individual where the images are captured intermittently. A second face can be identified, and the first face and the second face can be tracked.

Abstract: Mental state data is gathered from a plurality of people and analyzed in order to determine mental state information. Metrics are generated based on the mental state information gathered as the people view media presentations. Norms, defined as the quantitative measures of the mental states of a plurality of people as they view the media presentation, are determined based on the mental state information metrics. The norms can be determined based on various viewer criteria including country of residence, demographic group, or device type on which the media presentation is viewed. Responses to new media are then compared against norms to determine the effectiveness of the new media presentations.

Abstract: A user interacts with various pieces of technology to perform numerous tasks and activities. Reactions can be observed and mental states inferred from these performances. Multiple devices, including mobile devices, can observe and record or transmit a user's mental state data. The mental state data collected from the multiple devices can be used to analyze the mental states of the user. The mental state data can be in the form of facial expressions, electrodermal activity, movements, or other detectable manifestations. Multiple cameras on the multiple devices can be usefully employed to collect facial data. An output can be rendered based on an analysis of the mental state data.

Abstract: A system and method for providing multivariate climate change forecasting are provided that obtain, from one or more climate model datasets, simulated historical and future climate model data, and from one or more climate observational datasets, historical observed climate data. A statistical distribution, using a Bayesian model, is provided of extremes or climate indices for one or more variable climate features using the simulated climate model data and the observed climate data. One or more metrics are determined, including a prediction of a future climate variable for a determined future time period, a confidence bound of the prediction of the future climate variable for the determined future time period, and a prediction bound for the future climate variable for the determined future time period. The metrics can be transmitted to a variety of applications in a variety of formats.

Abstract: Mental state event signatures are used to assess how members of a specific social group react to various stimuli such as video advertisements. The likelihood that a video will go viral is computed based on mental state event signatures. Automated facial expression analysis is utilized to determine an emotional response curve for viewers of a video. The emotional response curve is used to derive a virality probability index for the video. The virality probability index is an indicator of the propensity to go viral for a given video. The emotional response curves are processed according to various demographic criteria in order to account for cultural differences amongst various demographic groups and geographic regions.

Abstract: A method and system for providing a recovery sequence for a network from a state of disruption to a state of partial or complete functionality are provided. The method and system can measure the response of a network to one or multiple hazards and can generate and compare the effectiveness of multiple recovery strategies in a quantitative and generalizable manner, providing a user with practical tools to implement an efficient restoration of the network.

Abstract: An individual can exhibit one or more mental states when reacting to a stimulus. A camera or other monitoring device can be used to collect, on an intermittent basis, mental state data including facial data. The mental state data can be interpolated between the intermittent collecting. The facial data can be obtained from a series of images of the individual where the images are captured intermittently. A second face can be identified, and the first face and the second face can be tracked.

Abstract: A user may react to an interaction by exhibiting a mental state. A camera or other monitoring device can be used to capture one or more manifestations of the user's mental state, such as facial expressions, electrodermal activity, or movements. However, there may be conditions where the monitoring device is not able to detect the manifestation continually. Thus, various capabilities and implementations are described where the mental state data is collected on an intermittent basis, analyzed, and an output rendered based on the analysis of the mental state data.

Abstract: Analysis of mental states is provided based on videos of a plurality of people experiencing various situations such as media presentations. Videos of the plurality of people are captured and analyzed using classifiers. Facial expressions of the people in the captured video are clustered based on set criteria. A unique signature for the situation to which the people are being exposed is then determined based on the expression clustering. In certain scenarios, the clustering is augmented by self-report data from the people. In embodiments, the expression clustering is based on a combination of multiple facial expressions.

Abstract: Mental state data is gathered from a plurality of people and analyzed in order to determine mental state information. Metrics are generated based on the mental state information gathered as the people view media presentations. Norms, defined as the quantitative measures of the mental states of a plurality of people as they view the media presentation, are determined based on the mental state information metrics. The norms can be determined based on various viewer criteria including country of residence, demographic group, or device type on which the media presentation is viewed. Responses to new media are then compared against norms to determine the effectiveness of the new media presentations.

Abstract: A method for accurate pain analysis using a combination of electrodermal data and self-report information is described. To obtain pain measurements, electrodermal activity is collected and analyzed. One or more biosensors obtain electrodermal data from a person. The electrodermal data is filtered to produce skin conductance values. The skin conductance values are associated with self-report pain information from a person over multiple time regions. The associating allows electrodermal activity to be related to self-reported pain (SRP) data to derive an objective pain measurement.

Abstract: A user interacts with various pieces of technology to perform numerous tasks and activities. Reactions can be observed and mental states inferred from these performances. Multiple devices, including mobile devices, can observe and record or transmit a user's mental state data. The mental state data collected from the multiple devices can be used to analyze the mental states of the user. The mental state data can be in the form of facial expressions, electrodermal activity, movements, or other detectable manifestations. Multiple cameras on the multiple devices can be usefully employed to collect facial data. An output can be rendered based on an analysis of the mental state data.

Abstract: Mental state data is collected from a group of people as they view a media presentation, such as an advertisement, a television show, or a movie. The mental state data is analyzed to produce mental state information, such as inferred mental states, facial expressions, or valence. The mental state information is used to automatically optimize the previously viewed media presentation. The optimization may change various aspects of the media presentation including the length of different portions of the media presentation, the overall length of the media presentation, character selection, music selection, advertisement placement, and brand reveal time.

Abstract: A user may react to an interaction by exhibiting a mental state. A camera or other monitoring device can be used to capture one or more manifestations of the user's mental state, such as facial expressions, electrodermal activity, or movements. However, there may be conditions where the monitoring device is not able to detect the manifestation continually. Thus, various capabilities and implementations are described where the mental state data is collected on an intermittent basis, analyzed, and an output rendered based on the analysis of the mental state data.