Abstract: A computing device generates profiles based on mobile device data. The computing device receives a plurality of mobile device records of a plurality of mobile devices in a region, that each include a timestamp, a location data, and an activity data, and assigns each of the plurality of mobile device records to one of a plurality of space-time boxes. The computing device performs analytics on the mobile device records assigned to the plurality of space-time boxes to yield a resulting plurality of profiles, which can include a mobility profile indicating the number of locations in the region that each mobile device occupies during a span, a hangout profile indicating the number of mobile devices that occupy each location in the region during a span, and a buddy profile indicating the mobile devices that occupy the same location in the region as a given mobile device.

Abstract: Instructional content is visually presented within a graphical user interface overlay on a display for an application window also presented on the display. Interactive events between a user and the application are dynamically detected. Responsive to the interactive events, state-specific substantive instructions are determined given a current state of the application as determined from the interactive events. The instructional content is dynamically modified to continuously present the state-specific substantive instructions that correspond with the detected interactive events.

Abstract: A computing device identifies a plurality of media files within a data store, each of the media files lacking user established file names. The computing device analyzing the plurality of media files to recognize humans in the media files based on facial recognition and/or voice recognition programs. Using results of the analyzing to generate a plurality of content identification keywords, which are scored and ranked. Establishing a filename prefix for the media files using scored and ranked content identification keywords. Automatically generating a unique file name for each of the media files, wherein each unique file name includes the established filename prefix.

Abstract: A method for adjusting aspects of an application in a user interface is provided. A user profile is received, wherein the user profile corresponds to a first user of a mobile device. Data corresponding to an application is received, wherein the application is compatible with the mobile device. An application is determined to be likely to be accessed by the first user based on the data corresponding to the application. At least one aspect of the application is adjusted on a user interface of the mobile device.

Abstract: The disclosure provides a computer-based learning system that minimizes the “distance” between applications (for which instructions are provided) and the instructions themselves. That is, the instructional material provided is dynamically integrated with a “state” of one or more applications, which constantly change as a user interacts with the application. Further, the instructional information is visually presented within a common screen, window, or focus region as the application, in a minimally intrusive manner. For example, the instruction window can be an overlay that is designed to “hide from” or to avoid obscuring application content of particular interest to a user. Various techniques can be used to ensure the instructions are provided unobtrusively, including use of transparency settings to make instructions legible, resizing techniques, variable shading, font size/contrast/style adjustments, and the like.

Abstract: Arrangements described herein relate to receiving, in real time, utterances spoken or sung by a first person when the utterances are spoken or sung and comparing, in real time, the detected utterances spoken or sung by the first person to at least a stored sample of utterances spoken or sung by the first person. Based, at least in part, on the comparing the detected utterances spoken or sung by the first person to at least the stored sample of utterances spoken or sung by the first person, a key indicator that indicates at least one characteristic of the detected utterances spoken or sung by the first person can be generated. Feedback indicating the at least one characteristic of the detected utterances spoken or sung by the first person can be communicated to the first person or a second person.

Abstract: Arrangements described herein relate to receiving, in real time, utterances spoken or sung by a first person when the utterances are spoken or sung and comparing, in real time, the detected utterances spoken or sung by the first person to at least a stored sample of utterances spoken or sung by the first person. Based, at least in part, on the comparing the detected utterances spoken or sung by the first person to at least the stored sample of utterances spoken or sung by the first person, a key indicator that indicates at least one characteristic of the detected utterances spoken or sung by the first person can be generated. Feedback indicating the at least one characteristic of the detected utterances spoken or sung by the first person can be communicated to the first person or a second person.

Abstract: Sensory inputs of a user can be received by a computing device. At least one of the sensory inputs can include a physiological input providing a physiological measurement from a body of the user. Each sensory input can be processed in a unique one of a set of standards-defined sensory channels, each corresponding to a specific emotion dimension. Processing the sensory inputs can transform the physiological measurement into an emotion dimension value. The emotion dimension values from each of the sensory channels can be aggregated to generate at least one emotion datum value, which is a standards-defined value for an emotional characteristic of the user. Historical data for a user can be optionally collected and used by a learning and calibration component to improve the accuracy of the generated emotion datum values for a specific individual. A programmatic action driven by the emotion datum value can be performed.

Abstract: A computer utilizes a matrix code to securely communicate information. To utilize the matrix code, the computer receives a scan of the matrix code, and identifies a first mask within a data region of the matrix code, wherein the first mask includes public user data, and identifies a second mask within the data region of the matrix code, wherein the second mask include private user data. The computer decodes the public user data and the private user data from the matrix code, and decrypts one or both of the public user data and the private user data. The computer also removes a distortion operation from the second mask, wherein removing the distortion operation includes reversing a transformation, rotation, skew, shear, reflection, or projection operation.

Abstract: A computing device utilizes matrix codes to securely communicate information with a variety of servers. The computing device receives public user data, and generates a display of a base matrix code for reading by a scanner associated with a first server, wherein the base matrix code includes the public user data in a first mask. Responsive to the display of the base matrix code to the scanner associated with the first server, the computing device receives first private user data from the first server. The computing device generates a display of a first combined matrix code for reading by a scanner associated with a second server, wherein the first combined matrix code includes the public user data in the first mask and includes the first private user data in a second mask. The computing device can receive the public and first private user data in a matrix code.

Abstract: A computing device identifies a plurality of media files within a data store, each of the media files lacking user established file names. The computing device analyzing the plurality of media files to recognize humans in the media files based on facial recognition and/or voice recognition programs. Using results of the analyzing to generate a plurality of content identification keywords, which are scored and ranked. Establishing a filename prefix for the media files using scored and ranked content identification keywords. Automatically generating a unique file name for each of the media files, wherein each unique file name includes the established filename prefix.

Abstract: Arrangements described herein relate to receiving, in real time, utterances spoken or sung by a first person when the utterances are spoken or sung and comparing, in real time, the detected utterances spoken or sung by the first person to at least a stored sample of utterances spoken or sung by the first person. Based, at least in part, on the comparing the detected utterances spoken or sung by the first person to at least the stored sample of utterances spoken or sung by the first person, a key indicator that indicates at least one characteristic of the detected utterances spoken or sung by the first person can be generated. Feedback indicating the at least one characteristic of the detected utterances spoken or sung by the first person can be communicated to the first person or a second person.

Abstract: A set of media files are identified within a data store. Each of the media files lack user established file names, lack user established icons, or lack user established file names and icons. The media files are analyzed to determine semantic metadata. For at least a subset of the media files, the semantic metadata is utilized to automatically generate unique and meaningful file names, file icons, or both file names and file icons for each of the media files in the subset.

Abstract: A media recording within a data store of a computing device can be identified. The media can be a photograph or a video. The media can be analyzed to determine a participant associated with the media. The participant can be a creator or a subject. The identity of the participant can be determined utilizing biometrics associated with an identity source. The identity can be associated with a confidence score which can indicate the accuracy of the identity. The identity source can be associated with a weighted value which can represent the validity of identity data associated with the source. The identity of the participant can be automatically tagged within the media. The tagging can be a participant name or participant user name.

Abstract: A computing device generates profiles based on mobile device data. The computing device receives a plurality of mobile device records of a plurality of mobile devices in a region, that each include a timestamp, a location data, and an activity data, and assigns each of the plurality of mobile device records to one of a plurality of space-time boxes. The computing device performs analytics on the mobile device records assigned to the plurality of space-time boxes to yield a resulting plurality of profiles, which can include a mobility profile indicating the number of locations in the region that each mobile device occupies during a span, a hangout profile indicating the number of mobile devices that occupy each location in the region during a span, and a buddy profile indicating the mobile devices that occupy the same location in the region as a given mobile device.

Abstract: A set of media files are identified within a data store. Each of the media files lack user established file names, lack user established icons, or lack user established file names and icons. The media files are analyzed to determine semantic metadata. For at least a subset of the media files, the semantic metadata is utilized to automatically generate unique and meaningful file names, file icons, or both file names and file icons for each of the media files in the subset.

Abstract: A computing device utilizes matrix codes to securely communicate information with a variety of servers. The computing device receives public user data, and generates a display of a base matrix code for reading by a scanner associated with a first server, wherein the base matrix code includes the public user data in a first mask. Responsive to the display of the base matrix code to the scanner associated with the first server, the computing device receives first private user data from the first server. The computing device generates a display of a first combined matrix code for reading by a scanner associated with a second server, wherein the first combined matrix code includes the public user data in the first mask and includes the first private user data in a second mask. The computing device can receive the public and first private user data in a matrix code.

Abstract: A computer utilizes a matrix code to securely communicate information. To utilize the matrix code, the computer receives a scan of the matrix code, and identifies a first mask within a data region of the matrix code, wherein the first mask includes public user data, and identifies a second mask within the data region of the matrix code, wherein the second mask include private user data. The computer decodes the public user data and the private user data from the matrix code, and decrypts one or both of the public user data and the private user data. The computer also removes a distortion operation from the second mask, wherein removing the distortion operation includes reversing a transformation, rotation, skew, shear, reflection, or projection operation.

Abstract: Sensory inputs of a user can be received by a computing device. At least one of the sensory inputs can include a physiological input providing a physiological measurement from a body of the user. Each sensory input can be processed in a unique one of a set of standards-defined sensory channels, each corresponding to a specific emotion dimension. Processing the sensory inputs can transform the physiological measurement into an emotion dimension value. The emotion dimension values from each of the sensory channels can be aggregated to generate at least one emotion datum value, which is a standards-defined value for an emotional characteristic of the user. Historical data for a user can be optionally collected and used by a learning and calibration component to improve the accuracy of the generated emotion datum values for a specific individual. A programmatic action driven by the emotion datum value can be performed.

Abstract: A media recording within a data store of a computing device can be identified. The media can be a photograph or a video. The media can be analyzed to determine a participant associated with the media. The participant can be a creator or a subject. The identity of the participant can be determined utilizing biometrics associated with an identity source. The identity can be associated with a confidence score which can indicate the accuracy of the identity. The identity source can be associated with a weighted value which can represent the validity of identity data associated with the source. The identity of the participant can be automatically tagged within the media. The tagging can be a participant name or participant user name.