Abstract: A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.

Abstract: A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.

Abstract: A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.

Abstract: A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.

Abstract: A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.

Abstract: A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.

Abstract: A pacing platform and functionality allows for controlling the pace of delivery of addressable assets in an addressable asset delivery system (100). The illustrated system (100) generally includes an asset delivery order system (102), a decisioning system (104), UEDs (106) and delivery platforms (108). The system (100) allows for delivery of targeted assets to users of UEDs (106) in connection with asset delivery opportunities of programming provided by one or more program delivery networks (122). The system (100) allows for more even pacing of assets delivered by individual UEDs while still collectively fulfilling the campaigns entered via the order system (102). In addition, the invention allows for operation of the order system (102) so as to avoid accepting campaign requests that likely cannot be fulfilled.

Abstract: A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.

Abstract: Embodiments of the invention provide systems and methods for constructing a schedule well before the time of an asset delivery opportunity that associates a collection of one or more assets, potentially from multiple advertisers or asset providers, that are planned to play in each asset delivery opportunity. Specific rules for each device also determine which asset each will play, thereby ensuring that campaigns of total asset delivery and asset delivery pacing are approximately fulfilled. This scheduling can be accomplished using marketing data associated with each user device and can be prepared in a practicable period of time using reasonable processing resources.

Abstract: A system (1000) is disclosed including a resource allocation optimization (RAO) platform (1002) for optimizing the allocation of resources in network (1004) for delivery of assets to user equipment devices (UEDs) (1012). The RAO platform (1002) determines probabilities that certain asset delivery opportunities (ADOs) will occur within a selected time window and uses these probabilities together with information concerning values of asset delivery to determine an optimal use of asset deliveries. In this regard, the RAO platform (1004) received historical data from repository (1014) that facilitates calculation of probabilities that ADOs will occur. Such information may be compiled based on asset delivery records for similar network environments in the recent past or over time.

Abstract: Embodiments of the invention provide systems and methods for constructing a schedule well before the time of an asset delivery opportunity that associates a collection of one or more assets, potentially from multiple advertisers or asset providers, that are planned to play in each asset delivery opportunity. Specific rules for each device also determine which asset each will play, thereby ensuring that campaigns of total asset delivery and asset delivery pacing are approximately fulfilled. This scheduling can be accomplished using marketing data associated with each user device and can be prepared in a practicable period of time using reasonable processing resources.

Abstract: Techniques for selecting a digital image are disclosed. The techniques may include receiving a first set of digital images, analyzing the first set of digital images to extract first image features from each of the first set of digital images, accessing a user profile, comparing the extracted first image features to a preset list of image features, ranking each digital image of the first set, selecting each digital image having a ranking that exceeds a threshold, assigning a category to each selected digital image based on a comparison of each selected digital image to a category database of digital image categories, displaying each selected digital image with the assigned category, receiving an input from the user in response to the displaying, updating the user profile and the category database based on the input, and selecting at least one subsequent digital image based on the updated user profile and category database.

Abstract: Embodiments of the invention provide systems and methods for constructing a schedule well before the time of an asset delivery opportunity that associates a collection of one or more assets, potentially from multiple advertisers or asset providers, that are planned to play in each asset delivery opportunity. Specific rules for each device also determine which asset each will play, thereby ensuring that campaigns of total asset delivery and asset delivery pacing are approximately fulfilled. This scheduling can be accomplished using marketing data associated with each user device and can be prepared in a practicable period of time using reasonable processing resources.

Abstract: Embodiments of the invention provide systems and methods for constructing a schedule well before the time of an asset delivery opportunity that associates a collection of one or more assets, potentially from multiple advertisers or asset providers, that are planned to play in each asset delivery opportunity. Specific rules for each device also determine which asset each will play, thereby ensuring that campaigns of total asset delivery and asset delivery pacing are approximately fulfilled. This scheduling can be accomplished using marketing data associated with each user device and can be prepared in a practicable period of time using reasonable processing resources.

Abstract: Techniques for selecting a digital image are disclosed. The techniques may include receiving a first set of digital images, analyzing the first set of digital images to extract first image features from each of the first set of digital images, accessing a user profile, comparing the extracted first image features to a preset list of image features, ranking each digital image of the first set, selecting each digital image having a ranking that exceeds a threshold, assigning a category to each selected digital image based on a comparison of each selected digital image to a category database of digital image categories, displaying each selected digital image with the assigned category, receiving an input from the user in response to the displaying, updating the user profile and the category database based on the input, and selecting at least one subsequent digital image based on the updated user profile and category database.

Abstract: A diamond reference standard contains a diamond composite of 60-90% diamond crystals and 10-40% silicon carbide binding agent doped with a plurality of elements. The standard is prepared by doping a diamond composite containing a silicon carbide binder with a plurality of elements, the presence of which can readily be detected using a variety of instruments, e.g. a mass spectrometer.

Abstract: Embodiments of the invention provide systems and methods for constructing a schedule well before the time of an asset delivery opportunity that associates a collection of one or more assets, potentially from multiple advertisers or asset providers, that are planned to play in each asset delivery opportunity. Specific rules for each device also determine which asset each will play, thereby ensuring that campaigns of total asset delivery and asset delivery pacing are approximately fulfilled. This scheduling can be accomplished using marketing data associated with each user device and can be prepared in a practicable period of time using reasonable processing resources.

Abstract: A diamond reference standard contains a diamond composite of 60-90% diamond crystals and 10-40% silicon carbide binding agent doped with a plurality of elements. The standard is prepared by doping a diamond composite containing a silicon carbide binder with a plurality of elements, the presence of which can readily be detected using a variety of instruments, e.g. a mass spectrometer.