Abstract: A computerized system performs automated schedule optimization. In particular, the system solves the problem of determining the range of advertisement placement prices that a seller can select from, while still satisfying all of the constraints on the buyers' orders. The system generates such a range of prices automatically based on a variety of data. As a result, the system helps the seller to maximize the prices of the potential placements that can satisfy a set of orders from buyers.

Abstract: Disclosed example audience measurement apparatus include first estimator means for determining a first audience metric based on set-top box return path tuning data obtained from a plurality of set-top boxes located in a first geographic area, second estimator means for determining a second audience metric from a portion of audience measurement data corresponding to a second geographic area different from the first geographic area, the portion of the audience measurement data associated with monitored sites in the second geographic area having second set-top box characteristics that correspond with first set-top box characteristics of the plurality of set-top boxes located in the first geographic area, and third estimator means for (i) determining a ratio of the first audience metric to the second audience metric, and (ii) processing the audience measurement data based on the ratio to determine an audience exposure metric estimating exposure to media in the first geographic area.

Abstract: A system draws an inference about the audience being targeted by the buyer of an advertisement placement opportunity by correlating the order for the advertisement placement opportunity with characteristics of the audience associated with the television program in which the advertisement placement opportunity is embedded. Sellers of advertisement placement opportunities may use the inferred target audience information to appropriately price their advertising inventories and to fulfill orders more effectively.

Abstract: Example methods, apparatus and articles of manufacture to estimate local market audiences of media are disclosed herein. Disclosed example methods include determining a first audience metric based on set-top box (STB) return path tuning data obtained from STBs located in a first geographic area. The disclosed example methods also include determining a second audience metric from a portion of audience measurement data corresponding to a different second geographic area, the portion of the audience measurement data associated with monitored sites in the second geographic area having second STB characteristics that correspond with first STB characteristics of the STBs located in the first geographic area. The disclosed example methods further include determining a ratio of the first audience metric to the second audience metric, and processing the audience measurement data based on the ratio to determine an audience exposure metric estimating exposure to media in the first geographic area.

Abstract: Delivery devices, systems, and methods may be configured to define a barrier region at a treatment site to deliver one or more therapeutic materials. A device for delivering one or more therapeutic materials to a treatment site may include a body; one or more members that are movable with respect to the body and that are configured to define a barrier region at the treatment site; and one or more delivery lumens configured to deliver one or more therapeutic materials to the barrier region.

Abstract: Methods, apparatus, systems and articles of manufacture to perform identity matching across audience measurement systems are disclosed.

Abstract: Example methods, apparatus and articles of manufacture to estimate local market audiences of media are disclosed herein. Disclosed example methods include determining a first audience metric based on set-top box (STB) return path tuning data obtained from STBs located in a first geographic area. The disclosed example methods also include determining a second audience metric from a portion of audience measurement data corresponding to a different second geographic area, the portion of the audience measurement data associated with monitored sites in the second geographic area having second STB characteristics that correspond with first STB characteristics of the STBs located in the first geographic area. The disclosed example methods further include determining a ratio of the first audience metric to the second audience metric, and processing the audience measurement data based on the ratio to determine an audience exposure metric estimating exposure to media in the first geographic area.

Abstract: This disclosure describes various system and methods for monitoring photons emitted by a heat source of an additive manufacturing device. Sensor data recorded while monitoring the photons can be used to predict metallurgical, mechanical and geometrical properties of a part produced during an additive manufacturing operation. In some embodiments, a test pattern can be used to calibrate an additive manufacturing device.

Abstract: The invention relates to methods and apparatus of measuring real time temperature conditions within a reformer. The data is then used for process control optimization, overheat protection, and improved creep damage and fatigue life prediction.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve reach calculation efficiency. An example method includes estimating, with a processor, a sample distribution of marketing data to generate a maximum entropy distribution, generating, with the processor, a geometric distribution based on estimating a minimum cross entropy of (a) the maximum entropy distribution and (b) the sample distribution of marketing data, and improving calculation efficiency of the public reach of the sample distribution of marketing data by generating, with the processor, conserved quantity expressions of the geometric distribution.

Abstract: Example methods, apparatus and articles of manufacture to estimate local market audiences of media are disclosed herein. Disclosed example methods include accessing set-top box return path tuning data obtained from a plurality of set-top boxes located in a first geographic area. Disclosed example methods also include determining a ratio of (1) a first audience metric determined from audience measurement data associated with a second geographic area different from the first geographic area to (2) a second audience metric determined from a portion of the audience measurement data identified to be associated with monitored sites in the second geographic area having second set-top box characteristics that correspond with first set-top box characteristics of the set-top boxes located in the first geographic area. Disclosed example methods further include processing the set-top box return path tuning data based on the ratio to determine an audience exposure metric in the first geographic area.

Abstract: Example methods, apparatus and articles of manufacture to estimate local market audiences of media are disclosed herein. Disclosed example methods include accessing set-top box return path tuning data obtained from a plurality of set-top boxes located in a first geographic area. Disclosed example methods also include determining a ratio of (1) a first audience metric determined from audience measurement data associated with a second geographic area different from the first geographic area to (2) a second audience metric determined from a portion of the audience measurement data identified to be associated with monitored sites in the second geographic area having second set-top box characteristics that correspond with first set-top box characteristics of the set-top boxes located in the first geographic area. Disclosed example methods further include processing the set-top box return path tuning data based on the ratio to determine an audience exposure metric in the first geographic area.

Abstract: Example methods, apparatus and articles of manufacture to estimate local market audiences of media content are disclosed herein. An example method disclosed herein includes weighting audience measurement data associated with a first geographic area based on population data associated with a second geographic area different from the first geographic area to form weighted data, determining a factor based on the audience measurement data and tuning data associated with the second geographic area, and processing the weighted data based on the factor to determine an audience exposure metric estimating exposure to media content in the second geographic area.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to project ratings for future broadcasts of media. Disclosed example methods include normalizing, with a processor, audience measurement data corresponding to media exposure data, social media exposure data and programming information associated with a future quarter to determine normalized audience measurement data. Disclosed example methods also include classifying a media asset based on the programming information to determine a media asset classification.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to predict time-shifted exposure to media. An example method includes normalizing, with a processor, audience measurement data corresponding to media exposure data and social media activity data. The example method also includes building an estimation model based on a relationship between a first subset of the normalized audience measurement data associated with a characteristic of the media asset and historical rating lift measurements associated with the media asset. The example method also includes estimating, with the processor, current ratings for the media asset based on time-period based ratings and broadcast time-periods. The example method also includes applying data related to the media asset and the estimated current ratings to the estimation model to estimate, with the processor, the ratings lift for the media asset.

Abstract: A method of defining data patterns for object handling includes obtaining an image of an input data area, processing the image to obtain image data, and comparing the image data with a pattern, wherein the pattern identifies spatial information of corresponding pattern fields of the pattern. The method further includes determining a confidence level of the comparison of the image data according to a success in matching the image data with the pattern fields, comparing the confidence level with a confidence threshold associated with the pattern, and selecting the pattern. A pattern output associated with the selected pattern is identified, wherein the pattern output corresponds to a canonical return format, and the pattern output is applied to the image data.

Abstract: A vent is disclosed that is particularly suited to use in ventilating attic spaces beneath a hip roof. The vent is configured to be installed along a hip of the roof overlying and covering a ventilation slot formed through the roof deck along the hip. The vent includes an elongated laterally flexible top panel from which baffle arrays depend. The baffle arrays are formed of a plurality of depending arcuately curved vanes that arc away from the vent. The vanes are aerodynamically shaped to redirect wind-blown rain and snow away from the vent and are configured to block the migration of rain and snow through the vent. A pair of spongy conformable filler strips is attached beneath the edge portions of the vent. The filler strips conform to the shapes of underlying shingles when the vent is installed to fill any gaps that otherwise might be formed between the vent and the shingles.

Abstract: A disclosed example method to determine audience duplication in cross-media campaigns involves determining a first duplicated audience reach for a demographic group between a total television audience and an internet publisher audience. The total television audience is representative of audience members across a plurality of television networks. The internet publisher audience is representative of audience members of one of a plurality of internet publishers. The example method involves determining a second duplicated audience reach between the total television audience and the internet publisher audience for a media campaign based on the first duplicated audience reach. The example method involves determining a third duplicated audience reach between a television network audience and the internet publisher audience for the media campaign based on the second duplicated audience reach.

Abstract: A disclosed example method to determine audience duplication in cross-media campaigns involves determining a first duplicated audience reach between a total television audience and an internet publisher audience for a demographic group. The total television audience is representative of audience members across a plurality of television networks, and the internet publisher audience is representative of audience members across one of a plurality of internet publishers. The example method involves determining a second duplicated audience reach between the total television audience and the internet publisher audience for a media campaign based on the first duplicated audience reach. The example method involves determining a third duplicated audience reach between a television network audience and the internet publisher audience for the media campaign based on the second duplicated audience reach.

Abstract: A disclosed example involves accessing an initial average unique web browser reach corresponding to a first duration, an initial average internet media impressions-per-user frequency corresponding to the first duration, an initial average unique web browser reach corresponding to a second duration, and an initial average internet media impressions-per-user frequency corresponding to the second duration. A probability model is used to determine an adjusted internet media audience reach corresponding to the first duration based on the initial average unique web browser reach corresponding to the first duration, the initial average internet media impressions-per-user frequency corresponding to the first duration, the initial average unique web browser reach corresponding to the second duration, and the initial average impressions-per-user frequency corresponding to the second duration.