Abstract: Example methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to assign respondents to geographic locations for audience measurement are disclosed. Example apparatus disclosed herein are to determine a set of constraints based on aggregate values of demographic features associated with respective ones of the geographic locations. Disclosed example apparatus are also to construct a model to return probabilities that respective ones the respondents are associated with the respective ones of the geographic locations, the model to have a set of parameters, respective ones of the parameters to be associated with respective ones of the constraints. Disclosed example apparatus are further to evaluate the model based on values of the set of parameters and values of the demographic features for a first one of the respondents to determine a set of probabilities that the first respondent is to be assigned to respective ones of the geographic locations.

Abstract: Example methods and apparatus disclosed herein include campaign mapping for total audience measurement. An example apparatus includes processor circuitry to train a machine learning model to determine first and second estimated duplication factors for respective first and second reference media campaigns; and determine, using the machine learning model, third estimated duplication factors for a query media campaign based on total exposure metrics associated with individual ones of media platforms for the query media campaign. The processor circuitry to select one of the first and second reference media campaigns based on a comparison of the third estimated duplication factors with each of the first and second estimated duplication factors; and determine fourth estimated duplication factors for the query media campaign based on (a) the respective first or second estimated duplication factors associated with the selected one of the first and second reference media campaigns and (b) the total exposure metrics.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to generate synthetic respondent level data. Example apparatus disclosed herein are to identify locations corresponding to monitored panelists, and when a first one of the identified locations corresponds to two or more affiliates, sum tuning minutes of the two or more affiliates. Disclosed example apparatus are also to generate an affiliate probability based on the sum, and convert first data of households in the first one of the locations to a candidate receivability session based on the affiliate probability. Disclosed apparatus are further to generate a seed panel, the seed panel to include at least one of the monitored panelists selected based on a population associated with return path data, and donate second data associated with a donor pool of first panelists to second panelists included in the seed panel, the second panelists associated with faulty media monitoring equipment.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to determine a duration of media presentation based on tuning session duration. Example apparatus a receiver to obtain a first tuning session duration indicative of an amount of time between channel changes of a first media presentation device at a first media presentation location, a presentation session estimator to select a model from storage, the model selected based on a match of the first tuning session duration and a second tuning session duration, the model including a relation between the second tuning session duration and a first presentation session duration of media presented on a second media presentation device at a second media presentation location, and estimate a second presentation session duration of media presented within the first tuning session duration based on the model.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to to estimate population reach from marginal ratings. An example apparatus includes an interface to access marginal ratings of the media for a recorded audience, marginal ratings of the media for a population audience, and reach of the media for the recorded audience; a reach determiner to iteratively estimate a reach of the media for the population audience based on the marginal ratings for the recorded audience, the marginal ratings for the population audience, and the reach for the recorded audience; and the interface to output the estimated reach for the population audience.

Abstract: Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach for different unions based on marginal ratings. An example apparatus includes memory and processor circuitry to determine a population reach estimate of a union of time intervals for which media ratings data is available, the population reach estimate based on a pseudo universe estimate of a population audience corresponding to the union of the time intervals; determine a pseudo universe estimate of a recorded audience corresponding to the union of the time intervals; determine the pseudo universe estimate of the population audience based on the pseudo universe estimate of the recorded audience; and in response to a decision to update the pseudo universe estimate of the population audience to reduce an error of the population reach estimate output the population reach estimate of the union when the error of the population reach estimate satisfies a threshold.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying, by executing an instruction with a processor, in the return path data, first tuning data corresponding to a first group of set top boxes, the first group of set top boxes classified as associated with machine events, determining, by executing an instruction with a processor, a ratio between first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set top boxes, the second tuning events attributed to a second group of the set top boxes classified at not associated with machine events, and in response to the ratio satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data.

Abstract: Methods and apparatus to calibrate media ratings based on return path data are disclosed. An apparatus includes a processor and memory including instructions that, when executed, cause the processor to: determine an initial rating for the media provided in a first geographic area based on return path data (RPD) tuning information obtained from RPD devices in subscriber households in the first geographic area; determine a first panelist rating for the media provided in a second geographic area based on first panel tuning information obtained from first metering devices in a first subset of panelist households in the second geographic area; determine a nonsubscriber calibration factor based on the first panelist rating; and determine a final rating for the media in the first geographic area by modifying the initial rating based on the nonsubscriber calibration factor.

Abstract: Processor systems to estimate audience sizes and impression counts for different frequency intervals are disclosed. An example processor system includes a memory management unit (MMU) to assign requests from computing devices indicative of accesses to media to a first block of memory and to assign user-identified impression data corresponding to user-identified impressions to a second block of memory. The processor system including an arithmetic logic unit (ALU) to determine multipliers relating a first probability distribution for the user-identified impressions to a second probability distribution for census impressions. The multipliers based on probability constraints defined by weighted probabilities associated with the second probability distribution, where different ones of the probabilities weighted based on estimated populations for corresponding ones of the different demographics.

Abstract: An electrified vehicle, system, and method include an electric machine, a traction battery coupled to the electric machine, and a controller programmed to control wheel slip to provide high wheel slip to traverse deformable terrain, such as sand or loose soil, and lower wheel slip to avoid excessive soil removal beneath the wheels after detecting a vertical acceleration or heave event, such as after landing when driving over a jump or bump. When vehicle vertical acceleration exceeds a first threshold, and a ratio of a wheel angular acceleration to vehicle longitudinal acceleration exceeds a second threshold, the electric machine is controlled to limit wheel slip to a lower value that provides sufficient tractive force to maintain some forward motion. Otherwise, the electric machine is controlled to limit wheel slip to a higher value to accommodate higher vehicle speeds over the deformable terrain.

Abstract: Methods and apparatus to correct for deterioration of a demographic model to associate demographic information with media impression information are disclosed. An example method includes estimating first and second ages of audience members based on demographic information; estimating a third age of an audience member who is not included in the audience members; applying a window function to the second ages to determine a distribution of ages based on the third age; multiplying window values by the first ages to determine corrected first age components; dividing a total of the corrected first age components by a sum of the window values to determine an estimated age of the audience member at a first time; and determining the corrected age of the audience member at a second time based on the estimated age of the audience member at the first time and a time difference between the first and second times.

Abstract: A vehicle includes a first axle have a first electric machine, a second axle having a second electric machine and a controller. The controller is programmed to, in a user-selected four-wheel drive mode, command a first torque to the first electric machine based on a driver-demanded torque and a speed of the second axle, and command a second torque to the second electric machine based on a comparison of the driver-demanded torque and the first torque and further based on a speed of the first axle.

Abstract: The present invention features a novel design for a bolometric infrared detector focused on LWIR range for human body high-resolution temperature sensing, The present invention incorporates an efficient plasmonic absorber and VO2 nanobeam to facilitate improvement in both aspects—thermal resolution and spatial resolution. The present invention significantly improves the detectivity, NETD, and responsivity for a smaller form-factor detector active area.

Abstract: Example methods and apparatus disclosed herein include campaign mapping for total audience measurement.

Abstract: Methods and apparatus to correct for deterioration of a demographic model to associate demographic information with media impression information are disclosed. An example method includes estimating first and second ages of audience members based on demographic information; estimating a third age of an audience member who is not included in the audience members; applying a window function to the second ages to determine a distribution of ages based on the third age; multiplying window values by the first ages to determine corrected first age components; dividing a total of the corrected first age components by a sum of the window values to determine an estimated age of the audience member at a first time; and determining the corrected age of the audience member at a second time based on the estimated age of the audience member at the first time and a time difference between the first and second times.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed. An example disclosed apparatus disclosed herein includes a database proprietor identifier (DPID) extractor to extract a panelist database proprietor identifier from a cookie, the panelist database proprietor identifier associated with credentials used by a panelist to access a website.

Abstract: A disclosed example includes: at least one memory; instructions; and processor circuitry to execute the instructions to at least: determine a first sum of estimated individual cardinalities of audience members of first and second media platforms; determine a second sum of estimated pairwise cardinalities of ones of the audience members belonging to both the first and second media platforms; and generate lower and upper bound estimates of a deduplicated audience size based on the first and second sums; and send the deduplicated audience size to a computing device via a network communication.

Abstract: Ensemble classification algorithms having subclass resolution are disclosed. An example disclosed apparatus includes a fingerprint generator to generate a fingerprint of class probabilities of each of a plurality of samples, a distribution creator to create a distribution of the samples based on the generated fingerprints, and a distribution applicator to apply the distribution to a population to predict sub-class probabilities of each of the population.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to monitor media presentation to determine a period of media presentation based on tuning session period are disclosed. Example methods disclosed herein include determining a first tuning session based on a period of time between channel changes of a first media presentation device, determining first presentation session data within the determined first tuning session, determining a model relating the first tuning session with the first presentation session data, determine a second tuning session for tuning data from a second media presentation device, selecting the model for the second tuning session, based on a match of a first duration of the second tuning session and a second duration associated with the model, and estimating second presentation session data for the second tuning session based on the model.