Abstract: Examples apparatus disclosed herein are to determine a plurality of weights based on a data structure having elements corresponding to pairings of ones of a plurality of demographic partition statistics and ones of a plurality of baseline demographic statistics obtained for a target population, the demographic partition statistics corresponding to a plurality of demographic partitions of a sample population, a first element of the data structure to combine a first one of the demographic partition statistics with a first one of the baseline demographic statistics of the target population based on a first value corresponding to a numerator term of an expression and a second value corresponding to a denominator term of the expression, the weights corresponding respectively to the demographic partitions of the sample population. Disclosed example apparatus are also to adjust the attribute data based on the weights to determine ratings data for the target population.

Abstract: Methods and apparatus to generate audience metrics using third-party privacy-protected cloud environments. An example apparatus includes at least one memory, programmable circuitry, and instructions to cause the programmable circuitry to generate a first demographic correction model based on a first matrix, the first matrix including first data indicative of user accesses to media, the first matrix associated with a first demographic, generate a second demographic correction model based on a second matrix, the second matrix including second data indicative of user accesses to the media, the second matrix associated with a second demographic, and generate predicted demographics of a user associated with the user accesses based on the first demographic correction model and the second demographic correction model, the predicted demographics including the first demographic and the second demographic.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to identify co-relationships between media using social media. An example apparatus includes an audience estimator to: estimate a first audience of first media based on a first set of media-exposure social media messages corresponding to client devices referencing the first media, and estimate a second audience of second media based on a second set of media-exposure social media messages corresponding to the client devices referencing the second media.

Abstract: Disclosed examples access data from a database, the data stored across multiple registers of the database; determine (a) a maximum rank for each of the multiple registers and (b) a maximum rank count for each of the multiple registers; determine a frequency distribution based on the maximum ranks and the maximum rank counts; and generate a report including at least one of the frequency distribution, the maximum ranks, or the maximum rank counts.

Abstract: Methods, apparatus, systems and articles of manufacture to impute media consumption behavior are disclosed. An example system includes one or more media meters to obtain tuning data, one or more people meters to obtain viewing data, and one or more servers to, in response to a determination that a difference satisfies a first threshold, determine that a first subset of the tuning data associated with first panelist households having tuned to first media in a first area exhibits local bias, determine that a second subset of the viewing data associated with second panelist households having viewed the first media in the second area represents heavy viewing, and impute the second subset of the viewing data for the first subset of the tuning data in response to the second subset of the viewing data representing heavy viewing.

Abstract: Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach for different unions based on marginal ratings. An example method includes performing first parallel computations to determine first multipliers corresponding to a total number of panelists exposed to media at (a) a first margin of time, (b) a second margin of time, and (c) a union corresponding to the first and second margins of time, keeping a subset of the first multipliers corresponding to unknown census data; performing second parallel computation to determine second multipliers corresponding to a total audience exposed to the media at the first margin of time and the second margin of time, the second parallel computations to be performed by solving second equations corresponding to a tree association; and determining an estimate for a population reach of the union based on the second multipliers.

Abstract: Methods and apparatus for multi-account adjustment in third-party privacy-protected cloud environments are disclosed herein. A disclosed example apparatus includes memory and processor circuitry to execute computer readable instructions to select a type of client device, determine a number of panelists associated with a demographic characteristic and the type of client device, the demographic characteristic defining a segment of the panelists, determine a number of user accounts associated with the number of panelists, determine a multi-account adjustment factor for the demographic characteristic and the client device based on a ratio of the number of the panelists to the number of user accounts, and adjust an initial estimate of a unique audience size based on the multi-account adjustment factor.

Abstract: Methods and apparatus to adjust media impressions based on media impression notification loss rates in network communications are disclosed.

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: An example system disclosed herein includes programmable circuitry to identify audience measurement panelists associated with database proprietor accounts, when a sign- out percentage of the audience measurement panelists is zero, determine a first probability that a second server of a database proprietor associated a first demographic with a logged impression when the logged impression corresponds to a second demographic, when the sign-out percentage of the audience measurement panelists is one hundred, determine a second probability that the second server of the database proprietor associated the first demographic with the logged impression when the logged impression corresponds to the second demographic, determine an adjustment factor based on a weighted combination of the first and second probabilities, and apply the adjustment factor to database proprietor impressions data to reduce a computer-generated error.

Abstract: An example system disclosed herein includes programmable circuitry to identify donor adjustment factors and recipient adjustment factors used for correction of media impressions logged by a database proprietor, the donor adjustment factors including first donor adjustment factors associated with a first geographic region and second donor adjustment factors associated with a second geographic region, determine a first reduced donor factor set corresponding to ones of the first donor adjustment factors that satisfy a threshold, determine a second reduced donor factor set corresponding to ones of the second donor adjustment factors that satisfy the threshold, and generate imputation factors based on an aggregation of retained ones of the donor adjustment factors, the retained ones of the donor adjustment factors selected based on the first reduced donor factor set and the second reduced donor factor set, the imputation factors to reduce error in the correction.

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, apparatus, systems, and articles of manufacture are disclosed to adjust demographic information of user accounts to reflect primary users of the user accounts. An example apparatus includes memory, programmable circuitry, and instructions in the memory, the instructions to cause the programmable circuitry to at least access impression data associated with a user account registered with a database proprietor, the user account associated with first demographics at a database of the database proprietor. The example programmable circuitry is also to determine a primary user of the user account based on the impression data and based on second demographics of multiple users of the user account, the multiple users including the primary user. Additionally, the example programmable circuitry is to modify the first demographics associated with the user account based on at least some of the second demographics, the at least some of the second demographics corresponding to the primary user.

Abstract: A disclosed example includes aggregating first performance results of computer-generated machine learning models to generate aggregated performance results, the first performance results based on a comparison of audience member demographic data to training results, the training results generated by the computer-generated machine learning models based on at least one of: (a) a composition of a household, (b) a type of first media, (c) a daypart during which the first media was accessed, or (d) a time at which the first media was accessed; selecting at least one of the computer-generated machine learning models based on a comparison of ones of the first performance results to the aggregated performance results; and applying the at least one of the computer-generated machine learning models to correct a computer-generated error in computer-collected audience measurement data, the computer-collected audience measurement data corresponding to accesses to second media.

Abstract: Methods and apparatus to generate audience metrics using third-party privacy-protected cloud environments. In some examples, an apparatus comprising processor circuitry to execute the instructions to at least generate an individualization model based on truth data indicating first true users exposed to media via first panelist client devices, produce user probabilities for second panelist client devices based on the individualization model, the user probabilities indicating likelihoods of second true users being exposed to media via the second panelist client devices, select a user probability from the user probabilities based on an impression, and assign the impression to the set of second true users.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to generate synthetic respondent level data. An example apparatus includes at least one memory; processor circuitry to execute instructions to: identify locations corresponding to monitored panelists; when a location of the identified locations corresponds to two or more affiliates, sum tuning minutes of the two or more affiliates; generate an affiliate probability based on the sum; convert first data of households in the location to a candidate receivability session based on the affiliate probability; 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 when the second panelists are included in the seed panel, the second panelists corresponds to faulty media monitoring equipment.

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: A computer-implemented method for efficiently estimating the number of unique elements in a collection of elements comprises generating, via hash logic, hash values for each element of the collection of elements. The method further comprises specifying, in a sketch-frequency table, a set of discrete statistical values associated with the hash values and, for each discrete statistical value of the set of discrete statistical values, information indicative of a frequency at which binary representations of the hash values are associated with the discrete statistical value. The cardinality of the collection of elements is estimated based on the sketch-frequency table.

Abstract: A computer-implemented method for efficiently estimating the number of unique elements in a collection of elements comprises generating, via hash logic, hash values associated with the elements. The hash values specify bit positions within an array of bits. Hash values output from the hash logic conform to a geometric distribution such that bit positions of the array of bits corresponding to lower orders bits are more likely to be generated than bit positions corresponding to higher-order bits. Bits of the array of bits corresponding to the bit positions are set. The number of bits of the array of bits that are set is counted. Estimation logic estimates the number of unique elements of the collection of elements as a function of the number of bits of the array of bits that are set.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to determine unique audience size via clustered data. An example apparatus includes memory, machine readable instructions, and processor circuitry to at least one of execute or instantiate the machine readable instructions. The example processor circuitry is to form a first matrix identifying matching and non-matching instances of first values of respective demographics of an audience of media and second values of the respective demographics. Also, the processor circuitry is to normalize the first matrix to generate an account sharing adjustment matrix. Additionally, the processor circuitry is to apply the account sharing adjustment matrix to a vector of one or more counts of impressions of the media to correct for one or more members of the audience that share a user account registered with a database proprietor, the one or more counts of the impressions corresponding to the respective demographics.