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: A method for image generation, preferably including: generating a set of mission parameters for a UAV mission of the UAV associated with aerial scanning of a region of interest; controlling the UAV to perform the mission; generating an image subassembly corresponding to the mission; and/or rendering the image subassembly at a display.

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 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, 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: Methods and apparatus to estimate cardinality of users represented across multiple bloom filter arrays are disclosed. Examples includes processor circuitry to execute and/or instantiate instructions to generate a first composite Bloom filter array based on first and second Bloom filter arrays. The processor circuitry is to generate a final composite Bloom filter array based on the first composite Bloom filter array and a third Bloom filter array. Different ones of the first, second, and third Bloom filter arrays representative of different sets of users who accessed media. The first, second, and third Bloom filter arrays including differential privacy noise. The processor circuitry to estimate a cardinality of a union of the first, second, and third Bloom filter arrays based on the final composite Bloom filter array.

Abstract: Techniques for managing an application token may include providing, by a first service provider application on a communication device to a first service provider computer, a first request for a first application token, receiving, by an account management application on the communication device from a token service computer in communication with the first service provider computer, the first application token, and storing the first application token in a token container in the account management application.

Abstract: Example methods and systems for ad insertion decision-making comprise: identifying an ad insertion opportunity in which an underlying advertisement is available for replacement by an addressable advertisement; determining a first expected revenue corresponding to presentation of the addressable advertisement and a first expected cost corresponding to presentation of the addressable advertisement, wherein the first expected cost is based on a current pacing of an advertisement campaign of the addressable advertisement; determining a second expected revenue corresponding to presentation of the underlying advertisement and a second expected cost corresponding to presentation of the underlying advertisement, wherein the second expected cost is based on a current pacing of an advertisement campaign of the underlying advertisement; determining an expected value of the ad insertion based on the first and second expected revenues and the first and second expected costs; and causing performance of the ad insertion bas

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: Methods and apparatus to model on/off states of media presentation devices based on return path data are disclosed. An apparatus includes a memory and processor circuitry to execute instructions stored in the memory to: generate a probability distribution of actual durations of first tuning segments, the first tuning segments representative of lengths of time during which panelists accessed first media; modify the lengths associated with ones of the first tuning segments to generate second tuning segments having second durations; and estimate a time when a media device associated with a return path data (RPD) device is powered on based on (i) the probability distribution, (ii) the second tuning segments, and (iii) a third tuning segment during which the RPD device accessed second media, the third tuning segment reported from the RPD device.

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: 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 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, 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 estimate cardinality across multiple datasets represented using Bloom filter arrays are disclosed. Disclosed examples include processor circuitry to execute and/or instantiate instructions to determine an inclusion-exclusion expression that defines an audience size for a user group of interest. Terms in the inclusion-exclusion expression corresponding to either a first cardinality of a first one of at least three Bloom filter arrays or a second cardinality of a union of two or more of the Bloom filter arrays. Different ones of the Bloom filter arrays representative of different sets of users who accessed media. The at least one processor further to estimate, based on the inclusion-exclusion expression, the audience size of the user group of interest.

Abstract: Methods and apparatus to determine probabilistic media viewing metrics are disclosed herein. An example apparatus includes memory including machine reachable instructions; and processor circuitry to execute the instructions to calculate a first probability for respective ones of a plurality of panelists as having viewed media based on viewing data, the viewing data including incomplete viewing data for one or more of the panelists relative to the media; identify respective ones of a plurality of panelists as included in a demographic subgroup based on demographic data for the panelists; assign a sampling weight to the respective ones of the plurality of panelists based on the demographic data; and calculate a second probability of the demographic subgroup having viewed the media based on the first probabilities and the sampling weights for the respective ones of the plurality of panelists in the demographic subgroup.

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: Example apparatus disclosed herein include a return path data classifier to classify a first viewing period associated with segments of return path data received from a set top box into tuning classifications based on the segments of the return path data; calculate a total reported tuning duration for the first viewing period when the first viewing period is classified as live or playback tuning; and compare the total reported tuning duration to a duration threshold to determine whether the segments of return path data associated with the first viewing period are valid. The example apparatus also includes a return path data rectifier to rectify missing tuning data associated with a second viewing period based on tuning data included in the segments of return path data associated with the first viewing period when the segments of the return path data associated with the first viewing period are determined to be valid.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to generate synthetic respondent level data. Example apparatus disclosed herein include means for generating a synthetic panel corresponding to a duration of time, the means for generating the synthetic panel to: generate a transition matrix corresponding to a first sub-duration of the duration of time and a second sub-duration of the duration of time; generate, based on the transition matrix, a plurality of synthetic panelists and associated viewing data; remove first ones of the synthetic panelists associated with one or more weights that do not satisfy a threshold to generate the synthetic panel corresponding to the duration of time, the synthetic panel representative of audiences of media presented by a plurality of media devices during the duration of time; and generate synthetic respondent level data based on the viewing data associated with remaining second ones of the synthetic panelists.