Abstract: One variation of a method includes: accessing a descriptor of a project; extracting a set of language signals from the descriptor; accessing a set of input parameters and a set of output characteristics; querying a language model for a range of values of input parameters exhibited within historical engineering solutions correlated with the set of language signals; accessing a virtual model for the project and a function representing a relationship between the set of input parameters and the set of output characteristics; for each analysis instance in a count of analysis instances, defining a combination of values of input parameters within corresponding ranges and based on the virtual model, the function, and the combination of values, executing the analysis instance to calculate a set of values of output characteristics; and rendering representations of combinations of values of input parameters and sets of values of output characteristics within a user interface.

Abstract: One variation of a method includes: receiving a descriptor of a design problem; selecting a set of output characteristics based on a set of language signals extracted from the descriptor; selecting a set of functions relating a set of input parameters to the set of output characteristics; accessing a virtual model representing a design solution and defining a set of model variables; linking a subset of input parameters to a subset of model variables analogous to the subset of input parameters; in response to the set of model variables omitting a model variable analogous to a first input parameter in the set of input parameters, prompting a user to update the virtual model to include a first model variable analogous to the first input parameter; and compiling the set of functions, the set of output characteristics, and the set of input parameters into a design specification.

Abstract: One variation of a method includes: accessing a descriptor of a project; extracting a set of language signals from the descriptor; accessing a set of input parameters and a set of output characteristics; querying a language model for a range of values of input parameters exhibited within historical engineering solutions correlated with the set of language signals; accessing a virtual model for the project and a function representing a relationship between the set of input parameters and the set of output characteristics; for each analysis instance in a count of analysis instances, defining a combination of values of input parameters within corresponding ranges and based on the virtual model, the function, and the combination of values, executing the analysis instance to calculate a set of values of output characteristics; and rendering representations of combinations of values of input parameters and sets of values of output characteristics within a user interface.

Abstract: One variation of a method includes: accessing a virtual model for a project; deriving a language concept descriptive of a model variable in a set of model variables in the virtual model; accessing a descriptor of an output characteristic in a set of output characteristics selected for the project; querying a function library for a set of functions; linking a first function and a second function, relating the model variable to the output characteristic, to form a composite function; accessing ranges of values of the set of model variables; and for each analysis instance in a count of analysis instances, defining a combination of values of model variables within corresponding ranges and based on the virtual model, composite functions, and the combination of values, executing the analysis instance to calculate values of output characteristics; and rendering representations of values of model variables and output characteristics within a user interface.

Abstract: One variation of a method includes: accessing a descriptor of a project; extracting a set of language signals from the descriptor; accessing a set of input parameters and a set of output characteristics; querying a language model for a range of values of input parameters exhibited within historical engineering solutions correlated with the set of language signals; accessing a virtual model for the project and a function representing a relationship between the set of input parameters and the set of output characteristics; for each analysis instance in a count of analysis instances, defining a combination of values of input parameters within corresponding ranges and based on the virtual model, the function, and the combination of values, executing the analysis instance to calculate a set of values of output characteristics; and rendering representations of combinations of values of input parameters and sets of values of output characteristics within a user interface.

Abstract: A method executes at a server system with one or more processors and memory. The server receives demographic information for a plurality of household members. The demographic information includes at least age and gender. The server receives web activity information for the household. The server identifies one or more web activity sessions from the web activity information and selects one of the web activity sessions. The server identifies one or more web sites visited during the selected web activity session and accesses demographic skew data for at least a subset of the web sites visited. The demographic skew data for a web site identifies fractions of visitors to the web site from predefined demographic segments. The server associates a household member with the web activity session at least in part by correlating the demographic skew data of the web sites visited with the demographic information of the first household member.

Abstract: A computer-implemented method for collecting and managing TV viewership data from multiple TV metering data providers is disclosed. The method includes: receiving an event log file at a distributed computer system that includes multiple computers; dynamically selecting one or more computers according to a predefined sharding function; at each of the selected computers: allocating a set of compressed event records, which corresponds to a subset of the event log file, at predetermined locations within the memory of the computer; and in accordance with a predefined schedule, replicating the compressed event records from a respective one of the selected computers to one or more other computers of the distributed system such that there are at least two replicas of any event record on at least two computers of the distributed computer system.

Abstract: A method executes at a server system with one or more processors and memory. The server receives demographic information for a plurality of household members. The demographic information includes at least age and gender. The server receives television viewing information for the household. The server identifies one or more television viewing sessions from the television viewing information and selects one of the television viewing sessions. The server identifies one or more television programs tuned during the selected televisions viewing session and accesses demographic skew data for at least a subset of the television programs tuned. The demographic skew data for a television program identifies fractions of viewers of the television program from predefined demographic segments. The server associates a household member with the television viewing session at least in part by correlating the demographic skew data of the television programs tuned with the demographic information of the first household member.

Abstract: A method for providing efficient and accurate estimates of TV viewership ratings through a distributed computer system that includes multiple computers is disclosed. The method includes: receiving a query from a client at the distributed computer system; dynamically selecting one or more computers according to a predefined sharding function; at each of the selected computers, determining a count of qualified event records that satisfy the query; aggregating the respective counts of qualified event records determined by the selected computers; statistically projecting the aggregated count of qualified event records into an estimated total count of qualified event records on the distributed computer system; and returning the estimated total count of qualified event records to the requesting client.

Abstract: A method for providing efficient and accurate estimates of TV viewership ratings through a distributed computer system that includes multiple computers is disclosed. The method includes: receiving a query from a client at the distributed computer system; dynamically selecting one or more computers according to a predefined sharding function; at each of the selected computers, determining a count of qualified event records that satisfy the query; aggregating the respective counts of qualified event records determined by the selected computers; statistically projecting the aggregated count of qualified event records into an estimated total count of qualified event records on the distributed computer system; and returning the estimated total count of qualified event records to the requesting client.

Abstract: A computer-implemented method for collecting and managing TV viewership data from multiple TV metering data providers is disclosed. The method includes: receiving an event log file at a distributed computer system that includes multiple computers; dynamically selecting one or more computers according to a predefined sharding function; at each of the selected computers: allocating a set of compressed event records, which corresponds to a subset of the event log file, at predetermined locations within the memory of the computer; and in accordance with a predefined schedule, replicating the compressed event records from a respective one of the selected computers to one or more other computers of the distributed system such that there are at least two replicas of any event record on at least two computers of the distributed computer system.

Abstract: A system for logging the TV viewing activities at a household includes a TV messaging device at the household and a remote TV viewership measurement server communicatively coupled to the messaging device. The TV messaging device receives an infrared signal including a TV operation code from a remote control device within the household. The infrared signal is directed to a particular TV to perform a predefined operation. The TV messaging device generates a TV operation message including the TV operation code and a household identifier associated with the household and transmits the TV operation message to the TV viewership measurement server. Upon receipt of the TV operation message, the TV viewership measurement server tries to identify one of multiple TV devices within the household as being the target of the TV operation code and updates TV viewership data associated with the household in accordance with the TV operation code.

Abstract: Content information is received from a first client. The content information is derived from a video stream being played on the first client device. The content information is matched to a content fingerprint. A set of instructions associated with the matched content fingerprint is determined. The determined set of instructions is sent to a second client device that is associated with a user of the fist client device for execution.

Abstract: Content information is received from a first client. The content information is derived from a video stream being played on the first client device. The content information is matched to a content fingerprint. A set of instructions associated with the matched content fingerprint is determined. The determined set of instructions is sent to a second client device that is associated with a user of the fist client device for execution.

Abstract: A method of classifying cells into subpopulations using cell classifying data is described. The method comprises receiving and analyzing image data to identify object areas in the image data to determine, for at least one selected first cell, one or more measurements. A first parameter set is derived from the measurements for the first cell, the first parameter set comprising at least one of said one or more measurements. The first set of cells are classified into subpopulations, and identified to produce first identifying data. Cell classifying data for use in classifying a second set of cells into subpopulations is derived from the first parameter set and the first identifying data. A second set of cells is classified into subpopulations on the basis of one or more measurements taken for cells in the second set of cells, by use of the cell classifying data. The parameter sets of cells may be represented as vectors in an n-dimensional space.

Abstract: A method of classifying cells into subpopulations using cell classifying data is described. The method comprises receiving and analyzing image data to identify object areas in the image data to determine, for at least one selected first cell, one or more measurements. A first parameter set is derived from the measurements for the first cell, the first parameter set comprising at least one of said one or more measurements. The first set of cells are classified into subpopulations, and identified to produce first identifying data. Cell classifying data for use in classifying a second set of cells into subpopulations is derived from the first parameter set and the first identifying data. A second set of cells is classified into subpopulations on the basis of one or more measurements taken for cells in the second set of cells, by use of the cell classifying data. The parameter sets of cells may be represented as vectors in an n-dimensional space.