Abstract: Various implementations include an arm rest system. The system includes a housing, one or more actuators, and an arm cushion. The actuators are at least partially disposed within a cavity of the housing. Each of the actuators includes a cylinder defining an opening, a piston slidably disposed within the cylinder opening, and a piston rod having a first end coupled to the piston and a second end opposite and spaced apart from the first end. Each of the actuators is movable between a first position and a second position. One of the cylinder or the piston rod of each of the actuators is static with respect to the housing and the other is coupled to the arm cushion such that moving the actuators between the first and second positions moves the arm cushion relative to the housing.

Abstract: Various implementations include a bimini mountable camera device. The device includes a camera and first and second shell portions. The first shell portion has a first end and a second end. The first end of the first shell portion defines a central opening extending along a central axis to the second end of the first shell portion. The second end of the first shell portion defines a first groove extending along a first groove axis that extends perpendicular to the central axis. The second shell portion has a first end and a second end. The first end of the second shell portion is couplable to the second end of the first shell portion. The first end of the second shell portion defines a second groove extending along a second groove axis that extends parallel to the first groove axis. The camera is at least partially disposed within the central opening.

Abstract: Methods and apparatus to solve for a minimum variance solution for a constrained weight problem in a scalable and memory efficient manner are disclosed. An example instructions cause a machine to at least store a constraint matrix and a population matrix into a memory, the constraint matrix representing demographics associated with a plurality of panelists in a population, the population matrix representing second demographics of the population; determine a linear system based on a set of constraints including the constraint matrix and the population matrix; determine a solution to the linear system by determining an inverse of a first matrix of the linear system; and output a resultant set of weights based on the solution, the resultant set of weights satisfying the set of constraints.

Abstract: Methods and apparatus to solve for a minimum variance solution for a constrained weight problem in a scalable and memory efficient manner are disclosed.

Abstract: Methods and apparatus to solve for a minimum variance solution for a constrained weight problem in a scalable and memory efficient manner are disclosed.

Abstract: Methods and apparatus to solve for a minimum variance solution for a constrained weight problem in a scalable and memory efficient manner are disclosed. An example method of reducing memory usage of a computing device disclosed herein comprises storing a constraint matrix and a population matrix into a memory, the population matrix representing a population related to data of the constraint matrix, determining, via a processor, a linear system based on a set of constraints including the constraint matrix and the population matrix, determining, via a processor, an inverse of a matrix of the linear system, the determination of the inverse including breaking down the matrix into blocks, the dimensions of the blocks being no larger than dimensions of the constraint matrix, and outputting a set of weights based on the inverse of the linear system, the set of weights satisfying the set of constraints.

Abstract: Methods and apparatus to solve for a minimum variance solution for a constrained weight problem in a scalable and memory efficient manner are disclosed. An example method of reducing memory usage of a computing device disclosed herein comprises storing a constraint matrix and a population matrix into a memory, the population matrix representing a population related to data of the constraint matrix, determining, via a processor, a linear system based on a set of constraints including the constraint matrix and the population matrix, determining, via a processor, an inverse of a matrix of the linear system, the determination of the inverse including breaking down the matrix into blocks, the dimensions of the blocks being no larger than dimensions of the constraint matrix, and outputting a set of weights based on the inverse of the linear system, the set of weights satisfying the set of constraints.

Abstract: Methods, apparatus, systems and articles of manufacture to estimate demographics of an audience of a media event using social media message sentiment are disclosed. An example method includes calculating a sentiment score for a media-exposure social media message received from a social media server. The media-exposure social media message is identified based on a media keyword. Demographic information associated with users who viewed the media-exposure social media message is retrieved. An estimated impact on a size of a demographic segment of viewers is calculated using the sentiment score and the demographic information.

Abstract: Example methods and apparatus to determine demographic distributions of online users is disclosed. An example method includes obtaining first demographic information of first visitors to a first web site, obtaining second demographic information of second visitors to a second web site, the first and second visitors both comprising a same user, and determining a demographic distribution of the user based on the first and second demographic information.