Abstract: Systems, methods, computing platforms, and storage media for decomposing data are disclosed. Exemplary implementations may receive an input data set, identify a first set of criteria for analyzing the input data set, identify a first and a second data subset, wherein the first and second data subset are defined by a first and a second set of filters, respectively, identify a first set of parent sets, each parent set being a subset of the input data set and a superset of the second data subset, and each parent set being defined by a subset of the second set of filters that define the second data subset, generate a directed acyclic graph based at least in part on identifying the first set of parent sets, the first data subset, and/or the second data subset, and display, via a user interface, the directed acyclic graph to a user.

Abstract: A quantitative pulse count (event detection) algorithm with linearity to high count rates is accomplished by combining a high-speed, high frame rate camera with simple logic code run on a massively parallel processor such as a GPU or a FPGA. The parallel processor elements examine frames from the camera pixel by pixel to find and tag events or count pulses. The tagged events are combined to form a combined quantitative event image.

Abstract: A quantitative pulse count (event detection) algorithm with linearity to high count rates is accomplished by combining a high-speed, high frame rate camera with simple logic code run on a massively parallel processor such as a GPU or a FPGA. The parallel processor elements examine frames from the camera pixel by pixel to find and tag events or count pulses. The tagged events are combined to form a combined quantitative event image.

Abstract: A quantitative pulse count (event detection) algorithm with linearity to high count rates is accomplished by combining a high-speed, high frame rate camera with simple logic code run on a massively parallel processor such as a GPU. The parallel processor elements examine frames from the camera pixel by pixel to find and tag events or count pulses. The tagged events are combined to form a combined quantitative event image.

Abstract: Systems, methods, computing platforms, and storage media for decomposing data are disclosed. Exemplary implementations may receive an input data set, identify a first set of criteria for analyzing the input data set, identify a first and a second data subset, wherein the first and second data subset are defined by a first and a second set of filters, respectively, identify a first set of parent sets, each parent set being a subset of the input data set and a superset of the second data subset, and each parent set being defined by a subset of the second set of filters that define the second data subset, generate a directed acyclic graph based at least in part on identifying the first set of parent sets, the first data subset, and/or the second data subset, and display, via a user interface, the directed acyclic graph to a user.

Abstract: A quantitative pulse count (event detection) algorithm with linearity to high count rates is accomplished by combining a high-speed, high frame rate camera with simple logic code run on a massively parallel processor such as a GPU. The parallel processor elements examine frames from the camera pixel by pixel to find and tag events or count pulses. The tagged events are combined to form a combined quantitative event image.

Abstract: The present inventions relate to improved acetabular cup positioning instruments and improved methods of positioning an acetabular cup. One embodiment of the present inventions is an acetabular cup positioning instrument that utilizes suction to form an attachment with an acetabular cup and a stabilization component to stabilize the connection between the acetabular cup positioning instrument and the acetabular cup.