Abstract: Disclosed herein is a golf club head comprising at least one crown opening and at least one crown insert attached to the body and covering the at least one crown opening. The golf club head further comprises at least one sole opening and at least one sole insert attached to the body and covering the at least one sole opening. The golf club head additionally includes at least one weight member configured to clamp first and second ledges at selected locations along a sliding weight track. The golf club head also comprise a coefficient of restitution (COR) feature located on the sole of the golf club head. The at least one crown insert is formed from a composite material having a density between 1 g/cc and 2 g/cc. The at least one sole insert is formed from a composite material having a density between 1 g/cc and 2 g/cc.

Abstract: Generating a data model may include receiving a raw data set and generating a first repository based on a first set of features of the raw data set, a second repository having a second set of features based on an aggregation of features of the first repository, and a third repository having a third set of features based on the first and second features sets. The data model may be generated based on a tradeoff between accuracy and provenance of the model.

Abstract: Generating a data model may include receiving a raw data set and generating a first repository based on a first set of features of the raw data set, a second repository having a second set of features based on an aggregation of features of the first repository, and a third repository having a third set of features based on the first and second features sets. The data model may be generated based on a tradeoff between accuracy and provenance of the model.

Abstract: Generating a data model may include receiving a raw data set and generating a first repository based on a first set of features of the raw data set, a second repository having a second set of features based on an aggregation of features of the first repository, and a third repository having a third set of features based on the first and second features sets. The data model may be generated based on a tradeoff between accuracy and provenance of the model.

Abstract: Generating a data model may include receiving a raw data set and generating a first repository based on a first set of features of the raw data set, a second repository having a second set of features based on an aggregation of features of the first repository, and a third repository having a third set of features based on the first and second features sets. The data model may be generated based on a tradeoff between accuracy and provenance of the model.

Abstract: Generating a data model may include receiving a raw data set and generating a first repository based on a first set of features of the raw data set, a second repository having a second set of features based on an aggregation of features of the first repository, and a third repository having a third set of features based on the first and second features sets. The data model may be generated based on a tradeoff between accuracy and provenance of the model.

Abstract: Various embodiments perform a fair ranking of citizen sensor reports. In one embodiment, a plurality of citizen sensor reports is received. Each of the plurality of citizen sensor reports is associated with a reporting target. At least one context event is identified for each of the plurality of citizen sensor reports. An impact factor is calculated for each the identified context events with respect to their citizen sensor reports. A rank is assigned to each of the plurality of citizen sensor reports with respect to each remaining citizen sensor report in the plurality of citizen sensor reports. The rank is determined based on at last a set of information within the citizen sensor report and the impact factor calculated for the citizen sensor report.

Abstract: A method for providing health-related recommendations based on previous end-user travel reports including: receiving data indicative of a current location or destination of a user; calculating correlation probabilities between a plurality physical conditions reported by a plurality of users in the current location or destination versus parameters of health context information of the current location or destination versus parameters of the user's profile; and providing the user with a personalized health-related recommendation based on the calculated correlation probabilities.

Abstract: Generating a data model may include receiving a raw data set and generating a first repository based on a first set of features of the raw data set, a second repository having a second set of features based on an aggregation of features of the first repository, and a third repository having a third set of features based on the first and second features sets. The data model may be generated based on a tradeoff between accuracy and provenance of the model.