Abstract: A method for regression and time series forecasting includes obtaining a set of hierarchical time series, each time series in the set of hierarchical time series including a plurality of time series data values. The method includes determining, using the set of hierarchical time series, a basis regularization of the set of hierarchical time series and an embedding regularization of the set of hierarchical time series. The method also includes training a model using the set of hierarchical time series and a loss function based on the basis regularization and the embedding regularization. The method includes forecasting, using the trained model and one of the time series in the set of hierarchical time series, an expected time series data value in the one of the time series.

Abstract: The present invention discloses a shale stress sensitivity testing device and method. The testing device comprises a support table. The left and right ends of the upper surface of the support table are respectively provided with a left side plate and a right side plate. The top of the left and right side plates are connected with the left and right ends of the top plate. The chucks of the clamps are capable of reciprocating motion in the horizontal direction and circular motion in the front-rear direction. The present invention can change the intensity and direction of the effective stress of the rock sample, and determine the permeability of the rock sample under different effective stresses, thus enabling comprehensive testing of the stress sensitivity of shale in different directions and enhancing the accuracy of shale stress sensitivity testing.

Abstract: Location history data can be used to identify attributes for a known geographic location of a business listing record for a business. As an example, location history data is received from each of a plurality of client computing devices. For each device, the location history data identifies an arrival and departure times for the known geographic location as well as prior and next visit information. The location history data is used as input into a classifier in order to identify a set of attributes for the geographic location and corresponding likelihood values for each of the attributes of the set of attributes. A subset of the set of attributes is determined such that the attributes describe aspects of the known geographic location based on the likelihood values. This subset is provided to a client computing device in response to a request for information about the geographic location.

Abstract: A double-stator and electric machine suitable for achieving sensorless control of the absolute position of a rotor. An inner stator is fixed to a stationary shaft, an outer stator and the inner stator are concentric, and the above components form a stationary part of the electric machine. A rotor is assembled between the outer stator and the inner stator, and forms a rotating part of the electric machine with a moving shaft through a front rotor support. The rotating part is isolated from a front end cap through a front outer bearing. The rotating part is isolated from a back end cap through a back outer bearing after the rotating part is connected with a back rotor support. The moving shaft is isolated from the stationary shaft through an inner bearing.