Abstract: Aspects of the disclosure are directed to an approach for training a multivariate time series forecasting model using linear regression and ARIMA. The training may be performed by accessing data stored in a data warehouse using structure query language commands. The disclosure further provides for forecasting utilizing the trained model.

Abstract: A foldable electric bed frame that is relatively thinner in a folded state and easy to pack and transport includes a bed frame body, subframes, driving motors, bed boards, and detachable bed legs. The driving motors and the bed boards are connected to the bed frame body and the subframes. Flexible covering members are further comprised. The flexible covering members are arranged along the edges of the periphery of the bottom of the bed boards and are connected to the bottom of the bed boards through velcro or other detachable connecting members; and when the bed frame body is in a folded state, the flexible covering members are located between the stacked bed boards. The flexible covering members are arranged around the bed boards, and when the bed frame is folded, the flexible covering members are used as a buffering measure.

Abstract: An adjustable neck support includes a neck holder front support, a left side plate, a right side plate, a lower jaw holder plate, and a height adjustment knob. The left side plate is movably connected at a left end of the neck holder front support, the right side plate is movably connected at a right end of the neck holder front support, the lower jaw holder plate is connected between the left side plate and the right side plate, and the height adjustment knob is mounted on the neck holder front support. The height adjustment knob includes an operating cover and a winding post connected to the operating cover, the winding post being mounted in the neck holder front support. The adjustable neck support provided by the application is smooth in height adjustment operation, easy to operate, and long in service life.

Abstract: An adjustable neck support includes a neck holder front support, a left side plate, a right side plate, a lower jaw holder plate, and a height adjustment knob. The left side plate is movably connected at a left end of the neck holder front support, the right side plate is movably connected at a right end of the neck holder front support, the lower jaw holder plate is connected between the left side plate and the right side plate, and the height adjustment knob is mounted on the neck holder front support. The height adjustment knob includes an operating cover and a winding post connected to the operating cover, the winding post being mounted in the neck holder front support. The adjustable neck support provided by the application is smooth in height adjustment operation, easy to operate, and long in service life.

Abstract: A method for forecasting time-series data, when executed by data processing hardware, causes the data processing hardware to perform operations including receiving a time series forecasting query from a user requesting a time series forecast forecasting future data based on a set of current time-series data. The operations include obtaining, from the set of current time-series data, a set of training data. The operations include training, using a first portion of the set of training data, a first sub-model of a forecasting model and training, using a second portion of the set of training data, a second sub-model of the forecasting model. The second portion is different than the first portion. The operations include forecasting, using the forecasting model, the future data based on the set of current time-series data and returning, to the user, the forecasted future data for the time series forecast.

Abstract: A method includes receiving a time series anomaly detection query from a user and training one or more models using a set of time series data values. For each respective time series data value in the set, the method includes determining, using the trained models, an expected data value for the respective time series data value and determining a difference between the expected data value and the respective time series data value. The method also includes determining that the difference between the expected data value and the respective time series data value satisfies a threshold. In response to determining that the difference between the expected data value and the respective time series data value satisfies the threshold, the method includes determining that the respective time series data value is anomalous and reporting the anomalous respective time series data value to the user.

Abstract: A method and an authentication apparatus are provided by the embodiments of the present disclosure. In the embodiments of the present disclosure, data to be processed is obtained, a character sequence is generated based on the data, physiological feature information sequentially inputted by a user is received to obtain a feature information sequence and it is determined whether every piece of physiological feature information in the feature information sequence matches with the corresponding character in the character sequence.

Abstract: A method and an authentication apparatus are provided by the embodiments of the present disclosure. In the embodiments of the present disclosure, data to be processed is obtained, a character sequence is generated based on the data, physiological feature information sequentially inputted by a user is received to obtain a feature information sequence and it is determined whether every piece of physiological feature information in the feature information sequence matches with the corresponding character in the character sequence.