Abstract: Aspects of the disclosure are directed methods, systems, and computer readable media for in-database holiday effect modeling for time series forecasting. The modeling can be accurate, explainable, customizable, and scalable. Machine learning models can receive a first dataset for time series data and a second dataset for configurable holiday data. The models can detect and model effects of each configurable holiday on one or more forecasts, effectively accumulating effects of overlapping holidays, to manage different levels of holiday modeling. Holiday data can be customizable, including an ability to modify existing holidays and/or add new holidays, through one or more interfaces that can display default holiday information, combined holiday information based on both default and customizable holidays, effects of each holiday on forecasts, and accumulated effects of multiple holidays on forecasts.

Abstract: The present disclosure provides a knob type rope adjuster, includes a base, a rope winding disc, a knob, and an unlocking button; the rope winding disc used for winding an adjustment rope is rotatably installed in the base; the knob is installed on the base in an unidirectional rotation mode; the knob is combined with the rope winding disc to drive the rope winding disc to rotate via the knob, thereby winding and locking the adjustment rope; the unlocking button is connected to the rope winding disc and passes through the knob, thereby switching combination or separation of the knob and the rope winding disc; the knob is separated from the rope winding disc, so that the rope winding disc is arranged to rotate in a direction opposite to the winding direction, thereby loosening the adjustment rope, the adjustment rope remains locked on the rope winding disc to avoid loosening.

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: 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.