Abstract: Systems and methods identify a behavior in multivariate time-series data. The systems and methods receive data representing a time series having steps each representing an event associated with a time stamp and being associated with one or more attributes; transform the data into a tensor; train a model using training data comprising a set of tensors; identify the behavior using predictions from the trained model and a target pattern; and provide an indication of the presence or absence of the behavior.

Abstract: Systems and methods for identifying a pattern in data to detect a behavior of interest. The systems and methods receive a data stream representing a series of events occurring over a time interval. The systems and methods determine, for the interval, a depth indicating the amount of interest during the interval, where the interest represents an amount of a selected activity during that interval for a selected parameter. The systems and methods also generate a depth chart for the activities at different values of the selected parameter over a series of intervals, train a machine-learning image-classification model using depth chart images; identify the behavior of interest using predictions from the trained machine-learning model and target pattern; and provide an indication of the presence or absence of the behavior of interest. The parameter can represent a quantity and associated price of a commodity in a market.

Abstract: Systems and methods identify a behavior in multivariate time-series data. The systems and methods receive data representing a time series having steps each representing an event associated with a time stamp and being associated with one or more attributes; transform the data into a tensor; train a model using training data comprising a set of tensors; identify the behavior using predictions from the trained model and a target pattern; and provide an indication of the presence or absence of the behavior.

Abstract: Systems and methods for identifying a pattern in data to detect a behavior of interest. The systems and methods receive a data stream representing a series of events occurring over a time interval. The systems and methods determine, for the interval, a depth indicating the amount of interest during the interval, where the interest represents an amount of a selected activity during that interval for a selected parameter. The systems and methods also generate a depth chart for the activities at different values of the selected parameter over a series of intervals, train a machine-learning image-classification model using depth chart images; identify the behavior of interest using predictions from the trained machine-learning model and target pattern; and provide an indication of the presence or absence of the behavior of interest. The parameter can represent a quantity and associated price of a commodity in a market.

Abstract: Provided is a portable heating rod for heating a beverage in a container and a method of using the same. The portable heating rod comprises a handle portion and a heating portion coupled to the handle portion along a longitudinal direction. The handle portion includes a first housing made of a heat insulating material, a control interface, a control circuit board and a power source within the first housing. The heating portion includes a second housing made of a heat conductive material, at least one heating element and at least one temperature sensor. During operation, the heating portion of the portable heating rod is at least partly immersed in the beverage.

Abstract: Provided is a portable heating rod for heating a beverage in a container and a method of using the same. The portable heating rod comprises a handle portion and a heating portion coupled to the handle portion along a longitudinal direction. The handle portion includes a first housing made of a heat insulating material, a control interface, a control circuit board and a power source within the first housing. The heating portion includes a second housing made of a heat conductive material, at least one heating element and at least one temperature sensor. During operation, the heating portion of the portable heating rod is at least partly immersed in the beverage.