Abstract: A neighboring user node of a user node is selected by using an attention model, to determine a selective adjacency matrix of a relation network based on the selected neighboring user node. Then, a neighboring node representation is propagated to a corresponding user node based on a selective adjacency matrix by using a graph neural network, to obtain a user aggregation representation. A tapping behavior between a user and an object is fitted based on a similarity between the user aggregation representation and an object representation, to construct a prediction loss based on a difference between the tapping behavior and an existing tapping behavior, and update the attention model. The trained attention model can select a more reliable neighboring user.

Abstract: The present invention relates generally to a therapeutic protocol for treating a subject having cancer. Taught herein is a method of treating cancer or reducing the risk of recurrence of cancer in a subject following an anti-cancer therapy.

Abstract: A plug-in device and a power conversion apparatus are provided. The plug-in device includes a housing, a connector and a temperature acquisition device. The housing is defined with a holding cavity. The connector includes a clamping part and a fixed connection part. The clamping part is arranged in the holding cavity. The fixed connection part partially extends out of the housing. The clamping part is configured to clamp a power conversion device. The fixed connection part is connected to a reactor. The temperature acquisition device is arranged close to the connector, and is configured to acquire a temperature at an overlapping point of the power conversion device and the clamping part.

Abstract: The present invention relates generally to a therapeutic protocol for treating a subject having cancer. Taught herein is a method of treating cancer or reducing the risk of recurrence of cancer in a subject following an anti-cancer therapy.

Abstract: An attachable self-resistance heating/super-hydrophobic integrated gradient film material. The film material is made of an adhesive resin, an electrically and thermally insulative resin, a thermally and electrically conductive filler, and a thermally conductive insulating filler. The adhesive resin and the electrically and thermally insulative resin respectively form an adhesive layer and a base body, and the two are bonded together. The thermally and electrically conductive filler and the thermally conductive insulating filler are respectively added to an intermediate layer and an upper layer of the base body, to divide the base body into three gradient regions from top to bottom, wherein a super-hydrophobic structure is constructed on the surface of the uppermost area.

Abstract: The present specification relates generally to a therapeutic protocol for treating a subject having cancer. Taught herein is a method of treating cancer or reducing the risk of recurrence of cancer in a subject following an anti-cancer therapy.

Abstract: The preset application discloses a method for route planning. At least one device including at least one processor and a storage may implement the method. The method may include one or more of the following operations. The device may first obtain a start location and a destination, road characteristic information and a plurality of historical routes. The device may then train a model based on the plurality of historical routes. Then the device may run the trained model to sequentially determine a plurality of road intersections between the start location and the destination, and a target entrance and target exit that corresponding to each of the plurality of the road intersections based on characteristic information. Finally, the device may generate a recommended route from the start location to the based on the target entrances and target exits.

Abstract: The preset application discloses a method for route planning. At least one device including at least one processor and a storage may implement the method. The method may include one or more of the following operations. The device may first obtain a start location and a destination, road characteristic information and a plurality of historical routes. The device may then train a model based on the plurality of historical routes. Then the device may run the trained model to sequentially determine a plurality of road intersections between the start location and the destination, and a target entrance and target exit that corresponding to each of the plurality of the road intersections based on characteristic information. Finally, the device may generate a recommended route from the start location to the based on the target entrances and target exits.

Abstract: The present specification relates generally to a therapeutic protocol for treating a subject having cancer. Taught herein is a method of treating cancer or reducing the risk of recurrence of cancer in a subject following an anti-cancer therapy.

Abstract: The present invention discloses a method for recognizing a handwritten character, which includes the following steps of: obtaining a coarse classification template and a fine classification template; receiving a handwritten character input signal from a user, gathering a discrete coordinate sequence of trajectory points of the inputted character, and pre-processing the discrete coordinate sequence; extracting eigenvalues and calculating a multi-dimensional eigenvector of the inputted character; matching the inputted character with the coarse classification template to select a plurality of the most similar candidate character classes; and matching the eigen-transformed inputted character with sample centers of the candidate character classes selected from the fine classification template, and determining the most similar character classes among the candidate character classes. The present invention further discloses a system for recognizing a handwritten character.

Abstract: The present invention discloses a method for recognizing a handwritten character, which includes the following steps of: obtaining a coarse classification template and a fine classification template; receiving a handwritten character input signal from a user, gathering a discrete coordinate sequence of trajectory points of the inputted character, and pre-processing the discrete coordinate sequence; extracting eigenvalues and calculating a multi-dimensional eigenvector of the inputted character; matching the inputted character with the coarse classification template to select a plurality of the most similar candidate character classes; and matching the eigen-transformed inputted character with sample centers of the candidate character classes selected from the fine classification template, and determining the most similar character classes among the candidate character classes. The present invention further discloses a system for recognizing a handwritten character.