Abstract: The application relates to an anti-back-transfer intake structure of a rotating detonation combustion chamber including a Tesla valve communicating with the rotating detonation combustion chamber and arranged at an inlet of the rotating detonation combustion chamber. The Tesla valve includes a casing and a flow passage, the casing is coaxially connected with an outer wall of the rotating detonation combustion chamber, the flow passage is arranged in the casing, and the flow passage has an inlet end for introducing air, and an outlet end connected with an annular passage of the rotating detonation combustion chamber.

Abstract: Disclosed in this application are a visual content dialog method performed by an electronic device. The method includes: acquiring an image feature of an input image and state vectors corresponding to first n rounds of historical question answering dialog, n being a positive integer; acquiring a question feature of a current round of questioning related to the input image; performing multimodal encoding on the image feature of the input image, the state vectors corresponding to the first n rounds of historical question answering dialog, and the question feature of the current round of questioning, to obtain a state vector corresponding to the current round of questioning; and performing multimodal decoding on the state vector corresponding to the current round of questioning and the image feature of the input image, to obtain an actual output answer corresponding to the current round of questioning.

Abstract: The present disclosure provides a motor rotor and a permanent magnet motor. The motor rotor includes a rotor body. In a section perpendicular to a central axis of the rotor body, a first slot side has a first and a second endpoint, and a second slot side has a third and a fourth endpoint. A distance from a connecting line between the first endpoint and the third endpoint to a center of the rotor body is denoted by h1, a radius of the rotor body is denoted by R, and h1 and R satisfy 0.96?h1/R?0.99. A connecting line between the first endpoint and the center of the rotor body is a first connecting line, a connecting line between the third endpoint and the center of the rotor body is a second connecting line, and an included angle between the two connecting lines is denoted ? and satisfies: 3.7°???5.6°.

Abstract: The present disclosure provides a motor rotor and a permanent magnet motor. The motor rotor includes a rotor body. In a section perpendicular to a central axis of the rotor body, a first slot side has a first and a second endpoint, and a second slot side has a third and a fourth endpoint. A distance from a connecting line between the first endpoint and the third endpoint to a center of the rotor body is denoted by h1, a radius of the rotor body is denoted by R, and h1 and R satisfy 0.96?h1/R?0.99. A connecting line between the first endpoint and the center of the rotor body is a first connecting line, a connecting line between the third endpoint and the center of the rotor body is a second connecting line, and an included angle between the two connecting lines is denoted ? and satisfies: 3.7°???5.6°.

Abstract: A thermally protected varistor includes a varistor chip, a temperature fuse, and a lead line, wherein the varistor chip includes a first conductive layer and a second conductive layer, and the lead line includes a first lead line, a second lead line, and a third lead line. One end of the first lead line is connected to the first conductive layer, and the other end of the first lead line is led out. A first end of the temperature fuse is led out as the second lead line, and a second end of the temperature fuse is connected to the second conductive layer. One end of the third lead line is connected to the second conductive layer, and the other end of the third lead line is led out. The temperature fuse is an axial temperature fuse and is tightly attached to the varistor chip.

Abstract: A method for identifying a botnet in a network, including analyzing historical network data using a pre-determined heuristic to determine values of a connectivity graph based feature in the historical network data, obtaining a ground truth data set having labels assigned to data units in the historical network data identifying known malicious nodes in the network, analyzing the historical network data and the ground truth data set using a machine learning algorithm to generate a model representing the labels as a function of the values of the connectivity graph based feature, analyzing real-time network data using the pre-determined heuristic to determine a value of the connectivity graph based feature for a data unit in the real-time network data, assigning a label to the data unit by applying the model to the value of the connectivity graph based feature, and categorizing the data unit as associated with the botnet based on the label.

Abstract: Embodiments of the invention address the problem of detecting bots in network traffic based on a classification model learned during a training phase using machine learning algorithms based on features extracted from network data associated with either known malicious or known non-malicious client and applying the learned classification model to features extracted in real-time from current network data. The features represent communication activities between the known malicious or known non-malicious client and a number of servers in the network.