Abstract: A computer-implemented method for training an encoder. The encoder is configured for determining a latent representation of an image. Training the encoder includes: determining a latent representation and a noise image by providing a training image to the encoder, wherein the encoder is configured for determining a latent representation and a noise image for a provided image; masking out parts of the noise image, thereby determining a masked noise image; determining a predicted image by providing the latent representation and the masked noise image to a generator of a generative adversarial network; training the encoder by adapting parameters of the encoder based on a loss value, wherein the loss value characterizes a difference between the predicted image and the training image.

Abstract: A computer-implemented method of processing digital image data. The method includes: determining, by an encoder configured to map a first digital image to an extended latent space associated with a generator of a generative adversarial network, GAN, system, a noise prediction associated with the first digital image, determining, by the generator of the GAN system, at least one further digital image based on the noise prediction associated with the first digital image and a plurality of latent variables associated with the extended latent space.

Abstract: A method for trajectory generation based on player tracking is described herein. The method includes determining a temporal association for a first player in a captured field of view and determining a spatial association for the first player. The method also includes deriving a global player identification based on the temporal association and the spatial association and generating a trajectory based on the global player identification.

Abstract: Provided are a bovine rotavirus fusion protein and calf diarrhea multivalent vaccine. The bovine rotavirus fusion protein contains a VP6 fragment, wherein the VP6 fragment contains an amino acid sequence as represented by SEQ ID NO. 4, and at least one loop region of the following (a)˜(c) is substituted with an antigenic epitope derived from bovine coronavirus and/or an antigenic epitope derived from E. coli: (a) amino acid residues of sites 168-177; with an amino acid sequence as represented by SEQ ID NO. 1; (b) amino acid residues of sites 194-205; with an amino acid sequence as represented by SEQ ID NO. 2; and (a) amino acid residues of sites 296-316, with an amino acid sequence as represented by SEQ ID NO. 3, The bovine rotavirus fusion protein contains a plurality of antigenic epitopes, and can enable a host to generate a plurality of antibodies after immunizing the host.

Abstract: Oral care based imaging computer-implemented systems and methods for analyzing attributes of a facial image portion of at least one person depicted in a digital image. An oral care digital imaging computer-implemented method for analyzing a facial image portion of a person depicted in a digital image may include analyzing the facial image portion for positive and negative attributes as defined by pixel data of the digital image and generating a probability value based on the positive and negative attributes in the facial image portion in the digital image.

Abstract: The present disclosure provides a sintered neodymium-iron-boron permanent magnet, a preparation method and use thereof. The permanent magnet described herein comprises a grain and a grain boundary phase. The grain boundary phase is located on an epitaxial layer of the grain. The grain boundary phase comprises at least an RH. The grain comprises at least Nd2Fe14B. In the grain boundary phase within a depth of 100 ?m from the surface to the center of the sintered neodymium-iron-boron permanent magnet, the area of the grain boundary phase with an RH content of more than 6 wt % accounts for 50% or more of the total area of the grain boundary phase. The present disclosure adopts an RH and an RL as the diffusion source for composite diffusion, significantly improving the coercivity of the permanent magnet and the utilization rate of the RH in the diffusion source.

Abstract: An information sharing method includes that a first redundancy device generates a first supervision frame that includes device information of the first redundancy device, where the first supervision frame detects whether a second redundancy device on a transmission link on which the first redundancy device is located in the redundancy network is in a working state, where the first redundancy device is any redundancy device in the redundancy network; and where the first redundancy device sends the first supervision frame to the second redundancy device in a multicast manner. The device information of the redundancy device is carried in the supervision frame.

Abstract: A method for ascertaining a 6D pose of an object. The method includes the following steps: providing image data, wherein the image data include target image data showing the object and labeled comparison image data relating to the object, and ascertaining the 6D pose of the object based on the provided image data using a meta-learning algorithm.

Abstract: A computer-based airplane flight path planning method based on the pigeon-inspired optimization (PIO) algorithm includes steps of establishing an uncertainty prediction model, determining the path to be optimized, and obtaining an optimal path using the PIO algorithm for a flight controller onboard to execute. The PIO algorithm treats a pigeon flock as a scale-free network, applies map and compass operators to the scale-free network, and performs landmark operations to obtain the optimal path. The device that performs the path planning includes an access module for obtaining the regional environment information and a flight controller onboard the airplane. The flight controller includes a building module for setting up the trajectory prediction model including uncertainties; a determining module to determine the trajectories which need optimization; an optimization module, which uses the PIO algorithm to optimize the flight path; and a computer memory module.

Abstract: A sector situation (SS) evaluation framework is based on knowledge transfer and is specifically applicable for small-training-sample environment. The SS evaluation framework is able to effectively mine knowledge hidden within the samples of both target and non-target sectors, and properly handle the integration between the knowledge derived from different sectors. This framework includes three main steps: (1) sufficiently mine the knowledge within the samples of the target sector using the strategies of multi-factor subset generation and multi-base evaluator construction, and build target base evaluators; (2) precisely learn the knowledge in the samples of the non-target sectors using similar strategies for the target sector, together with a sample transformation, and build non-target base evaluators; and (3) efficiently integrate the target and non-target base evaluators based on evaluation confidence analysis of those base evaluators.

Abstract: An interaction method, device and equipment for operable object. The mobile terminal acquires a moving direction and a moving displacement when moving (S101); an initial position of an operable object is an original position of the operable object before the mobile terminal moves; the mobile terminal determines, according to the moving direction, the moving displacement, and the initial positions of the operable objects, determines an application to be launched corresponding to a screen of the mobile terminal; the application to be launched is displayed on the screen of the mobile terminal (S102); and the application to be launched is launched (S103).

Abstract: Provided are flight conflict resolution method and apparatus based on ultimatum game theory. The method includes: obtaining a first priority of a first aircraft and a second priority of a second aircraft when it is determined that a minimum distance between the first aircraft and the second aircraft within a preset time period is less than a preset distance; determining a first angle and a second angle of the first aircraft and a fourth angle and a fifth angle of the second aircraft according to the first priority, the second priority, and a preset limiting deflection angle; determining a third angle of the first aircraft and a sixth angle of the second aircraft; determining a first deflection angle of the first aircraft and a second deflection angle of the second aircraft according to the first and second priorities, the first, second, third, fourth, fifth and sixth angles.

Abstract: This application provides an airspace complexity evaluation method based on deep unsupervised learning for air traffic management, which includes the following parts. A stacked autoencoder is used to establish an airspace complexity evaluation model. Input the airspace complexity factors into the stacked autoencoder to obtain the low-dimensional embedded representations of the airspace complexity factors. Cluster the low-dimensional embedded points to capture the centroids of the airspace complexity data. The application utilizes the soft assignment distribution and real assignment distribution of the embedded representations to construct a training loss function which optimizes the airspace complexity evaluation model by gradient descent algorithm. The trained airspace complexity evaluation model and the three obtained cluster centroids describing the airspace complexity level are used to evaluate the current airspace complexity.

Abstract: A method, a device and a mobile terminal for data transmission are provided. The transmission method is applied in the mobile terminal, when a user wants to share data, target data can be determined in a present application by the mobile terminal, then the mobile terminal is moved to obtain a moving direction and a moving displacement when the mobile terminal moves; an application currently corresponding to the screen of the mobile terminal is determined according to the moving direction, the moving displacement and an initial position of each application; when a predetermined condition is satisfied, an application corresponding to the screen of the mobile terminal is determined to be a target application, and the determined target data are transmitted to the target application; it only needs to move the mobile terminal to determine the target application when a predetermined condition is met for transmitting data to the target application.

Abstract: An interaction method, device and equipment for operable object.

Abstract: A computer-based airplane flight path planning method based on the pigeon-inspired optimization (PIO) algorithm includes steps of establishing an uncertainty prediction model, determining the path to be optimized, and obtaining an optimal path using the PIO algorithm for a flight controller onboard to execute. The PIO algorithm treats a pigeon flock as a scale-free network, applies map and compass operators to the scale-free network, and performs landmark operations to obtain the optimal path. The device that performs the path planning includes an access module for obtaining the regional environment information and a flight controller onboard the airplane. The flight controller includes a building module for setting up the trajectory prediction model including uncertainties; a determining module to determine the trajectories which need optimization; an optimization module, which uses the PIO algorithm to optimize the flight path; and a computer memory module.

Abstract: A method, a device and a mobile terminal for data transmission are provided. The transmission method is applied in the mobile terminal, when a user wants to share data, target data can be determined in a present application by the mobile terminal, then the mobile terminal is moved to obtain a moving direction and a moving displacement when the mobile terminal moves; an application currently corresponding to the screen of the mobile terminal is determined according to the moving direction, the moving displacement and an initial position of each application; when a predetermined condition is satisfied, an application corresponding to the screen of the mobile terminal is determined to be a target application, and the determined target data are transmitted to the target application; it only needs to move the mobile terminal to determine the target application when a predetermined condition is met for transmitting data to the target application.

Abstract: Provided are flight conflict resolution method and apparatus based on ultimatum game theory. The method includes: obtaining a first priority of a first aircraft and a second priority of a second aircraft when it is determined that a minimum distance between the first aircraft and the second aircraft within a preset time period is less than a preset distance; determining a first angle and a second angle of the first aircraft and a fourth angle and a fifth angle of the second aircraft according to the first priority, the second priority, and a preset limiting deflection angle; determining a third angle of the first aircraft and a sixth angle of the second aircraft; determining a first deflection angle of the first aircraft and a second deflection angle of the second aircraft according to the first and second priorities, the first, second, third, fourth, fifth and sixth angles.

Abstract: A sector situation (SS) evaluation framework is based on knowledge transfer and is specifically applicable for small-training-sample environment. The SS evaluation framework is able to effectively mine knowledge hidden within the samples of both target and non-target sectors, and properly handle the integration between the knowledge derived from different sectors. This framework includes three main steps: (1) sufficiently mine the knowledge within the samples of the target sector using the strategies of multi-factor subset generation and multi-base evaluator construction, and build target base evaluators; (2) precisely learn the knowledge in the samples of the non-target sectors using similar strategies for the target sector, together with a sample transformation, and build non-target base evaluators; and (3) efficiently integrate the target and non-target base evaluators based on evaluation confidence analysis of those base evaluators.

Abstract: An airplane flight path planning method based on the pigeon-inspired optimization algorithm includes steps of establishing an uncertainty track prediction model, determining the path to be optimized within the specified area, and obtaining an optimal path using the pigeon-inspired optimization algorithm. The pigeon-inspired optimization algorithm uses map and compass operators and performs landmark operations to obtain the optimal path. The device that performs the path planning includes an access module for getting the regional path information; a building module for setting up the trajectory prediction model including uncertainties; a determining module, which utilizes the regional path information and the trajectory prediction model to determine the trajectories which need optimization; and an optimization module, which uses the pigeon-inspired optimization algorithm to optimize the trajectories.