Abstract: The disclosure discloses a method for detecting an intrusion in parallel based on an unbalanced data Deep Belief Network, which reads an unbalanced data set DS; under-samples the unbalanced data set using the improved NCR algorithm to reduce the ratio of the majority type samples and make the data distribution of the data set balanced; the improved differential evolution algorithm is used on the distributed memory computing platform Spark to optimize the parameters of the deep belief network model to obtain the optimal model parameters; extract the feature of data of the data set, and then classify the intrusion detection by the weighted nuclear extreme learning machine, and finally train multiple weighted nuclear extreme learning machines of different structures in parallel by multithreading as the base classifier, and establish a multi-classifier intrusion detection model based on adaptive weighted voting for detecting the intrusion in parallel.

Abstract: An electronic device low-temperature protection method includes: obtaining, by an electronic device, an environmental temperature and a temperature of a battery of the electronic device; determining, by the electronic device based on the environmental temperature and the temperature of the battery, that the electronic device is in a low-temperature environment; and implementing, by the electronic device, low-temperature protection in response to the determined being in the low-temperature environment. According to the electronic device low-temperature protection method provided in this application, both the environmental temperature and the temperature of the battery are considered, and whether the electronic device is in a low-temperature state is detected based on the environmental temperature and the temperature of the battery.

Abstract: The present disclosure provides a resource allocation method and apparatus, a readable medium and an electronic device. The method includes: acquiring a target resource type corresponding to a target task; acquiring a plurality of resource types of a target processor, wherein each resource type corresponds to one or more virtual processor resources of the target processor; determining a specified resource type that is identical to the target resource type from the plurality of resource types; determining a target processor resource from one or more virtual processor resources corresponding to the specified resource type; and allocating the target processor resource to the target task.

Abstract: A computer-implemented method for partially supervised image segmentation having improved strong mask generalization includes obtaining, by a computing system including one or more computing devices, a machine-learned segmentation model, the machine-learned segmentation model including an anchor-free detector model and a deep mask head network, the deep mask head network including an encoder-decoder structure having a plurality of layers. The computer-implemented method includes obtaining, by the computing system, input data including tensor data. The computer-implemented method includes providing, by the computing system, the input data as input to the machine-learned segmentation model. The computer-implemented method includes receiving, by the computing system, output data from the machine-learned segmentation model, the output data including a segmentation of the tensor data, the segmentation including one or more instance masks.

Abstract: The present disclosure relates to a visible light-catalyzed translucent concrete, and a preparation method and use thereof. The preparation method includes: extracting an iron oxide from a copper slag, mixing the iron oxide with TiO2 to obtain a photocatalyst, and then mixing the photocatalyst with an additive to obtain a photocatalytic slurry; preparing a concrete slurry using the copper slag after iron extraction as an aggregate; and pouring the photocatalytic slurry, the concrete slurry, and the photocatalytic slurry in sequence into a mold pre-laid with an optical fiber, to obtain the visible light-catalyzed translucent concrete. In the visible light-catalyzed translucent concrete, iron in the copper slag is used as a part of raw materials of the photocatalyst, and the copper slag after iron extraction is used as an aggregate to replace natural sand and gravel. This solves environmental pollutions caused by the copper slag and realizes resource utilization.

Abstract: Provided are a neural network training method and apparatus for image retrieval, and an electronic device. A neural network includes: one feature extractor and a plurality of learners. The method includes: for each training image group, inputting three images of the training image group into the feature extractor, and determining features of the three images (501); for each image in each training image group, respectively multiplying the features of the image by a random weight corresponding to each learner, so as to obtain weighted features corresponding to each learner (502); for each image in each training image group, inputting the weighted features of the image corresponding to each learner into the corresponding learner, and determining a plurality of feature vectors of the image (503); and adjusting parameters of the neural network on the basis of the plurality of feature vectors of each image in a plurality of training image groups (504).

Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. A server retrieves a set of nodes and generates a primary prediction model using data aggregated based on all nodes. The server then executes various clustering algorithms in order to segment the nodes into different clusters. The server then generates a secondary (corrective) prediction model to calculate a correction needed to improve the results achieved by executing the primary prediction model for each cluster. When a node with unknown/limited data and attributes is identified, the server identifies a cluster most similar the new node and further identifies a corresponding secondary prediction model. The server then executes the primary prediction model in conjunction with the identified secondary prediction model to populate a graphical user interface with an accurate predicted future attribute for the new node.

Abstract: A media application receives user input that indicates one or more objects to be erased from a media item. The media application translates the user input to a bounding box. The media application provides a crop of the media item based on the bounding box to a segmentation machine-learning model. The segmentation machine-learning model outputs a segmentation mask for one or more segmented objects in the crop of the media item and a corresponding segmentation score that indicates a quality of the segmentation mask.

Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. A server retrieves a set of nodes and generates a primary prediction model using data aggregated based on all nodes. The server then executes various clustering algorithms in order to segment the nodes into different clusters. The server then generates a secondary (corrective) prediction model to calculate a correction needed to improve the results achieved by executing the primary prediction model for each cluster. When a node with unknown/limited data and attributes is identified, the server identifies a cluster most similar the new node and further identifies a corresponding secondary prediction model. The server then executes the primary prediction model in conjunction with the identified secondary prediction model to populate a graphical user interface with an accurate predicted future attribute for the new node.

Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. The systems and methods described herein retrieve a set of nodes and execute various clustering algorithms in order to segment the nodes into different clusters. The systems and methods described herein also describe generating one or more prediction models, such as time-series models, for each cluster of nodes. When a node with unknown/limited data and attributes is identified, the methods and systems described herein first identify a cluster most similar the new node, identify a corresponding prediction model, and execute the identified prediction model to calculate future attribute of the new node.

Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. The systems and methods described herein retrieve a set of nodes and execute various clustering algorithms in order to segment the nodes into different clusters. The systems and methods described herein also describe generating one or more prediction models, such as time-series models, for each cluster of nodes. When a node with unknown/limited data and attributes is identified, the methods and systems described herein first identify a cluster most similar the new node, identify a corresponding prediction model, and execute the identified prediction model to calculate future attribute of the new node.

Abstract: An electronic device low-temperature protection method includes: obtaining, by an electronic device, an environmental temperature and a temperature of a battery of the electronic device; determining, by the electronic device based on the environmental temperature and the temperature of the battery, that the electronic device is in a low-temperature environment; and implementing, by the electronic device, low-temperature protection in response to the determined being in the low-temperature environment. According to the electronic device low-temperature protection method provided in this application, both the environmental temperature and the temperature of the battery are considered, and whether the electronic device is in a low-temperature state is detected based on the environmental temperature and the temperature of the battery.

Abstract: An application control method and an electronic device are provided. The method includes: The electronic device displays a first user interface of a first application, where the first user interface has N graphical controls; and the electronic device updates the first user interface if a temperature of the electronic device is less than or equal to a first preset temperature, so that an updated first user interface has less than N graphical controls, where N is a natural number greater than 1. In this manner, when the electronic device has a relatively low temperature, a user may be restricted from using some functions of an application.

Abstract: The invention provides a mud circulation system for reducing swab pressure while tripping out, including drilling tool components, a normal drilling circulation channel and a tripping circulation channel, the drilling tool components include a drill string, a drill bit, and a top drive, the normal drilling circulation channel includes a first rotary valve, a solid phase control device, a mud tank, a mud pump, and a forth rotary valve connected in sequence, the tripping circulation channel includes a second rotary valve, a tripping mud pump, a tripping mud tank and a third rotary valve connected in sequence; the mud circulation system for reducing the swab pressure is operated to: shut down the mud pump, close the first rotary valve, and open the second rotary valve and the third rotary valve before tripping out; determine the pumping flow rate according to relevant parameters.

Abstract: The invention provides a mud circulation system for reducing swab pressure while tripping out, including drilling tool components, a normal drilling circulation channel and a tripping circulation channel, the drilling tool components include a drill string, a drill bit, and a top drive, the normal drilling circulation channel includes a first rotary valve, a solid phase control device, a mud tank, a mud pump, and a forth rotary valve connected in sequence, the tripping circulation channel includes a second rotary valve, a tripping mud pump, a tripping mud tank and a third rotary valve connected in sequence; the method to operate the mud circulation system for reducing the swab pressure is as follows: shutting down the mud pump, closing the first rotary valve, and opening the second rotary valve and the third rotary valve before tripping out; determining the pumping flow rate according to relevant parameters.

Abstract: A camera control method and a terminal the method including starting, by a terminal, a first camera and a second camera, where the first camera and the second camera are located on a same side of the terminal, and where the first camera operates in a first operating state, and switching the first camera from the first operating state to a second operating state in response to an operating parameter of the terminal meeting a preset condition, where the second operating state is a low power consumption state or a closed state.