Abstract: A method of recommending an object, an electronic device, and a storage medium are provided. The method includes: determining, in response to receiving target user behavior data of a target user from a target client, a target object according to the target user behavior data and at least one candidate user behavior data corresponding to a plurality of candidate users; and sending the target object to the target client, so as to recommend the target object to the target user, where each of the candidate user behavior data is stored in a predetermined block chain, each of the candidate user behavior data corresponds to at least one of a plurality of block chain nodes contained in a block chain network, and each of the candidate user behavior data indicates a preference of a candidate user for at least one candidate object.

Abstract: The present disclosure provides a method of processing an agreement task, which relates to a field of an Internet technology. The method includes: determining, in response to an acquired agreement task request, a task event model and task event data associated with the agreement task request as an event configuration information; calling a target smart contract associated with the event configuration information, so as to generate an agreement task event matching the agreement task request based on the target smart contract; performing, in response to acquired event response data of a target business node for the agreement task event, a legitimacy verification on the event response data; and on-chaining, in response to the verification being successful, the agreement task event and the event response data in a blockchain.

Abstract: Disclose are a roadway/tunnel excavation robot and an automatic cutting control method. The robot includes a rack, a moving platform, a supporting and stabilizing mechanism, a milling mechanism, a telescoping mechanism, an inclined cutting feed adjusting mechanism, a horizontal swinging mechanism, a lifting mechanism and a controller. The milling mechanism includes a drive unit, a milling shaft, an eccentric rotary casing, a high-pressure jet nozzle unit, a tension and compression sensor and a direction sensor. Through the deflection of a center line of an inner hole of the eccentric rotary casing, the milling mechanism drives a milling cutter head to carry out a rotational oscillation motion for rock breaking; and the milling cutter head is in discontinuous contact with a rock mass. The telescoping mechanism, the inclined cutting feed adjusting mechanism, the lifting mechanism and the horizontal swinging mechanism are controlled such that the milling mechanism performs coal rocks milling.

Abstract: A data storage method, an apparatus, an electronic device, and a computer-readable storage medium. The method includes: detecting a mode switching behavior performed by an operator of a vehicle, the mode switching behavior being used to trigger switching a driving mode of the vehicle between a manual driving mode and an automatic driving mode; acquiring first data corresponding to the mode switching behavior, the first data including a vehicle identification of the vehicle, switching trigger information corresponding to the mode switching behavior and time information corresponding to the mode switching behavior; storing the first data to a blockchain network.

Abstract: An image processing method includes: receiving a processing instruction for an image; screening out a plurality of target images from a plurality of acquired images; determining a first feature value and a second feature value of the target area of each of the target images; determining a similarity between the first feature values of the target areas in every two target images according to all the determined first feature values, and determining a similarity between the second feature values of the target areas in every two target images according to all the determined second feature values; and, if a first target similarity is within a first preset range, and a second target similarity is within a second preset range, determining that a first image and a second image belong to the same image set.

Abstract: The present disclosure relates to traffic information processing methods, including: receiving transaction information sent by a first vehicle, the transaction information carrying violation information of the target vehicle detected by the first vehicle; the smart contract being used to determine second vehicles to verify the transaction information, and sending the violation information to the second vehicles such that the second vehicles generate verification results based on the violation information; determining whether the target vehicle has violated traffic rules based on the verification results; if determining that the target vehicle has violated traffic rules, storing the violation information in the blockchain network.

Abstract: The present application discloses a method and apparatus for device configuration parameter processing, a method and apparatus for data analysis, a computing device, a computer-readable storage medium and a computer program product. The method for device configuration parameter processing includes: acquiring collection data of a collection device located at a target position, wherein the collection data is configured to be input into a content analysis model for the target position so as to obtain a content analysis result of the collection data, determining, based on the collection data, whether a current configuration parameter of the collection device has changed, sending, in response to the current configuration parameter of the collection device having changed, a preset configuration parameter for the target position to the collection device so as to adjust the current configuration parameter of the collection device based on the preset configuration parameter.

Abstract: Provided are a method and apparatus for identifying the defect grade of a bad picture, and a storage medium. The method includes: determining the defect size of a defect from a bad picture; according to a product model corresponding to the bad picture, determining the design size of a pattern corresponding to a component that is adjacent to the position of the defect; determining the defect grade of the defect according to the defect type of the defect and a magnitude relationship between the defect size and the design size, wherein the defect grade is the degree to which the defect affects product yield.

Abstract: Embodiments of the present application provide a method for constructing, running and implementing a cross-platform application, a terminal, a server, a system, and a non-transitory computer-readable storage medium. The method includes: obtaining a project template of the cross-platform application and information about a microprogram component corresponding to the project template of the cross-platform application, in response to an operation of selecting the project template of the cross-platform application by a user on a first platform, where the project template of the cross-platform application comprises a Flutter component based on a domain-specific language, and the Flutter component is configured to parse the microprogram component and load an interface of the microprogram component; and constructing an application on the first platform and generating an application package, based on the project template of the cross-platform application and the information about the microprogram component.

Abstract: An image processing method includes: receiving a processing instruction for an image; screening out a plurality of target images from a plurality of acquired images; determining a first feature value and a second feature value of the target area of each of the target images; determining a similarity between the first feature values of the target areas in every two target images according to all the determined first feature values, and determining a similarity between the second feature values of the target areas in every two target images according to all the determined second feature values; and, if a first target similarity is within a first preset range, and a second target similarity is within a second preset range, determining that a first image and a second image belong to the same image set.

Abstract: A method for classifying an image of a displaying base plate includes: acquiring an image to be checked; from a first predetermined-type set, determining a type of the image to be checked. The first predetermined-type set includes: a first image type, a second image type and a third image type. An image of the first image type is a no-defect image, an image of the second image type is a blurred image, and an image of the third image type is a defect image. When the type of the image to be checked is the third image type, by using a first convolutional neural network, determining a defect data of the image to be checked, wherein the defect image refers to an image of a displaying base plate having a defect, and the defect data contains a defect type of the displaying base plate in the image to be checked.