Abstract: A patrol helmet and method for livestock and poultry farms is described herein. The patrol helmet is wirelessly connected to an online farm management system on a cloud platform. The patrol helmet includes a helmet body, a controller, an augmented reality (AR) display component, an infrared (IR) camera, and a visible light camera. The AR display component is secured at the bottom edge of the helmet body. Both the IR camera and the visible light camera are disposed on the helmet body. The IR camera, the visible light camera, and the AR display component each is electrically connected to the controller. The IR camera and the visible light camera are configured to photograph livestock or poultry in an area in front of a wearer to obtain a temperature and an image of the livestock or the poultry.

Abstract: An action recognition method includes: obtaining original feature submaps of each of temporal frames on a plurality of convolutional channels by using a multi-channel convolutional layer; calculating, by using each of the temporal frames as a target temporal frame, motion information weights of the target temporal frame on the convolutional channels according to original feature submaps of the target temporal frame and original feature submaps of a next temporal frame, and obtaining motion information feature maps of the target temporal frame on the convolutional channels according to the motion information weights; performing temporal convolution on the motion information feature maps of the target temporal frame to obtain temporal motion feature maps of the target temporal frame; and recognizing an action type of a moving object in image data of the target temporal frame according to the temporal motion feature maps of the target temporal frame on the convolutional channels.

Abstract: An intelligent driving system (10). A vehicle-mounted subsystem (100), a road subsystem (200), and a platform subsystem (300) are provided, wherein traffic information of each road section is acquired in real time by using the road subsystem (200), and traveling paths of vehicles in each road section are obtained according to the traffic information; the platform subsystem (300) comprehensively obtains, according to the traffic information of each road section, traffic information of the entire administrative area, and the optimal traveling path; and the vehicle-mounted subsystem (100) provides a traveling path on the basis of the road subsystem (200) and the platform subsystem (300), controls an operation state of the current vehicle in view of a traveling state of itself, and performs traveling path planning according to actual road conditions of each road section, thereby improving the accuracy of traveling path planning and the safety of automatic driving.

Abstract: A parallel remote control driving system for an intelligent network vehicle, comprising an intelligent network vehicle control device, a parallel driving control and a remote control driving device. The remote control driving device generates, according to a remote control driving request signal from the parallel driving control device, a remote control driving instruction signal, and generates, according to user operations, a driving mode signal and a vehicle control signal and transmits the vehicle control signal to the intelligent network vehicle control device through the parallel driving control device, for remote control of the intelligent network vehicle. With the parallel remote control driving system, the human driver is no longer necessary when the intelligent network vehicle is on the road. Therefore, the manpower cost including training cost, the technical requirement, and the safety cost of the human driver is significantly reduced, thus facilitating the promotion of intelligent network vehicle.

Abstract: An online monitoring device of 3D printing equipment includes a signal collection module, a signal processing module, a feature extraction module, a monitoring module and a knowledge base module. A vibration signal of a preset component of the 3D printing equipment is collected by a vibration sensor. The collected vibration signal of each preset component is converted from an analog signal to a digital signal and the spectrum characteristics are extracted. Based on the spectrum characteristics of each preset component, the operation state type of the preset component is obtained by a comparative analysis model. The knowledge base module is configured to store newly added samples and initial samples of the 3D printing equipment. The initial samples include spectrum characteristic information and corresponding fault category of known faults, and the newly added samples include spectrum characteristic information and corresponding fault category of new faults.

Abstract: A neural network-based error compensation method for 3D printing includes: compensating an input model by a deformation network/inverse deformation network constructed and trained according to a 3D printing deformation function/inverse deformation function, and performing the 3D printing based on the compensated model. Training samples of the deformation network/inverse deformation network include to-be-printed model samples and printed model samples. The deformation network constructed according to the 3D printing deformation function is marked as a first network. During training of the first network, the to-be-printed model samples are used as real input models, and the printed model samples are used as real output models. The inverse deformation network constructed according to the 3D printing inverse deformation function is marked as a second network.

Abstract: A neural network-based error compensation method for 3D printing includes: compensating an input model by a deformation network/inverse deformation network constructed and trained according to a 3D printing deformation function/inverse deformation function, and performing the 3D printing based on the compensated model. Training samples of the deformation network/inverse deformation network include to-be-printed model samples and printed model samples. The deformation network constructed according to the 3D printing deformation function is marked as a first network. During training of the first network, the to-be-printed model samples are used as real input models, and the printed model samples are used as real output models. The inverse deformation network constructed according to the 3D printing inverse deformation function is marked as a second network.

Abstract: A parallel remote control driving system for an intelligent network vehicle, comprising an intelligent network vehicle control device, a parallel driving control and a remote control driving device. The remote control driving device can generate, according to a remote control driving request signal from the parallel driving control device, a remote control driving instruction signal, and generates, according to user operations, a driving mode signal and a vehicle control signal and transmits the vehicle control signal to the intelligent network vehicle control device through the parallel driving control device, so as to realize a remote control of the intelligent network vehicle. With the parallel remote control driving system, the human driver is no longer necessary when the intelligent network vehicle is on the road.

Abstract: An online monitoring device of 3D printing equipment includes a signal collection module, a signal processing module, a feature extraction module, a monitoring module and a knowledge base module. A vibration signal of a preset component of the 3D printing equipment is collected by a vibration sensor. The collected vibration signal of each preset component is converted from an analog signal to a digital signal and the spectrum characteristics are extracted. Based on the spectrum characteristics of each preset component, the operation state type of the preset component is obtained by a comparative analysis model. The knowledge base module is configured to store newly added samples and initial samples of the 3D printing equipment. The initial samples include spectrum characteristic information and corresponding fault category of known faults, and the newly added samples include spectrum characteristic information and corresponding fault category of new faults.

Abstract: A ball-dropping sliding sleeve with a removable ball seat, comprising an outer barrel (1), an inner sliding sleeve (6) and a removable ball seat assembly; an inner ring downward facing shoulder (2) is disposed at an upper end of the outer barrel (1), a lower joint (3) is fixedly mounted in a lower end of the outer barrel (1), a sliding groove (4) is formed in the outer barrel (1) between the downward facing shoulder (2) and the lower joint (3), and at least one fracturing lateral hole (5) is distributed on a circumference of the outer barrel (1) at an upper side of the sliding groove (4). The structure of the present invention is reasonable and compact, and its usage is convenient.

Abstract: A pruning robot system, which comprises: a signal tag device (2) for detecting and storing information of trees and crops and positioning information, and assisting positioning; a robot (1) comprising a central processing device (10) for storing and analyzing data information of each part of the robot (1) and issuing action instructions to each part of the robot (1), and a positioning and navigating device (11) for positioning and navigating the robot (1), and for planning a path and providing obstacle-avoiding navigation for the robot (1) according to an electronic map; a cloud platform terminal (3), which is in connection and communication with the central processing device (10) of the robot (1) and is used for storing data of trees and crops as well as detection data of the robot (1), and for planning a path for the robot (1) through computing and experimenting according to the information data; a map building device (4) for building a three-dimensional electronic map corresponding to the plantation throug

Abstract: The invention discloses a vehicle detection method based on hybrid image template. This method consists of the three steps. Firstly, use no less than one vehicle image for template learning. Secondly, use information projection algorithm to learn a hybrid image template from the training images for vehicle object. The hybrid image template consists of no one less than image patch. Meanwhile, calculate the likelihood probability distribution of this template. Thirdly, use the learned HIT template to detect vehicle objects from testing images. The invention is suitable to detect vehicles with various vehicle shapes, vehicle poses, time-of-day and weather conditions. Besides vehicle localization, this method can also provide the detailed description of vehicle object.

Abstract: The present invention relates to a technical field of 3D printing, and more particularly to a 3D printer spray nozzle structure and a method thereof for controlling speed and precision. According to the present invention, a feeding pipeline is embedded in an external shell, the feeding pipeline and an extruder are coaxially connected; the extruder is driven by a driving device, so as to rotate relative to the feeding pipeline. A rotation angle of the extruder relative to the feeding pipeline is controlled by rotation of a motor, for controlling a filament area actually sprayed by the extrude, in such a manner that printing speed and precision is controlled for suiting different requirements of different printing area. The present invention controls the printing speed and precision, for improving overall printing speed with precision requirements satisfied, and is applicable to 3D printer spray nozzle structure and controlling.

Abstract: A 3D printer spray nozzle includes a feeding pipeline, an extruder located under the feeding pipeline, an external housing and a driving device; wherein the feeding pipeline is embedded in the external housing, the extruder is coaxially fixed under the feeding pipeline, a center of gravity of a cross section area of an inner channel of the feeding pipeline and that of the extruder are located on a same axis which is perpendicular to the cross section area of the inner channel of the feeding pipeline and that of the extruder, the feeding pipeline is driven by the driving device to rotate around the axis relative to the extruder, thereby aiming at different rotation angles, widths of extruding forming areas of the extruder at a same direction are different so as to adjust a cross section area of a sprayed filament.

Abstract: A 3D printer spray nozzle includes a feeding pipeline, an extruder located under the feeding pipeline, an external housing and a driving device; wherein the feeding pipeline is embedded in the external housing, the extruder is coaxially fixed under the feeding pipeline, a center of gravity of a cross section area of an inner channel of the feeding pipeline and that of the extruder are located on a same axis which is perpendicular to the cross section area of the inner channel of the feeding pipeline and that of the extruder, the feeding pipeline is driven by the driving device to rotate around the axis relative to the extruder, thereby aiming at different rotation angles, widths of extruding forming areas of the extruder at a same direction are different so as to adjust a cross section area of a sprayed filament.

Abstract: A ball-dropping sliding sleeve with a removable ball seat, comprising an outer barrel (1), an inner sliding sleeve (6) and a removable ball seat assembly; an inner ring table (2) is disposed at an upper end of the outer barrel (1), a lower joint (3) is fixedly mounted in a lower end of the outer barrel (1), a sliding groove (4) is formed in the outer barrel (1) between the inner ring table (2) and the lower joint (3), and at least one fracturing lateral hole (5) is distributed on a circumference of the outer barrel (1) at an upper side of the sliding groove (4). The structure of the present invention is reasonable and compact, and its usage is convenient.

Abstract: A 3D printing system comprises: a digital micro-mirror device (DMD) mobile device (1); a light source (3), fixed on said DMD mobile device (1) for emitting ultraviolet light, blue light or visible light; multiple DMDs (2) carried on the DMD mobile device (1) for receiving the ultraviolet light, blue light or visible light emitted by the light source (3) and generating 3D object section light; a lens (4) for receiving the 3D object section light reflected by the DMDs (2) and refracting and amplifying the 3D object section light; a material box (5) for containing and providing printing materials; a workbench (6), wherein the 3D object section light refracted by the lens irradiates the printing materials provided by the material box (5) to solidify the printing materials into a 3D object carried on the workbench (6); and a lifting device (7) for lifting the workbench (6).

Abstract: The present invention relates to a technical field of traffic monitoring, and more particularly to a method for detecting traffic violation. The present invention includes firstly localizing vehicle salient parts through salient features including vehicle license numbers and vehicle rear lights, and representing a vehicle with the vehicle salient parts, then tracking the vehicle with a Kalman filter based on the vehicle salient parts, and finally detecting vehicle violation through moving trajectory analysis and setting violating detecting areas. The present invention solves vehicle violation detection problems in complex engineering application conditions such as illumination change and detection noise, and is suitable for city traffic management under complex conditions.

Abstract: A pruning robot system, which comprises: a signal tag device (2) for detecting and storing information of trees and crops and positioning information, and assisting positioning; a robot (1) comprising a central processing device (10) for storing and analyzing data information of each part of the robot (1) and issuing action instructions to each part of the robot (1), and a positioning and navigating device (11) for positioning and navigating the robot (1), and for planning a path and providing obstacle-avoiding navigation for the robot (1) according to an electronic map; a cloud platform terminal (3), which is in connection and communication with the central processing device (10) of the robot (1) and is used for storing data of trees and crops as well as detection data of the robot (1), and for planning a path for the robot (1) through computing and experimenting according to the information data; a map building device (4) for building a three-dimensional electronic map corresponding to the plantation throug

Abstract: The present invention relates to a technical field of 3D printing, and more particularly to a 3D printer spray nozzle structure and a method thereof for controlling speed and precision. According to the present invention, a feeding pipeline is embedded in an external shell, the feeding pipeline and an extruder are coaxially connected; the extruder is driven by a driving device, so as to rotate relative to the feeding pipeline. A rotation angle of the extruder relative to the feeding pipeline is controlled by rotation of a motor, for controlling a filament area actually sprayed by the extrude, in such a manner that printing speed and precision is controlled for suiting different requirements of different printing area. The present invention controls the printing speed and precision, for improving overall printing speed with precision requirements satisfied, and is applicable to 3D printer spray nozzle structure and controlling.