42results about How to "Fully aware" patented technology

The invention discloses a multimode switching method for a heterogeneous network. The method mainly comprises the following steps of: determining a real-time service and a non-real-time service in each communication mode in the heterogeneous network, and determining priority among a plurality of communication modes in the heterogeneous network; setting respective packet loss threshold values of the real-time service and the non-real-time service in each communication mode; acquiring respective packet losses of the real-time service and the non-real-time service in each communication mode; and comparing the obtained packet losses and corresponding threshold values according to a sequence ranging from high propriety to low priority, and finding a current most proper access network for switching. Due to the adoption of the method, the current communication performance is sensed through a communication service, an optimal communication mode can be selected through a decision, a network resource can be effectively used by a user, and interrupt communication capability resistance is enhanced.

The invention relates to an unmanned underwater vehicle IVFH (intelligent vector field histogram) collision avoidance method, in particular, an unmanned underwater vehicle two-dimensional IVFH (intelligent vector field histogram) collision avoidance method. With the method adopted, an unmanned underwater vehicle can obtain the location information of an obstacle through processing sensor data in a navigation process, so that the unmanned underwater vehicle can focus on security and rapidity, and the unmanned underwater vehicle can have a certain intelligence like human beings; and reasonable collision avoidance actions can be decided based on factors such as the distance of the obstacle, the distance of a target point, free grid percentage and known field of vision percentage, for example, course and navigational speed instructions can be determined, so that the unmanned underwater vehicle can avoid the obstacle so as to prevent danger. The method of the invention is suitable for collision avoidance conditions of unmanned underwater vehicles.

The invention discloses a heterogeneous network communication-based water supply network monitoring and information service system, which is characterized by comprising an equipment layer, a control layer, a dispatching layer and an information layer. The invention also discloses a monitoring method of the heterogeneous network communication-based water supply network monitoring and information service system. The method comprises the following steps of firstly measuring a water supply network parameter and an equipment working condition parameter by a flow sensor, a pressure sensor, a pump / valve working condition sensor and the like, acquiring the parameters by a measurement and control module, and sending to a wireless communication gateway; then, sending to a management center server for processing, issuing a control command by the management center server according to processing results, firstly sending the control command to the wireless communication gateway and finally sending to the measurement and control module by a ZigBee short range communication network to control corresponding control equipment; meanwhile, sending service information to an information service terminal by the management center server. The heterogeneous network communication-based water supply network monitoring and information service system and the monitoring method have the advantage that a water supply network can run safely and reliably, and the like.

The invention discloses a heterogeneous network communication-based urban inland inundation monitoring and information service system, which comprises a data acquisition layer, a transmission control layer, a dispatching management layer and an information distribution layer. The invention also discloses a monitoring method of the heterogeneous network communication-based urban inland inundation monitoring and information service system. The method is based on heterogeneous network communication, and comprises the following steps of firstly measuring an inland inundation parameter and an equipment working condition parameter by a sensor and the like, and acquiring the inland inundation parameter and the equipment working condition parameter by a measurement and control module, and sending the acquired parameters to a wireless communication gateway; then, sending to a management center server for processing, issuing a control command by the management center server according to processing results, sending the control command to the measurement and control module so as to control corresponding control equipment; meanwhile, sending service information to an information service terminal by the management center server through the internet and a short message GSM (global system for mobile). The heterogeneous network communication-based urban inland inundation monitoring and information service system and the monitoring method thereof disclosed by the invention have the advantage that urban inland inundation loss is greatly reduced by omnibearing urban digitized draining and waterlogging control guidance dispatching management, and the like.

The invention provides a method based on visual cognition in radio communication, comprising the steps of obtaining visual information, detecting image features, identifying targets, analyzing radio scenes, selecting radio communication modes and managing resources, etc. The invention can observe the radio communication environment by way of seeing, actively interact with the radio environment, fully recognize the whole scene of the radio environment, learn and reason the radio communication environment and make more effective and accurate decisions. In addition, the invention can be widely applied to the existing radio communication systems, flexibly provide more diversified application services, provide solutions with pertinence for meeting the all-round requirements of the users and realize humanization and intellectualization of radio communications.

The invention discloses an object identification method based on UWB communication signals. According to the object identification method based on the UWB communication signals, a wireless sensor network is formed by a plurality of communication nodes, wherein each node comprises multiple MIMO antennas to receive signals. Firstly, characteristic parameters of signals received by the multiple antennas are extracted, parameter fusion is carried out on the extracted characteristic parameters, and a classification model is obtained through a fusion parameter training classifier. The classification model enters an identification mode after training is completed, and an object is identified by using the classification model. Through the utilization of the multi-antenna technology, the accuracy of object identification is improved, the anti-jamming capability of a system is enhanced, and normal wireless node communication is not influenced.

The invention relates to a detection method for compound radix salviae miltiorrhizae dripping pills through quantitative analysis of multiple components by single marker; the method is a content determination method for six kinds of phenolic acid components through UPLC and quantitative analysis of multiple components by single marker; protocatechualdehyde is adopted as a single calibration object in experiments, and determination is carried out through a method with an external standard method and a correction factor; the method provides an effective and accurate quality control method for pharmacodynamic substances of the compound radix salviae miltiorrhizae dripping pills.

The invention provides a video processing method, a video processing device, a video processing system, a computer readable storage medium and electronic equipment, and relates to the technical fieldof video processing. The video processing method comprises the steps of obtaining a to-be-processed video, and determining an original video frame sequence to be subjected to frame insertion in the to-be-processed video; determining the change degree of foreground objects of two preset original video frames in the original video frame sequence; according to the change degree of the foreground objects of the two original video frames, determining a selectable time phase of to-be-interpolated frames between the two original video frames; and performing frame interpolation between the two original video frames based on the selectable time phase of the to-be-interpolated frame between the two original video frames to generate a processed video. According to the invention, the inherent contentof the video can be modified.

The invention discloses a traffic contraband recognition method based on self-attenuation weight and multiple local constraints. The method comprises the following steps: preparing original data; datapreprocessing. Data set creation. A structure of a classical convolutional neural network LeNet-5 network is used as a structure of a contraband classification network; for different layers of convolution features output by the LeNet-5 network, transverse connection is carried out according to the direction from a deep layer to a shallow layer in combination with the self-attenuation weight to construct fusion features; a self-attenuation weight coefficient is adjusted in a self-adaptive manner during model training; and a final category is calculated by designing a local multi-constraint strategy for the traffic contraband. According to the invention, automatic recognition and classification of traffic prohibited articles are realized based on deep learning and the convolutional neural network; and automatically learning high separability characteristics of the traffic forbidden objects by extracting a design characteristic learning network, training a traffic forbidden object automatic classification model, and completing the traffic forbidden object automatic recognition method for the common RGB image.

The invention, which relates to the field of the intelligent vehicle cognitive technology, claims for protection of an intelligent vehicle threat estimation system and method based on a variable-structure Bayesian network thereby evaluating a threat degree of a moving target to a vehicle. The system is composed of a threat modeling module, a data collection module and a threat estimation module. At a threat modeling stage, factors affecting intelligent vehicle threat estimation are determined, wherein the factors include an external environmental factor, a target characteristic factor and a driver factor; a topology of a Bayesian network model is constructed; and then a local condition probability table of the model is determined. During the driving process, the data acquisition module uses sensors to collect real-time data of various influence factors; the threat estimation module reconstructs corresponding variable nodes only for quickly changing factors according to changing rates of all factors to obtain a variable-structure Bayesian network model and then carries out reasoning calculation to obtain a target threat index. Therefore, the performance of intelligent vehicle threatestimation can be improved effectively.

The invention discloses an elevator display device and relates to the technical field of elevator display. The invention comprises a panel, one or more display units and a display control unit; the display units are arranged in landing and / or a lift car and are used for displaying elevator operation information; the display control unit is used for controlling the elevator operation information tobe displayed on the display units, and display unit display image areas include running direction arrows, current floor display, pre-registration information display, current speed display, current floor height display and lift car position indication; and building floor indication is printed on one surface of the panel. The elevator display device can display the speed and the current height information according to the building floor indication model matched with the actual floor and the lift car position indication, can conduct more intuitive dynamic simulation information display for passengers, and solves the problem that an existing elevator display device is not intuitive enough for the passenger.

The invention relates to an unmanned cooperative detection method, comprising the steps: S1, respectively obtaining the related information of a main vehicle and a shielding vehicle through a vehicle-mounted sensor, and respectively building a main vehicle coordinate system and a shielding vehicle coordinate system; S2, judging whether obstacles exist around the shielding vehicle, if so, executingthe step S3, and otherwise, returning to the step S1; S3, acquiring position information and speed information of the obstacle based on the coordinate system of the shielding vehicle; S4, judging whether the obstacle is located in the detection blind area of the main vehicle, if so, executing the step S5, and otherwise, returning to the step S1; and S5, sending the shielding vehicle related information and the obstacle related information to the main vehicle by the shielding vehicle, and generating a corresponding scene based on the main vehicle coordinate system by the main vehicle. Comparedwith the prior art, through cooperative detection between vehicles, the unmanned cooperative detection method solves the problem that the detection range is limited due to shielding of relative movement of the vehicles, so that the vehicle safety is effectively improved, and holographic perception of scenes around the vehicles is realized.

The invention provides a laser radar and vision fusion integrated target tracking system and method. The system comprises a solid-state laser radar, a monocular vision sensor and a fusion tracker. The fusion tracker comprises a monocular vision target detection module, a laser radar target detection module, a laser radar-vision fusion tracking module and a communication module. The monocular vision target detection module acquires target information from the image; the laser radar target detection module acquires target information from the point cloud; the laser radar-vision fusion tracking module performs spatial registration on measurement, establishes a target state model and a measurement model, establishes a tracking door through target state one-step prediction, and completes fusion tracking of an image target and a point cloud target through data association and target state filtering. According to the system and method, the integration level and development efficiency of the intelligent mobile platform are improved, and the accuracy of a fusion tracking result is improved.

The invention discloses a device for testing the tensile performance of a high polymer material. The device comprises an engine base, wherein stepper motors are mounted on the side surfaces of the engine base symmetrically; a transmission mechanism is mounted on the output shaft of each stepper motor; each transmission mechanism is movably connected with the engine base through a sliding mechanism; the side surface of each sliding mechanism is fixedly provided with a connecting rod; and the end of each connecting rod is connected with a mounting rack. According to the device for testing the tensile performance of the high polymer material, the experimental temperature is adjusted by a temperature adjusting device, the experimental humidity is adjusted by a humidity adjusting device, the adjusting capacity is high, different experimental requirements can be met, the completeness of experimental conditions is guaranteed, the experimental process is monitored by a monitoring device, the boundedness of manpower monitoring is avoided, the experimental process is convenient for a worker to know sufficiently, the experimental tension is monitored by a tension monitoring device, the monitoring is accurate, and convenience is provided for the work of the worker.

The invention discloses a human body detection method in a low-illumination environment based on image enhancement, electronic equipment and a storage medium, and the detection method comprises the steps: inputting a low-illumination image into a low-illumination image enhancement module, and obtaining an enhanced image; inputting the enhanced image into an improved human body detection module, and outputting a human body detection prediction result; performing multi-stage joint optimization on the low-illumination image enhancement module and the human body detection module through a multi-task loss function, and training to obtain an end-to-end low-illumination human body detection framework; and inputting the low-illumination image into the trained end-to-end low-illumination human body detection framework, carrying out image enhancement and human body detection, and outputting a human body detection prediction result. The end-to-end low-illumination image human body detection framework constructed by the invention realizes higher detection precision through mutual adaptation of the low-illumination image enhancement module and the human body detection module, and has stronger robustness for human body detection in different illumination environments.

The invention provides a mining area target identification method based on fusion of a fisheye camera and a laser radar. The mining area target identification method comprises the following steps: 1) carrying out information acquisition, distortion correction and data augmentation; 2) feature extraction and fusion: performing feature extraction on the data subjected to distortion correction and data augmentation by using different branches, and then performing fusion output on the features of the two kinds of data through a bilinear interpolation-based method; and 3) target identification: using a classic RPN structure, and performing result output through several important steps of generating an anchor frame, determining a mapping relationship between the anchor frame and a real frame, mapping parameter learning, non-maximum suppression and determining an effective candidate frame according to a score. The advantages of the two are integrated, the recognition performance of unmanned driving in a mining area environment is effectively improved by using a fusion mode, rich, real-time and accurate target pose information is provided for a subsequent decision control module, and unmanned driving landing is assisted.

The invention discloses a statistics teaching device for economic management science. The statistics teaching device comprises a demonstration frame, a sliding mechanism, pointers and a moving unit. The sliding mechanism comprises sliding rails and sliding blocks, the sliding rails are evenly and vertically fixed to the demonstration frame, the sliding blocks are connected to the sliding rails inan up-down sliding mode, scales are evenly arranged on the side faces of the sliding rails, and the sliding blocks are fixed to the sliding rails through fixing units; the pointers are fixed on the side surfaces of the sliding blocks and are arranged corresponding to the scales; the moving unit is installed on the demonstration frame, and an adjusting mechanism is installed on the moving part of the moving unit and connected to the sliding blocks through a connecting unit. The statistics teaching device for economic management science is convenient to adjust, the trouble of manual drawing is omitted, the classroom time can be effectively saved, the volatility of data can be demonstrated, and the teaching effect can be effectively improved.

The invention provides a feature matching method based on an attention mechanism and neighborhood consistency. The method comprises the following steps: extracting a picture key point and a descriptor thereof by using a convolutional neural network; key point positions are coded, and position information is fused into descriptors; using a self-attention network and a cross-attention network to enhance the characterization capability of the descriptors and searching a corresponding relation between the descriptors of the two pictures; constructing a graph by using a k-nearest neighbor algorithm according to the attention weight, evaluating neighborhood consistency of nodes by using a graph neural network, and fusing consistency information into attention aggregation; and according to the enhanced descriptor, calculating a matching result by using a Sinkhorn algorithm and mutual neighbor screening. The invention provides a method for integrating neighborhood consistency into an attention mechanism, the neighborhood consistency in the attention aggregation process is dynamically evaluated while global context information is aggregated by the attention mechanism, and local information and global information are combined to jointly enhance the characterization capability of a descriptor, so that higher-quality matching is obtained.

The invention relates to the technical field of power equipment, specifically to an amorphous alloy transformer, which comprises a shell, wherein an annular opening is formed in the top of the shell,a rubber ring is arranged in the annular opening, a fixing hole penetrating through the rubber ring up and down is formed in the rubber ring, a fixing block is mounted in the fixing hole, a mounting hole and a first conducting wire hole are formed in the fixing block, a bearing is mounted in the mounting hole, a screw rod is mounted in the inner ring of the bearing, a bushing is in threaded connection with the end, located in the shell, of the screw rod, a positioning rod is arranged on one side of the screw rod, a containing shell is mounted on the end face, facing the center of the shell, ofthe bushing, and a camera is arranged in the containing shell. The amorphous alloy transformer is simple in structure, the condition in the transformer can be shot through the camera, the camera canmove up and down through rotation of the screw rod and can rotate along the annular opening, external personnel can comprehensively know the condition in the transformer, and maintenance is convenient.

The present disclosure provides a video processing method, a video processing apparatus, a video processing system, a computer-readable storage medium and an electronic device, and relates to the technical field of video processing. The video processing method includes: acquiring a video to be processed, and determining an original video frame sequence to be interpolated in the to-be-processed video; determining the degree of change of foreground objects of two preset original video frames in the original video frame sequence; The degree of change of the foreground object of the video frame determines the optional time phase to be interpolated between the two original video frames; based on the optional time phase to be interpolated between the two original video frames, the Interpolate between frames to generate a processed video. The present disclosure can make modifications to the inherent content of the video.

The invention discloses a delay line type surface acoustic wave based sensing circuit system design method. The method comprises the following steps of: 1, manufacturing a delay line type surface acoustic wave device without a sensitive film; 2, manufacturing a delay line type SAW gas sensor comprising a sensitive film; 3, selecting proper parameters for forming a reference oscillation generationcircuit; 4, selecting proper parameters for forming an oscillation generation circuit; 5, selecting proper parameters for forming an oscillation signal mixing processing circuit; 6, selecting proper parameters for forming a low-frequency signal conditioning circuit; and 7, connecting the reference oscillation generation circuit, the oscillation generation circuit, the oscillation signal mixing processing circuit and the low-frequency signal conditioning circuit. The method is reasonable in design, the designed delay line type surface acoustic wave based sensing circuit system is low in power consumption and can generate high-stability sensing signals.

The invention relates to a full fabric skin sensing autonomous flexible deformation search and rescue robot and an operating method thereof. The search and rescue robot consists of three parts, namely a head part, a body part and a tail part, wherein the three parts are connected together through a connecting mechanism; the head part is provided with a life detection device, a driving device, a control device, a power device, a communication device, a camera and an infrared device; the body part and the tail part are provided with a driving device, a control device and a power device; each part consists of a plurality of joints; a deformation mechanism is a structure which is used for supporting in the joints; the joints are connected together through the driving device; and the outer surface of the entire robot is covered by a flexible fabric skin layer. The robot is suitable for executing detection tasks of living bodies under ruin environments of earthquake, coal mine disasters andthe like; the robot can also enter a narrow space in ruins through deformation of the robot to detect life information; and thus, the search and rescue range of the robot is expanded, the rescue efficiency is increased, and valuable time is brought for rescuing more lives.

The present invention relates to a method for predicting vehicle queuing dissipation time based on image self-learning, comprising: S1, preset the analysis area of ​​each lane of the entrance; S2, collect the image of the entrance; S3, segment the lane image from the image of the entrance; S4 1. The self-learning neural network analyzes the lane image to obtain the predicted time of vehicle queuing and dissipation; S5. Obtain the actual time of vehicle queuing and dispersal; S6. Calculate the predicted difference between the predicted time of queuing and disperse and the actual time; S7. Judge the predicted difference Whether they are all less than the first preset threshold, if it is judged to be yes, start to predict the vehicle queuing dissipation time in the next cycle, otherwise execute step S8; S8, add the lane image and the actual time of queuing dissipation to the sample relationship database, retrain and Update the self-learning neural network of step S4. Compared with the prior art, the present invention realizes prediction model evolution through image self-learning, and can accurately predict vehicle queuing dissipation time.

The invention discloses a garment treatment control system which represents garment treatment condition through thread crumb generation condition so as to adopt corresponding response measures. The garment treatment control system comprises a thread crumb representing value generation module, a storage module and a thread crumb generation and analysis module, the thread crumb representing value ismainly used for acquiring amount of thread crumbs in a detection area and generating a thread crumb content representing value according to the amount of the thread crumbs, the storage module is mainly used for storing data acquired and generated by each module and threshold values and set values, and the thread crumb generation and analysis module is mainly used for analyzing thread crumb generation condition during running of a garment treatment program according to data in the thread crumb representing value generation module and the storage module. The invention further discloses garmenttreatment equipment with the garment treatment control system.

The invention relates to a method for one measurement and multiple evaluations of the effective parts of total flavonoids of Xintahua. The relative correction factor between anthocyanins was calculated by the correction factor to calculate the contents of Brassin, luteolin, and montiflorin in Xintahua, and determined by liquid chromatography. The detection method of the invention has the advantages of high practicability, simple operation and cost saving, makes up for the deficiency of only measuring the content of a single component of rutin, and can effectively detect four components of rutin, apigenin, luteolin and montanulin in Xintahua. At the same time, the quality control of the effective parts of the total flavonoids of Xintahua was further improved.

The invention discloses a method for designing a mine safety monitoring system based on a surface acoustic wave sensor. The method comprises the following steps: 1. fabricating a delay line type surface acoustic wave device including a sensitive film; 2. selecting suitable parameters for forming an oscillation generating circuit 3. Select the appropriate parameters to form the low-frequency signal conditioning circuit; 4. The connection between the oscillation generating circuit and the low-frequency signal conditioning circuit; 5. The connection between the sensor group and the FPGA main controller; The method of the invention has simple steps, reasonable design, low power consumption of the designed mine safety monitoring system, improves the accurate monitoring of environmental parameters such as temperature, humidity, gas concentration in the mine, facilitates the accurate transmission of the mine environmental parameters to the monitoring center, and improves the performance of the mine. The accuracy of environmental detection and corresponding measures such as early warning are made to avoid the occurrence of safety accidents.