48results about How to "Accurate resolution" patented technology

The utility model provides an intelligent operation system for spontaneously intracerebral hematoma. The intelligent operation system comprises an endoscopic component, an endoscopic signal cable and an endoscopic probe, wherein the endoscopic component comprises an endoscopic signal cable and an endoscopic probe; comprising an ultrasonic signal cable and an ultrasonic probe; comprising a stretching-in end and a holding end, and a drainage channel, an ultrasonic channel and an endoscopic channel which are communicated are formed in the operation tube; an endoscopic probe of the endoscopic assembly is arranged at the extending end, and an endoscopic signal cable penetrates through the endoscopic channel and is electrically connected with the control assembly; an ultrasonic probe of the ultrasonic imaging assembly is arranged at the stretching-in end, and an ultrasonic signal cable penetrates through the ultrasonic channel to be electrically connected with the control assembly; the image display assembly is electrically connected with the control assembly and is used for displaying image information acquired by the endoscopic probe and the ultrasonic probe in real time; the problems that a traditional craniotomy hematoma removal operation is high in operation requirement and low in hematoma removal rate, brain tissue is prone to being damaged, and the operation effect is difficult to be universally homogenized are solved.

The invention belongs to the technical field of automatic sorting, and particularly relates to building waste reclaimed material automatic sorting equipment and method.The equipment comprises a vibrating feeder, a plurality of funnel-shaped material distribution grooves are formed below an ultrasonic atomization spraying device side by side, a belt conveyor is used for conveying building waste crushed materials, and the vibrating feeder is used for feeding the building waste crushed materials; a fluorescence detection box is arranged above the belt conveyor, connecting columns in one-to-one correspondence with the funnel-shaped material distribution grooves are arranged in the fluorescence detection box, ultraviolet lamps are arranged on the connecting columns, and photosensitive sensors are arranged on the rear sides of the ultraviolet lamps. According to the invention, through cooperation of fluorescence recognition feedback and high-pressure gas, building waste crushed materials are automatically sorted, building waste materials of different substances with similar density, size, color, shape and the like can be finely sorted, and the device has the characteristics of sensitive reaction, accurate distinguishing, high precision and the like.

The invention discloses a C + L transmission system noise wave automatic filling method and device, and relates to the technical field of optical communication, the C + L transmission system noise wave automatic filling method comprises the following steps: if the power of an optical amplifier of a downstream station of a C + L transmission system is abnormal, optical channel monitoring OCM scanning is started, and the frequency and power information of a missing channel is acquired; and starting automatic filling of noise waves based on the frequency and power information of the missing channel. According to the invention, the stability of the service channel can be maintained in the dynamic process of the C + L transmission system.

The invention relates to the technical field of data analysis, and particularly discloses a water quality parameter inversion method based on hyperspectral data analysis, which comprises the following steps: S1, carrying out grid division on a hyperspectral image, and obtaining a hyperspectral curve based on reflectivity values of pixel points in a grid; s2, sub-grids are determined according to the difference degree of the initial grid and the to-be-determined grid; determining a to-be-determined grid according to the existing sub-grids, determining the sub-grids again, and repeating the steps until no new sub-grids exist; counting the total number of the sub-grids, and determining a target image according to the maximum total number of the sub-grids; s3, grouping the target images, and ensuring that the number of groups is greater than a number threshold; determining representative images in the groups, and determining a training set and a verification set according to the representative images; and training a water quality parameter inversion model based on the training set and the verification set, and performing inversion on the water quality parameters. The diversity of the training set can be ensured, and the accuracy of artificial intelligence water quality inversion is improved.

The utility model discloses an automobile air filter air inlet pipe testing fixture comprising a base plate, the base plate is provided with an upper detection box and a lower detection box, the upper detection box is connected with the base plate through a lifting mechanism, and a pipeline is clamped between the upper detection box and the lower detection box through the lifting mechanism for internal detection. An auxiliary mechanism connected with an air outlet of the pipeline body is arranged at one end of the lower detection box, an air conveying mechanism connected with an air inlet of the pipeline body is fixed at the other end of the lower detection box, and a detection mechanism is arranged in the lower detection box to detect the performance of the pipeline. The pipeline is placed in the detection space formed by splicing the upper detection box and the lower detection box, and then the air conveying mechanism is started to guide air into the pipeline, so that the pipeline is simulated to guide the air, and the simulated pipeline is detected through the detection mechanism; therefore, the broken cracks in the pipeline can be quickly and accurately distinguished.

The invention relates to the technical field of otolith sample preparation, in particular to a freshwater fish otolith sample preparation method which comprises the following steps: 1, sampling otolith; 2, otolith cleaning; 3, weighing the otolith; 4, fixing the otolith; 5, vacuumizing and hardening; 6, cutting the otolith; 7, fixing and cutting for the second time; 8, otolith polishing; 9, polishing the otolith; 10, otolith dyeing. According to the method, the freshwater fish otolith sample can be well prepared.

The present invention discloses a method for monitoring, managing and optimizing traffic flow at an intersection of a campus CPS system, wherein the monitoring and management methods include: S1, dividing the campus intersection into four sub-area systems; S2, each sub-area system includes a camera perception module, an information processing module and a CPS calculation module; S3, deploying the trained SAM‑s target detection model into the CPS calculation module to locate the vehicle and determine the traffic flow; S4, judging whether a campus traffic accident has occurred; S5, when the traffic flow at any two intersections is greater than k_1, a one-way green light is used for N seconds, and when the traffic flow at any intersection is greater than x_1, additional personnel are dispatched to manage the intersection; wherein the optimization method includes: S6, using the monitoring and management methods as described above at the school gate and all intersections, setting up graph nodes and forming a traffic flow network, and using an improved graph neural network to regulate them; purpose: to achieve real-time and regional level traffic optimization and regulation, and alleviate regional congestion during campus peak hours.

The invention discloses an interaction method and device based on a virtual environment, equipment and a medium, and belongs to the field of man-machine interaction. The method comprises the following steps: displaying at least one array individual in a virtual environment; the display forms of different array individuals are the same or the similarity exceeds a threshold value; in response to the resurrection skill selection operation, displaying role information of a first virtual role corresponding to the first array individual; the first array individual is one selected by the resurrection skill selection operation in the at least one array individual, and the first array individual is a corresponding display element after the first virtual character array; and in response to the reviving skill release operation, switching and displaying the first array individual as a revived first virtual character. According to the scheme, a player can accurately select the to-be-revived array individual from a plurality of array individuals with the same or similar display forms, and the virtual character corresponding to the array individual is revived by using the reviving skill, so that the man-machine interaction efficiency can be improved.

The application provides a method for identifying a wafer, comprising the following steps. A mark frame is obtained from a wafer detection picture. A gray scale index corresponding to the mark frame is calculated based on respective gray scale values of a plurality of pixels included in the mark frame. The gray scale index represents a proportion of pixels with a gray scale value greater than a specified value. Whether a trace pattern in the mark frame is a scratch or a grain boundary is determined based on the gray scale index.

The present invention relates to the field of optical lens technology, and specifically to an optical lens calibration method and system. First, an original optical lens parameter vector is obtained, and an image quality evaluation value of the original parameter vector is calculated by a ray tracing method, so as to effectively distinguish the optical lens that needs to be calibrated and determine the first optical lens parameter vector; then, the first optical lens parameter vector is input into a conditional generative adversarial network to generate a second optical lens parameter vector, and the conditional generative adversarial network introduces image quality evaluation loss and manufacturing constraint loss, which can guide the generator to generate an optical lens parameter vector that meets imaging requirements and complies with physical manufacturing limitations; then, the image quality evaluation value of the second optical lens parameter vector is calculated by a ray tracing method to ensure that the second optical lens parameter vector can meet the imaging requirements, and then the optical lens is calibrated according to the second optical lens parameter vector, thereby improving the accuracy of optical lens calibration and reducing the calibration cost.

The invention discloses an intelligent jujube sorting machine, comprising a frame, a plurality of profiling tugboat sorting and conveying mechanisms arranged side by side are installed in the frame, a blanking conveyor belt is installed below the front of the profiling tugboat sorting and conveying mechanism, a plurality of discharging conveyor belts arranged side by side are installed below the rear, a visual detection system and a sorting mechanism are arranged above the profiling tugboat sorting and conveying mechanism along one side of the conveying direction, the sorting mechanism is located directly above the discharging conveyor belt, and a cleaning mechanism is installed at the bottom of the profiling tugboat sorting and conveying mechanism. The invention can sort and convey single red dates, effectively prevent the friction problem of red dates, and avoid damaging the red dates. At the same time, different qualities of dates can be sorted and collected one by one, without manual secondary sorting, thereby improving sorting efficiency and reducing labor costs. The invention also has an overall integrated design, a compact structure, and adopts automatic control to realize automatic production.

The utility model discloses a kind of tactile sensor and robot.The tactile sensor includes: first detection structure, first electric conductor and second electric conductor, and first detection structure extends along first direction;First detection structure is used to produce corresponding deformation according to the force state of tactile sensor in second direction, and the first electric parameter of first detection structure changes according to the force state of tactile sensor in second direction;First electric conductor and second electric conductor are alternately wound on first detection structure, and along first direction, and first electric conductor and second electric conductor are arranged with interval;The second electric parameter between first electric conductor and second electric conductor changes according to the force state of tactile sensor in first direction;Wherein, first electric conductor is wound at least one circle on first detection structure, and second electric conductor is wound at least one circle on first detection structure.The tactile sensor provided by the technical scheme of the utility model can accurately distinguish and measure force in different directions.

The present disclosure provides a detection method, apparatus, computer equipment and storage medium, wherein the method includes acquiring first point cloud data in a target environment and target geometric features of a target object; based on the target geometric features, filtering first target point cloud data belonging to the target object from the first point cloud data, and performing object segmentation on the first point cloud data other than the first target point cloud data to obtain second target point cloud data of other objects other than the target object; based on the second target point cloud data and the first target point cloud data, determining the positional relationship information between each other object and the target object; based on the positional relationship information, filtering a first obstacle located on the target object and at least a preset distance beyond the target object from other objects. The embodiments of the present disclosure utilize the target geometric features to accurately segment the first target point cloud data of the target object and the second target point cloud data of other objects, thereby accurately distinguishing the first obstacle.

The invention discloses a vacuum glass heat transfer coefficient measuring method and device, and the method comprises the steps: placing to-be-detected vacuum glass in a vacuum chamber provided with a vacuumizing system and an air pressure detection device, enabling the air pressure detection device to display the air pressure value of the chamber in real time, and forming a uniform polarized light field perpendicular to the placement direction of the glass in the chamber; and during vacuumizing, the light spot is detected on the side, opposite to the light source, of the glass through a polarization analyzing polaroid, the air pressure value P is recorded when the light spot disappears, and then the heat transfer coefficient is calculated according to the air pressure value P. Based on the photoelastic principle, the air pressure in the vacuum glass is determined by observing stress light spot changes, then the heat transfer coefficient is accurately calculated, the method is not affected by the environment temperature, measurement repeatability is good, measurement can be rapidly completed, the measurement efficiency and accuracy are greatly improved, and the method is suitable for popularization and application. And the urgent requirement of the vacuum glass production detection field on accurate measurement of the heat transfer coefficient is effectively met.

The invention provides a medical insurance fraud cross identification method based on fusion of multiple machine learning algorithms, and belongs to the field of machine learning technology and insurance risk management cross technology in information technology. The technical problems that in medical insurance fraud recognition, the recognition precision is not high, characteristics are complex, behaviors are hidden, and distinguishing is difficult are solved. According to the technical scheme, the method comprises the following steps of S1, performing data preprocessing on an original data set D0; s2, finding out feature information with high correlation by using the heat map; s3, constructing a medical insurance fraud detection model based on multiple machine learning algorithms; s4, checking the model; and S5, extracting main medical features influencing fraud discrimination through an algorithm. The method has the advantages that the accuracy and efficiency of medical insurance fraud detection are improved, and a more effective risk management solution is provided for insurance companies.

The application provides a kind of electrochemical immune sensing detection method for fruit and vegetable organochlorine pesticide multi-residue, belongs to the technical field of food safety detection, comprising: using liquid pulse discharge plasma synchronous reduction method to prepare g-C3N4-COOH / AuNPs heterojunction composite material with lattice coupling interface and modify on the surface of silk screen printing carbon electrode, through click chemistry reaction, azide modified organochlorine antigen is covalently fixed on the electrode surface, and the labeled immune probe loaded with different electrochemical signal substances and different organochlorine pesticide specific antibodies is used for competitive immune reaction, the differential pulse voltammetry response curve in the whole potential interval is collected, a plurality of characteristic parameters are extracted, and the concentration of multiple organochlorine pesticides is simultaneously solved by using partial least squares multivariate correction model.The application solves the problems of low interface electron transport efficiency, uncontrollable antigen fixation orientation, serious interference of complex matrix and difficult multi-residue signal resolution in the prior art.

The application discloses a mahjong machine with a control lighting lamp, and belongs to the technical field of mahjong machines, and has the technical scheme as follows: the mahjong machine comprises a mahjong machine main body, irradiation lamp strips are rotationally arranged on four sides of the mahjong machine main body, placing areas for placing mahjong hands are arranged on the four sides of the mahjong machine main body, the light beams of the irradiation lamp strips are obliquely shot from bottom to top to the mahjong hands in the corresponding placing areas, a controller is arranged on the mahjong machine main body, human body sensing modules are arranged on the four sides of the mahjong machine main body, the human body sensing modules are electrically connected with the controller, the controller is electrically connected with the irradiation lamp strips, when the human body sensing modules sense a human body, the controller controls the corresponding irradiation lamp strip to be turned on, and the four sides of the mahjong machine main body are provided with adjusting knobs for adjusting the brightness of the corresponding irradiation lamp strips, the mahjong machine forms effective light zones on the mahjong hands through the irradiation lamp strips, the recognition of the mahjong hands by users is enhanced, and the use experience is improved.

The invention relates to a method for carrying out early warning on network attacks on a networked automobile, which comprises the following steps of: 1) establishing a semi-supervised generative adversarial network for judging network attack behaviors, the semi-supervised generative adversarial network comprising a discriminator comprising a plurality of residual jump connection blocks and a generator; 2) collecting data traffic of various vehicle-mounted applications of the networked automobile to form a real-time network data traffic set; 3) preprocessing various data traffic in the real-time network data traffic set to obtain a corresponding data traffic graph; and 4) inputting the data flow graph obtained in the step 3) into a discriminator of the semi-supervised generative adversarial network so as to judge whether the intelligent system of the connected automobile is subjected to network attack or not.

The invention provides a multi-intention instruction recognition method and device, electronic equipment and a storage medium. The method comprises the following steps: inputting an intention instruction of a user into a pre-trained multi-intention instruction recognition model to obtain a first label which is output by the pre-trained multi-intention instruction recognition model and is used for indicating whether the intention instruction is a multi-intention instruction, the second label is used for indicating a sentence segmentation position under the condition that the intention instruction is a multi-intention instruction; and if the second label contains a preset character, segmenting the intention instruction according to the position of the preset character at the second label. Therefore, through the pre-trained multi-intention instruction recognition model, whether the intention instruction of the user is the multi-intention instruction or not and the position of sentence segmentation between single-intention instructions under the condition that the intention instruction of the user is the multi-intention instruction can be determined, so that follow-up execution is facilitated.

The utility model relates to the technical field of medical instruments, and discloses a multi-hook type infusion support convenient to arrange, which comprises a vertical rod, a circular hanging disc detachably connected with the vertical rod and an arranging unit positioned below the circular hanging disc, the arranging unit is slidably connected with the vertical rod along the height direction, and the arranging unit comprises a classification column sleeved on the outer side of the vertical rod. A plurality of containing grooves are formed in the side face of the classification column in the circumferential direction, the containing grooves correspond to the hooks one to one, arc-shaped buckle plates used for opening and closing are arranged on one sides of the containing grooves, and the colors of the arc-shaped buckle plates are consistent with the colors of the hooks corresponding to the arc-shaped buckle plates. Through the arrangement of the circular hanging discs and the classification columns, the infusion hoses corresponding to the infusion bags are separated and arranged, and mutual winding of the infusion hoses is avoided; the corresponding arc-shaped buckle plates and hooks are marked through the same color, so that medical staff can distinguish infusion bags and corresponding infusion hoses more visually, rapidly and accurately, and the technical problem that the infusion hoses are wound mutually and cannot be distinguished is solved.

The invention discloses a temperature compensation method of a capacitive force / torque sensor and a sensor structure of the capacitive force / torque sensor. The sensor comprises an upper-layer substrate, a middle substrate and a lower-layer substrate, and an interdigitated electrode is arranged between the upper-layer substrate and the middle substrate and used for tangential force detection; a strip-shaped dielectric layer and a capacitor electrode array are arranged between the middle substrate and the lower substrate and are used for normal force and torque detection; the lower substrate is provided with a temperature compensation reference electrode used for collecting the environment temperature. The system takes a capacitance digital conversion chip as a core to realize multi-channel signal sampling and real-time resolving, and establishes a mapping relation between capacitance variation and five-dimensional force / torque components. In addition, in order to reduce the influence of the environment temperature on the output of the sensor, a temperature compensation method based on a binary polynomial regression model is used, a capacitance-temperature characteristic curved surface is established through a temperature and load experiment matrix, temperature compensation parameters are calculated in real time, and dynamic correction is achieved. The method is small in calculation amount, and improves the precision and stability.

A nano cantilever beam array and a preparation method thereof, and a resonant array gas sensor, the nano cantilever beam array comprising a substrate and a cantilever beam array, each cantilever beam of the cantilever beam array comprising: a support layer, arranged on the substrate, one end in contact with the substrate forming a U-shaped cantilever beam support arm, the end of the support layer away from the U-shaped cantilever beam support arm being suspended on the substrate; a metal conductive layer, arranged on the support layer; and a sensitive layer, arranged on the metal conductive layer away from the U-shaped cantilever beam support arm, on which a sensitive unit is arranged. The present invention adopts a cantilever beam structure with double arm support, which can effectively improve the sensitivity of the sensor; the cantilever beam array with a double arm support structure has multiple sensitive units, which can respond to a variety of chemical gases quickly and sensitively.

The present invention discloses a method, device, equipment and computer-readable storage medium for counting cell information, and the method includes: S1, obtaining target image information of a cell group to be counted; S2, selecting a pre-built model, and inputting the target image information into the pre-built model to obtain a result image; S3, judging whether there is a defect feature in a region of the result image, the defect feature includes cell adhesion, at least partial disappearance of cells, and several items of cell abnormality, if so, executing steps S4-S6, otherwise executing step S6; S4, marking at least one region with defect features; S5, retraining the pre-built model according to the marking operation, and inputting the target image information into the retrained model to obtain a new result image; S6, counting cells based on the current result image. The present invention adopts deep learning combined with a semi-supervised learning method, and only a small amount of marking is required for the region with unsatisfactory results to achieve the desired effect.

The application discloses a dynamic power quality disturbance signal detection method, device and medium, and the method steps comprise the following steps: S01, acquiring a dynamic power quality disturbance signal to be detected; S02, dividing a signal frequency band, and performing time-frequency analysis on the dynamic power quality disturbance signal by using an improved variable resolution S transform method; the improved variable resolution S transform method is an S transform based on a Gaussian window, and a Gaussian window scale factor is used to optimize the Gaussian window function; S03, performing a synchronous squeezing rearrangement operation on the improved variable resolution S transform result, so that energy components scattered in adjacent frequency intervals are aggregated to real frequency axis positions, and a time-frequency matrix after synchronous squeezing rearrangement is obtained; and S04, detecting signal components of the time-frequency matrix after synchronous squeezing rearrangement. The application can reduce energy diffusion and realize high-precision detection of non-stationary multi-scale complex dynamic power quality disturbance signals.

The invention discloses a color night vision imaging method based on infrared imaging, and the method comprises the steps: enabling a low-light sensor and a neural network to be embedded into an infrared imaging system, and inputting the contour information extracted through an infrared imaging technology and the weak color information in a dark state into a deep learning neural network; and fitting the image with a real color through a neural network, and finally outputting a target image, so that the night vision device can generate a night vision image with a real color. According to the method, the visibility and authenticity of night vision imaging can be effectively improved, information in various spectral bands can be accurately distinguished, powerful support is provided for follow-up data analysis and decision making, and the method is suitable for multiple fields such as traffic, aviation, medical treatment and security and protection.

The present invention provides an automatic frequency correction circuit and method. The automatic frequency correction circuit comprises a first counting module, a second counting module, a counting comparison module, a high-frequency four-phase clock generating module, a high-frequency four-phase clock auxiliary judgment module, a composite judgment and optimal selection module, and a segment selection logic module. The high-frequency four-phase clock auxiliary judgment module samples and judges the lowest bit of a first counting value and the lowest bit of a second counting value under the control of four high-frequency clocks, judges the speed of a feedback frequency-dividing clock relative to the phase-locking clock, and obtains a second judgment result. Sampling and detection are performed based on the four introduced high-frequency out-of-phase clocks, thereby getting rid of the dependence of segment selection accuracy and time on the phase-locking clock frequency. Even in the application of low phase-locking frequency, the frequency difference between the phase-locking clock and the feedback frequency-dividing clock can be quickly and accurately distinguished. When applied to a phase-locked loop, the output frequency correction speed and accuracy of a phase-locked loop based on a multi-segment voltage-controlled oscillator are improved.

The present invention relates to the field of feeding technology in underwater fish management, and in particular to an unmanned boat feeding method for a target fish school based on a temporal network algorithm, so as to solve the problems of fish school identification, position distance positioning and classification and feeding of different fish schools in an underwater environment. By treating each fish in the fish school as a temporal node, extracting characteristic data of swimming speed, pattern spot category, spacing and pixel ratio of fish on an image, constructing a characteristic sequence of continuous fish, and providing strong data support for temporal network analysis, the improved LSTM network analysis can accurately identify the type of fish school and reasonably select suitable feed. At the same time, according to the movement speed of the fish school, the number of input vectors is intelligently adjusted to achieve dynamic adaptation. With the help of an adaptive amplification factor, the network algorithm will automatically adjust according to the classification accuracy of the pattern spots, and further improve the system accuracy. In addition, through a sonar device, the distance between the ship and the fish is accurately measured to accurately guide the movement of the ship and implement the feeding operation.

The application discloses a C+L transmission system noise wave automatic filling method and device, relates to the optical communication technical field, and the C+L transmission system noise wave automatic filling method comprises the following steps: if the power of the optical amplifier of the downstream station of the C+L transmission system is abnormal, then starting optical channel monitoring OCM scanning, acquiring the frequency and power information of the missing channel; based on the frequency and power information of the missing channel, starting the automatic filling of the noise wave.The application can maintain the stability of the service channel of the C+L transmission system in the dynamic process.

The invention discloses a comparator and a control method thereof, which can realize offset elimination and improve operation speed and accuracy. The comparator comprises an amplifier, a transmission gate switch, a dynamic latch comparator and a coupling capacitor. A first preamplifier, a second preamplifier and the dynamic latch comparator are connected in sequence, an output end of the dynamic latch comparator is connected to a SAR control logic circuit, a differential signal transmission gate switch is connected to the first preamplifier, and a reference signal transmission gate switch is respectively connected to the first preamplifier, the second preamplifier and the dynamic latch comparator. The comparator control method comprises: when a sampling circuit samples, switches S1 and S2 are disconnected, switches S3 to S8 are closed, differential input ends of the first preamplifier, the second preamplifier and the dynamic latch comparator are connected to a reference signal, when a comparison circuit compares, switches S1 and S2 are closed, switches S3 to S8 are disconnected, and the input of the first preamplifier is connected to a differential signal.

The invention relates to an automatic parking method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: identifying a vehicle classification, a vehicle body color and a vehicle brand of a second vehicle according to video data around a first vehicle; the second vehicle comprises a vehicle which is parked adjacent to the parking space of the first vehicle; displaying a virtual vehicle corresponding to the second vehicle in a parking virtual view of the parking auxiliary interface; the color of the virtual vehicle is consistent with that of the vehicle body, and a brand identifier of a vehicle brand is displayed; the virtual vehicle is obtained by rendering a vehicle model matched with the vehicle classification. By adopting the method, the operation convenience of automatic parking can be improved.