73results about How to "Reduce inaccuracy" patented technology

The invention relates to the technical field of anorectal operation suturing, in particular to an anorectal operation suturing effect evaluation method and system based on image recognition, which can improve the objectivity and accuracy of evaluation and realize real-time feedback and immediate adjustment. The method comprises the following steps: acquiring treatment scheme data of an anorectal operation, and extracting a suture feature influence parameter set from the treatment scheme data; the suturing feature influence parameter set comprises a suturing tissue structure, a suturing wound shape, a suturing wound width and a suturing wound length; inputting the stitching feature influence parameter set into a pre-trained standard stitching feature contrast model to generate a standard stitching feature set; the standard suture feature set comprises a standard suture needle density, a standard suture edge distance and a standard suture needle distance; acquiring a surgical suturing image in real time, and segmenting and extracting suturing part sub-images from the surgical suturing image; and inputting the suturing part sub-image into a pre-constructed suturing feature image recognition model.

The invention provides a children's ability assessment method and device based on multi-modal data fusion, and the method comprises the following steps: S1, collecting the voice data of parent communication, and collecting the video data of children; s2, converting the voice data obtained in S1 into text data, and preprocessing video data; s3, inputting the text data and the preprocessed video data into a multi-modal large language model; and S4, inputting a questionnaire into the multi-modal large language model, and generating a child ability evaluation result by the multi-modal large language model. The beneficial effects of the invention are that by acquiring the child video data and the parent voice data and performing evaluation through the artificial intelligence multi-mode large language model, the subjective deviation of the evaluation personnel is reduced, and the child video data form is convenient for parents to acquire and reduces the inaccurate evaluation result caused by child tension.

The invention relates to the technical field of aerial image detection and the technical field of small target detection, in particular to a small target detection model in an unmanned aerial vehicle aerial scene, which is characterized in that an aerial image data set is acquired, an improved YOLOv8s model is trained by adopting the aerial image data set, and the improved YOLOv8s network model comprises a backbone feature network, a detection head and a loss function; an SPD-Conv module is introduced into a P2 layer, a P3 layer, a P4 layer and a P5 layer of the backbone feature network, a Dynamic Head module is introduced into a detection head, a specific small target detection head (SODH) is added, Shape-IoU is used as a loss function, and a to-be-detected aerial image is input into a trained improved YOLOv8s model for detection; the SDSS-YOLOv8 not only can execute a small target detection task in an aerial image shot by an unmanned aerial vehicle, but also has good performance in the aspect of small target detection in an unmanned ship image, the model has strong generalization ability, and although the image environment and target distribution have changes, the SDSS-YOLOv8 can maintain high detection performance in different scenes.

The invention discloses an automatic fracture scanning electron microscope image recognition method based on a convolutional neural network, and the method comprises the steps: collecting a fracture scanning electron microscope image, and manually calibrating the type of the fracture scanning electron microscope image; secondly, performing image preprocessing to form a data set; then, based on a deep learning convolutional neural network, an improved CNN network model is adopted, and based on a plurality of convolution kernels, a maximum pooling layer and a global average pooling algorithm, the metal fracture scanning image is analyzed, and the type of the metal fracture image is determined; and finally, inputting a to-be-recognized image, and performing statistics on a classification model of the image by using a global average pooling algorithm. According to the method, the risk that the accuracy is reduced due to experience or long-time work of personnel can be avoided, the time cost of analysis work is reduced, the type of metal fracture analysis is obtained, and the analysis result is reliable and efficient.

The invention provides a remote monitoring method and system for lymphedema pressure treatment of a patient at home, and relates to the field of lymphedema pressure treatment. The remote monitoring system based on the lymphedema pressure treatment of the household patient comprises an intelligent tubular bandage, a multifunctional sensor module is embedded in the inner layer of the intelligent tubular bandage, and the intelligent tubular bandage comprises an ultrathin pressure sensor, a human body composition sensor, a skin texture monitor, a temperature sensor and a humidity sensor and is used for comprehensively monitoring various physiological parameters wound on limbs of the patient. Through the design of the multifunctional sensor module and the flexible circuit embedded in the intelligent tubular bandage, the accuracy and sensitivity of monitoring physiological parameters of a patient by the system are remarkably improved, the flexible circuit can be adaptively adjusted to adapt to the shape and movement of limbs of the patient, measurement errors caused by movement of the bandage or movement of the patient are reduced, and the measurement accuracy is improved. And the stability of data acquisition is ensured.

The invention provides a method and a system for predicting a poultry growth model based on environmental monitoring. The method comprises the following steps: acquiring a historical image and a current image of each breeding cage in which poultry is bred; training a support vector machine model according to the historical images to obtain a trained support vector machine model, obtaining first future growth index data corresponding to each current image according to the trained support vector machine model, and calculating second future growth index data corresponding to each current image; and performing weighted summation on the first future growth index data and the second future growth index data to obtain final future growth index data corresponding to each current image. According to the method, environmental monitoring data is introduced into the poultry breeding field, a prediction model is constructed by using a machine learning algorithm, the limitation of a traditional breeding method is broken through, a novel and scientific growth index prediction method is provided, and subjectivity and inaccuracy of traditional manual judgment are reduced.

The invention discloses a cfRNA male hormone alopecia early screening method and system based on a machine learning model, and belongs to the field of male hormone alopecia, and the method comprises the following steps: extracting RNA from a sample set to obtain an RNA data set; constructing a library based on the RNA data set; performing quality inspection and NGS sequencing on the library to obtain sequencing data; performing bioinformatics analysis on the sequencing data to obtain significant differential genes; and establishing a prediction model by taking the significantly differential genes as input features of a random forest model, and inputting new sample information into the prediction model to obtain the alopecia risk of the subject corresponding to the sample.

The invention relates to a regulation and control method and system for mine fireproof doors, a terminal and a medium, and belongs to the technical field of mine fireproofing. The regulation and control method comprises the steps that sensing data sent by sensors around each fireproof door are received; according to the multiple sets of sensing data, whether a fire occurs in the mine or not is judged; if yes, determining a target fireproof door according to the fire spreading area; acquiring personnel position information of workers around the target fireproof door; based on the personnel position information, whether a worker is on a fire spreading path and is located between the target fireproof door and a fire spreading boundary is judged; if yes, the closing degree of the target fireproof door is controlled according to the spreading speed of the fire; if not, the closing degree of the target fireproof door is controlled according to the fire behavior of the fire. The intelligent monitoring management system has the beneficial effect that intelligent monitoring management of the fireproof door can be conveniently realized according to the field environment.

The invention discloses a traditional Chinese medicine information acquisition and processing system assisted by intelligent equipment, and belongs to the technical field of medical information processing. Comprising an equipment inspection module, a pulse pressure initial value acquisition module, an acquisition window length adjustment module and an information uploading module. The pulse acquisition period window length is adjusted according to the pulse acquisition signal real-time steady-state value, and the data uploading rate is adjusted in combination with the data uploading demand parameter and the data transmission characteristic parameter, so that the effect of accurately acquiring and transmitting the effective data of the individual pulse diagnosis information of the patient is achieved; the problem that effective data of individual pulse diagnosis information of a patient is difficult to accurately obtain and transmit in the prior art is solved.

The invention belongs to the field of vehicle-mounted tire pressure monitoring, and discloses a vehicle-mounted tire pressure monitoring platform and method based on the Internet of Things. Comprising the following steps: collecting comprehensive state data of each tire, and constructing a joint structure chart of the tires; calculating the difference data of the joint structure chart at the current time point and the previous time point to form a difference packet, and transmitting the difference packet by using an improved difference technology; building and training a monitoring and early warning model, and importing the difference packet into the trained monitoring and early warning model to obtain early warning information; and the early warning information is displayed through a vehicle-mounted interface, and the vehicle is adjusted, so that intelligent, high-efficiency and high-quality monitoring of the vehicle-mounted tire pressure based on the Internet of Things is realized.

The invention discloses a method for carrying out simultaneous transmission call translation by using an earphone, relates to the field of call translation, and solves the problem that in the process of simultaneous transmission call translation, if only the paraphrase of original voice is rigidly transmitted in a target language, the connotation and context of an original text cannot be fully captured and expressed, and the interpretation of the original text cannot be fully captured and expressed. The problems of serious information distortion and connotation loss are often caused; by simulating the mood of a speaker, the quality of simultaneous transmission call translation can be remarkably improved, the emotion expression is enhanced, the information accuracy is improved, the communication effect is enhanced, and the user experience is improved; in the aspect of technology implementation, the speech synthesis and sentiment analysis technology can provide powerful support, so that tone simulation is more natural and real; according to the method, voice data of different accent, different speakers, different background noise and different speech speeds are collected, a more robust and accurate voice recognition model can be trained, the method is suitable for diversified voice input, and the generalization ability of the method in different scenes is improved.

The embodiment of the invention provides a rotor magnetic steel temperature estimation method and device, equipment, a medium and a product. The method comprises the steps that firstly, if a current motor of the vehicle is in a first working state, the current motor rotating speed, a first counter electromotive force peak value and the first stator winding temperature are obtained; then, according to the current motor rotating speed, the first counter electromotive force peak value and the mapping relation, the first rotor magnetic steel temperature of the current motor is obtained; then, calculating a first temperature difference value between a first rotor magnetic steel temperature and a first stator winding temperature of the current motor; and finally, when the current motor is in a second working state, determining a second rotor magnetic steel temperature according to the first temperature difference value and a second stator winding temperature of the current motor. By means of the method, estimation of the temperature of the rotor magnetic steel is achieved, and the accuracy and reliability of calculation of the temperature of the rotor magnetic steel are improved.

The invention discloses an intelligent closestool cleaner performance test system, an intelligent closestool cleaner comprises a spray rod and a nozzle, the nozzle is arranged on the spray rod, and the intelligent closestool cleaner performance test system comprises a controller, an industrial personal computer, a manipulator, an image acquisition module, a cleaning water consumption measuring module, a cleaning force measuring module, a cleaning area measuring module and a nozzle self-cleaning force measuring module; the nozzle stretching time measuring module is used for measuring the stretching time and the retracting time of the nozzle; the cleaning water consumption measuring module is used for measuring the water consumption of one-time cleaning of the closestool cleaner; the cleaning force measuring module is used for measuring the cleaning force of the closestool cleaner; the cleaning area measuring module is used for measuring the cleaning area of the closestool cleaner; according to the full-process test, image recording, test process semi-automation, test result program judgment and test report automatic generation are carried out. Inaccuracy of test data caused by human factors in the test process is reduced, the whole test process is traceable in the whole process, and the test efficiency is greatly improved.

The utility model relates to the technical field of temperature and humidity acquisition, and discloses a laboratory temperature and humidity acquisition instrument which is applied to a laboratory main body, the top of the laboratory main body is a laboratory ceiling, and an experiment table is arranged on the inner bottom wall of the laboratory main body. According to the laboratory temperature and humidity acquisition instrument, the pushing assembly is arranged, after the pushing assembly is used, a movable rod can push a movable frame, a connecting column and a telescopic hydraulic cylinder to move, due to the fact that a guide groove is in a wavy line shape, the connecting column, the movable frame and the telescopic hydraulic cylinder move front and back while transversely moving, and the telescopic hydraulic cylinder stretches out and draws back; the temperature sensor and the humidity sensor at the output end of the telescopic hydraulic cylinder can move to all positions of the laboratory body, temperature and humidity collection of all positions of the laboratory body is facilitated, comprehensiveness of temperature and humidity collection is guaranteed, inaccuracy of temperature and humidity collection of a single area is reduced, and the working efficiency is improved. Therefore, an experimenter can perform an experiment in an environment with proper temperature and humidity.

The invention discloses a method and system for automatically evaluating strength training action posture safety, and the method comprises the steps: receiving a video transmitted by a user side, extracting frame image features, and outputting an action category sequence number; outputting a calling model vector according to the frame image features and the action category serial numbers; calling a corresponding body part granularity grade model according to the calling model vector; outputting human body posture key point coordinates according to the body part granularity grade model; calculating a movement speed and a joint angle according to the human body posture key point coordinates and the action category serial numbers; judging whether the movement speed or the joint angle is within a safety threshold range or not; and if the movement speed or the joint angle is recognized not to be within the safety threshold range, giving a prompt alarm. According to the method, subjectivity and inaccuracy in manual observation are reduced, and the safety and effect of exercise training are improved.

The utility model provides an automatic suction cup distance separation mechanism, which relates to the field of suction cup distance separation equipment, and comprises a fixed support and a plurality of suction cups, the inner wall of the fixed support is fixedly connected with an adjusting device, and the plurality of suction cups are fixedly connected to the bottom of the adjusting device. The driving piece drives the threaded rod to rotate, when the threaded rod rotates, the sliding block drives the guide plate to ascend and descend along the threaded rod, while the guide plate moves, the connecting frame is driven to slide on the inner wall of the guide frame, the fixing assembly is driven to slide, and the fixing assembly drives suction cups arranged on the fixing assembly to move at equal intervals. According to the device, the probability that the detection result of the suction cup is inaccurate is reduced, the influence on the quality and reliability of a product is reduced, the problem that the shutdown time of a production line is increased due to the fact that the belt needs to be frequently shut down for adjustment or replacement is solved, and the production efficiency is improved.

The utility model relates to the technical field of monitoring equipment, in particular to an intelligent electric power monitor convenient to install, which comprises an instrument shell serving as a novel monitor main body, an anti-reflection film arranged on the surface of the instrument shell, toughened glass connected to the bottom of the anti-reflection film, wire fixing grooves arranged on the side surfaces of the instrument shell, and thread grooves arranged on the side surfaces of the instrument shell. The wire fixing grooves penetrate through the surface of the instrument shell and the surface of the wire fixing groove. According to the utility model, the defects in the prior art are overcome, through the conductive sharp teeth and the antireflection film, in order to increase the connection stability, the intelligent power monitor adopts the conductive sharp teeth between the extruded conductive sheet and the wire pressing terminal to ensure line clamping and stable connection, and in order to improve the observation experience and protect the screen, the antireflection film and the toughened glass are adopted. Light reflection is reduced and impact resistance is provided, these designs and assemblies improve connection stability, data transmission accuracy, and enhance observation experience and screen protection capability.

The invention relates to the technical field of data processing, in particular to a data acquisition and processing method for Actiwatch, which comprises the following steps of: obtaining a sleep state level at each moment according to data in all index data sequences, and obtaining a sleep time period of each small fragment sequence; according to the fluctuation condition of data in the sleep time period, the sleep abnormality degree of each small fragment sequence is obtained, according to the data of each sleep quality parameter of each small fragment sequence, the user exercise amount of each small fragment sequence is obtained, a sleep curve is obtained through fitting, and a low-sleep-quality sequence and a high-sleep-quality sequence are obtained; obtaining a sleep quality index of each small fragment sequence; and scoring the sleep quality of each small fragment sequence according to the sleep quality index of each small fragment sequence, and obtaining an evaluation parameter most suitable for the user. According to the method, the most suitable evaluation parameters of the sleep quality are obtained in combination with the physical conditions of different users, and the degree of misjudgment is reduced.

The present invention discloses a pest identification and counting method, including obtaining pictures of various pest types to form an original data set, calibrating the original data set; performing a first process on the calibrated original data set, training and verifying a target detection model based on the first process result; selecting pest pictures of similar types for a second process to train and verify a classification model; using a target detection model to perform object detection on the pest pictures to be detected to obtain pest detection results; performing a segmentation process on the pest pictures to be detected based on location information of similar categories, and using a classification model to classify the pest types on the segmentation results to obtain pest classification results; based on the location information, preliminary classification results and pest classification results, the types and quantity of pests are obtained. The present invention uses AI image recognition technology to complete the image acquisition and counting functions of trapping insects remotely, monitors target insects in real time, and reduces the inconvenience and inaccuracy of manual segmentation and re-verification of data.

The invention discloses a portable delivery room data automatic acquisition device which comprises a delivery room data acquisition device, a frame is arranged on the delivery room data acquisition device, a partition plate is horizontally arranged in the center of the interior of the frame, and a weighing tray is arranged above a weighing sensor in the center above the partition plate. Weighing trolley doors are symmetrically arranged on the two sides, below the partition plate, of the assembly matching installation box, a storage battery and a transformer are arranged in the assembly matching installation box, a handrail is arranged on the top of the right side box wall of the frame, a discharging hopper and a control host are arranged on the top of the frame, and the bottom of the discharging hopper and the top end of the frame are installed in a matched mode through a matching installation base; the control host comprises a touch display, a two-dimensional code scanning gun and a weighing sensor, the delivery room data acquisition equipment can automatically acquire data related to a delivery room, reduces the error probability in personnel recording, directly stores the data in a database, does not need secondary recording, reduces deviation and mistakes and omissions in information transmission, and improves the efficiency of data transmission. Inaccurate weighing data caused by human intervention of pig stability is reduced, the working process of a delivery room is optimized, and the working efficiency of the delivery room is improved.

The application discloses a motion control system of a robot flexible joint module based on double encoders, and the flexible joint module comprises a drive controller, a motor, a first encoder and a second encoder. The drive controller comprises a communication module, a control module and an intelligent drive module which are sequentially connected. The intelligent drive module is electrically connected with the motor. The first encoder and the second encoder are both connected with the control module through the communication module. The intelligent drive module detects three-phase current and bus voltage of the motor and sends them to the control module. Meanwhile, the intelligent drive module receives and amplifies the control signal output by the control module to drive the motor to move. The control module runs a flexible joint motion control algorithm according to the position information of the motor end and the load end, the three-phase current of the motor and the bus voltage, and outputs the control signal to the intelligent drive module. The application has the advantages of small structure size, easy use and high positioning accuracy of the joint.

The invention discloses a transponder PCB testing device and method, electronic equipment and a storage medium, the device comprises a signal switching module, a probe power module, a clamp module and a cable, the signal switching module comprises a first digital control unit and a driving and collecting instrument, and the probe power module comprises a second digital control unit, an electromagnetic valve and a stable gas source. The clamp module comprises a processing circuit provided with an impedance matching circuit and a noise filtering circuit, a clamp and a single-head pneumatic probe, the first digital control unit is connected with the driving and collecting instrument through a cable, the driving and collecting instrument is connected with the processing circuit through a cable, and the processing circuit is connected with the single-head pneumatic probe through a cable. The second digital control unit is connected with an electromagnetic valve through a cable, the electromagnetic valve is connected with a stable air source through an air pipe and connected with a single-head pneumatic probe through an air pipe, and a PCB of the transponder to be tested is fixed through a clamp. The device can reduce the influence of noise or impedance on the test result of the transponder PCB.

A light curtain detection device includes a light curtain transmitting unit, a light curtain receiving unit, the light curtain receiving unit is arranged opposite to the light curtain transmitting unit, and receives the light beam emitted from the light curtain transmitting unit; and a transparent protective shell, including a first protective shell and a second protective shell respectively sealed, the light curtain transmitting unit and the light curtain receiving unit are respectively arranged inside the first protective shell and the second protective shell; a detection channel for the product to pass through is formed between the opposite surfaces of the first protective shell and the second protective shell. Compared with conventional photoelectric switches, the light curtain can detect a wider range; the transparent protective shell can reduce the probability of inaccuracy when the light curtain sensor structure is affected by external factors such as water droplets splashing.

The invention discloses an industrial robot operation fault determination method, which relates to the technical field of fault determination, and evaluates the degree of influence of the robot operation state on an observation time window by comprehensively analyzing trajectory data to be executed by a robot and corresponding load data; the influence degree of the operation state of the robot on the observation time window is subjected to influence grade division, the influence is divided into low-grade influence and high-grade influence, and corresponding solving measures are started to improve the accuracy of robot operation fault judgment, so that the accuracy of robot operation fault judgment is improved. Whether the size of an observation time window needs to be properly increased or not can be judged according to actual conditions, and missed judgment and inaccuracy of fault judgment are reduced, so that potential safety hazards of equipment are reduced, and the influence on production efficiency is reduced.

The invention discloses a self-testing device for an ultrasonic transducer array, relates to the technical field of transducer array testing, and solves the technical problem that the development speed of a transducer array integration process is too slow due to insufficient transducer array testing accuracy and efficiency. According to the technical scheme, the magnitude of a to-be-measured capacitor is obtained by calculating the rising time and the falling time of charging and discharging of the to-be-measured capacitor, and measurement of array elements in a transducer array is achieved; and meanwhile, a reference capacitor is introduced to reduce current errors and inaccuracy caused by circuit parasitic capacitance. By means of the self-testing device, measurement of electrical parameters of all mainstream transducers can be achieved, and the development speed of the transducer array integration process is greatly increased.

The present invention discloses a Chinese medicinal material seedling bed with air permeability detection, relates to the technical field of Chinese medicinal material planting, comprises a seedling rack and a seedling tray, the top of the seedling rack is slidably connected with the seedling bed, the bottom of the seedling bed is provided with two symmetrical groups of four sliding racks, the bottom of the sliding rack slides on the seedling bed, the two groups of sliding racks are rotatably connected with movable rotating rods, the two movable rotating rods roll between the seedling bed and the seedling rack, and the ends of the two movable rotating rods that are far away are fixedly connected with a handle. The seedling tray can be vibrated synchronously by the vibration of the placement rack, so that the compacted soil in the seedling tray is vibrated and loosened, reducing the steps of manually loosening the soil one by one, and improving the efficiency of loosening the soil in the seedling tray. In addition, loosening the soil by vibration can also avoid the existing manual loosening of the soil causing the soil to leak out of the seedling tray, reducing the steps of additional soil cleaning, and avoiding waste.

The present application discloses a water pump fault prediction method and system based on big data, which relates to water pump fault prediction, and includes an acoustic wave information acquisition module, an acoustic wave safety factor analysis module, a first-level safety prediction module, an operation information detection module, a second-level safety prediction module, a comprehensive safety analysis prediction module and a database. The operation of the water pump is fully monitored by the acoustic wave information acquisition module and the operation information detection module, which solves the potential danger of the prediction result, reduces the one-sidedness and inaccuracy of the prediction result, and analyzes the first and second-level safety prediction coefficients by the first-level safety prediction module and the second-level safety prediction module, and finally analyzes the comprehensive prediction coefficient of the water pump, so that the prediction of the water pump fault is comprehensive, the accuracy of the water pump fault prediction is improved, and the prediction results and corresponding data are uploaded to a shared database, which promotes the development of water conservancy and hydropower technology.

The invention relates to a device and method for estimating the number or density of animal populations in the field. The method comprises the following steps: step 1, placing an infrared camera in a field area where animals frequently move close to a water source; step 2, installing a reference object A in a fan-shaped area 10-20m away from the infrared camera; step 3, installing a reference object B in a fan-shaped area 20-30 m away from the infrared camera; 4, a reference object C is arranged in parallel at the position 5-10 m away from the reference object A; and 5, selecting a reference object D at a position 5-10m away from the reference object B, and arranging the reference object D in parallel. According to the method, the camera and the reference object are regarded as a whole, the population number or density of animals distributed in the picture can be conveniently calculated by using the actually measured distance between the reference object and the camera through the animal picture shot in the field, the principle is simple, and the actual implementation is convenient; the problem of inaccuracy of estimating the number or density of animal populations by using photos can be effectively reduced, and the error risk of estimating the animal populations by using a field infrared camera through the shot photos is reduced.

The invention discloses an ultrasonic atomization dye liquor dispersing device and a slide dyeing system. The ultrasonic atomization dye liquor dispersing device comprises an operation table and a spray dyeing device, a spray dyeing area is arranged on the operation table, and the spray dyeing area is provided with a plurality of slide carrying tables; the spray dyeing device comprises a liquid injection unit and an atomization unit, the atomization unit comprises a first adjusting part and an atomizer, the atomizer is movably arranged on the operation table, the first adjusting part drives the atomizer to be close to or away from the liquid injection unit, and the liquid injection unit can store and inject dye liquor; the liquid injection unit is communicated with the atomizer, and the atomizer atomizes the dye liquor and sprays the dye liquor to the slide on the slide carrier.

The invention discloses an equipment fault detection method based on Internet of Things and data driving. The method comprises the following steps: deploying and installing a production line environment monitoring module, an equipment state monitoring module, a fault detection module, a control module, a plurality of environment sensors and a plurality of equipment state sensors in a target monitoring area; the production line environment monitoring module obtains environment data around the equipment; the equipment state monitoring module obtains equipment state data; the production line environment monitoring module and the equipment state monitoring module respectively pre-process the acquired data and then transmit the data to the fault detection module; the fault detection module performs fault detection on the received data to obtain a detection result, and transmits the detection result to the control module; the control module adjusts equipment on the production line in real time according to the detection result. According to the method, efficient production line equipment fault detection is realized through the synergistic effect of the sensor, the monitoring module, the fault detection module and the control module.