36results about How to "Save time resources" patented technology

The invention discloses a small-scale greenhouse gas emission prediction method based on a pre-training model, and belongs to the field of greenhouse gas emission prediction. According to the method, a greenhouse gas monitoring micro station is arranged in a park, data such as greenhouse gas concentration and meteorological factors are collected in real time, and high-precision traceability of a greenhouse gas emission source and accurate accounting of greenhouse gas emission can be achieved in combination with a high-precision meteorological numerical value mode, a backward trajectory tracking algorithm, a receptor model and a diffusion model; the greenhouse gas emission amount is predicted in real time by calling the pre-training model, and the prediction efficiency and accuracy are remarkably improved. Different from a mode that a traditional model depends on a large amount of historical data training, the pre-training model can be finely adjusted on the basis of a small amount of existing data, so that effective learning and prediction are realized. According to the method, a large amount of time and computing resources are saved, the environmental change can be quickly responded, and real-time and accurate emission prediction is provided.

The invention discloses a bearing vibration signal processing model construction method, a model and a signal classification method, which are used for constructing time domain and frequency domain loss functions by calculating a plurality of feature vector distances so as to train an encoder. According to the method, by minimizing the difference value of different distances in the time domain and frequency domain loss functions, an encoder can be guided to extract similar feature representations in signals, so that the similar feature representations are gathered in a feature space, and dissimilar features are separated. When a trained encoder (a convolutional neural network with an attention mechanism) processes a vibration signal of an unknown fault type, some feature representations in the signal are different from those of other signals, so that the feature representations are gathered in a feature space and are far away from the feature representations of other signals, and the fault detection accuracy is improved. Therefore, the recognition of the vibration signal of the unknown fault type is effectively realized.

The invention relates to a laser cutting-off technology, in particular to a laser bonding wire cutting-off device for chip detection, which comprises a workbench and the like, a fixed block is arranged above the workbench, and the fixed block moves through a first linear module mounted on the top surface of the workbench; a laser cutting device used for cutting off a welding wire is installed on the fixing block, and a datum plate is fixedly connected to the top face of the fixing block. The laser cutting device is provided with wiping blocks and other parts, the vertical positions of the wiping blocks are adjusted through the adjusting part, so that one wiping block can make contact with the bottom face of the lens of the laser cutting device, and when tiny impurities or dust on the lens of the laser cutting device needs to be wiped, the second linear module is started; the second linear module drives the moving block to move, so that one wiping block can wipe the lens of the laser cutting device, wiping can be completed in a laser cutting gap, manual wiping is not needed after each time of use, and time and manpower resources are saved.

The invention relates to a network intrusion detection method based on hierarchical Bloom filtering and a large language model, and belongs to the technical field of network security. The method comprises the following steps: carrying out preliminary rapid screening on input network communication data by using a hierarchical Bloom filter, training a network intrusion detection model, carrying out anomaly detection through a final network intrusion detection model obtained after training, and generating a detailed report of detected anomaly by using a large language model. According to the method, time and computing resources are saved, the overall efficiency of detection is also improved, real-time anomaly detection and response can be realized, the interpretability of a detection result is enhanced through a report generated by a large language model, and the specific condition and possible influence of an abnormal behavior can be understood conveniently.

The invention discloses a pedestrian tumble detection method based on NanoDet-Plus and fine tuning CLIP. The method comprises the following steps: S1, collecting data to make a data set; s2, a NanoDet-Plus target detection model is trained, and a trained algorithm model weight file is obtained; s3, performing pedestrian recognition on the image by using a target detection model NanoDet-Plus, and independently storing the recognized pedestrian image as an image file; s4, training the CLIP model and the improved Resnet50 model; s5, performing preliminary classification prediction on the pedestrian attitude image by using a CLIP model, performing further classification prediction by using an improved Resnet50 model, and connecting two classification prediction results so as to obtain a pedestrian attitude prediction result; and judging the current state of the pedestrian according to a posture prediction result, and taking feedback measures. And the recognition accuracy of the pedestrian falling event in the complex scene is improved.

This application provides a method, apparatus, electronic device, and storage medium for predicting battery heat generation power. It acquires multiple first average heat generation powers of the battery when charged and discharged at different rates at a target temperature, and multiple second average heat generation powers of the battery when charged and discharged at the target rate at different temperatures. The target temperature includes the middle temperature of the battery's operating temperature range, and the target rate includes the rate at the middle position of the battery's rate range and the rate at the beginning and / or end positions. The multiple first average heat generation powers and multiple second average heat generation powers are fitted to obtain a relationship between the heat generation power of the battery when charged and discharged at different rates at different temperatures. Based on the obtained heat generation power relationship, the heat generation power of the battery when charged and discharged at any rate at any temperature is determined. This application can save testing time and resources while ensuring prediction accuracy.

The invention provides a small group unmanned aerial vehicle high-voltage line fault emergency inspection fault system and method. The system mainly comprises a small group unmanned aerial vehicle module, a mobile control center module and a maintenance personnel module. And the small group unmanned aerial vehicle module performs automatic fault identification and fault related parameter detection for the cooperative combination of the three unmanned aerial vehicles, and performs data transmission among the three unmanned aerial vehicles in real time so as to improve the efficiency. And the mobile control center module is used for receiving the data sent by the small group unmanned aerial vehicles, processing the data to obtain some accurate data, and controlling the unmanned aerial vehicles according to the accurate data. And the maintenance personnel module is used for receiving accurate data from the mobile control center by the maintenance personnel, and performing maintenance under the assistance of small group unmanned aerial vehicles when the maintenance personnel arrive at a fault point site. Therefore, a safer and more efficient inspection and maintenance method is realized.

The application provides a soil component analysis system and device based on a spectrum technology, comprising a light source. In order to solve the problem that the soil samples sent to the laboratory are affected by the environment or are not properly preserved, resulting in errors in the results, the soil component analysis system is built-in the soil component analysis device. Compared with the traditional soil component analysis method, the system can perform rapid and accurate soil component analysis on the spot, without the need to take the samples back to the laboratory for processing, thereby saving time and human resources. When the electric telescopic sleeve and the electric telescopic inner tube are completely contracted, the first rotating assembly and the second rotating assembly are in the same horizontal plane with the L-shaped support column as a whole, which assists the L-shaped support column in supporting the detection assembly as a whole, and plays an auxiliary role in fixing the equipment during detection.

The utility model discloses a wheat seed and fertilizer integrated moisture-resistant seeding machine which comprises a box body, supports are fixedly arranged on the two sides of the box body respectively, a bottom plate is installed below the supports, a plurality of fertilizer applying mechanisms are fixedly arranged on the front side of the bottom of the box body, each fertilizer applying mechanism comprises a fertilizer discharging device, and a fertilizer conveying pipe is fixedly arranged at the bottom of each fertilizer discharging device. A plurality of seeding mechanisms are fixedly arranged on the rear side of the bottom of the box body, each seeding mechanism comprises a seed metering device, a seed metering pipe is fixedly arranged at the bottom of each seed metering device, the bottom end of each seed metering pipe penetrates through the bottom plate, and mounting plates are fixedly arranged on the two sides of the bottom of the bottom plate respectively; according to the utility model, multiple functions of fertilization, seeding, shallow rotary tillage, soil covering and the like are integrated, so that the tedious operation of the links of ploughing, fertilization, seeding and the like in the traditional seeding process is reduced, the labor intensity and the operation cost are reduced, the operation efficiency is improved, and the time, manpower and material resources are saved.

The application discloses an anti-data-damage heterogeneous federated learning system and method, which first adopts a robust data enhancement strategy in the local update stage, minimizes the adverse effects of local damage by performing multiple random data enhancement operations, and enables the model to learn rich local knowledge. Secondly, a robust reweighting communication method is designed in the collaborative update stage, which realizes communication between heterogeneous models while reducing the damaged knowledge obtained from other models. Finally, for the damaged feedback of unreliable clients, the application minimizes the learning of damaged knowledge by dynamically adjusting the contribution of the clients. The application achieves this goal by using a public data enhancement strategy that dynamically adjusts the contribution of the clients according to their ability to cope with data damage. The application can significantly improve the robustness to various data damage, thereby improving the performance of model heterogeneous federated learning.

The application relates to a knowledge base synchronization method, system and computer readable medium for space-based semantic communication, the knowledge base synchronization method comprising: initializing a general semantic knowledge base; in a first communication stage, training the general semantic knowledge base according to a first quantity of communication data to obtain a first semantic knowledge base, and transmitting the first semantic knowledge base to a sending end node and a receiving end node; judging whether the semantic knowledge base of the receiving end node needs to be updated, if the semantic knowledge base of the receiving end node needs to be updated, updating the semantic knowledge base of the receiving end node according to the first data transmitted by the sending end node to obtain a synchronized first communication semantic knowledge base; and the sending end node and the receiving end node communicating according to the synchronized first communication semantic knowledge base. The application can reduce the semantic knowledge base updating frequency of both communication parties in a satellite communication system, and save the time and bandwidth resources required for semantic knowledge base synchronization.

This invention relates to a plasma generator based on a dense microporous material catalysis, belonging to the field of low-temperature plasma technology. The plasma generator contains at least one discharge unit, which includes a first electrode, a microporous ceramic medium, and a second electrode. The first electrode is used to connect to a power source, and the second electrode is used for grounding. The microporous ceramic medium is used to adsorb gas molecules and active particles generated by the plasma discharge. This invention generates micro-discharge in a dense microporous medium, which has an extremely high specific surface area. When gas passes through, it is adsorbed onto the surface of the micropores in the medium. Similarly, active substances in the plasma are adsorbed onto the surface of the micropores in the medium. This improves the contact efficiency between short-lived, highly active particles and free radicals in the plasma and the reactants, promotes surface catalytic reactions, and improves the overall efficiency of the device.

The utility model discloses a clamping device for rubber tire detection, which belongs to the technical field of rubber tire detection and comprises a first mounting box, a second mounting box arranged at the top of the first mounting box, and a clamping assembly arranged at the top of the second mounting box and used for clamping during tire detection. The clamping assembly comprises a first motor fixedly mounted in the second mounting box, the output end of the first motor penetrates through the second mounting box and is connected with a rotating disc, and a plurality of sliding grooves are formed in the top of the rotating disc. The rotating disc drives the sliding groove to drive the connecting column to move, the connecting column drives the connecting plate to move, the fixing plate is driven to move, and then the tire is fixed, so that the tire can be kept stable in the detection process, measurement errors caused by movement or shaking of the tire are reduced, and the detection accuracy is improved. Therefore, the accuracy of detection results is improved.

The invention provides a visitor management and verification method and system for an exhibition self-service registration machine, and relates to the field of data processing.The method comprises the steps that an exhibition participation request is received in response, and a preset primary collection interface is called for content filling; in response to scanning of the secondary participation code by any secondary user side, sending a preset secondary acquisition interface to the secondary user side for content filling; in response to completion of content filling by each user side, sending payment information generated by the automatic registration machine based on the area number corresponding to all the acquisition areas to the primary user side; controlling the automatic registration machine to perform interface printing in response to fee payment of the main-level user side; and in response to the fact that registration operation is executed on each real exhibition bill, creating an exhibit evaluation area in the acquisition interface corresponding to each real exhibition bill, and uploading evaluation information uploaded by the corresponding user side to the exhibit evaluation area. The management efficiency is at least improved.

The invention relates to an automatic hidden danger identification method and device for an optical cable external force construction site, and belongs to the technical field of communication construction safety. Performing data standardization processing on the image data to obtain a target size image; constructing a hidden danger recognition model based on the convolutional neural network; and taking the target size image as the input of the hidden danger identification model based on the convolutional neural network, and carrying out hidden danger automatic identification. The system does not depend on manual patrol and a traditional three-staring management mode any more, a large amount of time and manpower resources are saved, real-time monitoring can be achieved, the phenomenon that hidden dangers cannot be found in time due to the fact that working time is not linked is avoided, and safety risks are reduced.

The application discloses a processing device, method and system of printing information in chip EDA simulation, and relates to the technical field of chip simulation.The device comprises: an information acquisition module, which is used for acquiring a printing control command input by a user in a command line, and is used for configuring printing information in an EDA simulation tool to control whether the printing information is displayed and output; a command analysis module, which is used for analyzing the printing control command to obtain simulation file and IP module information to which printing information to be displayed and output and printing information not to be displayed and output belong; and a printing control module, which is used for matching simulation files of each IP module in the EDA simulation tool based on a regular expression according to an analysis result, performing normal printing output on the printing information to be displayed and output, and performing annotation on the printing information not to be displayed and output to control the printing information not to be printed.The application is simple and flexible to operate, accurate in printing information, and saves time resources and computing resources.

The present invention provides a method, device, electronic device and storage medium for identifying diseased DNA, the method comprising: obtaining a DNA sequence to be tested and preprocessing the DNA sequence to be tested to obtain multiple DNA sequence fragments; for each DNA sequence fragment, inputting it into a trained first neural network model to output a first feature vector corresponding to the DNA sequence fragment; for each first feature vector, inputting it into a trained second neural network model to output a second feature vector corresponding to the first feature vector, and adding the first feature vector and the corresponding second feature vector to obtain a combined feature vector; inputting each combined feature vector into a trained classifier to obtain a classification result, the classification result indicating whether the input DNA sequence to be tested is a diseased DNA. The present invention can improve the accuracy of diseased DNA identification.

The invention discloses a reflection frequency estimation method, device and equipment for millimeter wave communication field intensity simulation and a medium, which are applied to the technical field of high-speed magnetic suspension vehicle-ground communication and aim to solve the problems of low reflection frequency determination accuracy and low efficiency. The method comprises the following steps: constructing a communication channel receiving power simulation model according to spatial scale data of a simulation environment; calculating a current precision value of each receiver according to the current reflection times in combination with a communication channel receiving power simulation model; according to each current precision value and the preset precision, whether the current reflection times meet the preset requirement is determined, so that the current reflection times are determined, the efficiency and accuracy of reflection times determination of millimeter wave communication field intensity simulation can be improved, and the computing power and time resources are saved.

The invention discloses a method for checking high-current wiring in a chip, which belongs to the technical field of chip layout design, and comprises the following steps of: determining metal layers in a layout subjected to conventional checking, and obtaining the minimum width and the number of through holes required when each metal layer passes through different current magnitudes under the limit working temperature of the chip; the method comprises the following steps: writing a DRC rule according to the minimum width and the number of through holes corresponding to different current magnitudes of each metal layer, executing the DRC rule by using a Calibre DRC tool to identify a first metal layer region, displaying the first metal layer region through a Calibre RVE tool, generating width information and through hole information of each first metal layer region, and determining the width information and the through hole information of each first metal layer region according to the current magnitude of a test current needing to pass through. The modification information is provided for the first metal layer area, inspection is carried out based on the preset DRC rule, the model is simple, the computing resource requirement is low, the inspection time is shortened, the inspection efficiency is improved, meanwhile, manual inspection is reduced, and the accuracy is improved.

The present invention discloses a method, device and medium for automatically optimizing the projection of trimming lines in an intelligent design process, and belongs to the field of industrial manufacturing technology. The method comprises: obtaining digital model data and trimming line data of a part, the digital model data comprises a product surface, a process supplementary surface and a pressing surface of the part, the process supplementary surface and the pressing surface form a process profile, the trimming line data comprises a suspended trimming line and a trimming direction line, one end of the suspended trimming line is connected to the outer contour line of the part, and is suspended above the process profile; a projection line is generated on the process profile according to the trimming direction line and the suspended trimming line; the projection line is discretized to obtain a plurality of discrete points, the discrete points are optimized according to the distance between adjacent discrete points, and a target projection line is formed according to the optimized discrete points. The present invention aims to reduce the process steps of the process design flow of parts, save time resources and human resources, and improve the design and production efficiency of parts.

The present invention provides a method and system for producing line information of a schematic diagram of an automobile circuit system. The method extracts the wiring harness information and fuse box information of the development vehicle model; searches for corresponding component information according to the wiring harness connector information; defines the development status of each configuration code by performing configuration comparison analysis, thereby further determining the development status of each pin information; and determines the plug-in relationship between each wiring harness by creating a wiring harness plug-in relationship generation rule. The extracted wiring harness information, fuse box information, component information, and pin information are integrated to automatically complete the production of the circuit information of the schematic diagram of the entire vehicle circuit system. By systematically extracting, automatically integrating, and completing the production of the circuit information of the schematic diagram of the entire vehicle system, the quality consistency of the production of the circuit information can be guaranteed, which lays a solid development foundation for the accurate drawing of subsequent system schematics.

The invention relates to a cynodon lawn coverage automatic identification method and system, a processing device and a storage medium, and the method is characterized in that the method comprises the steps: obtaining a cynodon lawn image of a to-be-identified sample plot, carrying out the preprocessing, and determining a target object; processing the preprocessed bermuda grass lawn image by adopting an edge segmentation algorithm to obtain a mask, and marking pixels occupied by vegetation in the mask; counting the proportion of the pixels occupied by the vegetation in the mask to the pixels of the whole image to obtain the vegetation coverage rate of the target object; the method is suitable for various lawn types and growth states, and can be widely applied to the field of lawn measurement.

Embodiments of the present application disclose a meta-information generation method and device for resource dependency analysis and a storage medium. A target reference resource file under a target file type in a reference resource file of a reference project is acquired, a node nesting relationship in the target reference resource file is analyzed, nodes with the same node nesting relationship are taken as the same analysis node, a first association relationship between each field and a field value under the same analysis node is determined, a target path mapping rule corresponding to each field in the first association relationship is determined based on a preset at least one path mapping rule and the field value in the first association relationship, the path mapping rule is used for mapping the field value into the form of a path, and path mapping meta-information corresponding to the target file type is generated based on each field and the target path mapping rule corresponding to each field. The generation efficiency and accuracy of the path mapping meta-information required when resource dependency analysis is performed can be improved, and human resources for generating the path mapping meta-information are saved.

The present invention belongs to the field of information processing technology, and discloses a continuous task planning system and method based on asynchronous causal inference reflection. Based on a large language model, through an actor module, task objectives and environmental observations are used as inputs, and the next action is predicted as output; through an association reasoning module, the association information between things is extracted from the environmental observation of the current trajectory, and the first level of hierarchical causal inference is performed to determine the association between things; through an intervention plan generation module, the second level of hierarchical causal inference is performed according to the new trajectory obtained by counterfactual reasoning and the previously extracted association information, and a plan for the next intervention implementation is generated to verify the cause of task failure; through a counterfactual reasoning module, the task trajectory is regenerated under the conditions of the task objectives and task trajectory, and the cause of the failure of the previous attempt is determined. The success rate of long-term task planning is significantly improved.

The utility model discloses a network to JTAG / URAT circuit, radar assembly and radar system, the circuit comprises a network interface, a USB to Ethernet controller chip, a USB to JTAG / URAT chip, a first clock circuit and a second clock circuit, the network interface is connected with the USB to Ethernet controller chip, the USB to Ethernet controller chip is connected with the USB to JTAG / URAT chip, the first clock circuit is connected with the USB to JTAG / URAT chip, and the second clock circuit is connected with the USB to JTAG / URAT chip. The first clock circuit is connected with the USB to Ethernet controller chip, and the second clock circuit is connected with the USB to JTAG / URAT chip. According to the utility model, remote JTAG debugging and serial port communication of the radar assembly can be realized, time resources and manpower resources are saved, and the debugging efficiency of a radar system is improved.

The present application relates to a method for setting category preferences based on model evaluation indicators and related devices, the method comprising the following steps: detecting the model type and obtaining the feature dimension to be evaluated of the model; detecting the output structure of the model's logits, and creating an adjustment layer based on the detected output structure; obtaining the pre-entered preference parameters based on the feature dimension to be evaluated, and determining the adjustment coefficient based on the preference parameters, the adjustment coefficient being an element in the adjustment layer and corresponding to the position of the feature dimension; detecting the output layer of the model, and inserting the adjustment medium before the output layer, the output layer being a linear layer for generating evaluation results using the output function and the logits value operation. The method quickly sets the preference parameters of the adaptation indicator category according to the specific evaluation indicator requirements, can meet the customization requirements in diversified application scenarios, and reduce the time and labor cost required for customization while maintaining the overall performance of the model.

The invention relates to a wound assessment method and device based on machine learning, equipment and a medium, and belongs to the field of intelligent medical treatment. The method comprises the steps that a user uploads an original wound image; wound labeling information is obtained based on the original wound image and is transmitted back to the user side, the wound labeling information comprises a wound contour, a wound size and a wound recovery stage, the wound contour comprises a conventional wound contour and a beautified wound contour, and the wound recovery stage comprises a blood coagulation stage, an inflammation stage, a repair stage and a mature stage; the user side comprises a conventional user side and a pure user side, the conventional wound contour is transmitted back to the conventional user side, and the beautified wound contour is transmitted back to the pure user side; according to the method and the system, the wound is quickly and conveniently identified, the wound information is returned according to different requirements of the user, and the reasonable wound nursing suggestion is provided.

The utility model discloses a multifunctional agricultural transport vehicle, which belongs to the field of agricultural carrying, and comprises a vehicle frame, the upper surface of the vehicle frame is fixedly connected with an arc-shaped plate, the inner side wall of the arc-shaped plate is provided with a chute track A, the inside of the chute track A is slidably connected with a slide rail block A, and the surface of the slide rail block A is fixedly connected with a transport box; through cooperative use of all the devices, the transport box is simple in structure and convenient and fast to operate, the angle of the transport box can be adjusted through cooperative use of the sliding groove track A and the sliding rail block A, internal materials can be poured out more conveniently and rapidly, in addition, the spraying head is additionally arranged on the transport vehicle, the spraying dust falling or irrigation effect can be achieved, and then the transport box is convenient to use. A sliding rail block B and a smooth scraping plate are additionally arranged in the transportation box, so that internal materials can be scraped more cleanly, residues are reduced, the structure is matched with one another, multiple functions are achieved, one vehicle has multiple purposes, multiple tasks of transportation, spraying and tillage can be completed, time and manpower resources are saved, and equipment investment is reduced.

The invention discloses a training method, a prediction method and a device of a diesel cetane number prediction model, and belongs to the technical field of petrochemical engineering, the training method of the diesel cetane number prediction model comprises the following steps: obtaining a training data set, the training data set comprising explanatory variables and corresponding target variables, the explanatory variables comprise physicochemical index data of different diesel oil samples, and the target variables comprise cetane numbers of different diesel oil samples; and based on the training data set, training a deep learning regression model to obtain a diesel cetane number prediction model. By utilizing the diesel cetane number prediction model constructed by the method, the cetane number of the diesel can be rapidly and accurately predicted.