111results about How to "Avoid dependency" patented technology

The invention relates to a server application architecture migration method and device and a storage medium, and the method comprises the steps that an automatic detection module analyzes and checks a to-be-migrated application under an X86 architecture, and the to-be-migrated application is subjected to static code analysis, dynamic performance analysis and system compatibility check; according to analysis and check results of the automatic detection module, the automatic adjustment module replaces an X86 specific instruction and a library function, performs memory allocation optimization and memory mapping adjustment, and generates an automatic adjustment report; and the automatic optimization module executes a performance benchmark test, and executes memory access optimization, algorithm optimization, task scheduling optimization and multi-core parallelization adjustment according to a test result. According to the server application architecture migration method and device and the storage medium, the architecture adaptation process can be simplified, performance optimization support and automatic dependency relationship management can be provided, the migration efficiency can be improved, and the cost can be reduced.

The invention provides an electromagnetic spectrum situation reinforcing method based on a K-means clustering algorithm, relates to the field of electromagnetic spectrum management and situation awareness, and aims to effectively complement electromagnetic spectrum data through unsupervised learning and overcome the problems of dependence on a large number of samples and sample imbalance and migration in a traditional method. The method comprises the following steps: firstly, carrying out grid division on a target area, and collecting electromagnetic spectrum data of each grid point through measuring equipment; then, an elbow method is used for determining the optimal clustering number of K-means clustering, clustering analysis is carried out on the collected data, and the clustering center of the frequency spectrum situation is obtained; and then, complementing missing spectrum data based on a clustering result to generate a complete spectrum situation map. And the accuracy of the complemented data is verified through similarity evaluation. According to the method, the calculation complexity is reduced, the accuracy and reliability of spectrum situation sensing are improved, and the method is suitable for real-time management and optimization of spectrum resources.

The invention provides an optical convolution calculation device. One path of output of a light source module loads a first group of vector data to a target light source comprising a single-wavelength light source so as to output an intermediate optical signal, and the other path of output outputs an optical carrier without a modulation signal according to the target light source; the programmable FIR filter loads a second group of vector data which is obtained based on tap self-configuration and serves as a weight vector to the middle optical signal; and the detection module detects the optical power corresponding to the optical signal and the optical carrier to which the modulation signal is not added and used for representing a vector convolution calculation result. According to the invention, only a single-wavelength light source is adopted, the difficulty of on-chip integration can be reduced on the basis of ensuring the rate, and the manufacturing cost of the device can be reduced; compared with the prior art, the method has the advantages that larger-scale convolution calculation can be achieved, the efficiency of image processing through the convolutional neural network can be improved, the computing power consumption of a computer can be effectively reduced, and high-speed, low-power-consumption and high-integration-level chip-level neural network optical calculation is achieved.

The invention discloses a nonlinear dynamic inverse control method based on a reinforcement learning agent. The nonlinear dynamic inverse control method comprises the following steps: establishing an attitude dynamic model of an aircraft; the attitude dynamics model is converted into an outer control loop and an inner control loop, the outer control loop controls the roll angle, the pitch angle and the yaw angle, and the inner control loop controls the roll angle speed, the pitch angle speed and the yaw angle speed; an outer loop control law is obtained based on the outer control loop, and control parameters of the outer loop control law are updated in real time based on reinforcement learning; an error is introduced on the basis of the inner control loop, a disturbance observer is constructed to estimate the error, and an inner loop control law is obtained based on the estimated error and the inner control loop; and performing flight control by combining the outer loop control law and the inner loop control law. The method is applied to the field of aircrafts, a reinforcement learning method is combined with a traditional nonlinear dynamic inverse method, controller parameters are dynamically optimized, and the robustness of a control system under the condition that model errors exist is improved.

The invention belongs to the technical field of electromagnetic interference elimination, and discloses a method and system for processing electromagnetic leakage interference of an electromagnetic vibration table, and the method comprises the steps: starting a signal collection and analysis module, monitoring an electromagnetic signal generated in the operation process of the electromagnetic vibration table in real time, and recognizing an interference frequency range; a proper filter is selected or designed based on the identified frequency range through a filter selection and design module; a filter processing unit is utilized to install filters on necessary power lines and signal lines, and interference suppression measures are executed; the test and optimization module is operated, the filtering effect is evaluated, the configuration of the filter is adjusted according to needs, and the electromagnetic interference suppression effect is optimized; and the monitoring and adjusting module is continuously executed to adapt to the change of an experimental environment, so that long-term effective electromagnetic interference control is ensured. The invention provides a solution which is more accurate, effective and flexible compared with the traditional physical shielding, and is suitable for the occasion of carrying out high-precision vibration test on the magnetic sensitive sample.

The invention discloses an automatic causal structure generation method based on semantic representation and logical reasoning of a large language model. The method comprises the following steps: acquiring an input text; performing semantic coding and clustering on the obtained input text by utilizing a large language model, and establishing a candidate causal variable set; causal relationship detection is carried out on the established candidate causal variable set based on anti-fact intervention and do-calculation; performing causal direction judgment, and generating a directed acyclic causal graph meeting logic consistency; and on the basis of the generated directed acyclic causal graph, natural language interpretation is generated by using a large language model, and logic consistency closed-loop verification is carried out. According to the method, automatic generation from the natural language to the causal structure is realized, the causal variable set is automatically extracted and constructed from the unstructured natural language text, the defects that variables need to be manually defined and modeling depends on field experts in the existing causal modeling process are avoided, and the labor cost and professional threshold of causal structure construction are remarkably reduced.

The invention relates to the field of earth-rock engineering, and discloses an organization design optimization method for improving the work efficiency of earth-rock engineering machinery, and the method comprises the following steps: S1, carrying out the modeling of each process in the earth-rock engineering through a directed acyclic graph; s2, calculating the earliest starting time and the latest starting time of each process by using a critical path method based on the process relation model, identifying a critical path of the project, and determining a critical process which affects the project construction period; s3, on the basis of the identified key process, performing process scheduling optimization by using mixed integer linear programming to ensure that the project period is minimized under resource limitation, and generating an optimized process scheduling scheme; and S4, based on the optimized process scheduling scheme, establishing a multi-stage queuing theory model, and optimizing the scheduling of the mechanical equipment. By optimizing procedure scheduling and mechanical equipment scheduling, the construction efficiency of earth-rock engineering is remarkably improved, the construction period and resource waste are reduced, and it is ensured that a project is efficiently completed on schedule.

The invention relates to the technical field of biological medicine, in particular to the field of cell therapy, and particularly relates to application of STAR and immune cells comprising the STAR to treatment and / or prevention of tumors, an antigen binding region of the STAR comprises one or more than two of an antibody, a ligand or an antibody fusion body which binds to LILRB4, the antibody such as scFv or VHH, and the ligand and the antibody fusion body can be combined with the LILRB4. Wherein the LILRB4 is used as a tumor antigen and / or a receptor in an immunosuppressive active cell. According to the invention, the targeted killing effect of immune cells on tumors is enhanced by targeting tumor cells and / or reducing immune escape caused by immunosuppressive active cells.

The invention provides a multi-microgrid load frequency control method based on dynamic event triggering, which can be applied to the technical field of intelligent microgrids. The method comprises the steps that a local sampling error of the micro-grid system is acquired, the local sampling error is obtained based on a global neighborhood error and a local neighborhood error of the micro-grid system, and the local neighborhood error is used for representing a state difference between the micro-grid system and a neighbor micro-grid system at a sampling moment; under the condition that the local sampling error meets a dynamic event triggering rule, updating an initial weight matrix of the action-evaluation neural network based on the local sampling error to obtain a target action-evaluation neural network; and determining a load frequency control strategy of the micro-grid system based on the system state of the micro-grid system at the sampling time and the target action-evaluation neural network. The invention further provides a multi-microgrid load frequency control device based on dynamic event triggering.

The invention relates to an optimized regulation and control method based on a model considering an uncertain source load operation scene, and the method comprises the steps: solving a predicted value of conventional load power through a load power prediction method, such as a neural network method, and solving predicted values of wind power output and photovoltaic output through a distributed power output prediction method, such as a data statistics prediction method; a prediction error distribution function of wind power output and load power is combined, a source load operation scene generation model considering prediction errors is established, a large number of original source load operation scenes are generated, an improved hierarchical K-means clustering algorithm is used for extracting the original source load operation scenes, and a source load uncertainty model based on the multi-scene technology is established; compared with the prior art, the method has the advantages that the calculation complexity is simplified while the uncertainty influence caused by prediction errors is fully considered, the dependence of a traditional clustering algorithm on the number of target scenes is avoided, and the strong uncertainty of the source side and the load side of the power distribution network is accurately described.

The invention discloses an automatic calibration system and method for an audiometer, and particularly relates to the technical field of automatic calibration of audiometers. The system comprises a calibration preprocessing unit, a calibration processing unit and a database, and the calibration preprocessing unit comprises a calibration judgment module, a calibration environment evaluation module and a calibration starting module and is used for preparing before the self-service physical examination machine audiometer is calibrated. And the calibration processing unit comprises a calibration parameter selection module, a calibration parameter synchronization module, a verification error evaluation module and a verification error processing module, and is used for the calibration control platform to execute various operations in the calibration process of the target self-service physical examination machine audiometer. The parameters of the self-service physical examination machine audiometer are monitored, all the to-be-calibrated self-service physical examination machine audiometers are calibrated, a full-automatic calibration mode is adopted to replace traditional manual calibration, and the calibration efficiency of the self-service physical examination machine audiometers is improved.

The invention provides a table structure identification method and device. The table structure identification method comprises the following steps: acquiring attribute information of a plurality of cells of a to-be-identified work table; according to the attribute information of the plurality of cells of the worksheet, performing region segmentation on the worksheet to obtain at least one target region in the worksheet; wherein different target areas belong to different tables in the worksheet; for each target area, obtaining feature data corresponding to each cell sequence according to attribute information of a plurality of cells contained in at least one cell sequence in the target area; and performing table structure identification on a target cell sequence according to the feature data corresponding to the target cell sequence in the at least one cell sequence. According to the embodiment of the invention, the table structure recognition effect can be improved.

The invention relates to a calibration method, device and tool for multiple radars of a material grabbing machine, and belongs to the technical field of robots. The objective of the invention is to solve the problems of low precision and poor applicability of an existing multi-radar calibration method for the material grabbing machine. According to the invention, material grabbing machine pose information and laser radar point cloud data are fused, point cloud splicing, point cloud segmentation, rough matching and fine matching are carried out, and a transformation matrix from all radars to a reference radar is obtained, so that material grabbing machine multi-radar calibration is completed. According to the invention, the radar overlapping region limitation caused by a large material grabbing machine body can be effectively broken, and the calibration precision and reliability are improved; effective calibration can be carried out under complex terrains, and dependence on flat roads is avoided; any two radars can be directly calibrated, accumulative errors caused by cascade calibration are avoided, and therefore the overall calibration precision and accuracy are improved. The method is suitable for unmanned projects of the grabbing machine, can improve the overall performance of a sensing system, and has important practical value.

The invention relates to a water supply network leakage identification system and method, and the method comprises the steps: carrying out the collection of an acoustic emission signal of a detected section of a water supply network through an acoustic emission collection device, carrying out the noise reduction and filtering of the acoustic emission signal through a signal noise reduction processing device in a variational mode decomposition and correlation test mode, obtaining a filtered acoustic emission signal, and carrying out the detection of the filtered acoustic emission signal. And finally, extracting the Mel-cepstrum coefficient characteristics from the filtered acoustic emission signals through a leakage identification device, and obtaining the leakage condition of the detected section of the water supply network according to the Mel-cepstrum coefficient characteristics through a deep neural calculation model. Due to the fact that the Mel-cepstrum coefficient characteristics of the acoustic emission signals obtained after noise reduction and filtering can accurately promote recognition and prediction of the leakage situation of the water supply network, it is ensured that the leakage situation of the detected section of the water supply network can be obtained by the deep neural calculation model, the leakage recognition precision is high, and human experience recognition is not needed.

The invention discloses a civil aviation logistics information query method based on big data analysis, and particularly relates to the technical field of aviation logistics information query, and the method specifically comprises the steps: constructing an empty window detection model to discriminate and judge the update state of logistics information, and outputting the type of an abnormal update state, constructing a machine learning model to judge the spatial state of the cargo, predicting the transportation node and time of the cargo in combination with logistic regression analysis and time sequence analysis, checking the cargo according to the predicted transportation node and time, and if the cargo cannot be checked, complementing lost logistics information through a graph neural network, so as to complete the logistics information of the cargo. And the completed logistics information is input into the empty window detection model to judge the space state of the cargo and predict the transportation node and time of the cargo until the actual logistics state of the cargo is checked and uploaded and updated, so that the searching and checking efficiency of the cargo with lost logistics information in air transportation is effectively improved, and the experience dependence of manual operation is avoided.

The invention belongs to the technical field of filter optimization, and discloses an EMI filter optimization method and system based on noise source impedance, and the method comprises the steps: measuring the noise source impedance and original noise corresponding to a common mode and a differential mode of a converter, judging an insertion loss demand based on the original noise, and determining a concerned frequency point through the insertion loss demand; the capacitance value of the safety capacitor is determined based on a capacitance value judgment rule, after the impedance characteristic value of the safety capacitor is determined according to the capacitance value, the impedance characteristic value is used for analyzing the inductance value needed by the concerned frequency point under the topological cluster, and a common-mode topological structure is determined; selecting a magnetic core based on a magnetic core selection rule, determining the number of turns required by the inductor corresponding to the concerned frequency point and the total differential mode capacity according to the magnetic core information, and selecting a differential mode optimal topology by using the total differential mode capacity; and determining a filter optimization scheme according to the common-mode and differential-mode optimal topology and the impedance characteristic value. According to the method, quantitative accurate optimization topology and parameter optimization design functions of the filter are realized.

The utility model relates to a square cosmetic bottle gilding device which comprises a machine frame, a gilding mechanism, a gilding foil releasing and collecting mechanism, a bottle rotating mechanism, a bottle ejecting mechanism and a bottle releasing mechanism, and the gilding mechanism, the gilding foil releasing and collecting mechanism, the bottle rotating mechanism, the bottle ejecting mechanism and the bottle releasing mechanism are all installed on the machine frame. The gold stamping mechanism is located between the unwinding end and the winding end of the gold stamping foil unwinding and winding mechanism, the bottle rotating mechanism is located below the gold stamping mechanism, the bottle ejecting mechanism is located right in front of the bottle rotating mechanism, and the bottle unwinding mechanism is located between the bottle rotating mechanism and the bottle ejecting mechanism. After the scheme is adopted, the gold stamping operation of the square cosmetic bottle can be carried out, the degree of dependence on skilled workers is reduced, manual operation errors are reduced, the gold stamping efficiency is improved, meanwhile, the consistency of the gold stamping effect of each bottle can be guaranteed, and the defective product rate is reduced.

The invention discloses a non-contrast super-resolution ultrasonic imaging method and system based on a diffusion model, and the method comprises the steps: transmitting a multi-angle composite plane wave to a target object, collecting an echo signal, and carrying out the beam synthesis to obtain an erythrocyte B-type ultrasonic image sequence; a space-time filtering algorithm based on singular value decomposition is applied to the erythrocyte B-type ultrasonic image sequence, erythrocyte signals are separated from tissue signals and noise signals, and an ultrasonic image sequence with the high signal-to-noise ratio is obtained for erythrocyte PD image reconstruction; and carrying out super-resolution mapping on the red blood cell PD image based on the trained diffusion model so as to reconstruct a super-resolution ultrasonic image in a non-contrast mode. According to the method, the dependence on an ultrasonic contrast agent is avoided, super-resolution mapping is carried out on the low-resolution erythrocyte PD image based on the deep learning diffusion model completed through training, ultrasonic imaging with ultrahigh resolution is achieved, the application flexibility of the SR-US imaging technology is improved, and the application range of the SR-US imaging technology is expanded.

The invention relates to the technical field of computers, and provides a data transmission method and device in a CAN network, equipment and a medium. The method comprises the following steps: in response to data arrival monitored by a current node in a CAN network, judging whether the data arrived on forward double CAN links of the current node corresponds to the same instruction or not; selecting a target instruction from the forward dual CAN link based on the judgment result; and based on the target instruction and the identifier of the current node, determining whether to transmit the target instruction to the next node through the backward dual CAN link of the current node. According to the scheme, the dependence of the CAN network on the monitoring node is avoided, and the communication load of the CAN bus is reduced under the condition of ensuring normal data transmission in the CAN network.

The invention provides a structural defect detection method and system based on mixing ultrasonic delay excitation, four piezoelectric ceramic sensors are arranged on the surface of a composite material layer in a rectangular shape, mixing sound waves received by the two piezoelectric ceramic sensors are subjected to band-pass filtering, EMD decomposition and reconstruction and frequency spectrum-energy spectrum analysis in sequence, and the frequency spectrum-energy spectrum analysis result is obtained. Extracting modulation sideband parameters from the time-frequency spectrum, and calculating defect identification parameters according to the modulation sideband parameters; if the defect identification parameter is greater than zero, determining that a defect exists in the modulation aliasing region under the excitation delay time; if the defect identification parameter is less than zero, determining that no defect exists in the modulation aliasing region under the excitation delay time; based on a frequency mixing excitation mode of delayed excitation of low-frequency pumping waves and high-frequency detection waves, frequency mixing incident waves do not need to be on the same axis, a sound wave aliasing area can be indirectly adjusted, and therefore large-range comprehensive scanning of the structure is achieved.

The invention discloses a laser cladding method, which belongs to the technical field of laser cladding process optimization, realizes intelligent regulation and control and automatic optimization of process parameters by collecting cladding images and performing HSV (hue, saturation, value) color space analysis in combination with a multi-channel process prediction model, and avoids the defects of dependence on artificial experience and repeated test in the traditional method. According to the method, two dimensions of molten pool quality and cladding layer quality are considered at the same time, and accurate optimization of process parameters is achieved by introducing a quality difference coefficient. According to the method, the quality of the cladding process is quantified through image processing, so that the control precision of process parameters is improved.

The present invention relates to a Bifidobacterium animalis subspecies lactis BGI-N3 ( Bifidobacterium animalis subsp. lactis BGI‑N3, deposit number: CCTCC NO:M20221585) or a composition comprising it as an active ingredient in the preparation of a product for preventing and / or treating metabolic diseases. The animal Bifidobacterium lactis subspecies comprises the 16S rDNA sequence shown in SEQ ID NO: 1. The animal Bifidobacterium lactis subspecies BGI‑N3 provided in an embodiment of the present invention has good safety and excellent gastrointestinal environmental tolerance, can effectively reduce the food calorie conversion rate, regulate the level of systemic chronic inflammation, and improve fat accumulation to prevent and / or treat metabolic diseases, such as obesity.

The present invention discloses a method for calibration and coaxial positioning of a dual-manipulator base coordinate system, wherein the dual-manipulator comprises a first manipulator and a second manipulator, and the method comprises the following steps: S1: installing the same calibration device on the two manipulators respectively, and fixing the calibration workpiece on a workbench; S2: moving the first manipulator to the workbench, and aligning the calibration device with the calibration workpiece, and obtaining the posture information of the end of the first manipulator at this time; using the same method to obtain the posture information of the end of the second manipulator; S3: repeating step S2 for multiple times, and then processing the data obtained in step S2 to obtain a calibration matrix; S4: changing the position of the calibration workpiece, repeating steps S2-S4, until the number of changes reaches a preset number of times, and obtaining a final calibration matrix; S5: coaxially positioning the dual manipulators according to the final calibration matrix. The present invention can realize rapid and accurate positioning and calibration of the dual manipulators, and further improve the stability and reliability of the operation.

The present invention proposes an electromagnetic spectrum situation reinforcement method based on the K-means clustering algorithm, which relates to the field of electromagnetic spectrum management and situation awareness, and aims to effectively complete electromagnetic spectrum data through unsupervised learning, and overcome the dependence on a large number of samples and the problems of sample imbalance and migration in traditional methods. The present invention first divides the target area into grids, and collects electromagnetic spectrum data of each grid point through a measuring device. Then, the elbow method is used to determine the optimal number of clusters for K-means clustering, and the collected data is clustered and analyzed to obtain the cluster center of the spectrum situation. Then, based on the clustering results, the missing spectrum data is completed to generate a complete spectrum situation map. The accuracy of the completed data is verified by similarity evaluation. The present invention reduces the computational complexity, improves the accuracy and reliability of spectrum situation awareness, and is suitable for real-time management and optimization of spectrum resources.

The application provides a multi-intention interactive game decision method and system for automatic driving path planning, which fuses current environment information and current state information by acquiring the current state information and the current environment information, extracts state features and intention features of a moving target from current scene features, fuses the intention features of the state features of the moving target, constructs a game relationship graph, calculates attention weights between an automatic driving vehicle and the moving target, weights and aggregates a value vector by a prediction probability and the attention weights of different preset intention features executed by the automatic driving vehicle, performs feature splicing, nonlinear conversion and decoding on the aggregated features, evaluates each game candidate trajectory, and selects a game candidate trajectory with the maximum game value score as the automatic driving path; the application reduces uncertainty in the interactive process, avoids the risk of sudden braking or collision caused by misjudgment, and has stronger environmental adaptability and generalization ability.

The embodiment of the present invention is about a method and device for processing a workflow, a storage medium, and an electronic device, and relates to the field of computer technology. The method includes: receiving a processing request including a workflow to be processed, responding to the processing request to determine whether there is process definition information corresponding to the workflow to be processed in a local cache pool; when it is determined that there is a process definition corresponding to the workflow to be processed in the local cache pool, executing the workflow to be processed according to the process definition information; when it is determined that there is no process definition information corresponding to the workflow to be processed in the local cache pool, obtaining the process definition information corresponding to the workflow to be processed from a distributed cache cluster, and executing the workflow to be processed according to the process definition information. The embodiment of the present invention improves the efficiency of executing the workflow to be processed.

The application belongs to the field of medical materials, and particularly relates to a metal core enhanced double-barrier piezoelectric nano system and a preparation method and application thereof. The preparation method comprises the following steps: first, a core-shell structure of'metal@mesoporous titanium dioxide@mesoporous barium titanate' is prepared through a step-by-step reaction, and then the target nanoparticles are obtained through lipid wrapping. The system innovatively constructs a double-barrier structure, can self-trigger active oxygen under a physiological pressure of 4 mmHg, realizes endogenous pressure self-driven treatment of malignant ascites, has the advantages of low pressure, high catalytic efficiency, long-term structural stability and good biocompatibility, solves the problems that existing treatment methods are highly invasive and depend on exogenous stimulation, and provides a new safe and efficient technical scheme for the treatment of malignant ascites.

The utility model relates to the technical field of round steel processing, in particular to a round steel shearing device which comprises a rack and a bearing frame, a transfer frame is arranged at the top of the rack, a plurality of roll shafts are installed in the transfer frame, a first servo air cylinder is arranged at the top of the bearing frame, and a second servo air cylinder is installed on a piston rod of the first servo air cylinder. A piston rod of the second servo air cylinder is provided with a first fixing plate, the side portion of the second servo air cylinder is provided with a second fixing plate connected with the bearing frame in a fastened mode, and the first fixing plate and the second fixing plate are used for stably clamping round steel. And a shearing tool is rotationally installed at the top of the bearing frame, and a storage barrel is arranged at the bottom of the bearing frame and used for storing residues generated after the round steel is sheared off. According to the round steel shearing device, the working efficiency of round steel machining is improved, the working time of shearing round steel is shortened, the requirement for batch machining can be met, the working precision of round steel machining is further improved, the rejection rate of round steel machining is reduced, and therefore it is guaranteed that round steel machining meets the production standard.

The utility model discloses a high -efficient spare part removal mechanism for production line relates to spare part removal technical field, including side plate, the side plate bottom rotatory installation advances the belt, and the side plate side wall below fixed mounting motor, and motor drive end fixed mounting synchronous assembly, the synchronous assembly includes with motor drive end fixed connection's drive rod, drive rod side end rotatory installation advances the rod, advances the rod side end rotatory installation and advances the plate, advances the plate top rotatory installation and turns the rod, in the utility model, through single motor drive synchronous assembly realizes mechanical linkage, and drive rod, advances the rod and the rod, long connecting rod form integrated power transmission chain, and the conveying action is bound through the pure mechanical structure and is caught the action, completely avoids the program dependence and the interference risk of the multi -power source cooperation, solves the problem of not being in step from the root, and the production line is interrupted to be prevented because of the action misplacement, and reduces the shutdown loss.

The invention discloses a signal-based WeChat applet state management method and system, and the method comprises the following steps: obtaining a signal of a double linked list data structure realized based on a TypeScript language, simplifying the declaration of a signal attribute through a decorator, converting the signal attribute into a responsive signal, and transmitting the responsive signal to a server; the method comprises the following steps: designing an Effect class of a double linked list according to a response type signal to perform signal collection and automatic tracking operation, performing batch processing on the response type signal through a batch updating mechanism to obtain a batch processing signal, when a dependent signal changes, notifying the Effect class to respond to the batch processing signal after the batch processing, and when the batch processing signal is updated, notifying the Effect class to respond to the batch processing signal after the batch processing. And automatically triggering to re-calculate batch processing signals, calling an Effect class to capture signal changes and notify page rendering updating based on a signal management framework and applet integrated response, and solving the problem that a simple dependency tracking mechanism is adopted in the implementation process of an existing signal model, so that the implementation efficiency is greatly improved. And a complex dependency relationship cannot be efficiently managed.