30results about How to "Realize dynamic" patented technology

The invention relates to the technical field of visual health management, in particular to a ciliary muscle adjustment training system and method based on eye movement tracking, and the method comprises the steps: collecting eye movement data of a fixation point track, an adjustment amplitude change rate and pupil response time in real time, and combining personalized parameters such as the age of a user, diopter and a training target; inputting a ciliary muscle training dynamic planning algorithm module, dynamically generating a stage scheme containing a training action type, a single-group duration, a stimulation interval and a focal length adjustment strategy, and adaptively adjusting the strategy according to real-time adjustment stability and a historical ability curve; through multi-dimensional matching analysis of a pre-stored standard eye movement template, a training specification score is calculated from the track goodness of fit, speed uniformity, amplitude standard-reaching rate and binocular coordination, visual fatigue parameters are obtained based on continuous training duration, pupil fluctuation and retina reflex change, a scoring result is dynamically corrected, and a visual fatigue evaluation result is obtained. Personalized, self-adaptive and quantitative safety control of the training process is realized.

The invention discloses a respiratory disease oxygen precise conveying system based on a sensor, and relates to the technical field of medical equipment, and the system comprises a sensing module which integrates multiple sensors to collect and process airway and physiological data of a patient; the disease matching module identifies disease types through database comparison; the dynamic adaptation module calculates exclusive oxygen concentration based on a multi-mode fusion initial algorithm; the conveying module executes adjustment; the closed-loop feedback module continuously fine-tunes the oxygen concentration through a closed-loop stepped fine-tuning algorithm to form a closed-loop link, so that accurate dynamic control of oxygen delivery is realized; according to the invention, multi-sensor collaborative acquisition and disease precise matching are combined with a dynamic algorithm and closed-loop feedback, so that individuation and dynamic oxygen delivery are realized, the system avoids misjudgment by relying on a standardized database, and the oxygen concentration, flow and pressure are ensured to be adjusted in real time along with physiological indexes of a patient through multi-parameter collaborative adjustment and stepped fine adjustment; the treatment comfort, the effectiveness and the long-term adaptability are improved.

This invention proposes an ESG-based comprehensive governance assessment method, electronic device, storage medium, and product for shipbuilding enterprises. The method includes: collecting multi-source ESG data and operational data from the shipbuilding enterprise during the assessment period; calculating state baseline parameters based on the operational data according to preset time slices; converting the multi-source ESG data into standard evaluation units and forming ESG vector data corresponding to the preset time slices; matching corresponding ESG assessment parameters from a preset ESG assessment parameter library based on the enterprise size, ship type, or production organization method; if no match is found, adaptively calibrating the ESG assessment parameters to obtain calibrated ESG assessment parameters; calculating governance efficiency indicators for each time slice based on the ESG vector data, state baseline parameters, and ESG assessment parameters; calculating a comprehensive ESG governance efficiency coefficient based on the governance efficiency indicators for each time slice; and obtaining the ESG governance assessment result based on the comprehensive ESG governance efficiency coefficient.

The invention discloses a dynamic evaluation and intelligent compensation system and method for contact rigidity of a machine tool joint part. The system comprises a digital twin and multi-source data interface module, a contact interface multi-scale morphology acquisition and characterization module, a joint part contact mechanical state online simulation module, a contact rigidity dynamic calculation model library, a performance evaluation and intelligent compensation decision-making unit and a compensation strategy execution and feedback module. According to the method, dynamic and high-precision contact stiffness analysis is achieved, the problem that a traditional static model is insufficient in precision is solved by deeply fusing microstructure measured data, a macrostructure model and a dynamic working condition load, and the time-varying characteristic of the joint part under the complex working condition can be reflected more truly. A perception-evaluation-compensation active control closed loop is constructed, and the digitization level of machine tool design and operation is improved. According to the method, the contact state of the joint part is actively optimized, so that the dynamic and static performance and machining quality of the machine tool are improved.

The invention discloses an auxiliary evaluation system for future scene guidance. The auxiliary evaluation system comprises an evaluation management module, an evaluation control module and an evaluation process module, the evaluation management module is used for defining an evaluation stage, an evaluation standard and a risk probability calculation method; the method comprises the following execution steps: defining an evaluated session scene, evaluation content and an evaluation stage; determining an evaluation standard and a scoring dimension, and determining a method for calculating a risk probability according to the evaluation standard; setting an evaluation plan according to the risk probability; the evaluation control module is used for executing the evaluation plan and initiating an evaluation event to the evaluation process module; the evaluation process module is used for responding to the evaluation event, providing evaluation content for the user side according to the evaluation stage, calculating the risk probability of the evaluation stage according to the feedback result of the user side, and generating an evaluation result and an evaluation plan. According to the technical scheme, assessment obstacles caused by high frequency and multi-mode characteristics in the future scene guidance psychological assessment process can be effectively solved, and the assessment process is dynamic and procedural.

The application belongs to the technical field of payment security, and provides an import and export cross-border payment chain supervision method based on a dynamic graph, comprising: payment knowledge graph construction, payment node portrait construction, initial graph risk data acquisition, influence diffusion processing, FinBERT model identification, decision generation and execution; the application upgrades the risk monitoring of cross-border payment from single node monitoring to risk tracking of the whole link and correlation by building a cross-border payment exclusive knowledge graph, adding an influence diffusion processing mechanism and combining a large language model; and the application realizes dynamic and scenario-based grading of cross-border payment risks by calculating the risk value and risk level interval boundary of the node and the payment chain, so that the grading can accurately adapt to the dynamic risk changes of cross-border payment and fit the scenario differences of different nodes and payment chains.

The invention provides a ship lock operation scheduling system and method based on big data analysis, and relates to the technical field of ship lock operation scheduling. By integrating big data analysis of historical operation data, ship priority evaluation, real-time navigation state monitoring and intelligent prediction, refinement, dynamics and intelligence of ship lock scheduling are achieved, the overall traffic efficiency is remarkably improved, and congestion of a lock area is effectively relieved. Low-efficiency links are identified through clustering analysis, congestion points are captured in real time in combination with a space thermodynamic diagram, and a declaration time period and interval time are dynamically adjusted, so that the adaptive capacity of the system to abnormal conditions such as load change, severe weather and equipment faults is enhanced; differentiated services and green channel support of high-priority ships are realized, and key transportation requirements are guaranteed; and upstream and downstream ship lock linkage scheduling is realized through a network cloud platform, and a neural network model is utilized to generate an optimization scheme containing a lockage sequence, suggested arrival time and a coordination instruction to improve watershed navigation collaboration.

The invention relates to the technical field of electric power computing power scheduling, and discloses an electric power cross-domain computing power elastic scaling scheduling system supporting a creative GPU (Graphics Processing Unit). The system receives a power cross-domain computing power scheduling request, and searches a matched historical computing power use record set from a historical computing power database according to the request. And carrying out load category division on the historical record set to generate historical computing power record subsets of a plurality of load categories. Computing power feature core calculation is performed on the subsets to obtain a plurality of computing power feature core points and associated time intervals; and using the associated time intervals as the time range of a plurality of scheduling analysis layers, performing multi-scale scheduling feature analysis on the computing power monitoring data sequence of the current power cross-domain within the specified time range through the plurality of set scheduling analysis layers, and outputting a plurality of computing power scheduling feature sets. And carrying out cross-scale fusion calculation on the feature sets to obtain a fusion computing power scheduling feature set.

The application discloses an intelligent carbon metering device and a carbon emission calculation method thereof, and the method comprises the following steps: pre-processing multi-source data; using a deep learning model to identify the working conditions of each device, and simultaneously considering device aging correction to improve identification accuracy; establishing a bottom-up calculation model of carbon emission driven by energy consumption and a top-down calculation model based on emission concentration for concentration inversion; and obtaining the final carbon emission result through adaptive Kalman filtering fusion. The application identifies the device state in real time through AI, dynamically matches the emission factor, and adopts adaptive Kalman filtering to fuse the energy consumption and concentration double models, thereby significantly improving the accuracy and robustness of carbon metering. The method can effectively solve the problems of hysteresis, singleness and error accumulation in the traditional carbon metering method, realize real-time, accurate and traceable carbon emission calculation from the device level to the regional level, and realize the digitization, dynamicization and intelligentization of carbon metering.

The invention relates to the field of intelligent wearable devices, and discloses a dimmable dice wearable device which comprises a dice shell, a main control circuit board is arranged in an inner cavity of the dice shell, and a central processing unit, an LED dot matrix module, a near-field induction unit, a wireless communication unit, an audio conversion unit and an electric power storage unit are integrated on the main control circuit board; the central processing unit is connected with the LED dot matrix module, the near-field induction unit, the wireless communication unit, the audio conversion unit and the power storage unit through an electrical loop. Through cooperation of the integrated LED display module and the light guide composite material shell, dynamic and digital adjustment of the wearable device is realized, and the wearable device integrates LED, audio playing, communication and user interaction functions. Different LED colors can be switched and corresponding audios can be played according to the emotion of a user, and meanwhile, emotion data can be transmitted and received through wireless communication.

The invention relates to the field of agricultural credit approval, and discloses an agricultural production process data generation method, which comprises the steps of receiving credit application data of a target farmer through a farmer terminal; querying a user file according to the peasant household attribute information to obtain a peasant household integrity score, a planting type, an Internet of Things crop monitoring equipment identifier and a key evidence chain storage file; if the integrity score does not meet the preset condition, verifying the authenticity of the asset ownership proof file through the key evidence chain storage file; after the authenticity verification is passed, acquiring corresponding agricultural production process data according to the planting type, forming agricultural production process display data, pushing the agricultural production process display data to an intelligent terminal for visual presentation, initiating interactive inquiry, and acquiring supplementary description information of the farmer; and receiving the supplementary description information and carrying out associative storage on the supplementary description information and agricultural production process data to generate an agricultural production process data evidence material. Therefore, the authenticity, the integrity and the verifiability of the data are improved.

The invention discloses a dynamic field retrieval method and system based on an extensible retrieval processor mechanism. The method comprises the steps that multiple retrieval types are defined, and corresponding retrieval processors are configured; constructing a dynamic mapping template based on regular expression matching, and automatically distributing data types for dynamic fields; configuring a search field pool which can be dynamically loaded, and defining a retrieval attribute and an interaction mode of a field; receiving and analyzing a dynamic retrieval request generated by a front end according to the field pool, and obtaining a retrieval parameter of each field; according to a retrieval type in the parameters, dynamically scheduling a corresponding retrieval processor through a processor factory; query conditions are automatically constructed by the processor based on the parameters and integrated into the primary query. Full-link configuration driving from field definition, type mapping, interface generation to query execution is achieved, non-intrusive expansion of retrieval logic is supported, and the flexibility, maintainability and development efficiency of a system facing business changes are remarkably improved.

The application discloses a low-cost high-accuracy e-commerce goods-carrying video analysis method and system, and belongs to the technical field of data processing, and comprises the following steps: performing multidimensional availability checking on a to-be-analyzed goods-carrying video, then demultiplexing the video into a video audio stream and a video picture stream; performing streaming voice transcription on the video audio stream to generate a text semantic sequence, performing dynamic analysis on the video picture stream to extract a motion intensity coefficient, dynamically dividing video clips based on the two, and generating picture frame sets corresponding to each semantic segment, and simultaneously performing cross-segment summary aggregation to generate a video overall summary; performing parallel reasoning analysis on the picture frame sets of each segment, the audio text and the overall summary, generating multidimensional text analysis results, structurally processing each dimension analysis result, and integrating and concatenating in time sequence to generate a complete video structured description document, so that low-cost, high-accuracy e-commerce goods-carrying video automatic analysis is realized.

The invention discloses an urban landscaping ecological benefit intelligent evaluation method based on digital twinning, and particularly relates to the technical field of smart city and ecological information crossing, which comprises the following steps: collecting vegetation multispectral images, canopy three-dimensional point cloud, soil temperature and humidity and atmospheric microclimate parameters in real time, and combining a landscaping geometric model and a plant physiological parameter library to evaluate the ecological benefit of urban landscaping. The method comprises the following steps: constructing a high-fidelity and time-space synchronous urban landscaping digital twinborn body, dynamically extracting a multi-dimensional characteristic index, inputting an ecological process dynamic coupling model, outputting an ecological benefit comprehensive evaluation index and a time-space distribution map thereof, and supporting virtual scene deduction and multi-objective optimization by a system. Greening configuration and maintenance decision suggestions considering ecological benefits and cost benefits are generated, and dynamic display and closed-loop intelligent evaluation are realized through a visual interaction platform. According to the invention, real-time, accurate and systematic evaluation and intelligent management of urban landscaping ecological benefits are realized.

This application provides a pointing remote controller, a display device, and a cursor positioning method. The pointing remote controller can acquire ultra-wideband data measured by a first ultra-wideband device and a second ultra-wideband device, as well as motion data of the pointing remote controller measured by an inertial measurement unit. Based on the ultra-wideband data and motion data, target parameters are calculated. Based on the motion data, the motion state of the pointing remote controller is determined. Based on the anchor point update mode corresponding to the motion state, the anchor point parameters corresponding to the target parameters are updated so that the anchor point parameters approach the target parameters. Based on the updated anchor point parameters, the cursor position is calculated and sent to the display device so that the display device moves the cursor according to the cursor position. By combining ultra-wideband data and motion data, and based on the anchor point update algorithm, a fast and smooth cursor response effect is achieved while ensuring tracking accuracy.

The application provides a kind of carbon footprint monitoring analysis and evaluation method and system based on blockchain, related to carbon footprint field, solve the technical problem that the result is distorted due to the dependence of carbon emission accounting on static or regional average emission factor in prior art, so that it is difficult to achieve high-precision carbon footprint quantification.The method comprises: collecting energy consumption data and production activity data, and attaching a timestamp to the collected data and applying a private key digital signature of the data collection device to form monitoring data; based on historical emission related data, an emission factor calibration model is constructed, and an emission factor is output, and the energy consumption data and production activity data corresponding to each emission source are subjected to carbon footprint quantification calculation to obtain carbon emissions; according to a preset carbon performance evaluation rule set, the carbon footprint results in the carbon accounting record are evaluated.The application is used in the process of carbon footprint monitoring.

This invention relates to the field of big data remote control technology, and discloses a high- and low-voltage switchgear monitoring platform and method, comprising: configuring a preset forward-looking window and sampling interval, registering system parameters and controllable load branch parameters, using a load prediction model to predict the switchgear operating data, establishing a charging power curve based on the discharge state, capacity, and target recovery time of energy storage equipment, and calculating the power supply margin based on the rated power of the power supply equipment, thereby obtaining the conflict accumulation. The system compares the conflict accumulation with a safety threshold to determine whether there is a conflict gap that needs to be eliminated; then, for each controllable load branch, it calculates the reduction contribution and unit priority contribution efficiency, and selects the optimal set of operations based on the contribution efficiency to ensure that the total reduction meets the conflict gap requirements. Finally, combining the conflict start time and system delay parameters, it generates and issues operation commands to realize intelligent control of the load branches.

The invention discloses a card surface image processing method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring a static card surface image of a target card; the static card surface image is disassembled into a first image layer and a second image layer, the first image layer comprises a first information element allowing dynamic processing, and the second image layer comprises a second information element not allowing dynamic processing; performing dynamic processing on the first information element to obtain at least one candidate video; and superposing the second information element and the candidate video to obtain a dynamic card surface image of the target card. According to the embodiment of the invention, before the image video is converted, the card surface image is automatically disassembled into the first image layer and the second image layer, only the first image layer is dynamically processed, and the first image layer and the second image layer are automatically superposed and synthesized after the dynamic processing is completed, so that the definition and the compliance of the second information element in the finally generated dynamic card surface image are ensured, and the image quality is improved. Therefore, the supervision risk caused by the randomness of the map video is avoided.

The embodiment of the application provides a kind of based on dynamic knowledge graph and multi-source data fusion's marine pasture intelligent site selection decision system and method, it is related to the technical field of marine information technology and intelligent decision-making technology.Its method includes: obtaining the multi-source heterogeneous data covering candidate sea area, and generating dynamic metadata label for data unit in the multi-source heterogeneous data;Based on the multi-source heterogeneous data and external knowledge source, the knowledge graph of the field of marine pasture site selection is constructed;Based on the knowledge graph, a dynamic association rule base is constructed;According to the site selection constraint condition input by the user, the knowledge graph and the dynamic association rule base, the recommended site selection area of the candidate sea area is generated.Through the application, the problem of low site selection decision accuracy is solved, and the effect of improving site selection decision accuracy is achieved.

This invention discloses a micro-space TCM-adaptive planning and AI self-learning control method based on holistic health care in the home environment, involving the fields of family health care and intelligent environmental control technology. The method includes the following steps: S1, Initialization and Record Building: The user inputs and stores the physical condition test reports of all family members and the distribution map of the family's micro-spaces into the system. This micro-space TCM-adaptive planning and AI self-learning control method based on holistic health care in the home environment deeply integrates TCM constitution theory with family micro-space planning. Through TCM constitution record building, it clarifies the basic constitution, chronic diseases, and allergens of family members, and marks and divides each micro-space in the home according to its location, function, lighting, and ventilation. This achieves TCM-adaptive planning of the micro-spaces. Simultaneously, it matches specific environmental parameters for each space according to different constitutions, upgrading family environmental control from physical parameter adjustment to personalized adaptation to meet the needs of human health care.

The invention discloses a cruising electric vehicle dynamic obstacle avoidance method and system based on image recognition, and relates to the technical field of vehicle obstacle avoidance, the method comprises the following steps: acquiring cruising characteristic information of a target cruising vehicle, and establishing a standard cruising control area; carrying out multi-angle environment image acquisition, and carrying out object identification on the acquired multi-angle environment image; in combination with the real-time coordinate set and the corresponding real-time cruise action time sequence information, carrying out follow-up correction on the standard cruise control area to obtain a real-time cruise control body, and carrying out collision risk judgment; and controlling the target cruising vehicle to perform dynamic obstacle avoidance according to the collision risk judgment result. The technical problems that an existing electric vehicle is single in obstacle avoidance strategy, response lags behind or excessive obstacle avoidance affects normal cruising efficiency are solved.

This invention discloses a multi-scenario smart elderly care service matching and media push system and method, belonging to the field of elderly care service management technology. It includes: a file management unit, a demand analysis unit, a service generation unit, a service control unit, and an industry-end empowerment unit. The file management unit is used to construct and dynamically update the user's full-dimensional data file; the demand analysis unit is used to complete the multi-dimensional tagging modeling and scenario-based precise service demand of users; the service generation unit is used to generate customized elderly-friendly service solutions corresponding to the target scenario; the service control unit is used to track and control the implementation of the customized elderly-friendly service solutions throughout the entire process, realizing the dynamic iterative update of the full-dimensional data file; and the industry-end empowerment unit is used to provide digital, multi-media push operation services.

This invention relates to the field of power system monitoring and discloses an online monitoring system and method for resistive current of surge arresters, comprising the following steps: acquiring the full current signal and system voltage signal of the surge arrester during operation using a sensor array; preprocessing the full current signal and voltage signal to separate the resistive current component; constructing a characteristic parameter model based on the resistive current component to calculate the amplitude, harmonic content, and phase characteristics of the resistive current; and comparing the characteristic parameters with preset thresholds to generate status warning information. By using frequency domain analysis and sliding window time series processing, a multi-dimensional characteristic parameter model including fundamental amplitude, harmonic content, and phase difference is constructed. Compared with traditional single-amplitude monitoring, this model not only extracts the fundamental component but also analyzes key harmonic components such as the third harmonic and dynamic phase changes, enabling the capture of subtle nonlinear characteristic changes during surge arrester insulation degradation and improving the comprehensiveness of status assessment.

This application provides a data scanning method, electronic device, storage medium, and program product, relating to the field of data storage technology. The method includes: obtaining the number of objects included in the data to be scanned in an object storage unit; the data to be scanned includes at least one storage sub-unit, and the storage sub-unit includes at least one object; determining the number of scanning tasks and the at least one storage sub-unit corresponding to each scanning task based on the number of objects; and allocating multiple scanning tasks to multiple worker nodes in a distributed system for execution based on the number of tasks and the at least one storage sub-unit corresponding to each scanning task. In this application's embodiments, dynamic and scalable task generation is achieved; allocating multiple scanning tasks to multiple worker nodes for execution utilizes the computing power of distributed computing, improving data scanning efficiency and avoiding the problem of excessive CPU utilization in single-machine scenarios, thus improving the running performance of data scanning tasks.

The invention belongs to the technical field of higher education management, and discloses a semi-supervised learning-based college student consumption data mining and distinguishing method, which comprises the steps of obtaining college multi-source original consumption data, converting the data into a desensitization behavior unit according to a preset mapping interval, counting a single score of each dimension, and generating a monthly consumption toughness index; creating a consumption toughness time sequence atlas, mounting external event tags, and integrating to form a whole school consumption toughness time sequence atlas database; optimizing a toughness rule weight through semi-supervised learning and mining a recessive consumption mode combination to obtain an optimized five-dimensional consumption toughness weight matrix and an enhanced feature set, and further generating a pseudo tag set; performing economic difficulty state judgment on the to-be-judged students through a three-step fusion judgment rule chain, generating a judgment analysis report, and performing division to obtain an economic difficulty student candidate list, a non-economic difficulty list and an observation list; and performing three-dimensional synchronous feedback optimization in combination with an artificial rechecking result to form a discriminant management link of closed-loop evolution.

This invention belongs to the field of hydrological modeling and flood forecasting technology, and discloses a flood runoff simulation method based on time-varying outflow coefficients. The method includes the following steps: determining the existence of interflows, modeling hydrological connectivity mechanisms, constructing a time-varying outflow coefficient model, and parameter calibration and verification. The method described in this invention accurately describes the behavior of interflows, can precisely simulate the inflection point of flood recession, significantly improves the accuracy of flood forecasting in semi-arid and semi-humid regions, and provides reliable technical support for flood prevention and disaster reduction.

The invention discloses a customer asset intelligent management system based on a hierarchical dynamic driving model, which relates to the technical field of business data processing and comprises a unified data middle table, a hierarchical dynamic driving engine, a strategy driving unit, a feedback optimization unit, a loss early warning and intervention unit and a quantitative stripping decision unit. According to the invention, dynamic and automatic customer asset management is realized, and the system can automatically execute a precise strategy for intervention, upgrading or stripping, so that the overall value and operation efficiency of customer assets are remarkably improved, and the management efficiency of the customer assets is improved.

This invention discloses a flux application method for SMT soldering based on regional solder joint density, belonging to the field of surface mount technology. The method includes: S10: acquiring relevant information on the PCB board, including the arrangement of solder joints on the pads, and distinguishing them based on the arrangement, including distinguishing high-density solder joint areas and low-density solder joint areas on the PCB board; S20: collecting relevant data based on the distinction results, including the size of the hole positions corresponding to each solder joint in the high-density and low-density solder joint areas, and the spacing between adjacent hole positions. This invention, by distinguishing between high-density and low-density solder joint areas, dynamically simulates and adjusts the flux dosage for different hole positions, effectively avoiding bridging, cold solder joints, and contamination problems caused by improper flux dosage during the soldering process. It also improves production efficiency and product quality, achieving precise and efficient flux application.

The invention relates to a wharf crossing external container truck flow prediction method and system based on a hybrid deep learning architecture, and the method comprises the steps: collecting data of a wharf crossing external container truck, carrying out the preprocessing, data matching calculation and feature engineering processing, and constructing a wharf crossing external container truck flow prediction data set; the wharf crossing outer container truck flow prediction data set comprises wharf crossing outer container truck flow time sequence characteristics, wharf crossing outer container truck flow space characteristics and wharf crossing outer container truck reservation quantity characteristics; and inputting the wharf crossing external container truck flow prediction data set into a pre-trained prediction model, and outputting a wharf crossing external container truck flow prediction value of each hour in a plurality of hours in the future. Compared with the prior art, the global feature and the short-time feature of the container truck flow time sequence outside the wharf crossing are fully considered, and the spatial feature and the container truck reservation quantity feature are introduced to realize the spatio-temporal information fusion of the container truck flow outside the wharf crossing, so that the dynamic real-time accurate prediction of the container truck flow outside the wharf crossing is realized.

This invention specifically discloses a method, system, device, and medium for behavioral intervention of children's visual and spinal health, relating to the field of children's health management service technology. The method comprises the following steps: S1. Based on a classification framework of posture, light, and distance, acquire children's sitting posture, environment, and spatial data in reading and writing scenarios; S2. Upload the collected data to a cloud server and compare it with preset standard data to calculate a multi-dimensional risk score and determine the overall risk level; S3. Generate a children's visual and spinal health behavioral optical diagnostic report including a measured data table, risk dimension charts, and risk interpretations; S4. Retrieve detailed plans from a pre-set intervention plan knowledge base according to the rectification plan code and output them synchronously; S5. Within a preset period after the intervention, generate a before-and-after comparison report and provide continuous optimization suggestions. This invention achieves seamless integration of assessment and intervention, effectively improving the accuracy, operability, and sustainability of children's reading and writing visual and spinal health management.