187 results about "Visualization model" patented technology

The invention belongs to the technical field of geological engineering monitoring and multi-physics field intelligent sensing, and discloses a separation grouting slurry migration monitoring method and system, and the method comprises the steps: constructing an acoustics-optics-electricity-electromagnetism multi-physics field coupling monitoring system; a grouting hole and a monitoring drilling hole array are arranged in a target stratum, a distributed optical fiber sensor, a drilling hole ultrasonic imager, a resistivity measuring device and a transient electromagnetic detection device are installed, and a three-dimensional monitoring network is formed; synchronously acquiring sound field, light field, electric field and magnetic field data; four-field monitoring data and overlying strata multi-parameter observation data are fused, a coal seam mining three-dimensional overlying strata separation model is constructed, and a slurry diffusion three-dimensional visualization model is generated through numerical simulation; and based on the four-field monitoring response difference of the separation space before and after grouting, in combination with a monitoring frequency domain correction model of multiple indexes of grout diffusion, the diffusion range, compactness and filling effect of the grouting grout are evaluated, and abnormal early warning is triggered.

The invention relates to the technical field of three-dimensional models, and discloses a GIS data-based low-altitude visual three-dimensional model automatic generation method, which comprises the following steps of: acquiring multi-source GIS vector data from an open geographic data source, performing standardized preprocessing through a data cleaning rule set, constructing a Cesium earth scene basic framework in a UE5 engine environment, and dynamically generating a city L2-level three-dimensional visualization model based on a preprocessed GIS data stream; when a low-altitude visual three-dimensional model is generated, a lightweight data format is adopted, data transmission efficiency and dynamic updating capability are improved, complex light environment changes can be adapted in real time, the problem of color distortion on the surface of the model is reduced, meanwhile, a visual angle deviation detection and correction mechanism is established, the geometric body edge distortion phenomenon is relieved, and the generation efficiency of the low-altitude visual three-dimensional model is improved. And the color rendition precision and the spatial positioning reliability of the low-altitude scene are improved.

The invention relates to the field of medical image processing and pathological diagnosis, aims to solve the problems that brain glioma multi-modal image fusion precision is low, heterogeneity feature and pathological association is weak, and visualization readability is poor, and provides a visualization method and device. The method comprises the steps of multi-modal image preprocessing and registration, regional adaptive multi-modal fusion, pathology association type heterogeneity feature quantification, multi-dimensional pathology visualization, and result verification and optimization. Images are rigidly registered and aligned through mutual information, features are enhanced by adopting a regional differentiation attention fusion algorithm, features are quantified through an improved LSSVM, pathological gold standards are associated, and a three-dimensional visualization model is constructed to visually present heterogeneity information. The device comprises a memory and a processor and can execute the method. According to the method, the heterogeneity evaluation accuracy and clinical readability are improved, treatment scheme optimization is assisted, and the method is suitable for accurate diagnosis and treatment scenes of brain glioma.

The embodiment of the invention discloses a building model rendering method and related equipment. The method comprises the following steps: when a rendering request is received, determining a rendering type of a building model in at least one to-be-rendered frame and a target component needing to be loaded based on the rendering request; screening out visual model data corresponding to the target component in a preset visual database, and identifying component attribute information of the target component in a preset graph database to generate a target rendering parameter; and loading the to-be-rendered frame, and rendering the building model in the to-be-rendered frame based on the rendering type and the target rendering parameter. Through the mode, the visual model data used for entity basic rendering is obtained from the preset visual database, the component attribute information used for entity attribute rendering is obtained from the preset graph database, so that the target rendering parameters are generated, and rendering is completed according to the target rendering parameters. Therefore, the integrity of the data required for rendering is ensured, and the rendering efficiency and the rendering quality are improved.

The invention discloses a visualization method and system for an oversized in-situ filling space under a composite roof, and belongs to the technical field of information processing. The method comprises the following steps: performing multi-angle data acquisition on a filling space under a composite roof structure to obtain original point cloud data; obtaining complete three-dimensional point cloud data based on the original point cloud data; preprocessing the three-dimensional point cloud data to obtain standard point cloud data; performing boundary contour recognition based on the standard point cloud data to obtain space boundary contour data; obtaining a spatial three-dimensional geometric model based on the spatial boundary contour data; performing section slicing based on the space coordinate range of the space three-dimensional geometric model, and obtaining size distribution data based on the obtained contour size parameters of the section; obtaining a total volume and a segmented volume of the filling space based on the size distribution data; and obtaining a three-dimensional visual model of the filling space based on the total volume and the segmented volume. The method provides reliable technical support for mine filling design and resource evaluation.

The invention provides a geological envelope body automatic generation method. The method comprises the following steps: defining a target work area; performing sparse horizon picking of a top interface and a bottom interface on the geological envelope in the defined target work area to determine a top interface horizon, a bottom interface horizon and corresponding top interface and bottom interface data; based on the grid positions corresponding to all the pickup point positions of the top interface horizon and the bottom interface horizon, according to the range of the top interface data and the range of the bottom interface data, boundary lines of the geological envelope body at the top interface and the bottom interface in the target work area are determined; determining horizon depth values in all grid points of the top interface and the bottom interface; constructing a top interface boundary constraint and a bottom interface boundary constraint according to the horizon depth value and based on boundary lines of the geological envelope body at the top interface and the bottom interface to determine an intersection point between the top interface and the bottom interface of the envelope body so as to optimize the boundary lines of the geological envelope body at the top interface and the bottom interface; and generating a three-dimensional visualization model of the geological envelope based on the optimized boundary line.

The invention discloses a system for realizing bidirectional conversion between a model and a code, and the system comprises a meta-model architecture module which is used for constructing a unified model specification; the meta-model engine module is used for generating, analyzing and processing the meta-model architecture module; and the bidirectional conversion module is used for realizing forward and reverse synchronous conversion between a zero code model and a Java model serving as a program code by adopting the meta-model engine module. By means of the scheme, a unified specification with the meta-model architecture as the core is established, a powerful meta-model engine is used for automatic processing, and the barrier between a zero-code visualization model used by business personnel and bottom-layer Java codes written by developers is seamlessly broken through. The synchronization capability of the model and codes ensures the continuous alignment of business design and technical implementation, and effectively supports the quick iteration of agile development and business.

The invention discloses a construction period carbon emission visual regulation and control method and system. The method comprises the following steps: obtaining a visualization level and a visualization model containing BIM data; responding to an input operation on the visual level and the visual model, and determining a to-be-processed component; when the input operation is a component updating operation, updating component data of the to-be-processed component in the visual model; and when the input operation is a component display operation, displaying the to-be-processed component according to the later rendering color corresponding to the to-be-processed component. The invention provides a construction period carbon emission visual regulation and control method and system, and aims to solve the technical problem that dynamic visual display and active regulation and control cannot be performed on construction period carbon emission in the prior art.

The invention relates to a construction quality management method based on BIM secondary development. In order to improve the informatization level of an outer protection frame erection size detection process, automatic comparison between a detection result and a design size is realized. Revit software is used for parametric modeling of the fastener type steel pipe scaffold component family model, and a standard component family library is constructed. Modeling is driven based on Dynamo data, and the fastener type steel pipe scaffold BIM model automatic generation and updating method is provided. And a construction quality management platform based on BIM secondary development is developed, automatic comparison of a design scheme and a detection result is realized, and construction errors are graded and fed back to the BIM visual model. In order to improve user experience, a user interface of the platform in Revit is customized and developed. Compared with the prior art, the system has excellent performance in the aspects of working efficiency and visual display, and can effectively promote the intelligentization and informatization process of construction quality detection and management.

The invention discloses a prediction method and a prediction system for fracture risk of an osteoporosis patient. The method comprises the following steps: firstly, collecting a plurality of parameters such as age, bone mineral density, vitamin D level and the like of the patient; constructing a bone time-varying factor and dynamic prediction model, and determining the influence weight of each parameter on the bone condition at different time nodes; then, a three-dimensional mechanical model is constructed through mechanical simulation of the skeleton microstructure, stress distribution, strain states and structural stability of the skeleton under different loads are simulated, and the model is corrected by fusing parameters to influence weights; then the fracture probability in a future preset time period is calculated; and finally, a result is presented through a nomogram visualization model. The system realizes the above method, can predict the fracture risk more accurately, and provides powerful support for clinical diagnosis and treatment.

The invention discloses a three-dimensional ground penetrating radar detection method, system and equipment for road roadbed diseases and a medium, and relates to the technical field of road engineering detection. Controlling a high-frequency antenna and a low-frequency antenna to emit electromagnetic waves to a road roadbed based on the movement of the detection vehicle so as to receive reflected high-frequency data and low-frequency data; processing the high-frequency data and the low-frequency data based on the positioning attitude data to obtain processed high-frequency data and processed low-frequency data; processing and fusing the processed high-frequency data and the processed low-frequency data to obtain a full-band reflection coefficient sequence; calculating the full-band reflection coefficient sequence to obtain broadband geological radar data; inputting broadband geological radar data into the convolutional neural network model to obtain a disease type and a disease semantic segmentation map; and generating a three-dimensional visual model of the roadbed disease based on the disease semantic segmentation map, and outputting maintenance suggestion data matched with the disease type. By implementing the technical scheme, the accuracy of deep hidden disease recognition is improved.

The application discloses an airplane hydraulic servo actuating system simulation method based on digital twinning, and the method comprises the following steps: (1) constructing a digital twinning hydraulic simulation model and a digital twinning three-dimensional visual model of an airplane hydraulic servo actuating system physical system; (2) storing simulation model output data of a monitoring point of the digital twinning hydraulic simulation model and sensor acquisition data of the airplane hydraulic servo actuating physical system in real time and synchronously to form twinning data; (3) comparing and analyzing the simulation model output data and the sensor acquisition data, iteratively optimizing the digital twinning hydraulic simulation model through a model optimization module, and simultaneously performing three-dimensional visual demonstration on the working condition of the airplane hydraulic servo actuating virtual model. The application can provide a simulation modeling and optimization method for airplane hydraulic servo actuating system design, and provide a reference for research and verification of virtual-real mapping technology of the airplane hydraulic servo actuating system based on digital twinning.

The invention discloses a classroom psychological state recognition system based on multi-modal data, particularly relates to the field of image recognition, and is used for solving the problem that an existing classroom monitoring mode cannot effectively capture group emotions and lacks targeted intervention. The method comprises the following steps: detecting and positioning a multi-view video sequence through a target tracking module, extracting a student face image and establishing an identity frame sequence relationship; the emotion recognition module performs expression recognition on the image to generate an emotion intensity time sequence; the emotion analysis module performs time-frequency analysis on the sequence, extracts rhythm frequency and phase parameters and generates a region-level emotion curve according to seat layout aggregation; the drift calculation module calculates the phase difference and the frequency difference between the regions, and constructs a rhythm drift matrix; the propagation visualization module maps the matrix into a space vector field, and generates an emotion propagation path visualization model; and the intervention prompt module completes source positioning and intervention strategy generation based on the model, and realizes classroom psychological state identification and regulation.

The invention discloses a footprint image human body attribute automatic inference method based on a multi-modal large model, and relates to the technical field of mode recognition. The inference method comprises the following steps: constructing a CLIP-based footprint image and text analysis multi-modal large model: the model adopts a double-flow network structure, a graphic encoder processes image features, a text encoder processes text features, and cross-modal feature fusion is realized through a feature fusion layer; and constructing a Grad-CAM interpretable visualization model, wherein Grad-CAM is a gradient-based feature visualization technology in deep learning. The gradient of the feature map is output through the calculation model, an attention map is generated, and key areas concerned by the convolutional neural network model during decision making are displayed; the correlation between the footprint image and the human body attribute is deeply discussed, a new multi-modal feature fusion method and model architecture are provided, and the algorithm, the model and the application method thereof formed in the research process also promote the industrial application of the technology.

The invention provides an antenna field pattern visual measurement method, device, equipment and medium, and relates to the technical field of electromagnetic field measurement, and the method comprises the steps: constructing a visual model of an antenna according to the geographic coordinate, the measurement radius and the antenna height of the antenna; determining a sampling track on the visual model according to the measurement parameters of the antenna; mapping the sampling track into a geographic track according to a preset track mapping rule; according to the geographical trajectory, generating a route file which can be identified by the unmanned aerial vehicle, so as to control the unmanned aerial vehicle to collect electromagnetic field intensity data along the geographical trajectory; and carrying out combination and image drawing on the electromagnetic field intensity data and the measurement parameters to generate an antenna field pattern image. According to the technical scheme of the embodiment of the invention, the problems of poor visualization effect and low planning operation efficiency can be solved.

The application relates to the field of data processing, in particular to a fish disease monitoring method and system based on feature image recognition. The method comprises the following steps: monitoring the water quality change in a target area in real time through a water quality sensor; collecting fish image information in the target area; performing behavior recognition on the fish image information to obtain fish behavior information of each fish object in the target area; performing lesion recognition on the fish behavior information, the fish image information and the water quality change through a fish lesion recognition model to obtain potential lesion information of each fish object; and generating lesion risk information of each fish object according to the potential lesion information and displaying the lesion risk information in a visual model corresponding to the target water area. The method can realize individualized potential fish lesion recognition for different types of fish, improve the accuracy of fish lesion monitoring, simplify the fish lesion monitoring process and further improve the monitoring efficiency of fish lesions.

This invention discloses a sweat microfluidic patch, its visualization model, and its preparation method. The visualization model uses characteristic data related to physiological indices in sweat as input variables to establish a correlation model with the microfluidic patch's scale. This model has advantages such as simple structure, strong compatibility, and easy acquisition of relevant data. The sweat microfluidic patch consists of an adhesion layer, a microfluidic main layer, a scale layer, and an encapsulation layer. Its simple structure requires no external power supply and meets the requirements for rapid detection and accurate reading. The preparation method involves pre-coating pigments and detection reagents onto the microfluidic main layer, and then encapsulating it after the solution has completely dried. This preparation method is simple, has low production costs, requires no additional investment, and is suitable for continuous industrial production.

The invention provides a surgical navigation system and method based on electromagnetic positioning and augmented reality, and the system comprises an image data three-dimensional reconstruction module which is used for importing preoperative medical image data into the system, and generating a visual model through a three-dimensional reconstruction algorithm; the pre-operation registration module is used for realizing space mapping of an image coordinate system and an operation coordinate system through a registration method based on mark points; the electromagnetic positioning and coordinate mapping module is used for tracking the pose of the surgical instrument in real time and mapping the coordinates of the instrument to the surgical coordinate system; the augmented reality and high-precision navigation module is used for fusing and displaying the registered virtual navigation image and a real operation scene; the electromagnetic positioning and coordinate mapping module and the augmented reality and high-precision navigation module form a surgical navigation platform integrating electromagnetic tracking and augmented reality display; by fusing the high-precision anti-shielding capability of electromagnetic positioning and the visual visualization effect of augmented reality, stable, accurate and visual intraoperative navigation can be realized.

The application discloses a kind of continuous monitoring methods of coal mine mining overburden rock three-dimensional interstice, belong to coal mining technical field.Through coal mine overburden rock multi-position separation layer monitoring device measurement coal seam mining after the three-dimensional interstice of overburden rock: based on coal seam mining thickness and water conducting fractured zone development height, formulate mining overburden rock interstice monitoring scheme;Perpendicular monitoring borehole is arranged on the surface above the stoping working face, and coal mine overburden rock multi-position separation layer monitoring device is installed in the borehole;Real-time acquisition, storage and analysis monitoring data are acquired by data acquisition box and computer;Based on the advancing distance of coal mining face, the evolution law of single-hole interstice of mining overburden rock is analyzed;Kriging interpolation method is used to predict the unknown point interstice of working face according to the multi-hole monitoring data, and the spatial curved surface visualization model of mining overburden rock interstice is generated.The application can realize the continuous monitoring of the distribution characteristics of overburden rock three-dimensional interstice in the process of coal seam mining, and provide a scientific basis for determining the key parameters of grouting and filling.

The invention belongs to the technical field of road surface detection, and relates to a multi-dimensional radar map construction method based on electromagnetic signals, which comprises the following steps: S1, scanning a target area through high-frequency three-dimensional ground penetrating radar equipment, acquiring electromagnetic reflection signals, and preprocessing the acquired signals; s2, converting the time domain data of the preprocessed electromagnetic reflection signal into spatial domain data, and generating a three-dimensional data model; s3, blank data in the three-dimensional data model are complemented through an interpolation method, and high-resolution three-dimensional grid data are generated; s4, extracting a disease area based on a reflection intensity threshold value and performing type identification; and S5, constructing a three-dimensional disease visualization model, and mapping disease characteristic parameters by adopting color coding. According to the method provided by the invention, the depth resolution and the spatial positioning precision of disease detection are improved, and the real distribution and form of the diseases in the pavement can be reflected more comprehensively.

The application discloses a kind of highway survey radar measurement systems based on electromagnetic wave, through quantum magnetic force gradient tensor analysis and space coordinate calibration, synthetic aperture radar echo feature extraction module cooperation, using quantum magnetic force navigation model and synthetic aperture radar algorithm, realize multi-source data space-time registration and weighted fusion, construct highway geology layered model and inversion geological parameter, after grid processing of fusion data, generate three-dimensional visual model.The system overcomes the defects of traditional technology multi-source data fusion deficiency and low precision of geological parameter inversion, improves the precision, efficiency and reliability of highway survey, provides accurate geological information and visual survey results for highway engineering design and construction, has important application value in the field of highway survey.

The application discloses a data simulation method based on data visualization, and relates to the technical field of data analysis, comprising: constructing a distributed stream processing framework, performing parallel preprocessing on a target data set to be simulated to generate a time sequence characteristic stream; converting the time sequence characteristic stream into a multi-dimensional visualization model through an adaptive mapping layer, and realizing dynamic rendering in a visualization interface; triggering a simulation engine to execute real-time simulation based on the multi-dimensional visualization model, and jointly optimizing the visualization parameters and the simulation parameters through a feedback optimization mechanism. Through the introduction of a dynamic calculation method of the job level correlation coefficient and the space-time overlap degree, the design of the time-varying adjustment factor and the hierarchical attention mechanism, and the construction of a novel data processing and visualization framework, the application realizes the accurate identification of the talent development path across different levels, the timeliness optimization of data preprocessing, and the effective sharing of the best practices among departments.

The invention belongs to the technical field of software development, and relates to a persistent modeling method based on model driving. Description files and component codes are automatically generated and are synchronously linked when configuration is changed, traditional manual configuration, XML solidification and manual synchronous operation are replaced, the labor cost is reduced, and inconsistency of parameters and the files is avoided; for the problem of verification missing, a double-layer verification mechanism of static verification and dynamic verification is set, it is ensured that the persistent component achieves necessary interfaces such as state recovery and port access, and the problem that the component is marked as persistent but has no recovery logic is avoided; for the problem of flow breakage, a synchronous linkage mechanism is automatically generated and changed to break the independent relation between XML and component codes, automatic synchronization of the XML and the component codes is achieved, code adaptation configuration does not need to be manually adjusted, the development amount is reduced, and mismatching caused by improper adaptation is avoided.

This invention relates to the field of container loading optimization technology, and particularly to a container loading optimization method and system considering palletizing. The method includes setting container information, palletizing constraints, and cargo information; generating available pallet sizes and corresponding stack shapes; eliminating stack shapes with bottom coverage below a threshold; using the selected stack shapes to form transverse pallets that meet preset requirements; establishing a mathematical model and solving it using integer programming to obtain an initial loading scheme; performing mixed pallet loading on the remaining container space and remaining cargo, ensuring that the mixed pallet loading meets the requirements of full pallet coverage and full support; generating the mixed pallet loading result and a three-dimensional visualization model. This invention incorporates the entire palletizing-related calculation process into the optimization algorithm to solve the technical problems of cumbersome, inefficient, inaccurate, poor space utilization, and high labor costs in existing container loading calculation processes.

The application discloses a tokamak discharge modeling system based on a bidirectional long short-term memory neural network, which is composed of multiple modules, and the modules are low-coupling functional units.The modules at least include a data transfer module, a Batch data access input module, a training self-defined parameter module, a bidirectional long short-term memory neural network modeling module and a data visualization module.The whole system architecture is mainly divided into two paths, namely data training and data modeling.Using the visualization technology, the tokamak discharge experiment personnel can refer to the discharge modeling results and visualize the model training process.The application can one-key type in the experiment proposal stage to model the whole process of the tokamak discharge curve in advance, so that the experiment personnel and the proposal design personnel can check the validity and rationality of the proposal.The application can also be used for assisting data discovery after the experiment.

The application discloses a brain glioma segmentation and three-dimensional visualization model training method and system based on multi-modal fusion, and comprises the following steps: inputting multi-modal medical image data into a Laplacian pyramid multi-modal fusion learning model to generate a fusion graph, then inputting the fusion graph into a U-net segmentation model comprising an encoder and a decoder to obtain a segmentation mask under the multi-modal fusion graph; and finally, based on the multi-modal fusion graph and the segmentation mask, adopting a Marching cubes (MC) algorithm to perform three-dimensional reconstruction visualization of brain regions and brain tumor region labeling. The brain glioma segmentation and three-dimensional visualization model training method and system based on multi-modal fusion provided by the application optimizes the disadvantages of insufficient information and incomplete modeling under single modal, fully utilizes the advantages of the completeness of multi-modal data, performs multi-modal fusion, segmentation and three-dimensional visualization, can more comprehensively assist surgeons in treatment, and improves the accuracy in the operation process.

The invention relates to the technical field of medical education and biological information visualization, in particular to a disease mechanism-associated protein structure and function visualization teaching virtual simulation system, which comprises a data storage module, a structure calling visualization module, a function-disease association module, an interactive operation module and a teaching evaluation module, all the modules interact through data interfaces. According to the protein structure and function visual teaching virtual simulation system associated with the disease mechanism, deep association of a protein three-dimensional structure, a function mechanism and a disease case is realized for the first time, the knowledge splitting barrier of traditional teaching is broken, and students are helped to construct a complete cognitive chain; autonomous operation and mutation simulation are supported, an abstract structure function relation is converted into an interactive visual model, the learning difficulty is remarkably reduced, and the knowledge absorption rate is increased; an experiment task and evaluation system is built in, a teaching closed loop of preview-operation-assessment-feedback is achieved, and the requirement for large-scale medical talent training is met.

The invention provides a control method of intelligent equipment, a storage medium, a program product and electronic equipment. The method comprises the following steps: establishing a three-dimensional visual model of a target house; a target interaction gesture is obtained, the target interaction gesture is a graph drawn by a user in the three-dimensional visualization model according to a control requirement, and the control requirement is the requirement that the user needs to control intelligent equipment in a target house in batches; according to the target interaction gesture, multiple target devices are controlled in batches, and the target devices are intelligent devices related to the target interaction gesture. The problem that the intelligent degree is low and the efficiency is low due to the fact that the linkage rule of the smart home system in the prior art needs to be preset individually or manually by a user is solved.

The embodiment of the application discloses a kind of building model rendering method and related equipment;The application can when receiving rendering request, the rendering type of building model in at least one frame to be rendered frame is determined based on rendering request and target component need to be loaded;In the visual model data corresponding to target component in pre-set visual database is filtered out, the component attribute information of target component is identified in pre-set graph database, to generate target rendering parameter;Load frame to be rendered, and based on rendering type and target rendering parameter, rendering is carried out to building model in frame to be rendered. Through the above-mentioned mode, the visual model data for entity basic rendering is obtained from the pre-set visual database, the component attribute information for entity attribute rendering is obtained from the pre-set graph database, to generate target rendering parameter, and rendering is completed according to the target rendering parameter. Therefore, the integrity of the data required for rendering is guaranteed, and the rendering efficiency and rendering quality are improved.

The application discloses a kind of mouse brain ischemic lesion automatic quantification method and system based on deep learning, belong to medical image processing and artificial intelligence technical field.The method includes: standardization pretreatment is carried out to T1WI, T2WI, DTI and ASL and other multi-modal MRI data, and enhanced feature tensor is constructed;Lesion intelligent preliminary segmentation is carried out using BA-U-Net network guided by physical prior, and biophysical consistency loss is introduced;Boundary refining is carried out to segmentation result using graph convolution network;Based on LDDMM registration and neural ordinary differential equation model, dynamic evolution modeling is carried out to multi-time point lesion, and severity score is calculated;Finally, comprehensive pathophysiological feature vector is constructed, XGBoost model is used for prediction, and interactive report containing 3D visual model is generated by SHAP explanation.The system includes corresponding functional module.The application realizes high-precision, reproducible automatic quantification to fuzzy lesion, improves the robustness of pathological pattern recognition, and provides dynamic biomarker for drug evaluation.