752 results about "Visual presentation" patented technology

The invention provides a firewall attacked surface carding and security reinforcing method, which comprises the following steps of: protecting sensitive data in each link of data flow in an identified supply chain, deploying a data leakage prevention gateway on a data flow link, and adopting deep packet detection of content awareness to carry out security reinforcement on the data flow link. Visualized presentation and security auditing of data flow behaviors are realized, and abnormal data flow is blocked and alarmed; the method comprises the following steps: constructing a security policy configuration knowledge base, mapping service description into a security policy component, automatically generating a fine-grained security policy matched with service semantics by adopting a policy generation engine based on combination of rules and deep learning, and realizing cross-scene policy conflict detection and correction by virtue of reasoning of a constructed knowledge graph.

Systems, computer program products, and methods are described herein for building material data management. With reference to an example method, the method receives a first dataset formed of first data entries associated with a building material data source and generates a building material data entity based on the building material data source. The method includes outputting a representation of the building material data entity. The first dataset may be formed of data records (e.g., construction documents, user inputs, sensor data, or machines data), and the representation may be a visual representation may include notifications, visual presentations of the building material entity, etc.

A system and a method for automatically discovering and managing actions in an application is disclosed. The system includes a data ingestion layer for receiving application data from multiple sources, a scanning and systematic traversal engine for interacting with UI elements and capturing network calls, an action mapping and generation module for correlating UI actions with API calls and categorizing actions, an AI-driven icon and description generator for creating visual representations and textual descriptions of actions, a user interface for displaying and modifying discovered actions, and a continuous monitoring component for triggering re-scanning based on coverage metrics, error detection, or version updates. The system employs synthetic data generation and AI-driven exploration to uncover hidden or undocumented APIs, enabling comprehensive mapping of an application's capabilities at the API level.

To provide a game machine capable of suitably changing a visual recognition mode.SOLUTION: A Pachinko machine W10 includes an upper operating member W710, an outer operation member W720, an inner operation member W730, and a lower operation member W740, and is configured such that the upper operation member W710, the outer operation member W720, the inner operation member W730, and the lower operation member W740 are displaced mutually relatively in the displacement of the mode of switching operation. Therefore, a change in a visual recognition mode of the upper operation member W710, the outer operation member W720, the inner operation member W730, and the lower operation member W740 can be made suitable.SELECTED DRAWING: Figure 925

To provide a game machine capable of suitably changing a visual recognition mode.SOLUTION: A Pachinko machine W10 includes an upper operating member W710, an outer operation member W720, an inner operation member W730, and a lower operation member W740, and is configured such that the upper operation member W710, the outer operation member W720, the inner operation member W730, and the lower operation member W740 are displaced mutually relatively in the displacement of the mode of switching operation. Therefore, a change in a visual recognition mode of the upper operation member W710, the outer operation member W720, the inner operation member W730, and the lower operation member W740 can be made suitable.SELECTED DRAWING: Figure 925

To provide a game machine capable of suitably changing a visual recognition mode.SOLUTION: A Pachinko machine W10 includes an upper operating member W710, an outer operation member W720, an inner operation member W730, and a lower operation member W740, and is configured such that the upper operation member W710, the outer operation member W720, the inner operation member W730, and the lower operation member W740 are displaced mutually relatively in the displacement of the mode of switching operation. Therefore, a change in a visual recognition mode of the upper operation member W710, the outer operation member W720, the inner operation member W730, and the lower operation member W740 can be made suitable.SELECTED DRAWING: Figure 925

The invention provides an AI assistance-based landscape garden scheme auxiliary generation method and system, and the method comprises the steps: firstly receiving initial topographic data and a landscape adjustment instruction containing a visual presentation requirement and an ecological function requirement, which are inputted by a user in an interactive interface, and then processing the initial topographic data through a topographic segmentation model; the method comprises the following steps: extracting gradient distribution, altitude interval and land cover features, dynamically correcting the gradient distribution features into stepped topographic features according to visual requirements, matching the land cover features according to ecological requirements to obtain vegetation distribution features, performing spatial superposition on the two features, and performing path connectivity analysis in combination with tourist flow data to determine touring path features. Finally, a landscape garden scheme containing a three-dimensional visualization model and ecological evaluation parameters is generated through multi-dimensional rendering according to the sightseeing path features and sent to a user terminal to achieve interactive feedback, so that various requirements are efficiently integrated, and scientificity and intuition of landscape garden design are improved.

The invention provides a different types of database visualization table management method and system, and relates to the technical field of computers.The method comprises the steps that a database general operation system comprising a general operation interface and a dialect abstract base class is constructed, and a query performance evaluation system is established based on performance data; and predicting an optimal database connection mode through deep reinforcement learning and generating a multi-stage execution plan. Meanwhile, an anomaly feature knowledge base based on a graph neural network is constructed, and anomaly prediction and preventive processing are carried out based on the anomaly feature knowledge base. A multi-stage execution plan is executed after a database operation request is subjected to grammar adaptation, and a distributed transaction processor dynamically adjusts a transaction isolation level and a concurrency control parameter. And finally, according to the terminal and the data volume, selecting a proper data display mode to carry out visual presentation.

The invention relates to the technical field of power systems, in particular to a power grid operation risk level visualization intelligent management tool system. The system obtains power grid operation data through an Internet of Things sensor network, wherein the power grid operation data comprises current, voltage, equipment operation state and other multi-dimensional information; performing real-time analysis on the acquired data by adopting multi-level clustering analysis, a predictive maintenance algorithm and a deep learning model to realize abnormal behavior identification and risk prediction; a dynamic risk map is constructed based on a GIS technology, and accurate positioning and real-time display of risk levels are realized in combination with regional feature recognition and personalized threshold setting. According to the invention, multi-source data acquisition, intelligent analysis and visual presentation are creatively and organically integrated to form a closed-loop risk management system, so that the system has adaptive learning ability. Practical application shows that the system can early warn potential risks 30 minutes in advance, the operation and maintenance response time is shortened to 3 minutes, and the power grid operation risk monitoring and management efficiency is remarkably improved.

The invention discloses a science and technology fast message intelligence perception system based on a large language model, and belongs to the field of intelligence perception, the system comprises an information collection module, a data standardization module and a database, the information collection module obtains multi-mode science and technology fast message data; the data standardization module is used for receiving the multi-modal data output by the information collection module and executing data cleaning, structured processing and semantic standardization operation; after standardization processing, storing the data into a database; the system further comprises an intelligence value screening module, an evaluation system module and a visualization module. And the intelligence value screening module is combined with the evaluation system to identify the intelligence value, and multi-dimensional visual presentation is realized through the visualization module. The method improves the efficiency and accuracy of information recognition and perception, and has significant advantages in the aspects of processing mass information and enhancing the information perception ability.

The invention discloses a language learning assistance application system based on speech recognition, and belongs to the technical field of learning assistance. The system comprises an intelligent voice acquisition and enhancement module for realizing acquisition and preprocessing of high-quality voice signals in a complex environment; the multi-modal feature extraction module dynamically extracts and fuses multi-dimensional learning feature information, completes feature analysis and boundary segmentation of a phoneme level, and is responsible for feature normalization and optimization; the deep speech recognition module is used for realizing high-precision speech recognition based on the normalized features; the intelligent evaluation engine module is used for realizing real-time and multi-dimensional evaluation on the language performance of the learner; the personalized learning management module integrates the evaluation results for dynamically planning an optimal learning path for the learner, manages the learning progress, and provides learning effect prediction and intervention suggestions at the same time; and the learning interaction experience module is responsible for visual presentation of learning feedback, multi-modal man-machine interaction design and user interface optimization.

The invention discloses a thermal power plant immersive equipment state monitoring method and system based on AI, and relates to the technical field of equipment monitoring, and the method comprises the steps: building a digital twinborn model of a thermal power plant after a monitoring sensor is deployed on equipment of the thermal power plant; executing attraction clustering according to an equipment topological relation in the digital twin model, and establishing a multi-level clustering result; reading a monitoring data set of the monitoring sensor; activating an independent anomaly recognition network, and establishing an independent anomaly recognition result; establishing equipment criticality according to the independent anomaly recognition result; establishing equipment abnormity joint early warning; and carrying out immersive visual presentation. The technical problems that in the prior art, the operation state of the thermal power plant equipment is not comprehensively and accurately monitored, the equipment management efficiency is low, and the reliability is difficult to guarantee are solved, and the technical effects that the operation state of the thermal power plant equipment is comprehensively and accurately monitored, and the efficiency and the reliability of equipment management are effectively improved are achieved.

The invention relates to the technical field of photovoltaic system monitoring, in particular to a photovoltaic power station fault supervision system based on a neural network model, and the system comprises a data collection module which is used for collecting string current data and voltage data; the IV analysis module is used for obtaining a fault diagnosis result; the digital power station modeling module is used for identifying and numbering the coordinates of the photovoltaic string; an inspection route planning module; the unmanned aerial vehicle inspection module is used for performing inspection control on the unmanned aerial vehicle to obtain inspection data; an inspection data uploading module; the CV analysis module is used for performing defect identification on the inspection data to obtain a defect identification result; the fusion inspection analysis module is used for outputting a fusion diagnosis result and also used for selecting a final fusion diagnosis result; the visual presentation module is used for carrying out visual presentation; the report module is used for generating a report; and the navigation defect elimination module is used for carrying out navigation defect elimination. According to the invention, the automation level and inspection efficiency of fault diagnosis are improved.

The invention discloses a metal structural part surface damage identification method based on machine vision, and belongs to the field of machine vision, and the method comprises the steps: obtaining reference image data with known damage features, carrying out the preprocessing, analyzing the change trend of a system detection state, and judging whether there is a deviation correction demand or not. And if the deviation exists, carrying out geometric correction processing on the lens distortion error to obtain a corrected reference image. Further separating the real change of the damage from the system deviation, and combining low-resolution and high-resolution detection to obtain the distribution data of the suspected damage area and the specific characteristic parameter data of the damage. According to the method, quantitative data of damage levels are obtained through automatic classification, detection differences among multiple devices are calibrated, visual presentation information of damage positions and levels is generated, and finally camera parameters and algorithm thresholds for subsequent detection are optimized and adjusted, so that high-precision damage detection and evaluation are realized.

The invention relates to the technical field of artificial intelligence, and particularly provides an enterprise risk comprehensive assessment method and device, and the method comprises the following steps: S1, obtaining enterprise related risk information from a multi-source heterogeneous data source; s2, performing cleaning, standardization and feature extraction on the collected original data so as to adapt to subsequent model training and analysis requirements; s3, performing automatic risk identification and classification labeling on the preprocessed enterprise multi-dimensional data; s4, carrying out risk conduction analysis from single enterprise risks to an industrial chain, a region and even a whole economic system by constructing an enterprise association map and quantifying a risk infection mechanism; s5, performing multi-dimensional aggregation analysis and visual presentation on the enterprise risk; s6, performing dynamic monitoring and future trend prediction on enterprise risks; and S7, a user interaction module realizes understandability and verifiability of a risk assessment result. Compared with the prior art, the business efficiency can be improved, the financial risk can be reduced, and the healthy development of the financial market is promoted.

To provide a game machine capable of suitably changing a visual recognition mode.SOLUTION: A Pachinko machine W10 includes an upper operating member W710, an outer operation member W720, an inner operation member W730, and a lower operation member W740, and is configured such that the upper operation member W710, the outer operation member W720, the inner operation member W730, and the lower operation member W740 are displaced mutually relatively in the displacement of the mode of switching operation. Therefore, a change in a visual recognition mode of the upper operation member W710, the outer operation member W720, the inner operation member W730, and the lower operation member W740 can be made suitable.SELECTED DRAWING: Figure 925

The invention relates to the technical field of artificial intelligence, and discloses a professional knowledge question and answer intelligent customer service system based on a self-optimization mechanism. The system comprises a user intention analysis module, a knowledge processing module, a self-optimization learning module and an interactive presentation module. A semantic understanding unit of the user intention analysis module generates a user intention signal; after the knowledge processing module receives the signal, a knowledge retrieval unit outputs related knowledge fragments and confidence, an answer generation unit forms candidate answers, and a quality evaluation unit determines an optimal answer according to the confidence; in the self-optimization learning module, a feedback analysis unit adjusts answer generation parameters according to user interaction data, a strategy adjustment unit optimizes a retrieval strategy in combination with an optimal answer and a historical dialogue, and a knowledge updating unit updates a knowledge base depending on an external knowledge source; and a multi-round dialogue management unit of the interactive presentation module adjusts a dialogue process, and a visual presentation unit outputs a natural language text and collects user feedback to a feedback analysis unit.

The present invention relates to the field of computer vision technology, and specifically to a pathological slice image analysis method and system, comprising the following steps: based on pathological slice image information, combined with image preprocessing, edge information in the image is detected and extracted, color information is analyzed, color distribution characteristics in the image are evaluated, and image edge and color information is generated. In the present invention, by analyzing edge and color information, combined with the extraction of texture features, the identification process of tissue structure is optimized, the identification and segmentation of lesion tissue is made more accurate, the identification and segmentation of lesion tissue is performed using tissue structure feature data, the location of the lesion area and the identification of the type are achieved, and the visual presentation quality of the data and the intuitiveness of the diagnosis are improved by mapping the pathological slice image into a three-dimensional model and annotating it, helping medical professionals to fully understand the pathological conditions in the slice image and make accurate treatment decisions.

The invention discloses a multi-modal data fusion-based intelligent management system for a thoracic surgery monitoring unit, belongs to the technical field of medical information and artificial intelligence, and aims to solve the limitation of an existing thoracic surgery monitoring system in the aspects of multi-modal data fusion, heterogeneous data semantic alignment and intelligent deep analysis and prediction decision. The system is characterized by comprising a multi-modal data acquisition unit, a heterogeneous data fusion and semantic alignment module, an intelligent analysis and prediction decision module, a man-machine interaction and visual presentation module and a secure storage and management module. By the adoption of the technical scheme, comprehensive multi-modal data fusion, high real-time performance, deep intelligent analysis and prospective prediction can be achieved, intelligent decision support, resource optimization, continuous learning and self-adaptive optimization are provided, and the intelligent level and patient management efficiency of the thoracic surgery intensive care unit are remarkably improved.

The invention discloses an enterprise information visual management system and method based on data sharing, and belongs to the technical field of enterprise information management.The method comprises the steps that by connecting business systems in an enterprise, user behavior data and business data are collected and preprocessed, and an internal data set is constructed; acquiring data from an external data source, and constructing an external data set through semantic analysis, screening and classification; internal and external data are integrated, a dynamic cleaning rule is formulated, multi-source fusion is realized through data association, data are stored in a classified manner according to business requirements, and a data warehouse with a layered architecture is constructed; meanwhile, a personalized data mart is generated based on user roles and permissions, user demands are automatically predicted, and analysis indexes and dimensions are pre-generated; and finally, constructing a visual analysis platform, generating a preliminary recommendation scheme in combination with the pre-generated content and the user operation track, fusing user-defined setting, and outputting a final visual result in real time, thereby realizing efficient management and visual presentation of enterprise information.

The invention discloses an intelligent home decoration system and method based on mixed reality, and the system comprises a data collection module which comprises a space scanning module, a 3D model generation module and a space feature recognition module; the intelligent assistant module comprises an AI drive design suggestion module based on deep learning, an automatic layout optimization module, a personalized recommendation engine and a design rule check module; the multi-party cooperation module comprises a cross-device synchronization module, a real-time multi-user interaction module, a remote cooperation support module and a role authority management module; and the visual presentation module comprises a mixed reality rendering module, a real-time light and shadow simulation module, a material reality presentation module and a virtual image presentation module. According to the method, the design efficiency is greatly improved, the design period is shortened, design errors and rework are reduced, the project cost is reduced, the design quality is improved, the whole-course visualization and traceability of the design process are realized, and the working mode of traditional home decoration design is changed.

The invention belongs to the technical field of bidding and tendering information management, and particularly provides a bidding and tendering information management method and system based on an electronic bidding and tendering transaction platform, and the method mainly comprises the steps: obtaining the original data of a bidding file; performing structured extraction and version calibration on the original data of the bid invitation file to obtain a versioned key clause set; performing change relation chain construction and response feasibility verification on the versioned key clause set to obtain a dynamic association body; obtaining a bidding file; performing rule-driven equivalent matching on the dynamic association body and the bidding file to obtain a bidding response mapping table; and performing bid evaluation rule synchronization processing on the dynamic association body to obtain an adapted bid evaluation rule. The bidding and tendering information processing efficiency and accuracy are effectively improved, full-process transparent management is realized through visual presentation, human intervention risks are reduced, fairness and normalization of bidding and tendering activities are guaranteed, and the scientificity and intelligent level of bidding and tendering management is remarkably improved.

The invention provides a full-automatic air compressor system integrating intelligent monitoring and fault diagnosis, and relates to the technical field of air compressor diagnosis. The management main system comprises an AI intelligent interaction module, an AR visual presentation module, a multi-source data fusion module, an intelligent diagnosis decision module, a fault prediction and prevention module, a user feedback learning module, an equipment linkage coordination module and a system core regulation and control unit. Operating parameters and microstructure change data of the air compressor are collected, and a high-precision comprehensive data vector is generated in cooperation with an algorithm based on tensor decomposition and generative adversarial network fusion. Compared with a traditional remote monitoring mode which depends on a single traditional sensor, the system can sense micro fault characteristics of a molecular level, and in cluster operation and maintenance of the air compressors in a factory, micro cracks of the air inlet valve are detected in advance, so that the problem of insufficient air pressure caused by delayed sensing is avoided.

The invention provides a visual detection device and method for building engineering wall quality, and the method comprises the steps: firstly obtaining a multi-angle image set of a to-be-detected wall, which comprises surface images and internal structure scanning images under different illumination conditions, and then carrying out the visual feature extraction of the multi-angle image set, according to the method, a comprehensive visual detection feature set covering surface integrity, internal crack distribution and material uniformity features is obtained, defect area positioning processing is performed on the comprehensive visual detection feature set based on a preset quality evaluation rule, a defect distribution map is generated, and then a visual quality report is generated according to the defect distribution map. And finally, the visual quality report is transmitted to terminal equipment to trigger wall maintenance operation, so that comprehensive and accurate detection and visual presentation of the wall quality are realized, wall maintenance can be effectively guided, and the construction engineering wall quality guarantee level is improved.

The invention discloses an offshore wind power fault monitoring method based on a knowledge graph and digital twinning, and aims to solve the problems that multi-source data acquisition is dispersed, the transmission delay is high, and real-time convergence and integration are difficult to realize in the operation state monitoring of offshore wind power equipment. According to the invention, the following modules are provided: a multi-source data acquisition layer is used for solving the problems of dispersed data acquisition and transmission lag and ensuring the real-time performance; the knowledge graph construction module is used for solving the problems of extraction, fusion and storage of equipment entity relationships; the digital twin modeling module realizes visual presentation and accurate simulation of the state of physical equipment; the fault monitoring reasoning module solves the problems of anomaly detection and root cause positioning; the intelligent early warning decision module determines an early warning level and efficiently matches a solution; the visual interaction module solves the problems of scattered information display and poor linkage, supports third-party docking, realizes accurate early warning and root cause positioning, improves the decision-making efficiency, adapts to severe environments, supports large-scale wind power plant monitoring, and reduces the operation and maintenance cost.

The invention provides a digital twinning method of multi-source heterogeneous data feedback mapping for track structure long-term service state evaluation. The method comprises the following steps: burying fiber grating sensors, stress-strain sensors and the like in a track structure and a lining to obtain data, and performing ballastless track damage condition simulation and vehicle dynamics response analysis under the action of basic deformation by adopting finite element software and multi-body dynamics software to form a simulation calculation result library; establishing a three-dimensional virtual model of structures such as a long-section ballastless track and a lining on site, respectively carrying out result correspondence and result correction on a simulation result library and the three-dimensional model by adopting a feedback coupling mapping correction method, and carrying out coupling feedback mapping verification between different simulation calculation results and actually measured data; accurate reflection and real-time visual presentation of stress characteristics of a track structure under the influence of large deformation of a foundation are achieved, and meanwhile real-time prediction and reasonable evaluation are conducted on changes of the stress state of the track structure.

The invention provides a leasing equipment full life cycle monitoring method and system based on the Internet of Things, and belongs to the technical field of equipment operation and maintenance monitoring, and the method comprises the steps: obtaining real-time state data of leasing equipment in an operation process through a multi-source sensor; performing feature extraction on the real-time state data to obtain various feature vectors, and constructing a multi-dimensional feature vector set; inputting the multi-dimensional feature vector set into a random forest model, and judging whether the leasing equipment is in an abnormal state or not in combination with a space-time clustering algorithm; if yes, fault prediction is carried out on the leasing equipment in combination with an abnormal detection result, historical operation data and a baseline model, and a fault probability value of the leasing equipment is obtained; the future position of the leasing equipment is predicted based on the position data, an electronic fence boundary is set for the leasing equipment, if the future position exceeds the electronic fence boundary, an early warning notification of trajectory deviation is generated, and the system finally realizes trajectory and fault visual presentation in a thermodynamic diagram mode, so that the equipment operation and maintenance intelligence and management precision are improved.

Systems, methods, and media for automated creation of analytics-driven audio-visual interactive episodes. The systems can include a specifically designed architecture that enables the systems to be configurable to any structured dataset and domain (including unstructured documents) while providing controls over analysis, content, language, flow, and visual presentation (theming) of the episodes. Additionally, the architecture can provide a deterministic implementation that allows for compliance with requirements of highly regulated industries.

The invention discloses a crew workload evaluation method and system based on multi-source data fusion, and the method comprises the steps: 1, carrying out the collection of multi-source data, and enabling the multi-source data to comprise objective data and sensory monitoring data; 2, performing feature extraction on the multi-source data; 3, based on the physiological data and the sensory monitoring data, performing feature layer fusion and decision-making layer fusion; and step 4, visualizing the workload evaluation result to present the real-time workload level of the sailors, and when the workload index exceeds a preset threshold value, triggering an early warning prompt to remind the sailors and managers to pay attention to the fatigue risk. According to the method, multi-source heterogeneous data are comprehensively utilized, comprehensive and accurate evaluation and real-time visual presentation of the load state of the sailors are achieved, an effective early warning mechanism is constructed, and the method has important application value in the aspect of improving the working safety and the working efficiency of the sailors.

The present disclosure provides systems and methods for improving detection and location determination accuracy of abnormalities during a gastroenterological procedure. One example method includes obtaining a video data stream generated by an endoscopic device during a gastroenterological procedure for a patient. The method includes generating a three-dimensional model of at least a portion of an anatomical structure viewed by the endoscopic device based at least in part on the video data stream. The method includes obtaining location data associated with one or more detected abnormalities based on localization data generated from the video data stream of the endoscopic device. The method includes generating a visual presentation of the three-dimensional model and the location data associated with the one or more detected abnormalities; and providing the visual presentation of the three-dimensional model and the location data associated with the detected abnormality for use in diagnosis of the patient.