23 results about "Visual analytics" patented technology

The present invention discloses a computer-implemented system and method for automated evaluation of Environmental, Social, and Governance (ESG) disclosures and detection of greenwashing. The system integrates artificial intelligence and machine learning techniques to extract, segment, and analyze ESG content from structured and unstructured sources. A retrieval and segmentation module identifies ESG-relevant sections, which are then vectorized and stored for semantic search. A semantic retrieval module fetches contextually relevant content, which is evaluated against predefined benchmarks using an analysis and validation module. The scoring module assigns ESG scores based on rule-based criteria including key strengths, specificity, and supporting evidence. A report generation module creates structured ESG reports with visual analytics, while an orchestrator module dynamically coordinates all processing steps based on ESG framework requirements.

A system incorporates a platform for analysis of electronic files relating to an old insurance policy using computer protocols such as visual analytics tools to identify attributes of the insurance policy. A policy migration process automates typically complex custom migrations in a methodical workflow employing a simplified metrics-driven process. Layers of a data migration and policy transformation workflow include source policies layer, normalization layer, and target policies layer. The normalization layer includes an extraction, transformation, and loading (ETL) engine. The ETL engine inputs configuration files that incorporate mapping rules for mapping source policies to normalized values within a data dictionary. Systems of the disclosure incorporate built-in personas that cater migration features to a specific set of migration execution team roles such as policy edit and QA. A cloud-based policy migration model includes a UI for inputs by migration team members, and back end components including the ETL engine.

The application discloses an airspace management system and method through grid visualization analysis, relates to the technical field of airspace management, and the system firstly divides the airspace into grids according to the flight conditions of unmanned aerial vehicles in the airspace, then performs a flight preliminary examination on the unmanned aerial vehicles aiming at the flight routes applied by the unmanned aerial vehicles, performs a reexamination on the submitted proof materials when the preliminary examination is unqualified, ensures that the conflict avoidance capability of the unmanned aerial vehicles is qualified, guarantees the safety of the unmanned aerial vehicle flight, effectively guarantees the safety of the flight of all the unmanned aerial vehicles in the airspace, and monitors the flight of the unmanned aerial vehicles when the unmanned aerial vehicles are flying, analyzes the real flight conditions of the unmanned aerial vehicles, ensures the safety of the real flight of the unmanned aerial vehicles and the authenticity of the proof materials, is favorable for maintaining the aviation order, reduces the flight risk of the unmanned aerial vehicles, reduces the threat to other aircraft in the airspace when the unmanned aerial vehicles are flying, and guarantees the safety of the airspace and the standardization of the management.

Computer terminal with Arc-and-Pulse Visual Analytics Interface

A system and method for the generation of automatic audio-visual analytics for object rendering in capture. One example provides a method of processing audiovisual content. The method includes receiving content including a plurality of audio frames and a plurality of video frames, classifying each of the plurality of audio frames into a plurality of audio classifications, and classifying each of the plurality of video frames into a plurality of video classifications. The method includes processing the plurality of audio frames based on the respective audio classifications and processing the plurality of video frames based on the respective video classifications. Each audio classification is processed with a different audio processing operation, and each video classification is processed with a different video processing operation. The method includes generating an audio / video representation of the content by merging the processed plurality of audio frames and the processed plurality of video frames.

A method is disclosed that provides visual analysis of a data set. A system receives a natural language search query directed to a data store that includes a data source and a data visualization. The system parses search terms to determine whether the natural language search query contains an analysis intent. The system also uses a semantic search to determine whether the search term matches a field in one or more data sources. When (i) the search term matches a field in the one or more data sources and (ii) the natural language search query contains an analysis intent, the system generates and displays a visual response. When (i) the search term does not match a field in the data source or (ii) the natural language search query does not contain the analysis intent, the system displays pre-written content from the data visualization.

The present invention relates to a visual analytics system for helping users better understand and diagnose multimodal models for sentiment analysis. By considering feature importance measured by post-hoc explainability techniques, the system produces explanations of intra- and inter-modality interactions learned by multimodal language models from three levels (i.e., global, subset, and local levels). At the global level, the present system extracts and visually summarizes three types of interactions (i.e., dominance, complementarity, and conflict) and adopts an augmented tree layout. At the subset level, the system summarizes influential and frequent multimodal features using compact templates and enables the exploration of features of interest to users using different symbolic designs. At the local level, the system visualizes individual multimodal instances and their explanations with details.

This application discloses a method and system for assisting decision-making in charging station site selection based on visual analytics, belonging to the field of computer technology. The method includes: analyzing the existing charging station layout based on traffic and power grid data; determining the charging station site selection task and constructing an objective function based on optimization target weights, charging demand coverage constraints, service time constraints, and resource input constraints; generating initial charging demand through a dual-network fusion model based on charging station demand parameters, and determining several recommended schemes based on a genetic algorithm; determining the time-varying charging demand coverage of the recommended schemes based on overall indicators and assessing their impact on the road network and power grid, obtaining the evaluation results, and visualizing them to assist user decision-making. This application can automatically generate charging station site selection schemes and evaluate their impact on the road network and power grid, providing visual representation and thus improving decision-making reliability and efficiency.

The present application belongs to the technical field of open domain question answering model analysis, and particularly relates to a visual analysis system for explaining an open domain question answering model.The system comprises an explanation engine module, a process analysis module and a view module; the explanation engine module uses an attribution method to attribute the final output and implicit output of each module of the OpenQA model at global and local levels; the process analysis module visualizes the model information, data and explainability data generated via the explanation engine in the VEQA as various views of a user analysis interface, and the user performs multi-level exploration in the order of data set, subset, single instance and single paragraph according to a linear workflow; the view module comprises a summary view, a context view, an instance view and a tree view, and is used for visual analysis; the system can help understand the decision reasons of the OpenQA model and provide insights for model improvement; and the system also supports fine-grained exploration of the decision process within a single module.

This invention relates to the field of visual analytics technology, and discloses a method and apparatus for flow field visual analysis driven by a large language model. The method includes: acquiring a flow field dataset to be analyzed and user commands; performing semantic analysis on the user commands using a large language model to obtain structured commands; based on the structured commands, retrieving corresponding target data from the flow field dataset using the large language model, and generating descriptive text corresponding to the target data; running a visualization agent based on the target data and the descriptive text to obtain visualization results; and displaying the target data according to the data display method indicated by the user commands. By using a large language model to achieve natural language-based interaction, user operation commands or text commands are converted into structured commands, thereby presenting visualization results and explanations in real time according to user needs, greatly improving the user experience.

A method and system for processing datasets having a number of data points are described. A portion of the dataset is received and processed in parallel. A view on a display is updated to include a first section of the portion of the dataset after the first section completes processing but before a remainder of the portion of the dataset completes processing. In some aspects, the portion of the dataset can include up to one million or more data points. In some aspects, if a change from the view to a second view is received before processing has completed, an unusable part of the dataset is discarded and / or a reusable part of the dataset that has completed processing is reused for the second view. In some aspects, columns of different dataset may be correlated and / or processed data is provided such that the processed data may be rapidly rendered.

The disclosure provides an automated process for determining the wear condition of a downhole tool that removes the subjectivity associated with manual observation. The automated process can advantageously evaluate a wear condition of a downhole tool using visual analytics and real-time analysis after the downhole tool has been extracted from the wellbore. An example of a method includes: (1) securing a downhole tool in a rig assembly, (2) obtaining, using sensors, surround tool data of the downhole tool in the rig assembly, wherein the surround tool data includes a first set of surround tool data obtained before a downhole operation by the downhole tool and a second set of surround tool data obtained after the downhole operation, and (3) automatically determining a wear condition of the downhole tool in real time by comparing the second set of surround tool data to the first set of surround tool data.

The application provides a visual analysis system and method for unified analysis of multiple computer vision tasks, which comprises the following steps: receiving multiple pictures containing at least one object, annotation results of the object in each picture and model prediction results of the object level in each picture, wherein the annotation results and the model prediction results both comprise detection classification results of the object level and detection position results of the object level or segmentation classification results of the object level and segmentation position results of the object level in each picture, the detection classification results and the segmentation classification results comprise discrete values of discrete attributes, and the detection position results and the segmentation position results comprise continuous values of continuous attributes; according to the annotation results of the object in each picture and the model prediction results of the object level in each picture, unified modeling of discrete attributes and continuous attributes in the results is performed by using a joint probability distribution, so that a multivariate probability distribution is obtained; and the multivariate probability distribution is displayed in multiple levels.

The present application relates to a kind of multimodal video content effectiveness feedback visual analysis method and system.The method comprises the following steps: collecting a certain type of video and its effectiveness objective index label;Quantitative extraction of the multi-modal data features of the content of interest in the video, and then determine the effectiveness factor in combination with the actual needs of the field, and calculate the effectiveness factor value of different content;The correlation between the effectiveness factor and the effectiveness objective index is analyzed, and the effectiveness feedback result of the video to be analyzed is extracted;Combined with the data of the video to be analyzed, a reference video recommendation result is generated;The effectiveness feedback result of the video to be analyzed and its multi-modal data context are displayed in different visual forms, for the user to explore the hierarchical effectiveness feedback result.The present application provides a whole-process solution for video content effectiveness feedback visual analysis, which can better support users to understand the effectiveness feedback result and explore it in a targeted manner.

The disclosure provides an image-based visual analysis interface automatic construction evaluation method and system, relating to the technical field of data visualization analysis, obtaining a visual analysis workbook file and parsing; constructing a first intermediate representation representing the semantics of the author in the workbook based on the parsing result, generating a second intermediate representation based on the first intermediate representation; generating a candidate reference code, and iteratively repairing in combination with feedback information during the candidate reference code generation process; performing verification on the candidate reference code after iterative repair to form a basic benchmark sample, and obtaining an amplified benchmark sample through interactive maintenance and recombination of the basic benchmark sample; generating a visual analysis interface based on the basic benchmark sample and the amplified benchmark sample, comparing the visual analysis interface with a reference executable interface, and outputting an evaluation result. The disclosure solves the problems of the lack of executable, verifiable, and data semantics and interactive annotation benchmark samples in the existing visual analysis interface, and the lack of a unified evaluation method.

This disclosure provides an automatic construction and evaluation method and system for image-based visual analytics interfaces, relating to the field of data visualization and analysis technology. The method involves acquiring and parsing a visual analytics workbook file; constructing a first intermediate representation representing the author's semantics in the workbook based on the parsing results; generating a second intermediate representation based on the first intermediate representation; generating candidate reference code and iteratively repairing it by incorporating feedback information during the candidate reference code generation process; verifying the iteratively repaired candidate reference code to form a basic benchmark sample; amplifying the basic benchmark sample through interactive recombination to obtain an amplified benchmark sample; generating a visual analytics interface based on the basic benchmark sample and the amplified benchmark sample; comparing the visual analytics interface with a reference executable interface; and outputting the evaluation results. This disclosure addresses the problems of existing visual analytics interfaces lacking executable, verifiable benchmark samples with data semantics and interactive annotations, as well as the lack of a unified evaluation method.

The application discloses a kind of simulation circuit parameter optimization methods based on multi-modal perception and layered inference.The application is first by mixed visual analytic architecture to the circuit schematic diagram image is structured reconstruction, generates STD file and annotated schematic diagram;Then annotated schematic diagram, STD file, SPICE netlist and design index are jointly input into multi-agent collaborative cognitive network, and initial parameter set is generated by full-time agent collaborative inference;Subsequently, in turn, direct current operating point fast calibration, pure inference iterative optimization based on comprehensive performance oriented function, and knowledge-guided trust domain efficient bayesian optimization;Finally, based on the optimal parameter set generation signature report, and support adaptive closed-loop iteration.The application realizes from circuit schematic diagram to industrial grade signature report Full-automatic, high efficiency, interpretable simulation circuit parameter optimization, effectively overcome the defects of existing method dependence netlist, lack of interpretability and easy to produce illusion.

The present disclosure relates to scalable visual analytics pipelines for large datasets. Mechanisms are provided for implementing a visual analytics pipeline. The mechanisms generate, from a recorded input database, a time-aware graph data structure that specifies a plurality of record-based features in an ontology data structure. The time-aware graph data structure has vertices representing events or records corresponding to one or more of the features and edges representing temporal relationships between the events. The mechanisms execute a time-aware graph query on the time-aware graph data structure to generate a filtered set of vertices and corresponding features that correspond to criteria of the time-aware graph query. The mechanisms execute a pattern discovery operation on the filtered set of vertices and corresponding features to identify a subset of vertices and corresponding features that correspond to a set of relatively higher frequency event path patterns and generate a visual analytics graphical representation of the subset of vertices and corresponding features.

This invention provides an interactive editing and visual analysis system for time series data, belonging to the field of data privacy protection. The visual analysis system includes ranking views, flow views, radial views, pattern views, editing views, and component views. Combining domain knowledge, it performs linked detection and visual localization of privacy risks in time series data from three dimensions: time, amplitude, and pattern. Through interactive editing in each view module, it provides three types of direct manipulation editing tools: time perturbation, amplitude perturbation, and pattern replacement. This allows users to precisely modify identified sensitive segments and supports batch processing of multiple time series and fine-grained editing of series trends and residual components. The modules are closely linked through data and events, forming a complete closed loop of "identification-editing-verification," effectively masking individual privacy characteristics while maximizing the overall utility and statistical authenticity of the time series data.

A visual analytics workflow and system are disclosed for assessing, understanding, and improving deep neural networks. The visual analytics workflow advantageously enables interpretation and improvement of the performance of a neural network model, for example an image-based objection detection and classification model, with minimal human-in-the-loop interaction. A data representation component extracts semantic features of input image data, such as colors, brightness, background, rotation, etc. of the images or objects in the images. The input image data are passed through the neural network to obtain prediction results, such as object detection and classification results. An interactive visualization component transforms the prediction results and semantic features into interactive and human-friendly visualizations, in which graphical elements encoding the prediction results are visually arranged depending on the extracted semantic features of input image data.

The workflow generally comprises three phases: an Explainable Data Slice-Finding phase, a Slice Summarization and Annotation phase, and a Slice Error Mitigation phase. In the Explainable Data Slice-Finding phase, the workflow employs pixel attributions to create interpretable features of the dataset. In the Slice Summarization andAnnotation phase, the workflow transforms the generated features into visualizations including a ‘Data Slice Mosaic.’ Finally, in the Slice Error Mitigation phase, the workflow leverages the annotation and user-verified spuriousness to mitigate slice errors in the machine learning model.

The present disclosure relates to methods and systems for establishing an edge-inclusive real-time multimedia tele-conferencing using tele-robots. Conventional techniques employ a WebSocket connection for the robot-to-edge device (R2E) connection which may not meet expected real-time behaviour. The present disclosure provides a resource-friendly application protocol using WebRTC that enables the same tele-robotic WebRTC session to fork the live feed of the tele-robot for consumption by the edge device. According to the present disclosure, a peer-to-peer connection is established between the plurality of peers by the cloud signaling server, based on the type of the unique type identifier. Then, the live stream of the tele-robot, in the tele-conferencing session, is forked based on the peer-to-peer connection established (i) between the tele-robot and the broadcaster, or (ii) between the tele-robot and the edge device, to obtain a stream forked from the live stream, which is then used for various visual analytics.

The present application relates to a kind of visual analysis system and method for astronomical spectral type inspection, belong to the field of visualization and man-machine interaction, the system includes: data preprocessing module is used to the reference spectrum and the pre-processing of the spectrum to be checked, completes the normalization of spectrum, spectrum feature detection and spectrum characterization;Selection module is used to help user select a spectrum to be checked, and determine possible red shift and the important spectral line under the red shift;Checking module is used to help user determine the red shift and type of the spectrum to be checked, checking module includes adjustment submodule, recommendation submodule and verification submodule, respectively for adjusting the red shift of the spectrum to be checked, recommend suitable spectral line to user and evaluate the inspection result;Generalization module is used to help user obtain other spectrum similar to the checked spectrum by searching.The system and method provided by the present application can significantly improve the classification efficiency under the premise of ensuring the accuracy of expert spectrum classification.