15 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.

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 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 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.

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.

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.

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.