44 results about "Case files" patented technology

The invention relates to the technical field of process automation and artificial intelligence technologies, in particular to a multi-modal-based agent collaborative auditing method and system, and the method comprises the following steps: obtaining file information,..., carrying out the similarity analysis of a feature vector set and a decision vector set, obtaining a weight set corresponding to the historical file with the highest similarity from a database; setting the weight set as an initial weight set or a final weight set based on a similarity result; performing decision conflict analysis based on the decision vector set, and optimizing the initial weight set based on an analysis result to obtain a final weight set; and performing weighted fusion based on the final weight set and the decision vector set to obtain a fusion decision, and the method has the advantages of effectively solving decision conflicts in a multi-modal data fusion process, accurately positioning a problem root and improving man-machine cooperation efficiency.

The invention discloses a verification method and device for accelerating function coverage rate convergence, a medium and equipment, the method is applied to a verification platform, the verification platform comprises a directional excitation generator, a function coverage rate model and a to-be-tested design, and the verification platform is provided with a simulation switch. Comprising the following steps: analyzing a code file of a function coverage rate model by utilizing a preset cross use case script file to extract coverage bin information corresponding to a cross function coverage point, and configuring a simulation switch according to the coverage bin information to generate a boundary use case file; and reading switch configuration information in the boundary case file by using a directional excitation generator, generating a directional excitation flow based on the directional instruction sequence according to the switch configuration information, and sending the directional excitation flow to the design to be tested to execute verification work. By adopting the technical scheme of the invention, the boundary use case of the cross function coverage point can be automatically generated, so that the convergence time consumption of the function coverage rate is effectively reduced, and the convergence rate of the function coverage rate is improved.

The invention provides a method and device for generating an electronic file of a non-performing asset, equipment and a medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining different case data for a non-performing asset case uploaded by a user; extracting multi-dimensional metadata of a non-performing asset case from different case data, and identifying a plurality of associated entities of non-performing assets and an association relationship between different associated entities; constructing a knowledge graph of the unhealthy asset case on the basis of the association entities and the association relationships; determining a graph relation network associated with the associated entity from a configured historical unhealthy asset case library; performing cross check on the knowledge graph, the graph relation network and the multi-dimensional metadata; and if the knowledge graph, the graph relation network and the multi-dimensional metadata pass the cross check, generating an electronic file of the non-performing asset case based on the multi-dimensional metadata and different case data. According to the invention, full-process intelligent management of the unhealthy asset case is realized.

The invention provides a tobacco file examination method and system based on a visual-language large model, and the method integrates multi-modal feature extraction, cross-file content association, a rule introduction mechanism based on the large model, and an evidence traceability mechanism based on the large model. The method comprises the following steps of: performing unified analysis, element extraction, signature normative detection and regular compliance examination on electronic files and paper scanning images including catalogs, attachments, photos and the like for case file materials of cases which have many cases in the tobacco industry and are not purchased in a specified tobacco enterprise; and outputting the results of whether the file archive is complete, whether the signature is correct, conclusion and evidence positioning and the like. In combination with a Prompt dynamic instruction and a rule knowledge base, flexible introduction of specifications and standards during case auditing in the industry is realized, and an automatic, interpretable and traceable file auditing task is completed.

The invention provides an intelligent file evaluation method and system based on cooperation of a multi-modal large model and a rule engine, and the method comprises the steps: carrying out the multi-modal content analysis of a file file, and generating an analysis result set containing a content segment, a page number identifier, a region position identifier, layout type information and a credibility score; combining the field description text with the anchor point description text to generate a structured evaluation fact set; inputting the set into a rule engine, executing normative rule judgment and generating a verification result with a judgment score; and finally, according to an evaluation dimension aggregation rule result, outputting a dimension score, an overall evaluation score and a question detail item. The system comprises a multi-modal content analysis module, an evaluation fact generation module, a rule engine module and an evaluation result output module. According to the method, high-precision automatic evaluation of complex file documents is realized, the evaluation efficiency and consistency are improved, and the method is suitable for smart office scenes.

This invention provides an automated online transaction testing system and method based on the AIX system, comprising: a test case interpreter / executor module: taking test case files written according to a predefined syntax as input, interpreting and executing the test case files, and outputting a test report file after execution; and a test case manager module: generating test case tar packages, and reusing, managing, and maintaining test cases based on these tar packages. The automated online transaction testing solution for banks provided by this invention standardizes online transaction testing; supports the writing of personalized test case content through preset syntax tags; and supports the automation of online transaction testing through the syntax interpretation and execution of test cases. This invention implements four main functions—test case packaging, test case unpacking, test case storage, and test case retrieval—through the test case manager, achieving centralized maintenance and management of test cases.

The application provides an intelligent work injury identification research and judgment method based on natural language understanding, which can assist business personnel to obtain identification conclusions according to investigation results, search similar case files, give judgment results and legal basis, improve the accuracy and efficiency of work injury identification of business personnel, and avoid unnecessary litigation risks. The application has the following advantages: first, the method does not add any additional information to the original submitted information, which does not increase the burden of work injury identification personnel; second, the method can automatically assist business personnel to issue work injury identification conclusions and identification legal basis, and improve the work efficiency of business personnel; third, the method can search similar judicial judgment cases, and ensure the last link of work injury identification; and finally, the method is based on text information data, and is convenient for popularization and use in different institutions and different regions.

Embodiments of the present disclosure disclose a wearable device monitoring scheduling method and device, an electronic device and a readable medium. A specific embodiment of the method comprises: obtaining case file information; performing file association processing on the case file information to obtain file association information; performing intent recognition processing on case query information to obtain query intent information; performing dynamic routing processing on the query intent information to obtain target query path information; performing multi-source query processing on a heterogeneous database to obtain case association query result information; generating performance requirement configuration information of a wearable monitoring device; obtaining each to-be-matched performance requirement configuration information; matching the to-be-matched performance requirement configuration information corresponding to the performance requirement configuration information as matched performance requirement configuration information; determining a to-be-scheduled device identifier; and controlling a preset robot to take out the wearable monitoring device and schedule it to a preset position. The embodiment reduces the number of incorrect scheduling of the wearable monitoring device.

Wireless Charging Dock for Lawyer Devices with Multi-Angle Case File Viewing

The invention discloses a DNA multi-dimensional genetic relationship intelligent matching tracking system and method, a storage medium and electronic equipment, and the system comprises a case management module which is used for creating a case file; the multi-modal data import module is used for providing an input interface of DNA-STR data; the target crowd library construction module is used for creating a target crowd library and storing the DNA-STR data of the target crowd into the target crowd library; the multi-dimensional genetic relationship calculation module is used for calling a preset standardized authoritative algorithm to calculate a genetic relationship according to a target crowd library and a to-be-analyzed material evidence inspection material selected by a user from the case file; the result output and sorting module is used for outputting analysis results containing the genetic indexes and intelligently sorting the analysis results according to the sequence of genetic index values from high to low; according to the invention, through multi-modal data import, target population library construction and multi-dimensional full-pedigree genetic relationship calculation, multi-dimensional genetic relationship intelligent matching pursuit and intelligent result sorting of case material evidence inspection materials are realized.

A system for integrating medical device case files with corresponding electronic patient care records (ePCRs) is provided. The system includes a database storing a plurality of medical device case files and at least one processor. The at least one processor receives, from a patient charting device, charting data documented in an ePCR for an encounter with a particular patient, generates a search criterion based at least in part on the charting data, the search criterion including a predetermined relationship between at least one first parameter from the charting data and at least one second parameter associated with a medical device case file, identifies the medical device case file based on the generated search criterion, and generates an integrated patient encounter record including at least a portion of medical device data from the medical device case file and the charting data.

The invention relates to a multivariate evidence correlation analysis method in the judicial field, and belongs to the technical field of intelligent processing of documents. The method comprises the following steps: loading judicial case file data and extracting an evidence content text; constructing an evidence rule template according to judicial domain knowledge and expert opinions; extracting evidence elements based on the rule template and constructing an evidence library; building a multivariate evidence information network, calculating the condition probability of association information among evidence elements based on a Bayesian network, and forming a multivariate evidence association analysis model; optimizing the multivariate evidence information network through a random strategy reinforcement learning algorithm; and calculating an information probability value of the multivariate evidence subnet, and selecting the most valuable multivariate evidence information network. According to the method, a multivariate evidence correlation analysis event of a judicial case is converted into an updating and optimizing task of a multivariate evidence information network, the complex correlation problem among multivariate evidences is simplified, a correlation model among the multivariate evidences is given, and certain auxiliary support is provided in a judicial decision support system.

The invention discloses a medical record file management and intelligent report interpretation system based on a multi-mode AI, and relates to the technical field of deep application and innovation of an artificial intelligence technology in the medical field, and the system comprises a medical record report uploading module, a medical record file management module, a report interpretation module, an auditing and modifying module and a digital duplicate video explanation module. The case file management module identifies and extracts contents in a medical record report based on optical character identification, large language model structuring and embedded model semantic alignment, and the identified and extracted contents are stored in a structured manner to obtain patient case file data; and the report interpretation module interprets the patient medical record file data to generate an interpretation report based on a private domain knowledge base and a generation framework generated by retrieval enhancement in combination with a pre-filtering and post-filtering dual guarantee mechanism. According to the method, the closed-loop workflow of first draft generation by the AI, examination and modification by the doctor and digital duplicate video explanation is adopted, so that the information reaching efficiency of special patient groups is greatly improved.

The application discloses a short video false news detection method based on multi-agent cooperative investigation, relates to the technical field of news content detection, and comprises the following steps: extracting and composing original modal vectors of short video news samples; performing multi-modal forensic analysis to obtain video analysis results of the short video news samples; performing intelligence information retrieval to obtain a structured credible evidence set; obtaining a main case file of the short video news samples; performing multi-round argumentation based on the main case file of the short video news samples to obtain an examination result of the short video news samples; and finally performing prediction to output a prediction score of the short video news sample as false news. The application has the advantages that the short video false news detection task is creatively reconstructed into a collaborative investigation process of forensics-examination-judgment. While ensuring that the output result has high interpretability and persuasiveness, excellent detection performance is achieved, and an innovative solution is provided for constructing a reliable automatic false news detection system.

The application discloses an intelligent auxiliary generation method and system of an administrative punishment case file. The method adopts a three-column parallel layout in a document preparation interface: left navigation, middle editing, and right intelligent review. When a user edits, the system analyzes the content in real time based on a rule base, classifies and displays the review results in the right area, and provides a contrast view of the original text, modification suggestions, and risk explanations for each result, as well as 'position original text' and 'accept revision' function keys. The user can adopt the suggestions with one key and automatically complete the correction. The application deeply embeds intelligent review in the document writing process, and realizes real-time guidance and efficient improvement of the quality of the case file documents through intuitive interaction design.

The present application relates to the technical field of virtual simulation training, and discloses a construction method of a case investigation training platform based on network crime. The method comprises the following steps: performing spatial topology modeling on a physical training site, generating a virtual three-dimensional space model, and performing function partitioning of case simulation, electronic evidence collection, and command research and judgment; dynamically injecting multi-modal virtual evidence into the simulation area according to real case files; collecting environmental state and user operation behavior data in real time through a deployed probe; processing data according to preset case state transition rules by using a dynamic response engine, driving virtual scene elements to evolve in real time in a logical manner; and realizing state monitoring and deduction parameter adjustment through an integrated interactive console. The constructed platform realizes dynamic correlation of evidence and intelligent deduction of case information, and can improve the fidelity and practicality of investigation training.

The invention belongs to a fault diagnosis method, and provides a generator fault diagnosis method and a related device for solving the technical problems that an existing automatic diagnosis scheme is difficult to cover complex fault scenes, or the professional degree requirement is extremely high, and the decision-making process in the diagnosis process is opaque. And inputting into a pre-trained fault diagnosis agent to obtain an interpretable reasoning path and a diagnosed fault occurrence reason. Wherein when the fault diagnosis agent is trained, a historical fault case file is analyzed through a large language model, a knowledge base composed of fault reasoning paths is obtained, the knowledge base composed of the obtained fault reasoning paths serves as a learning target of the fault diagnosis agent, and a more intelligent guarantee is provided for safe and stable operation of power generation equipment.

This invention provides a method for exchanging power market trading platform server, client, and clearing cases, comprising: the server in the operating environment compressing and encrypting power market optimization clearing data in the platform database into case information files according to data type and storing them; the client extracting the stored case information files, encrypting them to form case exchange files, and outputting them to a target location; the client in the laboratory environment reading, decrypting, decompressing, and verifying the case exchange files at the target location to form case files, which are then stored in the server; the loading module of the server extracting and decompressing the stored case information files into optimization clearing data and storing it in the platform database in the laboratory environment. The case information exchanged in this invention adopts a step-by-step encryption method to ensure the security of core data of market members in the case files, ensure that the case files can only be exchanged within the trading platform, and ensure that the multi-encrypted case exchange files cannot be decrypted offline.

The invention provides an NLP-based text core information rapid extraction method and system, and the method comprises the following steps: S1, carrying out data preprocessing operation, collecting case file texts, and carrying out cleaning, word segmentation and named entity recognition; s2, extracting time information, and extracting case occurrence time and duration through a time expression recognition and standardization algorithm; s3, extracting site information, and extracting and sequencing case accurate sites in combination with a geographic knowledge base and an importance rule judgment algorithm; s4, event types are extracted, and the event types and core elements are recognized through text classification and semantic role labeling technologies; and S5, verifying the consistency and rationality of the extracted information through co-reference resolution and domain knowledge constraint.

This application proposes a case file quality assessment method, controller, storage medium, and product, applied in the field of data processing technology. The method includes: acquiring case file data; performing data recognition processing on the case file data to obtain an electronic dataset; assessing each case file in the electronic dataset according to preset structured knowledge base assessment rules to obtain assessment results; conducting human-machine collaborative review of the assessment results based on the case file qualification in the assessment results to obtain assessment opinions; and rectifying the case files based on the assessment results or assessment opinions. This application uses preset structured knowledge base assessment rules to achieve intelligent case file assessment, improving assessment efficiency while ensuring the consistency and objectivity of assessment results; simultaneously, this application's human-machine collaborative review of assessment results based on case file qualification can reduce misjudgments in case file assessment.

This application relates to a case file review method, apparatus, computer equipment, computer-readable storage medium, and computer program product. The method is executed by a review model and includes: acquiring a case file to be reviewed; extracting case file keywords from the case file; determining the review type of the case file based on the case file keywords; searching for review prompt words corresponding to the case file in a prompt word rule base according to the review type and case file keywords, and combining the review prompt words corresponding to the case file to be reviewed to obtain a review prompt word chain; and reviewing the content in the case file to be reviewed sequentially according to the review prompt word chain to obtain a review result. This method enables efficient and accurate case file review.

The invention discloses a power grid dispatching instruction and potential risk association analysis method, which comprises the following steps of: obtaining multi-source data related to a power grid dispatching instruction and a potential risk, and preprocessing the multi-source data; based on the preprocessed multi-source data, a scheduling instruction and potential risk association knowledge base is constructed, the basic information layer serves as a bottom layer support of the association knowledge base, and the association rule layer extracts a hidden association rule of the scheduling instruction and the potential risk from the multi-source data through a data mining algorithm to form an association rule base; the case library layer collects historical scheduling instructions and potential risk associated cases, establishes a structured case file and an efficient retrieval mechanism, and provides referenced historical experience for risk pre-judgment of the current scheduling instructions; and inputting to-be-analyzed data into the deep learning-based correlation analysis model for analysis, and outputting a correlation analysis result. By constructing the association knowledge base and combining with the deep learning model, the accuracy and reliability of the risk analysis result are improved, and the model accuracy is high.

The invention discloses a multi-dimensional feature-based case filing risk assessment method and system, and belongs to the field of law science and technology. According to the algorithm, a multi-dimensional risk feature library including party features, case behavior features, social influence features, special subject features and production breaking risk features is constructed, and a machine learning technology is adopted to realize automatic assessment of case filing risks. According to the invention, the efficiency and accuracy of case filing risk assessment can be improved, assessment standards are unified, scientific decision support is provided for case filing examination, and the method has important judicial practice value.

The invention relates to the technical field of virtual simulation practical training, and discloses a method for constructing a case investigation practical training platform based on network crimes. The method comprises the following steps: carrying out spatial topology modeling on a physical training site, generating a virtual three-dimensional space model, and carrying out case simulation, electronic evidence collection and command research and judgment function division; dynamically injecting a multi-modal virtual evidence into the simulation area according to a real case file; collecting environment state and user operation behavior data in real time through a deployed probe; a dynamic response engine is utilized to process data according to a preset case state transition rule, and virtual scene elements are driven to carry out real-time evolution conforming to logic; and state monitoring and deduction parameter adjustment are realized through the integrated interactive console. The constructed platform realizes dynamic association of evidences and intelligent deduction of the case, and can improve the simulation degree and the actual combat of investigation practical training.

The invention relates to the technical field of interface automatic testing, and provides a universal API interface automatic testing method which comprises the following steps: S1, constructing a self-research framework which supports an automatic system framework of continuous integration and data driving; s2, designing use cases according to a function test thought, developing a method for reading a function, supporting to read each use case file according to rows, and realizing data driving execution; s3, constructing a configuration file, and performing configuration management on parameters including a test environment, an execution mode and a retry strategy; s4, compiling an algorithm, and supporting flexible configuration of a to-be-executed use case and a concurrent use case group through a file; s5, executing the use case, embedding an automatic retry and result merging algorithm, automatically merging multiple test results, and displaying the results through an Allure report platform; and S6, a table test report is generated, and interactive cooperation functions including module-level and system-level execution time statistical analysis, screening and sorting are supported. And the adaptability, the execution efficiency, the maintainability and the team cooperation efficiency of the test scene are remarkably improved.

The application discloses a case state synchronization method, device, equipment, medium and product, relates to the technical field of process automation, and the method is applied to a process automation robot RPA. When a preset query period is reached, preconfigured task scheduling information is read. The task scheduling information is used to log in a lawyer service platform, and case filing state data is captured from the lawyer service platform according to the task scheduling information. A case filing state table is generated according to the case filing state data, and the case filing state table is sent to a law enforcement system. Thus, the problem that case state synchronization depends on manual operation and thus leads to low efficiency is solved, and the efficiency of case state synchronization is improved.

The invention provides a method for constructing a case knowledge graph, electronic equipment and a storage medium, and relates to the technical field of big data and artificial intelligence application, and the method comprises the steps: obtaining a case file text, and carrying out the preprocessing of the case file text. And extracting the preprocessed case file text through an information extraction model to obtain entity information. And mapping based on the entity information to obtain a graph node, and constructing a relation edge according to the graph node and information in the case file text. And constructing the case knowledge graph based on the graph nodes and the relation edges. According to the method, a framework combining natural language processing and a knowledge graph is introduced, structured extraction of entity information in a case file text is realized, and a graph database is constructed to carry out relationship modeling among entities. The mode breaks through the limitation of a traditional information island, and provides a new thought for upstream and downstream role chain identification.

The application relates to the technical field of process automation and artificial intelligence technology, in particular to a multi-modal-based agent collaborative auditing method and system, which comprises the following steps: obtaining case file information, performing similarity analysis on a characteristic vector set and a decision vector set, and obtaining a weight set corresponding to a historical case file with the highest similarity from a database; based on the similarity result, setting the weight set as an initial weight set or an optimal weight set; based on the decision vector set, performing decision conflict analysis, and optimizing the initial weight set based on the analysis result to obtain the optimal weight set; and based on the optimal weight set and the decision vector set, performing weighted fusion to obtain a fusion decision, so that the application has the advantages of effectively solving decision conflicts in a multi-modal data fusion process, accurately locating problem roots and improving human-machine collaborative efficiency.

The invention discloses a template matching-based file single-suite automatic test paper generation method and system. The method comprises the following steps of: constructing a file category template system which comprises a preset data organization form and a hierarchical directory type hierarchical file organization structure, determining association between categories and project levels, and defining each level path and node configuration rules of a hierarchical directory; organizing electronic archive files by taking a project as a unit according to template classification requirements, intensively storing the electronic archive files to corresponding project node containers, standardizing and arranging storage paths and folder names, and completing classification and archiving preprocessing; the method comprises the following steps: displaying a file to be subjected to test paper formation in a directory tree according to categories and projects, selecting a target category and project nodes to generate temporary test paper formation and distribute identity information, finishing formal test paper formation according to a preset requirement, distributing unique file identity information and recording the unique file identity information to an attribute table; and collecting official test paper composition attribute information, and supporting manual single input or file number associated batch import to form complete electronic file test paper composition data. And the file management efficiency and standardization are improved.

The application relates to the technical field of electronic file management and intelligent data processing, and particularly discloses a method and device for quickly grouping electronic files based on metadata intelligent extraction, wherein the method comprises the following steps: generating an initial metadata set; performing weighted normalization processing; outputting a conflict set and a consistent metadata set; generating a case file abstract set and an element anchor mapping table; constructing a case file directory index tree; and performing high-concurrency and quick output of multi-modal evidence files. Compared with the prior art, the method can solve the technical problem that the efficiency of manual indexing and grouping is limited when multi-modal evidence files are processed, especially under the conditions of cross-source and multi-thread concurrency, and it is difficult to realize high-consistency and low-delay quick grouping of case files. By introducing a BERT semantic normalization mechanism, cross-file consistency scoring and multi-thread consistency scheduling algorithms, the application realizes efficient organization and real-time quick grouping of evidence files under the condition of multi-modal high concurrency, and significantly improves the efficiency of case file generation.