86 results about "Logical analysis" patented technology

The invention relates to the technical field of artificial intelligence in the education industry, in particular to an intelligent composition quality evaluation method and system based on a large language model, and the method comprises the steps: carrying out the text normalization and semantic unit segmentation of a composition, extracting a semantic vector through a first large language model in combination with a context enhancement strategy, and positioning a semantic fracture risk position; recognizing composition core elements through a second large language model, and mapping the composition core elements back to the semantic unit sequence; constructing a demonstration logic diagram, extracting a core demonstration path and abstracting the core demonstration path into a logic role topological graph; in combination with a pre-constructed writing specification knowledge graph, comparing structural compliance, connection strength and an expected support relationship, identifying and demonstrating logic defects, and generating a global deduction item list; semantic clustering is carried out on illegal items to form an error label set, comprehensive weight is calculated in combination with historical data of students, and core weak items are positioned; according to the application, the logic analysis depth of intelligent evaluation of the argument is remarkably improved, and the pertinence and practicability of teaching feedback are improved.

The invention discloses an intelligent medical record quality control method based on a rule and large language model hybrid engine, and relates to the technical field of natural languages, and the method comprises the steps: obtaining original electronic medical record data from a medical information system; performing post-structured processing on the original electronic medical record data, and converting an unstructured or semi-structured text in the original electronic medical record data into a unified structured data object readable by a machine; traversing a plurality of quality control points in a preset quality control rule base, and for each quality control point, adaptively selecting and executing a corresponding quality control path based on the converted structured data object; and based on the quality control results of all the quality control points, performing score calculation and generating a quality control report. According to the method, the automatic and deep quality control of the full-dose medical record can be realized, form inspection is covered, connotation logic analysis can be executed, the system is endowed with excellent flexibility and regional expansion capability, and reliable technical support is provided for improving the overall level of medical quality management.

The invention discloses a new-generation emergency command system scene analysis system integrated with a convolutional neural network, particularly relates to the technical field of computer vision and intelligent emergency command, and is used for solving the problem that the dynamic association and situation evolution logic analysis capability among emergency scene elements is insufficient in the prior art. Visual element features are extracted from a video stream through a feature extraction module by using a convolutional neural network, an association graph construction module constructs a space-time association graph based on the features, a movement evaluation module calculates element group movement feasibility indexes, and a situation analysis module analyzes divergence features and antagonism degrees in combination with movement track convergence. And the risk identification module identifies a derived risk aggregation mode according to the situation prediction, and the semantic generation module finally outputs high-level semantic description information containing situation prediction to realize closed-loop analysis from scene perception to cognitive decision.

The invention discloses a general data exchange system based on a configurable label structure, which relates to the technical field of data processing and information integration, and comprises a parameter module used for establishing an identity authentication mechanism of two exchange parties; the business document module is used for establishing a data structure definition based on a preset exchange demand; the receipt logic module is used for carrying out logic analysis and code decoupling on the data structure definition, generating a marked language script code and an execution instruction, constructing an execution matrix and realizing mapping between a database physical field and a memory logic variable; and the standard adaptation module is used for comparing and checking the content of the generated data and feeding back a checking result to the parameter module to correct the exchange rule and parameter configuration. A more intelligent logic separation strategy is implemented through structural insight, data reading, writing and transmission are cooperatively controlled, complete decoupling of service logic and program codes is achieved through a nested tag structure, and flexibility, universality and maintenance efficiency of data exchange are optimized.

The invention discloses an English teaching writing error diagnosis method based on artificial intelligence, and relates to the technical field of artificial intelligence, and the method comprises the following steps: obtaining an English composition text, and obtaining initial writing data; performing grammatical structure analysis according to the initial writing data to obtain grammatical features; performing vocabulary error analysis according to the grammatical features to obtain vocabulary errors; performing syntactic and semantic consistency analysis according to the vocabulary errors to obtain syntactic and semantic errors; performing article logic analysis according to the syntactic and semantic errors to obtain article logic errors; and performing comprehensive diagnosis according to the article logic error to obtain a diagnosis result. According to the method, the conjunction matching degree and the semantic compatibility are combined, cross-sentence logic analysis is achieved, misjudgment of isolated sentences is avoided, a complete error set is formed, the comprehensiveness and accuracy of diagnosis are improved, and practicability and guidance are enhanced.

The invention discloses a subjective question intelligent marking system and method based on a large language model, and relates to the technical field of online education and examination intelligent marking, and the system comprises a scoring rule configuration module, an AI scoring engine module, a teacher review interaction module and a result presentation and archiving module. The scoring rule configuration module is used for receiving AI scoring related parameters configured by a user; the AI scoring engine module integrates a large language model and is used for receiving test question related information, examinee answers and AI scoring related parameters and carrying out natural language understanding, knowledge reasoning, logic analysis and standard comparison on the basis of the large language model to obtain an AI scoring result; the teacher re-checking interaction module provides an interaction interface for the user to check the AI scoring result to obtain a final scoring result; and the result presenting and archiving module is used for archiving, storing and visually displaying the final scoring result. According to the invention, the manual reviewing cost can be reduced, and the accuracy and efficiency of subjective question reviewing are improved.

The application provides an engineering education system and method fusing explainable multi-objective intelligent optimization, and relates to the technical fields of intelligent education and artificial intelligence optimization. The method comprises the following steps: obtaining an initial engineering design scheme of a user, and obtaining a standardized multi-dimensional index vector through physical simulation analysis and logical analysis; configuring weights with structured reasons for each index, identifying critical weight values leading to decision reversal through sensitivity analysis, and then determining optimization objectives and constraint conditions; performing multi-objective optimization search using an explainable multi-objective optimizer, generating a Pareto optimal solution set and outputting explainable data; simultaneously generating a behavior interaction sequence of the user; generating a capability evaluation report of the user according to the behavior interaction sequence; and adjusting a preset teaching logic sequence according to the capability evaluation report to form a closed-loop teaching process. The application is suitable for cultivating and evaluating the decision-making ability of students in balancing technical performance and environmental sustainability in engineering design.

The invention relates to the technical field of voice real-time translation, in particular to a voice real-time translation and proofreading system oriented to cross-border e-commerce, which comprises the following modules: a voice semantic processing module used for receiving voice input, converting the voice input into text data, performing semantic analysis on the text data, extracting commodity names, attribute information and logic relationships, and sending the extracted commodity names, attribute information and logic relationships to a server; semantic structure data is generated and stored in a context cache; and the anaphora analysis module is used for reading the semantic structure data from the context cache, detecting anaphora words in the semantic structure data, determining anaphora objects and updating the semantic data subjected to anaphora resolution to the context cache. According to the method, word segmentation, part-of-speech tagging, syntactic analysis and dependency analysis are carried out on a text, commodity names, the number, colors, sizes and attribute relations are extracted to generate structured semantic data, the structured semantic data are stored in a context cache, and when anaphora words are detected, anaphora objects are determined through semantic similarity and context logic analysis, and the semantic data are updated.

The invention provides an evidence-driven large language model MISRA C rule review method and system for aviation safety. According to the method, formalized feature extraction is carried out from four aspects of grammar structure features, semantic structure features, logic analysis features and preprocessing behavior features for target codes according to various rules of MISRA C forcing class rules, and diagnosis information is diagnosed in combination with an industrial-grade compiler; generating a structured evidence set comprising abstract syntax tree node statistical features, code context structure features, control flow graph features, function internal data flow analysis features, symbol and type table features and macro definition analysis features; and based on the structured evidence set and the large language model, executing evidence tracing, rule matching and logical reasoning according to a preset thinking chain process, and outputting a structured judgment result containing illegal rule numbers, evidence description and code positions. According to the method, the false alarm rate can be remarkably reduced while the high rule coverage rate and the detection accuracy are kept.

The invention provides an intelligent contract distributed computing method based on a virtual block chain node, which comprises the following steps: S1, a central coordination node and a plurality of cooperative terminal nodes are dynamically combined on a logic level to form a virtual block chain node, and the central coordination node performs management and task scheduling on the cooperative terminal nodes; s2, the central coordination node receives the smart contract execution request, performs logic analysis on the smart contract and decomposes the smart contract into a plurality of parallel subtasks; s3, the central coordination node assigns the subtasks to the cooperation terminal nodes for parallel processing, and validity verification is carried out on a calculation result through a verification process; and S4, the central coordination node encapsulates the verified final execution result into a transaction and submits the transaction to the target block chain network, and after the transaction is subjected to consensus processing, the smart contract is executed to update the state data on the chain. According to the method, the contradiction between limited computing resources of the Internet of Things equipment and high computing resource overhead of the block chain during integration of the Internet of Things and the block chain is solved.

The invention relates to the technical field of seafood radioactivity detection, in particular to a radioactivity detection information report generation method, device and equipment. Performing abnormal value detection on historical radioactivity detection data based on a quartile distance method; constructing a risk assessment model based on an analytic hierarchy process, an abnormal value judgment lower limit threshold and an abnormal value judgment upper limit threshold; performing logical analysis on the real-time radioactivity detection data according to the risk assessment model and a preset logical reasoning algorithm; when the logic analysis result meets the logic relation condition, constructing a radioactivity detection report template according to the logic analysis result; performing data filling on the radioactivity detection report template according to the real-time radioactivity detection data to obtain a radioactivity detection information report; according to the scheme, through abnormal identification, model adaptability improvement, comprehensive risk quantification and automatic report generation, marine product safety and consumer health are guaranteed, and supervision decision is assisted.

This invention discloses a pre-prepared food preservation device and method. The device includes a housing, a multi-dimensional sensing module and a control module disposed within the housing, as well as an interaction module, a communication module, and a central control module. The multi-dimensional sensing module and the control module are connected to the central control module via the communication module, used to detect parameters of the pre-prepared food inside the housing and to regulate the temperature. The interaction module communicates with the central control module for parameter setting and information display. The central control module performs logical analysis based on the real-time parameters collected by the multi-dimensional sensing module, determines the preservation status, and generates a preservation strategy. The preservation status is pushed to the interaction module, and the preservation strategy controls the control module to adjust the temperature, humidity, and ventilation rate inside the housing. This invention uses the multi-dimensional sensing module to monitor temperature, humidity, and various characteristic gases in real time, and the central control module performs multi-dimensional spoilage risk quantification calculations, dynamically synthesizing a freshness index, thereby executing targeted preservation strategies.

This invention discloses a large-scale model defense method based on semantic logic. By employing semantic logic analysis and model learning techniques, it systematically identifies and blocks the confusion effect of bias, thereby reducing the impact of bias in pre-training data on the guidance process. It includes an interpretable component that provides insight into the alignment between the generated output and the desired direction, enhancing the interpretability of the guidance process, increasing model transparency and user trust. This method may reduce reliance on manual annotation and computational resources, thus improving resource efficiency. Through unbiased guidance representation, it improves the model's generalization ability across different tasks and domains, contrasting with the limited generalization capabilities of existing technologies, exhibiting high scalability and adaptability. It can be applied to different language models, providing in-depth understanding of the consistency between the generated output and the desired direction, thereby enhancing the interpretability of the steering process while mitigating the impact of bias.

The application discloses a multifunctional bronchoscope simulation training teaching method, and belongs to the technical field of training teaching, and specifically comprises the following steps: collecting instrument moving track data and real-time video stream data in bronchoscope operation, comparing the track data with a standard path to identify a path deviation section, extracting bronchial bifurcation position marks and mucosa morphological feature marks from the video stream, establishing a space-time correlation between path deviation and anatomical features and constructing an operation logic analysis report, converting the report into semantic features and image features, inputting the semantic features and the image features into a multimodal large model for feature fusion to generate an operation rationality evaluation vector, finally analyzing the vector to obtain a path compliance score, a clinical decision score and a strain capacity score, and finally obtaining a final score result by fusing the three scores; the application effectively distinguishes between operation mistakes and reasonable clinical strain, and realizes real evaluation of the clinical decision-making ability of students.

The invention discloses an omni-channel intelligent customer service response interaction system and method based on artificial intelligence, and belongs to the technical field of intelligent customer service. Multi-channel user session data is received and uniformly mapped into structured semantic data through a semantic coding rule, and cross-channel data is associated; constructing a dynamic session memory library based on the entity-feature-association three-dimensional data structure, and capturing session core information in real time; for anaphora and omission information in a dialogue, double-path parallel processing is carried out: a first path generates an entity candidate set through time sequence reverse retrieval, a second path generates a feature candidate set through semantic logic analysis, and a complete semantic expression is formed after cross validation; and respectively generating core response and potential demand guide content through double paths, and adjusting an output form in combination with channel adaptability to complete omni-channel intelligent interaction.

The invention belongs to the field of aviation fault logic analysis, and particularly relates to a fault propagation logic analysis method and system of a multi-redundancy architecture. Determining the total number M and the maximum cycle index of the redundancy architecture, and setting a shaping variable i as 1; judging whether the shaping variable i is within the maximum cycle index range or not; if yes, dividing the redundancy architecture into i left redundancy architectures and M-i right redundancy architectures based on the shaping variable i; weight intermediate values are set, different fault propagation logics are respectively formed by comparing the weight values, and different logic gates are respectively selected according to the different fault propagation logics; the weight of the left side and the weight of the right side are considered at the same time, the left side and the right side approach at the same time, and fault propagation logic can be analyzed on the premise of adopting few cycle times; and for the fault propagation logic in which at least any multiple or more faults occur at the same time, the fault propagation logic can be completely and comprehensively considered only by adopting one voting gate for explicit.

The invention relates to a server task management system, method and device based on BMC collaboration and a medium. The system comprises a BMC decision and analysis module, a server operating system and a shared data area, the BMC decision and analysis module is used for executing logic analysis and decision according to hardware state data collected by the server operating system and generating a decision instruction when a preset type of task is received; the server operating system is used for executing hardware state data acquisition and executing a decision instruction generated by the BMC decision and analysis module; and the shared data area is used for being in communication connection with the BMC decision and analysis module and a server operating system, storing the decision instruction and the hardware state data and carrying out data sharing. Task decomposition is carried out on the server operating system through the BMC decision and analysis module, data storage and interaction are achieved in combination with the shared data area, resource occupation of the server operating system can be reduced, and the service processing response speed of the server operating system side is increased.

The application discloses a classroom instant interaction feedback analysis method and system based on a portable multimedia display device, relates to the field of educational information technology, and discloses the classroom instant interaction feedback analysis method and system based on the portable multimedia display device, which automatically acquires student answer data, performs logical analysis, verification correction, cluster analysis and common error identification, and generates visual feedback in real time, solves the problems of low artificial review efficiency and incapability of accurately positioning common errors in the prior art, can automatically analyze the solution logic of open questions, identify common errors, and provide real-time visual feedback, improves classroom interaction efficiency and teaching accuracy, and thus improves teaching quality.

The invention discloses a data analysis system and method applied to power fault detection, and relates to the technical field of circuit fault detection.The method comprises the steps that multi-source core data are collected in a segmented mode and preprocessed, and a target feature set is obtained through scene admission judgment, homology verification and time sequence rationality verification; carrying out correlation logic analysis on the pressure value, the contact area value and the wire resistance variation based on the target feature set, and outputting a logic analysis result; according to a logic analysis result, respectively establishing corresponding relations among the contact area value, the pressure value and the lead resistance influence quantity, and integrating the two corresponding relations to construct a lead resistance total influence quantity calculation model; and substituting the pressure value and the contact area value which are acquired in real time into the model, and completing fault grading judgment according to the obtained total influence quantity of the wire resistance.

The invention relates to the field of audio processing, in particular to a voice call quality analysis method and device, equipment and a medium. According to the method, by accurately matching the call service progress stage with the corresponding audio analysis template, binding of'service stage-evaluation standard 'is technically constructed, discrete indexes are replaced by structured dimensions and key point options, and the problem of result discretization in the prior art is fundamentally solved; secondly, by means of semantic understanding and logic analysis of a large language model, the limitation of surface analysis of traditional keyword retrieval is broken through, and precise capture of dialogue context and deep intention is achieved; and finally, the model outputs a standardized quality analysis result according to template key points, a closed loop of data input-deep analysis-structured output is completed in the technical level, deep evaluation based on business logic is realized, the technical accuracy of evaluation is ensured, and the analysis result fits business reality.

The invention provides an interactive security testing method and device based on a large model, and can be applied to the technical field of artificial intelligence and security testing. The method comprises the following steps: preliminarily identifying a security vulnerability set of an application by using a taint analysis technology to obtain a first security vulnerability set; function information related to the first security vulnerability set is extracted, and the function information comprises at least one of function content and taint parameters related to the first security vulnerability set; performing logic analysis on at least one of the function content and the stain parameters by utilizing a large model to obtain a logic analysis result aiming at the function information; and processing the first security vulnerability set according to the logic analysis result to obtain a second security vulnerability set, and outputting the second security vulnerability set as at least one part of an interactive security test result.

The invention discloses a state machine graphical modeling packaging method and device, equipment and a storage medium. The method comprises the steps of obtaining an event description file of a to-be-modeled encapsulation event implementation logic; performing logic analysis on the event description file, extracting a state machine structure, and obtaining hierarchical nesting information corresponding to a finite state machine in the event description file; according to the hierarchical nested information, plane view modeling processing is carried out, a state view model corresponding to a finite state machine in the event description file is obtained, and the state view model displays display information of all event states in a plane display mode; and performing graphic packaging processing on the sub-state machine in the state view model to obtain an event modeling packaging view corresponding to the to-be-modeled packaging event. According to the technical scheme, multi-layer nested state machine graph modeling can be realized, the complexity of the model is effectively reduced, and the readability and maintainability of the model are improved.

The application relates to the technical field of cardiovascular disease diagnosis and treatment and artificial intelligence, and discloses a cardiovascular disease diagnosis and treatment scheme optimization system based on architecture, which comprises an original data preprocessing module, which is used for collecting and standardizing time series monitoring data and static data of medical history texts, adopts an improved and normalized algorithm, utilizes model structured text data, and outputs standardized patient feature data; and an improved logic analysis module, which is used for receiving the standardized patient feature data, optimizing the architecture by introducing a sparse attention mechanism, and performing time series correlation analysis, pathological feature mapping and individual difference modeling. The improved logic analysis module is used for introducing the sparse attention mechanism, deeply mining time series correlation and implicit pathological logic coupling relationships in complex time series monitoring data, generating a high-dimensional patient state feature vector, and solving the problem that traditional methods are shallow in analysis and cannot accurately identify individualized pathological states.

The application discloses a liver cancer diagnosis kit combined with DNA logic gate and nucleic acid aptamer sequencing, belongs to the field of diagnosis kits, and particularly relates to a double-stranded "and gate" logic operation composed of DNA sequences of cT1, cT2, cT35 and I, and an amplification reagent containing S-II, W, F, F-Cy5, M1 and M1-Cy3 based on entropy-driven amplification reaction. After PBMC is extracted from whole blood, the kit can perform logic analysis on whether target proteins corresponding to nucleic acid aptamers Apt51, GR-30 and IBA are simultaneously present on the PBMC, so that early screening of liver cancer is realized. The specific target of liver cancer patients found by high-throughput sequencing of nucleic acid aptamers can be effectively distinguished from healthy people and cancer patients by the kit.

The invention discloses a decision logic analysis method and related equipment, and the method comprises the steps: collecting a real-time rule trigger event flow and a decision logic source code of a server in parallel when a decision engine of the server runs; constructing a dynamic call graph based on the real-time rule trigger event flow, wherein the dynamic call graph comprises rule nodes and dynamic attributes triggered by rules; constructing a static dependency graph based on the decision logic source code, wherein the static dependency graph comprises a dependency relationship between variable nodes and a code level; analyzing an association relationship between the dynamic call graph and the static dependency graph, and generating a dynamic and static fusion strategy graph; and rendering a thermodynamic diagram based on the dynamic and static fusion strategy map, so as to display the thermodynamic diagram on a visual interface.

The application provides an action timing counting method and device, electronic equipment and machine readable storage medium, the method comprises: obtaining a target video; using a human pose estimation model to extract the skeleton key point information of the target; converting the skeleton key point information into a space-time vector feature and performing retrieval matching with the features in the standard action library to obtain different action state labels of the standard action; performing logical analysis on the matched different action state labels to obtain the counting timing result of the standard action. The method has the characteristics of high efficiency and strong function expansion, and can use general logic to obtain the counting timing result of different actions.

This specification discloses a decision logic analysis method and related equipment. The method includes: concurrently collecting real-time rule trigger event streams and decision logic source code from the server during server-side decision engine runtime; constructing a dynamic call graph based on the real-time rule trigger event stream, the dynamic call graph containing rule nodes and dynamic attributes of rule triggers; constructing a static dependency graph based on the decision logic source code, the static dependency graph containing variable nodes and code-level dependencies; parsing the association between the dynamic call graph and the static dependency graph to generate a dynamic-static fusion strategy graph; and rendering a heatmap based on the dynamic-static fusion strategy graph for display on a visualization interface.

The invention relates to the technical field of fault type diagnosis, in particular to a three-phase full-bridge inverter fault diagnosis method, system and equipment. The method comprises the following steps: acquiring a PWM command signal in a three-phase full-bridge inverter and an electric signal and a temperature signal of an IGBT device; based on the bridge arm on-off logic performance, the electric signal and the temperature signal of the IGBT device in the PWM instruction signal period, obtaining an on-off logic analysis coefficient and a conduction efficiency coefficient of the IGBT device, combining a fault determination threshold and a constraint condition, obtaining a fault type label of the IGBT, constructing a fault sample set, training a fault type identification model, and obtaining a fault type identification result; obtaining a trained fault type identification model; according to the method, the on-off logic analysis coefficient and the conduction efficiency coefficient are accurately obtained, so that the accuracy of fault type tag identification is effectively improved, the fault type of the IGBT device can be accurately identified in real time, corresponding processing is carried out in time, and the fault loss of the three-phase full-bridge inverter is effectively reduced.

The utility model relates to the technical field of oscilloscope, especially intelligent oscilloscope of integrated logic analysis function, including the installation support of flat type appearance, the side of installation support is bent to the upper, and the bent position fixed installation has the oscilloscope body, the utility model has the advantages that: through setting up the installation support, its side is bent to the upper, and then provides the installation position for the oscilloscope body, through setting up two support cross bars, guide rail, push rod, sliding block and butterfly bolt, the sliding block is installed in the inside of guide rail, and its top end is rotatably connected with one end of push rod, the bottom surface of support cross bar is installed with a plurality of sucking disc, a plurality of sucking disc can be stably adsorbed on the external workbench, simultaneously, the butterfly bolt is screwed, the position of sliding block is stabilized, thereby making the oscilloscope body and installation support stable installation on the external workbench, preventing the oscilloscope body from falling due to accidental dragging, thereby effectively solving the problem in the prior art.

A chip-embedded logic analyzer autonomously sequences between logic analysis scenarios, dynamically revising match criteria and match-responsive behavior as match conditions for each successive scenario are met. Through this cascading-scenario operation, the logic analyzer may log selected debug vectors as and / or after complex sequences of device conditions unfold, enabling substantially more targeted and sophisticated operational debugging than conventional trigger-and-log analyzers.