1188 results about "Verification system" patented technology

The invention relates to an engineering document index consistency proofreading method and system based on a multi-modal large model, and the method comprises the steps: Q1. OCR detection and recognition: carrying out the optical character recognition and format analysis of a source document, converting an uploaded PDF document into a processable text message in a Markdown format, and carrying out the format discrimination of a table, a formula and a plain text; and Q2, table and formula processing: adopting a hierarchical processing strategy, intelligently selecting an optimal processing mode according to the complexity of the table, and converting table information into a descriptive long text through a language large model and cue words. According to the method, accurate, reliable and efficient document index checking service can be provided for a user, the quality and efficiency of professional document processing are remarkably improved, the efficiency and quality of knowledge graph construction are remarkably improved, a knowledge verification system capable of being evolved continuously is established, and the method is suitable for popularization and application. And a reliable technical support is provided for knowledge management and professional decision-making in a complex field.

The invention discloses an SQL statement structure verification system based on large model and knowledge graph fusion enhancement. The SQL statement structure verification system comprises a knowledge graph construction module, an input design module, a verifier design module and an output design module. According to the method, a knowledge graph is introduced as a structured semantic support, and a closed-loop enhancement processing flow of SQL statements from generation, verification to optimization is realized in combination with a structure perception cue word design, a rule verification mechanism and a Function Call feedback interface; the defects that an existing Text2SQL method is insufficient in structural understanding, lack of semantic reasoning, weak in generalization ability, dependent on computing power and the like are overcome. According to the method, triple guarantee of semantic perception, rule driving and model assistance is realized, the accuracy, robustness and interpretability of SQL generation are remarkably improved, and the cognitive load and operation risk of non-professional users in database interaction are effectively reduced.

The invention relates to document verification, in particular to a heterogeneous document set-oriented cross-modal semantic alignment and logic consistency verification system, which is used for heterogeneous document input, supports multi-format document input and comprises multi-modal elements including texts, pictures, tables and charts. The document analysis module is used for carrying out structured extraction on document contents; extracting multi-modal elements, identifying and classifying various elements in the document, and establishing position and type labels of a foundation; the knowledge graph construction module is used for uniformly modeling heterogeneous elements into a multi-modal knowledge graph; the graph neural network semantic alignment module is used for realizing accurate cross-modal semantic alignment by using a specially designed graph neural network based on the multi-modal knowledge graph; the hybrid consistency verification engine is used for performing logic consistency verification in combination with a symbol logic verification mechanism and a semantic consistency verification mechanism; according to the method, the defect that accurate cross-modal semantic alignment and logic consistency verification are difficult to carry out on professional documents with multi-modal elements can be effectively overcome.

The invention relates to a carbon emission checking system and method based on a block chain, and the system comprises a basic resource layer which collects enterprise energy consumption data in real time, employs cloud computing resources to provide data storage and computing capability, and employs a Hash algorithm to process the enterprise energy consumption data, and obtains a data abstract; the block chain network layer carries out distributed storage through an alliance chain architecture, carries out consensus evidence storage on the data abstract by adopting a PBFT consensus algorithm, and generates an encrypted data abstract; the intelligent contract layer receives the encrypted data abstract transmitted by the block chain network layer, and executes verification, calculation and supervision rules; and the application service layer calls the processing result of the intelligent contract layer, and respectively provides an enterprise carbon checking terminal service interface, an institution carbon checking terminal service interface and a competent department carbon supervision terminal service interface for the enterprise, a third-party checking institution and the competent department to check the carbon emission. According to the invention, high-efficiency check, high-credibility verification and whole-process traceable supervision of the carbon emission data are realized.

The invention provides a code agent construction system, a construction method thereof and a code generation method, and relates to the technical field of computers, in particular to the technical field of artificial intelligence such as large models. According to the specific implementation scheme, the code agent construction system comprises an intelligent cooperation engine, a layered template library, a semantic understanding and layered retrieval system, a T-RAG generation and optimization system and a closed loop verification system; wherein the layered template library comprises a project-level template, a function-level template and an API-level template; the semantic understanding and hierarchical retrieval system is configured as follows: analyzing user requirements through a natural language understanding module to generate an intention vector, and sequentially executing project-level, function-level and API-level three-level progressive template retrieval; and the T-RAG generation and optimization system is configured to inject the hierarchical retrieval result into the cue word of the large language model to generate deployable codes containing front-end and rear-end logics.

The present disclosure provides for technology that addresses technological challenges arising in the field of identity verification. In particular, the present disclosure provides for out-of-band identity verification workflows that allow a first user to issue a verification challenge to a second user to confirm the identity of the second user. For example, the first user may receive a communication claiming to be from the second user. Rather than attempting to confirm the identity of the second user in-band, the first user initiates an out-of-band verification challenge to the second user.

The invention relates to the technical field of industrial internet-of-things data security, in particular to an edge calculation differential privacy industrial internet-of-things data desensitization verification system and method.According to the system and the method, edge nodes are divided in a three-dimensional mode according to resource capacity, function positioning and privacy requirements, differential differential privacy parameters are formulated in combination with data attributes and leakage influences, and the safety of the industrial internet-of-things data is improved. And a dynamic adaptive grid is matched to realize hierarchical alignment, scene binding and elastic reconstruction, so that a cross-hierarchical privacy risk is avoided, and verification logic is simplified. Noise intensity is dynamically corrected by integrating multi-dimensional factors based on grids, lightweight, medium and deep hierarchical desensitization is designed for three types of nodes, and privacy protection and data availability are balanced. A privacy security and data availability two-dimension, terminal-gateway-area three-level verification chain is constructed, the desensitization effect is comprehensively evaluated, closed-loop iteration is achieved through hierarchical judgment and accurate adjustment, and industrial scene requirements are efficiently met.

The invention discloses an interpretability analysis and decision sharing verification method and system for a rectal cancer prognosis model, and relates to the field of medical artificial intelligence interpretability. The method comprises the following steps: carrying out gradient weighting class activation mapping analysis on a prognosis model to generate an image thermodynamic diagram; calculating the contribution degree of the multi-modal features by using an SHAP interpreter; an integrated visual interface is constructed, and patient data, model prediction and the explanation result are presented to a doctor together; the doctor performs independent risk assessment based on the interface information; finally, decisions of doctors and the model are compared, and model auxiliary efficiency is evaluated. Through a doctor-model decision sharing verification mechanism which is explained and innovated in a multi-level mode, the transparency and clinical credibility of the complex AI prognosis model are remarkably improved, the value of time sequence data in dynamic risk assessment can be verified, and clinical landing application of the AI model is powerfully promoted.

The invention relates to code verification, in particular to a code and document consistency reasoning verification system based on a cross-modal logic atlas, which comprises an input layer for receiving source codes and software documents; the feature extraction layer is used for performing feature extraction on the source code and the software document; the abstraction layer is used for converting the extracted features into comparable intermediate representations; the unified modeling layer is used for mapping code logic and document semantics into a unified atlas structure and performing formalized representation by using description logic to obtain a cross-modal logic atlas; the reasoning verification layer is used for performing reasoning verification on the consistency of the code and the document according to the cross-modal logic graph; the result processing layer is used for judging a verification result according to the reasoning verification condition, starting a contradiction positioning mechanism when inconsistency is found, and carrying out contradiction positioning and report generation to obtain an interpretable report; according to the technical scheme provided by the invention, the defects that the consistency between the code and the document is difficult to accurately verify, and accurate contradiction positioning and an interpretable report are difficult to provide can be effectively overcome.

The invention belongs to the technical field of civil engineering monitoring, and discloses an optical fiber strain sensor performance verification method and system for highway infrastructure monitoring, and the method comprises the steps: analyzing the influence rule of the parameter change of a coupling layer on the strain transmission efficiency of a measured sensor based on a layered material coupling mechanical model; based on the three-dimensional entity numerical model, analyzing an influence rule of layout process parameters of the tested sensor on the strain transmissibility; verifying the performance of the sensor in a laboratory environment by using a reduced scale model; on a real highway infrastructure or a constructed full-scale model, the performance of the sensor on an actual structure is verified through monitoring data. According to the invention, by constructing an integrity performance verification system from a theoretical model to numerical simulation and then to a reduced scale model test and entity structure verification, multi-dimensional and progressive performance verification of the performance of the optical fiber strain sensor for highway infrastructure monitoring is realized.

A system is provided for dynamic analysis and verification of smart contracts. The system includes an autoencoder configured to preprocess smart contract code to reduce noise and highlight critical features; a capsule network configured to analyze the preprocessed smart contract code, capturing hierarchical relationships and dependencies within the code; a generative adversarial network (GAN) configured to generate optimal routing coefficients for the capsule network, enhancing the efficiency and accuracy of the analysis; and a blockchain-based platform for deploying and executing smart contracts, wherein the platform utilizes the capsule network to continuously monitor the smart contracts for anomalies during execution.

Methods and systems described herein may implement blockchain asset authentication. A verification system may generate an encryption key associated with a digital asset, wherein the digital asset is associated with a first entity. The verification system may sign the digital asset using the encryption key. The verification system may generate a first key and a second key based on the encryption key, wherein the first key and the second key are part of a set of multi-party secret keys. The verification system may send the first key to the first entity and store the second key on the verification system. The verification system may receive a request to authenticate the digital asset. The verification system may in response to the request to authenticate, generate the encryption key based on the first key and the second key. The verification system may authenticate the digital asset based on the recreated first secret.

A neural-symbolic hybrid system for generating binary document formats directly from natural language input comprises a binary-aware hierarchical tokenizer operating across four levels (binary bytes, structural elements, semantic content, and concepts), a constraint satisfaction engine with 64 parallel processing cores for enforcing structural integrity and mathematical consistency, format-specific processors for Excel, PowerPoint, PDF, and CAD documents, and a formal verification system generating mathematical proofs of correctness. The system includes custom AI Document Generation Processor (AIDGP) silicon spanning 600 mm2 with specialized cores providing 500 TOPS processing power. Performance characteristics include 99.7% structural accuracy, 100% format compliance, 15.3 second average generation time for complex documents, and distributed capacity of 1,000,000 documents per hour. The system eliminates intermediate conversion steps while maintaining semantic preservation through hardware-accelerated constraint satisfaction and formal verification engines ensuring structural integrity, format compliance, and security through AES-256 encryption and automated regulatory compliance across 25+ international standards.

A model verification system and associated method for employing a multi-party verification technique to verify machine learning models and generative AI systems. The models and associated systems can be deployed in an enterprise and require verification to ensure that cohorts are properly verifying the models and systems and evaluation to ensure that the models and systems operate responsibly and achieve intended outcomes. A dynamic, multi-stakeholder blinded verification process can be employed for the continuous verification and evaluation of machine learning models and the systems that use them. This helps promote unbiased, reproducible verification, evaluation and assessments by preventing potential biases from cohorts form part of the verification process.

The invention discloses a building fire-fighting automatic verification and evacuation path verification system based on a rule engine, and relates to the technical field of building fire-fighting intellectualization. Comprising the steps that a rule generation module analyzes a fire-fighting standard text and generates an executable rule set; the model analysis module is used for extracting component attributes and a spatial topological relation from the building information model; the real-time sensing module collects environment state data. The rule engine module matches the component attributes with the executable rule set to generate a first verification result; spatial topology and real-time sensing data are fused, the dynamic passing weight of each path segment is calculated, and an evacuation path network model is constructed. The path verification module verifies the safety of a path from a preset point to an exit based on the model, and generates a path verification result. And the result generation module outputs fire-fighting compliance data. According to the invention, through the dynamic optimal evacuation path planning from the static fire-fighting standard examination of the building design to the occurrence of the disaster, the guarantee capability and the emergency response efficiency of the building fire-fighting safety are improved.

The invention provides a chip design and verification system and method.The system comprises a tool chain integration and automation module, the tool chain integration and automation module is provided with a tool containerization unit and a multi-physics field collaborative optimization unit, and the tool containerization unit is used for containerizing and packaging an EDA tool into an independent functional unit; each EDA tool container comprises a complete runtime environment, a dependency library and a license; the multi-physics field collaborative optimization unit is used for acquiring design parameters of the chip and evaluating the performance of the chip design scheme; the system further comprises a chip particle heterogeneous integration module which is used for carrying out system modeling and layout planning on the chip according to the received chip design file and carrying out multi-physics field simulation on a chip model. The system further comprises a security and credibility verification module which is used for carrying out vulnerability detection and security analysis on the chip design file in a credible environment in the chip design process. The invention further provides a working method of the system. According to the invention, the problem of isolation of a chip design tool chain can be avoided.

The invention discloses a power system data integrity verification system based on a dynamic data block division mechanism and a block chain. The system comprises a data preprocessing module, a hash generation module, a block chain storage module and a verification processing module. The data preprocessing module divides original data into data blocks with dynamically adjustable sizes; the Hash generation module adopts an iterative Hash algorithm to generate a chain Hash structure and an integrity Hash abstract; the block chain storage module uploads the hash data to a block chain network through a smart contract; and the verification processing module outputs a verification result by recalculating and comparing the hash values. The system realizes efficient and reliable data integrity verification, and has the advantages of high storage efficiency, good verification precision and low system load.

To verify the identity and non-alteration of a document prepared in relation to a prescribed activity or operation by a qualified person in a certain site or organization in another site or organization.SOLUTION: A system according to claim 1, further comprising: a first device configured to execute a process of acquiring biometric information; and a second device configured to execute a process of performing biometric authentication using the biometric information and a process of determining whether or not a person authenticated as the principal is qualified to perform a predetermined activity or an operation, wherein the first device performs an authentication process on a document created in relation to the predetermined activity or the operation of the person determined to be qualified by the second device. The information processing apparatus further includes a third apparatus that further executes a process of creating a signature using the biometric information for signature of the individual and executes a process of registering the document and the signature created by the first apparatus in a first storage unit, and a fourth apparatus that executes a process of verifying correctness of a set of the document and the signature registered in the first storage unit of the third apparatus using a public key for verifying the signature.SELECTED DRAWING: Figure 1

The invention relates to the technical field of dangerous cargo management, in particular to an intelligent compliance verification system for dangerous cargo boxing operation. Comprising a data acquisition preprocessing unit; the law and regulation graph construction iteration unit is used for extracting a'law and regulation term number-verification dimension-constraint condition 'triple of the law and regulation in the dangerous cargo boxing field and introducing an improved three-dimensional dynamic weight conflict resolution algorithm according to the efficacy level, the release subject and the application range indexing; a multi-agent collaborative verification unit; a risk early warning report generation unit; and a man-machine cooperation closed loop unit. According to the method, the problems of lagging of laws and regulations and clause conflicts are solved by adopting triple extraction of'laws and regulations clause numbers-verification dimensions-constraint conditions', a three-dimensional dynamic weight conflict resolution algorithm based on laws and regulations effectiveness-scene matching degree-release time and a technical means of periodically optimizing weight parameters through a reinforcement learning model.

The invention discloses a VerilogA code automatic error correction method based on a classification error library and a large language model, and the method comprises the steps: constructing a classification system of the error types of VerilogA codes, starting from an MTJ device, carrying out the statistics of 84 common errors in the VerilogA codes of MTJ based on the system, and developing an automatic training sample generation system according to the 84 common errors; the method comprises the following steps: selecting a DeepSeek-R1-7B model as a basic model through a benchmark test, and carrying out fine tuning training by utilizing a classified error data set generated by scripting to form a special error correction model for the field. The processing process comprises the steps that VerilogA codes to be corrected are received, error types and reasons are positioned through a trained model, correction codes are generated, and verification of eight types of typical circuits is passed. An error classification-model training-simulation verification system is established, verification and error correction of VerilogA codes are achieved, and time and resources in the development process are saved.

The invention discloses a video monitoring and AI linkage intelligent alarm verification system, and particularly relates to the technical field of video analysis, which comprises the following steps: carrying out dual anomaly preliminary screening by using a flow field structure entropy and a signal track singular value ratio, eliminating environmental noise interference, and constructing a multi-mode normal state baseline; generating a multi-modal event report containing a spatio-temporal context, uploading the multi-modal event report to a cloud, inputting the multi-modal event report into a physical perception cross attention network, configuring a physical embedding vector into a query vector and configuring a visual embedding vector into a key vector and a value vector through an asymmetric feature fusion architecture, and performing multi-modal event report analysis; actively guiding the attention weight distribution of the model on the video picture by using the change trend of the physical parameters, and outputting a confidence score based on the weighted fusion feature; performing closed-loop parameter correction on the baseline model by utilizing online incremental learning based on a verification result; the problems of high false alarm rate caused by lack of physical logic constraints and poor anti-interference capability in a complex environment in traditional monitoring are effectively solved.

The invention discloses a false information intelligent detection and traceability method based on cross-modal consistency verification. The method specifically comprises the following steps: S1, multi-modal content feature extraction; s2, carrying out cross-modal consistency verification; s3, performing deep counterfeiting detection; s4, propagation anomaly detection; s5, checking knowledge enhancement facts; s6, information tracing and variation tracking; s7, comprehensive authenticity evaluation; s8, a model training strategy; a multi-task learning framework is adopted, and parameters of all modules are jointly optimized. According to the method, a multi-dimensional consistency verification system is constructed by fusing multi-source information such as video content, text semantics, a propagation network and an external knowledge base, and automatic identification, authenticity evaluation and information traceability of various false information are realized.

The invention provides a file operation control method and device, equipment and a storage medium, relates to the technical field of data processing, and is used for reducing security risks caused by tampering of an application file of a target process. The method comprises the following steps: in response to an access operation of a target process on a protected file, when a verification system is in a kernel mode, if it is determined that the target process is a trusted process, obtaining a preset Hash verification result; wherein the preset Hash verification result is a result of Hash verification performed on the target process, and the Hash verification result is used for representing the permission of the target process to execute the access operation on the protected file. And controlling the access operation of the target process on the protected file according to the preset Hash verification result.

The invention provides an e-commerce order efficient order checking system based on a hierarchical time wheel and an intelligent prediction model, and belongs to the field of artificial intelligence, and the system comprises a feature extraction module which extracts a multi-dimensional feature vector from e-commerce order data; the evaluation module is used for constructing a cascade decision tree architecture based on the multi-dimensional feature vectors; the prediction module is used for predicting the future order quantity based on the historical order quantity time sequence by adopting a long short-term memory network and an attention mechanism to obtain an order prediction value and prediction confidence; the scheduling control module is used for mapping the e-commerce orders to the corresponding levels of the layered time wheel according to the dynamic priority levels, triggering the execution of an order checking task, and dynamically adjusting the scheduling parameters and system resource configuration of the time wheel of each level according to the predicted future order quantity and the system state; and the strategy execution module is used for collecting system performance indexes, determining a system state through a double-layer judgment mechanism and executing a protection strategy.

The invention belongs to the field of network security, and relates to a method and a device for constructing a network security operating system, electronic equipment and a storage medium, and the method comprises the following steps: constructing an autonomously controllable improved microkernel infrastructure; based on the microkernel infrastructure, constructing a full-stack layered security control computing architecture base; constructing intelligent agent components, and deploying a multi-intelligent agent collaborative protection component system; integrating trusted computing and an integrity measurement verification system; performing dynamic adaptation and execution of multiple security policies; and a standardized safety evaluation and adaptive optimization closed loop is established. A trusted computing base is cut from a design source, so that the probability of occurrence of high-risk vulnerabilities is reduced; the real-time defense that the threat is changed and the strategy is changed is realized, and the blind area of the static strategy in resisting the unknown threat is made up; the malicious codes can be blocked before running, and the post passive situation that traditional security software only depends on a feature library for searching and killing is broken; and the contradiction between security capability solidification and threat dynamic evolution is fundamentally solved.

The invention discloses an automatic driving planning method based on semantic scene flow and a verification system training method, and the method comprises the steps: inputting point cloud data corresponding to a plurality of continuous moments into a pre-trained unsupervised joint network, and obtaining a dynamic region in the point cloud data corresponding to each moment through a coarse level preprocessing module; all instances in the point cloud data corresponding to each moment are obtained; acquiring global geometric features and local geometric features of the point cloud data corresponding to each moment through a spatial-temporal feature extraction module; a semantic scene flow is obtained through a double-head task decoding module in combination with all examples corresponding to each point cloud data; and based on a dual-path planning mechanism, obtaining a first path planning result and / or a second path planning result according to the semantic scene flow, and further obtaining an automatic driving planning result. Based on a double-head task decoder and a double-path planning mechanism, high-precision perception and security decision of a dynamic environment are realized, and the controllability and security of path planning in a complex environment are effectively improved through a verification system.

The invention discloses a face quality label generation method based on cooperation of a multi-modal large model and a computer vision algorithm, and relates to the technical field of artificial intelligence and computer vision crossing, in particular to a face quality label generation method based on collaborative decision making of the multi-modal large model and the computer vision algorithm. The method is especially suitable for a high-security-level identity verification system, an automatic identification photo auditing platform, a large-scale face registration pre-screening process, a living body detection front level and other scenes, and is used for carrying out fine-grained, interpretable and high-robustness quality evaluation and defect positioning on an input face image. The core problems of weak semantic understanding ability, unstable discrimination precision, rigid fusion strategy, poor scene adaptability and the like in the prior art are solved by constructing a four-level technical architecture of dimension decoupling, double-channel parallelism, dynamic confidence fusion and scene adaptive evaluation.

A QR Code Verification Engine provides a multi-layered security framework for generating, validating, and authenticating QR codes while preventing tampering, fraud, and unauthorized access. The system embeds a hidden security layer within the QR code using steganographic encoding or invisible watermarking techniques, ensuring detection of any modifications. The hidden layer is encrypted using asymmetric cryptography, allowing only an authorized verification system to extract and validate it. An AI-powered tamper detection module analyzes QR codes for anomalies, while cryptographic hash verification ensures integrity. The system employs biometric authentication, push notification approvals, and contextual security measures to enhance user verification. Dynamic QR codes with expiration rules prevent replay attacks. Secure offline verification allows authentication without network connectivity. The system integrates with financial platforms, web security tools, and real-time fraud detection mechanisms, ensuring a highly secure and scalable QR code validation framework for transactions, identity verification, and access control applications.

Systems, devices, and methods for aircraft in-flight entertainment (IFE) devices installation verification are disclosed herein. In some implementations, a verification system includes a computing device that can operably connect to multiple IFE devices and a reader device. Each IFE device can report its own stored identity to the computing device, and the computing device can determine the position of each IFE device based on a network topology-based network address assigned to each IFE device. The reader device can obtain and communicate, to the computing device, actual identities and expected installation positions of the IFE devices. The verification system can then compare, for each position, the actual identity, which indicates which IFE device should be installed in that position, against the reported stored identity, which indicates which IFE device has been installed in that position. The verification system can display, on a graphical user interface, the comparison.