113 results about "Analysis tools" patented technology

The invention discloses a strategic recommendation method and device, and relates to the technical field of intelligence analysis tools, the method is applied to a computer device capable of calling a knowledge base and a large model, and the method comprises the following steps: retrieving an obtained text fragment based on an input request of a user; based on the input request, calling a large model to carry out site analysis on the input request to obtain a site analysis result; based on the input request, the text fragment and the standing analysis result, calling the large model to combine with the text fragment to perform qualitative analysis on the standing analysis result, and outputting a qualitative analysis result; based on the input request and the qualitative analysis result of the dictionary format, determining an optimal feature vector of the dictionary format by using an analytic hierarchy process; and on the basis of the optimal feature vector, four-quadrant analysis data of each strategy is calculated by using a four-quadrant analysis method, and then optimal strategy pushing is completed. According to the method, qualitative analysis, an analytic hierarchy process and a four-quadrant analysis method are combined, development strategic intelligence analysis is carried out according to requirements input by a user, and strategic suggestions are generated.

The application discloses a smart contract vulnerability detection method based on static analysis and large language model fusion, comprising the following steps: obtaining a smart contract source code to be detected, using a static analysis tool to analyze the pretreated smart contract source code, and generating a static analysis abstract; the smart contract source code and the static analysis abstract information are spliced according to a preset prompt template, and then input into a large language model to obtain a vulnerability detection result. The application effectively integrates the structured priori knowledge of static analysis into the input features, significantly improves the recognition ability of the model for seven core Solidity vulnerabilities, can accurately adapt to the classification task while maintaining the efficiency, and effectively prevents the false negatives, false positives and model security risks.

The application relates to an integrated circuit technology field, and discloses a delay prediction method and a computer readable storage medium. The method comprises the following steps: obtaining a to-be-calibrated circuit, and converting the to-be-calibrated circuit into graph structure data; calculating the to-be-calibrated circuit by using a timing analysis tool to determine a to-be-calibrated delay of the to-be-calibrated circuit; encoding the graph structure data corresponding to the to-be-calibrated circuit to determine a cell feature vector, a node feature matrix and an edge feature matrix; fusing the node feature matrix and the edge feature matrix by using a feature extraction model to obtain a fused node feature matrix; aggregating the fused node feature matrix to obtain a graph-level feature vector; integrating the cell feature vector and the graph-level feature vector to determine a context feature vector; splicing the context feature vector and the to-be-calibrated delay to determine a combined feature vector; performing residual prediction on the combined feature vector, and correcting the to-be-calibrated delay based on the predicted residual to obtain a calibrated delay.

The application discloses a multimodal intelligent interaction method based on a large language model, and the interaction method comprises the following steps: receiving multimodal input of a user; analyzing the user's intention, decomposing a complex task into multiple subtasks, and coordinating the execution of various professional tools; processing multiple types of input data; integrating various financial professional analysis tools and services; managing and maintaining the knowledge base of the system, dynamically updating and real-time searching knowledge; and providing the infrastructure required for system operation. Through automatic task decomposition and tool calling, the manual maintenance workload is reduced.

The application discloses a yield analysis tool evaluation method and device, and relates to the technical field of EDA. The method comprises the following steps: performing function testing on a yield analysis tool to be evaluated, obtaining a first test result, and obtaining a first evaluation result corresponding to the function testing based on the first test result and a standard function test result; performing performance testing on the yield analysis tool to be evaluated, obtaining a second test result, and obtaining a second evaluation result corresponding to the performance testing based on the second test result and a standard performance test result; obtaining a third evaluation result of the yield analysis tool to be evaluated by a user; and performing comprehensive evaluation on the yield analysis tool to be evaluated based on the first evaluation result, the second evaluation result and the third evaluation result. In the application, the function testing, the performance testing and the subjective evaluation of the user are comprehensively considered to comprehensively evaluate the yield analysis tool, the accuracy of the evaluation on the yield analysis tool is improved, and the accuracy and effectiveness of the yield analysis tool are ensured.

A system and method for end-to-end transaction management, for example, for a structured finance market. The system and method digitizes and deconstructs complex interconnected transaction documents. The system creates transparency around the complexities of the transactions, generating significant efficiencies for existing market participants and enabling access to previously hidden and / or inaccessible data. In some embodiments, the platform supports a selected ecosystem (compared to specific use-cases within a market vertical) with a seamless integration of frameworks and schemas for the organization and structure of provisions, analytical tools extracting the required data, and the creation of metrics to informatively assess and calibrate the market. The system advantageously creates a digital language providing a tool, which will further enable the digitization of the finance ecosystem.

The application discloses a population migration dynamic attribution assessment method and system for air pollution health risk, and belongs to the technical field of environmental health risk assessment and spatio-temporal big data analysis. The method firstly fuses multi-source spatio-temporal data and carries out standardization preprocessing; secondly, based on night light and built-up area statistical data, a provincial adaptive threshold algorithm is used to dynamically identify three types of spatial units, i.e. urban core area, expansion area and rural area; then, a "no migration" counterfactual population distribution scenario is constructed based on the population pattern in the base year; finally, the health risk in the real and counterfactual scenarios is calculated in parallel, and the net health risk caused by population migration is quantified by difference. The application effectively solves the exposure misclassification and attribution capability loss problems caused by the use of static population and fixed boundaries in the traditional assessment method, improves the spatio-temporal accuracy of the assessment and the calculability of the attribution result, and provides a standardized analysis tool for environmental health risk management.

The application discloses a wallet cleaning contract detection method and system based on an intermediate representation and a large language model, and solves the technical problem that the existing intelligent contract detection method based on supervised learning highly depends on labeled data support. On-chain lacks large-scale labeled data, the model cannot fully learn the core malicious features, and finally the detection effectiveness of the wallet cleaning contract is greatly reduced. The method comprises the following steps: constructing a contract intermediate representation according to the obtained contract address on the Ethereum chain through the Gigahorse intelligent contract analysis tool; carrying out fund transfer behavior identification and semantic recovery processing on a plurality of functions in the contract intermediate representation, obtaining the original contract function level fund behavior and the pre-check feature corresponding to each function; using the explicit routing distribution rule to preliminarily judge and filter the functions, obtaining the explicit distribution candidate function and the routing distribution candidate function; based on the explicit routing distribution prompt word, using a large language model to detect the two types of candidate functions, and outputting the wallet cleaning contract detection result.

We provide the system. [Solution] An input method for receiving commercial transaction requests from users, An information generation means that proposes product information based on a request obtained by the input means, A presentation means for presenting the aforementioned product information to the user and accepting their selection, An analytical tool that creates an order list based on user selections and makes additional suggestions, An ordering method in which an online order is completed after final confirmation of the aforementioned order list, Information processing means that converts input information into text using speech recognition, A system that includes this.

The present application belongs to the technical field of lead-based reactors, and particularly relates to a method for determining a flow blocking measuring point and a flow blocking assembly of a lead-based reactor core. The present application comprises the following steps: Step 1, obtaining a database required for model construction and program verification; Step 2, obtaining a database required for model optimization and program verification; Step 3, constructing a core-chamber coupling analysis tool for analyzing the thermal characteristics of the reactor after flow blocking; Step 4, based on the core-chamber coupling analysis tool, analyzing the cladding temperature after flow blocking of the core and the temperature field of the core outlet chamber; Step 5, based on the changes of the cladding temperature and the outlet chamber temperature field before and after flow blocking, determining a core outlet temperature measuring point arrangement scheme; Step 6, based on the temperature change of the flow blocking measuring point, determining the position of the core flow blocking assembly. The present application can help to reduce the number of core flow blocking measuring points on one hand, and effectively identify the position of the core flow blocking assembly on the other hand, which helps to ensure the long-term safe and stable operation of the reactor.

This invention provides a method for identifying polysaccharides from traditional Chinese medicine (TCM) based on multispectral fusion and machine learning, applicable to the rapid and non-destructive identification of polysaccharides from different types and origins. The method first uses infrared and Raman spectroscopy to acquire and construct a raw spectral dataset of TCM polysaccharide samples. The dataset is then preprocessed using standardization to eliminate noise, baseline drift, and other non-sample-related interferences. Effective spectral information is then filtered through feature extraction, followed by feature-level complementary fusion of the infrared and Raman spectral features. Based on the fused feature set, a machine learning classification model is constructed and trained using a cross-validation strategy to achieve accurate identification of the type and origin of TCM polysaccharides. Furthermore, the SHAP interpretability analysis tool is used to analyze the key spectral feature bands upon which the model's discrimination decisions rely, and to analyze the correlation between these key bands and specific functional groups and chemical bond vibrations in the TCM polysaccharide molecules, providing chemical mechanism support for the identification results.

The application relates to a large model iterator-based global optimization method for main circuit parameters of equipment, and belongs to the field of power electronic equipment design.The method comprises the following steps: generating an initial parameter set by a parameter generation LLM; performing feasibility grouping based on a feasibility flag; judging the domination relationship of data in the feasible solution pool; judging the front stability; and performing decision by the parameter optimization LLM according to a termination flag and a maximum number of iterations to obtain a final main circuit parameter set.The application can realize systematic optimization meeting physical constraints through cooperation of multiple external tools when the calculation capacity of a large model is limited.Through the construction of a closed-loop feedback iteration mechanism, the parameters are strictly checked according to physical boundaries by using a steady-state analysis tool, and the data are grouped according to the Pareto domination logic; meanwhile, the front stability judgment and the differentiated optimization strategy are introduced, so that the physical feasibility of the design scheme is ensured, and the globally optimal design considering the technical performance and the economic cost is realized.

This invention relates to the field of special education and rehabilitation technology, and particularly to a large-scale anti-hallucination model method and system for the education and rehabilitation of children with special needs, comprising: S1, fusing input data or instructions with context to construct a global state feature vector; S2, reasoning about and verifying the target action: if valid, calling knowledge retrieval or data analysis tools to obtain professional evidence and observation results and looping; if invalid, activating the automatic regression channel and switching to a preset template as a fallback output for each domain score; S3, accumulating the scores to obtain a total score and determining the developmental level, outputting a diagnostic report containing professional evidence constraints; S4, constructing a capability profile, extracting indicators of weak domains and interference parameters, weighting and quantifying them to obtain an intervention priority score; S5, reasoning progressively along the vertical logical chain according to priority, with downstream nodes embedding the feature constraints of upstream nodes, and outputting a personalized intervention plan.

We provide the system. [Solution] A data analysis tool for selecting the optimal mode of transport based on the geographical location and destination of the user of the mode of transport, A learning means for learning the user's preferences and reflecting them in the selection of the means of transport, A demand forecasting means for optimizing the arrangement of the aforementioned transport means, An instruction means for providing instructions to the transport means, A communication means for transmitting the operation information of the aforementioned means of transport to a user terminal in real time and requesting confirmation, The terminal includes a display means that allows the user to visually monitor the operating status, A system that includes this.

We provide the system. [Solution] An interface for receiving user inquiries in text format, A processing means for syntactically analyzing received text using natural language processing, A search method that uses keywords obtained through syntactic analysis to retrieve related information from a data structure, A response generation means that generates new information using artificial intelligence when relevant information cannot be obtained, A means of presentation for presenting generated information to the user, A payment analysis tool that analyzes electronic payment operations to identify information, A system that includes this.

The application relates to the biomedical technology field, in particular to a brain electrical power spectrum density feature extraction method based on music tonality function attributes, which comprises the following steps: acquiring brain electrical signals collected under long-section natural music stimulation; after pre-processing the brain electrical signals to remove noise and artifacts, performing window slicing operation on the pre-processed brain electrical signals based on tonality function attributes to obtain multiple brain electrical signal segments; extracting power spectrum density features in each brain electrical signal segment through a time-frequency analysis tool; and analyzing differences in brain electrical responses induced by different tonality function attributes based on the extracted power spectrum density features, so as to determine the weight of each tonality function attribute in the brain electrical signals. The method can solve the technical problem of the defect that the existing technology cannot quantize the weight of functions and chords in long-section natural music.

This invention discloses a semi-analytical method and system for calculating the stiffness and damping coefficients of foil gas dynamic bearings, relating to the field of air conditioning and clothing temperature control technology. It aims to address the shortcomings of traditional Reynolds equation methods in terms of accuracy and universality, as well as the low computational efficiency and mesh distortion issues of existing CFD methods. The method includes: constructing a fluid-structure interaction (FSI) computational model to calculate and obtain the static equilibrium position of the journal; applying an eccentricity perturbation at the static equilibrium position and performing an additional steady-state FSI calculation to obtain the four stiffness coefficients of the foil bearing using a first set of analytical formulas; applying small-amplitude simple harmonic vibrations along the x and y directions to the journal and performing two transient FSI calculations to obtain the four damping coefficients of the foil bearing using a second set of analytical formulas. This invention combines high accuracy and high computational efficiency, providing an efficient and reliable analytical tool for evaluating the dynamic characteristics of foil bearings and designing the stability of the rotor systems they support.

Disclosed in the present invention is a network and log intelligent management method, comprising the following steps: deploying a network monitoring tool and a log analysis tool in a target network; defining a network monitoring index, monitoring the target network in real time by means of the network monitoring tool, and acquiring log data by means of a log monitoring tool; performing fusion analysis on network monitoring information and the log data, and on the basis of the analysis result, determining whether the target network has had an anomaly; and defining an alarm mechanism, and issuing an alarm when the target network has had an anomaly. By implementing monitoring, the present invention can discover anomalies in a system and a network quickly, thus reducing the processing time, improving the availability and stability of the system and the network, and by means of monitoring, performing configuration and optimization on network resources; the present invention can identify and prevent potential problems by means of data analysis, and can perform fusion analysis on network monitoring information and log data, so as to further enhance the anomaly detection capability; and by means of establishing a robust monitoring and emergency alarm mechanism, the present invention can ensure continuity and stability of services.

An automated migration system based on static analysis and large model co-optimization includes: a source code indexing module, a static analysis module, a performance analysis module, a vector database module, a RAG code generation module, and an automated testing module connected in sequence. By combining the accuracy of static analysis tools with the semantic understanding and generation capabilities of large language models, this invention can significantly improve migration efficiency and ensure consistency in code semantics and performance.

The application belongs to the field of bioinformatics and relates to an RNA small molecule interaction prediction method based on a pre-trained large model. First, multi-modal feature extraction is performed by inputting an RNA single-dimensional sequence and a small molecule SMILES string to obtain sequence feature and molecular feature vectors. Second, cross-modal attention mechanism and adaptive gating network are used for distance-aware feature fusion. Third, a phased optimization mechanism is constructed to solve the calculation dependence on three-dimensional space data. Fourth, the fused features are input into a multi-layer perception network to infer and output the binary classification prediction probability of the target binding of RNA and small molecules. Finally, the self-learning attention weight is analyzed by reverse word segmentation mapping to output a sequence variation sensitivity evaluation report. The application realizes high-precision and high-explainable RNA small molecule interaction prediction and provides a calculation and analysis tool for high-throughput virtual screening of target RNA lead compounds.

We provide the system. [Solution] A means of human-machine interface for receiving voice input, A natural language processing means that converts received voice input into string data, Information analysis tools for acquiring fraud-related information and analyzing its risk level, Information provision means to provide users with the results of the analysis, An emotional analysis tool that analyzes the user's psychological state and provides appropriate feedback, Educational and training methods to provide simulations and educational content for fraud prevention, A system that includes this.

The present invention discloses a fluorescence in situ hybridization method for co-localization of multiple genes in shellfish hemocytes, belonging to the technical field of cell biology of marine invertebrates. By optimizing the osmotic pressure buffer system and the preparation method, the present invention can stably obtain a monolayer sample with complete and uniform cell morphology. By advancing the cell morphology imaging step, the complete morphological information of cells is obtained and fixed as a reference before implementing the stringent in situ hybridization process. The present invention can achieve in situ visualization of multiple target genes while better preserving the cell morphological structure, which helps to obtain more accurate and stable spatial distribution information of gene expression at the single-cell level, improves the overall reliability of the experiment, and provides a more effective analysis tool for the study of cell functions of marine invertebrates.

The application relates to the technical field of fuel cells, in particular to a generalized SOFC system energy flow calculation and visual analysis method and device, which comprises the following steps: inputting preset boundary conditions of a target generalized SOFC system, a steam reforming reaction degree parameter determined by experimental data and steady-state data into a thermodynamic calculation model, and outputting fluid components and material enthalpy values of each node of the target component; after detecting that the preset thermodynamic assumption is met, calculating actual heat exchange efficiencies of each heat exchanger, and then constructing a system energy flow distribution matrix based on the efficiencies and the component input and output enthalpy values, so as to determine a visual data structure and obtain a visual analysis result. According to the embodiment of the application, an analysis tool directly reflecting energy flow and distribution can be automatically generated according to experimental data, researchers can directly grasp the details of energy transmission and loss in the system, and the efficiency and accuracy of SOFC system research and development testing are improved.

This invention relates to the field of power system automation technology, specifically to a method for intelligent dispatching and analysis of customer power outages based on low-voltage topology AI perception. The method includes: S1, periodically running the first automation module to automatically query customer power outage event data in the electricity information collection system; S2, processing and intelligently analyzing the power outage data, accurately determining the fault range based on a five-level analysis logic of "single household - meter box - branch - transformer area - line," matching responsible persons, and generating formatted notification messages; S3, securely pushing the message to the external network via an internal / external network connectivity tool, automatically forwarding it to the corresponding responsible group; S4, collecting on-site power outage causes through online forms, and generating a decision report through multi-dimensional statistical analysis using AI analysis tools. This invention achieves minute-level automatic perception of customer power outages, accurate fault location, and proactive dispatching, reducing power outage discovery time by more than 90%, effectively promoting a fundamental shift in customer service models from "passive reporting" to "proactive intelligent emergency repair."

A system and method are provided for assessing potentially malicious data files. The method includes receiving a data file possessing one or more unknown security characteristics, and providing an interface for enabling automatic selection of at least one of a plurality of analysis tools to determine the one or more unknown security characteristics. The method includes automatically determining the selected at least one of the plurality of analysis tools to be applied to the received data file, and automatically providing the data file to each of the at least one selected analysis tool to have at least one corresponding analysis performed to determine one or more of the unknown security characteristics. The method includes receiving results generated by the at least one selected analysis tool, and aggregating and outputting the results in a review interface.

A method includes receiving, from a client device associated with an enterprise, information regarding software code, generating, via a large language model (LLM), a recommendation regarding the software code based on the information and a plurality of software library profiles, wherein each of the plurality of software library profiles is associated with a corresponding software library of a plurality of software libraries associated with the enterprise, and wherein each of the plurality of software library profiles indicates a corresponding key performance indicator (KPI) associated with usage of the corresponding software library, and providing, to the client device, the recommendation.

The application discloses a cell PD-L1 glycosylation in-situ visualization and biological function research method based on hybridization chain reaction. The application adopts a hybridization chain reaction strategy (HCR) of a logic "AND" gate activated by nucleic acid aptamer recognition and metabolic glycan labeling, and constructs a new method for a cell PD-L1 glycosylation in-situ visualization and biological function research method. Through HCR signal amplification induced by adjacent double recognition, the detection sensitivity of PD-L1 glycosylation on different cells is significantly improved, and subtle fluctuations in the PD-L1 glycosylation level can be accurately captured, so as to provide an analysis tool for revealing the dynamic changes under different physiological or pathological conditions. Meanwhile, the application first clarifies the immune regulation function of the PD-L1 glycosylation of dendritic cells, and further expands the research scope of tumor immune checkpoints.