127 results about "Research efficiency" patented technology

The invention relates to the technical field of medical data management, in particular to a medical data document classification and marking system which comprises a document structure analysis module, a semantic information identification module, a classification and marking module and a document intelligent label module. According to the method, document visualization and retrieval efficiency is improved by analyzing document content and extracting titles, texts and appendixes, analytic performance and operability of data are enhanced by identifying key information and semantic relations and accurately extracting and labeling medical terms, medicine research data and medical record records, storage is optimized according to priorities in combination with classification and marking, and the method is high in practicability and easy to popularize and use. Clinical values and application scenes of documents are clarified, document management processes are refined, management compatible with clinical data formats is formed through structured storage of marked data and classification label generation, storage normalization and retrieval efficiency are improved, the requirement for accurate information calling in clinical tests is met, document management capacity is improved, and the document management efficiency is improved. And support is provided for improvement of clinical decision-making and research efficiency.

The embodiment of the invention discloses a life omics research method and device based on artificial intelligence, and the method comprises the steps: carrying out the preprocessing of a project according to the intelligent interaction between a user and a system, and generating standardized data; and meanwhile, carrying out transfer learning on the large language model to construct a life science large language model. And according to the standardized data, decomposing a research target by adopting a life science big language model in cooperation with an intelligent agent, and generating an analysis plan. And based on the analysis plan, the intelligent agent is scheduled through the coordinator, and a hierarchical task is generated. And calling a multi-omics analysis tool by the intelligent agent to calculate and analyze the grading task, and outputting an analysis result. And based on data features, integrating analysis results through an integrated advanced model, and outputting a final report to complete the research of life omics. According to the embodiment of the invention, full-process automation and natural language interaction are realized, the standardization of data analysis and the repeatability of results are ensured, the research efficiency is remarkably improved, and the technical threshold is reduced.

The invention discloses an automatic scientific research method and system, and the method comprises the steps: generating a paper outline based on the obtained existing research literature through the first function of a scientific research agent; based on the obtained existing research literature and the thesis outline, generating an experimental design scheme of the thesis by using a second function of a scientific research agent; obtaining an experiment result according to the experiment design scheme of the thesis; on the basis of the obtained existing research literature, the thesis outline, the experiment design scheme of the thesis and the experiment result, generating a complete thesis by utilizing a third function of a scientific research intelligent agent; and optimizing the complete paper according to the review opinions to obtain a new paper meeting a preset standard. According to the method, through deep integration of a large language model, semantic retrieval, code generation, simulation review and other technologies, the whole process independence from topic selection to paper completion is realized, the scientific research efficiency and the result quality are remarkably improved, and a foundation is laid for a scientific research normal form driven by artificial intelligence.

The invention provides a medical literature intelligent processing and analysis system and method based on a large model and a terminal.The method comprises the steps that firstly, a query request of a user is obtained through a user search interface, then the large model is called for user intention recognition, related biological entities are extracted, and a corresponding logic chain instruction is generated; matching background information of related entities in a pre-constructed biological entity library according to the extracted biological entities; matching in a literature abstract knowledge graph database according to the logic chain instruction to obtain a correlation sequence of the literatures; and finally, integrating the logic chain instruction, the biological entity background information and the related literature information to generate and display a corresponding query result. According to the method, the problems of tedious document acquisition, time-consuming reading, complicated analysis and the like faced by medicine researchers are solved, intelligent document processing and analysis are performed by adopting a method based on a large model, the document reading process is accelerated, the manual analysis cost is reduced, and the research efficiency is improved.

The invention provides a quantum anomalous Hall insulator aging number determination method and system based on topological defects, computer equipment, a storage medium and a program product. The method comprises the steps that the topological charge of each topological defect of two belt models is determined; determining the contribution of the corresponding topological charge to the aging number so as to determine the aging number of the valence band or the conduction band; fourier transform is carried out on the Hamiltonian to obtain a tight constraint Hamiltonian in a real space; performing one-dimensional Fourier transform on the tightly bound Hamiltonian in the real space to obtain a one-dimensional effective Hamiltonian; judging whether the number of the energy-gap-free edge states is equal to the absolute value of the conduction band aging number or not; if so, taking the number of the edge states without the energy gap as the aging number of the quantum abnormal Hall insulator; and if not, reconstructing the Hamiltonian of the two-band model and the expression of the component x and the component y of the Hamiltonian with respect to the two-dimensional momentum, and calculating the momentum again. According to the method, a large number of high aging models can be constructed, and the research efficiency is improved.

The invention discloses a method and a system for improving carbon dioxide mineralization and storage efficiency. The method comprises the following steps: building a microfluidic experiment platform integrated with an online CO2 mineralization and storage monitoring system; on a microfluidic experimental platform, simulating a formation temperature and pressure condition to carry out a CO2 mineralization corrosion experiment to obtain pore scale reaction kinetic parameters and a pore structure evolution rule; macromineralization efficiency data are obtained through an indoor physical simulation mineralization reaction experiment of the core scale; a CCM-GEM reaction flow numerical model is constructed; determining a Pareto optimal solution set by using a CMG-GEM reaction flow numerical model; and based on the pore scale reaction kinetic parameters, the pore structure evolution law, the macromineralization efficiency data and the Pareto optimal solution set, determining a CO2 mineralization storage efficiency improvement path of the target rock sample. According to the method, global sensitivity analysis and automatic optimization of multiple parameters are rapidly completed, the research and development period is shortened, the economic cost and the time cost are reduced, and the research efficiency is improved.

The invention discloses a carbon nanotube mechanical property analysis method based on machine learning molecular dynamics, and relates to the technical field of carbon nanotube mechanical property analysis. The diameter, the length and the defect proportion serve as variables to construct a structure parameter library; the temperature and the strain rate serve as supplementary variables to establish a tensile model parameter library; carrying out molecular dynamics simulation analysis on tensile mechanical properties; drawing a stress-strain curve and extracting key parameters; establishing a parameter association library between the structural parameters and the mechanical properties by using a machine learning method; selecting a machine learning algorithm to predict mechanical properties; and extracting a function relationship through the trained machine learning model to establish a fitting function. Starting from the relationship between different diameters, lengths, defect proportions, temperatures and strain rates and the mechanical properties of the carbon nanotubes, the optimal structure parameters of the carbon nanotubes under specific conditions are obtained through machine learning, the calculation amount is greatly reduced, the experiment cost is saved while the effectiveness of the model is ensured, and the research efficiency is remarkably improved.

The invention relates to the technical field of high-performance computing and artificial intelligence crossing, and discloses a method for automatically generating a simulation computing task on a supercomputing platform, which comprises the following steps of: receiving a task demand of a user; performing semantic understanding and parameter extraction on the input by using a parameter dynamic analysis engine to generate a simulation parameter table; based on the simulation parameter table and the input format specification of the target simulation software, an executable parallel computing task script is automatically generated through a self-adaptive script generator; according to the real-time resource state and the task requirement of the supercomputing platform, a dynamic scheduling algorithm is adopted to distribute the task script to the optimal computing node; in the task execution process, the running state is monitored in real time, and when abnormity is detected, a fault-tolerant and self-repairing mechanism is triggered; by automatically generating the task script, the user parameter configuration time is saved, and the overall scientific research efficiency is improved by more than 30%; natural language input and zero code configuration are supported, and common scientific researchers can quickly master the method.

The invention provides an intelligent investment attraction target matching method and system based on an industrial chain atlas, and the method comprises the steps: extracting and structuring key elements from an investment attraction policy text through a natural language processing technology, and generating an investment attraction policy portrait; constructing an industrial chain knowledge graph including products, technologies, enterprise entities and multiple association relationships; taking the policy portrait as a query condition, performing multi-dimensional matching and reasoning in the map, and calculating the comprehensive matching degree of the potential target enterprise; generating a priority recommendation list and a matching analysis report according to the matching degree sequence; according to the method, an investment attraction policy is automatically analyzed and structured through a natural language processing technology, and automatic matching is performed by utilizing the constructed industrial chain knowledge graph, so that screening and comparison of massive global enterprise information can be instantly completed, the research working time is greatly shortened, the search range of investment attraction targets is greatly expanded, and the research efficiency is improved. Therefore, the working efficiency is improved.

The invention discloses an environmental chemistry research automation system and method based on a large language model, and relates to the technical field of environmental chemistry automatic research. The environmental chemistry research automation system based on the large language model comprises a key information extraction module, a structure generation and optimization module, an experiment scheme generation module, an experiment management module and a visual editing module. According to the method, full-automatic workflow from experimental design to data analysis is achieved, the research efficiency and accuracy are remarkably improved, through the method, complex scientific problems can be converted into understandable input of a language model, complex analysis and reasoning processes are completed through the model, and a physical and chemical calculation tool is combined, so that the research efficiency is improved. According to the method and the system, comprehensive simulation and calculation of a research object are realized, the degree of human participation is effectively reduced, subjective deviation caused by human decision is reduced, and scientific research becomes more systematized and accurate.

The invention discloses a network academic resource association selection optimization method driven by a knowledge graph, and the method comprises the steps: defining an ontology through a top-down method, and constructing a network academic resource association selection ontology through a seven-step method; preprocessing the network academic resources; identifying entities from the preprocessed network academic resources and determining a relationship between the entities to form a structured knowledge representation; integrating the identified entities and relationships into a knowledge graph, and storing the knowledge graph into a graph database Neo4j; carrying out resource association query and deep analysis by utilizing the constructed knowledge graph, wherein the analysis comprises statistical analysis, path analysis, key object analysis and clustering analysis; and according to the user feedback and the progress of the academic field, optimizing the knowledge graph and the association selection algorithm. According to the method, efficient knowledge graph construction and management, accurate resource association and recommendation, dynamic optimization and continuous improvement can be realized, and scientific research efficiency and knowledge innovation speed are remarkably improved.

The invention provides a scientific discovery intelligent system embedded with a scientific and technological text reverse reasoning mechanism, and relates to the technical field of data processing, and the system comprises a planning module which is used for extracting and clustering research problems, research methods and research limitations, and generating structured information; the storage module is used for forming a management knowledge base; the tool module is used for providing operation tools for the planning module, the storage module and the execution module; and the execution module is used for reasoning and optimizing a scientific discovery direction by combining a reverse reasoning mechanism based on the management knowledge base. The technical problems that in the prior art, an analysis result is limited by knowledge reserve and prejudice of experts, a current large model mainly depends on basic knowledge to conduct forward derivation, fusion of fine-grained knowledge is lacked, subjective dependence is high, and a reasoning path is single exist, the possible future research direction can be reversely deduced from existing research limitations, and the research efficiency is improved. And full-flow support of the scientific discovery process is realized, so that the accuracy of the reasoning direction is ensured.

The application discloses a crop gene function research scheme planning method based on an experimental reasoning chain and belongs to the technical field of scientific research experiment intelligent planning. In view of the problems of lack of experimental reasoning chain modeling, insufficient search and recommendation capacity and low experimental scheme planning precision in the prior art, the application constructs a gene research knowledge graph by extracting research hypothesis-experimental operation-result interpretation triplets from historical documents, receives user experimental information, generates single-step experimental recommendations based on semantic vector matching and graph traversal, simultaneously generates a multi-round experimental scheme set through multi-scenario search, standardization processing and multi-dimensional score sorting, realizes the automatic planning of the crop gene function research experimental scheme, and improves the research efficiency and scientificity.

The invention discloses a preparation method and application of a multi-material cell-loaded 3D scaffold, and the preparation method comprises the following steps: S1, preparing at least two kinds of printing ink; s2, various printing inks prepared in the step S1 are added into 3D printing equipment, and a 3D support is printed according to a designed model; the printing ink comprises a main material and a photoinitiator, the main material comprises one or a mixture of a photosensitive material and a non-photosensitive material, and at least one kind of printing ink further comprises a cell-loaded suspension. The processing and manufacturing efficiency and convenience can be improved, the manufacturing cost is reduced, meanwhile, dynamic culture and testing of the carrier cells are achieved, and the scientific research efficiency is improved.

The invention relates to the technical field of data auditing, in particular to a data auditing method applied to market research, which comprises the following steps of: 1, receiving business data sent by a server, and obtaining content data uploaded by a target user; 2, dividing research fields of market investigation according to the investigation direction and the investigation method; 3, preprocessing the obtained content data of the target user; 4, extracting data features, and constructing a multi-dimensional data auditing model; and 5, generating a questionnaire according to an audit result through the data manager, and uploading the questionnaire to the cloud processing terminal. According to the method, invalid data can be removed by preprocessing the obtained content data of the target user so as to improve the data quality, and research fields of market research are divided by determining the research direction and the investigation method, so that research standard indexes and index standard options of the research fields are conveniently formulated, a research standard library is formed, and the research efficiency is improved. And the investigation efficiency and the data accuracy are improved.

The invention discloses an intelligent financial engineering quantitative research and reproduction method and related components, and relates to the field of finance. The method comprises the following steps: firstly, determining a target workflow by combining a workflow template and meta-information extracted from a quantitative research document by an information extraction agent; when the target workflow is executed, the information extraction agent extracts quantitative calculation information from the document; the code agent generates a quantitative calculation code according to the quantitative calculation information and the data source information, and quantitative factor data is obtained after the quantitative calculation code is executed; performing quantitative back-testing on the quantitative factor data according to a back-testing tool corresponding to a back-testing method specified in the document to obtain a back-testing result; and the verification agent compares the back-test result with the quantitative research result in the document to obtain a quantitative research conclusion. The whole process of financial engineering quantitative research is automatically completed based on the large model agent, practitioners are enabled to concentrate on core work of quantitative design and strategy design, and the research efficiency of users is improved.

The invention discloses a crop gene function research scheme planning method based on an experimental reasoning chain, and belongs to the technical field of scientific research experiment intelligent planning. Aiming at the problems of lack of experimental reasoning chain modeling, insufficient retrieval and recommendation ability and low experimental scheme planning precision in the prior art, the method comprises the following steps: extracting a research hypothesis-experimental operation-result interpretation triple from historical literatures to construct a gene research knowledge graph; user experiment information is received, single-step experiment recommendation is generated based on semantic vector matching and graph traversal, meanwhile, a multi-round experiment scheme set is generated through multi-situation retrieval, standardized processing and multi-dimensional scoring sorting, automatic planning of crop gene function research experiment schemes is achieved, and research efficiency and scientificity are improved.

The invention discloses a spectrogram data management method based on laboratory equipment, and relates to the technical field of medical data management, and the method comprises the steps: constructing a topological graph through a graph theory method, describing the incidence relation between different target drugs, collecting the drug component data of a target drug sample through the laboratory equipment, in combination with a traditional Chinese medicine compatibility theory and a formula standard, edges and weights between different nodes are initialized, the relation between attributes of the nodes and the edges in the topological graph is adjusted by comparing with a medicine component database in an existing pharmaceutical standard, and finally the verified and optimized topological graph is stored as standardized spectrogram data. According to the method, the relationship among the medicine components is visualized through a graph theory method, and the edges and the weights of the edges among the nodes in the topological graph are generated in combination with the attributes and interaction of the medicine components, so that researchers can visually check the action relationship among the components, and the research efficiency is improved. And the problems of information isolation and difficult query in traditional experimental data management are reduced.

The invention relates to the technical field of artificial intelligence, and discloses a research report generation method, device and equipment and a storage medium, and the method comprises the steps: responding to an input research type subject, carrying out research step planning through a planning agent based on the research type subject, and obtaining a multi-step research plan with a logic progressive relationship, gradually searching in a search engine through a research agent based on the multi-step research plan to obtain research related information corresponding to each research step, and generating a research report corresponding to the research type subject according to the research related information corresponding to each research step; due to the fact that the multi-step research plan with the logic progressive relation is generated through cooperative work of the multiple agents and step-by-step searching is carried out in the search engine to generate the research report, intelligent planning of research report generation is achieved, and then the research efficiency and the knowledge integration capacity are improved.

The invention discloses a machine learning-based isowurtzitane cage compound reaction substrate prediction method, which comprises the following steps: establishing a database containing condensation reactions of glyoxal and primary amine reaction substrates, marking the condensation reaction of which the product is an isowurtzitane cage compound as 1, and marking the condensation reaction of which the product is other types of compounds as 0; the method comprises the following steps: performing quantum chemistry calculation on primary amine reaction substrates, collecting descriptors describing chemical information, screening feature descriptors, and performing normalization processing; taking the feature descriptor as an input variable, taking a condensation reaction product marking result as an output variable, and selecting a random forest and a factorization machine to carry out weight distribution to construct an optimal fusion model; and performing prediction by using the optimal fusion model. According to the method, the reactivity of the primary amine reaction substrate can be quickly and accurately predicted, the research efficiency is improved, the experiment cost is reduced, and effective guidance is provided for synthesis of the isowurtzitane cage compound.

The invention relates to the technical field of subject hot spot monitoring, and discloses a subject hot spot dynamic monitoring method and system, and the monitoring method comprises the following steps: S1, determining a monitoring target and a monitoring range, determining a subject field needing to be monitored and a specific direction, carrying out the data collection, carrying out the preprocessing of the collected data, and carrying out the processing of the collected data; carrying out format unification and standardization processing on data from different sources; based on the big data operation and maintenance technology, the subject hot spot dynamic state can be monitored in real time, the real-time performance and accuracy of the data are ensured, the collected data can be efficiently processed and analyzed through the big data analysis and mining technology, valuable information and insight are extracted, the research direction is grasped, and the research efficiency is improved. The big data operation and maintenance system can collect data from various sources, ensures comprehensive coverage of subject hotspot dynamics, can accurately predict the subject hotspot dynamics through big data analysis and a machine learning algorithm, and provides a basis for scientific research and decision making.

The invention relates to an intelligent auxiliary method, system and device for scientific research and innovation topic selection, and the method comprises the steps: obtaining scientific and technological literatures, processing the scientific and technological literatures, carrying out the keyword extraction of a preprocessed data set through a TextRank algorithm, and carrying out the classification of the scientific and technological literatures, such as papers / patent standards, according to the keywords. And then calculating the number of science and technology literatures such as papers / patent standards under each category, performing scoring according to the number to obtain a hot word and new word list, obtaining a recent hot theme list according to the hot word and new word list, displaying the list to a user, and intelligently assisting the user to perform scientific research innovation topic selection. According to the method, the auxiliary decision-making effect of artificial intelligence and a big data technology in scientific research topic selection is exerted, the topic with the most potential and prospect is rapidly screened out from massive scientific research literatures, data and trends, scientific research personnel and innovation teams can select the research direction in a more targeted mode, blind exploration is avoided, and the research efficiency is improved. And scientific and technological innovation efficiency and achievement quality are improved.

The invention discloses a method for researching the corrosion resistance behavior of zinc alloy based on a first principle. The method comprises the following steps: firstly, retrieving a zinc primitive cell model from a material database and carrying out structure optimization; performing crystal face cutting, cell expansion and re-structure optimization to obtain a zinc plate model; then aluminum atom random replacement doping processing is carried out, and optimization is carried out to obtain a doping model; performing static self-consistent calculation to obtain surface energy, and screening out the most stable doping model; fixing two layers of atoms at the bottom of the most stable doping model, performing chloride ion adsorption calculation and structure optimization, and calculating adsorption energy to determine a most stable adsorption site; and finally, carrying out electronic structure calculation of state density and a work function, and representing the corrosion resistance of the zinc alloy. According to the method, a zinc alloy corrosion micromechanism is deeply analyzed, theoretical guidance is provided for component optimization and corrosion resistance improvement, and compared with a traditional experimental method, the research and development cost and time are remarkably reduced, the research efficiency is improved, and the method has important theoretical and practical application value.

The invention relates to an academic hotspot analysis system, which comprises the following steps: acquiring target field information of a plurality of to-be-analyzed literatures in a target field by utilizing a literature data extraction module, acquiring literature data according to the target field information, analyzing a literature publishing trend by utilizing a literature publishing trend display module, and generating a literature publishing trend interface, the method comprises the following steps: realizing visualization of a document publishing trend, analyzing the occurrence time and frequency of each keyword by utilizing a keyword trend display module, and generating a keyword trend interface for displaying a development trend of a research hotspot; the publishing unit display module is used for calling a preset map API to convert publishing unit names in the literature data into latitude and longitude coordinates, and thermodynamic diagrams of all publishing units are generated according to the latitude and longitude coordinates, so that academic research hotspots, development trends and regional popularity can be visually displayed, scientific research layout is facilitated, academic research efficiency and quality are improved, and the method is suitable for popularization and application. And development of academic research is promoted.

The invention provides a multi-agent-based user interaction method and device, equipment and a medium. The method comprises the following steps: executing an interactive dialogue operation on user equipment through an interview dominant agent to obtain interactive dialogue data; generating a corresponding interview task chain through the interview dominant agent according to the interactive dialogue data; the interview task chain comprises a first interview task, a second interview task, a third interview task and a fourth interview task; for the first interview task, obtaining target user interaction information through a data mining agent; for the second interview task, constructing a user sample library for interview through a data mining agent; generating a plurality of interview object agents based on the user sample library; for a third interview task, obtaining answer deep information through an interview expert agent; and for the fourth interview task, generating a structured interaction content through the interview expert agent according to the answer deep information. Therefore, the investigation efficiency and the investigation depth are greatly improved.

The invention discloses a clinical test ethical examination system which comprises a submission application end, an examination process management end, a file management end, an examination cooperation end, an examination recording and tracking end, a notification and reminding end, an ethical examination report generation end, a data analysis and statistics end and a privacy and security end which are in data communication through a private network and a private line network. The clinical test ethical examination system aims at simplifying and optimizing management and processes of ethical examination, researchers can more effectively manage and track the ethical examination process through the clinical test ethical examination system, it is ensured that tests meet ethical principles and related regulation requirements, the rights and interests of test participants are protected, and the clinical test ethical examination system has the advantages that the research efficiency is improved, and the research cost is reduced. And the proceeding and development of scientific research are promoted.

The application relates to the technical field of artificial intelligence, and discloses a research report generation method, device, equipment and storage medium, the method comprising: in response to an input research topic, planning an agent to plan research steps based on the research topic, obtaining a multi-step research plan with a logical progression relationship, and based on the multi-step research plan, gradually searching in a search engine by a research agent to obtain research-related information corresponding to each research step, and generating a research report corresponding to the research topic according to the research-related information corresponding to each research step. In the application, multi-agents work together to generate a multi-step research plan with a logical progression relationship and gradually search in a search engine to generate a research report, thereby realizing intelligent planning of research report generation and improving research efficiency and knowledge integration capability.

The invention discloses a method and system for synchronously detecting host chromatin openness and in-vivo microbiome based on transposase, and belongs to the technical field of biological sequencing data analysis. According to the method, transposase is used for selectively fragmenting an open chromatin region of a host, and a microbial genome is almost randomly cut, so that synchronous enrichment of host and microbial DNA is realized; after high-throughput sequencing library construction and double-end sequencing, sequencing data is split into host source and non-host source reads through bioinformatics analysis, host chromatin state and microorganism composition are analyzed respectively, and a microorganism-host epigenetic regulation network is constructed; the invention further provides a matched DNA sequencing library and an analysis system, multi-scene research of infectious diseases, intestinal microecology, tumor microenvironment and the like is supported, a public database can be reanalyzed, and potential microbial interaction signals are mined. According to the method, the host-microorganism interaction research efficiency is remarkably improved, and a high-sensitivity and integrated technical scheme is provided for epigenetic regulation mechanism analysis.

This invention discloses a visual analysis method for identifying media bias in large-scale news sources, comprising the following steps: Step 1, constructing a data corpus based on the Global Open News Dataset (GDELT); Step 2, constructing time-series encoding and dimensionality reduction representation of reporting features based on related reports from large-scale media sources; Step 3, constructing hierarchical media cluster visualization results; Step 4, generating visualization results of media reporting differences on different event types based on representative media selected by the user; Step 5, constructing the event development context of related news reports by selected media on specific topics; Step 6, allowing users to interactively compare and analyze the continuous evolution pattern of media bias in the development path of specific events based on the event development context. This invention provides users with an intuitive interactive platform to explore media bias identification results, reduces the workload of users reading and understanding news reports from different media sources, improves research efficiency, and helps users gain a deeper understanding of media bias.

The invention discloses a construction method of a rat deep vein thrombosis model, and relates to the technical field of animal models, and the key points of the technical scheme are that the construction method comprises the following steps: step 1) experimental animal selection; step 2) setting in groups; 3) preparing experimental materials and equipment; step 4) preparation before an experiment; 5) anesthesia and surgical operation; and 6) taking down the vascular clamp and closing the abdomen for disinfection. The invention provides a stable and clinically related rat deep vein thrombosis model, the repeatability and reliability of experiments are improved through accurate surgical operation, the experimental process is simplified, the research efficiency is improved, and a powerful experimental tool is provided for research and treatment of deep vein thrombosis.