30 results about "Research data" patented technology

This application discloses a method, equipment, medium, and product for comprehensive evaluation of equalization of basic medical services, relating to the field of medical geography. The method includes: spatial processing of research data to construct a unified geospatial database; calculating multiple evaluation index values ​​representing the spatial allocation level of medical resources and the spatial convenience of residents' access to medical care through spatial analysis to form an original decision matrix; using the entropy weight method, calculating the objective weights of each evaluation index based on the degree of variation of the multiple evaluation index values ​​across different evaluation areas; processing the original decision matrix using the objective weights based on the TOPSIS model to calculate the comprehensive evaluation index of equalization of basic medical services for each evaluation area; and performing spatial hierarchical mapping based on the comprehensive evaluation index of equalization of basic medical services to generate a multidimensional diagnostic report, thereby avoiding evaluation distortion, accurately reflecting residents' comprehensive employment opportunities in accessing medical services, and enhancing public credibility.

This invention proposes a method, system, and storage medium for constructing a Rorschach corpus for depression screening. It collects multimodal raw data related to the Rorschach test, and performs editing and preprocessing. A core data model is constructed to store the multimodal data and their relationships. Through a data entry and import module, the multimodal data is stored in the core data model. Through a data association and retrieval module, cross-modal relational queries and a unified view are provided. Through a data export and sharing module, the data is exported in a specified structured format. Through a deep learning model integration module, the multimodal data is used for predictive analysis and stored in the core data model. The method, system, and storage medium for constructing a Rorschach corpus for depression screening provided by this invention avoid the problems existing in current Rorschach test research data management, such as poor multimodal data correlation, difficult version management, low collaboration efficiency, non-standard metadata recording, and difficulty in supporting deep learning model training.

This invention provides a method, device, and storage medium for medical research target management based on big data. The method includes: establishing a collection association between collection units with the same sequence number and research targets; controlling the collection units to track and collect research targets with the collection association; when any collection unit is determined to be in a fuzzy tracking state at any collection time, determining whether there are other collection units in a fuzzy tracking state at that collection time; if so, determining the unit sequence number corresponding to each collection unit in a fuzzy tracking state as the target sequence number, and determining research targets with the same sequence number as the target sequence number as lost-association targets; controlling the collection units in the fuzzy tracking state to track and collect different lost-association targets; performing attitude analysis on each second collection video based on the attitude data of each lost-association target to determine the target sequence number of each lost-association target. This invention at least improves the accuracy of research data analysis.

The application discloses a kind of for educational research synthetic data generation and compliance sharing method and its device, its characteristics are that the method is by to a small amount of educational research seed data variable level structured analysis, combined conditional generation and scene generation mechanism, form the data set that can be used for educational research statistical analysis and reproduction experiment, realize the data production and compliance delivery that can be carried out educational research for researchers;Device includes: processor, memory and computer program stored in memory, realize the step of any one in the method.The application compared with corresponding technology has broken data barrier, realizes zero risk sharing, has stripped personal information, cooperates differential privacy and compliance package, so that originally unable to open sensitive educational research data can be risk-free in scientific research institutions circulation, support large-scale reproduction research and algorithm competition, provide standardized unbiased benchmark data for the fairness of education AI research, with good application prospect.

Provided in the present application are a multimodal research data recording method, and a system, a terminal and a storage medium. The method is applied to a multimodal research data entry system, wherein the multimodal research data entry system comprises a back-end module. The method comprises: on the basis of a current research unit protocol, receiving, by means of an input interface, multimodal research data collected by an input apparatus, wherein the multimodal research data comprises at least one of the following data forms: text data, voice data, image data and structured data; on the basis of a data field format specification, invoking the back-end module to perform structured processing on the multimodal research data, so as to generate a structured operation instruction; and on the basis of the research unit protocol, converting the structured operation instruction into a structured research record. The embodiments of the present application can reduce manual input time, improve experimental recording efficiency, and automatically identify and record multimodal research data. Moreover, errors can be corrected by means of conversational interaction, thereby ensuring data accuracy and consistency.

The application discloses a shallow sea heavy mineral sand mine resource exploration method and related equipment, and the method comprises the following steps: obtaining pre-research data of a target shallow sea area, predicting an exploration scheme based on the pre-research data, and arranging a bottom seismograph in the target shallow sea area based on the exploration scheme; collecting passive source micro-motion data by using the bottom seismograph, and extracting original data from the passive source micro-motion data based on a preset data quality standard; constructing a horizontal and vertical spectral ratio curve based on the original data, performing frequency spectrum separation on the horizontal and vertical spectral ratio curve, and obtaining a low-frequency curve of a bedrock resonance peak; constructing a palaeotopographic map through bedrock surface depth inversion based on the low-frequency curve; obtaining a regional geological model of the target shallow sea area, superimposing and analyzing the palaeotopographic map and the regional geological model, and obtaining an evaluation result of heavy sand mine resource potential. The application can effectively improve the exploration directivity and the accuracy of resource potential evaluation by identifying the change of ore-controlling landforms, and can be widely applied to the technical field of data processing.

The utility model provides a kind of rat weight-bearing climbing ladder resistance training device. The rat weight-bearing climbing ladder resistance training device includes bottom plate, the top of the bottom plate is fixedly installed with support column, the top of the support column is fixedly installed with cave-like cover, the outside of the cave-like cover is equipped with multiple bionic caves, the bottom of the cave-like cover is hingedly connected with multiple climbing ladders, the bottom of the climbing ladder is hingedly connected with placing plate, the placing plate is fixedly installed with vertical guide tube, the vertical guide tube is slidably installed with slide rod. The rat weight-bearing climbing ladder resistance training device provided by the utility model has the advantages of structural innovation and functional optimization, ensuring the reliability of scientific research data, while considering the convenience of operation and animal welfare requirements. The modular design concept reserves space for subsequent function expansion, and the standardized training environment provides professional tools for research in the fields of exercise physiology and neuroscience, with wide application prospects and scientific research value.

The present application relates to a kind of analog power supply driving system big impact load test system and method, belong to the field of vehicle reliability.The test system of the present application includes: engine and its auxiliary system, generator and power supply system, power load, inertia load, test bench, test system and shift mechanism.The present application is to the test of actual load under the working characteristic environment of all operating conditions of power supply driving system, focuses on the operating condition of big impact load to explore and research, finds the operating condition and magnitude of impact load that cannot be obtained by theoretical research, provides effective technical support for improving the solution of power supply driving system work reliability.The present application realizes the operating condition of big impact load under the working characteristic environment of all operating conditions of power supply driving system to explore and research, finds the research data that cannot be obtained by theoretical research, the present application can be applied in other armored vehicle power supply driving system research field.

The application provides a power scientific research data semantic retrieval method and system fused with a knowledge graph, and relates to the technical field of semantic retrieval.The method comprises the following steps: performing associated label identification on incremental power scientific research data to obtain a plurality of associated label sets; performing topological relationship reconstruction by taking a predefined knowledge associated attribute as an associated rule to generate a power scientific research knowledge graph; performing semantic analysis to generate explicit retrieval requirements and implicit retrieval requirements; performing extension associated indexing after executing bidirectional dynamic weighted screening to locate core entity nodes to obtain a primary retrieval result set; performing expansion correction to output a plurality of expansion associated results; generating a retrieval display priority sequence; and performing progressive visual screen display feedback.The application solves the technical problem that power scientific research data management and retrieval in the prior art mostly depend on traditional keyword retrieval and database query-based modes, cross-field comprehensive query is difficult to implement, and retrieval results are inaccurate.

The application discloses a kind of education experiment synthesis student intelligent agent construction method, system and electronic equipment, it is related to artificial intelligence education simulation field.The method includes: initialization configuration covers the multi-dimensional feature parameter set of cognitive ability, personality characteristics and knowledge state, and builds simulation environment including private reasoning channel;Double closed loop mechanism is introduced in simulation interaction: use in for consistency check closed loop, based on multi-dimensional feature matching or reward model, real-time correction "role deviation" behavior;With state dynamic evolution closed loop, combine positive cognitive gain, forgetting curve and "inherent characteristics-transient state" separation model, real-time update agent knowledge and psychological state;Synchronous generation includes the structured data set of behavior traceability label.The application solves the problem of behavior homogeneity and unexplainable in education simulation, and can generate high reliable and attribution ability scientific research data.

This invention relates to an intelligent research and study question-and-answer method and system based on a three-layer knowledge base and multi-layer retrieval enhancement, belonging to the fields of artificial intelligence, natural language processing, and scientific research knowledge service technology. The method includes: acquiring multi-source data from a research team; performing text extraction, OCR recognition, content cleaning, chapter recognition, and text segmentation on the multi-source data to obtain standardized text data; constructing a three-layer knowledge base based on the standardized text data, consisting of a summary index layer, a structured information layer, and a text block layer; querying and rewriting user research and study questions and recalling multi-layer candidate evidence, and obtaining a final context set through deduplication and re-sorting; generating research and study question-and-answer results based on user questions, the final context set, and evidence source information, and outputting source traceability information. This invention can improve the efficiency of scientific research data retrieval, question-and-answer generation, and knowledge reuse, and enhance the accuracy and traceability of question-and-answer results.

The application discloses a medical research data space-oriented data discovery and privacy computing cooperation method, device, medium and product; the method comprises the following steps: establishing a contract unique identifier for medical research data; opening data structure information of medical research data not containing real data entities to a data user; generating sample data corresponding to the medical research data, and providing the sample data to the data user after opening the data structure information; receiving a probe condition input by the data user on the sample data, and associating the probe condition to the contract unique identifier; converting the probe condition associated with the contract unique identifier into a data delivery range; after the contract takes effect, performing a real query operation on original real data corresponding to the medical research data according to the contract unique identifier and the data delivery range, obtaining real data results, and connecting the real data results to a data space privacy computing platform; and the safety of the medical research data is ensured.

The present application relates to the field of urban planning management, and more particularly to a multi-modal planning research data processing method and system based on street view analysis, in response to a street view analysis instruction for a planning research project, a planning semantic target associated with the project is issued to a mobile terminal; based on the issued result, the mobile terminal is used to execute acquisition of field collection data; the field collection data is acquired from the mobile terminal; according to the field collection data, the chain street view analysis result is associated and fused with the corresponding research track, multimedia data and attribute information according to the time stamp and positioning information; the processed data is visualized and displayed, including displaying the spatial distribution and statistical chart of the chain street view analysis result on an electronic map; based on the fused data, a structured data packet and a research report conforming to a preset format are generated and output. The pain points of scattered data and low efficiency of manual integration are solved.

This invention discloses a method and medium for quantitatively predicting the thickness of source rocks, comprising: establishing a multidimensional source rock identification index system based on multidimensional research data; defining favorable development facies zones of source rocks according to the source rock identification index system; within the defined favorable development facies zones, calibrating the seismic response of source rocks according to the determined source rock identification index system; combining the seismic response calibration with the source rock thickness to establish a quantitative prediction model for source rock thickness; and calculating the predicted source rock thickness using the quantitative prediction model. This invention integrates multidimensional research data into the establishment of the multidimensional source rock identification index system and the quantitative prediction model for source rock thickness, forming a complete technical closed loop. This effectively avoids the limitations of a single data source and, through the constraint of favorable development facies zones, ensures a high degree of consistency between the prediction results and geological laws, avoids purely mathematical prediction errors, and improves the accuracy and reliability of source rock thickness prediction.

The application belongs to the technical field of military research data management, and discloses a data right protection and contribution calculation system of a block chain, which comprises: an application layer, which is used for providing trusted military research data based on a block chain core layer to realize data evidence, whole-process operation tracing, multi-dimensional contribution calculation and auditing functions for a collaborative research and development scene; an enhanced component layer, which is used for providing management services, data scheduling, user access and security enhancement support for the application layer; a block chain core layer, which is used for providing block chain basic capabilities supporting multi-chain collaboration, high-throughput consensus, automatic execution of intelligent contracts, national secret level security protection and trusted node management; and an infrastructure layer, which provides computing, storage and network resources for the application layer, the enhanced component layer and the block chain core layer. The application realizes data right protection and contribution calculation by adopting block chain encryption algorithms, consensus mechanisms, distributed ledgers and intelligent contracts and other technologies.

The application discloses a kind of based on pre-training language model's fetal congenital heart disease diagnosis and treatment text generation method and system, it is related to fetal congenital heart disease diagnosis and treatment technical field.The method is by selecting biomedical field pre-training model, and further fine-tuning is carried out in fetal congenital heart disease field, while constructing the knowledge graph of fetal congenital heart disease, and using search enhancement generation technology real-time into generation process with professional knowledge.The direction of generation is guided by designing structured prompt word, and an expert verification and feedback mechanism is introduced for iterative optimization, and finally a high-quality, personalized simulation diagnosis and treatment text that meets clinical practice is generated.The application effectively solves the problem of professional, accuracy and logical consistency in medical text generation, and the generated text can be used for decision support, clinical teaching and research data enhancement, with high fidelity, personalization and real-time knowledge advantages.

This invention provides a method and system for the transformation of scientific research results based on a large-scale research model of birth defects in children. It relates to the field of computer application technology within bioinformatics. The method involves performing correlation mapping on input research data on birth defects, generating a cross-data source data correlation network using the large-scale research model, and performing research discovery mining processing accordingly. This generates a package of research discovery mining results, which are then screened for transformation potential. A transformation potential screening report is generated by combining relevant biological knowledge bases and clinical translation rules. Based on the transformation goals that meet the screening criteria, a scientific research result transformation plan is generated. Finally, a scientific research result transformation implementation link is established based on the transformation plan, generating a transformation implementation plan and matching transformation tasks with clinical research institutions and scientific validation platforms. This ensures the smooth implementation of scientific research result transformation and improves transformation efficiency and success rate.

The application is a slow landslide building vulnerability analysis method based on FLAC3D and PS-INSAR, including the following steps: S1, collecting the required research data; S2, obtaining the building disaster resistance capability evaluation index system and weight through literature research and expert scoring, and obtaining the building disaster resistance capability index calculation value R; S3, using PS-InSAR technology to calculate the cumulative displacement of the landslide at different locations, and according to the cumulative displacement value and the building disaster resistance capability index value R obtained in S2, the landslide disaster causing strength inversion value I is obtained by inversion p , and then the displacement-I p scatter plot fitting obtains the landslide disaster causing strength empirical curve; S4, using FLAC3D to simulate the cumulative displacement of the landslide under extreme conditions, and using the landslide disaster causing strength empirical curve to obtain the landslide disaster causing strength index calculation value I under extreme conditions; S5, using R and I to obtain the disaster body vulnerability under extreme conditions. The quantitative problems of building disaster resistance capability and landslide disaster causing strength are solved.

This utility model discloses a row-type rice transplanter for experimental fields. Several ground rails are arranged parallel to each other on the field ridges. The self-propelled frame has its own drive source and works with the ground rails to move along them. Two self-propelled frames are connected to both ends of the row frame, and each self-propelled frame can slide on the row frame to adjust the distance between the two self-propelled frames. The transplanter itself has a drive source and works with the row frame to move along it. This utility model can significantly shorten the transplanting cycle, reduce manual labor intensity and time costs, and reduce manual labor in high-temperature and high-intensity environments. It achieves full automation of the transplanting process, greatly improving the standardization of transplanting in experimental fields and the accuracy of scientific research data.

The application discloses an intelligent auxiliary system for medical scientific research training based on an artificial intelligence large model, and particularly relates to the field of artificial intelligence and scientific research data processing, and is used for solving the problems of multi-source dispersion, non-uniform structure, missing steps difficult to identify and dependence on manual verification of experimental records in the existing medical scientific research process; a digital experimental record file is constructed by image acquisition on an experimental table record carrier and in combination with target detection and text recognition, logical breakpoints are recognized based on numerical jump and semantic co-occurrence, and jump record recognition is realized by using phenotype feature distribution and optimal transport calculation; missing steps are further reasoned and completed by dynamic programming, and finally, a complete experimental process draft is generated in combination with a structured template, automatic analysis, abnormal identification, process completion and multi-modal data fusion processing of scientific research data are realized, and the intelligent level of experimental data processing and the standardization of the scientific research process are improved.

The application discloses a disease single cell AS detection marker panel construction method, device and system, and belongs to the field of database construction. Compared with a conventional database, the obtained marker panel is used for sequencing samples with different geographical sources on a plateau and a plain, so that dynamic changes of variable splicing driven by regional factors can be revealed, and defects of single data dimension and large deviation from a real scene of the conventional database can be made up. Secondly, cell type labels, barcodes and PSI matrices are integrated to construct a high-resolution variable splicing map, and cell heterogeneity and space-time expression patterns can be accurately captured. Finally, the AS marker panel obtained through differential screening and function annotation can provide more accurate, reliable and comprehensive research data for researchers.

A kind of agent system construction method and device based on prompt word enhancement and dynamic arrangement belong to electric power scientific research data management technical field, method includes based on prompt word reinforcement algorithm, specific unit, terminology, field for electric power industry are parallelly searched and semantic reconfiguration is carried out, eliminate the semantic gap between natural language input and bottom layer database mode, obtain the reinforcement prompt word corresponding to natural language query, and generate SQL matching bottom layer database;Introduce agent dynamic arrangement framework and state management mechanism, electric power scientific research data analysis task is decomposed into multiple agent nodes that can work cooperatively, and is dynamically arranged and managed by state machine;MCP is used as the standardized interface of agent and external resource interaction, and different sources of external resources are connected to the agent system in the form of plug-in, and the agent dynamic arrangement framework uniformly manages and schedules various external resources.The present application can improve the completion efficiency and success rate of query task.

The application discloses a kind of court information system-oriented data comprehensive performance evaluation method and system, belong to information measurement field, including: obtaining the court data set stored in court information system, and respectively calculating 12 types of information measurement indexes, realize court information system data comprehensive performance evaluation;Court data set includes: legal regulations data, judicial case data, judicial personnel data, judicial research data, judicial administrative data, external data and information management data;12 types of information measurement methods are: capacity, delay, breadth, granularity, variety, time length, sampling rate, aggregation degree, pervasion degree, distortion degree, mismatch degree and efficiency.The application can consider different types of data resources and service fields, realize the comprehensive and accurate measurement of court data, effectively solve the problem of previous evaluation being not comprehensive and inaccurate, and provide reliable quantitative basis for promoting digital court construction and judicial technology application.

This invention belongs to the fields of information management and artificial intelligence technology, and provides a machine learning-based intelligent assessment and control method for technology business risks. The method includes: acquiring textual data, numerical data, relational data, and third-party research data from the entire technology business process; extracting textual consistency features based on textual data; performing anomaly detection based on numerical data to extract funding anomaly features; constructing a knowledge graph from relational data to obtain expert conflict features; extracting achievement correlation features from third-party research data; inputting the above features into an integrated learning model to output risk probability values; implementing hierarchical control strategies based on the risk probability values; and using the control results as feedback data for incremental model training and updates. This invention enables intelligent risk identification, hierarchical control, and continuous optimization, improving the accuracy of risk identification and management efficiency.

The application discloses a production-study-research transformation intelligent decision support system and method based on multi-source data fusion, comprising a multi-source heterogeneous data acquisition module, a data preprocessing and standardization module, a multi-dimensional data fusion module, a production-study-research feature extraction and quantification module, a production-study-research transformation knowledge graph construction module, an intelligent decision analysis and scheme generation module, a decision execution feedback and model optimization module; the application realizes efficient processing and deep fusion of multi-source heterogeneous production-study-research data, breaks the data silos among colleges and universities, enterprises, governments and industries, eliminates the format and measurement differences of heterogeneous data through standardized processing, mines the correlation value among different data sources based on a scientific weighted fusion algorithm, and improves the overall utilization efficiency of production-study-research data.

This invention discloses a system and method for synergistic regulation of nitrous oxide emission reduction and soil nitrogen leaching in farmland, relating to the field of farmland nitrogen management technology. The method integrates meta-analysis and enhanced regression tree models. Through steps such as collecting relevant research data on biochar application, screening effective sample data, constructing a meta-analysis database, identifying key influencing factors, establishing mathematical quantitative relationships, constructing an enhanced regression tree model, and developing simulation optimization schemes, it achieves accurate prediction and synergistic regulation of N2O emissions and soil nitrogen leaching under different farmland conditions. This invention can quantify the relative importance of each influencing factor, dynamically generate quantitative and operable field management plans adapted to different production scenarios, and ensure the stability of emission reduction effects through long-term monitoring and dynamic feedback mechanisms. It promotes efficient nitrogen utilization and sustainable development in farmland, possesses broad application value, is easy to implement and promote in large-scale farmland, and provides a reliable path for effective greenhouse gas emission reduction.

The application provides a kind of intelligent data security situation awareness and management method and device based on multi-modal fusion, applied to data processing field.By collecting commercial transactions, contract, supply chain, financial and multi-modal business data of authority operation, configure acquisition node parameters and rely on standard interface and API gateway authentication to realize heterogeneous data security access;After format normalization, redundancy elimination and normalization preprocessing, multi-dimensional business features are extracted and special research data sets are generated;Integrative fusion strategy is constructed by combining business value, real-time, computing power allocation and compliance standards, and data set batch splitting and encrypted edge cloud transmission are completed according to scene;Adaptive dynamic weight algorithm is used to learn feature mapping relationship, optimize model parameters and dynamically adapt research rules, and finally output compliance awareness results and whole-process management scheme.

A digital honest broker system and method for managing patient specimens and data that links patients to their de-identified specimens and data across multiple studies and institutions is disclosed. The platform allows patients to access and engage with their data anytime after consenting, transforming informed consent into a dynamic, long-term membership. The system integrates with existing research protocols and infrastructure without requiring substantial changes. It enables scientists to find additional specimens from their patients and collaborate with other researchers studying the same individuals. Physicians can also locate their patients' specimens and fuse relevant research data from multiple siloed settings. By empowering patients and enabling data aggregation across institutions, the digital honest broker system increases trust, participation, and accelerates scientific discoveries in biomedical research.