38 results about "Research process" patented technology

The invention provides a causal algorithm-based plant nutrition management model construction method and system, and the method comprises the steps: collecting the historical planting data of a target plant, and determining and screening a plurality of key factors in plant nutrition management; constructing a causal relationship set among the plurality of key factors based on a causal relationship model; and training and correcting the causal relationship model by using the historical planting data to predict the nutritional status of the target plant under different conditions. According to the method, the model is constructed based on the causal relationship model, so that the optimal proportion and time scheme of plant nutrition is calculated, the fertilization guidance suggestions are generated, a user is helped to avoid the phenomenon that the model generation content does not conform to reality in the planting research process, the model illusion is reduced, and meanwhile the generalization ability of the model in a planting scene is improved. The method can be applied to planting industry model training, improves the accuracy of fertilization guidance, and can be used for agricultural machinery design guidance.

The invention discloses a research process planning method and device, electronic equipment and a readable storage medium, and relates to the technical field of scientific research, and the method comprises the steps: carrying out the understanding analysis of key research information, carrying out the article retrieval according to a determined search phrase, and obtaining a target article set, and determining a target research direction according to the key research information and the target article set after the structured hierarchical representation, and planning a research process based on the target research direction, so that the problem that the research process is difficult to carry out during literature review and research process planning in the professional technical field can be solved. The scientific research process planning method solves the technical problems that the scientific research process planning method depends on manual retrieval and analysis of researchers and has high professional quality requirements on the researchers, and the technical effects of improving the intelligence degree and efficiency of scientific research process planning, providing comprehensive and accurate research support for the researchers, accelerating the scientific research process and improving the scientific research efficiency and quality are achieved.

The embodiment of the invention provides an e-commerce product market research method and system based on artificial intelligence, and the method comprises the steps: S1, analyzing user input information, converting the information into structured data, and decomposing the structured data into a plurality of subtasks; s2, analyzing the requirements of the sub-tasks and the dependency relationship between the sub-tasks by using the large language model, and generating an investigation strategy; s3, calling the MCP tool according to the investigation strategy to generate preliminary investigation data; s4, evaluating the preliminary investigation and survey data, judging whether each subtask reaches an expected investigation and survey requirement or not, and obtaining an evaluation result; s5, judging whether the preliminary investigation data is sufficient or not according to the evaluation result; and S6, calling a special statistical MCP tool according to the research result, and generating a research report. According to the method, data sufficiency is guaranteed through dynamic evaluation and supplementary investigation through a large language model and an MCP tool, an investigation report is finally generated, the whole investigation process is intelligent, and efficiency and conclusion credibility are improved.

The invention discloses a scientific and technological achievement prediction and evaluation system based on big data, and relates to the technical field of scientific and technological achievement prediction and evaluation, and the system specifically comprises a research and development process data collection module, an information scientific and technological achievement prediction module, and an information scientific and technological achievement comprehensive evaluation module. Wherein the research and development process data collection module is used for collecting historical research data, feature data and network transmission performance data of scientific research projects in the research and development process in real time, and the information scientific and technological achievement prediction module is used for establishing a prediction model of the feature data of the scientific and technological achievement research process and setting research process state indexes based on the feature data. The LSTM prediction module is used for obtaining network transmission performance data in a stationary time range and screening out the network transmission performance data in the stationary time range for further training and optimizing the LSTM prediction model, and the information scientific and technological achievement comprehensive evaluation module is used for comprehensively evaluating the research process stability of the information scientific and technological achievements. And setting an information research fluctuation index to predict the stability of the research process.

The invention discloses an intelligent follow-up visit method and device for clinical test subjects, computer equipment and a storage medium. The method comprises the following steps: acquiring a clinical test scheme; generating a subject follow-up table according to the clinical test scheme; sending and updating a subject follow-up table according to the clinical test scheme; and carrying out detection and early warning on the updated subject follow-up table. By implementing the method, the research process can be optimized, the operation cost can be reduced, the clinical research quality can be improved, the internal communication efficiency can be enhanced, the test progress can be tracked in real time, and the problem can be quickly identified, so that the overall efficiency and quality can be improved.

The application relates to a multi-round scientific research workflow evaluation system and method for a multi-modal intelligent agent, and belongs to the technical field of large language models and multi-modal large models. The application comprises a multi-round task generation module, a multi-modal information processing module, and the like. The multi-round task generation module constructs a multi-round task scene closer to a real scientific research process. The multi-modal information processing module enables the measured intelligent agent to complete paper active retrieval, multi-modal evidence extraction alignment, cross-paper evidence integration, and round reuse of evidence. The protection points of the application are not limited to a single task sample or a single scoring index, but are focused on a multi-round evaluation benchmark constructed around a real scientific research workflow, a process-level evaluation protocol matched with the benchmark, and an overall implementation scheme supporting landing execution and fine-grained diagnosis of the benchmark.

This invention discloses a big data-based system for predicting and evaluating scientific and technological achievements, relating to the field of scientific and technological achievement prediction and evaluation technology. Specifically, it includes: a research and development process data collection module, an information technology achievement prediction module, and an information technology achievement comprehensive evaluation module. The research and development process data collection module collects historical research data, feature data, and network transmission performance data of scientific research projects in real time during the research and development process. The information technology achievement prediction module establishes a prediction model for the feature data of the research process of scientific and technological achievements, sets research process status indicators based on the feature data, and selects network transmission performance data within a stable time range for further training and optimization of the LSTM prediction model. The information technology achievement comprehensive evaluation module comprehensively evaluates the stability of the research process of information technology achievements by predicting real-time network transmission performance data and setting information research fluctuation indicators to predict the stability of the research process.

The invention belongs to the technical field of artificial intelligence, and discloses a knowledge service management method and device fusing generative AI and enhanced retrieval. Comprising the steps of constructing a knowledge base for multi-source heterogeneous data fusion, deploying a dynamic task planning engine, executing a whole-process service, establishing an evaluation and feedback closed loop and the like. Wherein the whole-process service covers AI knowledge questions and answers, AI enhanced retrieval, AI intelligent research and reading, AI auxiliary creation and intelligent agent service, and through intention recognition, mixed retrieval, RAG enhancement, cue word engineering, Deep Research and other technologies, the whole-process run-through from accurate knowledge acquisition and deep content understanding to generative creation is realized. The problems that in the prior art, knowledge obtaining efficiency is low, literature processing intellectualization is insufficient, and scientific research processes are split are solved, a credible, controllable, processized and intellectualized closed-loop knowledge service system is constructed, the efficiency and innovation ability of scientific research work are remarkably improved, and the system is suitable for various academic research and scientific research management scenes.

1. Name of the product of this design: Graphical User Interface for Application Management in the Product Research and Development Process of Electronic Devices. 2. Use of the product of this design: An electronic device. 3. Design key points of the product of this design: The part of the graphical user interface in the electronic device that is claimed for protection. 4. Picture or photo that best shows the design key points: Front view. 5. The electronic device is of a conventional design, and other views are omitted. 6. Use of the graphical user interface: The product interface is an interactive interface for application management in the product research and development process; it is used for application retrieval, construction, and release and deployment in the integrated product research and development process system; in the main view interface, after clicking "Continuous Integration" in the left navigation bar, the interface change status diagram 1 is displayed; in the interface change status diagram 1, after clicking "Application Management" under "Continuous Integration" in the left navigation bar, the interface change status diagram 2 is displayed; in the interface change status diagram 2, after entering the application code in the upper AppCode and clicking the "Query" button on the right, the interface change status diagram 3 is displayed; in the interface change status diagram 3, after clicking the "Build Now" button on the right side of the list, the interface change status diagram 4 is displayed; in the interface change status diagram 4, after clicking the "+" icon in the upper right corner of the list, the interface change status diagram 5 is displayed; in the interface change status diagram 5, after clicking the "Create Now" button at the bottom of the pop-up window, the interface change status diagrams 6, 7, 8, and 9 are displayed in sequence; in the interface change status diagram 9, when clicking the "Release Environment" drop-down box in the lower right corner, the interface change status diagram 10 is displayed; in the interface change status diagram 10, after selecting "DEV" in the drop-down box, the interface change status diagram 11 is displayed; in the interface change status diagram 11, after clicking the "Regular Release" button in the lower right corner, the interface change status diagram 12 is displayed; in the interface change status diagram 12, after scrolling the scroll wheel down to view, the interface change status diagram 13 is displayed; in the interface change status diagram 13, after clicking the "Deploy Now" button, the interface change status diagrams 14 and 15 are displayed in sequence; the content screen is within the gray area of the interface.

The invention relates to the technical field of medical education, and provides an informatization management system based on a medical conjunct nursing education platform, and the system comprises a user management module which is used for enabling nursing personnel and researchers in a medical conjunct to log in the system, carrying out the intelligent research, and distributing corresponding permissions according to different roles of users; the intelligent research module is used for creating a highly vivid clinical medical care space by using a VR technology, and combining the nursing research data with the generated medical care space through an AR technology; and the intelligent analysis module analyzes the research tendency and formulates a personalized research process line and a research mode by means of an AI algorithm according to the research performance and the evaluation effect of the nursing personnel. Resources are pushed in a targeted mode according to the research conditions of nursing personnel, waste is avoided, the resource utilization efficiency and the education return on investment rate are improved, the research route is updated in time according to new knowledge in the nursing field, the research route quality is improved, and the research route effect is evaluated and improved by integrating multi-dimensional data.

The invention provides a library subject service intelligent recommendation method and system based on big data mining, and relates to the technical field of library services.The method comprises the steps that firstly, library subject service big data is mined, and subject user research process features covering subject user research stages, resource use tracks and demand evolution features are constructed; and establishing a dynamic adaptation relationship between the research process and the resources in combination with a library subject resource pool. And splitting resource service modules according to research process stages to form staged subject resource service architectures, and generating a staged subject service recommendation list after series connection. And collecting user research process data in real time, dynamically adjusting a recommendation list, supplementing transition resources and services, and forming dynamic subject service recommendation contents. And finally, outputting recommended content and collecting feedback data, and integrating big data to optimize research process characteristics and dynamic adaptation relationships. According to the invention, accurate, dynamic and systematic library subject service recommendation can be provided for the user, and the service quality and the user research efficiency are improved.

The application discloses an error-driven adaptive research process rectification method and system, and relates to the technical field of natural language processing. The method comprises the following steps: decomposing a research task submitted by a user into a plurality of subtasks with a dependency relationship, and generating an initial directed acyclic graph (DAG); executing each subtask according to the DAG, and performing logical verification on an intermediate result to identify an error type; when an error is identified, mapping the error type to a rectification action; adjusting the DAG according to the rectification action, including deleting an error branch, reconstructing a node sequence or inserting a new node; repeatedly executing the process based on the updated DAG until a research completion condition is met, and generating a research report. The application realizes nonlinear re-planning through dynamic adjustment of the DAG, effectively avoids error accumulation, and improves the accuracy and reliability of a complex research task.

The utility model discloses a silage compacting device for an automatic test, and aims to solve the problem that no special experimental instrument for silage exists in the experimental research process of the silage. Comprising a tank body, a shell is clamped and embedded in the inner wall of the tank body, a wire passing pipe is fixedly arranged on the outer wall of the shell, clamping and embedding devices are evenly arranged on the outer wall of the shell, a telescopic device is arranged on the inner wall of the shell in a matched mode, a compaction device is arranged at one end of the telescopic device in a matched mode, and a connecting rod is arranged above the compaction device in a matched mode; according to the device, the research process of experimenters on the green feed is optimized, the experiment research process is more efficient, accurate in compaction and convenient to operate, the research process of the experimenters on the silage is optimized, the efficiency of the silage is improved, and meanwhile the quality of the silage is guaranteed.

A system and method for AI-mediated discovery, notification, and licensed access to copyrighted works during a research session. The system comprises: a content registry in which copyright holders register works and grant trusted read access to authorized AI tools; a trusted content ingestion module that reads the full text of registered works and generates internal representations including semantic embeddings, structural analysis, and portion-level summaries, and generates indexing information for the content registry; an AI research tool that draws on its comprehension of registered works to identify works relevant to a user's research query and present a non-disclosive notification describing relevance and pricing; a trust boundary enforced by technical and contractual controls preventing disclosure of protected content prior to authorized payment; a transaction processing layer that processes payment from the user to the copyright holder; and a content delivery module that delivers the authorized portion within the research session.

The invention relates to an interactive discussion platform construction method based on a knowledge graph, and belongs to the field of discussion. A task initiator constructs a research task framework; the research task framework and the research tasks in different fields are distributed to researchers in the corresponding fields; the researchers carry out association analysis on the received research tasks; obtaining an answer, generating a conclusion and reporting the conclusion to the task initiator; the task initiator performs primary examination and approval on each conclusion and sends a primary examination and approval result of each conclusion to summarizing personnel; after summarizing by the summarizing personnel, feeding back to the task initiator for secondary examination and approval; after secondary examination and approval, outputting a research report; according to the invention, standardization and intellectualization of the discussion process are realized, high-efficiency discussion communication is supported, and an effective conclusion is output.

The invention relates to the technical field of teenager teaching, in particular to a teenager scientific literacy improvement teaching system and method based on cross-domain exploration, and the system comprises an enrollment evaluation module, a teaching improvement module and a stage evaluation module. According to the invention, the traditional mode of introducing scientific conclusions into a classroom is converted into the mode of introducing scientific research processes into the classroom, so that students can develop, observe and propose good habits of problems, make hypotheses and design experiments based on the proposed problems, collect evidences and verify the hypotheses in the experiment process, and further think to make explanations when supporting the hypotheses. The method comprises the steps of obtaining a conclusion, sharing the conclusion, making deep thinking and proposing a new problem, and when the hypothesis is not supported, observing and collecting new evidence again and trying to make a new hypothesis, so that an active thinking thought can be gradually formed, and the own scientific literacy is gradually improved.

The invention discloses a project data processing method and system applied to a scientific research management system and a medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining a feature set corresponding to each piece of project data; calculating the feature weight of each feature vector in the feature set, which is linearly represented by other feature vectors, and obtaining a feature weight set formed by the feature weights of the feature vectors; constructing and forming a corresponding target set through feature weights which are not less than a preset value in the feature weight set; performing mapping on a target data matrix established by the target set by adopting PCA to obtain a construction data matrix formed by the feature construction set of each item data; calculating an abnormal score of each piece of data in the item data, and determining the data with the abnormal score not less than a threshold value as abnormal data; the data processing difficulty is reduced, residual data, abnormal data, repeated data and the like can be removed, related personnel can clearly know the scientific research process, and meanwhile the data processing aspect is more efficient.

The invention discloses a college scientific research process automation and intelligent decision-making system and method, and aims to solve the problem of college scientific research management. According to the method, various data such as scientific research achievements of teachers and student participation projects are collected through a multi-channel data interface, and a Bayesian probability model is used for cleaning and standardization processing. Data are stored by means of the block chain in combination with an RSA asymmetric encryption algorithm, and safety is guaranteed. And constructing a knowledge graph by applying a natural language processing technology and a Skip-gram model, and mining a scientific research relationship. And deeply analyzing data through a machine learning algorithm, and identifying project risks and opportunities. And personalized scientific research service recommendation is provided for teachers and students based on user preferences. A scientific research process is automatically generated and monitored, intelligent suggestions are provided for scientific research management decisions according to analysis results, resource allocation is optimized by integrating multiple factors, and intelligent and scientific development of scientific research management of colleges and universities is promoted.

This application provides a scientific research assistance system and method based on a large language model. The system provides basic data support and available knowledge base support for the system through the metadata layer and the basic computing layer, and provides customized experimental analysis and paper draft writing services for user input information through the experimental simulation layer and the paper generation layer; and in the process of generating the first draft of the paper, the basic computing layer, the experimental simulation layer and the paper generation layer iteratively feedback their respective output results based on the principle validity measurement index and the effect evaluation index, so as to fine-tune the model used by themselves according to the output results. In this way, based on the powerful information processing ability and tool calling ability of the large language model, the system gradually realizes in-depth discussion and rigorous reasoning of the paper from the bottom up through four functional modules according to user needs and heuristic strategies, and obtains a first draft of the paper that is scientific and authentic and meets the paper specifications, providing efficient and accurate scientific research assistance for the scientific research process.

The invention relates to an isomerization compiling method based on a mimicry system simulation platform, which comprises the following steps: a user uploads an application service source code file A in an operation page of the mimicry system simulation platform, and sends an http request to a mimicry isomerization compiling service; the mimicry isomerization compiling service firstly carries out preprocessing operation and parameter verification work; the mimicry isomerization compiling service analyzes parameters transmitted in the http request, matches a target architecture required by a user according to transmitted arcs parameters, and constructs directory parameters; the mimicry isomerization compiling service traverses a configuration parameter arcsarg array corresponding to the target architecture parameter, and corresponding makefile files are constructed in sequence; the mimicry isomerization compiling service stores a plurality of output heterogeneous simulation application service files to a specific directory Y; and returning the result to an operation page of the mimicry system simulation platform. The problem that a large number of physical resources are occupied in the scientific research process of the mimicry system is solved, research and development and verification work can be more conveniently carried out by researchers, and the research and development cost is saved.

The embodiment of the invention provides a consensus decision-making method and device, equipment and a program product. The method comprises the following steps: sending an initial questionnaire to each expert according to input information of a user; the input information comprises mail addresses and questionnaire contents of all experts, performing consistency evaluation on the received opinions of all the experts, determining an updated questionnaire based on a large language model when the consistency is not achieved, sending the updated questionnaire to all the experts until the opinions of all the experts achieve the consistency, and obtaining a consensus conclusion, in the consensus decision making process, the questionnaire is automatically adjusted and updated through the large language model, the accuracy of the adjusted and updated questionnaire is improved, the needed time is shortened, and therefore the efficiency and accuracy of the whole research process are improved.

1. Name of the design product: process control comprehensive training system. 2. Use of the design product: teaching equipment for simulating common physical quantities in modern industrial production process and researching process control law. 3. Design points of the design product: in the shape and structure, composition of the product. 4. Picture or photo best indicating the design points: perspective view.

The invention relates to a method for generating a yeast core promoter sequence based on a potential diffusion model. The problems that in the prior art, a promoter sequence generation method is unstable in training, the quality of generated samples is low, and the calculation cost is high are solved. The method comprises the following steps: S1, collecting and preprocessing data; s2, sequence coding; s3, constructing a potential diffusion model; s4, performing model training; s5, generating a new promoter sequence; and S6, comparing the generated sequence with an original natural sequence. The method has the advantages that a potential diffusion model based on deep learning is trained by using an existing saccharomycetes core promoter sequence data set, so that the model learns and has the capability of generating a new saccharomycetes core promoter, high-quality and diversified saccharomycetes core promoter sequences are generated, and the defects that a traditional method is high in calculation cost and high in calculation efficiency are overcome. The generation speed is slow, and the quality of generated samples is poor. The biological experiment cost of the saccharomycetes promoter is reduced, the research process is accelerated, and the industrial fermentation optimization of the saccharomycetes is promoted.

The invention provides a blockchain-based platform for secure management and sharing of research data. It integrates modules for smart contract execution, decentralized data marketplaces, dynamic consent management, cross-chain interoperability, and advanced security features, including post-quantum cryptography and multi-signature authentication. The platform ensures data integrity, transparency, and compliance with evolving privacy regulations by automating research agreements, incentivizing participation through tokenomics, and enabling seamless multi-party collaborations. A decentralized reputation scoring system and comprehensive version control enhance accountability and traceability of research activities. Additionally, the platform supports data anonymization and dynamic consent updates, safeguarding participant privacy while fostering collaborative research. By leveraging AI-driven analysis and decentralized governance through a DAO model, the invention optimizes research processes, facilitates efficient data exchange, and promotes ethical standards in research environments, offering a robust and innovative solution to the challenges of modern research data management.

The application discloses a clinical test subject intelligent follow-up method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a clinical test scheme; generating a subject follow-up table according to the clinical test scheme; sending and updating the subject follow-up table according to the clinical test scheme; and detecting and warning the updated subject follow-up table. The method of the application can optimize the research process, reduce the operation cost, improve the clinical research quality, enhance the internal communication efficiency, track the test progress in real time, quickly identify problems, and thus improve the overall efficiency and quality.

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 invention discloses a ship demand automatic generation and difference adaptation method and system based on a historical demand template library, and the method comprises the steps: building a hierarchical and classified historical template library (comprising a universal template, a professional template and a subitem template), receiving the natural language input of a user, and carrying out the automatic generation and difference adaptation of the ship demand. Analyzing and extracting demand elements by using a natural language processing technology (such as a BERT model); calculating a semantic, parameter and context matching degree with a template library through a multi-dimensional matching function, and screening candidate templates; starting a research process (including automatic query of an external knowledge base and manual confirmation) based on difference analysis, and dynamically adjusting the template (such as parameter calibration and entry addition and deletion); and carrying out association verification on the generated demand draft and the ship design model, and finally outputting a customized document and updating a template library to realize self-evolution. The method solves the problems that a traditional method is low in efficiency and poor in adaptability, the automation degree and accuracy of demand generation are remarkably improved, and the method is suitable for demand customization design of various ship projects.

The application provides a method for predicting the aggregation structure of layered minerals based on density functional theory, adopts the density functional theory in the first principle, constructs a layered mineral cell model and an inhibitor molecule model by using Material Studio quantum simulation software, and cuts the cell model; the structure of the inhibitor molecule and the layered mineral cell is optimized by a CASTEP module, and the adsorption energy of the inhibitor molecule on the edge and the surface of the layered mineral is calculated, the aggregation structure of the inhibitor molecule to the layered mineral is predicted according to the adsorption energy data; finally, the prediction result is verified by a cryo-EM, and a basis is provided for further optimization. The adsorption energy of the layered mineral is calculated based on the density functional theory, the aggregation structure between the layered minerals can be quickly predicted; the application is beneficial to understanding the aggregation structure of the layered minerals from the atomic level, so that more efficient flotation reagents and optimized flotation processes can be designed, and the experimental cost in the research process is reduced.

We provide the system. [Solution] Means of collecting research information, A means of analyzing collected research information using natural language processing technology, A means of proposing a research process to the user based on the analyzed results, A means of providing learning materials to support the improvement of expertise for new users, A means of notifying expert users of the latest research results and technological trends, A means of recording users' technical knowledge and thought processes, and accumulating knowledge within the organization, A system that includes this.