9 results about "Taxonomic database" patented technology

A method for automatically assigning changed permissions for diagnostic purposes for work container instances is provided including: in a reconfiguration unit of a runtime environment of the device or an orchestration device, receiving configuration information for starting a container instance, identifying diagnostic configuration information for providing at least one diagnostic container instance of a diagnostic application that carries out diagnostic activities, retrieving existing work container instances from a classification database, determining a reconfiguration requirement of the retrieved work container instances, changing initial work configuration information to provide diagnostic data according to the diagnostic configuration information for each work container instance for which a reconfiguration requirement has been determined, restarting the changed work container instances according to the changed work configuration information, and starting the at least one diagnostic container instance of a diagnostic application according to the diagnostic configuration information.

The invention provides a spacecraft general assembly data fusion processing system and method, and the system comprises a dual-core architecture which comprises a general assembly cooperation model module and a knowledge-driven engine module; the hierarchical classification database is connected with the dual-core architecture; the version penetration management module is used for establishing a product version penetration management mechanism based on a preset code; and a rule verification engine for automatically verifying the data based on a preset rule. The method comprises the following steps: carrying out collaborative sharing and intelligent decision making through a dual-core architecture, storing spacecraft general assembly data into a hierarchical classification database for standardized storage, establishing a product version penetration management mechanism, and automatically checking the data based on a preset rule obtained from a knowledge-driven engine module. According to the method, the data normalization and accuracy can be remarkably improved, the full-life-cycle accurate tracing of the data is realized, and the cross-professional collaboration efficiency is improved.

The application discloses a method and system for homologous heterogeneous power grid topology mapping, and belongs to the technical field of power system simulation calculation. The method comprises the following steps: establishing a classification database according to a classification result; determining the mapping mode of homologous heterogeneous power grid equipment according to the type of power grid equipment and the modeling mode of power grid equipment; determining the unique power grid topology of the first-level network of the power grid network; determining the electrical data of the second-level network according to the power grid topology, and mapping the electrical data to the classification database; determining the primary equipment data of the third-level network according to the power grid topology, and mapping the equipment data to the classification database; for the external network, generating a supplementary file according to the power grid topology of the primary equipment connected by the external network, and mapping the supplementary file to the database. The application realizes the fusion of multi-source data.

The application discloses a method for detecting viruses and virus replication in media based on Small-RNA high-throughput sequencing. The application belongs to the technical field of virus detection, and the method for identifying virus types in a to-be-detected sample by Small-RNA sequencing developed by the application comprises the following steps: 1) extracting total RNA from a virus-infected to-be-detected sample, constructing a cDNA library, and separating small RNA sequence fragments from the cDNA library; 2) downloading virus sequences and classification databases from GenBank, and comparing the small RNA sequence fragments with virus sequence files; 3) comparing a contigs3 file with a virus nucleic acid database, selecting sequences with the minimum e value in the comparison results in the contigs3 file, calculating the coverage of the contigs3 sequences in corresponding virus genomes, distinguishing virus information with a coverage threshold, and deducing the virus source of the small RNA sequence.

The invention discloses a dynamic comprehensive monitoring platform for an artificial fish reef, which obtains ecological data such as fish varieties and water quality parameters in real time through a data acquisition module, ensures timeliness and continuity of the data, enables managers to master ecological dynamic states immediately, and overcomes the defect that the traditional method is difficult to know ecological changes in time. Meanwhile, a classification database construction module stores data in a multi-dimensional classification mode, regionalized reference data are formed, a dynamic monitoring and evaluation engine calculates an ecological benefit comprehensive index according to the data, multi-dimensional comprehensive evaluation can comprehensively and systematically reflect the ecological benefits of the artificial fish reef, and the problem that the evaluation index is single is solved; besides, the intelligent early warning and decision support module sets a safety threshold value, performs automatic early warning when indexes are abnormal, and generates a targeted and operable repair suggestion report, so that the platform can respond quickly, managers can take repair measures in time, ecological problem deterioration is avoided, and the problem that targeted repair cannot be performed in time is effectively solved.

The invention provides a full life cycle competency data acquisition and storage system based on observable behavior classification, and belongs to the technical field of personnel training evaluation. The system comprises a competency-OB classification analysis module used for performing multi-dimensional analysis on competency and observable behaviors to generate a structured classification framework; the multi-source data acquisition module is used for acquiring data from multiple systems in real time and automatically marking the data according to a structured classification framework; the special classification database cluster adopts a three-layer architecture to support efficient data processing; the data quality guarantee module is used for implementing verification in multiple links to guarantee data quality; the offline-online integrated module supports full-function offline evaluation and automatic account checking; the block chain evidence storage interface ensures that the evaluation record cannot be tampered; and the standardized API gateway provides an external system interface. The technical problems that traditional competency assessment data acquisition is low in structuralization degree, poor in cross-system interoperability, insufficient in data credibility and the like are solved, and the method can be widely applied to full-life-cycle training and assessment of high-risk occupational posts such as civil aviation and nuclear power.

The present application relates to the field of engineering surveying and mapping technology, in particular to an engineering surveying and mapping data intelligent acquisition, analysis and processing system and method, mainly applied to data acquisition, analysis and processing in the process of engineering construction; the system covers image acquisition, data classification, database storage, data processing, data analysis and decision feedback modules; the image acquisition module obtains an engineering surveying and mapping image feature set, the data classification module receives and classifies and stores the data; the database stores the classified data, the data processing module divides and calculates the importance of the image feature nodes; the data analysis module identifies abnormal data, and the decision and data feedback module receives the identification result and adjusts the data threshold; the system significantly improves the surveying and mapping precision through feature node processing and importance calculation; at the same time, the multi-level comparison mechanism improves the accuracy of abnormal detection, and provides efficient and accurate data support for engineering construction.

The invention discloses a metadata classification method and device based on large language model and multi-agent collaboration. The method comprises the following steps: acquiring original metadata of a database table to be classified; performing semantic integrity evaluation and complementation on the original metadata to generate an enhanced metadata packet; based on the enhanced metadata packet, performing step-by-step classification through a classification pipeline comprising at least two levels of category judgment units, and generating a multi-level classification label path; wherein each level of category judgment unit performs judgment by utilizing a large language model and combining reference information provided by a retrieval enhancement generation technology; carrying out legality verification on the multi-level classification label path; and if the verification is not passed, starting a decision mechanism to correct the multi-level classification label path, and outputting a corrected multi-level classification label. According to the embodiment of the invention, the classification accuracy can be improved while the annotation amount is reduced.

A plurality of features associated with a uniform resource locator (URL) are extracted. It is determined that the plurality of features associated with the URL do not match a known campaign. In response to determining that the plurality of features associated with the URL do not match a known campaign, a machine learning model is utilized to determine whether the URL is infected. The URL is labeled as being infected based on an output of the machine learning model. A URL classification database is updated based on the URL label. Network access to the URL is controlled based on the URL label.