234 results about "Administrative database" patented technology

The invention relates to the field of artificial intelligence, in particular to an intelligent standard knowledge retrieval system based on an AI large model, which comprises a standard knowledge management database, a multi-source acquisition preprocessing module, a semantic understanding and indexing module, an intelligent retrieval engine module, a knowledge enhancement module, a user interaction feedback module, a security control module and a deployment expansion module. The standard knowledge management database is used for storing standard knowledge design data, real-time retrieval data and feedback data and constructing a dynamically updated standard knowledge resource pool; through the multi-source standard knowledge acquisition and preprocessing module, multi-channel objective standard data can be integrated and dynamically updated, and the problem of knowledge fragmentation is solved; and through the semantic understanding and indexing module, industry professional semantic accurate matching is realized, the limitation of traditional keyword retrieval is broken through, and the accuracy and efficiency of standard knowledge retrieval are remarkably improved.

The invention discloses a drainage basin water environment intelligent management method and system, and belongs to the technical field of environment monitoring and water resource management. Multi-source heterogeneous water environment data is obtained, and a multi-modal pollution sensing map is constructed through fusion; extracting a time mutation vector and a spatial offset path of a pollution abnormal diffusion source point based on the map, and generating a pollution propagation sensitive weight map; performing cross-space-time matching on the sensitive weight map and historical climate disturbance data, generating a pollution causal chain path map by using a deep causal learning model, identifying a potential hidden pollution source distribution unit, predicting a response trend of the potential hidden pollution source distribution unit to future water quality change, and forming a multi-scene pollution evolution simulation result; and finally, constructing a pollution response priority index map, and generating a treatment resource optimal allocation sequence and an intervention strategy in combination with the drainage basin management database. According to the invention, intelligent identification and dynamic treatment optimization of complex pollution diffusion behaviors can be realized, and scientificity and timeliness of water environment management are improved.

The invention relates to a medical data dynamic management method based on multi-modal data fusion and deep reasoning, which comprises the following steps: establishing a three-layer dynamic management architecture, collecting various medical data of a patient in real time through a bottom layer, performing primary processing on the various medical data of the patient, receiving the primarily processed medical data through a middle management layer, and performing dynamic management on the medical data through the middle management layer. The double-flow Transform network architecture performs medical event prediction, the event-driven architecture triggers a data processing flow, medical data after primary processing is subjected to dynamic extraction, data conversion, data loading and multi-modal data fusion processing, a data processing result is transmitted to the application layer, the application layer performs dynamic field generation, and the event-driven architecture performs multi-modal data fusion processing. And data automatic dynamic management and real-time feedback calibration are carried out based on a data fusion analysis result. The limitation of a static field structure existing in an existing medical data management SEER database is solved, the data quality is improved, automatic management and real-time feedback calibration of follow-up visit data are achieved, and separation of a follow-up visit system and a data management platform is avoided.

A change management task automation system reduces manual effort required for change audits and streamlines the change management process, enforcing preventative compliance with change management best practices. A plurality of automation modules provides change management task automation functionality for several processes, including software change management, database change management, key report change management, data lake change management, patch change management, and controlled version document repository management automation.

The invention relates to the technical field of sectional material excess material management, and discloses a sectional material excess material management method and device and electronic equipment, and the method comprises the following steps: S1, setting a minimum available length threshold value of excess materials, which is used for judging whether the minimum available length threshold value is included in an excess material management process or not; s2, the excess materials generated by cutting are recognized, information including the color, the length, the surface state and the profile structure attribute is obtained, and a unique identifier is generated for each section of excess materials; s3, storing the excess material information meeting the conditions into an excess material management database, and associating storage position information of the excess material management database; and S4, after a new order request is received, screening matched excess materials in the excess material database according to an order demand to form a candidate set. According to the method, a structural management technical scheme based on geometric contour reconstruction and matching of the excess materials is adopted, and the identifiability, traceability and reutilization of the excess materials in the machining process are achieved. The technical effects of intelligent classification and efficient scheduling of the processing residual materials are achieved.

Embodiments relate to system and methods involving use of a technique for managing a database for producing a material composition having a thermodynamic phase. The technique can include: receiving a binary phase diagram for each material to be used as a component of a high-entropy alloy (HEA); using one or more active learning machine learning techniques for generating a feature, the feature including: a primary feature that is representative of a probability that an HEA will exhibit a solid solution phase and / or an intermetallic phase, and a physics-based feature that is representative of a factor related to formation of a desired intermetallic HEA phase; encoding the primary feature and the physics-based feature; generating an output representation of a HEA alloy composition and phase of a predicted materials composition; and selecting a HEA composition and phase that will meet a material design criterion.

The invention provides an internet right product agent management system, and relates to the technical field of product agent management. The system comprises a product management module, an order management module, an agent management module, a database and a data analysis module. The system processes on-off and stock of products through the product management module, the order management module calculates commission, and the agent management module achieves credit evaluation. The data analysis module predicts requirements through a multi-layer architecture; a data input layer integrates internal and external data; the analysis engine layer adopts feature coding and a time attention mechanism to model space-time correlation, and outputs a demand prediction formula; and the decision output layer generates an agent personalized report through inventory calibration, credit grading and regional weighting strategies, recommends products and early warns risks. The system realizes intelligent acquisition and sales decision making, and improves the operation capability and market influence of the system.

The invention relates to the field of engineering management, in particular to a project engineering whole-process data intelligent evaluation system which comprises a project relation construction module, a carbon emission information acquisition module, a correlation analysis module, a path optimization module, a carbon emission improvement analysis module and a management database. According to the system, the whole process of a project is divided into construction stages, a network diagram is drawn, a carbon emission source is identified, emission factors are associated to carry out carbon emission accounting, the carbon emission proportion of each device in the corresponding stage is calculated, key devices are screened, correlation is analyzed, an optimal combination scheme is provided, device use can be optimized, overall carbon emission in the construction stage is reduced, and the construction efficiency is improved. And meanwhile, whether the transportation path is optimized or not is judged in combination with the transportation mileage and carbon emission correlation coefficient, the transportation cost and the transportation time, so that the optimized path is found for each transportation material through the weighted graph, the carbon emission in the transportation link is reduced, and the overall benefit of the project is enhanced.

The invention discloses a Text2SQL (Structured Query Language) system and method based on cue words. The system comprises a natural language input module for receiving and preprocessing a natural language query statement; the metadata management module is used for managing database metadata information; the cue word generation module is used for generating cue words containing database modes, user problems and SQL requirements on the basis of the query statements and the metadata; the large language model module is used for generating a preliminary SQL based on the cue word; the SQL grammar verification module is used for verifying grammar and feeding back errors; the manual auditing module is used for auditing and editing the SQL statements passing the verification; and the SQL execution module is used for executing the SQL passing the audit and returning a result. According to the method, the accuracy is improved by combining cue word guidance and a large model, the field adaptability is enhanced by relying on metadata, the data security is ensured by introducing manual auditing, the accuracy and security of SQL generation in a complex query scene are remarkably improved, and the development and maintenance cost of the system is reduced.

The invention discloses an automatic operation and maintenance system based on fusion of an AI agent and a configuration management database, and the system comprises a data collection module which is used for automatically collecting configuration information of IT infrastructures through a multi-mode collection technology; the configuration management database is used for converting the configuration information into configuration items and dependencies to construct a knowledge graph; the AI agent comprises a log analysis unit used for carrying out structured processing on the unstructured log data; the anomaly detection unit is used for carrying out anomaly detection on the structured log data and time sequence index data by adopting an unsupervised machine learning algorithm; the root cause positioning unit is used for performing topological relation reasoning on the detected abnormal events based on a knowledge graph, and determining a fault type and a root cause configuration item causing the fault; and the automatic executor is used for calling an automatic operation and maintenance tool to execute repair operation according to the fault type and the root cause configuration item. The operation and maintenance efficiency can be improved, and the fault repair time can be shortened.

The invention provides a cross-platform asset synchronization method and system for a configuration management database, and the method comprises the steps: monitoring the creation, reading, updating and deletion events of resources, and triggering an asset synchronization instruction according to the events; in response to a trigger instruction of asset synchronization, generating a corresponding multi-dimensional synchronization task according to a dynamically configured synchronization strategy and according to preset condition filtering, priority ranking and dependency in the synchronization strategy; queuing the multi-dimensional synchronization tasks according to a synchronization strategy and a time level, generating an asynchronous task queue according to a queuing sequence, and sequentially scheduling and executing each task in the asynchronous task queue; and according to the specific requirements of the task and the type of the target system, dynamically adapting to a supported protocol, and sending the task to the corresponding target system for execution. Through the four-layer architecture design of event-driven triggering, rule engine decision, task queue scheduling and resource gateway adaptation, a complete asset synchronous closed loop is formed, and asset synchronous management of the CMDB is realized.

An illustrative data storage management system comprises a management database that stores administrative preferences and system configurations, as well as results and / or statistics of completed secondary storage operations, i.e., information needed by the system to protect customers' data and to track and recover the protected data, including secondary copies such as backup copies, archive copies, etc. The disclosed data storage management system is configured to protect its own system data subject to a very aggressive (short) Recovery Point Objective (RPO), by using an innovative infrastructure that enables the system's storage manager to fail over to any number of other failover destination storage managers, each one comprising a destination management database. An illustrative database granularly tracks whether each and every transaction log file has been successfully applied to each and every destination management database to synchronize with the source management database.

A system and method are provided for integrating a property management system and a cyber vulnerability management system to provide remediation for assets in an environment. Information obtained about network connected mechanical assets within the environment is respectively obtained from a tag on the asset. For each asset the asset is identified through a property management database based on the information in the tag and a cyber position of the asset is obtained through a digital network identifier in the tag from the cyber vulnerability management system. In response to identification of the asset having a cyber vulnerability, remediation for the cyber vulnerability is determined, scheduled, and initiated.

The invention belongs to the technical field of property management, and provides an intelligent property management method and system based on the Internet of Things, and the method comprises the steps: S1, building a property management database; s2, acquiring the operation state of facility equipment, environment quality parameters and personnel activity data in the community in real time through an Internet of Things sensor network; s3, processing and analyzing the data in the property management database by using a big data analysis technology; s4, automatically generating a property management strategy according to an analysis result; by establishing the property management database and collecting and analyzing data in real time, automatically generating the property management strategy and pushing customized information to property management personnel, owners and visitors, and establishing a feedback mechanism to continuously optimize services, intelligence, individuation and high efficiency of property management are realized, the management efficiency and service quality are remarkably improved, and the management cost is reduced. And construction of a harmonious community is facilitated.

A cloud-based private access system integrates static CMDB data with real-time access telemetry to automate Zero Trust segmentation. Administrators upload CMDB files (e.g., CSV / JSON) describing applications, FQDNs, IPs, ports, protocols, ownership, and priorities. An analytics management service stages and normalizes the data, retrieves reference domain data from an in-memory cache, and queries a telemetry engine to correlate intended configurations with observed usage. The system detects mismatches, over-permissive wildcard access, and auto-discovers non-listed elements such as subdomains, ports, or protocol combinations. It then generates prioritized recommendations to refine wildcard rules, create explicit allow policies, and merge or split application groups. Administrators review, simulate, and approve updates, enabling phased rollout, rollback, auditing, and continuous policy tuning based on evolving user and application behavior.

A system for integrated data provenance and reconciliation across heterogeneous financial systems, the system includes: a data ingestion module implemented as a hardware interface and configured with high-throughput adapters for structured and unstructured data ingestion from multiple heterogeneous financial subsystems, including bank ledgers, securities trading platforms, risk management databases, and regulatory reporting systems; a schema harmonization processing unit consisting of a dedicated FPGA (Field Programmable Gate Array) structure configured to perform real-time schema alignment, metadata normalization, and semantic mapping across different data models; a lineage tracking processor array implemented on application-specific integrated circuits (ASICs) and configured to encode dataflow transitions into a graph-encoded structure in which each node represents a transformation and each edge represents a dependency; a reconciliation computation cluster unit embodied as a set of graphics processing units (GPUs) configured to execute parallelized reconciliation techniques, anomaly detection routines, and balance verification processes between transformed financial records and reference records; a cryptographic verification unit comprising secure key storage hardware, quantum-resistant encryption modules, and tamper-resistant enclaves configured to generate, anchor, and verify cryptographic signatures for provenance and reconciliation events; a secure storage subsystem configured in a WORM (write-once, read-many) configuration with hardware-based integrity locks for storing immutable provenance and reconciliation logs; a controller with a dedicated visualization processor configured to generate interactive dashboards and drill-down analyses of lineage charts and voting results; and a modular chassis structure consisting of a high-speed backplane interconnect, secure power distribution modules, and tamper-evident enclosures, enabling the system to achieve real-time scalability, hardware-level security, and auditability of financial data flows across heterogeneous infrastructures.

A system and method for maintaining database integrity. A first storage appliance receives data writes and increments an associated last sequence number (LSN) X upon each data write thereto. A second storage appliance receives data writes and increments an associated LSN Y upon each data write thereto and an external device is coupled to the first storage appliance and the second storage appliance. The first storage appliance and the second storage appliance comprise a cluster management database with data writes being replicated on both the first storage appliance and the second storage appliance. Upon the first storage appliance beginning to shut down, the LSN X is written to the external device.

A system and method are provided for integrating a property management system and a cyber vulnerability management system to provide remediation for assets in an environment. Information obtained about network connected mechanical assets within the environment is respectively obtained from a tag on the asset. For each asset the asset is identified through a property management database based on the information in the tag and a cyber position of the asset is obtained through a digital network identifier in the tag from the cyber vulnerability management system. In response to identification of the asset having a cyber vulnerability, remediation for the cyber vulnerability is determined, scheduled, and initiated.

A system for managing data availability for database transactions is disclosed. The system is programmed to receive source data and extract a plurality of events from the source data. The system is programmed to create a halt record corresponding to each event of the plurality of events. The system is programmed to resolve conflicts among one or more halt records. The system is programmed to receive a request for a specific database transaction related to a specific database item from a client device. The system is programmed to determine whether any halt record is in effect for the specific database item. The system is programmed to perform the specific database transaction in response to determining no halt record is in effect. The system is programmed to transmit a result of the specific database transaction in response to the request to the client device.

A system for balancing query execution against ontology-based databases among multiple user accounts and related methods are disclosed. The system is programmed to receive database queries transformed from ontology queries from user accounts. The system is further programmed to manage execution of the database queries to enable fair utilization of computing resources among the user accounts, based on tracked usage of computing resources of each user account or estimated costs of pending database queries considering access controls associated with the ontology. Managing execution of the database queries comprises preempting a complex database query for another database query associated with a user account having a current top priority in query execution.

The invention provides a power supply system operation and maintenance monitoring method and platform based on a neural network, and relates to the technical field of power supply system operation and maintenance. Historical operation data of a power supply system is collected, and an operation and maintenance management database is constructed according to the historical operation data to mark historical operation states of power supply stations in the power supply system; based on the historical sensing detection images and the historical operation and maintenance management parameters, the current sensing detection images and the operation and maintenance management parameters are integrated into a multi-source splicing feature map through a wavelet neural network model; fault feature classification is carried out on the multi-source splicing feature map based on a softmax classifier, and the operation state of each power supply station is updated in real time according to the classification result of a jump convolution network model, so that the real-time operation state of each power supply station is obtained; and comparing the historical operation state of each power supply station with the real-time operation state, and generating an operation and maintenance report and fault trend prediction of the corresponding power supply station. According to the invention, supervision efficiency and reliability of operation and maintenance of the power supply system are improved.

The invention discloses a space environment welding digital twinning method based on multi-scale dynamic coupling, which comprises the following steps: S1, collecting key data in a welding process, and establishing a basic numerical model of the welding process and tissue change in combination with experimental data; s2, on the basis of the basic numerical model, a numerical simulation method is adopted to construct a digital twinborn model of the welding process; s3, establishing a real-time data interaction mechanism between the digital model and actual welding equipment by utilizing a virtual-real synchronization model in the digital twin model; s4, on the basis of feedback data obtained by a real-time data interaction mechanism, welding process parameters are automatically adjusted through an intelligent optimization model in the digital twin model, so that the structure change in the welding process is matched with a target prediction result; and S5, establishing a welding process data management database, storing the key data and the adjusted process parameters, and continuously training and optimizing the prediction precision of the digital twin model based on historical data in the database.

The invention relates to the technical field of information processing, in particular to an intelligent key cabinet management method, device and equipment and a storage medium. Lock position and vehicle associated information is stored in a key management database, and a key control model is constructed in combination with the key management database and a user permission mapping framework; the key control model is used for matching the user operation authority corresponding to the user identity authentication result, the key management difficulty is reduced, the key operation request is received in real time based on the user operation authority, the alcohol detection is triggered, the risk of drunk driving of the user is reduced, and the safety is improved; if yes, a dynamic taking and returning voucher is generated according to the key operation request, key state information in a key management database is updated, the authenticity of key taking and returning records is improved, the key loss risk is reduced, and the dynamic taking and returning voucher is sent to the key cabinet terminal so that the key cabinet terminal can control a target lock position to execute lock opening and closing operation based on the dynamic taking and returning voucher. The key taking and returning efficiency is improved.

Disclosed herein are systems and methods for energy management. A system, such as a vehicle, includes power packs and a photovoltaic array with interconnected photovoltaic cells that supplies electric charge to the power packs for charging the power packs. A charge management database stores data tracking respective charge cycles of the power packs based on the charging and discharging of the power packs. An energy control system controls flow of power in the system to control the charging and the discharging of the power packs, optimizes the flow of power in the system based on the respective charge cycles as tracked in the data stored in the charge management database, and updates the charge management database based on the optimization(s). An output interface outputs a status of the power packs based on the flow of power, for instance to indicate effect(s) of the optimization(s) on the power packs.

A method includes receiving a permission request from a user to perform an operation in a computer environment. Data elements of operations previously performed by a plurality of users are received. A set of operation types are generated by identifying data elements of operations previously performed by other users of the plurality of users having operation types performed by the user. The data elements in the set are mapped into a graph database. Permission messages are generated with a correct response identified from a data attribute from a specific operation type previously performed by the user, and wrong responses identified from the specific operation type previously performed by the other users. An accumulated probability based on the permission respond message is computed using the graph database. The user is tagged based on the accumulated probability as a permissioned user for performing the operation, or a non-permissioned violator user.

A maintenance work assistance system (1) comprises: a basic event inference engine (20) that infers, in accordance with a pre-created causal model, a basic event (42) that will cause a failure in an industrial machine (2) and the probability of occurrence thereof; a confirmation task presentation engine (21) that, in accordance with a pre-created processing model, presents a confirmation task for confirming whether or not the basic event (42) is occurring; a history information extraction engine (22) that extracts, from a history management database (31), a history of environment-related information related to the operating environment of the industrial machine (2) serving as a target of the confirmation task, and a history of maintenance work records; and a basic event identification engine (23) that, in accordance with the pre-created processing model, identifies the basic event (42) for which there is a causal relationship therebetween with a top event (40) or an intermediate event (41).

Techniques are disclosed relating to managing database queries. In some embodiments, a server system receives a query from a computer system and determines a set of aspects for the query, including at least a number of columns specified in the query and a computational cost of executing the query. The system generates a query vector based on the set of aspects determined for the query. The system then compares the query vector with a plurality of clusters, ones of the plurality of clusters comprising two or more previously generates query vectors generated based on aspects of queries previously received by the server system. Based on the comparing, specifically a distance between the query vector and the plurality of clusters of previously generated query vectors, the system classifies the query. Based on a classification of the query determined during the classifying, the system manages the query.

The invention relates to the field of database management, in particular to a maintenance method and device for a configuration management database, and discloses the maintenance device for the configuration management database, which comprises an NLP model, a time sequence analysis model, a graph neural network, a database and an interaction module, the time sequence analysis model is used for predicting a resource use trend or a fault risk, the graph neural network is used for establishing a CI relation model and analyzing a dependency relation and an influence range, the database is used for storing user data, and the interaction module is used for supporting human-computer interaction between a user and the device. According to the method, the text information is extracted through the NLP model, the CI information in the data is obtained, the dependency relationship in the information is captured for the graph neural network in combination with semantic understanding, and the limitation that a traditional tool can only process structured data is solved.

The invention provides a ship transition skew design system and method, and the system comprises a data acquisition and analysis module which obtains a ship three-dimensional design model, and automatically extracts the geometric information of a plate and the process attribute information of a butt joint boundary from the ship three-dimensional design model; the rule management database is used for storing transition skew discrimination rules and a design rule base; the judging module is used for judging a target docking boundary needing to be provided with a transition slope according to a judging rule; the parameter design module is used for automatically calculating and generating corresponding transition skew geometric parameters for each target docking boundary; and the model updating module is used for modifying the ship three-dimensional design model according to the transitional oblique geometric parameters. The system integrates discrimination rules and design specifications, and reduces the dependence of design on designers, reduces errors caused by human experience and improves the design quality when the transition skew parameters are judged and calculated.

The present application relates to the technical field of computer, and especially relates to a hybrid cloud architecture graph construction method and system, electronic equipment and storage medium. The method comprises the following steps: deploying a collection agent on at least one cloud platform of a hybrid cloud, or burying a point in a container image of an application system of the cloud platform, so as to obtain application container information when the application container is started; performing container self-discovery based on the container name in the application container information to obtain new container information; performing container asset life cycle management and asset data integration based on the new container information to obtain a container asset information table; and constructing an architecture graph of the application system based on the container asset information table and a dependency relationship in a configuration management database. The method can effectively improve the efficiency and accuracy of container self-discovery in the hybrid cloud, and can update the architecture graph in a timely manner, has high accuracy, and has strong application adaptive ability.