26877 results about "Data bank" patented technology

The invention provides an HBase client main-standby switching method and system based on fault perception, and relates to the technical field of database management, and the method comprises the steps: collecting system operation data through a distributed fault monitoring module, building an anomaly detection baseline model, carrying out fault diagnosis based on a system health assessment distribution matrix, and generating a fault characteristic spectrum; and switching is triggered according to a risk level evaluation result, and the optimal standby node is selected for sequential switching by using a deep strategy learning algorithm, so that rapid and accurate fault detection, diagnosis and intelligent switching can be realized, and the reliability and performance of the system are improved.

A system for multi-stage planning of construction processes and resource allocation, consisting of: a central planning engine configured to receive input data, including architectural design models, structural constraints, procurement schedules, and historical performance indicators; a task decomposition processor that is operationally connected to the central planning engine and configured to generate a hierarchical construction task graph by decomposing macro-level construction milestones into mid-level and micro-level subtasks, with each subtask having time estimates, location identifiers, resource requirements, and mutual dependencies; a hybrid planning processing unit configured to resolve time and resource constraints across the entire task diagram; a resource coordination controller that is operationally connected to the central planning engine, wherein the resource coordination controller includes a real-time database of work units, machines and material stocks, each resource being tagged with attributes such as availability, usage history, operating status and spatial location; a multitude of distributed execution units distributed across the construction zones, each distributed execution unit comprising an embedded controller, sensor interfaces, task status processing logic, and communication circuitry, each distributed execution unit being configured to receive planning instructions from the central planning machine, execute localized control logic for task confirmation and resource activation, and transmit task execution data back to the central planning machine; an adaptive conflict resolution processing unit that is operationally connected to the central planning engine and configured to detect conflicts in task execution or resource conflicts, simulate alternative task-resource allocation scenarios using a real-time multi-agent model, and autonomously update the task graph with revised task sequences and resource allocations; and A dashboard for the construction process, configured to visualize task progress, deviations from the planned schedule, and resource efficiency metrics, with the dashboard also being able to receive manual override inputs or approve automated conflict resolution proposals generated by the adaptive conflict resolution module.

Systems and methods are disclosed for providing at least one report relating to a wireless communications spectrum. At least one device is operable for wideband scan; to detect and measure at least one signal transmitted from at least one signal emitting device autonomously, thereby creating signal data; to analyze the signal data in near real-time, thereby creating analyzed data; generate the at least one report in near real-time; and to communicate at least a portion of the at least one report over a network to at least one remote device.

Systems, methods, and apparatus are provided for automated identification of baseline data and changes in state in a wireless communications spectrum, by identifying sources of signal emission in the spectrum by automatically detecting signals, analyzing signals, comparing signal data to historical and reference data, creating corresponding signal profiles, and determining information about the baseline data and changes in state based upon the measured and analyzed data in near real time, which is stored on each apparatus or device and / or on a remote server computer that aggregates data from each apparatus or device.

An example operation may include one or more of storing a database of payment card data, conversing with a user via a chatbot within a chat window of a software application, wherein the conversing comprises receiving a query from the user about a payment card during a chat session between the user and the chatbot, executing a large language model (LLM) on the query about the payment card and the database of payment card data to generate a chatbot response, and displaying the generated chatbot response via the chatbot within the chat window of the software application during the chat session.

An example operation may include one or more of storing a database of payment card data, receiving an identifier of a product from a digital wallet on a user device, identifying one or more payment cards stored within the digital wallet on the user device, determining the benefits that will be obtained by using each of the one or more payment cards to purchase the product via execution of an LLM on the identifier of the product and the database of payment card data; and displaying a chat message within a chat window on the user device with a description of the determined benefits that will be obtained.

The invention relates to the technical field of production line control, and discloses an automatic control method and system for a plastic processing production line. The method comprises the steps of collecting technological parameters of a plastic processing production line and transmitting the technological parameters to a central control system to generate a database; multi-dimensional parameter correlation analysis is executed, a parameter and quality mapping relation is established through a CNN-LSTM hybrid network, and an optimization model is formed; calculating an optimal control parameter, generating a control strategy and issuing the control strategy to an execution unit; and monitoring a response result, updating the model in real time, and forming closed-loop adaptive control. According to the method, the mapping relation between the process parameters and the product quality is accurately established through the deep learning model, the optimal control parameters are automatically calculated, and closed-loop adaptive control based on production feedback is realized.

Job clusters take time to instantiate. A computing system is provided comprising a plurality of non-interactive job clusters, a control database storing a task queue, and a controller. The controller instantiates one or more clusters of the plurality of non-interactive job clusters based on a size of the task queue and monitoring if the one or more clusters are successfully instantiated. Each of the one or more clusters, after successfully being instantiated by the controller, executes a dispatcher process that includes: querying the control database to identify an available task from the task queue; obtaining and processing the available task; and, after completion of the available task, further querying the control database prior to terminating.

The invention provides a resource dynamic monitoring and control method and system based on quota tracking. According to the pipe gallery deformation monitoring and resource optimization system based on optical fiber and sound wave sensing, underground pipe gallery structure stress field propagation data are obtained through an optical fiber sensor array, energy attenuation characteristics of stress waves at reinforcing rib intersection points are analyzed, and a dynamic mapping model of structure deformation risks and monitoring node resource requirements is established. Meanwhile, the frequency domain propagation characteristics of abnormal vibration signals are captured through acoustic sensors arranged at the expansion joints, and a resource allocation strategy matrix is formed; and constructing a quota tracking database, comparing the actual consumption rate of the frequency spectrum quota with a predicted value, generating a resource use efficiency report, and performing frequency spectrum redistribution of frequency hopping interval optimization and transmitting power adjustment on the nodes in the high stress concentration region. According to the technical scheme provided by the invention, the resource dynamic optimization of the underground pipe gallery structure is realized, and the risk early warning precision and the communication efficiency are improved.

This disclosure relates to methods, systems, and devices for AI / ML assisted management of a radio access network (RAN). In particular, an LLM is employed to generate answer to user queries, for example in the form of code that can be executed upon streaming data from the RAN, including performance management and control management databases. To provide prompts the LLM can understand, an LLM agent employs a knowledge base and experience base to transform the language of the queries from the highly technical telecommunications domain to a general domain. Frequently asked questions and their answers may be stored in the experience base and used instead of using the LLM.

A multi-modal articulation system translates human gestures into control commands for digital and automation devices. The system integrates a camera module, which captures facial and hand movements, with an image processing unit that extracts facial features, such as eyebrow movement, lip curvature, eyelid motion, and eye trajectory. These extracted features are analyzed in real time by an articulation recognition module that compares them against a database to recognize specific gestures. The system tracks and processes air-drawn hand gestures using a gesture trajectory tracking unit, which converts the motions into digital representations and classifies them using deep learning algorithms. The recognized gestures are converted into machine-readable control signals and executed on various connected devices via a relay control unit. The system incorporates adaptive algorithms to improve accuracy, account for environmental conditions, and stabilize hand tremors, providing a gesture-based control interface for applications ranging from smart home systems to multimedia devices.

A database system generates a prompt for an LLM or other machine learning (ML) model to narrow the search space to highly relevant information about a database. A distinct instance of a classifier, a clustering algorithm, or a topic modeling model can be trained based on information from ML automation within the database system, respectively for each column or table in the database. Model instances can then be used during generative LLM inferencing to identify relevant sources of data to answer the user's question. Thus, the prompt generation combines ML automation and other ML models or an LLM for topic modeling and schema description.

Searches based on an incoming ticket identify quality ticket enrichment data using a vector database. Language model prompts target particular kinds of quality ticket data. The incoming quality ticket, or a search result ticket, or both, are enriched using enrichment data, such as a user intent identification, a workaround suggestion, a resolution description, a target audience description, a relevance description, an impact description, a description of missing resolution facilitation information, an association between the incoming quality ticket and the search result ticket, a user sentiment identification, a tag suggestion, or a feedback utility estimate. The enrichment reduces engineering and support burdens, and facilitates faster more effective resolution of the problem or the request that is stated or implied in the incoming quality ticket. Duplicate tickets are merged or removed. Tickets are prioritized. Missing problem resolution information is identified and requested sooner.

The invention relates to the technical field of food storage management, in particular to a food storage management system, which comprises a data acquisition layer, is composed of a plurality of devices and is used for acquiring food, environment and user operation data; the data transmission layer transmits data by using wired and wireless network technologies; the data storage layer stores various types of data in combination with a relational database and a non-relational database; the data processing layer comprises a plurality of functional modules, such as an intelligent warehousing management module, and is used for realizing automatic input verification and batch management of food information; the intelligent ex-warehouse management module is used for optimizing ex-warehouse sequence and tracking food directions; the expiration and waste management module is used for carrying out expiration reminding and surplus value evaluation; the data analysis and purchase optimization module is used for predicting demands and analyzing loss; and the dish and inventory association module is used for matching the dish formula and the inventory and predicting the sales allocation inventory. The system improves the management efficiency, reduces the waste, optimizes the purchase decision, enhances the dish and inventory association management, guarantees the system safety, and provides data support to assist the decision.

The invention relates to the technical field of data exchange, in particular to a data exchange system of a nested tag structure, which comprises a data carrier adaptation module, a structure analysis module, a field mapping module, a logic driving module and a script generation module. According to the method, carrier identifiers are generated through comparison of MIME types, file header features are positioned through pattern matching, the recognition accuracy and adaptability are improved, a nesting relation is calculated through depth-first traversal of file paths, node sequences are generated through analysis in combination with a DOM tree, the label analysis efficiency is optimized, and a mapping table is generated through algorithm matching of field identifiers and database codes; the method comprises the following steps: dynamically constructing a field mapping relation, reducing manual configuration, constructing a decision matrix based on a mapping table, executing logical operation to generate a status bit and triggering a threshold write-in instruction, enhancing strategy dynamic adjustment capability, reducing semantic ambiguity through multi-algorithm collaboration and a dynamic decision mechanism, improving data exchange robustness, and supporting real-time state response. And the transmission timeliness of the industrial Internet of Things is ensured.

A system and method for AI-based dynamic pricing, mapping, and emissions control to optimize inner-city mobility. The system acquires real-time nitrogen dioxide data across a geographic area from sources including satellites, feeds this data into a decision support system along with road-specific weight matrices from authorities, and updates a dynamic penalty matrix for roads in the area. Automatic number plate recognition tracks vehicle movement, queries vehicle databases for emissions profiles, and updates the platform. Users input journey parameters and the system, using AI tools including a genetic algorithm economic and environmental dispatch (GA-EED) optimizer, generates an optimized route based on user-selected criteria such as time, emissions, penalty, and cost. The system enables dynamic, environmentally-aware route optimization for inner-city mobility.

A video streaming system including a video cache system having a cache database and a video storage device, and including a video server configured to communicate with a gateway system configured to store multiple video streams, communicate with a cloud backup system configured to store video in a file system, and communicate with a cloud server to receive a stream request, the stream request indicating requested video that comprises multiple video segments. The video server is further configured to receive the stream request and determine a playlist that indicates where on the video cache system, the cloud backup system, and the gateway system the video segments that are needed to fulfill the stream request are stored, and to communicate needed video segments to the video cache system in preparation for providing streaming video to fulfill the stream request.

The invention relates to the technical field of data processing, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a database migration method, device, equipment and medium. And deploying a double-write control module of the application program layer to write the source database and the target database in parallel, and completing consistency verification through a data verification comparison task. And controlling a target database write-in channel according to a difference analysis result, closing a source database write-in channel in combination with a service takeover state, and completing a migration process from the source database to the target database. According to the method, full migration, application layer double writing, differential data verification and dynamic write-in channel control are combined, data consistency of the source database and the target database in the migration process is guaranteed, the source database and the target database are safely switched to after the service takeover capacity is verified, and the migration safety and continuity are improved.

The invention relates to the technical field of image processing, and discloses a stranded wire production quality monitoring method and system based on machine vision. The method comprises the following steps: acquiring the surface of a stranded wire at multiple angles through a high-speed camera array to obtain an original image; filtering high reflection and noise to obtain a feature map; performing edge detection, segmenting and identifying defects, and generating a position mapping table; quantitatively calculating defect parameters to form a quality score; performing correlation analysis to adjust process parameters; and constructing a defect-process database to realize quality tracing early warning. According to the invention, full-process automatic control from defect identification, quantitative evaluation to process parameter optimization is realized, the defect-process relational database is constructed, and the tracing and early warning functions of production quality are supported, so that the quality stability and the intelligent level of stranded wire production are improved.

The invention relates to the technical field of task allocation, in particular to a task allocation method for flexible employment. According to the technical scheme, the method comprises the following steps that a database of related information of tasks and employees is constructed, wherein the database comprises detailed information of the tasks and comprehensive information of the employees; respectively constructing a task model and an employee portrait based on the information in the database; and matching the task with the employee through an intelligent matching algorithm, wherein the intelligent matching algorithm comprises matching algorithm selection and optimization, real-time matching and dynamic adjustment, and multi-objective optimization and tradeoff. According to the method, multiple matching algorithms are combined for optimization, weights are selected and adjusted according to tasks and employee characteristics, accurate matching is achieved, a task model and employee portrait multi-dimension consideration adaptability is achieved, adaptive changes are matched in real time, tasks and multiple aspects of employees are optimized and balanced in a multi-objective mode, the development of rights and interests of the employees is considered, and the matching quality, the working enthusiasm and the stability are improved; flexible employment resources are managed more effectively, and the task allocation effect is improved.

A SQL generation method based on a large language model, comprising: generating data definition language (DDL) prompt slot information and data example slot information on the basis of a configuration operation of a user on a SQL database; receiving a natural language query request input by the user, and transcribing the natural language query request to obtain question transcribing slot information; on the basis of the question transcribing slot information, the DDL prompt slot information and the data example slot information, acquiring complete prompt information matched with a large language model; and inputting the complete prompt information into the large language model to generate an executable SQL statement matched with the natural language query request.

The invention discloses an intelligent server management method and system in an edge computing environment, and relates to the field of electrical digital data process.The method comprises the steps that a dynamic load buffer database is established; calculating a load stability coefficient of each server node; when the load stability coefficient of the server node is smaller than a first preset threshold value, marking the server node as a fluctuation node; calculating a node cooperation efficiency value; determining a target server candidate set, and calculating to obtain a task allocation weight; distributing tasks on the fluctuation nodes to server nodes in the target server candidate set; when the continuous preset duration of the real-time load value of the fluctuation node is lower than a third preset threshold value, calculating a processing efficiency improvement proportion; for the task of which the processing efficiency improvement proportion is greater than a fourth preset threshold value, keeping continuous processing at the current server node; and for the tasks of which the processing efficiency improvement proportion is smaller than or equal to a fourth preset threshold value, returning to the original fluctuation node. The method and the device are used for reducing communication overhead and service processing delay between nodes.

A system for timing or zone alert determination from vehicle events and / or an accident database includes an interface and a processor. The interface is configured to receive a location of a translating object. The processor is configured to trigger a warning to the translating object based at least in part on its location and the existence of an associated hazard.

The invention relates to the technical field of municipal road construction, and discloses a municipal road construction section scheduling optimization method and system based on artificial intelligence, and the method comprises the steps: collecting the multi-source dynamic data of a construction region through Internet of Things equipment and a satellite remote sensing technology, and constructing a time sequence database; a multi-objective optimization model is established, and an initial scheduling scheme is generated by adopting a non-dominated sorting genetic algorithm with the goal of minimizing construction period, resource waste and traffic jam influence. Dynamically adjusting the priority of the construction section by using a reinforcement learning algorithm, and updating a construction task sequence; a graph neural network is utilized to detect space-time conflicts of construction sections, and conflict-free scheduling constraint conditions are generated; and optimizing resource allocation based on mixed integer linear programming, simulating a construction process in combination with a digital twinborn technology, correcting a construction progress deviation by using a Kalman filtering algorithm, and outputting a final scheduling instruction. According to the invention, optimization of municipal road construction section scheduling is realized, the construction period is effectively shortened, resource waste is reduced, and traffic jam is relieved.

A checkout terminal is provided. The checkout terminal comprises a camera array, a display device, a weight scale, and a control circuit. The control circuit is configured to identify, based at least on images captured by the camera array, product identifiers associated with a plurality of different items placed in a placement area and on the weight scale, determine a combined weight of the plurality of different items based on product weight information stored in a product database, retrieve a weight measurement measured by the weight scale, detect for unaccounted items based on comparing the combined weight the plurality of different items and the weight measurement, and in the event that an unaccounted item is detected, display, via the display device, instructions to move one or more items to identify the unaccounted item.

The invention discloses a JDK8-based heterogeneous service large model dynamic adaptation and intelligent scheduling method and system, and belongs to the technical field of artificial intelligence service integration, and the method comprises a unified service module which provides standardized HTTP / WebSocket access for an application layer and shields the difference of multiple platforms at the bottom layer; the dynamic routing module is used for dynamically selecting service nodes based on service quality indexes and supporting weight calculation, fusing recovery and flow dyeing; the service execution module is used for loading a platform adapter through a dual-mode service factory, integrating a tool calling function and realizing protocol conversion and authentication injection; and the configuration management module supports dual-configuration source hot loading of the static file and the dynamic database and provides versioning rollback and consistency verification. According to the method, the problems of multi-platform protocol difference, service rigid expansion, tool calling coupling and the like can be solved, the complexity of multi-platform management is remarkably reduced, and the flexibility and maintainability of the system are improved.

The invention provides a circuit board production yield root cause tracing method, which comprises the following steps of: acquiring process parameters, equipment states, environment variables and quality detection results of a whole production process, and constructing a multi-dimensional time sequence database; extracting a typical manufacturing process modeling unit through a sliding time window and dynamic time warping; establishing a cross-process dynamic causal relationship graph in combination with nonlinear Granger causal test, a structural equation model and a dynamic Bayesian network; an intervention and anti-factual reasoning method is applied, the causal effect and path stability under parameter disturbance of each process are evaluated, and the influence of a key causal path is quantified; according to the method, the accuracy of defect rate root cause positioning can be improved, and powerful support is provided for circuit board production process optimization and quality improvement.

The invention relates to the technical field of agricultural irrigation, and discloses a regional crop rolling correction intelligent irrigation decision-making method, which comprises the following steps of S1, collecting basic data and dividing an irrigation decision-making region; s2, crop growth model parameter sensitivity analysis; s3, localizing parameters of the crop growth model; s4, a regional space long-term irrigation decision scheme is formulated; s5, establishing a farmland information database based on remote sensing and Internet of Things technologies; and S6, constructing a regional irrigation system rolling correction system. The invention provides a regional crop rolling correction intelligent irrigation decision-making method. The method comprises the following steps: analyzing a mutual relation and an evolution trend of each element of an irrigation decision-making model; a regional grain and cotton crop irrigation system based on crop water shortage information perception-process recognition-efficient decision is constructed, and irrigation decisions are dynamically adjusted in real time according to future climate changes and field management changes, so that the balance between the water resource utilization efficiency and the crop yield is achieved.

An AI orchestration system dynamically manages multiple artificial intelligence (AI) agents within a cloud computing environment to efficiently process user requests. A model orchestration subsystem determines whether a request is handled locally using a domain-specific database or by invoking one or more AI agents. The system maintains AI agents in active and inactive states, provisioning computing resources for inactive agents as needed. Real-time model metrics guide the selection of target AI agents, and if a degrading performance trend is detected, the system preemptively spins up additional AI instances. The system provisions processor cycles, memory, and network bandwidth through a cloud-based resource manager, instantiates containerized execution environments or virtual machines, and performs automated load balancing among AI instances.

The invention provides a non-performing asset cross-scene question and answer framework based on a knowledge graph, and relates to the field of artificial intelligence and legal science and technology, and the framework comprises a framework, a knowledge fusion layer is provided with a multi-source data access module which is used for obtaining heterogeneous data of a law and regulation database, a judicial case library, an enterprise financial statement system and an asset transaction platform; configuring a legal entity analysis engine, and converting the unstructured legal text into an entity-relationship-attribute triple which can be represented by a knowledge graph based on an ontology mapping technology; setting a financial data standardization component, and converting the financial data in different formats into unified semantic representation through a predefined financial index mapping rule; the knowledge fusion layer of the framework can integrate multi-source heterogeneous data such as laws and regulations, financial data, business processes and the like through a multi-source data access module, a legal entity analysis engine, a financial data standardization component and the like.