592 results about "Usage data" patented technology

The invention provides a timed task execution optimization method and system. The method comprises the following steps: forming a timed task execution optimization system architecture; determining a corresponding calculation factor to obtain a dynamic priority score; predicting the to-be-predicted task data by using the task prediction model to obtain a task execution time prediction value; analyzing the to-be-executed task queue, calculating the average waiting time, determining a multiple factor according to the task priority and the system load state, and identifying the task with the task execution time prediction value larger than the dynamic threshold value in the to-be-executed task queue as a long task; performing automatic fragmentation processing on the long task, generating a fragmentation result, determining a scheduling sequence based on the dynamic priority score and the task execution time prediction value, and generating a scheduling decision; and performing resource availability evaluation on the resource use data to obtain a node resource evaluation result, and allocating execution resources for the selected task. According to the method, the problems of efficiency and reliability of the timed task execution system in a high-load scene are solved.

Techniques for constraining the results of a generative language model to valid information using knowledge-grounded documentation. A generative language model may generate invalid results, including compound entities and incorrect entity relations. The techniques include, for a given user inquiry, determining a set of documented information, from a particular knowledge base, that corresponds to the user inquiry. The techniques further include determining a subgraph from a knowledge graph representing the knowledge base, as well as determining a trie data structure representation of the set of documented information. The user inquiry and subgraph are provided as input to a trained generative language model for generating a response to the user inquiry. The techniques include using the trie data structure to validate that the generated response corresponds to real information from the set of documented information.

The present disclosure provides a method of facilitating intelligent budget governance for a cloud resource. Further, the method may include receiving a budget data. Further, the method may include receiving a usage data. Further, the method may include determining a group budget status based on the budget data and the usage data. Further, the method may include calculating a threshold variance representing a deviation of the group budget status from a predefined budget threshold. Further, the method may include generating a control intent data representing a scheduled action on the cloud resource based on the threshold variance and a time policy. Further, the method may include storing each of the budget data, the usage data, the group budget status, the threshold variance, and the control intent data. Further, the method may include transmitting the control intent data to the cloud account system.

The invention discloses a multi-model intelligent management scheduling method and system. The method comprises the following steps: receiving a to-be-registered model and corresponding metadata, and executing integrity check to generate an integrity check result; generating a model identifier for the to-be-registered model according to an integrity check result, and storing the model identifier into a model storage warehouse; receiving a deployment request, and extracting a target model file and target metadata according to the deployment request; selecting a target computing node according to the target metadata; configuring a running environment according to a deployment environment requirement, and combining the target model file with the running environment to obtain a container mirror image; creating a containerized operation instance based on the container mirror image, and configuring a network access endpoint; predicting the page view of the network access endpoint to obtain predicted page view data; and adjusting the number of the containerized operation instances according to the predicted page view data and the system resource use data. By implementing the technical scheme, the problems of hysteresis and lack of perspectiveness of resource adjustment based on a real-time system load are solved.

A method of displaying an operational parameter of a surgical system is disclosed. The method includes receiving, by a cloud computing system of the surgical system, first usage data, from a first subset of surgical hubs of the surgical system; receiving, by the cloud computing system, second usage data, from a second subset of surgical hubs of the surgical system; analyzing, by the cloud computing system, the first and the second usage data to correlate the first and the second usage data with surgical outcome data; determining, by the cloud computing system, based on the correlation, a recommended medical resource usage configuration; and displaying, on respective displays on the first and the second subset of surgical hubs, indications of the recommended medical resource usage configuration.

Systems, methods, and computer-readable media are provided for triggering functionality on data to be generated in a user interface and / or data shown or visualized in a user interface based on a natural language request that references actions to be performed and data items to use in performing the actions. The user interface actions are triggered based on a structured object generated by a large language model (LLM), which may then be processed, validated, and used to carry out the actions. The LLM may be instructed to use control(s) of a displayed representation of a set of data, and the structured object generated by the LLM may cause updating, on the user interface, the displayed representation to reflect change(s) requested (e.g., to adjust filters, change a visualization or view, or zoom in or out on a set of multidimensional data). The control(s) may be selected from among representation transformation action(s) that are also available to be performed against the displayed representation via direct user input.

The invention belongs to the technical field of information retrieval, and discloses a structure-enhanced SQL (Structured Query Language) generation method for information retrieval, which comprises the following steps of: constructing and encoding a query graph, a mode graph and a standard knowledge graph, and capturing semantic information of natural language query, structural characteristics of a database and standard semantic reference; candidate nodes are screened based on semantic similarity, a mixed sub-graph is constructed, an alignment model is trained in combination with a loss function, and an entity alignment result of a query graph and a standard knowledge graph is obtained in combination with a predefined link set, so that semantic fuzziness can be reduced; an example prompt library is constructed through de-semantization, the most similar examples are screened, and the adaptability of the model to a query mode is enhanced by means of few-sample learning; the syntax tree is traversed to decompose subtasks, so that the reasoning difficulty of complex query can be reduced; according to the method, the accuracy and robustness of the Text-to-SQL task are remarkably improved, the threshold for non-technical personnel to use the database is lowered, and the information retrieval requirement is efficiently met.

The embodiment of the invention discloses a cluster tenant resource scheduling method and device, electronic equipment and a storage medium, relates to a cloud computing technology and can be used in the field of financial science and technology, and the method comprises the following steps: predicting a future resource demand of a target tenant namespace based on historical resource use data of the target tenant namespace in a cluster, the target tenant namespace comprises a tenant namespace bearing a key service; determining a real-time resource quota of the target tenant namespace based on the available resources of the shared pool and the future resource demand predicted value, the service level and the comprehensive priority of the target tenant namespace; and performing real-time resource scheduling on the target tenant namespace based on the real-time resource quota. According to the embodiment of the invention, the service quality of key services in a multi-tenant mixed deployment scene can be improved, and the resource utilization rate can be effectively improved.

The invention provides a cloud platform database storage use prediction method based on time sequence modeling, and belongs to the technical field of cloud computing operation and maintenance management. The method comprises the steps that historical storage use data of a target database in a cloud platform is collected, a time sequence prediction model is built based on the historical storage use data, and the time sequence prediction model is a Prophet model supporting trend term and periodic term modeling; using the time sequence prediction model to predict the storage usage amount of the target database in a future preset period, and generating a prediction result value; and comparing the prediction result value with a preset capacity threshold value, and if the prediction result value exceeds the preset capacity threshold value, generating capacity early warning information. By automatically and accurately predicting the use trend of database storage and providing early warning information, the automation and foresight of database capacity management are improved.

The invention provides a material scheduling method, a computer readable storage medium and a material scheduling system.The material scheduling method comprises the steps that material information of to-be-warehoused materials is received, multiple candidate warehouse areas are determined according to the material information, and the material information comprises a material sequence of the to-be-warehoused materials; determining a target reservoir area from the plurality of candidate reservoir areas at least according to the historical use data of each candidate reservoir area, the distance between each candidate reservoir area and the target position and the residual storage amount of each candidate reservoir area; determining whether a target bearing tool exists in the target reservoir area according to the material sequence; determining a final bearing tool from the target bearing tools under the condition that the target bearing tools exist in the target reservoir area, and determining the final bearing tool from the empty bearing tools of the target reservoir area under the condition that the target bearing tools do not exist in the target reservoir area; and according to the position of the final bearing tool, taking and placing equipment is controlled to carry the to-be-warehoused materials into the final bearing tool from the warehousing opening.

Systems and methods have been developed to increase user compliance and adherence to various devices and services including respiratory therapy devices, exercise equipment, and online or other software services. For instance, in some examples the disclosed technology may monitor usage data output from a respiratory therapy device, exercise equipment or computer software program to determine, based on the trends of usage, when a user is likely to terminate or reduce usage within a specified time window. Flagging a user may also trigger further actions to automatically intervene before the user terminates engagement with the service.

The embodiment of the specification provides a gas safety management method and an Internet of Things system for gas safety training. The method is executed based on a wisdom gas safety management platform of a gas safety management Internet of Things system for gas safety training. The method comprises the following steps: acquiring gas use data of at least one gas use end, wherein the gas use data comprises at least one of a gas use amount, gas alarm data and gas maintenance data; determining a user type of each of the at least one gas use end based on the gas use data of the at least one gas use end, and determining a gas safety training scheme corresponding to each user type; pushing a safety training to a corresponding user terminal based on the gas safety training scheme; acquiring feedback information of the user terminal; determining a gas safety detection frequency of the gas use end of each user type and a gas safety risk level of the gas use end of each user type based on the feedback information corresponding to each user type and the gas use data corresponding to each user type.

The invention relates to the field of data storage, in particular to a block chain technology-based data storage system, which comprises a registration platform, data extraction, comparison verification, data storage and overall operation, and is characterized in that the registration platform comprises an operation platform, personnel authentication and personnel identification; the data extraction comprises data indexing, data exporting, data integrating and recording taking; the comparison verification comprises marking point comparison, page comparison and verification recording; according to the method, uploaded data are split and fragmented, then the fragmented data are randomly stored in regional chain nodes with similar data, and the fragmented data are covered by the same data, so that the fragmented data are shielded to a certain degree, and meanwhile, exclusive data of the fragmented data are subjected to certain replacement through a secret library for encryption; therefore, the data is prevented from being leaked, and the accuracy of the data can be known through the use record when the data is used, so that the safety and the accuracy of the data used by the user are guaranteed.

The invention discloses a cyclic resource scheduling method, system and device based on Kubernetes and a medium, and the method specifically comprises the steps: collecting resource use data of Pod and nodes in a Kubernetes cluster in real time, and predicting a load trend; dividing the resources into a hot resource pool, a cold resource pool and an idle resource pool based on the prediction results of the resource use data and the load trend; according to the electricity price and carbon emission data of each region, dynamically adjusting task distribution, and preferentially scheduling the task of the thermal resource pool to a region with a high renewable energy source proportion; for the cold resource pool and the idle resource pool, executing a progressive dormancy process by monitoring the power consumption change in real time; and training a reinforcement learning scheduling strategy by taking the queue length of the hot resource pool, the recovery time of the cold resource pool and the calling frequency of the idle resource pool as input. According to the invention, intelligent cyclic scheduling of Kubernetes cluster resources is realized, the resource utilization rate is improved, the energy consumption cost is reduced, the service continuity is guaranteed, and the intelligent level of scheduling decision is improved.

Embodiments of the disclosed technologies are capable of deconstructing a graph using database management approaches. Embodiments describe receiving an event trigger associated with a first node of a graph. The event trigger includes a node identifier of the first node. The embodiments further describe generating a first query for a neighbor identifier associated with a second node of the graph using the node identifier. The neighbor identifier is queried from a first data store. Embodiments further describe generating a second query for a feature corresponding to the neighbor identifier. The feature is queried from a second data store. Embodiments further describe generating an embedding of the event trigger using the node identifier, the neighbor identifier and the feature.

There is provided a method of improving the operation of a generative AI large language model (LLM)-based data processing system, by operating the LLM-based system in conjunction with a non-LLM data processing system; and in which (a) the LLM-based system sends a continuation as an input to the non-LLM system, and (b) the non-LLM system (i) uses symbolic representations to perform non-statistical reasoning on the input from the LLM-based system and (ii) generates a reasoned prompt or other context.

Illustrative embodiments provide a system, method, platform, and block chain network for managing licensing, distribution, and monetization of digital content across multiple platforms. A content platform receives a digital representation of content and associated copyright information. Usage data associated with a request to utilize the content is detected, including device type, application type, geographic region, or distribution channel. One or more licensing parameters are identified based on the usage data, and a license instance is automatically generated for the requested utilization. Usage of the content is tracked, and compensation is calculated for one or more copyright owners according to monetization terms.

The invention discloses a filter element anti-counterfeiting and full life cycle management device and method, and relates to the technical field of filter element anti-counterfeiting, the filter element anti-counterfeiting and full life cycle management device comprises a production management device, an anti-counterfeiting filter element is manufactured and produced by the production management device, the anti-counterfeiting filter element is installed on a whole water purifier, and the anti-counterfeiting filter element is used for filtering water flow discharged by the whole water purifier; the user module is connected with the whole water purifier, the user module is used for controlling the whole water purifier to quantitatively drain water, the cloud server is connected with the user module, and the cloud server is used for regulating and managing the whole water purifier and the anti-counterfeiting filter element through the user module. According to the filter element anti-counterfeiting and full-life-cycle management device, the two-dimensional code plaintext SN and the chip encryption SN are associated through the cloud end, the product is judged to be a certified product only when the two SN are matched and are not activated, the problem that a static two-dimensional code is easy to copy is solved, chip physical locking accumulated values are only accumulated and do not modify characteristics, and a host encryption instruction is combined, so that the anti-counterfeiting and full-life-cycle management of the filter element is realized. And the usage data are real and cannot be tampered.

A system for transferring a session between devices includes a first device including a first software development kit for collecting data and behaviors related to viewing digital media on the first device, a second device including a second SDK for collecting data and behaviors related to viewing digital media on the second device, and an intermediary device coupled to the first and second devices, including a collection of the data and behavior received from the first and second devices, and a session transfer function operating to use the collection of data and behavior to identify a use of an application on the second device to view a digital media representation present in an application on the first device, determine a session of the application on the first device, and transfer the session to the second device without requiring authentication for the use of the second device.

The application relates to the technical field of echo data prediction, and discloses an echo map prediction method and system based on prior data, a terminal and a storage medium.The method comprises the following steps: constructing an echo model, defining a plurality of parameters of a training vehicle, receiving reflection signals of the training vehicle by using the echo model to obtain a plurality of signals, and sampling original data after screening and processing; performing multi-dimensional fast Fourier transform on the original data to output an echo map; and predicting a target vehicle after training a U-Net network by using the echo map, and outputting a target echo map.The application takes the advantages of a signal-level radar model based on a mechanism architecture as a prior model in real-time performance, high generalization capability and main feature prediction accuracy, generates main features in an echo map according to scene information, and then uses a data-driven model to quickly adjust detailed parts of the echo map, so that the shortcomings of the prior model in detailed feature prediction are made up, and the prediction accuracy of the echo map is significantly improved.

An object of a system according to an embodiment is to appropriately evaluate a usage status of a business messaging platform of a small-to-medium-sized company and provide the evaluation result to a financial institution or the like.SOLUTION: A system according to an embodiment includes a data collection unit, an analysis unit, a scoring model construction unit, and an evaluation provision unit. The data collector collects usage data of the business messaging platform. The analysis unit analyzes the data collected by the data collection unit. The scoring model construction unit constructs a unique scoring model based on the data analyzed by the analysis unit. The evaluation providing unit provides an evaluation result to a financial institution or the like based on the scoring model constructed by the scoring model construction unit.SELECTED DRAWING: Figure 1

The present disclosure relates to a computing high speed link (CXL) device configured to protect data by using data encryption and a method of operation thereof. An example CXL device includes a volatile memory connected to a plurality of channels; and a CXL controller. The CXL controller includes: a CXL subsystem controller configured to search a key index table for a first key index based on first host data and a first device physical address; and a memory subsystem controller configured to search for at least one first key in a key table based on the first key index, and generate first encrypted data based on the first data, the first device physical address, the at least one first key, and an encryption algorithm.

This system provides a systematic mechanism for permanently saving and utilizing voice messages sent from simple devices such as GPS terminals, without requiring users to take any extra effort. Conventional technologies had problems such as voice messages being lost after the server's storage period expired, or users having to manually save them. [Solution] An information processing device receives voice messages transmitted from a GPS terminal and forwards them to a display terminal. The information processing device extracts voice characteristics, keywords, contextual information, etc., from the voice message and scores the message's value for saving. For messages with high scores, it sends a notification to the display terminal recommending saving. In addition, upon request from the display terminal, it sends the voice message in a data format that can be saved. This prevents users from missing valuable messages and allows them to easily save and utilize data.

Computer-implemented methods, mobile computing devices, and tangible, non-transitory computer-readable media storing instructions for creating one or more new insurance policy quotes for a customer associated with a customer vehicle may be described. The computer-implemented methods may include tracking, by a mobile computing device in conjunction with one or more sensors, a particular type of usage data of a customer vehicle based on a coverage type, of a plurality of coverage types, for the customer vehicle, wherein a first type of usage data is tracked for a first coverage type and a second type of usage data is tracked for a second coverage type, the first type of usage data being distinct from the second type of usage data; and transmitting, by the mobile computing device to a computing device, the particular type of usage data.

A backup process implemented by generating data to be backed up from a file-based application or an object-based application from a respective application host. A generic proxy component collocated with the application host is deployed and contains protocol specific servers and a DDBoost client. The data is transmitted from the application host to the generic proxy using a defined file transfer protocol. The data is then transformed in a protocol specific server of the generic proxy to a format compatible with the DDBoost client, and to leverage distributed segment processing (DSP) to optimize data transfers using the generic proxy. The transformed data is then transmitted to a backup system over a network using a data transmission protocol and the data stored by the backup system in a data storage target.

The application provides a multi-isomer third-party eSIM package standardization adaptation and intelligent scheduling system and method, comprising: analyzing the package advantages and package protocols corresponding to each operator, generating an operation adaptation rule library in combination with a preset unified interface specification, supervising the remaining life cycle of the purchased package of a user, inferring the user demand of the user when using the eSIM package in combination with historical use data, screening the package matched with the user demand information in the operation adaptation rule library, and constructing a corresponding adaptation display path to put the package on the shelf, filtering inefficient packages with insufficient display times or insufficient remaining validity period, and updating each operation adaptation rule library, performing multi-dimensional evaluation on the put-on package according to the user demand, recommending the best put-on package to the user according to the evaluation result, avoiding the one-sidedness of the recommendation caused by single-dimensional evaluation, and guaranteeing the scientificity and rationality of the recommended result.

The invention relates to the technical field of information processing, in particular to an intelligent identification method, device and equipment for a logistics environment-friendly bag and a storage medium. A multi-channel input tensor is constructed through a visible light texture image, a near-infrared reflectivity image and three-dimensional point cloud data of the logistics environment-friendly bag; a light diffusion model is used for enhancing a low-illumination image in the multi-channel input tensor, the standardized multi-channel input tensor is input into an OneThinker model for contamination degree quantification, and a life prediction basic feature vector is constructed based on contamination degree information, accumulated use frequency information and stress historical information; and based on the life prediction basic feature vector, the historical use data and the transportation environment temperature and humidity data, adopting a lightweight graph neural network or a long-short-term memory network to model an aging process of the logistics environment-friendly bag, and outputting a predicted value of the number of remaining usable times of the logistics environment-friendly bag according to the aging process. And accurate identification, intelligent state evaluation and scientific life prediction of the logistics environment-friendly bag can be realized.

A system is provided.SOLUTION: A system comprising: means for acquiring energy and water usage data in real time from sensors installed in each home or business; means for cleaning the acquired data, removing noise, and converting the data into a format suitable for learning; means for training a model using the cleaned data and generating an algorithm for proposing an optimal resource management method for each home or business; means for generating a specific action plan based on an analysis result and delivering the action plan to a user; and means for collecting feedback from the user and retraining the model.SELECTED DRAWING: Figure 1

The invention provides a scaffold monitoring management system and method, and the system comprises a component identification module which is used for distributing and managing a unique digital identification code for each scaffold component; the digital archive module is associated with the component identification module and used for establishing and maintaining a digital archive for each scaffold component, and the digital archive at least comprises specification information, state information and dynamically updated historical use data of the component; the circulation monitoring module is used for tracking and recording circulation states and events of each scaffold component in the links of warehousing, ex-warehouse, project erection, warehouse returning and scrapping based on the digital identification codes; and the health degree evaluation module is used for calculating the dynamic health degree of each scaffold component through a preset evaluation model based on the component historical use data and state information recorded in the digital file module. The invention aims to improve the safety, economy and refinement level of scaffold management.

The invention provides an annotation-driven database field encryption and decryption method and device, and the method comprises the steps: adding an encryption annotation at a specific business interface, encrypting all request parameters for accessing the business interface, encrypting a specific field based on the parameters of the interface annotation, transmitting the encrypted data to a persistence layer through a business layer, and carrying out the encryption of the specific field through the persistence layer. The persistence layer stores the encrypted data into a database; and the decryption annotation is added to a data return interface of the service layer, decryption is carried out according to the data inquired from the persistence layer and in combination with the annotation field, the decrypted data is returned to the control layer, and the control layer returns the data to the user side. The method does not depend on the database type and the encryption and decryption algorithm type, interception encryption and decryption are carried out on different tables and different fields based on annotation definition and analysis, and data privacy is protected again in the process of normally using the database.