707 results about "Data needs" patented technology

The embodiment of the invention discloses an in-memory computing circuit based on a magnetic cache, and the circuit comprises at least one magnetic cache unit, at least one in-memory computing unit, and a timer. The magnetic cache unit in the at least one magnetic cache unit is used for caching data output by the corresponding in-memory computing unit as to-be-processed data within the corresponding data retention time; the timer is used for respectively setting data retention time for the at least one magnetic cache unit; and the in-memory computing unit in the at least one in-memory computing unit is used for extracting the data to be processed from the corresponding magnetic cache unit for calculation and outputting the computed data to other magnetic cache units. According to the embodiment of the invention, the invention achieves the flexible adjustment of the data retention time of the magnetic cache unit in various in-memory calculation scenes, and achieves the provision of a high-capacity cache for the data needed by in-memory computing under the lower power consumption.

The invention provides a method and a device for generating a customized report of an SAAS (Software as a Service) system based on dynamic template configuration. The method comprises the following steps: acquiring a customized visual report template for realizing business data decoupling; editing the report template based on a preset editor, and generating a template configuration file; analyzing a structured marker in the template configuration file to generate a metadata description file; querying a business database through a unified data interface according to a data requirement defined by the metadata description file, and obtaining and assembling customized business data corresponding to the tenant ID; and at least based on the customized business data, controlling a rendering process through a dynamic position calculation algorithm, and dynamically filling the data to a corresponding position of the report template to generate a customized report. According to the method, the problems of code redundancy and difficulty in maintenance of the SAAS multi-tenant report are solved, zero code configuration is realized, and report generation efficiency and tenant personalized adaptation capability are improved.

The invention discloses a data classification and grading method and device based on rule engine and artificial intelligence fusion, and belongs to the technical field of Internet, and the method comprises the steps: obtaining source data needing to be classified and graded, and processing the source data into source data in a uniform format; training the extracted useful features to obtain a trained artificial intelligence model, and predicting the preprocessed source data through the trained artificial intelligence model to obtain a data classification and grading result output by the artificial intelligence model; the rule engine performs preliminary classification and grading on the preprocessed source data according to a set data classification and grading rule to obtain a preliminary classification and grading result; and fusing a data classification and grading result output by the artificial intelligence model with a preliminary classification and grading result output by the rule engine to generate a final accurate and reliable data classification and grading result. According to the invention, interaction between the user and the advertisement content through voice or gestures is supported, so that the attraction and effect of the advertisement are improved.

The invention provides a number card distribution system based on message middleware, relates to the field of data management, and solves the technical problem of high data storage security risk of an existing number card distribution system. The system comprises a message center module which is used for processing asynchronous communication and data transmission in the system by adopting a distributed message middleware cluster; the data security module is used for managing distribution data of each region by adopting a data fragmentation storage mechanism; and the demand prediction module is used for predicting the number card demand quantity of the next period according to the sales data and the demographic data of each region, and guiding the formulation of a sales strategy of the next period. The method and the device are used in the whole-process management process of the number card distribution service.

The application discloses a short video code rate self-adaptive method based on meta learning, relates to the technical field of streaming media, and comprises the following steps: S1, offline training, a model is established to represent user characteristics and network prediction information; S2, online learning, according to the characteristics of the current user environment, the model parameters are adjusted and optimized. The short video code rate self-adaptive method based on meta learning is adopted, a new SABR framework based on meta learning is successfully realized, the framework can quickly adapt to different user demands, the practicability and the calculation speed of the system are improved, and the framework has industrial application; the offline training and the online learning technology are successfully combined, the generalization and the stability of the model are enhanced; the idea of action masking is introduced in pre-training, the rationality and the reliability of decision are enhanced, the data amount required by meta learning is effectively reduced, the learning efficiency and the accuracy are improved, and the data demand and the training time in the industrial environment are significantly reduced.

The invention discloses a data processing method and device, a medium, equipment and a product. According to the scheme, after the data platform receives the data processing request sent by the data demander, the encrypted first privacy data set can be determined according to the data processing request, and the privacy data set can be processed based on the user data adopted by at least one data provider. The method comprises the following steps: acquiring a first private data set, acquiring a second private data set encrypted by adopting an encryption mode of encrypting the first private data set, comparing the first private data set with the second private data set to obtain an intersection data set, and further returning a service result for a specified service to a data demander based on the obtained intersection data set.

The invention provides an exception handling method and device, a storage medium, electronic equipment and a product. The exception handling method is applied to a credit investigation system corresponding to a credit investigation mechanism, and comprises the following steps: receiving a data query request for target data sent by a data demand side, and querying the target data from a data provider according to the data query request; processing the target data returned by the data provider to obtain a processing result; if the data processing result is successful, credit investigation data obtained after the target data is processed is returned to the data demander; if the data processing result is failure, determining a failure type causing data processing failure based on an abnormal state code carried in the data processing result, and triggering an exception processing flow matched with the failure type; wherein different abnormal state codes correspond to different failure types, and the failure types comprise service side failures caused by inconformity with service rules and system side failures caused by abnormity of the credit investigation system.

The invention relates to a branch database management method and device, computer equipment and a storage medium. The method comprises the steps that in response to a first change request for a branch database, the existence state of first to-be-changed data in a branch data block needing to be changed in the branch database is determined; the branch database is used for recording database contents in the original database at a target moment; the target moment is an establishment moment of the branch database; under the condition that the existence state characterization branch database does not exist, obtaining a first snapshot of the branch data block; generating a branch data block in a branch database according to the first snapshot; and executing a change operation matched with the first change request on the first to-be-changed data in the branch data block. By adopting the method, the influence on the performance of the original database can be reduced to the greatest extent, and continuous and stable operation of the main business is guaranteed.

The invention provides an operation system and an operation control method of an intelligent agent product. According to the system, through a knowledge base templated import and dynamic maintenance mechanism, batch rapid import of multi-format product documents can be supported, and manual operation is greatly reduced. According to the system, a fine-grained multi-role authority management system is constructed, authority boundaries of a super administrator, an operation administrator, customer service personnel and equipment developers are clearly divided, and the safety and manageability of the system are enhanced. The system can comprehensively collect and analyze operation data including question and answer logs, control logs, model calling times, cost and the like; a multi-dimensional operation result is generated through hotspot problem analysis, control frequency statistics and the like, meanwhile, the cost-benefit ratio is calculated, and a data basis is provided for identifying user requirements and optimizing an intelligent agent response strategy. According to the system, through standardization and configuration design of an equipment adaptation process, a novel equipment access template is provided, a data demand and a test process are defined, a new product access period is shortened, and the market response speed is improved.

The invention provides an AI-driven heterogeneous data optimization management method and system, and the method comprises the steps: extracting the production dynamics, equipment association and data demand dimensions in a flexible production scene through AI modeling, constructing a scene knowledge graph, carrying out the analysis of data from a heterogeneous terminal, and converting the data into a standard format matched with a current production scene; according to a multi-dimensional association relationship in the scene knowledge graph, performing exception recognition, deletion repair or redundancy elimination on the data in the standardized format to realize quality optimization, allocating storage resources for the data subjected to quality optimization, and pre-loading associated data before nodes are produced; according to the method, decision information for production scheduling, equipment predictive maintenance and product quality tracing is output in combination with the incidence relation among equipment, processes and data defined in the scene knowledge graph, and the timeliness and accuracy of core services such as production scheduling, equipment maintenance and quality tracing are improved by constructing and updating the scene knowledge graph in real time.

The invention provides a positioning method and a positioning device, the positioning device can comprise a transducer module, the transducer module can comprise a plurality of transducers sharing the same piezoelectric material, and the plurality of transducers can be used for receiving sound signals emitted by a sound source. The positioning device can determine the position of the sound source according to the sound signals received by the plurality of transducers. The effective working area of the transducers sharing the same piezoelectric material is larger, and the transducers can receive sound signals with lower frequency due to the larger effective working area. In the process of positioning the sound source, the positioning device can sample the sound signal with the lower frequency by adopting the lower sampling frequency, so that the amount of data needing to be processed in unit time is less, and the power consumption is lower. The transducer module can be suitable for a positioning device with a limited accommodating space, and the accuracy of sound source positioning by using the transducer module is higher.

The invention discloses a prefabricated part quality optimization method and system based on digital twinning, and relates to the technical field of digital twinning. The method comprises the following steps: constructing a sample performance data set; determining a plurality of prediction time scales of the component, and recombining the data set to construct a component index prediction agent model group containing the corresponding time scales; and acquiring a real-time digital twinborn model of the component, establishing a design optimization problem in combination with the proxy model group, and updating the digital twinborn model by solving the optimization problem to realize quality optimization. According to the method, through multi-time scale decomposition and cascade knowledge distillation training, the precision and efficiency of long-term performance prediction are improved while the high-fidelity data requirement is reduced, meanwhile, the prediction reliability and the adaptive evolution ability of the model are ensured in combination with multi-model cross check and a trigger type feedback mechanism, and the prediction efficiency is improved. Accurate prediction and reliable lightweight design of the full life cycle performance of the prefabricated part are achieved.

The invention provides a regression test method and device, a storage medium, electronic equipment and a product. The regression test method comprises the following steps: acquiring credit investigation service data generated by a credit investigation system in a process of executing an actual credit investigation service, the credit investigation service data comprises input request parameters input by the data demander to the credit investigation system, original data returned by the data provider to the credit investigation system, actual output request parameters sent by the credit investigation system to the data provider and actual credit investigation data returned by the credit investigation system to the data demander; after business change is executed on the credit investigation system, inputting the input request parameter into the credit investigation system to obtain an analog output request parameter, and inputting the original data into the credit investigation system to obtain analog credit investigation data; and according to the deviation between the actual output request parameter and the analog output request parameter and the deviation between the actual credit investigation data and the analog credit investigation data, determining whether the credit investigation system successfully completes the business change.

The present application relates to the technical field of computers. Disclosed are an implementation method for an immersive conference, and a related electronic device. In the method, a 3D stereoscopic image of a second conference participant is constructed by using a second rendering model, and instead of an original video stream, only a relatively small amount of feature data needs to be transmitted, thereby effectively reducing the network bandwidth required by transmission; each conference participant can obtain the 3D stereoscopic image of the second conference participant at his / her own angle of view, thereby supporting a multi-person and multi-angle of view mode; and by means of the pre-constructed second rendering model, the 3D stereoscopic image of the second conference participant can be reconstructed in real time on the basis of the feature data, without the need for complex real-time rendering calculation, such that the overall rendering efficiency is improved, and even a terminal device with a relatively weak performance can also smoothly present a vivid 3D visual effect. The present application reduces the network bandwidth required by transmission, enables each conference participant to obtain an immersive experience at his / her own angle of view, and also improves the overall rendering efficiency.

The invention provides a medical data intelligent query analysis method, system and device and a medium, and belongs to the technical field of medical data query. The method comprises the steps that a query request of a medical worker is responded, and a first analysis instruction is generated in combination with the role of the medical worker, the emergency degree of a diagnosis and treatment scene, historical behaviors and patient real-time data; and calling a rendering engine to generate an adaptive visual interface according to the terminal type and the like. And then receiving a second analysis instruction with a larger analysis amount, evaluating the data demand complexity of the second analysis instruction, and after identifying a data gap with the first instruction, calling the knowledge base and the interface supplementary data to generate second medical query information. And then identifying the difference between the first analysis instruction and the second analysis instruction, generating a recommendation card based on historical interaction, performing split-screen comparison or progressive replacement display, recording, feeding back and updating the user preference model, further adjusting a subsequent first analysis instruction generation strategy, and circularly responding to a new request. The whole medical query requirement can be accurately met, the information display suitability and the interaction efficiency are improved, the user experience is optimized, and efficient diagnosis and treatment are assisted.

The invention relates to the technical field of data circulation and data security, and discloses a digital ecological data market circulation system, comprising: a data provider node deployed with a federated learning client and used for locally training a model by using original data, generating an encrypted intermediate result and managing a corresponding data asset voucher; the data demand side node is deployed with a federated learning coordination server and is used for defining a federated learning task, distributing an initial model and aggregating intermediate results from each data provider node to update a global model; the data element circulation method comprises the following steps of data capitalization and voucher generation, federal learning and process evidence storage, under-chain credible contribution degree evaluation and intelligent contract driven settlement. Compared with the prior art, the method has the advantages that the leakage risk is completely eradicated from the root of technology, a dynamic and accurate value evaluation and distribution system is achieved, a credible environment which is traceable in the whole process and transparent in rule is constructed, and the mobility and financial attributes of data assets are improved.

The invention discloses a task scheduling method and system based on dynamic credibility and data security level self-adaption, and relates to the field of task scheduling, and the method comprises the steps: obtaining the data security level of target data needing to be processed by a to-be-scheduled task; matching the data security level with node trust degrees of a plurality of preset computing nodes to determine candidate computing nodes in the plurality of preset computing nodes; determining a target computing node in the candidate computing nodes; scheduling the to-be-scheduled task to the target computing node for execution; obtaining execution state data of the to-be-scheduled task on the target computing node; and updating the node credibility of the target computing node based on the execution state data. By implementing the method and the device, an intelligent matching mechanism between the data security level of the to-be-scheduled task and the dynamically updated node trust degree can be realized, so that the security of related data of the to-be-scheduled task is ensured by utilizing the dynamically updated node trust degree.

The invention provides a virtual power plant load resource allocation method and system based on comprehensive energy storage, and relates to the technical field of power systems, comprising the steps of obtaining operation state data, a demand response instruction and power demand data, analyzing operation characteristics of multiple types of energy storage equipment, constructing a demand response optimization target, and quantifying the response capability of an energy storage cluster. A demand response task is decomposed into a continuous adjustment task and a transient balance task which are respectively allocated to energy-type and power-type energy storage devices, a dynamic coupling relationship is established, rolling prediction is performed, and a scheduling priority and a power allocation proportion are dynamically adjusted. The virtual power plant response capability can be improved, the resource configuration efficiency can be optimized, and the system stability can be enhanced.

The invention discloses a federal forgetting learning method based on knowledge distillation, and the method simplifies the two steps of target data influence removal in the forgetting process and model performance maintenance after forgetting into one step through a teacher-student model structure. When the server receives a forgetting request, the server issues a forgetting instruction and a global model copy to each client; the client divides data needing to be forgotten and reserved data according to local data and generates three types of teacher models; carrying out local training on the student model under the guidance of a plurality of teacher models, learning random distribution on target forgotten data so as to eliminate the influence of trained knowledge, and meanwhile, keeping prediction performance consistent with an original model and a real label on reserved data; then, each client uploads the updated model to the server, and the server aggregates the update and judges whether forgetting is completed or not; by means of the method, efficient data forgetting can be achieved under the condition that the global model is not retrained, and meanwhile reduction of model performance on reserved data is avoided.

The invention is suitable for the technical field of real-time audio and video communication and digital human interaction, and provides a real-time digital human audio and video synchronization method and device based on TRTC. In the embodiment of the invention, for the voice data needing to be synchronized, the device firstly converts the voice data into the audio stream and uploads the audio stream to the cloud server, and then the cloud server generates the lip-shaped video stream according to the lip-shaped action video clip pre-generated based on the digital human image; the method comprises the following steps: receiving a lip-shaped video stream, generating a second audio stream of which the timestamp is synchronous with that of the lip-shaped video stream, returning the lip-shaped video stream and the second audio stream to equipment, and finally playing by the equipment according to the timestamps in the lip-shaped video stream and the second audio stream, thereby realizing audio and video synchronization. Therefore, the system delay of the real-time dialogue of the digital person is greatly reduced, the phenomenon that the sound and the mouth shape are not synchronous is effectively avoided, and the problem that low delay and high-precision mouth shape synchronization are difficult to consider when the digital person type and the voice are synchronous is solved.

This invention discloses an end-to-end examination behavior analysis method and system, comprising a video input management module, a video decoding module, an image preprocessing module, a raw frame prediction queue, a raw frame queue, an AI module, an analysis result recording module, and an abnormal event video generation module. It utilizes an end-to-end AI model training and inference scheme, enabling efficient training using large amounts of historical data. In practice, it offers fast processing speed and high efficiency. The end-to-end AI model takes continuous video frames as input and outputs bounding boxes indicating suspected violations after inference. In the post-processing section, the model output undergoes spatiotemporal correlation and filtering to finally generate spatiotemporal location information of suspected violations. It exhibits good scene adaptability; when new scenes are needed or new actions to be identified are added, only new training data needs to be added and retrained to expand the algorithm, saving manpower and improving efficiency.

A first dashboard is generated utilizing a machine learning model and user settings associated with a user. One or more follow-up prompts are received. Data needed to answer the one or more follow-up prompts is determined and obtained utilizing one or more data catalogs. One or more subsequent dashboards are generated utilizing the machine learning model and the user settings associated with the user.

The invention provides a data forwarding method, device and system, relates to the technical field of satellite communication, and is applied to a system comprising a satellite and user equipment, in the method, the satellite receives and stores data needing to be forwarded to the user equipment in a target service area in advance, and when the satellite enters the target service area, the data are forwarded to the user equipment in the target service area. The satellite respectively forwards data to user equipment in different sub-service areas in different time periods, the target service area is divided into N sub-service areas, the service time of the satellite in the target service area is divided into a plurality of time periods, the plurality of time periods comprise N time periods, and the N time periods are in one-to-one correspondence with the N sub-service areas. According to the application, the data is forwarded to the user equipment in the target service area in a batch forwarding mode, so that the problems of network congestion, signaling storm and the like can be avoided.

The invention relates to the technical field of data encryption, in particular to a transmission encryption method based on a Beidou communication data architecture, which comprises the following steps of: S1) adjusting related communication data and calibrating the related communication data as a data item to be filled or a data item to be missing based on the related communication data needing to be transmitted in the stage and an adaptive data transmission channel in the related data architecture; s2) performing priority processing on the to-be-missing data items, selecting part of data from the corresponding to-be-missing data items based on changed capacity data of the to-be-missing data items, calibrating the part of data as to-be-filled data, then determining to-be-transmitted missing items, performing related filling on the to-be-filled data items, and preferentially confirming filling capacity data corresponding to the to-be-filled data items; relevant data are selected from the to-be-filled data, and then to-be-transmitted filling items are determined; and S3) performing data transmission based on the determined data transmission channel of the corresponding data item, and determining an encryption key of the corresponding data item based on the transmission delay of each group of different data items in the transmission process.

The invention discloses an LWIP TTE network adaptation system based on a static ARP table. The LWIP TTE network adaptation system comprises a transmission module, a protocol conversion module, an LWIP protocol stack and a network calling module. The transmission module enables the standard TTE frame to be normally transmitted on the TTE switch; the protocol conversion module is used for protocol adaptation and data conversion; the LWIP protocol stack is used for packaging data needing to be sent and analyzing a received standard IP data packet; and the network calling module is used for transmitting the data and the target IP address information to the LWIP protocol stack and receiving a data packet fed back by the LWIP protocol stack. Protocol adaptation and data conversion are carried out through the protocol conversion module, the communication barrier between an IP protocol and a TTE protocol is broken, and conversion from an IP address to a communication identifier supported by TTE is realized; the network adaptation system uses the simple query logic of the LWIP protocol stack and the static address mapping table, so that the embedded program developed by depending on the TCP / IP protocol stack can be accessed to the TTE network at low cost, and the complexity of program migration work is simplified.

A data transaction system and method based on data empowerment, the system comprises an identity authentication module for receiving input of the identity information of a provider or a demander, and obtaining a score matched with the identity information of the provider or the demander; a provider module for registering data matched with the score of the data provider according to the score of the data provider; a demander module for calling data matched with the score of the data demander according to the score of the data demander, and generating a transaction request according to selected to-be-transacted data; a management platform for storing registered data and user information, classifying and grading the stored data, scoring the user information, and feeding back the score matched with the provider or the demander to the identity authentication module; and a transaction module for auditing the transaction request and the information of the transaction parties, and sending the demander information and the transaction request to the provider after the audit is passed, and completing the data transaction and empowerment after the provider is verified.

The invention discloses a cross-scene self-adaptive flexible load dynamic interval prediction method. The method comprises the following steps of multi-modal scene identification, dynamic interval prediction and cross-scene self-adaptive migration. According to the cross-scene adaptive flexible load dynamic interval prediction method provided by the invention, the cross-scene adaptive capability is realized, automatic identification of industrial, commercial and resident scenes is realized, cross-scene prediction MAPE errors are reduced to be within 3%, which is better than that of a traditional model, the interval reliability is improved, quantile non-cross constraint enables PICP to be stabilized to be more than 95%, PINAW is reduced to be 5%-8%, and the interval reliability is improved. According to the method, the requirement of power grid dispatching for a narrow and reliable interval is met, knowledge migration is efficient, through field adaptive migration learning, the new scene model training time is shortened by 60%, the data demand quantity is reduced by 50%, and the engineering application cost is reduced.

The invention specifically discloses a data skeleton matching method and system based on an intelligent Internet of Vehicles environment, and the method comprises the steps: carrying out the type division of a vehicle according to the automatic driving level of the vehicle, calculating the specific data demand intensity, scene emergency degree score and communication constraint degree of the vehicle, constructing a quantitative model based on a spatial view level demand, calculating a view demand factor, and determining the spatial view level demand; global fusion is carried out on the vehicle automatic driving level, the specific data demand intensity of the vehicle, the scene emergency degree score, the communication constraint degree and the view demand, and the precision level and scale of a final data skeleton are output; and according to the precision grade and the scale of the final data skeleton, the road side unit encapsulates the sensing data and sends the sensing data to the requesting vehicle. By adopting the technical scheme, the personalized and accurate matching of the data response in the vehicle-road cooperation system is realized through a multi-level and self-adaptive decision process, and the communication resource utilization rate, the data transmission real-time performance and the vehicle driving safety are improved.

The embodiment of the invention provides a humanoid robot behavior data processing method and related device.The method comprises the steps that in response to a first selection operation of a user for a first control of a first action label in an action interaction interface, a first resource calling instruction of the first action label is generated, the first resource calling instruction is received and transmitted to the cloud server, the cloud server is used for querying a first action resource according to the first resource calling instruction and transmitting the first action resource to the humanoid robot, and the first action resource is used for representing action data needed by the humanoid robot for completing a first action; acquiring an action execution feedback message from the cloud server; and displaying the action execution feedback message. The action library of the humanoid robot in the cloud server is started and called through the terminal equipment, multiple functional components of the humanoid robot are in one-key linkage, complex actions are completed, and the intelligence of behavior data processing of the humanoid robot is improved.