176 results about "Data slice" patented technology

The invention provides a UCIe standard protocol layer data transmission circuit, a related method and a chip, and the circuit comprises a slicing circuit which is configured to segment a data packet from a service port; sending the slice frame and slice description information associated with the slice frame to a framing device; the framing device is configured to fill a flow control unit Flit with the slice frames from the slice devices and slice description information associated with the slice frames, and send the Flit to the deframing device; the frame deframer is configured to determine slice frames belonging to the same service port from the Flit, and send the slice frames and slice description information associated with the slice frames to a packing circuit corresponding to the service port; and the packing circuit is configured to splice the data slices belonging to the same data packet in the slice frame based on the slice description information and output the data packet. The technical problem that extra delay is introduced due to beat insertion due to the fact that large multiplexers need to be introduced in existing protocol layer data transmission of the UCIe standard is solved.

The invention discloses an RAG knowledge base construction method and device and a medium, and the method comprises the steps: carrying out the analysis of the format, structure and semantic features of input data through a multi-level priority judgment logic, and automatically recognizing the specific data type. And calling a corresponding adaptive segmentation strategy for processing according to the identified data type, and generating data slices with semantic coherence. And asynchronously calling the large language model to generate a keyword set for each data slice, and uniformly storing the data slices, the keyword sets and associated multi-modal resource links by adopting a mixed storage mode to construct an enhanced RAG knowledge base. In the retrieval stage, query keywords are generated for user query according to the same logic, and related results are accurately retrieved from the knowledge base through a keyword matching mechanism. According to the method, the semantic segmentation problem is effectively avoided through intelligent segmentation with adaptive types, multi-modal data access is supported, and unified management and efficient retrieval of heterogeneous resources are realized.

The invention discloses a method and a system for detecting vertical floating of duct pieces in a shield tunnel splicing stage, and belongs to the field of tunnel engineering monitoring. The method comprises the following steps: acquiring a laser point cloud and an apparent image of the inner surface of a segment, and constructing a ring position data slice set indexed according to ring numbers; performing refined section fitting considering segment local deformation on the slice set, and extracting an actual measurement center of each ring through physical rigid body separation or statistical joint optimization; self-adaptive parameterization interpolation is executed based on the fitting sensitivity features, and an actual measurement tunnel center line is generated; constructing a self-calibration optimization objective function containing multi-source constraints, and performing incremental updating on external parameters and ring-by-ring attitudes of the sensor by using a sliding window; and establishing a multidirectional component unified coordinate system, decomposing spatial deviation and judging a segment floating mode. The problem of coupling of rigid body displacement and elastic deformation is solved, and high-precision and anti-drifting duct piece floating closed-loop detection is achieved.

The embodiment of the invention discloses a method for generating a video abstract, which comprises the following steps of: after slicing video data, respectively extracting a visual description text, a text abstract and an emotion label from each video clip, and fusing all modal extraction results to determine a comprehensive description text of each video clip; and then determining the logic relationship of each video clip by analyzing the semantic relevance of the comprehensive description text, integrating each video clip based on the time sequence and the logic relationship to obtain a text sequence, and finally generating a video abstract based on the text sequence. Through division processing of multi-modal data and later fusion, the processing efficiency and universality are improved while the accuracy and coherence of the abstract are ensured, and through cross-fragment semantic correlation analysis, a text sequence with smooth logic coherence and narration is constructed, and the accuracy of the generated video abstract is improved.

Methods for a machine learning network that provide efficient, scalable, and granular analyses during validation of an object detection model are disclosed. The system described herein is configured to use extraction of visual concepts to provide interpretable metadata to a data slice finding technique. The identified, poor-performing slices are then provided to a user for selection as to which slice or slices to focus on when preparing a subsequent training dataset that is to be used to further refine the object detection model. The system then coordinates with a large language model and with a vision and language foundational model to augment the original validation dataset with supplementary image samples that are determined to be associated with the problems currently causing poor performance of the model.

The invention discloses a carbon emission factor calculation verification method based on a block chain, particularly relates to the technical field of carbon emission accounting and block chain credible measurement, and is used for solving the problems that an existing carbon emission factor calculation process depends on a dispersed system and manual summarization, the publication caliber is not uniform, a traceable evidence chain is lacked, and the calculation efficiency is low. And a supervision mechanism and a third party are difficult to carry out independent re-calculation and credible verification on the factor result submitted by the enterprise. A carbon emission factor calculation template is taken as a core at an enterprise node side, a device range, a statistical period and a data preprocessing rule are configured in a unified manner, abstract identifiers are generated step by step for dimensionalized data abstracts and calculation evidence chain fingerprints, calculation certificates are written into an alliance chain, and a calculation result is obtained. And the verification node obtains a verification fingerprint and registers a verification result based on the same template fingerprint and data slice recalculation, so that an integrated evidence closed loop of factor calculation, recalculation verification and factor selection is formed, and the problems that a factor source is non-transparent, cross-subject recalculation is difficult and a credible basis is lacked are solved.

The invention discloses a rapid magnetic resonance imaging reconstruction and segmentation method and system, a medium and a product, and relates to the technical field of image processing. The method comprises the following steps: decomposing original three-dimensional magnetic resonance data into a plurality of independent two-dimensional magnetic resonance data slices along a slice sequence; image reconstruction is carried out on the two-dimensional magnetic resonance data slices through a pre-trained forward generator in the frequency domain Schrodinger bridge diffusion model so as to generate a two-dimensional magnetic resonance image, and the forward generator integrates a Fourier convolution module and is used for carrying out frequency domain transformation and feature enhancement processing on feature mapping in the image reconstruction process; inputting each two-dimensional magnetic resonance image into a pre-trained segmentation model in sequence, performing segmentation of a target region and a preset dangerous organ, and generating a corresponding two-dimensional segmentation mask; all the two-dimensional segmentation masks are rearranged and stacked according to the slicing sequence, and a three-dimensional segmentation result is generated through three-dimensional fusion operation. By implementing the technical scheme, magnetic resonance imaging reconstruction and segmentation can be quickly and accurately carried out.

The invention discloses a virtual space-time environment automatic completion method and system based on data density dynamic perception and a medium, and relates to the field of computer data processing. The method comprises the following steps: monitoring a data activeness index (such as spatio-temporal information entropy) of a spatio-temporal grid in real time in a distributed index database of a virtual spatio-temporal environment; when the index meets a preset data sparseness condition, generating a completion request; analyzing the space-time attribute tag of the target grid and acquiring associated multi-modal reference data from an external heterogeneous data source; carrying out feature recombination on the reference data by utilizing a generative neural network model, and generating discrete spatio-temporal data slices containing spatio-temporal anchor points and scene content attributes (such as environment illumination and material mapping); and finally, injecting the slices into the database to fill data holes. According to the method, a passive trigger mechanism and a structured reconstruction technology of unstructured data are introduced, so that the computing power cost of a large-scale virtual environment is effectively reduced, the problems of data sparseness and cold start of a long-tail region are solved, and the historical authenticity and time-space consistency of a virtual scene are ensured.

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 structured object may cause generation, on the user interface, of a representation of slice(s) of data across different dimensions with different filter(s) applied to include one or more dimensions and exclude one or more other dimensions. The slice(s) of data may be determined based on available dimension(s) and / or dimension value(s) specified, in the prompt, for the data schema. If the representation is a grid, a shape of a grid may be recommended for showing the slice(s) of data determined.

The application provides a large language model-based electronic form standardization processing method and system, and belongs to the technical field of data processing, and specifically comprises the following steps: a file acquisition module is responsible for intelligently screening a target worksheet set containing valid data; a slicing module is responsible for partitioning the content of the worksheet to obtain a plurality of data slices; the table header of each data slice and sample data are input into a large language model workflow to intelligently identify the dimension type and structural characteristics of the data; an execution module is responsible for generating management strategies and prompt words, calling a large language model to dynamically generate a targeted data processing function code, executing the generated function code through a function execution engine, and standardizing and converting the data slices; and all successfully processed data is combined and exported as a standardized electronic form, thereby improving the efficiency of the standardization processing of the electronic form.

The application discloses a kind of data acquisition and association method and system of substation secondary circuit, belong to substation technical field, by establishing structure topological graph and generating data label for node, using event-driven mechanism to capture the data slice of state change moment.Based on the establishment of verification task based on theoretical connection relationship, the multi-dimensional response characteristics of the node are extracted, a multi-dimensional physical constraint model integrating time dimension, electrical logic dimension and signal quality dimension is constructed, and the confidence of node connection is quantified by calculating comprehensive verification indicators.When the connection is found to be untrustworthy, the system automatically scans all network nodes to establish a temporary verification task, locates and corrects the real connection nodes, and completes the topology update.The technical problems of static label unable to track physical connection changes, passive diagnosis unable to actively prevent, and unable to automatically repair after problem discovery are solved.

This application provides a graph data sampling and graph neural network training method, system, device, and medium. The graph data sampling method is applied to a first node device and includes: acquiring a sampling task and determining multiple objects to be sampled corresponding to the sampling task; for any object to be sampled, determining a target data slice for storing the object according to a preset allocation relationship; if the target data slice is stored in the first node device, using the resources of the first node device to perform a sampling task on the object to be sampled to obtain a sampling result; if the target data slice is stored in a second node device, calling the resources of the second node device to perform a sampling task on the object to be sampled to obtain a sampling result; and obtaining the sampling result of the sampling task based on the sampling results of each object to be sampled. This application embodiment can improve the sampling efficiency of graph data, thereby improving the training efficiency of graph neural networks.

This application relates to the field of data transmission technology and discloses a data transmission method, apparatus, electronic device, and computer-readable storage medium, comprising: in response to a data transmission operation, acquiring target transmission data of a first terminal; slicing the target transmission data to obtain a target data sequence, the target data sequence including at least two data slices; performing a graphical encoding conversion on the target data sequence based on metadata of the target data sequence to generate a target graphical encoding, the metadata including at least first metadata used to indicate the length of the target data sequence; and displaying the target graphical encoding for transmitting the target transmission data. This application improves the convenience of data output while ensuring reliable data transmission.

The application discloses a kind of data disaster recovery methods of supporting multiple backup path switching, comprising, based on the sensitivity of input data and the generation of dynamic granularity data slice of storage medium characteristics, and generate the metadata label containing data slice identification, storage preference and recovery priority;Path quality atlas is generated for each data slice by constructing heterogeneous transmission path performance model through metadata label, and optimal transmission path is allocated, and path performance is monitored;Abnormality is detected and migrated slice by the standard deviation of cumulative transmission delay;Incremental integrity verification and Merkle proof of blockchain storage are used for parallel checking, and retransmission is preferentially checked failed slice;The application ensures the reliability and stability of data disaster recovery through the synergistic cooperation of dynamic data slicing, backup path optimization and recovery verification, to meet the real business needs.

The invention provides a low-speed unmanned vehicle running state data recording and analyzing system, which relates to the technical field of data processing, and comprises a processor used for analyzing a multi-dimensional state matrix based on a decision geometric structure and generating an event trigger sequence; based on a time reference in the event trigger sequence, extracting data slices in an event time neighborhood from the multi-dimensional state matrix, and constructing a spatio-temporal data cube; the feature extraction module is used for performing feature extraction on the spatio-temporal data cube to obtain event feature fingerprints and generate event feature codes; the event risk level evaluation module is used for inputting the event feature codes into a pre-trained deep belief network to obtain an event risk level evaluation result; and the event fusion module is used for fusing the event trigger sequence, the spatio-temporal data cube, the event feature code and the event risk level evaluation result to generate a structured event analysis report. According to the method, the accuracy of abnormal event detection in the running state of the low-speed unmanned vehicle, the reliability of risk assessment and the analysis efficiency can be improved.

The invention discloses a pet food production line intelligent scheduling system and method based on the Internet of Things, and relates to the technical field of production line scheduling. Internet of Things nodes corresponding to the positions of a plurality of pet food production lines are deployed, and convergence channels corresponding to different Internet of Things nodes are established for collecting production line data of the corresponding pet food production lines; the method comprises the steps of establishing a data slicing window of each pet food production line, dividing respective production line data into a plurality of sub-stage data, generating a scheduling atlas database based on historical production line data, establishing respective real-time scheduling atlases based on the sub-stage data of each pet food production line, and comparing and traversing the real-time scheduling atlases in the scheduling atlas database. And obtaining a plurality of stage scheduling maps of each pet food production line, integrating all stage scheduling maps of each pet food production line, obtaining a global production line scheduling map of the corresponding pet food production line, and executing production line scheduling of the corresponding pet food production line.

The present disclosure provides a low-distortion PAM-4 optical transmitter with a piecewise compensation scheme for VCSEL-based optical communication links. The input half-rate least significant bit (LSB) and most significant bit (MSB) data streams of the transmitter are firstly encoded into half-rate unary-weighted data streams by thermometer encoders. The half-rate unary-weighted data streams are then fed into three data slices with 2-tap feed-forward equalizer (FFE), continuous-time linear equalizer (CTLE), pre-emphasis circuit for serialization and piecewise pre-distortion. Finally, outputs from the three data slices are added in the form of current and fed into VCSEL. A thermal control loop is implemented to monitor the temperature of the VCSEL as well as provide compensation to the bias current of the VCSEL.

The invention discloses a multi-modal document generation and consistency verification method, which relates to the technical field of document processing, and comprises the following steps: 1, solidifying a text statement and chart data into a verifiable calculation voucher containing a calculation process list, and a data slice containing a proof and a timestamp; step 2, establishing an alignment table, marking a region of interest, and identifying visual invariants such as logarithm, truncation, stacking, biaxial and the like; thirdly, double-loop consistency verification is formed through question and answer readings and data playback, and consistency scores, difference types and evidence paths are output; 4, constructing patch synchronous write-back texts, charts and lists according to difference types, and rechecking the texts, the charts and the lists; 5, setting a release gate and a machine readable footnote, and generating version chain archiving; sentence-level sources can be traced, calibers are consistent, and release is controlled; the method adapts to financial management scientific research and government affair scenes, reduces manual re-checking, avoids caliber drift and image reading deviation, and supports independent checking and tracing.

The invention provides a communication method and device, electronic equipment, a computer readable storage medium and a computer program product. The method comprises the steps that to-be-processed data are distributed to a plurality of target computing cards, each target computing card comprises a plurality of computing core particles and at least one communication core particle, and each computing core particle is distributed with one data fragment in the to-be-processed data; for each target computing card, determining a target core particle corresponding to the target computing card from the at least one communication core particle, and constructing a first communication network based on each computing core particle and the target core particle; controlling each computing core particle to carry out protocol processing on each data fragment through the first communication network to obtain a first processing result of the target computing card; and constructing a second communication network based on each target core particle, and controlling each target core particle to perform global protocol processing on the first processing result of each target computing card through the second communication network to obtain a second processing result. According to the invention, the set communication efficiency between the computing cards can be improved.

Disclosed in the present application are a resource transmission method and apparatus, and a device and a storage medium. The method comprises: acquiring N broadcast messages, wherein different broadcast messages comprise different data slices, and the data slices in the N broadcast messages are used for indicating media resources to be transmitted by a first device; broadcasting the N broadcast messages in a communication scenario, such that a second device in the communication scenario determines, on the basis of data slices in received broadcast messages, that the second device supports the transmission of media resources with the first device, and then sends a communication connection request to the first device; and establishing a communication connection with the second device that sends the communication connection request, and transmitting media resources between the first device and the second device on the basis of the communication connection. It can be seen that a valid communication connection can be established by means of the present application, thereby reducing the wastes of connection costs and time costs, and improving the success rate and efficiency of resource transmission.

The invention provides a DPU capability multiplexing method and device, electronic equipment, a storage medium and a program product, relates to the technical field of communication, and is used for improving the resource utilization rate of a DPU. The method comprises the following steps: receiving a DPU call request message, wherein the DPU call request message comprises a DPU capability demand of a target application; based on the calling request, determining N reusable DPUs meeting the DPU capability requirement; n is an integer greater than or equal to 1; a calling response message is sent to a source DPU where the target application is located, the calling response message comprises the address information of the N reusable DPUs and is used for indicating the source DPU to segment the to-be-processed data of the target application according to the address information of the N reusable DPUs to obtain N data slices, and the N data slices are sent to the N reusable DPUs respectively.

This invention relates to the field of medical data technology and discloses an AI-based method for managing cardiovascular chronic disease data. The method constructs a cardiovascular data pool containing patients' historical medical records and real-time physiological signals; establishes a dynamic ontology in the cardiovascular data pool based on a clinical knowledge graph, which defines the semantic relationships between different data entities; maps and generates data evolution trajectories on the dynamic ontology according to a preset treatment target path; activates an intelligent agent configured to traverse the dynamic ontology along the data evolution trajectory, resolving causal constraints between data entities based on the semantic relationships encountered during the traversal; the intelligent agent adaptively reorganizes new data flowing into the cardiovascular data pool in real time according to the resolved causal constraints, generating data slices with temporal correlation; inputs the data slices into a pre-trained deep learning network for feature fusion, outputting a dynamic profile of the patient's cardiovascular health status.

The application provides a UCIe standard protocol layer data transmission circuit, a related method and a chip. The circuit comprises: a slicing circuit configured to split data packets from a service port; a framing device configured to send a slice frame and slice description information associated with the slice frame to a framing device; the framing device is configured to fill the slice frame and the slice description information associated with each slice frame from each slicer into a flow control unit Flit, and send the Flit to a deframer; the deframer is configured to determine the slice frame belonging to the same service port from the Flit, and send the slice frame and the slice description information associated with the slice frame to the packet assembly circuit corresponding to the service port; the packet assembly circuit is configured to splice and output the data packets in the slice frame based on the slice description information. The existing UCIe standard protocol layer data transmission needs to introduce a large multiplexer, which causes a technical problem of inserting a snapshot and introducing additional delay.

A method for execution by one or more computing devices of a storage network, the method includes de-selecting a sequence of input encoded data slices based on de-selection information to produce deselected encoded data slices of a set of encoded data slices, where the input encoded data slices include a set of encoded data slices interspersed with a set of auxiliary data slices. The method further includes error decoding at least a decode threshold number of encoded data slices of the deselected encoded data slices in accordance with error decoding parameters to reproduce a data segment. The method further includes outputting the data segment to a requesting computing device of the storage network.

The application discloses a kind of firmware upgrade methods based on data piece, including the following steps: data piece processing stage: firmware file is divided into multiple standardized data pieces according to preset size, and unique identifier and check code are generated for each data piece;Multi-channel transmission stage: using multi-channel parallel transmission mechanism, simultaneously using multiple communication channels to transmit data piece;Verification and recovery stage: after data piece is all received, combination verification is carried out, including check code verification and digital signature verification, to ensure firmware;Before upgrade, original firmware is automatically backed up, and when upgrade fails, rollback mechanism is triggered to recover to original version.The firmware upgrade process is divided into three stages of data piece processing, multi-channel transmission and verification recovery, and efficient and reliable firmware upgrade is realized by fine control of each stage operation;It is mainly applied to the functional update and firmware upgrade occasions of embedded system.

The present application relates to the technical field of data processing, and especially relates to a sparse direct solution method based on data kernel external storage, which comprises the following steps: obtaining a coefficient matrix of a high-dimension sparse linear equation group, analyzing a non-zero element distribution mode and a matrix topological structure to establish a task dependency relationship; detecting a system memory capacity and a disk performance parameter to set a slice size parameter, dividing a wavefront matrix into data slices with balanced floating-point operation amounts to execute a left-looking numerical decomposition; creating a message queue and a monitoring mechanism to realize asynchronous disk storage; reading data from the disk to execute a numerical update cycle; and establishing a back substitution solution memory work area to generate a numerical solution by using a previous generation back substitution algorithm. The present application utilizes disk storage to relieve memory pressure and supports large-scale finite element simulation application.

A hardware accelerator can receive, from a host processor, a slice of input data at a time-step. The hardware accelerator can process the input data using a machine learning model deployed on the hardware accelerator to compute a respective probability among multiple probabilities for each of multiple classes. The respective probability for each class being a likelihood that content in the slice belongs to the class. The hardware accelerator can determine, from the multiple probabilities, a preset number of highest probabilities for the slice of input data. The hardware accelerator can transmit the preset number of highest probabilities for the slice to the host processor. Related apparatus, systems, techniques and articles are also described.

The invention relates to the technical field of business and financial flow automation, in particular to a strategy arrangement and elastic deployment method and system for business and financial flow automation. The method comprises the following steps: in an operation monitoring stage of a business process, capturing and integrating multi-modal data streams, including structured transaction data, unstructured voucher image texts and user operation behavior sequences, generated by process execution in real time; and then, inputting the multi-modal data stream into a financial risk identification model which is trained based on historical compliance and violation cases in advance for real-time analysis. When the model identifies a potential risk pattern, the system automatically triggers an auditing alarm and generates a visual auditing report containing the risk data slices and associated contexts thereof. According to the invention, real-time, accurate and automatic monitoring of business and financial process risks is realized, and the depth, breadth and timeliness of risk identification are effectively improved.

This invention discloses a blockchain-based carbon emission factor calculation and verification method, specifically relating to the fields of carbon emission accounting and blockchain-based trusted measurement technology. It addresses the problems of existing carbon emission factor calculation processes relying on decentralized systems and manual aggregation, inconsistent public disclosure standards, and a lack of traceable evidence chains, making it difficult for regulatory agencies and third parties to independently recalculate and reliably verify the factor results submitted by enterprises. By using a carbon emission factor calculation template as the core at the enterprise node side, and uniformly configuring device scope, statistical periods, and data preprocessing rules, a summary identifier is generated level by level from dimensional data summaries and calculation evidence chain fingerprints. The calculation voucher is written into the consortium blockchain, and the verification node recalculates the verification fingerprint based on the same template fingerprint and data slices, registering the verification results. This forms an integrated evidence closed loop of factor calculation, recalculation verification, and factor selection, solving the problems of opaque factor sources, difficulty in cross-entity recalculation, and lack of credible evidence.