237 results about "Full data" patented technology

The invention discloses a reinforcement learning model training method and device based on dynamic data selection and electronic equipment, and the method comprises the steps: carrying out the screening from an original mathematical problem data pool according to preset data quality, diversity and difficulty evaluation indexes, and obtaining a candidate training set; calculating a data validity score of each training sample in the candidate training set; difficulty filtering is carried out on the candidate training set, and an adaptive training course is constructed; further filtering the candidate training set according to the solution reasoning process and the reward score of the candidate training set; dynamically selecting a data subset for the current training period by setting a temperature parameter attenuated along with the training process and a probability threshold based on the further filtered candidate training set and the data validity score; the selected data subsets are put into a reinforcement learning model for training, and the reinforcement learning model is trained in an optimized mode according to the correctness reward and the format reward. The model training period can be remarkably shortened, and the performance equivalent to or even better than that of full data training is achieved.

The invention relates to the technical field of chip design, and provides a critical path screening method based on a chip time sequence report, which comprises the following steps: collecting chip time sequence report data, screening out first N critical paths from the data based on time sequence index data, and establishing a path ID-delay type-scene three-dimensional data model; and calculating the delay ratio of the unit delay to the interconnection line delay in each critical path. Performing single-type delay, type relevance and RC condition influence comparison on different scenes to obtain delay characteristic data. The invention discloses a system for executing the method, which can avoid full data redundancy and improve the analysis efficiency by screening the first N critical paths. And the delay change rule in different scenes is quantified. The delay characteristic data reflects the actual influence of the key path delay on the time sequence, so that a designer can quickly position the delay bottleneck of the key path, and a basis and a reference are provided for the targeted optimization of the total delay of the chip in the later period.

The invention discloses a multi-dimensional credit asset traceability system and method. The system comprises a data acquisition and encryption module (10) which is used for performing encryption and digital signature on credit asset data based on a trusted execution environment (TEE) and a hardware security module (HSM) at a data generation end; the parallel Hash processing module (20) is used for performing parallel Hash operation on the encrypted data and generating leaf node Hash values based on GPU acceleration and a multi-thread technology; the nested hash and zero-knowledge proof module (30) constructs leaf node hash values into a compression type Merkle tree and generates a zero-knowledge proof (ZKP), so that a third party can verify the authenticity and consistency of data without accessing full data; the on-chain evidence storage module (40) is used for recording root Hash (RootHash) and zero knowledge proof of the compression type Merkle tree to the block chain; the dynamic authorization and secure multi-party computing module (50) performs access clipping on the credit asset data based on the access intention and realizes verification of the minimum data dimension through secure multi-party computing (SMPC). Through combination of technical means such as trusted hardware acquisition, parallel hash calculation and privacy protection verification, rapid verification is realized on the premise of not exposing original data, and verification performance, data security and privacy protection capability are remarkably improved.

The invention provides a memory management method and a storage device. The method comprises the following steps: before executing a complete data reading operation in response to a reading instruction of a target page, acquiring slowly-changed metadata and quickly-changed metadata of the target page; obtaining a first voltage adjustment parameter according to the slow change metadata; acquiring a second voltage adjustment parameter according to the quick change metadata; according to the first voltage adjustment parameter and the second voltage adjustment parameter, adjusting the reading voltage of the target page from a preset reading voltage to a target reading voltage; according to the target reading voltage, the complete data reading operation is executed on the target page, and the complete data reading operation is executed under the condition that historical reading failure does not occur for the target page. Therefore, the data reading efficiency of the storage device can be improved.

The invention provides a self-adaptive data consistency maintenance method for an electric power information system based on incremental updating, and relates to the technical field of big data processing, and the method comprises an initialization step, a detection step and a feedback step. In the initialization step, a network including regional power data nodes and a distributed account book is constructed, and full power data is stored; in the detection step, power data changes are confirmed, key attributes are used for marking data, automatic conflict detection is carried out through a distributed consensus algorithm, solutions for coping with conflicts are dynamically selected, and then an incremental updating mechanism is adopted for synchronously changing the data; in the feedback step, a monitoring system with a closed-loop feedback mechanism is established, the data consistency state is automatically tracked when the electric power data is changed, and abnormity is recognized. Compared with a traditional data synchronization method which needs to synchronize full data, the method provided by the invention only synchronizes the changed data fragments through an incremental updating mechanism, thereby ensuring the consistency of the data, remarkably improving the data processing efficiency and saving the network bandwidth.

The invention discloses a full-data backup method for a fast and slow operation period of an industrial controller. The full-data backup method comprises the following steps: detecting whether a main power supply is powered down or a backup command is received by an FPGA (Field Programmable Gate Array); if yes, the FPGA writes the latest fast-cycle integrity data into the power-down nonvolatile storage chip by comparing the integrity marks and the timestamps of the fast-cycle data of the data A area and the data B area of the memory chip; then, the FPGA writes the completeness data of the latest slow period into the power-down nonvolatile storage chip by comparing the completeness marks and the timestamps of the data of the slow period of the data A area and the data B area of the memory chip; according to the data backup method, data does not need to be selected, one cycle of complete data can be recovered under the condition of power failure or no power failure, common memory chips and power failure non-volatile storage chips are used, and cost and implementation complexity are effectively reduced.

The invention relates to a medical image retrieval method and system based on a DICOM protocol and a storage medium, by setting a unified proxy forwarding service and combining with an image prefetching and caching mechanism linked with a clinical business event, the configuration difference of a back-end heterogeneous PACS system is shielded, single access point connection of a client is realized, and the user experience is improved. The complexity of system deployment and maintenance is reduced; meanwhile, the image data are pre-stored in the cache, so that the retrieval waiting time of the remote image is shortened, and the data access performance and the user experience are improved; and centralized authority authentication and log auditing are realized through the agent layer, so that the controllability and the security of a cross-mechanism data sharing process are guaranteed under the condition of avoiding high cost of centralized storage of full data.

The invention provides an automatic process management method and system applied to foreign trade business intellectualization, and relates to the technical field of foreign trade business management.The method comprises the steps that firstly, initial order data, preset document template data, logistics resource configuration data and order change data of foreign trade business are obtained and integrated to form a foreign trade business total data set; then, carrying out change influence definition processing on the order change data, and determining influenced foreign trade business links and associated data; performing linkage adaptation processing on the associated data based on a defining result, and adjusting preset document template data and logistics resource configuration data; according to a linkage adaptation processing result and a foreign trade business process knowledge base, generating operation execution instructions of all links; finally, the instructions are distributed to the corresponding execution main bodies according to the execution sequence, operation execution results are received and integrated to form feedback information, automatic and intelligent management of the foreign trade business process is achieved, and the management efficiency and accuracy are improved.

The invention provides a block chain-based data security processing platform, which relates to the technical field of computer software and information, and comprises a block chain architecture system, a data security processing system and a data sharing system, the block chain architecture system comprises a data provider node, a data user node, a supervision node and a consensus node; according to the invention, multiple system modules are covered, a data security processing system combines AES and RSA encryption, integrity is verified by means of a Hash algorithm, access control is set by means of a smart contract, a data sharing system sets a sharing rule according to the smart contract, data is traced by means of a block chain, and sharing is promoted by means of an incentive mechanism; various block chain types and adaptive consensus mechanisms are provided, a system management and maintenance module checks nodes every day, full data backup is performed to three places every week, a system is audited every month, node faults are processed within 24 hours, safety problems are repaired in seven workdays, and stable, safe and compliant operation of a platform is guaranteed.

The invention belongs to the technical field of operation and maintenance secret communication, and particularly relates to a secret communication system and method for operation and maintenance service management based on the block chain technology, and the system comprises a three-layer data framework which comprises an operation and maintenance layer, a data center layer and a block chain layer, the operation and maintenance layer is used for storing operation and maintenance service data, operating an operation and maintenance system and a communication system, and outputting full data fragments to be encrypted and stored to the operation and maintenance layer; and a cross-layer transmission control module and a block chain encryption recording module. According to the invention, the confidentiality and security of data communication in operation and maintenance service management can be improved, data leakage and illegal access are effectively prevented, data exception is handled, the security protection capability of the system is improved, and potential risks are avoided.

The application provides a data consistency verification method and system for long-distance heterogeneous ends, aiming to solve the technical pain points of low efficiency, long time consumption, high cost and sensitivity to network delay caused by relying on full data network transmission when performing massive data consistency verification between long-distance heterogeneous databases in the prior art. By pushing down data-intensive computing tasks (such as hash calculation and aggregation) to the source and target databases for execution, only lightweight summary data (usually megabyte level) is transmitted in the network, and the final comparison is completed by the coordination end. The application has the following technical advantages: extreme network efficiency, order of magnitude improvement; not sensitive to high network delay; maximum utilization of computing resources; high compatibility of heterogeneous databases; robustness and intelligent degradation.

The application provides a super block management method and device and electronic equipment, comprising: obtaining a target storage block in a storage unit in a plurality of NandFlash; the block number of the target storage block is the same; initializing a minimum heap container; constructing a super block according to the target storage block; writing a first data structure of a first sub-super block in the super block in a full data state into a first minimum heap in the minimum heap container; and writing a second data structure of a second sub-super block in the super block in an unwritten data state into a second minimum heap in the minimum heap container; and managing the write operation and the garbage collection operation of the super block through the first minimum heap and the second minimum heap. The method improves the garbage collection and wear leveling algorithm efficiency of the SSD firmware.

The application relates to a data migration method and device, a computer readable storage medium and computer equipment. The method comprises the following steps: obtaining corresponding original full data in a source database; inserting the identifier of the source data table corresponding to the data according to the data position in the original full data to obtain target full data; modifying the original primary key corresponding to the data in the target full data into an updated primary key, wherein the updated primary key is determined by the original primary key corresponding to the data and the identifier of the source data table corresponding to the data; migrating the target full data to a target data table in a target database; obtaining incremental data of the source database, migrating the incremental data to the target data table, and inserting the identifier of the source data table corresponding to the data according to the data position in the incremental data. The scheme provided by the application can reduce the influence of the database migration process on normal access operations of the database.

The present application discloses a network congestion prediction method based on DPI data and related products. First, the service with the highest proportion of users in the target network system can be determined as the target service. The network traffic data to be predicted of the target service in the target network system is obtained, and the network traffic data to be predicted is input into the congestion prediction model to perform network congestion prediction and obtain a state prediction result. The congestion prediction model is based on the full data of the network traffic basic data table and the network management basic data table of each service in the target network system, as well as the historical service congestion performance label, and the Prophet model is trained. Then the state prediction result is output. By focusing on core services, integrating multi-source full data and applying advanced prediction algorithms, the present application can effectively reflect the real perception of users and improve the accuracy of network congestion prediction, thereby reducing detection and processing lags, thereby improving the user's network experience.

The invention discloses an enterprise evaluation method, and relates to the technical field of computers, and the method comprises the steps: collecting the total data of a plurality of enterprises; determining industry key feature vectors of the enterprises based on the total data; determining the industry category of each enterprise based on the industry key feature vectors; establishing a multi-level index system architecture for a plurality of enterprises, and determining an initial weight of each level of dimension in the index system architecture; adjusting the weight of each level of dimension based on the weight adjustment rule of the inter-industry evaluation difference and the industry category to obtain the adjusted weight; and performing index evaluation on each enterprise based on the industry category and the adjusted weight to obtain an index evaluation result. Therefore, the accuracy of enterprise index evaluation is improved.

This invention discloses a tax-electronic loop joint analysis method based on privacy computing, and also discloses an apparatus and storage medium for this method. The method establishes an interactive device between three terminals, enabling encrypted processing of each computational stage. Each terminal is unable to see the original data, only receiving the computational results. This ensures that no single terminal can deduce the original data of any other terminal from the intermediate results. Thus, data security is ensured while achieving full data utilization.

The invention discloses a dynamic data mapping method and system based on field matching, and relates to the technical field of data processing. The dynamic data mapping method based on field matching comprises the following steps: maintaining a full data address by a communication management module; dynamically generating a field mapping table by judging whether the lower-level service input can be covered by the output field combination of the upper-level service group; and extracting the required field from the superior service according to the mapping table by using a preset algorithm, and filling the required field into the subordinate input Message. According to the method, the limitation that communication between services needs strict data type matching is solved, flexible connection and efficient data multiplexing are achieved, and the method is suitable for constructing a complex and changeable distributed task process.

The invention provides an object storage volume management method, device and equipment and a readable storage medium, and the method comprises the steps: responding to a write-in request associated with a clone volume, and obtaining a data state of a data object in the clone volume associated with the write-in request; writing data associated with the write-in request in a data area associated with the write-in request in a data object according to an acquisition result that the data state of the data object in the clone volume associated with the write-in request is unready; and marking or keeping marking the data object as a clone object. Through the technical scheme of the specification, the state of the data object is dynamically identified, and local writing and marking are carried out when necessary, so that the overhead of reading and copying full data in copy-on-write is avoided, the writing delay of the clone object is remarkably reduced, the writing operation performance is improved, and meanwhile, the data independence and the space efficiency of the clone volume are kept.

This invention provides a method, apparatus, electronic device, and storage medium for data migration from a storage pool. The storage pool includes a metadata server and an object storage server. The metadata server stores object metadata, including the storage location of the object data. The object storage server stores the object data. The method involves deleting versions of the target object's metadata from the first metadata server, determining the versions to be deleted based on deletion indicators in the target object's metadata from the second metadata server, and then migrating the remaining target object metadata to the second object storage server. Additionally, the method involves updating the storage location in the remaining target object's metadata and writing it in batches to the second metadata server. This achieves the full migration of data from the first storage pool to the second storage pool, avoiding data consistency issues and improving user experience during the full data migration process.

The invention provides a data transmission method and system for a confined space and electronic equipment. According to the data transmission method provided by the invention, a self-adaptive transmission mechanism based on real-time link quality is introduced, so that the problem of unreliable data transmission caused by signal attenuation in a limited space is effectively solved. The method has the beneficial effects that the transmission reliability of the most critical security data is preferentially guaranteed when personnel are in the most dangerous area by intelligently switching from the full-quantity data transmission mode to the simplified core data transmission mode when the link quality is deteriorated, so that the data transmission delay, failure and error code risks are remarkably reduced. Meanwhile, according to the method, the bandwidth is fully utilized to transmit total data when the link is good, the monitoring continuity is maintained with the minimum necessary data volume when the link is poor, and the optimal balance between efficient utilization of communication resources and safety monitoring real-time performance is achieved.

The invention relates to the technical field of drug package anti-counterfeiting management, in particular to a drug package anti-counterfeiting management method and system based on a block chain, the system constructs an innovative anti-counterfeiting system of physical-digital strong binding and full-link credible verification, a unique UUID is generated based on drug package digital twinborn full-volume data, and the unique UUID is stored in a database. And when an abnormity is found through verification, the system can quickly adjust key parameters such as sensor deployment, an uplink interval and a query step through an algorithm according to an abnormity triggering stage and type, so that dynamic iteration of an anti-counterfeiting strategy is realized, and the anti-counterfeiting effect is ensured when a counterfeiting means is upgraded and a service scene is changed. And the anti-counterfeiting management capability is always kept in an optimal state.

The invention discloses a data transmission method and device, a storage medium and electronic equipment. The method relates to the field of edge calculation, and comprises the steps that target data collected by a data collection device are acquired, the target data are data representing the change condition of electrical parameters, and the electrical parameters change in a sine wave mode; even-number-bit sampling data in target cycle data in the target data are deleted, updated target cycle data are obtained, and the target cycle data are one piece of complete sine wave data in the target data; and the updated target cyclic wave data are sent to a target master station, and the target master station restores missing data values in the updated target cyclic wave data based on an interpolation method. Through the method and the device, the problem of high data transmission pressure caused by uploading the total data acquired by the data acquisition device to the master station in related technologies is solved.

The application provides a method and system for ensuring consistency of data synchronization of a distributed file system. The method comprises the following steps: responding to an update period of acquired business data; performing secondary processing on the data according to an actual update period of the acquired business data; and responding to periodic full data processing to ensure that all data is up-to-date. The method is used in an offline data warehouse based on HDFS storage+HIVE analysis, is applicable to consistency of business data in various industries, and is particularly suitable for a scenario in which the amount of synchronized data is large and the actual update period of data is short. The method ensures data consistency by performing secondary processing on large amounts of business data according to the actual update period of the business data and combining periodic full data processing. Since the amount of data read from a source library is reduced, the read pressure of the source library is reduced.

The application discloses an energetic material processing parameter optimization method and system based on a force-heat coupling model, and relates to the technical field of intelligent simulation optimization based on specific calculation models. In view of the problems that 3D printing and mechanical processing data are disconnected, and common force-heat coupling models are not suitable for energetic materials in the prior art, the method of the application first collects 3D printing operation and initial state data of the grain, then constructs a force-heat two-way coupling intelligent calculation model special for energetic materials, adopts a Bayesian algorithm to multi-objective optimize processing parameters based on the model, and carries out model-driven closed-loop dynamic processing control. The method of the application realizes full data connection and adaptation to material characteristics, takes into account safety, precision and efficiency, and improves the processing stability and consistency of the energetic material.

The application discloses a kind of based on gypsum board production full data acquisition's defect detection avoidance method, comprising the following steps: time series analysis of the adjustment amount of gypsum board production equipment adjustment item is carried out, the associated relationship between gypsum board production equipment adjustment item is extracted, and associated relationship is abstracted as the associated network between gypsum board production equipment adjustment item;And according to the number of gypsum board real-time production equipment adjustment item, the production condition of gypsum board production equipment is set in real time.This application carries out learning training to the characterization data of gypsum board defect item and the adjustment amount of gypsum board production equipment adjustment item to obtain defect adjustment calculation model, and the associated relationship between gypsum board production equipment adjustment item is extracted by time series analysis of the adjustment amount of gypsum board production equipment adjustment item, and associated relationship is abstracted as the associated network between gypsum board production equipment adjustment item, realize the full detection and full avoidance of potential defect of gypsum board, improve the initiative of defect detection and avoidance.

The invention provides a multi-strategy task distribution method and system based on index space random sampling. The method comprises the following steps: receiving a sampling inspection request containing a data screening condition and a target sample quantity; determining a logical index space of the data set meeting the screening condition, wherein the logical index space is divided into a plurality of index units; randomly selecting M index units from the logical index space; obtaining all data in the selected M index units to form a preliminary sample set; judging whether the number of data in the preliminary sample set meets requirements or not; randomly extracting a plurality of data from the preliminary sample set meeting the quantity requirement as a final sample set; and distributing the final sample set to a plurality of processing entities according to a preset task distribution strategy. According to the method, full data loading and database full sorting are avoided, memory consumption and query pressure are remarkably reduced, and efficient, fair and auditable sampling inspection and task distribution are achieved.

The application discloses a virus searching and killing method and system for distributed energy safety data, relates to the field of virus processing, and comprises the following steps: acquiring a virus original characteristic code, splitting the original characteristic code into N discontinuous but sequentially fixed segments F i , calculating the starting offset S i of each segment F i relative to the first segment F1, and constructing a virus characteristic database; then, the data stream is divided into multiple data blocks B i of fixed size, a fixed-size sliding window is adopted to perform scanning and matching association, and finally, threshold judgment is performed; the original virus characteristic code is subjected to fragmentation processing, the storage requirement of the virus characteristic database is reduced; the sliding window scanning can ensure that any characteristic combination is covered, and a matching event FP i is recorded instead of full data, so that the memory occupation is reduced; through comparison of the absolute offset SB i with an expected position, the correct sequence of the segment in the virus is ensured, a state machine can track the matching progress in real time, and the weight of only the segment with correct sequence is accumulated, so that the detection reliability is improved.

This invention presents a heuristic recovery mechanism for malicious shortcut file parsing and threat detection. It employs a resilience-oriented parsing engine, utilizes a dynamic byte ordering mechanism to adapt to underlying data, leverages a sliding window algorithm to accurately locate variable-length field terminators to extract hidden strings, and employs a recursive parsing strategy to deeply traverse undocumented nested structures and extension blocks. Parsing anomalies are treated as threat features and archived during the parsing process, and an iterative extraction strategy with adaptive parameters ensures full data acquisition. Based on the comprehensive parsing results, a three-dimensional threat model encompassing deception, evasion, and execution is constructed, achieving a deep mapping of malicious shortcut files from binary structure to logical behavior. This invention not only significantly improves the parsing success rate of variant samples but also effectively extracts fingerprint features from automatically generated samples, providing key technical support for modern shortcut-based attack and defense countermeasures.

According to the biological recognition method and device, the storage medium and the computer equipment, the hardware parameters and the sample feature sets of the new equipment and the old equipment are collected, and accurate conversion from the old template features to the new equipment features is achieved. The conversion process not only considers hardware differences, but also combines multiple groups of sample features, and ensures that the converted new template features can fully adapt to the hardware environment of new equipment. Meanwhile, local fine tuning is performed on the feature extraction model in the new equipment by using the feature image set of a small number of users and the corresponding new template features, so that the recognition accuracy of the model on the new equipment is further improved. The local fine tuning mode avoids the problems of large data transmission quantity, privacy leakage risk, high operation and maintenance cost, equipment elimination and the like caused by full data synchronization and unified algorithm framework forced upgrading. In addition, the method is also helpful for promoting the popularization and deepening of a biological recognition technology in more fields and scenes.

The application provides a multi-source data query analysis method, a query engine, an electronic device and a storage medium, and belongs to the technical field of big data query and analysis. In the method, the query is directly pushed to a data source for execution, the pulling of full data is avoided, memory calculation is reduced, server resource occupation is reduced, and the parser interface is diversified. The parser interface of the fast query syntax supports a custom extended syntax, the compatibility of multiple query syntaxs is realized, the custom extended syntax is also supported, the customization of a query process is met, complex business rules can be adapted, the parser interface of the pipeline syntax can be connected to a pipeline syntax query statement, is compatible with a standardized pipeline, each interface in the query engine is pluggable design, any interface therein can be customized according to business requirements, and only interface semantics needs to be met, and the flexibility is high.