301 results about "Full data" patented technology

The invention discloses a BIM (Building Information Modeling)-based hoisting construction safety monitoring and early warning system. The system comprises a terminal sensing layer which is used for collecting environmental parameters and personnel behavior data in a closed space in real time; the edge computing layer is used for carrying out cleaning, compression and encrypted transmission on original data by utilizing an explosion-proof edge computing gateway; the cloud collaboration layer is used for storing full data based on a BIM digital twinborn platform, constructing a'danger mode-construction feature-disposal measure 'three-dimensional meta-knowledge graph by adopting an MAML + + algorithm, meanwhile, coupling a physical mechanism data enhancement engine with a multi-physics field coupling model and a physical constraint generative adversarial network, generating virtual data conforming to mass conservation and energy conservation, and sending the virtual data to the cloud collaboration layer; performing mixed training with real data; according to the intelligent decision-making layer, a space-time adaptive threshold evolutionary algorithm encodes a space-time context through a graph attention network and Transform, an alarm threshold is dynamically optimized through deep reinforcement learning, meanwhile, a digital twin deduction engine calculates a shortest safety path in real time, and rescue resource allocation is optimized.

The invention relates to the technical field of electrical equipment analysis, and particularly discloses an electrical equipment operation state monitoring system and method, and the method comprises the steps: the system is deployed at an electrical equipment site, integrates a low-power-consumption processor and an FPGA acceleration module, and is used for collecting multi-source data in real time, and executing lightweight model calculation and local early warning; and storing full data and operating a global analysis model, and communicating with the edge computing node to realize data collaborative analysis. According to the electrical equipment operation state monitoring system and method provided by the embodiment of the invention, through edge computing lightweight deployment, data preprocessing and local early warning are completed on the equipment site, and high efficiency of monitoring response and low-power-consumption hardware adaptation are realized; by means of an electromagnetic interference dynamic evaluation module, an acquisition strategy is intelligently adjusted, noise is suppressed, the reliability of multi-source data is guaranteed, the efficiency, precision and intelligent capability of electrical equipment state monitoring are remarkably improved, and technical support is provided for reliable operation of power system equipment.

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 present application provides a graphical monitoring dynamic refresh method and device, which are applied to the field of information technology. By setting an interceptor in the persistence layer service, the change event of the database can be captured in real time. The change event is then pushed to the global Actor using the transaction message middleware. The global Actor is responsible for maintaining the full data view, and the local Actors filter out customized data on demand to meet the personalized monitoring needs of different users. Finally, the socket service is used to accurately push incremental data and only transmit the data that the user is concerned about, thereby significantly reducing unnecessary data transmission, greatly reducing the pressure on the database and network, and realizing millisecond-level customized dynamic refresh of monitoring data, which significantly improves the real-time performance and accuracy of the monitoring system and meets the strict requirements of terminal production operations for real-time monitoring.

The invention discloses an Internet of Things full data persistent storage system and method based on multi-stage time granularity. The system comprises a data acquisition module, a multi-stage storage management module, a dynamic index module, a compression engine module and a query engine module. The data acquisition module is used for receiving equipment data in real time, the multi-level storage management module is used for dynamically dividing time windows and executing a cold and hot data migration strategy, the dynamic index module is used for constructing a joint index of time dimensions and equipment IDs, and the compression engine module is used for selecting an optimal compression algorithm according to data features and transmitting the optimal compression algorithm to the storage management module. And the query engine module is used for analyzing a query condition, positioning a data block through an index and optimizing an IO reading sequence. Compared with a traditional time sequence database, the storage cost is reduced through a dynamic time granularity division and hierarchical compression algorithm; and on the basis of query optimization of multi-level indexes, the query efficiency in the complex time range is improved by several times, and the query response time in the complex time range is reduced from the minute level to the sub-second level.

The invention provides a real-time data updating method and device based on AI prediction and computer equipment. The method comprises the steps that a server side collects a historical behavior data set of a user to train an LSTM time sequence model; the client establishes a long connection with the server, and reports the current operation behavior of the user to the server in real time; the server predicts the next operation behavior of the user based on the LSTM time sequence model; the server side compares a local version number carried by the client side with a server version number by maintaining the version number of the data item, adopts a Diff algorithm to calculate incremental data, and issues full data if the incremental data volume exceeds a full data threshold value; compressing the incremental data by using a compression algorithm, and actively issuing the incremental data to a client through long connection; and the client side merges the incremental data and then executes MD5 verification, and if the verification is inconsistent, the client side requests to update the total data. The method has the beneficial effect that the data updating efficiency and reliability in the long connection environment are 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 discloses a rail vehicle intelligent welding all-data collection and analysis system based on structural parameters and a use method, and relates to the technical field of rail transit welding digital production. The system comprises a welding file compiling unit, a welding monitoring execution unit, a welding data processing and analyzing unit, a welding data collecting unit, a welding parameter switching unit and a welding control unit. According to the method, the digital welding process file and the welding parameter package are compiled and issued to the welding machine, the welding monitoring activity is carried out in the mode of binding persons, machines, materials and methods, the welding parameters of the welded welding seam are strictly controlled, the one-time qualification rate of the welding seam is increased to 90%, and the welding quality is improved; welding parameters are monitored in real time, so that a welder carries out welding strictly according to a welding process procedure, and the welding quality problem caused by human factors is avoided.

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 auxiliary switching method and device for a new system and an old system, electronic equipment and a storage medium, and is applied to the field of finance or medical treatment. The method provided by the invention comprises the following steps: after a new system and an old system are switched, respectively and correspondingly comparing total data of a new database and an old database, output parameters of interfaces of the new system and the old system and configurations of the new system and the old system, and displaying corresponding difference data; the method comprises the following steps: when a new system is subjected to pilot run, injecting a preset proportion of flow into the new system, monitoring the new system, and if the new system is monitored to be abnormal, switching the flow back to an old system; and obtaining the interface calling time of the new system during pilot run to obtain a difference value of the corresponding interface calling time of the new and old systems, and if the difference value exceeds a preset threshold value, performing early warning. According to the auxiliary switching method for the new and old systems, switching of the new and old systems can be assisted, the system switching time cost is reduced, and the accuracy and integrity of system switching can be guaranteed.

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 data processing method comprises the steps that a client detects that a user triggers a target event; and the client sends a first message to the server, the first message comprises total user behavior data which is dotted by the client and is related to the target event, and the first message is used for indicating the server to carry out data analysis based on the user behavior data. Therefore, due to the fact that the client reports full data, the client does not need to be used for development in the data analysis process, complete data is reported before, the problem of compatibility of new and old versions of the client does not need to be worried about with zero development cost, and meanwhile dotting reporting logic does not need to be modified.

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.