410 results about "Data location" patented technology

Provided are an anomaly detection method and system for multi-source heterogeneous data, an electronic device, a vehicle, a computer-readable storage medium, a computer program product, and a computer program. The method comprises: performing statistical modeling on multi-source heterogeneous data, and obtaining background distribution features of multi-source heterogeneous data distribution through a data splitting method; preprocessing the background distribution features by using a preset sliding window to obtain a background image sequence on a specific time series; on the basis of the size of a target in the background distribution features, performing adaptive partitioning on the background image sequence to obtain an adaptive partitioning result, and identifying single source points of each partition in the adaptive partitioning result through a decoupling representation method; and on the basis of the identified single source points, determining the location of anomalous data in the background image sequence, and on the basis of a comparison calculation result of the multi-source heterogeneous data and the background image sequence from which the anomalous data is removed, obtaining an anomalous data location of the multi-source heterogeneous data.

The invention relates to the technical field of computers, in particular to a heterogeneous computing power scheduling method and device, equipment, a storage medium and a product. The method comprises the following steps: generating an equipment topological graph based on equipment information in a node resource pool; performing partition management on the computing devices in the device topological graph; based on a partition management result, analyzing the to-be-calculated task through a preset flow gateway, and determining a task request data position, a task scale and a task feature; determining a to-be-calculated node according to the task request data position, the task scale and the task feature; and distributing the to-be-calculated task to the to-be-calculated node, and generating a target scheduling strategy based on the real-time performance index and the historical execution data of the to-be-calculated node. According to the method, the utilization efficiency of computing resources is improved by generating the equipment topological graph and performing partition management, the scheduling strategy is optimized by combining real-time performance data, it is ensured that scheduling optimization can be performed according to the real-time state, and the effect of heterogeneous computing power scheduling is improved.

The invention relates to the technical field of data processing, and discloses a cold and hot data exchange method and system based on optical storage and a storage medium. The method comprises the following steps: performing access feature acquisition and analysis on data in the optomagnetic hybrid storage system, calculating an access life cycle factor, generating a logic interval heat evaluation result, performing temperature grading, formulating a cold and hot data placement strategy, generating a data placement mapping table, executing batch migration according to priority, and updating a data position record. According to the method, the problem of how to realize logic interval hot degree accurate identification, temperature grade dynamic grading, storage mapping optimal matching and batch migration task efficient organization under the optomagnetic hybrid architecture is solved.

The embodiment of the invention provides a memory access method and device, electronic equipment and a readable storage medium. The method comprises the following steps: receiving a cache line access request; extracting label information from a target memory address corresponding to the cache line access request, wherein the label information comprises a shared label, a private label, a group index, inter-block offset and intra-block offset; querying whether the cache line access request hits the L1 cache or not based on the label information; the group index is used for determining a target group, the shared tag and the private tag are used for determining a target cache line in the target group, and the inter-block offset is used for determining a target cache block in the target cache line; and if the cache line access request hits the L1 cache, determining a target data position in a hit target cache block based on the in-block offset, and executing a corresponding memory access request based on the target data position. According to the embodiment of the invention, on the basis of ensuring the data access efficiency, the storage space of the cache line is fully utilized, and the waste of the cache space is reduced.

The invention provides an automatic data fitting method and system combined with equipment position calibration, and the method comprises the steps: firstly collecting a multi-source sensor data set of target equipment in a three-dimensional space, including equipment motion track data, position coordinate offset and environment interference parameters, carrying out the feature extraction of the multi-source sensor data set, and carrying out the feature extraction of the target equipment; generating a target feature set containing spatial position correlation features, dynamic trajectory fluctuation features and environment coupling features, then calling a pre-trained adaptive fitting model, inputting the target feature set to perform dynamic parameter matching, and generating an initial calibration parameter set; and generating a dynamic path sequence of equipment position calibration based on the initial calibration parameter set, triggering the equipment to execute automatic position calibration according to the sequence, and feeding back calibrated verification data to the model update parameters, thereby improving the precision, real-time performance and adaptivity of equipment position calibration.

The invention discloses a GIS field-electricity fusion real-time state sensing and early warning system and method. The system comprises a signal synchronous acquisition and measurement embedded device and an industrial personal computer, and a simulator, a position searcher and an early warning device are deployed in the industrial personal computer; when the embedded device monitors that the electromagnetic field signal in the GIS contains the partial discharge signal according to the strong correlation characteristics, obtaining a full time domain oscillogram containing a time domain oscillogram and a frequency domain oscillogram of the partial discharge signal; the simulator performs coarse positioning on the partial discharge source based on the full time domain oscillogram of GIS partial discharge, and performs simulation enhancement calculation by taking a coarse positioning result as an initial injection point to obtain simulation enhancement data of the partial discharge source; the position searcher carries out iterative search on the actually measured discharge intensity obtained through calculation according to the full-time-domain oscillogram and the simulation enhancement result, and the actual discharge position of the partial discharge source is obtained; the early warning device carries out early warning based on the time domain full waveform and early warning information including the actual discharge position of the partial discharge source.

The invention discloses a memory management method, electronic equipment, a storage medium and a computer program product, and relates to the technical field of computers. The cold and hot marks are set for the memory pages according to the cold and hot scores, memory data of different cold and hot grades can be distinguished, whether data transfer is conducted on the memory data of the memory pages or not is judged by comparing with the types of the storage media where the memory pages are located, and energy consumption can be reduced by transferring the data to the storage media matched with the cold and hot marks; whether the current operation mode of the target storage medium supports data transfer or not is judged before data transfer, the target storage medium is adjusted to be in the operation mode supporting data transfer, all the storage media do not need to be kept in the operation mode supporting data transfer all the time, the lowest energy consumption of the operation mode of the storage medium can be kept, and the operation efficiency is improved. The energy consumption can be reduced by combining the dynamic adjustment of the data position according to the load and the static power consumption management.

Apparatuses, systems, and techniques to use parallel processing unit(s) (“PPU(s)”) to perform data access(es) in response to data access request(es). The data access(es) may be performed by accessing at least a first portion of data stored in at least a first location of data location(s) if the first location is on a first tier of a plurality of data tiers that is accessible by the PPU(s), and causing server interface(s) to access at least a second portion of the data stored in at least a second location of the data location(s) if the second location is on a second tier of the plurality of data tiers. The data access request(s) may be performed using an API. The data access(es) may be performed by client(s) and the server interface(s) may be implemented by server(s). The client(s) and server(s) may be implemented by node(s), and may be paused and migrated to other node(s) during execution time. The client(s) may implement synchronous and / or asynchronous interfaces.

The invention discloses a computer batch data storage method and system based on a block chain, and relates to the technical field of computer batch data storage.The computer batch data storage method comprises the steps that computer batch data are analyzed through a data classification method, the computer batch data are divided into hot data and cold data according to the access frequency, and a classified data set is obtained; performing encryption processing on the classified data set by adopting a homomorphic encryption method to obtain an encrypted data set; distributing the encrypted data set to a corresponding storage level by adopting intelligent contract definition logic to obtain a data record with a distributed storage position; creating a detailed index record and storing the detailed index record on the block chain to obtain an index record on the block chain; determining a data position when the specific data is retrieved by adopting a method of querying the index record on the block chain, and obtaining verified data; and checking the integrity of the data and the running state of the system by adopting a security auditing method to obtain an auditing result, and adjusting a storage strategy based on the auditing result.

Example channel circuits, data storage devices, and methods for data read synchronization from phase modulated synchronization fields are described. A data synchronization detector may receive an oversampled digital read signal read from a synchronization field that uses a single written pattern to encode the start of data position, phase, and gain for the read channel. The write pattern may use a phase modulated carrier signal to encode a pseudo-random binary sequence indicating the start of data position.

The invention discloses an intelligent operation and maintenance management method and system based on an artificial intelligence data center, and relates to the technical field of data processing, and the operation and maintenance management system comprises a data collection module, a data classification storage module, a data prediction module, a data processing module and a data evaluation module. The data acquisition module is used for acquiring different hardware equipment data and software data in the operation and maintenance management system in real time. The data classification storage module is used for classifying and storing the data in the operation and maintenance management system, and then the importance of different data is determined by utilizing grades; and then the data prediction module analyzes the classified data, so that the operation and maintenance management system can predict different classification data conveniently, after fault data occurs in the operation and maintenance management system, judgment is performed between the fault data and the classification, and the position of the fault data in the operation and maintenance management system is effectively and quickly positioned.

The invention discloses a multi-modal robot interaction system, and relates to the technical field of robots, the system comprises a robot subsystem and a cloud processing subsystem which are in communication connection with each other, the robot subsystem comprises a multi-modal sensing module and an interaction execution module, and the cloud processing subsystem comprises a cloud processing module. The multi-mode sensing module is used for collecting target data of at least one target user and sending the target data to the cloud processing module, and the target data comprises at least one of touch data, distance data, posture data, position data, action data and voice data; the cloud processing module is used for analyzing the target data, generating an interaction instruction and sending the interaction instruction to the interaction execution module; and the interaction execution module is used for receiving and executing the interaction instruction, so that the higher expectation of the user in the aspects of emotion accompanying and personalized service is effectively met.

The invention relates to the technical field of electric vehicle charging pile management and distribution, and discloses a new energy charging pile management and distribution method and system, and the method comprises the steps: collecting charging user data, position data and environment data, and carrying out the preprocessing; and analyzing the preprocessed data, and constructing a prediction model of the charging demand of the user. And calculating the load condition of each charging pile according to a demand result predicted by the model, and adjusting a charging pile distribution strategy. According to the invention, through the steps of data preprocessing, charging demand prediction, load calculation and distribution strategy optimization, real-time monitoring and feedback and the like, intelligent management of charging pile resources is realized. The method plays a key role in improving the efficiency of the charging service, reducing overload and idle phenomena, optimizing the user experience and the like. A more intelligent, efficient and personalized charging pile management and distribution system is provided for electric vehicle users, the utilization rate of charging pile resources is effectively improved, the waiting time of the users is shortened, and the flexibility and stability of the system are enhanced.

The invention discloses a computer data remote security management system based on block chain encryption, relates to the technical field of data security, and solves the problems that an existing verification mechanism is difficult to resist man-in-the-middle attack, and an attacker can bypass detection by tampering data and forging a verification code. According to the invention, through feature matching and dynamic interval feature calculation of the block chain storage node, dual binding of the transmission channel and the storage node is realized; in combination with randomization processing of virtual data positions, check codes have high uniqueness and reverse cracking resistance, man-in-the-middle attack and data forgery risks are effectively resisted, and a dual check code comparison mechanism before and after data transmission is realized; the verification code is generated before transmission, the identification code is generated after transmission, whether the data is tampered or lost can be accurately detected through consistency verification of the verification code and the identification code, and the integrity of the data in the remote transmission process is ensured.

The invention discloses a method for dynamically processing large-scale STDF data based on an index table and computing equipment, and the method comprises the following steps: firstly traversing a large-scale STDF file, constructing a general index table according to a data type, a data position and a data length, and then constructing a service index table according to a test item and a test result; according to user requirements, the position of required data in the STDF file is positioned by querying the general index table and the service index table, and the required data is dynamically read and processed; and outputting a processed data result. By constructing the general index table and the service index table respectively, rapid positioning and data extraction of large-scale STDF files can be achieved, and the tedious process of line-by-line scanning and analysis in a traditional method is avoided. Besides, due to the fact that the data are dynamically processed, the data are only read and processed when needed, the problem of resource consumption caused by one-time loading of the whole file in a traditional method can be avoided, and the data processing efficiency is greatly improved.

The invention discloses a multi-target information recommendation method, system and device based on position depolarization, and the method comprises the steps: obtaining log data of information browsed by a user, and carrying out the preprocessing and analysis, and obtaining a user related data set, a position related data set and an information data set; performing feature extraction on the user related data set to obtain a user feature set, and performing feature extraction on the information data set to obtain an information feature set; constructing an information recommendation pre-training model; training an information recommendation pre-training model based on the sample label data, the position related data and the sample feature data to obtain an information recommendation model; reasoning the to-be-recommended data based on the information recommendation model to obtain a click preference score and a browsing preference score so as to obtain an information recommendation result. According to the information recommendation method, the limitation of an existing information recommendation method on the information arrangement sequence and effective browsing is solved, the accuracy of an information recommendation system and the user experience are improved, and the requirements of a user for personalized and efficient information acquisition are met.

The invention discloses a pressure reducing valve multi-mode working condition abnormity monitoring method based on voice recognition. The method comprises the steps that pressure data, flow data, audio data, position switch switching value data, vibration analog quantity data and image data are collected through a comprehensive data collection module; voiceprint recognition related data acquired by the comprehensive data acquisition module is transmitted to a cloud server platform through a network transmission module; identifying and scoring the audio data through a voiceprint scoring module; the fault comprehensive judgment module is used for carrying out fault judgment, the problems that in the prior art, a means for carrying out comprehensive judgment on multiple types of defects is lacked, manual on-site checking is relied on, and the efficiency and accuracy of fault recognition are low are solved, and the advantages that comprehensive fault judgment can be carried out through combination of multi-modal data and voiceprint scoring, and the efficiency and accuracy of fault recognition are improved are achieved. And the recognition rate and the accuracy rate of working condition abnormity or fault judgment of the pressure reducing valve equipment are greatly improved.

The invention relates to a player negative behavior detection method and system, electronic equipment and a storage medium, and the method comprises the steps: comprehensively collecting behavior data such as player operation times, chat content, combat data, position information and cooperation request response conditions in a single game; multi-dimensional detection data such as game behaviors, game performance and social behaviors are obtained by processing and analyzing data such as calculation of operation frequency scores and single behavior scores, construction of a position thermodynamic diagram, statistics of the number of negative words, calculation of cooperation request response times and the like, and the comprehensive operation frequency scores and single behavior scores of players are compared with expected scores. Comparing with scores of other players of the team to judge negative behaviors, and outputting prompt information. According to the scheme, the problems that an existing reporting system depends on active reporting of players, and the detection efficiency is low are effectively solved, negative behaviors can be detected more comprehensively and accurately, game fairness and a healthy environment are maintained, and the game experience of the players is improved.

The invention provides a battery capacity correction method suitable for an intermittent data loss scene, and relates to the application field of a battery technology. The method comprises the following steps: in a mode based on intermittent data loss, marking a capacity actually corresponding to a unit SOC change in a discharge process as an actual denominator, clustering the actual denominator, obtaining a theoretical capacity corresponding to the unit SOC change, and marking the theoretical capacity as a standard denominator; according to the method, a difference value between a standard denominator and an actual denominator is utilized to carry out capacity compensation on a current data loss position, and only one of data loss positions of the same SOC is selected for compensation, so that a corrected ampere-hour integral capacity value is obtained. According to the method, the influence of data loss on the ampere-hour integral capacity value is greatly overcome, the universality and accuracy of the battery diagnosis technology in a data loss scene are improved, the feasibility of data loss vehicle diagnosis early warning is guaranteed, and a guarantee is provided for the safety of a new energy vehicle.

The invention relates to the technical field of intelligent monitoring, and discloses a pipeline corrosion monitoring method and system based on an ultrasonic thickness sensor, electronic equipment and a storage medium, and the method comprises the steps: arranging the ultrasonic thickness sensor at a vulnerable position of a pipeline, collecting the thickness data of the pipeline, building a data-position matrix, and judging whether offset data occurs or not; when the offset data exists, pipeline vibration data are collected and compared with a vibration threshold value, and whether data interference exists or not is judged; when it is judged that data interference exists, the thickness data of the pipeline is collected again after waiting time, and the pipeline corrosion amount is determined according to the second data-position matrix and the standard pipeline thickness; determining the current state parameter and comparing the current state parameter with a historical parameter, and determining a cycle detection interval; and recording the corrosion amount of the pipeline during each cycle of detection, and performing early warning when the corrosion amount of the pipeline is higher than a corrosion threshold value. The anti-interference capability is improved by analyzing the offset data, and the false alarm rate is reduced and the detection precision is improved by multiple times of data acquisition and comparative analysis.

According to an embodiment of the disclosure, a toll-free telecommunications validation system determines a confidence value that an incoming phone call to an enterprises' toll-free number is originating from the station it purports to be by incorporating one or more layers of signals and data in determining said confidence value. The data and signals can include one or more call identifiers and / or toll-free call routing logs, service control point (SCP) signals and data, service data point (SDP) signals and data, dialed number information service (DNIS) signals and data, session initiation protocol (SIP) signals and data, carrier identification code (CIC) signals and data, location routing number (LRN) signals and data, jurisdiction information parameter (JIP) signals and data, charge number (CN) signals and data, billing number (BN) signals and data, and originating carrier information (such as information derived from the ANI).

The invention provides a data processing method and device for a stream processing framework, equipment and a medium, and relates to the technical field of big data, in particular to the technical field of data warehouses. The method comprises the steps of pausing a real-time task of a stream processing framework in response to a first task control instruction, obtaining a first consumption data position corresponding to the real-time task when the real-time task is paused, and starting a first offline batch task, the first task control instruction is sent based on a real-time monitoring result of a real-time task state and consumption delay data in the streaming processing framework; after the capacity expansion operation is executed on the stream processing framework, the real-time task is started again, so that the real-time task starts to process data from a corresponding second consumption data position when the real-time task is started; wherein the first offline batch task is used for processing data between the first consumption data position and the second consumption data position. According to the invention, an integrated data warehouse of real-time stream and offline stream can be realized, and the concurrency and accuracy of data are improved.

Performing charge / showback operations in a large-scale data system by scanning multiple data sources to identify data objects for processing as a unitary group with respect to common characteristics that have an impact on finances within the system. Metadata of the identified data objects are stored in a dynamic dataset that defines a single data access unit for the referenced data objects. The system processes a user query regarding cost allocations, cost forecasts, and resource usage of respective groups within an organization. The query initiates a charge-back or show-back operation that allocates costs associated with each respective usage of resources by a department or cost center, and accesses the referenced data objects through the dataset as a single unit based on data content rather than data location in a file directory of the system.

The invention provides a game strategy planning method and system, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence, the method is applied to multiple agents, and the multiple agents comprise at least one unmanned aerial vehicle and at least one unmanned ship. According to the method, environment data, attitude data, position data and game party data of a target game region are acquired in real time, an accurate environment model and a state and action space are constructed, an objective function of a current task is efficiently solved by applying a Monte Carlo algorithm and a deterministic strategy gradient algorithm, a game countering strategy set is generated, and the game countering strategy set is calculated. And based on the game countering strategy set, the motion planning data of each agent for executing the current task is determined, each agent is controlled to execute the task according to the plan, and the game countering strategy generation accuracy, the task allocation accuracy and the task execution efficiency of the multiple agents are remarkably improved.

The invention discloses an encryption method based on an RSA algorithm, and relates to the technical field of data encryption, and the method comprises the steps: collecting to-be-encrypted data; generating a session key of the to-be-encrypted data by adopting a symmetric block encryption algorithm RC5; encrypting the generated session key by adopting an RSA public key; encrypting the to-be-encrypted data by adopting a symmetric block encryption algorithm RC5 and the encrypted session key to generate encrypted data, dividing the to-be-encrypted data into N1 groups, and encrypting the grouped to-be-encrypted data by calling the RC5 algorithm in parallel through multiple threads; and performing confusion processing of sequentially and circularly exchanging adjacent data positions on the encrypted data to obtain the encrypted data. Aiming at the low encryption security based on an RSA algorithm in the prior art, the method comprises the following steps: collecting to-be-encrypted data, and generating a session key based on data content by using an RC5 algorithm; encrypting the session key by adopting an RSA algorithm; an RC5 algorithm is called in parallel for encryption; and block position confusion processing is carried out on the encrypted data, so that the encryption security of the RSA algorithm is improved.

The invention relates to the technical field of cold chain logistics management, in particular to an intelligent cold chain management method and system based on the Internet and multi-dimensional analysis, and the method comprises the following steps: S1, collecting multi-dimensional data in a cold chain transportation process in real time, including temperature data, humidity data, vibration data, position data and state data of a transportation vehicle; s2, preprocessing the collected multi-dimensional data; s3, abnormal conditions in the cold chain transportation process are analyzed, and an abnormal analysis report is generated; s4, judging whether abnormal conditions such as temperature exceeding, humidity abnormity or excessive vibration occur in the cold chain transportation process or not, and recording specific information of occurrence of the abnormal conditions; and S5, sending the corresponding abnormal information to terminal equipment of related management personnel. According to the invention, through combination of multi-dimensional data acquisition and a big data analysis technology, comprehensive real-time monitoring and automatic abnormity early warning of the cold chain transportation process are realized, and the management efficiency is significantly improved.

The invention discloses a method and an apparatus in a node used for wireless communication. The node receives the first request; generating a first result through the first model as a response to receiving the first request; the first model is used for at least one of training or reasoning; the identifier of the first model is a first identifier, and the first identifier is a non-negative integer; the first identifier is associated with a first index, and the first index is one of a plurality of indexes included in a first index set; the first index set is associated to a first sub-identifier set; the plurality of types of data indicated by the plurality of sub-identifiers included in the first sub-identifier set comprise at least one of channel quality information data, codebook data and position auxiliary information data; the sub-identifier associated with the first identifier depends on the first index. According to the method, the design of the model identifier and the matching of the data in the system adopting human intelligence and machine learning are optimized, so that the overall performance of the system is optimized.

The invention discloses a drug inspection information sharing method and system based on a block chain, and relates to the technical field of drug inspection data management, and the method comprises the steps: sending an authentication request to a block chain network when a drug inspection device is started, verifying the state of the device according to a device digital identity certificate after an intelligent contract receives the authentication request, and sending the verification result to a server; generating a temporary operation token, encrypting the temporary operation token by using the equipment public key and returning the temporary operation token to the medicine inspection equipment; the medicine inspection equipment performs medicine inspection through the temporary operation token, synchronously acquires inspection data, a GPS position, an inspection timestamp and an equipment fingerprint, calculates a composite hash value, and encrypts the inspection data; and submitting the composite hash value to a block chain network, performing space-time compliance verification through an intelligent contract, obtaining a drug batch DID, and generating an on-chain block associated with the drug batch DID. According to the invention, the identity credibility of the medicine inspection equipment is ensured, and the authenticity, integrity and time-space consistency of inspection data are realized.

A communication system includes: a plurality of positioning signal transmission devices that transmit positioning signals; a positioning signal reception device that receives the positioning signals; and a location calculation device that calculates a location of a terminal to be positioned on the basis of reception results of the positioning signals by the positioning signal reception device, and the plurality of positioning signal transmission devices output integrity assistance data to be used to calculate integrity of a location of the terminal to be positioned, and the location calculation device calculates integrity of a location calculation result of the terminal to be positioned by using the integrity assistance data output from the plurality of positioning signal transmission devices.

The invention provides an animal product traceability terminal based on Beidou positioning, which comprises a power management module, an antenna, a data acquisition module, a communication module and a main processor which are arranged on a circuit board mainboard, and is characterized in that the main processor is respectively connected with the data acquisition module and the communication module; the data acquisition module comprises an acceleration sensor, a Beidou positioning module and a temperature sensor which are respectively used for acquiring movement step number data, position information data and vital sign condition data of a fed animal, the communication module is connected with the antenna, and the data acquired by the data acquisition module are subjected to signal receiving and transmitting through the antenna; and the power management module supplies power to the terminal. According to the invention, the obtained livestock movement condition, body temperature and positioning information can be sent to the central server at regular time, and the position, health condition, oestrus, abnormal grazing and the like of the livestock can be monitored.