3008 results about "Unique identifier" patented technology

The invention relates to the technical field of financial data processing, in particular to a multi-source heterogeneous fund data processing method and system, and the method comprises the steps: recording source information through building a data source registry, and marking a unique identifier for data; performing differential analysis on the fund data in different formats to generate standardized column type storage data; traversing column type storage data to extract statistical characteristics, performing field classification through metadata analysis and financial dictionary matching, analyzing business connotations of fields difficult to classify in combination with a localized large language model, and mapping the business connotations to a header fusion knowledge graph; generating a mapping rule from the source field to the enterprise-level data model by applying a rule engine template on the basis of field classification and semantic recognition results; converting the data structure according to the mapping rule and executing standardization processing; the quality is further optimized through data cleaning; and finally, the data are verified, standardized fund data supporting data traceability are output, and the strict requirements of financial supervision application are met.

The invention relates to a method convenient for data consanguinity collection and analysis, which comprises the following steps of: obtaining original consanguinity data comprising a task execution log, application metadata and a cross-system dependency relationship, and carrying out standardization processing on the original consanguinity data to generate structured consanguinity information comprising an asset unique identifier, an upstream and downstream association relationship and a data operation type; structured consanguinity information is synchronously written into a graph database and a distributed data warehouse, the graph database stores real-time association topology, the distributed data warehouse stores full-amount historical versions, and a transaction consistency algorithm is adopted to ensure the atomicity of double-write operation, so that the data storage efficiency is improved. Single-asset-level consanguinity tracking is performed based on real-time topology of a graph database, global consanguinity analysis is performed based on batch computing power of a distributed data warehouse, a direct dependence path, a deep association network and a closed-loop link detection result are generated, and a closed-loop management mechanism from data acquisition, analysis to optimization is formed. And the problem that an analysis result is disjointed from an acquisition end in a traditional scheme is solved.

Techniques for verifying authenticity of a cosmetic product using a distributed ledger include generating a transaction including identification information for a cosmetic product indicating a manufacturer of the cosmetic product. The transaction is augmented with a cryptographic signature from the manufacturer to prove the identity of the manufacturer. Additionally, the transaction is transmitted to at least one other participant in a distributed ledger network of participants maintaining the distributed ledger. A unique identifier is embedded on the cosmetic product or on packaging for the cosmetic product that references the identification information for a cosmetic product in the distributed ledger.

The invention relates to a network attack tracing method, system and device based on a user portrait, and a medium. The attack tracing method comprises the following steps: collecting interactive behavior data of a user in a Web page; performing compression and serialization processing on the interaction behavior data to generate a structured interaction log file; collecting fingerprint data of the user terminal and performing standardization processing to generate a fingerprint feature vector; based on the structured interaction log file and the fingerprint feature vector, generating a user unique identifier containing a risk level tag; performing clustering analysis on the interaction behavior data according to the unique identifier of the user, identifying an abnormal behavior mode of the abnormal user and marking an attack type; acquiring a public network IP address of an abnormal user, and positioning a geographic position in combination with an IP database; and constructing an attack traceability report based on the user unique identifier of the abnormal user, the abnormal behavior mode, the public network IP address and the geographic position. According to the invention, the user portrait can be accurately constructed, and the network attack behavior can be effectively identified and traced.

The invention relates to the technical field of agent construction, and discloses an agent construction method and system based on agentive workflow, and the method comprises the following steps: defining an agent core function module and distributing a unique identifier, building an inter-module communication protocol standard, and determining a message format and a priority rule; the method comprises the following steps: distributing computing resources for each module, setting an elastic capacity expansion and contraction strategy, generating a module dependency graph and an architecture metadata file, detecting the loss and delay of multi-modal input data, generating compensation characteristics based on historical context, calculating the quality confidence of each modal, and carrying out dynamic weighted fusion. According to the invention, a three-level alignment architecture is provided to realize cross-modal semantic consistency, and the generated content is ensured to accord with real scene logic; a double-layer decision-making mechanism is designed to drive workflow dynamic optimization, and the system agility under a complex task is remarkably enhanced; a privacy-efficiency balanced federated architecture is constructed, and differential content generation is supported while enterprise data sovereignty is protected.

The invention discloses a cross-container application fusion switching method of a swan monk system, which comprises the following steps: a system service layer deploys a container application management service, an application framework layer realizes a proxy application manager, when a container application is started, a container side allocates a shared memory and configures authority, the container manager collects metadata to initiate registration, and the application framework layer realizes a proxy application manager; the container application management service converts a memory handle into a texture handle, allocates a unique identifier and triggers a proxy application manager to generate a proxy application, and the proxy application initializes a Vulkan rendering environment; the container side renders an application interface to a shared memory, the proxy application imports texture and constructs a lightweight Vulkan rendering pipeline, and scaling sampling is carried out to generate a thumbnail of the container application; and when the container application exits, the shared memory is released, the container application management service cleans the shared memory reference, triggers and destroys the proxy application, and recycles the texture resources through the reference counter, so that seamless fusion, low-delay switching and efficient resource utilization of the container application in a native application thumbnail form are realized.

According to the archive data tracking and multi-party cooperation auditing method based on the block chain smart contract provided by the invention, the authenticity and non-tampering property of archive data are guaranteed through a block chain technology, and an efficient and transparent auditing process is realized in combination with the smart contract. According to the method, a multi-level encryption storage and unique identifier generation mechanism of archive data is designed and is used for accurately tracking an archive circulation process; the access behavior is automatically recorded and verified through the intelligent contract, and the operation compliance is ensured. A distributed consensus algorithm is adopted for multi-party cooperative auditing, multiple auditing parties are allowed to participate together, and meanwhile objectivity and authority of auditing results are ensured. The method improves the safety, transparency and efficiency of archive data management and auditing, and can be widely applied to archive management and auditing scenes in the fields of governments, enterprises, education and the like.

The invention belongs to the technical field of computers, and particularly relates to an information integration management method and system supporting real-time updating, and the method comprises the steps: accessing a heterogeneous data source through a distributed gateway, carrying out the adaptive analysis of a protocol, and standardizing a structure; adding a millisecond timestamp and a unique identifier, and generating a semantic data cluster through streaming engine sliding window association analysis; after multi-dimensional consistency verification is executed, writing and storing are carried out by adopting a double-buffering and snapshot isolation mechanism; and dynamically assembling the customized view according to the user role and the context and safely returning the customized view. The system correspondingly comprises a protocol analysis module, a time sequence marking module, a streaming association module, a semantic verification module, a double-buffer control module, an index updating module, a view assembling module and a secure transmission module. According to the invention, millisecond-level real-time convergence, conflict-free fusion and on-demand view output are realized, and the data access flexibility, the quality guarantee capability and the service adaptation flexibility are comprehensively improved.

The invention provides an electronic data evidence storage verification method and system based on hierarchical hash and an intelligent contract, and relates to the technical field of block chains and data security, and the method comprises the steps: obtaining to-be-stored electronic data; to-be-stored electronic data is divided into data blocks according to a preset rule, a unique identifier and a timestamp are added to each data block, and a standardized data unit is generated; performing hierarchical hash calculation on the standardized data unit, generating a leaf node hash value by each data block, aggregating the leaf node hash values layer by layer according to a Merkle tree structure, and generating root hash; calling a block chain smart contract, submitting the tree structure hash, the timestamp and the public key encrypted signature to a block chain network, after verification of a consensus node, writing the evidence information into the block chain, analyzing a hash path submitted by a user by the smart contract to perform data verification, if the hash path is consistent with the data verification, returning verification success, otherwise, triggering an exception handling contract; through the dynamic partitioning algorithm and the layered hash structure, the calculation overhead of large file processing is reduced.

Systems and methodologies are provided for the automated collection, transformation, and documentation of API endpoints in cloud environments, streamlining cybersecurity workflows. A discovery module autonomously identifies endpoints accessible by various user roles. An Identifier Normalization Module dynamically adapts unique identifiers to a standardized naming convention for documentation. The system can further include a comparison engine to evaluate and visualize API access across different user roles, facilitating a comprehensive audit and compliance process. Systems and methods enable consistent endpoint mapping, role-based access clarity, and enhanced security posture management through an interactive dashboard, generating insights into the cloud instance's API landscape.

The invention discloses a multi-platform Internet of Things equipment unified access management method, equipment and a storage medium, and relates to the technical field of Internet of Things integration. The method comprises the step of solving the fragmentation problem of cross-platform equipment access through dynamic configuration adaptation. The method comprises the following steps: starting from receiving a front-end equipment operation request, indexing a pre-configured mapping relation database through an equipment unique identifier, and obtaining a target platform type, an API address and an encryption certificate; dynamically calling a protocol adapter based on a platform type, and injecting an account certificate into a request header or a message body according to a platform specification; converting the original parameters into a format supported by a target platform through a protocol conversion engine, and combining the original parameters with the authentication information to generate a complete request; and realizing high-reliability communication by using an asynchronous message queue, and finally returning a platform response to a front end. According to the invention, through mapping management of the configuration driver and dynamic adapter scheduling, equipment access unification across the Internet of Things platform is realized.

The invention relates to a network security protection method and system based on a block chain, and aims to solve a series of challenges of identity authentication single-point failure, insufficient static block chain fragmentation, threat detection limitation, encryption algorithm security problem and the like in the existing network security protection technology. According to the method, an on-chain digital identity is generated by fusing an equipment unique identifier and user biological characteristics, dynamic authority management is performed based on the identity, network traffic is detected in real time by using a deep learning model of adversarial training, a threat detection result is generated, an authority level is updated according to the detection result through an intelligent contract, and meanwhile, the user experience is improved. A fragmented block chain network technology is adopted, the number of sub-chains is dynamically adjusted according to a network load, cross-chain threat intelligence synchronization is realized through a relay chain, in addition, a threshold signature and zero-knowledge proof technology is also adopted, permission change records and cross-chain data are encrypted and verified, the security and privacy of the data are ensured, and the security and privacy of the data are improved. According to the invention, the efficiency and reliability of network security protection can be effectively improved, and a safer and more reliable network environment is provided for users.

A System for providing Interactive Transaction Frameworks, utilizing biometric authentication and semantic web technologies is disclosed. The system registers users with a unique biometric-based identifier, and employs ontologies, schemas, and knowledge graphs to create a semantic foundation. A Large Language Model integrated with the Knowledge Graph Module enables intelligent processing of Interactive Transaction data. The system composes Interactive Transactions with fields mapped to semantic triples, maintains them in an Interactive Transaction Library, and manages user permissions. A Transaction Publishing Platform facilitates Interactive Transaction distribution and submission-response cycles. The system refines inputs and responses, determining outcomes based on these interactions. The system offers a sophisticated, secure, and adaptable approach to Interactive Transaction management and processing across various domains.

The invention relates to a distributed outbound system optimization method based on cloud computing. The method comprises the following steps: disassembling an outbound task into fine-grained subtasks including dialing, recording, interaction and recording; generating a unique identifier for each subtask; based on a distributed task scheduler; according to node real-time performance and network delay, dynamically distributing tasks, and introducing a task priority rule; monitoring a task execution state in real time through a distributed tracking system; recovering and redistributing abnormal and failed tasks; fragmenting the call-out data according to regions or customer groups, and distributing the call-out data to different nodes; processing the call record and the client feedback by using a stream processing framework comprising Apache Flink; adding a call task including Kafka into a distributed task queue; setting a dynamic priority queue, and adjusting the priority according to the task timeliness; setting an overtime threshold value for the call task, and monitoring a task state in real time; and when the task is overtime or failed, triggering a retry strategy including adjusting the call period and switching the node.

The invention provides an identity recognition method and system based on unmanned aerial vehicle management and control. The method comprises the following steps: acquiring encrypted identity data based on unmanned aerial vehicle state monitoring, and generating an initial code containing a unique identifier, a position and a state parameter; dynamically adjusting a coding rule according to the acceleration variation, and generating a differential sequence matched with the motion state; generating a composite identifier containing a timestamp and a geo-fence through irreversible conversion; fusing the positioning data to dynamically bind the identifier and the track to generate synchronous track data; when the geofence is triggered, redundancy calibration is activated to generate anti-interference data; the composite identification and the anti-interference data are subjected to fragmentation packaging, and a topology dependence encryption block is constructed through a Hash abstract chain; and recombining the encrypted blocks in sequence based on the Hash chain, and checking the space-time consistency of the encrypted blocks and the geofence during recombining. According to the invention, the identity anti-counterfeiting and cross-region transmission security in the dynamic flight of the unmanned aerial vehicle is improved.

The invention provides a laboratory equipment access and configuration method and system based on dynamic protocol analysis, and the method comprises the steps: firstly, monitoring a physical connection signal of a port, automatically triggering communication link configuration, calling a preset protocol parameter based on an interface type, and obtaining first identification information of equipment; then, based on a preset protocol mapping table or a dynamic matching rule base, determining a protocol type, and based on the protocol type, performing segmented analysis on the original data stream, identifying an effective frame and checking integrity to obtain a field definition, an instruction template and a communication parameter for binding storage with the unique identifier of the equipment; and finally, automatically generating an instruction according to the communication configuration, performing communication interaction with laboratory equipment, and triggering retransmission or link recovery operation when the communication state is abnormal by monitoring the communication state in real time. In addition, the communication condition of the laboratory equipment is displayed in real time through the interaction platform. According to the method, the deployment cost is reduced through full-automatic identification configuration, and the communication stability is improved through communication link optimization and exception handling.

The invention discloses a cloud mobile phone end-to-end performance tracking method and related equipment, and relates to the technical field of cloud computing, and the method comprises the steps: obtaining client touch event data and network event data, and generating a global unique identifier based on a preset Hash algorithm; obtaining server resource event data; performing timestamp calibration on the client touch event data and the server resource event data based on a hardware-level clock synchronization and software compensation algorithm to generate a synchronous timestamp; based on the synchronization timestamp, aligning the event sequences of the client and the server through a dynamic time warping algorithm to generate an aligned event sequence; performing causal probability calculation on the aligned event sequence based on a Bayesian network model, and determining a causal relationship weight between resource events; and performing root cause matching according to the causal relationship weight and a preset abnormal mode library, generating a root cause list with priority ranking, and triggering execution of a self-healing strategy.

A system for extracting a number of data elements from one or more unstructured data sources. The system may separate the text from the tables in a document, such that only the table data may be sent to the large language model (LLM), when the LLM only needs to review the table data. The system generates chunks from the document. The system associates unique identifiers with each chunk to provide traceability. The system identifies relevant chunks from the documents and includes the relevant chunks with a request to extract the data elements in a prompt to the LLM. The system also includes a request for the LLM to report the chunks used during extraction of the data elements. The reported chunks are stored with the extracted data for verification, auditing, and error control.

The invention discloses a high-precision instrument assembly fault backtracking method and system, belongs to the field of precision manufacturing, and aims to solve the problems that in a traditional backtracking method, assembly data are scattered and unreliable, fault root positioning is fuzzy, and new scene adaptation depends on a large amount of data. The method comprises the following steps: collecting assembly structured data, video images and environment data in a multi-source manner, filtering out low-quality images, and distributing unique identifiers for products; fusing the multi-modal data to generate a depth feature matrix; constructing an anomaly detection model to output a risk score and a label; hashing the data and then storing the data into a product exclusive private block chain; when a fault occurs, extracting data on the chain through a unique identifier, reconstructing an assembly process by using a graph neural network, and comparing a standard positioning root; and based on the fault report incremental training model, parameters are optimized in combination with meta-reinforcement learning. According to the method, the data authenticity is guaranteed, the fault backtracking precision and efficiency are improved, a new scene is quickly adapted, the production rework rate is reduced, and the stable assembly quality is maintained.

The invention provides a drug identification information intelligent association method and system based on multi-source data fusion. According to the method, firstly, multi-source heterogeneous data generated in the medicine circulation process is obtained, then key information elements printed on the surface of a medicine package are recognized, meanwhile, a unique identifier bound with the medicine identity is extracted, and then a dynamic tracking link of a medicine transportation path is established; then cross-modal association matching is carried out on the key information element, the unique identifier and the dynamic tracking link to generate a dynamic mapping relation, finally the consistency of the dynamic mapping relation is verified, and the verified dynamic mapping relation is synchronously updated to a supervision terminal of a medicine circulation link. According to the technical scheme provided by the invention, the identification precision and timeliness of risks such as package tampering and path forgery are improved, the abnormal omission ratio caused by data acquisition errors or artificial tampering is reduced, and the reliability of cross-modal data collaborative verification is enhanced.

The embodiment of the invention provides a security authentication method, device and system for a test platform, and a storage medium, and relates to the technical field of network security. The method comprises the following steps: performing fingerprint acquisition on virtual and real equipment to generate a unique identifier, dynamically slicing based on a software defined network to form an isolated test environment, and injecting a zero-trust access strategy associated with the fingerprint; and based on the zero-trust access policy and the device fingerprint, allocating a minimum permission through an attribute-based access control model, continuously evaluating device behaviors to calculate a dynamic trust score, and adaptively updating the permission according to the trust score. By constructing a full-process security certification system and through multi-dimensional mechanism cooperation, dynamic risk perception and timely strategy adjustment, fine-grained control of virtual and real equipment access in an industrial control scene is realized, the dynamic adaptability and risk resistance of a test platform in a complex network environment are improved, and the test efficiency is improved. Equipment access safety, authority distribution minimization and behavior monitoring continuity are ensured, and the safety risk of the industrial control system is reduced.

The invention discloses a food production traceability management system based on a block chain, which belongs to the field of food management systems, and is characterized in that a unique identifier ID of an inheritor is generated based on an SHA-256 Hash algorithm, a Merkle tree root Hash value of food production data is dynamically associated, a non-tampering digital identity file is constructed, a data island of traditional decentralized management is broken through, and the traceability of food production is improved. According to the technical scheme, full-chain credible association between the non-abandoned technology and the production process is ensured, validity of an electronic signature is automatically verified by means of an intelligent contract, data tampering or identity failure risks are recognized in real time by comparing a public key decryption result with a signature hash value, JSON format alarms are pushed by means of Apache Kafka message middleware, cross-department collaborative response is achieved, and the security and reliability of the electronic signature are improved. The risk prevention and control efficiency is remarkably improved, encryption signature is performed in combination with an ECDSA key pair of a hardware security module, strong binding of an inheritor identifier, a production batch and equipment is ensured, identity fraudulent use or qualification counterfeiting is prevented, and traceability of the whole life cycle of non-abandoned skill inheritance is achieved.

The embodiment of the invention provides a bill collaborative management method and system based on multi-source heterogeneous data fusion, and belongs to the technical field of data processing. The method comprises the following steps: performing hash calculation according to standardized bill data to obtain a unique identifier; and obtaining a map node corresponding to the standardized bill data to obtain a target map node. The path from the map root node to the target map node is a target structure path. And obtaining a complete behavior sequence of the standardized bill data according to the unique identifier and the behavior log. And constructing a behavior structure joint sequence according to the target structure path and the complete behavior sequence. And inputting the behavior structure joint sequence into the structure perception embedding model to obtain a sequence embedding vector. And obtaining a structure behavior inconsistency score and an abnormal type label according to the structure behavior consistency evaluation function, the behavior structure joint sequence and the sequence embedding vector. And generating a suggestion text according to the structure behavior inconsistency score and the abnormal type label, and displaying the suggestion text. Accurate identification of abnormal bills is realized.

The invention relates to an aviation equipment manufacturing digital main line engine system supporting multi-source heterogeneous data access, and belongs to the technical field of aviation manufacturing data management. The system comprises a multi-source heterogeneous data access adaptation module, a data fusion processing module and a full-process data link construction module. The multi-source heterogeneous data access adaptation module passes through a data interface protocol and format conversion component; the data standardization and fusion processing module completes association fusion through an aviation heterogeneous data collaborative computing framework by means of an aviation manufacturing field data element standard library, a unified heterogeneous data model is generated, and the framework comprises a data fragmentation layer, a parallel node layer and a result aggregation layer; and the full-process data link construction module constructs a data link covering the full life cycle of the product based on a time sequence association algorithm and a product unique identifier mapping mechanism. The system can effectively solve the integration and management problems of multi-source heterogeneous data in aviation equipment manufacturing, and improves the data processing efficiency and the whole-process data tracing capability.

The invention provides a firmware encryption method and system based on a device unique identifier and dynamic key verification, and relates to the technical field of firmware protection, and the method comprises the steps: obtaining a unique identifier of a device, the unique identifier being hardware feature information which cannot be modified; a dynamic key is generated based on the unique identifier and the random number, and the dynamic key is realized through an encryption algorithm and is regenerated every time the device is started or firmware is updated; the dynamic key is stored in a storage area protected by hardware, and the storage area is subjected to double protection of hardware isolation and logic encryption; and when the device is started, the dynamic key is regenerated, the unique identifier of the dynamic key and the unique identifier of the dynamic key stored in the storage area are compared and verified, if the dynamic key and the unique identifier are consistent, firmware operation is allowed, and otherwise, a safety response mechanism is triggered. According to the invention, the security and reliability of firmware protection can be improved.

The invention relates to a video frame data segmentation right confirmation and dynamic transaction method and system based on a block chain. The method comprises the following steps: segmenting video stream data according to a preset frame rate to generate independent frame images, and carrying out anti-collision hash calculation on the independent frame images to generate a unique identifier; generating a comprehensive value score through a multi-modal analysis model in combination with the independent frame image and the corresponding script text data; generating NFT assets anchored to the block chain according to the comprehensive value score and the unique identifier; and dynamically adjusting the income distribution proportion of the NFT assets through the smart contract based on the user film watching data. According to the method, uniqueness right confirmation of frame data is realized through precise segmentation and anti-collision hash coding, value evaluation is performed by using a multi-modal analysis model, and capitalization and on-chain right confirmation are completed by means of a block chain technology. In addition, the income distribution proportion is dynamically adjusted in combination with the smart contract, efficient transaction and right distribution of the video frame data are realized, and the commercial value and transaction efficiency of the video data are improved.

Embodiments are described herein for document authentication certification using information stored on a distributed ledger such as a blockchain. A distributed ledger may securely store document data describing the document. Use of a distributed ledger may provide an immutable, readily auditable record of the history of the document. Each user participating in the system may be assigned a unique identifier to be used for conducting transactions on the distributed ledger network. A user may also be provided with a digital security token such as a cryptographic key that is useable to authenticate the user and enable access to the document data stored on the distributed ledger(s).

The invention discloses a multi-field business collaborative management system and method based on a block chain, and relates to the technical field of business collaborative management. Standardization rules are introduced, the field name, the data type and the unique identifier of data are processed in a unified manner, and by labeling sources, timestamps and operation records, the business collaborative management efficiency is improved; an anomaly detection algorithm based on statistical distribution, machine learning and rule verification is adopted, consistency verification and repeated data cleaning are combined, key features are extracted through principal component analysis, sparse coding and a deep learning embedding model, semantic alignment and feature fusion of texts, numerical values, time sequences and image data are achieved through multi-modal modeling, and the feature fusion of the text, numerical values, time sequences and image data is achieved. Cross-modal unified data representation is generated; a knowledge graph technology and a block chain technology are combined, a semantic relationship between fields is constructed through semantic alignment, an alliance chain is used for recording data circulation and operation, dynamic access authority management is realized in combination with an intelligent contract, and transparency and non-tampering performance of data are guaranteed.

The invention discloses an Internet of Things data transmission security enhancement method combined with quantum random number generation, which comprises the following steps of: generating a high-security and unpredictable random number seed through a quantum random number generator, and generating a dynamic binding key in combination with a unique identifier of equipment and a timestamp, the binding key is used for generating a shared session key between devices through a quantum secure handshake protocol, so that the confidentiality and integrity of data transmission are ensured, a dynamic key updating mechanism is introduced, the binding key and the session key are updated regularly, the security risk caused by long-term use of the same key is avoided, a key destruction mechanism is designed, and the security of data transmission is ensured. A session key is completely destroyed after a session is ended, a malicious attacker is prevented from recovering the key, and a standby key generation and synchronization mechanism ensures that the system can automatically switch to a standby key when key synchronization fails or communication is abnormal, so that data transmission is not affected. The method has the advantages of good expandability and high safety.

The invention relates to a spatio-temporal data prediction method based on space grid coding and a large language model, and belongs to the field of artificial intelligence and spatio-temporal data analysis. The method comprises the following steps: according to a spatial range of a geographic area, dividing the area into grid units, processing the grid units by adopting a coding method, and identifying each unit through a unique identifier; constructing a space-time dependency model based on the stay record of the user, representing each stay as a tuple, and predicting the next position of the user by analyzing a historical stay sequence and a context stay sequence; and designing a space-time instruction optimization prompt template in combination with a large language model, guiding the model to analyze historical data and context data by introducing grid coding and context perception reasoning, generating next position prediction, and providing explanation for each prediction. According to the invention, through grid coding and hierarchical modeling, the generalization ability of the model is enhanced, and accurate spatio-temporal behavior prediction is realized.