84 results about "Index mapping" patented technology

The invention provides a data security encryption method and system based on high-security machine learning, and the method comprises the steps: collecting an access behavior of to-be-encrypted data, and calling context and environment meta-information to construct a structured feature sequence; establishing index mapping between the feature sequence and a historical encryption execution record, and extracting significant features by using a feature scoring and information gain evaluation method; the system executes multi-level decision path search based on hierarchical condition division according to the significant feature sequence of the current task, and judges the security level and the encryption risk situation of data; the system constructs an encryption control sequence including a parameter instruction block and an execution logic structure according to the task risk level and the strategy index; the encryption engine analyzes the instruction packet and executes a corresponding encryption task, and generates a complete record file containing metadata and a tracking tag at the same time; and the system performs statistical analysis on decryption feedback logs and encryption abnormal records, and optimizes the strategy dictionary by adopting a sample weight updating and feature re-evaluation method.

The invention provides a vector index-based data retrieval method and apparatus, and an electronic device, and relates to the field of databases. The method comprises the steps of receiving a query task of a target user; determining a plurality of pre-selected data blocks in the target database according to the query range; determining target data in the plurality of pre-selected data blocks through vector retrieval based on the vector index; returning the target field of the target data to the target user; and based on the vector index, determining the target data in the plurality of pre-selected data blocks through vector retrieval: if the pre-selected data blocks are combined data blocks generated after the plurality of initial data blocks are combined, and new vector indexes are not generated for the combined data blocks, determining the target data in the plurality of pre-selected data blocks, and if yes, retrieving target data in the plurality of pre-selected data blocks based on respective vector indexes and index mapping data of a plurality of initial data blocks corresponding to the pre-selected data blocks. According to the method and the device, data query interruption caused by initial data block merging is avoided, and time and computing resources required by data retrieval are reduced.

The invention relates to the technical field of intelligent scoring, in particular to a teacher teaching skill multi-dimensional intelligent scoring method and system.The method comprises the following steps that based on a teaching behavior multi-dimensional evaluation system, scoring standard connectivity strength is recognized, behavior consistency and language stability are analyzed, a feature behavior set is extracted, adjacent areas are expanded, interference nodes are removed, and the scoring standard connectivity strength is obtained; marking isolated point and breakpoint complementation structures, combining small regions, removing fragments, extracting behavior coding sequences, clustering and distributing labels, identifying index mapping, and outputting a teacher teaching skill classification and partition identification label set. The judgment of behavior consistency and language expression stability on skill features is enhanced, the accuracy and real-time performance of an evaluation result are improved, particularly, the strength and deficiency of teachers are meticulously analyzed and fed back in a complex teaching scene, teacher growth and teaching quality optimization are effectively supported, the high efficiency and unbiasedness of an evaluation framework are improved, and the evaluation efficiency is improved. And valuable education decision support is provided.

The invention discloses a data processing system and method for big data modeling, and belongs to the technical field of data processing.The method specifically comprises the steps that feature tree operation records, geometric grids and constraint solving logs are collected in a computer aided design environment and combined into an initial data packet, and a design number and a time stamp are bound; respectively converting the three types of data into a topological sequential sequence, a graph data structure and a constraint conflict trajectory sequence, and unifying the topological sequential sequence, the graph data structure and the constraint conflict trajectory sequence into a sample unit format; generating a geometric semantic slice sequence and bidirectional index mapping on the graph data structure according to a topological time sequence, generating a multi-view rendering result for the slice, synthesizing a tensor, and keeping an index relationship from pixels to topological entities; performing time sequence alignment based on the multi-view rendering tensor, the topology time sequence and the constraint conflict trajectory sequence, generating a geometric sample index table, and performing fragmentation storage; and finally, exporting a uniform-format data packet containing a graph data structure, a time sequence and image features from the index table for direct reading of a big data modeling processor.

The invention relates to a distributed data consistency characterization and credibility verification method based on a block chain, and the method comprises the steps: collecting multi-source power grid operation data in real time among a dispatching master station, a transformer substation and edge equipment, carrying out the unified structural processing of the multi-source power grid operation data, and extracting a hash abstract to guarantee the normalization of a data source; hash abstracts generated by all the nodes are uploaded to a consistency comparison engine, a multi-dimensional consistency calculation model is established based on key parameters including timestamps, voltages and currents, and data differences and conflicts are identified; state coding is carried out on a comparison result, a power grid data consistency state identifier is generated, and the state identifier is written into a block chain in combination with a device ID and a time label; and the system constructs an index mapping mechanism based on the on-chain state identifier, so that the master station and the dispatching center can perform cross-system consistency verification. According to the method, automatic consistency judgment and credible evidence storage of the distributed power grid data can be realized, and the accuracy of cross-system data sharing, the real-time performance of verification and the safety of system operation are improved.

The application provides an AI agent memory management method and system based on cold and hot layering, relates to the technical field of artificial intelligence, and comprises the following steps: obtaining and preprocessing AI agent historical information, and storing the information in a vector form; calculating scores based on access frequency and semantic association; constructing a double-threshold triggering mechanism to realize data cold and hot layering migration; establishing index mapping and dynamically monitoring data heat to realize back migration; and dynamically adjusting the migration strategy by monitoring the storage water level in real time. The application solves the problem of low AI agent memory management efficiency, realizes efficient access of memory content, and reduces storage cost.

The embodiment of the invention discloses a password information processing method and device, electronic equipment and a storage medium, multiple groups of encryption key pairs are bound with a key effective time interval, a key corresponding to a playing time period is quickly matched in combination with an index mapping table, a user does not need to manually input multiple passwords, and the user experience is improved. The problem that the password needs to be input repeatedly after being replayed after being modified is solved; a key is stored by an asymmetric encryption algorithm, and is transmitted through a secure transmission channel, so that the key storage and transmission security is ensured, and the problem of insufficient security of existing key management is improved; the integrity of the decrypted data is verified by means of the verification key, and the equipment end is triggered to retransmit incomplete data fragments, so that the defects of lack of data integrity guarantee and an exception recovery mechanism are overcome; and meanwhile, the key query efficiency is improved by the index mapping table.

The invention provides a method and a system for dynamically maintaining a Token, computing equipment and a computer readable storage medium, in the method, after a server generates a first Token after login verification of a client is passed and before the first Token is returned to the client, the first Token is stored in a first database, and an index mapping table of a unique identifier of the Token is established; 'pseudo-stateful 'management of the Token is realized by intercepting a client request; when the risk of Token leakage occurs, the corresponding record in the first database can be directly deleted or the interface is called to forcibly expire the Token. Furthermore, all active Tokens of the user are stored by taking a user name as a key to form a global view of the login user, an automatic cleaning function, manual revocation and a self-defined capacity control strategy are integrated through a dynamic maintenance strategy, the Token number upper limit and validity period rule of a single user are supported to be dynamically adjusted, and flexible management of concurrent login of multiple devices is realized.

The invention relates to the field of data lookup, and discloses a locality perception lookup table lookup method, which comprises the following steps of: S1, reordering between rows: clustering and reordering the rows of an input vector and a weight matrix according to the same quantized value to enable elements with the same quantized value to be continuously distributed; for a common matrix GeMV scene, cache locality is improved through rearrangement and subsequent blocking operation, and repeated loading of a lookup table LUT is reduced. And the data locality of the GeMV scene is remarkably improved through inter-line reordering and a virtual mapping strategy. On the basis of reordering of input vector element values, elements with the same value are aggregated, so that the LUT line loading times are reduced to 256 times at most from being in direct proportion to the input dimension d, and frequent replacement of the LUT lines in the WRAM is avoided; meanwhile, a weight matrix is divided into BR * BC sub-matrixes, the characteristic that vertical adjacent rows share an accumulator is utilized, multi-row sub-matrix calculation is loaded at a time, and virtual rearrangement maintains the row matching relation between an input vector and the weight matrix through index mapping.

The invention relates to a multi-line text searching and replacing method and system, and the method comprises the steps: carrying out the preprocessing of an original multi-line text, a multi-line searching content and a multi-line replacing content, removing the head and tail spaces of each line, and obtaining a corresponding logic text, a logic searching content and a logic replacing content, judging whether the logic search content contains a preset wildcard character or not, if the logic search content does not contain the preset wildcard character, carrying out simple character string matching on the logic text to obtain a logic index search result, converting the logic index search result into an original character index by utilizing a preset index mapping relation for positioning, and executing simple replacement operation, and if the logic search content contains the preset wildcard character, carrying out simple character string matching on the logic text to obtain a logic index search result; and if the logic text is matched with the fuzzy item list, regarding the logic search content as an integral matching block, performing sliding comparison according to rows in a row array corresponding to the logic text, if the matching succeeds, extracting the fuzzy item list and the starting and stopping row indexes of the matching block, performing positioning by utilizing an index mapping relation, and executing fuzzy replacement operation of inserting the fuzzy item list into a placeholder.

The invention discloses a multi-modal database-oriented adaptive index structure selection method, which comprises the following steps of: analyzing statistical characteristics such as data dimensions, variances, sparseness and distance distribution of each modal, calculating hidden dimensions of the modals, and describing effective data complexity of the modals; based on a preset index adaptation rule, automatically mapping each mode to an optimal index type in the candidate index structure set, and completing automatic construction of a local index and binding of the local index and a global routing structure according to the optimal index type; on the basis, the multi-modal query can be automatically routed to the corresponding index to execute retrieval according to the index mapping relation. According to the method, an index structure self-adaptive selection mechanism without manual configuration is realized, the index maintenance cost of the multi-modal database can be remarkably reduced, and the query efficiency and expandability in a complex retrieval scene are improved.

This application provides a rapid migration method and system based on customized data packages, as well as a readable storage medium. The rapid migration method based on customized data packages includes: extracting metadata from oil and gas exploration data using a general data acquisition module, employing the system's native API and file parsing algorithms; based on the metadata and the target operating system, formulating a migration strategy and monitoring the migration process through a control module, and generating a task execution list; dynamically adjusting the execution plan of the task execution list through a scheduling module, and generating a task execution priority list; and according to the task execution priority list, encapsulating and transmitting the data to the target system through a migration module, and unpacking the data according to the mapping index file and the unpacking priority list. Through the technical solution of this application, seamless data synchronization across operating systems can be achieved through customized data packaging and index mapping strategies, ensuring that the migrated data is immediately available and improving the execution efficiency of seismic exploration projects in multi-platform collaborative scenarios.

The invention provides an imaginary number hybrid simulation consistency data interaction method and system based on puppet entities, and the method comprises the steps: determining virtual simulator force resources participating in simulation, and generating a virtual force-puppet entity four-layer element index mapping table; according to the four-layer element index mapping table, exclusive data field intervals are divided for puppet entities of the same kind, data field identifiers are further dynamically distributed to members in the intervals, and data field isolation between the puppet entities in the digital space is completed; configuring transmission strategies for different theme protocol types according to different types of protocol data of different puppet entities in respective data interaction exclusive domains; the puppet entity carries out frequency division on the synchronization time macro-beat to the micro-beat capable of being scheduled and calculated in the simulator according to the simulation period requirement of the mapped simulator; and formulating a set of full life cycle management mechanism for the puppet entity, and performing unified management on the states of stages such as creation, initialization, operation, pause / recovery, termination and destruction of the puppet entity in the simulation process. According to the method, the data transmission overhead is effectively reduced, and the space-time consistency and situation consistency of imaginary number hybrid simulation are ensured.

The invention discloses an embedded device word stock dynamic replacement system and method based on Unicode and GB2312 coding mapping, and belongs to the technical field of embedded system character coding and word stock management. According to the method, a lightweight Unicode-GB2312 bidirectional index mapping table is constructed, and on-demand loading and mixed rendering of Unicode characters are achieved on the premise that an original word stock is reserved. And by adopting a hash table accelerated query, virtual zone bit code expansion and incremental updating mechanism, the storage occupation is reduced by more than 95%, the word stock updating efficiency is improved by 100 times, and the progressive adaptation of a full Unicode character set is supported. The method can be widely applied to intelligent terminals, industrial equipment and other scenes, and the contradiction between multi-language compatibility and resource limitation is solved.

This invention discloses a multimodal event joint extraction method based on a link matrix. It determines the event structure system of the application domain and constructs a cross-modal event extraction dataset. A link matrix between image patches and text sequences is constructed. A multimodal event extraction model is built based on ViLT, where the multimodal Transformer encoder takes image patch pixel features, word instance features, and image patch-text word instance pair features as input to obtain a multimodal feature input decoder, acquiring image-text event type consistency features, event type features, and image-text event element features. Using maximum likelihood estimation, the image-text event type matching result with the highest probability, the event type, and the image-text event element are taken as an index, and the text event information is obtained by index mapping. This invention solves the problems of low recognition accuracy in weakly supervised and unsupervised methods and inaccurate matching of pipeline-style multimodal event element information, providing a new event extraction strategy for the field of multimodal information extraction.

Techniques for vector database indexing are described. In an example, a plurality of unstructured data is obtained. Vector embeddings are performed on each unstructured data from amongst the plurality of unstructured data to generate a plurality of vectors. Each vector from amongst the plurality of vectors is indicative of attributes of the unstructured data from amongst the plurality of unstructured data. The plurality of unstructured data and the plurality of vectors is stored in the vector database. A vector index corresponding to the plurality of vectors based on a first indexing mechanism is generated where the vector index includes at least one cluster of vectors with similar attributes. An index mapping is performed to store the vector index into a relational database.

The application belongs to the technical field of computer software and information security, and particularly relates to a pseudo-random dictionary generation and distribution method and system based on index mapping. The method comprises the following steps: obtaining a character dictionary and a target string length to obtain an initial character sequence; randomly rearranging the initial character sequence to generate a disordered character dictionary; calculating a total combination space of the string according to the disordered character dictionary and a character repetition constraint condition; mapping a numerical index into a target string on demand based on the total combination space of the string through a pseudo-random dictionary mapping method; grouping the numerical index to form a serial number pool, and persistently storing the index sequence in each serial number pool after randomly disturbing the index sequence; and taking out an actual index value from the current serial number pool according to a distribution cursor during the running period, converting the actual index value into a final string result through a mapping method, and outputting the final string result. The application realizes the unique generation and safe distribution of the string through the index mapping and double disordering mechanism, avoids the running period repetition verification, and prevents the number from being speculated.

The application discloses a kind of embedded device font library dynamic replacement system and method based on Unicode and GB2312 encoding mapping, belong to embedded system character coding and font library management technical field.Its method is by constructing lightweight Unicode-GB2312 bidirectional index mapping table, realizes Unicode character on-demand loading and mixed rendering under the premise of reserving original font library.Hash table is used to accelerate query, virtual area code extension and incremental updating mechanism, so that storage occupancy is reduced by more than 95%, font library updating efficiency is improved by 100 times, and progressive adaptation of full Unicode character set is supported.The application can be widely applied to intelligent terminal, industrial equipment and other scenes, and solves the contradiction between multi-language compatibility and resource limitation.

The invention discloses a large-model-based case material intelligent homing system and method, and relates to the technical field of data storage. After case type feature information is extracted through a large language model, a unique code is analyzed according to a preset coding rule and is bound with a homing target; the method comprises the following steps: classifying and storing case materials, constructing a field index mapping table containing a unique case identifier and a storage partition address, creating a distributed intelligent homing dual-channel and a homing shunt, accurately distinguishing cases to be homed, supplementing materials and invalid submission based on the index mapping table, performing corresponding processing, synchronously cleaning index table completion records, and completing the homing process. Homing delay and data disorder caused by mixed storage are avoided; the problems of unreasonable resource scheduling and server waste are solved by extracting a cross-regional space-time rate threshold to judge abnormality, predicting the number of abnormalities in combination with a sliding window and dynamically configuring a dual-channel memory proportion. The retrieval and eye-returning efficiency is greatly improved, the eye-returning process in a cross-domain scene is ensured to be stable and efficient, and resource utilization is remarkably optimized.

The invention provides an information processing method and device, equipment, a storage medium and a computer program product, and the information processing method comprises the steps: extracting semantic features for training data through a semantic encoder, obtaining a similar codebook corresponding to the semantic features from a quantized codebook stored in a semantic knowledge base, and storing the similar codebook in the semantic knowledge base; mapping the index of the similar codebook into first digital information for transmission; using a semantic knowledge base to determine a similar codebook according to the received first digital information, and transmitting the similar codebook to a semantic decoder; carrying out feature fusion on the similar codebook by utilizing a semantic decoder, and then carrying out decoding to obtain decoded data corresponding to the training data; obtaining a processing loss value according to the training data, the decoding data, the semantic features and the similar codebook; and according to the processing loss value, updating a model parameter of the semantic encoder, a quantization codebook parameter of the semantic knowledge base and a model parameter of the semantic decoder. According to the scheme, the problem that a semantic communication system is difficult to actually deploy in the prior art can be solved.

The embodiment of the application provides a data processing method, device and electronic equipment, the method comprises: obtaining to be stored data, the to be stored data comprises at least two key-value pair data, each key-value pair data in at least two key-value pair data comprises: string and the value corresponding to string;Determine any one key-value pair data in at least two key-value pair data, according to the string size ordering of key-value pair data, determine the storage location of each character in the corresponding key-value bucket in string, and store each character of string to the corresponding key-value bucket;According to the storage order of the value corresponding to string, determine the storage location of the value corresponding to string in value partition and store the value corresponding to string to value partition;According to the storage location of each character in the corresponding key-value bucket in string and the storage location of the value corresponding to string in value partition, establish index mapping table.

The invention provides a power plant equipment multi-modal fault causal chain retrieval and self-evolution method and system, and the method comprises the steps: obtaining equipment multi-modal heterogeneous data, extracting features through coding and projection, and outputting potential physical states and static semantic features; constructing a hybrid neurodynamic equation, and describing a physical quantity continuous flow by using a hypergraph convolution differential equation with an incidence matrix; driving hypergraph evolution based on formalized Ricci curvature, calculating a Wasserstein distance of a node pair by adopting Sinkhorn entropy regularization, and updating a hyperedge weight through a curvature flow equation; designing a physical topology double constraint loss function; variational neural symbol reasoning is introduced, and gradient propagation of discrete logic variables is achieved through GumbelSoftmax; aligning the physical state with the query vector by utilizing Poincare sphere index mapping in the hyperbolic retrieval space; an invariant causal prediction framework is adopted to carry out anti-fact intervention verification, knowledge base self-evolution is realized based on feedback, and fault causal chain retrieval which is physically consistent, feasible in calculation and deeply fused with multi-modal information is realized.

The embodiment of the invention discloses a meta-object code generation method and device, electronic equipment and a storage medium. According to the technical scheme, before the first source code file is compiled, the first source code file is pre-analyzed, the first connection statement in the source code is recognized, and the first connection statement is used for connecting the first function and the second function; obtaining a corresponding first function index and a second function index based on the first connection statement, and generating index mapping information based on the first function index and the second function index; and in the process of compiling the first source code file, generating a meta-object code corresponding to the first connection statement based on the index mapping information. By means of the technical means, the code size can be effectively controlled while the function binding efficiency is improved, and the dual requirements for program efficiency and size in the resource-constrained environment are met.

The application discloses an X:M dynamic attention sparsification method and device, the method comprises the following steps: predicting an attention score matrix, and performing X:M structured pruning based on a prediction result to obtain a pruning result; updating a minimum row number and an index row number in a cache and adjusting a scheduling threshold based on the pruning result, and storing an index block number meeting a condition into a priority queue to map a corresponding index to a PEA processing unit array for execution. The application greatly reduces the storage and calculation overhead of attention prediction, and combines X:M with a scheduling algorithm, so that processing units in an application-specific integrated circuit can maintain a very high utilization rate under different sparsities.

A method includes receiving, by a user equipment (UE), a configuration for mapping a first port associated with a channel state information reference signal (CSI-RS) resource in a resource set to a second port from a first apparatus The UE performs a first mapping of the first port to a first group of indices based upon the received configuration, and performs a second mapping of the first group of indices to the second port based upon the received configuration.

Aspects of the subject disclosure may include, for example, a technique for processing a decision network that includes obtaining an index encoding a mapping from potential values of an input parameter to decision parameters of the network's predicates, wherein the mapping associates potential values of the input parameter with decision parameters affected by those potential values; evaluating decision parameters affected by specified values of the input parameter, including identifying each decision parameter to which the index maps at least one specified values of the input parameter, and setting the values of those decision parameters in accordance with the input parameter's specified values; and analyzing the decision network, including evaluating the predicates of one or more of the decision nodes based on the values of the predicates' decision parameters, and determining, based on the values of the evaluated predicates and a topology of the decision network, that a particular terminal node encodes the network's output. Other embodiments are disclosed.

This invention discloses an adaptive index structure selection method for multimodal databases. By analyzing the statistical characteristics of each modality, such as data dimensionality, variance, sparsity, and distance distribution, the hidden dimension of each modality is calculated, and its effective data complexity is characterized. Based on preset index adaptation rules, each modality is automatically mapped to the optimal index type in the candidate index structure set, thereby automatically constructing local indexes and binding them to the global routing structure. Furthermore, multimodal queries can be automatically routed to the corresponding index for retrieval based on the index mapping relationship. This invention achieves an adaptive index structure selection mechanism that requires no manual configuration, significantly reducing the index maintenance cost of multimodal databases and improving query efficiency and scalability in complex retrieval scenarios.

The invention provides a data storage device and an operating method thereof. A data storage device may include a memory device and a memory controller. The memory controller is configured to extract a key value from the modified logical address and map an index generated based on the modified logical address and the key value to a physical address of the memory device.

The invention provides a code positioning method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. The method comprises the following steps of: dividing a structured data region and a common text region of an input mixed text, respectively processing, analyzing a target code library, establishing index mapping between the text and a code position, carrying out query matching based on the mapping, and returning code position information. The problems that in the prior art, formatting fails or semantic errors are caused due to the fact that structured data and unstructured texts cannot be distinguished, and log checking is low in efficiency due to lack of a log exclusive searching and indexing mechanism can be solved. The technical effects that intelligent formatting is achieved, original typesetting of a common text is reserved, and associated codes are rapidly positioned to improve the development efficiency are achieved.

The invention discloses a method and apparatus for performing a reduction operation on a plurality of data element values. Embodiments detailed herein pertain to reduction operations on a plurality of data element values. In one embodiment, a processor includes a decode circuit to decode an instruction and an execution circuit to execute the decoded instruction. The instruction specifies a first input register including a plurality of data element values, a first index register including a plurality of indexes, where each index of the plurality of indexes maps to one unique data element position of the first input register, and an output register. Performing includes: identifying data element values associated with each other based on an index; performing one or more reduction operations on the associated data element values based on the identification; and storing results of the one or more reduction operations in an output register.