25 results about "Compressed structure" patented technology

The invention discloses a multi-dimensional time sequence data compression and rapid retrieval method and system, and relates to the technical field of large data compression retrieval. The multi-dimensional time sequence data compression and rapid retrieval method comprises the following steps: S1, collecting and preprocessing multi-source data in a monitoring abstract video stream, and constructing a standardized time sequence behavior data set; s2, analyzing behavior characteristics of frame segments in the sliding window, and dynamically adjusting anchor point labeling and compression strategies; s3, evaluating the coverage integrity of anchor point information in a compression section, and driving generation of an index path; s4, comprehensively evaluating the path behavior association strength and dynamically adjusting a loading decision; and S5, verifying the matching integrity of the behavior anchor point field and the jump pointer, and guaranteeing the localizability and jump stability of the event in the compression structure. The problems that in an intelligent monitoring scheme, video abstract compression is not bound with behavior semantics, a fine-grained positioning mechanism based on behavior labels is lacked, and key action segments cannot be directly positioned during user playback are solved.

A geometry compression format is described. The compression format eliminates the need to store duplicate vertex information by storing unique vertices in each compressed data structure. Different triangles can refer to the same vertex using an index value, meaning that even if the same vertex is used multiple times in the compressed data structure, the entirety of the vertex information (e.g., positional information) does not need to be stored multiple times. An improvement includes representing further subdivision of the geometry in an efficient manner to represent highly detailed geometry. The subdivision can be specified by sideband information which can specify any of a variety of types of information.

The invention discloses a high-speed fixed-point multiplication circuit. The multiplication circuit is mainly composed of a multiplier coding module, a partial product generation module, a partial product compression module and a traveling wave carry adder module. The multiplier coding module is composed of a radix-4-Booth coding algorithm and an opposite number generation module, and is used for carrying out three-bit block coding on input multiplication data and generating an opposite number of a multiplicand in advance. The partial product generation module generates a plurality of groups of partial products with symbol extension according to the multiplicand coded signal. And the partial product compression module adopts an improved Wallace compression structure to perform layered compression on the partial product. And the traveling wave carry adder module sums the two groups of results output by compression and outputs a multiplication result. According to the invention, multiplication accumulation series can be reduced, the switching times of invalid signals in the circuit can be reduced, and the longest delay path in an operation link can be shortened, so that fixed-point multiplication which is high in speed, low in power consumption and more favorable for a comprehensive tool in structure is realized.

The invention is applicable to the technical field of artificial intelligence, and provides a large-model multi-agent-based method for automatically generating a complex-structure document, which comprises the following steps of: mapping an original structured document template into a compressed structure mark sequence with a reserved layout, and performing zero-sample semantic understanding and planning through a structure planning agent to obtain a complex-structure document; generating an atomic operation execution plan; according to the semantic logic relationship among the atomic operations in the structured execution plan, constructing a field-dependent directed acyclic graph, carrying out topological sorting on the field-dependent directed acyclic graph, and determining an execution sequence of content generation; through collaborative iteration of the content generation agent and the symbol verification agent, each field content is generated under the condition that a hard constraint condition is met; and finally synthesizing a complete document. According to the method, accurate understanding, reliable generation and format guarantee of the complex document under the zero sample condition are realized.

A geometry compression format is described. The compression format eliminates the need to store duplicate vertex information by storing unique vertices in each compressed data structure. Different triangles can refer to the same vertex using an index value, which means that even if the same vertex is used multiple times in the compressed data structure, the entirety of the vertex information (e.g., positional information) does not need to be stored multiple times. While the format provides good compression characteristics, improvement can be gained by eliminating the indices and instead using an indication of an “implicit geometry.” The implicit geometry is a commonly-used geometry type that indicates a particular correspondence between unique vertices and triangles. In other words, by indicating an implicit geometry type, it is automatically known which vertices make up which triangles, and explicit index information does not need to be stored in the compressed data structure.

The application relates to the technical field of energy-saving control of communication base stations, and discloses an energy-saving optimization control method and system for a communication base station. The method comprises the following steps: collecting and preprocessing traffic energy consumption data of the communication base station to obtain standardized features; inputting the features into a double-flow space-time convolution network to predict the load through parallel calculation of time and space branches; performing hierarchical quantization pruning on the network, allocating bit widths according to the influence degree to obtain a compressed structure; and processing real-time data based on the compressed network to generate an energy-saving control strategy for radio frequency resource configuration and power adjustment. Based on accurate load prediction and a differentiated resource scheduling strategy, the application realizes the optimal balance between energy saving and service quality, effectively overcomes the problems of passive response and coarse-grained control in traditional methods, and maximizes the energy saving effect under the premise of guaranteeing the communication quality.

A method for compressing molecular tagged sequence data includes: grouping sequence reads associated with a molecular tag sequence to form a family of sequence reads, corresponding vectors of flow space signal measurements and corresponding sequence alignments, calculating an arithmetic mean of the corresponding vectors of flow space signal measurements to form a vector of consensus flow space signal measurements, calculating a standard deviation of the corresponding vectors of flow space signal measurements to form a vector of standard deviations, determining a consensus base sequence based on the vector of consensus flow space signal measurements, determining a consensus sequence alignment and generating a compressed data structure comprising consensus compressed data, the consensus compressed data including for each family, the consensus base sequence, the consensus sequence alignment, the vector of consensus flow space signal measurements, the vector of standard deviations and the number of members.

The utility model relates to the technical field of scroll compressors, in particular to a scroll compression structure for a scroll compressor and the scroll compressor, the scroll compression structure for the scroll compressor comprises a movable scroll plate, the movable scroll plate is made of aluminum alloy, and the surface of the movable scroll plate is coated with a nano graphene coating; and the static scroll plate is meshed with the movable scroll plate. According to the scroll compression structure for the scroll compressor and the scroll compressor, the problem that an existing scroll compression structure for the scroll compressor is seriously abraded can be solved.

An accelerator device determines a compression format based on a header of a structured data element to be decompressed. The accelerator device may configure the accelerator device based on the compression format. The accelerator device may decompress a data block of the structured data element based on the configuration.

This invention discloses a structured crime scene modeling method based on 3D graph convolution, comprising the following steps: collecting data to generate a multi-source crime scene input dataset; constructing a 3D spatial graph of the crime scene, establishing graph edges based on the constraint set of structural relationships between nodes, and generating the 3D spatial graph; initializing node features and edge weights to generate an initial graph structure; performing 3D graph convolution processing on the initial graph structure, constraining the convolutional neighborhoods of nodes, performing neighborhood-based convolution operations on the features of nodes within the neighborhoods, and generating an intermediate feature map; performing graph pooling operations on the intermediate feature map to generate a compressed structural representation of the crime scene; and decoding and modeling the compressed structural representation to obtain a structured 3D scene representation. This invention constructs a structured crime scene model based on 3D graph convolution, realizing the fusion of multi-source data and criminal investigation relationships, and possesses the advantages of high semantic fidelity, complete structural representation, and strong modeling reliability.

The application discloses an OFD cross-format conversion method, computer equipment and a storage medium, relates to the technical field of electronic document format conversion, and comprises the following steps: scanning an OFD document file, detecting a compression header identifier, recursively decompressing a nested compression structure and performing directory verification to obtain an OFD document structure; analyzing the structure to obtain root document information, signature information and resource information containing fonts and pictures; constructing a font mapping relationship for replacing missing fonts during rendering based on the resource information; obtaining the page content of each document page according to the root document information and the signature information; concurrently rendering all the page content in a multithreading mode to generate rendering data corresponding to each page; and merging the rendering data of each page to generate a target format output file. The application ensures complete extraction of nested compressed resources through recursive decompression, guarantees consistency of formats by using font mapping, improves conversion efficiency by combining multithreading rendering, and realizes high-fidelity and high-efficiency conversion of OFD documents into formats such as PDF.

The present application relates to the technical field of data transmission, and particularly relates to an information transmission method and system for a data center, the method comprising: obtaining original information data to be transmitted, and dividing the original information data into a plurality of data blocks; calculating a periodic autocorrelation significant index and a periodic regularity index of the data blocks; taking the product of the periodic autocorrelation significant index and the periodic regularity index as a periodic structure significant index, and calculating a compression structure change index of the data blocks, the compression structure change index being negatively correlated with the periodic structure significant index; adjusting the search depth of a Zstd compression algorithm by using the compression structure change index to obtain an optimal search depth, and compressing the original information data by using the Zstd compression algorithm, so as to be used for transmission of the original information data. The present application improves the information transmission real-time performance and overall computing resource utilization rate of the data center.

The invention relates to the technical field of data transmission, in particular to an information transmission method and system for a data center, and the method comprises the steps: obtaining to-be-transmitted original information data, and dividing the original information data into a plurality of data blocks; calculating a periodic autocorrelation significance index and a periodic rule index of the data block; the product of the periodic self-correlation significance index and the periodic rule index serves as a periodic structure significance index, a compression structure change index of the data block is calculated, and the compression structure change index is in negative correlation with the periodic structure significance index; and adjusting the search depth of the Zstd compression algorithm by using the compression structure change index to obtain the optimal search depth, and compressing the original information data by using the Zstd compression algorithm for transmission of the original information data. According to the invention, the information transmission real-time performance and the overall computing resource utilization rate of the data center are improved.

The application discloses a kind of multi-dimensional time series data compression and fast retrieval method and system, it is related to big data compression retrieval technical field.The kind of multi-dimensional time series data compression and fast retrieval method and system, including S1, the multi-source data in monitoring abstract video stream is collected and preprocessed, constructs standardization time series behavior dataset;S2, the behavior characteristics of frame section in sliding window are analyzed, anchor point labeling and compression strategy are dynamically adjusted;S3, the coverage completeness of anchor point information in compressed section is evaluated, and index path generation is driven;S4, the behavior correlation strength of path is comprehensively evaluated and dynamically adjusted loading decision;S5, the matching integrity of behavior anchor point field and jump pointer is verified, and the positionability and jump stability of event in compression structure are guaranteed.Solve the problem that video abstract compression is not bound with behavior semantics in intelligent monitoring scheme, lacks fine-grained positioning mechanism based on behavior label, and user playback cannot directly locate key action section.

The invention relates to the technical field of cryptography, and discloses a stream cipher algorithm and device based on a multilayer filter, and the device comprises an initialization algorithm and a key stream generation algorithm. The initialization algorithm fully fuses a seed key and an initial vector through a multiplexing key stream generation algorithm. According to the key stream generation algorithm, the unpredictability of the key stream is increased through an extension-diffusion confusion-compression structure, so that the generated password sequence has an excellent pseudo-random statistical characteristic, and known cryptographic analysis methods such as algebraic attacks and related attacks can be effectively resisted. The algorithm does not depend on special hardware and has the advantage of low use cost; and high-speed encryption and decryption operation can be realized in a lightweight environment, and the requirements of 5G and even 6G times on encryption and decryption speeds can be met.

A hardware-implemented file reader (20) includes an interface (32), a plurality of hardware-implemented column readers (36), and a record reconstructor (40). The interface is configured to access a file (24) comprising a plurality of records. The recording stores values according to a nested structure that supports selectable values and duplicate values. The file is stored in a column format having a plurality of columns, each column storing (i) a compressed value and (ii) corresponding compressed structure information associating values in the column with a recorded nested structure. Each column reader is configured to be assigned to a respective selected column, and to read and decompress values and structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records according to at least a portion of the column read by the column reader, and output the reconstructed records.

A method for compressing molecular tagged sequence data includes: grouping sequence reads associated with a molecular tag sequence to form a family of sequence reads, corresponding vectors of flow space signal measurements and corresponding sequence alignments, calculating an arithmetic mean of the corresponding vectors of flow space signal measurements to form a vector of consensus flow space signal measurements, calculating a standard deviation of the corresponding vectors of flow space signal measurements to form a vector of standard deviations, determining a consensus base sequence based on the vector of consensus flow space signal measurements, determining a consensus sequence alignment and generating a compressed data structure comprising consensus compressed data, the consensus compressed data including for each family, the consensus base sequence, the consensus sequence alignment, the vector of consensus flow space signal measurements, the vector of standard deviations and the number of members.

The invention relates to a task scheduling method and system for warehouse connection, and the method comprises the steps: obtaining task data, and extracting task features based on the task data; encoding the task features, and compressing the task features to obtain a compressed structure encoding vector; identifying the compressed structure coding vector to obtain a task identification tag; dynamically adjusting the priority of the task according to the task identification tag; and allocating an execution path for the task according to the priority of the task. According to the invention, the scheduling efficiency and flexibility of the storage connection link are significantly improved, and the overall storage operation process is optimized, so that the system can efficiently deal with multi-task, high-frequency and dynamically changing complex scenes, and the development of storage operation in the intelligent, real-time and high-precision directions is comprehensively promoted.

A hardware-implemented file reader includes an interface, multiple hardware-implemented column readers and a hardware-implemented record reconstructor. The interface is configured to access a file including multiple records. The records store values in accordance with a nested structure that supports optional values and repeated values. The file is stored in a columnar format having multiple columns, each column storing (i) compressed values and (ii) corresponding compressed structure information that associates the values in the column to the nested structure of the records. Each column reader is configured to be assigned to a respective selected column, and to read and decompress both the values and the structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records from at least portions of the columns that are read by the column readers, and to output the reconstructed records.

The invention discloses a quantum storage compression structure supporting online calculation, which is characterized in that the compression structure comprises an input module, a compression module, a conversion module, a calculation module and a decompression module, and the input module is used for converting an input form of an initial state vector and a quantum circuit into an identified legal form; the compression module is used for compressing and converting the state vector into a linked list for storage through a vernier, and compressing and unloading the periodic data again; the conversion module is used for converting the quantum circuit into a form which can be processed by RepeatCounter; and the decompression module decompresses the output stream or the memory according to requirements, and decompresses and destroys the RepeatCounter when the memory is limited. Compared with the prior art, the method has the advantages of optimization of storage space, reduction of calculation loss, efficient parallel support and the like, online quantum calculation can be performed without frequent compression and decompression, frequent internal and external memory exchange caused by offline compression can be reduced, and larger-scale quantum calculation can be better simulated on a machine with lower configuration.

A geometry compression format is described. The compression format eliminates the need to store duplicate vertex information by storing unique vertices in each compressed data structure. Different triangles can refer to the same vertex using an index value, meaning that even if the same vertex is used multiple times in the compressed data structure, the entirety of the vertex information (e.g., positional information) does not need to be stored multiple times. An improvement can be made to the dense geometry format to support interpolation. More specifically, in an example, geometry for two different interpolation points can be provided in a compressed data structure encoded using the dense geometry format. Using an interpolation parameter, new interpolated geometry can be derived from the two different interpolation points. This interpolated geometry represents an intermediate point between the two interpolation points, where the similarity to either interpolation point is dependent on the interpolation parameter.

An example computing platform is configured to receive configuration data that defines a pipeline for building a deep learning model, the configuration data including data defining an input dataset, data type assignments for a set of input data variables included within the dataset, data transformations that are to be applied to the dataset, and a machine learning process that is to be utilized to train the deep learning model. Based on the received configuration data, the computing platform functions to build the deep learning model by obtaining the input dataset, assigning a data type to data in the dataset, selecting transformation operations for the data in the dataset, splitting the dataset into a sequence of data blocks, applying the transformation operations to each data block to produce a transformed dataset, generating a compressed data structure that includes the transformed datasets, and applying the machine learning process to the transformed datasets.

The application relates to the field of natural language processing and large-scale language models, and proposes a business query language generation method, system, device and medium, the method comprising the following steps: receiving a natural language query sentence input by a user, preprocessing the natural language query sentence, and converting the natural language query sentence into structured information; calling a business entity compression structure service, obtaining a compression structure of a corresponding business entity based on the structured information, optimizing the compression structure, and integrating the compression structure into a large model; obtaining user permission information, extracting permission restrictions in the user permission information, and inputting the permission restrictions into the large model; based on the optimized and integrated compression structure and the permission restrictions, generating a query sentence of a business query language through the large model, querying according to the query sentence of the business query language, and displaying a query result. Through multi-layer conversion and compression structure optimization, and in combination with permission management, efficient conversion from a natural language to a business query language is realized.

A geometry compression format is described. The compression format eliminates the need to store duplicate vertex information by storing unique vertices in each compressed data structure. Different triangles can refer to the same vertex using an index value, meaning that even if the same vertex is used multiple times in the compressed data structure, the entirety of the vertex information (e.g., positional information) does not need to be stored multiple times. An improvement can be made to the dense geometry format to support interpolation. More specifically, in an example, geometry for two different interpolation points can be provided in a compressed data structure encoded using the dense geometry format. Using an interpolation parameter, new interpolated geometry can be derived from the two different interpolation points. This interpolated geometry represents an intermediate point between the two interpolation points, where the similarity to either interpolation point is dependent on the interpolation parameter.